{"meta":{"query_hash":"481f82bad2ca","filters":{"topic":"Advanced Neuroimaging Techniques and Applications"},"cohort_total":2751,"direct_labels_cover":6,"predictions_cover":2751,"exported":2751,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/481f82bad2ca","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+Neuroimaging+Techniques+and+Applications"},"results":[{"id":"W108913140","doi":"10.1016/s0079-6123(01)34025-6","title":"Chapter 24 Visual pathways following cerebral hemispherectomy","year":2001,"lang":"en","type":"review","venue":"Progress in brain research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"China Scholarship Council","keywords":"Superior colliculus; Pretectal area; Superior Colliculi; Midbrain; Hemispherectomy; Neuroscience; Visual system; Commissure; Anatomy; Psychology; Cerebral cortex; Retina; Biology; Central nervous system; Epilepsy","score_opus":0.3964250188350444,"score_gpt":0.5568198452668143,"score_spread":0.1603948264317699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W108913140","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032059773,0.99340445,0.00056498166,0.000277945,0.0005890367,0.000012311786,0.000022619415,0.000021360478,0.0047868183],"genre_scores_gemma":[0.0012617343,0.99290013,0.00039170313,0.00027033716,0.0006217911,0.000014658255,0.000055932334,0.0000051716006,0.0044785272],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998969,0.000012586416,0.000017994338,0.000020676702,0.000040410265,0.000011465823],"domain_scores_gemma":[0.9998504,0.00007327796,0.000023905175,0.000006517374,0.000036145924,0.000009733491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036041578,0.0007541846,0.0011677453,0.001826082,0.00028357768,0.0009149131,0.00073522766,0.00095735776,0.0058769276],"category_scores_gemma":[0.00055446615,0.0001906086,0.0003806487,0.0014438267,0.0005709964,0.0011674222,0.00045709603,0.001177431,0.002842142],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100807876,0.00006505369,0.00009109004,0.006837431,0.000040179828,0.0004897245,0.000035161032,0.00019680723,0.0030032725,0.001726474,0.028533677,0.9588803],"study_design_scores_gemma":[0.000042279393,0.00019721698,0.002182887,0.0032294544,0.00012563185,0.006167932,0.00006281758,0.000091720794,0.002833471,0.002795017,0.98224306,0.000028535054],"about_ca_topic_score_codex":0.0020482487,"about_ca_topic_score_gemma":0.0045903046,"teacher_disagreement_score":0.0058769276,"about_ca_system_score_codex":0.0006707957,"about_ca_system_score_gemma":0.0012624358,"threshold_uncertainty_score":0.019660294},"labels":[],"label_agreement":null},{"id":"W1143664502","doi":"10.1016/j.bbr.2015.08.028","title":"Neuromarkers of the common angiotensinogen polymorphism in healthy older adults: A comprehensive assessment of white matter integrity and cognition","year":2015,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health; National Center for Advancing Translational Sciences; DNA Genotek","keywords":"White matter; Cingulum (brain); Cognition; Uncinate fasciculus; Psychology; Superior longitudinal fasciculus; Diffusion MRI; Fractional anisotropy; Hyperintensity; Internal medicine; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.2334855925832703,"score_gpt":0.4665982097030035,"score_spread":0.23311261711973316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1143664502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991264,0.00034196762,0.00006612826,0.000027520315,0.0000043847913,0.000012027838,0.00014331818,0.0000039735805,0.00027416306],"genre_scores_gemma":[0.9991721,0.00015808977,0.00015992598,0.000045624474,0.000011859029,0.000009082216,0.00019377415,0.0000012990995,0.000248257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982446,0.000029190209,0.00003260449,0.000045865832,0.000040540195,0.00002727264],"domain_scores_gemma":[0.99966323,0.00003621482,0.00013821661,0.000023365998,0.000058576803,0.00008035981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038329506,0.00046528244,0.0006581835,0.0007099779,0.00039394756,0.0003782189,0.00021316866,0.00063522457,0.0005244081],"category_scores_gemma":[0.00090289343,0.00024999148,0.0003447416,0.0005181743,0.00018823628,0.0004161544,0.00035465485,0.00041050208,0.00014509061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075390324,0.00023187386,0.9893182,0.00003051692,0.00028264007,0.0004049648,0.00014630365,0.000078467456,0.0027330888,0.000018544537,0.00013513041,0.005866288],"study_design_scores_gemma":[0.00000858345,0.00015747467,0.99922657,0.000002782148,0.000054264186,0.0002790886,0.000043335443,0.000055773708,0.00010849417,0.000021494316,0.000039827675,0.0000023516543],"about_ca_topic_score_codex":0.004745265,"about_ca_topic_score_gemma":0.010975752,"teacher_disagreement_score":0.004745265,"about_ca_system_score_codex":0.00020173877,"about_ca_system_score_gemma":0.00019768917,"threshold_uncertainty_score":0.009435296},"labels":[],"label_agreement":null},{"id":"W1161154887","doi":"10.1089/neu.2013.2866","title":"To Exclude or Not To Exclude: Further Examination of the Influence of White Matter Hyperintensities in Diffusion Tensor Imaging Research","year":2013,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Hyperintensity; Magnetic resonance imaging; Medicine; Psychology; Nuclear medicine; Radiology","score_opus":0.16270061074861494,"score_gpt":0.41914143939694887,"score_spread":0.25644082864833395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1161154887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866261,0.0017675544,0.0047349576,0.002016095,0.00044048225,0.00055884005,0.00023846958,0.000030958992,0.0035865845],"genre_scores_gemma":[0.9869474,0.00048527247,0.009419268,0.0013842654,0.0004484772,0.0004279679,0.000255886,0.000038445676,0.00059298327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.94996566,0.028852686,0.00885057,0.0035324509,0.007929141,0.0008695449],"domain_scores_gemma":[0.85896355,0.08183542,0.025569106,0.017109804,0.013365691,0.003156426],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.065350905,0.000793328,0.0011619189,0.0015301504,0.0014235827,0.0019637987,0.0014097327,0.0017603314,0.0013434911],"category_scores_gemma":[0.17042075,0.0004239654,0.0014969234,0.0013187019,0.0021182057,0.0017836179,0.0014653829,0.0014444531,0.0003638616],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006975052,0.0008413213,0.8773809,0.00088601664,0.002241624,0.0020536322,0.008958506,0.00035573795,0.0063436325,0.0010654704,0.003502727,0.08939536],"study_design_scores_gemma":[0.0005434928,0.0038895742,0.9735281,0.00047353588,0.0010063308,0.0025649741,0.002046042,0.0018092487,0.0031300571,0.002044382,0.008887596,0.00007677034],"about_ca_topic_score_codex":0.0023092183,"about_ca_topic_score_gemma":0.0067730546,"teacher_disagreement_score":0.9346491,"about_ca_system_score_codex":0.0004990546,"about_ca_system_score_gemma":0.0016259126,"threshold_uncertainty_score":0.34561276},"labels":[],"label_agreement":null},{"id":"W12021418","doi":"10.1186/1532-429x-17-s1-p383","title":"In vivo free-breathing DTI &amp; IVIM of the whole human heart using a real-time slice-followed SE-EPI navigator-based sequence: a reproducibility study in healthy volunteers","year":2015,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Reproducibility; Medicine; Intravoxel incoherent motion; Angiology; In vivo; Breathing; Sequence (biology); Biomedical engineering; Nuclear medicine; Cardiology; Diffusion MRI; Anesthesia; Magnetic resonance imaging; Radiology; Biology; Chromatography","score_opus":0.11894399807139165,"score_gpt":0.3863276348346188,"score_spread":0.26738363676322713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W12021418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96760267,0.00054163596,0.031405356,0.00003167191,0.00001764459,0.000057178288,0.000049536757,0.00008418108,0.00021020068],"genre_scores_gemma":[0.9820188,0.00018863237,0.01723554,0.000041318293,0.00003545578,0.000053977838,0.00012155235,0.00005857116,0.00024603473],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99943286,0.00020635192,0.000039774477,0.00023124274,0.000066182874,0.000023609193],"domain_scores_gemma":[0.99916804,0.00025141507,0.00013828785,0.00026039794,0.00012932066,0.000052482395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017850787,0.00045214902,0.00027022863,0.00023197841,0.00019476039,0.00032744222,0.00035717795,0.0006846064,0.00040802738],"category_scores_gemma":[0.0021966896,0.00023041047,0.00020532755,0.00012836755,0.00044908444,0.00037884424,0.00022192343,0.00020585406,0.00017260217],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028343857,0.00055361056,0.03976443,0.00032087244,0.0003665988,0.00043699617,0.00091691274,0.001504878,0.892428,0.00020816957,0.0002520712,0.060413096],"study_design_scores_gemma":[0.00047151354,0.02445562,0.5819105,0.000055457953,0.0012033496,0.0104219215,0.0005363159,0.036177978,0.3398354,0.00046937616,0.0043049324,0.0001576808],"about_ca_topic_score_codex":0.00030299218,"about_ca_topic_score_gemma":0.00054630695,"teacher_disagreement_score":0.0017850787,"about_ca_system_score_codex":0.000072189185,"about_ca_system_score_gemma":0.00011525933,"threshold_uncertainty_score":0.009440541},"labels":[],"label_agreement":null},{"id":"W123779339","doi":"10.1139/jpn.0842","title":"Microstructural thalamic changes in schizophrenia: a combined anatomic and diffusion weighted magnetic resonance imaging study","year":2008,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Thalamus; Magnetic resonance imaging; Schizophrenia (object-oriented programming); Diffusion MRI; Functional magnetic resonance imaging; Diffusion-Weighted Magnetic Resonance Imaging; Neuroscience; Medicine; Pathophysiology; Nuclear magnetic resonance; Psychology; Radiology; Psychiatry; Pathology; Physics","score_opus":0.020601816042030686,"score_gpt":0.29871461153270473,"score_spread":0.278112795490674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W123779339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99865,0.00061762624,0.0002025183,0.00003414213,0.0000019039899,0.000011300002,0.00009716369,0.0000057794414,0.00037962824],"genre_scores_gemma":[0.99927753,0.00028424658,0.00025814536,0.000009972575,0.000004651445,0.0000046374616,0.000082243554,0.0000015019867,0.00007714618],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998703,0.000018175746,0.000023741795,0.000024277388,0.000044091834,0.000019427727],"domain_scores_gemma":[0.99971884,0.000025066318,0.00015630588,0.000016349446,0.000039058927,0.00004425373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003429423,0.0004116234,0.00019625692,0.0014832966,0.00021748822,0.00039401458,0.00019387512,0.0002248428,0.001354646],"category_scores_gemma":[0.00055928406,0.00030047397,0.00024599468,0.00059897295,0.00031347654,0.0003374334,0.0004942839,0.00015821414,0.00017081902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008150207,0.000091442,0.8972068,0.00022737926,0.00034179926,0.0046325,0.0007689497,0.00021832947,0.08132686,0.00012394837,0.000111588684,0.014135531],"study_design_scores_gemma":[0.00001707908,0.00024483737,0.99235535,0.000022384864,0.000080236394,0.0055911196,0.00035726232,0.00018785852,0.00092039525,0.000063241525,0.00015309012,0.0000071498644],"about_ca_topic_score_codex":0.00368594,"about_ca_topic_score_gemma":0.0073781535,"teacher_disagreement_score":0.00368594,"about_ca_system_score_codex":0.00032119668,"about_ca_system_score_gemma":0.00028880022,"threshold_uncertainty_score":0.007328987},"labels":[],"label_agreement":null},{"id":"W125137646","doi":"10.1007/978-3-642-23629-7_20","title":"Apparent Intravoxel Fibre Population Dispersion (FPD) Using Spherical Harmonics","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Population; Computer science; Autocorrelation; Spherical harmonics; Voxel; Orientation (vector space); Dispersion (optics); Anisotropy; Diffusion MRI; Kurtosis; Diffusion; Quaternion; SIGNAL (programming language); Artificial intelligence; Acoustics; Algorithm; Mathematics; Optics; Physics; Statistics; Geometry; Mathematical analysis","score_opus":0.09551955099753882,"score_gpt":0.34454474679262476,"score_spread":0.24902519579508592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W125137646","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042346004,0.0006315833,0.9495781,0.00019476327,0.00006461204,0.00008466487,0.00034911788,0.0007264039,0.0060247565],"genre_scores_gemma":[0.304796,0.0017360689,0.68679595,0.00008514022,0.00009024979,0.00012292962,0.00041559056,0.00038555544,0.00557253],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979526,0.000053882562,0.000009827015,0.00004057065,0.00008065198,0.000019874076],"domain_scores_gemma":[0.9993519,0.00030350548,0.00009236676,0.000121418576,0.00009368534,0.000037227837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068830367,0.00074968755,0.00031884288,0.0013288789,0.00039545624,0.0011111589,0.0007537,0.0009018063,0.0034996916],"category_scores_gemma":[0.0017208748,0.00036384547,0.00057874224,0.0014943058,0.00075664406,0.0019643884,0.0009402928,0.0010204605,0.00063483755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006481229,0.00014663812,0.007945737,0.0010607387,0.00022942534,0.00080009986,0.0010665281,0.058978174,0.32883424,0.10214625,0.0040944936,0.49404952],"study_design_scores_gemma":[0.000073598894,0.0001658667,0.012169499,0.00015084556,0.00011411599,0.0020359221,0.00025365833,0.7814938,0.1309466,0.057126082,0.015280123,0.0001899621],"about_ca_topic_score_codex":0.0018783448,"about_ca_topic_score_gemma":0.0033988084,"teacher_disagreement_score":0.0034996916,"about_ca_system_score_codex":0.0006218612,"about_ca_system_score_gemma":0.00056931336,"threshold_uncertainty_score":0.011707604},"labels":[],"label_agreement":null},{"id":"W131673369","doi":"10.1007/978-3-540-71512-2_8","title":"Insights into Brain Connectivity Using Quantitative MRI Measures of White Matter","year":2007,"lang":"en","type":"book-chapter","venue":"Understanding complex systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"White matter; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.4724008109973974,"score_gpt":0.4077308608957799,"score_spread":0.06466995010161747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W131673369","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013753532,0.019215833,0.93286103,0.0016022626,0.00035243528,0.000034570836,0.0005673208,0.0011740517,0.030438887],"genre_scores_gemma":[0.17266275,0.038393155,0.76061374,0.0007098151,0.0007242234,0.00011324119,0.000788946,0.0005981619,0.025396021],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999125,0.000016995516,0.0000044859694,0.000025705991,0.000036198122,0.00000405284],"domain_scores_gemma":[0.9997341,0.000177926,0.000022735465,0.000021934196,0.00003205126,0.000011149482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039705427,0.0010494946,0.0004301233,0.0015169805,0.00012804761,0.0010406238,0.0006182937,0.00049300474,0.004066849],"category_scores_gemma":[0.0010237137,0.000372245,0.00038184936,0.0009809013,0.0008083693,0.0021600802,0.0003481305,0.0010586476,0.0010235591],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006181078,0.00006856547,0.0020333002,0.0008914587,0.00015126487,0.00025148227,0.00025763092,0.013768689,0.1593778,0.19347063,0.016819753,0.6128476],"study_design_scores_gemma":[0.000017055358,0.00014115064,0.012475488,0.00029782485,0.00013481695,0.0028931948,0.0002778501,0.08294836,0.042331405,0.78774196,0.07061321,0.00012771346],"about_ca_topic_score_codex":0.0004098143,"about_ca_topic_score_gemma":0.0011286492,"teacher_disagreement_score":0.004066849,"about_ca_system_score_codex":0.00022976835,"about_ca_system_score_gemma":0.00021173914,"threshold_uncertainty_score":0.013604999},"labels":[],"label_agreement":null},{"id":"W136828434","doi":"10.1016/j.nic.2012.12.001","title":"Normal Myelination","year":2013,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; University of Toronto","funders":"","keywords":"Myelin; Medicine; Central nervous system; Neuroscience; Myelin basic protein; Oligodendrocyte; Peripheral; Peripheral nervous system; White matter; Nervous system; Magnetic resonance imaging; Anatomy; Pathology; Biology; Radiology; Internal medicine","score_opus":0.14336042343664893,"score_gpt":0.439233678035619,"score_spread":0.29587325459897007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W136828434","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010245454,0.98683155,0.0008871028,0.00063096546,0.0004067961,0.000016125286,0.00006504859,0.000057476886,0.010080454],"genre_scores_gemma":[0.010753399,0.98152494,0.0012036788,0.00097567646,0.00053936726,0.000018968316,0.00016935873,0.000012675041,0.0048019625],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998166,0.000026406584,0.000034620876,0.000041010237,0.00005441016,0.000026925918],"domain_scores_gemma":[0.9997143,0.000088783716,0.00007261549,0.000014748653,0.00008054169,0.000029015977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034763783,0.00096093357,0.0008399576,0.0033267697,0.00030992692,0.0009552408,0.00049776287,0.0007964536,0.003874533],"category_scores_gemma":[0.0010793332,0.00018443883,0.00024288315,0.0018690395,0.0008453799,0.0013168198,0.00081640197,0.00091200875,0.0018201077],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008439481,0.000035364425,0.00077712483,0.0056120683,0.000059351423,0.002087949,0.00007672453,0.00015413125,0.0021189363,0.003008795,0.031404164,0.954581],"study_design_scores_gemma":[0.000033405122,0.00010232511,0.0045181965,0.006934137,0.00030011902,0.039169114,0.0002656449,0.00018097983,0.003299407,0.0058506564,0.939299,0.000047007572],"about_ca_topic_score_codex":0.00221423,"about_ca_topic_score_gemma":0.0042438074,"teacher_disagreement_score":0.003874533,"about_ca_system_score_codex":0.0006365415,"about_ca_system_score_gemma":0.0016837905,"threshold_uncertainty_score":0.012961626},"labels":[],"label_agreement":null},{"id":"W1427495351","doi":"10.1007/s00406-003-0414-9","title":"Influence of genetic loading, obstetric complications and premorbid adjustment on brain morphology in schizophrenia:","year":2003,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schizophrenia (object-oriented programming); Atrophy; Ventricle; Psychology; Frontal lobe; Corpus callosum; Brain morphometry; Cerebrospinal fluid; Audiology; Medicine; Physiology; Internal medicine; Psychiatry; Neuroscience; Magnetic resonance imaging","score_opus":0.05276867094052904,"score_gpt":0.366264441450614,"score_spread":0.3134957705100849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1427495351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993826,0.00015660869,0.000038175604,0.000047634167,0.0000036504396,0.0000020357381,0.00008586932,0.0000020575321,0.0002813021],"genre_scores_gemma":[0.9996458,0.00007737794,0.000059005702,0.000009763729,0.0000034848592,0.0000021417854,0.000062397914,0.0000033632414,0.00013670602],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995956,0.00015620109,0.00003929695,0.000070154674,0.000057339723,0.00008149564],"domain_scores_gemma":[0.9987324,0.00034580316,0.0003505584,0.00013943917,0.00008517586,0.0003467134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051015604,0.00042378536,0.0003154769,0.0007188562,0.00067587895,0.00061399187,0.00032826676,0.0005426296,0.0019455715],"category_scores_gemma":[0.0027208442,0.00026948558,0.00048997806,0.00086599676,0.00055047387,0.00038673638,0.0006337545,0.0006083434,0.00016712492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012029996,0.000097329605,0.9899254,0.0000124260205,0.00021985208,0.00093386305,0.00041619176,0.000087745175,0.0027890732,0.000097893164,0.000062433675,0.004154764],"study_design_scores_gemma":[0.0000023646617,0.00006270644,0.99941504,0.0000017734532,0.000026699128,0.0002027471,0.00013319045,0.000036685582,0.000052683645,0.0000343579,0.000029005465,0.0000027705555],"about_ca_topic_score_codex":0.011207325,"about_ca_topic_score_gemma":0.01870867,"teacher_disagreement_score":0.011207325,"about_ca_system_score_codex":0.0005464614,"about_ca_system_score_gemma":0.00096327794,"threshold_uncertainty_score":0.02228415},"labels":[],"label_agreement":null},{"id":"W1446022853","doi":"10.3233/jad-142079","title":"Diffusion Tensor Imaging Correlates of Cognitive-Motor Decline in Normal Aging and Increased Alzheimer's Disease Risk","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Cognitive decline; Disease; Cognition; Neuroscience; Psychology; Medicine; Dementia; Cognitive psychology; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.046967013432982166,"score_gpt":0.3415765063678017,"score_spread":0.29460949293481953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1446022853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991103,0.0004043183,0.0000683666,0.000029345754,0.0000025260001,0.0000071770232,0.00009546912,0.0000038322055,0.00027853233],"genre_scores_gemma":[0.99946946,0.000112780894,0.00015475418,0.000010505295,0.000006708439,0.0000043473424,0.00012963681,0.0000010713775,0.00011085897],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998317,0.000022770972,0.000035888737,0.000044513552,0.00004083153,0.000024260411],"domain_scores_gemma":[0.9982868,0.00011802345,0.0011027239,0.00007340623,0.0002072866,0.00021179044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005998417,0.00040151013,0.0003722979,0.0014713935,0.00031523127,0.00038188614,0.00030548376,0.00043135986,0.00071782083],"category_scores_gemma":[0.0025885408,0.00018899216,0.00019054263,0.0006357975,0.00032355922,0.00038139842,0.00048213618,0.00035517017,0.00015422831],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032415608,0.0000693192,0.9933202,0.000025585488,0.00009616448,0.00021486408,0.00025687306,0.00008232713,0.0028875768,0.000050919516,0.00007929383,0.0025927876],"study_design_scores_gemma":[0.0000022825895,0.00004384127,0.99943,0.0000018278487,0.000009862851,0.0002420883,0.000040468665,0.000081886355,0.00006563691,0.000046549485,0.000033565317,0.0000018437227],"about_ca_topic_score_codex":0.0038718472,"about_ca_topic_score_gemma":0.0049427883,"teacher_disagreement_score":0.0038718472,"about_ca_system_score_codex":0.00024445856,"about_ca_system_score_gemma":0.00016186913,"threshold_uncertainty_score":0.007698655},"labels":[],"label_agreement":null},{"id":"W1446429242","doi":"10.3233/pep-13039","title":"Diffusion-weighted magnetic resonance imaging and pediatric epilepsy","year":2015,"lang":"en","type":"article","venue":"Journal of Pediatric Epilepsy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Magnetic resonance imaging; Epilepsy; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion MRI; Pediatric epilepsy; Medicine; Nuclear magnetic resonance; Diffusion; Neuroscience; Functional magnetic resonance imaging; Psychology; Radiology; Physics","score_opus":0.03669287988482227,"score_gpt":0.3121617593605929,"score_spread":0.27546887947577064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1446429242","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018126483,0.9948137,0.00078261126,0.00074595114,0.00021122133,0.0000056934223,0.000023894656,0.000012860878,0.0015913715],"genre_scores_gemma":[0.0082389135,0.98906785,0.0010368024,0.00030756654,0.0006366901,0.0000069432263,0.00004434683,0.000003806889,0.0006570201],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997613,0.00003551517,0.000053679883,0.000048643116,0.00007657806,0.000024342155],"domain_scores_gemma":[0.9996432,0.00015131329,0.000101227466,0.000006925378,0.000071226284,0.00002609043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033370225,0.000697676,0.0007581124,0.0015058367,0.00018702651,0.00058364915,0.0004134294,0.00072868966,0.0012560855],"category_scores_gemma":[0.0007799404,0.00013441412,0.00032355185,0.0015646026,0.00055776635,0.0011656376,0.00051006925,0.0010369587,0.0008831346],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007873022,0.000053913103,0.00798977,0.007857851,0.000112284426,0.009745436,0.00028611484,0.00032722583,0.0051362235,0.0045419093,0.018939227,0.9449313],"study_design_scores_gemma":[0.000020281124,0.00020955243,0.03924598,0.0054637706,0.0003850989,0.16483444,0.0005813749,0.00034470105,0.004050688,0.006573724,0.7782103,0.00007997448],"about_ca_topic_score_codex":0.0010485331,"about_ca_topic_score_gemma":0.0016151437,"teacher_disagreement_score":0.0015058367,"about_ca_system_score_codex":0.00034033312,"about_ca_system_score_gemma":0.00084596535,"threshold_uncertainty_score":0.0042020082},"labels":[],"label_agreement":null},{"id":"W1481624280","doi":"10.1002/nbm.3326","title":"Quantitative MRI in a non‐surgical model of cervical spinal cord injury","year":2015,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Sunnybrook Hospital; McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research; Lantheus Medical Imaging","keywords":"White matter; Medicine; Spinal cord; Magnetic resonance imaging; Diffusion MRI; Luxol fast blue stain; Hemosiderin; Histology; Spinal cord injury; Pathology; Myelin; Radiology; Central nervous system; Internal medicine","score_opus":0.16688352249975225,"score_gpt":0.4616736964257666,"score_spread":0.29479017392601436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481624280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96955633,0.0023083815,0.02237417,0.00024932614,0.00014920293,0.00040463105,0.0013433133,0.000470397,0.0031442258],"genre_scores_gemma":[0.9554415,0.0036469311,0.027730007,0.00016945545,0.00008597262,0.0006922309,0.0021491742,0.00015293206,0.00993175],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996031,0.00004884711,0.00003769461,0.000101100595,0.00012365705,0.000085581654],"domain_scores_gemma":[0.99937904,0.00007924125,0.00020757853,0.000065592765,0.00017326079,0.0000953554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071226846,0.0009839325,0.00047884244,0.0015006856,0.00036557592,0.00040417447,0.0005016161,0.0006896421,0.0016833176],"category_scores_gemma":[0.00047111468,0.00032101606,0.0004523747,0.0005923282,0.0007034909,0.00059446914,0.0003870628,0.00084966817,0.00039513496],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022326845,0.00007105184,0.00008144898,0.00005879836,0.0000051836614,0.000059451417,0.0000316855,0.00008539867,0.99860424,0.00004597389,0.000025269936,0.0007080609],"study_design_scores_gemma":[0.000046870846,0.0043808385,0.007886754,0.000022986558,0.000086394364,0.00085924816,0.0001036501,0.0017884,0.9833763,0.00010752259,0.001308512,0.000032411976],"about_ca_topic_score_codex":0.0034275202,"about_ca_topic_score_gemma":0.004437195,"teacher_disagreement_score":0.0034275202,"about_ca_system_score_codex":0.0006998552,"about_ca_system_score_gemma":0.000567416,"threshold_uncertainty_score":0.0068151355},"labels":[],"label_agreement":null},{"id":"W1482977697","doi":"10.1007/978-3-642-15705-9_67","title":"Inference of a HARDI Fiber Bundle Atlas Using a Two-Level Clustering Strategy","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Fiber bundle; Cluster analysis; Computer science; Tractography; Artificial intelligence; Bundle; Pattern recognition (psychology); Atlas (anatomy); Segmentation; Pairwise comparison; Diffusion MRI; Inference; Normalization (sociology); Fiber tract; Population; Spatial normalization; Voxel; Anatomy; Medicine; Magnetic resonance imaging","score_opus":0.10183918342541161,"score_gpt":0.3880531155902251,"score_spread":0.2862139321648135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482977697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004539232,0.000059357306,0.99357694,0.00013659532,0.000025849286,0.00004541773,0.00015951954,0.0010907836,0.00036629254],"genre_scores_gemma":[0.13401146,0.000111489695,0.8606044,0.000178843,0.00008366254,0.00016216519,0.0013669119,0.0008866111,0.0025943944],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978123,0.00055928243,0.00012029737,0.00091878936,0.00036759456,0.00022178824],"domain_scores_gemma":[0.9931924,0.0033180276,0.00047918106,0.0013471772,0.0012829674,0.00038030633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041094786,0.0015938568,0.0025350475,0.0038935388,0.0022498725,0.0038881262,0.0046955743,0.0037957337,0.006884179],"category_scores_gemma":[0.01457581,0.0027285225,0.0032877473,0.0024740973,0.001598012,0.0028657166,0.003578624,0.004745033,0.003358597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006937951,0.00025001419,0.005172933,0.00044530994,0.0005535185,0.0003727432,0.00046680192,0.4861888,0.01692403,0.055662636,0.014910679,0.41835877],"study_design_scores_gemma":[0.000024894476,0.000024364155,0.00060772296,0.000019937073,0.00003094701,0.00007276811,0.000022676473,0.9697398,0.0016502781,0.026835324,0.0009425698,0.000028694685],"about_ca_topic_score_codex":0.01638773,"about_ca_topic_score_gemma":0.020958057,"teacher_disagreement_score":0.01638773,"about_ca_system_score_codex":0.0018211138,"about_ca_system_score_gemma":0.0035430437,"threshold_uncertainty_score":0.032584667},"labels":[],"label_agreement":null},{"id":"W1483514369","doi":"10.1007/978-3-642-23629-7_8","title":"Sparse Multi-Shell Diffusion Imaging","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Mental Health","keywords":"Computer science; Spherical harmonics; Diffusion MRI; Shell (structure); Artificial intelligence; Representation (politics); Compressed sensing; Generalization; Pattern recognition (psychology); Artificial neural network; Computer vision; Algorithm; Magnetic resonance imaging; Physics; Mathematics; Materials science","score_opus":0.083009533607663,"score_gpt":0.33806608395518184,"score_spread":0.25505655034751884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1483514369","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067149713,0.000597869,0.9885018,0.00043339338,0.000061583436,0.0000176847,0.00011635493,0.00048558868,0.003070911],"genre_scores_gemma":[0.13322158,0.0019462052,0.85388714,0.0002125972,0.00017275002,0.000044157223,0.00053482654,0.0003560663,0.009624688],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986994,0.00003509585,0.000012028562,0.000029148612,0.000043931148,0.000009801448],"domain_scores_gemma":[0.999212,0.00025691892,0.00011789874,0.00021334496,0.00014351388,0.000056206038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004125784,0.0007254823,0.00050131284,0.0006518175,0.0002762066,0.001084296,0.00056987966,0.0010248072,0.0048729773],"category_scores_gemma":[0.0022737149,0.0005123702,0.00046558926,0.0010043756,0.0004425702,0.0015795609,0.0010468031,0.0009702099,0.0022249413],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031125892,0.00011064472,0.001989144,0.00070752105,0.00023785229,0.000712839,0.00025285583,0.083009616,0.2019155,0.07383131,0.018617928,0.61830354],"study_design_scores_gemma":[0.000032348744,0.00008734127,0.0013205752,0.00007316277,0.000114319446,0.003251175,0.00008042235,0.8216481,0.0837229,0.056516323,0.033097204,0.0000561986],"about_ca_topic_score_codex":0.00047854515,"about_ca_topic_score_gemma":0.0010535141,"teacher_disagreement_score":0.0048729773,"about_ca_system_score_codex":0.00015540693,"about_ca_system_score_gemma":0.00045121214,"threshold_uncertainty_score":0.016301751},"labels":[],"label_agreement":null},{"id":"W1489388295","doi":"10.1007/978-3-642-33418-4_36","title":"Sparse DSI: Learning DSI Structure for Denoising and Fast Imaging","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Diffusion MRI; Noise reduction; Artificial intelligence; SIGNAL (programming language); Diffusion; Pattern recognition (psychology); Dictionary learning; Computer vision; Algorithm; Image (mathematics); Magnetic resonance imaging; Physics","score_opus":0.035530827183147325,"score_gpt":0.3374550121171708,"score_spread":0.3019241849340235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489388295","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00075149996,0.00011764841,0.9969079,0.000089672285,0.000041571962,0.000022556826,0.00017350138,0.0016042169,0.00029151293],"genre_scores_gemma":[0.016969189,0.000550389,0.97757643,0.000119820616,0.00009236107,0.00013689739,0.0010059192,0.00081992435,0.002728962],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999602,0.00007904749,0.000024761282,0.000073693576,0.0001927836,0.000027689091],"domain_scores_gemma":[0.9990778,0.00040060692,0.000068324814,0.00019583126,0.00019052198,0.00006682844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011398899,0.001455108,0.0009921602,0.0010871736,0.0003660296,0.0013862356,0.0017703343,0.0017620374,0.008628285],"category_scores_gemma":[0.0048179263,0.0008498483,0.0009144838,0.0014512263,0.0006156065,0.0014525793,0.0018091885,0.0024396589,0.0044838083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035208795,0.000109519904,0.00060169376,0.00045655886,0.00014414873,0.0001743852,0.00012213866,0.07294827,0.0465141,0.03150677,0.045675553,0.8013948],"study_design_scores_gemma":[0.000056493875,0.00007543835,0.00034083493,0.00002898539,0.000030254367,0.0003002352,0.00003080219,0.91804594,0.028485445,0.030344548,0.022221578,0.000039367085],"about_ca_topic_score_codex":0.0020241202,"about_ca_topic_score_gemma":0.0033570493,"teacher_disagreement_score":0.008628285,"about_ca_system_score_codex":0.00037483545,"about_ca_system_score_gemma":0.0009974426,"threshold_uncertainty_score":0.028864443},"labels":[],"label_agreement":null},{"id":"W1496266809","doi":"10.1007/978-3-642-15705-9_69","title":"Probabilistic Anatomical Connectivity Using Completion Fields","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Probabilistic logic; Computer science; Diffusion; Diffusion MRI; SIGNAL (programming language); Imaging phantom; Artificial intelligence; Field (mathematics); Algorithm; Probabilistic analysis of algorithms; Machine learning; Data mining; Magnetic resonance imaging; Mathematics; Physics","score_opus":0.05624690948395681,"score_gpt":0.3600744338762137,"score_spread":0.30382752439225685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496266809","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005151657,0.00009213089,0.9935029,0.00012424198,0.000022074795,0.000021834288,0.00009105424,0.0004948763,0.00049922976],"genre_scores_gemma":[0.3719701,0.0005831645,0.619894,0.00012059734,0.00021038608,0.0002465421,0.0009408882,0.0006180902,0.005416232],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992292,0.000307256,0.000036623143,0.00018528574,0.00019060119,0.00005114876],"domain_scores_gemma":[0.99531555,0.002956666,0.00043854793,0.0006530448,0.00041591085,0.00022029116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002257206,0.0009638205,0.0015674521,0.0025182853,0.00063778664,0.0014648534,0.002355491,0.0017411778,0.004271551],"category_scores_gemma":[0.0088459,0.0013375476,0.0019409022,0.0020541844,0.00132178,0.003082867,0.001916616,0.0022838393,0.0009786591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026032448,0.00011911876,0.0009841957,0.00019073975,0.00015112331,0.00017034766,0.00015756776,0.6160871,0.0042074407,0.16060628,0.0059814993,0.21108444],"study_design_scores_gemma":[0.0000142468125,0.000019576724,0.000115856106,0.000007746367,0.000011413689,0.00005957326,0.000004852757,0.9291597,0.00052466954,0.06947002,0.0005987896,0.000013580641],"about_ca_topic_score_codex":0.006774819,"about_ca_topic_score_gemma":0.006102841,"teacher_disagreement_score":0.006774819,"about_ca_system_score_codex":0.0008175448,"about_ca_system_score_gemma":0.0011787018,"threshold_uncertainty_score":0.014289737},"labels":[],"label_agreement":null},{"id":"W1496884366","doi":"10.3171/2012.1.peds11363","title":"Corticospinal tract mapping in children with ruptured arteriovenous malformations using functionally guided diffusion-tensor imaging","year":2012,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Diffusion MRI; Corticospinal tract; Fractional anisotropy; Tractography; White matter; Motor cortex; Radiology; Magnetic resonance imaging; Neuroscience; Psychology","score_opus":0.06553312276105167,"score_gpt":0.31434234697393987,"score_spread":0.2488092242128882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496884366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982318,0.00038093104,0.0010151275,0.00006804609,0.0000049400896,0.000017173763,0.00005819131,0.000024678575,0.00019900619],"genre_scores_gemma":[0.99728286,0.00038743005,0.0021841421,0.00002079599,0.000006224997,0.000014288268,0.000055541557,0.000008099855,0.000040609968],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99958116,0.00010733004,0.000065971806,0.00010183894,0.00007347863,0.00007015687],"domain_scores_gemma":[0.99919707,0.00030474438,0.00026394258,0.00006273296,0.00007100194,0.000100560275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063277164,0.00064992986,0.0005243421,0.0012398006,0.0003369313,0.000342047,0.0002811859,0.0006594446,0.00038292585],"category_scores_gemma":[0.0031691047,0.00028334014,0.00030919292,0.00058692426,0.00077244214,0.0006723182,0.00038904676,0.00060351496,0.00011673063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035709402,0.00015775296,0.8980406,0.00021793775,0.00005798671,0.042746633,0.0012989875,0.0011882765,0.027463323,0.0001901826,0.0002560168,0.028025165],"study_design_scores_gemma":[0.000070657086,0.0018707362,0.79224324,0.000095267926,0.00013472987,0.18288383,0.001381296,0.003041864,0.016818866,0.00025975413,0.001150173,0.000049524657],"about_ca_topic_score_codex":0.0022778052,"about_ca_topic_score_gemma":0.0025685716,"teacher_disagreement_score":0.0022778052,"about_ca_system_score_codex":0.0004721534,"about_ca_system_score_gemma":0.00049710687,"threshold_uncertainty_score":0.004529059},"labels":[],"label_agreement":null},{"id":"W1497909821","doi":"10.1002/047134608x.w8258","title":"High Angular Resolution Diffusion Imaging (<scp>HARDI</scp>)","year":2015,"lang":"en","type":"other","venue":"Wiley Encyclopedia of Electrical and Electronics Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Tractography; Angular resolution (graph drawing); White matter; Diffusion; High resolution; Computer science; Geology; Neuroscience; Magnetic resonance imaging; Medicine; Remote sensing; Psychology; Physics; Radiology; Mathematics","score_opus":0.009248931267733814,"score_gpt":0.24429748537093068,"score_spread":0.23504855410319686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1497909821","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008708221,0.102681324,0.46869734,0.012339335,0.0094777765,0.00042951357,0.01292033,0.019925646,0.36482054],"genre_scores_gemma":[0.113182634,0.11927314,0.4208723,0.009825425,0.008879328,0.0009088175,0.017401684,0.006706017,0.3029507],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995541,0.00007506895,0.000046444664,0.00007837572,0.00021500367,0.00003105967],"domain_scores_gemma":[0.998993,0.00029868365,0.00013355665,0.00017999593,0.00030080555,0.00009403204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010002904,0.0009363546,0.00054949336,0.0021435195,0.00046978882,0.0018235138,0.0009083123,0.0013432321,0.06593763],"category_scores_gemma":[0.0028644826,0.00035048503,0.00031307363,0.0029115442,0.0007279977,0.0024013491,0.0018178455,0.0013727719,0.033223484],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014085532,0.000028223852,0.00042558482,0.0018449487,0.000066608736,0.0005340326,0.00006478007,0.0006473638,0.028057365,0.025956906,0.31751204,0.6247212],"study_design_scores_gemma":[0.000026114394,0.000075623255,0.0019828766,0.00048243563,0.000041707448,0.0038597004,0.000046470283,0.0037193424,0.037289623,0.01655747,0.9358225,0.00009607687],"about_ca_topic_score_codex":0.00058219157,"about_ca_topic_score_gemma":0.0011601284,"teacher_disagreement_score":0.06593763,"about_ca_system_score_codex":0.00045371262,"about_ca_system_score_gemma":0.00056120584,"threshold_uncertainty_score":0.22058338},"labels":[],"label_agreement":null},{"id":"W1499087426","doi":"10.1007/978-3-540-39903-2_26","title":"Visualization of Neural DTI Vector Fields Using Line Integral Convolution","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Diffusion MRI; Voxel; Tractography; Tensor field; Fractional anisotropy; Visualization; Fiber bundle; Artificial intelligence; Vector field; Anisotropy; Line integral; Tensor (intrinsic definition); Computer science; Bundle; Computer vision; Convolution (computer science); Line (geometry); Physics; Mathematics; Mathematical analysis; Artificial neural network; Geometry; Optics; Integral equation; Materials science","score_opus":0.07878309860122387,"score_gpt":0.36631929826678017,"score_spread":0.2875361996655563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1499087426","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013005892,0.00057570037,0.9750728,0.00044968253,0.00007274623,0.00004578475,0.00058685633,0.0065358547,0.0036546015],"genre_scores_gemma":[0.17365614,0.0018314304,0.81549406,0.00011253493,0.000083858315,0.00013368737,0.00081570476,0.0020893344,0.005783267],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999429,0.000013342476,0.0000051374627,0.000009147694,0.000021923384,0.0000075424337],"domain_scores_gemma":[0.99961287,0.00019815353,0.000044920194,0.00004117696,0.00006681559,0.00003601857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033460668,0.00065950275,0.0003361513,0.0010714903,0.00025880983,0.001905528,0.00057763123,0.0005526707,0.012663071],"category_scores_gemma":[0.0012796791,0.00037892623,0.00036097268,0.0011310908,0.00019587835,0.001097987,0.00056799065,0.0009636231,0.0016052909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003857988,0.00009101193,0.0010878869,0.0008508755,0.0001043633,0.0005996279,0.00063019013,0.08842046,0.16262616,0.056779698,0.040611345,0.6478126],"study_design_scores_gemma":[0.000049178103,0.000057508354,0.001359118,0.00011286143,0.0000371059,0.00085033634,0.00010873773,0.85187584,0.0705761,0.04377022,0.031133762,0.00006926335],"about_ca_topic_score_codex":0.0014955947,"about_ca_topic_score_gemma":0.0016639228,"teacher_disagreement_score":0.012663071,"about_ca_system_score_codex":0.00037052168,"about_ca_system_score_gemma":0.00055428833,"threshold_uncertainty_score":0.042362154},"labels":[],"label_agreement":null},{"id":"W1506092539","doi":"10.1002/mrm.25865","title":"Surface‐to‐volume ratio mapping of tumor microstructure using oscillating gradient diffusion weighted imaging","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Cancer Institute; National Institutes of Health; School of Medicine, New York University; National Institute of Biomedical Imaging and Bioengineering; York University; Center for Advanced Imaging Innovation and Research","keywords":"Thermal diffusivity; Ex vivo; Diffusion; In vivo; Nuclear magnetic resonance; Diffusion MRI; Effective diffusion coefficient; Chemistry; Range (aeronautics); Volume (thermodynamics); Materials science; Surface-area-to-volume ratio; Biophysics; Analytical Chemistry (journal); Biomedical engineering; Thermodynamics; Physics; Magnetic resonance imaging; Chromatography; Biology","score_opus":0.05642136463734083,"score_gpt":0.3310188081416106,"score_spread":0.2745974435042698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1506092539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9208973,0.0011155822,0.07697579,0.00007247421,0.0000074988416,0.000020237452,0.00010665014,0.00016215727,0.00064228097],"genre_scores_gemma":[0.9569863,0.001025721,0.04118626,0.00004212544,0.000015444928,0.000041398176,0.00015171734,0.000058922342,0.00049211114],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999298,0.000013331771,0.0000033942092,0.00002282021,0.000023721388,0.000007041723],"domain_scores_gemma":[0.9998456,0.00005100184,0.00005370438,0.000010634711,0.000025856114,0.000013074032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017989725,0.00030421047,0.00016030474,0.00041863142,0.00007264808,0.00027155847,0.00019125087,0.00024335209,0.00035488486],"category_scores_gemma":[0.0005726825,0.00013615703,0.000108369946,0.0002078938,0.00027462875,0.0004874908,0.00023033381,0.00019890736,0.00009398793],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052807765,0.000005865739,0.00058160716,0.00004142633,0.0000052027463,0.000019105977,0.000013585624,0.00053320016,0.99341935,0.00006420691,0.000019751382,0.0052438206],"study_design_scores_gemma":[0.000022223325,0.00033825904,0.031167839,0.000021356316,0.00005848838,0.00074633944,0.00006483551,0.039130744,0.9264986,0.0006505903,0.001267888,0.00003284376],"about_ca_topic_score_codex":0.0005311744,"about_ca_topic_score_gemma":0.00073773746,"teacher_disagreement_score":0.0005311744,"about_ca_system_score_codex":0.00017054056,"about_ca_system_score_gemma":0.00016235311,"threshold_uncertainty_score":0.0012373924},"labels":[],"label_agreement":null},{"id":"W150669400","doi":"10.1007/978-3-642-39094-4_67","title":"Reconstruction of HARDI Data Using a Split Bregman Optimization Approach","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion MRI; Noise (video); Artificial intelligence; SIGNAL (programming language); Noise reduction; Diffusion imaging; Algorithm; Signal reconstruction; Exploit; Signal-to-noise ratio (imaging); Pattern recognition (psychology); Computer vision; Signal processing; Image (mathematics); Magnetic resonance imaging","score_opus":0.11902295309021613,"score_gpt":0.3356993330657442,"score_spread":0.21667637997552805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W150669400","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016902385,0.00007993397,0.99651694,0.00017619896,0.000021754751,0.000023115777,0.00008038576,0.00025748526,0.0011539683],"genre_scores_gemma":[0.03297995,0.00022987643,0.96242017,0.00018147577,0.000036567824,0.00011931803,0.00045756032,0.00044098424,0.0031341973],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946445,0.00017076076,0.00003680177,0.0000690107,0.00021569803,0.00004333634],"domain_scores_gemma":[0.99899405,0.00042632394,0.000097637625,0.00021754166,0.00018779715,0.000076601216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017447461,0.0012006407,0.0014912417,0.0012742766,0.0006464553,0.0024528948,0.00172604,0.0022359386,0.004702988],"category_scores_gemma":[0.004581808,0.0012372985,0.0012736134,0.0018678362,0.0011499039,0.00201493,0.0031319582,0.0031681287,0.002296252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002593186,0.00010279839,0.0006683407,0.00048135148,0.00016943691,0.00031522615,0.00027988147,0.6340158,0.020521665,0.121185444,0.009979672,0.21202107],"study_design_scores_gemma":[0.000007996565,0.000014577231,0.00007669535,0.000016869872,0.0000065143745,0.00010412796,0.000018190996,0.9778151,0.0025874428,0.017245762,0.0020881179,0.000018576231],"about_ca_topic_score_codex":0.0017150898,"about_ca_topic_score_gemma":0.0019936326,"teacher_disagreement_score":0.004702988,"about_ca_system_score_codex":0.0006170683,"about_ca_system_score_gemma":0.0015329213,"threshold_uncertainty_score":0.015733063},"labels":[],"label_agreement":null},{"id":"W1508815940","doi":"10.1002/jmri.24256","title":"Correlation between fractional anisotropy and motor outcomes in one‐year‐old infants with periventricular brain injury","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Research Resources","keywords":"Fractional anisotropy; Diffusion MRI; Internal capsule; White matter; Medicine; Correlation; Treadmill; Physical medicine and rehabilitation; Physical therapy; Magnetic resonance imaging; Radiology","score_opus":0.02002616906693191,"score_gpt":0.3024408896021785,"score_spread":0.28241472053524663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508815940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974304,0.00006881145,0.000035726604,0.000007438309,0.0000012052818,0.0000020785362,0.000044231685,0.0000019010325,0.00009560633],"genre_scores_gemma":[0.99964106,0.000054305543,0.0000946737,0.0000038084613,0.0000016972691,0.0000070758206,0.00011498534,0.0000013476239,0.000081196624],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997162,0.00005850688,0.000036242793,0.000065981476,0.000071933064,0.00005103674],"domain_scores_gemma":[0.9980361,0.0003671504,0.0010341549,0.00008222658,0.00023364334,0.00024680197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005837629,0.00028989097,0.00026673437,0.0005622451,0.00019692254,0.00028020347,0.00020184672,0.00037663107,0.0007176457],"category_scores_gemma":[0.0041212356,0.00012206641,0.00017708252,0.00022430727,0.00033764512,0.0002196384,0.00028252442,0.00037632152,0.00016204812],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023888209,0.00006087483,0.99503714,0.000011394449,0.000025992042,0.00020711904,0.00012491515,0.00006887267,0.001256685,0.000011224043,0.00004112466,0.002915794],"study_design_scores_gemma":[0.0000014607999,0.00010911783,0.9992736,0.0000025106615,0.0000055950677,0.00026557533,0.00004401634,0.00004542847,0.0002207373,0.00000495481,0.000025768994,0.0000012767779],"about_ca_topic_score_codex":0.003638437,"about_ca_topic_score_gemma":0.00384548,"teacher_disagreement_score":0.003638437,"about_ca_system_score_codex":0.00027571223,"about_ca_system_score_gemma":0.00019767239,"threshold_uncertainty_score":0.0072345138},"labels":[],"label_agreement":null},{"id":"W1513935208","doi":"10.3389/fnins.2015.00257","title":"Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; National Center for Research Resources; F. Hoffmann-La Roche; Synarc; University of Southern California; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Bayer HealthCare; Meso Scale Diagnostics; National Science Foundation","keywords":"Neuroimaging; Connectome; Disease; Prodromal Stage; Alzheimer's disease; Human Connectome Project; Artificial intelligence; Singular value decomposition; Computer science; Alzheimer's Disease Neuroimaging Initiative; Logistic regression; Neuroscience; Diffusion MRI; Cognitive decline; Pattern recognition (psychology); Cognition; Medicine; Machine learning; Psychology; Cognitive impairment; Magnetic resonance imaging; Pathology; Dementia; Functional connectivity; Radiology","score_opus":0.15730349016295483,"score_gpt":0.41116882441069313,"score_spread":0.2538653342477383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1513935208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76970124,0.0018718727,0.22232872,0.0010189695,0.00014185229,0.0001016678,0.0006528709,0.001873673,0.0023092474],"genre_scores_gemma":[0.9492727,0.00029619777,0.04837569,0.000114644856,0.00010266805,0.000036860067,0.0008845725,0.00005905589,0.00085766206],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99935335,0.00022071536,0.000036221176,0.00019471563,0.00011734631,0.000077604236],"domain_scores_gemma":[0.99715626,0.0015634082,0.0002632001,0.00027624864,0.0005937849,0.00014714542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026419056,0.00082175346,0.0010462417,0.0018428059,0.0003284953,0.0006917245,0.00049400085,0.0009158463,0.0008110934],"category_scores_gemma":[0.009640251,0.00024443923,0.00061400916,0.0008076783,0.00039466628,0.0007870098,0.00061396556,0.0009975025,0.00060580485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014332993,0.00074935856,0.10465704,0.00021098775,0.00044644563,0.00033125788,0.0002929961,0.19615564,0.042895254,0.0021771295,0.010307195,0.64034337],"study_design_scores_gemma":[0.000034502715,0.00011961455,0.020634824,0.00002532164,0.00006446748,0.00011787875,0.00003369401,0.9718848,0.0037218344,0.0028741555,0.00046855383,0.00002029192],"about_ca_topic_score_codex":0.0037473997,"about_ca_topic_score_gemma":0.005923621,"teacher_disagreement_score":0.0037473997,"about_ca_system_score_codex":0.00038254602,"about_ca_system_score_gemma":0.00050546404,"threshold_uncertainty_score":0.013971865},"labels":[],"label_agreement":null},{"id":"W1520400319","doi":"10.1002/nbm.3104","title":"Effects of diffusion on high‐resolution quantitative <i>T</i><sub>2</sub> MRI","year":2014,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Nuclear magnetic resonance; Effective diffusion coefficient; White matter; Diffusion; Diffusion imaging; Spin echo; Diffusion MRI; Anisotropy; Physics; Resolution (logic); Isotropy; Chemistry; Magnetic resonance imaging; Optics; Medicine; Thermodynamics","score_opus":0.02169109480085831,"score_gpt":0.3219398308283474,"score_spread":0.3002487360274891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1520400319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49590877,0.01979839,0.47758055,0.00082268706,0.00019001657,0.00016864424,0.00023017215,0.0008199335,0.0044809626],"genre_scores_gemma":[0.8644725,0.007588698,0.12415214,0.00037640546,0.00006526543,0.0001963851,0.0001309736,0.00039578052,0.0026218938],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989807,0.00040574707,0.00008102097,0.00016480255,0.00029129538,0.000076485005],"domain_scores_gemma":[0.9954596,0.0034261192,0.00052908727,0.00019423573,0.00032303244,0.00006784858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029624866,0.0011736265,0.00043141987,0.0003944641,0.0003780954,0.0006598951,0.0005580641,0.00078032067,0.0010423543],"category_scores_gemma":[0.00853014,0.0005548928,0.00033914705,0.0003693304,0.0009618601,0.0012294381,0.00084062736,0.0007361212,0.00030312885],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004774019,0.000018094723,0.0017096453,0.000643116,0.000047909565,0.00049121556,0.00026306443,0.0046104114,0.9697355,0.0013465232,0.00016326475,0.020493833],"study_design_scores_gemma":[0.000028345446,0.00047074078,0.009220825,0.0000820245,0.00014292958,0.001768913,0.00010805159,0.024447523,0.95777553,0.0012363049,0.004642457,0.00007636137],"about_ca_topic_score_codex":0.0017764948,"about_ca_topic_score_gemma":0.0023436372,"teacher_disagreement_score":0.0029624866,"about_ca_system_score_codex":0.0006549924,"about_ca_system_score_gemma":0.00054464006,"threshold_uncertainty_score":0.01566732},"labels":[],"label_agreement":null},{"id":"W1525443459","doi":"10.1002/hbm.22441","title":"Gray matter alterations in early aging: A diffusion magnetic resonance imaging study","year":2013,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Gray (unit); Neuroscience; Magnetic resonance imaging; Neuroimaging; Precuneus; Context (archaeology); Psychology; Hum; Brain aging; Anatomy; Functional magnetic resonance imaging; Biology; Medicine; Nuclear medicine; Cognition; Radiology","score_opus":0.04402403207313782,"score_gpt":0.3263843318786671,"score_spread":0.2823602998055293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525443459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995887,0.0029033013,0.00060124387,0.0000472838,0.0000064164115,0.000014318404,0.00007294657,0.0000063976418,0.00046111894],"genre_scores_gemma":[0.9985366,0.0007460933,0.00041567907,0.000019935715,0.000019430308,0.000005362279,0.00005438457,0.000001703127,0.00020081067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992144,0.000015444566,0.000008090735,0.000029107943,0.000014913502,0.000011025279],"domain_scores_gemma":[0.9997844,0.000026843365,0.000083680054,0.000020861738,0.00003258087,0.00005174115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005343497,0.00029364735,0.0002559137,0.001021241,0.0002267472,0.00025397423,0.00015071606,0.00026322325,0.00046137645],"category_scores_gemma":[0.0005462791,0.00010449793,0.00013601221,0.00045826987,0.00034732858,0.00029495684,0.00027129115,0.0001791142,0.00013335134],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010230358,0.00035375377,0.8808863,0.00023749497,0.00026503953,0.0041589565,0.0016057297,0.00037979195,0.07184869,0.0005970486,0.0003930262,0.038251147],"study_design_scores_gemma":[0.000009816024,0.0004805676,0.99282175,0.000012166235,0.0000699079,0.0030999929,0.00019237779,0.000289154,0.0019044931,0.0003121754,0.0008010033,0.000006642311],"about_ca_topic_score_codex":0.0014378245,"about_ca_topic_score_gemma":0.0014322835,"teacher_disagreement_score":0.0014378245,"about_ca_system_score_codex":0.00015863182,"about_ca_system_score_gemma":0.00020680446,"threshold_uncertainty_score":0.0028589368},"labels":[],"label_agreement":null},{"id":"W1525759131","doi":"10.1002/jmri.24604","title":"Fast computation of myelin maps from MRI T<sub>2</sub>relaxation data using multicore CPU and graphics card parallelization","year":2014,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Multi-core processor; Parallel computing; MATLAB; Computation; Graphics; CUDA; Graphics hardware; Computational science; Relaxation (psychology); Algorithm; Computer graphics (images)","score_opus":0.051499703464215535,"score_gpt":0.3265626779576491,"score_spread":0.27506297449343353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525759131","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023130758,0.000093489194,0.97373736,0.0000679802,0.000022503495,0.000058677146,0.00011471152,0.002160323,0.0006142798],"genre_scores_gemma":[0.06301918,0.000082207436,0.9352989,0.000037196656,0.000011400455,0.00013054523,0.00019424174,0.00021077784,0.0010155817],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997298,0.00004096419,0.000023607201,0.00006755587,0.00011324251,0.000024886067],"domain_scores_gemma":[0.9991698,0.00028374957,0.00007685604,0.000112263726,0.00031342986,0.000043936823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005478763,0.0008844892,0.00049908145,0.0005890437,0.0003063263,0.00071104907,0.0010569758,0.00057390454,0.0024640593],"category_scores_gemma":[0.0024145963,0.00036781863,0.000502134,0.00059853215,0.0003454094,0.00081079744,0.000690425,0.00046635992,0.00094723766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007559378,0.00015281227,0.006985228,0.00046045912,0.0003649663,0.00048765476,0.0003270361,0.12000434,0.1895505,0.0047858604,0.0061460775,0.6699792],"study_design_scores_gemma":[0.00011979079,0.00018656168,0.005289666,0.000030894065,0.00006036594,0.000619641,0.000060329618,0.90075994,0.082097225,0.0039397976,0.0067830742,0.00005262093],"about_ca_topic_score_codex":0.003086577,"about_ca_topic_score_gemma":0.0056641176,"teacher_disagreement_score":0.003086577,"about_ca_system_score_codex":0.00051835313,"about_ca_system_score_gemma":0.00094682665,"threshold_uncertainty_score":0.008243084},"labels":[],"label_agreement":null},{"id":"W1525872531","doi":"10.1111/j.1528-1167.2007.01105.x","title":"Evaluation of Subcortical White Matter and Deep White Matter Tracts in Malformations of Cortical Development","year":2007,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Pathology; Cortical dysplasia; Anatomy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06337090375870061,"score_gpt":0.3646028097670102,"score_spread":0.3012319060083096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525872531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992274,0.000095974116,0.00033236403,0.0000058214496,4.6666537e-7,0.000009471375,0.00003945518,0.000005939019,0.0002831766],"genre_scores_gemma":[0.9989623,0.00007150311,0.00072125637,0.000004733219,0.0000010713005,0.000008084932,0.000053436535,0.0000020698774,0.00017564963],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998115,0.000039791747,0.000022078104,0.000050928647,0.000040316205,0.00003546625],"domain_scores_gemma":[0.999569,0.000063246516,0.00016572459,0.00002193752,0.00008740272,0.00009261266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043830287,0.00037007054,0.00014744597,0.0011395931,0.00020190254,0.00024660406,0.00014235948,0.00017216148,0.0018417186],"category_scores_gemma":[0.0010039026,0.00012375752,0.00009072009,0.0003328282,0.0003693966,0.00022004798,0.00023521183,0.0001470259,0.00015444098],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022757986,0.000042778283,0.9504492,0.00007906862,0.000031063122,0.0021825084,0.00023026229,0.00013134585,0.03514125,0.00005970479,0.00006350307,0.0113618225],"study_design_scores_gemma":[0.0000075873427,0.00026725346,0.9849915,0.000016037793,0.000020107766,0.007948148,0.00019651928,0.00028572045,0.0060178307,0.000051531235,0.00019312689,0.000004610795],"about_ca_topic_score_codex":0.002403572,"about_ca_topic_score_gemma":0.004748748,"teacher_disagreement_score":0.002403572,"about_ca_system_score_codex":0.00022072838,"about_ca_system_score_gemma":0.0003393419,"threshold_uncertainty_score":0.0061611533},"labels":[],"label_agreement":null},{"id":"W1530581289","doi":"10.1007/978-3-642-15705-9_74","title":"Fast and Accurate Reconstruction of HARDI Data Using Compressed Sensing","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Computer science; Compressed sensing; Diffusion MRI; Diffusion; Pattern recognition (psychology); Artificial intelligence; Data mining; Magnetic resonance imaging","score_opus":0.09438748449517516,"score_gpt":0.3712630114860339,"score_spread":0.27687552699085877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1530581289","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01143316,0.00037353789,0.9843231,0.00076365046,0.0001545602,0.00004353339,0.00036301478,0.0005607313,0.0019846708],"genre_scores_gemma":[0.16241065,0.0008991741,0.8316149,0.0003710282,0.00020574263,0.00010630652,0.0011389868,0.00023944167,0.0030137924],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994573,0.000102479324,0.00003569715,0.000050760566,0.00030538792,0.000048393034],"domain_scores_gemma":[0.9980233,0.0010237382,0.00016578044,0.00044315017,0.00024500783,0.000099184705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007834679,0.0010167524,0.00093093584,0.0007637889,0.0003527223,0.0014183518,0.00082991854,0.0013957847,0.003081025],"category_scores_gemma":[0.0052558538,0.00066325,0.0004890134,0.0013129327,0.00074790855,0.0017815026,0.0018438444,0.002547279,0.0013725889],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011085646,0.0001740849,0.0018974922,0.0009173765,0.00013218973,0.00096525624,0.0004076799,0.23374882,0.1783482,0.043083068,0.017510591,0.5217067],"study_design_scores_gemma":[0.000033302862,0.00005950232,0.0005203836,0.00003575541,0.0000109965395,0.0006086584,0.000058010148,0.9552709,0.024646608,0.014675483,0.0040358733,0.00004455128],"about_ca_topic_score_codex":0.0011743428,"about_ca_topic_score_gemma":0.0015850464,"teacher_disagreement_score":0.003081025,"about_ca_system_score_codex":0.00022714231,"about_ca_system_score_gemma":0.00072536996,"threshold_uncertainty_score":0.010307074},"labels":[],"label_agreement":null},{"id":"W1533378118","doi":"10.1007/978-3-642-15705-9_71","title":"Symmetric Positive-Definite Cartesian Tensor Orientation Distribution Functions (CT-ODF)","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cartesian coordinate system; Tensor (intrinsic definition); Cartesian tensor; Diffusion MRI; Orientation (vector space); Tensor field; Parametrization (atmospheric modeling); Computer science; Positive-definite matrix; Mathematical analysis; Mathematics; Pure mathematics; Geometry; Physics; Tensor density; Exact solutions in general relativity; Optics","score_opus":0.023883811653267608,"score_gpt":0.3153876280106692,"score_spread":0.29150381635740163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533378118","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069634398,0.00029856994,0.98748606,0.0002541767,0.0001431728,0.00005411554,0.00065086986,0.00037837887,0.003771153],"genre_scores_gemma":[0.19769147,0.0016934982,0.7845009,0.0004334716,0.0002700762,0.00024276073,0.0018201466,0.00081103964,0.012536507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946684,0.00015800449,0.00003865514,0.00010271327,0.00017621901,0.00005765193],"domain_scores_gemma":[0.9976006,0.0004663188,0.00041716002,0.00052569824,0.0007664483,0.00022374412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016285931,0.0012157874,0.00049179804,0.0011884165,0.00039553258,0.0017516079,0.0009577592,0.0012416366,0.0073882076],"category_scores_gemma":[0.005737646,0.00030163466,0.00049266417,0.0012982282,0.0011355532,0.00204661,0.0008928878,0.0013028645,0.0029084592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025604988,0.000099724275,0.002000323,0.00045926307,0.00003935633,0.00047307677,0.00028137767,0.0328258,0.02015565,0.50704753,0.029376421,0.40698537],"study_design_scores_gemma":[0.00004764711,0.00012418977,0.0027443913,0.00015938283,0.000035167235,0.0028650893,0.00026521622,0.4629812,0.017743256,0.45500895,0.05785991,0.00016558815],"about_ca_topic_score_codex":0.0018244643,"about_ca_topic_score_gemma":0.0017532262,"teacher_disagreement_score":0.0073882076,"about_ca_system_score_codex":0.00040172203,"about_ca_system_score_gemma":0.0013208941,"threshold_uncertainty_score":0.02471602},"labels":[],"label_agreement":null},{"id":"W1536516995","doi":"10.1016/b978-0-444-53355-5.00014-2","title":"Real-time functional magnetic imaging—brain–computer interface and virtual reality","year":2011,"lang":"en","type":"review","venue":"Progress in brain research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec en Outaouais; Université du Québec à Montréal; Université du Québec à Trois-Rivières; Institut Philippe Pinel de Montréal","funders":"Solar Energy Technologies Office; Canadian Institutes of Health Research","keywords":"Virtual reality; Brain–computer interface; Interface (matter); Computer science; Human–computer interaction; Functional Brain Imaging; Computer graphics (images); Psychology; Neuroscience; Neuroimaging; Operating system; Electroencephalography","score_opus":0.25519859627306263,"score_gpt":0.5071566394127673,"score_spread":0.2519580431397047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536516995","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024489005,0.9950075,0.0019865201,0.00030996854,0.0002614519,0.000010229308,0.000024766416,0.000029894174,0.0021248688],"genre_scores_gemma":[0.0020518359,0.9934411,0.0021232744,0.00032759344,0.0005752603,0.00001815814,0.00006542116,0.0000072370813,0.0013901361],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996996,0.000050002967,0.000035699402,0.00006513449,0.00012738103,0.000022128792],"domain_scores_gemma":[0.99925274,0.00042296955,0.00008808723,0.000025882266,0.00016943204,0.000040923955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069950917,0.0012236101,0.0015829349,0.0021098596,0.00020020007,0.0011266067,0.0015261605,0.0015344963,0.0033407183],"category_scores_gemma":[0.0012213861,0.0003509058,0.0004815983,0.0027771972,0.00085961533,0.001656089,0.0006579201,0.0015534253,0.0029693255],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050774644,0.000080348924,0.00012154165,0.005205138,0.00005618242,0.0001258792,0.000024822733,0.0003918578,0.0020627,0.002396463,0.014767679,0.9747167],"study_design_scores_gemma":[0.00003907299,0.0002459113,0.0026520381,0.0031222745,0.0001863206,0.005021066,0.00010915111,0.001104598,0.0029205768,0.009131553,0.97537607,0.000091182286],"about_ca_topic_score_codex":0.0017393404,"about_ca_topic_score_gemma":0.0023064679,"teacher_disagreement_score":0.0033407183,"about_ca_system_score_codex":0.0004508009,"about_ca_system_score_gemma":0.0009098953,"threshold_uncertainty_score":0.011175811},"labels":[],"label_agreement":null},{"id":"W1536611676","doi":"10.1002/hbm.22715","title":"Striatal shape abnormalities as novel neurodevelopmental endophenotypes in schizophrenia: A longitudinal study","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children; Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; National Human Genome Research Institute; University of Toronto; Government of Ontario; Weston Brain Institute; Alzheimer's Society; National Institute of Mental Health; Ontario Brain Institute; Michael J. Fox Foundation for Parkinson's Research","keywords":"Endophenotype; Psychology; Globus pallidus; Neuroscience; Schizophrenia (object-oriented programming); Basal ganglia; Cognition; Psychiatry; Central nervous system","score_opus":0.11409521056844762,"score_gpt":0.35374477765786844,"score_spread":0.2396495670894208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536611676","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999079,0.00014225267,0.00020531756,0.0000370962,0.0000025934723,0.000009276252,0.00026212574,0.000005677548,0.00025661686],"genre_scores_gemma":[0.99870694,0.0001460324,0.00033172237,0.000018829498,0.000004569664,0.0000147325545,0.00049903657,0.0000063157054,0.00027183906],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968946,0.00007790839,0.000028263868,0.000089515124,0.00006578882,0.000049063765],"domain_scores_gemma":[0.9987685,0.00009316507,0.0004683033,0.00015864984,0.0002897577,0.00022158811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009999875,0.00030632835,0.0002483146,0.0012012263,0.0007236797,0.00061974383,0.00024589713,0.0003980368,0.00079373515],"category_scores_gemma":[0.0016362299,0.000283462,0.0003862933,0.00069211476,0.00033995925,0.0005427987,0.0008173064,0.0005452491,0.00017865587],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023143241,0.00008083391,0.99035454,0.000009019836,0.000084641186,0.00034620272,0.0006224985,0.0000644399,0.003651725,0.000056328307,0.00009702992,0.0044013024],"study_design_scores_gemma":[0.0000033441306,0.00014555884,0.99853754,0.000005277911,0.00003206258,0.00042224542,0.0002195288,0.00011589843,0.00024378378,0.00004827966,0.00022069886,0.0000058166042],"about_ca_topic_score_codex":0.009888703,"about_ca_topic_score_gemma":0.013675713,"teacher_disagreement_score":0.009888703,"about_ca_system_score_codex":0.0004355027,"about_ca_system_score_gemma":0.00058414496,"threshold_uncertainty_score":0.01966232},"labels":[],"label_agreement":null},{"id":"W1537667007","doi":"10.1097/00004647-200010000-00013","title":"Does Labeled α-Methyl-L-Tryptophan Image ONLY Blood–Brain Barrier Transport of Tryptophan?","year":2000,"lang":"en","type":"letter","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Tryptophan; Blood–brain barrier; Chemistry; Neuroscience; Biophysics; Biochemistry; Biology; Central nervous system; Amino acid","score_opus":0.015682009674359256,"score_gpt":0.286477622615402,"score_spread":0.27079561294104276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537667007","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018611673,0.0043529775,0.002553804,0.950675,0.014233112,0.00005199783,0.00010446479,0.00021086413,0.009206088],"genre_scores_gemma":[0.20410268,0.015247122,0.0066178776,0.65374607,0.098286524,0.00030681348,0.00018579318,0.00014630434,0.02136084],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99959415,0.00010505248,0.0000568361,0.00006219905,0.00009644589,0.00008534591],"domain_scores_gemma":[0.99750537,0.0017339141,0.00017086446,0.000099471414,0.00028791657,0.00020249754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013838995,0.000680907,0.0012046649,0.00040885556,0.0011990132,0.0016031982,0.001469049,0.031388894,0.004634471],"category_scores_gemma":[0.008260789,0.0004661106,0.0008512857,0.00034005553,0.002163838,0.0036404827,0.0006017662,0.014115565,0.0040636],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032475528,0.00049506046,0.007057202,0.0010262828,0.0002419164,0.14641593,0.0005506461,0.0006057234,0.014554432,0.013173815,0.6974246,0.115206845],"study_design_scores_gemma":[0.0032717027,0.00148081,0.0094198035,0.0006098129,0.0008208012,0.1793026,0.002096377,0.009741639,0.025934858,0.062879264,0.7040583,0.00038408156],"about_ca_topic_score_codex":0.0021531056,"about_ca_topic_score_gemma":0.0020637214,"teacher_disagreement_score":0.031388894,"about_ca_system_score_codex":0.0022790409,"about_ca_system_score_gemma":0.0007347174,"threshold_uncertainty_score":0.0165357},"labels":[],"label_agreement":null},{"id":"W1545733638","doi":"10.1111/j.1528-1167.2011.03149.x","title":"Diffusion tensor imaging in temporal lobe epilepsy","year":2011,"lang":"en","type":"review","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Temporal lobe; Diffusion MRI; White matter; Epilepsy; Neuroscience; Psychology; Neuroimaging; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.13661580210335458,"score_gpt":0.40329472578486264,"score_spread":0.26667892368150803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1545733638","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000741561,0.9991128,0.000065008535,0.00015944836,0.00007010816,0.0000024091555,0.000008544522,0.0000037554846,0.0005038159],"genre_scores_gemma":[0.0007144146,0.9985145,0.00013951834,0.000083597755,0.00015368093,0.000003649109,0.000020507094,0.000001084612,0.00036909484],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99980706,0.00003888026,0.000043517088,0.000030465877,0.0000647645,0.000015375745],"domain_scores_gemma":[0.99953544,0.0001836972,0.0001101611,0.000017450075,0.00011498262,0.000038218346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072642486,0.0013515996,0.0017939617,0.0046825022,0.00025746285,0.0009192073,0.00080345897,0.0010768238,0.0032235656],"category_scores_gemma":[0.0009681872,0.00036321298,0.00049935415,0.004509589,0.00091856235,0.001565496,0.00077424396,0.0014365653,0.0030736758],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004825606,0.000046711288,0.00041767338,0.011215522,0.00011790909,0.00048421512,0.000072492825,0.0003164307,0.00090644864,0.0018463085,0.026597163,0.9579309],"study_design_scores_gemma":[0.000044014443,0.00010947994,0.005202586,0.008497992,0.00023420826,0.010508005,0.00017951189,0.00024894302,0.0006351889,0.0053284205,0.9689577,0.000053912147],"about_ca_topic_score_codex":0.0033255843,"about_ca_topic_score_gemma":0.0046386635,"teacher_disagreement_score":0.0046825022,"about_ca_system_score_codex":0.00073636783,"about_ca_system_score_gemma":0.0013213143,"threshold_uncertainty_score":0.010783911},"labels":[],"label_agreement":null},{"id":"W1548276524","doi":"10.1007/978-3-540-85988-8_34","title":"Joint Segmentation of Thalamic Nuclei from a Population of Diffusion Tensor MR Images","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health","keywords":"Segmentation; Computer science; Artificial intelligence; Diffusion MRI; Population; Pattern recognition (psychology); Cluster analysis; Scale-space segmentation; Market segmentation; Image segmentation; Consistency (knowledge bases); Computer vision; Magnetic resonance imaging; Medicine","score_opus":0.042578165811634254,"score_gpt":0.31693476319321184,"score_spread":0.2743565973815776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548276524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5461018,0.0019851606,0.4473696,0.00041904085,0.000099434255,0.00013263673,0.0010183625,0.0013222041,0.0015518294],"genre_scores_gemma":[0.8649598,0.00079332484,0.12908241,0.00006107513,0.000119407574,0.00008329889,0.0023508351,0.00026959745,0.0022803228],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996183,0.00006194174,0.00002237002,0.00013791348,0.00009425552,0.00006514565],"domain_scores_gemma":[0.9990584,0.00023335931,0.00014695697,0.00014340835,0.0003422817,0.0000756086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013803737,0.00077233097,0.0011177362,0.0020826298,0.0004977804,0.0016381635,0.00094613095,0.0011669252,0.00090618577],"category_scores_gemma":[0.0031838361,0.0006166512,0.0014202509,0.0021081252,0.0004976269,0.0006855299,0.00070748356,0.0006638909,0.00060931046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019299127,0.00033303586,0.048591595,0.00041628213,0.0010372804,0.0009807589,0.0011187932,0.07768987,0.37523225,0.004171606,0.0048002372,0.48369846],"study_design_scores_gemma":[0.0000867852,0.00040916484,0.10245571,0.0000743814,0.00086025824,0.0021424827,0.0004937749,0.7727123,0.10399935,0.012535242,0.0040880605,0.00014249986],"about_ca_topic_score_codex":0.009391286,"about_ca_topic_score_gemma":0.015424386,"teacher_disagreement_score":0.009391286,"about_ca_system_score_codex":0.0006633527,"about_ca_system_score_gemma":0.0011278496,"threshold_uncertainty_score":0.018673241},"labels":[],"label_agreement":null},{"id":"W1548601077","doi":"10.1002/hbm.22145","title":"A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults","year":2012,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Cancer Institute; National Institute of Mental Health; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Psychology; Openness to experience; Personality; Extraversion and introversion; Big Five personality traits; Agreeableness; Inferior parietal lobule; Neuroticism; Conscientiousness; Brain size; Lateralization of brain function; Developmental psychology; Cognition; Neuroscience; Magnetic resonance imaging; Social psychology; Medicine","score_opus":0.1885079530509189,"score_gpt":0.3825435778354087,"score_spread":0.1940356247844898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548601077","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99956566,0.000077358745,0.0001513512,0.000012491894,0.00000294141,0.000006672675,0.00008828557,0.0000028303239,0.000092374365],"genre_scores_gemma":[0.9994541,0.000042621978,0.00018072866,0.000012608648,0.0000051545476,0.000009196856,0.0001532615,0.0000013459719,0.00014104159],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999811,0.00005674432,0.000015758593,0.000052200492,0.0000301441,0.00003415715],"domain_scores_gemma":[0.9991936,0.00011664132,0.00026868406,0.000105997424,0.000117033094,0.00019792466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006786978,0.00023855284,0.00019635705,0.000417494,0.00034516864,0.00028463706,0.0001425551,0.00035093792,0.00057899137],"category_scores_gemma":[0.0015574226,0.00024295496,0.00024425006,0.0003519937,0.00017870784,0.00032015936,0.00024128525,0.0004145135,0.00016718007],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045367374,0.00014368608,0.9940732,0.000009053948,0.00011986293,0.00012387849,0.0002133711,0.000048596714,0.0015895948,0.0000159534,0.000063124666,0.0031458375],"study_design_scores_gemma":[0.00000775559,0.00023639321,0.9993573,0.0000010311558,0.00001586906,0.00009801474,0.00004949819,0.00010530962,0.000056190842,0.00001267634,0.000057790272,0.0000022755794],"about_ca_topic_score_codex":0.0030674809,"about_ca_topic_score_gemma":0.0037805247,"teacher_disagreement_score":0.0030674809,"about_ca_system_score_codex":0.0001378083,"about_ca_system_score_gemma":0.00019159328,"threshold_uncertainty_score":0.0060992837},"labels":[],"label_agreement":null},{"id":"W1548679134","doi":"10.1002/mrm.24987","title":"Oscillating gradient spin‐echo (OGSE) diffusion tensor imaging of the human brain","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Fondation pour la Recherche Médicale","keywords":"Diffusion MRI; White matter; Nuclear magnetic resonance; Splenium; Corpus callosum; Fractional anisotropy; Spin echo; Human brain; Cingulum (brain); Physics; Nuclear medicine; Magnetic resonance imaging; Chemistry; Medicine; Anatomy; Neuroscience; Psychology; Radiology","score_opus":0.03501310678795453,"score_gpt":0.33755879262844846,"score_spread":0.3025456858404939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548679134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98250854,0.0019044279,0.014283108,0.00013450495,0.00002077289,0.00004063738,0.00014442722,0.00006304301,0.0009004137],"genre_scores_gemma":[0.97810054,0.0014154112,0.019417293,0.00008278625,0.000034470315,0.000036381945,0.00026171078,0.000023196895,0.00062806276],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990165,0.00002988953,0.000008388928,0.000023441124,0.00002457354,0.000012109029],"domain_scores_gemma":[0.99961406,0.0001689496,0.00008001281,0.00003469841,0.000070639086,0.000031686737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047758906,0.00036851256,0.0001874089,0.00034284426,0.00010979959,0.0002609153,0.0001749649,0.00029126284,0.0010333164],"category_scores_gemma":[0.0019893232,0.0001245943,0.00012446998,0.00023146915,0.0004931307,0.00037811793,0.00021251521,0.00015113414,0.00020838797],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026073556,0.00017136129,0.102261625,0.00081860775,0.0003032946,0.0011721223,0.00051367347,0.0050942237,0.69440764,0.0010029605,0.0010147996,0.19063233],"study_design_scores_gemma":[0.00032054793,0.004024767,0.74167144,0.00019478388,0.0004851368,0.014136163,0.00049075764,0.024867909,0.1970508,0.0072686505,0.009393024,0.0000959924],"about_ca_topic_score_codex":0.0009345903,"about_ca_topic_score_gemma":0.0014657408,"teacher_disagreement_score":0.0010333164,"about_ca_system_score_codex":0.00010627381,"about_ca_system_score_gemma":0.00020986507,"threshold_uncertainty_score":0.0034567714},"labels":[],"label_agreement":null},{"id":"W1555964684","doi":"10.1111/j.1753-4887.2010.00327.x","title":"A primer for brain imaging: a tool for evidence-based studies of nutrition?","year":2010,"lang":"en","type":"review","venue":"Nutrition Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institutes of Health; Canadian Institutes of Health Research; FrieslandCampina; Pfizer; European Commission; Royal Society; Danone; PepsiCo","keywords":"Magnetoencephalography; Brain function; Brain Structure and Function; Neuroimaging; Observational study; Brain activity and meditation; Neuroscience; Psychology; Human brain; Functional Brain Imaging; Functional magnetic resonance imaging; Randomized controlled trial; Magnetic resonance imaging; Brain aging; Electroencephalography; Medicine; Pathology; Cognition; Radiology","score_opus":0.4072667511973302,"score_gpt":0.5307548116773119,"score_spread":0.12348806047998168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555964684","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000057878337,0.9116386,0.008407704,0.06955669,0.00791901,0.0000867911,0.000077791396,0.000050447343,0.0022049327],"genre_scores_gemma":[0.0015035571,0.90049857,0.03153031,0.047698848,0.015602673,0.00048095812,0.00009765192,0.000076116485,0.0025113865],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925479,0.0043863147,0.0012635012,0.00041310786,0.001277648,0.0001115028],"domain_scores_gemma":[0.97238255,0.023040036,0.0010696375,0.00075475423,0.0021409844,0.0006120153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01582171,0.002480675,0.004072305,0.007751685,0.001160129,0.005021174,0.002798528,0.013474993,0.005121617],"category_scores_gemma":[0.023529034,0.0012139151,0.0014730366,0.0043806206,0.008565733,0.016392404,0.0030479217,0.02048544,0.0050349543],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019107558,0.00016825303,0.00040634495,0.02265065,0.00023201121,0.00087684713,0.0013869986,0.0004311638,0.003353953,0.14648159,0.29393268,0.5298884],"study_design_scores_gemma":[0.000033887714,0.00012391084,0.00041922295,0.01716232,0.00006972585,0.0015909505,0.0005051904,0.00018117912,0.0003386985,0.081054814,0.8984514,0.0000686899],"about_ca_topic_score_codex":0.0015663966,"about_ca_topic_score_gemma":0.0016425374,"teacher_disagreement_score":0.01582171,"about_ca_system_score_codex":0.0025594218,"about_ca_system_score_gemma":0.0040891957,"threshold_uncertainty_score":0.08367419},"labels":[],"label_agreement":null},{"id":"W1557791310","doi":"10.1002/jmri.24424","title":"Symmetry of the fornix using diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; National Research Council Canada; National Research Council Institute for Biodiagnostics; University of Winnipeg; Alberta Innovates","funders":"Manitoba Health Research Council","keywords":"Tractography; Fornix; Diffusion MRI; Fractional anisotropy; Physics; Magnetic resonance imaging; Nuclear magnetic resonance; Symmetry (geometry); Medicine; Mathematics; Psychology; Radiology; Neuroscience; Geometry","score_opus":0.029181777633138926,"score_gpt":0.31313057351235196,"score_spread":0.283948795879213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557791310","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743561,0.0005748073,0.021229558,0.00013153547,0.000019530877,0.00017563111,0.0009133899,0.00020271465,0.0023967668],"genre_scores_gemma":[0.9895,0.00014268745,0.009327971,0.000012983226,0.000012956953,0.000041032617,0.00038374498,0.000049908576,0.0005286676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996074,0.00007051806,0.00004565358,0.00014610957,0.00009324812,0.000037123107],"domain_scores_gemma":[0.99901533,0.00012107755,0.00042941113,0.00024428222,0.00014229775,0.000047557893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010930285,0.0007931515,0.00036955407,0.0014273049,0.00034835312,0.0010141004,0.00033661022,0.00041095805,0.0027507388],"category_scores_gemma":[0.0034903996,0.00019443141,0.00035783488,0.00051208,0.0006637043,0.000961812,0.0004332724,0.00024366668,0.00045029089],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031078658,0.0002542107,0.42283508,0.00083123177,0.0009531819,0.004038427,0.0034174218,0.005604454,0.30598772,0.004774417,0.002635463,0.24556054],"study_design_scores_gemma":[0.00007995579,0.0007669723,0.92823803,0.000110605746,0.00021965994,0.012363623,0.0005536699,0.012696416,0.03659788,0.0049206396,0.0033695227,0.000082967876],"about_ca_topic_score_codex":0.0037355,"about_ca_topic_score_gemma":0.005429891,"teacher_disagreement_score":0.0037355,"about_ca_system_score_codex":0.00041376278,"about_ca_system_score_gemma":0.00064037007,"threshold_uncertainty_score":0.009202063},"labels":[],"label_agreement":null},{"id":"W1565146755","doi":"10.71781/32272","title":"Anatomo-functional magnetic resonance imaging of the spinal cord and its application to the characterization of spinal lesions in cats","year":2008,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Université de Montréal; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale","keywords":"Spinal cord; White matter; Spinal cord injury; Magnetic resonance imaging; Medicine; Central nervous system; Neuroscience; Diffusion MRI; Functional magnetic resonance imaging; Paralysis; Psychology; Radiology; Surgery","score_opus":0.05947184844213551,"score_gpt":0.37398807487980196,"score_spread":0.31451622643766647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565146755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.968965,0.0013457184,0.026601994,0.00019614887,0.000016437663,0.00016831381,0.00018752782,0.00008694662,0.0024319014],"genre_scores_gemma":[0.9618792,0.0017483131,0.03336616,0.00005233427,0.000008364137,0.00010876528,0.00016370494,0.000018033985,0.0026551632],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999596,0.0000060466978,0.0000030326225,0.000011857548,0.000010978001,0.000008520316],"domain_scores_gemma":[0.9998035,0.00004848127,0.00003671178,0.000023987292,0.00005506819,0.00003234314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021533034,0.00015334159,0.000093143004,0.0005214334,0.00013409562,0.00027148574,0.00019177586,0.0005060965,0.0007243117],"category_scores_gemma":[0.00056404696,0.00018057934,0.000118242126,0.00015160641,0.0003221059,0.00031516215,0.00019506183,0.00018158113,0.00013748265],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000119304714,0.000033291693,0.003193789,0.0001515201,0.000012076232,0.00024713392,0.00009060259,0.0011003204,0.9769627,0.00045386207,0.000047151898,0.017588245],"study_design_scores_gemma":[0.000068140675,0.0029554127,0.26048517,0.0001642138,0.00016945672,0.006465707,0.00063718215,0.03133716,0.6887399,0.0015131041,0.007367301,0.00009726015],"about_ca_topic_score_codex":0.0035375585,"about_ca_topic_score_gemma":0.006028329,"teacher_disagreement_score":0.0035375585,"about_ca_system_score_codex":0.00026109695,"about_ca_system_score_gemma":0.00044012707,"threshold_uncertainty_score":0.007033944},"labels":[],"label_agreement":null},{"id":"W1565314341","doi":"10.1136/thoraxjnl-2011-201054b.92","title":"S92 Cognitive function &amp; cerebral white matter tract microstructure in COPD","year":2011,"lang":"en","type":"article","venue":"Thorax","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Medicine; Diffusion MRI; Cardiology; COPD; Grey matter; Internal medicine; Cognition; Working memory; Montreal Cognitive Assessment; Pathology; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.07821473167748443,"score_gpt":0.3400433047447701,"score_spread":0.2618285730672857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565314341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97816306,0.003928922,0.0015993628,0.0017991744,0.00014678056,0.0001936635,0.004199064,0.00006388166,0.009906011],"genre_scores_gemma":[0.99406344,0.0007553724,0.0011248094,0.00033094417,0.0001324391,0.0000888659,0.0011871096,0.000009882702,0.0023071314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999385,0.0000146620405,0.0000075170155,0.000011185323,0.000018573892,0.000009573739],"domain_scores_gemma":[0.99966466,0.000094348936,0.000109961205,0.000025141666,0.00005879695,0.000047114332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005477705,0.00021493959,0.00020228542,0.00032647655,0.00023246686,0.0003712334,0.00018228611,0.00046268693,0.014409134],"category_scores_gemma":[0.00080176076,0.000056384528,0.0002474213,0.00038586324,0.00049557444,0.0002988629,0.00023332243,0.00027782956,0.00087664556],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004306256,0.00040888286,0.8447793,0.0010514474,0.00036808845,0.0021693488,0.00039833423,0.0010363542,0.032074172,0.0013738986,0.012126642,0.09990723],"study_design_scores_gemma":[0.0000398574,0.0005395968,0.9926817,0.000101122794,0.000038519098,0.0012879927,0.000114847295,0.0004548925,0.0017718228,0.0008308335,0.0021326991,0.0000061335913],"about_ca_topic_score_codex":0.0029614416,"about_ca_topic_score_gemma":0.0035122994,"teacher_disagreement_score":0.014409134,"about_ca_system_score_codex":0.00022046588,"about_ca_system_score_gemma":0.0004111469,"threshold_uncertainty_score":0.04820335},"labels":[],"label_agreement":null},{"id":"W1576590016","doi":"10.1002/mrm.25093","title":"Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Undersampling; Compressed sensing; Computer science; Sampling (signal processing); Algorithm; Artificial intelligence; Wavelet; Pattern recognition (psychology); Computer vision","score_opus":0.06568937023446123,"score_gpt":0.3810956298662001,"score_spread":0.31540625963173885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576590016","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31139347,0.0019923563,0.6832714,0.00024688893,0.00008863936,0.00014669175,0.00009841404,0.00043850992,0.0023236417],"genre_scores_gemma":[0.60404754,0.0010526484,0.39406663,0.00006984935,0.000033998607,0.00008782462,0.0001832373,0.00008073949,0.0003776078],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936754,0.00021816451,0.000055720433,0.00008202935,0.00023651832,0.00004006058],"domain_scores_gemma":[0.9978181,0.0012344972,0.00021731708,0.0002779626,0.00037797142,0.00007412749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018598037,0.0007753611,0.00039917178,0.0007238907,0.00018845106,0.0005104401,0.0004464024,0.000580501,0.0006747211],"category_scores_gemma":[0.0065827835,0.00019864259,0.0003587934,0.0007460329,0.00052377366,0.0008668157,0.00048187838,0.0005564454,0.0001858786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019677964,0.0006355872,0.0045967074,0.00068462396,0.00023006025,0.00025814027,0.00028150066,0.30676037,0.17310385,0.012547568,0.0011504407,0.49778327],"study_design_scores_gemma":[0.00014679588,0.0013578413,0.002124471,0.000076290664,0.00011728492,0.00048384216,0.000084686886,0.887926,0.10337291,0.0023923842,0.0018704912,0.00004698572],"about_ca_topic_score_codex":0.00092955015,"about_ca_topic_score_gemma":0.0009230166,"teacher_disagreement_score":0.0018598037,"about_ca_system_score_codex":0.00024760063,"about_ca_system_score_gemma":0.00044003813,"threshold_uncertainty_score":0.00983566},"labels":[],"label_agreement":null},{"id":"W1578806482","doi":"10.1002/syn.21765","title":"Quantitative imaging of neuroinflammation in human white matter: A positron emission tomography study with translocator protein 18 kDa radioligand, [<sup>18</sup>F]‐FEPPA","year":2014,"lang":"en","type":"article","venue":"Synapse","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Translocator protein; Positron emission tomography; Radioligand; White matter; Nuclear medicine; Fractional anisotropy; Diffusion MRI; Binding potential; Corpus callosum; Internal capsule; Magnetic resonance imaging; Nuclear magnetic resonance; Psychology; Chemistry; Neuroscience; Medicine; Pathology; Neuroinflammation; Internal medicine; Physics; Radiology; Receptor","score_opus":0.023151158286920333,"score_gpt":0.3166299127115478,"score_spread":0.29347875442462745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1578806482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99704355,0.00017211025,0.0026304817,0.000011766884,9.720492e-7,0.000012002879,0.000047226524,0.000011410719,0.000070484515],"genre_scores_gemma":[0.9971437,0.00010463716,0.0024443618,0.000012325033,0.00000551847,0.000017365639,0.0000842239,0.000011665077,0.00017627043],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986756,0.000050906496,0.0000054167754,0.000050406834,0.000014852604,0.00001080071],"domain_scores_gemma":[0.9997682,0.000097181524,0.000048778915,0.00003773342,0.000028291606,0.000019871017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069118605,0.000304912,0.00025127974,0.00022912299,0.00012999798,0.00024115322,0.00014368465,0.00037488242,0.00062834134],"category_scores_gemma":[0.0010080842,0.00027774004,0.00013495854,0.00018519413,0.00037505815,0.00022306919,0.000118201206,0.0001479589,0.00015736363],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005675897,0.00041179865,0.11881716,0.0002144299,0.00050673116,0.0017308668,0.000872298,0.0029418436,0.84343094,0.00030333654,0.00021064637,0.024884159],"study_design_scores_gemma":[0.00022333488,0.0031454868,0.9052474,0.000010336488,0.0003823487,0.008729655,0.00021605688,0.015951432,0.06467513,0.0003885469,0.0009807815,0.000049506238],"about_ca_topic_score_codex":0.00172327,"about_ca_topic_score_gemma":0.0012632471,"teacher_disagreement_score":0.00172327,"about_ca_system_score_codex":0.00013842016,"about_ca_system_score_gemma":0.000099812416,"threshold_uncertainty_score":0.0036554337},"labels":[],"label_agreement":null},{"id":"W1581093187","doi":"10.1002/hbm.22620","title":"A DTI-based tractography study of effects on brain structure associated with prenatal alcohol exposure in newborns","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital","funders":"National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; South African Medical Research Council","keywords":"Tractography; Fractional anisotropy; Diffusion MRI; White matter; Neuroimaging; Prenatal alcohol exposure; Psychology; Neuroscience; Medicine; Pregnancy; Magnetic resonance imaging; Biology; Radiology","score_opus":0.04296533638788373,"score_gpt":0.3226505155792089,"score_spread":0.27968517919132513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581093187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971596,0.00010580223,0.0023987098,0.00001588082,0.0000015327479,0.000009931491,0.00014589197,0.000015436613,0.00014722184],"genre_scores_gemma":[0.9955024,0.00018545243,0.003917689,0.0000042858646,0.0000018372373,0.000015191464,0.00015137989,0.000011918743,0.00020992658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999223,0.00002529395,0.000006960873,0.000019549492,0.000014239943,0.0000118299295],"domain_scores_gemma":[0.9996679,0.00010495488,0.000106123916,0.000034610643,0.00004068729,0.000045697463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003136628,0.00019669041,0.00015490362,0.0008382242,0.0001989546,0.0002053066,0.00013205796,0.00015268766,0.0006646354],"category_scores_gemma":[0.0013834224,0.00014476656,0.00018708414,0.0005097774,0.00026297593,0.00012443414,0.00021426148,0.00012572487,0.00009855067],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011321064,0.00008903585,0.7149677,0.00018170296,0.00022520756,0.0044722757,0.0014632379,0.005034788,0.20811558,0.0012879602,0.00032840413,0.06270192],"study_design_scores_gemma":[0.000008445803,0.00023411676,0.9751914,0.000031155785,0.00005570957,0.0038702374,0.0002712502,0.008627776,0.010731494,0.00029278416,0.00066723244,0.00001838323],"about_ca_topic_score_codex":0.0118652405,"about_ca_topic_score_gemma":0.00892795,"teacher_disagreement_score":0.0118652405,"about_ca_system_score_codex":0.0004489329,"about_ca_system_score_gemma":0.00041562194,"threshold_uncertainty_score":0.023592353},"labels":[],"label_agreement":null},{"id":"W1583057043","doi":"10.1002/mrm.24325","title":"Oscillating and pulsed gradient diffusion magnetic resonance microscopy over an extended<i>b</i>‐value range: Implications for the characterization of tissue microstructure","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Institute of Biomedical Imaging and Bioengineering; University of Florida","keywords":"Spin echo; Diffusion; Nuclear magnetic resonance; Effective diffusion coefficient; Resolution (logic); Materials science; Analytical Chemistry (journal); Characterization (materials science); Chemistry; Magnetic resonance imaging; Physics; Nanotechnology; Computer science; Thermodynamics","score_opus":0.02941873910434306,"score_gpt":0.35205289786474825,"score_spread":0.3226341587604052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583057043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74477327,0.01942465,0.23033127,0.00078190095,0.00010486811,0.00007620554,0.00023079973,0.0003712485,0.003905806],"genre_scores_gemma":[0.8312058,0.009380428,0.15677738,0.00039982828,0.00008215069,0.00013510571,0.0002565426,0.00011235105,0.0016504135],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998623,0.00002589998,0.000009969556,0.00004955769,0.000032541513,0.00001961319],"domain_scores_gemma":[0.9992347,0.00028586845,0.00015096884,0.00008479082,0.00014044777,0.000103305974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008569558,0.00032429484,0.00033613414,0.0003558453,0.00020361655,0.0005321963,0.0005857353,0.00073897303,0.0004409605],"category_scores_gemma":[0.0012831478,0.00027827043,0.00013969041,0.00036230346,0.0008566199,0.0015307917,0.0004880634,0.0005539575,0.00014973729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069817506,0.000009966432,0.00079291814,0.00015295454,0.000007168489,0.00006548416,0.000039884253,0.0002771073,0.9854697,0.0008995057,0.00005659421,0.012158867],"study_design_scores_gemma":[0.000056230096,0.0009135158,0.0440081,0.00017180714,0.00015435719,0.0030182628,0.00037587935,0.02100572,0.91252375,0.008814291,0.008827064,0.00013107673],"about_ca_topic_score_codex":0.0006256796,"about_ca_topic_score_gemma":0.0011819083,"teacher_disagreement_score":0.0008569558,"about_ca_system_score_codex":0.00018484131,"about_ca_system_score_gemma":0.00027901452,"threshold_uncertainty_score":0.004532039},"labels":[],"label_agreement":null},{"id":"W1585992480","doi":"10.1007/978-3-642-04271-3_96","title":"A New Approach for Creating Customizable Cytoarchitectonic Probabilistic Maps without a Template","year":2009,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Institute of Biomedical Imaging and Bioengineering; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Computer science; Probabilistic logic; Pairwise comparison; Artificial intelligence; Pattern recognition (psychology); Computer vision; Image registration; Image (mathematics)","score_opus":0.04725669324274098,"score_gpt":0.3433014189683457,"score_spread":0.2960447257256047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1585992480","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012475667,0.000015960888,0.99518496,0.00002625254,0.000027093945,0.000023396013,0.00008272155,0.0028644418,0.0005277048],"genre_scores_gemma":[0.039735533,0.000084207044,0.9555033,0.00007401054,0.000022061973,0.0001518224,0.00034273794,0.0017221131,0.0023641929],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943227,0.00004911031,0.00003484588,0.00017052548,0.00027488987,0.000038383478],"domain_scores_gemma":[0.9985067,0.00038676886,0.00008004523,0.0006946288,0.00024067919,0.00009117058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076113833,0.001029516,0.0008259841,0.0011609088,0.00053798355,0.0021116955,0.0035918565,0.0011333115,0.007861577],"category_scores_gemma":[0.003368847,0.0010344298,0.0017028416,0.0015896502,0.0006275896,0.0021019862,0.0029437656,0.0017675438,0.0028140685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001861573,0.00015987485,0.001346712,0.0003018276,0.00032675566,0.00053745636,0.000525213,0.081860766,0.12123088,0.04954009,0.017469138,0.7265152],"study_design_scores_gemma":[0.000053561926,0.00008579406,0.0009957047,0.00003332641,0.00012546049,0.0013540509,0.000099351775,0.77776086,0.11356329,0.058056936,0.047750313,0.000121279896],"about_ca_topic_score_codex":0.0027066553,"about_ca_topic_score_gemma":0.004602847,"teacher_disagreement_score":0.007861577,"about_ca_system_score_codex":0.00048421795,"about_ca_system_score_gemma":0.0009795602,"threshold_uncertainty_score":0.026299596},"labels":[],"label_agreement":null},{"id":"W1586285828","doi":"10.3233/jad-2012-121156","title":"MRI Signatures of Brain Macrostructural Atrophy and Microstructural Degradation in Frontotemporal Lobar Degeneration Subtypes","year":2012,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Northern California Institute for Research and Education; U.S. Department of Veterans Affairs","keywords":"Frontotemporal lobar degeneration; Atrophy; White matter; Fractional anisotropy; Frontotemporal dementia; Diffusion MRI; Magnetic resonance imaging; Semantic dementia; Pathology; Medicine; Psychology; Dementia; Neuroscience; Radiology; Disease","score_opus":0.0342027077982406,"score_gpt":0.3304098974408907,"score_spread":0.29620718964265014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586285828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961936,0.0001253875,0.00003982411,0.000009344318,6.2555944e-7,0.0000029271225,0.00004888649,0.000001914619,0.00015176709],"genre_scores_gemma":[0.99953747,0.000054920863,0.000092561175,0.00001566484,0.0000035695398,0.0000045323713,0.00015188684,0.0000022974789,0.00013705982],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986565,0.000020323574,0.000021792226,0.000039719667,0.000026434764,0.000025978288],"domain_scores_gemma":[0.99951494,0.00007648963,0.0002536425,0.000038746763,0.00005294949,0.00006320843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031849137,0.0002701256,0.00033072356,0.0011080164,0.00023670113,0.0003912853,0.00017819073,0.00036387512,0.0006252001],"category_scores_gemma":[0.0012096104,0.00019207195,0.0002095074,0.00032799368,0.0002852717,0.0002683687,0.00024071516,0.00018220168,0.00018958289],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014427935,0.00006193975,0.9524809,0.000035675883,0.0001423713,0.00079908053,0.00073173054,0.00019665124,0.03299842,0.000052948963,0.000169363,0.010888117],"study_design_scores_gemma":[0.0000051272123,0.00006325532,0.9985056,0.0000030058939,0.00000986313,0.0008294175,0.000088485205,0.000106750835,0.0003106672,0.00003231973,0.00004308852,0.0000024515264],"about_ca_topic_score_codex":0.0035030209,"about_ca_topic_score_gemma":0.005171363,"teacher_disagreement_score":0.0035030209,"about_ca_system_score_codex":0.00024018741,"about_ca_system_score_gemma":0.000104528524,"threshold_uncertainty_score":0.0069652796},"labels":[],"label_agreement":null},{"id":"W1586359640","doi":"10.3171/2014.12.jns142690","title":"Letter to the Editor: Correlation of diffusion tensor imaging and intraoperative macrostimulation","year":2015,"lang":"en","type":"letter","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medtronic Europe; London Health Sciences Centre; Boston Scientific Corporation; Case Western Reserve University","keywords":"Medicine; Diffusion MRI; Intraoperative neurophysiological monitoring; Medical physics; Radiology; Magnetic resonance imaging; Surgery","score_opus":0.04195500756839228,"score_gpt":0.3228766359568912,"score_spread":0.28092162838849893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586359640","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013489178,0.0040342384,0.0010915784,0.91114515,0.06256308,0.000041076983,0.0001560187,0.00012940721,0.00735037],"genre_scores_gemma":[0.18561347,0.0056716856,0.0024128372,0.512839,0.27901024,0.00011847351,0.000121160716,0.00012962178,0.014083529],"study_design_codex":"not_applicable","study_design_gemma":"case_report","domain_scores_codex":[0.998973,0.0002863035,0.00017193015,0.00016225726,0.00023918903,0.00016722005],"domain_scores_gemma":[0.99573237,0.0023661419,0.0005210749,0.00015942832,0.00070124055,0.00051972654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011295876,0.0006633113,0.001196289,0.00073942565,0.0011725253,0.0018360477,0.0012237174,0.014761471,0.0028435234],"category_scores_gemma":[0.020119978,0.00051559217,0.00066242117,0.0004944189,0.0013481479,0.0020241453,0.00055885053,0.009732142,0.0022310407],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003547279,0.00012737328,0.0051732324,0.00022329394,0.000092966635,0.34979337,0.0004296258,0.00044833426,0.0009643332,0.0038588485,0.61708885,0.021445056],"study_design_scores_gemma":[0.0004917061,0.00038957645,0.0074594836,0.00067484553,0.00022372058,0.4563563,0.0015022503,0.0057123657,0.002569381,0.016654948,0.5077393,0.00022622976],"about_ca_topic_score_codex":0.0009121352,"about_ca_topic_score_gemma":0.0014083795,"teacher_disagreement_score":0.014761471,"about_ca_system_score_codex":0.0013784465,"about_ca_system_score_gemma":0.0012317426,"threshold_uncertainty_score":0.010001361},"labels":[],"label_agreement":null},{"id":"W1588899353","doi":"10.1016/j.neuroimage.2015.06.040","title":"White matter atlas of the human spinal cord with estimation of partial volume effect","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"Atlas (anatomy); White matter; Segmentation; Brain atlas; Computer science; Voxel; Partial volume; Artificial intelligence; Magnetization transfer; Pattern recognition (psychology); Cartography; Anatomy; Magnetic resonance imaging; Medicine; Geography; Radiology","score_opus":0.051300732631459865,"score_gpt":0.35632173538735296,"score_spread":0.3050210027558931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588899353","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13562709,0.0014557637,0.810623,0.0011174812,0.0003481774,0.000597583,0.013868492,0.008900939,0.027461503],"genre_scores_gemma":[0.54403466,0.0014149541,0.42900014,0.00029220385,0.000110025096,0.00047551675,0.0045727165,0.0012442337,0.018855587],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987817,0.000025224133,0.000009745827,0.000034347937,0.00003854134,0.000013993056],"domain_scores_gemma":[0.9998367,0.000044848483,0.00001635627,0.00003422716,0.000053457403,0.000014366639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029613296,0.0004459458,0.00023767832,0.0012031439,0.0006339475,0.0012511928,0.0004910565,0.00091766584,0.009345576],"category_scores_gemma":[0.00096711214,0.00030942116,0.0003697835,0.0013228505,0.0002935866,0.00038911615,0.00046473526,0.00053282926,0.001794728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012599131,0.00021863022,0.009420411,0.0014000562,0.00035055992,0.0028747255,0.001594094,0.11249919,0.24376287,0.055270102,0.05684255,0.5145068],"study_design_scores_gemma":[0.00030000333,0.0009060292,0.076550305,0.0002775915,0.0005070573,0.010501302,0.00073615654,0.36139187,0.22519518,0.07509045,0.24829489,0.0002491433],"about_ca_topic_score_codex":0.01365848,"about_ca_topic_score_gemma":0.020891335,"teacher_disagreement_score":0.01365848,"about_ca_system_score_codex":0.00045164136,"about_ca_system_score_gemma":0.0028357652,"threshold_uncertainty_score":0.031264007},"labels":[],"label_agreement":null},{"id":"W1595872863","doi":"10.1002/mrm.25108","title":"Investigating the stability of mcDESPOT myelin water fraction values derived using a stochastic region contraction approach","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; Medical Research Council; Michael Smith Health Research BC","keywords":"Parameter space; Sensitivity (control systems); Contraction (grammar); Imaging phantom; Biological system; Range (aeronautics); Mathematics; Computer science; Mathematical optimization; Physics; Statistics; Materials science; Optics","score_opus":0.10386940134591494,"score_gpt":0.3451068070371636,"score_spread":0.24123740569124869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1595872863","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4445366,0.00042191378,0.5527301,0.00016241007,0.000017084332,0.00008850088,0.00012474388,0.00041432417,0.0015043757],"genre_scores_gemma":[0.8131527,0.0001513812,0.18578479,0.000041415085,0.00000588501,0.000085006286,0.00021646915,0.000096743526,0.0004655786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957997,0.00011276088,0.000025243897,0.00009588793,0.00016544753,0.000020743253],"domain_scores_gemma":[0.9968052,0.0020948339,0.00032147046,0.0001883194,0.0005395809,0.000050694565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025229345,0.00046678088,0.0003031095,0.00061850145,0.0002714319,0.00044846692,0.0006243816,0.00060813327,0.00071361987],"category_scores_gemma":[0.011365802,0.00023617658,0.00027287143,0.00029546936,0.0005527346,0.0005979656,0.0007452818,0.0004923454,0.00013782458],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011409295,0.00014205293,0.015193542,0.00060048205,0.00016735117,0.00045548676,0.00062356325,0.5593228,0.3162024,0.0070962687,0.00053665054,0.09851847],"study_design_scores_gemma":[0.000015457928,0.00012330277,0.0032282015,0.000021443266,0.000017426784,0.0002037045,0.000039676175,0.90229356,0.09254522,0.00097562996,0.00051408506,0.00002227324],"about_ca_topic_score_codex":0.002350362,"about_ca_topic_score_gemma":0.0023996844,"teacher_disagreement_score":0.0025229345,"about_ca_system_score_codex":0.00050123566,"about_ca_system_score_gemma":0.0008020817,"threshold_uncertainty_score":0.013342679},"labels":[],"label_agreement":null},{"id":"W1596591320","doi":"10.1007/s10489-016-0833-8","title":"A multicomponent approach to nonrigid registration of diffusion tensor images","year":2016,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Diffusion MRI; Affine transformation; Computer science; Tensor (intrinsic definition); Distortion (music); Structure tensor; Diffusion; Mutual information; Computer vision; Artificial intelligence; Image registration; Orientation (vector space); Pattern recognition (psychology); Image (mathematics); Mathematics; Geometry; Magnetic resonance imaging; Physics; Radiology; Medicine","score_opus":0.08411722725463726,"score_gpt":0.3464097997324712,"score_spread":0.26229257247783394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596591320","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014985881,0.00013855228,0.9977064,0.00007708198,0.000025479543,0.000029150158,0.000031328957,0.00015201369,0.00034143002],"genre_scores_gemma":[0.030719556,0.00039469168,0.9655813,0.000055803128,0.00006352844,0.000105738094,0.00016235402,0.00025098445,0.002666112],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999008,0.00026881223,0.00007741305,0.00021559911,0.00037863117,0.000051583556],"domain_scores_gemma":[0.9989675,0.0003326038,0.00014724648,0.00025550814,0.00024059102,0.000056642137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001514028,0.0010261603,0.0011210286,0.00211519,0.001105642,0.0019252076,0.0021097139,0.001444612,0.0028270534],"category_scores_gemma":[0.004001175,0.0010064744,0.0019323888,0.0026843206,0.0009966603,0.0021139947,0.0027326194,0.002079549,0.0014429297],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015651443,0.00016079644,0.0005188944,0.00033693018,0.00023048099,0.00024389586,0.00031597796,0.20717958,0.056077756,0.08923401,0.0051170182,0.6404282],"study_design_scores_gemma":[0.00001296955,0.00008146385,0.00048631037,0.000023573568,0.000039679857,0.0002342647,0.0000421153,0.94035214,0.008906814,0.04220825,0.007574121,0.000038268605],"about_ca_topic_score_codex":0.004839697,"about_ca_topic_score_gemma":0.00834367,"teacher_disagreement_score":0.004839697,"about_ca_system_score_codex":0.0005824116,"about_ca_system_score_gemma":0.0018548603,"threshold_uncertainty_score":0.009623051},"labels":[],"label_agreement":null},{"id":"W1598901374","doi":"10.3389/fnagi.2015.00131","title":"Gray matter blood flow and volume are reduced in association with white matter hyperintensity lesion burden: a cross-sectional MRI study","year":2015,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Toronto Western Hospital; Heart and Stroke Foundation","funders":"University of Toronto; Canadian Stroke Network; Canadian Institutes of Health Research; Sunnybrook Research Institute; Heart and Stroke Foundation of Canada","keywords":"Hyperintensity; White matter; Magnetic resonance imaging; Fluid-attenuated inversion recovery; Lesion; Cerebral blood flow; Medicine; Cardiology; Voxel-based morphometry; Voxel; Grey matter; Putamen; Psychology; Internal medicine; Radiology; Pathology","score_opus":0.04051851309697691,"score_gpt":0.3136729019631118,"score_spread":0.2731543888661349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1598901374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99969757,0.00008388891,0.000075553224,0.000010155734,0.000001811007,0.0000051167053,0.000039256905,0.0000030444692,0.000083648694],"genre_scores_gemma":[0.9994861,0.00005411717,0.00015166395,0.000020903743,0.000007976651,0.000008560718,0.00012237574,0.000003216883,0.00014514846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998191,0.000048670063,0.000016958587,0.00006401477,0.000028239081,0.000023053848],"domain_scores_gemma":[0.99894315,0.00017892894,0.00040377828,0.00014421975,0.00013710037,0.00019288853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065894105,0.00030320516,0.00024451356,0.00060565566,0.00026720218,0.00029640185,0.00021895133,0.0004540713,0.0014208386],"category_scores_gemma":[0.0018798761,0.00047806982,0.000190002,0.00026698317,0.00031545165,0.0003287209,0.00028466608,0.0003337557,0.00031608623],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079441536,0.00032344752,0.98570144,0.00002211151,0.0002694525,0.00052694464,0.0005828369,0.00007797315,0.00869749,0.000034029337,0.00011433364,0.0028555442],"study_design_scores_gemma":[0.00000792384,0.00021875909,0.99896526,0.0000015315907,0.000025577101,0.00043398878,0.00003867268,0.000072372895,0.00015548422,0.000012709261,0.000065290245,0.0000024232975],"about_ca_topic_score_codex":0.0013893064,"about_ca_topic_score_gemma":0.0016021278,"teacher_disagreement_score":0.0014208386,"about_ca_system_score_codex":0.0001024756,"about_ca_system_score_gemma":0.00012276668,"threshold_uncertainty_score":0.004753113},"labels":[],"label_agreement":null},{"id":"W1607963120","doi":"10.1007/978-3-540-85990-1_22","title":"Human Brain Myelination from Birth to 4.5 Years","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Internal capsule; Computer science; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.04755122668089339,"score_gpt":0.3491319561679287,"score_spread":0.3015807294870353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1607963120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9696684,0.016051458,0.000691141,0.00036862327,0.00006809812,0.000011294586,0.005264607,0.00010806985,0.007768366],"genre_scores_gemma":[0.9862432,0.003630151,0.00033612252,0.000054882534,0.000029733332,0.000018354722,0.0030697933,0.000020730147,0.0065970714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997985,0.000028048795,0.0000132446885,0.00006284636,0.00003948515,0.000057987076],"domain_scores_gemma":[0.9986903,0.00027909127,0.0004117702,0.00010154267,0.00036131355,0.00015589807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071000867,0.00016517565,0.00024035327,0.001694075,0.00044454477,0.0006435304,0.00033455947,0.00044163145,0.003492769],"category_scores_gemma":[0.002605369,0.000115518786,0.0003692364,0.0009226759,0.0003090703,0.0005296052,0.0007777324,0.00037070204,0.00087707833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006154907,0.00018723222,0.5838255,0.0004987225,0.0006088783,0.0057705557,0.0038598205,0.0013465198,0.031220665,0.0038748793,0.00963834,0.353014],"study_design_scores_gemma":[0.00001316023,0.00034979428,0.97386205,0.00012386017,0.00014438773,0.0027847395,0.00037357566,0.00014212413,0.0040249676,0.0010118742,0.017144963,0.000024546136],"about_ca_topic_score_codex":0.0087516485,"about_ca_topic_score_gemma":0.007203084,"teacher_disagreement_score":0.0087516485,"about_ca_system_score_codex":0.00053440675,"about_ca_system_score_gemma":0.0004363897,"threshold_uncertainty_score":0.017401457},"labels":[],"label_agreement":null},{"id":"W1613048622","doi":"10.1177/1971400915598071","title":"Reversible restricted-diffusion lesion representing transient intramyelinic cytotoxic edema in a patient with traumatic brain injury","year":2015,"lang":"en","type":"article","venue":"The Neuroradiology Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital","funders":"","keywords":"White matter; Corpus callosum; Medicine; Diffusion MRI; Traumatic brain injury; Effective diffusion coefficient; Magnetic resonance imaging; Emergency department; Diffuse axonal injury; Lesion; Radiology; Pathology; Psychiatry","score_opus":0.11228367959974137,"score_gpt":0.3642983670378126,"score_spread":0.2520146874380712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1613048622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9821066,0.0039577927,0.002970742,0.0014926081,0.0001696038,0.00014577419,0.00013799426,0.00017318626,0.008845616],"genre_scores_gemma":[0.99661934,0.0011304677,0.0008545752,0.00036809262,0.00028724415,0.00001618079,0.000048402097,0.0000126910045,0.0006630477],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9996265,0.00004353081,0.000055742737,0.00009356382,0.000047436555,0.00013311919],"domain_scores_gemma":[0.99905914,0.00020076674,0.000324241,0.00013622374,0.00007569321,0.00020393108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028964537,0.0014609749,0.0008029554,0.0017112325,0.002150901,0.0012902681,0.000955274,0.0031960174,0.0020837986],"category_scores_gemma":[0.0023302066,0.0009873897,0.00062314887,0.0010982068,0.0014098074,0.002146317,0.0011024893,0.0021712077,0.0009994288],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024853094,0.000026427762,0.0034963186,0.00002058108,0.000004202179,0.99480397,0.00014919553,0.000027069113,0.00063909404,0.00006967087,0.0000667537,0.00067187723],"study_design_scores_gemma":[0.0000065779977,0.00005155624,0.0015352496,0.000007001802,0.000010969265,0.9974016,0.00007947049,0.00008084123,0.0005062228,0.0000710764,0.00024440797,0.000005178056],"about_ca_topic_score_codex":0.0012565455,"about_ca_topic_score_gemma":0.0014895833,"teacher_disagreement_score":0.0031960174,"about_ca_system_score_codex":0.0006347709,"about_ca_system_score_gemma":0.0005965747,"threshold_uncertainty_score":0.006971061},"labels":[],"label_agreement":null},{"id":"W1615815280","doi":"10.3171/2010.3.jns091832","title":"Tractography of the amygdala and hippocampus: anatomical study and application to selective amygdalohippocampectomy","year":2010,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fornix; Uncinate fasciculus; White matter; Tractography; Diffusion MRI; Neuroscience; Hippocampus; Amygdala; Anatomy; Corpus callosum; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Medicine; Psychology; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.018225487089576643,"score_gpt":0.31826215321891266,"score_spread":0.300036666129336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1615815280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842015,0.00052673445,0.014467374,0.000042939202,0.00000540657,0.00002954984,0.000048886726,0.00003761058,0.0006400687],"genre_scores_gemma":[0.9914001,0.00040504217,0.007789989,0.000009369156,0.0000042596066,0.00001868158,0.000045520595,0.000010259443,0.0003167993],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995613,0.000008747138,0.0000034305515,0.000012407365,0.000011538584,0.000007748271],"domain_scores_gemma":[0.99990344,0.000024847202,0.000030156289,0.00001798725,0.000014072784,0.000009451913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018591847,0.00015606389,0.0001268496,0.0003298293,0.00013809427,0.00015886237,0.00011746603,0.00017719889,0.00059620774],"category_scores_gemma":[0.00038645757,0.00010841419,0.00014596288,0.00018097994,0.00035400782,0.00022112462,0.00017248634,0.00010594345,0.00009033206],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006559085,0.00011939754,0.05776533,0.000355072,0.00015622325,0.0016350914,0.0009584644,0.004875142,0.8259645,0.0012905399,0.00018516777,0.106039196],"study_design_scores_gemma":[0.00007400583,0.0014493031,0.730081,0.00008412633,0.00022472703,0.01658885,0.00073628814,0.03209896,0.21079235,0.0029659034,0.0048509594,0.000053582888],"about_ca_topic_score_codex":0.0027110507,"about_ca_topic_score_gemma":0.0039730337,"teacher_disagreement_score":0.0027110507,"about_ca_system_score_codex":0.00025161705,"about_ca_system_score_gemma":0.00035676805,"threshold_uncertainty_score":0.0053905845},"labels":[],"label_agreement":null},{"id":"W163465042","doi":"10.1007/978-3-642-40760-4_59","title":"A Cross-Sectional Piecewise Constant Model for Segmenting Highly Curved Fiber Tracts in Diffusion MR Images","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Alberta; Western Canada Research Grid; Compute Canada","keywords":"Piecewise; Segmentation; Constant (computer programming); Diffusion; Computer science; Diffusion MRI; Cross section (physics); Fiber; Artificial intelligence; Market segmentation; Image segmentation; Mathematics; Mathematical analysis; Physics; Materials science; Magnetic resonance imaging; Medicine","score_opus":0.05039745930564653,"score_gpt":0.34868536098693936,"score_spread":0.2982879016812928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W163465042","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018038547,0.00035418136,0.9804817,0.00017988708,0.000026808706,0.000028957116,0.00018250637,0.00045993066,0.00024756684],"genre_scores_gemma":[0.5718224,0.001297179,0.41857457,0.00016972485,0.00009519613,0.00025498238,0.00092903373,0.0003960914,0.0064607575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996859,0.00009131725,0.00002139088,0.000114762406,0.000050828665,0.000035888224],"domain_scores_gemma":[0.99867404,0.00075195415,0.00016455616,0.0001231423,0.00021823986,0.000068187604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012855412,0.000834922,0.0010051783,0.0010208898,0.00047847096,0.0013474528,0.0026536363,0.0029614037,0.0016786971],"category_scores_gemma":[0.003774929,0.0013001387,0.0012264485,0.001548464,0.0007690701,0.0013232782,0.0008657257,0.0018911571,0.0006929897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009822664,0.000027914346,0.00061236473,0.00007107739,0.000038763294,0.00008262682,0.00006954712,0.9595473,0.0033528686,0.004136309,0.000756643,0.031206401],"study_design_scores_gemma":[0.0000017122857,0.000008625261,0.00006384624,0.000003142382,0.0000058498067,0.0000127238445,0.0000019362349,0.9991468,0.00017603647,0.00045807371,0.00011771814,0.000003570933],"about_ca_topic_score_codex":0.020390416,"about_ca_topic_score_gemma":0.015505934,"teacher_disagreement_score":0.020390416,"about_ca_system_score_codex":0.0010424232,"about_ca_system_score_gemma":0.0012778528,"threshold_uncertainty_score":0.040543497},"labels":[],"label_agreement":null},{"id":"W1706210574","doi":"10.1016/j.pscychresns.2015.06.017","title":"Investigation of white matter abnormalities in first episode psychosis patients with persistent negative symptoms","year":2015,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto; McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Fornix; Uncinate fasciculus; Cingulum (brain); White matter; Fractional anisotropy; Psychology; Psychosis; Fasciculus; Superior longitudinal fasciculus; Schizophrenia (object-oriented programming); Inferior longitudinal fasciculus; Anhedonia; Internal medicine; Medicine; Neuroscience; Psychiatry; Magnetic resonance imaging; Hippocampus; Radiology","score_opus":0.1073756453976198,"score_gpt":0.36467744201648505,"score_spread":0.25730179661886526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1706210574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99865216,0.00033864458,0.000043438973,0.000067509754,0.0000054787533,0.000010639149,0.000055683897,0.0000038073324,0.0008226129],"genre_scores_gemma":[0.99946636,0.00020053296,0.00008519522,0.000041601055,0.000010562584,0.0000054658867,0.000054573735,0.0000015943923,0.00013407858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986494,0.000022877779,0.000022998905,0.000022356537,0.000023295566,0.00004351948],"domain_scores_gemma":[0.9995664,0.00013435556,0.00012476419,0.000015782844,0.000053044452,0.000105687046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003327419,0.00040965277,0.00031075446,0.0013873985,0.00060185086,0.00070281245,0.0003680817,0.0006867979,0.0020214722],"category_scores_gemma":[0.0016314541,0.00030353776,0.00018922765,0.000499219,0.0004091427,0.00053462276,0.00039051377,0.0004182381,0.0002437673],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014369395,0.00018748078,0.9477807,0.00010081223,0.000071669114,0.02530146,0.0006739049,0.00009355155,0.0145189,0.00007422773,0.00026905574,0.009491266],"study_design_scores_gemma":[0.000037644524,0.00047411313,0.9705047,0.00003137669,0.00005707745,0.026005236,0.0010363101,0.00029101825,0.0011374397,0.00016555552,0.00024964163,0.00000994592],"about_ca_topic_score_codex":0.0035829383,"about_ca_topic_score_gemma":0.0056254617,"teacher_disagreement_score":0.0035829383,"about_ca_system_score_codex":0.0003687645,"about_ca_system_score_gemma":0.00049201,"threshold_uncertainty_score":0.007124126},"labels":[],"label_agreement":null},{"id":"W1726170819","doi":"","title":"Connectivity directionally-encoded color map: a streamline-based color mapping","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Artificial intelligence; Computer science; Computer vision; Orientation (vector space); Color image; Set (abstract data type); Pattern recognition (psychology); Image (mathematics); Image processing; Mathematics; Physics","score_opus":0.03975453725186294,"score_gpt":0.2916540061378824,"score_spread":0.25189946888601944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1726170819","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08162815,0.00063546456,0.90665835,0.0005650425,0.00018171377,0.00016469411,0.0024558445,0.0027502617,0.004960526],"genre_scores_gemma":[0.45007402,0.0016187457,0.541226,0.00016873427,0.00017877079,0.00019670013,0.0018228501,0.00095075613,0.0037633665],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998753,0.00002596878,0.0000036998679,0.00003673497,0.000036293357,0.000022096914],"domain_scores_gemma":[0.99938846,0.0001208907,0.000050814313,0.00008122808,0.00027413588,0.00008446359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027583056,0.0006478201,0.00046030307,0.0018026291,0.00034615688,0.0016006038,0.0009133257,0.0004726433,0.005490712],"category_scores_gemma":[0.0024188315,0.00026623104,0.00044661458,0.0024047787,0.00036958544,0.0010082715,0.0007360023,0.00064881216,0.0008381759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013401521,0.00023779152,0.005482459,0.00057045184,0.0001558929,0.00032192035,0.00039176678,0.0850604,0.14704344,0.02179692,0.018131018,0.71946776],"study_design_scores_gemma":[0.000076302225,0.00015526795,0.007490445,0.00007622906,0.00011042913,0.00067521585,0.00014481318,0.9142614,0.04021313,0.02478519,0.011900466,0.00011109736],"about_ca_topic_score_codex":0.006538162,"about_ca_topic_score_gemma":0.0062399996,"teacher_disagreement_score":0.006538162,"about_ca_system_score_codex":0.00048858917,"about_ca_system_score_gemma":0.0010023954,"threshold_uncertainty_score":0.018368304},"labels":[],"label_agreement":null},{"id":"W1743269311","doi":"10.1002/hbm.22830","title":"Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Connectome; Neuroscience; Diffusion MRI; White matter; Connectomics; Grey matter; Psychology; Alzheimer's disease; Neuroimaging; Clustering coefficient; Tractography; Computer science; Disease; Cluster analysis; Medicine; Artificial intelligence; Magnetic resonance imaging; Functional connectivity; Pathology","score_opus":0.23436285183982716,"score_gpt":0.40772388790035974,"score_spread":0.17336103606053258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1743269311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933315,0.00013901776,0.005819069,0.00002367406,0.0000020780838,0.0000104606825,0.00020879926,0.000050155184,0.0004151265],"genre_scores_gemma":[0.9978362,0.000050840103,0.0016883733,0.0000070216734,0.0000036392928,0.000007916959,0.00027264428,0.000008864434,0.0001244117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997582,0.0000699218,0.000017954682,0.00005789351,0.000057443805,0.000038505157],"domain_scores_gemma":[0.9986834,0.0005250319,0.00032582984,0.0001906212,0.000110694375,0.00016441525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055442256,0.00026400443,0.00036945753,0.0030364692,0.00040027915,0.0005066002,0.00027012482,0.00028303155,0.0010146222],"category_scores_gemma":[0.002902229,0.00019301522,0.00027776096,0.0013783934,0.0006184676,0.0005877323,0.000611368,0.00024369873,0.00020144468],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026762588,0.00022374118,0.6679446,0.00041879076,0.0010924863,0.005179767,0.0020459997,0.05095092,0.17975391,0.0067463256,0.0027456474,0.08022159],"study_design_scores_gemma":[0.000034571785,0.00020097301,0.85312194,0.00003694484,0.00013808682,0.0030395433,0.00040877875,0.11780968,0.012637208,0.011188325,0.0013359663,0.000048134632],"about_ca_topic_score_codex":0.0026127421,"about_ca_topic_score_gemma":0.005079052,"teacher_disagreement_score":0.0030364692,"about_ca_system_score_codex":0.00023417913,"about_ca_system_score_gemma":0.00016735295,"threshold_uncertainty_score":0.005195141},"labels":[],"label_agreement":null},{"id":"W1749485375","doi":"10.1371/journal.pone.0139434","title":"Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health","keywords":"Visualization; Tractography; Computer science; Fiber bundle; Rendering (computer graphics); Bundle; Data visualization; Connectomics; Diffusion MRI; Artificial intelligence; Computer vision; Neuroscience; Connectome; Biology; Functional connectivity; Materials science; Medicine; Magnetic resonance imaging","score_opus":0.2423786497573033,"score_gpt":0.3739727231724838,"score_spread":0.1315940734151805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1749485375","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02963563,0.00031599024,0.96173006,0.00045391746,0.00010730233,0.00009492825,0.00013828163,0.004483788,0.0030400963],"genre_scores_gemma":[0.26720682,0.000615815,0.7279329,0.00018551896,0.00006319747,0.00013388348,0.00018010703,0.0016456215,0.0020361277],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996911,0.000095047915,0.000020119294,0.000040305815,0.00011048571,0.000042928976],"domain_scores_gemma":[0.9988747,0.0005838476,0.000085224645,0.0001844578,0.00011828829,0.00015348353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006685281,0.0008601836,0.0004219635,0.00067420275,0.00041974933,0.0016136135,0.0008525923,0.000877574,0.0050515626],"category_scores_gemma":[0.0032770762,0.00048750333,0.0007017192,0.00037530277,0.00075944007,0.0012466831,0.0024663717,0.0015228636,0.0006636531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096762856,0.00017702254,0.002116002,0.0006241304,0.000104029874,0.001643772,0.0026579418,0.09151823,0.5942625,0.045257468,0.010834373,0.24983694],"study_design_scores_gemma":[0.00023116928,0.00032190164,0.0021305385,0.0001635471,0.00010041724,0.0019121679,0.0003465257,0.7497995,0.1702102,0.03313301,0.041393198,0.00025779504],"about_ca_topic_score_codex":0.0009835716,"about_ca_topic_score_gemma":0.0015468819,"teacher_disagreement_score":0.0050515626,"about_ca_system_score_codex":0.00034344647,"about_ca_system_score_gemma":0.0005955935,"threshold_uncertainty_score":0.016899109},"labels":[],"label_agreement":null},{"id":"W1762773937","doi":"10.1684/epd.2008.0217","title":"Pathways of seizure propagation from the temporal to the occipital lobe","year":2008,"lang":"en","type":"article","venue":"Epileptic Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Temporal lobe; Epilepsy; Neuroscience; Occipital lobe; Psychology; Audiology; Medicine","score_opus":0.052372395229716213,"score_gpt":0.29463392937806654,"score_spread":0.24226153414835033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1762773937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9493091,0.010152427,0.017038012,0.000803828,0.000035262474,0.00006012369,0.00020132356,0.00019399784,0.022205837],"genre_scores_gemma":[0.9931926,0.0030585756,0.0024314383,0.00007929725,0.000025532625,0.00001874694,0.00007117243,0.00001060863,0.0011119462],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9999169,0.000024749554,0.000007905343,0.0000075241906,0.000012779516,0.000030223173],"domain_scores_gemma":[0.99968886,0.000087361695,0.00011908642,0.000024383466,0.000048997383,0.000031379594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001483464,0.00034708463,0.00010984932,0.0006284401,0.00024291837,0.0006031032,0.000121638,0.00022351331,0.0021799991],"category_scores_gemma":[0.00079363043,0.00013705752,0.00016811729,0.0003272999,0.0004300249,0.0005980449,0.00034901014,0.0003594132,0.00041168262],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019377097,0.00011225073,0.22142209,0.00060906314,0.00014151038,0.16220507,0.002790403,0.0025140024,0.2662207,0.022145329,0.002694426,0.31720746],"study_design_scores_gemma":[0.00030840727,0.0012147317,0.2902227,0.00054063916,0.00021185893,0.52441424,0.0027132235,0.00830075,0.10318918,0.035091728,0.033608258,0.0001842537],"about_ca_topic_score_codex":0.001438047,"about_ca_topic_score_gemma":0.0014372297,"teacher_disagreement_score":0.0021799991,"about_ca_system_score_codex":0.00034361138,"about_ca_system_score_gemma":0.00041825225,"threshold_uncertainty_score":0.0072928667},"labels":[],"label_agreement":null},{"id":"W1775970683","doi":"10.1089/neu.2015.3948","title":"Long-Term Abnormalities in the Corpus Callosum of Female Concussed Athletes","year":2015,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Diffusion MRI; Concussion; White matter; Fractional anisotropy; Corticospinal tract; Athletes; Psychology; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Physical therapy; Neuroscience; Poison control; Radiology; Injury prevention","score_opus":0.24330807292608725,"score_gpt":0.40574201952635947,"score_spread":0.16243394660027222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1775970683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99951196,0.00015217206,0.000028698469,0.000017164837,0.0000031725936,0.0000032743358,0.000037065405,0.000001787841,0.00024457596],"genre_scores_gemma":[0.99929273,0.000100456215,0.000073303745,0.00001298328,0.000008462267,0.0000072002663,0.00007779893,0.0000018989044,0.00042520653],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998981,0.000012437446,0.000010880107,0.000028707995,0.000021077964,0.000028861943],"domain_scores_gemma":[0.9996834,0.000024742289,0.00015754486,0.00001557598,0.000055318105,0.00006346083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016974255,0.00026960275,0.00023249055,0.00080197473,0.00039917164,0.0002837808,0.00015144501,0.00037787287,0.0015396357],"category_scores_gemma":[0.0007167841,0.000111414214,0.00014830778,0.00022472726,0.00035997096,0.00020511463,0.00031969426,0.00016342044,0.00025960733],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014664662,0.00027196747,0.90379125,0.00011306247,0.00012258218,0.0039219283,0.0016999167,0.0001622809,0.065032616,0.00008726874,0.00027548397,0.023055224],"study_design_scores_gemma":[0.0000032709372,0.00028326618,0.9971042,0.0000058555565,0.000012365373,0.001461332,0.00031848898,0.000040219464,0.00060570403,0.000011790202,0.00015060748,0.0000029783218],"about_ca_topic_score_codex":0.0043752478,"about_ca_topic_score_gemma":0.0045588436,"teacher_disagreement_score":0.0043752478,"about_ca_system_score_codex":0.00029641797,"about_ca_system_score_gemma":0.00023403406,"threshold_uncertainty_score":0.008699536},"labels":[],"label_agreement":null},{"id":"W1778022616","doi":"10.48550/arxiv.1207.0677","title":"Local Water Diffusion Phenomenon Clustering From High Angular Resolution\\n Diffusion Imaging (HARDI)","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Voxel; Computer science; Angular resolution (graph drawing); White matter; Artificial intelligence; Tractography; Diffusion; Cluster analysis; Pattern recognition (psychology); Magnetic resonance imaging; Computer vision; Physics; Mathematics; Medicine","score_opus":0.0774502445703158,"score_gpt":0.22902166133265325,"score_spread":0.15157141676233746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1778022616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36716628,0.0032521957,0.6122733,0.0007643389,0.0001225976,0.00029096066,0.0052070427,0.00407239,0.0068509053],"genre_scores_gemma":[0.76399195,0.001992707,0.21731535,0.00012472055,0.00016689724,0.00012831908,0.011360708,0.00041380996,0.0045054355],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995055,0.00007491877,0.000041741703,0.00018130576,0.000135683,0.000060784754],"domain_scores_gemma":[0.99869776,0.0002987167,0.000323355,0.00037701597,0.00022188833,0.00008120267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008112771,0.00090197724,0.0005940294,0.0041198423,0.00047594003,0.0012685928,0.0006504054,0.0007467908,0.001419022],"category_scores_gemma":[0.0034348231,0.00027589736,0.00063265255,0.0023182726,0.0007991525,0.0011016121,0.0013228266,0.0006641339,0.0011392604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063086534,0.00025334515,0.03640523,0.0015384584,0.00042629268,0.0016100757,0.0010478321,0.06729014,0.1723541,0.009877952,0.017134165,0.6914315],"study_design_scores_gemma":[0.000066688284,0.00025911228,0.10165871,0.00017494448,0.0002923843,0.003039378,0.0006839002,0.64618707,0.17607845,0.04673369,0.024584288,0.00024139645],"about_ca_topic_score_codex":0.0027391112,"about_ca_topic_score_gemma":0.005091872,"teacher_disagreement_score":0.0041198423,"about_ca_system_score_codex":0.000340879,"about_ca_system_score_gemma":0.00042976096,"threshold_uncertainty_score":0.0054463744},"labels":[],"label_agreement":null},{"id":"W1780280682","doi":"10.1016/j.schres.2015.10.023","title":"Neuroimaging predictors of functional outcomes in schizophrenia at baseline and 6-month follow-up","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Canada Research Chairs; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Brain and Behaviour Research Institute, University of Wollongong; Canadian Institutes of Health Research; Ontario Mental Health Foundation; Centre for Addiction and Mental Health Foundation; Brain Research Foundation; Foundation for the National Institutes of Health","keywords":"Arcuate fasciculus; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Neuroimaging; Functional neuroimaging; Default mode network; Diffusion MRI; Audiology; Internal medicine; Neuroscience; Psychiatry; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.16042183449652586,"score_gpt":0.3977267967092128,"score_spread":0.23730496221268693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1780280682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993266,0.00013252224,0.000023039414,0.00004642564,0.000003980446,0.0000031124514,0.00017675674,0.000002160666,0.00028559746],"genre_scores_gemma":[0.9994729,0.00007143965,0.000025237823,0.000006786763,0.000004885647,0.0000032606376,0.00027794234,6.886828e-7,0.00013681577],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998282,0.000030394434,0.000016644455,0.00002747632,0.000028292174,0.00006891393],"domain_scores_gemma":[0.99848264,0.00020435388,0.0006817008,0.000058989455,0.00020965518,0.00036272075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000536464,0.0003231252,0.0003624427,0.00064725237,0.0005027597,0.0005751975,0.00028031386,0.000565643,0.0010769193],"category_scores_gemma":[0.0029079777,0.00016854424,0.0004907037,0.00047809535,0.000308626,0.0006394489,0.00056485855,0.00080669374,0.00016269172],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000994906,0.00013031838,0.994925,0.000008885335,0.00007570209,0.00013310366,0.00011910042,0.0001542256,0.00048037426,0.000026657213,0.000104670726,0.002846996],"study_design_scores_gemma":[0.0000045268753,0.00011731397,0.9994629,0.0000040573236,0.00002484924,0.00006019291,0.00010351687,0.00010068589,0.000053113672,0.000037300208,0.000027789247,0.0000037639875],"about_ca_topic_score_codex":0.02053372,"about_ca_topic_score_gemma":0.02729062,"teacher_disagreement_score":0.02053372,"about_ca_system_score_codex":0.00069430843,"about_ca_system_score_gemma":0.00070946885,"threshold_uncertainty_score":0.040828407},"labels":[],"label_agreement":null},{"id":"W1784432185","doi":"10.1002/nbm.2992","title":"Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination","year":2013,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":153,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Saskatchewan; University of Manitoba","funders":"","keywords":"Magnetization transfer; Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Magnetic resonance imaging; Myelin; Nuclear magnetic resonance; Axon; Internal capsule; Chemistry; External capsule; Nuclear medicine; Pathology; Anatomy; Biology; Medicine; Central nervous system; Physics; Endocrinology; Radiology","score_opus":0.0570184849446915,"score_gpt":0.3443379311878083,"score_spread":0.2873194462431168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1784432185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867561,0.0013496425,0.008544133,0.00007965457,0.000029404171,0.00007461264,0.0014943377,0.00034104934,0.0013311415],"genre_scores_gemma":[0.9826397,0.00091649086,0.010149501,0.000072613286,0.00001523598,0.0001413629,0.0015753299,0.0000988135,0.0043909387],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997135,0.00003487501,0.00003960371,0.00007776966,0.000080862796,0.000053345502],"domain_scores_gemma":[0.99924624,0.00006998711,0.00028888346,0.00007742339,0.00015886794,0.0001586348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051553,0.00084019976,0.00035544168,0.0018684488,0.0002923774,0.00037625586,0.00029588322,0.0005906758,0.0009635542],"category_scores_gemma":[0.00024903278,0.00028309657,0.00028768668,0.00047163494,0.0004004326,0.0003498164,0.00027227684,0.0006134128,0.00032838667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023811619,0.0000428356,0.000539377,0.000051185572,0.000014311327,0.00011807014,0.000043246724,0.00007972509,0.99822754,0.00008669499,0.000031467345,0.00052747806],"study_design_scores_gemma":[0.000035721343,0.00084897515,0.041716155,0.000036933583,0.00009722262,0.0013579853,0.00011369598,0.0023951654,0.95157784,0.00014275979,0.0016465144,0.00003092315],"about_ca_topic_score_codex":0.0013065428,"about_ca_topic_score_gemma":0.0015810446,"teacher_disagreement_score":0.0018684488,"about_ca_system_score_codex":0.0003704048,"about_ca_system_score_gemma":0.00014224727,"threshold_uncertainty_score":0.0032234788},"labels":[],"label_agreement":null},{"id":"W1799381395","doi":"10.1016/j.neuroimage.2015.07.074","title":"Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Diffusion MRI; Diffusion; Noise (video); SIGNAL (programming language); Estimator; Computer science; Algorithm; Contrast (vision); Signal-to-noise ratio (imaging); Gaussian; Artificial intelligence; Statistics; Mathematics; Physics","score_opus":0.04526567435901944,"score_gpt":0.3122587677662398,"score_spread":0.2669930934072203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1799381395","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087028146,0.0042407885,0.8946558,0.001530752,0.0003981742,0.00013591691,0.0003854317,0.0020988612,0.009526036],"genre_scores_gemma":[0.30524158,0.0034749317,0.6839781,0.0004884929,0.00037436443,0.00012242302,0.0004288652,0.0007561014,0.0051351236],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956614,0.0001290811,0.00003597727,0.000097110016,0.00012892805,0.00004269421],"domain_scores_gemma":[0.9988782,0.00046448375,0.0001146688,0.00026854879,0.00020136003,0.000072777904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014707015,0.00092760683,0.0004445278,0.0006905622,0.00036093258,0.0019064867,0.0009521713,0.0017014804,0.0053755427],"category_scores_gemma":[0.0038935684,0.0009458961,0.00031891858,0.00050344475,0.00089512125,0.0035421061,0.0013562506,0.0016846523,0.0018146217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004981936,0.0000878783,0.0006253016,0.000828782,0.000086197244,0.0008886311,0.00016265939,0.0024745811,0.8815078,0.019155148,0.0034474838,0.0902374],"study_design_scores_gemma":[0.00010094934,0.00036983233,0.0019881346,0.00012258142,0.00013127059,0.009487818,0.00007043852,0.029069815,0.9123286,0.017008016,0.029222287,0.00010020416],"about_ca_topic_score_codex":0.00021181587,"about_ca_topic_score_gemma":0.0004526769,"teacher_disagreement_score":0.0053755427,"about_ca_system_score_codex":0.0002586986,"about_ca_system_score_gemma":0.0005459904,"threshold_uncertainty_score":0.01798296},"labels":[],"label_agreement":null},{"id":"W1806292349","doi":"10.1167/15.12.434","title":"The reorganization of extrastriate cortex in patients with lobectomy","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Hemispherectomy; Extrastriate cortex; Visual cortex; Ocular dominance; Neuroscience; Psychology; Cortex (anatomy); Neuroplasticity; Epilepsy","score_opus":0.02815280108009934,"score_gpt":0.33598243270137534,"score_spread":0.307829631621276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1806292349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994777,0.000056150682,0.00004951846,0.00002416642,0.0000015760347,0.0000036099507,0.000067937275,0.0000069119856,0.00031255945],"genre_scores_gemma":[0.99958545,0.000054216467,0.000078133526,0.0000120181,0.0000025459515,0.0000035228143,0.00008456181,0.0000033447552,0.0001763694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998925,0.000012161622,0.000012421042,0.000037045866,0.000019491516,0.00002633133],"domain_scores_gemma":[0.99963903,0.0000487882,0.00019491045,0.00002796692,0.000020175463,0.000069140944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011750949,0.00038430764,0.00030766445,0.0008503379,0.00035230423,0.00034707936,0.0001459569,0.00025890855,0.0024337661],"category_scores_gemma":[0.0006632231,0.00017499443,0.00018464454,0.00040563816,0.0006788876,0.00033366887,0.00037057255,0.00037983712,0.00029994987],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008518072,0.00019232921,0.85859245,0.00009916531,0.00008487326,0.029913293,0.0020291195,0.0003669486,0.091370165,0.00025358977,0.00040040567,0.015845831],"study_design_scores_gemma":[0.000009054993,0.0001880126,0.973929,0.000005874007,0.000013824608,0.023071101,0.00046611822,0.00009393447,0.0019280408,0.0000785167,0.00020939665,0.0000070148485],"about_ca_topic_score_codex":0.0021693583,"about_ca_topic_score_gemma":0.004783365,"teacher_disagreement_score":0.0024337661,"about_ca_system_score_codex":0.00035076632,"about_ca_system_score_gemma":0.00032825427,"threshold_uncertainty_score":0.008141816},"labels":[],"label_agreement":null},{"id":"W1822844310","doi":"10.1016/j.neuroimage.2015.08.079","title":"STEAM — Statistical Template Estimation for Abnormality Mapping: A personalized DTI analysis technique with applications to the screening of preterm infants","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; Women's College Hospital; University of British Columbia; Hospital for Sick Children; BC Children's Hospital; University of Toronto; Children's & Women's Health Centre of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Government of Alberta","keywords":"Diffusion MRI; Computer science; Voxel; Artificial intelligence; Population; Smoothing; Template; Pipeline (software); White matter; Pattern recognition (psychology); Computer vision; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.13194532553374547,"score_gpt":0.3973218709353064,"score_spread":0.26537654540156097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1822844310","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0094597,0.0001276203,0.9869789,0.000085481406,0.000029034363,0.000034356635,0.0001566616,0.0027883744,0.00033988847],"genre_scores_gemma":[0.07614232,0.00028487528,0.92066246,0.00011479647,0.00005461,0.000100018944,0.0003669343,0.0010786626,0.001195308],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975747,0.00006637943,0.000019489813,0.00006118695,0.000075412834,0.000020030053],"domain_scores_gemma":[0.99896824,0.0004582201,0.00011828673,0.00019047111,0.00019557166,0.0000692361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011145694,0.00074385246,0.0006091885,0.00100309,0.00038256534,0.0009339605,0.0009737757,0.00076768186,0.0035118605],"category_scores_gemma":[0.004981788,0.00055901275,0.0008101024,0.0009187309,0.00027450098,0.0009972231,0.0011869447,0.0009765904,0.0010465767],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040173752,0.00011173342,0.0044065975,0.00021918294,0.00028311225,0.00031941716,0.0002723825,0.032756854,0.07295951,0.0074661127,0.008359824,0.8724436],"study_design_scores_gemma":[0.000080590355,0.00032688188,0.009703893,0.000048848968,0.00024336201,0.002056444,0.00011688693,0.86194676,0.09044017,0.017738512,0.017172286,0.00012537038],"about_ca_topic_score_codex":0.0021539265,"about_ca_topic_score_gemma":0.004997431,"teacher_disagreement_score":0.0035118605,"about_ca_system_score_codex":0.00023646026,"about_ca_system_score_gemma":0.0011109842,"threshold_uncertainty_score":0.011748314},"labels":[],"label_agreement":null},{"id":"W1823166105","doi":"10.1371/journal.pone.0138910","title":"Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Instituto de Salud Carlos III; European Regional Development Fund; Engineering and Physical Sciences Research Council","keywords":"Deconvolution; Voxel; Regularization (linguistics); Noise (video); Gaussian; Gaussian noise; Algorithm; Rician fading; Diffusion MRI; Computer science; Mathematics; Artificial intelligence; Physics; Magnetic resonance imaging","score_opus":0.15017531334030934,"score_gpt":0.314680585050419,"score_spread":0.16450527171010967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1823166105","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012934418,0.00013818058,0.9862635,0.000046871475,0.000011506611,0.000020452666,0.000023859426,0.00031117862,0.00024993913],"genre_scores_gemma":[0.15258001,0.00038458302,0.84493864,0.00007158956,0.000017782837,0.000091166585,0.00021349633,0.00019016792,0.0015125043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926287,0.00022258714,0.000053359203,0.00014315032,0.0002784782,0.000039531085],"domain_scores_gemma":[0.99843603,0.0006511855,0.00023252174,0.00027667783,0.0003573329,0.000046274163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002218679,0.0010675977,0.00068774563,0.0008160072,0.00023847826,0.0006394272,0.0008403259,0.001037863,0.0006034373],"category_scores_gemma":[0.004456733,0.00038133605,0.001110661,0.0007908594,0.00092458463,0.001180182,0.0012027995,0.0009984181,0.00032218237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032735965,0.00014626082,0.0026819755,0.00044514134,0.0003208602,0.00030600198,0.0003385709,0.5848278,0.15928839,0.029387673,0.0014780415,0.22045198],"study_design_scores_gemma":[0.000011024491,0.00008397047,0.0006189794,0.000010436753,0.000023587287,0.00018915639,0.000021412212,0.94970256,0.04406453,0.0032237729,0.0020136698,0.000036845406],"about_ca_topic_score_codex":0.0033930487,"about_ca_topic_score_gemma":0.004715936,"teacher_disagreement_score":0.0033930487,"about_ca_system_score_codex":0.00056178495,"about_ca_system_score_gemma":0.001455239,"threshold_uncertainty_score":0.011733651},"labels":[],"label_agreement":null},{"id":"W1826765467","doi":"10.1007/978-3-642-40760-4_64","title":"Diffusion Propagator Estimation from Sparse Measurements in a Tractography Framework","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Center for Research Resources; U.S. Public Health Service; National Institutes of Health","keywords":"Propagator; Diffusion MRI; Computer science; Tractography; Artificial intelligence; Diffusion; Voxel; Exponential function; Algorithm; Computer vision; Pattern recognition (psychology); Physics; Mathematics; Mathematical analysis","score_opus":0.05872241666313185,"score_gpt":0.3324979438030909,"score_spread":0.27377552713995906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1826765467","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014931903,0.000075076845,0.99808925,0.00007495937,0.000009741722,0.0000075118774,0.00002185042,0.00008755777,0.00014077459],"genre_scores_gemma":[0.14228202,0.0011139535,0.852305,0.000089301866,0.0001519931,0.00016277081,0.0003862339,0.00027199154,0.0032368158],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954396,0.00018245599,0.000030586634,0.00009339546,0.00011866808,0.000030824056],"domain_scores_gemma":[0.9966557,0.0025205647,0.00026315005,0.00020422328,0.0002489248,0.00010742984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014177657,0.0010021495,0.0013712686,0.0010059745,0.00044183692,0.0016082574,0.0012096744,0.0021925766,0.0014582701],"category_scores_gemma":[0.00857678,0.0012344439,0.0011349536,0.0014611356,0.0011315343,0.0021267575,0.0016887657,0.002716335,0.00071957277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017315784,0.00007064273,0.0005986472,0.00029392424,0.00012093208,0.00022859103,0.00016358444,0.81262636,0.01681843,0.06855969,0.0016328596,0.09871317],"study_design_scores_gemma":[0.000011078073,0.000017579961,0.00008651395,0.000012250152,0.000011702573,0.000057907448,0.000007945081,0.98174816,0.0010335506,0.016325595,0.00067399204,0.000013773073],"about_ca_topic_score_codex":0.003983269,"about_ca_topic_score_gemma":0.0041822917,"teacher_disagreement_score":0.003983269,"about_ca_system_score_codex":0.0004993551,"about_ca_system_score_gemma":0.0016545785,"threshold_uncertainty_score":0.007920146},"labels":[],"label_agreement":null},{"id":"W1831984264","doi":"10.1111/jon.12283","title":"The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":172,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering","keywords":"Tractography; Diffusion MRI; Medicine; Neurosurgery; Pyramidal tracts; White matter; Medical physics; Radiology; Magnetic resonance imaging; Anatomy","score_opus":0.23813646896515533,"score_gpt":0.4263831107608204,"score_spread":0.18824664179566508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1831984264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11911963,0.0069770697,0.8429352,0.012833101,0.0008154081,0.005477002,0.002323482,0.0021250143,0.0073940726],"genre_scores_gemma":[0.14514796,0.0013644102,0.84596616,0.00067975116,0.00030007318,0.0036689255,0.0017264364,0.000719623,0.00042668407],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.8470237,0.10311383,0.016495278,0.0068707126,0.024596805,0.0018995709],"domain_scores_gemma":[0.6272742,0.14412872,0.04341597,0.052618727,0.120087676,0.012474615],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2605611,0.0026384927,0.0027271372,0.012074751,0.0028637117,0.012917038,0.005963652,0.0028926518,0.0017780504],"category_scores_gemma":[0.38837594,0.001216524,0.0014165153,0.005614667,0.007408696,0.009765165,0.014382363,0.004639379,0.0010646628],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010006977,0.000994171,0.13660644,0.003783759,0.0009768518,0.00057115924,0.013157262,0.024603395,0.011033269,0.05544681,0.03343243,0.71839374],"study_design_scores_gemma":[0.00071719754,0.0048616724,0.23173648,0.012502975,0.00072640466,0.0029635658,0.020480882,0.27934512,0.033765577,0.27122512,0.14008239,0.0015925592],"about_ca_topic_score_codex":0.004739564,"about_ca_topic_score_gemma":0.0050346805,"teacher_disagreement_score":0.2605611,"about_ca_system_score_codex":0.00577251,"about_ca_system_score_gemma":0.024424125,"threshold_uncertainty_score":0.9118598},"labels":[],"label_agreement":null},{"id":"W1834846057","doi":"10.1002/mrm.25852","title":"In vivo free‐breathing DTI and IVIM of the whole human heart using a real‐time slice‐followed SE‐EPI navigator‐based sequence: A reproducibility study in healthy volunteers","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche; LabEx PRIMES; Siemens USA","keywords":"Reproducibility; Intravoxel incoherent motion; Sequence (biology); Breathing; In vivo; Medicine; Nuclear medicine; Biomedical engineering; Magnetic resonance imaging; Chemistry; Diffusion MRI; Anatomy; Biology; Radiology; Chromatography","score_opus":0.14417269337912406,"score_gpt":0.4277169462949297,"score_spread":0.28354425291580565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1834846057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9758114,0.0006998049,0.022990596,0.000026953792,0.000017701543,0.000051232888,0.000071648465,0.000084804204,0.0002458426],"genre_scores_gemma":[0.9858931,0.00023226193,0.013270543,0.00004194782,0.00003563065,0.000056024997,0.00016656477,0.00006016954,0.00024382285],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99935895,0.00023297027,0.00004329508,0.0002593952,0.00008060748,0.000024761495],"domain_scores_gemma":[0.99888915,0.0003354559,0.00019497683,0.00032846304,0.00018029005,0.00007171149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018794977,0.0004627615,0.00031586483,0.00022692974,0.00020694511,0.00035521606,0.00035680222,0.00065786456,0.0004362211],"category_scores_gemma":[0.0027673196,0.00026627444,0.0002176573,0.00014662885,0.00044440708,0.00037013492,0.00025705324,0.00024552696,0.00021150005],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049912883,0.00069422886,0.08109929,0.0004735462,0.0005743478,0.0005819821,0.00127459,0.001960641,0.82659054,0.0002973096,0.00043962663,0.08102261],"study_design_scores_gemma":[0.00047473647,0.019899273,0.719446,0.0000672609,0.0011251334,0.010897728,0.00053184776,0.029228406,0.21340325,0.00050852,0.0042731664,0.00014469646],"about_ca_topic_score_codex":0.0003506324,"about_ca_topic_score_gemma":0.00062835176,"teacher_disagreement_score":0.0018794977,"about_ca_system_score_codex":0.00008601451,"about_ca_system_score_gemma":0.00013392782,"threshold_uncertainty_score":0.009939849},"labels":[],"label_agreement":null},{"id":"W1840441345","doi":"10.3389/fnana.2015.00069","title":"A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Regional Development Fund; Freistaat Sachsen; Universität Leipzig; European Commission","keywords":"Brain morphometry; White matter; Population; Human brain; Brain size; Brain atlas; Biology; Anatomy; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.049700239167075354,"score_gpt":0.3387245445767364,"score_spread":0.28902430540966106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1840441345","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21615858,0.0046501574,0.7243111,0.00041602107,0.00031223893,0.001467148,0.024391657,0.004264452,0.02402867],"genre_scores_gemma":[0.24527662,0.0052561555,0.7048522,0.00021311236,0.00014244542,0.0025580912,0.025300656,0.0012387953,0.015161871],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997578,0.00004121052,0.000039024926,0.00008732724,0.000059195954,0.000015473084],"domain_scores_gemma":[0.99962103,0.0000584519,0.000116839205,0.00009425147,0.00009299142,0.000016489677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000541528,0.00063435815,0.0004956557,0.0020546585,0.00041928721,0.00073551154,0.00057630404,0.0009293845,0.005840185],"category_scores_gemma":[0.000723966,0.0004943082,0.00031654403,0.0014103061,0.00044073086,0.0006216807,0.00054897426,0.00060608354,0.0019246358],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086833356,0.00017469694,0.013162398,0.0021275736,0.00023314958,0.0018156021,0.0014661642,0.006406553,0.58205587,0.0098299375,0.02798828,0.35387143],"study_design_scores_gemma":[0.00016084545,0.0020892,0.28261587,0.00072583376,0.00066696474,0.023870843,0.00093563535,0.027554916,0.12908645,0.008548983,0.52344733,0.00029716015],"about_ca_topic_score_codex":0.0016941458,"about_ca_topic_score_gemma":0.0056148535,"teacher_disagreement_score":0.005840185,"about_ca_system_score_codex":0.00027544293,"about_ca_system_score_gemma":0.00072523375,"threshold_uncertainty_score":0.01953733},"labels":[],"label_agreement":null},{"id":"W1843575755","doi":"10.1007/11566465_16","title":"3D Curve Inference for Diffusion MRI Regularization","year":2005,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Diffusion MRI; Voxel; Regularization (linguistics); Inference; Imaging phantom; Artificial intelligence; Computer science; Mathematics; Algorithm; Physics; Magnetic resonance imaging; Medicine; Radiology; Optics","score_opus":0.03428829711341734,"score_gpt":0.34748213446659865,"score_spread":0.3131938373531813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1843575755","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010348905,0.00018591176,0.99785006,0.00013246521,0.00002295709,0.000014839043,0.00006301396,0.0005141281,0.00018177075],"genre_scores_gemma":[0.06173178,0.00066737505,0.93238366,0.0001948883,0.00013366199,0.00018871666,0.0006395311,0.0008273035,0.0032330817],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913245,0.00033986743,0.000048987164,0.00018880876,0.00023712593,0.000052762058],"domain_scores_gemma":[0.9960157,0.002394211,0.00026267255,0.00071345846,0.00047753289,0.00013637074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025706517,0.0011807571,0.0020956665,0.0017328713,0.0008168607,0.0016631213,0.0030903956,0.003995706,0.005148557],"category_scores_gemma":[0.0122968415,0.0020892275,0.002128013,0.0018178981,0.001432227,0.0021925713,0.0026608584,0.0041625663,0.0022772625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025439452,0.0001001534,0.00079253066,0.000391436,0.00021509475,0.00012046004,0.0001337352,0.5460291,0.009432448,0.07084965,0.013730504,0.3579505],"study_design_scores_gemma":[0.0000096182175,0.000008878827,0.000056904348,0.000010818674,0.000007558509,0.000021902393,0.0000038601847,0.9706288,0.0008617966,0.026975527,0.0014043075,0.000009960063],"about_ca_topic_score_codex":0.010066852,"about_ca_topic_score_gemma":0.010205995,"teacher_disagreement_score":0.010066852,"about_ca_system_score_codex":0.0012832481,"about_ca_system_score_gemma":0.0025258558,"threshold_uncertainty_score":0.020016551},"labels":[],"label_agreement":null},{"id":"W1847146623","doi":"10.1002/mrm.25363","title":"A model for extra‐axonal diffusion spectra with frequency‐dependent restriction","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Tortuosity; Diffusion; RADIUS; Spectral line; Monte Carlo method; White matter; Statistical physics; Materials science; Molecular physics; Physics; Biological system; Computational physics; Mechanics; Mathematics; Computer science; Thermodynamics","score_opus":0.05993902862841297,"score_gpt":0.32893073206625056,"score_spread":0.26899170343783757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1847146623","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21187507,0.0005570476,0.7749948,0.0009953334,0.000088269706,0.00012979188,0.00023665334,0.00043833576,0.010684614],"genre_scores_gemma":[0.93432206,0.0005486122,0.05544818,0.00023470398,0.000049699316,0.00031446738,0.00018176585,0.00013732372,0.008763292],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999772,0.00005769952,0.000010221302,0.000055681994,0.0000677939,0.00003656785],"domain_scores_gemma":[0.9988182,0.0006078045,0.00019423643,0.00009704818,0.00021201497,0.00007061752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008013705,0.0006398186,0.0006184534,0.00073822134,0.00047866392,0.0008073785,0.0017096318,0.0021706077,0.002078622],"category_scores_gemma":[0.0029962969,0.0004569257,0.0008663054,0.00050114084,0.0013004651,0.0019940217,0.00053653563,0.0008301356,0.00065500836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057245554,0.00007608898,0.00061736355,0.00005690731,0.000016137104,0.00026008053,0.00013118141,0.9526385,0.008300617,0.03425784,0.00053739053,0.0030505932],"study_design_scores_gemma":[0.000008287579,0.000009920929,0.00012555369,0.00000392247,0.0000034170291,0.00005605216,0.0000070131146,0.99522555,0.00027962032,0.0041025304,0.00017094852,0.000007129461],"about_ca_topic_score_codex":0.0058608055,"about_ca_topic_score_gemma":0.0025691187,"teacher_disagreement_score":0.0058608055,"about_ca_system_score_codex":0.0012116607,"about_ca_system_score_gemma":0.0010048054,"threshold_uncertainty_score":0.011653364},"labels":[],"label_agreement":null},{"id":"W1847972783","doi":"10.1007/978-3-642-22092-0_58","title":"Rotation Invariant Completion Fields for Mapping Diffusion MRI Connectivity","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Rotation (mathematics); Imaging phantom; Spherical harmonics; Invariant (physics); Partial differential equation; Focus (optics); Artificial intelligence; Algorithm; Mathematics; Mathematical analysis; Physics","score_opus":0.09198212027283113,"score_gpt":0.3301112670399717,"score_spread":0.23812914676714053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1847972783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051113227,0.00019126176,0.9936603,0.0000980029,0.0000232657,0.000033746634,0.00015975276,0.00039585537,0.00032642874],"genre_scores_gemma":[0.15234432,0.0011550299,0.8379915,0.00010911199,0.00015998234,0.0002967665,0.0015862846,0.00068243116,0.005674629],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995685,0.00017016353,0.00002715154,0.00008088546,0.00011981649,0.00003339333],"domain_scores_gemma":[0.9981499,0.00097128283,0.00020294127,0.0003009779,0.00027767132,0.00009713615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014771317,0.0010395161,0.0011472879,0.00164121,0.00045858583,0.0011235013,0.0013299981,0.001045231,0.003555797],"category_scores_gemma":[0.005683158,0.0006888158,0.0010560921,0.0018468492,0.0009971657,0.0018752677,0.0014471676,0.002173555,0.0013214779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003836687,0.0001902445,0.0006668514,0.0003709057,0.00009268965,0.00014321264,0.0002209113,0.31144792,0.02446571,0.1452862,0.014106684,0.50262505],"study_design_scores_gemma":[0.000028903285,0.000083456915,0.00033391616,0.000021106847,0.000017065286,0.00008453091,0.000025330584,0.92257607,0.0040449584,0.069589525,0.003163987,0.000031129883],"about_ca_topic_score_codex":0.0046652732,"about_ca_topic_score_gemma":0.003521681,"teacher_disagreement_score":0.0046652732,"about_ca_system_score_codex":0.0006183158,"about_ca_system_score_gemma":0.0012497117,"threshold_uncertainty_score":0.011895359},"labels":[],"label_agreement":null},{"id":"W1854006008","doi":"10.1016/j.jneumeth.2015.09.025","title":"A reliability assessment of constrained spherical deconvolution-based diffusion-weighted magnetic resonance imaging in individuals with chronic stroke","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Fractional anisotropy; Corticospinal tract; Tractography; Voxel; Superior longitudinal fasciculus; Magnetic resonance imaging; White matter; Stroke (engine); Effective diffusion coefficient; Arcuate fasciculus; Nuclear medicine; Psychology; Medicine; Radiology; Physics","score_opus":0.06964000050974346,"score_gpt":0.4333532296103157,"score_spread":0.36371322910057224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1854006008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966067,0.00034373594,0.0022333509,0.00006664725,0.000022972697,0.000029295847,0.00016098417,0.0000186709,0.0005175921],"genre_scores_gemma":[0.9989134,0.00005219752,0.00075445016,0.00000930134,0.000015596317,0.00000992788,0.00016855834,0.000005260252,0.00007128297],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9953819,0.0018114201,0.00083953026,0.00076690695,0.0009990607,0.0002010872],"domain_scores_gemma":[0.95985967,0.020181214,0.005372798,0.0036489358,0.010433674,0.0005037767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013025412,0.0005549153,0.0006046881,0.002210954,0.0006484641,0.0012920747,0.0009269442,0.0011437344,0.0006856887],"category_scores_gemma":[0.06603092,0.000462649,0.000980542,0.00091327477,0.0009687075,0.000991624,0.0011962593,0.00056024495,0.00026471997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014589601,0.00010971656,0.9776858,0.00008040734,0.000822195,0.00013374546,0.0013316771,0.001425715,0.0013808361,0.00024517137,0.00046549275,0.014860297],"study_design_scores_gemma":[0.0000670346,0.0011250742,0.9753255,0.00006189656,0.00063169474,0.00071689906,0.0008538243,0.018772602,0.0012677212,0.0005978114,0.00052868837,0.000051235023],"about_ca_topic_score_codex":0.005468336,"about_ca_topic_score_gemma":0.0058547575,"teacher_disagreement_score":0.013025412,"about_ca_system_score_codex":0.0005246563,"about_ca_system_score_gemma":0.0006959279,"threshold_uncertainty_score":0.0688858},"labels":[],"label_agreement":null},{"id":"W1854389798","doi":"","title":"Comparison of generalized autocalibrating partially parallel acquisitions and modified sensitivity encoding for diffusion tensor imaging.","year":2007,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Nuclear magnetic resonance; Nuclear medicine; White matter; Magnetic resonance imaging; Medicine; Scanner; Effective diffusion coefficient; Physics; Artificial intelligence; Computer science; Radiology","score_opus":0.11230532866843362,"score_gpt":0.3740393363990045,"score_spread":0.2617340077305709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1854389798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7121879,0.013914894,0.268228,0.0005474875,0.0004831736,0.0007101815,0.00041374596,0.0010482443,0.0024664032],"genre_scores_gemma":[0.73872834,0.0025096263,0.25687584,0.00015615388,0.00010746053,0.0003272575,0.0005202626,0.00024110416,0.0005340536],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980919,0.0012690554,0.00011762503,0.0001618054,0.00031721976,0.000042379146],"domain_scores_gemma":[0.9933201,0.003995769,0.000654015,0.00051722437,0.0011851856,0.00032772415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050277123,0.00070409453,0.000363373,0.00063077465,0.00017383878,0.0006317692,0.00058731623,0.00073163724,0.0011182736],"category_scores_gemma":[0.019872896,0.00031327698,0.00040806393,0.00042396516,0.00043440744,0.0008457586,0.00061368477,0.0004885873,0.0002215826],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.028918808,0.00092665403,0.016943347,0.0029743449,0.0021305452,0.00086565636,0.0009428351,0.04278779,0.24739237,0.004024722,0.0025247824,0.64956814],"study_design_scores_gemma":[0.003986471,0.037315715,0.117849775,0.0005636712,0.0025755211,0.013578229,0.00045938834,0.58407694,0.20954734,0.00794093,0.021482663,0.0006233237],"about_ca_topic_score_codex":0.00069883285,"about_ca_topic_score_gemma":0.0011870373,"teacher_disagreement_score":0.0050277123,"about_ca_system_score_codex":0.00033631062,"about_ca_system_score_gemma":0.00052180834,"threshold_uncertainty_score":0.026589394},"labels":[],"label_agreement":null},{"id":"W18545325","doi":"10.1007/978-3-642-23629-7_12","title":"Detecting Structure in Diffusion Tensor MR Images","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Structure tensor; Curse of dimensionality; Curvature; Feature (linguistics); Diffusion; Artificial intelligence; Differential (mechanical device); Manifold (fluid mechanics); Dimensionality reduction; Pattern recognition (psychology); Computer vision; Image (mathematics); Mathematics; Physics; Pure mathematics; Geometry; Magnetic resonance imaging","score_opus":0.045158095133525394,"score_gpt":0.31949255465252796,"score_spread":0.2743344595190026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W18545325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3450983,0.0018186774,0.6494591,0.00073050207,0.00014071257,0.00009961681,0.0004148221,0.00082255783,0.0014157863],"genre_scores_gemma":[0.5961765,0.003190202,0.3964129,0.00012141728,0.00024481583,0.00004241642,0.00077695533,0.0002864642,0.0027482721],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998049,0.000031275144,0.000017055514,0.000046291534,0.00007172475,0.0000287457],"domain_scores_gemma":[0.99871206,0.0005235856,0.00026773347,0.00015000363,0.00023152662,0.00011502593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065521564,0.0008765988,0.0005406994,0.0023052238,0.00043910876,0.0014454714,0.0005393082,0.00097451627,0.0009728604],"category_scores_gemma":[0.004168896,0.0007030824,0.00048351733,0.0010870451,0.000535803,0.0015147711,0.0006144564,0.00085473154,0.0005640322],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004957533,0.00014520416,0.010961378,0.00046373802,0.000155276,0.0009999061,0.00033470528,0.01985178,0.581816,0.006497742,0.0029241748,0.37535426],"study_design_scores_gemma":[0.000082023595,0.00050038914,0.026604252,0.00011047233,0.00030621188,0.0038112083,0.00040967,0.6103831,0.31626096,0.035186637,0.00621689,0.00012809187],"about_ca_topic_score_codex":0.0016160366,"about_ca_topic_score_gemma":0.0025377232,"teacher_disagreement_score":0.0023052238,"about_ca_system_score_codex":0.00021768427,"about_ca_system_score_gemma":0.000579351,"threshold_uncertainty_score":0.0034651756},"labels":[],"label_agreement":null},{"id":"W1861127629","doi":"10.1007/978-3-642-18421-5_17","title":"A Texture Manifold for Curve-Based Morphometry of the Cerebral Cortex","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Artificial intelligence; Computer science; Orientation (vector space); Texture (cosmology); Computer vision; Salient; Geometry; Shape analysis (program analysis); Segmentation; Surface (topology); Pattern recognition (psychology); Image (mathematics); Mathematics","score_opus":0.056575578061976016,"score_gpt":0.3083700348121913,"score_spread":0.2517944567502153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1861127629","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076695345,0.00042746542,0.98884076,0.00019807038,0.000089500754,0.000027552784,0.00017151752,0.00051040197,0.0020652728],"genre_scores_gemma":[0.16177921,0.0015749184,0.82795423,0.000087484914,0.00025565704,0.00008132776,0.00048387653,0.0006952263,0.0070880186],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988484,0.000015908512,0.000006323076,0.0000306756,0.00005168391,0.000010561758],"domain_scores_gemma":[0.99983597,0.000046670695,0.000014852448,0.000037483474,0.000041603107,0.0000233022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021967526,0.00038354765,0.0005638172,0.0009124177,0.00035331832,0.0011607043,0.00078417634,0.00075658644,0.0035481162],"category_scores_gemma":[0.00090090063,0.00026583028,0.00065215083,0.0009201737,0.0008889371,0.000954689,0.0011894505,0.0013062522,0.0010394433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008711306,0.00003811634,0.00047138348,0.0003300554,0.000048386963,0.00021375589,0.00035109848,0.07738043,0.057082847,0.29552862,0.011563101,0.55690515],"study_design_scores_gemma":[0.000010186602,0.000068374386,0.00092921377,0.000025781972,0.000015711432,0.0004044314,0.00007601962,0.74469274,0.005909527,0.22009876,0.027735284,0.000033933487],"about_ca_topic_score_codex":0.0016717003,"about_ca_topic_score_gemma":0.0014054585,"teacher_disagreement_score":0.0035481162,"about_ca_system_score_codex":0.0004207414,"about_ca_system_score_gemma":0.00044427085,"threshold_uncertainty_score":0.011869609},"labels":[],"label_agreement":null},{"id":"W1870643104","doi":"10.1139/jpn.0741","title":"Corpus callosum abnormalities in women with borderline personality disorder and comorbid attention-deficit hyperactivity disorder","year":2007,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Borderline personality disorder; Psychology; Attention deficit hyperactivity disorder; Magnetic resonance imaging; Audiology; Neuroscience; Psychiatry; Medicine; Radiology","score_opus":0.024147707497322844,"score_gpt":0.32115468178687717,"score_spread":0.2970069742895543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1870643104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99959224,0.00009133752,0.00005450716,0.000034449502,0.000002541144,0.000003169818,0.00003558646,0.0000040641844,0.00018217618],"genre_scores_gemma":[0.9997876,0.0000374589,0.00009734361,0.000008198861,0.0000029666653,0.0000032105338,0.000026356784,9.920192e-7,0.000035922083],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989307,0.000028350567,0.0000088345105,0.000027462906,0.000023460045,0.000018759178],"domain_scores_gemma":[0.99964213,0.00008961262,0.00016661087,0.000022009073,0.000024021052,0.00005557651],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023587728,0.00033877316,0.00025516888,0.00076391734,0.00054186024,0.00030843948,0.00022124713,0.00036160022,0.0015834242],"category_scores_gemma":[0.00203357,0.00029498074,0.00011791627,0.0003871348,0.00047398015,0.0001782776,0.00033582363,0.00020332924,0.000105155465],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007345189,0.000054288324,0.97012657,0.00006073049,0.00008806076,0.008883858,0.001332728,0.00020274046,0.009913036,0.000085638174,0.000323856,0.0081940405],"study_design_scores_gemma":[0.00002342011,0.00014951387,0.98030144,0.00001654981,0.00003898662,0.017587211,0.0007309707,0.00037820172,0.00041890892,0.00009862802,0.00025093244,0.000005297356],"about_ca_topic_score_codex":0.0032570036,"about_ca_topic_score_gemma":0.0053929323,"teacher_disagreement_score":0.0032570036,"about_ca_system_score_codex":0.00022535467,"about_ca_system_score_gemma":0.0001606138,"threshold_uncertainty_score":0.0064761043},"labels":[],"label_agreement":null},{"id":"W1902410198","doi":"10.3233/jad-150306","title":"White Matter Changes are Associated with Ventricular Expansion in Aging, Mild Cognitive Impairment, and Alzheimer’s Disease","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; National Institute on Aging; National Institutes of Health; IC Design Education Center; Canadian Institutes of Health Research; Biogen","keywords":"White matter; Neuroimaging; Diffusion MRI; Dementia; Neurodegeneration; Psychology; Cognitive decline; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Disease; Atrophy; Alzheimer's disease; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.07360605050306968,"score_gpt":0.33927411104680216,"score_spread":0.2656680605437325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1902410198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989599,0.0005577055,0.000080996186,0.000018607068,0.000004028154,0.0000052479545,0.00006364227,0.0000037642178,0.0003060445],"genre_scores_gemma":[0.9994655,0.00015696588,0.000115099865,0.000015336742,0.000015932153,0.0000037941338,0.00011682103,0.0000013553661,0.0001091466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997743,0.00003656197,0.000036536734,0.00006966208,0.000055656208,0.00002729422],"domain_scores_gemma":[0.99875426,0.00011038217,0.00083971006,0.00007373684,0.000094639436,0.00012726641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039811456,0.00034485696,0.00028772288,0.0011151598,0.00029647644,0.0003213483,0.00021676777,0.000332519,0.0005649277],"category_scores_gemma":[0.0015495525,0.00014140933,0.00022389083,0.0006824258,0.0004463862,0.0002873128,0.0004201745,0.00025208722,0.00010356584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036006465,0.000053715128,0.989503,0.0000365263,0.00010976482,0.00032056347,0.00014509352,0.000062558574,0.0034544207,0.00004569887,0.000098205805,0.005810295],"study_design_scores_gemma":[9.798116e-7,0.00003134047,0.99959916,0.0000013374097,0.0000059063104,0.00022016621,0.000015515665,0.000022179853,0.000046301964,0.00003221016,0.000024054061,9.643892e-7],"about_ca_topic_score_codex":0.0018967828,"about_ca_topic_score_gemma":0.0031818105,"teacher_disagreement_score":0.0018967828,"about_ca_system_score_codex":0.00015218923,"about_ca_system_score_gemma":0.00013236394,"threshold_uncertainty_score":0.0037715435},"labels":[],"label_agreement":null},{"id":"W190629664","doi":"10.1007/978-3-642-40763-5_63","title":"Cardiac Fiber Inpainting Using Cartan Forms","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Villum Fonden","keywords":"Inpainting; Computer science; Connection (principal bundle); Interpolation (computer graphics); Curvature; Orientation (vector space); Artificial intelligence; Curvilinear coordinates; Computer vision; Fiber; Algorithm; Diffusion MRI; Tensor (intrinsic definition); Mathematics; Image (mathematics); Geometry; Materials science","score_opus":0.03970193718831911,"score_gpt":0.3337795257651178,"score_spread":0.2940775885767987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W190629664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015552288,0.00046076303,0.97846586,0.0002731522,0.00017474254,0.00009580482,0.00019840487,0.0011725295,0.0036064119],"genre_scores_gemma":[0.11614334,0.0012691128,0.8712913,0.00016814673,0.0002838793,0.0000765362,0.00037845678,0.00060233637,0.009786838],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997212,0.00005446171,0.000020237634,0.000040197086,0.00014014411,0.000023738006],"domain_scores_gemma":[0.99912816,0.00030643633,0.000085646134,0.00020635453,0.00020603242,0.00006740494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006337038,0.00097333925,0.00059160654,0.0010803785,0.00036097804,0.001395594,0.00062060537,0.0009492555,0.013239289],"category_scores_gemma":[0.001760267,0.00044824101,0.0006256286,0.0010280213,0.00039017884,0.0009447478,0.00090397464,0.0012663226,0.0020318783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003644055,0.00008881568,0.00087332266,0.00037837867,0.0000630491,0.00052392564,0.00019392396,0.02172588,0.071702056,0.009925271,0.010424371,0.8837365],"study_design_scores_gemma":[0.000066026456,0.00038717888,0.0034886813,0.00010452947,0.00009533223,0.003117772,0.00017292459,0.8554905,0.080290884,0.010201578,0.046516355,0.00006822971],"about_ca_topic_score_codex":0.0008993483,"about_ca_topic_score_gemma":0.0025416901,"teacher_disagreement_score":0.013239289,"about_ca_system_score_codex":0.00018437045,"about_ca_system_score_gemma":0.0004051207,"threshold_uncertainty_score":0.044289827},"labels":[],"label_agreement":null},{"id":"W1929404890","doi":"10.1111/psyp.12565","title":"Microstructural white matter changes mediate age‐related cognitive decline on the Montreal Cognitive Assessment (MoCA)","year":2015,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University; Jewish General Hospital","funders":"","keywords":"Montreal Cognitive Assessment; Cognitive decline; White matter; Psychology; Cognition; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Gerontology; Cardiology; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Cognitive impairment; Disease; Dementia","score_opus":0.0625847552079232,"score_gpt":0.38543859345350506,"score_spread":0.3228538382455819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1929404890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99810684,0.0005300674,0.00025778546,0.000071997405,0.0000074055056,0.000022565224,0.00021396898,0.00001004849,0.00077940203],"genre_scores_gemma":[0.9991972,0.00015367796,0.00022717199,0.000017344093,0.000012601958,0.000009520143,0.00016477602,0.0000017905775,0.0002157786],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997254,0.00007006075,0.000021208742,0.00006826701,0.00007118916,0.000043918517],"domain_scores_gemma":[0.99761,0.0005219288,0.0010883441,0.00016720335,0.00039245514,0.00022008356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012247383,0.00051200285,0.00029037145,0.0005750761,0.00027064013,0.00054690504,0.0004492088,0.0004074451,0.001326122],"category_scores_gemma":[0.006263506,0.00019352439,0.00033462487,0.00040250574,0.00026276542,0.0005776822,0.00060844637,0.0004541687,0.0001811134],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031082955,0.00009895128,0.9898991,0.000030081832,0.00023366115,0.0000558035,0.00020880511,0.00018031431,0.0006844148,0.000061266765,0.00020790618,0.008028886],"study_design_scores_gemma":[0.0000020161544,0.00006471163,0.9994855,0.0000042788197,0.000022701646,0.000028769393,0.000026664138,0.00020911197,0.00005524137,0.00004518311,0.000054128494,0.000001743632],"about_ca_topic_score_codex":0.024831768,"about_ca_topic_score_gemma":0.03380634,"teacher_disagreement_score":0.024831768,"about_ca_system_score_codex":0.0002970245,"about_ca_system_score_gemma":0.0005061436,"threshold_uncertainty_score":0.04937446},"labels":[],"label_agreement":null},{"id":"W1930375114","doi":"10.1109/isbi.2015.7163905","title":"Using 3D-SHORE and MAP-MRI to obtain both tractography and microstructural constrast from a clinical DMRI acquisition","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Human Connectome Project; Undersampling; Tractography; Diffusion MRI; Computer science; White matter; Artificial intelligence; Pattern recognition (psychology); Magnetic resonance imaging; Functional connectivity; Neuroscience; Radiology","score_opus":0.17042363007432199,"score_gpt":0.4361045140076044,"score_spread":0.26568088393328243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1930375114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048238184,0.00016587839,0.9478547,0.000180743,0.000026313037,0.000081226135,0.00056506076,0.0019694516,0.0009184437],"genre_scores_gemma":[0.13776158,0.00033182834,0.8588415,0.00008798003,0.00003456992,0.00012714793,0.0013034968,0.00046495802,0.0010468768],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99954814,0.000108225635,0.000028410983,0.000106907144,0.00018062885,0.000027752765],"domain_scores_gemma":[0.99859947,0.00047907676,0.00026733306,0.00030201624,0.00026546096,0.000086556676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097501266,0.000978765,0.00058504543,0.0016167355,0.000400229,0.0012501993,0.0006350057,0.001006274,0.0020154305],"category_scores_gemma":[0.005430988,0.0007185277,0.0006939899,0.0015102287,0.00068463874,0.0011800415,0.0016575458,0.000932003,0.0013686157],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008746923,0.00016117776,0.018220931,0.0008586119,0.00041278667,0.0010484672,0.0009006137,0.13186674,0.27764064,0.014731524,0.0061702104,0.5471136],"study_design_scores_gemma":[0.000039112816,0.00026823673,0.01985868,0.00006337881,0.000110674366,0.00324927,0.00021015607,0.81996703,0.11667633,0.023798073,0.015576766,0.00018230663],"about_ca_topic_score_codex":0.0030559232,"about_ca_topic_score_gemma":0.00716917,"teacher_disagreement_score":0.0030559232,"about_ca_system_score_codex":0.0003434054,"about_ca_system_score_gemma":0.00088983664,"threshold_uncertainty_score":0.0067422986},"labels":[],"label_agreement":null},{"id":"W1932112317","doi":"10.1002/ajmg.b.32354","title":"A magnetic resonance imaging family study of cortical thickness in schizophrenia","year":2015,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part B Neuropsychiatric Genetics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; University Grants Committee; Health Research Board; University of Calgary","keywords":"Schizophrenia (object-oriented programming); Abnormality; Psychology; Psychosis; Magnetic resonance imaging; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.04792218276242896,"score_gpt":0.3500492225481932,"score_spread":0.3021270397857643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1932112317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937963,0.00011177798,0.00012788146,0.00004311982,0.0000034168456,0.0000030852855,0.000060981467,0.0000048773236,0.00026519952],"genre_scores_gemma":[0.9995939,0.00009190335,0.00012128917,0.0000138596715,0.0000035005464,0.0000024485994,0.000031471827,0.0000026462471,0.00013905912],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968815,0.00008555156,0.000029005312,0.000092778675,0.00006805054,0.000036573463],"domain_scores_gemma":[0.99922,0.00021107215,0.00025525707,0.000061049395,0.00007190208,0.00018066136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047930566,0.0007357894,0.0003459131,0.0014825424,0.0014977924,0.00031098354,0.00022586514,0.0003887233,0.0029765505],"category_scores_gemma":[0.0021555165,0.00037986352,0.00026390323,0.00070597016,0.0006569305,0.0003579323,0.00045091932,0.000396051,0.00018848323],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006127265,0.00014787284,0.9523546,0.000044725093,0.00018988062,0.020501029,0.0040861857,0.00031916448,0.013275073,0.00041793165,0.0004276713,0.0076231486],"study_design_scores_gemma":[0.000016391674,0.000265765,0.96593237,0.000030037432,0.000083879,0.030400695,0.0011370723,0.00035272574,0.0010436038,0.00037437901,0.00033518145,0.00002785123],"about_ca_topic_score_codex":0.0099621015,"about_ca_topic_score_gemma":0.010947339,"teacher_disagreement_score":0.0099621015,"about_ca_system_score_codex":0.00043894764,"about_ca_system_score_gemma":0.0004232843,"threshold_uncertainty_score":0.019808233},"labels":[],"label_agreement":null},{"id":"W1947057053","doi":"10.1002/ca.22349","title":"Spinal diffusion tensor imaging: A comprehensive review with emphasis on spinal cord anatomy and clinical applications","year":2014,"lang":"en","type":"review","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Diffusion MRI; Tractography; Medicine; Spinal cord; Magnetic resonance imaging; Neuroscience; Anatomy; Radiology; Psychology","score_opus":0.20652838312261718,"score_gpt":0.5499473226266137,"score_spread":0.34341893950399655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1947057053","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010608163,0.9988607,0.00014039868,0.00023560882,0.000106818035,0.0000043645077,0.000031776537,0.000007022237,0.0005071517],"genre_scores_gemma":[0.0005487088,0.9986492,0.00028958992,0.000099371355,0.00014584874,0.0000049243104,0.000039885148,0.0000016742255,0.00022082566],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997745,0.00003185211,0.000068916335,0.000037695318,0.00007194652,0.0000151176],"domain_scores_gemma":[0.9992524,0.00034911704,0.0001315241,0.000018248827,0.00020267197,0.000046107212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068754866,0.001125861,0.0015039931,0.0054716663,0.0003021052,0.0009531235,0.00081367046,0.000933908,0.0047508106],"category_scores_gemma":[0.0015120439,0.00035706357,0.0007193362,0.00488202,0.0005944292,0.0016435127,0.0006562127,0.0010216997,0.0022760201],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004262865,0.0000395588,0.00042363623,0.030405542,0.00014223244,0.00036579158,0.00008931596,0.00025336264,0.0010416096,0.0014978563,0.030900702,0.9347977],"study_design_scores_gemma":[0.000016297296,0.000099737204,0.0031441555,0.014528365,0.00042834447,0.005669382,0.00013137242,0.0001397723,0.000623963,0.002445504,0.97272056,0.000052458516],"about_ca_topic_score_codex":0.0018306021,"about_ca_topic_score_gemma":0.0029758401,"teacher_disagreement_score":0.0054716663,"about_ca_system_score_codex":0.00052172755,"about_ca_system_score_gemma":0.0018884104,"threshold_uncertainty_score":0.015893042},"labels":[],"label_agreement":null},{"id":"W1947571038","doi":"10.1002/ana.24318","title":"Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy","year":2014,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Magnetic resonance imaging; Diffusion MRI; Neocortex; Epilepsy; Fractional anisotropy; Temporal lobe; Relaxometry; Epilepsy surgery; Pathology; Medicine; Correlation; Radiology; Nuclear medicine; Psychology; Neuroscience; Spin echo; Mathematics","score_opus":0.05706631913948104,"score_gpt":0.3483404934136802,"score_spread":0.2912741742741991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1947571038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987734,0.00021314558,0.0007937019,0.00002343422,0.000001408946,0.0000052407236,0.000041244843,0.0000073329225,0.00014096878],"genre_scores_gemma":[0.9992261,0.000072849645,0.00053397863,0.000006443226,0.0000029317305,0.0000041164467,0.000057196485,0.0000023673192,0.0000939905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999876,0.000040534862,0.000018085488,0.00002756051,0.000027751994,0.000009924008],"domain_scores_gemma":[0.9990349,0.0003443793,0.00041238862,0.00006349185,0.000098377874,0.000046495774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006278079,0.00022948527,0.0001541166,0.00055771606,0.00008764245,0.00020587645,0.00012522223,0.00016044284,0.000977925],"category_scores_gemma":[0.0029877394,0.00011922476,0.00011606269,0.00022339485,0.00032708218,0.0002659053,0.00016260736,0.00010220313,0.00016910235],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006952382,0.00004566794,0.9430898,0.00010416982,0.00014837517,0.00072452833,0.0001916,0.0013054446,0.036666304,0.00011026318,0.00008686939,0.016831754],"study_design_scores_gemma":[0.000022583352,0.0003131352,0.9900949,0.000010227806,0.00006494959,0.0023809262,0.000089288566,0.0028161483,0.0038754384,0.00016737057,0.00015708021,0.000007886902],"about_ca_topic_score_codex":0.0008036489,"about_ca_topic_score_gemma":0.0019288292,"teacher_disagreement_score":0.000977925,"about_ca_system_score_codex":0.0001594699,"about_ca_system_score_gemma":0.0002488004,"threshold_uncertainty_score":0.0033201575},"labels":[],"label_agreement":null},{"id":"W1956119885","doi":"10.1002/hbm.22795","title":"Visualization and segmentation of reciprocal cerebrocerebellar pathways in the healthy and injured brain","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; Pediatric Oncology Group","funders":"Hospital for Sick Children","keywords":"Tractography; Diffusion MRI; White matter; Cerebellum; Neuroscience; Cohort; Psychology; Medicine; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.16246080296942378,"score_gpt":0.39720303049791067,"score_spread":0.2347422275284869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1956119885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868478,0.00040002563,0.011810328,0.000043073014,0.0000023650946,0.000017150966,0.00023248063,0.000054984517,0.0005917312],"genre_scores_gemma":[0.97907,0.00052799156,0.019729791,0.000011368758,0.0000026831333,0.000021369591,0.00022277012,0.00002556822,0.00038851573],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998872,0.000019279145,0.000011080112,0.00003237421,0.000028694463,0.000021273094],"domain_scores_gemma":[0.9997805,0.000045805107,0.00008944392,0.000026443986,0.000030870542,0.000027007212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027233033,0.0001570093,0.00009579508,0.0011303121,0.00014434586,0.00041810854,0.00015118992,0.0002218261,0.0007818729],"category_scores_gemma":[0.0009054651,0.00016558186,0.00013092389,0.0003902938,0.00031148293,0.00035446914,0.00031090737,0.00016553389,0.00011717069],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053269713,0.000066737215,0.356958,0.0003990522,0.00014522175,0.0020009368,0.0030573031,0.010918938,0.5089671,0.0031204824,0.00052364386,0.11331001],"study_design_scores_gemma":[0.00001467133,0.0002299186,0.89296645,0.00012397325,0.00008340485,0.005190928,0.0013342008,0.022825472,0.07053637,0.0026282107,0.0040268474,0.000039505183],"about_ca_topic_score_codex":0.0072698286,"about_ca_topic_score_gemma":0.014795197,"teacher_disagreement_score":0.0072698286,"about_ca_system_score_codex":0.0002811666,"about_ca_system_score_gemma":0.00073370576,"threshold_uncertainty_score":0.01445502},"labels":[],"label_agreement":null},{"id":"W1958816175","doi":"10.1111/jon.12268","title":"Quantitative Mapping of Human Brain Vertical‐Occipital Fasciculus","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fasciculus; Diffusion MRI; Fractional anisotropy; Tractography; Inferior longitudinal fasciculus; Medicine; Uncinate fasciculus; Superior longitudinal fasciculus; Neuroscience; Anatomy; Medial longitudinal fasciculus; Magnetic resonance imaging; Psychology; Radiology; Midbrain; Central nervous system","score_opus":0.19372760595790758,"score_gpt":0.4214888592713708,"score_spread":0.22776125331346322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1958816175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97795427,0.0007448615,0.020083172,0.000028871154,0.000007754273,0.000039161405,0.00044936276,0.000057446123,0.00063501287],"genre_scores_gemma":[0.99325484,0.00014432968,0.0059918803,0.000005342784,0.0000048772304,0.000026729516,0.00026108898,0.000010019583,0.0003009825],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999025,0.000025244,0.00000579766,0.000033401942,0.000021160413,0.00001179681],"domain_scores_gemma":[0.9997545,0.000078956095,0.0000702311,0.000030656425,0.000043571938,0.00002202902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034098688,0.00024024284,0.0001283279,0.00054702675,0.00011938858,0.000253223,0.000117724274,0.00015944814,0.0011819032],"category_scores_gemma":[0.0013202087,0.00008061832,0.00008820185,0.00021419163,0.00022203728,0.00023610475,0.00015161379,0.00008213231,0.00015825988],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028530755,0.00011627826,0.22191174,0.00062092266,0.00027901365,0.0008757616,0.00063420023,0.0068301107,0.5307128,0.001847515,0.0011919913,0.23212661],"study_design_scores_gemma":[0.000087986926,0.00060862803,0.8922478,0.00006812116,0.000087911605,0.006229053,0.00026854582,0.020190546,0.07369235,0.0021915594,0.0042774803,0.00005000642],"about_ca_topic_score_codex":0.003137316,"about_ca_topic_score_gemma":0.0030178146,"teacher_disagreement_score":0.003137316,"about_ca_system_score_codex":0.00023941895,"about_ca_system_score_gemma":0.00021298826,"threshold_uncertainty_score":0.006238103},"labels":[],"label_agreement":null},{"id":"W1963512073","doi":"10.1002/cmr.b.20134","title":"Magnetic resonance imaging with composite (dual) gradients","year":2009,"lang":"en","type":"article","venue":"Concepts in Magnetic Resonance Part B","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Dental and Craniofacial Research; National Institute on Deafness and Other Communication Disorders; National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; National Institutes of Health","keywords":"Magnetic resonance imaging; Dual (grammatical number); Composite number; Nuclear magnetic resonance; Materials science; Functional magnetic resonance imaging; Psychology; Medicine; Physics; Neuroscience; Art; Radiology; Composite material","score_opus":0.026903926246213683,"score_gpt":0.3257950959079198,"score_spread":0.2988911696617061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963512073","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1221152,0.00578827,0.86172265,0.00055709726,0.00020889881,0.00011136341,0.000066848224,0.0010921033,0.008337514],"genre_scores_gemma":[0.46417296,0.0028208066,0.52750754,0.000430499,0.0002426585,0.00012515386,0.00007774656,0.00017626243,0.0044463216],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975175,0.00006688825,0.000012240482,0.000071475195,0.00007039728,0.000027151827],"domain_scores_gemma":[0.9995597,0.00015118584,0.000064786276,0.00006362039,0.000082408274,0.000078151046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059361535,0.0005047512,0.00049301976,0.0005365824,0.00019193647,0.0010531568,0.00051679986,0.0007660646,0.0010212064],"category_scores_gemma":[0.0010965941,0.00034785847,0.00021731513,0.00034142326,0.00059318356,0.0014301547,0.001051684,0.00066968193,0.0007453298],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061648316,0.00008388581,0.0012600542,0.00038239927,0.00005734996,0.00058511354,0.000077353114,0.0043037995,0.8379308,0.009818972,0.0016087547,0.14327511],"study_design_scores_gemma":[0.00019542729,0.0028947843,0.008471808,0.00017163358,0.00025113064,0.012495055,0.000092693714,0.09814541,0.7930277,0.029184368,0.05484527,0.00022481212],"about_ca_topic_score_codex":0.000097086326,"about_ca_topic_score_gemma":0.00028546024,"teacher_disagreement_score":0.0010531568,"about_ca_system_score_codex":0.0001717701,"about_ca_system_score_gemma":0.00021701738,"threshold_uncertainty_score":0.0034162998},"labels":[],"label_agreement":null},{"id":"W1963531852","doi":"10.1016/j.mri.2008.11.009","title":"Alteration of diffusion tensor parameters in postmortem brain","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Alberta Children's Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Autopsy; Postmortem Changes; White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Internal capsule; Anatomy; Brain tissue; Autolysis (biology); Fixation (population genetics); Pathology; Medicine; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Radiology","score_opus":0.028318049218847282,"score_gpt":0.32386317757864297,"score_spread":0.2955451283597957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963531852","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993905,0.0012185634,0.00246335,0.00009561188,0.000060390976,0.000025386118,0.00029791208,0.0000869431,0.001846735],"genre_scores_gemma":[0.99714524,0.0006066363,0.00091147434,0.000031710348,0.000021554082,0.000015751988,0.0001871752,0.000024679846,0.0010558082],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999895,0.00001484218,0.000015233994,0.000029059107,0.000020513287,0.00002532785],"domain_scores_gemma":[0.9995005,0.00009492608,0.00012253447,0.00012258753,0.00010859296,0.000050938797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036010362,0.00044660945,0.00029981838,0.0012547235,0.0004845751,0.0003159871,0.0003247747,0.00046531067,0.0024099697],"category_scores_gemma":[0.0017460661,0.0003720242,0.00017163226,0.000371782,0.00091103424,0.00044984557,0.00039049867,0.00062666315,0.00046791445],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006598858,0.00026116657,0.04028379,0.00038781625,0.00017296364,0.023978807,0.0009481544,0.00033672588,0.90194124,0.00090678164,0.00073801266,0.023445787],"study_design_scores_gemma":[0.00011864331,0.0015774666,0.28971553,0.000069506226,0.0003546681,0.057016037,0.0014053042,0.0017725449,0.64306927,0.0017533416,0.0031026765,0.000044955366],"about_ca_topic_score_codex":0.00088707864,"about_ca_topic_score_gemma":0.0007842686,"teacher_disagreement_score":0.0024099697,"about_ca_system_score_codex":0.00016581065,"about_ca_system_score_gemma":0.00021103412,"threshold_uncertainty_score":0.008062124},"labels":[],"label_agreement":null},{"id":"W1963887794","doi":"10.1371/journal.pone.0075061","title":"A Connectome-Based Comparison of Diffusion MRI Schemes","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"Centre Hospitalier Universitaire Vaudois; Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; École Polytechnique Fédérale de Lausanne","keywords":"Diffusion MRI; Diffusion imaging; Computer science; Connectome; Fractional anisotropy; Artificial intelligence; Human Connectome Project; Pattern recognition (psychology); Magnetic resonance imaging; Neuroscience; Medicine; Biology; Functional connectivity","score_opus":0.14972148776896047,"score_gpt":0.35274573444311697,"score_spread":0.2030242466741565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963887794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8083074,0.0015458832,0.17539975,0.00042650467,0.00011995679,0.00031573419,0.0038060707,0.0011945101,0.008884087],"genre_scores_gemma":[0.93797547,0.00041169606,0.05666534,0.00003237919,0.000023959197,0.0001501086,0.003670368,0.00016912997,0.0009015526],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987576,0.00048390782,0.00010377929,0.00026933345,0.00030227442,0.00008303459],"domain_scores_gemma":[0.99260664,0.0039801463,0.0006647247,0.0011998524,0.001340991,0.00020754685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035969422,0.0006286393,0.00039394214,0.0066379234,0.000435196,0.001475289,0.0005699527,0.000987209,0.0038005565],"category_scores_gemma":[0.019379472,0.00023637347,0.0008046236,0.0025891662,0.000626952,0.0021409632,0.0012374665,0.0005262212,0.00073275506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003377637,0.00043004457,0.10542494,0.0014125538,0.0014450232,0.0006273549,0.0015924387,0.3629272,0.06842987,0.051815156,0.008121382,0.39439636],"study_design_scores_gemma":[0.00012841712,0.00079657906,0.12398328,0.00019845636,0.0003603978,0.001293301,0.00063985074,0.8125177,0.023013411,0.030215131,0.006679194,0.00017428504],"about_ca_topic_score_codex":0.0018444186,"about_ca_topic_score_gemma":0.001632182,"teacher_disagreement_score":0.0066379234,"about_ca_system_score_codex":0.00061293156,"about_ca_system_score_gemma":0.0004019674,"threshold_uncertainty_score":0.019022703},"labels":[],"label_agreement":null},{"id":"W1964048159","doi":"10.1159/000097371","title":"Gross Anatomy of the Corpus Callosum in Alzheimer’s Disease: Regions of Degeneration and Their Neuropsychological Correlates","year":2006,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; Neuropsychology; Psychology; Degenerative disease; Dementia; Alzheimer's disease; Neuroscience; Audiology; Central nervous system disease; Anatomy; Disease; Medicine; Pathology; Cognition","score_opus":0.02145171469897885,"score_gpt":0.3069777132471275,"score_spread":0.2855259985481487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964048159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99909353,0.00025305775,0.0002481497,0.000011644531,0.0000017404866,0.000007751775,0.0000631631,0.000008868675,0.00031209807],"genre_scores_gemma":[0.99927205,0.00008378023,0.0004943396,0.0000044063836,0.0000037715322,0.0000050916296,0.000066339235,0.0000037243874,0.00006641842],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990666,0.000018429992,0.000011822426,0.000022968103,0.000027846618,0.000012189407],"domain_scores_gemma":[0.9991009,0.00019206613,0.0004220737,0.0000848568,0.0001056457,0.00009448341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029258456,0.0003214862,0.00015804332,0.0016472829,0.00022753574,0.00038712224,0.00020453149,0.0002604587,0.0010467676],"category_scores_gemma":[0.0014809269,0.00013725972,0.00012636861,0.00054985116,0.00075035327,0.00028456651,0.00032215443,0.00019143916,0.00011747455],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019198677,0.00009977422,0.87610286,0.00023473869,0.0002921774,0.0016568251,0.0008644902,0.0013116206,0.07646094,0.00029842425,0.00023490442,0.040523373],"study_design_scores_gemma":[0.0000048361317,0.00006362327,0.9964888,0.0000037351308,0.000020462721,0.0016649407,0.00006764335,0.00014567097,0.0013211884,0.0001241826,0.00009058632,0.000004393281],"about_ca_topic_score_codex":0.0016163536,"about_ca_topic_score_gemma":0.002632449,"teacher_disagreement_score":0.0016472829,"about_ca_system_score_codex":0.00029058248,"about_ca_system_score_gemma":0.00019907585,"threshold_uncertainty_score":0.0035018325},"labels":[],"label_agreement":null},{"id":"W1964447312","doi":"10.1191/1352458504ms1036oa","title":"Cervical cord atrophy assessment on magnetic resonance imaging: PRO MiSe trial","year":2004,"lang":"en","type":"review","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Medicine; Magnetic resonance imaging; Multiple sclerosis; Atrophy; Spinal cord; Clinical trial; Cord; Nuclear medicine; Radiology; Surgery; Pathology","score_opus":0.26893492290091914,"score_gpt":0.4225708523278115,"score_spread":0.15363592942689236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964447312","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046300003,0.9933518,0.000072890536,0.00056938274,0.00019046059,0.00005388509,0.0000897795,0.000007146813,0.0010345537],"genre_scores_gemma":[0.029764868,0.96660733,0.00056208635,0.0011378385,0.0003979792,0.00020744011,0.00025354986,0.0000027295587,0.0010662562],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9997719,0.00010494938,0.000021539729,0.000026033587,0.00005669299,0.000018815812],"domain_scores_gemma":[0.9996568,0.00018568615,0.00006106444,0.000008582095,0.00005467781,0.000033237728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009416941,0.00059174193,0.00226492,0.00036371662,0.00013868083,0.00037638735,0.0005533295,0.0008155867,0.0018757293],"category_scores_gemma":[0.0011153442,0.00009762906,0.00059714064,0.00053649314,0.00016063187,0.00032470227,0.00015354205,0.0010023143,0.0003663132],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0126815485,0.00038902523,0.0010658732,0.029813979,0.0016896181,0.00024093915,0.00003602362,0.00031890196,0.0016693515,0.00057081366,0.02857219,0.92295176],"study_design_scores_gemma":[0.11008993,0.034785524,0.07956801,0.05024984,0.020663531,0.009267392,0.0003449536,0.0013895499,0.005290807,0.00461554,0.68357193,0.00016300834],"about_ca_topic_score_codex":0.00058721885,"about_ca_topic_score_gemma":0.002419698,"teacher_disagreement_score":0.00226492,"about_ca_system_score_codex":0.00030931734,"about_ca_system_score_gemma":0.00072347664,"threshold_uncertainty_score":0.0062749386},"labels":[],"label_agreement":null},{"id":"W1964469261","doi":"10.1002/hbm.20995","title":"Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Centers for Disease Control and Prevention","keywords":"Diffusion MRI; Fractional anisotropy; Linear discriminant analysis; Psychology; Magnetic resonance imaging; Artificial intelligence; Medicine; Audiology; Nuclear medicine; Pattern recognition (psychology); Radiology; Computer science; Cognitive psychology","score_opus":0.02383509416645939,"score_gpt":0.29040974318599344,"score_spread":0.26657464901953404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964469261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993068,0.000114240574,0.00019491388,0.000037378057,0.000008299817,0.000011725241,0.000072568866,0.000007167168,0.0002469805],"genre_scores_gemma":[0.9991473,0.00008069662,0.00037565763,0.000028885443,0.00001099791,0.00000727045,0.00023809161,0.000002798916,0.000108253436],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996718,0.00008912385,0.00006144519,0.00007104272,0.00005482468,0.000051723582],"domain_scores_gemma":[0.99878174,0.00039310104,0.00040033777,0.00010668569,0.00016514918,0.00015309079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008220479,0.0004982264,0.00043576118,0.00084486377,0.00030091256,0.00053275534,0.00012879545,0.00045491697,0.0011319434],"category_scores_gemma":[0.004185494,0.00020156034,0.00021551253,0.00019303327,0.00037416784,0.0004848241,0.00030046134,0.0002029407,0.0005369119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002204916,0.00024545722,0.93703717,0.000076200035,0.00012429147,0.00081153633,0.00070521655,0.0003425957,0.026281452,0.00015178457,0.00070569623,0.031313643],"study_design_scores_gemma":[0.000114031995,0.0010183605,0.98998123,0.000030970918,0.00007501215,0.0021705849,0.0006312038,0.001611153,0.0032120799,0.00040896662,0.0007191709,0.000027179729],"about_ca_topic_score_codex":0.0014299804,"about_ca_topic_score_gemma":0.0024977468,"teacher_disagreement_score":0.0014299804,"about_ca_system_score_codex":0.00017127357,"about_ca_system_score_gemma":0.00025652073,"threshold_uncertainty_score":0.004347503},"labels":[],"label_agreement":null},{"id":"W1964752900","doi":"10.1109/isbi.2014.6867974","title":"DTI-DeformIt: Generating ground-truth validation data for diffusion tensor image analysis tasks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Artificial intelligence; Ground truth; Image (mathematics); Noise (video); Computer vision; Eigenvalues and eigenvectors; Diffusion; Pattern recognition (psychology); Mathematics","score_opus":0.11847501302179933,"score_gpt":0.3941550786239827,"score_spread":0.2756800656021834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964752900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0295876,0.00032071554,0.9480995,0.00036610957,0.0002655508,0.00059827755,0.005927133,0.012829582,0.0020055408],"genre_scores_gemma":[0.14200354,0.00017934662,0.82804865,0.0002728231,0.00007205319,0.0012677778,0.02433275,0.002624898,0.0011981417],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966587,0.001389614,0.00023956524,0.0008211392,0.00071318954,0.00017784345],"domain_scores_gemma":[0.987386,0.0043473057,0.0010083964,0.0050150934,0.0019057506,0.00033750563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007827264,0.0025299499,0.0011692613,0.0026338738,0.0011252112,0.0020565612,0.003975575,0.0030027907,0.004728376],"category_scores_gemma":[0.028594319,0.0011530673,0.001523853,0.0013532089,0.0015386356,0.0018385586,0.0031182913,0.0024120787,0.0027149364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010041677,0.0010411949,0.009295408,0.0012393473,0.0004763452,0.0007166976,0.0005513993,0.3913823,0.057427194,0.021459954,0.070522346,0.4448836],"study_design_scores_gemma":[0.00013422016,0.0003413731,0.0017739116,0.00012502511,0.000041352872,0.0005066947,0.000080118545,0.9095209,0.05454915,0.016510054,0.016318517,0.000098646036],"about_ca_topic_score_codex":0.0029919797,"about_ca_topic_score_gemma":0.0047884267,"teacher_disagreement_score":0.007827264,"about_ca_system_score_codex":0.000967549,"about_ca_system_score_gemma":0.0015487825,"threshold_uncertainty_score":0.04139507},"labels":[],"label_agreement":null},{"id":"W1965000453","doi":"10.1002/mrm.21977","title":"Aldehyde fixative solutions alter the water relaxation and diffusion properties of nervous tissue","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":309,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Fixative; Formaldehyde; Glutaraldehyde; Nervous tissue; Chemistry; Fixation (population genetics); Brain tissue; Paraformaldehyde; Central nervous system; Biophysics; Chromatography; Anatomy; Biochemistry; Biology; Neuroscience","score_opus":0.05351128851339552,"score_gpt":0.31812302749269455,"score_spread":0.264611738979299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965000453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96294904,0.012836227,0.020223595,0.00028943797,0.0001744061,0.00011044622,0.00021610055,0.00015479606,0.003046023],"genre_scores_gemma":[0.9631684,0.011328836,0.021537714,0.00021942261,0.00006582948,0.0001397755,0.0004739587,0.00009866788,0.002967525],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999749,0.000047890626,0.000022019343,0.00007110372,0.000044842287,0.00006508021],"domain_scores_gemma":[0.9995227,0.00015539747,0.00016891515,0.000039124694,0.00006484142,0.000048967893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053300196,0.0011583925,0.00031529047,0.0004487729,0.00030471408,0.00044545444,0.00045066213,0.00054476026,0.0014519113],"category_scores_gemma":[0.0008096514,0.00037051374,0.0003879816,0.00017569381,0.00059723685,0.0006070756,0.00038332684,0.0005442848,0.0002856135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020557112,0.000018510984,0.00031755088,0.00013276543,0.00003298996,0.00010760114,0.0000356254,0.000105896484,0.99709845,0.00011834738,0.000028094504,0.0017985533],"study_design_scores_gemma":[0.000016242699,0.0011409322,0.006652581,0.000033767636,0.00011777803,0.00043881734,0.00006967704,0.0005903905,0.9887394,0.00016172812,0.0020191525,0.000019585317],"about_ca_topic_score_codex":0.0014979139,"about_ca_topic_score_gemma":0.0037027432,"teacher_disagreement_score":0.0014979139,"about_ca_system_score_codex":0.00036642252,"about_ca_system_score_gemma":0.00030583635,"threshold_uncertainty_score":0.004857123},"labels":[],"label_agreement":null},{"id":"W1965033190","doi":"10.3171/jns-07/09/0509","title":"Diffusion tensor imaging analysis of long association bundles in the presence of an arteriovenous malformation","year":2007,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Hôpital Notre-Dame; Université de Montréal","funders":"","keywords":"Arcuate fasciculus; Medicine; Diffusion MRI; Anatomy; Inferior longitudinal fasciculus; Fasciculus; White matter; Superior longitudinal fasciculus; Magnetic resonance imaging; Radiology; Fractional anisotropy","score_opus":0.035055606811048044,"score_gpt":0.33693906236866666,"score_spread":0.30188345555761864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965033190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99909186,0.00007583891,0.0006247972,0.000013177845,9.991364e-7,0.0000039294027,0.000019514377,0.0000046087252,0.00016528965],"genre_scores_gemma":[0.99898773,0.00004408574,0.00088513404,0.000002218937,0.0000025613472,0.0000023168018,0.000029277975,0.0000014779955,0.000045149325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987936,0.000027974284,0.000020689356,0.000023743323,0.000024873654,0.00002331306],"domain_scores_gemma":[0.9992212,0.00014973298,0.00036125953,0.000052725496,0.00008939755,0.00012562286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043108358,0.00025246988,0.0001236247,0.0010972944,0.00020422612,0.00026036633,0.00014066014,0.00018272919,0.00090062775],"category_scores_gemma":[0.0015087324,0.000107581465,0.00011602041,0.00041872982,0.00041364483,0.00038475232,0.00027132969,0.00017195314,0.000112337635],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007791599,0.000073170486,0.85147464,0.00009613696,0.00015407232,0.009391765,0.0005769747,0.0004484074,0.11444415,0.00024385394,0.00013551771,0.022182181],"study_design_scores_gemma":[0.000026963602,0.00038172049,0.94118154,0.000018130424,0.00010708275,0.036062468,0.00041398042,0.0033263278,0.017586106,0.00040661843,0.0004734469,0.00001558273],"about_ca_topic_score_codex":0.00078338094,"about_ca_topic_score_gemma":0.0010192537,"teacher_disagreement_score":0.0010972944,"about_ca_system_score_codex":0.00021593254,"about_ca_system_score_gemma":0.00017415732,"threshold_uncertainty_score":0.0030128956},"labels":[],"label_agreement":null},{"id":"W1965146525","doi":"10.1016/j.neuroimage.2008.03.024","title":"FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":179,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; National Institutes of Health","keywords":"Putamen; Artificial intelligence; Segmentation; Thalamus; Computer science; Pattern recognition (psychology); Caudate nucleus; Hippocampus; Basal ganglia; Metric (unit); Neuroscience; Psychology; Central nervous system","score_opus":0.13714103280498316,"score_gpt":0.3705583009984875,"score_spread":0.23341726819350436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965146525","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0512942,0.00016546842,0.9435411,0.00018110397,0.000049461087,0.000069376096,0.00017490253,0.0031116356,0.0014127472],"genre_scores_gemma":[0.41571316,0.00015855231,0.57893556,0.00009338801,0.00003759786,0.00011828046,0.00041973477,0.0011853053,0.0033383863],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997218,0.000056960573,0.000013989414,0.00004796534,0.00012865702,0.0000306121],"domain_scores_gemma":[0.99944574,0.00023910352,0.00005801285,0.00012180076,0.00010396534,0.000031268733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077323016,0.00070307904,0.0009798538,0.00077037467,0.0006710962,0.0010868085,0.0012129898,0.0012115568,0.0020309784],"category_scores_gemma":[0.002417902,0.0007244905,0.00094618736,0.0008316371,0.00044596175,0.0011179859,0.0011615116,0.0010042298,0.0008096856],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005803462,0.00016528749,0.0021349776,0.0003381632,0.00024616046,0.00045980673,0.0005803966,0.3811902,0.13008705,0.022774559,0.0067072343,0.45473582],"study_design_scores_gemma":[0.000018297498,0.00004569345,0.0010103321,0.000009441992,0.000019475821,0.0002014166,0.000023778834,0.9534922,0.03610723,0.0069604134,0.0020752447,0.000036509995],"about_ca_topic_score_codex":0.00651527,"about_ca_topic_score_gemma":0.013136773,"teacher_disagreement_score":0.00651527,"about_ca_system_score_codex":0.0006849389,"about_ca_system_score_gemma":0.0020644206,"threshold_uncertainty_score":0.012954712},"labels":[],"label_agreement":null},{"id":"W1965400726","doi":"10.1016/j.neuroimage.2006.04.187","title":"Diffusion tensor imaging of time-dependent axonal and myelin degradation after corpus callosotomy in epilepsy patients","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":285,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; National Institutes of Health; University of Alberta","keywords":"White matter; Diffusion MRI; Corpus callosum; Fractional anisotropy; Myelin; Neuroscience; Tractography; Magnetic resonance imaging; Psychology; Medicine; Radiology; Central nervous system","score_opus":0.013631079485931348,"score_gpt":0.2664515432814151,"score_spread":0.2528204637954838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965400726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991291,0.00013541969,0.000033032156,0.000058923873,0.000004944681,0.0000058448295,0.00005185148,0.0000022159813,0.00057867216],"genre_scores_gemma":[0.9996031,0.00008706469,0.000021434238,0.000023346305,0.0000093919,0.0000038084618,0.000091367096,0.0000018014811,0.00015866406],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998988,0.0000124175795,0.000016124854,0.000014884293,0.000017071552,0.000040779207],"domain_scores_gemma":[0.9994659,0.00014650634,0.0001665861,0.00003520584,0.000061952385,0.00012386583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027365878,0.00032586674,0.0003962079,0.00065829046,0.0004980642,0.00032794898,0.00030092118,0.00064141885,0.0011889668],"category_scores_gemma":[0.001938194,0.00020188463,0.00030296302,0.00056875154,0.00051624916,0.00064802234,0.00019059207,0.0006075653,0.00019635781],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018628921,0.0009986929,0.83553505,0.0001715394,0.0003796459,0.08350503,0.0017581421,0.0012183464,0.032968022,0.00031822606,0.0009560603,0.023562271],"study_design_scores_gemma":[0.00012036403,0.0009292709,0.9732776,0.000008979972,0.0001163252,0.022094037,0.00041862897,0.00041173663,0.0021404417,0.00014926269,0.00030879764,0.000024527988],"about_ca_topic_score_codex":0.010017817,"about_ca_topic_score_gemma":0.010369278,"teacher_disagreement_score":0.010017817,"about_ca_system_score_codex":0.0005749798,"about_ca_system_score_gemma":0.00048544057,"threshold_uncertainty_score":0.019918978},"labels":[],"label_agreement":null},{"id":"W1965597062","doi":"10.1007/s00406-012-0383-y","title":"The effect of aerobic exercise on cortical architecture in patients with chronic schizophrenia: a randomized controlled MRI study","year":2012,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Aerobic exercise; Neuroplasticity; Schizophrenia (object-oriented programming); Medicine; Physical medicine and rehabilitation; Psychology; Physical therapy; Neuroscience; Psychiatry","score_opus":0.013416767832689924,"score_gpt":0.3244817430771266,"score_spread":0.3110649752444367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965597062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99689746,0.0016128966,0.00017547794,0.00018783961,0.00015649346,0.00045303832,0.00017924429,0.000021699723,0.00031593014],"genre_scores_gemma":[0.9967026,0.0010350295,0.00034303658,0.00031084768,0.00026890234,0.0005881955,0.00021360765,0.000006701209,0.0005310786],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9994759,0.00019299416,0.000049565337,0.00012889515,0.000040772073,0.0001119302],"domain_scores_gemma":[0.9991333,0.00020093085,0.00024500448,0.000111031666,0.000061311075,0.00024847026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088554964,0.001701205,0.0030379377,0.00042830355,0.0006850649,0.000784164,0.0007565427,0.0018979975,0.0041246517],"category_scores_gemma":[0.0014732218,0.0009791665,0.001647722,0.0005102993,0.0015101079,0.0008283218,0.00051152555,0.002154566,0.0005062135],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.9818796,0.0068085454,0.0016669106,0.00030914583,0.00126862,0.000031241147,0.00003540579,0.00012791522,0.0023015698,0.000029538072,0.0001364211,0.0054052086],"study_design_scores_gemma":[0.85910845,0.11565727,0.020908335,0.00004788836,0.0028845519,0.000034384146,0.00007352457,0.00034306632,0.00047766443,0.00014778096,0.00027487686,0.000042093718],"about_ca_topic_score_codex":0.0032374645,"about_ca_topic_score_gemma":0.0043855105,"teacher_disagreement_score":0.0041246517,"about_ca_system_score_codex":0.0007130057,"about_ca_system_score_gemma":0.0007782184,"threshold_uncertainty_score":0.013798296},"labels":[],"label_agreement":null},{"id":"W1965738837","doi":"10.1016/j.nicl.2014.08.003","title":"Cellular correlates of longitudinal diffusion tensor imaging of axonal degeneration following hypoxic–ischemic cerebral infarction in neonatal rats","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Research Council Canada; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Cerebral peduncle; Diffusion MRI; Fractional anisotropy; Wallerian degeneration; Pathology; Cerebral cortex; Neuroscience; Medicine; Corpus callosum; Ischemia; Anatomy; Internal capsule; Biology; White matter; Cardiology; Magnetic resonance imaging","score_opus":0.060909995904924706,"score_gpt":0.3620996991850905,"score_spread":0.3011897032801658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965738837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979157,0.00080781564,0.0006035009,0.000035670415,0.0000120950335,0.000013920396,0.00025030857,0.000027937936,0.00033310134],"genre_scores_gemma":[0.9943884,0.0015705877,0.0012496121,0.00003403961,0.000010393562,0.0000900015,0.00059612986,0.000015537249,0.0020452281],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987316,0.0000095605965,0.000012428184,0.000036326903,0.00002809951,0.00004043606],"domain_scores_gemma":[0.9995548,0.000022094508,0.00023520818,0.00003155628,0.000058048845,0.000098300836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021606497,0.00042920254,0.0003324917,0.00066513533,0.00014459838,0.00019991375,0.00018813436,0.00017924933,0.0007711327],"category_scores_gemma":[0.0002458444,0.00020183536,0.0002016707,0.00018392921,0.00045957306,0.00028741418,0.00023219528,0.00065109326,0.00017078155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006688873,0.00007807897,0.002386451,0.000057390647,0.00001529884,0.00019926605,0.00009990949,0.000079155216,0.99451494,0.00007771517,0.000031487514,0.0017914169],"study_design_scores_gemma":[0.0000316845,0.0018356539,0.18791714,0.000024996374,0.000087810695,0.00064347463,0.00033153602,0.00066106545,0.807649,0.00016246298,0.0006275066,0.000027611737],"about_ca_topic_score_codex":0.002396366,"about_ca_topic_score_gemma":0.0032259938,"teacher_disagreement_score":0.002396366,"about_ca_system_score_codex":0.0004373907,"about_ca_system_score_gemma":0.00036591236,"threshold_uncertainty_score":0.0047647953},"labels":[],"label_agreement":null},{"id":"W1966454855","doi":"10.3389/fneur.2014.00240","title":"Subjectâ€“Motion Correction in HARDI Acquisitions: Choices and Consequences","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Children's Hospital of Philadelphia; National Institute on Drug Abuse; University of Alberta; University of Washington; National Institutes of Health","keywords":"Computer science; Outlier; Motion (physics); Artificial intelligence; Interpolation (computer graphics); Noise (video); Orientation (vector space); Computer vision; Mathematics","score_opus":0.023021209426620136,"score_gpt":0.3007784304700382,"score_spread":0.2777572210434181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966454855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7346349,0.0069812397,0.24569507,0.0018244274,0.0004184663,0.0021369674,0.0013177928,0.0008400436,0.006151224],"genre_scores_gemma":[0.7788416,0.002298057,0.21140324,0.0011901624,0.00019144878,0.0023501005,0.0015491432,0.00082875346,0.0013473296],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.93379194,0.03956954,0.0072015324,0.0062209163,0.012402631,0.000813424],"domain_scores_gemma":[0.8876612,0.080529615,0.011826459,0.012199115,0.006727662,0.0010559589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07001045,0.0016877948,0.00094869133,0.001248886,0.001314873,0.0027555788,0.0014519279,0.002254334,0.0016388445],"category_scores_gemma":[0.14814502,0.00068300654,0.00089915254,0.0013623046,0.0038649035,0.0024492806,0.0026235324,0.0013631177,0.00080287654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.026720064,0.0021558001,0.14019446,0.0060242857,0.0033811086,0.0015057367,0.00385965,0.049044766,0.12592088,0.02589542,0.007346673,0.6079511],"study_design_scores_gemma":[0.0033386406,0.025054917,0.2606336,0.004774712,0.0038607547,0.0064610234,0.0030602543,0.14007959,0.3696896,0.1163949,0.064932264,0.0017197556],"about_ca_topic_score_codex":0.00065233913,"about_ca_topic_score_gemma":0.0010477423,"teacher_disagreement_score":0.07001045,"about_ca_system_score_codex":0.0007365187,"about_ca_system_score_gemma":0.000766689,"threshold_uncertainty_score":0.3702551},"labels":[],"label_agreement":null},{"id":"W1966699768","doi":"10.1016/j.neuroimage.2010.10.028","title":"Robust clustering of massive tractography datasets","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Cluster analysis; Tractography; Computer science; Fiber; Voxel; Preprocessor; Diffusion MRI; Fiber tract; Artificial intelligence; Fiber bundle; Pattern recognition (psychology); Segmentation; Inference; Data mining","score_opus":0.07886799074879142,"score_gpt":0.34430207222581993,"score_spread":0.2654340814770285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966699768","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013665126,0.00034321082,0.98212725,0.00026660546,0.00006600735,0.0000726225,0.0006712587,0.0024209684,0.00036703097],"genre_scores_gemma":[0.23064008,0.00057940796,0.7555699,0.00016174486,0.0002624462,0.000395435,0.008082941,0.001352323,0.002955771],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968995,0.0010536839,0.00022128316,0.0009406463,0.0006258348,0.00025913044],"domain_scores_gemma":[0.9900759,0.003325802,0.0011214487,0.0036649788,0.0014487968,0.00036304942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036266118,0.0021047597,0.0025345725,0.0050337007,0.0016491251,0.0029421512,0.0029880763,0.0023969167,0.0014654924],"category_scores_gemma":[0.01890765,0.0017238139,0.0035154752,0.0052491045,0.0015919002,0.0020621342,0.0038562666,0.0030066862,0.0017839695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005358588,0.00020346412,0.004126102,0.0005082116,0.0010150017,0.00035444082,0.00044014773,0.6069966,0.02007912,0.02596868,0.020088132,0.31968424],"study_design_scores_gemma":[0.000028397246,0.000047630194,0.0017724219,0.000032702308,0.00005960382,0.00012729471,0.00005002968,0.95055455,0.0033848938,0.040848453,0.00305696,0.000037021102],"about_ca_topic_score_codex":0.015336352,"about_ca_topic_score_gemma":0.022983296,"teacher_disagreement_score":0.015336352,"about_ca_system_score_codex":0.0017591672,"about_ca_system_score_gemma":0.0031383187,"threshold_uncertainty_score":0.030494213},"labels":[],"label_agreement":null},{"id":"W1966831294","doi":"10.1097/wnr.0b013e32834dc301","title":"White matter integrity and math performance in pediatric multiple sclerosis","year":2011,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Hospital for Sick Children; University of Toronto; York University","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Multiple sclerosis; Psychology; Cognition; Neuroscience; Audiology; Developmental psychology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.15051486782692222,"score_gpt":0.30392088421986124,"score_spread":0.15340601639293902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966831294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997987,0.000074206095,0.000017740655,0.00001270534,6.316971e-7,8.2223374e-7,0.0000307526,0.0000027597239,0.000061748186],"genre_scores_gemma":[0.99961406,0.0001353968,0.00007897896,0.0000061397377,0.0000035447667,0.0000022487473,0.000091176684,0.0000019893632,0.000066536646],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998097,0.00003135664,0.000024670906,0.000045990335,0.0000559007,0.00003237318],"domain_scores_gemma":[0.9988148,0.0001166288,0.0008500294,0.000034691966,0.00008579329,0.0000979549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031905816,0.00036576294,0.0002687228,0.0010430008,0.00026183933,0.00036266993,0.0001590999,0.00030549246,0.00081924483],"category_scores_gemma":[0.001632527,0.00025947223,0.00018576591,0.0005347792,0.00042234638,0.00036204432,0.00030350738,0.00031350795,0.00014883833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011437699,0.000046099445,0.9935409,0.000016749027,0.000031048294,0.00056533393,0.00022295922,0.000086789245,0.0023438921,0.000023831333,0.00005649558,0.0029515831],"study_design_scores_gemma":[0.0000017710929,0.00005891183,0.99834394,0.000003537303,0.000011890358,0.0010381108,0.0000682275,0.00007824097,0.0003409734,0.000012059258,0.000041075542,0.0000013296133],"about_ca_topic_score_codex":0.003721917,"about_ca_topic_score_gemma":0.004325035,"teacher_disagreement_score":0.003721917,"about_ca_system_score_codex":0.0002597138,"about_ca_system_score_gemma":0.00026178567,"threshold_uncertainty_score":0.0074005127},"labels":[],"label_agreement":null},{"id":"W1967337284","doi":"10.1006/nimg.2000.0652","title":"Measurement of Cortical Thickness Using an Automated 3-D Algorithm: A Validation Study","year":2001,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":253,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Computer science; Cortex (anatomy); Grey matter; Cerebral cortex; Algorithm; Artificial intelligence; White matter; Pattern recognition (psychology); Medicine; Magnetic resonance imaging; Neuroscience; Psychology; Radiology","score_opus":0.18357196677323348,"score_gpt":0.42272643995512665,"score_spread":0.23915447318189317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967337284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92967325,0.00040064403,0.06727112,0.000060113452,0.000053709784,0.00040227346,0.0006065468,0.00050019193,0.0010320942],"genre_scores_gemma":[0.9538384,0.00014885937,0.04418064,0.00007131243,0.000018591858,0.0002025992,0.00075682654,0.0001910401,0.00059178105],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9950955,0.0025291373,0.00050547515,0.00073685736,0.0009862715,0.00014689173],"domain_scores_gemma":[0.967404,0.014134082,0.0017126412,0.007430391,0.008998516,0.00032032086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012098636,0.0011170635,0.00083343644,0.0018110918,0.0008117962,0.0008464847,0.0018160007,0.0019092044,0.0012666362],"category_scores_gemma":[0.021909319,0.00071385416,0.0010084843,0.0009888139,0.0014427436,0.00085793703,0.0010064839,0.00074783945,0.0007466908],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016735394,0.005102946,0.29503128,0.0012219606,0.0028480368,0.0012719533,0.0036055918,0.05367814,0.23104519,0.0016396182,0.0028184208,0.38500148],"study_design_scores_gemma":[0.0020476154,0.011709795,0.52220595,0.0001943445,0.0018790691,0.008589254,0.00084181834,0.30013984,0.14591625,0.0013370529,0.0047590435,0.00037992714],"about_ca_topic_score_codex":0.0056980997,"about_ca_topic_score_gemma":0.005164751,"teacher_disagreement_score":0.012098636,"about_ca_system_score_codex":0.0007255742,"about_ca_system_score_gemma":0.00088227505,"threshold_uncertainty_score":0.06398451},"labels":[],"label_agreement":null},{"id":"W1967998939","doi":"10.1016/j.neuroimage.2013.04.018","title":"Surface fluid registration of conformal representation: Application to detect disease burden and genetic influence on hippocampus","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; U.S. National Library of Medicine; Takeda Pharmaceutical Company; National Institute of Neurological Disorders and Stroke; Genentech; National Institutes of Health; Servier; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; National Institute on Aging; Abbott Laboratories; Pfizer; BioClinica; Dana Foundation; Bayer HealthCare; National Institute of Mental Health; Novartis Pharmaceuticals Corporation; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Amorfix Life Sciences; Eli Lilly and Company; Roche","keywords":"Conformal map; Artificial intelligence; Computer vision; Surface (topology); Mean curvature; Conformal geometry; Computer science; Smoothing; Image registration; Feature (linguistics); Pattern recognition (psychology); Mathematics; Algorithm; Curvature; Geometry; Image (mathematics); Conformal field theory","score_opus":0.029985208639051502,"score_gpt":0.3289520843861529,"score_spread":0.2989668757471014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967998939","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.078747876,0.00035166653,0.91640395,0.00031626815,0.00009220212,0.00011783724,0.00029230153,0.0024438798,0.0012339542],"genre_scores_gemma":[0.58402145,0.00060481904,0.4116888,0.00012725493,0.00008892642,0.00015327011,0.0003317126,0.00093944685,0.0020443434],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997707,0.00007955707,0.0000146883385,0.000043906268,0.0000683602,0.00002282683],"domain_scores_gemma":[0.99927086,0.00037020596,0.00007668487,0.00012584878,0.000122283,0.000033988228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008544416,0.00054134504,0.0007576452,0.001373989,0.00040945268,0.0015703831,0.0005458273,0.0009337132,0.0018911634],"category_scores_gemma":[0.0060905614,0.00036035586,0.0009567382,0.0016552324,0.00039283023,0.00063729356,0.0010908066,0.00085682195,0.00049111433],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009085458,0.00017419922,0.008867126,0.00041988262,0.00029116,0.0005905114,0.0008084181,0.15706281,0.08209868,0.017999563,0.0069186054,0.7238605],"study_design_scores_gemma":[0.000085915606,0.00012087581,0.0042462475,0.000024941779,0.00008343513,0.00059790607,0.00013452701,0.95263946,0.020428268,0.016895697,0.00467906,0.000063584666],"about_ca_topic_score_codex":0.00442301,"about_ca_topic_score_gemma":0.0033591606,"teacher_disagreement_score":0.00442301,"about_ca_system_score_codex":0.00038228644,"about_ca_system_score_gemma":0.0010866248,"threshold_uncertainty_score":0.008794546},"labels":[],"label_agreement":null},{"id":"W1968301261","doi":"10.1016/j.media.2013.08.006","title":"Denoising and fast diffusion imaging with physically constrained sparse dictionary learning","year":2013,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Artificial intelligence; Computer science; Noise reduction; Dictionary learning; Diffusion MRI; Pattern recognition (psychology); Gaussian; Diffusion; Sparse approximation; Computer vision; Physics","score_opus":0.012633093816359044,"score_gpt":0.29270872219528005,"score_spread":0.280075628378921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968301261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027751988,0.00031601632,0.99588925,0.00023460099,0.000051858362,0.000012649673,0.000032179698,0.00006444523,0.0006238284],"genre_scores_gemma":[0.10435398,0.0015389986,0.88753885,0.00019344885,0.00019424137,0.000079756726,0.00022541915,0.00013316065,0.005742077],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965966,0.00012290101,0.00002161672,0.00006081367,0.00011603067,0.000019017109],"domain_scores_gemma":[0.99890804,0.00060707587,0.0001070003,0.00017840622,0.00016271048,0.00003675793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009868573,0.0006327719,0.00080016983,0.0006943118,0.00025689768,0.00097282144,0.00078984903,0.0014478017,0.0016832302],"category_scores_gemma":[0.0045020473,0.0006122026,0.0006671866,0.00094909954,0.0009772754,0.0017141005,0.0013301242,0.0017270378,0.0005331582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029493787,0.000101404046,0.00071971514,0.00058444636,0.00018714943,0.00022987173,0.00024343714,0.3382022,0.045933425,0.2448675,0.0073140324,0.3613219],"study_design_scores_gemma":[0.000017198065,0.00002965057,0.00016179038,0.000018582743,0.00001596162,0.00015420004,0.000018615843,0.94244885,0.005731,0.047440138,0.0039455146,0.000018515559],"about_ca_topic_score_codex":0.0015896737,"about_ca_topic_score_gemma":0.0018320341,"teacher_disagreement_score":0.0016832302,"about_ca_system_score_codex":0.00031983445,"about_ca_system_score_gemma":0.0006257395,"threshold_uncertainty_score":0.00563097},"labels":[],"label_agreement":null},{"id":"W1968326787","doi":"10.1371/journal.pone.0117759","title":"Voxel-Based Texture Analysis of the Brain","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Killam Trusts; University of Alberta","keywords":"Voxel; Pattern recognition (psychology); Voxel-based morphometry; Artificial intelligence; Computer science; Texture (cosmology); Statistical analysis; Medicine; Magnetic resonance imaging; Mathematics; Statistics; Radiology; Image (mathematics)","score_opus":0.18334773477366884,"score_gpt":0.3470493817397412,"score_spread":0.16370164696607237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968326787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023010094,0.00045312347,0.97409886,0.00007624002,0.000050455536,0.000045398578,0.00033159283,0.0008821793,0.0010519453],"genre_scores_gemma":[0.43047237,0.0009913668,0.5650549,0.000084958505,0.000119312535,0.00015580608,0.00085195963,0.0004043081,0.0018651006],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996364,0.000068520836,0.000021409456,0.00006717413,0.00016211018,0.00004439981],"domain_scores_gemma":[0.99947804,0.00021224952,0.000067791676,0.00007682566,0.00013510251,0.000030022762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004759464,0.00040844435,0.0005839321,0.0022074936,0.00021350631,0.001212559,0.0005240131,0.0004292169,0.0019984029],"category_scores_gemma":[0.0018618514,0.00023955524,0.0007451138,0.001325603,0.0003893629,0.0006010111,0.00051232794,0.00049606076,0.0005939671],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039716138,0.0000702981,0.004946596,0.00054427143,0.00027261602,0.00041687462,0.0002619964,0.06470328,0.28546607,0.015686132,0.0035779446,0.6236567],"study_design_scores_gemma":[0.000053045223,0.00018338015,0.020323232,0.00005273854,0.000170373,0.0020835921,0.00019681342,0.84910864,0.086991884,0.023065748,0.01765684,0.00011381045],"about_ca_topic_score_codex":0.0013171021,"about_ca_topic_score_gemma":0.0013669938,"teacher_disagreement_score":0.0022074936,"about_ca_system_score_codex":0.0002825756,"about_ca_system_score_gemma":0.0004807411,"threshold_uncertainty_score":0.0066853166},"labels":[],"label_agreement":null},{"id":"W1968710739","doi":"10.4137/mri.s11149","title":"Measuring Restriction Sizes Using Diffusion Weighted Magnetic Resonance Imaging: A Review","year":2013,"lang":"en","type":"review","venue":"Magnetic Resonance Insights","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Health Research Council","keywords":"Diffusion; Spin echo; Magnetic resonance imaging; Nuclear magnetic resonance; Resonance (particle physics); Spin (aerodynamics); Diffusion MRI; Effective diffusion coefficient; Materials science; Physics; Atomic physics; Thermodynamics","score_opus":0.13278998106167303,"score_gpt":0.35619641840935345,"score_spread":0.22340643734768043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968710739","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000099391444,0.9986234,0.0003855679,0.00019335307,0.00011339833,0.000004605347,0.000014972128,0.0000094586285,0.0005558273],"genre_scores_gemma":[0.0005211315,0.9984842,0.00050270127,0.00008677238,0.00012958673,0.0000075644557,0.000021288693,0.0000020880784,0.0002445767],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997074,0.000037686677,0.000045894063,0.000059864335,0.00013161886,0.00001759748],"domain_scores_gemma":[0.9990889,0.00050946523,0.000112202935,0.0000214791,0.00022081756,0.000047208418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009550851,0.0014295242,0.0019163113,0.0044458336,0.00031020684,0.0010091119,0.0011829315,0.0014012981,0.0024613931],"category_scores_gemma":[0.0013283937,0.00052704266,0.000560594,0.0035998193,0.0009253329,0.0025141716,0.0007528845,0.0014056433,0.002482057],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003896627,0.0000631187,0.00023987281,0.016577296,0.00007172279,0.00019678292,0.000052871557,0.00040574328,0.0025242846,0.0027939554,0.017040264,0.9599952],"study_design_scores_gemma":[0.000012749077,0.000113812945,0.0013095038,0.0047207214,0.0001614455,0.0027661547,0.00009986821,0.00023525402,0.0019931209,0.0034535099,0.98507625,0.000057674955],"about_ca_topic_score_codex":0.0011178928,"about_ca_topic_score_gemma":0.0014602141,"teacher_disagreement_score":0.0044458336,"about_ca_system_score_codex":0.0006599853,"about_ca_system_score_gemma":0.0009881845,"threshold_uncertainty_score":0.008234203},"labels":[],"label_agreement":null},{"id":"W1968795166","doi":"10.1016/j.neuroimage.2004.05.026","title":"Quantitative measurement of neurodegeneration in an ALS–PDC model using MR microscopy","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research and Materiel Command; McKnight Foundation; National Center for Research Resources; ALS Association; Natural Sciences and Engineering Research Council of Canada; Scottish Rite Charitable Foundation of Canada","keywords":"Neurodegeneration; Neuroscience; Medicine; Pathology; Psychology; Disease","score_opus":0.24835171843965798,"score_gpt":0.431423795188646,"score_spread":0.183072076748988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968795166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9538141,0.0010919216,0.040377237,0.00027712088,0.00006237452,0.00014649637,0.0009248028,0.00045053646,0.002855491],"genre_scores_gemma":[0.966958,0.000748235,0.027754514,0.00006952173,0.000014828324,0.00014059938,0.0003578374,0.00009082896,0.0038656464],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997471,0.000045589823,0.000019656503,0.000065242035,0.00007231855,0.000050055634],"domain_scores_gemma":[0.99940157,0.00015621187,0.00014231897,0.00007963683,0.00013996201,0.00008020329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006824135,0.0007410485,0.00046682783,0.0011434827,0.00056971214,0.00048751384,0.00054874463,0.0010967113,0.0010399227],"category_scores_gemma":[0.00040365104,0.00031031156,0.0003262659,0.0004086231,0.000640631,0.00066798256,0.00040052325,0.001150163,0.00028099242],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036674924,0.00014009642,0.00033611755,0.000053395448,0.00001997441,0.00018113197,0.00006131553,0.0015596887,0.9947465,0.00035847616,0.00010489755,0.0020717015],"study_design_scores_gemma":[0.000043628,0.000791795,0.0034131738,0.000013590742,0.00008245274,0.0005888522,0.000086849075,0.019789785,0.97410446,0.00019280038,0.00087017426,0.000022471007],"about_ca_topic_score_codex":0.005935448,"about_ca_topic_score_gemma":0.0045241606,"teacher_disagreement_score":0.005935448,"about_ca_system_score_codex":0.00062929746,"about_ca_system_score_gemma":0.00055355765,"threshold_uncertainty_score":0.011801839},"labels":[],"label_agreement":null},{"id":"W1968931994","doi":"10.1016/j.schres.2014.03.034","title":"Genetic underpinnings of white matter ‘connectivity’: Heritability, risk, and heterogeneity in schizophrenia","year":2014,"lang":"en","type":"review","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Genome-wide association study; Polygene; White matter; Schizophrenia (object-oriented programming); Heritability; Biology; Candidate gene; Missing heritability problem; Genetic association; Genetics; Psychology; Quantitative trait locus; Gene; Medicine; Psychiatry; Single-nucleotide polymorphism; Genotype","score_opus":0.14795541773113713,"score_gpt":0.4495631878651363,"score_spread":0.3016077701339992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968931994","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004718731,0.9988055,0.00014473997,0.00026493875,0.00003125699,0.0000023489379,0.000026068068,0.0000035064957,0.00024968738],"genre_scores_gemma":[0.0026036948,0.9969597,0.00019021472,0.00006452981,0.00006953696,0.0000025289226,0.00003008486,6.1784135e-7,0.00007922837],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998759,0.000026253967,0.000018569328,0.000030161988,0.0000390001,0.000010144187],"domain_scores_gemma":[0.99969697,0.0001771465,0.00006297257,0.000008118549,0.000040989773,0.0000139013055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063284306,0.0005572405,0.0010466644,0.0010932519,0.00014596038,0.00056688976,0.00061589375,0.00054924225,0.0012379304],"category_scores_gemma":[0.0009614245,0.00020224413,0.00043083317,0.0015473908,0.0004599375,0.00058181933,0.0004945358,0.0006539567,0.00027466906],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014206115,0.00003179783,0.001880293,0.013903466,0.0006503336,0.00031090114,0.00007068746,0.0006684708,0.0016811013,0.0032283734,0.0076278015,0.9698047],"study_design_scores_gemma":[0.00015986105,0.00025071058,0.06664485,0.02264299,0.0038401948,0.008227696,0.00048577602,0.00093624525,0.0021423264,0.03745992,0.85703623,0.00017320251],"about_ca_topic_score_codex":0.0034299723,"about_ca_topic_score_gemma":0.0056599462,"teacher_disagreement_score":0.0034299723,"about_ca_system_score_codex":0.0004371277,"about_ca_system_score_gemma":0.0013717473,"threshold_uncertainty_score":0.006820023},"labels":[],"label_agreement":null},{"id":"W1969053905","doi":"10.3389/fpsyg.2015.00009","title":"Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Heart and Stroke Foundation; Sunnybrook Health Science Centre; University of Toronto","funders":"Economic and Social Research Council; Wellcome Trust","keywords":"Arcuate fasciculus; Psychology; Tractography; Neuroscience; Audiology; Diffusion MRI; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.058940382029320976,"score_gpt":0.3526427880386574,"score_spread":0.2937024060093364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969053905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93827873,0.00041137778,0.059056308,0.0002990255,0.000029832634,0.000052755022,0.00015105482,0.00017845875,0.001542466],"genre_scores_gemma":[0.96829355,0.0001507835,0.031084806,0.00006528455,0.0000124877415,0.000032496988,0.00013523764,0.000081926024,0.00014345293],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99662375,0.00085711165,0.0005087622,0.0011160127,0.0007140125,0.00018040568],"domain_scores_gemma":[0.97916436,0.013606294,0.0029747193,0.0022681113,0.00162403,0.0003624869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006206084,0.0006148319,0.0005892807,0.0010775395,0.00045234262,0.0016811521,0.00051345193,0.0008832605,0.0013726328],"category_scores_gemma":[0.051357962,0.00039676312,0.00053114834,0.00051830226,0.001396423,0.0015560366,0.0008438593,0.0007875695,0.00041320774],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018265559,0.00018577323,0.6990083,0.00039134163,0.00062699907,0.0008974702,0.002069367,0.015805738,0.092564255,0.0036741311,0.001002321,0.1819477],"study_design_scores_gemma":[0.00007557447,0.00067006855,0.8539653,0.00031040455,0.00031602243,0.0068302983,0.0005680164,0.08600266,0.038365357,0.010524661,0.0022495799,0.00012203052],"about_ca_topic_score_codex":0.0045203716,"about_ca_topic_score_gemma":0.0053477944,"teacher_disagreement_score":0.006206084,"about_ca_system_score_codex":0.00045582224,"about_ca_system_score_gemma":0.0007915734,"threshold_uncertainty_score":0.032821298},"labels":[],"label_agreement":null},{"id":"W1969164666","doi":"10.1007/s00256-011-1310-4","title":"Diffusion tensor imaging of the median nerve: intra-, inter-reader agreement, and agreement between two software packages","year":2011,"lang":"en","type":"article","venue":"Skeletal Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Diffusion MRI; Intraclass correlation; Medicine; Fractional anisotropy; Nuclear medicine; Limits of agreement; Effective diffusion coefficient; Software; Magnetic resonance imaging; Radiology; Computer science","score_opus":0.053217293732524686,"score_gpt":0.3252695101188046,"score_spread":0.2720522163862799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969164666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85130864,0.0015789972,0.1367938,0.00025145643,0.00061826635,0.0008104818,0.0015848295,0.0018370375,0.0052164835],"genre_scores_gemma":[0.93437463,0.00018493788,0.061679427,0.000071994036,0.0000536186,0.00047784706,0.00088638463,0.0008561253,0.0014150237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9499543,0.023698054,0.008714982,0.009754294,0.0068799094,0.0009985894],"domain_scores_gemma":[0.79741424,0.12839049,0.011192819,0.02558582,0.035449874,0.0019667542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0616838,0.0011396295,0.0016158189,0.0034676376,0.0012633349,0.0028170873,0.0014675936,0.0016536147,0.0023555872],"category_scores_gemma":[0.1543613,0.0011618127,0.0023053193,0.0016091418,0.0018683181,0.0029054931,0.0029203435,0.0018453213,0.0014524803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019195598,0.0008424019,0.66607344,0.0018800411,0.012869762,0.00071373314,0.017896079,0.010820809,0.04697656,0.0041881953,0.009202776,0.20934068],"study_design_scores_gemma":[0.0010164767,0.002589169,0.81157726,0.00046700763,0.005149072,0.0033247964,0.006569808,0.0923619,0.055564404,0.010124612,0.010396308,0.00085910765],"about_ca_topic_score_codex":0.0016517706,"about_ca_topic_score_gemma":0.0045798426,"teacher_disagreement_score":0.0616838,"about_ca_system_score_codex":0.0009981589,"about_ca_system_score_gemma":0.0011027819,"threshold_uncertainty_score":0.32621902},"labels":[],"label_agreement":null},{"id":"W1969637629","doi":"10.1016/j.neuroimage.2014.04.074","title":"Towards quantitative connectivity analysis: reducing tractography biases","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":353,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Voxel; Computer science; Diffusion MRI; Artificial intelligence; Probabilistic logic; Position (finance); Pattern recognition (psychology); Mathematics; Magnetic resonance imaging","score_opus":0.12397581088359226,"score_gpt":0.3996962134668545,"score_spread":0.27572040258326225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969637629","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005954779,0.00017046505,0.9926484,0.0002787282,0.000027017259,0.00002428213,0.0001066023,0.00054931163,0.00024041488],"genre_scores_gemma":[0.14986053,0.00055278157,0.84553623,0.00028759442,0.0001436115,0.00013412476,0.0005487085,0.0013784029,0.0015580788],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99702793,0.0014535701,0.00015919608,0.0005865085,0.0006683388,0.0001044902],"domain_scores_gemma":[0.9810797,0.0107807405,0.0017628327,0.003916618,0.0021624041,0.0002977085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007279806,0.0019452549,0.0016861663,0.003107804,0.0009825522,0.0037187166,0.0020932686,0.0020892452,0.0023655295],"category_scores_gemma":[0.042471513,0.0011258589,0.00121071,0.0028208538,0.0015014574,0.003856882,0.0028119548,0.0029330337,0.0014286668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005137615,0.00024306687,0.008574205,0.0012432482,0.0010435672,0.00028720495,0.0008239248,0.16428101,0.09525249,0.111249,0.012384032,0.60410446],"study_design_scores_gemma":[0.00005118809,0.00009750054,0.003366689,0.000086033004,0.00022160003,0.00040332685,0.000106687774,0.7969087,0.01583978,0.1763583,0.006502156,0.000058070895],"about_ca_topic_score_codex":0.003562526,"about_ca_topic_score_gemma":0.004982423,"teacher_disagreement_score":0.007279806,"about_ca_system_score_codex":0.00075031543,"about_ca_system_score_gemma":0.0022572319,"threshold_uncertainty_score":0.038499713},"labels":[],"label_agreement":null},{"id":"W1969880629","doi":"10.1093/cercor/10.5.454","title":"A New Anatomical Landmark for Reliable Identification of Human Area V5/MT: a Quantitative Analysis of Sulcal Patterning","year":2000,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":499,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Sulcus; Anatomy; Landmark; Cortex (anatomy); Superior temporal sulcus; Geology; Biology; Neuroscience; Computer science; Functional magnetic resonance imaging; Artificial intelligence","score_opus":0.07129634739844613,"score_gpt":0.38371110447618323,"score_spread":0.3124147570777371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969880629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8322068,0.0010929571,0.16305517,0.0000381521,0.000011105287,0.0000717489,0.0005241491,0.0003763621,0.0026236388],"genre_scores_gemma":[0.94561845,0.00014289103,0.053508956,0.0000062461713,0.000008151012,0.000050026898,0.0002634168,0.00006020112,0.00034164725],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997917,0.00004228509,0.000017892242,0.00006328004,0.00006431205,0.000020507747],"domain_scores_gemma":[0.99948955,0.00018469775,0.00011572848,0.00008597135,0.000088573324,0.000035510227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045894354,0.0002135949,0.00023325435,0.0019059061,0.00026850717,0.00046254185,0.00025609406,0.00022789637,0.0015130016],"category_scores_gemma":[0.0011343986,0.00014877335,0.00014993931,0.0006085026,0.00044967898,0.0004908288,0.00041337698,0.00018466392,0.0002664184],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026988797,0.000018987676,0.025339311,0.00021032328,0.00005281391,0.00012772041,0.00026804113,0.000989627,0.9151337,0.0013253626,0.00017739125,0.05608683],"study_design_scores_gemma":[0.00004329014,0.0005069335,0.63962954,0.000057562447,0.00016347627,0.0034812684,0.00035922416,0.03287612,0.31549084,0.0019628832,0.005363745,0.0000651857],"about_ca_topic_score_codex":0.0018127107,"about_ca_topic_score_gemma":0.003064225,"teacher_disagreement_score":0.0019059061,"about_ca_system_score_codex":0.00030430764,"about_ca_system_score_gemma":0.00023704782,"threshold_uncertainty_score":0.005061507},"labels":[],"label_agreement":null},{"id":"W1969886036","doi":"10.1016/j.neurobiolaging.2010.02.009","title":"Age-related decline in white matter tract integrity and cognitive performance: A DTI tractography and structural equation modeling study","year":2010,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":305,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of General Medical Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Cingulum (brain); White matter; Inferior longitudinal fasciculus; Corpus callosum; Uncinate fasciculus; Psychology; Diffusion MRI; Splenium; Superior longitudinal fasciculus; Corticospinal tract; Tractography; Cognition; Cognitive decline; Neuroscience; Fractional anisotropy; Audiology; Medicine; Magnetic resonance imaging; Dementia","score_opus":0.052617199970105506,"score_gpt":0.3485499098354151,"score_spread":0.2959327098653096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969886036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99978584,0.000024176545,0.000081957085,0.000009018035,0.0000011305924,0.000002716735,0.0000471933,0.0000013600533,0.000046573343],"genre_scores_gemma":[0.9993382,0.00004868077,0.00023218825,0.000010166878,0.000004722517,0.000006003769,0.00010659365,0.0000025060012,0.00025084976],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997571,0.000070413436,0.000029057843,0.000075936165,0.00003600495,0.00003145815],"domain_scores_gemma":[0.99814785,0.00045733823,0.0005496408,0.00040811373,0.00023210772,0.00020498343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021279936,0.00057141396,0.0005028505,0.00070351374,0.000608253,0.0005255826,0.00038405275,0.00062631356,0.00077282754],"category_scores_gemma":[0.0038692001,0.00030536405,0.0005894683,0.0008266085,0.00052739674,0.001265493,0.00043713104,0.0007466328,0.00022706024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031391424,0.0011146619,0.97985506,0.00002328958,0.00034529448,0.0006193543,0.0014430666,0.0007744973,0.0043703318,0.00022623237,0.0002135486,0.007875533],"study_design_scores_gemma":[0.000041425552,0.00095717114,0.9945269,0.0000031360898,0.00013282851,0.00059593754,0.0002784629,0.0026026429,0.00043698496,0.00024175287,0.00017211663,0.0000104816945],"about_ca_topic_score_codex":0.010423994,"about_ca_topic_score_gemma":0.01023818,"teacher_disagreement_score":0.010423994,"about_ca_system_score_codex":0.00051377405,"about_ca_system_score_gemma":0.0006668739,"threshold_uncertainty_score":0.020726621},"labels":[],"label_agreement":null},{"id":"W1970218933","doi":"10.3174/ajnr.a0742","title":"Preliminary Experience with Visualization of Intracortical Fibers by Focused High-Resolution Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; White matter; Anisotropy; Imaging phantom; Nuclear magnetic resonance; Fractional anisotropy; Biomedical engineering; Magnetic resonance imaging; Physics; Optics; Medicine","score_opus":0.018151319757508447,"score_gpt":0.32864973964086,"score_spread":0.31049841988335153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970218933","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43724707,0.014926164,0.52863455,0.0025119488,0.00021852336,0.00068022485,0.00026034,0.0011195589,0.014401558],"genre_scores_gemma":[0.5048731,0.008499566,0.4793134,0.0009029565,0.00035347894,0.00044110097,0.0006219942,0.00027993813,0.0047144596],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99747604,0.0014079824,0.00015321207,0.0004760611,0.000309989,0.00017674587],"domain_scores_gemma":[0.9920506,0.004137038,0.000272614,0.0013274259,0.0014933677,0.0007189412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011046038,0.0011745833,0.00040155603,0.0008549034,0.00055931654,0.0010336181,0.0022929048,0.0019079889,0.008702659],"category_scores_gemma":[0.010653033,0.00047307782,0.00042272,0.0004996922,0.0020015275,0.0015633553,0.0011930936,0.0014772754,0.002720746],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027845232,0.0034766234,0.03832681,0.001448348,0.00035076606,0.004933685,0.006558609,0.003542105,0.5541221,0.003453752,0.0037714897,0.3772312],"study_design_scores_gemma":[0.0006387375,0.027733227,0.06823756,0.0007940647,0.00076862646,0.117015734,0.0019896585,0.01804667,0.6303979,0.012437004,0.121483386,0.00045730715],"about_ca_topic_score_codex":0.0008436772,"about_ca_topic_score_gemma":0.001093057,"teacher_disagreement_score":0.011046038,"about_ca_system_score_codex":0.0003795868,"about_ca_system_score_gemma":0.00047058726,"threshold_uncertainty_score":0.058417737},"labels":[],"label_agreement":null},{"id":"W1970455232","doi":"10.1159/000088526","title":"Corpus Callosum in Neurodegenerative Diseases: Findings in Parkinson’s Disease","year":2005,"lang":"en","type":"review","venue":"Dementia and Geriatric Cognitive Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; NIH Clinical Center; National Institute on Aging; University of Alberta","keywords":"Corpus callosum; Degenerative disease; Parkinson's disease; Neuroscience; Disease; Central nervous system disease; Dementia; Psychology; Medicine; Pathology","score_opus":0.03978926997217109,"score_gpt":0.3575897639484629,"score_spread":0.31780049397629184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970455232","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02459785,0.9737453,0.00033669738,0.00040416364,0.00019226428,0.000029046478,0.00026659723,0.000014192783,0.00041394445],"genre_scores_gemma":[0.7363642,0.25848436,0.0021009042,0.001022564,0.00084453594,0.00019235813,0.0005507824,0.000034956494,0.00040531805],"study_design_codex":"meta_analysis","study_design_gemma":"not_applicable","domain_scores_codex":[0.9925695,0.0030239627,0.0015091009,0.0018097333,0.0009328048,0.00015481557],"domain_scores_gemma":[0.97772855,0.016504087,0.0033622847,0.00091470015,0.0011768051,0.0003135257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011601456,0.0014608554,0.0046876366,0.006652176,0.0006291788,0.0027089242,0.0016333666,0.002182706,0.0019404368],"category_scores_gemma":[0.023329228,0.000851016,0.013525277,0.007628087,0.0013413497,0.0012942688,0.0016143756,0.0014088444,0.00013395464],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006443474,0.00006415424,0.21336456,0.13009207,0.55465156,0.0007759685,0.00060373615,0.0010181827,0.0021749057,0.0006821598,0.0021565384,0.087972745],"study_design_scores_gemma":[0.0010844737,0.00086936954,0.31822747,0.022212563,0.643662,0.0017660378,0.0004511469,0.0007088513,0.0007328859,0.0021139567,0.008066103,0.00010515295],"about_ca_topic_score_codex":0.007382296,"about_ca_topic_score_gemma":0.010400336,"teacher_disagreement_score":0.011601456,"about_ca_system_score_codex":0.0012545908,"about_ca_system_score_gemma":0.0012880402,"threshold_uncertainty_score":0.061355114},"labels":[],"label_agreement":null},{"id":"W1970921286","doi":"10.1118/1.3181244","title":"SU‐FF‐I‐123: Clinical Value of Diffusion‐Weighted MRI in White Matter in Vivo","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"Splenium; White matter; Diffusion MRI; Nuclear magnetic resonance; Magnetic resonance imaging; Corpus callosum; Diffusion; Chemistry; Nuclear medicine; Relaxation (psychology); Effective diffusion coefficient; Materials science; Physics; Medicine; Anatomy; Radiology","score_opus":0.03935547254952559,"score_gpt":0.3827982810644111,"score_spread":0.3434428085148855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970921286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9121787,0.040239356,0.023738572,0.0019812416,0.0002003325,0.00026327762,0.00068852486,0.0008989323,0.01981113],"genre_scores_gemma":[0.99236506,0.001996397,0.004273411,0.0001250804,0.000041189745,0.000046930567,0.00016998251,0.000047849026,0.0009340792],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997651,0.00009781694,0.000021230593,0.000053138552,0.00004200155,0.00002082619],"domain_scores_gemma":[0.99957246,0.00015701397,0.00008574054,0.00003528378,0.0000811395,0.00006827401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013404832,0.0006112733,0.000419142,0.00091236376,0.00030641278,0.0010316279,0.00060768775,0.0015165781,0.0015435661],"category_scores_gemma":[0.0025591687,0.00026199842,0.00012300514,0.00041335,0.000789653,0.0011686382,0.0002313145,0.000467949,0.00065159105],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011704153,0.0004448053,0.28619775,0.0013256448,0.0002094081,0.009002647,0.00044566471,0.003926501,0.2762396,0.0022205128,0.0065925554,0.4016907],"study_design_scores_gemma":[0.0006380847,0.010471424,0.53162175,0.0006072786,0.00053839607,0.05133879,0.00086691545,0.16047937,0.19715287,0.00835605,0.037560925,0.00036817],"about_ca_topic_score_codex":0.0011670758,"about_ca_topic_score_gemma":0.0007658157,"teacher_disagreement_score":0.0015435661,"about_ca_system_score_codex":0.00031510115,"about_ca_system_score_gemma":0.00029806813,"threshold_uncertainty_score":0.0070891976},"labels":[],"label_agreement":null},{"id":"W1971120154","doi":"10.1016/j.schres.2012.02.015","title":"Diffusion tensor imaging tractography of the fornix and belief confidence in first-episode psychosis","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Douglas Mental Health University Institute; McGill University","funders":"Canadian Institutes of Health Research","keywords":"Fornix; Tractography; Diffusion MRI; Psychosis; Psychology; Medicine; Psychiatry; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.10104243861373237,"score_gpt":0.41056369593165964,"score_spread":0.3095212573179273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971120154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976398,0.0002366721,0.0007933717,0.00023261675,0.000006075098,0.000009763744,0.00016340821,0.000008632908,0.0009097201],"genre_scores_gemma":[0.9990435,0.00010214083,0.00039374855,0.000010027187,0.0000040541554,0.000004331769,0.000066579065,0.0000049736495,0.00037057258],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988186,0.0000396467,0.00001031732,0.000020052785,0.000023842042,0.000024180805],"domain_scores_gemma":[0.99864644,0.00044578392,0.0005524237,0.0001198955,0.00011566814,0.00011979481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007595229,0.00026032416,0.0002448145,0.00065611105,0.00046086832,0.0010912212,0.00036803712,0.0005213107,0.0023764002],"category_scores_gemma":[0.0053689,0.00025472092,0.00024210631,0.0006652758,0.0005854939,0.0010787469,0.00042942987,0.00073019403,0.00016038913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018154467,0.00025472254,0.9052433,0.00019372113,0.00058208697,0.0023903728,0.0037506903,0.007889507,0.025463894,0.005451227,0.0009869189,0.045978222],"study_design_scores_gemma":[0.00003566509,0.00012749367,0.98166656,0.000040291383,0.000062463405,0.001391997,0.00086421415,0.0072127786,0.0018464247,0.006399517,0.00032111933,0.000031432603],"about_ca_topic_score_codex":0.030642398,"about_ca_topic_score_gemma":0.03424931,"teacher_disagreement_score":0.030642398,"about_ca_system_score_codex":0.00081870094,"about_ca_system_score_gemma":0.0010691615,"threshold_uncertainty_score":0.060928047},"labels":[],"label_agreement":null},{"id":"W1971405799","doi":"10.1016/j.media.2010.07.001","title":"Multiple q-shell diffusion propagator imaging","year":2010,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Association France Parkinson","keywords":"Diffusion MRI; Propagator; Computer science; Diffusion; Laplace transform; Fourier transform; SIGNAL (programming language); Diffusion equation; Algorithm; Artificial intelligence; Physics; Computer vision; Mathematical analysis; Mathematics","score_opus":0.01894291456037772,"score_gpt":0.3416434039444404,"score_spread":0.3227004893840627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971405799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015143542,0.00042462503,0.97843325,0.00060208095,0.000059938768,0.00004506614,0.00007847533,0.0004038547,0.0048091616],"genre_scores_gemma":[0.20760486,0.0010393584,0.7784467,0.00035541292,0.000103400394,0.00010132417,0.0001419971,0.0003787929,0.011828189],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983716,0.00006186698,0.000013386769,0.000030874944,0.000043201606,0.000013525335],"domain_scores_gemma":[0.99921787,0.0003243219,0.00010707902,0.00013122498,0.0001532947,0.00006618384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088031177,0.0008925688,0.0003490487,0.0006950192,0.0003961658,0.0014291499,0.0006854476,0.0011819083,0.007830753],"category_scores_gemma":[0.0030046643,0.00041621685,0.00040531368,0.0007274672,0.0005906786,0.002446343,0.0010249463,0.0009420145,0.001289991],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076016365,0.00018954271,0.0040449933,0.00102872,0.00023372157,0.0021116333,0.0006708677,0.04357714,0.33454388,0.16312684,0.008119147,0.44159326],"study_design_scores_gemma":[0.00012857396,0.00030353165,0.0037804535,0.00017621521,0.00019854285,0.0066029904,0.0002486123,0.673852,0.16681527,0.12249178,0.025265737,0.00013630187],"about_ca_topic_score_codex":0.000433782,"about_ca_topic_score_gemma":0.0009408439,"teacher_disagreement_score":0.007830753,"about_ca_system_score_codex":0.0002808411,"about_ca_system_score_gemma":0.0006514827,"threshold_uncertainty_score":0.02619642},"labels":[],"label_agreement":null},{"id":"W1971698195","doi":"10.1016/j.schres.2012.08.026","title":"Alexithymia and reduced white matter integrity in schizophrenia: A diffusion tensor imaging study on impaired emotional self-awareness","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; White matter; Psychology; Fractional anisotropy; Schizophrenia (object-oriented programming); Diffusion MRI; Toronto Alexithymia Scale; Corpus callosum; Clinical psychology; Psychiatry; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.1105734440366848,"score_gpt":0.41577066083614433,"score_spread":0.30519721679945955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971698195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995091,0.000049680326,0.000023502016,0.000029677929,0.0000019372214,0.000006125356,0.000032316475,0.0000011252204,0.00034666221],"genre_scores_gemma":[0.9997025,0.00005773475,0.000051351286,0.000017116825,0.000006350505,0.0000033374931,0.000058662405,0.0000010322735,0.00010188268],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998361,0.000031766882,0.00002658207,0.000027539181,0.00004716508,0.000030772026],"domain_scores_gemma":[0.9995608,0.00007693555,0.00018278875,0.000029098857,0.000034191686,0.00011622605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037977952,0.000574437,0.00037654923,0.0012549775,0.00093751465,0.0005928953,0.0003746545,0.00055668043,0.0018403253],"category_scores_gemma":[0.0010496875,0.00048903836,0.00034792346,0.00088491954,0.0008499641,0.0005406211,0.00055192783,0.00055465195,0.00016444523],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029100098,0.0008866747,0.94616896,0.00007368854,0.00031982508,0.011129376,0.001472984,0.00017922145,0.03067507,0.00030625478,0.0001781027,0.0056999247],"study_design_scores_gemma":[0.00002489514,0.00019210277,0.9956216,0.0000033319366,0.00004705167,0.0031709021,0.00035547372,0.000117599855,0.0002912146,0.000121343866,0.00004710052,0.000007313409],"about_ca_topic_score_codex":0.010362727,"about_ca_topic_score_gemma":0.010635237,"teacher_disagreement_score":0.010362727,"about_ca_system_score_codex":0.0004588226,"about_ca_system_score_gemma":0.0005038343,"threshold_uncertainty_score":0.02060479},"labels":[],"label_agreement":null},{"id":"W1972541617","doi":"10.1016/j.baga.2011.06.029","title":"P28 Human medial forebrain bundle (MFB) and anterior thalamic radiations (ATR): Diffusion tensor imaging anatomical description of two affective pathways that promote a dynamic balance of opposite affects (SEEKING and GRIEF)","year":2011,"lang":"en","type":"article","venue":"Basal Ganglia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; Medial forebrain bundle; Neuroscience; Psychology; Bundle; Balance (ability); Forebrain; Medicine; Radiology; Central nervous system","score_opus":0.04191054394480809,"score_gpt":0.29892928450899536,"score_spread":0.2570187405641873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972541617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9588531,0.0012538957,0.022298556,0.0005946742,0.00007090043,0.00013853222,0.000683518,0.00020139816,0.015905445],"genre_scores_gemma":[0.9842061,0.0004083203,0.008103284,0.00011193537,0.000036084883,0.000057649733,0.00036251533,0.000049009584,0.0066650393],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993396,0.000011399836,0.000005688023,0.000022266646,0.000014316977,0.00001232065],"domain_scores_gemma":[0.99988186,0.000033557604,0.000029853385,0.000022575194,0.000013484417,0.000018700986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020529464,0.00031583384,0.00020699108,0.00044275692,0.00031281408,0.00052320707,0.00031083685,0.0005790882,0.006076641],"category_scores_gemma":[0.00049487606,0.0002522721,0.00022799397,0.00020418406,0.00062732643,0.00047596748,0.0002708066,0.0006278705,0.001034595],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021623448,0.0003451674,0.015979642,0.00048616627,0.0002485491,0.03293511,0.0013612477,0.001927208,0.85365796,0.019819207,0.0030905541,0.06798682],"study_design_scores_gemma":[0.00061447825,0.0025641809,0.23710227,0.00017912264,0.00038015711,0.18081322,0.0013448928,0.022708913,0.47809684,0.031030852,0.045019206,0.00014582608],"about_ca_topic_score_codex":0.0023447468,"about_ca_topic_score_gemma":0.0021467756,"teacher_disagreement_score":0.006076641,"about_ca_system_score_codex":0.00026216783,"about_ca_system_score_gemma":0.00035738028,"threshold_uncertainty_score":0.020328343},"labels":[],"label_agreement":null},{"id":"W1973562248","doi":"10.1016/j.neuroimage.2006.07.024","title":"White matter growth as a mechanism of cognitive development in children","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":192,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; Hospital for Sick Children; SickKids Foundation; McMaster University; University of Toronto","funders":"Sick Kids Foundation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Cognition; Cognitive psychology; Neuroscience; Developmental psychology; Audiology; Magnetic resonance imaging; Medicine","score_opus":0.019398143052890362,"score_gpt":0.29172072513163827,"score_spread":0.27232258207874793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973562248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99394625,0.0019466681,0.0010619226,0.00029971806,0.000014873835,0.000012670177,0.00031562426,0.000059925784,0.0023423005],"genre_scores_gemma":[0.99510115,0.0018029264,0.001885736,0.000025813697,0.000013005964,0.000020174908,0.00014551112,0.00002519928,0.000980431],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980634,0.000036392816,0.000018461353,0.000044770502,0.000054285887,0.0000398024],"domain_scores_gemma":[0.9991429,0.00022023535,0.00037165123,0.000049251546,0.00015660634,0.000059409784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000608487,0.00061191915,0.0003052261,0.0021660475,0.0004177524,0.0007107855,0.0005537793,0.0004950351,0.0010349487],"category_scores_gemma":[0.0018434839,0.00037705875,0.0003045378,0.00079736486,0.0011600223,0.0010769546,0.00045243232,0.00065744965,0.00017145264],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011201364,0.00025418465,0.8247787,0.0003491924,0.00018581956,0.0062896637,0.0019473751,0.003735729,0.08043655,0.010596018,0.0016302427,0.068676345],"study_design_scores_gemma":[0.000021097183,0.0002949653,0.94903,0.000067285706,0.000121528465,0.005871182,0.0011691031,0.0023492377,0.035752613,0.003885356,0.0014103217,0.000027285647],"about_ca_topic_score_codex":0.0120420195,"about_ca_topic_score_gemma":0.006273162,"teacher_disagreement_score":0.0120420195,"about_ca_system_score_codex":0.00084660365,"about_ca_system_score_gemma":0.0011330827,"threshold_uncertainty_score":0.023943841},"labels":[],"label_agreement":null},{"id":"W1973670636","doi":"10.2478/s13380-011-0018-1","title":"Gyral window mapping of typical cortical folding using MRI","year":2011,"lang":"en","type":"article","venue":"Translational Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; McGill University","keywords":"Gyrification; Occipital lobe; Anatomy; Lateralization of brain function; White matter; Temporal lobe; Frontal lobe; Parietal lobe; Occipital region; Psychology; Magnetic resonance imaging; Medicine; Cerebral cortex; Neuroscience; Radiology","score_opus":0.28190502056661515,"score_gpt":0.3853648685491616,"score_spread":0.10345984798254643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973670636","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920678,0.00014735528,0.006221026,0.000010113416,0.0000031558193,0.000021367612,0.00053552113,0.0001340185,0.0008596002],"genre_scores_gemma":[0.99191356,0.000114125534,0.0072399257,0.0000039700567,0.0000035600904,0.000029687586,0.000407114,0.000045812954,0.0002422657],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979633,0.00004955726,0.00002007024,0.00006969166,0.000035549285,0.000028864124],"domain_scores_gemma":[0.9996599,0.00010391595,0.00011257219,0.000053768606,0.00004276933,0.000027005988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044656242,0.00036715964,0.00020271674,0.0016341927,0.00014282286,0.00060334266,0.00013326958,0.00012163047,0.0016177801],"category_scores_gemma":[0.0014896756,0.00016272042,0.00026567953,0.00068534893,0.00024235528,0.0003328076,0.0004037522,0.0001482282,0.0002605183],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028480757,0.00007041472,0.47089103,0.00024687493,0.000264873,0.0012599105,0.0030168304,0.0052238307,0.36808166,0.0025487083,0.0012733988,0.14427435],"study_design_scores_gemma":[0.0000116626,0.00011311775,0.9727297,0.000022782688,0.000032023665,0.0015829002,0.00029486517,0.005554055,0.017329214,0.0010029782,0.0013079817,0.000018716504],"about_ca_topic_score_codex":0.002655267,"about_ca_topic_score_gemma":0.0034559648,"teacher_disagreement_score":0.002655267,"about_ca_system_score_codex":0.00017684748,"about_ca_system_score_gemma":0.00020827056,"threshold_uncertainty_score":0.005412042},"labels":[],"label_agreement":null},{"id":"W1974268522","doi":"10.1016/j.schres.2004.08.023","title":"Smaller corpus callosum subregions containing motor fibers in schizophrenia","year":2004,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); Neuroscience; Psychology; Anatomy; Medicine; Psychiatry","score_opus":0.1720332418465958,"score_gpt":0.4201316797792233,"score_spread":0.24809843793262748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974268522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963793,0.0006157352,0.0010678503,0.00015224615,0.000011052332,0.000011419897,0.00030209523,0.00004845962,0.0014117518],"genre_scores_gemma":[0.99673045,0.00030119263,0.0014319003,0.000048615406,0.000015422936,0.00002072857,0.0001293822,0.00003164774,0.001290677],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998493,0.00002021966,0.000017503464,0.000045385983,0.00004425947,0.000023350585],"domain_scores_gemma":[0.9989235,0.00023670019,0.00043916088,0.00013870183,0.000097156386,0.00016473733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006127458,0.00064761983,0.0005775481,0.002800942,0.00096675655,0.000990851,0.0005563311,0.0006069087,0.0068506883],"category_scores_gemma":[0.0011367741,0.0005647848,0.00033831614,0.0008445406,0.001494875,0.0009736866,0.0007768636,0.0007024529,0.0003769975],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049648923,0.00012217449,0.10378978,0.00064495456,0.00056417804,0.0038200691,0.0033521669,0.0016748466,0.8449346,0.004642026,0.00093225745,0.030558119],"study_design_scores_gemma":[0.00020478235,0.00029156392,0.92878294,0.000088905865,0.00047866232,0.009858999,0.0018434384,0.0021863482,0.05012061,0.003861182,0.0022270433,0.00005543773],"about_ca_topic_score_codex":0.015073265,"about_ca_topic_score_gemma":0.019428734,"teacher_disagreement_score":0.015073265,"about_ca_system_score_codex":0.0006392307,"about_ca_system_score_gemma":0.0009320199,"threshold_uncertainty_score":0.029971063},"labels":[],"label_agreement":null},{"id":"W1974674847","doi":"10.1371/journal.pone.0115229","title":"Gestational Age and Neonatal Brain Microstructure in Term Born Infants: A Birth Cohort Study","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council","keywords":"Gestational age; Internal capsule; Corpus callosum; Medicine; Fractional anisotropy; Diffusion MRI; White matter; Pediatrics; Pregnancy; Cohort; Neuroimaging; Cohort study; Obstetrics; Magnetic resonance imaging; Internal medicine; Pathology; Biology; Radiology","score_opus":0.03348481545723665,"score_gpt":0.30082018310346625,"score_spread":0.2673353676462296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974674847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993461,0.00016887886,0.000050544073,0.00002285126,0.000002994924,0.000008939239,0.00025824585,0.0000016548803,0.00013982896],"genre_scores_gemma":[0.9990497,0.00024575548,0.00010509133,0.000016934922,0.0000041561966,0.000018692019,0.0003386011,0.0000029953098,0.00021794272],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996722,0.000057147307,0.000041503252,0.00009416824,0.000075523414,0.000059485315],"domain_scores_gemma":[0.9992536,0.00010202211,0.00029006822,0.00010112193,0.0000940215,0.00015927794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007379115,0.0003604847,0.00043976682,0.0005446058,0.0006459484,0.0006571809,0.00044932505,0.00050825486,0.0011184041],"category_scores_gemma":[0.0021010982,0.00032757618,0.0005827786,0.00069062045,0.00026156387,0.00046302774,0.0006872113,0.0006053486,0.00022865225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016865694,0.000029009192,0.9975171,0.0000131540255,0.00006680051,0.0003601262,0.00037089598,0.000017082486,0.00039040344,0.00002516918,0.000067320194,0.0009743444],"study_design_scores_gemma":[0.0000027217875,0.00010900933,0.9990952,0.000009394893,0.00003203056,0.00034164844,0.00024439098,0.000034134915,0.000034161876,0.000011303228,0.00008288138,0.0000030670071],"about_ca_topic_score_codex":0.017530857,"about_ca_topic_score_gemma":0.015022564,"teacher_disagreement_score":0.017530857,"about_ca_system_score_codex":0.0004023801,"about_ca_system_score_gemma":0.00035524587,"threshold_uncertainty_score":0.03485763},"labels":[],"label_agreement":null},{"id":"W1974790621","doi":"10.1016/j.neurobiolaging.2014.04.035","title":"Measuring brain atrophy with a generalized formulation of the boundary shift integral","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute for Health and Care Research; Canadian Institutes of Health Research; Engineering and Physical Sciences Research Council; Sparks; Medical Research Council","keywords":"Atrophy; Probabilistic logic; Imaging biomarker; Magnetic resonance imaging; Biomarker; Medicine; Artificial intelligence; Computer science; Pathology; Pattern recognition (psychology); Radiology; Biology","score_opus":0.04606133593290812,"score_gpt":0.29650136270906957,"score_spread":0.25044002677616145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974790621","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013437077,0.0002236948,0.9856161,0.00009673288,0.00002170225,0.000045119363,0.000031885367,0.00012468647,0.00040306483],"genre_scores_gemma":[0.24446133,0.000477022,0.7531049,0.00016797718,0.00009964418,0.00028631042,0.00015610692,0.00010327784,0.0011434655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896884,0.00039799127,0.00007109629,0.00020696921,0.000313273,0.000041763913],"domain_scores_gemma":[0.9983222,0.0009510188,0.00024643354,0.00020952996,0.00022475894,0.000046008445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002666375,0.00079002633,0.00091162126,0.000925982,0.00022350051,0.0009015382,0.0012326281,0.0011200855,0.00081039616],"category_scores_gemma":[0.0077882856,0.0004196235,0.00069368083,0.0007163099,0.0012804527,0.0015552219,0.0010464112,0.00107691,0.00017517775],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038526312,0.00016482049,0.0051655904,0.00043220547,0.00039729924,0.0003281378,0.00042084977,0.5251132,0.07760545,0.05954274,0.001281819,0.3291625],"study_design_scores_gemma":[0.000035520687,0.00018666666,0.0030145484,0.000026778585,0.00006503055,0.00027512427,0.00003390125,0.96071565,0.006283275,0.027771568,0.0015430372,0.000048930877],"about_ca_topic_score_codex":0.0014673831,"about_ca_topic_score_gemma":0.0013642872,"teacher_disagreement_score":0.002666375,"about_ca_system_score_codex":0.0004519411,"about_ca_system_score_gemma":0.00082897476,"threshold_uncertainty_score":0.014101267},"labels":[],"label_agreement":null},{"id":"W1975017507","doi":"10.1016/j.neuroimage.2010.05.043","title":"Orientationally invariant indices of axon diameter and density from diffusion MRI","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":697,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Lundbeckfonden","keywords":"Axon; White matter; Diffusion MRI; Spherical mean; Corpus callosum; Magnetic resonance imaging; Human brain; Tractography; Fractional anisotropy; Neuroscience; Nuclear magnetic resonance; Anatomy; Physics; Biology; Mathematics; Mathematical analysis; Medicine; Radiology","score_opus":0.03159739527235598,"score_gpt":0.31454506195342613,"score_spread":0.28294766668107013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975017507","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4696007,0.0035365005,0.51102364,0.00038768863,0.00015507729,0.00013325881,0.0033434764,0.0017137252,0.010105923],"genre_scores_gemma":[0.748848,0.0033627527,0.24195136,0.0001133111,0.00020678107,0.00012999511,0.0021863796,0.0006935331,0.0025079174],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998455,0.00003053855,0.000017130902,0.000036845973,0.00005609282,0.000013751001],"domain_scores_gemma":[0.99934465,0.00017656788,0.00016637349,0.000091469614,0.00017420683,0.000046714405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065989443,0.0005421935,0.0003688872,0.0029697036,0.00028246868,0.0014892997,0.0004001212,0.00055734994,0.0013359288],"category_scores_gemma":[0.0031693052,0.0003235003,0.0002505742,0.0018018254,0.000349061,0.0017305186,0.00042515426,0.00047579917,0.00056676037],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008321403,0.00012947178,0.04616754,0.0008965431,0.00042571238,0.0005864067,0.00042337543,0.022393651,0.4397846,0.024837358,0.006126319,0.4573969],"study_design_scores_gemma":[0.00009264341,0.0003937035,0.29218575,0.00021945052,0.0008123701,0.009705692,0.00054055534,0.29632512,0.30666006,0.07385887,0.018818734,0.0003870724],"about_ca_topic_score_codex":0.0013669638,"about_ca_topic_score_gemma":0.0036269096,"teacher_disagreement_score":0.0029697036,"about_ca_system_score_codex":0.00037712185,"about_ca_system_score_gemma":0.00054347067,"threshold_uncertainty_score":0.0044690967},"labels":[],"label_agreement":null},{"id":"W1975385958","doi":"10.1016/j.jpain.2012.01.017","title":"DTI 3T MRI assessment of lumbar stabilization muscles","year":2012,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Medicine; Oswestry Disability Index; Lumbar; Low back pain; Effective diffusion coefficient; Longissimus; Multifidus muscle; Tractography; Magnetic resonance imaging; Anatomy; Physical therapy; Radiology; Pathology","score_opus":0.08122468068329128,"score_gpt":0.4172462930282494,"score_spread":0.3360216123449581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975385958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91736794,0.011816703,0.041669775,0.0018331597,0.0001251968,0.0003398052,0.0021701488,0.00029790396,0.024379222],"genre_scores_gemma":[0.9744211,0.0050927456,0.014804016,0.0005475979,0.00012454954,0.00011407692,0.00064111414,0.000062995954,0.0041918354],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999157,0.000018176033,0.000013243488,0.000015734742,0.000018349014,0.000018731196],"domain_scores_gemma":[0.99984634,0.00004224919,0.000021252412,0.000009153328,0.00006425874,0.000016753813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036536093,0.00039650337,0.00023126445,0.001295615,0.00030994404,0.00038298388,0.00025989587,0.00087432057,0.0024113525],"category_scores_gemma":[0.0009287294,0.0002181318,0.00024181469,0.0004409754,0.00021048653,0.00061677926,0.00022087702,0.00036386936,0.000530704],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026143026,0.00032034845,0.04647662,0.0014412367,0.00025958125,0.012712352,0.0007198666,0.00415688,0.73334414,0.0021414792,0.0055580107,0.19025515],"study_design_scores_gemma":[0.0002395192,0.0028037825,0.44721782,0.00078392844,0.000928893,0.078823686,0.0012441893,0.039594676,0.3955762,0.005953372,0.026652073,0.00018190285],"about_ca_topic_score_codex":0.0037159706,"about_ca_topic_score_gemma":0.004939984,"teacher_disagreement_score":0.0037159706,"about_ca_system_score_codex":0.00027326067,"about_ca_system_score_gemma":0.00047501162,"threshold_uncertainty_score":0.008066833},"labels":[],"label_agreement":null},{"id":"W1975446567","doi":"10.1002/jmri.10205","title":"Serial quantitative diffusion tensor MRI of the premature brain: Development in newborns with and without injury","year":2002,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":328,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research; National Institutes of Health","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Medicine; Effective diffusion coefficient; Radiology","score_opus":0.0266579262998272,"score_gpt":0.30540103550898806,"score_spread":0.27874310920916084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975446567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996941,0.00010798193,0.000063254796,0.000006443036,0.0000016162214,0.0000025687425,0.000058604037,0.0000020516964,0.00006323718],"genre_scores_gemma":[0.9994754,0.0001174538,0.00017286651,0.000007227563,0.0000042468964,0.000008766152,0.00014143968,0.0000018618331,0.000070698225],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980336,0.000046214274,0.000027644612,0.000048295296,0.000044813514,0.000029707284],"domain_scores_gemma":[0.99868864,0.00026824776,0.000565185,0.00007512415,0.00019654552,0.00020632867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054403045,0.00032060652,0.0003296992,0.0008725783,0.0002514034,0.0003028374,0.00021445626,0.0003235361,0.00041898797],"category_scores_gemma":[0.005014834,0.00014026382,0.00018874399,0.00032799962,0.00031485254,0.00033832583,0.0002629887,0.00027466592,0.00013924237],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003997415,0.00002935683,0.9870595,0.000026418464,0.000022685977,0.0015047463,0.000318489,0.00007398643,0.0050830427,0.000022743601,0.000051684456,0.0054076225],"study_design_scores_gemma":[0.0000040233404,0.00041561888,0.9943711,0.00000718998,0.000016028402,0.0037899865,0.00014125218,0.000098249,0.001026009,0.00001911409,0.000107185624,0.000004236283],"about_ca_topic_score_codex":0.0018054148,"about_ca_topic_score_gemma":0.0011978847,"teacher_disagreement_score":0.0018054148,"about_ca_system_score_codex":0.0002818943,"about_ca_system_score_gemma":0.00022007085,"threshold_uncertainty_score":0.003589809},"labels":[],"label_agreement":null},{"id":"W1975596980","doi":"10.1002/mrm.24781","title":"Constrained diffusion kurtosis imaging using ternary quartics &amp; MLE","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Université de Sherbrooke","keywords":"Kurtosis; Ternary operation; Diffusion; Chemistry; Nuclear magnetic resonance; Mathematics; Statistics; Computer science; Physics; Thermodynamics","score_opus":0.06393749245486953,"score_gpt":0.35592426035750097,"score_spread":0.29198676790263145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975596980","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018433826,0.00008015391,0.99714845,0.000057671892,0.000011497499,0.000014197217,0.000021544472,0.00021026428,0.0006128556],"genre_scores_gemma":[0.12014764,0.0003102474,0.876977,0.00009794063,0.00004453679,0.00010551438,0.00016966934,0.00022194658,0.0019254009],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993247,0.00019689064,0.000053922162,0.00011105231,0.00028486765,0.000028648688],"domain_scores_gemma":[0.99846625,0.00079327245,0.00025021177,0.00016243482,0.00028245672,0.000045418914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013589672,0.0012385867,0.00090013957,0.001025975,0.0004288839,0.0014432824,0.0010298289,0.0010117071,0.003314873],"category_scores_gemma":[0.0065051476,0.0004614074,0.0007963496,0.0013105245,0.0009525465,0.0017889972,0.0016039632,0.0013177891,0.0011441784],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022102917,0.000097550444,0.0012847338,0.00049213873,0.00011237843,0.00031861864,0.00019049017,0.45477372,0.04044918,0.054501504,0.0031154994,0.4444431],"study_design_scores_gemma":[0.000008708672,0.000025560645,0.00017186196,0.0000150135365,0.000010511358,0.00013037116,0.000008236104,0.9830709,0.007033889,0.0074769356,0.0020278667,0.00002010814],"about_ca_topic_score_codex":0.001121772,"about_ca_topic_score_gemma":0.0013566104,"teacher_disagreement_score":0.003314873,"about_ca_system_score_codex":0.000592599,"about_ca_system_score_gemma":0.0011456923,"threshold_uncertainty_score":0.011089385},"labels":[],"label_agreement":null},{"id":"W1975760079","doi":"10.1016/j.neurobiolaging.2014.05.037","title":"Diffusion weighted imaging-based maximum density path analysis and classification of Alzheimer's disease","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Takeda Pharmaceuticals North America; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; U.S. National Library of Medicine; IXICO; Genentech Foundation; Servier; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; Roche; Elan; Novartis; U.S. Department of Defense; Eli Lilly and Company; AstraZeneca; Bristol-Myers Squibb Foundation; Merck; Alzheimer's Drug Discovery Foundation; Eisai; Abbott Fund; Alzheimer's Association; Bayer HealthCare","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Tractography; CTL*; Multiple sclerosis; Medicine; Artificial intelligence; Neuroscience; Psychology; Computer science; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.028035943194510245,"score_gpt":0.30318512917007656,"score_spread":0.2751491859755663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975760079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7871097,0.0035127304,0.20565698,0.000795382,0.000086944216,0.00016988291,0.0010942017,0.00043685772,0.0011373471],"genre_scores_gemma":[0.857827,0.001664087,0.1380275,0.000042180305,0.000059657155,0.00008454623,0.0008002718,0.00004542582,0.0014493794],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998091,0.00008340693,0.000017317714,0.00003653302,0.000036657897,0.00001700222],"domain_scores_gemma":[0.999297,0.00035252472,0.00009680013,0.000051106254,0.00015797764,0.00004446803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001423151,0.0004746927,0.00044227287,0.002137552,0.00036078537,0.00088385737,0.0004964546,0.0006410274,0.0009122481],"category_scores_gemma":[0.003941425,0.00022907821,0.0004412622,0.0009299797,0.00034464546,0.0008209649,0.00039704423,0.0006394324,0.00024947122],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009848565,0.00034559975,0.13524434,0.00029605458,0.00037770925,0.00052441336,0.00034517486,0.09159302,0.015297787,0.0074662254,0.0069193165,0.7406055],"study_design_scores_gemma":[0.00004941304,0.00013503358,0.05366052,0.000048593727,0.00009286069,0.0006061229,0.00016081241,0.92660606,0.0028220187,0.01421573,0.0015668555,0.000036046353],"about_ca_topic_score_codex":0.0074717314,"about_ca_topic_score_gemma":0.006649829,"teacher_disagreement_score":0.0074717314,"about_ca_system_score_codex":0.0004039817,"about_ca_system_score_gemma":0.0012487343,"threshold_uncertainty_score":0.014856517},"labels":[],"label_agreement":null},{"id":"W1975879525","doi":"10.1117/12.878293","title":"Comparison between fourth and second order DT-MR image segmentations","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Diffusion MRI; Tensor (intrinsic definition); Segmentation; Image segmentation; Euclidean distance; Artificial intelligence; Random walker algorithm; Mathematics; Pattern recognition (psychology); Computer science; Voxel; Fractional anisotropy; Algorithm; Computer vision; Image (mathematics); Geometry; Magnetic resonance imaging","score_opus":0.04608585751868017,"score_gpt":0.3125824173644806,"score_spread":0.26649655984580045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975879525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29171255,0.0030693605,0.6887301,0.00074244005,0.00027820453,0.0002964685,0.0013004686,0.0063985884,0.00747186],"genre_scores_gemma":[0.51405644,0.0014686403,0.4759285,0.00015680442,0.00007358077,0.00015807798,0.0025263282,0.0020259449,0.0036056642],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985607,0.00029629713,0.0002120788,0.00024150156,0.0005349963,0.00015436036],"domain_scores_gemma":[0.990191,0.005007913,0.000934087,0.001388219,0.0021859263,0.00029288593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003656685,0.00094367366,0.0010473641,0.0054373587,0.000619813,0.0030886948,0.0010591551,0.0018770815,0.0029666373],"category_scores_gemma":[0.014220787,0.0004336493,0.0012118806,0.002029935,0.0007460343,0.0020678432,0.00070853374,0.0007568186,0.0011594368],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00299362,0.00027657548,0.0134611,0.0011888553,0.00053099886,0.00050598005,0.0010245848,0.36648235,0.13461027,0.01914588,0.004527516,0.4552523],"study_design_scores_gemma":[0.00007683816,0.0005145441,0.016863875,0.00010130253,0.00020095488,0.0011246466,0.00032807532,0.85958296,0.10308997,0.009274707,0.008693815,0.0001482998],"about_ca_topic_score_codex":0.004479079,"about_ca_topic_score_gemma":0.0049051475,"teacher_disagreement_score":0.0054373587,"about_ca_system_score_codex":0.0015959098,"about_ca_system_score_gemma":0.0015057952,"threshold_uncertainty_score":0.019338608},"labels":[],"label_agreement":null},{"id":"W1976238938","doi":"10.2147/ndt.s4329","title":"Bipolar disorder and neurophysiologic mechanisms","year":2008,"lang":"en","type":"article","venue":"Neuropsychiatric Disease and Treatment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; University of British Columbia","keywords":"Uncinate fasciculus; Orbitofrontal cortex; Neuroscience; Bipolar disorder; Tractography; Diffusion MRI; Corpus callosum; Cognitive psychology; Psychology; Medicine; Cognition; Fractional anisotropy; Prefrontal cortex; Magnetic resonance imaging","score_opus":0.038044536969324055,"score_gpt":0.2908950098284775,"score_spread":0.2528504728591534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976238938","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28071734,0.61087084,0.0016640777,0.036639962,0.0014993614,0.000106245025,0.00032204334,0.00006783703,0.06811229],"genre_scores_gemma":[0.78575337,0.1997784,0.0012506496,0.0047108904,0.0020812785,0.0000740636,0.00025269005,0.000015483232,0.0060832924],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99986446,0.00003501435,0.00001418293,0.00002057528,0.000030806546,0.000034992187],"domain_scores_gemma":[0.99977654,0.00006990075,0.00007283967,0.000011078209,0.000033734425,0.000035933404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041332596,0.00035961662,0.00033999683,0.0011017496,0.00036282104,0.0012152583,0.00034062154,0.000892244,0.0038453045],"category_scores_gemma":[0.0005843987,0.00017617743,0.00022191118,0.0005823367,0.0012334607,0.0007877084,0.00038941004,0.00092545367,0.0003569834],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002413112,0.0010175622,0.15553626,0.0021458322,0.0010202816,0.023967052,0.0034387151,0.0018679423,0.024266528,0.11405954,0.059147242,0.61112],"study_design_scores_gemma":[0.00064056,0.0007250865,0.6803401,0.0025855827,0.00025731543,0.018541014,0.003589786,0.0013262173,0.00083909766,0.22790334,0.06312911,0.00012279906],"about_ca_topic_score_codex":0.004865383,"about_ca_topic_score_gemma":0.007682866,"teacher_disagreement_score":0.004865383,"about_ca_system_score_codex":0.0011524765,"about_ca_system_score_gemma":0.0005110007,"threshold_uncertainty_score":0.012863815},"labels":[],"label_agreement":null},{"id":"W1976839446","doi":"10.1007/s00429-010-0271-z","title":"Histochemical visualization and diffusion MRI at 7 Tesla in the TgCRND8 transgenic model of Alzheimer’s disease","year":2010,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg; St. Boniface Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Effective diffusion coefficient; Gliosis; Pathology; Magnetic resonance imaging; White matter; Alzheimer's disease; Neurology; Neuroscience; Atrophy; Genetically modified mouse; Neurodegeneration; Hippocampus; Medicine; Disease; Chemistry; Psychology; Transgene; Radiology","score_opus":0.03251908929101044,"score_gpt":0.3162464972375224,"score_spread":0.28372740794651197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976839446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96810895,0.0028550727,0.022442412,0.001093963,0.00021657915,0.00005891037,0.0009395199,0.00048454903,0.0038000208],"genre_scores_gemma":[0.9449124,0.0026753217,0.03912946,0.00018313985,0.00007437099,0.00017029518,0.0009616949,0.00030280964,0.011590447],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957174,0.000060848404,0.000062028,0.0001238245,0.00007685689,0.00010461044],"domain_scores_gemma":[0.99955016,0.000063431675,0.00012263852,0.000060569364,0.00009894162,0.000104340164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081335264,0.00085313915,0.0005227674,0.0014265894,0.0007671768,0.0005980383,0.0008515526,0.0011093018,0.001658467],"category_scores_gemma":[0.00037733957,0.000723868,0.00056833425,0.00043356267,0.0009819111,0.0010534804,0.00040759976,0.0020644886,0.00044149315],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003253621,0.000071689996,0.00013642282,0.00005820129,0.000018599272,0.00033422175,0.000086489155,0.00006855316,0.9973858,0.00045145978,0.00010740647,0.00095595006],"study_design_scores_gemma":[0.00012343633,0.0003625948,0.0042050984,0.000027899552,0.00010981419,0.0026870056,0.0001587076,0.0022099132,0.9863934,0.00076428225,0.002926226,0.00003159462],"about_ca_topic_score_codex":0.003691541,"about_ca_topic_score_gemma":0.004579223,"teacher_disagreement_score":0.003691541,"about_ca_system_score_codex":0.00069834024,"about_ca_system_score_gemma":0.0003628074,"threshold_uncertainty_score":0.007340133},"labels":[],"label_agreement":null},{"id":"W1977068575","doi":"10.1016/j.jocn.2011.12.031","title":"Correlation between cognitive function and the association fibers in patients with Alzheimer’s disease using diffusion tensor imaging","year":2012,"lang":"en","type":"article","venue":"Journal of Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fasciculus; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Medicine; White matter; Dementia; Neuropsychology; Boston Naming Test; Inferior longitudinal fasciculus; Clinical Dementia Rating; Cognition; Internal medicine; Mini–Mental State Examination; Audiology; Cardiology; Magnetic resonance imaging; Psychiatry; Disease; Radiology","score_opus":0.11136910572180679,"score_gpt":0.4142269644688937,"score_spread":0.30285785874708687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977068575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99925214,0.00020081835,0.00006791022,0.000037406753,0.0000062504846,0.0000030548745,0.000069111746,0.0000022614925,0.00036100575],"genre_scores_gemma":[0.9995741,0.000088957124,0.00009227354,0.000012059284,0.000015129915,0.0000029315465,0.00010424887,0.0000013396572,0.00010894277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997247,0.00005358473,0.00007409347,0.000063059764,0.000045060555,0.000039487997],"domain_scores_gemma":[0.99813193,0.00053303,0.0007445434,0.00011667339,0.00024220196,0.00023165399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007551717,0.0005638312,0.00043895518,0.001680772,0.00060842576,0.0007203285,0.00032596153,0.00066848734,0.0014498159],"category_scores_gemma":[0.0029023176,0.00034811092,0.00045371955,0.0010930732,0.00045981578,0.00082179887,0.0004193778,0.0007377115,0.00022782576],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046730944,0.000067272216,0.9964156,0.00001003353,0.0001394789,0.00028250745,0.00008910404,0.00006745814,0.00077381975,0.000028047618,0.00004249552,0.0016168376],"study_design_scores_gemma":[0.000012127639,0.00011877672,0.99818414,0.0000037776044,0.00006548623,0.0008434258,0.00013166206,0.0003323043,0.00014623586,0.000098657445,0.00005674554,0.000006652767],"about_ca_topic_score_codex":0.0026952815,"about_ca_topic_score_gemma":0.0035610993,"teacher_disagreement_score":0.0026952815,"about_ca_system_score_codex":0.00028908148,"about_ca_system_score_gemma":0.00029790335,"threshold_uncertainty_score":0.005359173},"labels":[],"label_agreement":null},{"id":"W1977168501","doi":"10.1016/j.schres.2015.01.019","title":"Abnormal white matter integrity in antipsychotic-naïve first-episode psychosis patients assessed by a DTI principal component analysis","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"White matter; Fractional anisotropy; Psychosis; Diffusion MRI; Antipsychotic; Psychology; Internal medicine; Schizophrenia (object-oriented programming); Medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.1532352842077878,"score_gpt":0.4333879517635373,"score_spread":0.2801526675557495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977168501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99939334,0.00007786229,0.00010765202,0.00002517572,0.0000019149072,0.0000057879915,0.00010348805,0.000004974642,0.0002798028],"genre_scores_gemma":[0.9994672,0.00007002388,0.00021808247,0.000009357974,0.00000280819,0.0000041859753,0.00013559696,0.0000019508798,0.00009080042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999243,0.000016573978,0.000012845005,0.000017010474,0.000016434715,0.00001282394],"domain_scores_gemma":[0.99976116,0.00005383224,0.000088857174,0.00001734513,0.000034374,0.000044426874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022321154,0.00029596643,0.00027853827,0.0006344084,0.0003252941,0.00041635893,0.00014460237,0.00025074676,0.0008773378],"category_scores_gemma":[0.001124164,0.00016211397,0.00018018961,0.00040010345,0.00017825312,0.0002595717,0.00020658177,0.00025486617,0.00012389626],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003215726,0.00021054801,0.9307707,0.00006201131,0.00027904363,0.0016263623,0.0005235153,0.0007997426,0.03710108,0.00015134401,0.00046139804,0.024798525],"study_design_scores_gemma":[0.000017706321,0.00018617974,0.99670345,0.0000045849088,0.000051447678,0.0008427146,0.00010517661,0.001077369,0.00083794905,0.00008785765,0.000079821235,0.0000057277375],"about_ca_topic_score_codex":0.006653332,"about_ca_topic_score_gemma":0.01068,"teacher_disagreement_score":0.006653332,"about_ca_system_score_codex":0.0003543301,"about_ca_system_score_gemma":0.00042808295,"threshold_uncertainty_score":0.013229251},"labels":[],"label_agreement":null},{"id":"W1977223300","doi":"10.1016/j.nicl.2015.03.007","title":"Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke","year":2015,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Mitacs; Michael Smith Health Research BC","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Voxel; White matter; Corticospinal tract; Corpus callosum; Stroke (engine); Effective diffusion coefficient; Neuroscience; Magnetic resonance imaging; Medicine; Psychology; Physics; Radiology","score_opus":0.17217852856447868,"score_gpt":0.40780868229600287,"score_spread":0.23563015373152418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977223300","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97615993,0.0013187327,0.021470498,0.00013347142,0.000020813153,0.00009558268,0.000183403,0.000049690843,0.00056792767],"genre_scores_gemma":[0.9800765,0.00084246445,0.018244036,0.000039255672,0.000025314203,0.00009962016,0.0002452747,0.000025410225,0.00040205647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989767,0.0005563072,0.000098561264,0.00015970177,0.00014316283,0.00006556936],"domain_scores_gemma":[0.9980349,0.0009936646,0.0003129825,0.00019396753,0.00031509,0.00014946311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036931953,0.000561418,0.0004958653,0.002400326,0.00036231813,0.0010256657,0.00030375837,0.00061020255,0.0007829585],"category_scores_gemma":[0.0056641363,0.00023633201,0.000460139,0.0010025449,0.0007048421,0.0009788843,0.0006894561,0.00034131814,0.00014656538],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013803397,0.0007627794,0.6235581,0.0016606954,0.002483282,0.00075221295,0.003032955,0.014835822,0.08449373,0.0041609025,0.00088191585,0.24957418],"study_design_scores_gemma":[0.00022725882,0.0028831104,0.92361706,0.00012075404,0.0003510544,0.001087257,0.001045739,0.057834327,0.0062025446,0.005314747,0.0012166579,0.00009950838],"about_ca_topic_score_codex":0.008372215,"about_ca_topic_score_gemma":0.018212235,"teacher_disagreement_score":0.008372215,"about_ca_system_score_codex":0.00073177076,"about_ca_system_score_gemma":0.00097500527,"threshold_uncertainty_score":0.019531727},"labels":[],"label_agreement":null},{"id":"W1977322234","doi":"10.1016/j.pain.2013.08.029","title":"Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia","year":2013,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research; Physicians' Services Incorporated Foundation","keywords":"Trigeminal neuralgia; White matter; Diffusion MRI; Medicine; Trigeminal nerve; Fractional anisotropy; Corpus callosum; Cingulum (brain); Anatomy; Fasciculus; Magnetic resonance imaging; Anesthesia; Radiology","score_opus":0.01801262259948639,"score_gpt":0.28827368561835376,"score_spread":0.2702610630188674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977322234","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993048,0.00021868928,0.00016272684,0.0000073244146,0.0000015586179,0.000005288701,0.000037716363,0.00000450273,0.0002574711],"genre_scores_gemma":[0.99959046,0.00009353627,0.00017470744,0.000004829967,0.000004396612,0.0000035489857,0.00006137015,0.0000013845547,0.00006575559],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998778,0.000015920676,0.00001886017,0.000037056594,0.00003018259,0.000020227199],"domain_scores_gemma":[0.99979895,0.000028014856,0.00010658078,0.000022169967,0.000018787776,0.000025509276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025339617,0.00030825223,0.00018119026,0.001221442,0.00023075279,0.00026098892,0.00015281029,0.00022362972,0.00088824664],"category_scores_gemma":[0.0007087718,0.00013512929,0.00012416579,0.0005689809,0.00044692034,0.00025182992,0.00024669294,0.00014364177,0.00008130924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017992074,0.000111361755,0.8981599,0.00012005589,0.00016620601,0.0051374966,0.0006700194,0.00047105737,0.067073785,0.00019065973,0.00014422777,0.025956042],"study_design_scores_gemma":[0.000007008682,0.00008231296,0.996046,0.000004734115,0.000019996689,0.002700183,0.00006926107,0.00023020955,0.00071455975,0.000060090362,0.000062987616,0.000002793674],"about_ca_topic_score_codex":0.0022157182,"about_ca_topic_score_gemma":0.0021101607,"teacher_disagreement_score":0.0022157182,"about_ca_system_score_codex":0.00024555952,"about_ca_system_score_gemma":0.00010592386,"threshold_uncertainty_score":0.0044056773},"labels":[],"label_agreement":null},{"id":"W1977436886","doi":"10.1016/j.neuroimage.2012.08.086","title":"Quantitative MRI in the very preterm brain: Assessing tissue organization and myelination using magnetization transfer, diffusion tensor and T1 imaging","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children; Toronto Centre for Phenogenomics","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Magnetization transfer; Concordance; Fractional anisotropy; Gestational age; Magnetic resonance imaging; Nuclear medicine; Psychology; Medicine; Radiology; Biology; Internal medicine","score_opus":0.05941181811663023,"score_gpt":0.36882342910063143,"score_spread":0.3094116109840012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977436886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9538788,0.008225039,0.03515431,0.00031270806,0.000036073492,0.00009329397,0.00038734145,0.00011680045,0.0017956502],"genre_scores_gemma":[0.9752367,0.003954814,0.01968876,0.00008298935,0.00003335207,0.00008392757,0.00012649779,0.000063093554,0.00072987634],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99960405,0.00013862556,0.00005277604,0.00007642667,0.000098997356,0.00002912455],"domain_scores_gemma":[0.9987305,0.0004590353,0.00034016484,0.00010755332,0.00024908123,0.0001137171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021207076,0.00077237294,0.00050050643,0.003042791,0.0004440029,0.0011444892,0.00088384724,0.001146866,0.0006624455],"category_scores_gemma":[0.0053670597,0.00040552914,0.00025064588,0.00094951695,0.00093251385,0.001226923,0.00069271494,0.00059397926,0.00018153143],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0047171367,0.0003214169,0.13644126,0.0029705446,0.00042526438,0.009312169,0.0016341447,0.0041209767,0.6218225,0.0033290037,0.0009980804,0.21390757],"study_design_scores_gemma":[0.00015516931,0.0038031768,0.5652827,0.0006435368,0.0009980962,0.048445325,0.0029379104,0.022756265,0.33368397,0.016241083,0.0048025656,0.00025017204],"about_ca_topic_score_codex":0.0021065963,"about_ca_topic_score_gemma":0.0018320314,"teacher_disagreement_score":0.003042791,"about_ca_system_score_codex":0.00053600833,"about_ca_system_score_gemma":0.00063067186,"threshold_uncertainty_score":0.011215508},"labels":[],"label_agreement":null},{"id":"W1977585542","doi":"10.1016/j.neuroimage.2014.03.026","title":"Improved DTI registration allows voxel-based analysis that outperforms Tract-Based Spatial Statistics","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":180,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Dana Foundation; Canadian Institutes of Health Research; Mayo Foundation for Medical Education and Research; Mayo Clinic","keywords":"Voxel; Computer science; Artificial intelligence; Projection (relational algebra); Pipeline (software); Skeleton (computer programming); Pattern recognition (psychology); Diffusion MRI; Computer vision; Algorithm; Medicine; Magnetic resonance imaging","score_opus":0.055837149039628026,"score_gpt":0.3331731859203047,"score_spread":0.27733603688067665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977585542","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022752127,0.00021889416,0.96623814,0.00024240493,0.00004666134,0.00007497862,0.00043979546,0.008465146,0.0015218934],"genre_scores_gemma":[0.12957989,0.00025011614,0.8651825,0.000102422455,0.000048821817,0.00013868095,0.0009859867,0.0021045897,0.0016070153],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998292,0.00042556773,0.00015124574,0.00046784536,0.000578315,0.00008498182],"domain_scores_gemma":[0.9965417,0.0010740235,0.00044907644,0.0013074256,0.0005562319,0.00007156739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031781844,0.0012429701,0.0013861246,0.0019613507,0.000569805,0.0017892579,0.0014863337,0.000929014,0.0055241957],"category_scores_gemma":[0.013363049,0.00081393216,0.0012857162,0.00330561,0.00089918845,0.002468238,0.001887819,0.001442846,0.0029306738],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065974344,0.00023097832,0.008504677,0.0005269061,0.000678816,0.0003976647,0.0004015423,0.09728231,0.20445989,0.023188105,0.014709226,0.6489601],"study_design_scores_gemma":[0.0001418952,0.0003841836,0.018161485,0.000053578042,0.00035944209,0.0017928119,0.00009555619,0.7963109,0.13091464,0.026016971,0.025601296,0.00016726804],"about_ca_topic_score_codex":0.0028820182,"about_ca_topic_score_gemma":0.008025152,"teacher_disagreement_score":0.0055241957,"about_ca_system_score_codex":0.0007587329,"about_ca_system_score_gemma":0.0018816082,"threshold_uncertainty_score":0.018480241},"labels":[],"label_agreement":null},{"id":"W1978373547","doi":"10.1007/s10334-003-0020-x","title":"Water self-diffusion tensor changes in an avian genetic developmental model of epilepsy","year":2003,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Siemens Canada","keywords":"Fractional anisotropy; Juvenile; Tectum; Diffusion MRI; Juvenile myoclonic epilepsy; Epilepsy; Anisotropy; Psychology; Stimulation; Endocrinology; Internal medicine; Neuroscience; Medicine; Biology; Physics; Central nervous system; Magnetic resonance imaging; Optics; Midbrain; Ecology","score_opus":0.04227321376209335,"score_gpt":0.3198672680626729,"score_spread":0.27759405430057954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978373547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99724376,0.000104102575,0.0017069957,0.00014960693,0.000014516139,0.000011450634,0.00017110107,0.000047646365,0.00055093324],"genre_scores_gemma":[0.9949715,0.0003005479,0.0024559144,0.000049683917,0.000004257627,0.00002456281,0.00011850921,0.000040953735,0.002033984],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999461,0.000010740378,0.0000075942517,0.000013548576,0.000012002114,0.00000993065],"domain_scores_gemma":[0.9997423,0.000064705484,0.00010724992,0.000019890656,0.000019681545,0.000046195233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118976604,0.00035846312,0.00014880003,0.00061494124,0.00024575673,0.0001991573,0.00036090042,0.00050148513,0.001094091],"category_scores_gemma":[0.00025091704,0.00027566703,0.00015309805,0.00013717925,0.00072653015,0.00027054286,0.00020532851,0.00057598995,0.00012781072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040320205,0.00009172619,0.0008927234,0.00004565365,0.000014770997,0.00140686,0.0001213617,0.0023939507,0.99079376,0.001866079,0.00019910518,0.0017707171],"study_design_scores_gemma":[0.00032761245,0.0014342361,0.03461914,0.00004934319,0.00021906027,0.006216565,0.0007133444,0.032215387,0.91656977,0.0034457038,0.004080818,0.00010912981],"about_ca_topic_score_codex":0.005551039,"about_ca_topic_score_gemma":0.009129437,"teacher_disagreement_score":0.005551039,"about_ca_system_score_codex":0.00055942585,"about_ca_system_score_gemma":0.00027312053,"threshold_uncertainty_score":0.011037469},"labels":[],"label_agreement":null},{"id":"W1978566928","doi":"10.1016/j.brainres.2010.04.064","title":"Sex differences in the human corpus callosum microstructure: A combined T2 myelin-water and diffusion tensor magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University of Toronto; Hospital for Sick Children","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Magnetic resonance imaging; Splenium; Nuclear magnetic resonance; Tractography; Psychology; Anatomy; Medicine; Radiology; Physics","score_opus":0.0805886032352576,"score_gpt":0.40131832234716747,"score_spread":0.32072971911190984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978566928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99861383,0.00044839882,0.00019246964,0.00004623154,0.000012113472,0.000004413597,0.0001345115,0.0000035064413,0.00054435304],"genre_scores_gemma":[0.99844766,0.00029459846,0.00019448016,0.000051789488,0.000022811433,0.0000050955528,0.000102519225,0.00001643516,0.00086460565],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999325,0.000011856537,0.0000060976718,0.000026366863,0.0000143168745,0.000008812223],"domain_scores_gemma":[0.9996791,0.00008076661,0.00008927243,0.00005569094,0.00004713038,0.000048165846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025442042,0.00017654707,0.00020533595,0.00038384195,0.00020931054,0.0003885338,0.00016099944,0.00033813686,0.0023563674],"category_scores_gemma":[0.0008286861,0.00018512511,0.00016036665,0.00032743538,0.00036101448,0.0002966478,0.00020929636,0.00016960294,0.00027861766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0077632032,0.00040853143,0.4558711,0.00028359392,0.0008130101,0.0044482523,0.004054599,0.00033653819,0.4447132,0.0011182206,0.0013065147,0.07888325],"study_design_scores_gemma":[0.000046396002,0.00032709932,0.98934644,0.000009127292,0.000105853665,0.0029916584,0.0003884056,0.00023851421,0.0051469347,0.0003190872,0.0010630284,0.000017569122],"about_ca_topic_score_codex":0.0014869955,"about_ca_topic_score_gemma":0.0017968914,"teacher_disagreement_score":0.0023563674,"about_ca_system_score_codex":0.00011648001,"about_ca_system_score_gemma":0.00017151283,"threshold_uncertainty_score":0.007882893},"labels":[],"label_agreement":null},{"id":"W1979259237","doi":"10.3171/foc/2008/25/9/e3","title":"Advances in neuroimaging in patients with epilepsy","year":2008,"lang":"en","type":"review","venue":"Neurosurgical FOCUS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Neuroimaging; Magnetoencephalography; Diffusion MRI; Context (archaeology); Epilepsy; White matter; Tractography; Magnetic resonance imaging; Neuroscience; Epilepsy surgery; Medicine; Psychology; Radiology; Electroencephalography","score_opus":0.05241057053761931,"score_gpt":0.36225222530215495,"score_spread":0.3098416547645356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979259237","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018205038,0.99757105,0.00020070643,0.00040125233,0.0001263077,0.0000029439343,0.000009857499,0.000009038963,0.001496751],"genre_scores_gemma":[0.001881079,0.9967379,0.0003535006,0.00024003345,0.00034300538,0.0000054684865,0.000022409611,0.0000021545266,0.00041442845],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997392,0.00006532033,0.000045684556,0.000048435548,0.000082861356,0.000018521516],"domain_scores_gemma":[0.9994516,0.000293371,0.00008811039,0.000019489593,0.00011653754,0.00003083703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005993576,0.0010053138,0.0013599104,0.0025345471,0.00018979104,0.0006837301,0.0007008748,0.0010221998,0.0027825255],"category_scores_gemma":[0.0015469687,0.00019085649,0.00044425437,0.0024970877,0.0005535706,0.0013547546,0.0005524873,0.0012240963,0.0019640566],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025688783,0.000029191911,0.000989951,0.005065366,0.0000483118,0.001246191,0.000058122077,0.00013638208,0.0005971702,0.0011191913,0.020207094,0.97047734],"study_design_scores_gemma":[0.000028285684,0.00008376832,0.00861298,0.007231625,0.00022904138,0.037976217,0.00022050993,0.000193089,0.00070292363,0.0040222676,0.94065857,0.000040735424],"about_ca_topic_score_codex":0.0014482739,"about_ca_topic_score_gemma":0.002545507,"teacher_disagreement_score":0.0027825255,"about_ca_system_score_codex":0.00046875104,"about_ca_system_score_gemma":0.0008666286,"threshold_uncertainty_score":0.009308457},"labels":[],"label_agreement":null},{"id":"W1979558268","doi":"10.1155/2013/350623","title":"Cognitive Intraindividual Variability and White Matter Integrity in Aging","year":2013,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Neuropsychology; Effects of sleep deprivation on cognitive performance; Cognition; Neuroimaging; Audiology; Tractography; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.05593590842472349,"score_gpt":0.3424525621474851,"score_spread":0.2865166537227616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979558268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993148,0.00014706788,0.00024469776,0.0000041920957,0.0000016948942,0.0000028802813,0.00007547051,0.000006966344,0.0002023258],"genre_scores_gemma":[0.9994925,0.000039676757,0.00021306219,0.0000048001393,0.0000040884674,0.0000038464964,0.00013419735,0.00000262967,0.000105145235],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981433,0.000031968477,0.00002535014,0.00006959263,0.000039578823,0.000019170946],"domain_scores_gemma":[0.99887127,0.00022786934,0.0005249283,0.00016692962,0.00011044523,0.00009853921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067490345,0.00029753294,0.00030456248,0.0009282716,0.00020004531,0.00037519404,0.00015684366,0.00026919978,0.00047445568],"category_scores_gemma":[0.0020503532,0.00015622796,0.00013689752,0.00042603276,0.0002640268,0.00030165334,0.00034408818,0.00022657518,0.00011227809],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005250875,0.000056366553,0.9756625,0.000026214006,0.00023361617,0.00013176158,0.0004584614,0.00030332562,0.011398134,0.00006430335,0.00008186375,0.011058197],"study_design_scores_gemma":[0.000001027181,0.000056785164,0.9992204,9.790631e-7,0.000008358169,0.00013634426,0.000031072585,0.0001362855,0.00031788117,0.00006113775,0.000027646203,0.0000021160572],"about_ca_topic_score_codex":0.0010712326,"about_ca_topic_score_gemma":0.0018609442,"teacher_disagreement_score":0.0010712326,"about_ca_system_score_codex":0.00010771872,"about_ca_system_score_gemma":0.00007064331,"threshold_uncertainty_score":0.0035692453},"labels":[],"label_agreement":null},{"id":"W1979588596","doi":"10.1016/j.neuroimage.2010.03.076","title":"Spectral-based automatic labeling and refining of human cortical sulcal curves using expert-provided examples","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Korea Science and Engineering Foundation","keywords":"Artificial intelligence; Pattern recognition (psychology); Preprocessor; Set (abstract data type); Mathematics; Data set; Computer science; Matching (statistics); Statistics","score_opus":0.12950641096684598,"score_gpt":0.3993977662580669,"score_spread":0.2698913552912209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979588596","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11118553,0.0002636389,0.87967664,0.00018004264,0.0000295362,0.00019053889,0.00035449068,0.005912981,0.002206626],"genre_scores_gemma":[0.3410015,0.00023431185,0.65533745,0.00004068352,0.000016745886,0.00009491952,0.0007333787,0.0013603377,0.001180606],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99929416,0.00020339667,0.000053813146,0.00020207942,0.00016593077,0.00008050423],"domain_scores_gemma":[0.99543864,0.0017880211,0.00022577336,0.0009277122,0.0015192926,0.00010053854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002046879,0.0011006278,0.0008164863,0.0024730465,0.00082922715,0.0018685901,0.0011486307,0.0017349503,0.0035654996],"category_scores_gemma":[0.008828717,0.00062293245,0.0010949188,0.0012185995,0.0007835515,0.0012542539,0.0009471221,0.0009326711,0.00134063],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010727585,0.00021105372,0.0050992267,0.0010611572,0.00014514297,0.00087654626,0.001471259,0.22982012,0.12163555,0.010565919,0.0056156497,0.6224255],"study_design_scores_gemma":[0.00004682334,0.0000854568,0.0018861206,0.00007325712,0.000049872375,0.0009657807,0.00022778616,0.9240544,0.06175849,0.0067745564,0.0040182155,0.000059314847],"about_ca_topic_score_codex":0.005324007,"about_ca_topic_score_gemma":0.0106079625,"teacher_disagreement_score":0.005324007,"about_ca_system_score_codex":0.0005909458,"about_ca_system_score_gemma":0.0011341063,"threshold_uncertainty_score":0.011927724},"labels":[],"label_agreement":null},{"id":"W1979696665","doi":"10.1016/j.nicl.2014.05.012","title":"Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Putamen; White matter; Fractional anisotropy; Diffusion MRI; Thalamus; Basal ganglia; Anatomy; Grey matter; Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Central nervous system; Radiology","score_opus":0.049143666304319995,"score_gpt":0.3918213596880391,"score_spread":0.3426776933837191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979696665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99963725,0.00010716647,0.000104359,0.000007676132,5.552051e-7,0.0000025661307,0.000054925506,0.0000027879776,0.00008256516],"genre_scores_gemma":[0.9991015,0.00018492404,0.0005644142,0.0000068075988,0.0000012379647,0.0000050295466,0.00007823854,0.0000021626201,0.00005574971],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988127,0.000020351123,0.000015441017,0.000030358444,0.000030843163,0.000021653475],"domain_scores_gemma":[0.9996859,0.000053283424,0.00016190592,0.000018599862,0.000035322733,0.000045009114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021706146,0.0002625125,0.00016012906,0.0010827802,0.00016769463,0.00019555457,0.0001011392,0.00017433177,0.0004360766],"category_scores_gemma":[0.0010773701,0.000240982,0.000111024674,0.00039772273,0.00030323377,0.0002440694,0.00027599235,0.00017825549,0.00007083651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001672137,0.000032714368,0.953948,0.00004755956,0.000033440952,0.0023307598,0.0005636863,0.0003330026,0.025267113,0.00007840812,0.000119884746,0.017078154],"study_design_scores_gemma":[0.0000027357678,0.00007080018,0.9954755,0.000006751682,0.000011909707,0.0030841443,0.00021505875,0.00014976153,0.00086441473,0.00003104749,0.00008497781,0.000002889073],"about_ca_topic_score_codex":0.0053080744,"about_ca_topic_score_gemma":0.00934589,"teacher_disagreement_score":0.0053080744,"about_ca_system_score_codex":0.00021394875,"about_ca_system_score_gemma":0.00023981625,"threshold_uncertainty_score":0.010554314},"labels":[],"label_agreement":null},{"id":"W1979757232","doi":"10.1016/j.neuroimage.2011.01.032","title":"Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":419,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Ground truth; Computer science; Diffusion MRI; Imaging phantom; Smoothness; Artificial intelligence; Diffusion; Algorithm; Data mining; Pattern recognition (psychology); Mathematics; Physics; Magnetic resonance imaging; Medicine; Optics","score_opus":0.31865904058259104,"score_gpt":0.43404562757906906,"score_spread":0.11538658699647802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979757232","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43369326,0.0016476453,0.5547625,0.00064993894,0.00017801764,0.00041139894,0.0006955337,0.0045417533,0.0034201005],"genre_scores_gemma":[0.6808708,0.00054821186,0.31344786,0.00011741614,0.00003390633,0.00015873529,0.0009835352,0.0014692036,0.0023702928],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986771,0.0005603371,0.00012564356,0.0001704727,0.00036238614,0.00010408214],"domain_scores_gemma":[0.9856741,0.010222806,0.0007274193,0.00079217704,0.002322523,0.0002609103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043359855,0.0014898231,0.0006588368,0.00183932,0.00058982434,0.0019186612,0.0009624968,0.0023679922,0.002393757],"category_scores_gemma":[0.020090345,0.00050905044,0.00055700896,0.0012627189,0.00066389504,0.0010664526,0.0008399892,0.00071358826,0.00046257977],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027542175,0.0005201299,0.005301501,0.0009378012,0.0003597986,0.000449281,0.00047317645,0.7208536,0.07169539,0.0047806744,0.0028283317,0.18904608],"study_design_scores_gemma":[0.00013201272,0.00036715658,0.0029773582,0.00006094704,0.00007593783,0.00044071543,0.00007425503,0.96034175,0.0333498,0.000925986,0.0011970962,0.00005712965],"about_ca_topic_score_codex":0.008222764,"about_ca_topic_score_gemma":0.0061640823,"teacher_disagreement_score":0.008222764,"about_ca_system_score_codex":0.0012656341,"about_ca_system_score_gemma":0.0015001312,"threshold_uncertainty_score":0.022931159},"labels":[],"label_agreement":null},{"id":"W1980193648","doi":"10.1017/s0317167100014669","title":"fMRI-Driven DTT Assessment of Corticospinal Tracts Prior to Cortex Resection","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cerebral peduncle; Diffusion MRI; Corticospinal tract; White matter; Glioma; Medicine; Magnetic resonance imaging; Tractography; Motor cortex; Cortex (anatomy); Radiology; Nuclear medicine; Neuroscience; Psychology; Internal capsule; Internal medicine","score_opus":0.07794176454895449,"score_gpt":0.3671880671293837,"score_spread":0.28924630258042916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980193648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96367425,0.00046847516,0.034600183,0.000050638708,0.000014904274,0.00007533024,0.00027425878,0.00013725125,0.0007046891],"genre_scores_gemma":[0.9799256,0.00021487166,0.01921729,0.000016794182,0.000013330485,0.000050238872,0.00023600226,0.000019162115,0.00030673717],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999126,0.000032570508,0.000009765683,0.000017554843,0.000017938111,0.000009637155],"domain_scores_gemma":[0.9996487,0.00009035138,0.00007769931,0.00003376809,0.000107098014,0.00004232463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026748946,0.00026651117,0.00015334891,0.00044698038,0.00013085936,0.00019176451,0.00013186167,0.0002640754,0.0008292446],"category_scores_gemma":[0.0016464611,0.00011229523,0.00013522041,0.00013433493,0.00012660127,0.0002128143,0.0001684851,0.0001630371,0.00019644358],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019693582,0.00021401148,0.1966109,0.00048568955,0.00014363202,0.0019080276,0.00057242956,0.017453458,0.6393699,0.00044068324,0.00084747624,0.13998447],"study_design_scores_gemma":[0.000060834795,0.002083562,0.75867784,0.000069199115,0.0001605796,0.007770056,0.0002764535,0.07016669,0.1566769,0.0008967376,0.0030706252,0.000090473965],"about_ca_topic_score_codex":0.0014118905,"about_ca_topic_score_gemma":0.0039882357,"teacher_disagreement_score":0.0014118905,"about_ca_system_score_codex":0.00013736472,"about_ca_system_score_gemma":0.00034736568,"threshold_uncertainty_score":0.0028073788},"labels":[],"label_agreement":null},{"id":"W1980234953","doi":"10.1016/j.schres.2015.01.005","title":"Effects of endurance training on brain structures in chronic schizophrenia patients and healthy controls","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Mental Health & Substance Use Services; University of British Columbia","funders":"Courant Forschungszentrum Geobiologie, Georg-August-Universität Göttingen; Georg-August-Universität Göttingen; Bristol-Myers Squibb","keywords":"Schizophrenia (object-oriented programming); Physical medicine and rehabilitation; Medicine; Endurance training; Neuroscience; Psychology; Physical therapy; Psychiatry","score_opus":0.12076892916585268,"score_gpt":0.42245545176386756,"score_spread":0.3016865225980149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980234953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99978906,0.000060156875,0.000008487577,0.000006561858,0.0000017804865,0.0000013937704,0.000033539614,5.1648556e-7,0.000098422475],"genre_scores_gemma":[0.9997609,0.00004615778,0.00001289937,0.0000053116514,0.000002382603,0.0000027167216,0.000044213244,4.5344893e-7,0.00012507729],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999949,0.000009772821,0.000003541034,0.000012456264,0.000004143854,0.000021000982],"domain_scores_gemma":[0.99982685,0.000040726336,0.000030136183,0.000008868002,0.0000121293415,0.00008128425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011679064,0.00024015763,0.0002343529,0.00029622557,0.00024227786,0.00019833524,0.000099997706,0.0002106616,0.0019342556],"category_scores_gemma":[0.00033754666,0.00009949578,0.00014602958,0.00012821353,0.00028886055,0.00015439473,0.0002499762,0.00019655713,0.0000944374],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.09749048,0.0028105525,0.72562784,0.00021141965,0.00058791763,0.0018606802,0.0017102739,0.0006650699,0.13539234,0.00020087339,0.00031496782,0.033127647],"study_design_scores_gemma":[0.00008772877,0.0016543387,0.99695694,0.000004068264,0.000050587285,0.00014306455,0.0003535501,0.000114584225,0.00054069643,0.000042381,0.000048677626,0.0000033567387],"about_ca_topic_score_codex":0.005663068,"about_ca_topic_score_gemma":0.0060136346,"teacher_disagreement_score":0.005663068,"about_ca_system_score_codex":0.0002388123,"about_ca_system_score_gemma":0.00014323214,"threshold_uncertainty_score":0.0112602115},"labels":[],"label_agreement":null},{"id":"W1980602340","doi":"10.1111/j.1749-6632.2002.tb07596.x","title":"Is the Cerebellum Important for Podokinetic Adaptation?","year":2002,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Deafness and Other Communication Disorders","keywords":"Medicine; Health science; Library science; Medical education","score_opus":0.30922424093643996,"score_gpt":0.416656914594485,"score_spread":0.10743267365804504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980602340","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8146945,0.057654306,0.058653243,0.029517567,0.0033864668,0.00010662313,0.0007784826,0.0009870892,0.034221783],"genre_scores_gemma":[0.9844483,0.007138099,0.0031938402,0.0008769714,0.0004902424,0.000057793903,0.00013498867,0.00009623416,0.0035635824],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999617,0.000052857362,0.000034285298,0.00010839278,0.000059934664,0.0001275194],"domain_scores_gemma":[0.99893457,0.000281024,0.00032711437,0.00018978657,0.0001264427,0.00014107802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067216315,0.0006735579,0.0010531559,0.00065718306,0.0006480375,0.0019762039,0.0010146367,0.002214269,0.0047809794],"category_scores_gemma":[0.0034815893,0.00042720832,0.0008082954,0.00047780309,0.0025910346,0.0036890232,0.0009025748,0.0015141215,0.0011457033],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005784598,0.00060804194,0.07888795,0.0020541877,0.0010660335,0.007855445,0.001399762,0.0060393903,0.37055525,0.09725208,0.011600618,0.41689667],"study_design_scores_gemma":[0.0013424964,0.0021470706,0.61005145,0.0012825439,0.0013436998,0.009446436,0.002563382,0.024673702,0.12300251,0.16226843,0.061399285,0.000479004],"about_ca_topic_score_codex":0.005353121,"about_ca_topic_score_gemma":0.0043652495,"teacher_disagreement_score":0.005353121,"about_ca_system_score_codex":0.00083569053,"about_ca_system_score_gemma":0.0017514745,"threshold_uncertainty_score":0.015993953},"labels":[],"label_agreement":null},{"id":"W1980949712","doi":"10.1117/12.911707","title":"Rician compressed sensing for fast and stable signal reconstruction in diffusion MRI","year":2012,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Undersampling; Computer science; Rician fading; Compressed sensing; Noise (video); Voxel; Algorithm; Decoding methods; Gaussian; Signal reconstruction; Reconstruction algorithm; Artificial intelligence; Stability (learning theory); Iterative reconstruction; Pattern recognition (psychology); Signal processing; Machine learning; Digital signal processing; Image (mathematics)","score_opus":0.022978919572354924,"score_gpt":0.2703057710605753,"score_spread":0.24732685148822037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980949712","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043288725,0.0011434186,0.9917795,0.0003657654,0.000055475677,0.000035529294,0.000064374275,0.00020958019,0.0020175811],"genre_scores_gemma":[0.23062576,0.0043844627,0.76022965,0.00027255388,0.0002467971,0.00018684147,0.00037678046,0.00025013837,0.003426953],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933475,0.00021989712,0.00003788997,0.00007220047,0.00030249238,0.00003278903],"domain_scores_gemma":[0.998626,0.0008888575,0.00011539847,0.00013913223,0.00019426704,0.000036354155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014810432,0.0007487658,0.0006218016,0.000718585,0.00035164724,0.0007932989,0.00065168174,0.0009293911,0.0017518522],"category_scores_gemma":[0.0057120626,0.00029369915,0.0005639658,0.0010995808,0.0009882767,0.0010892977,0.0010890736,0.0016780149,0.00067599164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019755989,0.000055687855,0.00048426253,0.0003827091,0.000041120038,0.0003041209,0.00031638503,0.5485808,0.033261474,0.2694759,0.004000021,0.14289989],"study_design_scores_gemma":[0.00000784506,0.00003666172,0.00011687417,0.000025131836,0.000005115546,0.00008015786,0.000015430076,0.9714035,0.004124033,0.021343952,0.002821913,0.000019390378],"about_ca_topic_score_codex":0.0024533945,"about_ca_topic_score_gemma":0.0020350823,"teacher_disagreement_score":0.0024533945,"about_ca_system_score_codex":0.0006797658,"about_ca_system_score_gemma":0.0009784978,"threshold_uncertainty_score":0.007832587},"labels":[],"label_agreement":null},{"id":"W1981036581","doi":"10.1016/j.pscychresns.2011.06.017","title":"Progressive membrane phospholipid changes in first episode schizophrenia with high field magnetic resonance spectroscopy","year":2012,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Thalamus; Hippocampus; Internal medicine; Anterior cingulate cortex; Schizophrenia (object-oriented programming); Endocrinology; Cingulate cortex; Phospholipid; Gyrus; Neuroscience; Psychology; Medicine; Chemistry; Central nervous system; Psychiatry; Biochemistry; Membrane","score_opus":0.055889709712357995,"score_gpt":0.3798581099472489,"score_spread":0.3239684002348909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981036581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99757713,0.00042216104,0.00031369217,0.00019498814,0.00002161353,0.000023955708,0.00009518891,0.000025142337,0.0013262052],"genre_scores_gemma":[0.9992849,0.00021336398,0.00012795438,0.00004440723,0.000021286145,0.0000039776914,0.000067281595,0.000005377994,0.00023142404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979466,0.00002639948,0.00003211832,0.000025745992,0.000060902676,0.00006020267],"domain_scores_gemma":[0.9990446,0.0002665277,0.00029666867,0.00006723701,0.00012802807,0.00019689946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004919729,0.0007341005,0.00047053435,0.0021450715,0.0009473658,0.00056195393,0.0005290701,0.0011987186,0.0029122834],"category_scores_gemma":[0.002299329,0.0004908974,0.00040231796,0.0006303005,0.0006966654,0.00076599047,0.00056736707,0.0011166938,0.0004401288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011146854,0.00071040355,0.44359472,0.00031747948,0.0003265744,0.34880155,0.002231201,0.00061488897,0.16393575,0.00049450254,0.0007783944,0.027047703],"study_design_scores_gemma":[0.00014371936,0.0010406757,0.7449091,0.000043276712,0.00025093704,0.23285474,0.001347351,0.0015616568,0.016341958,0.00080484245,0.00064600294,0.000055627308],"about_ca_topic_score_codex":0.005801066,"about_ca_topic_score_gemma":0.0042608315,"teacher_disagreement_score":0.005801066,"about_ca_system_score_codex":0.00056223274,"about_ca_system_score_gemma":0.00051598425,"threshold_uncertainty_score":0.011534572},"labels":[],"label_agreement":null},{"id":"W1981581208","doi":"10.1002/mrm.22786","title":"Preterm neonatal diffusion processing using detection and replacement of outliers prior to resampling","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Outlier; Resampling; Diffusion MRI; Voxel; Computer science; Artificial intelligence; Estimator; Diffusion; Computer vision; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Medicine; Radiology; Physics","score_opus":0.08458024766958966,"score_gpt":0.3526075372995314,"score_spread":0.26802728962994177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981581208","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05522017,0.00016868944,0.9431432,0.0000793835,0.000040410705,0.000034209297,0.00004047628,0.0009372606,0.00033620352],"genre_scores_gemma":[0.2370783,0.00016226241,0.7614842,0.000023203784,0.000024011255,0.0000524324,0.00016593683,0.00019337879,0.0008162764],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999681,0.0000862884,0.000030567207,0.000053516505,0.00012007076,0.000028613405],"domain_scores_gemma":[0.99889165,0.00041035414,0.00020503135,0.00016180768,0.00029515984,0.00003602397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010109104,0.00061602937,0.00054932025,0.0004719914,0.0003023141,0.000540876,0.0006414433,0.000564464,0.0008174902],"category_scores_gemma":[0.004877155,0.00024598904,0.00046070645,0.00045486947,0.000306968,0.00054353493,0.00057320483,0.00057059573,0.0003788518],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009001952,0.00014302353,0.005894713,0.00022088758,0.0001330559,0.0005971551,0.00058425154,0.16626339,0.15808497,0.0059239874,0.0019682476,0.6592861],"study_design_scores_gemma":[0.000031951855,0.00017522679,0.004325162,0.000018391327,0.000045386114,0.00049637817,0.000073659314,0.8777696,0.112012774,0.0020180803,0.0029665092,0.00006678138],"about_ca_topic_score_codex":0.0026404634,"about_ca_topic_score_gemma":0.002475624,"teacher_disagreement_score":0.0026404634,"about_ca_system_score_codex":0.00023635678,"about_ca_system_score_gemma":0.00077148067,"threshold_uncertainty_score":0.0053462386},"labels":[],"label_agreement":null},{"id":"W1981639529","doi":"10.1161/strokeaha.109.573287","title":"Acute Corticospinal Tract Wallerian Degeneration Is Associated With Stroke Outcome","year":2010,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre","funders":"","keywords":"Medicine; Corticospinal tract; Wallerian degeneration; Stroke (engine); Effective diffusion coefficient; Magnetic resonance imaging; Radiology; Pyramidal tracts; Diffusion MRI; Cardiology; Pathology; Anatomy","score_opus":0.051155344151690096,"score_gpt":0.3530123602458715,"score_spread":0.3018570160941814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981639529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99947256,0.0001665364,0.00007729167,0.000017935725,0.0000022145753,0.0000032225598,0.00006093359,0.0000040847185,0.00019516532],"genre_scores_gemma":[0.9997008,0.000056524415,0.000057136294,0.0000061791707,0.0000059694703,0.0000032430416,0.00010614725,0.0000012671007,0.000062805644],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999665,0.00006476116,0.00007451626,0.000074466254,0.00007027017,0.000050921288],"domain_scores_gemma":[0.99637526,0.00049158395,0.0023915658,0.00012556861,0.00025760217,0.00035841274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004068507,0.00025596932,0.0003041075,0.00068528816,0.0002642071,0.00036609953,0.00016820533,0.00037257306,0.0021827808],"category_scores_gemma":[0.0030445866,0.00011762642,0.00018633358,0.00049609196,0.00040361407,0.00029469797,0.0003178289,0.00030885646,0.00031733056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008278775,0.000013127862,0.998552,0.000008160796,0.000023342427,0.00012645047,0.000026170992,0.000023628034,0.0003225013,0.000006336328,0.000024241308,0.00079114427],"study_design_scores_gemma":[0.0000023603263,0.00009615421,0.9988489,0.000005015263,0.000013800796,0.00074465264,0.000025616178,0.000058099147,0.00015256122,0.0000149286525,0.00003621353,0.0000016395987],"about_ca_topic_score_codex":0.00105656,"about_ca_topic_score_gemma":0.001624489,"teacher_disagreement_score":0.0021827808,"about_ca_system_score_codex":0.00019162195,"about_ca_system_score_gemma":0.0002210032,"threshold_uncertainty_score":0.0073021054},"labels":[],"label_agreement":null},{"id":"W1982080133","doi":"10.1109/tbme.2012.2230262","title":"Multistructure Large Deformation Diffeomorphic Brain Registration","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Image registration; Artificial intelligence; Robustness (evolution); Diffeomorphism; Computer vision; Computer science; Brain morphometry; Matching (statistics); Pattern recognition (psychology); Neuroimaging; Neuroscience; Magnetic resonance imaging; Mathematics; Psychology; Medicine; Biology","score_opus":0.028345193542547557,"score_gpt":0.2996760640480542,"score_spread":0.27133087050550664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982080133","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077739665,0.00016471445,0.9890492,0.00012436464,0.000039139344,0.00010003612,0.00018301107,0.0011717944,0.0013937866],"genre_scores_gemma":[0.1730528,0.00036901428,0.81999624,0.00015655968,0.00005357098,0.00042457448,0.00082152593,0.0010781415,0.0040475465],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991025,0.00020810333,0.00006579505,0.00026576343,0.00030049158,0.00005749203],"domain_scores_gemma":[0.9991898,0.00020946859,0.00008798144,0.00037206805,0.000113365735,0.000027233244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014822551,0.0011662091,0.0011162466,0.0018482272,0.000750309,0.0014115255,0.0012527436,0.0016211253,0.0040553855],"category_scores_gemma":[0.003692695,0.0006868329,0.0014900075,0.0019939202,0.0007934187,0.001360735,0.002399931,0.0014824126,0.0020268373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003165473,0.0002475427,0.0021977788,0.00049771677,0.00044328385,0.00089995086,0.00056188577,0.22054785,0.16764645,0.07692532,0.0126143135,0.51710135],"study_design_scores_gemma":[0.000064137115,0.00026072699,0.004946698,0.00004541709,0.000112521426,0.0018858959,0.00012079388,0.7934999,0.08435708,0.07765475,0.036905225,0.00014676596],"about_ca_topic_score_codex":0.0011179625,"about_ca_topic_score_gemma":0.002490815,"teacher_disagreement_score":0.0040553855,"about_ca_system_score_codex":0.000505867,"about_ca_system_score_gemma":0.0010834747,"threshold_uncertainty_score":0.013566613},"labels":[],"label_agreement":null},{"id":"W1983444688","doi":"10.1117/12.911770","title":"HARDI denoising using nonlocal means on S<sup>2</sup>","year":2012,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Noise reduction; Artificial intelligence; Filter (signal processing); Pattern recognition (psychology); Diffusion MRI; Voxel; Computer vision; Algorithm","score_opus":0.03767626150169793,"score_gpt":0.29729123398891316,"score_spread":0.2596149724872152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983444688","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050688195,0.00016031794,0.99288744,0.000099922414,0.000055823868,0.000019298395,0.000044313372,0.00024432794,0.0014197762],"genre_scores_gemma":[0.09926036,0.00050768035,0.88708943,0.00025024283,0.00014968753,0.00011175723,0.00050802086,0.00024502174,0.011877768],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995977,0.00007959574,0.000023175946,0.000086378524,0.00018750322,0.000025580093],"domain_scores_gemma":[0.9994485,0.00023294537,0.000060946884,0.000102242964,0.00013283249,0.000022449647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006501461,0.000777396,0.00065016345,0.00060291815,0.00036851183,0.0007714454,0.0007802846,0.0010428246,0.0038149143],"category_scores_gemma":[0.001823369,0.0002349348,0.00096544356,0.0007093637,0.00067701645,0.000848339,0.000889515,0.0008609918,0.0018948303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003788506,0.000076249555,0.0009514017,0.00032960926,0.00011298956,0.00024565047,0.00023631794,0.15166587,0.09861599,0.042100254,0.009041455,0.69624543],"study_design_scores_gemma":[0.000009450242,0.00008084712,0.0007040676,0.000018439807,0.000019783347,0.00016082833,0.000029657338,0.9491019,0.027408486,0.011594465,0.010846083,0.000026057744],"about_ca_topic_score_codex":0.0014117305,"about_ca_topic_score_gemma":0.0028644144,"teacher_disagreement_score":0.0038149143,"about_ca_system_score_codex":0.0005357193,"about_ca_system_score_gemma":0.00044889678,"threshold_uncertainty_score":0.012762129},"labels":[],"label_agreement":null},{"id":"W1983624319","doi":"10.3171/jns.2002.97.2.0388","title":"Functional topography of the low postcentral area","year":2002,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Postcentral gyrus; Tongue; Medicine; Sensory system; Magnetic resonance imaging; Anatomy; Radiology; Neuroscience; Pathology; Psychology","score_opus":0.09191322709090725,"score_gpt":0.2852543003152716,"score_spread":0.19334107322436433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983624319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99331576,0.0005475692,0.0037105794,0.000062836116,0.000005992339,0.00002131649,0.00018338209,0.0000563285,0.0020961766],"genre_scores_gemma":[0.9976555,0.00010170112,0.001113388,0.00001772592,0.0000064835294,0.000018827874,0.0000971855,0.000011096872,0.0009780184],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992526,0.000007845609,0.0000041073,0.000025273459,0.000023122,0.000014449975],"domain_scores_gemma":[0.99962246,0.000090412614,0.00013399469,0.00004458393,0.00008706671,0.000021512184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001776035,0.00025123134,0.00019321372,0.0006031308,0.0002510721,0.00056213554,0.00034113255,0.00019455288,0.0043129427],"category_scores_gemma":[0.00087889744,0.00010845876,0.00011700333,0.00026779948,0.0005791868,0.0004467057,0.00021782069,0.0002119185,0.0007980137],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016947808,0.0001554258,0.1603772,0.0003844385,0.0001073469,0.0034241145,0.00087107485,0.0013230402,0.6815185,0.0017936834,0.0010098928,0.14734057],"study_design_scores_gemma":[0.000055340086,0.0005555592,0.9060317,0.000058717334,0.000063817715,0.009229116,0.0002918954,0.002995047,0.076420814,0.0011964093,0.0030819618,0.000019538269],"about_ca_topic_score_codex":0.004413255,"about_ca_topic_score_gemma":0.006310282,"teacher_disagreement_score":0.004413255,"about_ca_system_score_codex":0.00058200565,"about_ca_system_score_gemma":0.0005307108,"threshold_uncertainty_score":0.014428198},"labels":[],"label_agreement":null},{"id":"W1983893112","doi":"10.1097/rct.0b013e3181c34626","title":"Magnetic Resonance Imaging Demonstration of a Single Lesion Causing Wallerian Degeneration in Ascending and Descending Tracts in the Spinal Cord","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Wallerian degeneration; Medicine; Magnetic resonance imaging; Degeneration (medical); Lesion; Spinal cord; Anatomy; Cord; Pathology; Radiology; Surgery","score_opus":0.059073338291609497,"score_gpt":0.33484728021925364,"score_spread":0.27577394192764415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983893112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99498355,0.00085709395,0.00044300058,0.0005994381,0.000029768253,0.000056342422,0.00011298146,0.000029875586,0.0028878932],"genre_scores_gemma":[0.99825686,0.00024898164,0.00035929133,0.00018362256,0.00009874936,0.000006605474,0.00007881572,0.0000033202755,0.00076357747],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9998518,0.000008098771,0.000022248385,0.000040618474,0.000023108509,0.000053979475],"domain_scores_gemma":[0.9995049,0.00012792982,0.000077638666,0.000040291237,0.000052438445,0.00019674425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019019013,0.0010072101,0.0006708695,0.0019057029,0.001180562,0.00043030476,0.00065514946,0.0029558518,0.0034391596],"category_scores_gemma":[0.0013682396,0.0006899807,0.00052621216,0.00059483503,0.0008101283,0.00075214024,0.0005281319,0.0013305196,0.0009678358],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003329645,0.00017038817,0.02804359,0.00006548527,0.00004707811,0.94998074,0.00045584,0.00013919667,0.017641872,0.00014531049,0.0003007689,0.0026767887],"study_design_scores_gemma":[0.00013320566,0.0011255521,0.101737335,0.000040186762,0.00010963355,0.88900477,0.00023116975,0.0009115796,0.005778093,0.0001992787,0.0006915224,0.000037628106],"about_ca_topic_score_codex":0.0071355994,"about_ca_topic_score_gemma":0.008276426,"teacher_disagreement_score":0.0071355994,"about_ca_system_score_codex":0.000708071,"about_ca_system_score_gemma":0.00043767827,"threshold_uncertainty_score":0.014188111},"labels":[],"label_agreement":null},{"id":"W1983906797","doi":"10.1016/j.neuroimage.2011.11.094","title":"Diffusion tensor imaging of white matter tract evolution over the lifespan","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1149,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Canadian Language and Literacy Research Network; Alberta Innovates; Alberta Innovates - Health Solutions; Canada Foundation for Innovation","keywords":"Diffusion MRI; White matter; Diffusion; Physics; Geology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.04806129546345709,"score_gpt":0.30829549359883773,"score_spread":0.2602341981353806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983906797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99404645,0.0017110731,0.0022517976,0.00024852567,0.000007278575,0.000004483858,0.0007344618,0.000019259884,0.0009766654],"genre_scores_gemma":[0.9958001,0.0013325237,0.0018226906,0.000021629294,0.000011588361,0.0000042171637,0.00036239056,0.000010809651,0.00063396635],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999261,0.000017118497,0.0000073353112,0.000024857103,0.000012476784,0.000012047308],"domain_scores_gemma":[0.99941385,0.000101964055,0.00021752788,0.00006154073,0.0001466259,0.000058489968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055490393,0.00014211197,0.000118289485,0.0009838617,0.00019214046,0.000378711,0.0001396394,0.00034588954,0.0007938944],"category_scores_gemma":[0.0022089016,0.00016399455,0.00019039934,0.00070197636,0.00022067958,0.0006305159,0.000198305,0.0002961081,0.00014783353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006612388,0.0000777934,0.773404,0.00018464772,0.0005662949,0.0012358068,0.0010706156,0.0040954207,0.08486339,0.002489207,0.0023315863,0.12902005],"study_design_scores_gemma":[0.000006057877,0.00011267467,0.98438615,0.00005373268,0.00011806785,0.0022870752,0.0002261497,0.0036885443,0.00402041,0.002795586,0.0022849308,0.000020709807],"about_ca_topic_score_codex":0.0069438154,"about_ca_topic_score_gemma":0.010461433,"teacher_disagreement_score":0.0069438154,"about_ca_system_score_codex":0.0003034715,"about_ca_system_score_gemma":0.00031253177,"threshold_uncertainty_score":0.01380682},"labels":[],"label_agreement":null},{"id":"W1984334616","doi":"10.1117/12.710434","title":"DT-MRI segmentation using graph cuts","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health","keywords":"Diffusion MRI; Segmentation; Voxel; Artificial intelligence; Image segmentation; Pattern recognition (psychology); Cut; Graph; Computer science; Tensor (intrinsic definition); Computer vision; Scale-space segmentation; Mathematics; Magnetic resonance imaging; Theoretical computer science; Geometry","score_opus":0.03143709235625768,"score_gpt":0.3093568050314218,"score_spread":0.27791971267516413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984334616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024328788,0.000155416,0.99504197,0.00008827309,0.000029899202,0.00008986822,0.00017600141,0.0011206589,0.0008649283],"genre_scores_gemma":[0.027046071,0.00030253793,0.96959573,0.00008678113,0.000034201297,0.00018797569,0.0009038232,0.0007203282,0.001122421],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987795,0.00019106272,0.00009695412,0.00041735396,0.00042059203,0.00009465039],"domain_scores_gemma":[0.99884534,0.00045026393,0.0001774521,0.00013628996,0.00033974292,0.00005092041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001051088,0.0016739953,0.0012208668,0.003558287,0.0008268672,0.0023345593,0.0016731445,0.0025314458,0.003577998],"category_scores_gemma":[0.003504639,0.0011526983,0.00212323,0.0029919797,0.0010847538,0.0014584652,0.0013492004,0.0021121707,0.00217319],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027655333,0.00010230952,0.0008608743,0.00045309696,0.00018592038,0.00039653518,0.00030586246,0.42357773,0.052154735,0.041028522,0.01472022,0.46593764],"study_design_scores_gemma":[0.00003197493,0.000054697415,0.00037677813,0.000044575765,0.000030458361,0.0002607291,0.000061216975,0.93092984,0.014687303,0.039356075,0.014126217,0.000040107],"about_ca_topic_score_codex":0.0071865954,"about_ca_topic_score_gemma":0.0070249285,"teacher_disagreement_score":0.0071865954,"about_ca_system_score_codex":0.0015264846,"about_ca_system_score_gemma":0.0016574939,"threshold_uncertainty_score":0.014289498},"labels":[],"label_agreement":null},{"id":"W1985596631","doi":"10.1371/journal.pone.0074776","title":"White Matter Abnormalities and Structural Hippocampal Disconnections in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; National Institutes of Health; National Natural Science Foundation of China; University of California, San Diego; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Eisai; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Internal medicine; Alzheimer's disease; Medicine; Cardiology; Audiology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.07348012820763344,"score_gpt":0.30650409645271315,"score_spread":0.2330239682450797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985596631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999699,0.00010073233,0.000039858365,0.00000759449,0.0000010197407,0.0000025204477,0.00004035906,0.0000022663282,0.00010665116],"genre_scores_gemma":[0.9996055,0.00005028757,0.000113981725,0.000007329631,0.000004298631,0.0000040928267,0.00011773512,0.0000013295627,0.00009547993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998385,0.000035213023,0.000023428134,0.000042073072,0.0000366139,0.000024112745],"domain_scores_gemma":[0.9993573,0.00014113235,0.0002990993,0.000050199964,0.00005630435,0.00009590415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056007487,0.00040918638,0.00028676356,0.0011467099,0.00040642024,0.00045860943,0.00023339986,0.00028244767,0.0010174061],"category_scores_gemma":[0.0018728282,0.00020802903,0.00022616789,0.0004104565,0.00032392284,0.00039876904,0.00053746486,0.0002505902,0.000172898],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008777637,0.000076058684,0.98993975,0.000025221954,0.0001134467,0.0005409074,0.0004008695,0.000115218936,0.0025817126,0.00003978307,0.000073555886,0.0052157445],"study_design_scores_gemma":[0.000010002269,0.00009512214,0.998672,0.000003455096,0.00002448102,0.00065362465,0.00010843654,0.00013301746,0.0001802237,0.00005077561,0.00006659781,0.0000023303114],"about_ca_topic_score_codex":0.0047237105,"about_ca_topic_score_gemma":0.0057716705,"teacher_disagreement_score":0.0047237105,"about_ca_system_score_codex":0.00021354643,"about_ca_system_score_gemma":0.00022628137,"threshold_uncertainty_score":0.009392381},"labels":[],"label_agreement":null},{"id":"W1986187732","doi":"10.1002/mus.23276","title":"Diffusion tensor MRI to assess skeletal muscle disruption following eccentric exercise","year":2011,"lang":"en","type":"article","venue":"Muscle & Nerve","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hamilton Health Sciences; McMaster University","funders":"","keywords":"Diffusion MRI; Skeletal muscle; Fractional anisotropy; Muscle biopsy; Magnetic resonance imaging; Medicine; Eccentric; Eccentric exercise; Vastus lateralis muscle; Anatomy; Effective diffusion coefficient; Biopsy; Internal medicine; Radiology; Muscle damage; Physics","score_opus":0.0953547086476023,"score_gpt":0.3426087067105918,"score_spread":0.24725399806298948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986187732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9549769,0.01455854,0.02561898,0.00045934567,0.00006575363,0.0002661897,0.00039471142,0.0001330278,0.0035265132],"genre_scores_gemma":[0.9721399,0.004736534,0.020895211,0.000102137165,0.000051552997,0.00010838002,0.00022498234,0.00001959181,0.0017216944],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998381,0.00005328346,0.000014190782,0.000033766628,0.000044811146,0.000015792013],"domain_scores_gemma":[0.9996125,0.00008900967,0.000113254166,0.000018439669,0.000107223306,0.000059576178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008895289,0.00045795392,0.00026398327,0.00093326264,0.00012133923,0.0002662168,0.00021816364,0.0003095802,0.0012662032],"category_scores_gemma":[0.0010632059,0.0001777565,0.000110188616,0.00033266516,0.00026103598,0.00038866367,0.0002229257,0.00035429344,0.0002928712],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038045067,0.00078271504,0.1627902,0.0013073216,0.00042535478,0.0010668059,0.00037339408,0.0016217784,0.6417422,0.00043448352,0.0017177489,0.18393345],"study_design_scores_gemma":[0.00031040917,0.007138458,0.8679144,0.00019618396,0.00040436443,0.009434985,0.00035010613,0.014096382,0.09358433,0.0010533002,0.0054372856,0.0000797221],"about_ca_topic_score_codex":0.0011355868,"about_ca_topic_score_gemma":0.0024804368,"teacher_disagreement_score":0.0012662032,"about_ca_system_score_codex":0.00019944254,"about_ca_system_score_gemma":0.00023290412,"threshold_uncertainty_score":0.0047042966},"labels":[],"label_agreement":null},{"id":"W1986384971","doi":"10.3109/02699052.2013.823659","title":"Moderate–severe traumatic brain injury causes delayed loss of white matter integrity: Evidence of fornix deterioration in the chronic stage of injury","year":2013,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University Health Network; University of Toronto; Toronto Rehabilitation Institute","funders":"Canadian Institutes of Health Research; Toronto Rehabilitation Institute","keywords":"Fornix; Traumatic brain injury; White matter; Fractional anisotropy; Medicine; Diffusion MRI; Magnetic resonance imaging; Internal medicine; Hippocampus; Radiology; Psychiatry","score_opus":0.07144293103194467,"score_gpt":0.3769062008827193,"score_spread":0.30546326985077465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986384971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995951,0.00015079304,0.000034512803,0.000011886733,0.0000016294572,0.0000074042864,0.000049781876,0.000001262049,0.00014760408],"genre_scores_gemma":[0.9995926,0.000078761026,0.00006464948,0.000008934906,0.0000047586527,0.0000059863482,0.00014886101,5.547637e-7,0.00009480355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998963,0.000016567099,0.00001607442,0.000020376598,0.00001932287,0.00003133368],"domain_scores_gemma":[0.9991948,0.000040227682,0.00050320796,0.000036233323,0.0000776014,0.00014799875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030056102,0.00022511456,0.00024271719,0.00038390412,0.00026993942,0.00024692004,0.00014946381,0.0002935463,0.0012807741],"category_scores_gemma":[0.0010150138,0.00012361692,0.00023656328,0.00021614552,0.000421947,0.0003786269,0.00040486263,0.00030904144,0.00025980594],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011038741,0.0001460053,0.9850277,0.000050197174,0.00006280418,0.0006035285,0.0002924321,0.00005751689,0.0069137495,0.000015518479,0.000105977364,0.0056206593],"study_design_scores_gemma":[0.000006957205,0.00047650613,0.998497,0.0000044040744,0.000006325751,0.0006367162,0.00007087631,0.000016936177,0.00022692232,0.000006812778,0.00004901655,0.0000015990175],"about_ca_topic_score_codex":0.0021386794,"about_ca_topic_score_gemma":0.004599189,"teacher_disagreement_score":0.0021386794,"about_ca_system_score_codex":0.00019151327,"about_ca_system_score_gemma":0.000290534,"threshold_uncertainty_score":0.00428468},"labels":[],"label_agreement":null},{"id":"W1986660440","doi":"10.1016/j.mri.2005.12.037","title":"Insights into brain microstructure from the T2 distribution","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":356,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); University of British Columbia","funders":"","keywords":"White matter; Magnetization transfer; Myelin; Fractional anisotropy; Nuclear magnetic resonance; Diffusion MRI; Chemistry; Multiple sclerosis; Pathology; Neuroscience; Central nervous system; Magnetic resonance imaging; Physics; Biology; Medicine; Radiology","score_opus":0.011278692546200186,"score_gpt":0.2781899913940416,"score_spread":0.2669112988478414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986660440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51726997,0.010358135,0.45104426,0.0029138085,0.00015604413,0.00004615855,0.0009229299,0.00058796897,0.01670075],"genre_scores_gemma":[0.9399441,0.00772572,0.048284374,0.0003765725,0.00042034686,0.000023683531,0.00036656365,0.00021587218,0.002642807],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999578,0.000009438195,0.0000020477703,0.000012143687,0.00001206351,0.000006566816],"domain_scores_gemma":[0.99975663,0.00010552637,0.00004608835,0.000027736616,0.000039041704,0.000024907536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024894348,0.00039247685,0.00021866175,0.0010580322,0.00021719561,0.00076144515,0.00026846747,0.0005460971,0.0018637993],"category_scores_gemma":[0.0009295342,0.00026432806,0.00017684915,0.000666613,0.00055688317,0.0016217452,0.00032894503,0.00051998196,0.00040675123],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032966203,0.000069710324,0.014317667,0.0005654488,0.00013349587,0.0015330495,0.00047618963,0.012970918,0.78215855,0.026407657,0.0027159962,0.15832159],"study_design_scores_gemma":[0.00013020646,0.00042181843,0.22487201,0.00017378983,0.0003792733,0.011101038,0.0010552709,0.198604,0.23144954,0.30250594,0.029080024,0.00022714755],"about_ca_topic_score_codex":0.0007476581,"about_ca_topic_score_gemma":0.001556974,"teacher_disagreement_score":0.0018637993,"about_ca_system_score_codex":0.00014194105,"about_ca_system_score_gemma":0.0002633209,"threshold_uncertainty_score":0.006235063},"labels":[],"label_agreement":null},{"id":"W1986739789","doi":"10.3389/fnana.2015.00041","title":"Diffusion tensor imaging of the human cerebellar pathways and their interplay with cerebral macrostructure","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"John S. Dunn Foundation","keywords":"Cerebellum; Diffusion MRI; White matter; Neuroscience; Dentate nucleus; Cerebellar hemisphere; Anatomy; Deep cerebellar nuclei; Cerebellar cortex; Cerebrum; Tractography; Magnetic resonance imaging; Psychology; Central nervous system; Medicine; Radiology","score_opus":0.019353587729796753,"score_gpt":0.27526188517925204,"score_spread":0.2559082974494553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986739789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99578273,0.00054246455,0.0025718175,0.000029182207,0.0000019474935,0.000014087713,0.00025546204,0.000018955247,0.0007835092],"genre_scores_gemma":[0.9975974,0.00031811453,0.0017496559,0.000005386421,0.000003860726,0.000007048914,0.0001230992,0.000007255504,0.000188125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999218,0.000026952695,0.000007825197,0.000021979862,0.00001298256,0.000008438218],"domain_scores_gemma":[0.9996947,0.00008807796,0.00010733823,0.000033503078,0.000045485947,0.00003080631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034093455,0.0002756862,0.0000904536,0.0008789662,0.00009926702,0.00036410536,0.00011391613,0.00015744602,0.00078573666],"category_scores_gemma":[0.0016555231,0.00013526824,0.000084385414,0.00044562222,0.00019884233,0.0002945401,0.00014043538,0.00008078809,0.00012167767],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001369697,0.000106221276,0.45434293,0.00043012688,0.00055235415,0.002555625,0.0025842364,0.0055652126,0.38770443,0.0019483784,0.0008245443,0.14201617],"study_design_scores_gemma":[0.000014721639,0.0001307142,0.98492,0.000015656657,0.000090536,0.0023402167,0.00019925759,0.0050852057,0.005875605,0.0006613943,0.00064344506,0.000023314273],"about_ca_topic_score_codex":0.003683038,"about_ca_topic_score_gemma":0.004678262,"teacher_disagreement_score":0.003683038,"about_ca_system_score_codex":0.000113125585,"about_ca_system_score_gemma":0.00014087906,"threshold_uncertainty_score":0.0073232055},"labels":[],"label_agreement":null},{"id":"W1987138508","doi":"10.1016/j.jad.2013.05.009","title":"Age of onset and corpus callosal morphology in major depression","year":2013,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Health Research Board","keywords":"Depression (economics); Psychology; Corpus callosum; Morphology (biology); Brain morphometry; Neuroscience; Medicine; Magnetic resonance imaging; Biology; Radiology","score_opus":0.017259921244291678,"score_gpt":0.3222138332380264,"score_spread":0.3049539119937347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987138508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99833435,0.00070171343,0.000047364487,0.000038674065,0.000009823256,0.0000026939395,0.00013080996,0.0000032931127,0.00073131686],"genre_scores_gemma":[0.9992163,0.0003243771,0.000034653916,0.000014794938,0.000017636725,0.0000017419094,0.00010801124,0.0000034788004,0.00027897928],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998903,0.000025539992,0.000017562823,0.000022269664,0.000017686414,0.000026686466],"domain_scores_gemma":[0.9988016,0.00035916117,0.00048561057,0.000065672626,0.00009973317,0.0001882185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030316843,0.00016299434,0.00031943008,0.0009117915,0.0002525722,0.0005042578,0.00024862518,0.00056255976,0.0019576075],"category_scores_gemma":[0.0023077454,0.00022475513,0.00024140673,0.00048976677,0.00022746545,0.00044848036,0.00023501054,0.00041152549,0.0003757992],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016099217,0.00006645077,0.9805366,0.000025187397,0.00006788512,0.0035647843,0.00022571303,0.00009713575,0.007178268,0.00006662202,0.00020178965,0.0063596442],"study_design_scores_gemma":[0.0000036220176,0.00004587333,0.9980482,0.0000043243344,0.000013722564,0.001569923,0.000071769355,0.000046354842,0.00010710781,0.000023438453,0.00006333339,0.0000024513852],"about_ca_topic_score_codex":0.002426234,"about_ca_topic_score_gemma":0.003448974,"teacher_disagreement_score":0.002426234,"about_ca_system_score_codex":0.00030399358,"about_ca_system_score_gemma":0.00015522211,"threshold_uncertainty_score":0.006548822},"labels":[],"label_agreement":null},{"id":"W1987611978","doi":"10.1002/mrm.21837","title":"Temporal stability of adaptive 3D radial MRI using multidimensional golden means","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Cancer Institute; Canadian Breast Cancer Research Alliance; Breast Cancer Alliance","keywords":"Undersampling; Symmetry in biology; Sampling (signal processing); Computer science; Radial line; Temporal resolution; Image resolution; Stability (learning theory); Projection (relational algebra); Artificial intelligence; Algorithm; Mathematics; Computer vision; Physics; Optics; Mathematical analysis","score_opus":0.08249435200894796,"score_gpt":0.3557246402436253,"score_spread":0.2732302882346774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987611978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.080924444,0.00019200845,0.9173531,0.000073733805,0.000022346634,0.00002334348,0.00002816379,0.00029350532,0.0010893098],"genre_scores_gemma":[0.4761832,0.00021308284,0.5223594,0.000040483686,0.000019568475,0.000066823326,0.00010277691,0.00012589656,0.0008887414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99932706,0.00022581276,0.000032627762,0.000112844005,0.00026537557,0.000036278576],"domain_scores_gemma":[0.99808073,0.0009097061,0.00030594552,0.00032567017,0.00030759966,0.00007041889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015804238,0.0005060867,0.0003765503,0.0006908749,0.0003331987,0.0008571138,0.0007429853,0.00049742346,0.0006382132],"category_scores_gemma":[0.0069883256,0.00038472243,0.00036937828,0.00052988133,0.00087922043,0.0009095437,0.001123716,0.0005345818,0.00024232178],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011581798,0.00007642522,0.008685361,0.00027693732,0.0001318662,0.00039795294,0.0009903278,0.41098148,0.19267273,0.06747621,0.0013864037,0.31576613],"study_design_scores_gemma":[0.000010802113,0.000081355975,0.0014710486,0.000012238705,0.000014380588,0.00029270325,0.000039190945,0.94011337,0.05011626,0.006370303,0.0014344245,0.00004394593],"about_ca_topic_score_codex":0.00089496386,"about_ca_topic_score_gemma":0.0010305984,"teacher_disagreement_score":0.0015804238,"about_ca_system_score_codex":0.0005392051,"about_ca_system_score_gemma":0.00050907425,"threshold_uncertainty_score":0.008358121},"labels":[],"label_agreement":null},{"id":"W1987990850","doi":"10.1159/000368442","title":"Age-Related Changes in Diffusion Tensor Imaging Metrics of Fornix Subregions in Healthy Humans","year":2015,"lang":"en","type":"article","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Fornix; Fractional anisotropy; Diffusion MRI; Hippocampal formation; White matter; Neuroscience; Hippocampus; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11243628212507754,"score_gpt":0.328259579016825,"score_spread":0.21582329689174745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987990850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998014,0.0007305738,0.0004752969,0.00001869853,0.0000040526243,0.000011958093,0.0002966751,0.00001905613,0.0004296241],"genre_scores_gemma":[0.99812406,0.00028019812,0.00087283744,0.000015835594,0.000007837543,0.000014832334,0.00026463807,0.0000069964035,0.00041278548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999212,0.000008987024,0.000007372979,0.000040467556,0.000010730271,0.000011199134],"domain_scores_gemma":[0.99959964,0.000039826897,0.00023283622,0.00004170083,0.000045902158,0.000040157604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026275462,0.0003937073,0.00024753076,0.0007461189,0.00017053114,0.0002367246,0.0000996324,0.0002804828,0.0012382299],"category_scores_gemma":[0.0008968945,0.00013198105,0.0001321919,0.00025323554,0.00023822147,0.00037542966,0.00016687762,0.00010135488,0.0002728769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029338417,0.00019495831,0.77147275,0.00024566194,0.00041745248,0.0022578698,0.0013149669,0.0009958138,0.1624693,0.00035802144,0.0013494538,0.05598997],"study_design_scores_gemma":[0.000010305284,0.00031555336,0.99582714,0.000011225297,0.00002584559,0.0014788961,0.00008828177,0.0002727906,0.0014151274,0.00014368998,0.00040203767,0.000009012687],"about_ca_topic_score_codex":0.0014902182,"about_ca_topic_score_gemma":0.0021472638,"teacher_disagreement_score":0.0014902182,"about_ca_system_score_codex":0.0001576604,"about_ca_system_score_gemma":0.000117733034,"threshold_uncertainty_score":0.0041422844},"labels":[],"label_agreement":null},{"id":"W1988234649","doi":"10.1016/j.neubiorev.2014.11.006","title":"Drawing connections between white matter and numerical and mathematical cognition: A literature review","year":2014,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Superior longitudinal fasciculus; Diffusion MRI; Corpus callosum; Corona radiata (embryology); Neuroscience; Tractography; Fasciculus; Psychology; Inferior longitudinal fasciculus; Cognition; Cognitive psychology; Cognitive science; Fractional anisotropy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.19444804492370443,"score_gpt":0.4640190083500259,"score_spread":0.2695709634263215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988234649","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012754631,0.99922454,0.00011414797,0.00024075714,0.0000611667,0.0000027962296,0.000017851764,0.0000021695632,0.00020909605],"genre_scores_gemma":[0.0006818538,0.99871814,0.00025825936,0.00013834667,0.000105506464,0.0000040453165,0.000018842858,7.876352e-7,0.000074187206],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9996879,0.00005704986,0.00007622446,0.000079584024,0.00008143239,0.000017774368],"domain_scores_gemma":[0.9980343,0.0013963815,0.00020543192,0.000029039516,0.00028970244,0.000045116733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012243616,0.0010221598,0.0019022704,0.004198476,0.00032626622,0.0015669194,0.0010719687,0.0015186686,0.0035849905],"category_scores_gemma":[0.0035917966,0.00045361966,0.00084310654,0.0055534733,0.0010496371,0.0023388804,0.0010022689,0.0014087597,0.0007777987],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009917378,0.00006800609,0.0010094187,0.059029564,0.00042702525,0.00033995684,0.00020076285,0.00025426917,0.00070325076,0.00378707,0.014914934,0.91916656],"study_design_scores_gemma":[0.00010758956,0.00023064124,0.016188037,0.1126667,0.0038537446,0.0062662247,0.0011988116,0.0003730334,0.0014180243,0.02543822,0.83205575,0.00020322346],"about_ca_topic_score_codex":0.0038030813,"about_ca_topic_score_gemma":0.0070161126,"teacher_disagreement_score":0.004198476,"about_ca_system_score_codex":0.0006174437,"about_ca_system_score_gemma":0.0029465072,"threshold_uncertainty_score":0.011992931},"labels":[],"label_agreement":null},{"id":"W1988561184","doi":"10.1016/j.clinph.2014.10.168","title":"9. Simultaneous imaging of the brain and spinal cord: Accounting for the brain-spine interaction into functional models of human motor system","year":2015,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Spinal cord; Neuroscience; Neuroimaging; Functional magnetic resonance imaging; Motor system; Neurophysiology; Presentation (obstetrics); Central nervous system; Human brain; Psychology; Sensory system; Nervous system; Medicine; Radiology","score_opus":0.14933393294480043,"score_gpt":0.43761675775798087,"score_spread":0.28828282481318046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988561184","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04440259,0.0016873187,0.9275596,0.004034377,0.00045245702,0.000077785866,0.00048143778,0.0007212623,0.020583183],"genre_scores_gemma":[0.6589484,0.0029305953,0.3148543,0.00088903744,0.00040571525,0.0001301407,0.00033752358,0.00030825625,0.021195991],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999404,0.000010967598,0.0000037104764,0.00001566168,0.000016330394,0.000012936183],"domain_scores_gemma":[0.9998784,0.000046453843,0.000010526143,0.000018942595,0.000026024172,0.000019742938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031569082,0.00034567,0.0002800753,0.00023393365,0.00026394677,0.00065090053,0.00094553264,0.0018659,0.003000589],"category_scores_gemma":[0.00058707723,0.000351858,0.00059230055,0.0001566758,0.0003886268,0.0014057136,0.0005502344,0.0005448008,0.0010229714],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004940312,0.0002093137,0.0023939554,0.0008148301,0.00021677018,0.0016190475,0.00037170746,0.13959152,0.39653832,0.22120288,0.027950753,0.20859689],"study_design_scores_gemma":[0.00006111099,0.00021648213,0.004139868,0.000045900237,0.00015731293,0.0014334376,0.000084860236,0.8433954,0.0646536,0.06464581,0.021109585,0.000056668792],"about_ca_topic_score_codex":0.0028724105,"about_ca_topic_score_gemma":0.005374393,"teacher_disagreement_score":0.003000589,"about_ca_system_score_codex":0.0002875227,"about_ca_system_score_gemma":0.00040129584,"threshold_uncertainty_score":0.010037959},"labels":[],"label_agreement":null},{"id":"W1989462236","doi":"10.1002/mrm.21527","title":"High‐resolution myelin water measurements in rat spinal cord","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Spinal cord; Myelin; Resolution (logic); Nuclear magnetic resonance; Myelin sheath; Chemistry; Neuroscience; Central nervous system; Biology; Physics; Computer science; Artificial intelligence","score_opus":0.12329312624909883,"score_gpt":0.3603831665679358,"score_spread":0.23709004031883696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989462236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9804441,0.00090732164,0.0178253,0.000032793996,0.0000056636773,0.000020506504,0.00015886228,0.0001663055,0.000439195],"genre_scores_gemma":[0.9623464,0.0018010202,0.0330741,0.00003874937,0.000008231976,0.00008508273,0.00040803774,0.00007931626,0.0021590116],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999362,0.000009415193,0.0000037830298,0.000015996886,0.00001802122,0.000016570857],"domain_scores_gemma":[0.9998293,0.000027565377,0.000045885477,0.0000137910165,0.00006019867,0.00002320498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026762058,0.00037565234,0.00020521264,0.00037603034,0.0001794602,0.00015753553,0.00018644998,0.00021964553,0.00058976194],"category_scores_gemma":[0.00035194587,0.00015028026,0.000113448914,0.0002000499,0.00026799922,0.0003160995,0.00025004582,0.00024732106,0.00015518023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004562168,0.000005935716,0.000091361384,0.000019980343,0.0000023218302,0.000018496854,0.000021609261,0.000069348614,0.998705,0.00001938461,0.000008148933,0.0009927567],"study_design_scores_gemma":[0.0000069056086,0.0003427696,0.0034618669,0.0000048211264,0.000019472009,0.00016984994,0.00004959191,0.0008971405,0.9946445,0.000048651174,0.00034867137,0.0000058580763],"about_ca_topic_score_codex":0.002334625,"about_ca_topic_score_gemma":0.0034426225,"teacher_disagreement_score":0.002334625,"about_ca_system_score_codex":0.0001755287,"about_ca_system_score_gemma":0.00022482051,"threshold_uncertainty_score":0.004642129},"labels":[],"label_agreement":null},{"id":"W1989653704","doi":"10.1002/jmri.20102","title":"Diffusion anisotropy in subcortical white matter and cortical gray matter: Changes with aging and the role of CSF‐suppression","year":2004,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":209,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Cerebrospinal fluid; Anisotropy; Psychology; Nuclear magnetic resonance; Medicine; Neuroscience; Magnetic resonance imaging; Physics; Radiology; Optics","score_opus":0.008772163671084085,"score_gpt":0.26853219880950296,"score_spread":0.2597600351384189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989653704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942194,0.0038770912,0.0012725993,0.000051351333,0.00001353359,0.000008913478,0.00009289484,0.00002369868,0.0004405588],"genre_scores_gemma":[0.99767274,0.00081920665,0.001151821,0.000020820497,0.000020889469,0.00000769423,0.000073430725,0.0000064538262,0.00022688294],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999504,0.000009206523,0.0000054334805,0.000016280206,0.0000126650075,0.000006020294],"domain_scores_gemma":[0.999597,0.00006858136,0.00019904492,0.000024423463,0.000060912593,0.0000500728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003857066,0.00040413867,0.00021997771,0.00038332082,0.00011005158,0.00023764274,0.00010621373,0.00016867928,0.0004814156],"category_scores_gemma":[0.0010888558,0.00009393659,0.00008404291,0.00020056672,0.00033164615,0.00024528644,0.00011541716,0.00015267063,0.00011438124],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024146505,0.00017157049,0.30190423,0.0004139775,0.00017895787,0.0012378094,0.0006484687,0.00044161326,0.58591896,0.0003198781,0.0004922377,0.10585759],"study_design_scores_gemma":[0.000029151908,0.0009218698,0.9448518,0.000026171556,0.00009839745,0.004086329,0.00012810252,0.0010498952,0.046958104,0.0004149477,0.0014220044,0.000013185991],"about_ca_topic_score_codex":0.0009006011,"about_ca_topic_score_gemma":0.00089620164,"teacher_disagreement_score":0.0009006011,"about_ca_system_score_codex":0.00012393678,"about_ca_system_score_gemma":0.00017250872,"threshold_uncertainty_score":0.0020397902},"labels":[],"label_agreement":null},{"id":"W1992049744","doi":"10.1159/000125684","title":"The Corticospinal Tract in the Kangaroo","year":2008,"lang":"en","type":"article","venue":"Brain Behavior and Evolution","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kensington Health","funders":"","keywords":"Corticospinal tract; Neuroscience; Pyramidal tracts; Psychology; Anatomy; Physical medicine and rehabilitation; Communication; Biology; Medicine; Magnetic resonance imaging; Diffusion MRI","score_opus":0.08109557937582283,"score_gpt":0.361586309226146,"score_spread":0.28049072985032314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992049744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9784349,0.0068190875,0.005211249,0.00020170212,0.00003244602,0.000012716032,0.00019029398,0.00008235696,0.009015174],"genre_scores_gemma":[0.9958021,0.0011979941,0.0011656864,0.00003187616,0.0000091985185,0.000004883913,0.000075753436,0.0000057726734,0.0017067874],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99997234,0.0000044142766,0.0000016656946,0.000011480793,0.000004954044,0.000005039282],"domain_scores_gemma":[0.99994004,0.0000055785727,0.000023908415,0.000005413026,0.000009295214,0.00001568314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047207446,0.00012855693,0.000101526384,0.00029978063,0.00021521583,0.00020593162,0.00012246701,0.00021616263,0.0012582036],"category_scores_gemma":[0.00015414202,0.000064037406,0.000069373826,0.0001900714,0.00038654788,0.00032022165,0.00015449192,0.00016370742,0.0002619722],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005888463,0.000036673886,0.02890518,0.00037975976,0.000066561464,0.0025924572,0.00073214923,0.0009395511,0.90816385,0.004132769,0.00050862564,0.05295358],"study_design_scores_gemma":[0.000026553998,0.0005981375,0.93452805,0.00013630485,0.00008213186,0.00783553,0.0006165917,0.0010570544,0.03494198,0.006648688,0.013482135,0.000046848894],"about_ca_topic_score_codex":0.0047074542,"about_ca_topic_score_gemma":0.0059452746,"teacher_disagreement_score":0.0047074542,"about_ca_system_score_codex":0.00032636733,"about_ca_system_score_gemma":0.00018920563,"threshold_uncertainty_score":0.009360135},"labels":[],"label_agreement":null},{"id":"W1992273569","doi":"10.1002/hbm.20734","title":"Handedness, motor skills and maturation of the corticospinal tract in the adolescent brain","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Centre Hospitalier de l’Université de Montréal; Cegep de Thetford; Université du Québec à Chicoutimi; Cégep de Jonquière; Cegep de Trois-Rivieres; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Heart And Stroke Foundation Of Quebec; Heart and Stroke Foundation of Canada","keywords":"Corticospinal tract; Psychology; Pyramidal tracts; White matter; Internal capsule; Testosterone (patch); Grey matter; Neuroscience; Hum; Magnetic resonance imaging; Laterality; Anatomy; Young adult; Physiology; Developmental psychology; Biology; Internal medicine; Medicine; Diffusion MRI","score_opus":0.051827367798209435,"score_gpt":0.34391305100881786,"score_spread":0.2920856832106084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992273569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99966466,0.00015964205,0.000031866297,0.0000081405915,0.0000017737201,0.0000011038557,0.000035830286,0.0000016530998,0.00009532472],"genre_scores_gemma":[0.999645,0.00012299193,0.00005488677,0.000005787622,0.0000032844393,0.0000026065866,0.000051095045,0.0000011790066,0.00011319889],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998735,0.000019972575,0.000011642303,0.000039318787,0.000029459423,0.000026082407],"domain_scores_gemma":[0.99930954,0.0001333903,0.00035295385,0.000033510485,0.000047664078,0.0001229011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032687333,0.00020083941,0.0001716892,0.00070577743,0.00015054486,0.00033591056,0.00010465959,0.00017222094,0.0009122647],"category_scores_gemma":[0.0013816621,0.00012744198,0.00012947209,0.00024797863,0.00035729323,0.00021865008,0.0001907475,0.00021197164,0.00013850149],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015400891,0.00003890863,0.98228467,0.000021613925,0.00003422771,0.0006063588,0.00045583578,0.000059682174,0.008287152,0.000070565446,0.000057069996,0.007929901],"study_design_scores_gemma":[0.0000010266616,0.00003767963,0.9991973,0.0000023839616,0.0000041737007,0.00042053286,0.000058150126,0.000029230017,0.00017945061,0.000028939636,0.000040100767,0.0000010091479],"about_ca_topic_score_codex":0.002541186,"about_ca_topic_score_gemma":0.0052734213,"teacher_disagreement_score":0.002541186,"about_ca_system_score_codex":0.00015268722,"about_ca_system_score_gemma":0.00023117028,"threshold_uncertainty_score":0.005052805},"labels":[],"label_agreement":null},{"id":"W1992959576","doi":"10.1016/j.jns.2013.10.026","title":"Thalamic cramplike pain","year":2013,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; London Health Sciences Centre","funders":"","keywords":"Thalamus; Somatosensory system; Medicine; Magnetic resonance imaging; Stroke (engine); Infarction; Diffusion MRI; Neuroscience; Lesion; Psychology; Cardiology; Pathology; Radiology","score_opus":0.0903855334629715,"score_gpt":0.3541012514387433,"score_spread":0.2637157179757718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992959576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74384665,0.016003542,0.01105695,0.0060885167,0.0013105803,0.0006907076,0.002196038,0.0009959925,0.21781103],"genre_scores_gemma":[0.98536426,0.0015006213,0.0008153268,0.0018486866,0.00032179107,0.000036863647,0.00025942223,0.000030895022,0.009822122],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99987245,0.000013314361,0.000007923324,0.000026766353,0.000022530867,0.000057051195],"domain_scores_gemma":[0.9996668,0.000052456242,0.00008766455,0.00008303429,0.000042822565,0.00006719436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010874644,0.00070072315,0.0003849284,0.0007241361,0.0006520427,0.00066136016,0.00061519153,0.0010977031,0.014721633],"category_scores_gemma":[0.0011886854,0.00023867436,0.0004098483,0.00068538653,0.0007197943,0.00074445235,0.00038455555,0.0015796653,0.0017805573],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032855924,0.0005426067,0.016370988,0.0014214782,0.00041363944,0.6869185,0.00101383,0.0005860431,0.09319751,0.008054928,0.01803633,0.1701586],"study_design_scores_gemma":[0.0004084254,0.0011789824,0.06860223,0.00014562024,0.00014863204,0.898483,0.0006566799,0.0007096036,0.0086034015,0.0024651333,0.018511886,0.000086511944],"about_ca_topic_score_codex":0.0016984555,"about_ca_topic_score_gemma":0.0021495086,"teacher_disagreement_score":0.014721633,"about_ca_system_score_codex":0.00059802097,"about_ca_system_score_gemma":0.00027479322,"threshold_uncertainty_score":0.049248755},"labels":[],"label_agreement":null},{"id":"W1993450982","doi":"10.1186/1532-429x-16-s1-p338","title":"Aberrant myocardial sheetlet mobility in hypertrophic cardiomyopathy detected using in vivo cardiovascular magnetic resonance diffusion tensor imaging","year":2014,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Imperial College London","keywords":"Hypertrophic cardiomyopathy; Medicine; Diffusion MRI; Magnetic resonance imaging; Angiology; Fractional anisotropy; Internal medicine; Cardiology; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.02090329498308082,"score_gpt":0.2593662823866934,"score_spread":0.23846298740361258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993450982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970675,0.00034983037,0.0018138492,0.00010475197,0.000010705619,0.000009780327,0.000024518731,0.000018766492,0.0006002246],"genre_scores_gemma":[0.9981427,0.00027660813,0.0013034308,0.000030488869,0.000029114355,0.000005448906,0.000042183437,0.000010755048,0.00015918633],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99983037,0.000047828657,0.000030004545,0.000029305133,0.000032099408,0.000030414825],"domain_scores_gemma":[0.999303,0.0001646174,0.0002475549,0.0000670104,0.00008607547,0.00013170572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074027805,0.0004637197,0.00027910818,0.0011807829,0.00023633741,0.0007949485,0.00028106396,0.0006666359,0.0009616953],"category_scores_gemma":[0.0021794746,0.000441846,0.00019497091,0.0002995812,0.00047830524,0.00065728714,0.0005983017,0.0004981003,0.00023698591],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026441559,0.0002523886,0.31070033,0.00018153393,0.00027607725,0.049708385,0.0012990304,0.0010422495,0.610743,0.00094350224,0.0006235093,0.021585857],"study_design_scores_gemma":[0.00011231069,0.00061823573,0.84440994,0.00014155978,0.0003170929,0.076776914,0.0011604608,0.015012207,0.0586629,0.0016451842,0.0010695733,0.00007368684],"about_ca_topic_score_codex":0.00045115512,"about_ca_topic_score_gemma":0.0005588063,"teacher_disagreement_score":0.0011807829,"about_ca_system_score_codex":0.000114510236,"about_ca_system_score_gemma":0.00011662805,"threshold_uncertainty_score":0.003915012},"labels":[],"label_agreement":null},{"id":"W1993512345","doi":"10.1016/j.neuroimage.2011.01.013","title":"Image analysis and statistical inference in neuroimaging with R","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut National de la Santé et de la Recherche Médicale","keywords":"Neuroimaging; Computer science; Context (archaeology); Compiler; Graphics; Diffusion MRI; Data science; Artificial intelligence; Natural language processing; Programming language; Psychology; Computer graphics (images); Neuroscience","score_opus":0.07151616042765449,"score_gpt":0.3564647139602621,"score_spread":0.2849485535326076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993512345","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041957432,0.00046047792,0.9963314,0.00024963584,0.00008249445,0.000037276008,0.00011555903,0.0019898622,0.00031379593],"genre_scores_gemma":[0.024292411,0.00054953835,0.97149456,0.00022275507,0.00021508022,0.0005709424,0.0003173131,0.0013911086,0.000946353],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9704968,0.022807466,0.0017384586,0.0026835182,0.0019095127,0.00036421485],"domain_scores_gemma":[0.86679554,0.109162286,0.003506451,0.016034508,0.0038331763,0.0006680812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03520109,0.0031047785,0.0043173684,0.00347677,0.0014555758,0.005332762,0.004283229,0.0027397585,0.012222204],"category_scores_gemma":[0.17000432,0.0025473721,0.004089029,0.004287909,0.0055083,0.0041854186,0.0036908344,0.007510702,0.008445826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009545154,0.00029530493,0.003858287,0.0027838224,0.0026378226,0.0012024811,0.0011407143,0.10532189,0.0050249086,0.3944707,0.052961003,0.42934856],"study_design_scores_gemma":[0.00028979915,0.00012667054,0.001127011,0.0002622139,0.00031739264,0.0006592538,0.000096857046,0.33803684,0.0047446536,0.62504375,0.029173141,0.00012244204],"about_ca_topic_score_codex":0.0050527966,"about_ca_topic_score_gemma":0.005432544,"teacher_disagreement_score":0.03520109,"about_ca_system_score_codex":0.0014437517,"about_ca_system_score_gemma":0.0056951805,"threshold_uncertainty_score":0.18616337},"labels":[],"label_agreement":null},{"id":"W1993585744","doi":"10.1002/cne.21048","title":"Efferent association pathways originating in the caudal prefrontal cortex in the macaque monkey","year":2006,"lang":"en","type":"article","venue":"The Journal of Comparative Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":228,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Centre National d’Etudes Spatiales","keywords":"Anatomy; Biology; Neuroscience; Superior longitudinal fasciculus; Gyrus; Superior parietal lobule; Fasciculus; Intraparietal sulcus; Cingulate cortex; Sulcus; Inferior parietal lobule; Limbic lobe; White matter; Posterior parietal cortex; Medicine; Central nervous system; Magnetic resonance imaging; Functional magnetic resonance imaging; Fractional anisotropy","score_opus":0.07048517042257545,"score_gpt":0.3602226539798041,"score_spread":0.2897374835572286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993585744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98288536,0.0011689194,0.0028221335,0.0005391828,0.000026684165,0.000014810532,0.0002062564,0.0000970972,0.012239567],"genre_scores_gemma":[0.99327916,0.00077990245,0.0030849609,0.00015435554,0.00002295032,0.00002021478,0.00010170579,0.000014347091,0.002542298],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999944,0.0000067983005,0.0000018250915,0.000015800479,0.00001465987,0.000017032235],"domain_scores_gemma":[0.99989223,0.000025945405,0.00002823829,0.000014839266,0.000023428904,0.000015211407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088308654,0.00018252787,0.000106712396,0.00043923708,0.0005097752,0.00034053338,0.00011098647,0.00022325006,0.0020686502],"category_scores_gemma":[0.00047480446,0.00014261832,0.00014101708,0.00019441436,0.00035931834,0.0002670746,0.00025340196,0.00033612663,0.00025247375],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006539153,0.00013994162,0.026612177,0.0002809338,0.00012801852,0.003053502,0.0013991153,0.0013868657,0.75839376,0.010560075,0.0023835439,0.19500811],"study_design_scores_gemma":[0.00019520955,0.00071911654,0.8562221,0.00035040776,0.0001712902,0.0125613175,0.0010117458,0.008197623,0.056533158,0.018181995,0.045796633,0.000059549067],"about_ca_topic_score_codex":0.0146396365,"about_ca_topic_score_gemma":0.016739555,"teacher_disagreement_score":0.0146396365,"about_ca_system_score_codex":0.0008101633,"about_ca_system_score_gemma":0.00042325747,"threshold_uncertainty_score":0.029108882},"labels":[],"label_agreement":null},{"id":"W1994129529","doi":"10.1167/9.8.482","title":"Disconnection of cortical face network in prosopagnosia revealed by diffusion tensor imaging","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Inferior longitudinal fasciculus; Disconnection; Fusiform face area; White matter; Diffusion MRI; Psychology; Neuroscience; Temporal lobe; Fractional anisotropy; Tractography; Cortex (anatomy); Superior temporal sulcus; Anatomy; Lateralization of brain function; Face perception; Magnetic resonance imaging; Medicine; Perception; Epilepsy; Radiology","score_opus":0.0184613101705857,"score_gpt":0.35449915315018193,"score_spread":0.3360378429795962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994129529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987155,0.00006255035,0.0003930808,0.000042610347,0.0000019012676,0.0000076088,0.000035740733,0.000016764578,0.00072420074],"genre_scores_gemma":[0.9991019,0.00010242344,0.00044940304,0.000014895737,0.000003924607,0.000009172719,0.00006255218,0.000005677883,0.0002501634],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988806,0.000013646938,0.000012620729,0.000036135363,0.000030242225,0.00001922421],"domain_scores_gemma":[0.9997292,0.000073654955,0.0001124641,0.00003118307,0.00002163689,0.00003172117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002864892,0.00074959215,0.0002836642,0.001561561,0.00034757456,0.00039852317,0.00023138023,0.00036373586,0.0016901739],"category_scores_gemma":[0.0007722655,0.00028511562,0.00020535396,0.00026660674,0.00089194014,0.00050400366,0.00042502276,0.00044465263,0.00020190078],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018815557,0.00036626853,0.22689101,0.00026435178,0.00025545654,0.10235574,0.00376154,0.0018259139,0.59195966,0.0022982936,0.00050942093,0.06763083],"study_design_scores_gemma":[0.00004033351,0.0005175936,0.7800379,0.00003297034,0.00017003567,0.18056373,0.00067596283,0.0033976354,0.03164955,0.0018306833,0.0010423103,0.000041299998],"about_ca_topic_score_codex":0.0013841967,"about_ca_topic_score_gemma":0.001514741,"teacher_disagreement_score":0.0016901739,"about_ca_system_score_codex":0.0003018657,"about_ca_system_score_gemma":0.0002243214,"threshold_uncertainty_score":0.005654216},"labels":[],"label_agreement":null},{"id":"W1994146809","doi":"10.1016/j.neuroimage.2014.12.003","title":"Rotarod training in mice is associated with changes in brain structure observable with multimodal MRI","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Corpus callosum; Diffusion MRI; Fractional anisotropy; Hippocampus; White matter; Neuroscience; Psychology; Motor cortex; Motor coordination; Neuroplasticity; Rotarod performance test; Primary motor cortex; Cortex (anatomy); Motor learning; Medicine; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.04653404142261984,"score_gpt":0.3046889380935284,"score_spread":0.2581548966709086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994146809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870799,0.0011177652,0.005982207,0.00086841726,0.00024485338,0.00007812271,0.0024556678,0.0008724728,0.0013004643],"genre_scores_gemma":[0.97508526,0.0015996847,0.005784713,0.0006029569,0.00009489738,0.00052386953,0.0033731735,0.0006101353,0.012325308],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99949276,0.000045724766,0.0000335536,0.00018967796,0.00009205009,0.00014608669],"domain_scores_gemma":[0.99876666,0.000060920873,0.00062262855,0.0001346381,0.00008277617,0.0003324827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036198873,0.0020840345,0.0009920176,0.0020409536,0.00045030788,0.0006976966,0.00092525966,0.0014458039,0.0029800679],"category_scores_gemma":[0.0004090086,0.000732428,0.0010869033,0.0005183798,0.0018966574,0.0008956813,0.0006807395,0.004004291,0.0009194205],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016007827,0.00034065524,0.0004339212,0.000045771736,0.000035629055,0.00014281513,0.000045696375,0.000093825125,0.99572396,0.0000875213,0.00025338755,0.0011960793],"study_design_scores_gemma":[0.00017240943,0.0035388388,0.036999013,0.000064277294,0.0001404434,0.00061488117,0.00022791061,0.0012869185,0.95487267,0.00042000847,0.0015999945,0.000062561776],"about_ca_topic_score_codex":0.0019059731,"about_ca_topic_score_gemma":0.0035416805,"teacher_disagreement_score":0.0029800679,"about_ca_system_score_codex":0.0008459158,"about_ca_system_score_gemma":0.0007036106,"threshold_uncertainty_score":0.009969294},"labels":[],"label_agreement":null},{"id":"W1994190062","doi":"10.1016/j.brainres.2009.10.031","title":"The macrostructural and microstructural abnormalities of corpus callosum in children with attention deficit/hyperactivity disorder: A combined morphometric and diffusion tensor MRI study","year":2009,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National High-tech Research and Development Program; National Natural Science Foundation of China","keywords":"Corpus callosum; Diffusion MRI; Abnormality; Fractional anisotropy; Psychology; Magnetic resonance imaging; Pathophysiology; Attention deficit hyperactivity disorder; Neuroscience; Medicine; Pathology; Psychiatry; Radiology","score_opus":0.03657203224725817,"score_gpt":0.3660293346083506,"score_spread":0.3294573023610924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994190062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99928695,0.00010905802,0.00006698754,0.000058717535,0.000004071399,0.000011756471,0.0001163994,0.0000065132663,0.00033959988],"genre_scores_gemma":[0.9989949,0.00020864945,0.00036480252,0.000031060004,0.000019255307,0.000020118092,0.00015511087,0.000008986221,0.00019703733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968994,0.00004598627,0.00004658158,0.00007899069,0.00008384724,0.00005466054],"domain_scores_gemma":[0.99919075,0.00018624766,0.0002916076,0.000050170253,0.00014346006,0.00013781493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069288333,0.00094115763,0.0004916443,0.0032569976,0.0010640246,0.00052169745,0.00072769873,0.0008496884,0.0013265958],"category_scores_gemma":[0.0020600392,0.00078087853,0.0004763851,0.001570307,0.0015748768,0.0011104811,0.00076549285,0.00082858896,0.00025441265],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073399255,0.0005279591,0.93451005,0.00014849253,0.00018278712,0.023171162,0.0021090305,0.000394903,0.030199135,0.00018724568,0.00045317,0.0073820218],"study_design_scores_gemma":[0.000023218488,0.00023892905,0.97606134,0.000010620126,0.000095277166,0.020450829,0.0010890302,0.00031409893,0.0014667583,0.0000476631,0.00018599402,0.000016215949],"about_ca_topic_score_codex":0.01966031,"about_ca_topic_score_gemma":0.014567846,"teacher_disagreement_score":0.01966031,"about_ca_system_score_codex":0.00060826866,"about_ca_system_score_gemma":0.0009744917,"threshold_uncertainty_score":0.039091766},"labels":[],"label_agreement":null},{"id":"W1994275622","doi":"10.1016/j.neuroimage.2013.01.069","title":"The acute phase of Wallerian degeneration: Longitudinal diffusion tensor imaging of the fornix following temporal lobe surgery","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; University of Alberta; Alberta Science and Research Authority; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Fornix; Wallerian degeneration; Temporal lobe; Diffusion MRI; Hippocampus; Epilepsy; Fractional anisotropy; Epilepsy surgery; Medicine; Pathology; Neuroscience; Radiology; Psychology; Internal medicine; Magnetic resonance imaging","score_opus":0.06141380470241224,"score_gpt":0.3439879654080169,"score_spread":0.28257416070560465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994275622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99304295,0.0011688907,0.0006181076,0.0013341211,0.00006267619,0.00007570364,0.00014995941,0.000015639858,0.003532137],"genre_scores_gemma":[0.9980439,0.00074010744,0.00014244288,0.00020095886,0.0001920112,0.000013717062,0.0001829643,0.0000049039395,0.00047896433],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997009,0.00004290353,0.000044200722,0.00002724738,0.000052843654,0.0001320028],"domain_scores_gemma":[0.9986702,0.0002122783,0.00055739604,0.0001075773,0.00018240068,0.00027020977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061798556,0.00063187606,0.00057502644,0.0013051075,0.0010152439,0.0008045783,0.00059818855,0.0013025606,0.0017053175],"category_scores_gemma":[0.0031561074,0.00035320956,0.0004369479,0.0011243803,0.0014334132,0.0016742861,0.0006361991,0.0015464724,0.00054640486],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045685815,0.000944689,0.48603138,0.0002098297,0.00020080394,0.46187103,0.0013710699,0.00079138356,0.017249644,0.000932942,0.0020852792,0.023743354],"study_design_scores_gemma":[0.00025672512,0.0025574155,0.69992983,0.00022587157,0.00024220698,0.2827262,0.0020076304,0.0014313473,0.0057321256,0.0024675748,0.0023313009,0.00009177512],"about_ca_topic_score_codex":0.0071790875,"about_ca_topic_score_gemma":0.008125243,"teacher_disagreement_score":0.0071790875,"about_ca_system_score_codex":0.0010162712,"about_ca_system_score_gemma":0.0013120271,"threshold_uncertainty_score":0.014274597},"labels":[],"label_agreement":null},{"id":"W1994415119","doi":"10.3174/ajnr.a1154","title":"Attenuation of Lower-Thoracic, Lumbar, and Sacral Spinal Cord Motion: Implications for Imaging Human Spinal Cord Structure and Function","year":2008,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Spinal cord; Medicine; Lumbar; Anatomy; Lumbar Spinal Cord; Cord; Thoracic vertebrae; Lumbar vertebrae; Surgery","score_opus":0.06898080948246568,"score_gpt":0.39469832099787516,"score_spread":0.3257175115154095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994415119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9807983,0.0062720934,0.010959442,0.00042842625,0.000017976772,0.000039830604,0.00014621291,0.000059195147,0.0012785231],"genre_scores_gemma":[0.9937384,0.0014110081,0.0044191508,0.000064447566,0.000023871971,0.00002324413,0.00008742728,0.0000097683205,0.0002226056],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986184,0.000045814606,0.0000124125145,0.000032376258,0.000034221623,0.000013290219],"domain_scores_gemma":[0.9987828,0.00065752206,0.00036709028,0.000052722877,0.00009081106,0.000048988793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053575425,0.0002017634,0.00015425096,0.00032874156,0.0001429005,0.00044884498,0.00021906095,0.0004090103,0.0016828505],"category_scores_gemma":[0.0045153447,0.000119841614,0.00007986379,0.00022938442,0.00061309105,0.00030431402,0.00016558172,0.00018898908,0.00016050419],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001114992,0.00016298254,0.24354118,0.0008834573,0.00012393373,0.001089996,0.0004441845,0.0044120746,0.5857527,0.0011652343,0.0004407648,0.16086844],"study_design_scores_gemma":[0.000026827342,0.00052467285,0.93415713,0.00009052303,0.00009939024,0.003030864,0.0001459314,0.006416266,0.05336216,0.00089960836,0.0012255074,0.000021064172],"about_ca_topic_score_codex":0.0016005071,"about_ca_topic_score_gemma":0.0015500851,"teacher_disagreement_score":0.0016828505,"about_ca_system_score_codex":0.00025523143,"about_ca_system_score_gemma":0.00028837376,"threshold_uncertainty_score":0.0056296587},"labels":[],"label_agreement":null},{"id":"W1994429981","doi":"10.1016/j.neuroimage.2004.12.053","title":"Imaging brain connectivity in children with diverse reading ability","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":284,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; University of Alberta","keywords":"Diffusion MRI; Reading (process); White matter; Psychology; Neuroscience; Tractography; Fractional anisotropy; Neuroimaging; Cognition; Functional magnetic resonance imaging; Magnetoencephalography; Cognitive psychology; Magnetic resonance imaging; Medicine; Electroencephalography","score_opus":0.03108061756068215,"score_gpt":0.3271740039062844,"score_spread":0.2960933863456023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994429981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983341,0.00013645047,0.00026182967,0.000105308405,0.0000026379462,0.0000069469284,0.00015111169,0.0000108189415,0.0009907093],"genre_scores_gemma":[0.9989078,0.000115396586,0.000511337,0.000029053015,0.0000058527767,0.000011992339,0.00010872633,0.000007957483,0.0003018192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997552,0.000043173804,0.000029683591,0.00007579126,0.000037439895,0.000058766116],"domain_scores_gemma":[0.99922097,0.00031184178,0.00021293039,0.00004394578,0.00012964278,0.00008062988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043357446,0.00057754706,0.00035741692,0.0016472772,0.0004061714,0.0005375263,0.0003515058,0.00057916885,0.002862718],"category_scores_gemma":[0.0026858323,0.00032121016,0.00026411947,0.0006462984,0.0005554484,0.0010504419,0.0004363764,0.0005895807,0.00022851932],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007254991,0.00027984823,0.9129492,0.00017122137,0.00022825849,0.013646657,0.0024625459,0.0015696185,0.037304487,0.0009036282,0.0010059146,0.02875305],"study_design_scores_gemma":[0.000037937996,0.00023161847,0.976179,0.000030284707,0.0001193751,0.014504263,0.0014634139,0.0015014496,0.0048074964,0.00074556883,0.00036471031,0.000014791491],"about_ca_topic_score_codex":0.009674565,"about_ca_topic_score_gemma":0.014751881,"teacher_disagreement_score":0.009674565,"about_ca_system_score_codex":0.00042166575,"about_ca_system_score_gemma":0.000362893,"threshold_uncertainty_score":0.019236505},"labels":[],"label_agreement":null},{"id":"W1994457811","doi":"10.1038/mp.2013.142","title":"The SORL1 gene and convergent neural risk for Alzheimer’s disease across the human lifespan","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Mental Health & Substance Use Services; University of British Columbia; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research","keywords":"Neuropathology; White matter; Alzheimer's disease; Fractional anisotropy; Biology; Psychology; Neuroscience; Disease; Pathology; Medicine","score_opus":0.03430807905002004,"score_gpt":0.3572886433012893,"score_spread":0.32298056425126925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994457811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99760675,0.0009728976,0.00021643825,0.0001518232,0.0000066421053,0.0000020230789,0.00021928588,0.000005810461,0.00081833306],"genre_scores_gemma":[0.9978289,0.000783798,0.00043963376,0.000058481808,0.000012921036,0.0000046825107,0.00023914738,0.0000075330154,0.0006248581],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999853,0.00003833842,0.000011797913,0.00005772467,0.000024987192,0.000014125602],"domain_scores_gemma":[0.9993081,0.00014040519,0.00032598764,0.000055572673,0.00009579788,0.00007423677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003639929,0.0003238132,0.0002593424,0.0011253759,0.00027845966,0.0004539789,0.00025393284,0.00035751148,0.0012920648],"category_scores_gemma":[0.0010738847,0.00017589444,0.00024954116,0.0005292857,0.00040245778,0.00032694626,0.0004964413,0.0004202576,0.00015008035],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029156369,0.00014733677,0.9220269,0.000079212834,0.00054340437,0.0021285005,0.0008538457,0.00034519614,0.03703386,0.0011868733,0.0004933364,0.032245964],"study_design_scores_gemma":[0.000018379435,0.00012613252,0.9951344,0.000022509936,0.000094587616,0.0016257565,0.00025523806,0.00021466159,0.0010261079,0.0009778602,0.0004949442,0.000009388586],"about_ca_topic_score_codex":0.0020207036,"about_ca_topic_score_gemma":0.0025403292,"teacher_disagreement_score":0.0020207036,"about_ca_system_score_codex":0.00024340478,"about_ca_system_score_gemma":0.00013756343,"threshold_uncertainty_score":0.0043224096},"labels":[],"label_agreement":null},{"id":"W1994690989","doi":"10.1016/j.neurobiolaging.2014.04.037","title":"Brain connectivity and novel network measures for Alzheimer's disease classification","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Neuroimaging; Artificial intelligence; Pattern recognition (psychology); Tractography; Diffusion MRI; Classifier (UML); Disease; Cognitive impairment; Computer science; Machine learning; Alzheimer's disease; Cognition; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.10838974823109572,"score_gpt":0.35760022029145566,"score_spread":0.24921047206035996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994690989","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87061274,0.010132624,0.109256506,0.0012009006,0.00016215436,0.00014347609,0.0044264765,0.00026887818,0.0037963006],"genre_scores_gemma":[0.9686836,0.0011454948,0.028174406,0.00003584235,0.00021092595,0.000076401855,0.0012105061,0.000014158136,0.00044869748],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99969304,0.000113083915,0.000031586296,0.00007797267,0.00006248036,0.000021906872],"domain_scores_gemma":[0.9987111,0.0006685078,0.00027544436,0.0000951295,0.00015956433,0.000090226866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013239955,0.00058560463,0.00056077517,0.003421174,0.00037350354,0.0007852722,0.00042972207,0.0005651871,0.0010910269],"category_scores_gemma":[0.0036124315,0.00011324658,0.0003962797,0.0019455521,0.00040706331,0.0011841034,0.00048270408,0.0005048448,0.00016484744],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016228532,0.00062051404,0.4321843,0.0007110393,0.0014504862,0.0005003194,0.00050223205,0.037765115,0.02446666,0.012251105,0.008202547,0.47972283],"study_design_scores_gemma":[0.00010117713,0.00078855775,0.56108147,0.0001716827,0.0006847192,0.0015609551,0.0005056792,0.37996334,0.004753986,0.04658602,0.0037015977,0.00010075664],"about_ca_topic_score_codex":0.0023806954,"about_ca_topic_score_gemma":0.0045510214,"teacher_disagreement_score":0.003421174,"about_ca_system_score_codex":0.00045793428,"about_ca_system_score_gemma":0.0003182367,"threshold_uncertainty_score":0.0070020556},"labels":[],"label_agreement":null},{"id":"W1994726328","doi":"10.1016/j.neurobiolaging.2014.04.036","title":"Unified voxel- and tensor-based morphometry (UVTBM) using registration confidence","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Western University","funders":"National Institute of Mental Health; National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; Michael Smith Health Research BC","keywords":"Voxel; Artificial intelligence; Computer science; Jacobian matrix and determinant; Normalization (sociology); Pattern recognition (psychology); Voxel-based morphometry; Image registration; Transformation (genetics); Computer vision; Mathematics; Medicine; Magnetic resonance imaging; White matter; Radiology","score_opus":0.08856435064750692,"score_gpt":0.3533324412531366,"score_spread":0.26476809060562967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994726328","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056522866,0.00014091085,0.9926722,0.00007139414,0.000030008376,0.000023695966,0.000114484894,0.0010787933,0.00021629885],"genre_scores_gemma":[0.14876296,0.00029835704,0.8475812,0.000084319596,0.000065892,0.00017241253,0.0007690243,0.0009169305,0.0013488466],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986979,0.0003598936,0.00011357801,0.0003443562,0.00038852813,0.000095818024],"domain_scores_gemma":[0.9971533,0.0008976852,0.0004541219,0.00084834266,0.00054605387,0.00010050851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027451722,0.00094174524,0.0015502815,0.0021933538,0.00072791585,0.0021494494,0.0027019742,0.0017195359,0.0024346367],"category_scores_gemma":[0.011652939,0.00083464594,0.002061364,0.0026394513,0.00090228074,0.0028527067,0.0029888616,0.0023645216,0.0013592559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031367718,0.00012790658,0.0029860993,0.00045235903,0.00041759913,0.00013403804,0.00027180486,0.21647093,0.021166878,0.08140908,0.007182238,0.6690674],"study_design_scores_gemma":[0.000013724633,0.000073153904,0.0009593102,0.000024412848,0.000059049715,0.0001379991,0.000030650783,0.96174973,0.0049375785,0.029582283,0.002393232,0.000039036924],"about_ca_topic_score_codex":0.0058430596,"about_ca_topic_score_gemma":0.007138668,"teacher_disagreement_score":0.0058430596,"about_ca_system_score_codex":0.00056650385,"about_ca_system_score_gemma":0.002246419,"threshold_uncertainty_score":0.014518023},"labels":[],"label_agreement":null},{"id":"W1995050389","doi":"10.1109/tip.2007.904964","title":"Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health","keywords":"Diffusion MRI; Image processing; Tensor (intrinsic definition); Magnetic resonance imaging; Artificial intelligence; Computer vision; Nuclear magnetic resonance; Computer science; Physics; Mathematics; Image (mathematics); Geometry; Radiology; Medicine","score_opus":0.0335951469893662,"score_gpt":0.3319622486764225,"score_spread":0.29836710168705627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995050389","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011969262,0.00018082422,0.9857598,0.00013291059,0.000058192494,0.000037874743,0.000099510966,0.00078025786,0.0009813609],"genre_scores_gemma":[0.16293365,0.00057410466,0.8318455,0.00013396598,0.00010597167,0.00008454616,0.00043014716,0.00038758313,0.0035044318],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913675,0.00011524694,0.000071232986,0.0001671153,0.00044207915,0.0000676165],"domain_scores_gemma":[0.9982443,0.0005793866,0.00023556763,0.00038893282,0.00048175422,0.00007006558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018189523,0.0008579792,0.00094643165,0.0012897883,0.00052465586,0.0011938467,0.0006659238,0.00083042594,0.003556598],"category_scores_gemma":[0.0076211705,0.0003534133,0.001141842,0.0015748213,0.00051725766,0.0016623591,0.0009939432,0.0008350565,0.001153052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034684487,0.00012881879,0.0017153011,0.0003521003,0.00016307237,0.0003015108,0.00021904957,0.11469865,0.16646737,0.025234286,0.0035842494,0.6867887],"study_design_scores_gemma":[0.00004570547,0.00025005595,0.0034747655,0.00003171773,0.000095592004,0.0006639359,0.000059966285,0.8313119,0.10813851,0.039424118,0.016427413,0.00007627607],"about_ca_topic_score_codex":0.00244083,"about_ca_topic_score_gemma":0.003434167,"teacher_disagreement_score":0.003556598,"about_ca_system_score_codex":0.00053508696,"about_ca_system_score_gemma":0.00079171633,"threshold_uncertainty_score":0.011898041},"labels":[],"label_agreement":null},{"id":"W1995147563","doi":"10.1016/j.neuroimage.2015.03.036","title":"MRI-detectable changes in mouse brain structure induced by voluntary exercise","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Dentate gyrus; Neuroscience; Hippocampus; Psychology; Cerebellum; Striatum; Brain Structure and Function; Gyrus; Pons; Physical exercise; Medicine; Cognition; Internal medicine","score_opus":0.05864062415783312,"score_gpt":0.3284128462837369,"score_spread":0.2697722221259038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995147563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879981,0.0013824834,0.0070512164,0.00030897307,0.00012149986,0.00006556151,0.0009070366,0.00025919426,0.0019058285],"genre_scores_gemma":[0.98373,0.0012270273,0.0041019972,0.00023860006,0.000041262712,0.0001920871,0.0009434296,0.00011652628,0.009408976],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998267,0.000018379707,0.000011170365,0.000053312382,0.00003383497,0.000056518922],"domain_scores_gemma":[0.99973255,0.000034724435,0.0000812338,0.000030541767,0.0000387026,0.000082185245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023942352,0.00076992146,0.00032252073,0.00064242556,0.00020613256,0.00030742696,0.0003486794,0.0007868617,0.0021414298],"category_scores_gemma":[0.00024650228,0.0003542092,0.00046590515,0.00027536627,0.00066414534,0.00041221495,0.0003423292,0.0014798365,0.0003611431],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089580857,0.000098372,0.00026702258,0.000036929523,0.000015020159,0.000100053105,0.000026172249,0.00006330306,0.9974464,0.00009017752,0.0000740015,0.0008868155],"study_design_scores_gemma":[0.00007793394,0.0018116633,0.015323144,0.000023081606,0.00009459036,0.0004265191,0.00010122094,0.00091551733,0.97983104,0.00020396302,0.0011786823,0.000012633319],"about_ca_topic_score_codex":0.0010290615,"about_ca_topic_score_gemma":0.0018125509,"teacher_disagreement_score":0.0021414298,"about_ca_system_score_codex":0.00023588804,"about_ca_system_score_gemma":0.00027199817,"threshold_uncertainty_score":0.007163763},"labels":[],"label_agreement":null},{"id":"W1995568058","doi":"10.1002/jmri.22535","title":"Quality assessment of high angular resolution diffusion imaging data using bootstrap on Q‐ball reconstruction","year":2011,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Mental Health","keywords":"Computer science; Diffusion imaging; Angular resolution (graph drawing); Spherical harmonics; Voxel; Artificial intelligence; Diffusion MRI; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Medicine","score_opus":0.2011310254859495,"score_gpt":0.4171718896569978,"score_spread":0.2160408641710483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995568058","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07561159,0.00022041179,0.92305446,0.00011120004,0.000019100089,0.00009168794,0.0001012428,0.0004911586,0.00029923508],"genre_scores_gemma":[0.5478224,0.00021665635,0.45054108,0.00008801573,0.00004802889,0.00022783325,0.0005144349,0.00028427914,0.00025730184],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99625385,0.0021053292,0.00025403497,0.00031702511,0.0009661857,0.000103650615],"domain_scores_gemma":[0.96984047,0.017656017,0.0028215942,0.003372735,0.0058503808,0.0004588092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017524313,0.0006792066,0.0009411649,0.0019258114,0.0005874159,0.0010215709,0.0011942441,0.0010877071,0.0012180216],"category_scores_gemma":[0.06187103,0.00035756364,0.00071091624,0.0009784428,0.0015143782,0.0013193381,0.0016429948,0.00083350943,0.00047172152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030113647,0.00039970604,0.08771002,0.0012570858,0.00075549516,0.0010813148,0.0016080628,0.2217855,0.10477474,0.017642114,0.0030775396,0.55689704],"study_design_scores_gemma":[0.000088237925,0.00035899982,0.028411187,0.00009232927,0.000074630036,0.0008864392,0.000138558,0.92572457,0.03104379,0.011379907,0.0016916279,0.000109594796],"about_ca_topic_score_codex":0.0014019876,"about_ca_topic_score_gemma":0.0012986659,"teacher_disagreement_score":0.017524313,"about_ca_system_score_codex":0.00045728867,"about_ca_system_score_gemma":0.00074071134,"threshold_uncertainty_score":0.09267855},"labels":[],"label_agreement":null},{"id":"W1995857959","doi":"10.1503/jpn.130280","title":"White matter tractography in early psychosis: clinical and neurocognitive associations","year":2014,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Medical Association; University of Sydney","keywords":"Inferior longitudinal fasciculus; Psychosis; White matter; Neurocognitive; Fractional anisotropy; Psychology; Diffusion MRI; Psychiatry; Superior longitudinal fasciculus; Fornix; Neuropsychology; Medicine; Clinical psychology; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.04788969070745097,"score_gpt":0.3834395871554806,"score_spread":0.3355498964480296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995857959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99916875,0.00026667397,0.00026304007,0.000027641005,0.0000012005412,0.0000062960994,0.000059433878,0.0000043943755,0.00020256864],"genre_scores_gemma":[0.99946076,0.00013447004,0.00025966915,0.0000054718957,0.0000025125762,0.0000040253412,0.00005594384,0.0000017212878,0.000075436765],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988794,0.000027835182,0.000012826324,0.000023447354,0.000020423859,0.000027510552],"domain_scores_gemma":[0.99897873,0.0002309583,0.00052583695,0.000039358674,0.00009250785,0.00013258532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045098807,0.0002365297,0.00014825336,0.00094368216,0.00027659585,0.00034256213,0.00012193204,0.00025374477,0.0018111669],"category_scores_gemma":[0.0018855723,0.00016340065,0.00011006805,0.0005148928,0.00038162485,0.00025834388,0.00031978017,0.0001786942,0.00014742333],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024333302,0.000017885934,0.98821276,0.000041176212,0.00003673818,0.0011237434,0.00023557829,0.00013432078,0.0043281075,0.000066216184,0.000078323894,0.005481772],"study_design_scores_gemma":[0.000004898214,0.00004773246,0.99568814,0.000016744072,0.000012063006,0.003278246,0.00014369623,0.00024692752,0.00031823202,0.000151634,0.00008883001,0.0000027837461],"about_ca_topic_score_codex":0.0043885363,"about_ca_topic_score_gemma":0.010184909,"teacher_disagreement_score":0.0043885363,"about_ca_system_score_codex":0.00035818008,"about_ca_system_score_gemma":0.00037387296,"threshold_uncertainty_score":0.008726001},"labels":[],"label_agreement":null},{"id":"W1996515464","doi":"10.1118/1.2965947","title":"Poster - Thurs Eve-28: New brain diffusion analysis method: White matter grey matter dissasociation","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Diffusion; White matter; Diffusion MRI; Diffusion imaging; Noise (video); Grey matter; Effective diffusion coefficient; White noise; Algorithm; Computer science; Mathematics; Physics; Statistics; Artificial intelligence; Medicine; Magnetic resonance imaging","score_opus":0.04249853042525955,"score_gpt":0.3641579012391296,"score_spread":0.3216593708138701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996515464","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025104735,0.004544976,0.9326817,0.00097420515,0.0023344026,0.0005066901,0.0011523913,0.003528142,0.02917269],"genre_scores_gemma":[0.108084485,0.0027790032,0.8066472,0.00035893827,0.0010965625,0.00067667896,0.0016901551,0.0015693868,0.07709754],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99943465,0.000117850694,0.00003222639,0.00016578547,0.00021214742,0.000037300644],"domain_scores_gemma":[0.9995383,0.00009108053,0.000039627565,0.00008368044,0.00016837368,0.000078918696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010073348,0.0008022529,0.0006656548,0.0016240963,0.000653605,0.0015000799,0.0008057281,0.0011716824,0.023288907],"category_scores_gemma":[0.0015754281,0.00031251868,0.00064139074,0.001014196,0.00053196785,0.0009987882,0.0012797522,0.00093470514,0.013098101],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068253017,0.00021657818,0.0021122075,0.0008788899,0.00014248722,0.0005577148,0.0002828545,0.0047050524,0.1406832,0.014972974,0.04335094,0.7914146],"study_design_scores_gemma":[0.00026277802,0.0009065168,0.02288709,0.0004014498,0.00033555378,0.006343396,0.00025910157,0.23146509,0.25810546,0.03547541,0.4431793,0.00037888135],"about_ca_topic_score_codex":0.00065568293,"about_ca_topic_score_gemma":0.0012812079,"teacher_disagreement_score":0.023288907,"about_ca_system_score_codex":0.00037028352,"about_ca_system_score_gemma":0.0007268809,"threshold_uncertainty_score":0.07790917},"labels":[],"label_agreement":null},{"id":"W1996646045","doi":"10.1016/j.apmr.2008.07.005","title":"Use of Diffusion-Tensor Imaging in Traumatic Spinal Cord Injury to Identify Concomitant Traumatic Brain Injury","year":2008,"lang":"en","type":"article","venue":"Archives of Physical Medicine and Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Toronto Western Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Diffusion MRI; Traumatic brain injury; Concomitant; Spinal cord injury; Medicine; Physical medicine and rehabilitation; Traumatic injury; Spinal cord; Magnetic resonance imaging; Surgery; Radiology; Psychiatry","score_opus":0.0758355367029867,"score_gpt":0.4138940345652408,"score_spread":0.3380584978622541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996646045","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930594,0.0023713836,0.0013860945,0.00034974157,0.00004514247,0.00005892699,0.00008425525,0.000017501425,0.0026275523],"genre_scores_gemma":[0.99640757,0.0015357364,0.0016922059,0.00006937706,0.00006886251,0.000014387103,0.000045798537,0.0000041316403,0.00016189413],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996056,0.00010180083,0.00010880862,0.00003740271,0.00009421209,0.000052165386],"domain_scores_gemma":[0.998147,0.00068805757,0.00034123973,0.00010673255,0.0005253154,0.00019163496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001411619,0.0006354231,0.00040258674,0.0034193746,0.0006686966,0.0009183725,0.0006653031,0.0010417432,0.00077843457],"category_scores_gemma":[0.010019813,0.00036243402,0.00041265192,0.00088256097,0.00076427776,0.0015448439,0.0004296639,0.00065696676,0.00025516743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017376089,0.00040182038,0.920605,0.00029670505,0.00023246155,0.009724044,0.0004785945,0.00062397274,0.021029655,0.00017895321,0.00041973733,0.04427135],"study_design_scores_gemma":[0.00016115706,0.0014926633,0.9212136,0.00032109628,0.000852277,0.035616614,0.0020779248,0.012590955,0.023247503,0.00077316817,0.0015716742,0.0000813258],"about_ca_topic_score_codex":0.007503539,"about_ca_topic_score_gemma":0.012364397,"teacher_disagreement_score":0.007503539,"about_ca_system_score_codex":0.00047954085,"about_ca_system_score_gemma":0.0009595504,"threshold_uncertainty_score":0.014919698},"labels":[],"label_agreement":null},{"id":"W1996774028","doi":"10.1016/j.neuroimage.2006.07.021","title":"Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":227,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Voxel; Region of interest; Diffusion MRI; Spatial normalization; Fractional anisotropy; Normalization (sociology); Computer science; Pattern recognition (psychology); Data set; Artificial intelligence; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09158179869847428,"score_gpt":0.3366103731330259,"score_spread":0.24502857443455162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996774028","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40060422,0.013441476,0.5767521,0.0016303216,0.00046500025,0.00024222159,0.0012351552,0.0011019227,0.0045274356],"genre_scores_gemma":[0.66341347,0.0037450574,0.32815993,0.00022598954,0.00025070622,0.00014818466,0.00044682669,0.00070640486,0.002903445],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988262,0.000689096,0.00009664146,0.00014274307,0.00017498057,0.00007019152],"domain_scores_gemma":[0.9968129,0.0020664928,0.00031074038,0.00027306768,0.0004526505,0.00008423025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004457463,0.00058571884,0.0007799389,0.001751165,0.0003412391,0.0017159544,0.00085197063,0.0011124808,0.0021925943],"category_scores_gemma":[0.011934123,0.00030527325,0.00078956864,0.0011870672,0.00065694173,0.0016503314,0.0005151672,0.0007448447,0.0005497524],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0057534706,0.00036550156,0.038345233,0.0018924385,0.0018231488,0.0012263798,0.0007187964,0.022069382,0.21785803,0.04193042,0.004921629,0.6630955],"study_design_scores_gemma":[0.00077566097,0.0034757706,0.1744697,0.000583004,0.00446287,0.01141737,0.0012084547,0.51138836,0.18809299,0.082945615,0.020749975,0.00043029775],"about_ca_topic_score_codex":0.0020657168,"about_ca_topic_score_gemma":0.004965714,"teacher_disagreement_score":0.004457463,"about_ca_system_score_codex":0.0003066331,"about_ca_system_score_gemma":0.0009704872,"threshold_uncertainty_score":0.023573577},"labels":[],"label_agreement":null},{"id":"W1996945064","doi":"10.1016/j.mri.2014.07.011","title":"Using Copula distributions to support more accurate imaging-based diagnostic classifiers for neuropsychiatric disorders","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"National Institute of Mental Health; U.S. Public Health Service","keywords":"Generalizability theory; Multivariate statistics; Univariate; Artificial intelligence; Copula (linguistics); Computer science; Neuroimaging; Pattern recognition (psychology); Machine learning; Multivariate analysis; Medical imaging; Statistics; Mathematics; Medicine; Econometrics","score_opus":0.044158445106677616,"score_gpt":0.36313149011155466,"score_spread":0.31897304500487705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996945064","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.081081316,0.0014784355,0.9108418,0.0015631104,0.00026298454,0.00014317011,0.0010843846,0.0019235435,0.0016211877],"genre_scores_gemma":[0.7788043,0.0009414895,0.21425858,0.00068723096,0.0006627946,0.00019438888,0.002868371,0.00030692632,0.001275956],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976993,0.0008736875,0.00023991558,0.0005435672,0.00044987432,0.00019360112],"domain_scores_gemma":[0.9783587,0.015567019,0.0013885791,0.0014606647,0.0027705913,0.00045437124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068825977,0.0013882588,0.0019027675,0.0034625414,0.0007002765,0.0031914208,0.0014660577,0.0020654278,0.0025204697],"category_scores_gemma":[0.04275351,0.0006033904,0.0013054109,0.001391957,0.00066485937,0.0027883044,0.0019251269,0.0029673623,0.002596354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014965961,0.0006885626,0.06999547,0.00033619523,0.00061979913,0.0009931237,0.00030858893,0.2644195,0.0116539,0.012274428,0.022391548,0.61482227],"study_design_scores_gemma":[0.000039836978,0.000044461158,0.0035565672,0.0000380229,0.00004302125,0.00025596665,0.00004908423,0.9816637,0.0017089669,0.011444862,0.001129675,0.000025842368],"about_ca_topic_score_codex":0.0031354066,"about_ca_topic_score_gemma":0.0024994034,"teacher_disagreement_score":0.0068825977,"about_ca_system_score_codex":0.0006546729,"about_ca_system_score_gemma":0.0014007284,"threshold_uncertainty_score":0.036399066},"labels":[],"label_agreement":null},{"id":"W1997040868","doi":"10.1016/j.neuroimage.2006.03.003","title":"Evidence of altered prefrontal–thalamic circuitry in schizophrenia: An optimized diffusion MRI study","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Medical Research Council; National Health and Medical Research Council","keywords":"Schizophrenia (object-oriented programming); Diffusion MRI; Neuroscience; Psychology; Prefrontal cortex; Cognitive psychology; Medicine; Psychiatry; Magnetic resonance imaging; Radiology; Cognition","score_opus":0.07816703362500697,"score_gpt":0.35940028564214754,"score_spread":0.28123325201714056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997040868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950342,0.0008271439,0.002122146,0.00020868517,0.000008249802,0.000033309443,0.0002646406,0.000014678516,0.001486813],"genre_scores_gemma":[0.9975581,0.00049652107,0.0013923127,0.000053825403,0.000016870465,0.000011022532,0.0001422822,0.000019890478,0.0003091102],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998989,0.000025750249,0.000012028475,0.000020223035,0.000016326805,0.000026710068],"domain_scores_gemma":[0.99965596,0.00010969934,0.000083572326,0.000068761576,0.000030033205,0.000052002753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007635233,0.00062554074,0.00040258231,0.0007329827,0.00042213066,0.00058932224,0.000623235,0.00071012304,0.00403928],"category_scores_gemma":[0.00096793217,0.00055733614,0.00036768717,0.00043601965,0.0010155777,0.00076627964,0.00048932043,0.00067772757,0.00028399326],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010198575,0.000468036,0.025721343,0.00042949704,0.00051869825,0.006046289,0.00038829996,0.0014428984,0.9369613,0.0020035729,0.00027794592,0.015543445],"study_design_scores_gemma":[0.0028371667,0.0060890443,0.5569786,0.0001247133,0.002520445,0.048219703,0.0014289964,0.0092043895,0.35786474,0.009435664,0.00509273,0.0002038118],"about_ca_topic_score_codex":0.0034281472,"about_ca_topic_score_gemma":0.0028462424,"teacher_disagreement_score":0.00403928,"about_ca_system_score_codex":0.00041203148,"about_ca_system_score_gemma":0.00047531165,"threshold_uncertainty_score":0.01351279},"labels":[],"label_agreement":null},{"id":"W1997403846","doi":"10.1016/j.neuroimage.2011.08.017","title":"Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":352,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Imperial Bank of Commerce","keywords":"Tractography; Connection (principal bundle); Diffusion MRI; Correlation; Diffusion; Cerebral cortex; Mathematics; Convergence (economics); Neuroscience; Physics; Psychology; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.07108956862805242,"score_gpt":0.33242430617664975,"score_spread":0.2613347375485973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997403846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9693907,0.00031770274,0.029041877,0.00015395219,0.000011003312,0.000014733034,0.00012897224,0.00007710926,0.000863872],"genre_scores_gemma":[0.99416393,0.00015680131,0.0051245075,0.000011775171,0.000021310452,0.000008118737,0.00013125727,0.000055466422,0.00032685374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99918956,0.00033631045,0.00004705589,0.00018933456,0.00015016714,0.00008749003],"domain_scores_gemma":[0.98378736,0.010986275,0.0015116851,0.0011580393,0.0019079699,0.0006487085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042195534,0.0005824965,0.0004494718,0.002644544,0.00045265636,0.0017961926,0.00066971575,0.0009591692,0.0013718434],"category_scores_gemma":[0.041430276,0.0007569037,0.00041154743,0.0011178295,0.0019474076,0.0028189297,0.0016401269,0.0010777813,0.00030938254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040733,0.00026653387,0.3403448,0.00071972655,0.0009802545,0.00196453,0.009137613,0.10463587,0.31265593,0.055122025,0.002490489,0.16760902],"study_design_scores_gemma":[0.00017580777,0.00034312645,0.63878214,0.000100887446,0.00024903344,0.0040107914,0.0012504914,0.23029524,0.036635615,0.08694363,0.00097623543,0.00023695128],"about_ca_topic_score_codex":0.001744888,"about_ca_topic_score_gemma":0.001781779,"teacher_disagreement_score":0.0042195534,"about_ca_system_score_codex":0.00040219352,"about_ca_system_score_gemma":0.0006079872,"threshold_uncertainty_score":0.022315383},"labels":[],"label_agreement":null},{"id":"W1997671128","doi":"10.1016/s0924-9338(13)76335-1","title":"1269 – Reduced Fractional Anisotropy In The Uncinate Fasciculus In Patients With Major Depression Carrying The Met-allele Of The Val66met Brain-derived Neurotrophic Factor Genotype","year":2013,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Uncinate fasciculus; Cingulum (brain); Fractional anisotropy; Psychology; Fornix; White matter; rs6265; Neuroscience; Brain-derived neurotrophic factor; Neurotrophic factors; Internal medicine; Hippocampus; Medicine; Magnetic resonance imaging","score_opus":0.02033858178127821,"score_gpt":0.271754700189662,"score_spread":0.2514161184083838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997671128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99958223,0.00011959951,0.00005787239,0.000028048958,0.0000040525174,0.0000020385112,0.00005511405,0.0000026377052,0.00014850002],"genre_scores_gemma":[0.9997676,0.000024324949,0.000059982867,0.000008701679,0.0000030049493,0.0000012521643,0.00004337496,0.0000011514969,0.000090745816],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986625,0.000026088412,0.000024480021,0.00004216799,0.000020414129,0.000020653659],"domain_scores_gemma":[0.99954045,0.00006713214,0.00027342557,0.000029370318,0.00002977803,0.000059883914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016654603,0.00035510637,0.00028893846,0.00035254026,0.00030933207,0.00028007344,0.00011355736,0.00033142552,0.0027964902],"category_scores_gemma":[0.0008952935,0.00017527265,0.00023777761,0.00024399586,0.00021473045,0.00012256748,0.00018012553,0.00019649228,0.00028787024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023571786,0.000092572416,0.960448,0.000062573694,0.00022878204,0.0021936754,0.00046410042,0.00014406758,0.025553448,0.00006621445,0.0002459075,0.008143492],"study_design_scores_gemma":[0.0000142510535,0.0001235693,0.9971206,0.0000056023687,0.000030134688,0.0021599047,0.000060993803,0.00011449717,0.00024099623,0.00004065528,0.0000861404,0.0000026033515],"about_ca_topic_score_codex":0.002652111,"about_ca_topic_score_gemma":0.004567434,"teacher_disagreement_score":0.0027964902,"about_ca_system_score_codex":0.00013765595,"about_ca_system_score_gemma":0.00009941214,"threshold_uncertainty_score":0.009355247},"labels":[],"label_agreement":null},{"id":"W1997903043","doi":"10.1016/j.neuroimage.2010.07.028","title":"Functional mapping in the corpus callosum: A 4T fMRI study of white matter","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Nova Scotia Health Research Foundation; Scottish Rite Charitable Foundation of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Functional connectivity; Psychology; Neuroscience; Cognitive psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07020572028637957,"score_gpt":0.3284273631834578,"score_spread":0.2582216428970782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997903043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98849934,0.0008620063,0.0057923216,0.0010906912,0.00004015537,0.00012493679,0.0003665389,0.000087974964,0.0031360872],"genre_scores_gemma":[0.9853558,0.0009419853,0.00814199,0.00048721896,0.00014552074,0.00014441267,0.00038563643,0.00012367216,0.0042738346],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998907,0.000026997492,0.0000063935186,0.000031768435,0.000018985256,0.00002513819],"domain_scores_gemma":[0.9997377,0.00013426035,0.000026190724,0.000037899892,0.000024719056,0.00003922892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006520514,0.00059300207,0.0004814099,0.0010950111,0.0015549554,0.0006209003,0.0010875966,0.0019009861,0.0032780017],"category_scores_gemma":[0.0013669685,0.0006135023,0.0005286847,0.0006218318,0.0019018177,0.001123314,0.00069284963,0.0015928873,0.000516446],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042836186,0.0017521054,0.010738241,0.0005311277,0.0003012954,0.033789083,0.0016043936,0.0021419688,0.9044063,0.003011107,0.0029352321,0.034505464],"study_design_scores_gemma":[0.0026831848,0.0067318436,0.36621702,0.0002763987,0.0019282071,0.09988456,0.0027484342,0.020142676,0.4447747,0.02518669,0.029031375,0.0003948855],"about_ca_topic_score_codex":0.0056895204,"about_ca_topic_score_gemma":0.0071784006,"teacher_disagreement_score":0.0056895204,"about_ca_system_score_codex":0.0006418276,"about_ca_system_score_gemma":0.0009156949,"threshold_uncertainty_score":0.011312842},"labels":[],"label_agreement":null},{"id":"W1998022841","doi":"10.1016/j.eplepsyres.2012.10.007","title":"Abnormal white matter on diffusion tensor imaging in children with new-onset seizures","year":2012,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Diffusion MRI; Epilepsy; Internal capsule; Psychology; Effective diffusion coefficient; Medicine; Neuroscience; Cardiology; Magnetic resonance imaging; Radiology","score_opus":0.07209311510518958,"score_gpt":0.3991317184371558,"score_spread":0.3270386033319662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998022841","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980673,0.00028546317,0.000060363807,0.0001212832,0.000012713807,0.000007514672,0.00016078266,0.000008814831,0.0012757495],"genre_scores_gemma":[0.99910516,0.00038091143,0.00011612666,0.000032540727,0.000018405439,0.0000062911968,0.00016343643,0.0000061027213,0.00017106606],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968207,0.00003512826,0.000056797966,0.000049209324,0.000083294035,0.00009349855],"domain_scores_gemma":[0.99878246,0.00031595482,0.00049693167,0.00004299094,0.00014534329,0.00021627132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038423273,0.0007204037,0.00050327583,0.0019337531,0.00044788694,0.00044128892,0.00037825134,0.00067893195,0.0018250592],"category_scores_gemma":[0.003580745,0.00033489804,0.0003821305,0.0011460137,0.0008245764,0.0011799572,0.00052442314,0.0005896324,0.00021729938],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019749247,0.00009251087,0.9495107,0.00006024024,0.000032414748,0.043084703,0.0005218992,0.00018380972,0.0024235838,0.00012333576,0.00042416045,0.00334519],"study_design_scores_gemma":[0.00001487701,0.00013213445,0.9193006,0.00002552951,0.000041921194,0.07816679,0.0009990158,0.0002074279,0.0006616817,0.00012240045,0.0003166666,0.0000108623935],"about_ca_topic_score_codex":0.007478418,"about_ca_topic_score_gemma":0.008844132,"teacher_disagreement_score":0.007478418,"about_ca_system_score_codex":0.0005146825,"about_ca_system_score_gemma":0.0007291495,"threshold_uncertainty_score":0.01486975},"labels":[],"label_agreement":null},{"id":"W1998171409","doi":"10.1523/jneurosci.2818-13.2014","title":"Brain White Matter Development Is Associated with a Human-Specific Haplotype Increasing the Synthesis of Long Chain Fatty Acids","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; Centre for Addiction and Mental Health Foundation; Eli Lilly and Company; Canadian Institutes of Health Research; Dana Foundation; Sunovion; Brain and Behavior Research Foundation","keywords":"Haplotype; Polyunsaturated fatty acid; White matter; Biology; Fractional anisotropy; Human brain; Myelin; Genetics; Allele; Genotype; Single-nucleotide polymorphism; Fatty acid; Gene; Endocrinology; Biochemistry; Neuroscience; Central nervous system; Medicine","score_opus":0.054766966338126354,"score_gpt":0.3154604945272163,"score_spread":0.26069352818909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998171409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993167,0.00014280515,0.00014066383,0.000014188442,0.0000022323457,0.000001534036,0.00011832822,0.00000369023,0.00025984793],"genre_scores_gemma":[0.9990677,0.00012902424,0.00028229473,0.000013653647,0.0000063402535,0.0000043796526,0.00017684718,0.000004843693,0.00031505982],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998888,0.000018778715,0.0000135360215,0.00005354029,0.00001208882,0.000013260875],"domain_scores_gemma":[0.99966,0.00005079076,0.0001851109,0.000032144326,0.000032335724,0.000039632876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013301948,0.00017883672,0.00021542133,0.00047557565,0.00022148989,0.00016738183,0.00009279185,0.00021912865,0.0024263668],"category_scores_gemma":[0.00043448075,0.00012203487,0.00013606696,0.0004117097,0.00017885376,0.00011663472,0.0002093884,0.00015000223,0.00023005244],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001692557,0.000102107144,0.866136,0.00006275712,0.00028832152,0.0010148907,0.00042131194,0.00016253155,0.11352366,0.00029434296,0.00041074608,0.015890831],"study_design_scores_gemma":[0.0000064515334,0.00011716197,0.9976084,0.000005789027,0.00002761693,0.0007919347,0.00004853157,0.000090916204,0.0009579405,0.00009467602,0.00024725797,0.0000032445328],"about_ca_topic_score_codex":0.0010014733,"about_ca_topic_score_gemma":0.0010947192,"teacher_disagreement_score":0.0024263668,"about_ca_system_score_codex":0.000076050965,"about_ca_system_score_gemma":0.000089560286,"threshold_uncertainty_score":0.0081169605},"labels":[],"label_agreement":null},{"id":"W1998571354","doi":"10.1016/j.neuroscience.2013.12.019","title":"White matter correlates of cognitive inhibition during development: A diffusion tensor imaging study","year":2013,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute","keywords":"Diffusion MRI; White matter; Psychology; Neuroscience; Cognition; Cognitive psychology; Neuroimaging; Magnetic resonance imaging; Medicine","score_opus":0.029009078991713115,"score_gpt":0.3059221236972878,"score_spread":0.27691304470557465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998571354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99943906,0.000071821756,0.00007656038,0.000017052493,0.0000012543591,0.0000037604893,0.000055172364,0.0000017549214,0.0003334826],"genre_scores_gemma":[0.99930584,0.000120979654,0.00015455335,0.000009727642,0.0000035758706,0.000008483168,0.00009723539,0.000003748867,0.00029581212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974126,0.000041403884,0.000019262345,0.000060082795,0.000082395345,0.000055636858],"domain_scores_gemma":[0.99852234,0.00038155625,0.0005986256,0.00010322918,0.00019673443,0.00019745923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005774612,0.00046293644,0.0002910147,0.00074891385,0.00042466028,0.0006957338,0.00048566822,0.00034738073,0.00073253934],"category_scores_gemma":[0.0026275718,0.00026151026,0.0002655276,0.00074765953,0.00071330374,0.0003256444,0.00043018928,0.0004841132,0.00015239224],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072412076,0.00046591935,0.96230567,0.000055507266,0.00014098363,0.0013084103,0.0018479436,0.00027721704,0.0207341,0.0003483123,0.00016608382,0.011625618],"study_design_scores_gemma":[0.000006344837,0.00011024044,0.9977915,0.0000041990916,0.00003609655,0.00033241193,0.00028320038,0.0001430137,0.001078015,0.000071166534,0.00013839187,0.000005425153],"about_ca_topic_score_codex":0.013793997,"about_ca_topic_score_gemma":0.015183186,"teacher_disagreement_score":0.013793997,"about_ca_system_score_codex":0.00046998746,"about_ca_system_score_gemma":0.00084164774,"threshold_uncertainty_score":0.027427435},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W1998604986","doi":"10.1038/sj.jcbfm.9600135","title":"MR Perfusion and Diffusion in Acute Ischemic Stroke: Human Gray and White Matter have Different Thresholds for Infarction","year":2005,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Perfusion; Infarction; White matter; Nuclear medicine; Medicine; Cerebral blood flow; Magnetic resonance imaging; Perfusion scanning; Effective diffusion coefficient; Voxel; Diffusion MRI; Stroke (engine); Cardiology; Internal medicine; Radiology; Myocardial infarction; Physics","score_opus":0.01812518800212716,"score_gpt":0.3014277858436252,"score_spread":0.283302597841498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998604986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99612075,0.00097380066,0.0023624585,0.000042401425,0.000002835208,0.000012049652,0.000039954655,0.00001941449,0.00042635005],"genre_scores_gemma":[0.998104,0.00029087297,0.0013555136,0.000025578967,0.000008686471,0.000012794162,0.00006231599,0.00000582048,0.00013449129],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99981755,0.000057443598,0.000015465012,0.00004949384,0.000036502995,0.000023599234],"domain_scores_gemma":[0.99951863,0.00020796857,0.00014531497,0.000033259203,0.000040898205,0.00005395763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006498754,0.00022696111,0.00028518384,0.00051807927,0.00011585061,0.0003597764,0.0001370063,0.0003381375,0.00095401524],"category_scores_gemma":[0.002534857,0.00015049076,0.00008962112,0.0002602368,0.0005190656,0.00037562798,0.00023006515,0.00016523537,0.0002851708],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045181303,0.00017810581,0.45511004,0.00029279143,0.0002431522,0.0014645158,0.0010643286,0.0016425904,0.46771416,0.0008721802,0.00039062562,0.066509314],"study_design_scores_gemma":[0.000045851993,0.0006950261,0.97154826,0.000014424476,0.00006216544,0.0030976497,0.00010907377,0.0013513806,0.021803016,0.00068931846,0.00057074265,0.000012977999],"about_ca_topic_score_codex":0.00050082087,"about_ca_topic_score_gemma":0.00045535102,"teacher_disagreement_score":0.00095401524,"about_ca_system_score_codex":0.00017094368,"about_ca_system_score_gemma":0.00011452585,"threshold_uncertainty_score":0.0034368634},"labels":[],"label_agreement":null},{"id":"W1998912534","doi":"10.1523/jneurosci.4563-11.2011","title":"Lifelong Bilingualism Maintains White Matter Integrity in Older Adults","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":407,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Corpus callosum; Psychology; White matter; Fractional anisotropy; Neuroscience of multilingualism; Diffusion MRI; Functional connectivity; Cognition; Neuroscience; Audiology; Developmental psychology; Cognitive psychology; Medicine; Magnetic resonance imaging","score_opus":0.08210191174784592,"score_gpt":0.3613664424519584,"score_spread":0.2792645307041125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998912534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995333,0.00012099912,0.000023394621,0.000022502807,0.0000015719479,0.0000013735312,0.00002601055,0.0000026126038,0.00026827067],"genre_scores_gemma":[0.9996891,0.000059073234,0.000043184868,0.000013909192,0.0000033763963,0.0000011371047,0.000041397223,9.234604e-7,0.00014791587],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999323,0.000008218979,0.000009585557,0.000021396765,0.000011546278,0.00001702385],"domain_scores_gemma":[0.99965036,0.000026472131,0.00018976214,0.000018953488,0.000048149166,0.000066356995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017527533,0.00016103828,0.0002214337,0.00041134097,0.0004236977,0.00032511982,0.00008901223,0.00024102519,0.0010468514],"category_scores_gemma":[0.0007584553,0.000124555,0.00008625591,0.00015860656,0.0002460653,0.00032320715,0.00025702605,0.00018320823,0.00017084346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018493654,0.00030926164,0.9002385,0.0000841135,0.00012338324,0.001795129,0.004018918,0.00007383059,0.06577127,0.00013556439,0.00034571177,0.025254915],"study_design_scores_gemma":[0.000011399446,0.00022354722,0.9973864,0.000005666221,0.0000185569,0.0007745235,0.00036140165,0.000058890135,0.00091037113,0.00008827752,0.00015756738,0.000003370004],"about_ca_topic_score_codex":0.0030914196,"about_ca_topic_score_gemma":0.008696014,"teacher_disagreement_score":0.0030914196,"about_ca_system_score_codex":0.00017578615,"about_ca_system_score_gemma":0.00016044926,"threshold_uncertainty_score":0.006146848},"labels":[],"label_agreement":null},{"id":"W1999068634","doi":"10.1016/j.neuroimage.2013.05.065","title":"A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":188,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Institute of Child Health and Human Development; National Institute for Health and Care Research; Canadian Institutes of Health Research; McLean Hospital","keywords":"Brain size; Longitudinal data; Volume (thermodynamics); Brain morphometry; Brain anatomy; Neuroscience; Computer science; Psychology; Medicine; Data mining; Magnetic resonance imaging; Radiology; Physics","score_opus":0.050849500093894204,"score_gpt":0.38315679766958416,"score_spread":0.33230729757568994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999068634","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023267819,0.00029025046,0.99552923,0.00006211441,0.000051053543,0.000045316203,0.00024449817,0.0012802707,0.00017048078],"genre_scores_gemma":[0.014619125,0.00047791895,0.98264873,0.000042312106,0.00007128366,0.00025097883,0.00041333426,0.0006886106,0.0007876587],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987055,0.0003461218,0.00014195385,0.00029024386,0.0004579967,0.000058162477],"domain_scores_gemma":[0.9948881,0.0030203718,0.00043797743,0.0006137226,0.0008539568,0.00018591525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038868815,0.0014192666,0.0014486002,0.005550317,0.000972285,0.002275483,0.0016168031,0.0011634406,0.0046754493],"category_scores_gemma":[0.00910647,0.0011706465,0.0019838014,0.004453089,0.0010696261,0.0023972737,0.0019754986,0.0021793977,0.0014376533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038137424,0.00011732905,0.0046692006,0.0006206044,0.0007281022,0.00035092753,0.000457526,0.0196765,0.07708339,0.017414914,0.0075949226,0.87090516],"study_design_scores_gemma":[0.00019312432,0.0003724838,0.018437022,0.00015897657,0.00064584246,0.005453505,0.00023806724,0.84952074,0.044764202,0.036846474,0.042862117,0.0005074822],"about_ca_topic_score_codex":0.005705764,"about_ca_topic_score_gemma":0.006967143,"teacher_disagreement_score":0.005705764,"about_ca_system_score_codex":0.00058183155,"about_ca_system_score_gemma":0.0019522588,"threshold_uncertainty_score":0.020556033},"labels":[],"label_agreement":null},{"id":"W1999743933","doi":"10.1503/jpn.110057","title":"Magnetic resonance imaging correlates of first-episode psychosis in young adult male patients: combined analysis of grey and white matter","year":2012,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Centre d'Imagerie BioMédicale","keywords":"White matter; Inferior longitudinal fasciculus; Fractional anisotropy; Grey matter; Superior longitudinal fasciculus; Arcuate fasciculus; Corpus callosum; Fasciculus; Psychosis; Psychology; Corticospinal tract; Diffusion MRI; Magnetic resonance imaging; Anatomy; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.012464151285470064,"score_gpt":0.28414364143033266,"score_spread":0.2716794901448626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999743933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954104,0.00018633145,0.000035907193,0.0000129525915,0.0000015206928,0.0000052788037,0.0000672844,0.0000018737476,0.00014774242],"genre_scores_gemma":[0.9997558,0.00006574502,0.000042583764,0.000008663437,0.0000038971198,0.000004313422,0.00007747203,6.754364e-7,0.0000408895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998578,0.000023103974,0.000019882293,0.0000349422,0.000031463147,0.00003279115],"domain_scores_gemma":[0.99949324,0.00008164606,0.00027668013,0.00001966914,0.000044299057,0.000084398685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024384819,0.00029088763,0.00038214325,0.000817602,0.00036310425,0.00039309508,0.00015321065,0.00040108853,0.0018203779],"category_scores_gemma":[0.0010264775,0.00020485214,0.00022959556,0.00044392693,0.00022479949,0.00023565654,0.00038651013,0.00020782839,0.00022510665],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025683595,0.000033470213,0.9925565,0.000028159679,0.000048128208,0.0009932272,0.0002477715,0.000030042214,0.0037373279,0.000012859579,0.000043286625,0.002012368],"study_design_scores_gemma":[0.0000034737263,0.00006433112,0.99819666,0.0000039883325,0.000014877147,0.0014266449,0.0001066947,0.000035494813,0.00010153091,0.000010554811,0.000034242526,0.0000014736469],"about_ca_topic_score_codex":0.002036365,"about_ca_topic_score_gemma":0.003373932,"teacher_disagreement_score":0.002036365,"about_ca_system_score_codex":0.0002298468,"about_ca_system_score_gemma":0.00019777683,"threshold_uncertainty_score":0.0060898066},"labels":[],"label_agreement":null},{"id":"W2000237353","doi":"10.1016/j.neuroimage.2009.12.102","title":"Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Tractography; Diffusion MRI; Neuroscience; Functional magnetic resonance imaging; Psychology; Splenium; Magnetic resonance imaging; Brain mapping; Medicine; Radiology","score_opus":0.038046980275423296,"score_gpt":0.3292281667758019,"score_spread":0.2911811865003786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000237353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6865309,0.003614745,0.298605,0.001628095,0.00019240905,0.00052785885,0.00048197864,0.0011449656,0.0072740247],"genre_scores_gemma":[0.872635,0.0018014761,0.12266453,0.00030273883,0.0001416021,0.00021542459,0.0002513645,0.00038164877,0.0016062759],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994429,0.00015544791,0.00006623362,0.0001286157,0.000102633356,0.00010423597],"domain_scores_gemma":[0.9976707,0.00097422267,0.00016834961,0.0003554406,0.0006872382,0.000144066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023705876,0.0008635745,0.0008213237,0.0030247073,0.0016409399,0.0010880065,0.000785203,0.0020610914,0.0027618902],"category_scores_gemma":[0.008176687,0.00054122513,0.0006867341,0.0009508042,0.0017812406,0.0016477031,0.0007970793,0.0013982261,0.0014770622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013931601,0.00016505143,0.019950846,0.00070743123,0.00014915974,0.010699678,0.00078531605,0.0012058136,0.9105068,0.0016611551,0.0009377421,0.05183802],"study_design_scores_gemma":[0.00014247489,0.00059995207,0.060727924,0.00015915668,0.0007028922,0.036640644,0.00079681625,0.022292571,0.86411774,0.004653838,0.009080591,0.000085438995],"about_ca_topic_score_codex":0.0061623678,"about_ca_topic_score_gemma":0.007973713,"teacher_disagreement_score":0.0061623678,"about_ca_system_score_codex":0.00048692146,"about_ca_system_score_gemma":0.001537573,"threshold_uncertainty_score":0.012537003},"labels":[],"label_agreement":null},{"id":"W2000702830","doi":"10.1371/journal.pone.0091400","title":"Differential White Matter Connectivity in Early Mild Cognitive Impairment According to CSF Biomarkers","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Servier; Northern California Institute for Research and Education; University of California, San Diego; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Eisai; Synarc; University of Southern California; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Corpus callosum; Fractional anisotropy; Cerebrospinal fluid; Fasciculus; Dementia; Neuroimaging; Superior longitudinal fasciculus; Internal medicine; Inferior longitudinal fasciculus; Medicine; Psychology; Neuroscience; Pathology; Endocrinology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.06708939899797958,"score_gpt":0.31041641088758803,"score_spread":0.24332701188960845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000702830","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99967873,0.00008553893,0.00004163665,0.000006576312,8.2632545e-7,0.0000037009436,0.000045008277,0.0000014623471,0.0001366147],"genre_scores_gemma":[0.9997582,0.000029828294,0.000052550415,0.0000049971977,0.0000027982753,0.0000033829149,0.000094914794,6.1408895e-7,0.000052745832],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986875,0.000028852784,0.000018295015,0.00003464587,0.000021753007,0.000027680795],"domain_scores_gemma":[0.9996501,0.00008874195,0.00014355982,0.000025332734,0.00003691189,0.00005524536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030375458,0.00037638843,0.0003560311,0.0012714856,0.00024922658,0.00035291823,0.00016803572,0.000269684,0.00087833946],"category_scores_gemma":[0.0014618239,0.00011999221,0.00015432863,0.0003997003,0.00024779642,0.00030165393,0.00038642407,0.00015515967,0.00012809293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016677352,0.000103831044,0.9763165,0.00003194409,0.00014865637,0.0007583026,0.0004620449,0.00012107977,0.010450813,0.000093570874,0.00011827722,0.009727281],"study_design_scores_gemma":[0.000004827843,0.000086763255,0.9989831,0.0000026448345,0.000014454104,0.00036440403,0.000094033894,0.00010410807,0.00022523315,0.0000858557,0.000032423934,0.0000022038962],"about_ca_topic_score_codex":0.0016209933,"about_ca_topic_score_gemma":0.0024117655,"teacher_disagreement_score":0.0016209933,"about_ca_system_score_codex":0.00013931634,"about_ca_system_score_gemma":0.00011099578,"threshold_uncertainty_score":0.0032231212},"labels":[],"label_agreement":null},{"id":"W2001443644","doi":"10.1007/s00415-011-6300-x","title":"Executive dysfunction in frontotemporal dementia is related to abnormalities in frontal white matter tracts","year":2011,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institutes of Natural Sciences; National Institute on Aging; National Institutes of Health","keywords":"Cingulum (brain); Fractional anisotropy; Psychology; White matter; Frontotemporal dementia; Audiology; Corpus callosum; Uncinate fasciculus; Executive dysfunction; Neuropsychology; Posterior cingulate; Atrophy; Frontal lobe; Neuroscience; Dementia; Cognition; Cardiology; Medicine; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.05085422040642587,"score_gpt":0.30905841470486195,"score_spread":0.2582041942984361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001443644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964636,0.0013355828,0.00018200962,0.00013304126,0.000020887845,0.000011637206,0.00013763146,0.000013928443,0.0017016155],"genre_scores_gemma":[0.9985921,0.00049811223,0.00022092614,0.00007194618,0.000064573,0.0000073554165,0.00017364505,0.0000036236254,0.00036771334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998267,0.000033352397,0.00003094578,0.000032978955,0.00004033582,0.000035657424],"domain_scores_gemma":[0.9988458,0.00028109978,0.0005853195,0.000059230402,0.00010924861,0.00011919292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006562199,0.0010666187,0.0005346684,0.0021037695,0.00075986644,0.00087052584,0.0005060927,0.0008854095,0.0022532812],"category_scores_gemma":[0.0017900756,0.0004822026,0.00035419347,0.0011445164,0.00078038685,0.00073019677,0.00034187373,0.0005682289,0.0003386658],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004628107,0.0008655578,0.87141293,0.00024470463,0.0006280946,0.067417964,0.0006901576,0.00038283027,0.029713035,0.00035062968,0.0008250992,0.022840882],"study_design_scores_gemma":[0.000050351973,0.0002236324,0.97656703,0.00002295593,0.00013086028,0.020677062,0.00021643158,0.0003006988,0.0009655702,0.0006314396,0.00020279078,0.000011189749],"about_ca_topic_score_codex":0.00486799,"about_ca_topic_score_gemma":0.006753829,"teacher_disagreement_score":0.00486799,"about_ca_system_score_codex":0.0005186746,"about_ca_system_score_gemma":0.00038618047,"threshold_uncertainty_score":0.0096793175},"labels":[],"label_agreement":null},{"id":"W2001696757","doi":"10.1016/j.neuroimage.2014.03.037","title":"Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":174,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Concordia University; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Anaesthetics Research Society; W. Garfield Weston Foundation; Ontario Mental Health Foundation; Garfield Weston Foundation; National Alliance for Research on Schizophrenia and Depression; Centre for Addiction and Mental Health Foundation; Marathon","keywords":"Template; Segmentation; Computer science; Artificial intelligence; Pattern recognition (psychology); High resolution; Resolution (logic); Cerebellum; Computer vision; Neuroscience; Biology; Geology; Remote sensing","score_opus":0.056387629759392835,"score_gpt":0.3236879625388993,"score_spread":0.2673003327795065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001696757","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010520577,0.00027230498,0.98289305,0.00011287055,0.00007341602,0.00017077144,0.0008228092,0.0034581039,0.001676211],"genre_scores_gemma":[0.1010328,0.0004549834,0.89248496,0.000080500504,0.000037485086,0.00032872643,0.0017618118,0.0017086541,0.0021099828],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951935,0.000058788966,0.000050654035,0.00015660949,0.00017152798,0.0000429978],"domain_scores_gemma":[0.9990295,0.0002844209,0.00012629203,0.00018173222,0.00034244912,0.000035687044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097131054,0.0011987288,0.0009196776,0.0024975676,0.00074570137,0.00231976,0.0015772578,0.0015844158,0.0039604753],"category_scores_gemma":[0.004401736,0.0013872536,0.0022597646,0.0021851948,0.00047274693,0.00093542284,0.0010660178,0.0014866252,0.0029719155],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032559648,0.00011477184,0.0040803757,0.00068876374,0.00048256348,0.0019276675,0.00078010955,0.21944466,0.09295184,0.027997222,0.020123351,0.6310831],"study_design_scores_gemma":[0.00007199568,0.00014129475,0.007775182,0.00015844285,0.0003241575,0.003214618,0.0002002529,0.83439404,0.09625079,0.027239628,0.03006808,0.00016157032],"about_ca_topic_score_codex":0.013345683,"about_ca_topic_score_gemma":0.022182982,"teacher_disagreement_score":0.013345683,"about_ca_system_score_codex":0.0010159517,"about_ca_system_score_gemma":0.0033152811,"threshold_uncertainty_score":0.026535988},"labels":[],"label_agreement":null},{"id":"W2001738903","doi":"10.1002/mrm.21260","title":"Investigation of human cervical and upper thoracic spinal cord motion: Implications for imaging spinal cord structure and function","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; Magnetic resonance imaging; Anatomy; Medicine; Diffusion MRI; Motion (physics); Cardiac cycle; Cord; Physics; Radiology; Cardiology","score_opus":0.07278503174635857,"score_gpt":0.4016625890271151,"score_spread":0.3288775572807565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001738903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701044,0.010502726,0.015496236,0.0005447381,0.000024953666,0.000075773314,0.0003668373,0.00005692298,0.0028274432],"genre_scores_gemma":[0.98035884,0.0058014467,0.012874595,0.00009303535,0.000040135274,0.0000346294,0.0001903246,0.0000089606865,0.0005981834],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995923,0.000010208173,0.0000029659411,0.000012124864,0.000009886866,0.00000558803],"domain_scores_gemma":[0.99985945,0.000060830233,0.000029935223,0.000009074483,0.00002049594,0.000020247304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017106337,0.00017980344,0.00013877964,0.000518405,0.00021148472,0.00027877657,0.00015213511,0.00037155382,0.0010804443],"category_scores_gemma":[0.00077815156,0.00010316537,0.00009135119,0.00043309713,0.00036423572,0.00031059037,0.00014111138,0.00014100068,0.00014246283],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048793227,0.000078319936,0.043052368,0.0007283785,0.000033377903,0.00037439974,0.00037474142,0.0018223326,0.83843344,0.00080363994,0.0004625954,0.11334844],"study_design_scores_gemma":[0.000052210682,0.0013244699,0.864337,0.0001854689,0.00010989098,0.0042964467,0.0006517134,0.015623345,0.10594467,0.0026258717,0.0047918027,0.000057004385],"about_ca_topic_score_codex":0.0028537377,"about_ca_topic_score_gemma":0.0047480697,"teacher_disagreement_score":0.0028537377,"about_ca_system_score_codex":0.00018319531,"about_ca_system_score_gemma":0.0003233178,"threshold_uncertainty_score":0.0056743026},"labels":[],"label_agreement":null},{"id":"W2001805220","doi":"10.1111/j.1528-1167.2007.01006.x","title":"Bilateral White Matter Diffusion Changes Persist after Epilepsy Surgery","year":2007,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Savoy Foundation; National Institutes of Health; University of Alberta; Fondation pour la Recherche Médicale","keywords":"Fornix; White matter; Splenium; Cingulum (brain); Diffusion MRI; Corpus callosum; Fractional anisotropy; Epilepsy; Medicine; Temporal lobe; Psychology; Anatomy; Neuroscience; Hippocampus; Magnetic resonance imaging; Radiology","score_opus":0.040881356948750246,"score_gpt":0.31324765616057015,"score_spread":0.27236629921181993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001805220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99934596,0.00025577124,0.000060690487,0.000024842493,0.0000022761112,0.0000029608027,0.00003643835,0.000006254357,0.00026478348],"genre_scores_gemma":[0.99963593,0.00009590026,0.000038482023,0.000011315712,0.000005811767,0.0000025125255,0.00009521632,0.0000012709469,0.000113592694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990094,0.000009985699,0.000013264299,0.000023747867,0.000023372824,0.000028780556],"domain_scores_gemma":[0.99927396,0.0000713743,0.000455508,0.000036673897,0.000056831006,0.00010562822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019766239,0.00026890475,0.00036849902,0.00036017914,0.00030133544,0.0002667964,0.00010517984,0.00023730537,0.0013271486],"category_scores_gemma":[0.00094834977,0.00009077746,0.00020843722,0.00028268067,0.00032709935,0.0002969656,0.00021202439,0.00024121671,0.00023501455],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013855706,0.00016698062,0.90154934,0.0001224715,0.00017878802,0.012752644,0.0003967274,0.00022289736,0.048782036,0.00007298684,0.00022663258,0.03414293],"study_design_scores_gemma":[0.000021476144,0.0005248728,0.98469156,0.000009801094,0.000035212055,0.011894065,0.00009628511,0.0001053528,0.0022889671,0.00006110438,0.00026542816,0.0000059537083],"about_ca_topic_score_codex":0.0011990749,"about_ca_topic_score_gemma":0.002111163,"teacher_disagreement_score":0.0013271486,"about_ca_system_score_codex":0.00024928004,"about_ca_system_score_gemma":0.00029131837,"threshold_uncertainty_score":0.004439771},"labels":[],"label_agreement":null},{"id":"W2002517543","doi":"10.1016/s8756-3282(00)00237-4","title":"Aging-induced osteopenia in avian cortical bone","year":2000,"lang":"en","type":"article","venue":"Bone","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Aging","keywords":"Rooster; Cortical bone; Osteopenia; Ageing; Anatomy; Osteoporosis; Internal medicine; Medicine; Bone mineral","score_opus":0.05894677940915273,"score_gpt":0.3552478083133669,"score_spread":0.29630102890421417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002517543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927799,0.0035926728,0.0011856927,0.00005300251,0.00001494353,0.000026210982,0.0002403784,0.000028332182,0.002078966],"genre_scores_gemma":[0.99605477,0.001398078,0.0010578776,0.000023912424,0.000006488448,0.000010152811,0.00010429457,0.0000067042524,0.0013375899],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999343,0.000015277528,0.00000608206,0.000013378931,0.000019560432,0.000011390504],"domain_scores_gemma":[0.9998567,0.00003314074,0.000044849,0.000013977191,0.000034444027,0.000016889062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018303574,0.00019685419,0.00012838544,0.0007636546,0.00018531337,0.00014608695,0.00014980369,0.00021960342,0.0011062088],"category_scores_gemma":[0.0002056226,0.00021865155,0.00012448552,0.00023929687,0.00041648856,0.00015547377,0.000111806396,0.00021450085,0.00014032067],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014361029,0.000081621656,0.02421958,0.0003113661,0.00006313817,0.0058393963,0.00022866967,0.00043713703,0.9494086,0.00056593074,0.00024028313,0.01716817],"study_design_scores_gemma":[0.00007663597,0.0016036682,0.6443245,0.000062768304,0.00014567605,0.038024094,0.0009664649,0.0016369844,0.3070936,0.00066645927,0.005370017,0.000029149662],"about_ca_topic_score_codex":0.006379132,"about_ca_topic_score_gemma":0.0090510165,"teacher_disagreement_score":0.006379132,"about_ca_system_score_codex":0.00030247265,"about_ca_system_score_gemma":0.0002213193,"threshold_uncertainty_score":0.012683988},"labels":[],"label_agreement":null},{"id":"W2002529139","doi":"10.1186/1471-2202-12-56","title":"Investigation of fMRI activation in the internal capsule","year":2011,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Internal capsule; Corpus callosum; White matter; Functional magnetic resonance imaging; Neuroscience; Magnetic resonance imaging; Psychology; Brain mapping; Medicine; Anatomy; Radiology","score_opus":0.2515510983112816,"score_gpt":0.3642218239612711,"score_spread":0.11267072564998953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002529139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99310815,0.00038598047,0.0048238244,0.00006522988,0.0000044900703,0.00003389362,0.00006741515,0.00002365531,0.0014874056],"genre_scores_gemma":[0.9927851,0.0002781364,0.006347755,0.000035150235,0.000013667799,0.000049485225,0.00010277063,0.0000089145005,0.0003790992],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99991894,0.00002284751,0.0000060653774,0.000026210766,0.000012515164,0.000013449148],"domain_scores_gemma":[0.9994709,0.00023927173,0.0001572631,0.000029471075,0.00006796085,0.0000352126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043328258,0.0002811835,0.00017589076,0.0004686009,0.00014662731,0.00021273477,0.00015995494,0.00023845985,0.0020287759],"category_scores_gemma":[0.0013914183,0.000076368044,0.00013074548,0.000189458,0.00039507094,0.00023168951,0.00021372426,0.00015916544,0.0001287067],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015017313,0.000107370266,0.032273218,0.0003940809,0.00010997887,0.0006378093,0.00061704236,0.00041909688,0.9279912,0.00046461806,0.00022346088,0.035260346],"study_design_scores_gemma":[0.00015951924,0.0026943465,0.6296892,0.00012356104,0.0003796537,0.008985357,0.00047323527,0.005778903,0.3469146,0.0016215931,0.0031356479,0.000044338354],"about_ca_topic_score_codex":0.00049269304,"about_ca_topic_score_gemma":0.0007705035,"teacher_disagreement_score":0.0020287759,"about_ca_system_score_codex":0.00013677956,"about_ca_system_score_gemma":0.00031268704,"threshold_uncertainty_score":0.006786883},"labels":[],"label_agreement":null},{"id":"W2003174799","doi":"10.1002/ar.b.10024","title":"Quantitative 3D analysis of the canal network in cortical bone by micro‐computed tomography","year":2003,"lang":"en","type":"review","venue":"The Anatomical Record Part B The New Anatomist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":202,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Science and Research Authority; Genome Prairie; Genome Canada; University of Calgary","keywords":"Computer science; Cortical bone; X-ray microtomography; Computed tomography; Cortex (anatomy); Skeletonization; Biomedical engineering; Artificial intelligence; Anatomy; Neuroscience; Medicine; Biology","score_opus":0.06958574776986375,"score_gpt":0.3822171975412235,"score_spread":0.31263144977135976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003174799","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50288343,0.0026444017,0.4860954,0.0003085669,0.000048275415,0.00028718647,0.001829121,0.002145218,0.0037583795],"genre_scores_gemma":[0.8268139,0.001045166,0.17029458,0.000076621356,0.000022094031,0.0002187019,0.0006470451,0.00017973002,0.0007021565],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996736,0.00002638886,0.000018961593,0.000038735474,0.00021285078,0.000029485936],"domain_scores_gemma":[0.9993498,0.0002476747,0.00010894304,0.00005977094,0.00020231919,0.00003157545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047086927,0.00040347787,0.00034763766,0.0033364075,0.00029049467,0.0010911516,0.0003615637,0.0005278196,0.0014209524],"category_scores_gemma":[0.00129353,0.00039383906,0.0002846756,0.0017803159,0.0005299273,0.0004986276,0.00039085528,0.00037403748,0.00019974283],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028188317,0.00007099607,0.026911266,0.00073993724,0.000109879,0.00071046024,0.00068879087,0.113002636,0.7334901,0.006529646,0.0014487585,0.11601551],"study_design_scores_gemma":[0.000039858427,0.000112647635,0.15496588,0.00016655405,0.00014091394,0.0024645617,0.0004986472,0.6443579,0.18097933,0.0047976873,0.011237879,0.00023818776],"about_ca_topic_score_codex":0.0056468914,"about_ca_topic_score_gemma":0.006175901,"teacher_disagreement_score":0.0056468914,"about_ca_system_score_codex":0.00049345446,"about_ca_system_score_gemma":0.0007942731,"threshold_uncertainty_score":0.011228025},"labels":[],"label_agreement":null},{"id":"W2003343999","doi":"10.1016/j.neuroimage.2008.09.054","title":"Postmortem interval alters the water relaxation and diffusion properties of rat nervous tissue — Implications for MRI studies of human autopsy samples","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":129,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Spinal cord; White matter; In vivo; Central nervous system; Diffusion MRI; Autopsy; Fixation (population genetics); Nervous tissue; Chemistry; Perfusion; Pathology; Anatomy; Magnetic resonance imaging; Medicine; Biology; Neuroscience; Internal medicine; Radiology","score_opus":0.17544763227774493,"score_gpt":0.3810734649209096,"score_spread":0.20562583264316467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003343999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945314,0.0024419592,0.0020429345,0.00008083893,0.000040791972,0.000014368273,0.00029135018,0.00003333067,0.0005230244],"genre_scores_gemma":[0.9956416,0.0017532893,0.0013089224,0.00005283507,0.000017161217,0.000023573753,0.00031103365,0.000028810371,0.00086266914],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999187,0.000016833734,0.000008280659,0.0000280219,0.000010745923,0.000017491297],"domain_scores_gemma":[0.9996706,0.000068434434,0.00012962842,0.00006473961,0.000030406978,0.00003613405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031903625,0.0003168351,0.00021510893,0.0004447722,0.00031065315,0.00035963053,0.00027104892,0.00037814278,0.0014816956],"category_scores_gemma":[0.00086377,0.0002275303,0.00019216153,0.00024976252,0.00040090698,0.0005032049,0.00019274304,0.00056366215,0.0002203438],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008121868,0.00020875498,0.006670451,0.00016064169,0.00007429048,0.0010998783,0.00021860273,0.00014823838,0.9739985,0.0003804712,0.00016027366,0.00875793],"study_design_scores_gemma":[0.0001251517,0.003160303,0.14593793,0.00005841102,0.00035036486,0.004014098,0.0006559584,0.00079977437,0.84165484,0.0009491598,0.0022578547,0.000036170888],"about_ca_topic_score_codex":0.00091149233,"about_ca_topic_score_gemma":0.0013288688,"teacher_disagreement_score":0.0014816956,"about_ca_system_score_codex":0.00015774912,"about_ca_system_score_gemma":0.00016101325,"threshold_uncertainty_score":0.0049567223},"labels":[],"label_agreement":null},{"id":"W2003370843","doi":"10.1093/brain/awn099","title":"Response monitoring, repetitive behaviour and anterior cingulate abnormalities in autism spectrum disorders (ASD)","year":2008,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":364,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Mental Health; U.S. Department of Energy","keywords":"Anterior cingulate cortex; Autism; Fractional anisotropy; Psychology; Diffusion MRI; Neuroscience; Autism spectrum disorder; Audiology; White matter; Cognition; Developmental psychology; Medicine; Magnetic resonance imaging","score_opus":0.03263168379777566,"score_gpt":0.32732045638226437,"score_spread":0.2946887725844887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003370843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995988,0.00007907966,0.00012735664,0.000009540106,7.861623e-7,0.00000393642,0.000038351376,0.000008729566,0.0001332847],"genre_scores_gemma":[0.9994086,0.00004653109,0.0003865951,0.000007024313,0.0000016219693,0.0000066382186,0.000059262926,0.0000021979154,0.00008144605],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985063,0.000028030041,0.000023055014,0.000051886895,0.00003109669,0.000015330586],"domain_scores_gemma":[0.9992705,0.00012982811,0.00043248892,0.00003973996,0.00005946119,0.000067911926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002367332,0.00037011056,0.00014038598,0.0007799159,0.00019796795,0.00022661146,0.00014654722,0.00032016702,0.00092245697],"category_scores_gemma":[0.0012488746,0.00018129568,0.0001292126,0.00020857343,0.00037043568,0.00017194593,0.00032090343,0.00019111088,0.00009197065],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007157922,0.00014674584,0.8753534,0.000111401925,0.00007576909,0.0021259221,0.0010824824,0.00025712463,0.09960284,0.0000695604,0.00014167563,0.020317124],"study_design_scores_gemma":[0.000004833969,0.00011500993,0.99699545,0.0000049773325,0.000010495192,0.0018237955,0.00009675363,0.00014998906,0.0007110185,0.000029664589,0.000055273114,0.0000027608555],"about_ca_topic_score_codex":0.0039334376,"about_ca_topic_score_gemma":0.0074897273,"teacher_disagreement_score":0.0039334376,"about_ca_system_score_codex":0.00020818698,"about_ca_system_score_gemma":0.00012271869,"threshold_uncertainty_score":0.007821083},"labels":[],"label_agreement":null},{"id":"W2003728643","doi":"10.1159/000323022","title":"Somatotopic Arrangement of the Corticospinal Tract at the Medullary Pyramid in the Human Brain","year":2011,"lang":"en","type":"article","venue":"European Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corticospinal tract; Diffusion MRI; Tractography; Human brain; Pyramidal tracts; Anatomy; Neuroscience; Medullary cavity; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.10066587102591618,"score_gpt":0.32900847486954216,"score_spread":0.22834260384362598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003728643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959997,0.00021326166,0.00217136,0.00006060344,0.0000016818097,0.000012518649,0.00011586932,0.000027712402,0.0013973643],"genre_scores_gemma":[0.9987264,0.00009743179,0.0009264687,0.000010248249,0.0000031542559,0.000005253908,0.000041275085,0.0000022421611,0.00018764964],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999943,0.000011330441,0.0000038035273,0.000016251328,0.000017782077,0.000007780343],"domain_scores_gemma":[0.9998486,0.000034519217,0.00005198426,0.000012324568,0.000031086904,0.000021465341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014785919,0.00014765278,0.00007859078,0.00061053963,0.00014538449,0.00021098924,0.00007663336,0.00015731921,0.0023900794],"category_scores_gemma":[0.00075314357,0.00009050821,0.00006494952,0.00026326618,0.00048030363,0.00025476122,0.00017200431,0.0000737755,0.0002144348],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013035348,0.0000740411,0.26152617,0.0003976305,0.00012748444,0.0029779505,0.0030629928,0.0025737532,0.65055037,0.0020772777,0.00093267445,0.074396096],"study_design_scores_gemma":[0.000030617368,0.0001967726,0.9806347,0.00002634707,0.00002908159,0.005078095,0.00038426652,0.0018730218,0.009104509,0.0018825668,0.00074181077,0.000018238443],"about_ca_topic_score_codex":0.0024470016,"about_ca_topic_score_gemma":0.005335547,"teacher_disagreement_score":0.0024470016,"about_ca_system_score_codex":0.00013504941,"about_ca_system_score_gemma":0.00027317912,"threshold_uncertainty_score":0.007995665},"labels":[],"label_agreement":null},{"id":"W2004087319","doi":"10.1021/bi100308d","title":"Interaction of Myelin Basic Protein with Actin in the Presence of Dodecylphosphocholine Micelles","year":2010,"lang":"en","type":"article","venue":"Biochemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Chemistry; Myelin; Actin; Myelin basic protein; Microfilament; Biophysics; Actin-binding protein; Citrullination; Cell biology; Biochemistry; Actin cytoskeleton; Cytoskeleton; Biology; Cell; Central nervous system","score_opus":0.026632719441036557,"score_gpt":0.3300988287992694,"score_spread":0.3034661093582328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004087319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99722064,0.0009321646,0.00082672597,0.00004754649,0.00001853334,0.000033327353,0.00006387319,0.000020663549,0.000836517],"genre_scores_gemma":[0.9936434,0.0012477427,0.0028976712,0.00007278973,0.000017487771,0.00006248824,0.00044830193,0.000026470065,0.0015835766],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996356,0.00011619951,0.000023997929,0.00005934245,0.00008217555,0.00008268503],"domain_scores_gemma":[0.99980766,0.000053626496,0.000045310273,0.00001329325,0.000044145032,0.00003607248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031781284,0.00052008184,0.00026429654,0.0001588504,0.00015844303,0.0002608041,0.00033542575,0.0003447794,0.00058374985],"category_scores_gemma":[0.00031985916,0.00018393483,0.00019679473,0.00020751989,0.00015337039,0.00022076901,0.0002217612,0.0005421555,0.0002453124],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012297566,0.000045927365,0.00012927734,0.00006383429,0.000012113049,0.000027261976,0.000031398937,0.00006179307,0.998818,0.00005219313,0.00002716341,0.0006079846],"study_design_scores_gemma":[0.000028185752,0.0004104076,0.0016840823,0.000013499821,0.00001618425,0.00005230676,0.000025818317,0.0014832516,0.9948295,0.000019054673,0.0014299158,0.0000078346675],"about_ca_topic_score_codex":0.0010282819,"about_ca_topic_score_gemma":0.0009777346,"teacher_disagreement_score":0.0010282819,"about_ca_system_score_codex":0.00020253901,"about_ca_system_score_gemma":0.00022583862,"threshold_uncertainty_score":0.0020446181},"labels":[],"label_agreement":null},{"id":"W2004299377","doi":"10.1007/s00247-009-1255-0","title":"Abnormal fetal cerebral laminar organization in cobblestone complex as seen on post-mortem MRI and DTI","year":2009,"lang":"en","type":"article","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Medicine; Cerebrum; Neuroradiology; Autopsy; Tractography; Fractional anisotropy; Pathology; Laminar flow; Fetus; Anatomy; Magnetic resonance imaging; Radiology; Neurology; Central nervous system; Pregnancy; Internal medicine; Biology","score_opus":0.028408956034250157,"score_gpt":0.31547368378788654,"score_spread":0.2870647277536364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004299377","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791925,0.0014766713,0.008484032,0.00090132136,0.00013524572,0.000085907996,0.00043849717,0.00018608564,0.00909973],"genre_scores_gemma":[0.99472165,0.00067968253,0.0030433498,0.00014100288,0.000079426456,0.000025033673,0.00020618165,0.000047216676,0.0010564555],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99978024,0.000023298415,0.000029458892,0.00004545536,0.000048489157,0.00007306655],"domain_scores_gemma":[0.99890554,0.00037575394,0.00032403227,0.0001420859,0.00014304864,0.000109571316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042865545,0.0005487313,0.0002982785,0.0018133257,0.00043196368,0.00066150044,0.00063123624,0.0013627503,0.0031401631],"category_scores_gemma":[0.0026934429,0.0005093849,0.0002435257,0.0005878516,0.0017299782,0.0007477992,0.00042684437,0.0012491476,0.000646422],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00200523,0.00017959197,0.06607237,0.00026217342,0.00013749258,0.6564471,0.0007494898,0.0016704195,0.24013644,0.00322783,0.001806819,0.02730493],"study_design_scores_gemma":[0.00011466124,0.00033791875,0.24432157,0.00012505874,0.0002158601,0.62397707,0.0005930599,0.0039160517,0.118655354,0.0027198747,0.004952563,0.00007096458],"about_ca_topic_score_codex":0.006279872,"about_ca_topic_score_gemma":0.0036535973,"teacher_disagreement_score":0.006279872,"about_ca_system_score_codex":0.0005192252,"about_ca_system_score_gemma":0.0006129059,"threshold_uncertainty_score":0.012486637},"labels":[],"label_agreement":null},{"id":"W2004302472","doi":"10.1017/s0317167100015560","title":"Tractography in the Study of the Human Brain: A Neurosurgical Perspective","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; White matter; Arcuate fasciculus; Superior longitudinal fasciculus; Diffusion MRI; Neuroscience; Inferior longitudinal fasciculus; Corpus callosum; Uncinate fasciculus; Corticospinal tract; Psychology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09812529099306126,"score_gpt":0.3664611723238286,"score_spread":0.2683358813307673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004302472","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048357997,0.4102711,0.50092673,0.023378456,0.0013670009,0.00021796666,0.0004086688,0.00071607897,0.0143559305],"genre_scores_gemma":[0.29645407,0.30595154,0.385765,0.0019094143,0.0035201877,0.00028825813,0.00027846007,0.00045472037,0.0053783827],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994368,0.00031490548,0.000053496293,0.00008563011,0.000085253814,0.000023868139],"domain_scores_gemma":[0.9962261,0.0028973198,0.0002037552,0.00026305442,0.0002628756,0.00014678345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031398556,0.0006319275,0.0007790802,0.004210119,0.0003907124,0.0020622115,0.0007795893,0.0018838394,0.0026872735],"category_scores_gemma":[0.0054018456,0.00033442013,0.0006245048,0.0032014453,0.0056197834,0.0029711497,0.0007716652,0.0013899045,0.0006048016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029605874,0.0001240764,0.023198273,0.0048046284,0.00057353533,0.003484307,0.0024152866,0.042525787,0.035870634,0.23065516,0.010941156,0.6451111],"study_design_scores_gemma":[0.000060957078,0.00072960905,0.035297778,0.0024518482,0.00021031343,0.013699082,0.0012995454,0.040733404,0.012166868,0.6676757,0.22541478,0.00026011985],"about_ca_topic_score_codex":0.0044562737,"about_ca_topic_score_gemma":0.0041790972,"teacher_disagreement_score":0.0044562737,"about_ca_system_score_codex":0.0012928963,"about_ca_system_score_gemma":0.0016416922,"threshold_uncertainty_score":0.016605318},"labels":[],"label_agreement":null},{"id":"W2004421347","doi":"10.1016/j.neurobiolaging.2006.09.013","title":"Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls","year":2006,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":281,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute of Mental Health","keywords":"Parahippocampal gyrus; Overtraining; Linear discriminant analysis; Gyrus; Medicine; Temporal lobe; Neuroscience; Pathology; Pattern recognition (psychology); Psychology; Artificial intelligence; Computer science; Epilepsy","score_opus":0.08276855514881212,"score_gpt":0.34811652876147176,"score_spread":0.2653479736126596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004421347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99448675,0.00074246834,0.0030953372,0.000053574695,0.000048660575,0.000015598442,0.00034943855,0.00016367783,0.0010445991],"genre_scores_gemma":[0.9972257,0.00022869208,0.0018691177,0.000039511564,0.000030220352,0.000008870662,0.00026891087,0.000017482793,0.0003114501],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997471,0.00007641166,0.00004099394,0.00005705846,0.00005480005,0.000023649027],"domain_scores_gemma":[0.99822015,0.0007730355,0.00038695114,0.00017478802,0.0003587514,0.00008621507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007949403,0.0006451467,0.0005644205,0.0013390089,0.00019131198,0.0006278519,0.00030440543,0.00049720355,0.0006026171],"category_scores_gemma":[0.0039599333,0.00021621685,0.00018737941,0.000415125,0.00019479977,0.00047573165,0.00021544658,0.00029993444,0.00031146573],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038886007,0.0002770251,0.80877626,0.0001670374,0.0005410624,0.000668395,0.00032364202,0.0025701344,0.036368065,0.00017406518,0.0027404116,0.14350533],"study_design_scores_gemma":[0.00006405479,0.00026684915,0.98020536,0.000015862099,0.00014000422,0.0015832372,0.00012137695,0.011027198,0.0055256933,0.00034581524,0.0006843206,0.000020311958],"about_ca_topic_score_codex":0.0023589467,"about_ca_topic_score_gemma":0.0035702037,"teacher_disagreement_score":0.0023589467,"about_ca_system_score_codex":0.0001429298,"about_ca_system_score_gemma":0.0001472014,"threshold_uncertainty_score":0.0046904683},"labels":[],"label_agreement":null},{"id":"W2005112198","doi":"10.1016/j.neulet.2007.04.049","title":"Fronto-striatal connections in the human brain: A probabilistic diffusion tractography study","year":2007,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":359,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University; Toronto Western Hospital; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Putamen; Neuroscience; Caudate nucleus; Basal ganglia; Thalamus; Premotor cortex; Prefrontal cortex; Striatum; Tractography; Dorsolateral prefrontal cortex; Supplementary motor area; Primary motor cortex; Psychology; Human brain; Diffusion MRI; Motor cortex; Biology; Anatomy; Functional magnetic resonance imaging; Medicine; Central nervous system; Dorsum; Magnetic resonance imaging; Dopamine","score_opus":0.07575795002800048,"score_gpt":0.3728317952173892,"score_spread":0.29707384518938873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005112198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97933984,0.0007366499,0.017691711,0.00031996644,0.0000062901777,0.000037152367,0.00021997349,0.00003938788,0.0016090452],"genre_scores_gemma":[0.98955256,0.000508681,0.009019129,0.00003831479,0.000019093257,0.000018078166,0.000107698506,0.00003566243,0.0007007173],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986124,0.000053871263,0.000007810066,0.00003500289,0.000027432638,0.000014525607],"domain_scores_gemma":[0.9990429,0.000630913,0.00010938788,0.00014180667,0.000042690706,0.000032322485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085237663,0.00034460097,0.00033721904,0.0005097679,0.00044408944,0.0009096854,0.00044296798,0.0008076883,0.0018637876],"category_scores_gemma":[0.0040320335,0.00056460046,0.00038450627,0.0006917795,0.0010372966,0.0014391807,0.0003667572,0.0005971814,0.00027778352],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0073568323,0.0013506929,0.13427648,0.0012538194,0.0016370083,0.011417648,0.006251634,0.08343978,0.46867168,0.05404506,0.0030902473,0.22720917],"study_design_scores_gemma":[0.00077375624,0.0013442452,0.62104714,0.0001125997,0.00095681415,0.03706334,0.0010471258,0.20870721,0.047076743,0.07260251,0.009016851,0.00025163224],"about_ca_topic_score_codex":0.006473538,"about_ca_topic_score_gemma":0.008949862,"teacher_disagreement_score":0.006473538,"about_ca_system_score_codex":0.0003604866,"about_ca_system_score_gemma":0.0006567983,"threshold_uncertainty_score":0.012871742},"labels":[],"label_agreement":null},{"id":"W2005300500","doi":"10.1016/j.neulet.2011.01.070","title":"Genetic and environmental influences on structural variability of the brain in pediatric twin: Deformation based morphometry","year":2011,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"Putamen; Brain morphometry; Corpus callosum; Heritability; Voxel-based morphometry; Twin study; Brain size; Voxel; Globus pallidus; Biology; Neuroimaging; White matter; Atrophy; Neuroscience; Psychology; Evolutionary biology; Genetics; Medicine; Central nervous system; Magnetic resonance imaging; Basal ganglia","score_opus":0.03058218078312898,"score_gpt":0.2707102656751852,"score_spread":0.24012808489205623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005300500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99831307,0.00008921755,0.0012117414,0.00005133383,0.000004512828,0.0000022415772,0.000116822506,0.0000075564117,0.00020347527],"genre_scores_gemma":[0.99847966,0.00013924963,0.0011688926,0.0000076226092,0.00000657752,0.000004584546,0.00008116032,0.000022794635,0.00008949595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999458,0.0001610268,0.00004461113,0.00015745076,0.00013011292,0.000048835733],"domain_scores_gemma":[0.99860865,0.0005598099,0.00042663811,0.00022743519,0.00010354801,0.00007387698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079167594,0.0004283497,0.00037329207,0.0013545402,0.00040833905,0.0004995508,0.0003700619,0.00037843763,0.0010908633],"category_scores_gemma":[0.0048856423,0.0003314881,0.0005173999,0.0015723453,0.0006738806,0.0005003087,0.0007100875,0.00048062328,0.00007978629],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009090003,0.00006710398,0.9146828,0.000056940036,0.000575867,0.0025412517,0.0014590884,0.00443307,0.049046464,0.002512711,0.00034744779,0.023368359],"study_design_scores_gemma":[0.000005659419,0.00004387378,0.99043524,0.000009233943,0.00015073178,0.0028190515,0.00024762185,0.0028736738,0.0026784244,0.0005305344,0.00019149504,0.000014508327],"about_ca_topic_score_codex":0.004946671,"about_ca_topic_score_gemma":0.00602363,"teacher_disagreement_score":0.004946671,"about_ca_system_score_codex":0.00024744865,"about_ca_system_score_gemma":0.0003670048,"threshold_uncertainty_score":0.00983578},"labels":[],"label_agreement":null},{"id":"W2005487413","doi":"10.1002/hbm.21484","title":"Whole‐brain white matter disruption in semantic and nonfluent variants of primary progressive aphasia","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network; Health Sciences Centre; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; University of Toronto; Heart and Stroke Foundation of Canada","keywords":"White matter; Primary progressive aphasia; Diffusion MRI; Fractional anisotropy; Atrophy; Pathology; Grey matter; Audiology; Psychology; Neuroscience; Voxel-based morphometry; Medicine; Magnetic resonance imaging; Frontotemporal dementia; Radiology; Dementia","score_opus":0.08366397990442903,"score_gpt":0.33407337270708753,"score_spread":0.2504093928026585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005487413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99980813,0.000033665776,0.00006170626,0.0000045894676,7.4483086e-7,0.0000031557818,0.000014894274,0.000002810815,0.00007033857],"genre_scores_gemma":[0.9997596,0.000020098654,0.00012946945,0.0000065285635,0.0000018122026,0.0000033201404,0.000033533124,0.0000016330813,0.00004400303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997621,0.000043340147,0.00003729131,0.00008982771,0.000041772255,0.00002572827],"domain_scores_gemma":[0.99953187,0.00011326231,0.00021078998,0.000042014544,0.00003357687,0.00006848141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031289464,0.00049774745,0.00035194805,0.0013175624,0.0004223088,0.0003935739,0.0002059864,0.00042542894,0.00097133045],"category_scores_gemma":[0.001232172,0.00033433916,0.00024218737,0.00040597783,0.0009203075,0.00038337967,0.00041610678,0.00025250216,0.00020221059],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011175686,0.00022099378,0.9164269,0.00010181252,0.00025294258,0.008783106,0.0019744562,0.00035535754,0.054891862,0.0001843474,0.0001317082,0.015558994],"study_design_scores_gemma":[0.000028365635,0.000465877,0.98405623,0.0000048470247,0.000027087854,0.013953577,0.0002784796,0.00022039298,0.00075113337,0.00014532148,0.000060423903,0.000008205485],"about_ca_topic_score_codex":0.0021324218,"about_ca_topic_score_gemma":0.0035932066,"teacher_disagreement_score":0.0021324218,"about_ca_system_score_codex":0.00022595322,"about_ca_system_score_gemma":0.00018250037,"threshold_uncertainty_score":0.004240036},"labels":[],"label_agreement":null},{"id":"W2005495240","doi":"10.1523/jneurosci.1619-09.2010","title":"<i>In Vivo</i>Diffusion Tensor Imaging and Histopathology of the Fimbria-Fornix in Temporal Lobe Epilepsy","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":215,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Savoy Foundation; National Institutes of Health; University of Alberta; National Center for Research Resources; Directorate for Biological Sciences; Fondation pour la Recherche Médicale","keywords":"Fornix; Temporal lobe; Diffusion MRI; White matter; Anatomy; Pathology; Hippocampus; Fractional anisotropy; Medicine; Neuroscience; Biology; Epilepsy; Magnetic resonance imaging; Radiology","score_opus":0.02665710038749993,"score_gpt":0.32383076454889814,"score_spread":0.29717366416139823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005495240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982035,0.0004047706,0.00054776587,0.000079952966,0.0000047416456,0.000010534319,0.00005976157,0.000007637373,0.00068138185],"genre_scores_gemma":[0.999057,0.00024719114,0.0003964423,0.00002365401,0.000010033932,0.000008454915,0.00009991997,0.0000022566692,0.00015502425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999156,0.000025678848,0.000015113519,0.000018882192,0.000010051178,0.000014660392],"domain_scores_gemma":[0.9997805,0.000034025154,0.00009516562,0.000024628813,0.000031917923,0.000033787554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034962554,0.00016432453,0.000093775496,0.00069661066,0.00022227898,0.00029851604,0.00013237126,0.00031589647,0.00093432405],"category_scores_gemma":[0.0006741272,0.00012918253,0.0000727722,0.00018805887,0.0005080277,0.00036915738,0.00020929339,0.00017383795,0.00019901399],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021797083,0.00015777908,0.48335162,0.00022232442,0.00009887999,0.012266232,0.0007677602,0.0004983218,0.4805084,0.00054239854,0.00070955476,0.018697001],"study_design_scores_gemma":[0.00002559918,0.00052887085,0.95721465,0.000017601125,0.000032301752,0.020269595,0.00044805545,0.00056440366,0.019944062,0.00022756933,0.0007151618,0.000012163188],"about_ca_topic_score_codex":0.0010774883,"about_ca_topic_score_gemma":0.001313565,"teacher_disagreement_score":0.0010774883,"about_ca_system_score_codex":0.000214161,"about_ca_system_score_gemma":0.00012568614,"threshold_uncertainty_score":0.0031256676},"labels":[],"label_agreement":null},{"id":"W2006080132","doi":"10.1016/j.neuroimage.2005.07.008","title":"Neuroanatomical differences between mouse strains as shown by high-resolution 3D MRI","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; Hospital for Sick Children","funders":"Canada Foundation for Innovation; Canadian Institutes of Health Research; Ontario Innovation Trust; Burroughs Wellcome Fund","keywords":"Neuroanatomy; Magnetic resonance imaging; Hippocampus; Strain (injury); High resolution; Artificial intelligence; Standard deviation; Biology; Lateral ventricles; Metric (unit); Anatomy; Pattern recognition (psychology); Neuroscience; Computer science; Mathematics; Medicine; Radiology; Geology; Statistics","score_opus":0.04755365049794241,"score_gpt":0.330409585953324,"score_spread":0.28285593545538157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006080132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95897317,0.0017411546,0.027602518,0.00096587377,0.00038444853,0.0001793972,0.004492606,0.00090598647,0.004754841],"genre_scores_gemma":[0.93651414,0.002010894,0.03254092,0.000929655,0.00008195949,0.0008767979,0.0044922307,0.0014916428,0.021061832],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988091,0.00013231751,0.00018789692,0.00040757077,0.00028767466,0.0001754645],"domain_scores_gemma":[0.9979997,0.0002673754,0.00073475216,0.0003241262,0.00026265893,0.00041133986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092342036,0.00107162,0.000562053,0.0034184258,0.0006428861,0.0011527719,0.00096937513,0.0014758229,0.004970863],"category_scores_gemma":[0.0009534222,0.0009694983,0.0009120917,0.0005479935,0.0012740587,0.0012218888,0.0010335905,0.0027129592,0.0011433586],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046928352,0.00009971295,0.000369597,0.000029969824,0.000034872326,0.00012646052,0.000055156066,0.000040844563,0.9970517,0.000473699,0.00011911132,0.0011296609],"study_design_scores_gemma":[0.00011995982,0.00055132125,0.022709662,0.000034415243,0.00020848506,0.0014346027,0.0001948407,0.0008878518,0.9690383,0.00082732027,0.0039342316,0.00005901969],"about_ca_topic_score_codex":0.0011739423,"about_ca_topic_score_gemma":0.0019055133,"teacher_disagreement_score":0.004970863,"about_ca_system_score_codex":0.00050718675,"about_ca_system_score_gemma":0.00036025248,"threshold_uncertainty_score":0.01662916},"labels":[],"label_agreement":null},{"id":"W2006419171","doi":"10.1002/hbm.21437","title":"Transcallosal sensorimotor fiber tract structure‐function relationships","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health","keywords":"Corpus callosum; Neuroscience; White matter; Diffusion MRI; Psychology; Fiber tract; Inhibitory postsynaptic potential; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.21177140730277447,"score_gpt":0.3344824964312587,"score_spread":0.12271108912848425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006419171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890365,0.00041285765,0.009019091,0.000023755236,0.0000027234044,0.000014066393,0.00036149303,0.00006798065,0.0010615776],"genre_scores_gemma":[0.99709225,0.00017118327,0.002046538,0.000008227924,0.0000035138596,0.000013063893,0.00022005475,0.000016487116,0.00042860844],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998503,0.000022975353,0.000012254011,0.000058915535,0.000034842575,0.000020678222],"domain_scores_gemma":[0.9991309,0.00022989727,0.00038370935,0.00008350932,0.000112199516,0.000059800153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035445072,0.0003974646,0.00023054914,0.0008318396,0.00017419219,0.0003245141,0.00014948065,0.00020822609,0.0022218006],"category_scores_gemma":[0.0016898763,0.00015972358,0.00021002283,0.0003963125,0.00024548577,0.00033294564,0.00030808157,0.00021312376,0.00023473821],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003772645,0.00007132342,0.31501898,0.00019911789,0.00042421682,0.0005404379,0.0007688818,0.0031297721,0.6160014,0.0010461272,0.00024537367,0.06217708],"study_design_scores_gemma":[0.0000028418203,0.00009210771,0.98265713,0.000005969373,0.00003520052,0.00061515183,0.00004643921,0.0026092767,0.013155411,0.00051565975,0.00025574668,0.000009145758],"about_ca_topic_score_codex":0.002915987,"about_ca_topic_score_gemma":0.005802051,"teacher_disagreement_score":0.002915987,"about_ca_system_score_codex":0.00018947788,"about_ca_system_score_gemma":0.00020680742,"threshold_uncertainty_score":0.0074326396},"labels":[],"label_agreement":null},{"id":"W2007069085","doi":"10.1615/critrevbiomedeng.v40.i1.10","title":"Diffusion Tensor Imaging in the Human Spinal Cord: Development, Limitations, and Clinical Applications","year":2012,"lang":"en","type":"review","venue":"Critical Reviews in Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Diffusion MRI; White matter; Spinal cord; Spinal cord injury; Multiple sclerosis; Magnetic resonance imaging; Neuroscience; Medicine; Amyotrophic lateral sclerosis; Tractography; Diffusion imaging; Myelitis; Pathology; Radiology; Psychology","score_opus":0.325175588118223,"score_gpt":0.5154178681987168,"score_spread":0.19024228008049382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007069085","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032738174,0.9971554,0.0010249749,0.00051872974,0.0001467911,0.00000632877,0.00001134245,0.000009975066,0.00079906156],"genre_scores_gemma":[0.0019163191,0.9957476,0.0014594279,0.00016004911,0.00022879278,0.00001328014,0.000018546563,0.000005091766,0.00045094336],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993563,0.00014548411,0.00008986536,0.00012135244,0.00024538516,0.000041564635],"domain_scores_gemma":[0.9981198,0.000946766,0.00023412891,0.00006366344,0.0005474073,0.00008812996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021996652,0.0011102585,0.0016087412,0.00226984,0.00032195088,0.0015989183,0.0011844876,0.0018090198,0.0021084493],"category_scores_gemma":[0.0026962867,0.0005087376,0.00051827705,0.002283958,0.0014133105,0.0023481583,0.00081338873,0.0020288571,0.0022381267],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061995386,0.00004800996,0.00049827667,0.011482605,0.00008262989,0.00035925116,0.00013485545,0.0005907551,0.0068038697,0.0055282954,0.009529968,0.9648796],"study_design_scores_gemma":[0.000030535717,0.00039458103,0.0035836655,0.008043284,0.00024839677,0.0075297016,0.00029988325,0.0012001138,0.009489559,0.011403766,0.9576496,0.00012700836],"about_ca_topic_score_codex":0.00248734,"about_ca_topic_score_gemma":0.0025164534,"teacher_disagreement_score":0.00248734,"about_ca_system_score_codex":0.00090578175,"about_ca_system_score_gemma":0.0024636784,"threshold_uncertainty_score":0.011633098},"labels":[],"label_agreement":null},{"id":"W2007162694","doi":"10.1002/mrm.10270","title":"Human erythrocyte ghosts: Exploring the origins of multiexponential water diffusion in a model biological tissue with magnetic resonance","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Permeability (electromagnetism); Chemistry; Extracellular; Diffusion; Biophysics; Compartment (ship); Cellular compartment; Membrane; Membrane permeability; Cell membrane; Nuclear magnetic resonance; Biological system; Cell; Thermodynamics; Biochemistry; Physics","score_opus":0.11531456346379637,"score_gpt":0.3327923303412229,"score_spread":0.21747776687742654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007162694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83136606,0.0019249548,0.16549233,0.00021496313,0.000044392484,0.00007357904,0.0002344842,0.00012886667,0.0005204314],"genre_scores_gemma":[0.89790064,0.001495893,0.09908582,0.000048967115,0.000017327739,0.00008426761,0.00036383612,0.00004069331,0.00096255314],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989283,0.000039686518,0.0000069736047,0.00002378668,0.000025744936,0.000010960803],"domain_scores_gemma":[0.9996216,0.0002137561,0.00006210053,0.00004403154,0.000030729036,0.000027671897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044604315,0.0004310127,0.00054732064,0.0002093315,0.00019186584,0.0003553461,0.00042023315,0.0006071337,0.00019269105],"category_scores_gemma":[0.0011066736,0.00023470576,0.00029740587,0.00028385033,0.00032954614,0.00056415825,0.00036474565,0.00053830055,0.00008753079],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033774835,0.0000686006,0.0012246085,0.00018053126,0.00003973203,0.0003588335,0.00008950815,0.053456962,0.9382379,0.002155718,0.000108543514,0.0037412245],"study_design_scores_gemma":[0.00009681898,0.00078685617,0.003342119,0.000021024855,0.0000860822,0.0009412919,0.000041955198,0.5548925,0.4351471,0.0021667911,0.0024197649,0.000057670633],"about_ca_topic_score_codex":0.0017014351,"about_ca_topic_score_gemma":0.0010368208,"teacher_disagreement_score":0.0017014351,"about_ca_system_score_codex":0.00035519796,"about_ca_system_score_gemma":0.00043202814,"threshold_uncertainty_score":0.0033830404},"labels":[],"label_agreement":null},{"id":"W2007276643","doi":"10.1002/mrm.20008","title":"MR properties of excised neural tissue following experimentally induced inflammation","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Inflammation; Histopathology; Magnetization transfer; Sciatic nerve; Brain tissue; Chemistry; Pathology; Nuclear magnetic resonance; Necrosis; Anatomy; Medicine; Magnetic resonance imaging; Internal medicine; Physics; Radiology","score_opus":0.07435044444015612,"score_gpt":0.3554056399747598,"score_spread":0.2810551955346037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007276643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99369884,0.0024564802,0.0028675152,0.000019697962,0.000020478788,0.000021004353,0.00014711428,0.000025756433,0.0007431193],"genre_scores_gemma":[0.99252105,0.0017533418,0.0034606454,0.000035745437,0.000014260868,0.00003816843,0.00041335105,0.000014622854,0.0017488812],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999001,0.000026581012,0.000007665186,0.000022007156,0.000024419385,0.000019184516],"domain_scores_gemma":[0.9997397,0.00008106629,0.00007195169,0.000029653875,0.000047911424,0.000029718822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003233921,0.00024349203,0.00024889177,0.00023313117,0.00011180747,0.0001533324,0.00015091841,0.00020630067,0.000758755],"category_scores_gemma":[0.00040211843,0.00014681912,0.00012216445,0.00017119684,0.000289052,0.00023407533,0.00013197312,0.00033065295,0.00020218862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002181542,0.000013515881,0.00019485982,0.000046860463,0.000004955003,0.000086430104,0.00002992744,0.00006372774,0.9985991,0.000013243846,0.000006130294,0.0007229106],"study_design_scores_gemma":[0.00001793808,0.0019461688,0.023967905,0.000021692167,0.0000626882,0.0012458706,0.00022146528,0.001151355,0.9700511,0.000065848966,0.0012331057,0.000014913229],"about_ca_topic_score_codex":0.00041691217,"about_ca_topic_score_gemma":0.00047263163,"teacher_disagreement_score":0.000758755,"about_ca_system_score_codex":0.00013796448,"about_ca_system_score_gemma":0.00009341893,"threshold_uncertainty_score":0.0025383234},"labels":[],"label_agreement":null},{"id":"W2007565673","doi":"10.1002/hbm.21257","title":"The neural basis of central proprioceptive processing in older versus younger adults: An important sensory role for right putamen","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Vlaamse regering","keywords":"Proprioception; Putamen; Functional magnetic resonance imaging; Psychology; Neuroscience; Somatosensory system; Secondary somatosensory cortex; Physical medicine and rehabilitation; Medicine","score_opus":0.08311152885122405,"score_gpt":0.3365693510946376,"score_spread":0.2534578222434135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007565673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989875,0.0002995912,0.00024579573,0.000028586384,0.000003937286,0.0000042136135,0.00008690302,0.000004105601,0.00033922592],"genre_scores_gemma":[0.9994067,0.0001100585,0.00018143226,0.00001945299,0.000005309309,0.0000045107113,0.000065976776,0.0000020761097,0.00020444277],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993896,0.000006233884,0.0000067467968,0.000023323344,0.000013767967,0.000010871196],"domain_scores_gemma":[0.99981123,0.000035585803,0.00007483098,0.00002231797,0.000023967195,0.000032134045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021167353,0.00029969035,0.00029148703,0.00041536507,0.00013304409,0.00032683968,0.00014885055,0.0002771708,0.0015306576],"category_scores_gemma":[0.0006209793,0.000114883194,0.00013229417,0.00014328664,0.00029720803,0.00042986198,0.00025484382,0.00014845352,0.00015422935],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032122494,0.0001582864,0.44865188,0.00024538214,0.0002803189,0.0026582326,0.0020512238,0.000340669,0.49704355,0.00054562243,0.00022329902,0.04458929],"study_design_scores_gemma":[0.000009731638,0.00014893367,0.99622524,0.0000051251814,0.00002039157,0.0004806409,0.0001478051,0.00018055741,0.002540712,0.00011012051,0.00012740649,0.0000032967243],"about_ca_topic_score_codex":0.0015259214,"about_ca_topic_score_gemma":0.0032689,"teacher_disagreement_score":0.0015306576,"about_ca_system_score_codex":0.00014578401,"about_ca_system_score_gemma":0.000109726105,"threshold_uncertainty_score":0.005120516},"labels":[],"label_agreement":null},{"id":"W2007618085","doi":"10.1016/j.neuroimage.2007.11.031","title":"In vivo DTI of the healthy and injured cat spinal cord at high spatial and angular resolution","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche Médicale; Canada Research Chairs","keywords":"Spinal cord; Tractography; Diffusion MRI; Neuroscience; Spinal cord injury; Anatomy; Medicine; Fractional anisotropy; Lumbar Spinal Cord; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.04383841280079468,"score_gpt":0.3602793689420522,"score_spread":0.3164409561412575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007618085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98445696,0.0010910336,0.010616905,0.0002862307,0.00002113811,0.0000468774,0.0010473842,0.00008180751,0.002351726],"genre_scores_gemma":[0.9869795,0.0011731656,0.007550424,0.000085785745,0.00001671788,0.00003054465,0.0008688222,0.0000495521,0.0032455595],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999553,0.00000796993,0.000005521979,0.000008175678,0.000010771003,0.0000123372565],"domain_scores_gemma":[0.9997969,0.00005563773,0.000026750984,0.000026299404,0.000067674606,0.000026730786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029752697,0.00022351374,0.00016864183,0.00067704223,0.00034115012,0.00035243577,0.00020965248,0.0004974249,0.0017367193],"category_scores_gemma":[0.0006066464,0.00034362383,0.000110324654,0.00045448937,0.00029491776,0.00031329071,0.0002545143,0.00033552473,0.00019835698],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014501127,0.00010318774,0.0034957817,0.00027624503,0.000059575425,0.00053897547,0.00023806954,0.001931506,0.97888136,0.00089168275,0.00060349377,0.011529976],"study_design_scores_gemma":[0.00021286223,0.001962162,0.30964214,0.00012302332,0.00052212336,0.017118325,0.00079921103,0.022078272,0.63319504,0.0022661022,0.011984553,0.00009611852],"about_ca_topic_score_codex":0.007037373,"about_ca_topic_score_gemma":0.008244355,"teacher_disagreement_score":0.007037373,"about_ca_system_score_codex":0.0002527936,"about_ca_system_score_gemma":0.0005498981,"threshold_uncertainty_score":0.013992846},"labels":[],"label_agreement":null},{"id":"W2007640411","doi":"10.1016/j.neuroimage.2014.03.069","title":"Individual differences in white matter anatomy predict dissociable components of reading skill in adults","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Uncinate fasciculus; Psychology; Diffusion MRI; Corpus callosum; Supramarginal gyrus; Reading (process); Neuroscience; Angular gyrus; Superior longitudinal fasciculus; Fractional anisotropy; Cognitive psychology; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Linguistics","score_opus":0.03304497735832924,"score_gpt":0.30976057988034167,"score_spread":0.27671560252201244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007640411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996251,0.000027144504,0.000056717436,0.000013553801,0.0000019414451,0.0000024335577,0.000045326586,0.00000238385,0.00022549613],"genre_scores_gemma":[0.99954283,0.000018934757,0.000078883684,0.000012695911,0.0000033005783,0.0000022775587,0.00008094889,0.0000023836626,0.0002577182],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985325,0.000016994705,0.000021278966,0.000056618068,0.000024706407,0.000027158756],"domain_scores_gemma":[0.998635,0.0005294418,0.00049272843,0.000098328645,0.00009316808,0.00015125253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032742193,0.00036655966,0.00024517305,0.00068716484,0.00019719198,0.00059718906,0.00019656293,0.0007153149,0.002384388],"category_scores_gemma":[0.002800558,0.00028144126,0.0002103898,0.00035012918,0.00038100051,0.00075510767,0.00047012302,0.00049990707,0.00051277154],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048457336,0.00017245549,0.98528695,0.00001761586,0.000097349206,0.00025867976,0.00074684946,0.00016030131,0.0076972856,0.00010159699,0.00013544218,0.004840891],"study_design_scores_gemma":[0.0000031142454,0.00006964252,0.9991953,0.0000013418494,0.0000101441865,0.00013372314,0.00011449198,0.00011411928,0.00026432675,0.000064668544,0.000027270611,0.0000019502356],"about_ca_topic_score_codex":0.002561398,"about_ca_topic_score_gemma":0.0064138593,"teacher_disagreement_score":0.002561398,"about_ca_system_score_codex":0.00013931941,"about_ca_system_score_gemma":0.00013428587,"threshold_uncertainty_score":0.007976592},"labels":[],"label_agreement":null},{"id":"W2007805846","doi":"10.1089/brain.2011.0005","title":"Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging","year":2011,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Center for Research Resources; National Institute on Aging; NIH Clinical Center; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; Johns Hopkins University","keywords":"Macaque; White matter; Neuroscience; Diffusion MRI; Human brain; Psychology; Brain mapping; Tractography; Fiber tract; Rhesus macaque; Functional organization; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.04069078313531951,"score_gpt":0.301647007924365,"score_spread":0.2609562247890455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007805846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9579987,0.00618073,0.02539773,0.0003992395,0.000079661484,0.000081552076,0.00035306715,0.00023533512,0.0092739295],"genre_scores_gemma":[0.9652025,0.002751371,0.028526954,0.00026584574,0.000034797624,0.00006322916,0.0002905816,0.000048278784,0.00281647],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998331,0.000032243086,0.000018118857,0.000062110936,0.00003389739,0.000020592812],"domain_scores_gemma":[0.9996761,0.00004660155,0.00015100761,0.000055227512,0.000042665404,0.000028439616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003909574,0.0004462975,0.00021609051,0.0012681959,0.00042847137,0.00074165117,0.00015338036,0.00032531485,0.0019135609],"category_scores_gemma":[0.0010077553,0.00016005182,0.00018363919,0.00061202096,0.0009114658,0.00058607117,0.00058182236,0.0002657738,0.00024530047],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045991887,0.00009068426,0.04625453,0.00064107025,0.0002479067,0.0047329753,0.002445536,0.0004764264,0.81068224,0.006473071,0.0016452441,0.12585047],"study_design_scores_gemma":[0.00005148599,0.00060004566,0.69617784,0.00028070709,0.00044967563,0.074612744,0.0021298558,0.0044943364,0.15141746,0.013393861,0.05626207,0.0001299281],"about_ca_topic_score_codex":0.0032185041,"about_ca_topic_score_gemma":0.0057416437,"teacher_disagreement_score":0.0032185041,"about_ca_system_score_codex":0.00016903706,"about_ca_system_score_gemma":0.00041008982,"threshold_uncertainty_score":0.0064014792},"labels":[],"label_agreement":null},{"id":"W2007845370","doi":"10.1002/1522-2594(200007)44:1<110::aid-mrm16>3.0.co;2-n","title":"Spreading waves of transient and prolonged decreases in water diffusion after subarachnoid hemorrhage in rats","year":2000,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources","keywords":"Cortical spreading depression; Subarachnoid hemorrhage; Effective diffusion coefficient; Perforation; Cortex (anatomy); Anesthesia; Diffusion; Nuclear magnetic resonance; Medicine; Depolarization; Magnetic resonance imaging; Neuroscience; Internal medicine; Materials science; Physics; Radiology; Psychology","score_opus":0.019873147470301753,"score_gpt":0.2907193973764593,"score_spread":0.2708462499061575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007845370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99796695,0.00033182258,0.0012352043,0.000031690754,0.000016502207,0.0000150717015,0.00007273544,0.00005868523,0.00027128297],"genre_scores_gemma":[0.99647814,0.00070742116,0.0013719421,0.00003930826,0.000010776916,0.000046042824,0.00018037413,0.000009945976,0.0011560646],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999013,0.000010920393,0.000009038148,0.000021350445,0.00002409086,0.000033228396],"domain_scores_gemma":[0.9996896,0.00002894147,0.00013776359,0.000033013574,0.000036744404,0.00007402116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001440946,0.00048514217,0.00036363807,0.00046138366,0.00010941434,0.00019531383,0.00018860224,0.00025117074,0.000738783],"category_scores_gemma":[0.00028706502,0.00027053308,0.00027441778,0.00015039508,0.00048779484,0.0003364936,0.00019906808,0.0006138942,0.00024308308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019926492,0.00017804168,0.002193721,0.000077865334,0.000023493134,0.00048955024,0.00012749317,0.00011811653,0.9857889,0.00010744186,0.0000899371,0.008812686],"study_design_scores_gemma":[0.00016524378,0.008678437,0.055654038,0.000022752103,0.00011584847,0.0011022805,0.00028954732,0.0014070799,0.93142205,0.00025062106,0.0008581303,0.000034020108],"about_ca_topic_score_codex":0.0008867372,"about_ca_topic_score_gemma":0.0013036596,"teacher_disagreement_score":0.0008867372,"about_ca_system_score_codex":0.00026477274,"about_ca_system_score_gemma":0.00018387291,"threshold_uncertainty_score":0.002471447},"labels":[],"label_agreement":null},{"id":"W2008071439","doi":"10.1249/01.mss.0000386540.28706.a6","title":"Use Of Diffusion Tensor Magnetic Resonance Imaging For Assessment Of Musculoskeletal Structure Following An Acute Bout Of Downhill Running","year":2010,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Creatine kinase; Skeletal muscle; Medicine; Isometric exercise; Muscle biopsy; Fractional anisotropy; Sarcolemma; Nuclear medicine; Nuclear magnetic resonance; Internal medicine; Biopsy; Radiology; Physics","score_opus":0.027616277414583515,"score_gpt":0.3694757063335947,"score_spread":0.3418594289190112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008071439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975586,0.0006457151,0.0012984342,0.00002442846,0.000004382581,0.000068460366,0.000046930185,0.00001303996,0.00034000538],"genre_scores_gemma":[0.99663746,0.00060201896,0.0022721551,0.000028189244,0.000008439202,0.000050225262,0.000107797125,0.0000039879665,0.00028970087],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998908,0.000024883644,0.000012301369,0.00003243245,0.000024142586,0.000015339758],"domain_scores_gemma":[0.9997434,0.000038204656,0.00008497885,0.000016931077,0.00006586533,0.000050606865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045384132,0.00048774527,0.00027349524,0.0005018873,0.00019934654,0.00020554848,0.00019487258,0.00029732962,0.00074917474],"category_scores_gemma":[0.00056203076,0.00016690738,0.00011689036,0.0001786431,0.0003029133,0.00025286278,0.00023631261,0.00017504735,0.00014749012],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025067057,0.00050164835,0.4125084,0.00034303128,0.0001288264,0.0013608857,0.0007001615,0.00030866836,0.53610176,0.00003859731,0.00013194521,0.045369405],"study_design_scores_gemma":[0.000031950654,0.0016852043,0.98923665,0.000018613951,0.00005625544,0.0008605954,0.00014435509,0.00039708457,0.0073511954,0.000013108498,0.00019573233,0.000009273871],"about_ca_topic_score_codex":0.0014883456,"about_ca_topic_score_gemma":0.003246303,"teacher_disagreement_score":0.0014883456,"about_ca_system_score_codex":0.00012185277,"about_ca_system_score_gemma":0.00014961469,"threshold_uncertainty_score":0.002959311},"labels":[],"label_agreement":null},{"id":"W2008221065","doi":"10.1002/mrm.10250","title":"Orientational diffusion reflects fiber structure within a voxel","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Canada Research Chairs","keywords":"Diffusion; Voxel; Diffusion MRI; Fiber; Orientation (vector space); Effective diffusion coefficient; Fiber bundle; Nuclear magnetic resonance; Materials science; Geometry; Physics; Mathematics; Magnetic resonance imaging; Computer science; Artificial intelligence","score_opus":0.057334700175877544,"score_gpt":0.35096536060955075,"score_spread":0.2936306604336732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008221065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.431987,0.0016333,0.55735016,0.0003094773,0.000057968173,0.00006497689,0.00040464735,0.00071128574,0.007481277],"genre_scores_gemma":[0.8905381,0.0013880322,0.106146395,0.000043943495,0.000026828555,0.000021288975,0.00018260736,0.00011564371,0.0015370924],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997818,0.000035683548,0.000010382286,0.00007865882,0.00007574074,0.000017880195],"domain_scores_gemma":[0.9991978,0.00030380613,0.00021631503,0.000102300706,0.00014146783,0.000038359616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053412514,0.00035276148,0.0003070573,0.0014102625,0.00025975466,0.000694371,0.00033262014,0.00044276725,0.0015790106],"category_scores_gemma":[0.0019142658,0.00028380327,0.00027080506,0.00086834753,0.000729292,0.0014497683,0.0004496428,0.00038235149,0.00047634487],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033638673,0.000107637534,0.035470713,0.00052423036,0.0002525008,0.0002584136,0.00070724584,0.044208854,0.7225217,0.03005133,0.00092331803,0.1646375],"study_design_scores_gemma":[0.00006709115,0.0008058938,0.13758993,0.00011147695,0.00034222993,0.0034091063,0.00059348944,0.3970405,0.3736671,0.06730861,0.018640576,0.00042402965],"about_ca_topic_score_codex":0.0020502352,"about_ca_topic_score_gemma":0.0025342444,"teacher_disagreement_score":0.0020502352,"about_ca_system_score_codex":0.00046369672,"about_ca_system_score_gemma":0.00045561118,"threshold_uncertainty_score":0.0052823424},"labels":[],"label_agreement":null},{"id":"W2008293972","doi":"10.1016/j.neuroimage.2011.08.005","title":"Cortical thickness is associated with gait disturbances in cerebral small vessel disease","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Gait; Cortex (anatomy); Cerebral cortex; Parietal lobe; Posterior cingulate; Neuroscience; Hyperintensity; Posterior parietal cortex; Prefrontal cortex; Orbitofrontal cortex; Psychology; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Cognition; Radiology","score_opus":0.09264949612268991,"score_gpt":0.3086791810961475,"score_spread":0.2160296849734576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008293972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991302,0.0002535137,0.000099143785,0.000045497556,0.000009220543,0.000003009312,0.0000530639,0.000007964949,0.00039836735],"genre_scores_gemma":[0.99954957,0.00012667013,0.000089833884,0.000012481559,0.000025241037,0.000002552149,0.000064177446,0.0000037836774,0.00012556542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973994,0.00006294561,0.000050548995,0.000044072214,0.000053238047,0.000049184022],"domain_scores_gemma":[0.9973104,0.0006382928,0.0014491313,0.000111842026,0.00020424365,0.00028606475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040982114,0.00070659956,0.00059351296,0.002467369,0.0005178417,0.00075032684,0.0004899342,0.0006953567,0.002411948],"category_scores_gemma":[0.0031721203,0.00054824405,0.0004092484,0.001972776,0.0006967972,0.0005501198,0.00041560765,0.0006833242,0.00022471826],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001877985,0.00015962268,0.97401834,0.00006983748,0.0004258274,0.008185618,0.00021362178,0.0002182722,0.008926937,0.0000913227,0.00017787017,0.0056347903],"study_design_scores_gemma":[0.000008554988,0.00007418995,0.99482626,0.000006047685,0.00007192431,0.004223795,0.000077559635,0.00021468311,0.0003396939,0.000115804025,0.000036060563,0.0000054226657],"about_ca_topic_score_codex":0.0026798078,"about_ca_topic_score_gemma":0.0029143237,"teacher_disagreement_score":0.0026798078,"about_ca_system_score_codex":0.00025088235,"about_ca_system_score_gemma":0.00026427262,"threshold_uncertainty_score":0.0080688},"labels":[],"label_agreement":null},{"id":"W2008410132","doi":"10.1167/3.9.205","title":"Texture regions are more easily detected than texture edges","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Texture (cosmology); Texture filtering; Classification of discontinuities; Artificial intelligence; Octave (electronics); Texture compression; Mathematics; Pattern recognition (psychology); Physics; Computer science; Image texture; Optics; Image (mathematics); Image processing; Mathematical analysis","score_opus":0.03576059417332198,"score_gpt":0.36665611878628984,"score_spread":0.33089552461296784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008410132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98593706,0.000533856,0.007686866,0.000080632526,0.000039238133,0.000051777646,0.00014035658,0.00014310835,0.005387082],"genre_scores_gemma":[0.99479985,0.00016281831,0.0037794886,0.000113809,0.000031409574,0.000018546094,0.000107082946,0.000058820995,0.0009282581],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995746,0.000036943467,0.000021581924,0.00015734076,0.00013353964,0.000075915574],"domain_scores_gemma":[0.99718153,0.0014358945,0.00076226296,0.0001881874,0.00019367752,0.00023853341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044670526,0.00041093846,0.0005447538,0.0007175978,0.00022504332,0.0010649784,0.00028916996,0.00056864606,0.010193364],"category_scores_gemma":[0.004555149,0.00031154382,0.00033177866,0.00028851457,0.0005431665,0.0013114791,0.00066967274,0.00048456262,0.0013138609],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044196695,0.00019944944,0.041446857,0.00047429476,0.000087480126,0.0005715298,0.0003332329,0.0009735731,0.87500423,0.0008059881,0.00054226007,0.07514132],"study_design_scores_gemma":[0.00021655283,0.0014881827,0.920606,0.00013423113,0.00016211325,0.0016058316,0.000313349,0.00554173,0.06404761,0.0031560834,0.0026720327,0.000056356763],"about_ca_topic_score_codex":0.0005751934,"about_ca_topic_score_gemma":0.00043988088,"teacher_disagreement_score":0.010193364,"about_ca_system_score_codex":0.00025631368,"about_ca_system_score_gemma":0.00012610428,"threshold_uncertainty_score":0.034100235},"labels":[],"label_agreement":null},{"id":"W2008478214","doi":"10.1109/mmbia.2012.6164747","title":"Multi-region competitive tractography via graph-based random walks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Random walk; Computer science; Tractography; Artificial intelligence; Mathematics; Diffusion MRI; Statistics; Medicine; Magnetic resonance imaging","score_opus":0.07566835506820181,"score_gpt":0.3519483959716024,"score_spread":0.2762800409034006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008478214","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013545277,0.000116728,0.98506933,0.00010831886,0.000011000349,0.000031012776,0.00003561042,0.00031189658,0.00077075796],"genre_scores_gemma":[0.570902,0.0002379577,0.42529505,0.00010804624,0.00006118438,0.00018848055,0.00019592719,0.0003072323,0.0027040893],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99898344,0.00043388762,0.00003469663,0.00021328639,0.00025630128,0.00007841715],"domain_scores_gemma":[0.9957831,0.0028349757,0.0004908516,0.0003291414,0.00033009262,0.00023186453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016730042,0.0008676655,0.0013323614,0.0017896685,0.0007691665,0.0014450606,0.0022854013,0.0022856023,0.0022365982],"category_scores_gemma":[0.0069534197,0.0008329366,0.0012789591,0.001648818,0.0014886516,0.0022320356,0.0016288395,0.0011820946,0.00065433106],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000622728,0.000033399076,0.00078336714,0.00006315893,0.00006196474,0.00018979357,0.00006886761,0.9251019,0.0044323266,0.04875353,0.00068673247,0.019762833],"study_design_scores_gemma":[0.000004980777,0.00000886449,0.000056356042,0.0000018811412,0.0000035029907,0.000027431108,0.0000020071927,0.99098676,0.0002395759,0.008526242,0.00013715346,0.000005188255],"about_ca_topic_score_codex":0.005435843,"about_ca_topic_score_gemma":0.0088271145,"teacher_disagreement_score":0.005435843,"about_ca_system_score_codex":0.0013337795,"about_ca_system_score_gemma":0.0010438081,"threshold_uncertainty_score":0.010808408},"labels":[],"label_agreement":null},{"id":"W2008655880","doi":"10.1016/j.mri.2008.01.047","title":"Is diffusion anisotropy an accurate monitor of myelination?","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":229,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of British Columbia Hospital","funders":"Killam Trusts; Bundesministerium für Bildung und Forschung","keywords":"Fractional anisotropy; Anisotropy; Diffusion MRI; White matter; Myelin; Thermal diffusivity; Nuclear magnetic resonance; Chemistry; Diffusion; Materials science; Physics; Neuroscience; Psychology; Thermodynamics; Optics; Magnetic resonance imaging; Medicine","score_opus":0.05355865973126047,"score_gpt":0.35313685121888166,"score_spread":0.2995781914876212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008655880","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23838703,0.4660694,0.16149706,0.097916536,0.011475464,0.000082937084,0.0014766667,0.0014438526,0.021651078],"genre_scores_gemma":[0.8207929,0.12260963,0.035707727,0.0074915285,0.008501105,0.00007631843,0.00034881145,0.00026453525,0.0042074434],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9974814,0.000790915,0.0003656388,0.0004638694,0.000783574,0.00011460416],"domain_scores_gemma":[0.98972625,0.004817028,0.0018615567,0.001119259,0.0021424075,0.00033351782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065201544,0.00073706394,0.0021513647,0.0018021154,0.00041385368,0.0023214743,0.0012413783,0.003323772,0.0010526909],"category_scores_gemma":[0.026728585,0.0006120384,0.00036133197,0.0018186434,0.0034998963,0.0058313156,0.00045465212,0.0016895739,0.0013127896],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017135241,0.00023636228,0.19872536,0.0027892797,0.0014398632,0.0017235543,0.0006669776,0.0028730782,0.068707675,0.036323704,0.04497791,0.6398227],"study_design_scores_gemma":[0.00021959885,0.001232009,0.33343413,0.0028159204,0.001986077,0.03670578,0.0022439419,0.028176771,0.16500527,0.20656233,0.22078137,0.0008368215],"about_ca_topic_score_codex":0.0018096131,"about_ca_topic_score_gemma":0.0013917013,"teacher_disagreement_score":0.0065201544,"about_ca_system_score_codex":0.00057667686,"about_ca_system_score_gemma":0.00058001373,"threshold_uncertainty_score":0.0344823},"labels":[],"label_agreement":null},{"id":"W2008774262","doi":"10.1016/j.neuroimage.2014.08.057","title":"Framework for integrated MRI average of the spinal cord white and gray matter: The MNI–Poly–AMU template","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Institut pour la Recherche sur la Moelle épinière et l'Encéphale; Agence Nationale de la Recherche; Multiple Sclerosis Society; National Multiple Sclerosis Society","keywords":"Gray (unit); White matter; Spinal cord; Medicine; Nuclear medicine; Neuroscience; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.0454597134860813,"score_gpt":0.3494802753450847,"score_spread":0.3040205618590034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008774262","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000691609,0.00014801444,0.9971264,0.0000896662,0.000036920672,0.000043635977,0.00024015404,0.0011484057,0.00047524748],"genre_scores_gemma":[0.024119869,0.00028337212,0.97149616,0.0001076797,0.00008885003,0.00023921613,0.0009800437,0.0008992674,0.0017855531],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99901307,0.00022471423,0.00007944456,0.00028005906,0.00031445213,0.000088278844],"domain_scores_gemma":[0.99908817,0.00020920792,0.000091886024,0.00021890392,0.00031958835,0.00007231301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020478521,0.001103356,0.0015802108,0.0016404837,0.00080794614,0.0026872237,0.0046340246,0.002250302,0.007506488],"category_scores_gemma":[0.005372291,0.000857158,0.0022825631,0.0022220048,0.00074356893,0.0016765058,0.0026572733,0.002656822,0.0055129016],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034345963,0.00016335405,0.001529258,0.00040659227,0.00039215403,0.0004090924,0.000223583,0.15751272,0.016875498,0.10065058,0.02906261,0.69243115],"study_design_scores_gemma":[0.00002861565,0.000053790576,0.00051511393,0.00004554424,0.00005921955,0.00036632872,0.000045278673,0.92425084,0.0061811376,0.045999974,0.022409745,0.000044319186],"about_ca_topic_score_codex":0.015874626,"about_ca_topic_score_gemma":0.020931162,"teacher_disagreement_score":0.015874626,"about_ca_system_score_codex":0.00095057685,"about_ca_system_score_gemma":0.0029718324,"threshold_uncertainty_score":0.031564474},"labels":[],"label_agreement":null},{"id":"W2008839569","doi":"10.1016/j.neurobiolaging.2015.02.022","title":"Superficial white matter as a novel substrate of age-related cognitive decline","year":2015,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas College; McGill University; Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Ontario Mental Health Foundation; Centre for Addiction and Mental Health Foundation; Centre for Addiction and Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Cognitive decline; White matter; Psychology; Gerontology; Medicine; Dementia; Internal medicine; Magnetic resonance imaging; Disease","score_opus":0.07380426568641628,"score_gpt":0.35419184202728377,"score_spread":0.2803875763408675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008839569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96913,0.013226768,0.013128931,0.00048403468,0.000056185778,0.00003485704,0.00023397684,0.00007944461,0.0036257224],"genre_scores_gemma":[0.9906843,0.003268455,0.004892598,0.00009190158,0.00008244465,0.000016364262,0.000096425814,0.000008529336,0.0008589689],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999428,0.000011889926,0.0000046812384,0.0000150170645,0.000014290967,0.000011381534],"domain_scores_gemma":[0.9997992,0.000042873715,0.00007160631,0.000024501736,0.000037007383,0.000024803181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042535912,0.00039183925,0.00028971635,0.00088142604,0.00021179547,0.00086761673,0.00045376993,0.00062186294,0.00078225],"category_scores_gemma":[0.0005138367,0.00017545423,0.00016329739,0.0005434702,0.0006901129,0.0013091499,0.00042540074,0.0005918237,0.00010961296],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020787523,0.00034133805,0.16183844,0.00087652757,0.00044689968,0.007327072,0.0012415485,0.0011091036,0.67010164,0.016584698,0.0011676456,0.13688637],"study_design_scores_gemma":[0.00008765311,0.0016151562,0.7879072,0.00019549711,0.0005203113,0.018909369,0.0015031246,0.0103077665,0.11763415,0.055968158,0.005275722,0.00007593511],"about_ca_topic_score_codex":0.0008896646,"about_ca_topic_score_gemma":0.0012854676,"teacher_disagreement_score":0.0008896646,"about_ca_system_score_codex":0.00021817612,"about_ca_system_score_gemma":0.00025359943,"threshold_uncertainty_score":0.0026168823},"labels":[],"label_agreement":null},{"id":"W2009202887","doi":"10.1016/j.nic.2012.12.002","title":"White Matter Anatomy","year":2013,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Diffusion MRI; White matter; Neuroradiologist; Medicine; Anatomy; Diffusion imaging; Neuroscience; Magnetic resonance imaging; Radiology; Biology","score_opus":0.10557107316373823,"score_gpt":0.43338817946058045,"score_spread":0.32781710629684224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009202887","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031367177,0.9923402,0.0004991137,0.0004997883,0.00035829618,0.000013088891,0.00007008635,0.000029442986,0.005876234],"genre_scores_gemma":[0.0017946729,0.99366236,0.00083462155,0.00036604062,0.0005243958,0.000010631842,0.00012096206,0.000005410395,0.0026808945],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998584,0.00001752674,0.000029158477,0.000033961347,0.000046847574,0.000014042522],"domain_scores_gemma":[0.999686,0.0000872542,0.00006815425,0.0000140745815,0.00011860156,0.000026003956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040787336,0.0011125099,0.0010098125,0.0048403353,0.00032740415,0.0011568222,0.0006435464,0.0008644719,0.005779753],"category_scores_gemma":[0.0011579843,0.0003408385,0.00035716128,0.0036537778,0.00076183496,0.0016284542,0.0008238527,0.0010540541,0.003219404],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031071053,0.00002566695,0.0004256927,0.005376154,0.00004788043,0.00036284627,0.000046402787,0.00012996137,0.0007872725,0.0015044308,0.037886783,0.9533757],"study_design_scores_gemma":[0.000017331588,0.000046570945,0.004194527,0.005977548,0.0002646465,0.0073466566,0.00013364354,0.00013544642,0.00078991684,0.003615875,0.97744215,0.000035789824],"about_ca_topic_score_codex":0.004179312,"about_ca_topic_score_gemma":0.009038622,"teacher_disagreement_score":0.005779753,"about_ca_system_score_codex":0.0006945474,"about_ca_system_score_gemma":0.0023451352,"threshold_uncertainty_score":0.01933515},"labels":[],"label_agreement":null},{"id":"W2010286633","doi":"10.1016/j.neuroimage.2009.11.039","title":"Group specific optimisation of fMRI processing steps for child and adult data","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Institute for Christian Studies; University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Motion (physics); Preprocessor; Artificial intelligence; Reproducibility; Functional magnetic resonance imaging; Computer science; Nonparametric statistics; Rotation (mathematics); Noise (video); Pattern recognition (psychology); Psychology; Statistics; Mathematics; Computer vision; Neuroscience","score_opus":0.09800500822373821,"score_gpt":0.36397871861428577,"score_spread":0.26597371039054757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010286633","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06308711,0.00032254055,0.93013936,0.00024602097,0.00010251104,0.00028456555,0.00047223282,0.0032458545,0.0020998132],"genre_scores_gemma":[0.13408983,0.00015106732,0.8600436,0.000121339246,0.000034912453,0.00041836934,0.0009425873,0.0010897769,0.0031085233],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996289,0.00010665965,0.000030228015,0.000101087775,0.00006152047,0.00007160326],"domain_scores_gemma":[0.9988193,0.00054082595,0.0000495746,0.00020726844,0.00032681876,0.00005619392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014987177,0.0010757165,0.0007872423,0.00079325086,0.0005287757,0.000773884,0.0008001316,0.00097277464,0.0087556],"category_scores_gemma":[0.0054815826,0.0004853859,0.0010008024,0.0007989736,0.00028668018,0.0006894581,0.00079086877,0.0012958088,0.0017465026],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018673991,0.00024711466,0.003525734,0.00033037114,0.00026969225,0.00017394798,0.0005460354,0.060419127,0.13905436,0.0045774984,0.0073840627,0.78160465],"study_design_scores_gemma":[0.00020856876,0.00085807446,0.023843918,0.00006540015,0.0005288849,0.0008234153,0.0005962289,0.7391054,0.18591015,0.01811454,0.029815514,0.0001299074],"about_ca_topic_score_codex":0.004603192,"about_ca_topic_score_gemma":0.010962973,"teacher_disagreement_score":0.0087556,"about_ca_system_score_codex":0.00039489398,"about_ca_system_score_gemma":0.0014788489,"threshold_uncertainty_score":0.029290378},"labels":[],"label_agreement":null},{"id":"W2010675754","doi":"10.1212/01.wnl.0000203412.56752.88","title":"White matter lesions and cognition","year":2006,"lang":"en","type":"letter","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Leukoaraiosis; White matter; Fractional anisotropy; Diffusion MRI; Hyperintensity; Medicine; Dementia; Neurology; Magnetic resonance imaging; Neuroradiology; Cognition; Vascular dementia; Stroke (engine); Psychology; Radiology; Pathology; Psychiatry; Physics; Disease","score_opus":0.04329229764664002,"score_gpt":0.3161124401590012,"score_spread":0.2728201425123612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010675754","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29783487,0.048588406,0.00055713335,0.53606623,0.0068483558,0.00011462325,0.00030671206,0.00014434583,0.10953926],"genre_scores_gemma":[0.8535059,0.014503274,0.00051986444,0.08228368,0.037407033,0.00006580798,0.0002125414,0.000017611423,0.011484256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990839,0.0002491556,0.00010461424,0.00011560905,0.0002965762,0.0001502154],"domain_scores_gemma":[0.9983741,0.000724665,0.00027583342,0.00008809022,0.00025203289,0.00028512938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069754,0.000466004,0.00060076965,0.00085011846,0.0014191828,0.0011590491,0.0005137968,0.0051643956,0.004439203],"category_scores_gemma":[0.006871606,0.00022234596,0.0003249519,0.0010845311,0.0014064567,0.0013730341,0.00039361106,0.0025580712,0.0012402756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007876119,0.0009270208,0.37491664,0.00047166125,0.00017617166,0.15939763,0.0015368991,0.0006370567,0.001457511,0.013128406,0.3075113,0.13905217],"study_design_scores_gemma":[0.0005078778,0.0007734082,0.4347492,0.001166646,0.00015469373,0.3657434,0.0015983585,0.0027931295,0.0007671356,0.044839688,0.14681962,0.00008684528],"about_ca_topic_score_codex":0.004448029,"about_ca_topic_score_gemma":0.0072338902,"teacher_disagreement_score":0.0051643956,"about_ca_system_score_codex":0.0017973866,"about_ca_system_score_gemma":0.00089995563,"threshold_uncertainty_score":0.014850616},"labels":[],"label_agreement":null},{"id":"W2010789651","doi":"10.1016/j.nicl.2013.04.002","title":"Assessing a standardised approach to measuring corticospinal integrity after stroke with DTI","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; European Commission; Wellcome Trust","keywords":"Internal capsule; Corticospinal tract; Diffusion MRI; Fractional anisotropy; Region of interest; White matter; Stroke (engine); Voxel; Pyramidal tracts; Psychology; Primary motor cortex; Physical medicine and rehabilitation; Motor cortex; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.25681073015730477,"score_gpt":0.4491802418842155,"score_spread":0.19236951172691075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010789651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6638013,0.00273771,0.31037813,0.00041057018,0.00042303,0.0063369987,0.002689286,0.0016406964,0.011582288],"genre_scores_gemma":[0.6500113,0.0015894338,0.3366923,0.00027910134,0.00014367563,0.00592826,0.0025291638,0.00040031766,0.0024264613],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99216676,0.0024735448,0.002235105,0.0011899938,0.0017512088,0.00018343954],"domain_scores_gemma":[0.99365485,0.0011367014,0.0015451799,0.0013884032,0.0020769758,0.00019784225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009564344,0.001046305,0.001071045,0.0036461256,0.0008326295,0.0013526704,0.0010178952,0.0010977905,0.0013933562],"category_scores_gemma":[0.019903922,0.00051363447,0.00073766086,0.0022307097,0.0012485945,0.0010167845,0.0018148168,0.000819547,0.0007601616],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018536774,0.00057583035,0.27120405,0.002273185,0.0015257106,0.0012055438,0.0066640456,0.0053848764,0.23787536,0.005273758,0.005494664,0.4606694],"study_design_scores_gemma":[0.00024834136,0.0049701794,0.9128375,0.0002915766,0.00033925983,0.004594927,0.0009910027,0.011257394,0.047219496,0.003811054,0.013124973,0.0003142327],"about_ca_topic_score_codex":0.0019565942,"about_ca_topic_score_gemma":0.0047780145,"teacher_disagreement_score":0.009564344,"about_ca_system_score_codex":0.0006029888,"about_ca_system_score_gemma":0.0009897065,"threshold_uncertainty_score":0.050581694},"labels":[],"label_agreement":null},{"id":"W2011034179","doi":"10.3389/fnhum.2014.00715","title":"Using fMRI non-local means denoising to uncover activation in sub-cortical structures at 1.5 T for guided HARDI tractography","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Functional magnetic resonance imaging; Diffusion MRI; Artificial intelligence; Thalamus; Pattern recognition (psychology); Neuroimaging; Noise reduction; Magnetic resonance imaging; Neuroscience; Computer vision; Psychology; Medicine; Radiology","score_opus":0.08443746703451681,"score_gpt":0.37853514445630126,"score_spread":0.29409767742178444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011034179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06818877,0.00044734858,0.928258,0.00027593403,0.00003576927,0.000074458825,0.00023518957,0.0016576329,0.0008269212],"genre_scores_gemma":[0.32064667,0.00038755249,0.6748097,0.00016391344,0.000048065027,0.00020709657,0.000771548,0.0006675772,0.0022979546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979275,0.000060117756,0.000012631338,0.000055552027,0.000051184787,0.000027877135],"domain_scores_gemma":[0.9994715,0.00024538304,0.000089292625,0.0000786927,0.00008132008,0.00003380776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091501424,0.0007192423,0.00059512083,0.0009408228,0.0003667205,0.00086523,0.0006117183,0.0009114884,0.0016500407],"category_scores_gemma":[0.0031975356,0.00045792706,0.0010016599,0.0006029535,0.0004972822,0.0005364364,0.0005642263,0.00078526733,0.0007543611],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076378346,0.00022562116,0.00624166,0.00078046054,0.00036199894,0.00088927534,0.0007910208,0.19480817,0.47000965,0.01071709,0.004958357,0.30945295],"study_design_scores_gemma":[0.00004650821,0.00019520782,0.009024532,0.0000474383,0.00011096298,0.00062540645,0.00010878231,0.8877625,0.08397078,0.013425377,0.0046211523,0.00006137503],"about_ca_topic_score_codex":0.003073014,"about_ca_topic_score_gemma":0.0055723237,"teacher_disagreement_score":0.003073014,"about_ca_system_score_codex":0.0003982296,"about_ca_system_score_gemma":0.00079196575,"threshold_uncertainty_score":0.006110251},"labels":[],"label_agreement":null},{"id":"W2011246142","doi":"10.1016/j.pain.2014.05.026","title":"Diffusion imaging in trigeminal neuralgia reveals abnormal trigeminal nerve and brain white matter","year":2014,"lang":"en","type":"letter","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Ontario Brain Institute; University of Toronto; Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Neurosurgery; Health science; University hospital; Library science; Medicine; Neuroscience; Trigeminal neuralgia; Psychology; Medical education; Family medicine; Psychiatry","score_opus":0.0271682825366193,"score_gpt":0.30762864157266223,"score_spread":0.28046035903604294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011246142","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21757266,0.022724086,0.0035757201,0.60328174,0.017645238,0.00034739444,0.00039859518,0.00035340025,0.13410121],"genre_scores_gemma":[0.80381703,0.011840266,0.002265035,0.12184514,0.039396968,0.00009288148,0.00014224161,0.00006898187,0.020531489],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.999166,0.0001494829,0.00012099988,0.00013939878,0.00021414825,0.00020991995],"domain_scores_gemma":[0.9982875,0.0009474499,0.00016041679,0.00011556858,0.0002789686,0.00021004824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007108126,0.00072559086,0.0009105422,0.0012166238,0.0019038483,0.0011592767,0.0013468227,0.013847654,0.0035065014],"category_scores_gemma":[0.006193894,0.0004883324,0.0007367739,0.0012470637,0.0025083132,0.0019622021,0.0005927639,0.008447727,0.0016878454],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023601782,0.00009989239,0.007918014,0.00014981316,0.00003473115,0.9350497,0.0004867867,0.0002242124,0.0015788204,0.002266563,0.03778312,0.014172309],"study_design_scores_gemma":[0.00026379133,0.00033834545,0.022775695,0.00041588262,0.00009597981,0.92491996,0.0007086532,0.0026575283,0.0014409486,0.006635143,0.03966134,0.00008676239],"about_ca_topic_score_codex":0.0073821037,"about_ca_topic_score_gemma":0.008250222,"teacher_disagreement_score":0.013847654,"about_ca_system_score_codex":0.0037635502,"about_ca_system_score_gemma":0.0011425464,"threshold_uncertainty_score":0.027306616},"labels":[],"label_agreement":null},{"id":"W2011842664","doi":"10.1016/j.neuroimage.2006.10.041","title":"An unbiased iterative group registration template for cortical surface analysis","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":417,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Gyrification; Template; Computer science; Artificial intelligence; Laterality; Lateralization of brain function; Pattern recognition (psychology); Set (abstract data type); Surface (topology); Computer vision; Mathematics; Psychology; Cerebral cortex; Neuroscience; Geometry","score_opus":0.08922525473517356,"score_gpt":0.4146023594206589,"score_spread":0.3253771046854853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011842664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012538112,0.000067131616,0.9973236,0.000038309034,0.00002316847,0.000044695116,0.00008453437,0.0007724204,0.00039233032],"genre_scores_gemma":[0.019489316,0.00010196845,0.97779536,0.00005387994,0.000018030334,0.00020990158,0.00029693323,0.0006063598,0.0014283247],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992312,0.00016091828,0.0000533218,0.00018726365,0.00030733485,0.000059865044],"domain_scores_gemma":[0.9991929,0.00020986235,0.000056339668,0.00020691536,0.00030618627,0.000027724784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013450626,0.00081101235,0.0008964024,0.0016077199,0.0007378067,0.0014966041,0.0016585428,0.0013634234,0.0060901283],"category_scores_gemma":[0.004747628,0.000722281,0.0013248124,0.0018058693,0.00048286104,0.0011149076,0.0015743416,0.0016325659,0.0041669663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023632486,0.00008183268,0.0010076421,0.0002644669,0.00018808014,0.0002415734,0.0003207763,0.025578473,0.069692455,0.030177318,0.017707499,0.8545036],"study_design_scores_gemma":[0.00009925641,0.00022254132,0.0038074765,0.00008099758,0.00025609075,0.0022908098,0.00017133883,0.7800004,0.10948799,0.050453503,0.052958146,0.00017142463],"about_ca_topic_score_codex":0.004393486,"about_ca_topic_score_gemma":0.008971818,"teacher_disagreement_score":0.0060901283,"about_ca_system_score_codex":0.0005773426,"about_ca_system_score_gemma":0.0027202284,"threshold_uncertainty_score":0.020373523},"labels":[],"label_agreement":null},{"id":"W2011879949","doi":"10.1017/s1355617708080533","title":"Regional atrophy of the corpus callosum in dementia","year":2008,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Corpus callosum; Dementia; Atrophy; Psychology; Medicine; Cognitive impairment; Audiology; Magnetic resonance imaging; Cognition; Disease; Neuroscience; Internal medicine; Radiology","score_opus":0.10458125889835851,"score_gpt":0.356042039643284,"score_spread":0.2514607807449255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011879949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99916387,0.0006064544,0.00003773864,0.000007869342,0.0000015767591,0.0000029267096,0.00002620339,0.000001800329,0.00015160594],"genre_scores_gemma":[0.999495,0.00020117543,0.00014939,0.0000067992933,0.0000047290187,0.000004786789,0.00006094083,0.0000010981616,0.000075980875],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998411,0.000054056993,0.000019119967,0.000032806085,0.00003884029,0.000014094134],"domain_scores_gemma":[0.999435,0.00014478629,0.0002291758,0.000049869835,0.00006588722,0.00007517958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067272974,0.00026631355,0.00023721241,0.0019214639,0.0003985697,0.00032522058,0.00020945987,0.00031862498,0.00074573007],"category_scores_gemma":[0.0024099252,0.00019533504,0.00018155239,0.000561589,0.00043984794,0.00035427453,0.00042627653,0.00020917508,0.00012855191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019440929,0.00008879497,0.95639616,0.00016175339,0.00034579073,0.0016496313,0.0016647764,0.00018505684,0.0152714085,0.00008435674,0.0002479085,0.021960292],"study_design_scores_gemma":[0.00001033915,0.000100882324,0.998054,0.000010298547,0.00003450988,0.0011590045,0.0001481971,0.000062703395,0.00024340073,0.000058943555,0.000113965885,0.0000036186418],"about_ca_topic_score_codex":0.0031391152,"about_ca_topic_score_gemma":0.0064347666,"teacher_disagreement_score":0.0031391152,"about_ca_system_score_codex":0.0002242057,"about_ca_system_score_gemma":0.00018386905,"threshold_uncertainty_score":0.006241679},"labels":[],"label_agreement":null},{"id":"W2011955966","doi":"10.1016/j.neuropsychologia.2013.03.014","title":"Functional organisation of visual pathways in a patient with no optic chiasm","year":2013,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canada Research Chairs","keywords":"Neuroscience; Psychology; Visual cortex; Retinotopy; Optic chiasm; Corpus callosum; Cortex (anatomy); Decussation; Visual system; Functional magnetic resonance imaging; Retina; Anatomy; Optic nerve; Medicine","score_opus":0.0428630383913633,"score_gpt":0.3065219515066142,"score_spread":0.2636589131152509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011955966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990802,0.0007095346,0.0008487828,0.0016402194,0.00008024032,0.000056588295,0.00027985746,0.000061351486,0.005521408],"genre_scores_gemma":[0.99846554,0.00027120998,0.00041164117,0.0002354388,0.0001219478,0.000008079879,0.00004061999,0.000014588137,0.00043086172],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9997521,0.000023821358,0.000029858451,0.000058348276,0.0000389736,0.000096855205],"domain_scores_gemma":[0.99850625,0.0007637562,0.0001186993,0.0001258979,0.000099056546,0.00038639634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027450465,0.0010887479,0.0009065982,0.0025778764,0.001749414,0.0010357483,0.0012105827,0.0037940268,0.002931733],"category_scores_gemma":[0.002601188,0.00084396783,0.00075554784,0.0010541481,0.0028759034,0.0013304752,0.0009536548,0.0025052477,0.000535078],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047945496,0.00008493069,0.00759272,0.00005123967,0.000021781821,0.9843269,0.00025237314,0.00018670957,0.004947212,0.00020434507,0.00008910198,0.0017633033],"study_design_scores_gemma":[0.00012251972,0.00072846195,0.046488844,0.000029464269,0.00007672274,0.9459867,0.00038222113,0.0012656206,0.0035480603,0.0010048624,0.00031384107,0.00005278174],"about_ca_topic_score_codex":0.0064963894,"about_ca_topic_score_gemma":0.00641768,"teacher_disagreement_score":0.0064963894,"about_ca_system_score_codex":0.001436891,"about_ca_system_score_gemma":0.0011527961,"threshold_uncertainty_score":0.012917161},"labels":[],"label_agreement":null},{"id":"W2012658403","doi":"10.1249/01.mss.0000355604.40179.ef","title":"Use Of Diffusion Tensor Magnetic Resonance Imaging For Assessment Of Musculoskeletal Structure Following High-force Eccentric Exercise: A Case Study","year":2009,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Magnetic resonance imaging; Medicine; Diffusion MRI; Isometric exercise; Eccentric; Skeletal muscle; Anatomy; Physical medicine and rehabilitation; Radiology; Physical therapy; Physics","score_opus":0.030806539661709906,"score_gpt":0.36364710678208717,"score_spread":0.33284056712037724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012658403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96341074,0.0066183303,0.010566746,0.0059378403,0.00059183047,0.00059482694,0.00021342197,0.00017404613,0.011892211],"genre_scores_gemma":[0.9916304,0.00248347,0.002792268,0.0009958214,0.0008216251,0.000056836776,0.00007149819,0.00003488107,0.0011132273],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99808747,0.0002617745,0.0003321039,0.00046408133,0.0003274266,0.0005271504],"domain_scores_gemma":[0.9972963,0.0008186563,0.0005796446,0.00025615626,0.0002678832,0.00078134204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013091324,0.0039493795,0.0018868427,0.0064279595,0.004188735,0.0020286553,0.0024382828,0.00828441,0.0019062988],"category_scores_gemma":[0.005252116,0.002121522,0.0025097094,0.002743696,0.0033091702,0.003491561,0.002397934,0.0049492703,0.0013435436],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026705577,0.00009619946,0.0041617565,0.000030045365,0.000010966095,0.9936342,0.00034972662,0.00005126466,0.00055403914,0.000087803535,0.00009909162,0.0008981599],"study_design_scores_gemma":[0.000010000244,0.00009865672,0.0026808893,0.000019662497,0.000019674559,0.99605995,0.00017427943,0.00022712229,0.00034418883,0.000078232486,0.00027132707,0.000016009937],"about_ca_topic_score_codex":0.0051773326,"about_ca_topic_score_gemma":0.006167595,"teacher_disagreement_score":0.00828441,"about_ca_system_score_codex":0.002513775,"about_ca_system_score_gemma":0.0012439158,"threshold_uncertainty_score":0.018238842},"labels":[],"label_agreement":null},{"id":"W2012970094","doi":"10.1007/s00381-010-1189-8","title":"Mapping of the cortical spinal tracts using magnetoencephalography and diffusion tensor tractography in pediatric brain tumor patients","year":2010,"lang":"en","type":"article","venue":"Child s Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Tractography; Magnetoencephalography; Diffusion MRI; Medicine; Corticospinal tract; White matter; Brain tumor; Cortex (anatomy); Motor cortex; Pyramidal tracts; Neurosurgery; Magnetic resonance imaging; Fiber tract; Neuroscience; Radiology; Anatomy; Pathology; Electroencephalography; Psychology","score_opus":0.020060007233097688,"score_gpt":0.2726924076174076,"score_spread":0.2526324003843099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012970094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992843,0.00007281014,0.00015093504,0.000027501288,0.0000017351205,0.0000046968144,0.00006771277,0.0000044142776,0.0003858533],"genre_scores_gemma":[0.9994211,0.000120668774,0.00025237925,0.000010479771,0.0000040407967,0.0000072242487,0.00007944268,0.000004069069,0.000100497105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990404,0.000017594968,0.000011499228,0.000021814625,0.000017774175,0.000027361277],"domain_scores_gemma":[0.99973005,0.000091131886,0.00007000897,0.000017062664,0.00004178227,0.00004991768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015630857,0.0003504969,0.00034593506,0.00077647244,0.00040677196,0.0002824366,0.00019435449,0.00028976524,0.0007356738],"category_scores_gemma":[0.0013194851,0.00017825923,0.0001648869,0.0005942831,0.0003809179,0.00039336478,0.00016444146,0.0002955088,0.000111550704],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046633568,0.0001609954,0.9417758,0.00004505998,0.000031797128,0.025808444,0.00047944495,0.0014083475,0.012395805,0.00020029323,0.00041024882,0.016817426],"study_design_scores_gemma":[0.00004067004,0.0006285037,0.93523675,0.000014830114,0.00005999126,0.05300115,0.0008475169,0.0022408795,0.00710836,0.00021030486,0.0005928106,0.00001822803],"about_ca_topic_score_codex":0.006024883,"about_ca_topic_score_gemma":0.0072176633,"teacher_disagreement_score":0.006024883,"about_ca_system_score_codex":0.00038378025,"about_ca_system_score_gemma":0.00059015636,"threshold_uncertainty_score":0.0119796395},"labels":[],"label_agreement":null},{"id":"W2013013539","doi":"10.1016/j.neuroscience.2006.08.080","title":"Development of a high resolution three-dimensional surgical atlas of the murine head for strains 129S1/SvImJ and C57Bl/6J using magnetic resonance imaging and micro-computed tomography","year":2006,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Skull; Brain atlas; Atlas (anatomy); Coordinate system; Surgical planning; Magnetic resonance imaging; Computer science; Neuroscience; Anatomy; Biology; Medicine; Computer vision; Radiology","score_opus":0.04056885429120004,"score_gpt":0.3086936459224558,"score_spread":0.26812479163125574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013013539","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13083507,0.0007654363,0.8484969,0.00060627965,0.0004484667,0.0010500373,0.0068375994,0.0033975153,0.0075627384],"genre_scores_gemma":[0.15005097,0.0010604011,0.832812,0.00013262278,0.000031324464,0.00063639024,0.002831066,0.0011933199,0.011251927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992887,0.000057978017,0.00007127944,0.00010798395,0.0003953974,0.00007872596],"domain_scores_gemma":[0.9986633,0.00017047572,0.00037878833,0.00030225798,0.0003242322,0.00016091487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012300401,0.0012025813,0.00067423354,0.0030915048,0.0009223823,0.0016001542,0.0012839522,0.0010734863,0.0037244626],"category_scores_gemma":[0.0006661028,0.001397842,0.0009087801,0.00082712737,0.0009433482,0.0012718769,0.0013843398,0.0022508746,0.0016998039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013435434,0.00006186895,0.00069628336,0.00015987674,0.000031884425,0.00031179894,0.00016930501,0.0034626788,0.9733893,0.005048299,0.0010647055,0.015469541],"study_design_scores_gemma":[0.000036063044,0.00031117996,0.0061752875,0.00007553421,0.00009869648,0.0016979054,0.00017823336,0.013233469,0.94405985,0.00156507,0.032474015,0.00009477681],"about_ca_topic_score_codex":0.003988162,"about_ca_topic_score_gemma":0.016311878,"teacher_disagreement_score":0.003988162,"about_ca_system_score_codex":0.00091332133,"about_ca_system_score_gemma":0.0017509833,"threshold_uncertainty_score":0.0124595165},"labels":[],"label_agreement":null},{"id":"W2013160622","doi":"10.1016/j.media.2013.03.009","title":"Tractometer: Towards validation of tractography pipelines","year":2013,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":236,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Artificial intelligence; Seeding; Pattern recognition (psychology); Computer vision; Mathematics; Diffusion MRI; Engineering; Magnetic resonance imaging","score_opus":0.04430028071975608,"score_gpt":0.3782283427137563,"score_spread":0.33392806199400027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013160622","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037336804,0.0002745076,0.92715234,0.00030357327,0.00027415573,0.00019166022,0.0016614253,0.031788968,0.0010166148],"genre_scores_gemma":[0.25039637,0.00020631538,0.73375833,0.00021449171,0.00007126011,0.000387158,0.0071348716,0.005650177,0.0021809875],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9913952,0.0035487006,0.00067645154,0.0019931414,0.0020447513,0.00034180837],"domain_scores_gemma":[0.9692982,0.014512064,0.002134421,0.007130958,0.0062021525,0.0007222289],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014358205,0.0022415933,0.0013206512,0.0031285672,0.001444544,0.0044967937,0.003763148,0.0037382175,0.005073681],"category_scores_gemma":[0.07169341,0.0012290898,0.0016850622,0.0017015192,0.0018934546,0.0035230669,0.00445503,0.003251757,0.0037300223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002087643,0.0006937502,0.026266644,0.0014713877,0.001517281,0.00052652054,0.0010556082,0.30119777,0.057843424,0.029097077,0.035247214,0.5429957],"study_design_scores_gemma":[0.00012115251,0.00017875458,0.0042104046,0.000119388125,0.00008500544,0.00030517776,0.00008978347,0.9475107,0.028473815,0.0111101335,0.0077191098,0.000076594435],"about_ca_topic_score_codex":0.011065129,"about_ca_topic_score_gemma":0.010859133,"teacher_disagreement_score":0.9856418,"about_ca_system_score_codex":0.0013332721,"about_ca_system_score_gemma":0.0048541683,"threshold_uncertainty_score":0.07593435},"labels":[],"label_agreement":null},{"id":"W2013162191","doi":"10.1016/j.neuroimage.2007.07.033","title":"Evidence of slow maturation of the superior longitudinal fasciculus in early childhood by diffusion tensor imaging","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"Neuroscience; Diffusion MRI; Superior longitudinal fasciculus; White matter; Tractography; Fiber tract; Myelin; Inferior longitudinal fasciculus; Uncinate fasciculus; Population; Fasciculus; Biology; Medial longitudinal fasciculus; Psychology; Anatomy; Fractional anisotropy; Central nervous system; Medicine; Magnetic resonance imaging","score_opus":0.036335385181827946,"score_gpt":0.3188146849552961,"score_spread":0.28247929977346814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013162191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949083,0.0014564861,0.001055685,0.00019530527,0.000016117187,0.0000103049115,0.00051615865,0.00003748313,0.001804179],"genre_scores_gemma":[0.99544734,0.0017699243,0.0015911304,0.00003893364,0.000016571556,0.00001979497,0.0003981969,0.000025560857,0.0006925031],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996972,0.000050968403,0.00004863425,0.0000673572,0.000068938745,0.00006699325],"domain_scores_gemma":[0.9972344,0.00077281776,0.001006687,0.00028422,0.00051998167,0.00018193445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011835413,0.00047850976,0.00038380187,0.002044413,0.00033682352,0.00076833577,0.00039261385,0.0005924101,0.0018333636],"category_scores_gemma":[0.0036211624,0.00055328937,0.00029690866,0.000940407,0.0009550329,0.000999334,0.00047170083,0.0007073268,0.00035730258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014971641,0.00014218033,0.80886245,0.0005365492,0.00024758928,0.00823487,0.001871647,0.00073567475,0.12996893,0.002161958,0.0011526078,0.044588268],"study_design_scores_gemma":[0.000014250785,0.00012784041,0.9790693,0.0000557156,0.00006114985,0.005510942,0.00039884713,0.00017426185,0.01289424,0.0003949718,0.001285877,0.000012738714],"about_ca_topic_score_codex":0.006570876,"about_ca_topic_score_gemma":0.0072209025,"teacher_disagreement_score":0.006570876,"about_ca_system_score_codex":0.00036823755,"about_ca_system_score_gemma":0.00069104315,"threshold_uncertainty_score":0.0130652785},"labels":[],"label_agreement":null},{"id":"W2013322489","doi":"10.1016/j.eplepsyres.2013.12.001","title":"Bilateral white matter abnormality in children with frontal lobe epilepsy","year":2013,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Splenium; Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Epilepsy; Medicine; Abnormality; Frontal lobe; Lateralization of brain function; Cardiology; Ictal; Psychology; Internal medicine; Magnetic resonance imaging; Audiology; Neuroscience; Anatomy; Psychiatry; Radiology","score_opus":0.06578619303712097,"score_gpt":0.38007455127018824,"score_spread":0.3142883582330673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013322489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99553156,0.00060282316,0.00013207931,0.00035912998,0.000025411688,0.000011214594,0.00021725893,0.000026404325,0.003094077],"genre_scores_gemma":[0.99892235,0.0004042646,0.00016359893,0.00008456223,0.000043256736,0.0000061413493,0.00013666427,0.000007495818,0.00023162903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968195,0.000036623285,0.000050082166,0.00006477308,0.00007316912,0.00009345834],"domain_scores_gemma":[0.9992663,0.00018452237,0.00029192408,0.000028057348,0.00007498496,0.00015417817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000313435,0.00082576607,0.00038945067,0.0023948094,0.0006079128,0.00049760746,0.00044586055,0.0009064219,0.0038249122],"category_scores_gemma":[0.0020108311,0.00039761353,0.000302007,0.0011062061,0.0009584247,0.0009694241,0.0005001101,0.00060910115,0.00033248856],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032797255,0.00015154519,0.71646225,0.0001093233,0.000064060354,0.26640683,0.00041074076,0.00021521299,0.008701421,0.0002656684,0.00086584507,0.0060190903],"study_design_scores_gemma":[0.000024913163,0.00012652975,0.7201464,0.000032987493,0.00006577706,0.27664366,0.0007316951,0.00035640292,0.0012556831,0.00016438079,0.00043972043,0.000011881513],"about_ca_topic_score_codex":0.009468471,"about_ca_topic_score_gemma":0.009625061,"teacher_disagreement_score":0.009468471,"about_ca_system_score_codex":0.0004895061,"about_ca_system_score_gemma":0.00089022034,"threshold_uncertainty_score":0.018826723},"labels":[],"label_agreement":null},{"id":"W2013700088","doi":"10.1007/s00381-007-0466-7","title":"Preserved structural integrity of white matter adjacent to low-grade tumors","year":2007,"lang":"en","type":"article","venue":"Child s Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"Epilepsy Society; Göteborgs Läkaresällskap; University of Toronto; Johns Hopkins University","keywords":"Medicine; White matter; Tractography; Fractional anisotropy; Magnetic resonance imaging; Diffusion MRI; Hyperintensity; Pyramidal tracts; Pathology; Nuclear medicine; Radiology; Anatomy","score_opus":0.03603578317029175,"score_gpt":0.3228802208097341,"score_spread":0.28684443763944234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013700088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961094,0.0006244738,0.001325979,0.0000725276,0.00000651594,0.0000065388986,0.00016126038,0.000039789556,0.0016533856],"genre_scores_gemma":[0.99863774,0.0002282928,0.00060118356,0.000012791072,0.0000055613064,0.0000027563221,0.000068933165,0.000007713668,0.00043503332],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999479,0.000006273529,0.0000048708257,0.000011984841,0.000012935392,0.000015995303],"domain_scores_gemma":[0.99965584,0.00006252107,0.00011891112,0.00005099488,0.00006932831,0.00004235966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001931439,0.00020825567,0.00016103136,0.0010843318,0.00036685212,0.00061568985,0.00025957543,0.00026511654,0.0020863414],"category_scores_gemma":[0.000719667,0.00014629005,0.00008054678,0.00043640987,0.00045285598,0.00049867795,0.00018352366,0.00027471778,0.00024958825],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022990082,0.00011659783,0.2210059,0.00056003686,0.00037302374,0.010919201,0.0009792969,0.0023687338,0.67072445,0.0042498615,0.0008134761,0.0855904],"study_design_scores_gemma":[0.000040613006,0.00036803342,0.77800536,0.000060998344,0.0002558497,0.022209495,0.0007935706,0.0033375586,0.1882553,0.0030136993,0.003631402,0.000028110648],"about_ca_topic_score_codex":0.0052151834,"about_ca_topic_score_gemma":0.0072456044,"teacher_disagreement_score":0.0052151834,"about_ca_system_score_codex":0.0002881921,"about_ca_system_score_gemma":0.00040572693,"threshold_uncertainty_score":0.0103696585},"labels":[],"label_agreement":null},{"id":"W2014773891","doi":"10.1002/mrm.20839","title":"Exploratory data analysis reveals visuovisual interhemispheric transfer in functional magnetic resonance imaging","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; Dalhousie University","funders":"","keywords":"Corpus callosum; Functional magnetic resonance imaging; Visual field; Splenium; Psychology; Neuroscience; Magnetic resonance imaging; White matter","score_opus":0.06520448534042662,"score_gpt":0.34690002665317227,"score_spread":0.28169554131274566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014773891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86541075,0.00011094769,0.13208191,0.00009000863,0.00000796456,0.00024600362,0.00025248408,0.00034538913,0.0014546614],"genre_scores_gemma":[0.93521225,0.000040348717,0.06401137,0.000016220425,0.000006080978,0.00022615142,0.00024178912,0.000070588525,0.00017515638],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99853706,0.0006439238,0.00009593462,0.0002640348,0.00035966514,0.000099303834],"domain_scores_gemma":[0.99350715,0.004430485,0.00061567617,0.00072823593,0.00056474406,0.00015382821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031220913,0.00048377112,0.00042593188,0.0013827013,0.00040261223,0.00065044634,0.00029471115,0.0003055053,0.0011352072],"category_scores_gemma":[0.014183763,0.00014108245,0.0004229096,0.0007191292,0.00066346617,0.00060163834,0.00082078535,0.0003547044,0.00014946696],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029069958,0.00046667794,0.040665712,0.00050862564,0.000573307,0.0020438216,0.0063247536,0.0059745316,0.71467,0.007050052,0.0012163536,0.21759918],"study_design_scores_gemma":[0.00016273971,0.0038097573,0.5630683,0.00009829565,0.0003846647,0.0048150406,0.0026419333,0.10012402,0.29493296,0.02339894,0.0063413563,0.00022196055],"about_ca_topic_score_codex":0.00044953285,"about_ca_topic_score_gemma":0.0006477865,"teacher_disagreement_score":0.0031220913,"about_ca_system_score_codex":0.00030556705,"about_ca_system_score_gemma":0.00047862518,"threshold_uncertainty_score":0.01651138},"labels":[],"label_agreement":null},{"id":"W2015088173","doi":"10.1016/j.neuroimage.2008.07.038","title":"Quantifying development: Investigating highly myelinated voxels in preadolescent corpus callosum","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Voxel; Corpus callosum; White matter; Psychology; Correlation; Wechsler Adult Intelligence Scale; Audiology; Mathematics; Cognition; Artificial intelligence; Neuroscience; Medicine; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.2040757350056761,"score_gpt":0.3643571969460059,"score_spread":0.16028146194032977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015088173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959336,0.00039115277,0.0025945653,0.000080944264,0.0000024455826,0.000017928518,0.00013812548,0.000022921391,0.000818377],"genre_scores_gemma":[0.99124134,0.0005354032,0.0071848016,0.000031155352,0.0000038561147,0.000020699657,0.00010736195,0.000021985512,0.0008533066],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999577,0.0000076273286,0.0000027737049,0.000011496554,0.000010256775,0.000010232545],"domain_scores_gemma":[0.99972755,0.00007904293,0.00006778326,0.000018221934,0.00006609268,0.000041223102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036394293,0.00020125885,0.00010935394,0.0009344768,0.00023766156,0.0005175829,0.0003009972,0.00040173886,0.0010304811],"category_scores_gemma":[0.0013282791,0.00016232618,0.00006966791,0.00039432143,0.00022499484,0.00040818882,0.0002785433,0.00031091212,0.00009835137],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076044997,0.00014793732,0.4411279,0.00039433365,0.00009157857,0.002522952,0.0022161994,0.0016260796,0.39580342,0.0014173656,0.0011012494,0.15279056],"study_design_scores_gemma":[0.000019726454,0.00019257981,0.9387625,0.000057638455,0.00006637835,0.0029907713,0.0018854016,0.0039815567,0.049339097,0.0010931137,0.0015885913,0.000022535538],"about_ca_topic_score_codex":0.009918889,"about_ca_topic_score_gemma":0.022271577,"teacher_disagreement_score":0.009918889,"about_ca_system_score_codex":0.00026312942,"about_ca_system_score_gemma":0.0006106558,"threshold_uncertainty_score":0.019722342},"labels":[],"label_agreement":null},{"id":"W2015100231","doi":"10.1016/j.neuroimage.2013.05.080","title":"Structural connectivity of visuotopic intraparietal sulcus","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Hotchkiss Brain Institute; Health Research Board","keywords":"Intraparietal sulcus; Neuroscience; Posterior parietal cortex; Psychology; Functional magnetic resonance imaging; Functional specialization; Retinotopy; Cortex (anatomy); Parietal lobe; Superior temporal gyrus; Cytoarchitecture; Visual cortex","score_opus":0.05488832759881571,"score_gpt":0.3393625634760009,"score_spread":0.2844742358771852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015100231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854069,0.0004988869,0.008302988,0.00032066446,0.000017975255,0.00002877422,0.0007009104,0.00009364925,0.0046292767],"genre_scores_gemma":[0.9976859,0.00015608074,0.0011300534,0.00001962829,0.000019643985,0.000013383953,0.0002133092,0.000015153125,0.0007469609],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992347,0.000013620845,0.0000039726715,0.000022295691,0.000016766584,0.000019852281],"domain_scores_gemma":[0.99974436,0.000092300164,0.00006627273,0.000019477982,0.00005105288,0.000026641175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016855645,0.00019997686,0.0001215106,0.0010785445,0.00026835233,0.0005169208,0.00028168203,0.00023655155,0.0027748488],"category_scores_gemma":[0.001711322,0.00016577398,0.00018263303,0.00072229345,0.000273032,0.0007305225,0.00031381176,0.00023250385,0.00025484845],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017367327,0.00022047861,0.27543938,0.00036557496,0.0006998008,0.0028031515,0.0023271146,0.007367189,0.4848186,0.021625595,0.005697642,0.19689879],"study_design_scores_gemma":[0.000044311848,0.00014985073,0.95320183,0.000028778832,0.00015627757,0.0019632909,0.00049545505,0.012333089,0.020609945,0.008960703,0.0020279088,0.000028501383],"about_ca_topic_score_codex":0.0060966373,"about_ca_topic_score_gemma":0.010096972,"teacher_disagreement_score":0.0060966373,"about_ca_system_score_codex":0.00034764246,"about_ca_system_score_gemma":0.00044710992,"threshold_uncertainty_score":0.012122273},"labels":[],"label_agreement":null},{"id":"W2015120800","doi":"10.1016/j.neuroimage.2006.03.036","title":"Reproducibility and reliability of MR measurements in white matter: Clinical implications","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Multiple Sclerosis Society","keywords":"Reproducibility; Reliability (semiconductor); White matter; Magnetization transfer; Nuclear magnetic resonance; Repeatability; Coefficient of variation; Nuclear medicine; Chemistry; Magnetic resonance imaging; Statistics; Mathematics; Physics; Medicine; Radiology; Thermodynamics","score_opus":0.1300008462921184,"score_gpt":0.40965703221596395,"score_spread":0.27965618592384556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015120800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8654142,0.036684178,0.07667421,0.0050554597,0.0021852336,0.00023917647,0.0011129322,0.0005138562,0.012120677],"genre_scores_gemma":[0.9884145,0.00080349203,0.008625911,0.0004341713,0.0007145738,0.00005995196,0.00020354247,0.00021192353,0.00053190254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9212528,0.040221263,0.007916562,0.016032195,0.0135992635,0.0009780821],"domain_scores_gemma":[0.4392074,0.44772664,0.031858526,0.05361801,0.026301047,0.0012884303],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.08991305,0.00082510617,0.0018045136,0.0014676956,0.0012045095,0.0026759377,0.002659535,0.0027037645,0.0011389061],"category_scores_gemma":[0.31170675,0.0010023358,0.00091343845,0.001684605,0.0045037596,0.0023595777,0.0011836985,0.001784795,0.0008352435],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031250375,0.00031852224,0.85764277,0.0013892247,0.0041814293,0.0008158844,0.004293488,0.0045576366,0.011829481,0.004680266,0.004401427,0.10276486],"study_design_scores_gemma":[0.00019764084,0.0011246625,0.95677674,0.00030393162,0.0014219383,0.0034595786,0.0008102455,0.011953829,0.008770557,0.010043633,0.0049990644,0.00013814933],"about_ca_topic_score_codex":0.0024122498,"about_ca_topic_score_gemma":0.0030474234,"teacher_disagreement_score":0.9100869,"about_ca_system_score_codex":0.00079552445,"about_ca_system_score_gemma":0.0007632112,"threshold_uncertainty_score":0.4755113},"labels":[],"label_agreement":null},{"id":"W2015151082","doi":"10.1016/j.neuroimage.2004.07.045","title":"Cortical thickness analysis examined through power analysis and a population simulation","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":722,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Reproducibility; Smoothing; Population; Gaussian; Mathematics; Statistical power; Sensitivity (control systems); Statistics; Physics","score_opus":0.05721126659594612,"score_gpt":0.37907689528163796,"score_spread":0.32186562868569185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015151082","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4791278,0.000091055146,0.51708686,0.0003061122,0.00003846248,0.00012246221,0.00019141291,0.00045744597,0.002578377],"genre_scores_gemma":[0.94824374,0.000033237975,0.049944904,0.00003933073,0.000012965395,0.0000851272,0.00011749021,0.000117860116,0.0014053499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984665,0.0010110027,0.000046054516,0.0002506331,0.00013639388,0.00008940068],"domain_scores_gemma":[0.9634666,0.032865554,0.0008273361,0.0016296451,0.0010465028,0.00016432718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065988833,0.0005082466,0.0008226889,0.0012239412,0.0005405675,0.00083601585,0.00090780185,0.00091508956,0.0036874255],"category_scores_gemma":[0.04466703,0.00050257833,0.0014359794,0.0007449864,0.0008096151,0.001033657,0.00059672596,0.0010906564,0.00024373012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000686175,0.00015225484,0.016368393,0.00006946824,0.00057516247,0.0008388956,0.0004314103,0.92508733,0.0024863288,0.023765977,0.0013219455,0.028216615],"study_design_scores_gemma":[0.000027612836,0.00006649209,0.0028442233,0.0000056104445,0.000073694224,0.00015930891,0.000047475954,0.9880413,0.0005105552,0.00802516,0.00018822931,0.000010282142],"about_ca_topic_score_codex":0.008587515,"about_ca_topic_score_gemma":0.005238747,"teacher_disagreement_score":0.008587515,"about_ca_system_score_codex":0.00059648143,"about_ca_system_score_gemma":0.0009915583,"threshold_uncertainty_score":0.0348987},"labels":[],"label_agreement":null},{"id":"W2015159159","doi":"10.1111/epi.12581","title":"Disrupted anatomic white matter network in left mesial temporal lobe epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; University of Alberta","keywords":"White matter; Diffusion MRI; Tractography; Precuneus; Temporal lobe; Epilepsy; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.0237875007295809,"score_gpt":0.315016801856946,"score_spread":0.2912293011273651,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015159159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999564,0.0000453396,0.0001816783,0.000017440094,5.2043754e-7,0.000002483269,0.000047230104,0.0000041193625,0.00013722092],"genre_scores_gemma":[0.99974567,0.000028391894,0.00010861867,0.000004172934,0.0000011546958,0.0000020354582,0.000054159213,8.2296674e-7,0.000054965265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994195,0.00000935436,0.0000061831433,0.000020802736,0.000011253518,0.000010491193],"domain_scores_gemma":[0.9997149,0.00004705603,0.00017234392,0.000019120364,0.000016773112,0.00002970267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014369849,0.00020450399,0.00014556843,0.0007232481,0.00023450982,0.00024545114,0.00010012232,0.00014509907,0.0015558781],"category_scores_gemma":[0.0006994308,0.000086416374,0.000108638145,0.00033283426,0.0003234229,0.00033951504,0.00021510727,0.000111382775,0.00012288884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007073042,0.00007058093,0.9316009,0.00008781476,0.00017072922,0.003793565,0.00095938763,0.0012994312,0.04427382,0.0003458652,0.000243815,0.016446766],"study_design_scores_gemma":[0.00001398191,0.0001722323,0.99042046,0.0000080192485,0.000052873616,0.0048257424,0.00027980894,0.0013446003,0.0021802548,0.000472424,0.00022455209,0.0000050721824],"about_ca_topic_score_codex":0.0018163353,"about_ca_topic_score_gemma":0.0046215598,"teacher_disagreement_score":0.0018163353,"about_ca_system_score_codex":0.00024602166,"about_ca_system_score_gemma":0.00015411012,"threshold_uncertainty_score":0.0052049756},"labels":[],"label_agreement":null},{"id":"W2015504855","doi":"10.1016/s0221-0363(07)89845-3","title":"Imagerie de diffusion : principes et applications cliniques","year":2007,"lang":"fr","type":"article","venue":"Journal de Radiologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ste. Anne's Hospital","funders":"","keywords":"Medicine; Nuclear medicine; Abscess; Diffusion MRI; Radiology; Magnetic resonance imaging; Surgery","score_opus":0.10111008318735644,"score_gpt":0.4514325129580886,"score_spread":0.3503224297707322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015504855","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008079494,0.050537907,0.92017704,0.004831271,0.0005234185,0.00011753628,0.00015038453,0.0005512136,0.015031823],"genre_scores_gemma":[0.2080302,0.0819233,0.69794935,0.000877358,0.0024353121,0.00037093143,0.00018442675,0.00033923937,0.00788982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985292,0.00063335197,0.00014361659,0.0002716764,0.00035299183,0.00006919339],"domain_scores_gemma":[0.9964101,0.002361492,0.00021325515,0.0002846263,0.0006245881,0.00010610218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004388843,0.0020501064,0.0020350504,0.0040090214,0.0011196929,0.0069204494,0.0017990909,0.004327475,0.0014647752],"category_scores_gemma":[0.009103614,0.0012386363,0.001833902,0.0023271656,0.009048245,0.0059195366,0.0015015068,0.0065014847,0.0011189901],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090759335,0.00006515403,0.0018261551,0.0012391326,0.00012856394,0.002083035,0.0009668927,0.013125773,0.009289733,0.83294207,0.0051546986,0.13308798],"study_design_scores_gemma":[0.000088926856,0.00012945321,0.0024315584,0.00056929333,0.0001150529,0.013412331,0.00047545283,0.076589555,0.012194301,0.83646685,0.057335,0.0001922695],"about_ca_topic_score_codex":0.002522878,"about_ca_topic_score_gemma":0.0018723317,"teacher_disagreement_score":0.0069204494,"about_ca_system_score_codex":0.0016256775,"about_ca_system_score_gemma":0.0013735997,"threshold_uncertainty_score":0.023210704},"labels":[],"label_agreement":null},{"id":"W2015629981","doi":"10.1016/j.neuroimage.2015.02.051","title":"Cerebral maturation in the early preterm period—A magnetization transfer and diffusion tensor imaging study using voxel-based analysis","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children; SickKids Foundation","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"White matter; Diffusion MRI; Voxel; Effective diffusion coefficient; Fractional anisotropy; Magnetization transfer; Linear regression; Gestational age; Magnetic resonance imaging; Nuclear medicine; Nuclear magnetic resonance; Medicine; Physics; Radiology; Mathematics; Biology; Statistics","score_opus":0.0695145498264368,"score_gpt":0.3393055475365746,"score_spread":0.2697909977101378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015629981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979963,0.0007098662,0.00035478096,0.00014181354,0.000013407538,0.000027098698,0.0001670067,0.000009310081,0.00058033614],"genre_scores_gemma":[0.9978156,0.001070737,0.0005024161,0.000049091883,0.000034814842,0.000037652833,0.00014402565,0.0000105831605,0.00033490814],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997621,0.00005138756,0.000025232104,0.00006746636,0.00004750837,0.000046252222],"domain_scores_gemma":[0.9993216,0.0002254223,0.00015098788,0.00007061383,0.00012306913,0.00010842339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077904266,0.0005579356,0.0007245382,0.0014401713,0.0007260626,0.0007404277,0.000781756,0.001111781,0.000975931],"category_scores_gemma":[0.0034653875,0.0005237687,0.0004897906,0.0012468339,0.0010280033,0.0006527176,0.00055436156,0.0012402843,0.00026461575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0095531875,0.0024509768,0.68749714,0.0006944116,0.00040349198,0.12286803,0.005856129,0.0008923141,0.105204694,0.0014491343,0.0013411852,0.061789203],"study_design_scores_gemma":[0.00010274514,0.0014127196,0.94775766,0.00006566051,0.00023846875,0.03820605,0.0013887418,0.0006788931,0.007990111,0.0007204657,0.0013953217,0.000043099135],"about_ca_topic_score_codex":0.0062797526,"about_ca_topic_score_gemma":0.0030611777,"teacher_disagreement_score":0.0062797526,"about_ca_system_score_codex":0.00064510456,"about_ca_system_score_gemma":0.00074395986,"threshold_uncertainty_score":0.012486458},"labels":[],"label_agreement":null},{"id":"W2016628198","doi":"10.1111/1467-7687.00369","title":"Mapping the development of white matter tracts with diffusion tensor imaging","year":2002,"lang":"en","type":"article","venue":"Developmental Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Corpus callosum; White matter; Fractional anisotropy; Psychology; Gyrus; Neuroscience; Audiology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06617429555506825,"score_gpt":0.2921760564081526,"score_spread":0.22600176085308432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016628198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96986526,0.000945047,0.027895657,0.000087076376,0.000010248111,0.000055625445,0.00021212183,0.000065846274,0.0008630269],"genre_scores_gemma":[0.9332256,0.0013920527,0.06432732,0.000022271695,0.000013534489,0.00005705487,0.0002625876,0.000025520287,0.0006740756],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989426,0.00003601703,0.000013791202,0.000027006783,0.000020984658,0.000007950103],"domain_scores_gemma":[0.99974555,0.000063007465,0.00008902703,0.000034171335,0.00004619468,0.000022042821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079738116,0.00032983875,0.00011931198,0.0008017806,0.0001659587,0.00032210193,0.00013737756,0.000165059,0.0008086374],"category_scores_gemma":[0.0014829073,0.00014496947,0.00011405809,0.00042354024,0.00032641276,0.0005903125,0.00019451132,0.00016870486,0.00019996807],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060158374,0.00013758313,0.1717279,0.0004892458,0.00020801535,0.0012988065,0.0012212677,0.001905852,0.60312974,0.0015475336,0.0008943353,0.21683812],"study_design_scores_gemma":[0.000069755035,0.0011098767,0.8256266,0.00010556338,0.00018066906,0.007391269,0.00067524787,0.011076794,0.14371593,0.003326902,0.006663259,0.00005809151],"about_ca_topic_score_codex":0.001489048,"about_ca_topic_score_gemma":0.0027923058,"teacher_disagreement_score":0.001489048,"about_ca_system_score_codex":0.00013687638,"about_ca_system_score_gemma":0.0002818067,"threshold_uncertainty_score":0.004216969},"labels":[],"label_agreement":null},{"id":"W2016960129","doi":"10.1016/j.neuroimage.2011.09.009","title":"Establishing the reproducibility of two approaches to quantify white matter tract integrity in stroke","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Science Council; Canada Research Chairs; Michael Smith Health Research BC","keywords":"White matter; Corticospinal tract; Fractional anisotropy; Diffusion MRI; Internal capsule; Stroke (engine); Psychology; Physical medicine and rehabilitation; Tractography; Pyramidal tracts; Medicine; Physical therapy; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.39545437201811084,"score_gpt":0.37861795609384064,"score_spread":0.01683641592427021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016960129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7665763,0.0041693826,0.2178172,0.000638172,0.0006977063,0.00055633136,0.00096092763,0.0007627509,0.00782137],"genre_scores_gemma":[0.95020473,0.00039265546,0.046408627,0.00027759158,0.00017041079,0.00039921774,0.0003944779,0.00031229452,0.001440028],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9632116,0.014573188,0.0038726004,0.008967891,0.008236026,0.001138691],"domain_scores_gemma":[0.8745061,0.06131459,0.012097509,0.026714763,0.024004888,0.0013622176],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.047513366,0.0011037829,0.0011395242,0.003654731,0.0019023636,0.0042783325,0.0021715187,0.004303979,0.0008532738],"category_scores_gemma":[0.12399805,0.0013482107,0.0015247798,0.0017192668,0.0039504077,0.0029375274,0.0024118654,0.0026514728,0.00079480384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009703881,0.0010877791,0.61339664,0.0012195398,0.010633587,0.00052696577,0.0063238307,0.01274173,0.1422462,0.010091041,0.0027280028,0.18930085],"study_design_scores_gemma":[0.0005194152,0.0028185914,0.8341899,0.0002991328,0.0029474131,0.0027750083,0.0008964878,0.05755849,0.080508664,0.01051132,0.0065602497,0.00041532217],"about_ca_topic_score_codex":0.0042901244,"about_ca_topic_score_gemma":0.009356554,"teacher_disagreement_score":0.95248663,"about_ca_system_score_codex":0.0012566904,"about_ca_system_score_gemma":0.0015638727,"threshold_uncertainty_score":0.2512777},"labels":[],"label_agreement":null},{"id":"W2017077053","doi":"10.1002/mrm.24120","title":"The effect of concomitant gradient fields on diffusion tensor imaging","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University Hospital Foundation; Canada Foundation for Innovation; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"Dephasing; Diffusion MRI; Diffusion; Physics; Nuclear magnetic resonance; Isocenter; Imaging phantom; Magnetic field; Amplitude; Pulsed field gradient; Pulse sequence; Computational physics; Magnetic resonance imaging; Optics; Condensed matter physics; Quantum mechanics","score_opus":0.025679313783316685,"score_gpt":0.33510791589481165,"score_spread":0.309428602111495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017077053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.422896,0.0060418835,0.56464744,0.00073013845,0.0005388578,0.00021603209,0.00030671,0.001490089,0.0031328667],"genre_scores_gemma":[0.7807451,0.0031719175,0.21206845,0.00024276879,0.00012587078,0.000064608605,0.00023546346,0.00048943766,0.0028563938],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99860686,0.0003658202,0.00012894196,0.00026262904,0.0005533326,0.00008248918],"domain_scores_gemma":[0.9867867,0.008474365,0.0014238654,0.001602132,0.0014606051,0.00025220885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024816203,0.0008559219,0.00054323947,0.0006572147,0.0005274103,0.00080965715,0.00049934915,0.00068177935,0.0010845565],"category_scores_gemma":[0.025018144,0.0004293466,0.00038033279,0.00091080595,0.0006617448,0.0014210179,0.000888346,0.0007301717,0.00039010932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015276088,0.00013350179,0.015581476,0.00095616473,0.0001887315,0.0015485638,0.0006566083,0.030379623,0.6882644,0.007821753,0.0012088795,0.25173265],"study_design_scores_gemma":[0.00007191273,0.0012226363,0.042964593,0.00012766244,0.00041793642,0.0045046858,0.00010904729,0.13247073,0.80372787,0.005678889,0.00852938,0.00017462572],"about_ca_topic_score_codex":0.0016593585,"about_ca_topic_score_gemma":0.002311357,"teacher_disagreement_score":0.0024816203,"about_ca_system_score_codex":0.0005025414,"about_ca_system_score_gemma":0.0007009773,"threshold_uncertainty_score":0.0131242275},"labels":[],"label_agreement":null},{"id":"W2017219549","doi":"10.1167/10.7.614","title":"Adaptation to Up/Down Head Rotation in Face Selective Cortical Areas","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; York University","funders":"","keywords":"Adaptation (eye); Fusiform face area; Psychology; Face (sociological concept); Lateralization of brain function; Cognitive psychology; Right hemisphere; Laterality; Sulcus; Occipital lobe; Neuroscience; Face perception; Perception","score_opus":0.048445987923890946,"score_gpt":0.4115470657456437,"score_spread":0.36310107782175277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017219549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988035,0.000036029553,0.00063263386,0.0000110230385,0.0000033095082,0.000010341745,0.00003640704,0.000012670198,0.0004541158],"genre_scores_gemma":[0.99877495,0.000036552672,0.00046219953,0.000029320605,0.000004765806,0.00001952581,0.000087723856,0.000011580968,0.0005733105],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998872,0.000020479705,0.000006202081,0.000034976973,0.000022414868,0.000028754785],"domain_scores_gemma":[0.9998223,0.000062002626,0.000033035154,0.000032406395,0.000024313827,0.000026006412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018120183,0.00021766352,0.00020414863,0.00017427675,0.00008411547,0.00015740939,0.00008095544,0.0001264014,0.0016457104],"category_scores_gemma":[0.0006076,0.00013395555,0.00019674143,0.00007627329,0.0002907174,0.00011107836,0.00018283774,0.00024980635,0.00014136323],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006247751,0.000045595887,0.0054112934,0.000010777221,0.000014895773,0.00007651285,0.000046598972,0.00013032787,0.98867804,0.00002740949,0.000039002836,0.0048948936],"study_design_scores_gemma":[0.000035214845,0.0007276537,0.912648,0.0000028483698,0.000026505315,0.0005215415,0.000062279985,0.0009664422,0.08467838,0.00010924266,0.00021232794,0.0000095062815],"about_ca_topic_score_codex":0.0010460912,"about_ca_topic_score_gemma":0.001506617,"teacher_disagreement_score":0.0016457104,"about_ca_system_score_codex":0.0001475734,"about_ca_system_score_gemma":0.00012582046,"threshold_uncertainty_score":0.0055054426},"labels":[],"label_agreement":null},{"id":"W2017283521","doi":"10.1016/j.mri.2013.12.006","title":"In vivo longitudinal Myelin Water Imaging in rat spinal cord following dorsal column transection injury","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; International Collaboration On Repair Discoveries","funders":"Canadian Institutes of Health Research","keywords":"Myelin; Ex vivo; Spinal cord injury; Spinal cord; In vivo; Anatomy; Pathology; Medicine; Posterior column; Diffuse axonal injury; Chemistry; Central nervous system; Biology; Internal medicine","score_opus":0.022089067594348564,"score_gpt":0.3245697248524415,"score_spread":0.3024806572580929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017283521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98414177,0.002347218,0.010921812,0.00021694035,0.00006400646,0.000052595682,0.00036930974,0.00020337876,0.0016829807],"genre_scores_gemma":[0.97818315,0.0025132434,0.00881353,0.000088179186,0.000026394635,0.00013003459,0.00038321377,0.000076315344,0.009785856],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998722,0.000011946917,0.0000063278467,0.000028828845,0.000019691086,0.000061003142],"domain_scores_gemma":[0.99973637,0.000023552084,0.000081020735,0.000017901835,0.00006782382,0.00007329428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032826178,0.00065385853,0.0003751329,0.0006915385,0.00046486265,0.00043820596,0.0004514896,0.0005669973,0.0015763171],"category_scores_gemma":[0.00022534413,0.00041798802,0.00032577233,0.0004258241,0.0007923733,0.0014723158,0.0003671311,0.0013391351,0.000384308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008255067,0.00010399428,0.00024992818,0.000074523,0.000012622256,0.000101494225,0.00011403971,0.00012471806,0.9956279,0.00018262673,0.000050914718,0.002531823],"study_design_scores_gemma":[0.000033917284,0.0009964752,0.0030240843,0.00001072853,0.00006923613,0.00019976521,0.00022951518,0.00130798,0.9934489,0.00012049102,0.00054873445,0.0000101434725],"about_ca_topic_score_codex":0.008023272,"about_ca_topic_score_gemma":0.011887697,"teacher_disagreement_score":0.008023272,"about_ca_system_score_codex":0.00047350937,"about_ca_system_score_gemma":0.001063446,"threshold_uncertainty_score":0.015953124},"labels":[],"label_agreement":null},{"id":"W2017712084","doi":"10.1006/brcg.1999.1179","title":"Cognitive Rehabilitation in Clinical Neuropsychology","year":2000,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University; Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Receiver operating characteristic; Pathology; Glioma; Region of interest; Chemistry; Nuclear medicine; Internal medicine; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07793029866147806,"score_gpt":0.44464794458901363,"score_spread":0.3667176459275356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017712084","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021812038,0.87278855,0.017826222,0.040308103,0.0052469033,0.000100145204,0.000082995975,0.0001560419,0.04167896],"genre_scores_gemma":[0.34789142,0.58467627,0.029204817,0.0097014755,0.016265698,0.00040351463,0.000094272764,0.00005534188,0.011707301],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99940264,0.00031216157,0.00007892786,0.00004219936,0.00010248399,0.000061654246],"domain_scores_gemma":[0.9983354,0.0011349118,0.0000854979,0.00007594543,0.00023176729,0.00013653409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026911625,0.00065876404,0.0009021285,0.0018862492,0.0006629691,0.0024797854,0.000838463,0.0023575332,0.0032458105],"category_scores_gemma":[0.0045557762,0.0002157325,0.00025351724,0.0017446779,0.0034504577,0.0026756513,0.0009389141,0.0022556924,0.00055078196],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022051715,0.0005635828,0.006198205,0.0027740637,0.00008693385,0.0017427376,0.0011267213,0.00156574,0.0014649802,0.058175392,0.04197552,0.8841056],"study_design_scores_gemma":[0.00025390263,0.0008345393,0.053929053,0.0056257723,0.0002451505,0.019103032,0.004470317,0.004742422,0.0020048926,0.5756357,0.33300725,0.00014797486],"about_ca_topic_score_codex":0.0030346725,"about_ca_topic_score_gemma":0.006522879,"teacher_disagreement_score":0.0032458105,"about_ca_system_score_codex":0.0012965273,"about_ca_system_score_gemma":0.0037268733,"threshold_uncertainty_score":0.014232397},"labels":[],"label_agreement":null},{"id":"W2018045853","doi":"10.1016/j.schres.2014.04.026","title":"White matter changes in early phase schizophrenia and cannabis use: An update and systematic review of diffusion tensor imaging studies","year":2014,"lang":"en","type":"review","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Capital District Health Authority; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Medicine; Psychology; Psychiatry; Radiology; Magnetic resonance imaging","score_opus":0.15938023987410593,"score_gpt":0.4821144066455719,"score_spread":0.322734166771466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018045853","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00061123347,0.9991503,0.000028926464,0.000060210186,0.000020895443,0.0000089268315,0.000079026155,0.0000012350782,0.000039202914],"genre_scores_gemma":[0.0056109796,0.99384284,0.00024673704,0.0001283562,0.00004450937,0.000013901578,0.00008300034,9.974669e-7,0.000028749604],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99855465,0.00028708097,0.000617992,0.00021092637,0.00027301212,0.00005627276],"domain_scores_gemma":[0.9954333,0.0027136772,0.0012771006,0.00008250597,0.00043248467,0.000060900627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030675072,0.0011768315,0.005250828,0.0055639353,0.000340755,0.0015255393,0.0011063832,0.0011154515,0.001441908],"category_scores_gemma":[0.007774398,0.00059388217,0.004134551,0.0057982043,0.00061189785,0.001381314,0.0011058047,0.000715395,0.00013019411],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069356896,0.00006458223,0.008443724,0.60437256,0.020480579,0.00049418764,0.00027716524,0.00028498087,0.0011985163,0.0003577767,0.0046785045,0.35865387],"study_design_scores_gemma":[0.0009269294,0.0007332559,0.121953785,0.44382346,0.28722098,0.0070433426,0.0010831095,0.00046647486,0.0015321723,0.0017642267,0.13309431,0.0003579168],"about_ca_topic_score_codex":0.007335202,"about_ca_topic_score_gemma":0.025518376,"teacher_disagreement_score":0.007335202,"about_ca_system_score_codex":0.0009302629,"about_ca_system_score_gemma":0.0038381766,"threshold_uncertainty_score":0.016222715},"labels":[],"label_agreement":null},{"id":"W2018703198","doi":"10.1016/j.neurobiolaging.2013.12.001","title":"Non-Gaussian water diffusion in aging white matter","year":2013,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"White matter; Diffusion MRI; Neuroimaging; Multivariate statistics; Kurtosis; Voxel; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Psychology; Radiology; Statistics; Mathematics","score_opus":0.020178301769400483,"score_gpt":0.29429660337560554,"score_spread":0.27411830160620504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018703198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75359863,0.015602844,0.22681268,0.0011080862,0.00009848077,0.000035054807,0.00018476999,0.00015072839,0.0024086938],"genre_scores_gemma":[0.93894494,0.007876585,0.049378794,0.00006787065,0.00008928587,0.000023599563,0.00010321096,0.000027838287,0.0034878962],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994516,0.000014014601,0.0000039776783,0.000016475184,0.000012490334,0.000007948066],"domain_scores_gemma":[0.99967957,0.00014068648,0.00005638813,0.000025934693,0.00007002487,0.000027330703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007151309,0.000266244,0.0001806503,0.0004163925,0.00021156782,0.0004819868,0.0003141638,0.00046927496,0.00036810487],"category_scores_gemma":[0.0020774286,0.0001897071,0.00015177955,0.00050511584,0.00061997015,0.0016874663,0.00037722613,0.00035070966,0.00009363887],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011488654,0.00022881855,0.038506575,0.0011681588,0.00023157764,0.002318376,0.0022845813,0.07330599,0.4842988,0.14866243,0.00346396,0.2443819],"study_design_scores_gemma":[0.00008765655,0.0003546831,0.10218566,0.00010614081,0.00019183307,0.0034345624,0.0008993466,0.5631305,0.09730333,0.22030634,0.011835036,0.00016487014],"about_ca_topic_score_codex":0.0042127385,"about_ca_topic_score_gemma":0.005979171,"teacher_disagreement_score":0.0042127385,"about_ca_system_score_codex":0.00032516292,"about_ca_system_score_gemma":0.0005026833,"threshold_uncertainty_score":0.00837642},"labels":[],"label_agreement":null},{"id":"W2018708850","doi":"10.1152/jn.01044.2011","title":"Transcallosal inhibition in patients with callosal infarction","year":2012,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Corpus callosum; Transcranial magnetic stimulation; Lesion; Infarction; Medicine; Silent period; Neurology; Stimulation; Neuroscience; Psychology; Anatomy; Cardiology; Pathology; Myocardial infarction","score_opus":0.028558945835012405,"score_gpt":0.3017571126646538,"score_spread":0.27319816682964143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018708850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99958104,0.00010812046,0.000040862822,0.0000135013815,0.0000016297793,0.0000036654967,0.000017179142,0.0000040540276,0.00022993241],"genre_scores_gemma":[0.99979454,0.000048186434,0.000031571733,0.000010229734,0.0000053647045,0.0000023016648,0.000052972027,0.0000010213771,0.000053917065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985635,0.00002156743,0.000020822412,0.00004430619,0.000025339701,0.0000315416],"domain_scores_gemma":[0.99949014,0.00008843496,0.00025190227,0.000033119242,0.000038814775,0.0000975768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014704792,0.0006253005,0.00053806073,0.0006704432,0.0005304385,0.0004184014,0.00021296185,0.00043447412,0.0012586303],"category_scores_gemma":[0.0011877137,0.00018624814,0.00023541713,0.00046683697,0.00044596876,0.00033574135,0.0002836477,0.00046177857,0.00016750637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000957576,0.000103907514,0.975717,0.000033806937,0.00007631156,0.009121613,0.0007269094,0.00012485476,0.0069793575,0.00006378125,0.00012106442,0.0059737335],"study_design_scores_gemma":[0.000038215974,0.0005689504,0.97148347,0.000010856874,0.000080590195,0.025885614,0.00039005524,0.0003067987,0.00087291276,0.00010420705,0.00024360468,0.000014800408],"about_ca_topic_score_codex":0.0013830661,"about_ca_topic_score_gemma":0.0017130174,"teacher_disagreement_score":0.0013830661,"about_ca_system_score_codex":0.00024121716,"about_ca_system_score_gemma":0.00019684725,"threshold_uncertainty_score":0.0042105913},"labels":[],"label_agreement":null},{"id":"W2018985403","doi":"10.3389/neuro.05.014.2009","title":"Could sex differences in white matter be explained by g ratio?","year":2009,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institutes of Health; Canadian Institutes of Health Research; Royal Society","keywords":"White matter; Myelin; Axon; Myelin sheath; Disconnection; Magnetic resonance imaging; Sex ratio; Nerve conduction velocity; Anatomy; Neuroscience; Nuclear magnetic resonance; Psychology; Biology; Medicine; Physics; Central nervous system; Population; Philosophy; Radiology","score_opus":0.02562428583731719,"score_gpt":0.3002404656535699,"score_spread":0.2746161798162527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018985403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.936806,0.02548415,0.017594084,0.0045625605,0.0008813936,0.00010087698,0.0023469604,0.00048689108,0.011737013],"genre_scores_gemma":[0.99364144,0.00240419,0.0015278303,0.0006259568,0.00020456674,0.000021171505,0.000307859,0.0000782248,0.001188832],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939394,0.00011331561,0.00005930378,0.00028025347,0.00007799417,0.00007515427],"domain_scores_gemma":[0.9982488,0.00075529574,0.0005898883,0.00024260323,0.000083481835,0.00007988023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012091087,0.0006698594,0.00065464014,0.0011001481,0.00022242824,0.0004771747,0.00074505707,0.0006841179,0.004653303],"category_scores_gemma":[0.0049902187,0.00019098553,0.00068712584,0.0008869358,0.0011949537,0.0008089052,0.0003906895,0.0004124504,0.00087071833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018774231,0.00011505153,0.85670537,0.00065252563,0.0014471468,0.00377183,0.0011630292,0.00067222724,0.023083592,0.012365974,0.0033437933,0.094802044],"study_design_scores_gemma":[0.000048462927,0.0006055807,0.9627607,0.00009454094,0.00039195697,0.0059643975,0.00037187754,0.001305334,0.0041721356,0.019419603,0.0048210155,0.00004430935],"about_ca_topic_score_codex":0.000935138,"about_ca_topic_score_gemma":0.0005979836,"teacher_disagreement_score":0.004653303,"about_ca_system_score_codex":0.00017223357,"about_ca_system_score_gemma":0.00015908731,"threshold_uncertainty_score":0.015566826},"labels":[],"label_agreement":null},{"id":"W2018989691","doi":"10.1016/j.neurobiolaging.2003.08.011","title":"The influence of sex on limbic volume and perfusion in AD","year":2003,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Sunnybrook Health Science Centre; University of Toronto; Health Sciences Centre","funders":"Medical Research Council Canada; Ontario Mental Health Foundation","keywords":"Limbic system; Limbic lobe; Atrophy; Posterior cingulate; Anterior cingulate cortex; Orbitofrontal cortex; Cingulate cortex; Perfusion; Magnetic resonance imaging; Neuroimaging; Medicine; Psychology; Alzheimer's disease; Cortex (anatomy); Neuroscience; Pathology; Internal medicine; Central nervous system; Prefrontal cortex; Radiology; Disease; Cognition","score_opus":0.024136816797427844,"score_gpt":0.31136517178810413,"score_spread":0.2872283549906763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018989691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949226,0.0018465043,0.0003022868,0.000083280436,0.000032261978,0.000005539576,0.0003160512,0.000012208722,0.0024794503],"genre_scores_gemma":[0.9978563,0.0005263558,0.0001519965,0.000034783043,0.000036999172,0.0000063742277,0.0000781979,0.000024237408,0.001284698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988914,0.00003740401,0.000007485027,0.00002854149,0.000019251293,0.00001810374],"domain_scores_gemma":[0.99935204,0.000281039,0.0001425764,0.000071758885,0.000056858215,0.000095728574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031716086,0.000264901,0.00037282155,0.0005281203,0.0001721277,0.00045303477,0.00022975696,0.0002614776,0.0032256502],"category_scores_gemma":[0.0014715728,0.00017503316,0.00017459194,0.0003500321,0.00040467104,0.00042312095,0.00016606934,0.00025641682,0.00024767715],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03343021,0.0005271811,0.51849574,0.0002661348,0.00091128255,0.003864115,0.0011892536,0.00077408616,0.29690772,0.0014553439,0.0012685566,0.14091036],"study_design_scores_gemma":[0.00004776113,0.00062744576,0.99184567,0.000008801995,0.000101641854,0.0012205837,0.00011582386,0.00031123267,0.0047731693,0.0005177117,0.00041583474,0.000014258017],"about_ca_topic_score_codex":0.0010572266,"about_ca_topic_score_gemma":0.0013874996,"teacher_disagreement_score":0.0032256502,"about_ca_system_score_codex":0.00018990345,"about_ca_system_score_gemma":0.00019256191,"threshold_uncertainty_score":0.0107908845},"labels":[],"label_agreement":null},{"id":"W2019737946","doi":"10.1002/mrm.22365","title":"Reconstruction of the orientation distribution function in single‐ and multiple‐shell q‐ball imaging within constant solid angle","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":381,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Office of Naval Research; U.S. Public Health Service; Defense Advanced Research Projects Agency; McGill University; W. M. Keck Foundation; National Institutes of Health; National Science Foundation","keywords":"Orientation (vector space); Dimensionless quantity; Sharpening; Geometry; Diffusion MRI; Distribution function; Mathematical analysis; Physics; Mathematics; Computer science; Artificial intelligence; Mechanics; Magnetic resonance imaging","score_opus":0.02405833203071902,"score_gpt":0.29755789276882655,"score_spread":0.27349956073810755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019737946","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058743104,0.000051645784,0.9405699,0.000065414584,0.000007017984,0.000012697533,0.00002367434,0.00011436775,0.00041220261],"genre_scores_gemma":[0.6004804,0.00027367356,0.39778888,0.000047438196,0.000009406708,0.00003998863,0.000120186625,0.00013748433,0.0011025359],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987197,0.00003711495,0.000008318858,0.000030018731,0.000039409122,0.000013029045],"domain_scores_gemma":[0.9995627,0.00017968238,0.00009212582,0.000070031914,0.00007247365,0.000023036617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000977294,0.0004424213,0.00039983523,0.0003524986,0.00015772822,0.000614549,0.00056935113,0.00068554847,0.00047108682],"category_scores_gemma":[0.0019755964,0.00037626305,0.00040774315,0.00038649075,0.0006924203,0.0011221654,0.00044688943,0.0005326566,0.00021130875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041051395,0.000098262775,0.0032112205,0.00022084985,0.000042457654,0.0007775546,0.00046277943,0.6315335,0.2133365,0.045000892,0.0010373932,0.103868075],"study_design_scores_gemma":[0.000010715925,0.00002755445,0.0005968879,0.00000511806,0.0000042650618,0.00021792823,0.00002047138,0.97578603,0.01714064,0.00556937,0.0006045831,0.000016351836],"about_ca_topic_score_codex":0.0015758331,"about_ca_topic_score_gemma":0.0011441861,"teacher_disagreement_score":0.0015758331,"about_ca_system_score_codex":0.00035827985,"about_ca_system_score_gemma":0.00062921713,"threshold_uncertainty_score":0.0051684976},"labels":[],"label_agreement":null},{"id":"W2019795338","doi":"10.1016/j.neuroimage.2008.07.009","title":"Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":583,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; University of California, Los Angeles; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"White matter; Diffusion MRI; Atlas (anatomy); Fiber tract; Neuroscience; Anatomy; Human brain; Cortex (anatomy); Neuroimaging; Biology; Magnetic resonance imaging; Medicine","score_opus":0.03712681418569049,"score_gpt":0.33040838274800466,"score_spread":0.2932815685623142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019795338","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10688499,0.0028104621,0.6695569,0.0015602739,0.00066587015,0.0015311574,0.1404193,0.03729537,0.039275628],"genre_scores_gemma":[0.22230415,0.0026463796,0.6733849,0.00056099216,0.0001477973,0.0030390122,0.05922837,0.0078799,0.030808546],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99982625,0.000032790304,0.000019918733,0.000054202384,0.00004340502,0.000023483413],"domain_scores_gemma":[0.9996877,0.00007794667,0.00003193058,0.00007423345,0.00009991718,0.000028334256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057454925,0.00090574723,0.0004861671,0.0021245102,0.0011266259,0.001653513,0.0010207365,0.001162421,0.019086316],"category_scores_gemma":[0.0016303438,0.000544584,0.00082539866,0.001976724,0.000358091,0.0008449108,0.000805945,0.0009925928,0.0051846737],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020236897,0.00022300001,0.006343986,0.0022014086,0.0006071295,0.0014931873,0.0018726756,0.01960427,0.101057135,0.030877482,0.42304134,0.4106547],"study_design_scores_gemma":[0.00072741346,0.00048844796,0.07740029,0.00037716338,0.00086896116,0.009852158,0.0005449244,0.08295462,0.06268179,0.057241205,0.7065192,0.00034387488],"about_ca_topic_score_codex":0.022727398,"about_ca_topic_score_gemma":0.04074079,"teacher_disagreement_score":0.022727398,"about_ca_system_score_codex":0.0007461463,"about_ca_system_score_gemma":0.0032523985,"threshold_uncertainty_score":0.063850164},"labels":[],"label_agreement":null},{"id":"W2020108690","doi":"10.1007/s00221-001-0921-8","title":"Stereological evaluation of neurons and glia in the monkey dorsal lateral geniculate nucleus following an early cerebral hemispherectomy","year":2002,"lang":"en","type":"article","venue":"Experimental Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Parvocellular cell; Neuroscience; Cytoarchitecture; Biology; Magnocellular cell; Brainstem; Lateral geniculate nucleus; Geniculate; Population; Nissl body; Thalamus; Visual cortex; Anatomy; Central nervous system; Nucleus; Medicine","score_opus":0.303410708727518,"score_gpt":0.4882797532445474,"score_spread":0.1848690445170294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020108690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97928965,0.0019101657,0.008877782,0.0002842071,0.00018741158,0.00007109143,0.0008744362,0.00019718058,0.008308118],"genre_scores_gemma":[0.98186505,0.0011805723,0.0037198148,0.00016047692,0.000047820064,0.00008374429,0.00069691875,0.00007846795,0.012167114],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99987364,0.0000087963235,0.000007673079,0.000025333758,0.00003303836,0.000051540297],"domain_scores_gemma":[0.99971634,0.00006644663,0.000048338872,0.000041971554,0.00007256233,0.00005427256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025935128,0.00025267169,0.00034789677,0.00084050203,0.0005623437,0.00033174764,0.0002823359,0.00056484423,0.0026294847],"category_scores_gemma":[0.00033529292,0.00027876647,0.0002938445,0.0003808598,0.0008495171,0.00044564725,0.0003430002,0.0012070001,0.00044479762],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009808042,0.00007021048,0.0012427695,0.000088050656,0.000023485114,0.00065295404,0.00017599078,0.00023975727,0.99042517,0.00076022826,0.00015205507,0.0051885727],"study_design_scores_gemma":[0.00012513131,0.0010118556,0.0865891,0.000035270474,0.0000888968,0.002174618,0.0006138145,0.002284154,0.90082484,0.0009864864,0.005237561,0.000028256854],"about_ca_topic_score_codex":0.008269772,"about_ca_topic_score_gemma":0.012555894,"teacher_disagreement_score":0.008269772,"about_ca_system_score_codex":0.00057636946,"about_ca_system_score_gemma":0.0005734515,"threshold_uncertainty_score":0.016443312},"labels":[],"label_agreement":null},{"id":"W2020130186","doi":"10.1007/s10548-013-0343-5","title":"The Role of Left Inferior Fronto-Occipital Fascicle in Verbal Perseveration: A Brain Electrostimulation Mapping Study","year":2013,"lang":"en","type":"article","venue":"Brain Topography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Perseveration; Fascicle; White matter; Stimulation; Medicine; Neuroscience; Psychology; Anatomy; Radiology; Magnetic resonance imaging; Cognition","score_opus":0.01787890440456127,"score_gpt":0.29982240863826876,"score_spread":0.2819435042337075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020130186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99896145,0.00008643574,0.00038439743,0.00006012445,0.0000058962914,0.000013286206,0.000024970792,0.0000048372967,0.00045847314],"genre_scores_gemma":[0.99965763,0.000031588974,0.00008268757,0.000020355596,0.000011215951,0.000006029401,0.000012420138,0.0000018020244,0.00017621333],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999008,0.000022361475,0.000008496431,0.000026926618,0.000016022823,0.000025423613],"domain_scores_gemma":[0.9993567,0.00040004693,0.00011319506,0.000049212922,0.00003176507,0.000049092265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033712166,0.0003872097,0.00019519244,0.0004448875,0.00029703553,0.00031932504,0.00035424836,0.00053122605,0.0031299626],"category_scores_gemma":[0.0013841228,0.00013943012,0.00018062929,0.00016311873,0.0011077425,0.0005218302,0.00020395583,0.00032663625,0.00022391987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012649477,0.0019235831,0.28082246,0.00024001685,0.00026366476,0.09920244,0.002763801,0.0009552197,0.54091555,0.0013136287,0.0003847049,0.058565512],"study_design_scores_gemma":[0.0003189469,0.0027010352,0.93699205,0.000015476688,0.00017516634,0.02900878,0.0012891247,0.0021658882,0.025392907,0.0012889864,0.00062133616,0.000030270981],"about_ca_topic_score_codex":0.001457494,"about_ca_topic_score_gemma":0.001089471,"teacher_disagreement_score":0.0031299626,"about_ca_system_score_codex":0.0001999109,"about_ca_system_score_gemma":0.0002464219,"threshold_uncertainty_score":0.010470748},"labels":[],"label_agreement":null},{"id":"W2020823327","doi":"10.1016/j.bandc.2009.06.002","title":"Growth of white matter in the adolescent brain: Myelin or axon?","year":2009,"lang":"en","type":"review","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":433,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Canadian Institutes of Health Research","keywords":"White matter; Myelin; Neuroscience; Psychology; Axon; Magnetic resonance imaging; Human brain; Brain Structure and Function; Brain size; Neuroimaging; Central nervous system; Medicine; Radiology","score_opus":0.1178505650643618,"score_gpt":0.3971825772982026,"score_spread":0.2793320122338408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020823327","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009580094,0.9991961,0.000083557476,0.0002319452,0.000086566106,0.0000014020438,0.000009642711,0.0000028055094,0.000292135],"genre_scores_gemma":[0.0004798255,0.99889815,0.00015083613,0.000085469765,0.00017522414,0.0000020283462,0.000011800188,7.2332426e-7,0.00019588588],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999795,0.000025064046,0.000041709496,0.00005406203,0.000067034125,0.000017210354],"domain_scores_gemma":[0.9992505,0.0003907914,0.00011040037,0.000017083259,0.00018707411,0.00004420011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081371743,0.0012309462,0.0020615798,0.00297269,0.0002771901,0.001078117,0.0011357513,0.0018621199,0.0020391808],"category_scores_gemma":[0.0013639085,0.0004334453,0.00045347738,0.0029110722,0.001339778,0.0020415306,0.00062392413,0.0017048182,0.0015385301],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006702033,0.000049259692,0.00060604274,0.008845858,0.000077119636,0.00045330697,0.00006323839,0.00025343045,0.0010729341,0.0030822875,0.019673668,0.96575594],"study_design_scores_gemma":[0.000037013633,0.0001638872,0.006897953,0.008962457,0.00033412335,0.010563665,0.00041252573,0.0002967798,0.0015220651,0.010210689,0.96051323,0.000085598695],"about_ca_topic_score_codex":0.004391258,"about_ca_topic_score_gemma":0.0067407135,"teacher_disagreement_score":0.004391258,"about_ca_system_score_codex":0.00090829754,"about_ca_system_score_gemma":0.0016921882,"threshold_uncertainty_score":0.008731365},"labels":[],"label_agreement":null},{"id":"W2020896724","doi":"10.1016/j.pscychresns.2003.09.003","title":"MRI volumetry of the vermis and the cerebellar hemispheres in men with schizophrenia","year":2004,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Philippe Pinel de Montréal","funders":"Kuopion Yliopistollinen Sairaala","keywords":"Cerebellar vermis; Schizophrenia (object-oriented programming); Cerebellum; Psychology; Magnetic resonance imaging; Neuroscience; Anatomy; Medicine; Psychiatry; Radiology","score_opus":0.04733860088722303,"score_gpt":0.36825973906920956,"score_spread":0.32092113818198653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020896724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99764854,0.00044490866,0.00014527787,0.000061627026,0.0000049071186,0.000005436878,0.00008709381,0.0000070541314,0.0015951865],"genre_scores_gemma":[0.9994394,0.00011258107,0.00008598254,0.000009600588,0.0000034995312,0.000001383869,0.000021513968,0.0000023060204,0.000323826],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999064,0.0000248596,0.000009060728,0.000019797548,0.000021660217,0.00001811153],"domain_scores_gemma":[0.9997373,0.000063084866,0.00009556166,0.00002374192,0.00003807341,0.00004221631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000283592,0.0002949335,0.00022232921,0.0012071433,0.0003696067,0.00047462483,0.00027040104,0.00032794147,0.0017253769],"category_scores_gemma":[0.0010107952,0.0003795613,0.00018023634,0.0004165481,0.0005046651,0.0004797351,0.00026007163,0.00026168834,0.00014818128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019659998,0.00013861945,0.85163337,0.00016934132,0.00037388474,0.012797508,0.0052215923,0.0029853215,0.09126369,0.0013548979,0.00056019635,0.031535625],"study_design_scores_gemma":[0.000019989562,0.00024557812,0.9891237,0.000013191798,0.00006266217,0.0057976255,0.00076740014,0.00074320723,0.0025725884,0.00029997173,0.00034302016,0.0000109799],"about_ca_topic_score_codex":0.028187158,"about_ca_topic_score_gemma":0.02944039,"teacher_disagreement_score":0.028187158,"about_ca_system_score_codex":0.0005218917,"about_ca_system_score_gemma":0.00047876066,"threshold_uncertainty_score":0.056046188},"labels":[],"label_agreement":null},{"id":"W2021173709","doi":"10.1016/j.neuroimage.2014.12.008","title":"The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Radiological Society of North America","keywords":"Diffusion MRI; In vivo; Axon; Diffusion; Biomedical engineering; Chemistry; Materials science; Neuroscience; Physics; Biology; Medicine; Magnetic resonance imaging; Radiology; Biotechnology; Thermodynamics","score_opus":0.032876289973721905,"score_gpt":0.3480370503872482,"score_spread":0.3151607604135263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021173709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8283343,0.00580532,0.16072719,0.00090430316,0.00024347926,0.00006706953,0.00057312957,0.0007000667,0.0026452309],"genre_scores_gemma":[0.9557437,0.0019208048,0.04029689,0.00019112472,0.00009515309,0.000023853949,0.00042872314,0.00052450114,0.0007753403],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983725,0.0010247163,0.00010815949,0.00019987879,0.00024270896,0.000052075702],"domain_scores_gemma":[0.9628748,0.032591257,0.0011478106,0.0012887802,0.0017591579,0.00033811075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063676783,0.000870822,0.00066439953,0.0008630826,0.0005300938,0.0018244983,0.0005472985,0.0012491626,0.00067502464],"category_scores_gemma":[0.057907045,0.00068293686,0.00033803904,0.0006507772,0.00074341905,0.0015925098,0.0007382027,0.0009966173,0.00031870065],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006947977,0.00024663802,0.077797726,0.0022301085,0.0015104664,0.00090580765,0.00085088133,0.099858366,0.5703808,0.0035849106,0.0023107417,0.2333756],"study_design_scores_gemma":[0.00016164349,0.0014354887,0.14647394,0.000288962,0.001978419,0.006440793,0.00030473038,0.45141953,0.38000494,0.008050922,0.0031464277,0.00029415253],"about_ca_topic_score_codex":0.0023398686,"about_ca_topic_score_gemma":0.003655714,"teacher_disagreement_score":0.0063676783,"about_ca_system_score_codex":0.00035970678,"about_ca_system_score_gemma":0.0006128731,"threshold_uncertainty_score":0.03367591},"labels":[],"label_agreement":null},{"id":"W2021577051","doi":"10.1523/jneurosci.3464-13.2014","title":"Frontal White Matter Tracts Sustaining Speech Production in Primary Progressive Aphasia","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":191,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Aging","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"White matter; Primary progressive aphasia; Neuroscience; Diffusion MRI; Speech production; Arcuate fasciculus; Inferior frontal gyrus; Supplementary motor area; Broca's area; Tractography; Psychology; Superior longitudinal fasciculus; Medicine; Fractional anisotropy; Cognition; Functional magnetic resonance imaging; Frontotemporal dementia; Magnetic resonance imaging; Pathology; Computer science; Disease; Speech recognition","score_opus":0.0360008379895664,"score_gpt":0.3397036808807934,"score_spread":0.303702842891227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021577051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993374,0.00008792657,0.0003102507,0.00000556369,8.0243643e-7,0.0000046932087,0.00005437926,0.00000885657,0.00018999024],"genre_scores_gemma":[0.99947065,0.000035942383,0.00032264285,0.0000036272456,7.982871e-7,0.0000029208818,0.000057435223,0.0000024285173,0.00010356241],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999335,0.000010514985,0.000009259445,0.000024828667,0.000011977242,0.000009917501],"domain_scores_gemma":[0.9997336,0.000069960035,0.00009357572,0.0000370009,0.000023720264,0.000042113294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017160771,0.00019451116,0.00012666117,0.0005095624,0.00019394614,0.00031377436,0.00010453989,0.00021880418,0.00093907875],"category_scores_gemma":[0.0009270483,0.00016995227,0.00012594865,0.00017483367,0.00045377665,0.00026208808,0.00021147604,0.00015168262,0.00014571994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001228964,0.00015500197,0.70142466,0.00014134197,0.00020012315,0.0150196925,0.0015119369,0.0020832994,0.23633401,0.00047353448,0.00023767343,0.041189868],"study_design_scores_gemma":[0.000012023509,0.00023217876,0.98614746,0.000007548779,0.000029265499,0.0076126745,0.00014791857,0.0008700458,0.004394462,0.00036802568,0.00017174505,0.0000066971984],"about_ca_topic_score_codex":0.004510668,"about_ca_topic_score_gemma":0.008843107,"teacher_disagreement_score":0.004510668,"about_ca_system_score_codex":0.00024000769,"about_ca_system_score_gemma":0.0002622638,"threshold_uncertainty_score":0.00896883},"labels":[],"label_agreement":null},{"id":"W2021708425","doi":"10.1016/j.clineuro.2011.12.045","title":"Diffusion tensor imaging as a surrogate marker for outcome after perimesencephalic subarachnoid hemorrhage","year":2012,"lang":"en","type":"article","venue":"Clinical Neurology and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Heart and Stroke Foundation; University of Toronto; St. Michael's Hospital","funders":"Brain Aneurysm Foundation; Heart and Stroke Foundation of Canada","keywords":"Medicine; Diffusion MRI; Subarachnoid hemorrhage; White matter; Biomarker; Imaging biomarker; Neuroimaging; Surrogate endpoint; Radiology; Intensive care medicine; Neuroscience; Magnetic resonance imaging; Internal medicine; Psychiatry","score_opus":0.08683934149102515,"score_gpt":0.40735841419512275,"score_spread":0.32051907270409763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021708425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969422,0.001188921,0.00037874005,0.00014490474,0.000049087,0.000010300996,0.00023690258,0.000013017805,0.0010359595],"genre_scores_gemma":[0.9988066,0.0003757995,0.00025891679,0.00002483536,0.00005450916,0.000011358102,0.00030281785,0.0000035195387,0.00016158003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994174,0.0002513055,0.000084468535,0.000058133046,0.0001155015,0.0000732778],"domain_scores_gemma":[0.993565,0.0019707156,0.0028522457,0.00033646822,0.0004255349,0.0008499784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001751803,0.0006385774,0.00067791843,0.0010492706,0.00036721985,0.001348029,0.000401981,0.00081468566,0.00042233875],"category_scores_gemma":[0.007930345,0.00015366141,0.0003624394,0.00076309155,0.0005875808,0.0010217173,0.0005095777,0.0013638436,0.00019548056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056692907,0.00024860038,0.97861755,0.00007545074,0.00022371141,0.000803833,0.0001689292,0.00059849414,0.0018656768,0.000276729,0.0002879747,0.01116374],"study_design_scores_gemma":[0.00006470633,0.0031240364,0.9875142,0.000055094366,0.00024731786,0.0015299629,0.0002871924,0.003520744,0.0020709008,0.0010261321,0.00051379605,0.00004581623],"about_ca_topic_score_codex":0.00085665216,"about_ca_topic_score_gemma":0.0012232611,"teacher_disagreement_score":0.001751803,"about_ca_system_score_codex":0.00046113704,"about_ca_system_score_gemma":0.0006336065,"threshold_uncertainty_score":0.009264588},"labels":[],"label_agreement":null},{"id":"W2021865008","doi":"10.1016/j.neuroimage.2008.12.028","title":"Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Diffusion MRI; Cluster analysis; Fractional anisotropy; Artificial intelligence; Region of interest; Tractography; White matter; Computer science; Pattern recognition (psychology); Voxel; Intraclass correlation; Magnetic resonance imaging; Mathematics; Statistics; Medicine; Radiology; Reproducibility","score_opus":0.1766558596002192,"score_gpt":0.3989820601226853,"score_spread":0.22232620052246607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021865008","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22667664,0.0005999162,0.76713604,0.00052543846,0.00015090345,0.00015674754,0.0004614691,0.001591988,0.0027008578],"genre_scores_gemma":[0.5025126,0.00025862842,0.4938808,0.000047471458,0.00006715586,0.0000721978,0.00048627975,0.00040289483,0.0022719284],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992374,0.00017948043,0.000054962846,0.00017908272,0.0002977586,0.000051277977],"domain_scores_gemma":[0.9964498,0.00091185124,0.00039878555,0.00052942045,0.0015436972,0.00016632226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021883077,0.0007737343,0.0004896188,0.00219932,0.00077027996,0.0016999552,0.0010020016,0.0012282553,0.0017085065],"category_scores_gemma":[0.0057231984,0.00034266614,0.0004720996,0.0013259294,0.00057018606,0.0014421076,0.0006504743,0.0004920041,0.00060000864],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001334814,0.00039922347,0.01983061,0.0007776904,0.0006833788,0.00047389162,0.00047059177,0.15698346,0.38238364,0.017084667,0.005300111,0.41427785],"study_design_scores_gemma":[0.00006745452,0.00021988314,0.019054014,0.000035118916,0.00013178056,0.0007225674,0.000107468695,0.9140675,0.059327234,0.0034837862,0.0026852307,0.000097865544],"about_ca_topic_score_codex":0.0062166774,"about_ca_topic_score_gemma":0.0076535875,"teacher_disagreement_score":0.0062166774,"about_ca_system_score_codex":0.00073921535,"about_ca_system_score_gemma":0.0011410677,"threshold_uncertainty_score":0.01236099},"labels":[],"label_agreement":null},{"id":"W2021874511","doi":"10.3171/2014.10.peds13644","title":"Postshunt lateral ventricular volume, white matter integrity, and intellectual outcomes in spina bifida and hydrocephalus","year":2015,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Medicine; Hydrocephalus; Lateral ventricles; Diffusion MRI; White matter; Fractional anisotropy; Shunt (medical); Ventricular system; Ventricle; Cerebral ventricle; Brain size; Spina bifida; Third ventricle; Fourth ventricle; Cardiology; Magnetic resonance imaging; Anatomy; Radiology; Surgery","score_opus":0.05589107948892645,"score_gpt":0.32050279834077006,"score_spread":0.2646117188518436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021874511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99951375,0.0001853894,0.000022313288,0.000028075405,0.0000024152855,0.0000016632231,0.00008862668,0.0000023702826,0.00015543922],"genre_scores_gemma":[0.9996697,0.0000754621,0.00007078652,0.000006497344,0.0000051042416,0.0000029555513,0.000118275784,9.665752e-7,0.000050234143],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975437,0.000039802457,0.000030389145,0.00004522467,0.000083775114,0.00004640332],"domain_scores_gemma":[0.99628913,0.0006499929,0.0023030946,0.00008376865,0.00020295201,0.00047105522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070399727,0.00033834518,0.00024029873,0.0010686177,0.00028154,0.00046044236,0.0003327305,0.00034503356,0.0012726706],"category_scores_gemma":[0.0044170213,0.00011691444,0.00024253558,0.000586601,0.00064258015,0.00047887984,0.00046308053,0.00042468437,0.00012855216],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054689062,0.000030698888,0.99737215,0.000008832732,0.000021504407,0.00024617038,0.000060246675,0.000056525638,0.00013253972,0.00001298952,0.000042618907,0.0019609754],"study_design_scores_gemma":[0.0000015484111,0.00007016328,0.9992292,0.000006206576,0.0000069913167,0.0004695031,0.000052230404,0.00006169748,0.000061265826,0.000017288054,0.000022638931,0.0000013927934],"about_ca_topic_score_codex":0.0034766411,"about_ca_topic_score_gemma":0.0043942514,"teacher_disagreement_score":0.0034766411,"about_ca_system_score_codex":0.00037442762,"about_ca_system_score_gemma":0.00045028917,"threshold_uncertainty_score":0.0069128275},"labels":[],"label_agreement":null},{"id":"W2022237952","doi":"10.1016/j.media.2014.06.003","title":"Multi-shell diffusion signal recovery from sparse measurements","year":2014,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Academy of Finland","keywords":"Algorithm; SIGNAL (programming language); Diffusion; Computer science; Range (aeronautics); Mathematics; Mathematical optimization; Physics","score_opus":0.08600627826693114,"score_gpt":0.35698312701008417,"score_spread":0.27097684874315303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022237952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006004083,0.0001483795,0.992935,0.00019588336,0.000021631906,0.000016164971,0.000060824652,0.00016356791,0.00045437829],"genre_scores_gemma":[0.17193136,0.0009333005,0.823344,0.00014204618,0.000094821255,0.00008844485,0.0004531921,0.00017115178,0.0028417718],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974316,0.00007710591,0.000020962107,0.00005053701,0.00009336882,0.000014870343],"domain_scores_gemma":[0.99891317,0.0004964495,0.00016202334,0.00022822928,0.00015637142,0.000043792028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006940038,0.000722605,0.0005580611,0.000652448,0.0002527418,0.0007828659,0.00064621255,0.0011132965,0.0012830623],"category_scores_gemma":[0.005170384,0.000570522,0.0005709719,0.00093633716,0.0006356294,0.0017266603,0.0013553629,0.0015460904,0.0007178813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037200615,0.00013261846,0.001526005,0.000738478,0.00021879408,0.00038739704,0.0003744925,0.2509223,0.14738792,0.05829751,0.0059944238,0.5336481],"study_design_scores_gemma":[0.000019260759,0.000062426174,0.0006150675,0.000034181674,0.000036195368,0.00041765056,0.00004336143,0.9406218,0.023966588,0.029855145,0.004297675,0.0000306006],"about_ca_topic_score_codex":0.000851536,"about_ca_topic_score_gemma":0.0013813028,"teacher_disagreement_score":0.0012830623,"about_ca_system_score_codex":0.000183304,"about_ca_system_score_gemma":0.0006512347,"threshold_uncertainty_score":0.0042922497},"labels":[],"label_agreement":null},{"id":"W2022349962","doi":"10.1002/hbm.20576","title":"Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity","year":2008,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":191,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Resting state fMRI; Multiple sclerosis; Neuroscience; Functional connectivity; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.1757230029556175,"score_gpt":0.278575081015041,"score_spread":0.10285207805942354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022349962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99956983,0.00007543276,0.00014534613,0.000012959228,7.61558e-7,0.0000018105408,0.000034506535,0.000009273908,0.00015016082],"genre_scores_gemma":[0.9995524,0.000039468807,0.00017684576,0.0000052112864,0.0000031419852,0.0000026455318,0.0000893249,0.0000024094204,0.00012855366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998765,0.00002440433,0.000013889951,0.000045533063,0.000024044954,0.0000155008],"domain_scores_gemma":[0.9990151,0.00025274773,0.00045495835,0.000075136384,0.00008936744,0.0001127165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002495076,0.00023162943,0.00024668567,0.00061269326,0.00018948746,0.00027055084,0.00012598746,0.00029199966,0.0017693082],"category_scores_gemma":[0.0020062411,0.0002092836,0.0001581784,0.00026120152,0.0003142971,0.00028224252,0.00025276325,0.00027453474,0.00026877815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000787654,0.00006517402,0.94861656,0.000029784593,0.00026592505,0.00056673813,0.000279785,0.0004838301,0.03834592,0.0000825993,0.00017902962,0.0102970805],"study_design_scores_gemma":[0.0000064519872,0.00009573959,0.99817634,0.0000015304832,0.000014597269,0.0008376007,0.000024877581,0.00031217333,0.0004272003,0.00006311968,0.00003786702,0.0000025882841],"about_ca_topic_score_codex":0.0014269691,"about_ca_topic_score_gemma":0.0022022328,"teacher_disagreement_score":0.0017693082,"about_ca_system_score_codex":0.00017626348,"about_ca_system_score_gemma":0.00011558225,"threshold_uncertainty_score":0.00591892},"labels":[],"label_agreement":null},{"id":"W2023527865","doi":"10.1002/mrm.23254","title":"Six is enough? Comparison of diffusion parameters measured using six or more diffusion‐encoding gradient directions with deterministic tractography","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Science and Research Authority; Canadian Institutes of Health Research; Alberta Innovates; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Diffusion; Tractography; Diffusion MRI; Encoding (memory); Statistical physics; Computer science; Nuclear magnetic resonance; Algorithm; Artificial intelligence; Physics; Medicine; Magnetic resonance imaging; Radiology; Quantum mechanics","score_opus":0.154233227715255,"score_gpt":0.37176231237995006,"score_spread":0.21752908466469506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023527865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95730007,0.0035665508,0.034358937,0.0012843716,0.00030510587,0.00007834414,0.0003341872,0.00017123345,0.0026011602],"genre_scores_gemma":[0.97958106,0.0010158963,0.018031888,0.00033681927,0.00006825747,0.00006305702,0.0004189172,0.00015615635,0.00032785465],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99456835,0.002144738,0.0008745646,0.0009505675,0.0011143463,0.00034751635],"domain_scores_gemma":[0.97365516,0.010374501,0.0047025974,0.0064754095,0.0031218422,0.0016705166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013213748,0.00080560485,0.0015586517,0.0015409485,0.00078922836,0.0020754861,0.0006607267,0.00168908,0.0019736576],"category_scores_gemma":[0.038773328,0.00070793205,0.0010241035,0.0013642567,0.0028010402,0.0046299994,0.0015720662,0.0011975351,0.0005752274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021576967,0.0012713916,0.3007468,0.0032204757,0.0033332882,0.0017325919,0.0048208265,0.011977737,0.3702605,0.017360918,0.0032807123,0.26041782],"study_design_scores_gemma":[0.0008618229,0.010679925,0.7158005,0.0013426463,0.0028342532,0.010112981,0.008592046,0.02717801,0.099106334,0.09944767,0.023262713,0.0007811208],"about_ca_topic_score_codex":0.00064641616,"about_ca_topic_score_gemma":0.0012893657,"teacher_disagreement_score":0.013213748,"about_ca_system_score_codex":0.0004315439,"about_ca_system_score_gemma":0.00070674665,"threshold_uncertainty_score":0.06988186},"labels":[],"label_agreement":null},{"id":"W2023600537","doi":"10.1310/3bxl-18w0-fpj4-f1gy","title":"Intrinsic Factors Influencing Post Stroke Brain Reorganization","year":2005,"lang":"en","type":"review","venue":"Topics in Stroke Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Victoria Hospital; St Joseph's Health Care","funders":"Canadian Stroke Network; Heart and Stroke Foundation of Canada","keywords":"Lesion; Stroke (engine); Stroke recovery; Spontaneous recovery; Physical medicine and rehabilitation; Neuroscience; Motor cortex; Motor function; Psychology; Medicine; Cortex (anatomy); Rehabilitation; Surgery; Stimulation","score_opus":0.05787192778041632,"score_gpt":0.39277183861708725,"score_spread":0.3348999108366709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023600537","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00058133114,0.9983064,0.00010704778,0.0000922367,0.000048362577,0.0000044560215,0.00001880718,0.0000056774547,0.00083564915],"genre_scores_gemma":[0.0021003357,0.9972343,0.000076195414,0.00004525287,0.0000444652,0.0000061391506,0.000029152985,6.234327e-7,0.00046349937],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998996,0.000016742984,0.000014811946,0.000023439401,0.000031668595,0.000013737222],"domain_scores_gemma":[0.9998913,0.000038748196,0.000029550552,0.0000038289077,0.000029949311,0.000006631285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003028452,0.00060563604,0.0012660361,0.0012296343,0.00015507283,0.0007235914,0.0005768764,0.00069593044,0.0028947927],"category_scores_gemma":[0.00044726065,0.00017461891,0.0003117346,0.0013489679,0.000329009,0.0007472421,0.00035046382,0.00043263295,0.0016908877],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011489428,0.00006933582,0.00070706825,0.015760291,0.00014624055,0.0004206969,0.00007223536,0.00031142516,0.0045811776,0.0015609699,0.007522584,0.96873313],"study_design_scores_gemma":[0.00008036682,0.00047890312,0.034613192,0.009641243,0.0005900423,0.007928303,0.0004161997,0.00026948014,0.007850233,0.0068946145,0.9311646,0.00007286015],"about_ca_topic_score_codex":0.0009819359,"about_ca_topic_score_gemma":0.0017490283,"teacher_disagreement_score":0.0028947927,"about_ca_system_score_codex":0.00041681025,"about_ca_system_score_gemma":0.0007271518,"threshold_uncertainty_score":0.009684026},"labels":[],"label_agreement":null},{"id":"W2023735007","doi":"10.1016/j.cmpb.2010.06.011","title":"Wavelets and fuzzy relational classifiers: A novel diffusion-weighted image analysis system for pediatric metabolic brain diseases","year":2010,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University; Hospital for Sick Children","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Categorization; Wavelet; Diffusion MRI; Fuzzy logic; Computer vision; Radiology; Medicine; Magnetic resonance imaging","score_opus":0.07758830664647474,"score_gpt":0.39900391453390194,"score_spread":0.3214156078874272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023735007","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038041595,0.0005830083,0.9596086,0.00018014292,0.00007670624,0.0000629323,0.00020425738,0.00073904457,0.0005035892],"genre_scores_gemma":[0.30462065,0.000842406,0.69196147,0.00012455885,0.000116657,0.00015256178,0.00033368348,0.00008999651,0.001758007],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995548,0.00009914791,0.000050263156,0.000106136,0.0001592169,0.000030370364],"domain_scores_gemma":[0.999361,0.00021527294,0.00006363625,0.00006762542,0.00024636553,0.000046119698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015064125,0.00041833243,0.0007044529,0.0009642986,0.00029070384,0.000982723,0.0007123767,0.0007812447,0.0013592313],"category_scores_gemma":[0.0023961382,0.00021768406,0.0005734502,0.0007983989,0.00021249797,0.0010173324,0.000555287,0.00070622895,0.0007335246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006169304,0.00015882829,0.0033441747,0.00013945215,0.00016605234,0.00012306268,0.00012754084,0.022478325,0.046280436,0.005150313,0.0037146285,0.91770023],"study_design_scores_gemma":[0.000049386977,0.00025961315,0.0037273937,0.00003676494,0.0002141636,0.00032586738,0.00006826846,0.96278477,0.0235466,0.004665064,0.0042748637,0.00004728218],"about_ca_topic_score_codex":0.0020246347,"about_ca_topic_score_gemma":0.0020421797,"teacher_disagreement_score":0.0020246347,"about_ca_system_score_codex":0.00036853095,"about_ca_system_score_gemma":0.0005813296,"threshold_uncertainty_score":0.007966816},"labels":[],"label_agreement":null},{"id":"W2023855780","doi":"10.1002/hbm.20248","title":"Inference for magnitudes and delays of responses in the FIAC data using BRAINSTAT/FMRISTAT","year":2006,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Smoothing; Inference; Novelty; Magnitude (astronomy); Computer science; Voxel; Mathematics; Psychology; Artificial intelligence; Statistics; Physics","score_opus":0.32076986253226,"score_gpt":0.4558225273935523,"score_spread":0.1350526648612923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023855780","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02475664,0.00007017351,0.94550633,0.00017557346,0.000081899656,0.0003208483,0.005915427,0.022586728,0.0005863499],"genre_scores_gemma":[0.12974934,0.000092003706,0.85290533,0.00020944372,0.000050344013,0.0019481828,0.0056209858,0.0076433187,0.0017810771],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978054,0.00078021066,0.00018494233,0.0007244426,0.00037182192,0.00013309266],"domain_scores_gemma":[0.9892791,0.008185069,0.00057269103,0.0011569809,0.00065184524,0.00015435976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009656928,0.0017879019,0.001802885,0.0021631184,0.00070885057,0.0016905691,0.0026578282,0.0011263082,0.01882],"category_scores_gemma":[0.035245363,0.0015835968,0.0028542369,0.0015642317,0.00086682016,0.0013541057,0.0011671054,0.0025140727,0.0036796676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055300635,0.00077850407,0.039679445,0.0026547974,0.005899108,0.0014420449,0.0013943701,0.20819853,0.14699924,0.031161927,0.06817617,0.4880858],"study_design_scores_gemma":[0.00051384437,0.00044727567,0.024749437,0.000058136273,0.0007786393,0.0005232003,0.00009546245,0.8667091,0.055648834,0.036649086,0.013563054,0.00026394048],"about_ca_topic_score_codex":0.010678393,"about_ca_topic_score_gemma":0.012195396,"teacher_disagreement_score":0.01882,"about_ca_system_score_codex":0.0007311089,"about_ca_system_score_gemma":0.002680784,"threshold_uncertainty_score":0.062959135},"labels":[],"label_agreement":null},{"id":"W2024559117","doi":"10.1117/12.2043493","title":"A dual spherical model for multi-shell diffusion imaging","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spherical harmonics; Diffusion; Spherical mean; Kurtosis; Parametric statistics; Metric (unit); Algorithm; Spherical shell; Physics; Computer science; Mathematical analysis; Mathematics; Shell (structure)","score_opus":0.03398852031043575,"score_gpt":0.29615372903892545,"score_spread":0.2621652087284897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024559117","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003624742,0.0001536922,0.9938346,0.00021568092,0.000030789786,0.000019753403,0.00006456688,0.00016617536,0.0018899788],"genre_scores_gemma":[0.35260558,0.0014109892,0.6212035,0.0006008081,0.00016840723,0.0002770313,0.0006499445,0.0005584739,0.022525338],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99966216,0.00010055547,0.000017020326,0.000077062614,0.00011468528,0.000028594397],"domain_scores_gemma":[0.9994295,0.00017796681,0.000086127926,0.00009682238,0.00015520824,0.000054337146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072651764,0.00093391875,0.00058281916,0.00055324147,0.00033968,0.0011501188,0.0016965872,0.0016690737,0.0022903222],"category_scores_gemma":[0.0016681063,0.000440706,0.0010215178,0.0005094801,0.00079186534,0.0014864412,0.0011892471,0.0012937197,0.0016499638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013307815,0.00007198141,0.0011548272,0.00016471006,0.00006807008,0.00036661592,0.00018784827,0.7509938,0.03576092,0.13473637,0.0055513913,0.07081034],"study_design_scores_gemma":[0.0000040531445,0.000016815477,0.00008354944,0.0000045419565,0.000005766193,0.00011098173,0.000008220187,0.99067396,0.0012949911,0.0051323725,0.00265277,0.000011984186],"about_ca_topic_score_codex":0.003547373,"about_ca_topic_score_gemma":0.0034318473,"teacher_disagreement_score":0.003547373,"about_ca_system_score_codex":0.0006974057,"about_ca_system_score_gemma":0.0008036393,"threshold_uncertainty_score":0.0076618195},"labels":[],"label_agreement":null},{"id":"W2024966367","doi":"10.1016/j.neuroimage.2014.07.030","title":"Structural network analysis of brain development in young preterm neonates","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; BC Children's Hospital; University of Toronto; Simon Fraser University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Michael Smith Health Research BC; Government of Alberta","keywords":"Connectome; Diffusion MRI; Brain development; Connectomics; White matter; Tractography; Neuroscience; Fractional anisotropy; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity","score_opus":0.03382792514136341,"score_gpt":0.32506724283525584,"score_spread":0.29123931769389244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024966367","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99199873,0.00031672494,0.00648056,0.00010765178,0.0000048087236,0.000008624343,0.0003665017,0.00002783125,0.0006884482],"genre_scores_gemma":[0.9948159,0.0003852694,0.0040001976,0.000008484358,0.0000073650913,0.000018208151,0.0002918911,0.000012989829,0.00045977003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999032,0.000034615918,0.000006214791,0.00002274599,0.000018221415,0.000015032318],"domain_scores_gemma":[0.99958104,0.00018136806,0.00009107417,0.000029941846,0.00007179771,0.000044820088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037833283,0.00020124271,0.00012905104,0.0012164013,0.00016229911,0.00031600217,0.0002448292,0.00018105847,0.00092402106],"category_scores_gemma":[0.0022068615,0.000116964395,0.0001972198,0.00059333706,0.00013760081,0.00027252437,0.00025599787,0.00017935448,0.00012418319],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006189041,0.00010032941,0.72991145,0.00015530996,0.0003632698,0.0019876526,0.0009440675,0.02051226,0.07603367,0.004219718,0.0014688285,0.16368455],"study_design_scores_gemma":[0.000006369884,0.000103767656,0.92228305,0.00003761457,0.00009745764,0.0018552295,0.00053871755,0.056960262,0.012825602,0.004108067,0.0011646635,0.000019257022],"about_ca_topic_score_codex":0.008163287,"about_ca_topic_score_gemma":0.011614449,"teacher_disagreement_score":0.008163287,"about_ca_system_score_codex":0.0004075426,"about_ca_system_score_gemma":0.0004225794,"threshold_uncertainty_score":0.016231537},"labels":[],"label_agreement":null},{"id":"W2025558610","doi":"10.1016/j.neuroimage.2014.05.017","title":"Pathways linking regional hyperintensities in the brain and slower gait","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Nursing Research; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"Hyperintensity; Gait; Digit symbol substitution test; Psychology; Physical medicine and rehabilitation; Cognition; Executive dysfunction; Neuroscience; Medicine; Magnetic resonance imaging; Pathology; Neuropsychology; Radiology","score_opus":0.08320849423806391,"score_gpt":0.31674733620989903,"score_spread":0.2335388419718351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025558610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97857624,0.0054292283,0.0070990347,0.0016999614,0.00009153242,0.00008481171,0.001016384,0.00012768919,0.00587515],"genre_scores_gemma":[0.9908029,0.002779113,0.0035577358,0.00019328487,0.00010439862,0.000051462055,0.0004149727,0.000029859033,0.00206627],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999908,0.0000200392,0.000006979159,0.000029213423,0.000015018289,0.000020758214],"domain_scores_gemma":[0.99935323,0.00015433326,0.0003184256,0.000039882558,0.00007522104,0.000058901413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033225343,0.0007264768,0.00031751816,0.0012926396,0.00031384407,0.0009949465,0.00034706626,0.0006430424,0.00403737],"category_scores_gemma":[0.0016660953,0.00035157116,0.00028961527,0.00087143335,0.0007074697,0.00074913865,0.00046957502,0.00088723283,0.00029480754],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009028128,0.0017281203,0.5010474,0.0013595318,0.0023335489,0.012197136,0.0017644931,0.011225406,0.23468268,0.018770425,0.005864759,0.19999851],"study_design_scores_gemma":[0.00017195258,0.00060820556,0.9552331,0.00017327214,0.00033153643,0.0029437602,0.00044977546,0.0041281804,0.0072225034,0.027263902,0.0014102175,0.00006354121],"about_ca_topic_score_codex":0.004627398,"about_ca_topic_score_gemma":0.0048793913,"teacher_disagreement_score":0.004627398,"about_ca_system_score_codex":0.00034519873,"about_ca_system_score_gemma":0.0006951569,"threshold_uncertainty_score":0.013506353},"labels":[],"label_agreement":null},{"id":"W2025904718","doi":"10.1089/neu.2012.2818","title":"Combining Whole-Brain Voxel-Wise Analysis with <i>In Vivo</i> Tractography of Diffusion Behavior after Sports-Related Concussion in Adolescents: A Preliminary Report","year":2013,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; University of British Columbia","funders":"Centers for Disease Control and Prevention","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Concussion; Tractography; Voxel; Traumatic brain injury; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Poison control; Radiology; Psychiatry; Injury prevention","score_opus":0.028456270786747027,"score_gpt":0.32057474693283416,"score_spread":0.29211847614608716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025904718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895873,0.00015557422,0.0099308705,0.000012911985,0.0000025498418,0.00002020328,0.00012573434,0.000049104303,0.00011564547],"genre_scores_gemma":[0.9854197,0.00015788611,0.013938579,0.0000062402482,0.0000048791176,0.000024281946,0.0002785337,0.000028375911,0.00014160165],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998672,0.00004493137,0.000013043801,0.000037260605,0.000021503318,0.000016111018],"domain_scores_gemma":[0.99962616,0.0000815734,0.000111812806,0.000047334994,0.00009787062,0.000035301833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005581718,0.00025083593,0.0002587188,0.000623876,0.00014352075,0.00035208667,0.00016412113,0.00019833032,0.00047378748],"category_scores_gemma":[0.0010816302,0.00016295706,0.0002955136,0.00032352345,0.00021422106,0.0002970423,0.00022876261,0.00014670508,0.00011602595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010277688,0.0001684713,0.56952775,0.0003188848,0.00058719295,0.00074887596,0.0008258331,0.0027661878,0.3519235,0.00022992515,0.0003217101,0.07155392],"study_design_scores_gemma":[0.000029703238,0.00069678854,0.94761485,0.000027685699,0.00024366565,0.0018779992,0.0004056072,0.013418486,0.034498557,0.000211925,0.0009449462,0.000029687895],"about_ca_topic_score_codex":0.0038752914,"about_ca_topic_score_gemma":0.006418641,"teacher_disagreement_score":0.0038752914,"about_ca_system_score_codex":0.00015018127,"about_ca_system_score_gemma":0.0002849808,"threshold_uncertainty_score":0.00770545},"labels":[],"label_agreement":null},{"id":"W2026088781","doi":"10.1016/j.neuropsychologia.2008.02.017","title":"Ipsilateral cortical representation of tactile and painful information in acallosal and callosotomized subjects","year":2008,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Corpus callosum; Insula; Neuroscience; Functional magnetic resonance imaging; Neuroplasticity; Magnetic resonance imaging; Stimulation; Agenesis; Agenesis of the corpus callosum; Sensory stimulation therapy; Cingulate cortex; Audiology; Anatomy; Medicine; Central nervous system; Radiology","score_opus":0.06905991710939997,"score_gpt":0.3613725698606633,"score_spread":0.29231265275126334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026088781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996314,0.00012258258,0.0005259724,0.00004642237,0.000017324472,0.000030859006,0.0001954151,0.00002424469,0.0027231406],"genre_scores_gemma":[0.99885964,0.00004430992,0.00017099385,0.000028650215,0.000012600669,0.000017742374,0.00006371033,0.0000056673002,0.0007966872],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998429,0.000016678576,0.000012449291,0.000046663674,0.000024890995,0.00005649343],"domain_scores_gemma":[0.999574,0.00025562572,0.00003499217,0.000056361478,0.00003272325,0.000046165704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027992632,0.00046066032,0.00045117084,0.0008294042,0.00051255437,0.0006318953,0.0002764026,0.0004985321,0.007182596],"category_scores_gemma":[0.0014967844,0.0001841094,0.00022043585,0.00027038864,0.0013403337,0.0005266186,0.00050976546,0.0005517995,0.00039551975],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013220621,0.0010867899,0.04348933,0.0004963767,0.00019017587,0.025752619,0.0068299244,0.00143934,0.84547615,0.005643504,0.00081123516,0.055563893],"study_design_scores_gemma":[0.0006429767,0.0034804002,0.8321032,0.00005520554,0.00037210455,0.034336623,0.004093347,0.006090557,0.1092314,0.0068128733,0.0026730606,0.000108212706],"about_ca_topic_score_codex":0.0046601105,"about_ca_topic_score_gemma":0.0043377234,"teacher_disagreement_score":0.007182596,"about_ca_system_score_codex":0.00039044657,"about_ca_system_score_gemma":0.0006496809,"threshold_uncertainty_score":0.024028182},"labels":[],"label_agreement":null},{"id":"W2026527527","doi":"10.1016/j.jpsychires.2010.07.007","title":"Fronto-temporal disconnectivity and clinical short-term outcome in first episode psychosis: A DTI-tractography study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Uncinate fasciculus; Fractional anisotropy; Psychosis; Cingulum (brain); White matter; Inferior longitudinal fasciculus; Psychology; Superior longitudinal fasciculus; Diffusion MRI; Fasciculus; Tractography; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.22425807753606666,"score_gpt":0.5432082754350517,"score_spread":0.31895019789898504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026527527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997193,0.00006722328,0.000028337909,0.0000112885655,0.0000013272789,0.0000051011816,0.00004171028,9.666397e-7,0.0001246949],"genre_scores_gemma":[0.9996468,0.000058551486,0.000041464264,0.000007323471,0.000004900871,0.000007089485,0.00009367625,0.0000013391312,0.00013882278],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998623,0.000036408048,0.0000098470755,0.000030020674,0.000019306906,0.000042057905],"domain_scores_gemma":[0.9992415,0.00021446121,0.00021055495,0.000069592694,0.000055636152,0.00020820575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041603556,0.0003801104,0.0004281054,0.00071835524,0.0007752739,0.000658383,0.00032010715,0.0005939,0.0015860731],"category_scores_gemma":[0.0014497587,0.00028635212,0.0002942454,0.0006857099,0.00070984184,0.00069668697,0.00042180906,0.0005195559,0.00029762855],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005893009,0.0008171772,0.9681588,0.000049556907,0.00025834556,0.0039431225,0.0011742084,0.00026375623,0.010840386,0.00012869232,0.00014228634,0.008330574],"study_design_scores_gemma":[0.00005861515,0.0006355098,0.9964026,0.0000055657442,0.00006620806,0.0018327406,0.00030242483,0.00028678786,0.00020425771,0.00011728135,0.00007571061,0.000012406739],"about_ca_topic_score_codex":0.009636383,"about_ca_topic_score_gemma":0.013300946,"teacher_disagreement_score":0.009636383,"about_ca_system_score_codex":0.0007786312,"about_ca_system_score_gemma":0.000525962,"threshold_uncertainty_score":0.019160569},"labels":[],"label_agreement":null},{"id":"W2027359048","doi":"10.1016/j.schres.2014.09.037","title":"A diffusion tensor imaging family study of the fornix in schizophrenia","year":2014,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"KU Leuven; Canadian Institutes of Health Research; European Commission; University of Calgary","keywords":"Fornix; Fractional anisotropy; Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Psychology; Neuroimaging; Abnormality; Neuroscience; Psychosis; Psychiatry; Magnetic resonance imaging; Medicine; Radiology; Hippocampus","score_opus":0.10979172091697886,"score_gpt":0.4104373090531239,"score_spread":0.30064558813614506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027359048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99868995,0.000084375504,0.00022069698,0.000185305,0.0000105266645,0.0000138161395,0.00018808854,0.000003559897,0.00060371344],"genre_scores_gemma":[0.9986601,0.00011042409,0.0003370011,0.000052549596,0.000012393648,0.000009563998,0.0001759502,0.0000120775585,0.0006299298],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942845,0.00018268476,0.000058146885,0.00014952416,0.000086619686,0.0000945637],"domain_scores_gemma":[0.997059,0.00048313505,0.00073637266,0.00039635587,0.0006983205,0.0006269524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014759275,0.0014993894,0.0007449697,0.0021649841,0.0050636893,0.0008436397,0.0009783533,0.0009975063,0.0043214574],"category_scores_gemma":[0.0056574615,0.0005822195,0.0007314002,0.0014046751,0.0016321074,0.0016292963,0.0014389841,0.0011558523,0.0005264821],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002418938,0.0009507374,0.8913786,0.00007296495,0.00044148217,0.049253996,0.016418984,0.0005293061,0.02463335,0.003375775,0.0019306839,0.008595245],"study_design_scores_gemma":[0.00007819423,0.0007411366,0.9333856,0.000075849115,0.0002303883,0.046599496,0.011663664,0.0010876562,0.0020609316,0.002634048,0.001331613,0.00011128309],"about_ca_topic_score_codex":0.055583797,"about_ca_topic_score_gemma":0.044343498,"teacher_disagreement_score":0.055583797,"about_ca_system_score_codex":0.0014276427,"about_ca_system_score_gemma":0.0021305631,"threshold_uncertainty_score":0.11052054},"labels":[],"label_agreement":null},{"id":"W2027591786","doi":"10.1186/1471-2202-9-84","title":"Detecting functional magnetic resonance imaging activation in white matter: Interhemispheric transfer across the corpus callosum","year":2008,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; Dalhousie University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Functional magnetic resonance imaging; Neuroscience; Magnetic resonance imaging; Psychology; Brain mapping; Medicine; Radiology","score_opus":0.06101308915189367,"score_gpt":0.3137955577162156,"score_spread":0.2527824685643219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027591786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868868,0.00016248261,0.011914086,0.00006139546,0.000006918414,0.000054607866,0.000036245747,0.00005472856,0.00082268124],"genre_scores_gemma":[0.9913599,0.00006156115,0.008283295,0.000024087582,0.000008946008,0.000036901074,0.000047537527,0.000013124035,0.00016461394],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972576,0.000086422464,0.000019475092,0.000076883254,0.00006331051,0.00002819979],"domain_scores_gemma":[0.9985726,0.0008442893,0.000268376,0.00013408215,0.00011979566,0.000060855273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013278972,0.00029257147,0.00030374908,0.00064607826,0.00029046807,0.00035298688,0.0003638796,0.0005043756,0.0024345093],"category_scores_gemma":[0.0034911626,0.00012601772,0.00015961472,0.00030814882,0.00076838594,0.00052745227,0.00030619872,0.00034117547,0.0002200035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012109705,0.0002554949,0.058115575,0.00033716517,0.0002282366,0.00058935373,0.0006401499,0.001673471,0.878936,0.00037738265,0.0002264557,0.05740974],"study_design_scores_gemma":[0.000065592,0.001421361,0.78733546,0.00003674118,0.00016641777,0.0024702966,0.00048816108,0.010803584,0.19413866,0.0023134241,0.0007245823,0.000035790203],"about_ca_topic_score_codex":0.0007296264,"about_ca_topic_score_gemma":0.0015446123,"teacher_disagreement_score":0.0024345093,"about_ca_system_score_codex":0.0002106847,"about_ca_system_score_gemma":0.00028354066,"threshold_uncertainty_score":0.008144259},"labels":[],"label_agreement":null},{"id":"W2028110903","doi":"10.1002/mrm.21640","title":"DWI of the spinal cord with reduced FOV single‐shot EPI","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":267,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Echo-planar imaging; Sagittal plane; Spinal cord; Physics; Field of view; Nuclear magnetic resonance; Single shot; Magnetic resonance imaging; Pulse (music); Diffusion MRI; SIGNAL (programming language); Nuclear medicine; Biomedical engineering; Optics; Medicine; Computer science; Anatomy; Radiology; Detector","score_opus":0.12057208484698714,"score_gpt":0.3621718104925367,"score_spread":0.24159972564554957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028110903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1299704,0.004758905,0.85867685,0.00042094628,0.00009342829,0.00023061661,0.0005705367,0.0013358355,0.003942454],"genre_scores_gemma":[0.15868749,0.003615681,0.8342499,0.00013475868,0.00008299772,0.00019425692,0.0005646445,0.00012024498,0.0023499914],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984026,0.000034274057,0.000016849306,0.000039799954,0.000056247067,0.000012597026],"domain_scores_gemma":[0.9997222,0.000067113935,0.000039819013,0.00005566164,0.00009323082,0.000022016378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000501515,0.00060419523,0.0005096821,0.0007553098,0.00017249506,0.0005574575,0.0006370061,0.0004939973,0.0014308023],"category_scores_gemma":[0.0010081106,0.0003969727,0.00027281084,0.00065262057,0.00025913477,0.0007734258,0.00049370923,0.0005865037,0.0005378267],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002033959,0.00004591807,0.0007415821,0.00072077586,0.00009521971,0.00037201834,0.000047810212,0.0021878008,0.875148,0.0013584371,0.0012830766,0.11779594],"study_design_scores_gemma":[0.00018140019,0.0016580883,0.018928789,0.00012078304,0.00039302104,0.013231228,0.00008631374,0.0980755,0.82786006,0.0044489997,0.034878388,0.00013752205],"about_ca_topic_score_codex":0.0005220805,"about_ca_topic_score_gemma":0.0013175281,"teacher_disagreement_score":0.0014308023,"about_ca_system_score_codex":0.00016113381,"about_ca_system_score_gemma":0.00049013126,"threshold_uncertainty_score":0.004786551},"labels":[],"label_agreement":null},{"id":"W2028382446","doi":"10.1002/mrm.22873","title":"Insight into in vivo magnetization exchange in human white matter regions","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Magnetization transfer; Relaxation (psychology); Chemistry; Magnetization; Nuclear magnetic resonance; Relaxometry; Magnetic resonance imaging; Biophysics; Chemical physics; Physics; Central nervous system; Magnetic field; Neuroscience; Biology; Spin echo","score_opus":0.06512422960414306,"score_gpt":0.3303473079514085,"score_spread":0.26522307834726544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028382446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.830163,0.0020512554,0.16218904,0.00048670778,0.00001860092,0.000044088018,0.00044787987,0.00027202268,0.004327389],"genre_scores_gemma":[0.97762644,0.0010443154,0.019736484,0.000076458855,0.00001360086,0.000020687892,0.00023940988,0.000049832837,0.0011927504],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999291,0.0000268794,0.0000040738755,0.000019764982,0.000010611525,0.000009671916],"domain_scores_gemma":[0.99983907,0.00010208276,0.000020579977,0.000014057231,0.00001525735,0.000008854074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000503914,0.00025900954,0.00020670157,0.00061884196,0.00014251418,0.00046225818,0.00024631197,0.0006979532,0.0021990696],"category_scores_gemma":[0.0018662269,0.00026282805,0.00017534035,0.00034585412,0.00019289895,0.0008048609,0.00015961335,0.00023256506,0.0003329158],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011014016,0.00021782894,0.04890872,0.0005059687,0.00024753073,0.0022579907,0.001535892,0.09724287,0.7013727,0.01811014,0.0018502361,0.12664872],"study_design_scores_gemma":[0.000102251906,0.0008948197,0.21650206,0.00008719992,0.0003710083,0.010343093,0.0010026931,0.55247015,0.15039922,0.0543453,0.013370446,0.00011185818],"about_ca_topic_score_codex":0.001618972,"about_ca_topic_score_gemma":0.00197568,"teacher_disagreement_score":0.0021990696,"about_ca_system_score_codex":0.00016551951,"about_ca_system_score_gemma":0.00028086948,"threshold_uncertainty_score":0.0073566437},"labels":[],"label_agreement":null},{"id":"W2028655791","doi":"10.1016/j.neuroimage.2014.03.029","title":"Fast and accurate modelling of longitudinal and repeated measures neuroimaging data","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":214,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Wellcome Trust; Synarc; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Longitudinal data; Psychology; Cognitive psychology; Computer science; Econometrics; Neuroscience; Data mining; Mathematics","score_opus":0.22642524957313795,"score_gpt":0.36751344285178345,"score_spread":0.1410881932786455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028655791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050769076,0.00025573323,0.9936725,0.00015587284,0.000030089363,0.00003873349,0.00024255947,0.000347125,0.00018042102],"genre_scores_gemma":[0.12808377,0.00097478373,0.86671466,0.00013960336,0.000115925024,0.0007953969,0.0010542806,0.00027349358,0.0018481207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9956857,0.0024298208,0.00025385572,0.000630191,0.0008214833,0.00017889195],"domain_scores_gemma":[0.984993,0.010633861,0.0011455559,0.001661619,0.0013280725,0.00023798224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012546344,0.00092233525,0.0019642669,0.0015121627,0.00057502155,0.0015562782,0.0026855106,0.001873216,0.0018066011],"category_scores_gemma":[0.04256132,0.0015087625,0.0021103765,0.0018068615,0.0010331612,0.0025485477,0.0020596676,0.0029900456,0.0011100624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019361977,0.00008241264,0.008802994,0.00039839037,0.00043568292,0.00047937987,0.0005085177,0.79671067,0.0060335593,0.063861445,0.003435608,0.119057655],"study_design_scores_gemma":[0.000024524845,0.000050798633,0.0021077597,0.000040341652,0.000036279125,0.00017732733,0.000032292348,0.9409884,0.001197064,0.052947596,0.002349426,0.00004821725],"about_ca_topic_score_codex":0.00799027,"about_ca_topic_score_gemma":0.011359293,"teacher_disagreement_score":0.012546344,"about_ca_system_score_codex":0.0009210631,"about_ca_system_score_gemma":0.0022554928,"threshold_uncertainty_score":0.06635219},"labels":[],"label_agreement":null},{"id":"W2028729341","doi":"10.1109/bmei.2011.6098482","title":"Model-free marginal orientation distribution function reconstruction in single-shell Q-Ball imaging","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Orientation (vector space); Computer science; Angular resolution (graph drawing); Artificial intelligence; Iterative reconstruction; Imaging phantom; Tomographic reconstruction; Diffusion MRI; Marginal distribution; Computer vision; Algorithm; Mathematics; Physics; Optics; Geometry","score_opus":0.11157469956844793,"score_gpt":0.30634302494673565,"score_spread":0.19476832537828773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028729341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004510008,0.000036911257,0.99504566,0.00003924168,0.0000044212156,0.000008672466,0.000012676669,0.00015428697,0.00018803772],"genre_scores_gemma":[0.19095612,0.00022573025,0.807086,0.000059380494,0.000015344094,0.00006275684,0.00014361115,0.00018488303,0.0012661498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974376,0.000093695344,0.000012739219,0.000039865623,0.00008882139,0.000021079253],"domain_scores_gemma":[0.9994673,0.00025681377,0.000074395735,0.00009417139,0.00007574313,0.000031597447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011908007,0.00045259358,0.00067738944,0.00045938868,0.00022226838,0.00069772755,0.0008557123,0.0007240653,0.0011721172],"category_scores_gemma":[0.0032857177,0.000502291,0.000657821,0.000377021,0.0007110118,0.0011432365,0.0009466034,0.0007593695,0.00044951402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041934216,0.00009987738,0.002126766,0.00033547994,0.00007052199,0.000431778,0.0003241788,0.4873907,0.06860701,0.08222656,0.0027440048,0.35522377],"study_design_scores_gemma":[0.000009023033,0.000020669379,0.00020968972,0.000004294666,0.000005393853,0.00017584342,0.000010171762,0.9846001,0.0066039558,0.007651983,0.0006951298,0.000013674543],"about_ca_topic_score_codex":0.0021052845,"about_ca_topic_score_gemma":0.0015002384,"teacher_disagreement_score":0.0021052845,"about_ca_system_score_codex":0.0003773547,"about_ca_system_score_gemma":0.00079021155,"threshold_uncertainty_score":0.0062975883},"labels":[],"label_agreement":null},{"id":"W2028748733","doi":"10.1016/j.nicl.2013.07.006","title":"Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":364,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; GE Healthcare; Genentech; National Institutes of Health; U.S. National Library of Medicine; Takeda Pharmaceutical Company; IXICO; Servier; Eisai; Northern California Institute for Research and Education; Synarc; Bayer HealthCare; Meso Scale Diagnostics; Medpace; DoD Alzheimer's Disease Neuroimaging Initiative; BioClinica; Pfizer; Biogen; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; National Institute on Aging; Abbott Laboratories; National Center for Research Resources; F. Hoffmann-La Roche","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Psychology; Neuroimaging; Cingulum (brain); Alzheimer's Disease Neuroimaging Initiative; Dementia; Alzheimer's disease; Neuroscience; Medicine; Nuclear medicine; Cognitive impairment; Magnetic resonance imaging; Cognition; Disease; Internal medicine; Radiology","score_opus":0.17854415510055016,"score_gpt":0.4330612784330466,"score_spread":0.25451712333249643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028748733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9029812,0.0464355,0.03749226,0.00045269253,0.0001995453,0.00041890622,0.0016033587,0.0003804543,0.010035932],"genre_scores_gemma":[0.9635444,0.004056433,0.030138463,0.00013403907,0.000120215926,0.00014264781,0.0009244421,0.00008084497,0.0008585409],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9953643,0.0020938646,0.0005013372,0.001344535,0.0005596748,0.00013629091],"domain_scores_gemma":[0.9933115,0.0039039892,0.0011032235,0.0007533088,0.00071701576,0.00021102853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012901792,0.0012565097,0.0012311595,0.004253092,0.00056528405,0.0014948879,0.00068351085,0.000632077,0.000759185],"category_scores_gemma":[0.014712029,0.00034693343,0.00087013067,0.00157373,0.0009340785,0.0014106205,0.00077912357,0.0005147262,0.00039935412],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003341708,0.00016015419,0.6355483,0.0011888095,0.0040554507,0.00038115875,0.0010049122,0.0035281826,0.029150723,0.0015069242,0.0019533974,0.31818023],"study_design_scores_gemma":[0.000076258264,0.001180668,0.9733419,0.00019779851,0.0012015131,0.0014047634,0.00035926548,0.009084668,0.005791153,0.0025084112,0.004753715,0.00009985565],"about_ca_topic_score_codex":0.0035230753,"about_ca_topic_score_gemma":0.008176092,"teacher_disagreement_score":0.012901792,"about_ca_system_score_codex":0.00042331053,"about_ca_system_score_gemma":0.00043108276,"threshold_uncertainty_score":0.06823206},"labels":[],"label_agreement":null},{"id":"W2029334347","doi":"10.1016/j.neuroimage.2007.03.041","title":"Integrity of white matter in the corpus callosum correlates with bimanual co-ordination skills","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":273,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Wellcome Trust","keywords":"Corpus callosum; White matter; Variation (astronomy); Tractography; Ordination; Psychology; Diffusion MRI; Neuroscience; Magnetic resonance imaging; Biology; Medicine","score_opus":0.03087854053533767,"score_gpt":0.34634432292921036,"score_spread":0.3154657823938727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029334347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984503,0.00008863383,0.00030629092,0.000044307264,0.0000027901858,0.0000047269323,0.00006969361,0.000015805881,0.0010175462],"genre_scores_gemma":[0.99912065,0.00004476319,0.00018336934,0.000013574171,0.0000066434486,0.0000069298685,0.00009525613,0.0000075530106,0.0005213232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997341,0.00003689922,0.000026213469,0.00008002456,0.000060737282,0.00006193421],"domain_scores_gemma":[0.9958544,0.0010077569,0.0021371497,0.00035925035,0.00033561492,0.00030592404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045522174,0.0003812961,0.0003071756,0.0012050495,0.00033939886,0.00067200913,0.0004635765,0.00051965617,0.0033935613],"category_scores_gemma":[0.00429781,0.00030585355,0.00014132926,0.0007095605,0.0007611568,0.0005568558,0.0005735114,0.0006874783,0.00038549557],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015323956,0.0006052483,0.86159676,0.000090872476,0.00033100866,0.001252465,0.0008561509,0.0010119838,0.09715037,0.00050472026,0.0006899619,0.034377906],"study_design_scores_gemma":[0.0000032936255,0.00004698631,0.99623364,0.0000034876243,0.000020249403,0.00077242445,0.000067800655,0.0003046088,0.0022590712,0.00021063288,0.00007366607,0.0000042483525],"about_ca_topic_score_codex":0.003614074,"about_ca_topic_score_gemma":0.005122346,"teacher_disagreement_score":0.003614074,"about_ca_system_score_codex":0.00024979157,"about_ca_system_score_gemma":0.00040346733,"threshold_uncertainty_score":0.011352599},"labels":[],"label_agreement":null},{"id":"W2029665903","doi":"10.1016/j.media.2011.01.005","title":"Extracting skeletal muscle fiber fields from noisy diffusion tensor data","year":2011,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Canada Research Chairs","keywords":"Smoothing; Diffusion MRI; Noise (video); Tensor (intrinsic definition); Noise reduction; Artificial intelligence; Pattern recognition (psychology); Mathematics; Fiber; Synthetic data; SIGNAL (programming language); Computer science; Algorithm; Computer vision; Geometry","score_opus":0.1199979832209549,"score_gpt":0.37935965336528793,"score_spread":0.25936167014433303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029665903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.068250395,0.0013046041,0.9275492,0.0003792661,0.000088806475,0.000062995925,0.0006114609,0.0011882521,0.000565011],"genre_scores_gemma":[0.3293868,0.002704155,0.6605772,0.00014201537,0.00027743544,0.00009985903,0.0020501208,0.0003852537,0.0043771793],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981064,0.000028464663,0.000020337637,0.00005283242,0.00006556954,0.00002212817],"domain_scores_gemma":[0.99929273,0.0002589272,0.00013294903,0.000104427956,0.00016401616,0.00004696283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008709697,0.001084978,0.0010800873,0.002052786,0.00035876207,0.00094879075,0.00066611735,0.001589278,0.0010027359],"category_scores_gemma":[0.0028425502,0.0009372499,0.0010799705,0.001491699,0.00046358956,0.0009816558,0.0007303788,0.0010112104,0.0011807503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000524417,0.00011859077,0.0062957862,0.0006413182,0.00023867673,0.0014206289,0.0002545368,0.10024789,0.30729213,0.0032659196,0.004602508,0.5750975],"study_design_scores_gemma":[0.0000413672,0.00015387437,0.010934958,0.00009522747,0.00020460533,0.001881486,0.00013941326,0.9157869,0.051014993,0.014063325,0.005621533,0.000062309045],"about_ca_topic_score_codex":0.0029847084,"about_ca_topic_score_gemma":0.0050619934,"teacher_disagreement_score":0.0029847084,"about_ca_system_score_codex":0.00025756744,"about_ca_system_score_gemma":0.00093089376,"threshold_uncertainty_score":0.0059346557},"labels":[],"label_agreement":null},{"id":"W2029713109","doi":"10.1038/sj.mp.4001337","title":"Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins","year":2003,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":436,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; U.S. Public Health Service","keywords":"White matter; Corpus callosum; Oligodendrocyte; Myelin; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Neuroscience; Myelin oligodendrocyte glycoprotein; Internal medicine; Endocrinology; Medicine; Magnetic resonance imaging; Central nervous system; Psychiatry","score_opus":0.008951304575866462,"score_gpt":0.2668794506618652,"score_spread":0.25792814608599873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029713109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99694663,0.0009697896,0.0008027285,0.00008549165,0.0000099001245,0.000009392174,0.00016774489,0.000013757262,0.0009945786],"genre_scores_gemma":[0.9967192,0.0008540025,0.001086498,0.00003587918,0.000012570357,0.000013596684,0.00019585845,0.000012050407,0.0010703416],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999049,0.000018041788,0.0000144781525,0.00001784672,0.000019946418,0.000024882926],"domain_scores_gemma":[0.9997377,0.00003626539,0.00009863964,0.000023422286,0.000051074745,0.00005278828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039295998,0.0006088217,0.00022352867,0.0010531613,0.00053893693,0.00026715812,0.0002738436,0.00046707728,0.00093016453],"category_scores_gemma":[0.0006522695,0.00037032852,0.00019964858,0.00035105436,0.0006715581,0.0003884753,0.0004430643,0.00063598936,0.00019527342],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0046530236,0.00015530044,0.049829558,0.0001314622,0.00010425852,0.0054065967,0.0004977953,0.00023352054,0.93080765,0.00037365084,0.0001948688,0.0076122493],"study_design_scores_gemma":[0.00017155685,0.0016770178,0.6720533,0.000053321237,0.0003076562,0.04000965,0.00129359,0.0014935012,0.27953935,0.0018227847,0.001528813,0.000049463768],"about_ca_topic_score_codex":0.004330223,"about_ca_topic_score_gemma":0.0042992714,"teacher_disagreement_score":0.004330223,"about_ca_system_score_codex":0.0003142875,"about_ca_system_score_gemma":0.00030162977,"threshold_uncertainty_score":0.00861001},"labels":[],"label_agreement":null},{"id":"W2029753145","doi":"10.1016/j.jsb.2014.09.009","title":"Changes in tissue directionality reflect differences in myelin content after demyelination in mice spinal cords","year":2014,"lang":"en","type":"article","venue":"Journal of Structural Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Luxol fast blue stain; Myelin; Multiple sclerosis; White matter; Pathology; Spinal cord; Demyelinating Disorder; Anatomy; Biology; Neuroscience; Medicine; Magnetic resonance imaging; Central nervous system; Immunology","score_opus":0.10685348356387424,"score_gpt":0.4028782614716706,"score_spread":0.29602477790779635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029753145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99488175,0.00045238063,0.0032395062,0.00006623044,0.000020725018,0.0000135881955,0.0006148698,0.00010530082,0.00060569204],"genre_scores_gemma":[0.9911015,0.00055483956,0.0033597792,0.00007414289,0.000010972558,0.000053411575,0.000519852,0.0000909137,0.0042346027],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997421,0.000021063523,0.000022787308,0.00009450303,0.000050055332,0.00006952889],"domain_scores_gemma":[0.9993425,0.000050846393,0.00027989267,0.00003638731,0.000105305146,0.0001851303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027796338,0.00040945836,0.00031731362,0.0009597971,0.00028839987,0.0005637089,0.00026292002,0.0005279208,0.0020981329],"category_scores_gemma":[0.00024253814,0.00048544793,0.00026996955,0.00040780436,0.000584536,0.0005592848,0.00032352007,0.0012441938,0.00037223526],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029414395,0.000020790712,0.00045547713,0.000020486817,0.000007993273,0.000024061592,0.000028990957,0.000049037546,0.998418,0.00006575956,0.00002162921,0.00059370336],"study_design_scores_gemma":[0.000030058705,0.00038568123,0.03649092,0.000013723136,0.00007435792,0.0002913027,0.00021820873,0.0011827264,0.9603993,0.00016655138,0.00072669616,0.000020506584],"about_ca_topic_score_codex":0.0020081114,"about_ca_topic_score_gemma":0.0026458472,"teacher_disagreement_score":0.0020981329,"about_ca_system_score_codex":0.0003765237,"about_ca_system_score_gemma":0.00029991986,"threshold_uncertainty_score":0.0070189834},"labels":[],"label_agreement":null},{"id":"W2029896563","doi":"10.1111/j.1492-7535.2004.01110.x","title":"Reply to letter on diffusion study","year":2004,"lang":"en","type":"article","venue":"Hemodialysis International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Columbia university; Library science; Citation; Health science; Center (category theory); Medicine; Sociology; Media studies; Computer science; Medical education","score_opus":0.04926919476538716,"score_gpt":0.36341337031121623,"score_spread":0.3141441755458291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029896563","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044254618,0.0010792394,0.00006552264,0.960011,0.03770576,0.000006359736,0.000034277018,0.000017418059,0.0006378256],"genre_scores_gemma":[0.0048958217,0.0008758626,0.00014478089,0.92587787,0.06559803,0.000025426476,0.000029694656,0.000024551433,0.0025280255],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997451,0.00075958483,0.0004119247,0.00042640715,0.00050672994,0.0004443756],"domain_scores_gemma":[0.9807623,0.012677143,0.00093559944,0.0008240274,0.0032232115,0.0015777269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003950933,0.0009398378,0.0021481712,0.0013380252,0.003170756,0.0027602187,0.0030763173,0.073881015,0.006800214],"category_scores_gemma":[0.045584563,0.00091102556,0.0016856623,0.0010933132,0.0033240912,0.004361146,0.0019264073,0.040307444,0.0044086836],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095708085,0.000017901413,0.00059464463,0.00007850361,0.000029461211,0.0033969802,0.00011286228,0.000035129044,0.00013038253,0.0014464514,0.99080807,0.003253816],"study_design_scores_gemma":[0.00041405985,0.00012787286,0.00347656,0.0006047249,0.00016635354,0.008839951,0.0008761197,0.0005854913,0.0007093153,0.012931526,0.9710724,0.00019576035],"about_ca_topic_score_codex":0.00413462,"about_ca_topic_score_gemma":0.005317007,"teacher_disagreement_score":0.073881015,"about_ca_system_score_codex":0.0047394857,"about_ca_system_score_gemma":0.0028568276,"threshold_uncertainty_score":0.03438747},"labels":[],"label_agreement":null},{"id":"W2030109209","doi":"10.1039/c4sm00676c","title":"Micro-heterogeneity metrics for diffusion in soft matter","year":2014,"lang":"en","type":"article","venue":"Soft Matter","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; U.S. Public Health Service","keywords":"Microbead (research); Soft matter; Diffusion; Tracking (education); Computer science; Biological system; Physics; Chemistry; Biology","score_opus":0.04407521153950298,"score_gpt":0.3407877974561752,"score_spread":0.2967125859166722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030109209","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13981196,0.0036397781,0.8490932,0.0012394029,0.00009117608,0.00014428774,0.00091918145,0.00057578174,0.004485189],"genre_scores_gemma":[0.88794094,0.001646297,0.10594124,0.00031003146,0.00020431587,0.0003459162,0.0010582053,0.00024213876,0.0023110572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991561,0.00019250199,0.00006881054,0.00021670699,0.0002934191,0.00007244135],"domain_scores_gemma":[0.9939027,0.0033669544,0.0012145729,0.00052810967,0.00063928275,0.0003484133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021531342,0.000754038,0.0006539779,0.0035773031,0.0006621614,0.0015576502,0.00083229324,0.0011982796,0.0011417934],"category_scores_gemma":[0.010832113,0.00024622816,0.0008057983,0.0015498763,0.0016021834,0.0028447474,0.0015780771,0.0013664588,0.00026918796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014746081,0.00009768246,0.016121283,0.0005178793,0.0001673326,0.00038870968,0.00047805242,0.51126665,0.03377634,0.37734658,0.0037958378,0.055896193],"study_design_scores_gemma":[0.000008951906,0.00006667211,0.008047993,0.000041555006,0.000029271245,0.00028216955,0.00011753427,0.82639885,0.0049028597,0.15587169,0.0041752034,0.000057292444],"about_ca_topic_score_codex":0.002672462,"about_ca_topic_score_gemma":0.0013804625,"teacher_disagreement_score":0.0035773031,"about_ca_system_score_codex":0.001632335,"about_ca_system_score_gemma":0.0005972147,"threshold_uncertainty_score":0.011843443},"labels":[],"label_agreement":null},{"id":"W2030134080","doi":"10.1109/prni.2012.11","title":"Connectivity-informed Sparse Classifiers for fMRI Brain Decoding","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Decoding methods; Artificial intelligence; Functional magnetic resonance imaging; Curse of dimensionality; Classifier (UML); Regularization (linguistics); Pattern recognition (psychology); Neural coding; Diffusion MRI; Prior probability; Neuroimaging; Machine learning; Magnetic resonance imaging; Neuroscience; Bayesian probability; Psychology; Algorithm","score_opus":0.2169931629477163,"score_gpt":0.4294514363842008,"score_spread":0.2124582734364845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030134080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069112023,0.00020967156,0.9915451,0.00035679806,0.000019318992,0.00001904616,0.00007607159,0.00025635213,0.0006065162],"genre_scores_gemma":[0.3527483,0.0008766257,0.64237946,0.00026372535,0.0002557733,0.00021606594,0.00068549544,0.00021643058,0.0023581341],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993192,0.00031567152,0.000030625986,0.00010032637,0.0001863553,0.00004794273],"domain_scores_gemma":[0.9971138,0.0019918846,0.00022929884,0.00024813626,0.00035447063,0.00006243356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015007171,0.00078573485,0.00084904785,0.00096822536,0.0004277091,0.00086760067,0.0008048375,0.0014459065,0.0018903788],"category_scores_gemma":[0.01272206,0.00038091137,0.00055572856,0.0012516123,0.0006844309,0.0015371492,0.0009195887,0.0017353888,0.0007628524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016786456,0.00011423179,0.0014479023,0.00016346571,0.00008541707,0.00018922216,0.00018900141,0.50187975,0.020394374,0.0664593,0.00622882,0.4026807],"study_design_scores_gemma":[0.0000062536465,0.000012771242,0.00018835087,0.0000070932065,0.0000053086815,0.00003219591,0.0000056443077,0.96637005,0.0018198369,0.03091687,0.00062871404,0.0000069037615],"about_ca_topic_score_codex":0.002211603,"about_ca_topic_score_gemma":0.0033570344,"teacher_disagreement_score":0.002211603,"about_ca_system_score_codex":0.00066374853,"about_ca_system_score_gemma":0.0009299656,"threshold_uncertainty_score":0.007936597},"labels":[],"label_agreement":null},{"id":"W2030642834","doi":"10.1038/jcbfm.2012.69","title":"Penumbra Detection using PWI/DWI Mismatch MRI in a Rat Stroke Model with and without Comorbidity: Comparison of Methods","year":2012,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Penumbra; Medicine; Perfusion; Diffusion MRI; Nuclear medicine; Effective diffusion coefficient; Stroke (engine); Lesion; Perfusion scanning; Magnetic resonance imaging; Radiology; Cardiology; Ischemia; Pathology; Physics","score_opus":0.10254098968316133,"score_gpt":0.4187287059527386,"score_spread":0.31618771626957726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030642834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.972668,0.002388309,0.023156421,0.00006707558,0.00006696233,0.000231508,0.00057072344,0.00021741011,0.0006333971],"genre_scores_gemma":[0.9509935,0.004953794,0.03893185,0.00012313107,0.000049553135,0.0009970207,0.0011310424,0.00010147571,0.0027186808],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99957556,0.00005437272,0.00004362209,0.00013719397,0.00012923802,0.00005992281],"domain_scores_gemma":[0.9993399,0.000057176272,0.00025989735,0.00007396436,0.00014061332,0.00012844482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000770353,0.0008602607,0.0010280968,0.0011735891,0.00022473415,0.00055966905,0.00031227057,0.00048473242,0.00076599786],"category_scores_gemma":[0.0006740649,0.00041109163,0.00038522997,0.0005236664,0.00043398672,0.00081999734,0.00046102254,0.00080333534,0.00030007918],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0059346794,0.0007766853,0.014136238,0.0005255396,0.00016355528,0.00023532043,0.00016350897,0.0004006858,0.9450251,0.00016436557,0.00018329974,0.03229093],"study_design_scores_gemma":[0.00024711114,0.020278856,0.18188797,0.00009726872,0.0008566503,0.002235096,0.00043350866,0.011824729,0.77950245,0.00034767124,0.0020941473,0.00019451731],"about_ca_topic_score_codex":0.0011396805,"about_ca_topic_score_gemma":0.0023150027,"teacher_disagreement_score":0.0011735891,"about_ca_system_score_codex":0.00031883043,"about_ca_system_score_gemma":0.0004243855,"threshold_uncertainty_score":0.0040740967},"labels":[],"label_agreement":null},{"id":"W2030691940","doi":"10.1203/pdr.0b013e3182110f7e","title":"Noninvasive MRI Measures of Microstructural and Cerebrovascular Changes During Normal Swine Brain Development","year":2011,"lang":"en","type":"article","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Toronto; University Health Network; Thornhill Medical (Canada); Hospital for Sick Children","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Cerebral blood flow; Medicine; Brain development; Human brain; Cardiology; Neuroimaging; Magnetic resonance imaging; Internal medicine; Neuroscience; Radiology; Psychology","score_opus":0.21616468121463356,"score_gpt":0.383783386415188,"score_spread":0.16761870520055444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030691940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949929,0.00051309477,0.0027416109,0.000038162107,0.000012504444,0.000032588378,0.00021544006,0.000025820886,0.0014279475],"genre_scores_gemma":[0.9953876,0.0006047648,0.0022737326,0.00003347582,0.000018063638,0.0000686908,0.00036322983,0.000017068742,0.0012334731],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999162,0.000015198489,0.0000057510956,0.00002244598,0.000020034016,0.00002040236],"domain_scores_gemma":[0.9995995,0.00009232183,0.00011420737,0.000023524439,0.00010185654,0.000068655674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031212714,0.00023044828,0.00017129154,0.00057548645,0.0001545248,0.00023007943,0.0001543176,0.00020941813,0.00055871607],"category_scores_gemma":[0.0005575678,0.00017895065,0.000113544265,0.0002817704,0.00037113077,0.00033264677,0.00017520932,0.00039220924,0.00008380962],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029342768,0.0003839854,0.053243574,0.00012094937,0.00006214633,0.0013397008,0.0003367781,0.0005089975,0.9128643,0.0005163379,0.00042156645,0.027267344],"study_design_scores_gemma":[0.000059985676,0.0037113633,0.71798676,0.000025873882,0.00016271995,0.0031467902,0.00068757654,0.0031258413,0.268106,0.0003331381,0.0026143761,0.00003960556],"about_ca_topic_score_codex":0.0018268201,"about_ca_topic_score_gemma":0.003350847,"teacher_disagreement_score":0.0018268201,"about_ca_system_score_codex":0.0002615816,"about_ca_system_score_gemma":0.00033167616,"threshold_uncertainty_score":0.0036323667},"labels":[],"label_agreement":null},{"id":"W2031448494","doi":"10.1016/j.neurobiolaging.2014.05.039","title":"Does MRI scan acceleration affect power to track brain change?","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; U.S. National Library of Medicine; Takeda Pharmaceuticals North America; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; Servier; Innogenetics; Eisai; Bayer HealthCare; National Institute of Mental Health; Pfizer; Novartis Pharmaceuticals Corporation; National Institute on Drug Abuse; AstraZeneca; Eli Lilly and Company; National Institute of General Medical Sciences; Northern California Institute for Research and Education; Roche; Alzheimer's Drug Discovery Foundation; Merck; National Institute on Aging; Alzheimer's Association","keywords":"Atrophy; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Medicine; Magnetic resonance imaging; Affect (linguistics); Nuclear medicine; Psychology; Neuroscience; Disease; Radiology; Internal medicine","score_opus":0.056274466005025184,"score_gpt":0.3609224230133714,"score_spread":0.30464795700834624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031448494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.960166,0.007603763,0.020806896,0.002514987,0.00058828166,0.0001065433,0.0006326877,0.000317937,0.007262865],"genre_scores_gemma":[0.99005413,0.0018227036,0.0059124012,0.00045415378,0.00030897447,0.0000242781,0.00018250996,0.00009956498,0.0011413386],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958795,0.0001672973,0.000036299123,0.00008149564,0.000078124045,0.000048701244],"domain_scores_gemma":[0.9944494,0.0034333044,0.00095601915,0.0004262131,0.00056723726,0.00016794722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002196209,0.00046559327,0.00050157885,0.0005676329,0.00017438213,0.0009907312,0.00030433986,0.0010923382,0.0027380276],"category_scores_gemma":[0.020054689,0.0003463426,0.00030854155,0.00052334653,0.00048013427,0.0013530994,0.00026746982,0.0005305328,0.00077997975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060035777,0.00050796836,0.5547393,0.00051413453,0.0010081079,0.00051899086,0.00076587993,0.004228879,0.08150057,0.0012991271,0.0036280002,0.3452855],"study_design_scores_gemma":[0.00015259445,0.0024235696,0.9570051,0.0001707058,0.0007198211,0.0014753947,0.00046186315,0.011915061,0.016761301,0.0043439055,0.004514884,0.000055840555],"about_ca_topic_score_codex":0.0018976099,"about_ca_topic_score_gemma":0.0031262834,"teacher_disagreement_score":0.0027380276,"about_ca_system_score_codex":0.00015847037,"about_ca_system_score_gemma":0.0003059046,"threshold_uncertainty_score":0.0116147995},"labels":[],"label_agreement":null},{"id":"W2031559738","doi":"10.1227/01.neu.0000163089.31657.08","title":"Sensory and Motor Interhemispheric Integration after Section of Different Portions of the Anterior Corpus Callosum in Nonepileptic Patients","year":2005,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canada Research Chairs","keywords":"Corpus callosum; Somatosensory system; Medicine; Sensory system; Anatomy; Neuroscience; Anterior commissure; Psychology; Audiology","score_opus":0.021206452959562062,"score_gpt":0.2734464932492773,"score_spread":0.2522400402897152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031559738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974126,0.000051164436,0.000054113385,0.00000903478,0.0000010103599,0.000004791641,0.000013665588,0.000003254876,0.0001217131],"genre_scores_gemma":[0.9997458,0.00003938281,0.0000680977,0.000011432963,0.0000023610226,0.000006494654,0.00004561116,0.0000021546614,0.000078689],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998586,0.000018503355,0.000018426173,0.000037582613,0.000025686497,0.000041050076],"domain_scores_gemma":[0.9997149,0.00007532783,0.0000993586,0.00002483437,0.0000229798,0.00006251045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016804325,0.0006553899,0.00044763446,0.0007676259,0.0007631923,0.00031729517,0.000249066,0.0005349554,0.0011431517],"category_scores_gemma":[0.0010008648,0.00025772714,0.00029172556,0.00035437586,0.0008677044,0.00028193998,0.00030899284,0.00036621265,0.00018087057],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005596785,0.0006516197,0.7293618,0.0002125155,0.00032598467,0.10294761,0.0031738698,0.0012021454,0.12656055,0.00023351994,0.00033843165,0.029395211],"study_design_scores_gemma":[0.00021517427,0.0032167947,0.8667321,0.000024993655,0.00015210343,0.11870628,0.00091022864,0.00068745896,0.008706851,0.0001578723,0.00045506674,0.0000351263],"about_ca_topic_score_codex":0.0017148613,"about_ca_topic_score_gemma":0.0026864493,"teacher_disagreement_score":0.0017148613,"about_ca_system_score_codex":0.000476029,"about_ca_system_score_gemma":0.0003762166,"threshold_uncertainty_score":0.003824234},"labels":[],"label_agreement":null},{"id":"W2031619354","doi":"10.1016/j.schres.2006.04.027","title":"Deficit in schizophrenia to recruit the striatum in implicit learning: A functional magnetic resonance imaging investigation","year":2006,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; University of Manitoba","funders":"","keywords":"Schizophrenia (object-oriented programming); Striatum; Psychology; Functional magnetic resonance imaging; Neuroscience; Ventral striatum; Antipsychotic; Audiology; Psychiatry; Medicine; Dopamine","score_opus":0.10089276205348557,"score_gpt":0.37331671164439606,"score_spread":0.2724239495909105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031619354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966522,0.0003620603,0.0012885414,0.00030971906,0.000011749215,0.000025700634,0.00010439505,0.000012331792,0.0012333998],"genre_scores_gemma":[0.99736446,0.00021444431,0.0014697479,0.000111328336,0.000009449317,0.000017117882,0.00009578213,0.000012687345,0.00070506195],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998605,0.00002944345,0.000013582604,0.000022663433,0.00005097814,0.000022755281],"domain_scores_gemma":[0.99917525,0.00019155996,0.00029029817,0.00016305494,0.00007167786,0.00010813883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008898209,0.0005400631,0.0003113606,0.0003848789,0.00029841813,0.00045135323,0.00058365887,0.00070314005,0.0021555433],"category_scores_gemma":[0.0015446248,0.00032650397,0.00024112838,0.00015125597,0.0011866525,0.000597601,0.00045967865,0.0009881939,0.00015226922],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008823244,0.002264061,0.08160982,0.0004411241,0.00075127464,0.003309223,0.0008733109,0.0031609577,0.83401126,0.006011045,0.00078320486,0.057961527],"study_design_scores_gemma":[0.0013211617,0.0046757865,0.8236786,0.00017206106,0.000785287,0.010193304,0.0010901206,0.0131616425,0.1292695,0.013209828,0.0023539914,0.00008873871],"about_ca_topic_score_codex":0.005124084,"about_ca_topic_score_gemma":0.0059087826,"teacher_disagreement_score":0.005124084,"about_ca_system_score_codex":0.00058083667,"about_ca_system_score_gemma":0.0010657305,"threshold_uncertainty_score":0.01018852},"labels":[],"label_agreement":null},{"id":"W2031846748","doi":"10.1016/j.cortex.2014.04.016","title":"The DCDC2/intron 2 deletion and white matter disorganization: Focus on developmental dyslexia","year":2014,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke","keywords":"Splenium; Dyslexia; Corpus callosum; Fractional anisotropy; Psychology; White matter; Diffusion MRI; Superior longitudinal fasciculus; Lateralization of brain function; Neuropsychology; Arcuate fasciculus; Neuroscience; Audiology; Reading (process); Medicine; Magnetic resonance imaging; Cognition","score_opus":0.01653911360927793,"score_gpt":0.276337482238475,"score_spread":0.25979836862919703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031846748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655385,0.006176352,0.0040785056,0.0024452521,0.000069824964,0.00007844682,0.00044245613,0.00010569148,0.02106506],"genre_scores_gemma":[0.99301004,0.0027332865,0.0016804596,0.0002517677,0.0001701798,0.000016686554,0.00015053188,0.000031493553,0.0019554736],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99989986,0.000013026674,0.000011275539,0.00003362667,0.000017524944,0.000024605037],"domain_scores_gemma":[0.9998591,0.00005353028,0.00003257861,0.000009649313,0.000018165474,0.000026996227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017935551,0.00065459864,0.0003688431,0.0019931972,0.00039537577,0.0004838094,0.00046704302,0.0007423197,0.0027660776],"category_scores_gemma":[0.0004201999,0.0001841612,0.00022700701,0.0008208847,0.00079170655,0.0002889484,0.00045450454,0.00052865373,0.00020117749],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014041899,0.00036309304,0.21142218,0.00056277914,0.00024723265,0.40685058,0.0010976037,0.0011291197,0.28303632,0.010424481,0.004597233,0.07886522],"study_design_scores_gemma":[0.00006540474,0.0003608581,0.4513679,0.00019737586,0.00037104115,0.48036456,0.0011926683,0.0015249457,0.04425569,0.005584407,0.014662499,0.000052697724],"about_ca_topic_score_codex":0.004186617,"about_ca_topic_score_gemma":0.0042757187,"teacher_disagreement_score":0.004186617,"about_ca_system_score_codex":0.00037113007,"about_ca_system_score_gemma":0.00046750403,"threshold_uncertainty_score":0.009253442},"labels":[],"label_agreement":null},{"id":"W2032234501","doi":"10.1002/jmri.20651","title":"Diffusion tensor imaging in evaluation of human skeletal muscle injury","year":2006,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":213,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"Johns Hopkins University","keywords":"Diffusion MRI; Fractional anisotropy; Effective diffusion coefficient; Skeletal muscle; Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Anatomy; Nuclear medicine; Biomedical engineering; Physics; Radiology","score_opus":0.03270774088411862,"score_gpt":0.3580757512026797,"score_spread":0.3253680103185611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032234501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9595091,0.021700589,0.01578824,0.00042133563,0.00007247244,0.00011400504,0.00022559999,0.00017353993,0.0019950096],"genre_scores_gemma":[0.9808797,0.0048116073,0.013418668,0.000070531416,0.000066418004,0.000057145702,0.00021080038,0.000019519204,0.00046564033],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942434,0.00025050607,0.000069456764,0.00009153267,0.00012664859,0.000037565933],"domain_scores_gemma":[0.9988703,0.00030793372,0.00035767912,0.00007976958,0.0002572858,0.00012694347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020957573,0.00062245294,0.0003642951,0.0015609916,0.00014478326,0.00049168814,0.0003068861,0.0004697633,0.0007805664],"category_scores_gemma":[0.004567031,0.00013160241,0.0001923342,0.0005019703,0.000598448,0.00049729523,0.00036938005,0.0002681858,0.00034277758],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026855571,0.000194692,0.61118954,0.0010780843,0.0004561715,0.0026513727,0.00049759034,0.0019619064,0.120371066,0.00058660284,0.0013716039,0.25695586],"study_design_scores_gemma":[0.00015048153,0.0023843767,0.9211877,0.00023227952,0.00032072995,0.028160192,0.0004529842,0.011597915,0.027775962,0.001280339,0.006369802,0.000087299995],"about_ca_topic_score_codex":0.0008626201,"about_ca_topic_score_gemma":0.0010298888,"teacher_disagreement_score":0.0020957573,"about_ca_system_score_codex":0.00023664182,"about_ca_system_score_gemma":0.00024765212,"threshold_uncertainty_score":0.011083543},"labels":[],"label_agreement":null},{"id":"W2032321212","doi":"10.1007/s00429-005-0045-1","title":"Large-scale morphometric analysis of neuroanatomy and neuropathology","year":2005,"lang":"en","type":"article","venue":"Anatomy and Embryology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuropathology; Neuroanatomy; Neuroimaging; Neuroscience; Brain research; Pipeline (software); Computer science; Data science; Medicine; Medical physics; Pathology; Disease; Psychology","score_opus":0.023360660036086653,"score_gpt":0.3367737933823231,"score_spread":0.31341313334623644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032321212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6376777,0.0013375502,0.34922948,0.00025481964,0.000058258054,0.00018884233,0.0019689933,0.0023578755,0.0069265217],"genre_scores_gemma":[0.82915276,0.0005603657,0.16524921,0.000058313362,0.00004341692,0.00013805505,0.0015994823,0.00052760146,0.0026708245],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99962294,0.00007589578,0.0000218642,0.000098837634,0.00015153737,0.000028957762],"domain_scores_gemma":[0.9983962,0.0003613488,0.00019134782,0.00052549696,0.0004484976,0.00007702758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009104538,0.00034495132,0.00040647737,0.0025664957,0.00094150024,0.0007869179,0.0004815102,0.0003072213,0.0024428812],"category_scores_gemma":[0.0017410286,0.00028696295,0.00038234767,0.0019167317,0.0005852473,0.0006802768,0.00079356425,0.00046662387,0.0006380116],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024270885,0.00018789111,0.050200075,0.0003536919,0.00043854822,0.00067856174,0.0005579869,0.00962665,0.64842045,0.005881842,0.0032768669,0.28013483],"study_design_scores_gemma":[0.00003411961,0.00020773614,0.76365775,0.00005281697,0.00032144133,0.005959624,0.0006697158,0.089283496,0.10774856,0.015591847,0.01634278,0.00013011703],"about_ca_topic_score_codex":0.0051155393,"about_ca_topic_score_gemma":0.013253032,"teacher_disagreement_score":0.0051155393,"about_ca_system_score_codex":0.00039953366,"about_ca_system_score_gemma":0.0007587496,"threshold_uncertainty_score":0.010171533},"labels":[],"label_agreement":null},{"id":"W2032585403","doi":"10.7490/f1000research.1552.1","title":"Differences in the Role of Context on Polar and Translational Glass Patterns","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Open peer review; Plant biology; Context (archaeology); Neuroscience; Polar; Physiology; Biology; Medicine; Botany; Physics; Paleontology","score_opus":0.08744461820397366,"score_gpt":0.31603049951423123,"score_spread":0.2285858813102576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032585403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9385396,0.0007749858,0.02580858,0.00044185057,0.00016106843,0.00008080352,0.00042925784,0.00024147549,0.03352229],"genre_scores_gemma":[0.9951279,0.00029295107,0.0030420707,0.000030811923,0.000036448142,0.000015087876,0.00014033656,0.00014307308,0.0011713735],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999411,0.00012318217,0.00003379124,0.00016823251,0.00013486779,0.00012893743],"domain_scores_gemma":[0.9967217,0.0014086454,0.0004131485,0.0005167721,0.00057243917,0.0003673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068326306,0.00039230852,0.00056505617,0.0010775303,0.0008047218,0.00308275,0.00054965756,0.00080323813,0.007807514],"category_scores_gemma":[0.008970669,0.00048300214,0.0003800144,0.00066040404,0.0015189361,0.0025731483,0.0012575394,0.00089269213,0.0010778368],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005138511,0.00037988662,0.07651327,0.0007216424,0.00022617838,0.0009339237,0.0048922813,0.014346223,0.66340005,0.103973135,0.0029037017,0.12657115],"study_design_scores_gemma":[0.0002956773,0.0011048038,0.6338734,0.0002745729,0.00054756284,0.0028073287,0.008165189,0.07299616,0.13377638,0.13458078,0.0110924905,0.00048560768],"about_ca_topic_score_codex":0.001208049,"about_ca_topic_score_gemma":0.0018947446,"teacher_disagreement_score":0.007807514,"about_ca_system_score_codex":0.0003695266,"about_ca_system_score_gemma":0.00052879,"threshold_uncertainty_score":0.026118755},"labels":[],"label_agreement":null},{"id":"W2032891048","doi":"10.2214/ajr.09.2517","title":"Evaluation of Diffusion Tensor Imaging and Fiber Tractography of the Median Nerve: Preliminary Results on Intrasubject Variability and Precision of Measurements","year":2009,"lang":"en","type":"article","venue":"American Journal of Roentgenology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Medicine; Diffusion MRI; Tractography; Fractional anisotropy; Effective diffusion coefficient; Nuclear medicine; Fiber; Nerve fiber; Magnetic resonance imaging; Radiology; Anatomy","score_opus":0.054078883348146464,"score_gpt":0.35089731278864056,"score_spread":0.2968184294404941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032891048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9604924,0.001704378,0.036320034,0.000046164798,0.000035149613,0.000083351566,0.0002534997,0.00012338704,0.0009417013],"genre_scores_gemma":[0.99467635,0.000121064724,0.004690028,0.000020255537,0.000028372311,0.00003485181,0.0001854854,0.000052599225,0.00019104968],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98939997,0.0048663197,0.0010553929,0.0021403893,0.002335105,0.0002028543],"domain_scores_gemma":[0.9310173,0.044962242,0.007404743,0.008516226,0.007558501,0.0005409968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015062345,0.000492108,0.0004516519,0.0006851893,0.00032324382,0.00084113935,0.00039466983,0.00062732917,0.0006820793],"category_scores_gemma":[0.046771046,0.0003113541,0.00030352213,0.00040336463,0.00087205094,0.0006419763,0.00083580636,0.00042904852,0.0003145102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006189082,0.00040969416,0.7228857,0.0008131637,0.002213791,0.00086837774,0.0035761464,0.004874041,0.12574622,0.0005381775,0.00053867145,0.13134688],"study_design_scores_gemma":[0.00007124078,0.0021930714,0.94290555,0.00007922072,0.00043162622,0.0030709552,0.0003426839,0.011863233,0.037027717,0.0006052998,0.0013376635,0.00007171187],"about_ca_topic_score_codex":0.0005869603,"about_ca_topic_score_gemma":0.000843117,"teacher_disagreement_score":0.015062345,"about_ca_system_score_codex":0.0001863652,"about_ca_system_score_gemma":0.00019494042,"threshold_uncertainty_score":0.07965827},"labels":[],"label_agreement":null},{"id":"W2033328586","doi":"10.1016/j.jalz.2012.05.2076","title":"P3‐402: Detection of PCC functional connectivity characteristics in subcortical vascular mild cognitive impairment: A resting‐state fMRI study","year":2012,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Resting state fMRI; Neuroimaging; Diffusion MRI; Medicine; Posterior cingulate; Dementia; Montreal Cognitive Assessment; Neuroscience; Spatial normalization; Neurology; Psychology; Temporal lobe; Voxel; Cognitive impairment; Cognition; Internal medicine; Radiology; Magnetic resonance imaging; Disease; Epilepsy","score_opus":0.07365815354748648,"score_gpt":0.33650352653085674,"score_spread":0.2628453729833703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033328586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999089,0.000072159724,0.00025503236,0.000023991031,0.00000371768,0.000026341982,0.00010834545,0.0000068177014,0.00041460022],"genre_scores_gemma":[0.9991454,0.000047249552,0.00031571777,0.000030594183,0.000017204733,0.000029620087,0.00016974924,0.0000050426297,0.00023941792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993443,0.000010124735,0.0000037416498,0.000025984857,0.000011268426,0.000014403111],"domain_scores_gemma":[0.99987745,0.000028056254,0.000026533504,0.000011879447,0.000017132985,0.000038858307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025031154,0.00040040968,0.0002658716,0.00034547085,0.00041123433,0.00030157831,0.0003153551,0.00047972164,0.0015406243],"category_scores_gemma":[0.0006499128,0.00017249161,0.00015508111,0.00021413874,0.0003548708,0.00022192048,0.00018176335,0.00036137106,0.0002204308],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008877127,0.003541355,0.504653,0.00036441613,0.00052497647,0.016885348,0.0031222808,0.00086204376,0.4084928,0.00047475504,0.0022639534,0.049938012],"study_design_scores_gemma":[0.000069711816,0.0006381791,0.9918183,0.000006259755,0.000074343276,0.0031013018,0.00017250614,0.00113531,0.0024645329,0.00016698103,0.00033871073,0.000013793524],"about_ca_topic_score_codex":0.003372196,"about_ca_topic_score_gemma":0.0051576872,"teacher_disagreement_score":0.003372196,"about_ca_system_score_codex":0.00016165736,"about_ca_system_score_gemma":0.00017074168,"threshold_uncertainty_score":0.0067051053},"labels":[],"label_agreement":null},{"id":"W2033352952","doi":"10.1016/j.jpain.2009.01.103","title":"Cerebral cortical thickness in a subject lacking large myelinated afferents","year":2009,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Somatosensory system; Precuneus; Insula; Medicine; Neuroscience; Cortex (anatomy); Anatomy; Cerebral cortex; Prefrontal cortex; Psychology; Audiology; Functional magnetic resonance imaging; Cognition","score_opus":0.049992112272739746,"score_gpt":0.36996607430645817,"score_spread":0.3199739620337184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033352952","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99628913,0.00017331548,0.0007429697,0.0005731121,0.000053255135,0.000027306127,0.00014872718,0.000053081618,0.0019390581],"genre_scores_gemma":[0.9993787,0.00007621949,0.00014527439,0.000056343528,0.00005813035,0.000003796946,0.000023586466,0.000009005736,0.00024899532],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.9998369,0.000021486348,0.000018059789,0.00003336594,0.000027773785,0.00006229413],"domain_scores_gemma":[0.99880385,0.00066263805,0.0001615779,0.000087430475,0.00012493371,0.0001596542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003868686,0.00073515024,0.0006837164,0.0015159928,0.00092915434,0.0005571322,0.0007830092,0.0013836768,0.0033092536],"category_scores_gemma":[0.0021759805,0.0004978926,0.00040582655,0.000526834,0.0016812226,0.0007152079,0.00046786334,0.0014369204,0.00025869758],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0052214814,0.00040219683,0.03612843,0.00016411868,0.00015474117,0.87768537,0.0007477615,0.0009284837,0.06952338,0.00059956993,0.00052698614,0.007917453],"study_design_scores_gemma":[0.00025566728,0.0017359925,0.3593937,0.000044569053,0.00047294548,0.60397077,0.00087302056,0.0044419314,0.027086731,0.0010916686,0.0005553129,0.0000776726],"about_ca_topic_score_codex":0.0044769216,"about_ca_topic_score_gemma":0.0031579258,"teacher_disagreement_score":0.0044769216,"about_ca_system_score_codex":0.00047697013,"about_ca_system_score_gemma":0.0005186205,"threshold_uncertainty_score":0.0110705495},"labels":[],"label_agreement":null},{"id":"W2033515328","doi":"10.1016/j.yebeh.2014.06.020","title":"Reliability and variability of diffusion tensor imaging (DTI) tractography in pediatric epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"University of Oxford; Health Research Board","keywords":"Tractography; Diffusion MRI; Fractional anisotropy; White matter; Uncinate fasciculus; Psychology; Medicine; Nuclear medicine; Radiology; Magnetic resonance imaging","score_opus":0.02306039480292636,"score_gpt":0.31451833347525704,"score_spread":0.29145793867233066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033515328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972524,0.00040140675,0.001686286,0.000048116653,0.000010205582,0.0000038254657,0.00020525415,0.000021389646,0.00037109383],"genre_scores_gemma":[0.9992976,0.00010998595,0.0003911253,0.000005732392,0.000007849349,0.0000030570625,0.00012960612,0.000011507762,0.000043508437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972765,0.0008115221,0.0004766509,0.0006600026,0.00061046286,0.00016491083],"domain_scores_gemma":[0.9650113,0.020157028,0.008003291,0.0025052777,0.0039057727,0.0004172533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052289064,0.00030427022,0.0003391425,0.0014691701,0.00021348393,0.0008468493,0.0004098803,0.00050824904,0.00043323316],"category_scores_gemma":[0.040204026,0.00027525547,0.00039022721,0.0009842175,0.0007191162,0.0010802149,0.0006127645,0.0004905089,0.00018044097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015776961,0.0000148003965,0.9854939,0.000032733627,0.00014395601,0.00015911456,0.00040405008,0.0015802449,0.0018047763,0.00022772055,0.00016961514,0.00981129],"study_design_scores_gemma":[0.0000052839187,0.00010472996,0.98969483,0.000025059004,0.00007498394,0.0012683154,0.00021353074,0.0060712327,0.001907037,0.00032884374,0.00029323096,0.000012968876],"about_ca_topic_score_codex":0.00334883,"about_ca_topic_score_gemma":0.003912881,"teacher_disagreement_score":0.0052289064,"about_ca_system_score_codex":0.00040793384,"about_ca_system_score_gemma":0.00046444897,"threshold_uncertainty_score":0.027653456},"labels":[],"label_agreement":null},{"id":"W2033516072","doi":"10.1016/j.neuroimage.2008.06.031","title":"Arrested development and disrupted callosal microstructure following pediatric traumatic brain injury: relation to neurobehavioral outcomes","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Traumatic brain injury; Diffusion MRI; Psychology; Neuropsychology; Diffuse axonal injury; Neuroscience; Medicine; Audiology; Psychiatry; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.07929021529102213,"score_gpt":0.36616433801510045,"score_spread":0.2868741227240783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033516072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99948066,0.00009917535,0.000043459506,0.00003630402,0.0000027300973,0.0000029216299,0.000054019525,0.0000036915008,0.00027706716],"genre_scores_gemma":[0.9994935,0.0001671826,0.000087449975,0.000007776919,0.0000053376275,0.0000055826954,0.00009261079,0.0000032459795,0.0001372259],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977046,0.000029478782,0.000022873915,0.00004140154,0.000054554013,0.00008114219],"domain_scores_gemma":[0.9972826,0.00027398093,0.0017515216,0.00008644912,0.00022580106,0.00037959448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003552225,0.00031218753,0.00034577464,0.0010145154,0.00043980748,0.0005687813,0.00041262995,0.00046052685,0.0012583116],"category_scores_gemma":[0.003558067,0.00018391885,0.00026017628,0.0007118498,0.00086433394,0.00045368558,0.00051773543,0.0008306761,0.0001499722],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003156699,0.00011267671,0.98772347,0.00002448723,0.000039401784,0.003247182,0.00034530935,0.00018817486,0.0036093325,0.00011934641,0.00011666795,0.0041582007],"study_design_scores_gemma":[0.000001875275,0.00012325466,0.9964102,0.0000060511816,0.000021912574,0.0022154136,0.0003650256,0.00009495251,0.0006399129,0.00004709909,0.00007031169,0.0000040018763],"about_ca_topic_score_codex":0.0077256397,"about_ca_topic_score_gemma":0.0075751506,"teacher_disagreement_score":0.0077256397,"about_ca_system_score_codex":0.0005109444,"about_ca_system_score_gemma":0.0008326913,"threshold_uncertainty_score":0.015361309},"labels":[],"label_agreement":null},{"id":"W2033793704","doi":"10.1016/j.neuroimage.2010.05.049","title":"Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":293,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Atlas (anatomy); White matter; Anatomy; Medicine; Medical physics; Computer science; Radiology; Magnetic resonance imaging","score_opus":0.04376621060552617,"score_gpt":0.34485028561503145,"score_spread":0.3010840750095053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033793704","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008149895,0.00012494103,0.9842227,0.000078701385,0.00001704454,0.000071213086,0.0004836702,0.006370091,0.0004818452],"genre_scores_gemma":[0.059394095,0.0001689958,0.9370366,0.00005267066,0.00001656286,0.00015291046,0.0006777836,0.0015131137,0.0009873122],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995859,0.00010988923,0.000038481492,0.00008703696,0.00013178033,0.00004682373],"domain_scores_gemma":[0.9983917,0.00076263654,0.00015619071,0.00031520234,0.00030452054,0.00006971478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013942516,0.00105469,0.0010845811,0.0024221072,0.0010185644,0.002158275,0.0011799167,0.001450682,0.0060510687],"category_scores_gemma":[0.0047423453,0.0010046341,0.0014519439,0.001974753,0.0005322177,0.0011726303,0.0013972771,0.0015816009,0.0020768396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006670776,0.00015750404,0.004063741,0.00062603364,0.00061617733,0.00053162995,0.0006804431,0.09918759,0.09201627,0.023048135,0.02013261,0.75827277],"study_design_scores_gemma":[0.000068478636,0.00007331049,0.0030195771,0.00005515421,0.00019707417,0.0014962546,0.00011275371,0.8969968,0.057599816,0.026556648,0.013716374,0.000107798514],"about_ca_topic_score_codex":0.01558015,"about_ca_topic_score_gemma":0.02621865,"teacher_disagreement_score":0.01558015,"about_ca_system_score_codex":0.0008952974,"about_ca_system_score_gemma":0.004548963,"threshold_uncertainty_score":0.030978918},"labels":[],"label_agreement":null},{"id":"W2033810762","doi":"10.1080/02841850802555646","title":"Effects of gradient encoding and number of signal averages on fractional anisotropy and fiber density index in vivo at 1.5 tesla","year":2008,"lang":"en","type":"article","venue":"Acta Radiologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"In vivo; Fractional anisotropy; Medicine; Physics; Diffusion MRI; Nuclear medicine; Biology; Genetics; Radiology; Magnetic resonance imaging","score_opus":0.02930522639298808,"score_gpt":0.29935467057932097,"score_spread":0.27004944418633287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033810762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882882,0.001649577,0.009055192,0.000120101504,0.000027836628,0.000031834385,0.000095768795,0.00014706461,0.00058435503],"genre_scores_gemma":[0.97613055,0.00066477683,0.022439007,0.00006627183,0.000030276446,0.000056561046,0.00012331115,0.00009820258,0.0003910674],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996737,0.00013652246,0.000036660866,0.000060507107,0.00005385341,0.000038654147],"domain_scores_gemma":[0.9967452,0.0020523136,0.0004666999,0.00021876766,0.00028181903,0.00023513313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015652002,0.0004861896,0.00032692007,0.00039003495,0.0002362137,0.00045759045,0.00020552301,0.00037395247,0.0011988408],"category_scores_gemma":[0.0052313646,0.00034314702,0.00021273353,0.0001864843,0.00046659852,0.0006068031,0.00028846506,0.00032927698,0.00025145803],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012167419,0.00043398485,0.03215666,0.0004422999,0.0003022466,0.00038122345,0.00036171905,0.0036440294,0.8465912,0.00031932982,0.0006006267,0.10259921],"study_design_scores_gemma":[0.0005693488,0.013067752,0.47512147,0.00024051001,0.0011808157,0.0053100814,0.0002508973,0.03451807,0.46451333,0.0017140466,0.0033207384,0.00019292286],"about_ca_topic_score_codex":0.0007169262,"about_ca_topic_score_gemma":0.001750016,"teacher_disagreement_score":0.0015652002,"about_ca_system_score_codex":0.00024382888,"about_ca_system_score_gemma":0.00032006233,"threshold_uncertainty_score":0.008277655},"labels":[],"label_agreement":null},{"id":"W2034026137","doi":"10.1016/j.parkreldis.2012.03.008","title":"Intact limbic-prefrontal connections and reduced amygdala volumes in Parkinson's disease with mild depressive symptoms","year":2012,"lang":"en","type":"article","venue":"Parkinsonism & Related Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Amygdala; Uncinate fasciculus; Psychology; Corpus callosum; White matter; Neuroscience; Prefrontal cortex; Diffusion MRI; Limbic system; Hippocampus; Internal medicine; Medicine; Magnetic resonance imaging; Central nervous system","score_opus":0.016036217061060246,"score_gpt":0.28172435509058524,"score_spread":0.265688138029525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034026137","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988463,0.00021101616,0.00009414761,0.000051506886,0.00000453946,0.0000054824845,0.00008606979,0.000004573816,0.00069627963],"genre_scores_gemma":[0.9997234,0.00004108196,0.00007632006,0.000020756104,0.0000041261533,0.000002207516,0.000037532904,0.0000011564177,0.00009342336],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998872,0.00002357312,0.0000200985,0.000024515206,0.0000246632,0.000019909483],"domain_scores_gemma":[0.9996124,0.000096287935,0.00014848949,0.000026594304,0.000035232366,0.00008099995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023086414,0.0004246785,0.00041318455,0.0007358431,0.00047158933,0.0005294275,0.00031804806,0.0006599605,0.002404543],"category_scores_gemma":[0.00091970264,0.0003485632,0.0002378166,0.00029958406,0.00072101393,0.0003639747,0.00032251183,0.0003656137,0.0001904945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056528626,0.0003021221,0.84775496,0.00022999443,0.0006347731,0.033323728,0.0009483467,0.0006007684,0.095538974,0.0004406261,0.00048320772,0.014089666],"study_design_scores_gemma":[0.000044597746,0.00018243046,0.9829606,0.000010052716,0.000081674196,0.014809521,0.00018431668,0.00029803583,0.0009957792,0.00032682176,0.00009849197,0.000007668305],"about_ca_topic_score_codex":0.0034903965,"about_ca_topic_score_gemma":0.008397184,"teacher_disagreement_score":0.0034903965,"about_ca_system_score_codex":0.00034322767,"about_ca_system_score_gemma":0.0002445054,"threshold_uncertainty_score":0.008044004},"labels":[],"label_agreement":null},{"id":"W2034644191","doi":"10.1002/jmri.21425","title":"3T MR with diffusion tensor imaging and single‐voxel spectroscopy in giant axonal neuropathy","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"National Center for Research Resources","keywords":"Creatine; Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Choline; Effective diffusion coefficient; Magnetic resonance imaging; Medicine; Nuclear medicine; Nuclear magnetic resonance; Pathology; Chemistry; Internal medicine; Radiology; Physics","score_opus":0.0246229344886476,"score_gpt":0.2799159646964428,"score_spread":0.2552930302077952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034644191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996546,0.0012354215,0.0010674071,0.0002039334,0.00001191116,0.000017400389,0.00004033888,0.000034268807,0.00084339466],"genre_scores_gemma":[0.9955296,0.001266984,0.0026308708,0.00006349842,0.000040480318,0.000017855551,0.00007447699,0.000008560677,0.00036767186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998709,0.000050857172,0.000016864662,0.000017605664,0.000026044409,0.000017763336],"domain_scores_gemma":[0.99977535,0.000057315643,0.000067871886,0.000023342667,0.000037673282,0.000038499176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008850642,0.00056410424,0.00031709738,0.0013498534,0.00028083628,0.0003992443,0.00035402452,0.00089298905,0.00076817576],"category_scores_gemma":[0.0012108057,0.00020902455,0.00028309738,0.00045930286,0.00051518093,0.00052645174,0.0002896658,0.00028027483,0.00019896028],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007064951,0.0013532256,0.5363503,0.00055854546,0.00054326875,0.07612783,0.0021346668,0.004415087,0.15281838,0.001336932,0.003021433,0.21427539],"study_design_scores_gemma":[0.00038952503,0.002654705,0.7923847,0.00014144075,0.0004350887,0.15970433,0.00091592997,0.01939399,0.017488647,0.0038300296,0.0025650144,0.000096603886],"about_ca_topic_score_codex":0.0026196975,"about_ca_topic_score_gemma":0.002473504,"teacher_disagreement_score":0.0026196975,"about_ca_system_score_codex":0.00029424933,"about_ca_system_score_gemma":0.00023682507,"threshold_uncertainty_score":0.00520885},"labels":[],"label_agreement":null},{"id":"W2034758511","doi":"10.1155/2014/963032","title":"Automatic Detection and Quantification of Acute Cerebral Infarct by Fuzzy Clustering and Histographic Characterization on Diffusion Weighted MR Imaging and Apparent Diffusion Coefficient Map","year":2014,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Central University; National Science Council","keywords":"Artificial intelligence; Pattern recognition (psychology); Segmentation; Effective diffusion coefficient; Magnetic resonance imaging; Diffusion MRI; Cluster analysis; Computer science; Fuzzy logic; Similarity (geometry); Medicine; Nuclear medicine; Radiology; Image (mathematics)","score_opus":0.03968038319729568,"score_gpt":0.3558230829756875,"score_spread":0.3161426997783918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034758511","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25891623,0.00040562294,0.73810995,0.000084810206,0.00003163781,0.00025967,0.00019795122,0.0008785159,0.0011155771],"genre_scores_gemma":[0.576846,0.00018473844,0.42202067,0.000039461804,0.000018837838,0.00015844643,0.00019609038,0.0000669573,0.0004687517],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991417,0.00019063376,0.00008343985,0.0002287254,0.00029010905,0.00006532147],"domain_scores_gemma":[0.9989016,0.00031893956,0.00014767509,0.00014500218,0.00043730027,0.000049483828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00133997,0.00044546442,0.00046776948,0.0023036364,0.0003815777,0.00072946755,0.0006622732,0.000618319,0.00062332174],"category_scores_gemma":[0.0029850123,0.00032711867,0.0005202841,0.0007247847,0.00047106142,0.000580003,0.0004982789,0.00035190294,0.00027769216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006610887,0.00016880153,0.024183875,0.0003652855,0.00013182132,0.00023738635,0.00070867426,0.022163114,0.5407028,0.003606256,0.0011227028,0.4059482],"study_design_scores_gemma":[0.000061172,0.00037753905,0.09487067,0.000068435605,0.00017497357,0.0015166013,0.00038642948,0.62335235,0.27015826,0.005723192,0.003032757,0.00027762796],"about_ca_topic_score_codex":0.0030575362,"about_ca_topic_score_gemma":0.0033873436,"teacher_disagreement_score":0.0030575362,"about_ca_system_score_codex":0.00038440034,"about_ca_system_score_gemma":0.0006959514,"threshold_uncertainty_score":0.0070865154},"labels":[],"label_agreement":null},{"id":"W2036436660","doi":"10.1002/nbm.1586","title":"Considerations for measuring the fractional anisotropy of metabolites with diffusion tensor spectroscopy","year":2010,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Nuclear magnetic resonance; Isotropy; Chemistry; Thermal diffusivity; Nuclear magnetic resonance spectroscopy; White matter; Spectroscopy; Diffusion; Attenuation; Analytical Chemistry (journal); Physics; Optics; Chromatography; Magnetic resonance imaging; Thermodynamics; Medicine","score_opus":0.05586982234251825,"score_gpt":0.35314608839945283,"score_spread":0.2972762660569346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036436660","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029658532,0.044809815,0.8920631,0.018352553,0.0027744807,0.00062449335,0.00060071575,0.0016144364,0.009501827],"genre_scores_gemma":[0.08344306,0.015063137,0.89192706,0.0038950173,0.0012930484,0.0008665855,0.00022285279,0.0008675373,0.002421627],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9631029,0.022534823,0.0018588535,0.0036564113,0.008343867,0.0005031338],"domain_scores_gemma":[0.89861816,0.07668293,0.0052372776,0.005370834,0.012686113,0.0014046164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.052794825,0.0023049507,0.003639573,0.0039380565,0.0016786652,0.0061769723,0.0049501625,0.0062988107,0.0025639567],"category_scores_gemma":[0.13657852,0.0022830951,0.0016232429,0.0036239573,0.0055437465,0.005582736,0.003528686,0.0073125325,0.0018403472],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002762825,0.0004707261,0.031928726,0.008130638,0.0010106498,0.003780092,0.0024722544,0.014834047,0.33078712,0.12164168,0.03262098,0.44956028],"study_design_scores_gemma":[0.0003926308,0.0044739535,0.06303145,0.0059903637,0.0018741125,0.03410235,0.0032546842,0.110668726,0.29928508,0.23894703,0.23624757,0.0017320992],"about_ca_topic_score_codex":0.005573431,"about_ca_topic_score_gemma":0.008850508,"teacher_disagreement_score":0.052794825,"about_ca_system_score_codex":0.002282712,"about_ca_system_score_gemma":0.0022117062,"threshold_uncertainty_score":0.27920908},"labels":[],"label_agreement":null},{"id":"W2036945687","doi":"10.1002/hbm.20197","title":"Sensorimotor organization in double cortex syndrome","year":2005,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroscience; Sensory system; Somatosensory system; Thalamus; Insular cortex; Supplementary motor area; Motor cortex; Psychology; Cortex (anatomy); Primary motor cortex; Stimulus (psychology); White matter; Magnetic resonance imaging; Functional magnetic resonance imaging; Medicine; Stimulation","score_opus":0.07614635344089178,"score_gpt":0.3461406210362564,"score_spread":0.26999426759536466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036945687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99796534,0.00018725931,0.0006919394,0.000042023214,0.000006897849,0.000017433602,0.00006308636,0.00003875929,0.0009871538],"genre_scores_gemma":[0.9991672,0.00008031488,0.00036508334,0.00004454829,0.000007075374,0.000008464617,0.00008282706,0.000007444361,0.00023716832],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99980336,0.00002230407,0.00001931037,0.00006713987,0.000047474634,0.000040433857],"domain_scores_gemma":[0.9996909,0.000055483208,0.00012248314,0.000021101067,0.000025497058,0.00008454033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011535466,0.0010472095,0.00042688896,0.0014304632,0.00033474804,0.00025664354,0.00025509298,0.0004151438,0.0027997526],"category_scores_gemma":[0.0007703457,0.00022163586,0.00017573853,0.00045739397,0.0007826806,0.00019049812,0.0006019621,0.00027554616,0.00019323418],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012082824,0.00021736643,0.22380458,0.00035560693,0.00027725153,0.25898647,0.0015209198,0.00072221615,0.46862832,0.0015543957,0.001146651,0.041577864],"study_design_scores_gemma":[0.00011787354,0.0006892162,0.5448862,0.00004111549,0.00012003985,0.43862444,0.0002390052,0.0010383636,0.012153033,0.0008877314,0.0011708793,0.000032005693],"about_ca_topic_score_codex":0.0014190321,"about_ca_topic_score_gemma":0.0025414967,"teacher_disagreement_score":0.0027997526,"about_ca_system_score_codex":0.00028773278,"about_ca_system_score_gemma":0.00032249553,"threshold_uncertainty_score":0.009366095},"labels":[],"label_agreement":null},{"id":"W2036969062","doi":"10.1523/jneurosci.3979-14.2015","title":"Functional Consequences of Neurite Orientation Dispersion and Density in Humans across the Adult Lifespan","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; McGill University; Douglas Mental Health University Institute; Douglas College; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Centre for Addiction and Mental Health; National Institutes of Health; W. Garfield Weston Foundation; National Alliance for Research on Schizophrenia and Depression","keywords":"Neuroscience; Diffusion MRI; Psychology; White matter; Fractional anisotropy; Hippocampal formation; Functional specialization; Hippocampus; Connectome; Resting state fMRI; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.10312702425535138,"score_gpt":0.38539053470223344,"score_spread":0.2822635104468821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036969062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990609,0.00021957328,0.00023368484,0.000013131973,0.0000013256348,0.0000021103433,0.00019204691,0.0000100322295,0.00026709697],"genre_scores_gemma":[0.99934393,0.00009737411,0.0002765449,0.000008205053,0.000001761199,0.0000023397379,0.00012933528,0.000003093141,0.00013739208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999255,0.000010272615,0.000006104588,0.00003914427,0.000012221635,0.0000066718762],"domain_scores_gemma":[0.9996908,0.000039850325,0.00015603028,0.00003793348,0.000037972608,0.000037511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022146074,0.00020076435,0.00014999078,0.0005042177,0.00015042348,0.00023860768,0.00008130815,0.00022654537,0.0004959473],"category_scores_gemma":[0.00088955055,0.00012003251,0.00008187067,0.00018679965,0.00024453478,0.00017678543,0.0001878988,0.0001153451,0.00008522711],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001154318,0.000099793484,0.8617518,0.000061869,0.00019892007,0.0018436539,0.0010026192,0.0015001413,0.09640187,0.00039390006,0.0005391241,0.035051994],"study_design_scores_gemma":[0.0000033229894,0.000101310776,0.99687433,0.0000045980833,0.000018236922,0.0009770906,0.000055831224,0.00045315246,0.0011470298,0.00020023753,0.00015939151,0.00000535418],"about_ca_topic_score_codex":0.0035625075,"about_ca_topic_score_gemma":0.00349907,"teacher_disagreement_score":0.0035625075,"about_ca_system_score_codex":0.0001452714,"about_ca_system_score_gemma":0.00007967947,"threshold_uncertainty_score":0.007083535},"labels":[],"label_agreement":null},{"id":"W2037701101","doi":"10.1016/j.neuroimage.2014.09.005","title":"Interpolation of diffusion weighted imaging datasets","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Lundbeckfonden","keywords":"Interpolation (computer graphics); Diffusion MRI; Voxel; Tractography; Artificial intelligence; Computer science; Image resolution; Bicubic interpolation; Orientation (vector space); Computer vision; Pattern recognition (psychology); Linear interpolation; Mathematics; Image (mathematics); Magnetic resonance imaging; Geometry; Medicine","score_opus":0.03212920246301052,"score_gpt":0.33635614610364456,"score_spread":0.304226943640634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037701101","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.072652385,0.0005901812,0.9097324,0.00022356042,0.00018714655,0.00046725303,0.008258526,0.0056052725,0.0022832453],"genre_scores_gemma":[0.22926573,0.000763378,0.74543965,0.00007357585,0.000029372339,0.001012713,0.020242939,0.0010915309,0.0020810757],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990482,0.00027678278,0.00012594208,0.00024258732,0.0002445084,0.00006202224],"domain_scores_gemma":[0.99749917,0.00075962004,0.00017421345,0.00083879643,0.0006700325,0.000058131907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022375355,0.0009396376,0.00078958116,0.0019393675,0.0004428519,0.0009590188,0.0009793348,0.00088510255,0.0039222273],"category_scores_gemma":[0.009810327,0.0005602596,0.0012462509,0.0025755665,0.00032552646,0.0008355723,0.0012952974,0.0012908949,0.0023123457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014614834,0.00038869254,0.0104624815,0.002139466,0.000531432,0.0008793671,0.00061225257,0.49226856,0.12549141,0.019682039,0.01955778,0.32652506],"study_design_scores_gemma":[0.00010343901,0.0003309502,0.009351382,0.0001483699,0.00010166474,0.00070256327,0.00011143134,0.8351581,0.08684515,0.018686267,0.04829506,0.00016567114],"about_ca_topic_score_codex":0.0029806474,"about_ca_topic_score_gemma":0.0028707914,"teacher_disagreement_score":0.0039222273,"about_ca_system_score_codex":0.0005632068,"about_ca_system_score_gemma":0.0014091978,"threshold_uncertainty_score":0.013121128},"labels":[],"label_agreement":null},{"id":"W2037972318","doi":"10.1109/tbme.2011.2181167","title":"Robust White Matter Lesion Segmentation in FLAIR MRI","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Fluid-attenuated inversion recovery; Voxel; Segmentation; Artificial intelligence; Computer science; Hyperintensity; Artifact (error); Pattern recognition (psychology); Ground truth; Image segmentation; White matter; Thresholding; Partial volume; Computer vision; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.071193842667303,"score_gpt":0.2907695990275098,"score_spread":0.21957575636020682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037972318","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012024407,0.00047690838,0.9852297,0.00008947684,0.000021817108,0.00006502065,0.00008622105,0.0014777738,0.00052879157],"genre_scores_gemma":[0.11422973,0.0005439172,0.881975,0.00015721597,0.000084859385,0.00013652022,0.00046758403,0.0007498838,0.0016552901],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890566,0.00023134435,0.00007183245,0.0002949459,0.00040387592,0.00009235441],"domain_scores_gemma":[0.99909425,0.00030455962,0.00023158561,0.00017967151,0.00016287868,0.000027096346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014158268,0.0011365045,0.0011077251,0.0025261273,0.00055313174,0.0015842777,0.0015248698,0.002009113,0.0010030125],"category_scores_gemma":[0.0041176905,0.0007762704,0.0013684708,0.0012855717,0.00085962564,0.0015416046,0.0012204308,0.00079628744,0.0015116689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030285685,0.000080941136,0.0018889918,0.00047823295,0.00027134918,0.00035823832,0.00041611458,0.18547735,0.1918405,0.0078080744,0.0031052064,0.607972],"study_design_scores_gemma":[0.000036109937,0.00020995169,0.0053354744,0.00007204951,0.00009435993,0.0010142395,0.000086073975,0.8338426,0.13618426,0.015000384,0.008000041,0.00012454325],"about_ca_topic_score_codex":0.0027691124,"about_ca_topic_score_gemma":0.0029858795,"teacher_disagreement_score":0.0027691124,"about_ca_system_score_codex":0.0007058441,"about_ca_system_score_gemma":0.0006514749,"threshold_uncertainty_score":0.0074877143},"labels":[],"label_agreement":null},{"id":"W2038418010","doi":"10.1016/j.pscychresns.2006.11.011","title":"Three-dimensional volumetric analysis and reconstruction of amygdala and hippocampal head, body and tail","year":2007,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Alberta","funders":"","keywords":"Hippocampus; Hippocampal formation; Amygdala; Medicine; Neuroscience; Magnetic resonance imaging; Nuclear medicine; Psychology; Radiology","score_opus":0.0851289550881558,"score_gpt":0.4149626736721997,"score_spread":0.32983371858404387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038418010","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43691573,0.0005768085,0.55406004,0.00036289715,0.00004263003,0.00015598339,0.0016482541,0.0016989348,0.004538742],"genre_scores_gemma":[0.8616767,0.00046669255,0.1338412,0.00007822269,0.000019633953,0.000101895224,0.0006927669,0.00044345218,0.0026794085],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99990904,0.000014562988,0.0000068224576,0.0000130909075,0.000036169702,0.000020393129],"domain_scores_gemma":[0.99978524,0.00005758468,0.000026575754,0.000051445186,0.000065567685,0.000013633932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004141724,0.00028514687,0.0002534834,0.0011044419,0.0003277002,0.0010576069,0.00043811597,0.00054126483,0.001678241],"category_scores_gemma":[0.0008038094,0.0004907264,0.00060226285,0.0007953425,0.00034909995,0.00044272418,0.000490844,0.0005320421,0.00045119599],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082579406,0.00013798127,0.032264836,0.0005958566,0.0003373712,0.0015152075,0.0018505194,0.09835062,0.5402055,0.012368391,0.0043869535,0.30716106],"study_design_scores_gemma":[0.00009773579,0.00029417215,0.1317687,0.0001439576,0.00046472249,0.015344406,0.0017099733,0.41219383,0.39976254,0.017797925,0.020140918,0.00028119184],"about_ca_topic_score_codex":0.0068520415,"about_ca_topic_score_gemma":0.0070006326,"teacher_disagreement_score":0.0068520415,"about_ca_system_score_codex":0.00026988695,"about_ca_system_score_gemma":0.0010704191,"threshold_uncertainty_score":0.0136243105},"labels":[],"label_agreement":null},{"id":"W2038568172","doi":"10.1016/j.neuroimage.2007.12.053","title":"Microstructural maturation of the human brain from childhood to adulthood","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1440,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Diffusion MRI; Brain development; Neuroscience; Human brain; Diffusion imaging; Psychology; Magnetic resonance imaging; Brain morphometry; Medicine","score_opus":0.035499247140400605,"score_gpt":0.3177595942313928,"score_spread":0.2822603470909922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038568172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98691535,0.003995713,0.0021949348,0.00030317946,0.000017256589,0.000009504743,0.0009311177,0.00006467608,0.005568177],"genre_scores_gemma":[0.9943598,0.0024792014,0.0012778775,0.00003350685,0.000012040951,0.00000948435,0.00032851394,0.000029669662,0.0014698135],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991095,0.00001353121,0.0000062603704,0.000030141016,0.000021585272,0.000017524586],"domain_scores_gemma":[0.999577,0.00009180911,0.00013496776,0.000041184558,0.00011791851,0.00003705393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027491638,0.00017521766,0.00012504552,0.0010540868,0.00026563925,0.0005073064,0.00019252596,0.00023809634,0.0016612515],"category_scores_gemma":[0.0011920598,0.00023109978,0.0001760708,0.00054164237,0.00033041093,0.0005829678,0.00032618502,0.00031589586,0.00034157123],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009471203,0.00013216367,0.4562031,0.00051302783,0.00038240963,0.0030321092,0.0057691336,0.0028533228,0.17132199,0.0062857447,0.005697697,0.34686214],"study_design_scores_gemma":[0.0000019131862,0.000083202125,0.98470205,0.000036870508,0.000038479924,0.0022998932,0.0004620126,0.0003044455,0.007051082,0.0010201121,0.003989584,0.000010254469],"about_ca_topic_score_codex":0.005630513,"about_ca_topic_score_gemma":0.009058581,"teacher_disagreement_score":0.005630513,"about_ca_system_score_codex":0.0003341795,"about_ca_system_score_gemma":0.00035822144,"threshold_uncertainty_score":0.011195481},"labels":[],"label_agreement":null},{"id":"W2039002182","doi":"10.1167/9.8.772","title":"The organization of inter-hemispheric projections from areas 17 and 18 in the human splenium, studied with DTI probabilistic fiber tracking","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Splenium; Corpus callosum; Diffusion MRI; Occipital lobe; Neuroscience; Cortex (anatomy); Anatomy; Visual cortex; Dorsum; Magnetic resonance imaging; Psychology; Biology; Medicine","score_opus":0.04060653980845177,"score_gpt":0.3605347643817167,"score_spread":0.319928224573265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039002182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99386287,0.00013168952,0.005077841,0.000025046838,0.0000017276928,0.000011040085,0.00014121381,0.00004330641,0.00070517976],"genre_scores_gemma":[0.99172103,0.00017568894,0.007363412,0.000010188998,0.000003948788,0.00001626194,0.000158107,0.000022880407,0.0005285875],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999602,0.0000047294598,0.00000332813,0.000013949552,0.000010526623,0.000007320717],"domain_scores_gemma":[0.99978155,0.000060638184,0.0000806558,0.00003329801,0.000021358353,0.000022524264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015689406,0.00020195819,0.00009432751,0.00072145724,0.00018418227,0.00026582548,0.00009994298,0.00016170963,0.0014042471],"category_scores_gemma":[0.00097426196,0.00018675228,0.00011371558,0.00023908408,0.00038751343,0.000277322,0.0002077022,0.00013278516,0.00026594943],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011386102,0.00007002111,0.15297222,0.00020695056,0.00010705851,0.0020774081,0.0032202725,0.0035392642,0.6767175,0.0035095855,0.00087608193,0.15556502],"study_design_scores_gemma":[0.000073963536,0.0004353812,0.8753302,0.000048285994,0.000113407776,0.009394804,0.0005068892,0.014913327,0.08921294,0.004269417,0.0056555374,0.0000458249],"about_ca_topic_score_codex":0.0027579293,"about_ca_topic_score_gemma":0.0036851715,"teacher_disagreement_score":0.0027579293,"about_ca_system_score_codex":0.0001445008,"about_ca_system_score_gemma":0.00028999298,"threshold_uncertainty_score":0.005483687},"labels":[],"label_agreement":null},{"id":"W2039147736","doi":"10.1016/j.bandc.2009.04.002","title":"A choice reaction time index of callosal anatomical homotopy","year":2009,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Index (typography); Cognitive psychology; Corpus callosum; Audiology; Neuroscience; Choice reaction time; Cognition; Computer science; Medicine","score_opus":0.030500184692867152,"score_gpt":0.3391868692968782,"score_spread":0.30868668460401105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039147736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9466707,0.0005217818,0.027369699,0.00010227459,0.00017417615,0.00022043183,0.0019892242,0.00040447337,0.022547327],"genre_scores_gemma":[0.9896812,0.00014106341,0.006229762,0.00006040217,0.000053777345,0.00014755895,0.00055450597,0.000120796336,0.0030109722],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99952316,0.000105821055,0.00003976935,0.00012466377,0.00016842718,0.000038078688],"domain_scores_gemma":[0.9946319,0.0035640402,0.00054904504,0.00044336333,0.00045626477,0.00035530175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093224546,0.00053957116,0.00040901965,0.0016324329,0.00024036907,0.0010365932,0.00026737116,0.0006848165,0.008349344],"category_scores_gemma":[0.009478403,0.00013510532,0.00031321097,0.0008841492,0.00035398992,0.0012871823,0.0005875744,0.000560567,0.000998625],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021580258,0.0009697521,0.20245121,0.00090926484,0.0007988866,0.00057366746,0.0011540096,0.0096248165,0.42971882,0.008986309,0.0052322983,0.3180007],"study_design_scores_gemma":[0.0002678926,0.0037402662,0.8654079,0.00008626769,0.00046794408,0.001390854,0.0004871276,0.040933818,0.07439099,0.008271398,0.0043969257,0.00015865696],"about_ca_topic_score_codex":0.0017054147,"about_ca_topic_score_gemma":0.0017523868,"teacher_disagreement_score":0.008349344,"about_ca_system_score_codex":0.00039900464,"about_ca_system_score_gemma":0.00028903328,"threshold_uncertainty_score":0.027931273},"labels":[],"label_agreement":null},{"id":"W2039257006","doi":"10.1002/ana.20334","title":"Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy","year":2004,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":272,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fornix; Cingulum (brain); Diffusion MRI; Temporal lobe; Fractional anisotropy; White matter; Epilepsy; Magnetic resonance imaging; Tractography; Limbic system; Neuroscience; Hippocampal sclerosis; Psychology; Medicine; Hippocampus; Radiology; Central nervous system","score_opus":0.11135876017310625,"score_gpt":0.3787210650055335,"score_spread":0.26736230483242723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039257006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99838877,0.00024893094,0.00028696924,0.000049528757,0.0000024258054,0.000006875839,0.000042757983,0.000017331398,0.0009565573],"genre_scores_gemma":[0.99970764,0.000068660476,0.00010463953,0.000013401448,0.000004674026,0.0000017152854,0.000024055022,0.000002053758,0.00007316779],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998535,0.000030545933,0.000022739676,0.000034048902,0.000030564668,0.000028592782],"domain_scores_gemma":[0.9996314,0.000078229656,0.00017316197,0.00004357189,0.000025443487,0.00004818119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022805962,0.00036869032,0.00024379193,0.0010427401,0.0003336504,0.0002041212,0.0001281264,0.00021592081,0.0015395128],"category_scores_gemma":[0.0012303513,0.00018823467,0.00012702099,0.00036577182,0.0007935767,0.00033917162,0.00032456176,0.0001322354,0.00015270672],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014853188,0.00010151055,0.68607783,0.00030707868,0.00017609696,0.11372743,0.0013933664,0.00083258614,0.13808754,0.00087525515,0.00065702636,0.05627896],"study_design_scores_gemma":[0.000048354166,0.00024742403,0.78441083,0.000016440605,0.00007813011,0.20755056,0.00029732182,0.00058215926,0.0056333113,0.0006122274,0.0005044779,0.000018708428],"about_ca_topic_score_codex":0.0021868786,"about_ca_topic_score_gemma":0.004213555,"teacher_disagreement_score":0.0021868786,"about_ca_system_score_codex":0.0003124293,"about_ca_system_score_gemma":0.00026172528,"threshold_uncertainty_score":0.0051501393},"labels":[],"label_agreement":null},{"id":"W2039280993","doi":"10.1016/j.neuroimage.2015.02.029","title":"Ultra-high resolution in-vivo 7.0 T structural imaging of the human hippocampus reveals the endfolial pathway","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Center for Research Resources; GE Healthcare; National Institutes of Health","keywords":"Hippocampal formation; Subiculum; Neuroscience; Hippocampus; Fornix; White matter; Neuroanatomy; Biology; Anatomy; In vivo; Entorhinal cortex; Medicine; Magnetic resonance imaging; Dentate gyrus","score_opus":0.05387784350167023,"score_gpt":0.33130764774635746,"score_spread":0.2774298042446872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039280993","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97212976,0.0032539677,0.018046714,0.0010868481,0.000034077475,0.000027675691,0.0002820025,0.00014282798,0.0049960595],"genre_scores_gemma":[0.9849311,0.001909965,0.010094944,0.00018128319,0.000025624548,0.00001370404,0.00024360078,0.00004589221,0.0025538139],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99997413,0.00000474485,0.0000017839744,0.0000051692546,0.0000068822987,0.000007286459],"domain_scores_gemma":[0.99989104,0.000042183037,0.000015969945,0.000013799131,0.000023027358,0.0000140155935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017917535,0.00019331601,0.00014636136,0.00039788848,0.0002704727,0.00047052087,0.0003594742,0.000764265,0.0015590925],"category_scores_gemma":[0.0005303973,0.00027369426,0.000110458976,0.00019758834,0.00041379945,0.0006395601,0.00023730654,0.00046225314,0.00037595845],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009153565,0.000097042335,0.005425279,0.0002713034,0.00006311029,0.0020397494,0.00033330335,0.00093659275,0.9565509,0.0014350675,0.001312179,0.030620245],"study_design_scores_gemma":[0.00031569012,0.0012400749,0.21690464,0.0001865133,0.0004228685,0.025246685,0.0017055714,0.011768657,0.7142008,0.013345294,0.014572088,0.000091107526],"about_ca_topic_score_codex":0.0021105723,"about_ca_topic_score_gemma":0.004203649,"teacher_disagreement_score":0.0021105723,"about_ca_system_score_codex":0.00014134771,"about_ca_system_score_gemma":0.00030974465,"threshold_uncertainty_score":0.005215645},"labels":[],"label_agreement":null},{"id":"W2039575924","doi":"10.1117/12.2043750","title":"Characterizing the spatial distribution of microhemorrhages resulting from Traumatic Brain Injury (TBI)","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Susceptibility weighted imaging; Corpus callosum; White matter; Diffusion MRI; Traumatic brain injury; Brain atlas; Medicine; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Computer science; Pathology; Radiology","score_opus":0.023114660498243976,"score_gpt":0.28060359176946736,"score_spread":0.2574889312712234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039575924","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981437,0.00040986098,0.00097528327,0.000017584842,0.0000019944114,0.000009993297,0.000109378576,0.000017916045,0.00031423633],"genre_scores_gemma":[0.99859613,0.0003487251,0.0007404241,0.000008365138,0.000008119127,0.0000060034436,0.00014980367,0.0000053450044,0.00013708818],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998783,0.000016220703,0.00001773662,0.00003105162,0.000032446926,0.000024201549],"domain_scores_gemma":[0.9996265,0.00007538138,0.00015955759,0.00003810718,0.00006603681,0.000034377033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016462267,0.00020183343,0.00019874886,0.0012832383,0.00020121873,0.00024127925,0.00014673697,0.00015837023,0.00075349753],"category_scores_gemma":[0.001155881,0.00012151141,0.00013149077,0.00060931774,0.00029603415,0.00035898775,0.00023651122,0.00008906699,0.0002043492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005395053,0.00006021708,0.8443567,0.00017166868,0.00012523131,0.0040725595,0.0011383557,0.00051061215,0.053831734,0.00009345319,0.00037319903,0.09472671],"study_design_scores_gemma":[0.0000048555985,0.00015639489,0.9877307,0.000005803763,0.000032483298,0.007319352,0.00031045263,0.00031511392,0.003688833,0.00007307021,0.0003543891,0.000008445328],"about_ca_topic_score_codex":0.0018611577,"about_ca_topic_score_gemma":0.0034828947,"teacher_disagreement_score":0.0018611577,"about_ca_system_score_codex":0.00013101206,"about_ca_system_score_gemma":0.00014923069,"threshold_uncertainty_score":0.0037006736},"labels":[],"label_agreement":null},{"id":"W2039631898","doi":"10.1097/00001756-200105250-00037","title":"Magnetic resonance imaging predicts neuropathology from soman-mediated seizures in the rodent","year":2001,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence; University of Saskatchewan; Royal University Hospital","funders":"","keywords":"Soman; Neuropathology; Hippocampus; Piriform cortex; Neuroscience; Thalamus; Status epilepticus; Entorhinal cortex; Pathology; Medicine; Chemistry; Epilepsy; Nuclear magnetic resonance; Psychology; Acetylcholinesterase; Physics","score_opus":0.04068828987462686,"score_gpt":0.32208652882462796,"score_spread":0.2813982389500011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039631898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99774086,0.0006672768,0.0007905954,0.00004038987,0.0000055917894,0.000015918136,0.000119613156,0.00005126983,0.0005684237],"genre_scores_gemma":[0.99457186,0.0013932794,0.0015630977,0.000049121933,0.0000052502965,0.000027079734,0.00044445755,0.000014388193,0.0019313667],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999573,0.000004831731,0.0000040144646,0.000009747231,0.000011722082,0.000012412338],"domain_scores_gemma":[0.999818,0.000012270338,0.00009588882,0.000010865829,0.000027034228,0.000035834928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013799882,0.00029308963,0.0001753024,0.00063060963,0.00008219469,0.00018022828,0.00010576952,0.0002730682,0.0007326747],"category_scores_gemma":[0.00023767672,0.00020333816,0.00011412979,0.0001267913,0.00020930136,0.0002699155,0.00014908364,0.00049451744,0.0002008084],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005358522,0.00010565442,0.014898909,0.00005034238,0.00002702194,0.00039220127,0.000040717325,0.00011354972,0.97858,0.000050898117,0.000094530784,0.005110369],"study_design_scores_gemma":[0.000059848542,0.0053292424,0.5419111,0.000038805236,0.00013170717,0.004985983,0.00025557133,0.0014144604,0.4436816,0.00032595944,0.0018374175,0.000028193284],"about_ca_topic_score_codex":0.00065113854,"about_ca_topic_score_gemma":0.0022335122,"teacher_disagreement_score":0.0007326747,"about_ca_system_score_codex":0.00019072896,"about_ca_system_score_gemma":0.00009214806,"threshold_uncertainty_score":0.0024510026},"labels":[],"label_agreement":null},{"id":"W2040016992","doi":"10.1016/j.neuroimage.2012.10.086","title":"Unbiased tensor-based morphometry: Improved robustness and sample size estimates for Alzheimer's disease clinical trials","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; National Center for Research Resources; F. Hoffmann-La Roche; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Bayer HealthCare; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Synarc","keywords":"Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Sample size determination; Statistical power; Magnetic resonance imaging; Atrophy; Robustness (evolution); Clinical trial; Psychology; Medicine; Alzheimer's disease; Disease; Neuroscience; Internal medicine; Statistics; Radiology; Mathematics; Biology","score_opus":0.32498342244630846,"score_gpt":0.48478028006484475,"score_spread":0.1597968576185363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040016992","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13437766,0.016517116,0.8352323,0.0040569087,0.0010656656,0.0030247567,0.000820802,0.0015905667,0.0033141768],"genre_scores_gemma":[0.6211124,0.0020244336,0.3697353,0.001076037,0.0004428,0.0037685735,0.00048092767,0.0003959204,0.00096368394],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.88328326,0.10708882,0.0032568783,0.0030139477,0.0030212658,0.00033590465],"domain_scores_gemma":[0.74303705,0.2135407,0.015414454,0.020470025,0.006571094,0.00096676],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.19160952,0.0014599264,0.004084344,0.001982082,0.0008863613,0.0027481606,0.0019329856,0.0035809882,0.0024243803],"category_scores_gemma":[0.35193714,0.0015560582,0.0023140481,0.001790351,0.002227975,0.003452639,0.0027441632,0.0030762763,0.00046346668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.091232054,0.0011491361,0.04492232,0.0055272747,0.022338206,0.00069939194,0.0017060237,0.07680267,0.017864432,0.044837978,0.012530637,0.68038994],"study_design_scores_gemma":[0.038083535,0.01485734,0.056902714,0.0012308989,0.018349493,0.0018347484,0.00029012238,0.6062512,0.018115114,0.22219302,0.02125086,0.00064091914],"about_ca_topic_score_codex":0.00094043114,"about_ca_topic_score_gemma":0.0011728023,"teacher_disagreement_score":0.19160952,"about_ca_system_score_codex":0.0007728055,"about_ca_system_score_gemma":0.0019388831,"threshold_uncertainty_score":0.9968894},"labels":[],"label_agreement":null},{"id":"W2040052605","doi":"10.1016/j.nicl.2014.10.006","title":"48 echo T2 myelin imaging of white matter in first-episode schizophrenia: Evidence for aberrant myelination","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Alberta; University of British Columbia","funders":"","keywords":"Splenium; White matter; Psychosis; Schizophrenia (object-oriented programming); Corpus callosum; Psychology; Audiology; Myelin; Internal medicine; Physiology; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Central nervous system; Radiology","score_opus":0.13971360487475387,"score_gpt":0.437893839152159,"score_spread":0.29818023427740514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040052605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994886,0.00015546067,0.00016790174,0.000013982122,9.550237e-7,0.000002457413,0.000016141774,0.0000039876336,0.00015044746],"genre_scores_gemma":[0.9995097,0.00011428263,0.0002399183,0.000006829385,0.000002161021,0.0000019592694,0.000025213565,0.0000023636837,0.00009761641],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991024,0.000018759714,0.000011061088,0.000017152706,0.00002284012,0.000019913243],"domain_scores_gemma":[0.99960476,0.00009179739,0.00016971299,0.000027281369,0.000048042988,0.000058443922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004762169,0.00024416856,0.00013964406,0.0011000722,0.000270967,0.00028753834,0.00013454877,0.00032614058,0.0013678722],"category_scores_gemma":[0.0019302019,0.00022461332,0.0001062268,0.00027859138,0.00036411715,0.00038148626,0.00032788643,0.00017896568,0.00016254954],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016011087,0.00010861124,0.8387187,0.0001849618,0.00015795852,0.0040342836,0.0018159305,0.0003345101,0.12769386,0.00013684634,0.00016436698,0.025048874],"study_design_scores_gemma":[0.000014531967,0.00033556548,0.9854307,0.000012983633,0.00004103778,0.006600119,0.00052494655,0.0004732593,0.0062259985,0.00016591273,0.00016761891,0.0000071873587],"about_ca_topic_score_codex":0.0031281894,"about_ca_topic_score_gemma":0.0053536007,"teacher_disagreement_score":0.0031281894,"about_ca_system_score_codex":0.00018315724,"about_ca_system_score_gemma":0.00019187134,"threshold_uncertainty_score":0.006219983},"labels":[],"label_agreement":null},{"id":"W2040187618","doi":"10.1159/000103689","title":"Motor Fiber Distribution within the Cerebral Peduncle","year":2007,"lang":"en","type":"article","venue":"Confinia Neurologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Cerebral peduncle; Neuroscience; Medicine; Anatomy; Physical medicine and rehabilitation; Distribution (mathematics); Psychology; Radiology; Mathematics; Magnetic resonance imaging","score_opus":0.06084176426775483,"score_gpt":0.33440825758654874,"score_spread":0.2735664933187939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040187618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97693914,0.0031957673,0.009927519,0.00028254083,0.000026598978,0.00005017435,0.00035510605,0.00007640044,0.00914681],"genre_scores_gemma":[0.9913488,0.0013274101,0.0045041987,0.000043855824,0.00004695813,0.000033692093,0.0001221498,0.000014806825,0.0025582374],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998994,0.000015262956,0.0000070282185,0.000031029806,0.000022873048,0.000024363122],"domain_scores_gemma":[0.9995765,0.0001807208,0.000060403618,0.000037067977,0.00010744526,0.00003777349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031070854,0.0002497268,0.00018887252,0.0010483145,0.0005339091,0.0006852546,0.00027013305,0.0004211441,0.0021892118],"category_scores_gemma":[0.001039117,0.00013834311,0.00008001297,0.00063530507,0.00064610876,0.00088147714,0.000260567,0.00056659454,0.00044590287],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005012049,0.00030357155,0.16587538,0.001125041,0.00030442173,0.022162283,0.0031164475,0.0049427585,0.4457975,0.026481405,0.0032739236,0.3216053],"study_design_scores_gemma":[0.00012281013,0.0010633324,0.7539931,0.0004095487,0.00030469167,0.040874504,0.0020335251,0.016881524,0.15385126,0.011215257,0.019144485,0.00010608473],"about_ca_topic_score_codex":0.008676748,"about_ca_topic_score_gemma":0.0065063806,"teacher_disagreement_score":0.008676748,"about_ca_system_score_codex":0.000630683,"about_ca_system_score_gemma":0.0005774598,"threshold_uncertainty_score":0.017252445},"labels":[],"label_agreement":null},{"id":"W2040977327","doi":"10.1002/ajmg.a.33305","title":"Magnetic resonance imaging of a unique mutation in a family with Pelizaeus–Merzbacher disease","year":2010,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part A","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Leukodystrophy; Hypotonia; Magnetic resonance imaging; Dysarthria; Nystagmus; Spasticity; Medicine; Disease; Pathology; Internal medicine; Radiology","score_opus":0.020936927887984853,"score_gpt":0.33612421771584367,"score_spread":0.3151872898278588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040977327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913696,0.00070310925,0.0019196913,0.0013178013,0.00014221703,0.00006412321,0.00022498217,0.000094572504,0.004163977],"genre_scores_gemma":[0.9970408,0.00033512956,0.001166362,0.00028709337,0.00018808838,0.000018625242,0.000082556886,0.000024412288,0.0008569017],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9994869,0.000053233714,0.000055406486,0.00021767286,0.00008848402,0.00009823933],"domain_scores_gemma":[0.9990907,0.00033579342,0.00012954851,0.000038989732,0.00008180447,0.00032309495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042740974,0.0018925897,0.0010418415,0.0025747619,0.0016633138,0.00069025427,0.00081864867,0.00398266,0.0022777086],"category_scores_gemma":[0.0021246276,0.0007396209,0.00076886493,0.00070000195,0.0013287574,0.0008872658,0.0010860871,0.0015405825,0.00048078166],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050520972,0.000045844616,0.005481945,0.000018268034,0.000015736427,0.9867343,0.000602905,0.00014020722,0.0052288086,0.00017565727,0.000260528,0.0012453193],"study_design_scores_gemma":[0.00002179417,0.00015872261,0.014963061,0.000018955214,0.00004311708,0.9811397,0.00018429202,0.00050295127,0.0020395264,0.00017162284,0.0007328628,0.000023522432],"about_ca_topic_score_codex":0.0032176385,"about_ca_topic_score_gemma":0.002066225,"teacher_disagreement_score":0.00398266,"about_ca_system_score_codex":0.00087850227,"about_ca_system_score_gemma":0.0004996501,"threshold_uncertainty_score":0.007619679},"labels":[],"label_agreement":null},{"id":"W2041765815","doi":"10.1016/j.neuroimage.2011.02.043","title":"Distribution of collateral fibers in the monkey cervical spinal cord detected with diffusion-weighted magnetic resonance imaging","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Lundbeckfonden","keywords":"White matter; Diffusion MRI; Spinal cord; Magnetic resonance imaging; Fractional anisotropy; Anatomy; Nuclear magnetic resonance; Fiber bundle; Fiber; Chemistry; Materials science; Physics; Neuroscience; Medicine; Radiology; Biology","score_opus":0.03891913667255878,"score_gpt":0.29721808275488787,"score_spread":0.25829894608232906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041765815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954314,0.00077643275,0.0013414327,0.00012776056,0.000005383462,0.000013608352,0.00011876452,0.0000322411,0.0021530173],"genre_scores_gemma":[0.9938689,0.0009476492,0.0026252451,0.000033199976,0.000009631532,0.000030910178,0.000103598504,0.000012142987,0.0023688474],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999678,0.0000042469223,0.0000016122283,0.000010959608,0.0000071747686,0.00000819693],"domain_scores_gemma":[0.9997346,0.0000647949,0.000059464353,0.000034599354,0.000056868375,0.000049706417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013262963,0.0001734611,0.00014441236,0.00064504344,0.00044143407,0.0003752774,0.00015647455,0.00041510284,0.0017236868],"category_scores_gemma":[0.0004867743,0.0001715892,0.00009243453,0.00030432304,0.00045794432,0.00051990664,0.00024381309,0.0004953277,0.00028903104],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085310306,0.000098214514,0.008040133,0.00020624325,0.00003747668,0.0015912588,0.0003342798,0.00038323432,0.9703892,0.0011218893,0.0002938669,0.016651014],"study_design_scores_gemma":[0.00021974204,0.0033875045,0.43574333,0.00021225741,0.00026790617,0.013982285,0.0014511166,0.011722163,0.52136135,0.0048910845,0.0066937157,0.00006753482],"about_ca_topic_score_codex":0.006540876,"about_ca_topic_score_gemma":0.008172454,"teacher_disagreement_score":0.006540876,"about_ca_system_score_codex":0.0003447973,"about_ca_system_score_gemma":0.00051663164,"threshold_uncertainty_score":0.013005614},"labels":[],"label_agreement":null},{"id":"W2041846560","doi":"10.1016/j.jradio.2012.02.019","title":"Tractographie du nerf médian à 3T : optimisation des paramètres d’acquisition et mesure des paramètres de diffusivité","year":2012,"lang":"fr","type":"article","venue":"Journal de radiologie diagnostique et interventionnelle","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.09967813379439042,"score_gpt":0.40383946021281664,"score_spread":0.3041613264184262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041846560","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48225886,0.003067992,0.5005428,0.0011928136,0.00012002312,0.00025867208,0.003298924,0.004455795,0.004804076],"genre_scores_gemma":[0.70209086,0.0016449102,0.29066524,0.00013684205,0.00007890416,0.00032913126,0.0010692887,0.0014576523,0.0025271953],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973255,0.000076202574,0.000028178314,0.00006866232,0.00006686178,0.00002762239],"domain_scores_gemma":[0.99898607,0.00054363697,0.00009760882,0.00007271112,0.00023445372,0.00006544552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085233967,0.001066226,0.0007520571,0.0015437683,0.0006275992,0.0018405548,0.0003877651,0.0016131026,0.0050007277],"category_scores_gemma":[0.0037431864,0.0005589134,0.0007392143,0.001075528,0.0003537963,0.0010981576,0.00041314552,0.0006842186,0.00094654295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003207987,0.00015251488,0.036279883,0.0011682368,0.0005346867,0.0021538013,0.0011631752,0.09147191,0.49426493,0.0022567867,0.004486607,0.36285952],"study_design_scores_gemma":[0.00027748512,0.00086934114,0.1804119,0.0003944186,0.0007757495,0.010948501,0.00097008224,0.42831057,0.34854957,0.005945652,0.022069393,0.0004774293],"about_ca_topic_score_codex":0.017198626,"about_ca_topic_score_gemma":0.01769098,"teacher_disagreement_score":0.017198626,"about_ca_system_score_codex":0.00057626836,"about_ca_system_score_gemma":0.0016049317,"threshold_uncertainty_score":0.034197032},"labels":[],"label_agreement":null},{"id":"W2042245762","doi":"10.1016/j.schres.2010.03.027","title":"Disrupted integrity of the fornix in first-episode schizophrenia","year":2010,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research","keywords":"Fornix; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychosis; Stage (stratigraphy); Medicine; Psychology; Internal medicine; Psychiatry; Diffusion MRI; Magnetic resonance imaging; Radiology; Hippocampus; Biology","score_opus":0.11892978607288768,"score_gpt":0.426580314473805,"score_spread":0.30765052840091733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042245762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960141,0.0013499105,0.00062499795,0.00039001807,0.000021425703,0.000012133343,0.0001451485,0.000015181539,0.0014271697],"genre_scores_gemma":[0.99870026,0.00044187676,0.00039508528,0.00004665673,0.00001188697,0.0000064520623,0.000058679645,0.000007634137,0.00033139763],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998901,0.00002577749,0.0000094948355,0.000018431303,0.000028018907,0.000028125725],"domain_scores_gemma":[0.99936765,0.00007845748,0.0003552241,0.00006443295,0.000051862426,0.00008234948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043626656,0.00048769952,0.00041672983,0.0010694314,0.0006576038,0.00082216936,0.00055911083,0.00081464136,0.0022642983],"category_scores_gemma":[0.0015901861,0.00039001188,0.0001648369,0.00053304364,0.0010454685,0.0009372588,0.00046418468,0.0007687195,0.00018175539],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010219797,0.00038453672,0.36509606,0.0008818417,0.00087500334,0.012789947,0.0032378568,0.0038583842,0.5179043,0.0036383101,0.0019416759,0.07917232],"study_design_scores_gemma":[0.000081303595,0.00039220002,0.972064,0.000053086802,0.00010641603,0.00536193,0.0008669886,0.0012341681,0.015501128,0.0037427736,0.0005663268,0.000029646779],"about_ca_topic_score_codex":0.008612657,"about_ca_topic_score_gemma":0.009800401,"teacher_disagreement_score":0.008612657,"about_ca_system_score_codex":0.0007898272,"about_ca_system_score_gemma":0.0007173992,"threshold_uncertainty_score":0.01712507},"labels":[],"label_agreement":null},{"id":"W2042564460","doi":"10.1002/mrm.22131","title":"Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent <i>T</i><sub>2</sub> relaxometry: A unified view via a four‐pool model","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Relaxometry; Magnetization transfer; White matter; Magnetization; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Relaxation (psychology); Physics; Magnetic field; Spin echo; Neuroscience; Radiology; Medicine","score_opus":0.06480513998380737,"score_gpt":0.3337138529243339,"score_spread":0.26890871294052654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042564460","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28924417,0.0008225926,0.707738,0.00035676613,0.000019357667,0.00008056731,0.00014314774,0.00037700456,0.0012184314],"genre_scores_gemma":[0.8603639,0.0010304175,0.13661036,0.00011637989,0.000025214518,0.00022533568,0.00014522966,0.00008652637,0.001396708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99984455,0.000047224843,0.000008809893,0.000050731924,0.000030617608,0.000018019911],"domain_scores_gemma":[0.9996902,0.00014305102,0.00006475403,0.000056923258,0.000025372,0.000019791341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008518337,0.00088930305,0.0005536268,0.00060097297,0.00018500882,0.0010189629,0.0009596115,0.0011252944,0.0003643986],"category_scores_gemma":[0.001528553,0.00045257807,0.00065239455,0.0003156192,0.0011193377,0.0018013616,0.0006456182,0.0004509204,0.00012415726],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015074195,0.00008021511,0.0024438673,0.00013607249,0.00008430244,0.0001832156,0.00014618036,0.76572406,0.20189196,0.0139134135,0.00021423177,0.015031792],"study_design_scores_gemma":[0.000010947756,0.00008012518,0.00091916515,0.000005469711,0.000022179962,0.000053366224,0.000020641648,0.97568125,0.01455968,0.008358242,0.00026477483,0.00002420366],"about_ca_topic_score_codex":0.0018816664,"about_ca_topic_score_gemma":0.0010682207,"teacher_disagreement_score":0.0018816664,"about_ca_system_score_codex":0.000670812,"about_ca_system_score_gemma":0.0005565332,"threshold_uncertainty_score":0.004867077},"labels":[],"label_agreement":null},{"id":"W2042794599","doi":"10.1117/12.2043103","title":"Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deconvolution; Isotropy; Diffusion MRI; Blind deconvolution; Image resolution; Computer science; Resolution (logic); Angular resolution (graph drawing); Artificial intelligence; Physics; Algorithm; Optics; Mathematics","score_opus":0.02265219539031553,"score_gpt":0.2706733839628472,"score_spread":0.24802118857253164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042794599","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015542485,0.00013439044,0.98373574,0.00006132849,0.000010353398,0.000011062371,0.000024671213,0.0001436922,0.00033619924],"genre_scores_gemma":[0.21838653,0.00078791234,0.7790691,0.000058687543,0.0000393465,0.000044871907,0.0001801872,0.00008503312,0.0013483339],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974555,0.00007451914,0.000018562696,0.000053384465,0.00008340615,0.000024510235],"domain_scores_gemma":[0.9994425,0.00021262528,0.00010107404,0.00011590108,0.00009547456,0.000032424254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007703342,0.00065157085,0.0005261658,0.00057178474,0.00025050112,0.00067623844,0.00051666953,0.0006512046,0.0005699076],"category_scores_gemma":[0.0022076597,0.0003300992,0.00053943926,0.0006626965,0.0008139206,0.0011042904,0.0010767464,0.0007024639,0.0003645395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003167531,0.00006323111,0.0029919068,0.000445422,0.0002165229,0.0006281769,0.00045663412,0.25073966,0.3685637,0.055800464,0.0015256106,0.318252],"study_design_scores_gemma":[0.000012182504,0.00006561331,0.0010686856,0.000012974826,0.00003003014,0.0005250482,0.00003598795,0.9456964,0.036787786,0.013290791,0.0024390072,0.0000353801],"about_ca_topic_score_codex":0.0021125558,"about_ca_topic_score_gemma":0.003579355,"teacher_disagreement_score":0.0021125558,"about_ca_system_score_codex":0.00028256373,"about_ca_system_score_gemma":0.0009308032,"threshold_uncertainty_score":0.004200518},"labels":[],"label_agreement":null},{"id":"W2043236948","doi":"10.1118/1.4811155","title":"Gray matter parcellation constrained full brain fiber bundling with diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Diffusion MRI; Bundle; Fiber bundle; Computer science; Cluster analysis; Artificial intelligence; Segmentation; Tractography; Consistency (knowledge bases); Pattern recognition (psychology); Computer vision; Medicine; Magnetic resonance imaging","score_opus":0.02028938762671474,"score_gpt":0.29402567756381554,"score_spread":0.2737362899371008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043236948","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022761475,0.00014063029,0.9760296,0.000062253384,0.000015849297,0.000059281374,0.00004877948,0.00061366754,0.00026861898],"genre_scores_gemma":[0.109561905,0.00013755006,0.8888061,0.000031372,0.000021266424,0.00010573389,0.0003339018,0.00026323125,0.00073896383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994935,0.00012055098,0.000038669594,0.00014400501,0.00016431199,0.000038896877],"domain_scores_gemma":[0.9987708,0.00026390323,0.00032209913,0.00021710468,0.00032019414,0.00010601351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016882585,0.0012287662,0.00091559155,0.0019022307,0.0007815806,0.0010073311,0.00095865934,0.0007429035,0.0011220777],"category_scores_gemma":[0.003263676,0.00064005767,0.0011511347,0.0014138732,0.00065876206,0.0014885716,0.0010589528,0.0009782386,0.00054859975],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021843315,0.00015781117,0.003060596,0.00023360086,0.0002196001,0.00021416048,0.00056440727,0.497292,0.080708966,0.015113746,0.003445104,0.3987716],"study_design_scores_gemma":[0.000008337682,0.000041987376,0.00066636596,0.0000099273275,0.000022921071,0.000057757865,0.000019405315,0.9859271,0.008524263,0.0035683515,0.0011346808,0.000019031271],"about_ca_topic_score_codex":0.0075074714,"about_ca_topic_score_gemma":0.008672484,"teacher_disagreement_score":0.0075074714,"about_ca_system_score_codex":0.00083685905,"about_ca_system_score_gemma":0.0017816952,"threshold_uncertainty_score":0.014927566},"labels":[],"label_agreement":null},{"id":"W2043379623","doi":"10.1155/2008/789539","title":"The Connectivity of the Human Pulvinar: A Diffusion Tensor Imaging Tractography Study","year":2007,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Superior colliculus; Neuroscience; Diffusion MRI; Tractography; Thalamus; Human brain; Visual cortex; Lateral geniculate nucleus; Visual system; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.03121094351563305,"score_gpt":0.39334704502979956,"score_spread":0.36213610151416653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043379623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9802028,0.0007005844,0.01691756,0.00020912343,0.000008696565,0.00005176459,0.00029631527,0.00008558591,0.0015275459],"genre_scores_gemma":[0.9915929,0.00036292613,0.0074245827,0.000032297314,0.00001055323,0.000020913258,0.00015302662,0.00001769671,0.0003851507],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998535,0.00002867481,0.000011672463,0.00006607782,0.00002561369,0.000014424624],"domain_scores_gemma":[0.9995003,0.00023824522,0.00008811939,0.000099708566,0.000043977103,0.000029626992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044044355,0.00020271444,0.00021151638,0.0011808173,0.0002531764,0.00053000764,0.00023190808,0.00039373976,0.0018954363],"category_scores_gemma":[0.001862635,0.0002219264,0.00019414797,0.0005517743,0.00078915764,0.00061389187,0.00022626214,0.00018990293,0.00028848182],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009098499,0.00033682174,0.33352005,0.00064144813,0.0006019415,0.026009677,0.009756724,0.013676461,0.31682536,0.014667388,0.0029245235,0.2801298],"study_design_scores_gemma":[0.000070726586,0.0004190234,0.8687722,0.00008479358,0.00019939963,0.042470284,0.00096178014,0.051273484,0.017800624,0.008220413,0.009642391,0.00008483298],"about_ca_topic_score_codex":0.0058650575,"about_ca_topic_score_gemma":0.008170171,"teacher_disagreement_score":0.0058650575,"about_ca_system_score_codex":0.00039510822,"about_ca_system_score_gemma":0.0005421589,"threshold_uncertainty_score":0.011661887},"labels":[],"label_agreement":null},{"id":"W2043948336","doi":"10.1001/jamapsychiatry.2013.865","title":"APOE ϵ 4, Aging, and Effects on White Matter Across the Adult Life Span","year":2013,"lang":"en","type":"letter","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Family medicine; Neurology; Otorhinolaryngology; Subspecialty; Psychiatry; Gerontology","score_opus":0.0173784978577727,"score_gpt":0.31277386654120337,"score_spread":0.2953953686834307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043948336","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6579183,0.01610858,0.00035148463,0.2711761,0.003166341,0.000052624513,0.002721831,0.0002184546,0.048286393],"genre_scores_gemma":[0.9161807,0.00832777,0.000791848,0.04552622,0.005832482,0.00006206221,0.0005637256,0.00004102026,0.022674156],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998666,0.00003127892,0.000021639924,0.000020873185,0.000037726986,0.000021764354],"domain_scores_gemma":[0.9995696,0.00018667149,0.000070699425,0.000023618144,0.00008437487,0.00006503689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034720576,0.00021822874,0.0003147928,0.000627085,0.0006852223,0.000472678,0.00022189085,0.0015801829,0.004312349],"category_scores_gemma":[0.0020803954,0.00011332252,0.00025757335,0.0007726818,0.00031831712,0.0004646057,0.00016563099,0.00092560315,0.00080307556],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019531844,0.00032013727,0.6648438,0.00015615777,0.00015142634,0.033359792,0.00081216526,0.00016039358,0.0017867382,0.001388939,0.19310474,0.10196258],"study_design_scores_gemma":[0.00022481156,0.00044630395,0.9161997,0.0003406619,0.00019460829,0.03223671,0.0006360167,0.00066879607,0.0006472335,0.0055159605,0.042856917,0.00003240259],"about_ca_topic_score_codex":0.010956343,"about_ca_topic_score_gemma":0.01456231,"teacher_disagreement_score":0.010956343,"about_ca_system_score_codex":0.00067619106,"about_ca_system_score_gemma":0.00045697083,"threshold_uncertainty_score":0.02178514},"labels":[],"label_agreement":null},{"id":"W2044093652","doi":"10.1109/isbi.2014.6868055","title":"A preliminary study on the effect of motion correction on HARDI reconstruction","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Calgary; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering","keywords":"Interpolation (computer graphics); Diffusion MRI; Motion (physics); Orientation (vector space); Diffusion; Voxel; Computer vision; Computer science; Artificial intelligence; Volume (thermodynamics); Fiber; Diffusion imaging; Mathematics; Physics; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.03671896397938755,"score_gpt":0.3329350652472624,"score_spread":0.29621610126787484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044093652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6053868,0.0062265303,0.37900984,0.0010009459,0.0005430956,0.00048791163,0.0014975214,0.00204575,0.0038016848],"genre_scores_gemma":[0.6811337,0.0022009888,0.31018138,0.00033870563,0.00012693337,0.00017090724,0.0022831333,0.0008886914,0.0026755354],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979802,0.000879293,0.00022073687,0.00033339905,0.00043257148,0.0001539006],"domain_scores_gemma":[0.9792165,0.013888871,0.0010632405,0.0028423483,0.0026944173,0.0002947107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040804744,0.0013679054,0.00073180534,0.00067392935,0.00073088176,0.0009487808,0.00078518427,0.0012580617,0.003647737],"category_scores_gemma":[0.035754826,0.00032416164,0.0006574089,0.0009186622,0.00064379635,0.0009237015,0.0009213818,0.00077386264,0.000739135],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007743727,0.00085289514,0.018314645,0.00326154,0.00064767315,0.0021252858,0.0009768509,0.15302886,0.38612866,0.0033296065,0.0051214746,0.4184687],"study_design_scores_gemma":[0.00037221832,0.0052143135,0.04176017,0.00061218924,0.00071199,0.004803163,0.0005738733,0.50043553,0.42053035,0.003046076,0.021653902,0.00028621498],"about_ca_topic_score_codex":0.0033525736,"about_ca_topic_score_gemma":0.0035727166,"teacher_disagreement_score":0.0040804744,"about_ca_system_score_codex":0.00029747168,"about_ca_system_score_gemma":0.00060444657,"threshold_uncertainty_score":0.021579862},"labels":[],"label_agreement":null},{"id":"W2044166387","doi":"10.1016/j.pscychresns.2014.12.004","title":"Comparison of grey matter volume and thickness for analysing cortical changes in chronic schizophrenia: A matter of surface area, grey/white matter intensity contrast, and curvature","year":2014,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Dietmar Hopp Stiftung","keywords":"Grey matter; White matter; Magnetic resonance imaging; Voxel-based morphometry; Volume (thermodynamics); Grey level; Anatomy; Psychology; Medicine; Physics; Radiology; Optics","score_opus":0.08532282439859742,"score_gpt":0.4130633234266466,"score_spread":0.32774049902804914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044166387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950191,0.00059253455,0.0035653205,0.000034599107,0.000012980829,0.000035183366,0.00018765847,0.000050517618,0.0005020545],"genre_scores_gemma":[0.9947883,0.00018979429,0.0046671117,0.000011309483,0.000012091961,0.00002227,0.00009015713,0.00002365814,0.00019532138],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992544,0.0002987504,0.00008706927,0.00009012095,0.0002157537,0.000053887732],"domain_scores_gemma":[0.9970252,0.0015897263,0.00046453092,0.00023286974,0.00046197078,0.00022568852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032879284,0.0005042518,0.00043332635,0.0025082033,0.0002616417,0.0010892132,0.00036449902,0.0006176838,0.00075298746],"category_scores_gemma":[0.005390084,0.00031245284,0.0004689141,0.0010218794,0.000539292,0.0010773969,0.000613011,0.00042590426,0.0001307213],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019330133,0.00018888857,0.6872047,0.00054290966,0.0014662454,0.0005915154,0.0014434459,0.004331963,0.17318504,0.000809171,0.00038162837,0.1105243],"study_design_scores_gemma":[0.00011030839,0.0016460326,0.9629973,0.00005252228,0.00031731557,0.0015765539,0.00074706186,0.01608048,0.015184702,0.00087866967,0.0003312199,0.00007774054],"about_ca_topic_score_codex":0.0021317971,"about_ca_topic_score_gemma":0.0047675055,"teacher_disagreement_score":0.0032879284,"about_ca_system_score_codex":0.00035049673,"about_ca_system_score_gemma":0.0003870962,"threshold_uncertainty_score":0.017388403},"labels":[],"label_agreement":null},{"id":"W2044271030","doi":"10.1016/j.mri.2007.03.010","title":"Efficacy of motion artifact reduction in neonatal DW segmented EPI at 3 T using phase correction by numerical optimization and segment data swapping","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Lawson Health Research Institute","funders":"","keywords":"Percentile; Artifact (error); Diffusion MRI; Noise (video); Noise reduction; Nuclear medicine; Population; Reduction (mathematics); Distortion (music); Mathematics; Medicine; Artificial intelligence; Computer science; Magnetic resonance imaging; Radiology; Image (mathematics); Statistics","score_opus":0.04959400590207793,"score_gpt":0.36294686813294436,"score_spread":0.31335286223086645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044271030","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74499434,0.0014203258,0.24978893,0.00032726393,0.00006507356,0.000091236645,0.00024559489,0.00096995995,0.0020972914],"genre_scores_gemma":[0.8769199,0.00041676135,0.120933995,0.00007919937,0.000022866743,0.00009063348,0.00032511045,0.00036666013,0.00084488234],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972576,0.00014419737,0.000024348114,0.0000360953,0.000049550737,0.000020031937],"domain_scores_gemma":[0.9986205,0.0009130431,0.00011537495,0.00013856366,0.00016334672,0.000049217022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013180276,0.000504441,0.00039171043,0.00032549107,0.00023181459,0.00047003946,0.00037134296,0.00054633507,0.0009783729],"category_scores_gemma":[0.006592957,0.00026349645,0.0002368097,0.000278615,0.00029352616,0.0005632809,0.0004135642,0.00034188025,0.00023423227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011819627,0.00055942533,0.0065571107,0.0005642462,0.0002801434,0.00033276257,0.00048201703,0.09844072,0.49388734,0.002044824,0.0012004814,0.38383126],"study_design_scores_gemma":[0.00027999966,0.002015665,0.017269732,0.00004866778,0.00034133342,0.0008949817,0.00008181852,0.449998,0.5258129,0.0015060437,0.0016822857,0.00006863309],"about_ca_topic_score_codex":0.00083434343,"about_ca_topic_score_gemma":0.00093606213,"teacher_disagreement_score":0.0013180276,"about_ca_system_score_codex":0.00015810029,"about_ca_system_score_gemma":0.00068562006,"threshold_uncertainty_score":0.006970465},"labels":[],"label_agreement":null},{"id":"W2044697134","doi":"10.1002/mrm.22971","title":"Results for diffusion‐weighted imaging with a fourth‐channel gradient insert","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Alberta","funders":"","keywords":"SIGNAL (programming language); Diffusion; Noise (video); Signal-to-noise ratio (imaging); Nuclear magnetic resonance; Insert (composites); Gradient echo; Image quality; Imaging phantom; Physics; Spin echo; Diffusion MRI; Acoustics; Optics; Materials science; Magnetic resonance imaging; Computer science; Image (mathematics); Artificial intelligence; Medicine","score_opus":0.0636049603211421,"score_gpt":0.3142896367512062,"score_spread":0.2506846764300641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044697134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6002948,0.0028845435,0.36323223,0.0011651403,0.00021561213,0.0016372736,0.004977551,0.004216369,0.021376394],"genre_scores_gemma":[0.76134175,0.0014444845,0.21479538,0.00042844116,0.00007724826,0.0017935418,0.005702218,0.0017006388,0.012716321],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984213,0.00041261318,0.00015585193,0.00022309007,0.000611582,0.00017560576],"domain_scores_gemma":[0.9960372,0.0016801716,0.00023323855,0.00049509853,0.0014072498,0.00014714268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003402105,0.0009921734,0.00079001277,0.00046150797,0.00056739623,0.0008462628,0.0007220866,0.0009858209,0.009937414],"category_scores_gemma":[0.006652315,0.00051849446,0.0006220906,0.00036734677,0.00050161825,0.00091091794,0.00041066646,0.0004975755,0.0024353063],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012128874,0.0017239765,0.025305228,0.002760994,0.00075503235,0.0016458881,0.0016679023,0.015836453,0.7691803,0.004687711,0.011405406,0.15290226],"study_design_scores_gemma":[0.0005487883,0.0045050494,0.03312529,0.0001803223,0.0010471671,0.0049371384,0.0003499802,0.019908905,0.8812522,0.0018898796,0.05201569,0.0002396499],"about_ca_topic_score_codex":0.0027039459,"about_ca_topic_score_gemma":0.0015156643,"teacher_disagreement_score":0.009937414,"about_ca_system_score_codex":0.00048238438,"about_ca_system_score_gemma":0.00055434095,"threshold_uncertainty_score":0.033243954},"labels":[],"label_agreement":null},{"id":"W2045092603","doi":"10.1109/isbi.2012.6235604","title":"Diffusion tensor image processing using biquaternions","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Convolution (computer science); Diffusion MRI; Fourier transform; Image processing; Computer science; Artificial intelligence; Tensor (intrinsic definition); Quaternion; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Image (mathematics); Mathematical analysis; Magnetic resonance imaging; Geometry; Artificial neural network","score_opus":0.12843603228419348,"score_gpt":0.4108350481169518,"score_spread":0.28239901583275834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045092603","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010887423,0.00023139802,0.99740654,0.00019731176,0.00006244729,0.00001663919,0.00008008792,0.00016745104,0.0007493297],"genre_scores_gemma":[0.071295716,0.0023542282,0.9199758,0.00025922997,0.00025309913,0.00016230709,0.0004964707,0.00030438675,0.0048987754],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939144,0.00017587918,0.00006777857,0.00011985274,0.00020715117,0.000037903177],"domain_scores_gemma":[0.9993716,0.00014378066,0.0001328661,0.00013486361,0.00017756032,0.000039412887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000989831,0.0012509753,0.0009234973,0.0009866703,0.00050549174,0.0017664159,0.0012634346,0.0011338395,0.0031730887],"category_scores_gemma":[0.0021275207,0.00046039518,0.0010646264,0.0017147011,0.00090868404,0.0034763073,0.001308868,0.0017134283,0.0019089953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056552635,0.000054198605,0.0006259917,0.00037637062,0.00016845117,0.00034694994,0.00029358827,0.32628137,0.043100435,0.4569887,0.010788069,0.16091928],"study_design_scores_gemma":[0.0000104589735,0.000052431744,0.00029680863,0.000030641906,0.000024766745,0.00018536765,0.000024618128,0.8705085,0.0059151733,0.101850174,0.021048892,0.000052219417],"about_ca_topic_score_codex":0.00281451,"about_ca_topic_score_gemma":0.0029685434,"teacher_disagreement_score":0.0031730887,"about_ca_system_score_codex":0.0005968258,"about_ca_system_score_gemma":0.00086923776,"threshold_uncertainty_score":0.010614991},"labels":[],"label_agreement":null},{"id":"W2045137447","doi":"10.1016/j.nicl.2013.04.006","title":"Evaluation of white matter myelin water fraction in chronic stroke","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Myelin; Internal capsule; Stroke (engine); Fractional anisotropy; Multiple sclerosis; Cerebrum; Internal medicine; Neuroscience; Medicine; Pathology; Psychology; Magnetic resonance imaging; Central nervous system; Radiology; Physics; Immunology","score_opus":0.16892122773044577,"score_gpt":0.4599771192522647,"score_spread":0.29105589152181893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045137447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994413,0.00018383568,0.00020790946,0.000003093838,7.449525e-7,0.000010542654,0.000041024763,0.0000042031393,0.000107349],"genre_scores_gemma":[0.9990396,0.00018130509,0.000414798,0.0000071726354,0.0000033505826,0.000024613073,0.00014351498,0.0000020306077,0.00018362672],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998512,0.000035180074,0.0000214172,0.00003549219,0.00003099743,0.00002563565],"domain_scores_gemma":[0.99959785,0.000059647387,0.00016663178,0.000034500263,0.00008747629,0.000053939577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004940133,0.00028238277,0.00031750303,0.0010129677,0.00024580758,0.00022767136,0.00012096228,0.00027690956,0.0005171411],"category_scores_gemma":[0.000990926,0.0001438497,0.00009795115,0.00048786617,0.00027776443,0.00020029822,0.00026821368,0.000126494,0.00014785765],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042687617,0.0003787307,0.8606705,0.00022659452,0.00020013952,0.00060337473,0.00080381625,0.00036247532,0.09006781,0.000045988647,0.00018321034,0.042188622],"study_design_scores_gemma":[0.000017441967,0.0015470532,0.9932493,0.000007817509,0.00003139572,0.0005115515,0.00012755275,0.0003771135,0.0039591626,0.000037116493,0.0001263134,0.000008239897],"about_ca_topic_score_codex":0.002268169,"about_ca_topic_score_gemma":0.0030930089,"teacher_disagreement_score":0.002268169,"about_ca_system_score_codex":0.00017337842,"about_ca_system_score_gemma":0.00017555397,"threshold_uncertainty_score":0.0045099854},"labels":[],"label_agreement":null},{"id":"W2045141677","doi":"10.1097/wno.0b013e3181a58ef8","title":"Combined Functional MRI and Diffusion Tensor Imaging Analysis of Visual Motion Pathways","year":2009,"lang":"en","type":"article","venue":"Journal of Neuro-Ophthalmology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Tractography; Superior colliculus; Thalamus; Neuroscience; Diffusion MRI; Visual cortex; Visual system; White matter; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.05239082641162501,"score_gpt":0.3446779752253634,"score_spread":0.2922871488137384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045141677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95230705,0.0014204787,0.04384461,0.00020758202,0.00001521517,0.00008445843,0.00044825918,0.00014457549,0.0015276805],"genre_scores_gemma":[0.9650192,0.0005671596,0.033433728,0.00003418176,0.00003704293,0.000046508347,0.0002607187,0.000025241627,0.000576251],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998832,0.000026965692,0.000012770642,0.00003327374,0.000029783669,0.000014057609],"domain_scores_gemma":[0.999731,0.0000624555,0.000066447275,0.00003540966,0.00007041368,0.00003418111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055044866,0.00047528444,0.00023577744,0.0020004734,0.00017271626,0.00038361165,0.0002177754,0.00031211937,0.001784743],"category_scores_gemma":[0.0009822624,0.0002052825,0.0002734436,0.00048620903,0.00024115713,0.0005164694,0.00028759375,0.00020813795,0.00025724375],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001235697,0.00017890088,0.083347335,0.00063154835,0.0007214871,0.0016723757,0.00040358794,0.002780948,0.7069898,0.0011436827,0.00083443045,0.20006016],"study_design_scores_gemma":[0.00022820717,0.0014386636,0.77672994,0.00016601948,0.00084927917,0.023618283,0.00044974958,0.060861543,0.12456174,0.006749134,0.004222455,0.00012499081],"about_ca_topic_score_codex":0.0014076695,"about_ca_topic_score_gemma":0.0038734826,"teacher_disagreement_score":0.0020004734,"about_ca_system_score_codex":0.0001780469,"about_ca_system_score_gemma":0.00021952012,"threshold_uncertainty_score":0.0059705377},"labels":[],"label_agreement":null},{"id":"W2045419273","doi":"10.1016/j.jneumeth.2009.08.022","title":"Visualizing the entire cortical myelination pattern in marmosets with magnetic resonance imaging","year":2009,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Institutes of Health","keywords":"Marmoset; Callithrix; Neuroscience; Visual cortex; Myelin; Cortex (anatomy); Gyrus; Biology; Cerebral cortex; Neuroplasticity; Temporal cortex; Auditory cortex; Primate; Central nervous system","score_opus":0.08844842152530552,"score_gpt":0.47037164696912986,"score_spread":0.38192322544382434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045419273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98902124,0.00039106378,0.009383517,0.00008833154,0.000005237048,0.0000124737835,0.000055571614,0.000053905533,0.0009886905],"genre_scores_gemma":[0.9852683,0.00030461597,0.013820271,0.000038065904,0.00000859101,0.000013417758,0.00004878268,0.000023838897,0.0004740632],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99995065,0.000010883958,0.000004365201,0.000010641529,0.000010927192,0.000012455667],"domain_scores_gemma":[0.9998523,0.000031471976,0.000036812893,0.000020840525,0.000023088167,0.000035438894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002703018,0.000174829,0.0001234393,0.0006994438,0.00028245844,0.00033061008,0.00020472035,0.00047357933,0.00067649694],"category_scores_gemma":[0.0005857412,0.00021555074,0.00011000111,0.00023621845,0.00020936901,0.00048839103,0.00043296217,0.00039889262,0.00011666253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042120545,0.000033059583,0.0061179893,0.00008751696,0.000057903242,0.0012985034,0.00028203256,0.0010221155,0.9704399,0.0006266445,0.00012964263,0.019483402],"study_design_scores_gemma":[0.00011693817,0.0013773121,0.3749553,0.00014121062,0.00036612997,0.03572459,0.0014410653,0.028297056,0.54182523,0.0101357205,0.005500601,0.00011884404],"about_ca_topic_score_codex":0.0009965668,"about_ca_topic_score_gemma":0.0013409709,"teacher_disagreement_score":0.0009965668,"about_ca_system_score_codex":0.00009744565,"about_ca_system_score_gemma":0.00020591117,"threshold_uncertainty_score":0.0022630692},"labels":[],"label_agreement":null},{"id":"W2045560368","doi":"10.1002/mrm.20777","title":"Diffusion tensor spectroscopy (DTS) of human brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Metabolite; Phosphocreatine; Chemistry; Nuclear magnetic resonance; Creatine; Effective diffusion coefficient; Human brain; Magnetic resonance imaging; Physics; Biology; Neuroscience; Medicine; Biochemistry; Endocrinology","score_opus":0.04192396674393264,"score_gpt":0.3738882482614556,"score_spread":0.331964281517523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045560368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7342352,0.020228807,0.20597991,0.0022073926,0.00035886405,0.0002908654,0.0119907735,0.0013297244,0.023378337],"genre_scores_gemma":[0.84677124,0.014534891,0.12769492,0.0004549365,0.00017957986,0.00017569767,0.00368459,0.00018610274,0.0063180206],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998913,0.00002359472,0.00001297954,0.00003501539,0.000027180102,0.000009935343],"domain_scores_gemma":[0.9997335,0.000038957416,0.0000805447,0.000042440024,0.00008424349,0.000020292884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047596,0.0003715023,0.00018329508,0.0009113212,0.0002536814,0.00044644088,0.00018445766,0.00039133738,0.0015717264],"category_scores_gemma":[0.0013844328,0.00017520682,0.00023375172,0.0011975841,0.0002520038,0.0005818426,0.00021410648,0.00022700246,0.0006385259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004604416,0.000056812147,0.021677723,0.0017260065,0.0003453584,0.0011809786,0.00073248317,0.003939778,0.62123716,0.0072404793,0.013091847,0.32831097],"study_design_scores_gemma":[0.00013807489,0.0013453397,0.39270708,0.00035467042,0.0006094747,0.022752808,0.00076408376,0.045523066,0.30545405,0.042517107,0.18752679,0.00030747225],"about_ca_topic_score_codex":0.0025433577,"about_ca_topic_score_gemma":0.004014472,"teacher_disagreement_score":0.0025433577,"about_ca_system_score_codex":0.00023914357,"about_ca_system_score_gemma":0.0005000605,"threshold_uncertainty_score":0.0052579045},"labels":[],"label_agreement":null},{"id":"W2045674645","doi":"10.1016/j.neuroimage.2010.11.089","title":"Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":240,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Institut pour la Recherche sur la Moelle épinière et l'Encéphale","keywords":"Fractional anisotropy; Magnetization transfer; Diffusion MRI; White matter; Spinal cord; Magnetic resonance imaging; Atrophy; Spinal cord injury; Medicine; Nuclear magnetic resonance; Nuclear medicine; Pathology; Radiology; Physics","score_opus":0.07255519224948061,"score_gpt":0.3258924484806467,"score_spread":0.2533372562311661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045674645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937925,0.00336828,0.0016588862,0.00007309444,0.000008989709,0.000031260417,0.000067604466,0.000014220281,0.0009851591],"genre_scores_gemma":[0.99615085,0.0014121322,0.0011877314,0.000046391313,0.000017472645,0.000021356016,0.000060520164,0.000005339803,0.0010982616],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999242,0.000021834236,0.000007991694,0.000014347824,0.000017291351,0.000014370665],"domain_scores_gemma":[0.99979,0.000055242344,0.00005560716,0.000023913126,0.000044661076,0.00003052454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037942038,0.0002771465,0.00019058079,0.0010904663,0.0002769893,0.0003845222,0.00018139198,0.00058643724,0.0012817748],"category_scores_gemma":[0.0010276508,0.00025102735,0.00012098859,0.0003912803,0.0006417062,0.0006242629,0.00030933856,0.000349087,0.00023897034],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008008275,0.00023203682,0.022310149,0.00073636055,0.00018114736,0.006482362,0.0009585468,0.00063779193,0.92287683,0.0006866676,0.0002941874,0.036595654],"study_design_scores_gemma":[0.000797431,0.0051638423,0.5823691,0.00016309811,0.0005136402,0.050697807,0.0018937412,0.0050347038,0.34495276,0.00315889,0.0051440517,0.00011092379],"about_ca_topic_score_codex":0.0014885446,"about_ca_topic_score_gemma":0.0012125925,"teacher_disagreement_score":0.0014885446,"about_ca_system_score_codex":0.00012406425,"about_ca_system_score_gemma":0.00020138669,"threshold_uncertainty_score":0.004287958},"labels":[],"label_agreement":null},{"id":"W2046091688","doi":"10.1159/000356219","title":"Improved Frontoparietal White Matter Integrity in Overweight Children Is Associated with Attendance at an After-School Exercise Program","year":2014,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Population and Public Health","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Science Foundation","keywords":"Overweight; Attendance; Aerobic exercise; Medicine; Physical therapy; Intervention (counseling); Cardiovascular fitness; Psychology; Obesity; Physical fitness; Psychiatry; Internal medicine","score_opus":0.01956911779889504,"score_gpt":0.29149615676303087,"score_spread":0.27192703896413584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046091688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997886,0.000059901464,0.000024142695,0.000012718959,0.0000013400673,0.0000017745186,0.000019630268,0.0000022839442,0.00008971905],"genre_scores_gemma":[0.9994678,0.000104311664,0.00012507531,0.000010126749,0.000004699765,0.0000057041734,0.00007617658,0.0000024540084,0.00020370849],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998534,0.00002678489,0.0000119803035,0.000034707045,0.000028849094,0.00004418028],"domain_scores_gemma":[0.99939764,0.00005828166,0.00039558462,0.00002252962,0.00003793596,0.00008813564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022415162,0.00026096753,0.00025377746,0.00036854026,0.00020179323,0.0002452149,0.00014474143,0.00022261663,0.0011012343],"category_scores_gemma":[0.001084279,0.00014319745,0.00021102346,0.00026137067,0.00020249227,0.00021020552,0.00019307045,0.00031435612,0.00010778242],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009698341,0.0005420209,0.9788792,0.00004500119,0.00009118293,0.0003264564,0.00025257503,0.00006562863,0.007405722,0.000025581214,0.000116234885,0.011280639],"study_design_scores_gemma":[0.0000038291014,0.00017045371,0.9992889,0.0000042421134,0.000019000956,0.00010932314,0.000046655212,0.000028921486,0.00028584662,0.000004415266,0.000037482794,8.5189754e-7],"about_ca_topic_score_codex":0.0036592379,"about_ca_topic_score_gemma":0.006635745,"teacher_disagreement_score":0.0036592379,"about_ca_system_score_codex":0.0002129247,"about_ca_system_score_gemma":0.00018786172,"threshold_uncertainty_score":0.0072758794},"labels":[],"label_agreement":null},{"id":"W2046264394","doi":"10.1016/j.neuroimage.2008.12.046","title":"The effect of template choice on morphometric analysis of pediatric brain data","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":148,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Brain morphometry; Brain size; Normalization (sociology); Spatial normalization; Human brain; Medicine; Biomedical engineering; Nuclear medicine; Neuroscience; Biology; Radiology; Magnetic resonance imaging","score_opus":0.0847654776393003,"score_gpt":0.4045926656445653,"score_spread":0.319827188005265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046264394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71431565,0.006694097,0.27138922,0.0009509345,0.00033632774,0.00021164934,0.0012516909,0.0027494417,0.002100857],"genre_scores_gemma":[0.8405029,0.0015610108,0.15350471,0.00022781068,0.00008495414,0.00008816142,0.0009077395,0.0021456953,0.0009769917],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99139714,0.0058480767,0.0007392027,0.00085142057,0.0009591915,0.00020491584],"domain_scores_gemma":[0.780758,0.20226787,0.0041724774,0.0065428223,0.005245346,0.0010134224],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.021589564,0.0008679127,0.0009720682,0.0012220895,0.0007852367,0.0019191524,0.000764923,0.001130612,0.002000201],"category_scores_gemma":[0.15187593,0.00057985977,0.001007405,0.0021956707,0.0007130043,0.0016578821,0.0010608581,0.0010511961,0.0005476353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0139107425,0.00027841429,0.11070143,0.0010548873,0.0017794647,0.0011913369,0.0018624032,0.071885444,0.13862062,0.0031137373,0.006393235,0.6492082],"study_design_scores_gemma":[0.0006130541,0.002902213,0.18225175,0.00036750513,0.0033063982,0.008992481,0.0008105174,0.55575174,0.2296393,0.006026535,0.008964635,0.0003738422],"about_ca_topic_score_codex":0.005753197,"about_ca_topic_score_gemma":0.0077052987,"teacher_disagreement_score":0.9784104,"about_ca_system_score_codex":0.0005266324,"about_ca_system_score_gemma":0.0017316121,"threshold_uncertainty_score":0.11417788},"labels":[],"label_agreement":null},{"id":"W2046933782","doi":"10.1016/j.neuroimage.2013.06.030","title":"Collaborative patch-based super-resolution for diffusion-weighted images","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministerio de Ciencia e Innovación; CHIST-ERA; Agence Nationale de la Recherche","keywords":"Diffusion MRI; Image resolution; Fractional anisotropy; Computer vision; Computer science; Angular resolution (graph drawing); Artificial intelligence; Interpolation (computer graphics); Anisotropic diffusion; Resolution (logic); Diffusion; Image (mathematics); Superresolution; Anisotropy; Tracking (education); Mathematics; Physics; Optics; Magnetic resonance imaging","score_opus":0.032529069693619024,"score_gpt":0.32801279861863425,"score_spread":0.29548372892501523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046933782","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037849764,0.0003833862,0.99487704,0.00009505982,0.000026904629,0.00002495553,0.000060696704,0.00033735446,0.00040961566],"genre_scores_gemma":[0.08707754,0.0008487873,0.9094735,0.00011711773,0.00009744094,0.00009265235,0.00031595654,0.00024479342,0.0017321471],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993861,0.00018215008,0.000034597586,0.00013717909,0.00020690622,0.000053088577],"domain_scores_gemma":[0.9981066,0.00097520056,0.00015458075,0.00037646035,0.00029588514,0.000091256414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012867699,0.0009845463,0.0014929482,0.0012579581,0.0004884453,0.0010380183,0.0016062349,0.0015072979,0.002611275],"category_scores_gemma":[0.005264841,0.0009659785,0.0013365288,0.0017398389,0.00069468434,0.0018228013,0.0019074704,0.0016038739,0.0011584929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004758331,0.00017514055,0.0009828843,0.000599645,0.00048007027,0.00036176312,0.00037843638,0.28836352,0.103608064,0.016961,0.011356409,0.5762572],"study_design_scores_gemma":[0.000017477943,0.000039592407,0.00029977472,0.000013231033,0.00004781694,0.00023572576,0.00001985098,0.9749049,0.013005233,0.008810327,0.0025848607,0.000021208381],"about_ca_topic_score_codex":0.004336809,"about_ca_topic_score_gemma":0.007892474,"teacher_disagreement_score":0.004336809,"about_ca_system_score_codex":0.00040839435,"about_ca_system_score_gemma":0.0008701717,"threshold_uncertainty_score":0.008735597},"labels":[],"label_agreement":null},{"id":"W2047361139","doi":"10.1016/s0006-8993(02)04160-4","title":"Topographical anatomy of the cerebellum in the guinea pig, Cavia porcellus","year":2003,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cavia; Guinea pig; Anatomy; Cerebellum; New guinea; Biology; Neuroscience; History","score_opus":0.16978598072589077,"score_gpt":0.48733316726173453,"score_spread":0.3175471865358438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047361139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9629334,0.0036771267,0.011415062,0.00044807876,0.00008032223,0.000083090825,0.00074014824,0.00032795648,0.020294702],"genre_scores_gemma":[0.9888959,0.0012253386,0.006106385,0.00003649839,0.000013947426,0.000027713415,0.00019445983,0.000036008318,0.0034637945],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999082,0.000009896503,0.000005768155,0.000044137007,0.000015677557,0.000016297477],"domain_scores_gemma":[0.9995241,0.0001099837,0.00014516852,0.00006956467,0.000109974586,0.000041236024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014833834,0.00020728575,0.00017910702,0.0015794864,0.0004093869,0.00047958788,0.00037875757,0.00065463386,0.0016136619],"category_scores_gemma":[0.00052995613,0.0002924864,0.00015124399,0.0005456195,0.0016074023,0.0006102572,0.0004599581,0.00075094344,0.0004908075],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025703511,0.00024143622,0.036380384,0.00087808433,0.0001543448,0.013609702,0.0018902416,0.007476604,0.7671962,0.028677175,0.0022664694,0.13865897],"study_design_scores_gemma":[0.00019576438,0.0025072973,0.7747106,0.00035646162,0.0002695275,0.04362872,0.0018929901,0.010640391,0.13602246,0.007996112,0.021647185,0.00013253487],"about_ca_topic_score_codex":0.012246892,"about_ca_topic_score_gemma":0.012908151,"teacher_disagreement_score":0.012246892,"about_ca_system_score_codex":0.00046638545,"about_ca_system_score_gemma":0.00065107987,"threshold_uncertainty_score":0.02435124},"labels":[],"label_agreement":null},{"id":"W2047768580","doi":"10.1503/jpn.100082","title":"White matter microstructure in patients with obsessive–compulsive disorder","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; White matter; Obsessive compulsive; Psychology; Internal medicine; Medicine; Cardiology; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.008944740036156664,"score_gpt":0.2848020489133342,"score_spread":0.2758573088771776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047768580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995328,0.0001597407,0.000025162719,0.000027246464,0.0000018685038,0.000005000137,0.000053620857,0.0000025568029,0.00019193377],"genre_scores_gemma":[0.99963236,0.00009174864,0.00008015634,0.000027987036,0.0000050650947,0.000005384684,0.000094954354,0.0000013679596,0.000060997354],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982363,0.000024312118,0.000032307813,0.000057225338,0.00003792691,0.000024606446],"domain_scores_gemma":[0.99907684,0.000118241616,0.0005229059,0.000040192255,0.00013643393,0.00010522967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036610305,0.0004148993,0.00031433036,0.0015199431,0.00051850954,0.0005283794,0.0002497356,0.00050014036,0.0012161771],"category_scores_gemma":[0.0016185427,0.00027541773,0.0001426054,0.0009112504,0.0004989345,0.00032158982,0.00028538186,0.00026809788,0.00015820947],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029082448,0.00006648019,0.98986757,0.000041248113,0.00008088174,0.0014425964,0.00060462224,0.00006482274,0.0042861197,0.000032995467,0.00012048632,0.0031012609],"study_design_scores_gemma":[0.00001396941,0.00008789906,0.997413,0.0000059277713,0.000027834263,0.0020018218,0.00017994363,0.00004470842,0.0001293823,0.000031193562,0.00006116654,0.0000032594894],"about_ca_topic_score_codex":0.0053241714,"about_ca_topic_score_gemma":0.0076897577,"teacher_disagreement_score":0.0053241714,"about_ca_system_score_codex":0.00048059216,"about_ca_system_score_gemma":0.00032374312,"threshold_uncertainty_score":0.010586381},"labels":[],"label_agreement":null},{"id":"W2047853664","doi":"10.1002/mrm.10708","title":"Quantitative diffusion imaging with steady‐state free precession","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Steady-state free precession imaging; Nuclear magnetic resonance; Effective diffusion coefficient; Diffusion MRI; Diffusion; Precession; SIGNAL (programming language); Echo-planar imaging; Relaxation (psychology); Diffusion imaging; Spin echo; Flip angle; Physics; Magnetic resonance imaging; Computer science; Condensed matter physics; Radiology","score_opus":0.037498526013615294,"score_gpt":0.35814868133528527,"score_spread":0.32065015532166996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047853664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03729166,0.00092020887,0.9597224,0.00010049777,0.000031228003,0.00009858001,0.00024373436,0.0008306424,0.00076102844],"genre_scores_gemma":[0.19576539,0.00089110155,0.8011694,0.000052354993,0.000025635984,0.0003304056,0.000348106,0.00017582618,0.0012417411],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988412,0.00032023844,0.00007823547,0.00032806036,0.00037532364,0.000056987305],"domain_scores_gemma":[0.9982078,0.00082375,0.00017496999,0.0003495209,0.00040203144,0.000041932886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028035052,0.00069822936,0.00052123616,0.0010341415,0.00035513582,0.0009721363,0.0010201922,0.0008709797,0.0013932734],"category_scores_gemma":[0.004842311,0.0006611453,0.0003484006,0.00063120376,0.0007277383,0.0012482789,0.0010379945,0.00085234974,0.0004425352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001955463,0.000036668655,0.0004944617,0.0002506639,0.0000470321,0.00006537569,0.00007340613,0.0026187971,0.94963634,0.0028507472,0.00036341927,0.04336756],"study_design_scores_gemma":[0.0000741902,0.0004110712,0.0028932155,0.000026428845,0.00006230959,0.001175412,0.000030553852,0.07924907,0.9042585,0.003934737,0.007792544,0.00009196588],"about_ca_topic_score_codex":0.00069936353,"about_ca_topic_score_gemma":0.0010016427,"teacher_disagreement_score":0.0028035052,"about_ca_system_score_codex":0.0005229065,"about_ca_system_score_gemma":0.0006057714,"threshold_uncertainty_score":0.014826536},"labels":[],"label_agreement":null},{"id":"W2048126458","doi":"10.1002/nbm.1581","title":"The influence of white matter fibre orientation on MR signal phase and decay","year":2010,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Parkinson Canada; Universidad de Guanajuato; Parkinson Society Canada; Michael Smith Health Research BC","keywords":"White matter; Diffusion MRI; Nuclear magnetic resonance; Phase (matter); Orientation (vector space); SIGNAL (programming language); Spin echo; Diffusion; Physics; Magnetic resonance imaging; Contrast (vision); Echo (communications protocol); Materials science; Chemistry; Optics; Medicine; Mathematics; Geometry; Radiology; Computer science","score_opus":0.021627259033592475,"score_gpt":0.3680753547450776,"score_spread":0.3464480957114851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048126458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9492941,0.0029060626,0.044201456,0.000100989855,0.00006027649,0.000049974493,0.00016568063,0.000115258495,0.0031062393],"genre_scores_gemma":[0.9842986,0.0015346867,0.012961157,0.000037588405,0.000023629469,0.000040832267,0.00013917961,0.00014543493,0.0008189508],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996662,0.00009858905,0.000021641303,0.0000735971,0.00009667055,0.00004331075],"domain_scores_gemma":[0.9978497,0.001341101,0.00034004933,0.0001326138,0.00022254323,0.000113938215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010876636,0.00043156647,0.00022046338,0.000403829,0.00017176961,0.0005006514,0.00016052193,0.00026318035,0.0007535234],"category_scores_gemma":[0.0070287883,0.00024436184,0.00018210823,0.00032465646,0.0004987172,0.0005005078,0.00028013324,0.00034082716,0.0003279524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053751207,0.000034210123,0.0074685374,0.00009455063,0.000029282432,0.00014529134,0.00010729645,0.0017535671,0.961981,0.0004545818,0.00005240289,0.027341828],"study_design_scores_gemma":[0.00007272815,0.0011757077,0.24364246,0.000064168285,0.00024501502,0.0017111178,0.000105405066,0.029760486,0.7177988,0.0023612264,0.0029575008,0.00010537614],"about_ca_topic_score_codex":0.0009793815,"about_ca_topic_score_gemma":0.001078955,"teacher_disagreement_score":0.0010876636,"about_ca_system_score_codex":0.0002315387,"about_ca_system_score_gemma":0.00031666626,"threshold_uncertainty_score":0.005752206},"labels":[],"label_agreement":null},{"id":"W2048918010","doi":"10.1016/j.neuroimage.2011.03.065","title":"Cerebello–thalamo–cerebral connections in pediatric brain tumor patients: Impact on working memory","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; British Columbia Children's Hospital; University of Toronto; Princess Margaret Cancer Centre; Hospital for Sick Children","funders":"C17 Council","keywords":"Working memory; White matter; Diffusion MRI; Fractional anisotropy; Medicine; Psychology; Brain tumor; Cerebellar Degeneration; Neuroscience; Cerebellum; Cognition; Magnetic resonance imaging; Radiology; Pathology","score_opus":0.06917056003496626,"score_gpt":0.3261621009068251,"score_spread":0.2569915408718589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048918010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988668,0.00024060096,0.00005035192,0.00007272393,0.000004240766,0.0000013594407,0.00005565487,0.000002342992,0.0007060055],"genre_scores_gemma":[0.99958426,0.00017032775,0.000055721786,0.000015113613,0.000010699622,0.0000021108808,0.000051023533,0.0000038109986,0.000106880114],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987936,0.00002632225,0.000010851633,0.00002669788,0.000025067857,0.00003173217],"domain_scores_gemma":[0.99909496,0.00038159726,0.0002943636,0.000036646,0.000080344005,0.00011200114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001675372,0.00027836516,0.0002184361,0.00046211854,0.0002766863,0.00044277296,0.00028012283,0.00032363788,0.0024751306],"category_scores_gemma":[0.0019307939,0.000119752636,0.00021020332,0.00050884625,0.000466299,0.000537439,0.00018880106,0.00038837828,0.00021636492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032716742,0.00012691242,0.9710617,0.000027420207,0.00006889831,0.008876674,0.00019869859,0.00035039705,0.0036305927,0.00016692335,0.00029125108,0.014873368],"study_design_scores_gemma":[0.000021381527,0.00023536342,0.97538835,0.000015437889,0.00011915087,0.019958112,0.000670106,0.0004940451,0.002318391,0.000367264,0.00040444528,0.000008030737],"about_ca_topic_score_codex":0.002761966,"about_ca_topic_score_gemma":0.004048593,"teacher_disagreement_score":0.002761966,"about_ca_system_score_codex":0.0003674326,"about_ca_system_score_gemma":0.00051915366,"threshold_uncertainty_score":0.008280158},"labels":[],"label_agreement":null},{"id":"W2049221173","doi":"10.1523/jneurosci.2650-08.2008","title":"Practice Makes Cortex: Figure 1.","year":2008,"lang":"en","type":"review","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Neuroscience; White matter; Magnetic resonance imaging; Gray (unit); Psychology; Variety (cybernetics); Neuroimaging; Cortex (anatomy); Brain morphometry; Computer science; Cognitive science; Artificial intelligence; Medicine; Nuclear medicine; Radiology","score_opus":0.19392571049719864,"score_gpt":0.4707699922771978,"score_spread":0.27684428177999915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049221173","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004069412,0.31087485,0.030648785,0.020051263,0.0071392693,0.0005330531,0.0026322054,0.0040615066,0.61998963],"genre_scores_gemma":[0.03966304,0.4967842,0.03208724,0.009177147,0.0018434206,0.00045310572,0.0021227635,0.00057928625,0.4172898],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974805,0.00004020929,0.000020637654,0.00007140775,0.00008630489,0.00003347829],"domain_scores_gemma":[0.99972016,0.00005152865,0.00004267095,0.000041835323,0.00009030202,0.000053440468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038189703,0.0012701488,0.00061375054,0.0015739339,0.0008396487,0.0024615442,0.0018457376,0.0023918597,0.11954615],"category_scores_gemma":[0.0010329722,0.00039088307,0.00047492536,0.0016695108,0.0018198409,0.0027964078,0.0017433107,0.001637277,0.10047427],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004917306,0.00003245606,0.00026582842,0.00193656,0.000017866256,0.0005959512,0.00018106888,0.000111197376,0.0018724436,0.025119156,0.19837148,0.77144676],"study_design_scores_gemma":[0.000008801941,0.000018227647,0.0006479059,0.000817224,0.000010107078,0.0022264156,0.00010157958,0.000037164507,0.0005961382,0.0077191545,0.98780966,0.0000076013775],"about_ca_topic_score_codex":0.003467717,"about_ca_topic_score_gemma":0.0064526494,"teacher_disagreement_score":0.11954615,"about_ca_system_score_codex":0.0007690895,"about_ca_system_score_gemma":0.0019225798,"threshold_uncertainty_score":0.39992172},"labels":[],"label_agreement":null},{"id":"W2049366374","doi":"10.1117/12.2043591","title":"A new method for joint susceptibility artefact correction and super-resolution for dMRI","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Image resolution; Computer science; Diffusion MRI; Distortion (music); Resolution (logic); Artificial intelligence; Nuclear magnetic resonance; Magnetic resonance imaging; Computer vision; Physics; Pattern recognition (psychology); Telecommunications","score_opus":0.030748187588681305,"score_gpt":0.3079255326921042,"score_spread":0.2771773451034229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049366374","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005454328,0.00013579945,0.99851996,0.000048178405,0.00006105028,0.00002317773,0.00003099858,0.00034156555,0.00029384173],"genre_scores_gemma":[0.007734314,0.00019290588,0.9895629,0.00008041781,0.0000585517,0.00007795291,0.0001246504,0.00027141685,0.0018967714],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99864537,0.0002750876,0.00008091487,0.00030496588,0.00062023435,0.00007342735],"domain_scores_gemma":[0.99862933,0.00038914577,0.00012913845,0.00036629185,0.00040014673,0.00008600219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011536265,0.0011264607,0.0009393901,0.0011940997,0.0006451012,0.0011405579,0.0016496441,0.0016802208,0.004312636],"category_scores_gemma":[0.0032107458,0.0006194214,0.0015436419,0.0013090214,0.00075227174,0.0015568822,0.0020741187,0.0023361414,0.0030721042],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022677332,0.00009917097,0.0008953317,0.0004969562,0.00029114189,0.0004502135,0.00024271845,0.024512969,0.19723205,0.040716074,0.009842809,0.7249937],"study_design_scores_gemma":[0.000058247115,0.00018091577,0.0019222889,0.00008134202,0.00021618512,0.0028198734,0.00005016577,0.7773171,0.10698243,0.018091785,0.09204318,0.0002365034],"about_ca_topic_score_codex":0.0015700071,"about_ca_topic_score_gemma":0.0025471298,"teacher_disagreement_score":0.004312636,"about_ca_system_score_codex":0.00051422964,"about_ca_system_score_gemma":0.0012181719,"threshold_uncertainty_score":0.014427185},"labels":[],"label_agreement":null},{"id":"W2049696735","doi":"10.1097/rli.0b013e31817e909f","title":"Diffusion Tensor Magnetic Resonance Imaging of the Human Calf","year":2008,"lang":"en","type":"article","venue":"Investigative Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Nuclear magnetic resonance; Anisotropy; Physics; Nuclear medicine; Medicine; Optics; Radiology","score_opus":0.07464072198649016,"score_gpt":0.3268939290368986,"score_spread":0.25225320705040843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049696735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9713326,0.007961873,0.016941154,0.00016483825,0.000028708806,0.00012628779,0.000688922,0.00007518842,0.0026803024],"genre_scores_gemma":[0.9883674,0.002053395,0.0083199255,0.00005115429,0.000026208061,0.000032000124,0.0004438991,0.000016547956,0.0006894531],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997849,0.00005264708,0.000017456861,0.000051431434,0.00006809647,0.000025605386],"domain_scores_gemma":[0.9992968,0.0001476366,0.00018050698,0.00005424456,0.00024320441,0.00007760317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087932847,0.00043325548,0.00021182152,0.0010306534,0.00015597805,0.0004875984,0.00023418026,0.0002671948,0.0012727155],"category_scores_gemma":[0.0028015478,0.00011846615,0.00014823004,0.00057759165,0.00015975694,0.00045284888,0.00025039606,0.00015639726,0.00031460318],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025212266,0.00022575927,0.06922707,0.0018162486,0.00039006775,0.0017290666,0.00082120113,0.0028786669,0.77160436,0.0010519082,0.0012082738,0.14652613],"study_design_scores_gemma":[0.00033914653,0.0041975128,0.80961794,0.00043356305,0.00067769137,0.021109467,0.000723487,0.02771841,0.1222704,0.0022682482,0.010474885,0.00016930074],"about_ca_topic_score_codex":0.0038175285,"about_ca_topic_score_gemma":0.0036370114,"teacher_disagreement_score":0.0038175285,"about_ca_system_score_codex":0.00023847871,"about_ca_system_score_gemma":0.00034835227,"threshold_uncertainty_score":0.007590592},"labels":[],"label_agreement":null},{"id":"W2049756811","doi":"10.1016/j.neuroimage.2008.04.243","title":"Detection of multiple pathways in the spinal cord using q-ball imaging","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche Médicale; Canada Research Chairs; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Spinal cord; Diffusion MRI; White matter; Magnetic resonance imaging; Neuroscience; Anatomy; Diffusion imaging; Medicine; Biology; Radiology","score_opus":0.14833073701900817,"score_gpt":0.360337032967762,"score_spread":0.2120062959487538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049756811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33576512,0.003934828,0.6498917,0.0017251363,0.00008864093,0.00043227238,0.00047792733,0.00091479335,0.006769559],"genre_scores_gemma":[0.72878706,0.0020091916,0.2649539,0.00032486042,0.00007711705,0.00015596178,0.00016553192,0.00017389454,0.0033524088],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964607,0.0001016572,0.000028131602,0.00006883405,0.000110811015,0.000044452525],"domain_scores_gemma":[0.9990313,0.00040905192,0.00014284538,0.00006389909,0.00024611427,0.00010681142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012072755,0.00065088226,0.0005377736,0.0019322904,0.00053206395,0.0015892418,0.0009837371,0.0015727519,0.0038380837],"category_scores_gemma":[0.003958621,0.0005458645,0.00028850877,0.0012426878,0.0008079766,0.0025089441,0.0010916616,0.00079133955,0.0008684869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031733676,0.00031561774,0.02670627,0.0018257846,0.0002221415,0.0035760137,0.00093468535,0.012480538,0.6621491,0.01399488,0.0037458113,0.27087578],"study_design_scores_gemma":[0.0010251439,0.0024140792,0.076513685,0.0007228623,0.00046623545,0.025083631,0.0011551307,0.44816977,0.3409498,0.0884485,0.01476749,0.00028362902],"about_ca_topic_score_codex":0.0048367744,"about_ca_topic_score_gemma":0.0035026895,"teacher_disagreement_score":0.0048367744,"about_ca_system_score_codex":0.00035731605,"about_ca_system_score_gemma":0.0010644966,"threshold_uncertainty_score":0.012839675},"labels":[],"label_agreement":null},{"id":"W2049895116","doi":"10.1523/jneurosci.2388-08.2008","title":"Dissociating the Human Language Pathways with High Angular Resolution Diffusion Fiber Tractography","year":2008,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":447,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Tractography; Macaque; Neuroscience; Angular gyrus; Superior temporal sulcus; Anatomy; Human brain; Psychology; Superior longitudinal fasciculus; Planum temporale; Fasciculus; Superior temporal gyrus; Primate; Diffusion MRI; Biology; Perception; Functional magnetic resonance imaging; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.05336429195147954,"score_gpt":0.3222376690851621,"score_spread":0.26887337713368253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049895116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9181374,0.0011259485,0.07643595,0.00021912291,0.000007720758,0.000043162185,0.00022598509,0.000118666525,0.0036859787],"genre_scores_gemma":[0.9611125,0.0007434454,0.037161153,0.00003757422,0.0000071113295,0.000019698835,0.00016107319,0.000024312036,0.0007331706],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999905,0.00002580001,0.000006050838,0.000034246706,0.000013905749,0.000014979224],"domain_scores_gemma":[0.99984694,0.00007004434,0.000036795358,0.00002313265,0.0000123121545,0.000010807245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033450304,0.00021575412,0.00010972202,0.0006870067,0.0001885269,0.0005065126,0.00013294618,0.0002534643,0.0014334591],"category_scores_gemma":[0.0009907769,0.00016920814,0.00012069808,0.00021912424,0.0006053212,0.00062796357,0.00024681835,0.00016937958,0.0002231279],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056122354,0.00008321238,0.044002324,0.00035341654,0.00017615604,0.0010233866,0.0024082442,0.005991422,0.74450386,0.014984835,0.0004916889,0.18542007],"study_design_scores_gemma":[0.00013385227,0.00030459755,0.70696634,0.00017757913,0.00016253517,0.006709287,0.0012357313,0.0697432,0.16592437,0.032507904,0.016009612,0.00012501761],"about_ca_topic_score_codex":0.0051903725,"about_ca_topic_score_gemma":0.010526474,"teacher_disagreement_score":0.0051903725,"about_ca_system_score_codex":0.0002530671,"about_ca_system_score_gemma":0.00037261104,"threshold_uncertainty_score":0.010320306},"labels":[],"label_agreement":null},{"id":"W2050722132","doi":"10.1002/mrm.10411","title":"Is multicomponent <i>T</i><sub>2</sub> a good measure of myelin content in peripheral nerve?","year":2003,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"College of Science and Health","keywords":"Myelin; Wallerian degeneration; Remyelination; Sciatic nerve; Myelin sheath; Relaxation (psychology); Chemistry; Peripheral nerve; Pathology; Neuroscience; Nuclear magnetic resonance; Anatomy; Biology; Medicine; Central nervous system; Physics","score_opus":0.08002056620811958,"score_gpt":0.3213260548635613,"score_spread":0.2413054886554417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050722132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.950485,0.02029172,0.024435846,0.0014359361,0.00016933658,0.000037395293,0.00034541285,0.00020032807,0.0025989804],"genre_scores_gemma":[0.98243386,0.004106913,0.012135186,0.0003397339,0.00017091597,0.000025323383,0.00013598076,0.000048451733,0.0006036481],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99966896,0.00007946253,0.000036173227,0.000094085444,0.00007637124,0.000044911834],"domain_scores_gemma":[0.99727386,0.00077936315,0.0010220831,0.00031173677,0.00039819774,0.00021479263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015838321,0.0003672414,0.00068126427,0.0014546099,0.0002529713,0.0007137318,0.0007924497,0.0014258812,0.00074481283],"category_scores_gemma":[0.0028529614,0.00032185452,0.00018576307,0.0009380092,0.0013905169,0.0024595018,0.0003402968,0.00056866126,0.000506348],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010802326,0.00012430841,0.049208574,0.0011971771,0.00018810203,0.00055558194,0.00038802688,0.00043594404,0.88857865,0.0006254292,0.0004512122,0.05716682],"study_design_scores_gemma":[0.000030194607,0.0031671636,0.5441716,0.0002380323,0.00031268754,0.01286403,0.0017626307,0.005311629,0.41968518,0.0062869363,0.0060350266,0.00013482045],"about_ca_topic_score_codex":0.0004314065,"about_ca_topic_score_gemma":0.0008250744,"teacher_disagreement_score":0.0015838321,"about_ca_system_score_codex":0.00024030195,"about_ca_system_score_gemma":0.00017217694,"threshold_uncertainty_score":0.008376181},"labels":[],"label_agreement":null},{"id":"W2051116857","doi":"10.1016/j.jpeds.2009.12.030","title":"Tractography-Based Quantitation of Corticospinal Tract Development in Premature Newborns","year":2010,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Corticospinal tract; Tractography; Diffusion MRI; Physical medicine and rehabilitation; Radiology; Magnetic resonance imaging","score_opus":0.044990503329603165,"score_gpt":0.35032872804986065,"score_spread":0.3053382247202575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051116857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.973611,0.00092166965,0.02422098,0.000044925102,0.000010603856,0.000028649913,0.00025711404,0.00014775747,0.0007573574],"genre_scores_gemma":[0.9895215,0.00046063575,0.009592759,0.00000838371,0.0000060063103,0.00002382314,0.000083619634,0.00003618764,0.00026706682],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99981636,0.000082874074,0.000015329637,0.000027626178,0.00004564127,0.00001219933],"domain_scores_gemma":[0.9992079,0.00041371243,0.00012298085,0.00004590194,0.0001499189,0.000059648235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005956841,0.00022893673,0.00023904303,0.0010246515,0.00018064151,0.00041101917,0.00022375127,0.00034489148,0.0004910839],"category_scores_gemma":[0.003586972,0.00012084307,0.000096602336,0.0004012679,0.00026014054,0.00031665267,0.00020712512,0.00022359558,0.00010617859],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002670808,0.000057839723,0.38810623,0.0004966191,0.00013785933,0.0042733084,0.00081016775,0.012084143,0.42258224,0.001993487,0.00058977224,0.16619758],"study_design_scores_gemma":[0.000029924287,0.0005084085,0.7842427,0.000118827404,0.00011855156,0.01270353,0.00046369547,0.07309349,0.12636337,0.0010955587,0.0011992801,0.0000627059],"about_ca_topic_score_codex":0.004367192,"about_ca_topic_score_gemma":0.0037525424,"teacher_disagreement_score":0.004367192,"about_ca_system_score_codex":0.00033923352,"about_ca_system_score_gemma":0.00041921227,"threshold_uncertainty_score":0.008683562},"labels":[],"label_agreement":null},{"id":"W2051523173","doi":"10.1016/j.pscychresns.2011.11.002","title":"Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits","year":2012,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; White matter; Psychology; Diffusion MRI; Psychopathy; Amygdala; Uncinate fasciculus; Orbitofrontal cortex; Conduct disorder; Neuroimaging; Neuroscience; Functional magnetic resonance imaging; Prefrontal cortex; Developmental psychology; Magnetic resonance imaging; Medicine; Personality; Cognition; Psychoanalysis","score_opus":0.192752080837448,"score_gpt":0.4060632442863208,"score_spread":0.2133111634488728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051523173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994388,0.00004496942,0.00006508459,0.000028144901,0.0000018232791,0.0000018982911,0.000090938935,0.0000071284803,0.00032117253],"genre_scores_gemma":[0.9996364,0.00003419306,0.000105004736,0.000013609611,0.0000025161041,0.0000017324046,0.00008204641,0.000003245447,0.00012115744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985933,0.000016625507,0.000012146567,0.000050748735,0.00002225649,0.000038875358],"domain_scores_gemma":[0.9995896,0.00004798466,0.00018770044,0.000020539239,0.000037165595,0.00011699821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017864157,0.00039613497,0.000221496,0.0009573632,0.00048431716,0.00042500754,0.00026112457,0.00035091868,0.002470521],"category_scores_gemma":[0.00077419926,0.00022105359,0.00015805899,0.0005022745,0.0005000386,0.0003160269,0.00034680066,0.00036587243,0.00015424185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065580814,0.00013346187,0.9370179,0.000051992934,0.0001518679,0.005677225,0.00050740177,0.0002802056,0.047234964,0.00019182674,0.00028996813,0.007807483],"study_design_scores_gemma":[0.00000440437,0.00004711922,0.9958346,0.0000048579464,0.000030448897,0.002983853,0.00018407869,0.000150161,0.0006416126,0.00007288696,0.000044040153,0.000001972954],"about_ca_topic_score_codex":0.01022295,"about_ca_topic_score_gemma":0.0225049,"teacher_disagreement_score":0.01022295,"about_ca_system_score_codex":0.00027353852,"about_ca_system_score_gemma":0.0003436949,"threshold_uncertainty_score":0.020326853},"labels":[],"label_agreement":null},{"id":"W2051586848","doi":"10.1177/0269881110363314","title":"Anterior internal capsule volumes increase in patients with schizophrenia switched from typical antipsychotics to olanzapine","year":2010,"lang":"en","type":"article","venue":"Journal of Psychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of British Columbia; University of Calgary","funders":"Eli Lilly Canada; AstraZeneca Canada; Pfizer","keywords":"Internal capsule; Corpus callosum; Olanzapine; External capsule; White matter; Schizophrenia (object-oriented programming); Psychology; Antipsychotic; Internal medicine; Medicine; Magnetic resonance imaging; Cardiology; Anesthesia; Neuroscience; Psychiatry; Radiology","score_opus":0.01478368326062822,"score_gpt":0.34369535028801035,"score_spread":0.3289116670273821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051586848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997403,0.00005615146,0.000011945545,0.000012881058,0.0000014608538,0.0000019398071,0.000027633932,0.0000029232863,0.00014484946],"genre_scores_gemma":[0.99974054,0.000035952024,0.000035278812,0.000016872726,0.000002526533,0.0000025247941,0.000083611936,0.0000014164162,0.00008126715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999056,0.000015955533,0.000011220382,0.000024219553,0.000024105948,0.000018938956],"domain_scores_gemma":[0.99960715,0.00006017921,0.00021286991,0.000018260549,0.000034895515,0.00006668337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012811381,0.00028642392,0.00036153008,0.00034190275,0.00025931964,0.00043784396,0.00016674498,0.00030575733,0.0010985354],"category_scores_gemma":[0.00089299545,0.00018774818,0.0002493937,0.00022139002,0.00026610465,0.00024851,0.00020820822,0.0003037178,0.00012326815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004104396,0.00037491534,0.92340255,0.000064081265,0.0003072679,0.002019588,0.0010202157,0.00030922276,0.050967243,0.00005820194,0.0002733038,0.017099017],"study_design_scores_gemma":[0.00003201264,0.00042355453,0.9980715,0.0000032106086,0.000036795336,0.00064955745,0.00014272869,0.000092076334,0.000443868,0.000023457898,0.000076763354,0.0000044820504],"about_ca_topic_score_codex":0.005515226,"about_ca_topic_score_gemma":0.009381182,"teacher_disagreement_score":0.005515226,"about_ca_system_score_codex":0.00049157377,"about_ca_system_score_gemma":0.00025165663,"threshold_uncertainty_score":0.010966241},"labels":[],"label_agreement":null},{"id":"W2052758289","doi":"10.1523/jneurosci.4611-09.2010","title":"Training of Working Memory Impacts Structural Connectivity","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":536,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Aging","funders":"","keywords":"Working memory; White matter; Working memory training; Corpus callosum; Neuroscience; Intraparietal sulcus; Fractional anisotropy; Psychology; Diffusion MRI; Short-term memory; Cognitive psychology; Cognition; Posterior parietal cortex; Medicine; Magnetic resonance imaging","score_opus":0.16608175240736123,"score_gpt":0.40057248613907814,"score_spread":0.23449073373171692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052758289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986596,0.00021576825,0.000248483,0.000089642264,0.000024252293,0.000008536583,0.000057273308,0.000026283571,0.0006701013],"genre_scores_gemma":[0.99758196,0.00024408926,0.00037703244,0.000059040765,0.000019478044,0.000035322963,0.00010170497,0.000014506321,0.0015667559],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985147,0.00002445826,0.000012798412,0.00004087758,0.000016289561,0.0000540475],"domain_scores_gemma":[0.9993106,0.00017606013,0.000121461155,0.000098244025,0.000050865143,0.00024274085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001841633,0.00037820445,0.0003395197,0.00018983449,0.00017136226,0.0003057215,0.00034047055,0.00044754532,0.003729363],"category_scores_gemma":[0.0012101774,0.00013479494,0.00021344465,0.00009684259,0.00036535432,0.00029490594,0.0003652958,0.00054311776,0.0003116689],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.014573405,0.01563874,0.014809005,0.0004622969,0.00041406587,0.00037051056,0.0006396192,0.0024918283,0.80354375,0.000491028,0.0012760046,0.14528973],"study_design_scores_gemma":[0.0013093202,0.07493527,0.5679461,0.0003609886,0.0012874154,0.0010473952,0.00065253925,0.008237808,0.33081913,0.0036708135,0.009618293,0.00011491768],"about_ca_topic_score_codex":0.0010911428,"about_ca_topic_score_gemma":0.0010795848,"teacher_disagreement_score":0.003729363,"about_ca_system_score_codex":0.00021865821,"about_ca_system_score_gemma":0.00035854738,"threshold_uncertainty_score":0.012475967},"labels":[],"label_agreement":null},{"id":"W2053324294","doi":"10.1159/000102806","title":"The Computer Brain Atlas: lts Use in Stereotaxic Surgery","year":2007,"lang":"en","type":"article","venue":"Confinia Neurologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Atlas (anatomy); Brain atlas; Stereotaxic surgery; Stereotaxy; Computer science; Artificial intelligence; Stereotactic surgery; Computer vision; Computer graphics (images); Terminal (telecommunication); Anatomy; Medicine; Neuroscience; Psychology; Surgery","score_opus":0.12076347041034677,"score_gpt":0.3422939545131749,"score_spread":0.22153048410282813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053324294","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00508041,0.0015030458,0.81914455,0.0010242953,0.0011055971,0.00039078374,0.011472685,0.06869649,0.091582194],"genre_scores_gemma":[0.081834316,0.0024586834,0.8152559,0.00060163456,0.0004937182,0.0014522697,0.01971719,0.02711043,0.051075857],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989779,0.00034165068,0.00012523177,0.00014003494,0.00035724102,0.00005787989],"domain_scores_gemma":[0.9971438,0.0008077638,0.00013805086,0.00093552587,0.0007121831,0.0002626923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020531544,0.0007264193,0.0005813332,0.0024902783,0.00076411176,0.0023929237,0.00193343,0.0008747431,0.083626896],"category_scores_gemma":[0.0059545254,0.0005131427,0.0003737322,0.004142605,0.00089512643,0.0029632894,0.002176632,0.0016847469,0.041560207],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039077006,0.000063642336,0.0010943891,0.00045698523,0.000023210401,0.00035667227,0.00065593125,0.0020673547,0.0067073577,0.05071898,0.3713169,0.56614774],"study_design_scores_gemma":[0.00008483887,0.000106850384,0.0036458068,0.00019630596,0.000034343117,0.0017085174,0.0001329498,0.01095077,0.0066209366,0.020151477,0.9563013,0.0000658955],"about_ca_topic_score_codex":0.0025185642,"about_ca_topic_score_gemma":0.0023412772,"teacher_disagreement_score":0.083626896,"about_ca_system_score_codex":0.0006130078,"about_ca_system_score_gemma":0.0015013403,"threshold_uncertainty_score":0.27975982},"labels":[],"label_agreement":null},{"id":"W2053610521","doi":"10.3389/fnins.2014.00427","title":"High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft; Wellcome Trust","keywords":"Kurtosis; Diffusion MRI; White matter; Image resolution; Partial volume; Artificial intelligence; Computer science; Nuclear magnetic resonance; Computer vision; Physics; Magnetic resonance imaging; Mathematics; Medicine; Radiology","score_opus":0.02711487761857282,"score_gpt":0.2998774151171251,"score_spread":0.2727625374985523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053610521","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08474679,0.0007546208,0.9048239,0.0005819641,0.000101825535,0.000157247,0.0013559903,0.0041484362,0.0033292416],"genre_scores_gemma":[0.19888201,0.00088958885,0.7931865,0.00028250457,0.00008687504,0.00033140424,0.0018626393,0.0018704521,0.002608049],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998066,0.000030476585,0.000020168589,0.000050124443,0.00007001386,0.000022682796],"domain_scores_gemma":[0.99957615,0.000105909654,0.0000478876,0.000078901445,0.00015727637,0.000033864188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009633789,0.0009847573,0.0005741289,0.0012833776,0.00039515606,0.0009381155,0.00060848903,0.0007443102,0.0055670543],"category_scores_gemma":[0.0017917688,0.00055225595,0.0005348022,0.0010859562,0.00043638432,0.0010260717,0.0008728415,0.0011067769,0.0018013846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033964415,0.000073898445,0.0012843596,0.0006306972,0.00011698562,0.0010125347,0.00037943193,0.012471333,0.82572037,0.0043764887,0.006584142,0.1470102],"study_design_scores_gemma":[0.00012993166,0.00046482886,0.014038035,0.00010316642,0.0002294488,0.0052266205,0.00023095855,0.23746935,0.68137765,0.017671954,0.042736545,0.00032151927],"about_ca_topic_score_codex":0.00084956695,"about_ca_topic_score_gemma":0.0014775222,"teacher_disagreement_score":0.0055670543,"about_ca_system_score_codex":0.0002446635,"about_ca_system_score_gemma":0.00074101955,"threshold_uncertainty_score":0.01862359},"labels":[],"label_agreement":null},{"id":"W2053838094","doi":"10.1016/j.neuroimage.2013.05.074","title":"The Human Connectome Project and beyond: Initial applications of 300mT/m gradients","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":391,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; Siemens; Consortia for Improving Medicine with Innovation and Technology","keywords":"Human Connectome Project; Tractography; Diffusion MRI; Human brain; Connectome; Neuroscience; Connectomics; Computer science; Diffusion; Psychology; Biomedical engineering; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Functional connectivity; Radiology","score_opus":0.05761848994976977,"score_gpt":0.37787842772149494,"score_spread":0.3202599377717252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053838094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60785383,0.054771006,0.23243149,0.028487453,0.0013309986,0.0028922574,0.008655288,0.0028519067,0.060725924],"genre_scores_gemma":[0.67500067,0.027680716,0.2745784,0.0031978714,0.00080284034,0.0022569778,0.003917505,0.0011995427,0.011365563],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996141,0.00016982209,0.000015559328,0.000054493074,0.00009271441,0.00005327284],"domain_scores_gemma":[0.99861693,0.0006614701,0.000049015336,0.00016613062,0.00030343502,0.000202977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036192825,0.00081765186,0.00048861036,0.0013518274,0.000700819,0.0012410766,0.0009276801,0.0012162629,0.0039771763],"category_scores_gemma":[0.0047709118,0.0005000629,0.0003508901,0.0010318382,0.001092023,0.001388676,0.0018862484,0.0015765241,0.00062846526],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053255153,0.000975117,0.031210115,0.0016493483,0.0005252827,0.002394943,0.0016667059,0.008988457,0.14495222,0.044198822,0.05047936,0.7076341],"study_design_scores_gemma":[0.0016039289,0.003068412,0.22937767,0.0020676858,0.0009241992,0.010642545,0.0014660466,0.042571705,0.17962718,0.172447,0.35569316,0.0005103995],"about_ca_topic_score_codex":0.0065397425,"about_ca_topic_score_gemma":0.014932384,"teacher_disagreement_score":0.0065397425,"about_ca_system_score_codex":0.00073440594,"about_ca_system_score_gemma":0.0016186992,"threshold_uncertainty_score":0.01914084},"labels":[],"label_agreement":null},{"id":"W2054050201","doi":"10.1117/12.878216","title":"Second order DTMR image segmentation using random walker","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Johns Hopkins University","keywords":"Computer science; Image segmentation; Computer vision; Artificial intelligence; Segmentation; Image (mathematics)","score_opus":0.03613040605175855,"score_gpt":0.2914629178595661,"score_spread":0.2553325118078075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054050201","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055504553,0.00007253425,0.99283946,0.00006762393,0.000018869127,0.00004292613,0.00004988749,0.0008507687,0.0005073866],"genre_scores_gemma":[0.07978837,0.00023835122,0.9158622,0.000077478784,0.0000326504,0.00017020862,0.0003372851,0.000555775,0.0029377108],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999577,0.00008130478,0.00003112428,0.00011580286,0.00015874239,0.000036092235],"domain_scores_gemma":[0.9993325,0.00026869192,0.00011393549,0.0001112095,0.00012534446,0.00004834806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009165438,0.0009192374,0.0011024657,0.0020632981,0.00057137175,0.001679156,0.00083401595,0.0016536872,0.0032045085],"category_scores_gemma":[0.0026502977,0.0005441959,0.0010381646,0.0014952738,0.00064728415,0.0016108127,0.0009343406,0.0010565227,0.001976219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033859958,0.00011932074,0.0013358275,0.00032821766,0.00012446906,0.00055724545,0.0004088238,0.3278083,0.21055181,0.04921918,0.005241506,0.40396675],"study_design_scores_gemma":[0.000013034647,0.000047665075,0.00039569262,0.000013948812,0.000010947513,0.0002149055,0.000024688987,0.95356125,0.025616424,0.015553377,0.0045117135,0.000036408845],"about_ca_topic_score_codex":0.002350465,"about_ca_topic_score_gemma":0.0032030086,"teacher_disagreement_score":0.0032045085,"about_ca_system_score_codex":0.0009286591,"about_ca_system_score_gemma":0.0010254029,"threshold_uncertainty_score":0.010720074},"labels":[],"label_agreement":null},{"id":"W2054766524","doi":"10.4137/mri.s10692","title":"Diffusion Tensor Metric Measurements as a Function of Diffusion Time in the Rat Central Nervous System","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance Insights","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Grey matter; Diffusion MRI; White matter; Fractional anisotropy; Diffusion; Physics; Thermal diffusivity; Anisotropy; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Medicine; Thermodynamics; Optics","score_opus":0.04734002903679904,"score_gpt":0.2858887376946053,"score_spread":0.23854870865780628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054766524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935869,0.00026827867,0.005730626,0.000020059644,0.0000035340277,0.000006394484,0.00016471175,0.00006779512,0.00015164584],"genre_scores_gemma":[0.98975605,0.0004306376,0.009026718,0.000009725316,0.0000020640068,0.000030292087,0.00031081575,0.000028016162,0.0004057271],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998969,0.000026916012,0.000011972008,0.000020188789,0.00003200382,0.000012081357],"domain_scores_gemma":[0.99947923,0.00015003786,0.00016002244,0.000057107514,0.000116253155,0.000037340465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003985298,0.00028530188,0.0002125837,0.00033654668,0.00013211893,0.00023868048,0.00023256749,0.00025715155,0.00038449306],"category_scores_gemma":[0.0012823207,0.00016717496,0.00016427315,0.00021413894,0.0002940334,0.00023782226,0.00013375234,0.00026893296,0.000079077996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036315125,0.000052415282,0.0024149416,0.00008587309,0.00003518539,0.000048474823,0.000071815026,0.011694211,0.98042023,0.00025221915,0.0000699697,0.004491495],"study_design_scores_gemma":[0.000026859721,0.0015853314,0.023963844,0.000012414189,0.00009083364,0.00029270467,0.000050505452,0.05267827,0.9203831,0.00034068088,0.0005217463,0.000053710755],"about_ca_topic_score_codex":0.0023280946,"about_ca_topic_score_gemma":0.0026006312,"teacher_disagreement_score":0.0023280946,"about_ca_system_score_codex":0.00029015366,"about_ca_system_score_gemma":0.00026171777,"threshold_uncertainty_score":0.0046290755},"labels":[],"label_agreement":null},{"id":"W2055302062","doi":"10.1002/mrm.20680","title":"Characterization of the NMR behavior of white matter in bovine brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Chemistry; Relaxation (psychology); Nuclear magnetic resonance; Relaxometry; Magnetization transfer; Analytical Chemistry (journal); Chromatography; Magnetic resonance imaging; Central nervous system; Biology; Physics; Spin echo; Endocrinology","score_opus":0.02681640786326605,"score_gpt":0.3202426312526226,"score_spread":0.29342622338935653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055302062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891623,0.0035420302,0.0062694894,0.00002997085,0.000010280121,0.000016660733,0.00033130206,0.000039824,0.0005981687],"genre_scores_gemma":[0.9853795,0.0025672365,0.009688132,0.000056308338,0.0000123356795,0.000037435286,0.0011789578,0.000045236695,0.001034916],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986243,0.000021486672,0.000009575969,0.00004823872,0.000026464973,0.000031814805],"domain_scores_gemma":[0.9997516,0.000060145103,0.00007048386,0.000019541661,0.000069839305,0.0000283971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037884354,0.0004558027,0.00028197412,0.00040946697,0.0002675323,0.00032321177,0.00032100873,0.00032632158,0.00045586287],"category_scores_gemma":[0.00039795294,0.0002304522,0.00018068803,0.00030885322,0.00028216103,0.00024126064,0.00014085461,0.00020330558,0.00022612995],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033393106,0.000003179191,0.0003061308,0.00002894075,0.000004482027,0.00003554159,0.000023665982,0.00008281268,0.99906427,0.0000086765795,0.0000050804733,0.000403848],"study_design_scores_gemma":[0.000008462343,0.0005864482,0.04295721,0.000020309828,0.00008480744,0.00075227296,0.00013238672,0.0017513854,0.9521011,0.00007651586,0.0015134228,0.000015532261],"about_ca_topic_score_codex":0.004030755,"about_ca_topic_score_gemma":0.004863333,"teacher_disagreement_score":0.004030755,"about_ca_system_score_codex":0.0002456204,"about_ca_system_score_gemma":0.00018567046,"threshold_uncertainty_score":0.008014619},"labels":[],"label_agreement":null},{"id":"W2055343237","doi":"10.1007/s10851-012-0377-4","title":"Analysis of Scalar Maps for the Segmentation of the Corpus Callosum in Diffusion Tensor Fields","year":2012,"lang":"en","type":"article","venue":"Journal of Mathematical Imaging and Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Diffusion MRI; Scalar (mathematics); Segmentation; Artificial intelligence; Watershed; Computer science; Computer vision; Image segmentation; Visualization; Computation; Context (archaeology); Pattern recognition (psychology); Mathematics; Algorithm; Geometry; Geology; Magnetic resonance imaging","score_opus":0.0417378077631324,"score_gpt":0.3923569160794435,"score_spread":0.3506191083163111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055343237","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19815119,0.0008696699,0.79698443,0.00041776395,0.00004189683,0.00012894429,0.0007552175,0.0015984027,0.0010524051],"genre_scores_gemma":[0.5867952,0.0009333216,0.4087815,0.000038629525,0.00006301423,0.000091253714,0.0011164763,0.0006476707,0.0015329114],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997793,0.00007595806,0.00001813382,0.000039077306,0.000062373576,0.000025273697],"domain_scores_gemma":[0.9974898,0.0015375224,0.00019089629,0.00016692115,0.00053355936,0.00008130116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015714121,0.00068613316,0.0005545293,0.0026829268,0.00049163046,0.0015307167,0.00051277794,0.00066260557,0.0018854942],"category_scores_gemma":[0.0068600057,0.00037581316,0.00069976324,0.0012160955,0.0003839433,0.000923742,0.00051796145,0.000550193,0.00044581067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019276727,0.00021906405,0.006791254,0.0009068577,0.00029857847,0.00036085022,0.0004819145,0.23888282,0.17009695,0.024116378,0.0046375287,0.55128014],"study_design_scores_gemma":[0.000027643588,0.00010856157,0.0041653863,0.000024551218,0.00007828201,0.00016459917,0.000072858034,0.9589019,0.028033031,0.0070216195,0.0013631502,0.00003845556],"about_ca_topic_score_codex":0.0052456646,"about_ca_topic_score_gemma":0.003797007,"teacher_disagreement_score":0.0052456646,"about_ca_system_score_codex":0.0005386552,"about_ca_system_score_gemma":0.0017514393,"threshold_uncertainty_score":0.010430217},"labels":[],"label_agreement":null},{"id":"W2055993761","doi":"10.1016/s0221-0363(10)70050-0","title":"IRM de diffusion et encéphale","year":2010,"lang":"fr","type":"review","venue":"Journal de Radiologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital Notre-Dame","funders":"","keywords":"Medicine; Diffusion MRI; Ischemia; Diffusion imaging; Magnetic resonance imaging; Radiology; Cerebral ischaemia; Effective diffusion coefficient; Nuclear medicine; Cardiology","score_opus":0.17000355134787423,"score_gpt":0.45796209045333286,"score_spread":0.28795853910545866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055993761","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009341978,0.99830365,0.0002738621,0.00018519745,0.00023605235,0.0000026621244,0.000009334466,0.000009959028,0.00088585884],"genre_scores_gemma":[0.0012219794,0.996031,0.0005301832,0.00022365472,0.0009115293,0.000007112485,0.00003197484,0.0000046996756,0.0010378937],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996177,0.00008635357,0.00008213632,0.00007406272,0.00010541364,0.000034287936],"domain_scores_gemma":[0.9988004,0.00063918607,0.00022360214,0.000049681283,0.0002326809,0.000054448243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011820433,0.0019483161,0.0027856298,0.0069563244,0.000366714,0.0013711217,0.0014089824,0.0019798176,0.004513039],"category_scores_gemma":[0.0025456753,0.00055599696,0.0007802054,0.0047632246,0.00170264,0.0034312308,0.0009289915,0.002022496,0.0034218617],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008530233,0.000046753412,0.00021504908,0.018097399,0.00010479935,0.00078333536,0.00007982491,0.0003063105,0.0018018525,0.0034049891,0.035866667,0.93920773],"study_design_scores_gemma":[0.000038038837,0.00010988495,0.0011898582,0.0052649067,0.00026419703,0.009590746,0.00008288297,0.0002304475,0.0018145611,0.00285856,0.97851515,0.00004070803],"about_ca_topic_score_codex":0.0020472452,"about_ca_topic_score_gemma":0.0023310825,"teacher_disagreement_score":0.0069563244,"about_ca_system_score_codex":0.0009648936,"about_ca_system_score_gemma":0.0015496269,"threshold_uncertainty_score":0.0150975585},"labels":[],"label_agreement":null},{"id":"W2056509200","doi":"10.1016/j.mri.2009.05.038","title":"Spinal fMRI investigation of human spinal cord function over a range of innocuous thermal sensory stimuli and study-related emotional influences","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Brainstem; Neuroscience; Spinal cord; Locus coeruleus; Sensory system; Functional magnetic resonance imaging; Inhibitory postsynaptic potential; Reticular formation; Anatomy; Psychology; Central nervous system; Periaqueductal gray; Medicine; Midbrain","score_opus":0.051803747408831875,"score_gpt":0.3523926906083048,"score_spread":0.30058894319947294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056509200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923551,0.0010050421,0.003929754,0.0001068898,0.000016571394,0.00006476934,0.00009212913,0.000018661754,0.0024110544],"genre_scores_gemma":[0.9960718,0.00057741464,0.0022537073,0.00013403443,0.000035890604,0.00006747642,0.000062588406,0.000011953343,0.0007851225],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999398,0.000016367774,0.0000031476186,0.000015821326,0.00001048337,0.000014359546],"domain_scores_gemma":[0.99987364,0.00007039874,0.000013715344,0.000008768533,0.000018588069,0.000014893062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020639256,0.00023579902,0.00014544855,0.00019181901,0.00029744642,0.00023861245,0.0001342878,0.00025565617,0.0015917169],"category_scores_gemma":[0.0006978731,0.00011405483,0.00010230238,0.00012692898,0.00041702547,0.00024062383,0.00015816135,0.00025442624,0.00011460199],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035710551,0.000175835,0.0028934581,0.0002149155,0.00004087493,0.00035232544,0.000281382,0.00036253716,0.97064596,0.00036042926,0.0001887874,0.020912483],"study_design_scores_gemma":[0.0004073698,0.00856693,0.38686785,0.000115305265,0.0005139981,0.0057174303,0.0010041995,0.007888745,0.5816417,0.0025605913,0.0046648537,0.000051051516],"about_ca_topic_score_codex":0.00070398115,"about_ca_topic_score_gemma":0.0016323295,"teacher_disagreement_score":0.0015917169,"about_ca_system_score_codex":0.00012030167,"about_ca_system_score_gemma":0.00020099343,"threshold_uncertainty_score":0.005324781},"labels":[],"label_agreement":null},{"id":"W2057123686","doi":"10.1016/j.bandl.2013.06.007","title":"Potential and limitations of diffusion MRI tractography for the study of language","year":2013,"lang":"en","type":"review","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; Psychology; Magnetic resonance imaging; Sensitivity (control systems); Neuroscience; Artificial intelligence; Computer science; Radiology; Medicine","score_opus":0.0932722955506512,"score_gpt":0.397243869124542,"score_spread":0.3039715735738908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057123686","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000106173844,0.99842,0.00044927094,0.00045089083,0.00008085905,0.0000022690956,0.000012738644,0.000005995445,0.000471796],"genre_scores_gemma":[0.0009068473,0.997177,0.0010529284,0.00025992637,0.00031395265,0.000006852597,0.000023918918,0.000003850625,0.0002547167],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99935836,0.00014994906,0.00009644567,0.00015379951,0.000199364,0.000042068426],"domain_scores_gemma":[0.9947068,0.0037802346,0.00030885846,0.0001672536,0.00088641426,0.00015042486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037098867,0.0013792102,0.002932094,0.004011933,0.00039070388,0.0022788404,0.0018265429,0.0021002765,0.0028414058],"category_scores_gemma":[0.0041055265,0.000543701,0.0009727867,0.003460691,0.0021752373,0.0032065152,0.001197108,0.0030501843,0.0018238628],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007753595,0.000051791147,0.0006392707,0.011582449,0.0001829318,0.00038280044,0.00009833558,0.0004174492,0.001975511,0.0062731574,0.011713878,0.9666049],"study_design_scores_gemma":[0.000050478193,0.0001920538,0.0046949442,0.011223332,0.0004854258,0.008086743,0.00031226192,0.0008146791,0.0024018625,0.020713508,0.95088416,0.00014053556],"about_ca_topic_score_codex":0.004535313,"about_ca_topic_score_gemma":0.009583841,"teacher_disagreement_score":0.004535313,"about_ca_system_score_codex":0.0011411846,"about_ca_system_score_gemma":0.0040530195,"threshold_uncertainty_score":0.019619942},"labels":[],"label_agreement":null},{"id":"W2057236586","doi":"10.1016/j.neuro.2009.07.007","title":"Altered myelination and axonal integrity in adults with childhood lead exposure: A diffusion tensor imaging study","year":2009,"lang":"en","type":"article","venue":"NeuroToxicology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Child and Family Research Institute","funders":"National Center for Research Resources; National Institute of Environmental Health Sciences; National Cancer Institute; NIH Clinical Center; National Institutes of Health","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Splenium; Lead exposure; Psychology; Neuroscience; Physiology; Magnetic resonance imaging; Internal medicine; Medicine","score_opus":0.031435246139275876,"score_gpt":0.3300036538207122,"score_spread":0.2985684076814363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057236586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999653,0.000048032296,0.000040421026,0.000024864015,0.0000014006624,0.0000041900926,0.00004050005,0.0000019733734,0.00018564472],"genre_scores_gemma":[0.9996284,0.00009626422,0.00006232397,0.000014763511,0.000004150656,0.0000036160363,0.00004653116,0.000001454596,0.00014251034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997588,0.000038434744,0.00003429353,0.00005897721,0.000057247067,0.00005226701],"domain_scores_gemma":[0.99932635,0.000100153295,0.00028749497,0.00004260446,0.0001287912,0.000114722876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033739096,0.0006012291,0.00048078757,0.0008785437,0.00094009977,0.0005369858,0.00026745885,0.0006882879,0.0009967834],"category_scores_gemma":[0.0014124304,0.000488799,0.0003381575,0.0011091004,0.00067125895,0.0007002098,0.00047582577,0.00052899495,0.00023069054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003977209,0.00033670221,0.98562336,0.00003349962,0.000043996133,0.0060158703,0.0015917562,0.000058831964,0.0037138986,0.00003160984,0.00008968015,0.0020631866],"study_design_scores_gemma":[0.000015103999,0.00059697445,0.9854798,0.000006709343,0.00006140728,0.011372046,0.0013895733,0.000090441135,0.00076576066,0.000042584772,0.00017193051,0.0000075596918],"about_ca_topic_score_codex":0.013723456,"about_ca_topic_score_gemma":0.012782687,"teacher_disagreement_score":0.013723456,"about_ca_system_score_codex":0.0003848737,"about_ca_system_score_gemma":0.00065534306,"threshold_uncertainty_score":0.027287185},"labels":[],"label_agreement":null},{"id":"W2057327718","doi":"10.1097/01.rli.0000261935.41188.39","title":"Diffusion-Tensor Imaging at 3 T","year":2007,"lang":"en","type":"article","venue":"Investigative Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Medicine; Diffusion imaging; Confidence interval; Anisotropy; Nuclear medicine; Magnetic resonance imaging; Nuclear magnetic resonance; Physics; Radiology; Optics; Internal medicine","score_opus":0.0760410469570088,"score_gpt":0.3612716232919629,"score_spread":0.2852305763349541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057327718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.070425354,0.0037742155,0.89595795,0.0015213534,0.00030445209,0.00042834875,0.009358474,0.0068289773,0.011400846],"genre_scores_gemma":[0.29843375,0.00350301,0.67939603,0.00091522466,0.00027256843,0.0011919568,0.007339072,0.0012956825,0.00765265],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995105,0.00016665061,0.000045896493,0.00012356591,0.00011695181,0.00003639666],"domain_scores_gemma":[0.99897754,0.0002173568,0.00023094613,0.00017616316,0.00033753933,0.000060508923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014339732,0.00091126777,0.0007683215,0.0012382788,0.0004315696,0.0013488149,0.0007785648,0.001113024,0.008403845],"category_scores_gemma":[0.0038843472,0.00039726877,0.00095384207,0.0016197684,0.00050108234,0.0011730839,0.0008687377,0.00086071366,0.0035210974],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001424405,0.00026556058,0.01694543,0.0033543585,0.0019064154,0.0022725684,0.0007995211,0.048673183,0.2739942,0.02097187,0.06891242,0.5604801],"study_design_scores_gemma":[0.0010017853,0.0019979589,0.104126506,0.0009680991,0.0019467481,0.013157159,0.00047064899,0.44388825,0.10967927,0.14075686,0.18118687,0.00081985706],"about_ca_topic_score_codex":0.0027917204,"about_ca_topic_score_gemma":0.0034212326,"teacher_disagreement_score":0.008403845,"about_ca_system_score_codex":0.00033891996,"about_ca_system_score_gemma":0.0012251128,"threshold_uncertainty_score":0.028113663},"labels":[],"label_agreement":null},{"id":"W2057477305","doi":"10.1016/j.compmedimag.2014.07.002","title":"Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging","year":2014,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research","keywords":"Support vector machine; Pattern recognition (psychology); Artificial intelligence; Epilepsy; Temporal lobe; Computer science; Diffusion MRI; Parametric statistics; Principal component analysis; Fractional anisotropy; Magnetic resonance imaging; Mathematics; Radiology; Medicine; Psychology; Neuroscience; Statistics","score_opus":0.0627627876946144,"score_gpt":0.3776114421191385,"score_spread":0.3148486544245241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057477305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26868019,0.0008220801,0.7287674,0.00028816378,0.000036691647,0.00009090264,0.0001585889,0.0005575763,0.00059850595],"genre_scores_gemma":[0.8548719,0.0003778741,0.14376375,0.00004847039,0.00003829061,0.00006825545,0.00013479182,0.000051251696,0.0006453649],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99960774,0.00012887959,0.00003761413,0.000054080883,0.00012165054,0.00005003596],"domain_scores_gemma":[0.9984113,0.0009887132,0.000194776,0.00007990054,0.0002696142,0.00005577595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012907726,0.00046374486,0.00045268313,0.0012717611,0.00021336043,0.0008830716,0.0004718751,0.0006362467,0.00050943345],"category_scores_gemma":[0.004609964,0.00025569738,0.0004447194,0.00062824454,0.0003118918,0.00061769644,0.0005209369,0.00052011776,0.00021954502],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010481378,0.00026629446,0.021637945,0.00036798746,0.0001487747,0.00064610125,0.00020106194,0.07732905,0.13330859,0.0031314138,0.0019657186,0.7599489],"study_design_scores_gemma":[0.000019020265,0.00013416399,0.009090258,0.000022150016,0.00004081513,0.00080220436,0.000068804,0.95554084,0.031190436,0.00237629,0.0006885281,0.000026471269],"about_ca_topic_score_codex":0.0012616328,"about_ca_topic_score_gemma":0.0011433961,"teacher_disagreement_score":0.0012907726,"about_ca_system_score_codex":0.00019089378,"about_ca_system_score_gemma":0.0005207317,"threshold_uncertainty_score":0.006826341},"labels":[],"label_agreement":null},{"id":"W2057517058","doi":"10.1093/brain/aws153","title":"Assessing the risk of central post-stroke pain of thalamic origin by lesion mapping","year":2012,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Thalamus; Lesion; Magnetic resonance imaging; Medicine; Stroke (engine); Odds ratio; Neuroscience; Psychology; Pathology; Radiology","score_opus":0.06828368282082552,"score_gpt":0.3703583069288995,"score_spread":0.30207462410807395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057517058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99820006,0.00017365851,0.0012500002,0.000020672898,0.00000205079,0.0000104431965,0.000042268293,0.000011437593,0.00028944865],"genre_scores_gemma":[0.99935085,0.00007020081,0.00045626136,0.000003893409,0.0000036437673,0.000004731593,0.00004193761,0.000001943176,0.00006651729],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996743,0.00011349949,0.000032858596,0.000075754695,0.00006500972,0.000038498143],"domain_scores_gemma":[0.99917644,0.00028595625,0.00035098696,0.000055125838,0.00005915126,0.000072213814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003700755,0.00043716663,0.00034586084,0.0009648725,0.00016437577,0.0005289982,0.00020486952,0.00043391163,0.0014656041],"category_scores_gemma":[0.0017440576,0.00015826998,0.00026651725,0.00034774226,0.00024549654,0.00033036523,0.00036431054,0.00021454236,0.00019651008],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012968259,0.00011532244,0.9504178,0.00007484826,0.00026389086,0.0009973417,0.00026868613,0.000561233,0.021547485,0.00013454854,0.000117074276,0.024205063],"study_design_scores_gemma":[0.000015701598,0.0005796662,0.9928376,0.000008929854,0.0000812945,0.0023375086,0.00021009489,0.0017271208,0.0018708821,0.00018178298,0.00013786957,0.000011571187],"about_ca_topic_score_codex":0.0006129561,"about_ca_topic_score_gemma":0.0009413944,"teacher_disagreement_score":0.0014656041,"about_ca_system_score_codex":0.00009318911,"about_ca_system_score_gemma":0.00011232683,"threshold_uncertainty_score":0.004902959},"labels":[],"label_agreement":null},{"id":"W2057680708","doi":"10.1523/jneurosci.1312-06.2006","title":"Genetic Contributions to Human Brain Morphology and Intelligence","year":2006,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":291,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"White matter; Corpus callosum; Cortex (anatomy); Posterior cingulate; Brain morphometry; Cingulate cortex; Temporal cortex; Posterior parietal cortex; Psychology; Neuroscience; Anatomy; Biology; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.05568312087274402,"score_gpt":0.4015405996213333,"score_spread":0.3458574787485893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057680708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977435,0.00038750496,0.0008701405,0.000044398395,0.000003002523,0.00000768969,0.00012469376,0.000019091813,0.0008001205],"genre_scores_gemma":[0.9985202,0.00024520888,0.00081980403,0.000007888024,0.000006199469,0.000005761763,0.00014646238,0.0000080670625,0.00024049659],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99946314,0.00017531321,0.000040615076,0.00016053588,0.0001271851,0.000033310524],"domain_scores_gemma":[0.99927133,0.00026942755,0.00021092684,0.00014378132,0.000057232523,0.000047314265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005769094,0.00044970922,0.00024211277,0.0009147056,0.000270731,0.00047314345,0.00018003264,0.00024309653,0.0014145203],"category_scores_gemma":[0.0035467176,0.00022527303,0.00024795972,0.00088701525,0.00064892287,0.00017219597,0.00060166186,0.00024752392,0.00015231976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028362236,0.000055509092,0.9335614,0.000056269782,0.0008759602,0.0010680349,0.0010622331,0.002915229,0.021122266,0.0017697329,0.00023500544,0.036994737],"study_design_scores_gemma":[0.0000043743626,0.00002544444,0.9968451,0.0000059668373,0.00006309414,0.0005522166,0.00005478108,0.0008994598,0.00042597463,0.00088454696,0.00023293962,0.000006158982],"about_ca_topic_score_codex":0.0041488116,"about_ca_topic_score_gemma":0.002878763,"teacher_disagreement_score":0.0041488116,"about_ca_system_score_codex":0.00022100995,"about_ca_system_score_gemma":0.00015702426,"threshold_uncertainty_score":0.008249342},"labels":[],"label_agreement":null},{"id":"W2058065446","doi":"10.3109/02699052.2013.794968","title":"Neurometabolic and microstructural alterations following a sports-related concussion in female athletes","year":2013,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Hôpital Saint-Luc; Université de Montréal","funders":"","keywords":"Concussion; Athletes; Medicine; Injury prevention; Physical therapy; Poison control; Occupational safety and health; Suicide prevention; Sports medicine; Human factors and ergonomics; Physical medicine and rehabilitation; Psychology; Medical emergency; Pathology","score_opus":0.023313523626571516,"score_gpt":0.3233919355875211,"score_spread":0.3000784119609496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058065446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99941456,0.0001598254,0.000063380925,0.000016685046,0.000002311375,0.0000074169197,0.000066684894,0.0000016912671,0.00026745052],"genre_scores_gemma":[0.9993135,0.00016591705,0.00009405512,0.000010371892,0.000011002046,0.000008959361,0.00008182709,0.0000012754124,0.00031321496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992204,0.000010222076,0.0000073920514,0.00002071567,0.000013429683,0.000026134692],"domain_scores_gemma":[0.99973387,0.000022125205,0.00015146114,0.000009458426,0.000047816382,0.000035271045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014951371,0.00020746488,0.00017609885,0.00049365463,0.0003154856,0.00021713058,0.00014146989,0.0002664776,0.0019344047],"category_scores_gemma":[0.0005201698,0.00009235162,0.00011954785,0.0002465293,0.00022673034,0.00014599517,0.00024730337,0.00008852052,0.0003392156],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085318985,0.00014699563,0.95778054,0.00010085832,0.00005941007,0.0023689177,0.00074424496,0.00009914383,0.020100124,0.000036042486,0.00019188198,0.017518671],"study_design_scores_gemma":[0.0000037602201,0.00050743733,0.9947824,0.000011131202,0.00001669209,0.0030998695,0.00045128263,0.00006160976,0.0008275488,0.00001564031,0.00021994796,0.0000027096587],"about_ca_topic_score_codex":0.0027248776,"about_ca_topic_score_gemma":0.0031545102,"teacher_disagreement_score":0.0027248776,"about_ca_system_score_codex":0.00019641062,"about_ca_system_score_gemma":0.00019757064,"threshold_uncertainty_score":0.0064712167},"labels":[],"label_agreement":null},{"id":"W2058457174","doi":"10.1007/s00429-012-0466-6","title":"Understanding white matter integrity stability for bilinguals on language status and reading performance","year":2012,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Psychology; Fractional anisotropy; White matter; Neuroscience of multilingualism; Reading (process); Diffusion MRI; Audiology; Age of Acquisition; Cognitive psychology; Developmental psychology; Cognition; Linguistics; Neuroscience; Medicine","score_opus":0.11788817718121347,"score_gpt":0.3463011893353268,"score_spread":0.2284130121541133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058457174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994117,0.000051716732,0.000069183385,0.000028670562,0.0000013375566,0.0000014762135,0.00008880654,0.000003101625,0.00034409988],"genre_scores_gemma":[0.9995547,0.00003098363,0.000058897273,0.000008599914,0.0000036158867,0.0000021344824,0.00013527994,0.0000037242971,0.00020210745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984634,0.000027016744,0.000015676407,0.000051430277,0.000029066783,0.000030422565],"domain_scores_gemma":[0.9989698,0.0003777165,0.00030562116,0.00007625939,0.00014266533,0.00012794256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006053388,0.00031963753,0.0003556164,0.001009962,0.0003768363,0.0007396244,0.00019476465,0.00047284408,0.002244292],"category_scores_gemma":[0.0021425018,0.00015952981,0.000283648,0.0005000412,0.00044648876,0.0007792198,0.00046778485,0.00032226596,0.00031911413],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019586484,0.00011372277,0.9531455,0.00003836012,0.00026501447,0.0003528687,0.001308853,0.00030024658,0.025664823,0.00022858684,0.00031392527,0.016309403],"study_design_scores_gemma":[0.0000058778223,0.00008635428,0.9978421,0.0000038601634,0.00003237952,0.00017077387,0.0003015639,0.0003400063,0.00089937245,0.00024023658,0.00007305681,0.0000045187844],"about_ca_topic_score_codex":0.0062149186,"about_ca_topic_score_gemma":0.010781612,"teacher_disagreement_score":0.0062149186,"about_ca_system_score_codex":0.00036045222,"about_ca_system_score_gemma":0.00031277025,"threshold_uncertainty_score":0.012357473},"labels":[],"label_agreement":null},{"id":"W2059013849","doi":"10.1016/j.pscychresns.2007.11.007","title":"Diffusion tensor imaging tractography and reliability analysis for limbic and paralimbic white matter tracts","year":2008,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"White matter; Cingulum (brain); Diffusion MRI; Uncinate fasciculus; Fractional anisotropy; Fornix; Inferior longitudinal fasciculus; Tractography; Psychology; Parahippocampal gyrus; Medicine; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Radiology; Hippocampus; Temporal lobe","score_opus":0.10378085638715982,"score_gpt":0.40735516343047434,"score_spread":0.3035743070433145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059013849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7407836,0.0009262359,0.25440222,0.00025391876,0.000042830183,0.00020266316,0.0011436036,0.0006152762,0.0016297111],"genre_scores_gemma":[0.89455736,0.000257872,0.10243901,0.000021968988,0.0000484225,0.00012532645,0.00077181024,0.00038896795,0.0013892028],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997586,0.0010733157,0.0002588296,0.0005536882,0.00039076622,0.00013742351],"domain_scores_gemma":[0.9844158,0.008364361,0.0020875854,0.001950174,0.002842142,0.00033995308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009170351,0.00083297864,0.00076012313,0.0029974522,0.0008972709,0.001393929,0.00075130205,0.0006665501,0.0017078415],"category_scores_gemma":[0.030242976,0.00064014306,0.001993293,0.0016045284,0.0009838898,0.0016845672,0.0009248423,0.0010162111,0.00054062443],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041848235,0.00025994828,0.53661436,0.0008028603,0.0034005637,0.001715204,0.0037832214,0.041246284,0.09090147,0.015727744,0.0047025485,0.29666102],"study_design_scores_gemma":[0.00016930206,0.0009916803,0.64844596,0.00013407502,0.0018063294,0.004774009,0.0007947141,0.28141665,0.03415434,0.023201926,0.0038606166,0.0002503744],"about_ca_topic_score_codex":0.013195208,"about_ca_topic_score_gemma":0.019907737,"teacher_disagreement_score":0.013195208,"about_ca_system_score_codex":0.0007549943,"about_ca_system_score_gemma":0.0026090068,"threshold_uncertainty_score":0.048498034},"labels":[],"label_agreement":null},{"id":"W2059177186","doi":"10.1016/j.neuroimage.2004.03.041","title":"Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":436,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Pyramidal tracts; Fractional anisotropy; Cerebral peduncle; Wallerian degeneration; Stroke (engine); Medicine; Corticospinal tract; Cardiology; Neuroscience; Pathology; Magnetic resonance imaging; Anatomy; Psychology; Internal capsule; Radiology; Physics; White matter","score_opus":0.022563115463479087,"score_gpt":0.2820871390897093,"score_spread":0.25952402362623017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059177186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974226,0.00036255445,0.00039830248,0.00019524335,0.000018328119,0.000018452465,0.000055243978,0.000012436126,0.001516993],"genre_scores_gemma":[0.9985291,0.00035403552,0.00032647338,0.000047467292,0.0000410485,0.000005297856,0.00009461088,0.0000058095247,0.0005961664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998791,0.000015958336,0.000017534847,0.000016163134,0.000024293466,0.000046917445],"domain_scores_gemma":[0.99929833,0.00016699923,0.00019283002,0.000042628137,0.00012813351,0.00017100941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005558401,0.0005838923,0.0005107039,0.0014169856,0.00044411718,0.0007505006,0.00039860237,0.00091997965,0.0018088338],"category_scores_gemma":[0.0028511768,0.00036274944,0.00026593727,0.0005666326,0.000613198,0.0012996033,0.00030394955,0.00067830586,0.00039690142],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008546085,0.0010896403,0.7389394,0.00033797132,0.00048989645,0.043565743,0.0009654635,0.0010864619,0.13698143,0.0005876745,0.0020312576,0.065379016],"study_design_scores_gemma":[0.00013316005,0.001031893,0.957042,0.00005154229,0.00023098111,0.021326415,0.000557699,0.0023063961,0.01582733,0.0009445898,0.00051176734,0.00003616303],"about_ca_topic_score_codex":0.005849606,"about_ca_topic_score_gemma":0.009321604,"teacher_disagreement_score":0.005849606,"about_ca_system_score_codex":0.0004559322,"about_ca_system_score_gemma":0.00057947414,"threshold_uncertainty_score":0.011631131},"labels":[],"label_agreement":null},{"id":"W2059189228","doi":"10.1002/mrm.21132","title":"Partial <i>k</i>‐space reconstruction in single‐shot diffusion‐weighted echo‐planar imaging","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Echo (communications protocol); Direct-conversion receiver; k-space; Physics; Artifact (error); Planar; Echo-planar imaging; Sampling (signal processing); Truncation (statistics); Homodyne detection; Nuclear magnetic resonance; Optics; Computer vision; Computer science; Magnetic resonance imaging; Fourier transform; Detector","score_opus":0.042459987427275275,"score_gpt":0.3291119296082759,"score_spread":0.28665194218100065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059189228","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019917732,0.0003815207,0.9785769,0.00007069427,0.000021868216,0.000024496985,0.000026574444,0.00038493896,0.0005952913],"genre_scores_gemma":[0.06362039,0.0006061665,0.93445396,0.0000402472,0.000013671029,0.000044380307,0.000084812964,0.00013233778,0.0010041234],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996182,0.00014360987,0.000029775063,0.00006822818,0.00011021583,0.00002992212],"domain_scores_gemma":[0.9993641,0.00028037664,0.0000742718,0.00015592977,0.000091602764,0.000033807708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009535476,0.0004398725,0.00049694296,0.00044510572,0.0003462097,0.0009072532,0.0007385929,0.0008074224,0.0015138029],"category_scores_gemma":[0.0023348904,0.00063189445,0.00039812046,0.0008025492,0.00069901167,0.00099013,0.0008767307,0.0007574979,0.0008575252],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005112779,0.00013607752,0.0021867398,0.000529603,0.0001233086,0.0006353339,0.00028626857,0.07288333,0.2113959,0.030735087,0.0034720905,0.67710495],"study_design_scores_gemma":[0.00005794861,0.00030761884,0.0030786816,0.000045241777,0.00008683899,0.003292309,0.000085888205,0.7162377,0.24528427,0.018062366,0.01333623,0.00012487391],"about_ca_topic_score_codex":0.0007182464,"about_ca_topic_score_gemma":0.0016725216,"teacher_disagreement_score":0.0015138029,"about_ca_system_score_codex":0.00019336207,"about_ca_system_score_gemma":0.0008866886,"threshold_uncertainty_score":0.0050641894},"labels":[],"label_agreement":null},{"id":"W2059786519","doi":"10.1117/12.878423","title":"Shape anisotropy: tensor distance to anisotropy measure","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Diffusion MRI; Tensor (intrinsic definition); Anisotropy; Fractional anisotropy; Physics; Euclidean distance; Isotropy; Tensor field; Measure (data warehouse); Mathematical analysis; Mathematics; Computer science; Artificial intelligence; Exact solutions in general relativity; Geometry; Optics; Magnetic resonance imaging","score_opus":0.03755359466630674,"score_gpt":0.2768961986355143,"score_spread":0.23934260396920753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059786519","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024075713,0.004888677,0.9634032,0.0009180288,0.0003801368,0.00007130227,0.00040806105,0.0007192701,0.0051356214],"genre_scores_gemma":[0.54163253,0.006017728,0.44228685,0.00051871233,0.0011074656,0.00027247914,0.0011909995,0.00063737266,0.0063359705],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977252,0.000595376,0.00020431535,0.0005294584,0.00082808034,0.000117619165],"domain_scores_gemma":[0.99446315,0.0016028037,0.0013527011,0.00095014524,0.0013433588,0.00028784576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020460512,0.0010161893,0.0011151115,0.0031688998,0.0006231828,0.0028117038,0.0011707452,0.0015431046,0.0017243942],"category_scores_gemma":[0.012107929,0.0003332327,0.0009857073,0.0036058226,0.002333691,0.003219459,0.0016594375,0.0018244991,0.00111221],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003475713,0.00012070203,0.012146413,0.00081393536,0.00041727137,0.00065185345,0.0004976322,0.08703831,0.047496755,0.3665368,0.0143121,0.46962067],"study_design_scores_gemma":[0.000054708282,0.0004338623,0.02308735,0.00025398287,0.00023660467,0.0048234332,0.0003809743,0.53469324,0.037600446,0.3226126,0.07539799,0.00042480734],"about_ca_topic_score_codex":0.0015581688,"about_ca_topic_score_gemma":0.00092230004,"teacher_disagreement_score":0.0031688998,"about_ca_system_score_codex":0.0012049152,"about_ca_system_score_gemma":0.0008989765,"threshold_uncertainty_score":0.010820687},"labels":[],"label_agreement":null},{"id":"W2059955071","doi":"10.1016/j.jcjo.2013.11.003","title":"Diffusion-weighted imaging in posterior ischemic optic neuropathy","year":2014,"lang":"en","type":"letter","venue":"Canadian Journal of Ophthalmology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Neuroimaging; Ischemia; Medicine; Stroke (engine); Extracellular; Diffusion imaging; Ischemic stroke; Nuclear medicine; Pathology; Cardiology; Radiology; Chemistry; Physics","score_opus":0.040146222436392355,"score_gpt":0.31031148746373977,"score_spread":0.2701652650273474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059955071","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17138788,0.025000144,0.0030497229,0.5907402,0.020248301,0.00038745653,0.0004812515,0.00047990686,0.18822518],"genre_scores_gemma":[0.74052143,0.013199684,0.00422785,0.12803711,0.08992779,0.00017032209,0.00019234992,0.00012608265,0.023597294],"study_design_codex":"case_report","study_design_gemma":"not_applicable","domain_scores_codex":[0.998642,0.00020555936,0.00028095563,0.000152543,0.00035881624,0.00036010417],"domain_scores_gemma":[0.9956086,0.0023059794,0.0004557856,0.00021729378,0.00070826913,0.0007040869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014127265,0.0013424219,0.0015951638,0.003306889,0.003421891,0.0028681103,0.0025160213,0.020647965,0.0042787953],"category_scores_gemma":[0.011803118,0.0009369998,0.0014582395,0.0020659438,0.0032390947,0.0033580433,0.00097459985,0.011214837,0.0020156808],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009435199,0.00009459345,0.0038925323,0.000120850316,0.000022536327,0.96656036,0.00012640221,0.00016075229,0.00037079857,0.0012868507,0.02164184,0.0056281644],"study_design_scores_gemma":[0.0002192044,0.00016617388,0.010142427,0.00049015455,0.00013167255,0.9574407,0.0005040831,0.0027870336,0.00095022295,0.0052264063,0.021878429,0.00006342107],"about_ca_topic_score_codex":0.014680764,"about_ca_topic_score_gemma":0.022062415,"teacher_disagreement_score":0.020647965,"about_ca_system_score_codex":0.006834058,"about_ca_system_score_gemma":0.0032597245,"threshold_uncertainty_score":0.049584806},"labels":[],"label_agreement":null},{"id":"W2059991735","doi":"10.1016/j.jmr.2013.10.012","title":"A pulse sequence optimization method for assessment of nucleus size in q-space analysis of idealized cells","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; Thunder Bay Regional Research Institute","funders":"","keywords":"Nucleus; Monte Carlo method; Impulse (physics); Pulse (music); Physics; Propagator; Gaussian; Sequence (biology); Pulse sequence; Chemistry; Computational physics; Mathematics; Nuclear magnetic resonance; Optics; Statistics; Classical mechanics; Biology; Quantum mechanics","score_opus":0.05521449007641873,"score_gpt":0.4072630609447733,"score_spread":0.3520485708683546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059991735","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006705306,0.00005161718,0.9924475,0.000035931174,0.00000945568,0.000033518376,0.000030498315,0.00033990786,0.00034623564],"genre_scores_gemma":[0.04065531,0.00006936777,0.9582646,0.00002745214,0.000008655674,0.000117302465,0.00007707827,0.00020111396,0.00057914323],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998124,0.00006725769,0.000013815281,0.000028367751,0.000063386084,0.000014786437],"domain_scores_gemma":[0.99925345,0.00036508575,0.000054303284,0.00006876805,0.0002190101,0.000039351144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009556413,0.0004891768,0.0004378001,0.00054597564,0.00044508983,0.00054425217,0.0007406581,0.00056412333,0.0018284478],"category_scores_gemma":[0.0021728498,0.00035696436,0.0003915508,0.0005630801,0.00037921715,0.0005112569,0.0006529706,0.00067113165,0.00051816046],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060840265,0.00020575835,0.0017812464,0.0004092844,0.00015409544,0.0003016565,0.00038289503,0.20044786,0.26860595,0.025380097,0.003853507,0.4978693],"study_design_scores_gemma":[0.00002965571,0.00008011327,0.00081864867,0.000012449951,0.000028447308,0.00014536649,0.000026590838,0.9625181,0.030087132,0.0035484813,0.0026769151,0.0000281715],"about_ca_topic_score_codex":0.0020408109,"about_ca_topic_score_gemma":0.002883175,"teacher_disagreement_score":0.0020408109,"about_ca_system_score_codex":0.0002920776,"about_ca_system_score_gemma":0.0013249001,"threshold_uncertainty_score":0.0061168075},"labels":[],"label_agreement":null},{"id":"W2060591289","doi":"10.1038/sj.jcbfm.9600294","title":"The Relationship between Diffusion Anisotropy and Time of Onset after Stroke","year":2006,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Medicine; White matter; Stroke (engine); Effective diffusion coefficient; Nuclear medicine; Nuclear magnetic resonance; Internal medicine; Pathology; Magnetic resonance imaging; Cardiology; Gastroenterology; Radiology; Physics","score_opus":0.02281011005075334,"score_gpt":0.28900441803984217,"score_spread":0.26619430798908883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060591289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977604,0.001092161,0.00023809807,0.000023360164,0.000006097589,0.000007936268,0.00017215533,0.000012210499,0.0006875786],"genre_scores_gemma":[0.99927455,0.0001671071,0.00011189548,0.0000079047095,0.000014958534,0.0000053137173,0.00018544107,0.00000365955,0.00022924019],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998385,0.00003446233,0.00001808805,0.000040887262,0.00002469278,0.000043404718],"domain_scores_gemma":[0.99763024,0.0006067152,0.0010933431,0.00010195822,0.00023989072,0.00032792956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002963524,0.0002036253,0.00022449512,0.0006443657,0.00014617697,0.00032307254,0.00016822664,0.00032482736,0.0015350598],"category_scores_gemma":[0.0031068823,0.00011666531,0.00017322574,0.00029556543,0.00018770415,0.00030944948,0.00023508763,0.00036101864,0.00044869568],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015768774,0.00005124383,0.9781845,0.000022490192,0.00011353826,0.00035488457,0.00008746923,0.00015802663,0.011004423,0.000041495474,0.00010645486,0.0082985535],"study_design_scores_gemma":[0.0000056132753,0.00012623204,0.998555,0.0000023120756,0.000009767112,0.0005188135,0.000019898072,0.0000864436,0.0005448242,0.000025001322,0.00010308243,0.0000030179403],"about_ca_topic_score_codex":0.0017486312,"about_ca_topic_score_gemma":0.0014942468,"teacher_disagreement_score":0.0017486312,"about_ca_system_score_codex":0.00021370898,"about_ca_system_score_gemma":0.00012208795,"threshold_uncertainty_score":0.005135298},"labels":[],"label_agreement":null},{"id":"W2060830357","doi":"10.1016/j.media.2011.10.001","title":"Tumor invasion margin on the Riemannian space of brain fibers","year":2011,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University; University of Alberta","funders":"","keywords":"Geodesic; Glioma; Margin (machine learning); Diffusion MRI; Magnetic resonance imaging; Fiber tract; Lesion; Brain tumor; Infiltration (HVAC); Computer science; Medicine; Mathematics; Pathology; Radiology; Mathematical analysis; Physics; Cancer research","score_opus":0.07676911403623363,"score_gpt":0.3431612832338788,"score_spread":0.2663921691976452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060830357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8890348,0.0007255138,0.10148879,0.00046303583,0.000017264203,0.000033223587,0.00027825436,0.00015266592,0.00780633],"genre_scores_gemma":[0.9830282,0.00036629438,0.013818092,0.000031178224,0.000042679636,0.000019497944,0.00012030305,0.00006666347,0.002507252],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998223,0.00004895479,0.0000075051043,0.00003574999,0.000064965054,0.000020574511],"domain_scores_gemma":[0.9990433,0.00035075162,0.00019248467,0.00005114276,0.00019390075,0.00016843945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048540582,0.00052348094,0.00026311385,0.0015614891,0.0002575763,0.0009999522,0.00031171553,0.00035482278,0.002615344],"category_scores_gemma":[0.0023916399,0.00019191763,0.00021705174,0.00038958475,0.00069012505,0.0008568248,0.0009690768,0.00046212118,0.00038287762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018925706,0.000253465,0.051890943,0.00062908424,0.00022955306,0.002849629,0.001879552,0.06755116,0.21548183,0.41484028,0.004223023,0.23827893],"study_design_scores_gemma":[0.000105000065,0.0007889152,0.21383111,0.00017756983,0.00020997658,0.0044307113,0.0006378809,0.52507627,0.027494544,0.21506736,0.011998717,0.00018200923],"about_ca_topic_score_codex":0.0014413306,"about_ca_topic_score_gemma":0.0013269704,"teacher_disagreement_score":0.002615344,"about_ca_system_score_codex":0.00041204345,"about_ca_system_score_gemma":0.00028023394,"threshold_uncertainty_score":0.008749187},"labels":[],"label_agreement":null},{"id":"W2060887411","doi":"10.1097/wnr.0000000000000247","title":"Cerebellum-specific 18F-FDG PET analysis for the detection of subregional glucose metabolism changes in spinocerebellar ataxia","year":2014,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Spinocerebellar ataxia; Spatial normalization; Cerebellum; Pet imaging; Normalization (sociology); Neuroscience; Nuclear medicine; Cerebellar cortex; Ataxia; Positron emission tomography; Medicine; Biology; Magnetic resonance imaging; Radiology","score_opus":0.06487165848581244,"score_gpt":0.3206678162297925,"score_spread":0.25579615774398007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060887411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9338908,0.0011129179,0.063384116,0.000026090307,0.00001547881,0.00007598692,0.00038123853,0.00045161144,0.0006617564],"genre_scores_gemma":[0.97078294,0.0002911006,0.028059285,0.000012079979,0.0000047385975,0.00004920701,0.0003732327,0.000059858747,0.00036756787],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998343,0.000028777431,0.00001686091,0.00006525644,0.00003433477,0.000020461715],"domain_scores_gemma":[0.9998672,0.00002626205,0.00003371883,0.000028524428,0.000027355862,0.000016871758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039088062,0.00039387456,0.00041152706,0.00091819005,0.00017931635,0.00048501688,0.0002882465,0.00030811914,0.00048216694],"category_scores_gemma":[0.0007023658,0.00018802981,0.00047311437,0.00048183042,0.00017929601,0.00018982816,0.00023913263,0.00015715713,0.00016125647],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010138532,0.000109327055,0.20679174,0.00024433594,0.0005607929,0.001137014,0.00029572152,0.009473861,0.5887481,0.00049692416,0.00050886313,0.19061947],"study_design_scores_gemma":[0.00006557167,0.0004204401,0.786738,0.000025246405,0.00054977887,0.0036754678,0.0001738175,0.07440465,0.13111019,0.0005458507,0.0022329246,0.000058073616],"about_ca_topic_score_codex":0.004555534,"about_ca_topic_score_gemma":0.0113122985,"teacher_disagreement_score":0.004555534,"about_ca_system_score_codex":0.00027460567,"about_ca_system_score_gemma":0.0003118597,"threshold_uncertainty_score":0.009057999},"labels":[],"label_agreement":null},{"id":"W2060995849","doi":"10.1016/j.pediatrneurol.2012.09.005","title":"Diffusion Tensor Imaging of Sports-Related Concussion in Adolescents","year":2013,"lang":"en","type":"article","venue":"Pediatric Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary; Child and Family Research Institute; University of British Columbia Hospital; University of British Columbia","funders":"","keywords":"Concussion; Fractional anisotropy; Diffusion MRI; White matter; Athletes; Medicine; Physical therapy; Poison control; Psychology; Injury prevention; Magnetic resonance imaging; Radiology","score_opus":0.01501533166526708,"score_gpt":0.28747167375349775,"score_spread":0.27245634208823066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060995849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99651355,0.001386694,0.00024387526,0.00020751776,0.00001156565,0.00001341392,0.000072240175,0.0000050391795,0.0015462397],"genre_scores_gemma":[0.9977683,0.0014351489,0.0003792325,0.00004182765,0.000031673084,0.0000073865053,0.00006538888,0.0000036703857,0.00026747177],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998654,0.000023214981,0.000027082373,0.000018391449,0.00002484422,0.000041064413],"domain_scores_gemma":[0.99956614,0.00007158565,0.000179414,0.000011829438,0.00010116813,0.000069801776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003458625,0.00033970427,0.000224795,0.0014426049,0.00042290398,0.00045785724,0.00026564684,0.0005184055,0.0008864149],"category_scores_gemma":[0.0018169355,0.00027421248,0.00020162511,0.00061661884,0.00039851898,0.00073744403,0.00029710378,0.00037069092,0.0001913968],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019400177,0.00016453526,0.9469991,0.00010933048,0.000059174366,0.028726768,0.00044521646,0.0004948138,0.0043619233,0.0004984262,0.0007517016,0.017194903],"study_design_scores_gemma":[0.000023131523,0.00027038294,0.9237147,0.00017247781,0.000104497216,0.067973025,0.001595356,0.0016073673,0.0028892893,0.00047091808,0.0011662171,0.000012538655],"about_ca_topic_score_codex":0.007691137,"about_ca_topic_score_gemma":0.007797241,"teacher_disagreement_score":0.007691137,"about_ca_system_score_codex":0.00038854938,"about_ca_system_score_gemma":0.00086904736,"threshold_uncertainty_score":0.015292764},"labels":[],"label_agreement":null},{"id":"W2061108093","doi":"10.1002/mrm.22019","title":"Robust correction of spike noise: Application to diffusion tensor imaging","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Heart and Stroke Foundation; University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Computer science; Diffusion MRI; Outlier; Artificial intelligence; Noise (video); Redundancy (engineering); Pattern recognition (psychology); Spike (software development); Noise reduction; Normalization (sociology); Computer vision; Algorithm; Magnetic resonance imaging; Image (mathematics)","score_opus":0.03172189684513755,"score_gpt":0.32552512427018004,"score_spread":0.2938032274250425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061108093","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006866831,0.00012313228,0.99206126,0.00008228256,0.000022346538,0.00001669328,0.000028957536,0.00061735825,0.00018119202],"genre_scores_gemma":[0.17442787,0.00040443105,0.82378817,0.00005961843,0.00006429964,0.000055973385,0.00018018529,0.0002451221,0.00077429175],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991855,0.00020040589,0.00006459783,0.0001297026,0.00037777104,0.00004204134],"domain_scores_gemma":[0.9966601,0.0014037563,0.00047052512,0.0005515047,0.0008048051,0.00010934378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001678992,0.00087031187,0.00090275455,0.00095405336,0.00035771448,0.0007626783,0.0011045007,0.0008467605,0.0006160693],"category_scores_gemma":[0.010285389,0.00037941657,0.0006691138,0.0011028097,0.00064938434,0.00082439295,0.0013892951,0.00093385467,0.00037220615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033548404,0.000093850176,0.0026790544,0.0002537294,0.00017263301,0.00049700204,0.000184678,0.26680964,0.10555745,0.013724446,0.0020569565,0.607635],"study_design_scores_gemma":[0.000015889002,0.000072926545,0.00092818285,0.000011212364,0.000022647157,0.0002852272,0.000015847958,0.948997,0.039590564,0.0073911757,0.002632692,0.000036551897],"about_ca_topic_score_codex":0.0015117027,"about_ca_topic_score_gemma":0.0014505576,"teacher_disagreement_score":0.001678992,"about_ca_system_score_codex":0.00047405763,"about_ca_system_score_gemma":0.00073751784,"threshold_uncertainty_score":0.008879423},"labels":[],"label_agreement":null},{"id":"W2061222352","doi":"10.1007/s004010100458","title":"Differential passage of [14C]sucrose and [3H]inulin across rat blood-brain barrier after cerebral ischemia","year":2001,"lang":"en","type":"article","venue":"Acta Neuropathologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Institute for Biological Sciences","funders":"","keywords":"Inulin; Ischemia; Blood–brain barrier; Biophysics; Chemistry; Vesicular transport protein; Sucrose; Diffusion; Vesicle; Pathology; Internal medicine; Biology; Medicine; Biochemistry; Membrane; Central nervous system","score_opus":0.031025491483959732,"score_gpt":0.3210774926010767,"score_spread":0.290052001117117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061222352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842218,0.008473051,0.0038804593,0.00015981589,0.00013037724,0.000036589983,0.00046498986,0.00008593298,0.0025469249],"genre_scores_gemma":[0.97497797,0.0070865494,0.009745967,0.00012022949,0.000097459655,0.00008302036,0.0013675113,0.000120950914,0.0064003533],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995989,0.00006238814,0.00002930251,0.00007136415,0.000051095474,0.00018692335],"domain_scores_gemma":[0.99956816,0.00008439197,0.00011216162,0.00007331682,0.00008697492,0.00007503015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062996417,0.0010555534,0.001191966,0.0007876843,0.00068536855,0.001140896,0.0011759066,0.0007242958,0.0010925141],"category_scores_gemma":[0.00033651717,0.00048425578,0.0006983299,0.00087392755,0.0007301317,0.0016403681,0.0004170205,0.0017601606,0.00043061844],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004243963,0.00009696308,0.0003850561,0.00017689563,0.000081441125,0.00037741225,0.00023205506,0.0002698561,0.98932964,0.0009679488,0.00010399157,0.0037347176],"study_design_scores_gemma":[0.000035672674,0.0005942422,0.0024571365,0.000018045166,0.000111885514,0.00021722403,0.00009706275,0.0009266661,0.9941327,0.0001429398,0.0012462403,0.000020096615],"about_ca_topic_score_codex":0.0069415565,"about_ca_topic_score_gemma":0.009143617,"teacher_disagreement_score":0.0069415565,"about_ca_system_score_codex":0.0014860074,"about_ca_system_score_gemma":0.0015235577,"threshold_uncertainty_score":0.01380229},"labels":[],"label_agreement":null},{"id":"W2062073930","doi":"10.1111/j.1749-6632.2009.05063.x","title":"MRI Measures of Alzheimer's Disease and the AddNeuroMed Study","year":2009,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Commission","keywords":"Neuroimaging; Alzheimer's disease; Magnetic resonance imaging; Pipeline (software); Protocol (science); Medicine; Disease; Nuclear medicine; Psychology; Computer science; Artificial intelligence; Pathology; Radiology; Neuroscience","score_opus":0.260902865287491,"score_gpt":0.42548356885769506,"score_spread":0.16458070357020405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062073930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9689306,0.008227614,0.0007844483,0.00095510867,0.00015118704,0.00031664557,0.008459826,0.00004233137,0.0121321855],"genre_scores_gemma":[0.9793053,0.002724268,0.0030943453,0.0008916666,0.00052195694,0.00073421345,0.009441884,0.000027667176,0.0032585731],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887484,0.00046656502,0.0001504941,0.00017724304,0.00027070215,0.00006014556],"domain_scores_gemma":[0.99743927,0.00043556668,0.0012149707,0.00028392157,0.00025625332,0.00037004612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021331324,0.00058644137,0.00061384065,0.0026525625,0.0010474969,0.0010164091,0.00072384556,0.000623421,0.0035904553],"category_scores_gemma":[0.003459351,0.0002391778,0.0003238552,0.0019797997,0.00036184952,0.0007009569,0.0009139716,0.00076501665,0.0005710481],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003716372,0.0005169194,0.97125566,0.00025349294,0.0009003623,0.00059285486,0.00046965704,0.00016285025,0.00088014983,0.0010515992,0.0044337064,0.015766438],"study_design_scores_gemma":[0.00022883808,0.00048420797,0.9917157,0.000054987908,0.00022115243,0.0013076335,0.00014407291,0.000079533216,0.00022482968,0.00068651926,0.004829847,0.000022661474],"about_ca_topic_score_codex":0.0017172154,"about_ca_topic_score_gemma":0.003177148,"teacher_disagreement_score":0.0035904553,"about_ca_system_score_codex":0.00032487413,"about_ca_system_score_gemma":0.00032639503,"threshold_uncertainty_score":0.01201129},"labels":[],"label_agreement":null},{"id":"W2062097146","doi":"10.1109/bmei.2011.6098483","title":"Estimation of orientation distribution function using spherical ridgelet basis with minimum L&lt;inf&gt;2&lt;/inf&gt; norm","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Orientation (vector space); Diffusion MRI; Angular resolution (graph drawing); Basis function; Image resolution; Norm (philosophy); Artificial intelligence; Mathematics; Computer science; Physics; Nuclear magnetic resonance; Magnetic resonance imaging; Mathematical analysis; Geometry; Combinatorics","score_opus":0.06009109494979183,"score_gpt":0.31535724471641574,"score_spread":0.25526614976662393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062097146","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035790887,0.000041208023,0.99604493,0.000054569326,0.000007864741,0.0000070894785,0.000018798626,0.000074452684,0.00017209715],"genre_scores_gemma":[0.12658308,0.00044521553,0.87088174,0.00004743013,0.00005170028,0.000101859296,0.00032444557,0.00013770002,0.0014268807],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994893,0.00017418005,0.000029134762,0.00008234795,0.00018541141,0.00003958494],"domain_scores_gemma":[0.9988433,0.0005632154,0.00014232319,0.00010786009,0.00030359527,0.000039699495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016759982,0.00059389434,0.0007647,0.00065760536,0.00020075575,0.000762868,0.0007426388,0.00084918004,0.0009856607],"category_scores_gemma":[0.004303554,0.00039355175,0.0006335419,0.0007203948,0.0005367274,0.0011163816,0.0006840865,0.00102546,0.00076561543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020548736,0.00014761976,0.0014848975,0.00021173827,0.00006905365,0.00016999035,0.00014992984,0.43950614,0.04681469,0.04346956,0.0047020805,0.4630688],"study_design_scores_gemma":[0.0000040569876,0.000014964923,0.00019228496,0.000005287274,0.0000033199756,0.00003961891,0.0000061481032,0.9937955,0.0026121354,0.0028314348,0.00048807976,0.000007121519],"about_ca_topic_score_codex":0.0013326983,"about_ca_topic_score_gemma":0.0010381577,"teacher_disagreement_score":0.0016759982,"about_ca_system_score_codex":0.00039201806,"about_ca_system_score_gemma":0.0008326267,"threshold_uncertainty_score":0.008863628},"labels":[],"label_agreement":null},{"id":"W2062170532","doi":"10.1016/s0361-9230(00)00434-2","title":"Maturation of white matter in the human brain: a review of magnetic resonance studies","year":2001,"lang":"en","type":"review","venue":"Brain Research Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":871,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fondation Brain Canada","keywords":"White matter; Diffusion MRI; Magnetic resonance imaging; Magnetization transfer; Psychology; Grey matter; T2 relaxation; Nuclear magnetic resonance; Diffusion imaging; Tractography; Neuroscience; Brain Structure and Function; Brain development; Relaxation (psychology); Neuroimaging; Medicine; Physics; Radiology","score_opus":0.3087303040642021,"score_gpt":0.5306154438457288,"score_spread":0.22188513978152669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062170532","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035490465,0.9990029,0.0002031246,0.0001335194,0.000053334432,0.0000049762416,0.000021144098,0.000005593717,0.0002205435],"genre_scores_gemma":[0.00081576966,0.9983931,0.00046350504,0.00006913266,0.00011407573,0.000004695128,0.000024387744,0.0000011087294,0.00011419874],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99963784,0.000038767346,0.000085554515,0.000119092496,0.00009953198,0.00001925879],"domain_scores_gemma":[0.99889416,0.00054982415,0.00018524234,0.000027785647,0.00029146572,0.000051446463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012387506,0.0011917629,0.0021007652,0.004244381,0.0002796132,0.0010551905,0.0012841002,0.001287677,0.0012320341],"category_scores_gemma":[0.0017510852,0.00046064847,0.0005893349,0.005032567,0.0007757361,0.0020888457,0.0005001654,0.00088188215,0.0010452704],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020004538,0.0000694031,0.001377706,0.022723274,0.0001349449,0.00065752695,0.00010258091,0.00027601497,0.006151703,0.00075712573,0.008107505,0.95944226],"study_design_scores_gemma":[0.00012032761,0.000926136,0.04012338,0.017011598,0.0019108753,0.026158784,0.00078127196,0.00052491995,0.012029664,0.005373228,0.89479536,0.000244502],"about_ca_topic_score_codex":0.0035544254,"about_ca_topic_score_gemma":0.0047454857,"teacher_disagreement_score":0.004244381,"about_ca_system_score_codex":0.0008528397,"about_ca_system_score_gemma":0.0017480438,"threshold_uncertainty_score":0.0070675015},"labels":[],"label_agreement":null},{"id":"W2062776012","doi":"10.1002/mrm.21936","title":"Myelin water measurement in the spinal cord","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Calgary; University of Alberta","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Multiple sclerosis; Myelin; Spinal cord; Magnetic resonance imaging; White matter; Lumbar; Context (archaeology); T2 relaxation; Nuclear medicine; Medicine; Nuclear magnetic resonance; Biomedical engineering; Anatomy; Central nervous system; Neuroscience; Radiology; Biology; Physics; Internal medicine","score_opus":0.1187628976268697,"score_gpt":0.38112381621288133,"score_spread":0.2623609185860116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062776012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850486,0.005286907,0.0089181,0.00005248573,0.000008415844,0.000016919554,0.00007177973,0.00005958097,0.00053719565],"genre_scores_gemma":[0.9856484,0.0021581748,0.011374516,0.000033172568,0.000007811285,0.000018694944,0.00009339497,0.000018648485,0.0006472116],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999798,0.00004711792,0.000011851901,0.00007195919,0.000053121403,0.000017965058],"domain_scores_gemma":[0.9997112,0.000058751488,0.00008296823,0.000020334588,0.0000900555,0.000036653713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044009165,0.00032176153,0.00020082983,0.00086502393,0.00030137366,0.0003391351,0.00028576984,0.00039091508,0.00056482916],"category_scores_gemma":[0.001038453,0.00017438647,0.00008251856,0.00032981107,0.0005490224,0.00060724077,0.00031359642,0.00025457403,0.00017179009],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014890097,0.000008900729,0.0019172276,0.00009700885,0.00000968281,0.00006518216,0.0000987076,0.00010624173,0.9905748,0.00004426116,0.00002249711,0.006906671],"study_design_scores_gemma":[0.000017145714,0.0012779355,0.03819881,0.000044562687,0.000058467154,0.0013435871,0.0002772014,0.0022550032,0.9548568,0.00025788136,0.0013851336,0.00002740337],"about_ca_topic_score_codex":0.00270733,"about_ca_topic_score_gemma":0.004874897,"teacher_disagreement_score":0.00270733,"about_ca_system_score_codex":0.00030228845,"about_ca_system_score_gemma":0.00036272543,"threshold_uncertainty_score":0.0053830743},"labels":[],"label_agreement":null},{"id":"W2062791478","doi":"10.3389/fninf.2014.00008","title":"Dipy, a library for the analysis of diffusion MRI data","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1462,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Diffusion; Data science; Information retrieval; Physics","score_opus":0.0558102439165102,"score_gpt":0.3277539162915454,"score_spread":0.2719436723750352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062791478","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018093849,0.0009174756,0.46555462,0.0003554848,0.00026845266,0.0004095232,0.035004415,0.490669,0.005011569],"genre_scores_gemma":[0.020575939,0.002220835,0.62700444,0.0013094846,0.0002103906,0.0027260666,0.08616072,0.24082525,0.018966828],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984213,0.00021912906,0.00021655898,0.0003642599,0.00059023453,0.00018847763],"domain_scores_gemma":[0.9976762,0.0009341468,0.00025388118,0.00041923288,0.00049283507,0.00022361282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002643627,0.0030399747,0.0026168758,0.002876928,0.0009982231,0.0030896096,0.004540981,0.0012919712,0.09584806],"category_scores_gemma":[0.008540688,0.0022781757,0.0032131914,0.0026266961,0.000980429,0.0042535854,0.0053090444,0.004492797,0.059600424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008615574,0.0002222117,0.0025323522,0.004542642,0.0007991542,0.00090069755,0.000555992,0.01099537,0.018742617,0.01828308,0.6877736,0.2537909],"study_design_scores_gemma":[0.0009202123,0.00022741279,0.0064081014,0.0007780087,0.00029950516,0.0018916063,0.00015198809,0.12520659,0.029925229,0.07090437,0.76281637,0.00047056848],"about_ca_topic_score_codex":0.0028484154,"about_ca_topic_score_gemma":0.00442436,"teacher_disagreement_score":0.09584806,"about_ca_system_score_codex":0.0009572738,"about_ca_system_score_gemma":0.003327929,"threshold_uncertainty_score":0.32064366},"labels":[],"label_agreement":null},{"id":"W2062848294","doi":"10.1038/jcbfm.2014.178","title":"Longitudinal Changes in Resting-State Brain Activity in a Capsular Infarct Model","year":2014,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute","funders":"","keywords":"Internal capsule; Medicine; Lesion; Thalamus; Positron emission tomography; Cardiology; Diaschisis; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Internal medicine; Psychology; Pathology; Cerebellum; Radiology; White matter","score_opus":0.04612121435652345,"score_gpt":0.3257840182514854,"score_spread":0.27966280389496195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062848294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99759334,0.00029452666,0.0015314316,0.000027546726,0.000014533031,0.00003966713,0.0002126545,0.000053115786,0.00023326548],"genre_scores_gemma":[0.99478924,0.0005351839,0.0017261785,0.000036125828,0.000012497963,0.00018899971,0.0009578893,0.00001607072,0.0017378358],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998622,0.000012215513,0.000010298193,0.000045373283,0.000030287161,0.00003967353],"domain_scores_gemma":[0.99978584,0.000013598386,0.00008245279,0.00003587881,0.000023536226,0.000058744667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022253576,0.00068380433,0.00048839406,0.000629809,0.00017512814,0.0002411622,0.00020961631,0.00020368646,0.0011750624],"category_scores_gemma":[0.00017043555,0.0001895386,0.00030232477,0.0002685878,0.0003402595,0.00023559676,0.00024915484,0.00075273967,0.00017641817],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022073276,0.0008538516,0.0043697297,0.000056592307,0.000081951504,0.0003009018,0.000062246916,0.00022720452,0.9864014,0.0000651412,0.00014091462,0.0052327407],"study_design_scores_gemma":[0.00022952136,0.026807215,0.21609321,0.000024576573,0.00041292846,0.0020186133,0.0002030317,0.0050910832,0.7469512,0.00017653483,0.0019378243,0.00005424559],"about_ca_topic_score_codex":0.0011071133,"about_ca_topic_score_gemma":0.0027558147,"teacher_disagreement_score":0.0011750624,"about_ca_system_score_codex":0.00028936742,"about_ca_system_score_gemma":0.00024440355,"threshold_uncertainty_score":0.0039310455},"labels":[],"label_agreement":null},{"id":"W2062861273","doi":"10.1016/j.neuroimage.2003.09.026","title":"Focal white matter density changes in schizophrenia: reduced inter-hemispheric connectivity","year":2003,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; White matter; Internal capsule; Anterior commissure; Psychology; Magnetic resonance imaging; Splenium; Schizophreniform disorder; Neuroscience; Anatomy; Psychosis; Medicine; Schizoaffective disorder; Radiology; Psychiatry","score_opus":0.04078560463149062,"score_gpt":0.3139178719540914,"score_spread":0.27313226732260076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062861273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982644,0.00018111397,0.00056759,0.00011762909,0.0000053498416,0.000009397425,0.00015670908,0.000017122122,0.0006808589],"genre_scores_gemma":[0.999361,0.00010197587,0.00023447484,0.000018999372,0.000009610313,0.000004814558,0.00006908375,0.0000048340103,0.00019523718],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999192,0.0000131828965,0.000010708792,0.00001598783,0.000025351057,0.000015490941],"domain_scores_gemma":[0.99955946,0.00008069851,0.00019813822,0.00003195393,0.000037428283,0.00009227729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026474977,0.0005290512,0.00035364117,0.0012642231,0.00041619583,0.00034919567,0.0003271951,0.0005855882,0.0038082912],"category_scores_gemma":[0.0010209962,0.00035851012,0.00021234486,0.0005078384,0.0005681041,0.0005325835,0.00037825748,0.00043518894,0.00020004818],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010260748,0.00043887875,0.18696097,0.00044226274,0.0008595636,0.014697815,0.0010139727,0.0021758971,0.74035245,0.0011748999,0.0008085344,0.040813953],"study_design_scores_gemma":[0.00012421761,0.0005259125,0.9731338,0.000011113391,0.00023090804,0.009269364,0.00040223656,0.0012102155,0.013408123,0.0015269261,0.00013870948,0.00001843441],"about_ca_topic_score_codex":0.006610776,"about_ca_topic_score_gemma":0.0071511604,"teacher_disagreement_score":0.006610776,"about_ca_system_score_codex":0.0003121649,"about_ca_system_score_gemma":0.00042176063,"threshold_uncertainty_score":0.013144612},"labels":[],"label_agreement":null},{"id":"W2063001897","doi":"10.1002/nbm.782","title":"The basis of anisotropic water diffusion in the nervous system – a technical review","year":2002,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4574,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Anisotropy; White matter; Fractional anisotropy; Neuroscience; Nervous system; Diffusion; Spinal cord; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Physics; Medicine; Biology; Optics; Radiology; Thermodynamics","score_opus":0.09857988122117965,"score_gpt":0.3996108336205039,"score_spread":0.30103095239932426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063001897","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00028483948,0.9964463,0.0010680004,0.00036118066,0.00021323077,0.0000055120763,0.000013836164,0.0000084385165,0.0015987094],"genre_scores_gemma":[0.0010241459,0.99726784,0.0009458645,0.00007363888,0.00016263117,0.0000063900734,0.000018416044,0.0000018682957,0.0004992193],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998416,0.000026782709,0.000031305768,0.000035803834,0.000052792355,0.000011716199],"domain_scores_gemma":[0.9997048,0.00014484156,0.000037071848,0.000011670639,0.00008722631,0.000014360087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006926166,0.0009514033,0.0014283552,0.0024372728,0.00032527206,0.0010170784,0.0010896927,0.0011889113,0.0019632783],"category_scores_gemma":[0.0006413791,0.0003815939,0.0004258355,0.0025254413,0.00090272696,0.002041719,0.00055169454,0.0010399459,0.0023229525],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006274789,0.000055148936,0.0002899242,0.016403222,0.00007192304,0.000734017,0.00014020996,0.0015303657,0.0076804548,0.020798052,0.0144085055,0.9378254],"study_design_scores_gemma":[0.000011321771,0.00011677036,0.0013209537,0.0033800164,0.00010980561,0.004015806,0.00015149229,0.0006163982,0.0038324553,0.016674034,0.9697062,0.00006470418],"about_ca_topic_score_codex":0.0013346119,"about_ca_topic_score_gemma":0.0012586316,"teacher_disagreement_score":0.0024372728,"about_ca_system_score_codex":0.0007615562,"about_ca_system_score_gemma":0.00125502,"threshold_uncertainty_score":0.006567836},"labels":[],"label_agreement":null},{"id":"W2063414088","doi":"10.1089/neu.2010.1721","title":"Bimanual Coordination and Corpus Callosum Microstructure in Young Adults with Traumatic Brain Injury: A Diffusion Tensor Imaging Study","year":2011,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"Vlaamse regering; Fonds Wetenschappelijk Onderzoek; Australian Government","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Traumatic brain injury; Motor coordination; Sensory system; White matter; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.06213891591036967,"score_gpt":0.34266421574404854,"score_spread":0.28052529983367885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063414088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996785,0.00009431209,0.000029505742,0.000010929272,0.0000018395438,0.000010030392,0.0000584109,0.0000015067479,0.00011505721],"genre_scores_gemma":[0.99958664,0.000076350676,0.00005754508,0.000017625938,0.0000069861912,0.000011663107,0.00011402393,8.588595e-7,0.00012825093],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985707,0.000012446951,0.00002597913,0.000042655145,0.00002836718,0.000033470194],"domain_scores_gemma":[0.99953175,0.000038210008,0.00021738243,0.000025503237,0.000067114976,0.000120164295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027311922,0.00041142863,0.0004180536,0.0013451293,0.00049444014,0.0004219116,0.00019953858,0.0006763825,0.0011115072],"category_scores_gemma":[0.0010513719,0.00029690866,0.0002761637,0.00067603285,0.00035399312,0.00043297905,0.0004283191,0.00032686992,0.00029129922],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035783133,0.00024302448,0.9905325,0.00003242611,0.00005353799,0.0016996078,0.0010583785,0.00004325203,0.0028476515,0.000027748167,0.00007852205,0.0030254652],"study_design_scores_gemma":[0.000004638359,0.00020295981,0.99833244,0.0000027725048,0.00001616854,0.0009550609,0.00029579384,0.000045414472,0.00007705382,0.0000112129155,0.000054341675,0.000002194973],"about_ca_topic_score_codex":0.006268432,"about_ca_topic_score_gemma":0.00621496,"teacher_disagreement_score":0.006268432,"about_ca_system_score_codex":0.00028047772,"about_ca_system_score_gemma":0.00034940962,"threshold_uncertainty_score":0.012463927},"labels":[],"label_agreement":null},{"id":"W2063571138","doi":"10.1002/mrm.24235","title":"Fast diffusion tensor imaging and tractography of the whole cervical spinal cord using point spread function corrected echo planar imaging","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; H. Lundbeck A/S; Lundbeckfonden","keywords":"Echo-planar imaging; Diffusion MRI; Point spread function; Tractography; Nuclear magnetic resonance; Planar; Spinal cord; Conus medullaris; Point (geometry); Echo (communications protocol); Physics; Magnetic resonance imaging; Tensor (intrinsic definition); Nuclear medicine; Medicine; Radiology; Computer science; Optics; Mathematics","score_opus":0.03672965975405169,"score_gpt":0.3230837666907384,"score_spread":0.2863541069366867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063571138","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3183379,0.005277458,0.6717309,0.00035395866,0.00008316114,0.00031950386,0.00072143,0.00064228463,0.002533484],"genre_scores_gemma":[0.51133746,0.0035560797,0.4822345,0.00006034647,0.00004489323,0.00018897619,0.00043700874,0.00013027232,0.0020104705],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997793,0.00007073665,0.000020417785,0.00004927878,0.00006187302,0.000018499539],"domain_scores_gemma":[0.9994418,0.00020288676,0.00009509855,0.00009652523,0.00013507184,0.000028530518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011005186,0.00069511286,0.00037164928,0.0017379622,0.00027780284,0.0007265948,0.00040390118,0.0007002165,0.0019670639],"category_scores_gemma":[0.00305817,0.00028759288,0.00044473272,0.0011380131,0.0005671532,0.0010512037,0.00039597476,0.00050585665,0.00036946475],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060957426,0.00007146093,0.0065233917,0.0010107536,0.00029690025,0.0013655346,0.0003734147,0.016732298,0.6691128,0.005951476,0.00075282075,0.29719958],"study_design_scores_gemma":[0.0002449803,0.0019459972,0.16592415,0.0003148839,0.00057104084,0.019725187,0.00046500048,0.2094261,0.5536126,0.029781736,0.01750435,0.00048390453],"about_ca_topic_score_codex":0.004742228,"about_ca_topic_score_gemma":0.0077557387,"teacher_disagreement_score":0.004742228,"about_ca_system_score_codex":0.00038981356,"about_ca_system_score_gemma":0.001092166,"threshold_uncertainty_score":0.009429276},"labels":[],"label_agreement":null},{"id":"W2064055696","doi":"10.1016/j.neuroimage.2007.03.015","title":"Minimum detectable change in water diffusion using 3-T magnetic resonance imaging","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Multiple Sclerosis Society; Health Research Board","keywords":"Fractional anisotropy; Diffusion MRI; Corpus callosum; Corticospinal tract; White matter; Putamen; Magnetic resonance imaging; Nuclear medicine; Optic radiation; Nuclear magnetic resonance; Effective diffusion coefficient; Psychology; Medicine; Physics; Neuroscience; Radiology","score_opus":0.07009384273387445,"score_gpt":0.35069178110586047,"score_spread":0.280597938371986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064055696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7718633,0.0039307415,0.21720168,0.00090956414,0.00013222809,0.00015432987,0.00091554126,0.0012382087,0.003654406],"genre_scores_gemma":[0.9270969,0.00086287153,0.07042131,0.00012387622,0.000057274843,0.000081309314,0.00027867823,0.00018658911,0.00089136383],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997843,0.00006588128,0.00002102211,0.000048604685,0.00005701859,0.000023312667],"domain_scores_gemma":[0.99923253,0.00039628267,0.00012107085,0.00007310679,0.000113966045,0.000063074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009399828,0.0005222915,0.00044144815,0.00083484047,0.00032162754,0.0009141145,0.00044648795,0.0012040737,0.0014167217],"category_scores_gemma":[0.003191659,0.00034970304,0.00034284996,0.000423452,0.00043155707,0.0013439922,0.000365116,0.00056169555,0.00023898562],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024983818,0.00014774223,0.009003332,0.00070490595,0.00022008909,0.0013236261,0.00039328611,0.0061618,0.84469706,0.0023331183,0.0017552723,0.13076143],"study_design_scores_gemma":[0.0002143586,0.0011113775,0.08982466,0.000104333034,0.00044838773,0.010005083,0.0003404498,0.089918986,0.78293496,0.018424062,0.0064678453,0.00020548496],"about_ca_topic_score_codex":0.0018353811,"about_ca_topic_score_gemma":0.002864466,"teacher_disagreement_score":0.0018353811,"about_ca_system_score_codex":0.00025777234,"about_ca_system_score_gemma":0.00054255564,"threshold_uncertainty_score":0.0049711466},"labels":[],"label_agreement":null},{"id":"W2064143475","doi":"10.1016/j.nicl.2012.09.010","title":"Mesial temporal sclerosis is linked with more widespread white matter changes in temporal lobe epilepsy","year":2012,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Temporal lobe; White matter; Cingulum (brain); Diffusion MRI; Hippocampal sclerosis; Corpus callosum; Epilepsy; Fractional anisotropy; Anatomy; Tractography; Limbic system; Neuroscience; Pathology; Psychology; Medicine; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.16390137192324708,"score_gpt":0.40934046853501627,"score_spread":0.2454390966117692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064143475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996829,0.00007536342,0.00004883913,0.000011753348,8.2906007e-7,0.0000019219412,0.00002212184,0.000003107806,0.00015320728],"genre_scores_gemma":[0.9997335,0.000060658982,0.00005387882,0.000008148243,0.0000038357225,0.0000018767125,0.000056152956,0.0000018305132,0.000080162994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998585,0.00002363119,0.00003245096,0.00004349883,0.00002469212,0.00001727217],"domain_scores_gemma":[0.99936026,0.00008007754,0.00041331683,0.000048177266,0.000035125762,0.00006310674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017893103,0.00033814076,0.000296492,0.0009940265,0.00027495492,0.00029276178,0.000118349744,0.0002594631,0.001661693],"category_scores_gemma":[0.00083016447,0.00018985983,0.0002448773,0.00068202306,0.00045108012,0.0003145096,0.0003417784,0.00019891343,0.00017021841],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010470191,0.00008150908,0.9350662,0.000061548286,0.00026653946,0.0058038537,0.00060525315,0.00021594058,0.048940454,0.00013346896,0.00009841881,0.0076797665],"study_design_scores_gemma":[0.0000085316115,0.000078875804,0.99431396,0.0000036060233,0.00002978305,0.0046864836,0.00008417605,0.000080423364,0.00056599296,0.000074218886,0.000070488175,0.00000351779],"about_ca_topic_score_codex":0.0017411188,"about_ca_topic_score_gemma":0.0024130645,"teacher_disagreement_score":0.0017411188,"about_ca_system_score_codex":0.00016293873,"about_ca_system_score_gemma":0.00014924009,"threshold_uncertainty_score":0.005558908},"labels":[],"label_agreement":null},{"id":"W2064172315","doi":"10.1007/s00247-012-2428-9","title":"Diffusion tensor imaging and fiber tractography in brain malformations","year":2013,"lang":"en","type":"review","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Diffusion MRI; Tractography; Neuroradiology; White matter; Medicine; Neuroscience; Magnetic resonance imaging; Radiology; Neurology; Psychology; Psychiatry","score_opus":0.06199651685777737,"score_gpt":0.3736353183857824,"score_spread":0.31163880152800505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064172315","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008042597,0.99917895,0.00014747186,0.00015414073,0.00008495939,0.0000022191036,0.0000094179195,0.0000041372286,0.00033815563],"genre_scores_gemma":[0.00046703126,0.9985751,0.0002657911,0.0001050927,0.00035389457,0.0000026543191,0.000019928024,0.0000015884256,0.00020892668],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99968386,0.00004553202,0.00008530247,0.0000615035,0.00010167259,0.000022160502],"domain_scores_gemma":[0.9986344,0.0007023577,0.00024309606,0.000034311557,0.00030889295,0.00007693392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010510159,0.0014128832,0.0018821985,0.0060494915,0.00030383453,0.0014677766,0.001144596,0.0015201515,0.002331565],"category_scores_gemma":[0.0020604637,0.000630827,0.0007023705,0.005542456,0.0012392375,0.002737197,0.0010101502,0.002103629,0.0016104095],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050860446,0.000063309584,0.0005434409,0.015709171,0.00012364612,0.00064478675,0.0000822896,0.00051158405,0.0010232131,0.002005069,0.022802867,0.9564398],"study_design_scores_gemma":[0.00004108555,0.00011639369,0.0035975834,0.0109715285,0.00053147186,0.0105061075,0.0001978117,0.00048467738,0.00094450824,0.0050608995,0.96745235,0.00009565202],"about_ca_topic_score_codex":0.002602409,"about_ca_topic_score_gemma":0.00432923,"teacher_disagreement_score":0.0060494915,"about_ca_system_score_codex":0.00064192,"about_ca_system_score_gemma":0.002293721,"threshold_uncertainty_score":0.007799804},"labels":[],"label_agreement":null},{"id":"W2064222308","doi":"10.1016/j.neurobiolaging.2014.05.038","title":"Empowering imaging biomarkers of Alzheimer's disease","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; Servier; Innogenetics; Eli Lilly and Company; AstraZeneca; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Synarc; Roche; Abbott Fund; National Institute on Aging; Alzheimer's Association; Genentech Foundation; Alzheimer's Drug Discovery Foundation; Amorfix Life Sciences","keywords":"Atrophy; Biomarker; Alzheimer's disease; Medicine; Internal medicine; Cardiology; Disease; Pathology; Biology","score_opus":0.03521939433595887,"score_gpt":0.35274108243259944,"score_spread":0.31752168809664055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064222308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2613234,0.2274769,0.44801113,0.017914787,0.0018673601,0.00038219793,0.0036481114,0.0032723937,0.03610368],"genre_scores_gemma":[0.53700346,0.06139786,0.38839123,0.0035152915,0.0015332205,0.00037561328,0.0010250843,0.00024519223,0.006513121],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99954104,0.00019997939,0.000031360716,0.00007295884,0.00011275176,0.00004194303],"domain_scores_gemma":[0.99838424,0.0009432613,0.00019143899,0.00012063477,0.0002855658,0.00007490256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022289432,0.0007448686,0.00076737907,0.0016578742,0.00029172056,0.0026033944,0.0007337515,0.0014231658,0.002961601],"category_scores_gemma":[0.0047650402,0.00046893692,0.00040094042,0.0010101382,0.00055918994,0.0025337443,0.0012344999,0.0012456516,0.0009571749],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007963699,0.00038378243,0.031192953,0.0026982697,0.00043022723,0.0007744297,0.00045556345,0.0037810549,0.29824004,0.02317947,0.015822966,0.6222449],"study_design_scores_gemma":[0.00040478108,0.0018053802,0.048155095,0.0019566508,0.001901743,0.008835876,0.0009958843,0.06478319,0.48409593,0.13351674,0.25320816,0.00034054145],"about_ca_topic_score_codex":0.000430963,"about_ca_topic_score_gemma":0.0011173253,"teacher_disagreement_score":0.002961601,"about_ca_system_score_codex":0.00023698117,"about_ca_system_score_gemma":0.0005898488,"threshold_uncertainty_score":0.011787951},"labels":[],"label_agreement":null},{"id":"W2064604305","doi":"10.1016/j.ejrad.2008.04.048","title":"A comparison of rapid-scanning X-ray fluorescence mapping and magnetic resonance imaging to localize brain iron distribution","year":2008,"lang":"en","type":"article","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg; Royal University Hospital; University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Pathology; Iron levels; In vivo; Susceptibility weighted imaging; Nuclear medicine; Radiology; Biology; Internal medicine","score_opus":0.0521245954782197,"score_gpt":0.32791722401583545,"score_spread":0.27579262853761577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064604305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84111905,0.013013833,0.13556461,0.0007511948,0.00025890526,0.0003643014,0.00047183235,0.00071696594,0.0077394187],"genre_scores_gemma":[0.9006405,0.0043761437,0.09144614,0.00027857156,0.00008779222,0.000106341715,0.0002599454,0.000372485,0.0024320674],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991954,0.0004065707,0.0000379068,0.00010824626,0.00020156443,0.000050402163],"domain_scores_gemma":[0.9947018,0.0041381917,0.0001984114,0.00030673112,0.000534082,0.0001207726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037216714,0.00055158784,0.0006850424,0.0014264012,0.0003164758,0.00088540616,0.0010793374,0.0010138854,0.0020050348],"category_scores_gemma":[0.00785616,0.00034942178,0.00029746853,0.00047083653,0.00057247403,0.0016406862,0.000536926,0.00045797028,0.00047356577],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.036382135,0.00073138875,0.03418474,0.0022666238,0.00057364185,0.0014840337,0.000883097,0.0064623947,0.5015483,0.0034057028,0.0019146239,0.41016328],"study_design_scores_gemma":[0.00223402,0.02004555,0.16917162,0.00043795854,0.002073976,0.037093636,0.0011323211,0.15835069,0.5878696,0.0045159594,0.016484449,0.00059019646],"about_ca_topic_score_codex":0.0014317185,"about_ca_topic_score_gemma":0.0014684973,"teacher_disagreement_score":0.0037216714,"about_ca_system_score_codex":0.00030331066,"about_ca_system_score_gemma":0.0006398704,"threshold_uncertainty_score":0.019682288},"labels":[],"label_agreement":null},{"id":"W2065568422","doi":"10.1097/npt.0b013e3182a3d353","title":"Motor Skill Learning Is Associated With Diffusion Characteristics of White Matter in Individuals With Chronic Stroke","year":2013,"lang":"en","type":"article","venue":"Journal of Neurologic Physical Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BGC Engineering (Canada)","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Psychology; Stroke (engine); Physical medicine and rehabilitation; Internal capsule; Motor learning; Rehabilitation; Physical therapy; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.02487291509713849,"score_gpt":0.2957891210714161,"score_spread":0.27091620597427757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065568422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997485,0.00005395059,0.00003318807,0.000012845563,9.744596e-7,0.0000025122883,0.000036020774,0.0000017215159,0.00011026689],"genre_scores_gemma":[0.9997453,0.000031997806,0.00005255029,0.000004798955,0.0000024568865,0.0000028443199,0.000079358026,7.473676e-7,0.00007986239],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998572,0.000015668984,0.000026590013,0.000054361593,0.000022532717,0.000023644323],"domain_scores_gemma":[0.99891925,0.00015168119,0.000679537,0.000054924283,0.000091315735,0.00010327514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000282633,0.00030136964,0.00028569196,0.0007286064,0.00038949022,0.00032683503,0.00017138416,0.00048740883,0.001379798],"category_scores_gemma":[0.0017234061,0.0001511425,0.00016597247,0.000589434,0.00033700565,0.00034898665,0.00034678614,0.00030867162,0.00014315103],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015547834,0.00004630577,0.9965848,0.000009365381,0.00003856625,0.00008141243,0.00013296319,0.000053253818,0.0010000053,0.000011642695,0.00003109697,0.0018550336],"study_design_scores_gemma":[0.0000014465603,0.000058530884,0.9996191,0.0000015333987,0.0000064354845,0.00013708317,0.00004571978,0.000050055434,0.00005156547,0.000012875162,0.000014470054,0.0000010847997],"about_ca_topic_score_codex":0.004059916,"about_ca_topic_score_gemma":0.0060019707,"teacher_disagreement_score":0.004059916,"about_ca_system_score_codex":0.0002103816,"about_ca_system_score_gemma":0.0002107944,"threshold_uncertainty_score":0.008072555},"labels":[],"label_agreement":null},{"id":"W2065679937","doi":"10.3389/fnagi.2014.00142","title":"Correlations between Limbic White Matter and Cognitive Function in Temporal-Lobe Epilepsy, Preliminary Findings","year":2014,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates","keywords":"Fornix; Fractional anisotropy; Temporal lobe; Diffusion MRI; Cingulum (brain); Hippocampal sclerosis; White matter; Psychology; Limbic system; Neuroscience; Epilepsy; Neuropsychology; Hippocampus; Hippocampal formation; Mesial temporal lobe epilepsy; Cognition; Medicine; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.028998416454080186,"score_gpt":0.29729655322361,"score_spread":0.2682981367695298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065679937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994166,0.0002123685,0.000057672296,0.000014352594,8.648378e-7,0.0000025583372,0.000058667774,0.0000015761564,0.00023533315],"genre_scores_gemma":[0.999703,0.00007172906,0.00007470481,0.0000073625743,0.0000029592034,0.0000018615397,0.00008329371,6.0594397e-7,0.000054491265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994385,0.000009809317,0.000012039827,0.0000147649735,0.000010539046,0.000009063505],"domain_scores_gemma":[0.9995345,0.00009911394,0.00022795236,0.000036435842,0.000050343737,0.000051595292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024499194,0.00025094982,0.00015266103,0.00060500455,0.00019954315,0.0002501202,0.00009055544,0.00018972773,0.0009162116],"category_scores_gemma":[0.0011000695,0.00007916393,0.00013265127,0.00034003815,0.00030392522,0.00023845486,0.00018046111,0.0001379366,0.00011428366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055139774,0.000024425564,0.98307276,0.00003331613,0.000066905406,0.0008335426,0.00016009125,0.00012806481,0.009330504,0.00003012665,0.000047487803,0.0057213805],"study_design_scores_gemma":[0.0000051702627,0.00014450283,0.99781215,0.0000022844802,0.000020172383,0.0011367893,0.0000739408,0.000096870106,0.0005902314,0.00004495501,0.00007065432,0.0000021767626],"about_ca_topic_score_codex":0.0020152684,"about_ca_topic_score_gemma":0.0047874837,"teacher_disagreement_score":0.0020152684,"about_ca_system_score_codex":0.00014683187,"about_ca_system_score_gemma":0.00014491253,"threshold_uncertainty_score":0.004007101},"labels":[],"label_agreement":null},{"id":"W2065883186","doi":"10.1002/hbm.20598","title":"Robust S1, S2, and thalamic activations in individual subjects with vibrotactile stimulation at 1.5 and 3.0 T","year":2008,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Thalamus; Functional magnetic resonance imaging; Somatosensory system; Sensory stimulation therapy; Neuroscience; Thalamic stimulator; Sensory system; Stimulation; Movement disorders; Psychology; Deep brain stimulation; Magnetic resonance imaging; Medicine; Radiology; Pathology; Parkinson's disease","score_opus":0.16101917893180656,"score_gpt":0.3273490108830669,"score_spread":0.16632983195126033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065883186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99728477,0.000072595314,0.0022850789,0.000015407868,0.0000042975444,0.000021149219,0.000051820316,0.00002459767,0.00024030972],"genre_scores_gemma":[0.9977309,0.000047013822,0.0016696884,0.000020660855,0.000008577709,0.000037016373,0.00008277199,0.000013265765,0.00039015972],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998704,0.00003053436,0.000008509707,0.000052365653,0.00001620454,0.00002203933],"domain_scores_gemma":[0.99982077,0.00007978376,0.000022299802,0.000023422917,0.000023010876,0.00003074448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004536486,0.00032609922,0.00038082837,0.00017321219,0.00021046604,0.00019896634,0.00010128271,0.00027940454,0.001500732],"category_scores_gemma":[0.0005474991,0.00018438433,0.00023126797,0.00010169934,0.00048419533,0.00013609524,0.0002590419,0.00021680437,0.00017313028],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002559117,0.00019446375,0.006645994,0.000070959075,0.000063517706,0.00047587973,0.00053995044,0.0007814429,0.97883487,0.00006287465,0.00012075945,0.009650186],"study_design_scores_gemma":[0.00034230266,0.010029499,0.7508759,0.0000200891,0.00033781852,0.0049916296,0.00056561147,0.005691763,0.22525239,0.00055812666,0.0012197865,0.0001150801],"about_ca_topic_score_codex":0.0008849882,"about_ca_topic_score_gemma":0.0016771188,"teacher_disagreement_score":0.001500732,"about_ca_system_score_codex":0.00011279641,"about_ca_system_score_gemma":0.00015193954,"threshold_uncertainty_score":0.0050204396},"labels":[],"label_agreement":null},{"id":"W2066276013","doi":"10.1155/2012/143705","title":"Characterization of DTI Indices in the Cervical, Thoracic, and Lumbar Spinal Cord in Healthy Humans","year":2012,"lang":"en","type":"article","venue":"Radiology Research and Practice","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; International Spinal Research Trust","keywords":"Medicine; Lumbar; Spinal cord; Anatomy; Thoracic vertebrae; Lumbar vertebrae","score_opus":0.30846501872392934,"score_gpt":0.5519831817347898,"score_spread":0.24351816301086043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066276013","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969694,0.0007395708,0.0015233923,0.000036332734,0.0000036005856,0.000015681318,0.00023315247,0.000016731756,0.00046223222],"genre_scores_gemma":[0.9972255,0.00033458674,0.001815464,0.000022786617,0.00000919792,0.000011263435,0.00027604552,0.0000069029384,0.00029820835],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999249,0.000011768185,0.000007502175,0.000035101126,0.000012911172,0.000007883212],"domain_scores_gemma":[0.9996861,0.00006235444,0.00012301859,0.000031744195,0.00006036601,0.000036384627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023371472,0.00021856691,0.00020035665,0.0006496103,0.00021706436,0.00027130332,0.00014115,0.0003494466,0.0007654283],"category_scores_gemma":[0.0012658426,0.00011040506,0.000071772534,0.0002529361,0.0002895399,0.00030839452,0.00010685129,0.000120355246,0.00016925832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002117729,0.00021932945,0.56423527,0.0005148625,0.00029937038,0.002272073,0.0012872022,0.0019278282,0.34084103,0.00051508,0.0011291233,0.08464113],"study_design_scores_gemma":[0.00001590379,0.00047147533,0.98623484,0.000018408453,0.000044593962,0.0029052806,0.0001647982,0.0011984712,0.00802373,0.0002181702,0.0006920533,0.00001231829],"about_ca_topic_score_codex":0.0025187356,"about_ca_topic_score_gemma":0.004560248,"teacher_disagreement_score":0.0025187356,"about_ca_system_score_codex":0.00016787334,"about_ca_system_score_gemma":0.00015544516,"threshold_uncertainty_score":0.0050081015},"labels":[],"label_agreement":null},{"id":"W2066289270","doi":"10.1159/000089233","title":"Regional Variability in the Prevalence of Cerebral White Matter Lesions: An MRI Study in 9 European Countries (CASCADE)","year":2005,"lang":"en","type":"article","venue":"Neuroepidemiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"European Commission","keywords":"Medicine; Dementia; Population; Hyperintensity; European population; Disease; Demography; Gerontology; Pediatrics; Environmental health; Pathology; Magnetic resonance imaging","score_opus":0.10366682734672028,"score_gpt":0.3945010594416823,"score_spread":0.290834232094962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066289270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99970394,0.000046980636,0.000025162202,0.0000072821013,8.390673e-7,0.0000043994264,0.000100948346,0.0000011329747,0.00010928659],"genre_scores_gemma":[0.9993206,0.00006333666,0.00009722764,0.000022174012,0.0000030463152,0.000010007123,0.00040785395,0.0000012858501,0.00007437099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99953413,0.00015326426,0.00006215748,0.00013522894,0.000046296394,0.000068848276],"domain_scores_gemma":[0.99941015,0.00009719408,0.00021341677,0.000061714716,0.00008827235,0.00012927334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091120176,0.00043895913,0.0004247224,0.0010723149,0.00041885796,0.00060107757,0.00022003749,0.00049170735,0.00074258],"category_scores_gemma":[0.0015449551,0.00037601992,0.00044009124,0.0008670027,0.00037898042,0.00039571172,0.000676652,0.0002664728,0.00020197839],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024492035,0.00003969485,0.9969374,0.000010847042,0.00008152951,0.00028407952,0.00042974594,0.000045801262,0.000395459,0.000024270483,0.00009695211,0.0014093246],"study_design_scores_gemma":[0.000016826847,0.000069033114,0.9993211,0.0000029294658,0.00001742967,0.0002483876,0.00014642952,0.00004142305,0.000038082864,0.00000892708,0.00008711977,0.0000023629493],"about_ca_topic_score_codex":0.00951683,"about_ca_topic_score_gemma":0.008251298,"teacher_disagreement_score":0.00951683,"about_ca_system_score_codex":0.000351573,"about_ca_system_score_gemma":0.0002049424,"threshold_uncertainty_score":0.018922865},"labels":[],"label_agreement":null},{"id":"W2066385232","doi":"10.1002/hbm.22018","title":"Callosal fiber length and interhemispheric connectivity in adults with autism: Brain overgrowth and underconnectivity","year":2012,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Corpus callosum; Psychology; Neuroscience; Tractography; Autism spectrum disorder; Brain size; Diffusion MRI; Fiber; Autism; Audiology; Anatomy; Biology; Magnetic resonance imaging; Developmental psychology; Medicine; Chemistry","score_opus":0.043277788979686434,"score_gpt":0.31120925597148474,"score_spread":0.2679314669917983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066385232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999739,0.00006507671,0.00004931276,0.000014825082,5.55829e-7,0.0000010158958,0.000034274115,0.0000024162953,0.0000935756],"genre_scores_gemma":[0.99963284,0.00004442977,0.00018627677,0.0000043923137,0.0000018208402,0.0000032968392,0.00006222008,0.000001653443,0.00006313045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998554,0.000024797455,0.000022680182,0.00004660306,0.000035639237,0.00001488623],"domain_scores_gemma":[0.9987197,0.00029979437,0.0006801183,0.00008316997,0.000084559666,0.00013271246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026087498,0.00028701304,0.00020455077,0.0008861421,0.00018934983,0.00030345962,0.00014316237,0.0004563418,0.001277211],"category_scores_gemma":[0.002269053,0.00015644157,0.00013104916,0.00035026108,0.0003932746,0.0005071237,0.00038455153,0.00024149167,0.00013772881],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029960636,0.000034064025,0.9820387,0.00002372095,0.000048952934,0.0003908819,0.00074214314,0.00019659106,0.009675837,0.00006616437,0.00007735193,0.0064060013],"study_design_scores_gemma":[0.0000020195928,0.000032747,0.9988249,0.0000020430152,0.000007335749,0.0005881951,0.00013943866,0.00013580376,0.00020184222,0.00003210651,0.00003183172,0.0000018025163],"about_ca_topic_score_codex":0.0029879597,"about_ca_topic_score_gemma":0.004916861,"teacher_disagreement_score":0.0029879597,"about_ca_system_score_codex":0.00016660655,"about_ca_system_score_gemma":0.00012578363,"threshold_uncertainty_score":0.005941093},"labels":[],"label_agreement":null},{"id":"W2067121405","doi":"10.1017/s0033291715000239","title":"Resilience and corpus callosum microstructure in adolescence","year":2015,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; SickKids Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Hospital for Sick Children; Université de Montréal","funders":"Medical Research Council; Fondation de France; Bundesministerium für Bildung und Forschung; Assistance publique-Hôpitaux de Paris; Agence Nationale de la Recherche; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Fractional anisotropy; Psychology; White matter; Anterior cingulate cortex; Diffusion MRI; Neuroticism; Clinical psychology; Personality; Psychiatry; Medicine; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.13766458626818556,"score_gpt":0.4330908503318179,"score_spread":0.2954262640636323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067121405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991999,0.0002865652,0.00008722126,0.000034301826,0.000001973996,0.0000046453692,0.00010013422,0.00000508934,0.0002800201],"genre_scores_gemma":[0.9995943,0.0001109423,0.0001261924,0.0000064099427,0.000001987439,0.000005526137,0.00007403197,0.0000021311416,0.00007855098],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999,0.000017954591,0.0000070086107,0.000033193097,0.000019426803,0.000022413828],"domain_scores_gemma":[0.9991486,0.00012109959,0.00047672886,0.000036707715,0.00009110113,0.00012581034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030087182,0.00020619841,0.00013227083,0.00094366196,0.00029294772,0.0003823207,0.00016084354,0.00023997316,0.0015708123],"category_scores_gemma":[0.0017418691,0.00011332285,0.00013463039,0.00043054417,0.0003851112,0.00030638004,0.00036570974,0.0002740575,0.00008494816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025203085,0.000052680323,0.98107016,0.00005116647,0.00006445517,0.00037406728,0.0008295599,0.00018770398,0.0058069653,0.0003265253,0.0002546022,0.01073016],"study_design_scores_gemma":[8.3058865e-7,0.000021333337,0.99920493,0.000009590667,0.000006010897,0.00023594324,0.00010539041,0.00006630745,0.00018241655,0.00006820102,0.00009769596,0.0000012924813],"about_ca_topic_score_codex":0.0045332387,"about_ca_topic_score_gemma":0.0043126117,"teacher_disagreement_score":0.0045332387,"about_ca_system_score_codex":0.00031080333,"about_ca_system_score_gemma":0.00027479007,"threshold_uncertainty_score":0.009013712},"labels":[],"label_agreement":null},{"id":"W2067187753","doi":"10.1177/1073858407300598","title":"Neural Substrates of Blindsight After Hemispherectomy","year":2007,"lang":"en","type":"review","venue":"The Neuroscientist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Blindsight; Hemispherectomy; Psychology; Neuroscience; Cognitive psychology; Neural substrate; Neural correlates of consciousness; Cognitive science; Epilepsy; Visual perception; Perception; Cognition","score_opus":0.20662972790212267,"score_gpt":0.45329818095269264,"score_spread":0.24666845305056997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067187753","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00069293746,0.9976816,0.00015014812,0.0001578014,0.0000817665,0.0000025879092,0.0000057898274,0.000009290119,0.0012180478],"genre_scores_gemma":[0.003453343,0.99536514,0.00014931614,0.0001293381,0.00017780208,0.0000050492235,0.000018327677,0.0000010321759,0.0007005779],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999207,0.000012632846,0.00001494205,0.00001666372,0.000026043348,0.0000090987505],"domain_scores_gemma":[0.9998969,0.00004738097,0.000022979359,0.000003604229,0.000021571923,0.0000075323464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024031912,0.00053752196,0.0008602573,0.0013320169,0.00016745496,0.00045807922,0.00045173563,0.0007288786,0.0012631532],"category_scores_gemma":[0.00041998446,0.00012220116,0.0002705671,0.0011179567,0.0004819691,0.0006226384,0.0002650056,0.00059282157,0.0009309563],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008271137,0.000040407835,0.00078601466,0.004864791,0.000052137955,0.0025595936,0.000059095873,0.00028821622,0.0026140069,0.0014989827,0.0108492635,0.9763049],"study_design_scores_gemma":[0.00010732702,0.00054324616,0.037239667,0.0085637225,0.00031882722,0.08683397,0.00045877422,0.00046120406,0.006072623,0.009821339,0.84949976,0.000079578596],"about_ca_topic_score_codex":0.0010152603,"about_ca_topic_score_gemma":0.0013421591,"teacher_disagreement_score":0.0013320169,"about_ca_system_score_codex":0.00042835358,"about_ca_system_score_gemma":0.00063853996,"threshold_uncertainty_score":0.0042256117},"labels":[],"label_agreement":null},{"id":"W2067560632","doi":"10.1016/j.neuroimage.2012.11.065","title":"Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Human brain; Somatosensory system; Secondary somatosensory cortex; Cortex (anatomy); Cerebral cortex; Diffusion; Nuclear magnetic resonance; Anisotropy; Neuroscience; Chemistry; Physics; Psychology; Optics; Magnetic resonance imaging; Medicine","score_opus":0.09156158250146589,"score_gpt":0.4080880453359844,"score_spread":0.3165264628345185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067560632","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46438125,0.0008486657,0.5314557,0.00022781223,0.00004253222,0.00006425108,0.00059455074,0.00094375043,0.0014414759],"genre_scores_gemma":[0.8353657,0.0007555133,0.16239476,0.000030963107,0.000036547288,0.0000352871,0.0003807485,0.0002120787,0.00078834634],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999325,0.000018275518,0.0000041105077,0.000013656568,0.00002138855,0.000010109452],"domain_scores_gemma":[0.99969006,0.00011946774,0.000040450253,0.000034516343,0.00009325023,0.00002234361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038207477,0.0004914583,0.00035112398,0.0018912462,0.00023985191,0.0009537952,0.00026309004,0.0004345802,0.00096694176],"category_scores_gemma":[0.0012709373,0.00018496277,0.0003544154,0.0012439928,0.00028752163,0.0006701653,0.00031363705,0.00041198084,0.00028070994],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008232567,0.00012752065,0.01319197,0.00028807577,0.00018822907,0.00028234415,0.00031967464,0.03538124,0.59652424,0.009238345,0.00217971,0.34145543],"study_design_scores_gemma":[0.00008477927,0.00020662959,0.04118012,0.000030033376,0.000180339,0.0012433794,0.00027487442,0.81179816,0.12528616,0.016728964,0.00289196,0.000094582974],"about_ca_topic_score_codex":0.0025822301,"about_ca_topic_score_gemma":0.0035380058,"teacher_disagreement_score":0.0025822301,"about_ca_system_score_codex":0.00024515527,"about_ca_system_score_gemma":0.00056849245,"threshold_uncertainty_score":0.0051344633},"labels":[],"label_agreement":null},{"id":"W2067685553","doi":"10.1007/s11682-013-9225-4","title":"Neuronal fiber bundle lengths in healthy adult carriers of the ApoE4 allele: A quantitative tractography DTI study","year":2013,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; DNA Genotek","keywords":"Tractography; Neuropsychology; Bundle; Allele; Neuroscience; Fiber bundle; Fiber; Diffusion MRI; Medicine; Psychology; Anatomy; Biology; Radiology; Magnetic resonance imaging; Genetics; Materials science; Cognition; Gene","score_opus":0.04570244697338806,"score_gpt":0.3642923779320556,"score_spread":0.31858993095866756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067685553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976796,0.000025452668,0.00008589833,0.0000036882436,5.843122e-7,0.0000017984684,0.00003780646,0.000001925275,0.00007481134],"genre_scores_gemma":[0.9994393,0.000029208584,0.00015175177,0.000004101445,0.0000022836384,0.0000027770855,0.0000648743,0.0000028162244,0.00030285164],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999331,0.000011763423,0.00000812496,0.000025617048,0.0000101822,0.000011300255],"domain_scores_gemma":[0.9996642,0.00007661197,0.000102944214,0.00004133891,0.000054248205,0.00006070003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002865564,0.00028455132,0.000267492,0.00062367506,0.00031299965,0.00025493884,0.0001730047,0.00035265269,0.0015025059],"category_scores_gemma":[0.0008416297,0.00021908685,0.00013196822,0.00031384826,0.00032158184,0.00038574022,0.00015310843,0.0001592526,0.000244556],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0057415017,0.00065711135,0.89390296,0.000040256247,0.00025724608,0.002872842,0.0011649572,0.00039966044,0.07975412,0.00024709213,0.00020833375,0.0147539405],"study_design_scores_gemma":[0.000022068867,0.00043960064,0.9965912,0.0000017309263,0.000042451768,0.0013255251,0.00014758525,0.00048119892,0.00079728913,0.000068531415,0.00007749196,0.0000054327325],"about_ca_topic_score_codex":0.0055526863,"about_ca_topic_score_gemma":0.0049047004,"teacher_disagreement_score":0.0055526863,"about_ca_system_score_codex":0.00022392775,"about_ca_system_score_gemma":0.0001449023,"threshold_uncertainty_score":0.011040747},"labels":[],"label_agreement":null},{"id":"W2067685645","doi":"10.1109/tip.2009.2035886","title":"On Approximation of Orientation Distributions by Means of Spherical Ridgelets","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Diffusion MRI; Voxel; Orientation (vector space); Computer science; Computation; Artificial intelligence; Visualization; Image resolution; Tractography; Multiresolution analysis; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Wavelet transform; Wavelet; Discrete wavelet transform; Geometry","score_opus":0.02645157815047293,"score_gpt":0.33669853003422534,"score_spread":0.3102469518837524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067685645","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0041185413,0.00009421358,0.9950218,0.00005616615,0.000020891623,0.000012079227,0.000021184082,0.00008692599,0.0005681722],"genre_scores_gemma":[0.23107222,0.0015480737,0.75997114,0.00011930576,0.00018274221,0.0001687826,0.00043471137,0.00026378134,0.006239323],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995871,0.0001757875,0.000018621573,0.000046419103,0.00013635217,0.00003581166],"domain_scores_gemma":[0.99900275,0.0005436084,0.000105550724,0.00011507367,0.00019437294,0.000038664246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001270867,0.000881686,0.0007975723,0.0007440637,0.00023857718,0.0009025283,0.00088916876,0.0008958196,0.001397273],"category_scores_gemma":[0.0036488043,0.00066180975,0.0009725847,0.00086916157,0.0007267136,0.0010444188,0.0008726723,0.0013403703,0.001170768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009755955,0.000047864967,0.00047451805,0.00008707698,0.00003770471,0.00012657657,0.000104115185,0.84445906,0.0068838056,0.05955568,0.0020717934,0.08605416],"study_design_scores_gemma":[0.0000015063557,0.0000057841307,0.00002471894,0.0000021880717,0.0000012689676,0.0000091354605,0.0000021379067,0.9972153,0.00021854525,0.0021946037,0.00032225513,0.0000026115463],"about_ca_topic_score_codex":0.0030327472,"about_ca_topic_score_gemma":0.0020034097,"teacher_disagreement_score":0.0030327472,"about_ca_system_score_codex":0.00043893716,"about_ca_system_score_gemma":0.0006487855,"threshold_uncertainty_score":0.0067210197},"labels":[],"label_agreement":null},{"id":"W2068145240","doi":"10.1016/j.jpeds.2010.05.026","title":"Extreme Premature Birth is not Associated with Impaired Development of Brain Microstructure","year":2010,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Medicine; Gestation; Magnetic resonance imaging; Gestational age; Internal medicine; Pregnancy; Radiology; Biology","score_opus":0.03924320301362916,"score_gpt":0.29975218516747376,"score_spread":0.2605089821538446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068145240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99760914,0.00067019265,0.00044681702,0.000099401725,0.000028764529,0.0000050368644,0.0002874469,0.00003055609,0.0008225664],"genre_scores_gemma":[0.99858034,0.0004488272,0.00043685458,0.000029764582,0.000029067545,0.000007954919,0.00023064963,0.00001488515,0.00022176834],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897075,0.00022847566,0.00013924479,0.00025107246,0.0002450789,0.00016546281],"domain_scores_gemma":[0.9887,0.0025481207,0.006423164,0.0011563145,0.00038913178,0.00078324066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010243903,0.00065392273,0.0009143845,0.0018240876,0.00044188494,0.0008260612,0.0010867831,0.0010136483,0.0027260003],"category_scores_gemma":[0.008062746,0.0005145329,0.0006786463,0.0012583241,0.0011023475,0.0005670757,0.0010692532,0.0012055477,0.0002877791],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041991994,0.00014984596,0.9253278,0.00026553476,0.000606772,0.011279299,0.00046733767,0.0004311039,0.0390294,0.0005325768,0.00032006737,0.017390952],"study_design_scores_gemma":[0.000010173611,0.00031758417,0.9904945,0.000033074197,0.0001104402,0.006156357,0.00010461555,0.00016236678,0.0020176927,0.00038875805,0.00018977784,0.0000146644825],"about_ca_topic_score_codex":0.0012627274,"about_ca_topic_score_gemma":0.0009990808,"teacher_disagreement_score":0.0027260003,"about_ca_system_score_codex":0.00025150695,"about_ca_system_score_gemma":0.0005987238,"threshold_uncertainty_score":0.009119332},"labels":[],"label_agreement":null},{"id":"W2068330969","doi":"10.1371/journal.pone.0056733","title":"The Relationship between Cortical Blood Flow and Sub-Cortical White-Matter Health across the Adult Age Span","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institutes of Health; Canadian Institutes of Health Research; Centre d'Imagerie BioMédicale","keywords":"White matter; Diffusion MRI; Cerebral blood flow; Neuroscience; Medicine; Young adult; Physiology; Pathology; Psychology; Cardiology; Magnetic resonance imaging; Internal medicine","score_opus":0.11822694693061801,"score_gpt":0.347580490753677,"score_spread":0.22935354382305895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068330969","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987967,0.00061292184,0.0001941367,0.000029078084,0.0000029065593,0.0000027819005,0.00009593074,0.0000053036447,0.00026026813],"genre_scores_gemma":[0.99940443,0.0002032351,0.00013159365,0.000014923572,0.000007395683,0.0000031482382,0.00006952497,0.0000012474289,0.00016451167],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998584,0.000021707046,0.000010846244,0.00006320705,0.000017313927,0.000028587903],"domain_scores_gemma":[0.99923205,0.00013184402,0.00033208897,0.00007293058,0.00012522697,0.00010589925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044332075,0.00020873237,0.00021953309,0.0007837789,0.00016845281,0.0002949712,0.00015669373,0.00027311663,0.0006997105],"category_scores_gemma":[0.0016781547,0.00012749886,0.000116638614,0.0003865733,0.00027285403,0.00033704887,0.00032680944,0.00023042849,0.00012275192],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003590027,0.00005525957,0.98073477,0.000023755063,0.00013640897,0.00013742628,0.00051560363,0.00013948197,0.0060432716,0.00007380134,0.00011227825,0.011668936],"study_design_scores_gemma":[7.573546e-7,0.00005852406,0.99958545,0.0000011415261,0.000010212204,0.000057513356,0.000047821868,0.000055449003,0.00011339862,0.00003272181,0.00003609199,9.082996e-7],"about_ca_topic_score_codex":0.0029558996,"about_ca_topic_score_gemma":0.003459731,"teacher_disagreement_score":0.0029558996,"about_ca_system_score_codex":0.00012340752,"about_ca_system_score_gemma":0.00011013609,"threshold_uncertainty_score":0.005877435},"labels":[],"label_agreement":null},{"id":"W2068562622","doi":"10.1016/j.neuroimage.2007.10.048","title":"Tactile-associated recruitment of the cervical cord is altered in patients with multiple sclerosis","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Fondazione Italiana Sclerosi Multipla","keywords":"Spinal cord; Multiple sclerosis; Cord; Medicine; Voxel; White matter; Magnetic resonance imaging; Functional magnetic resonance imaging; Lesion; Pathology; Radiology; Surgery; Psychiatry","score_opus":0.14085646941828112,"score_gpt":0.33817751071618235,"score_spread":0.19732104129790123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068562622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887735,0.00027005587,0.00008694781,0.000055900204,0.0000032922717,0.0000041269336,0.00007384233,0.0000078378425,0.0006206426],"genre_scores_gemma":[0.99959713,0.0000839317,0.000056373963,0.000025222289,0.000009581539,0.000003992763,0.00004655691,0.000002375527,0.00017497373],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987876,0.00002259022,0.000014833151,0.00003140813,0.000027263148,0.00002515319],"domain_scores_gemma":[0.9990522,0.0002931355,0.00044656324,0.00004515715,0.000083016326,0.00007984378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018706184,0.000282795,0.00035346084,0.0009851181,0.00035797394,0.0003714189,0.00027173277,0.00067796884,0.0033804274],"category_scores_gemma":[0.0024521262,0.00016824543,0.00014354305,0.0006624963,0.00044688027,0.00041424172,0.00027729318,0.00029167358,0.00030743427],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004151168,0.00022931321,0.8362759,0.00030007993,0.00023219004,0.008723232,0.00089032925,0.00041685282,0.12212228,0.00012556452,0.0004419171,0.026091134],"study_design_scores_gemma":[0.000009572086,0.000116125804,0.9957409,0.0000056352756,0.000028922157,0.0028531223,0.000096926764,0.00012251522,0.000887271,0.00006866749,0.00006667482,0.000003641611],"about_ca_topic_score_codex":0.0030061633,"about_ca_topic_score_gemma":0.003780106,"teacher_disagreement_score":0.0033804274,"about_ca_system_score_codex":0.00024990638,"about_ca_system_score_gemma":0.00019067804,"threshold_uncertainty_score":0.01130861},"labels":[],"label_agreement":null},{"id":"W2069243625","doi":"10.1016/j.neuroimage.2012.06.064","title":"Rapid whole cerebrum myelin water imaging using a 3D GRASE sequence","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":276,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Cerebrum; Sequence (biology); Myelin; Chemistry; Neuroscience; Biology; Central nervous system; Biochemistry","score_opus":0.132648105994973,"score_gpt":0.37151191621320556,"score_spread":0.23886381021823255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069243625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12508942,0.0029510634,0.8566552,0.0021518925,0.000284548,0.00056036364,0.0013509174,0.002263563,0.008693031],"genre_scores_gemma":[0.27421388,0.0038529246,0.71054304,0.0008899986,0.00024719085,0.00068922155,0.0013720612,0.0011539137,0.0070378142],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985266,0.000035405563,0.000016623731,0.000025651338,0.000044571665,0.000025169235],"domain_scores_gemma":[0.9995054,0.00019016648,0.00006213288,0.000060810664,0.000110383786,0.00007122415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012249447,0.0010765838,0.0005279341,0.0015253947,0.0005592755,0.0015661787,0.00072103244,0.0024776515,0.0050404808],"category_scores_gemma":[0.002817097,0.0009101857,0.0004636439,0.0008891099,0.00073896954,0.0020988868,0.0012540072,0.0019868133,0.001309337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016746452,0.00022731384,0.0036042484,0.0014879688,0.00032231855,0.0038832761,0.00065899757,0.014636782,0.7392114,0.015672574,0.014292097,0.2043283],"study_design_scores_gemma":[0.0007708348,0.0016433626,0.017459797,0.0007018919,0.00072646263,0.028524617,0.0009309053,0.21754156,0.61177534,0.03914724,0.080226675,0.00055133697],"about_ca_topic_score_codex":0.001241212,"about_ca_topic_score_gemma":0.0024662297,"teacher_disagreement_score":0.0050404808,"about_ca_system_score_codex":0.00028066014,"about_ca_system_score_gemma":0.0013467476,"threshold_uncertainty_score":0.016862035},"labels":[],"label_agreement":null},{"id":"W2069494733","doi":"10.1371/journal.pone.0073021","title":"Diffusion Weighted Image Denoising Using Overcomplete Local PCA","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":447,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Agence Nationale de la Recherche","keywords":"Noise reduction; Pattern recognition (psychology); Artificial intelligence; Noise (video); Computer science; Diffusion; Principal component analysis; Filter (signal processing); Non-local means; Diffusion MRI; Signal-to-noise ratio (imaging); Diffusion process; Mathematics; Image denoising; Image (mathematics); Computer vision; Statistics; Physics; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.12655914984200248,"score_gpt":0.31722485969303177,"score_spread":0.1906657098510293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069494733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013055266,0.00026596698,0.98575944,0.00006545664,0.00002151689,0.000018123825,0.000036414116,0.000301621,0.00047617065],"genre_scores_gemma":[0.17859283,0.0011001638,0.81669074,0.0000769094,0.00006654671,0.00007211807,0.0003254965,0.00015900929,0.0029162467],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995833,0.000083182604,0.000026712973,0.00011128973,0.0001707153,0.000024728844],"domain_scores_gemma":[0.9994355,0.00016452887,0.00008204792,0.00011607525,0.00017414178,0.000027572813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008971244,0.0007706981,0.0008308704,0.0007566095,0.00028084405,0.0006502309,0.0005151179,0.0007521958,0.0007959108],"category_scores_gemma":[0.0019446728,0.00027599942,0.00090114103,0.00070716237,0.00054027466,0.0008543362,0.00070068374,0.00088544586,0.0004604323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002340866,0.00012499533,0.001033449,0.00041238984,0.0002344841,0.0002980855,0.00022918162,0.2077218,0.28555295,0.014695361,0.0024895442,0.48697364],"study_design_scores_gemma":[0.000014879386,0.00010570176,0.0014153797,0.000021203245,0.000060305436,0.00034244722,0.00003483318,0.92708313,0.061747015,0.004486408,0.0046569984,0.000031664655],"about_ca_topic_score_codex":0.0015765558,"about_ca_topic_score_gemma":0.0023494442,"teacher_disagreement_score":0.0015765558,"about_ca_system_score_codex":0.000300254,"about_ca_system_score_gemma":0.00066930614,"threshold_uncertainty_score":0.0047445297},"labels":[],"label_agreement":null},{"id":"W2069831612","doi":"10.1002/jmri.21076","title":"Application of voxelwise analysis in the detection of regions of reduced fractional anisotropy in multiple sclerosis patients","year":2007,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Fluid-attenuated inversion recovery; Multiple sclerosis; Diffusion MRI; White matter; Nuclear medicine; Spatial normalization; Medicine; Radiology; Pathology; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Psychiatry","score_opus":0.038915548621932514,"score_gpt":0.3127707706016108,"score_spread":0.27385522197967826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069831612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9828067,0.0009759035,0.014927856,0.00016322108,0.000036293266,0.000057095745,0.00016952942,0.00017756522,0.0006857687],"genre_scores_gemma":[0.9829412,0.00014505636,0.01656813,0.000032393313,0.000025671276,0.000034778015,0.00014243179,0.00002200869,0.00008836844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998345,0.0010802256,0.000102891354,0.00022707524,0.00019199733,0.000052813168],"domain_scores_gemma":[0.9951439,0.0022632794,0.0010938436,0.0004736743,0.00084081,0.00018441632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036016826,0.0003672757,0.00046544953,0.0014014697,0.00026003143,0.0005855405,0.0003355564,0.00043375968,0.0007187116],"category_scores_gemma":[0.015349133,0.00022464884,0.00023551748,0.00041584665,0.0003807966,0.00038599755,0.0004491628,0.0002844401,0.00025614022],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033130017,0.0001546483,0.7458717,0.00024827864,0.00065703114,0.00074631313,0.0005721668,0.0030769962,0.07113635,0.00049673463,0.0015456794,0.1721811],"study_design_scores_gemma":[0.00016043104,0.0015356668,0.8842912,0.00008384956,0.0004925502,0.00856279,0.00031505778,0.050363082,0.050171547,0.0015253867,0.0024062144,0.00009222686],"about_ca_topic_score_codex":0.0005202492,"about_ca_topic_score_gemma":0.0010001542,"teacher_disagreement_score":0.0036016826,"about_ca_system_score_codex":0.00018709803,"about_ca_system_score_gemma":0.0003714518,"threshold_uncertainty_score":0.019047737},"labels":[],"label_agreement":null},{"id":"W2069922847","doi":"10.1038/sj.npp.1301347","title":"Focal Gray Matter Changes in Schizophrenia across the Course of the Illness: A 5-Year Follow-Up Study","year":2007,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":311,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Gray (unit); Magnetic resonance imaging; Psychology; Caudate nucleus; Voxel; Voxel-based morphometry; Olanzapine; Schizophrenia (object-oriented programming); Neuroscience; Medicine; Psychiatry; Nuclear medicine; Radiology","score_opus":0.034378644205534305,"score_gpt":0.396604617838392,"score_spread":0.3622259736328577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069922847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99936825,0.00017381134,0.000065244676,0.000032182204,0.000007920801,0.000020117726,0.00009595845,0.0000046616774,0.00023196703],"genre_scores_gemma":[0.99888724,0.00012162328,0.00007900604,0.00004092795,0.000010711522,0.000017473703,0.00041384166,0.0000022993852,0.00042686844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997322,0.00004154844,0.00002367169,0.00005641902,0.000043999808,0.00010207438],"domain_scores_gemma":[0.99924797,0.000072627256,0.00015481199,0.00006925298,0.00017956518,0.0002757341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080827344,0.0005603341,0.0010333916,0.0012629787,0.0015879415,0.00065253786,0.0004244982,0.0010907016,0.00078606093],"category_scores_gemma":[0.0010945221,0.00035824825,0.0010464112,0.0007436844,0.00070886035,0.0010669937,0.0006996455,0.0010295459,0.00044544172],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008963784,0.0048855287,0.94658387,0.00005849713,0.0004397242,0.0055908207,0.0018314129,0.00026225447,0.011240687,0.000056451125,0.00045922524,0.019627731],"study_design_scores_gemma":[0.00009214546,0.0038335496,0.9933956,0.000007760791,0.00016681282,0.0010371488,0.0004946011,0.00014664207,0.00044788717,0.000040197712,0.00031227662,0.000025252382],"about_ca_topic_score_codex":0.016919933,"about_ca_topic_score_gemma":0.017345835,"teacher_disagreement_score":0.016919933,"about_ca_system_score_codex":0.0007941452,"about_ca_system_score_gemma":0.00056165,"threshold_uncertainty_score":0.033642888},"labels":[],"label_agreement":null},{"id":"W2070125936","doi":"10.1111/j.1085-9489.2005.10107.x","title":"Histological and magnetic resonance analysis of sciatic nerves in the tellurium model of neuropathy","year":2005,"lang":"en","type":"article","venue":"Journal of the Peripheral Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto; Women's College Hospital; Sunnybrook Health Science Centre","funders":"","keywords":"Myelin; Sciatic nerve; Weanling; Hindlimb; Anatomy; Myelin sheath; Pathology; Atrophy; Magnetic resonance imaging; Medicine; Paralysis; Axonal degeneration; Chemistry; Internal medicine; Central nervous system; Surgery","score_opus":0.042761520594179786,"score_gpt":0.2955533619228332,"score_spread":0.2527918413286534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070125936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960586,0.0005601549,0.0022588652,0.000026853633,0.000023193741,0.000035714893,0.00013202654,0.00005110622,0.00085346814],"genre_scores_gemma":[0.9846544,0.0015843529,0.005939171,0.00004627418,0.000015212992,0.00008433824,0.00045111764,0.000024229792,0.007200801],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998592,0.000022522772,0.000012907099,0.000024369767,0.000049263974,0.00003179059],"domain_scores_gemma":[0.9997594,0.000025984991,0.00007306397,0.000025063271,0.00004883723,0.0000676149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002903958,0.00046843523,0.0002896396,0.00077464175,0.00027814152,0.00016943757,0.0001880386,0.00045824627,0.0014819864],"category_scores_gemma":[0.00019909616,0.00022169924,0.00022870436,0.00025316628,0.00036159472,0.00031214705,0.00017542698,0.0005003673,0.00026495504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034215322,0.000056004166,0.0002676711,0.000042018688,0.000009077461,0.00017411812,0.000029446674,0.000058122263,0.9983215,0.000046952995,0.000012308819,0.000640641],"study_design_scores_gemma":[0.000071698065,0.0046595726,0.019901415,0.0000172345,0.00009743861,0.002163683,0.00013669787,0.0007517007,0.9711802,0.00008515769,0.0009175164,0.00001771584],"about_ca_topic_score_codex":0.0009018772,"about_ca_topic_score_gemma":0.0016213323,"teacher_disagreement_score":0.0014819864,"about_ca_system_score_codex":0.00019564465,"about_ca_system_score_gemma":0.00020566159,"threshold_uncertainty_score":0.0049577355},"labels":[],"label_agreement":null},{"id":"W2070753161","doi":"10.1002/nbm.951","title":"MR properties of excised neural tissue following experimentally induced demyelination","year":2005,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Myelin; Sciatic nerve; Histopathology; Nuclear magnetic resonance; Magnetization transfer; Relaxation (psychology); Quantitative assessment; Magnetic resonance imaging; Chemistry; Anatomy; Pathology; Central nervous system; Biology; Medicine; Endocrinology; Physics; Neuroscience; Radiology","score_opus":0.10304264220097002,"score_gpt":0.39545321888825574,"score_spread":0.2924105766872857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070753161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99450076,0.0019376746,0.0028921352,0.000011524153,0.000013204521,0.000017944469,0.00012253289,0.000023496852,0.00048078867],"genre_scores_gemma":[0.9922013,0.0015441134,0.004161561,0.000032032047,0.000010638649,0.000034608358,0.00043566432,0.000013682069,0.0015663258],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999144,0.000021984522,0.0000066141583,0.0000215406,0.000021113756,0.000014464268],"domain_scores_gemma":[0.99974984,0.000072189134,0.00006627785,0.000029333416,0.000052765467,0.000029523528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029832002,0.000222706,0.00022581968,0.00022883218,0.0000976502,0.000141536,0.00015727722,0.00021372773,0.0006133181],"category_scores_gemma":[0.00036610043,0.0001424055,0.00011062868,0.00017360058,0.00024430663,0.00022498218,0.00012730206,0.00024073305,0.00018838405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015045356,0.000010492403,0.00019790971,0.000035403587,0.000004492892,0.000069021735,0.000026680766,0.000039999402,0.99877816,0.000010839952,0.0000049115365,0.0006715138],"study_design_scores_gemma":[0.000013646079,0.0015114511,0.020154411,0.00001401975,0.000051134874,0.0011399933,0.00019001302,0.00080035714,0.9749333,0.000050554365,0.0011304613,0.000010700722],"about_ca_topic_score_codex":0.00037033364,"about_ca_topic_score_gemma":0.00046961912,"teacher_disagreement_score":0.0006133181,"about_ca_system_score_codex":0.0001042689,"about_ca_system_score_gemma":0.00007933412,"threshold_uncertainty_score":0.0020517707},"labels":[],"label_agreement":null},{"id":"W2071252649","doi":"10.1145/1993886.1993909","title":"Diversification improves interpolation","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interpolation (computer graphics); Computer science; Diversification (marketing strategy); Artificial intelligence; Business","score_opus":0.15029607006859882,"score_gpt":0.35099958668034065,"score_spread":0.20070351661174182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071252649","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038561147,0.00043783415,0.95088,0.0006984343,0.000119512064,0.0000667412,0.00009742354,0.0011976851,0.0079413],"genre_scores_gemma":[0.36336836,0.0003410395,0.62933886,0.0005671681,0.00012031014,0.00014025964,0.00032490055,0.00053394074,0.0052652317],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832207,0.0005546016,0.00007665956,0.00035876644,0.0005046525,0.00018324442],"domain_scores_gemma":[0.9948702,0.0029212772,0.00032504855,0.0010998772,0.0005823491,0.00020122739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028458012,0.0008482363,0.001447191,0.0008276398,0.00084738206,0.00109695,0.0014518802,0.0016605707,0.0067720856],"category_scores_gemma":[0.014609957,0.0004585255,0.0010713955,0.0008566199,0.0014426261,0.0021492173,0.0038899197,0.0023388849,0.0024340798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084636896,0.00029126997,0.0054705073,0.00031996155,0.00010336461,0.00042039464,0.00041040604,0.46137282,0.022855362,0.1924197,0.00991206,0.30557775],"study_design_scores_gemma":[0.00009691672,0.00016176427,0.0003445233,0.0000340031,0.000019693976,0.00018092325,0.000042142427,0.9214363,0.0053116926,0.06613302,0.00621448,0.000024510344],"about_ca_topic_score_codex":0.001275068,"about_ca_topic_score_gemma":0.0016332034,"teacher_disagreement_score":0.0067720856,"about_ca_system_score_codex":0.00072311884,"about_ca_system_score_gemma":0.0013776309,"threshold_uncertainty_score":0.022654831},"labels":[],"label_agreement":null},{"id":"W2071297770","doi":"10.1016/j.neuroimage.2006.09.016","title":"Segmentation of thalamic nuclei using a modified k-means clustering algorithm and high-resolution quantitative magnetic resonance imaging at 1.5 T","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Segmentation; Artificial intelligence; Magnetic resonance imaging; Computer science; Cluster analysis; Brain atlas; Similarity (geometry); Pattern recognition (psychology); Thalamus; Reproducibility; Euclidean distance; Surgical planning; Computer vision; Nuclear medicine; Medicine; Mathematics; Radiology; Image (mathematics)","score_opus":0.04463760690121317,"score_gpt":0.3221354639266813,"score_spread":0.27749785702546814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071297770","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036323447,0.00040678293,0.9592168,0.00015780819,0.000054407905,0.00034903098,0.0004178993,0.0018437976,0.0012300843],"genre_scores_gemma":[0.061315343,0.00019795471,0.93593925,0.000034124514,0.000013538087,0.00021544866,0.00042350078,0.0004768577,0.0013840279],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989839,0.00016942911,0.000109887376,0.0002754127,0.00036077067,0.00010052837],"domain_scores_gemma":[0.99919873,0.00017383955,0.00009867808,0.00015677516,0.00033701796,0.000035064935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015027262,0.001063138,0.0013014891,0.0035348043,0.0013937597,0.0027166968,0.0017376174,0.002125669,0.0033868626],"category_scores_gemma":[0.0028320772,0.0010623939,0.0017578423,0.002694159,0.0007984073,0.001485733,0.0010069252,0.000953242,0.0018653176],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007356147,0.00020554448,0.0031031838,0.0010706771,0.00045303052,0.0004835718,0.0012043847,0.072702974,0.48553935,0.008323115,0.005024196,0.42115432],"study_design_scores_gemma":[0.000191242,0.00034553703,0.027562,0.00017313148,0.00044644234,0.0025189125,0.0006919649,0.68215334,0.2487165,0.01849318,0.018219896,0.00048788823],"about_ca_topic_score_codex":0.01770276,"about_ca_topic_score_gemma":0.027097989,"teacher_disagreement_score":0.01770276,"about_ca_system_score_codex":0.0011543405,"about_ca_system_score_gemma":0.0032768068,"threshold_uncertainty_score":0.035199463},"labels":[],"label_agreement":null},{"id":"W2071509460","doi":"10.1002/ana.20772","title":"Pyramidal tract maturation after brain injury in newborns with heart disease","year":2006,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; White matter; Medicine; Diffusion MRI; Magnetic resonance imaging; Pyramidal tracts; Traumatic brain injury; Corticospinal tract; Tractography; Perioperative; Autopsy; Population; Cardiology; Pathology; Anesthesia; Radiology; Anatomy","score_opus":0.04713136753085785,"score_gpt":0.36660210204259863,"score_spread":0.3194707345117408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071509460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957603,0.00016262221,0.00012251941,0.000006652425,9.540494e-7,0.000003054338,0.000034371562,0.0000033072768,0.00009041118],"genre_scores_gemma":[0.99938166,0.00016542073,0.00031052198,0.0000058515498,0.0000020841794,0.0000049828973,0.000070700225,0.0000017032571,0.00005704337],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998062,0.000042224692,0.00002560454,0.000047243033,0.000047703375,0.000030976564],"domain_scores_gemma":[0.99916077,0.00013289458,0.00047728783,0.000027675549,0.000107371074,0.00009406174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004412386,0.00022218765,0.00016083081,0.0006452485,0.00018897359,0.00030196414,0.00013986915,0.00022111113,0.00044785172],"category_scores_gemma":[0.0027321412,0.00008897582,0.00011741887,0.0002281044,0.0002777583,0.0002762543,0.00029310893,0.00017104883,0.00008926435],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026614405,0.000014853201,0.9832918,0.000024945484,0.00001553824,0.0010118118,0.00021086982,0.00011910737,0.0075222095,0.000024021065,0.000041478954,0.0074572396],"study_design_scores_gemma":[0.0000019018303,0.00019243144,0.9943374,0.000011524941,0.000009063178,0.0031259726,0.00013867325,0.0001703868,0.0019326624,0.00001471304,0.0000619474,0.0000033069616],"about_ca_topic_score_codex":0.0027948073,"about_ca_topic_score_gemma":0.0026022706,"teacher_disagreement_score":0.0027948073,"about_ca_system_score_codex":0.00038940966,"about_ca_system_score_gemma":0.0002678876,"threshold_uncertainty_score":0.0055570602},"labels":[],"label_agreement":null},{"id":"W2071666283","doi":"10.1016/j.neuroimage.2014.12.058","title":"A new compression format for fiber tracking datasets","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Connectomics; Diffusion MRI; Data compression; Tractography; Pipeline (software); Lossless compression; Compression (physics); JPEG 2000; Artificial intelligence; Algorithm; Image compression; Connectome; Image processing","score_opus":0.2118934394563405,"score_gpt":0.4215440450161156,"score_spread":0.20965060555977508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071666283","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007269095,0.00078776595,0.95979804,0.0011750748,0.0011968554,0.00045436004,0.007563368,0.017175512,0.0045798738],"genre_scores_gemma":[0.053888597,0.0013665003,0.9123571,0.0006278894,0.0013062624,0.0012237284,0.017398117,0.0031525958,0.008679161],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99817526,0.00025032854,0.0004054443,0.00023889776,0.0007923616,0.00013777877],"domain_scores_gemma":[0.98693955,0.002686224,0.0006033387,0.0057452274,0.003725887,0.0002997301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025117921,0.0016930809,0.0008714479,0.0038702881,0.0010079372,0.0036823223,0.001699837,0.0016149661,0.017021485],"category_scores_gemma":[0.018912807,0.0006576185,0.0008722362,0.0056871823,0.0006685663,0.0048150164,0.002884557,0.00280512,0.008380323],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015721356,0.00023186315,0.0011186755,0.00049281423,0.00008631829,0.00044409995,0.00024318058,0.016932325,0.032621,0.04125569,0.08257438,0.82242745],"study_design_scores_gemma":[0.00061616814,0.00062551664,0.003895933,0.0006873157,0.00018365662,0.002681207,0.00036278315,0.46280408,0.15466048,0.11709286,0.25599703,0.00039304362],"about_ca_topic_score_codex":0.0018405688,"about_ca_topic_score_gemma":0.0016374891,"teacher_disagreement_score":0.017021485,"about_ca_system_score_codex":0.0007457258,"about_ca_system_score_gemma":0.0015670297,"threshold_uncertainty_score":0.056942523},"labels":[],"label_agreement":null},{"id":"W2071833700","doi":"10.1155/2008/320195","title":"Accurate Anisotropic Fast Marching for Diffusion‐Based Geodesic Tractography","year":2007,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Dr Hadwen Trust for Humane Research","keywords":"Fast marching method; Geodesic; Computer science; Robustness (evolution); Tractography; Diffusion MRI; Algorithm; Noisy data; Computation; Perturbation (astronomy); Anisotropy; Mathematics; Mathematical analysis; Physics","score_opus":0.044136633047763454,"score_gpt":0.4014732143271156,"score_spread":0.35733658127935214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071833700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0076789055,0.00018091308,0.99108195,0.00015576567,0.000023534802,0.000028177568,0.00005064099,0.00037368288,0.00042637505],"genre_scores_gemma":[0.07760322,0.00029209416,0.92066187,0.00001970317,0.000021223475,0.00011924795,0.00015057773,0.00019651647,0.0009355609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994955,0.0001836051,0.000035379653,0.000059197246,0.00020327282,0.00002299964],"domain_scores_gemma":[0.9981968,0.0009603065,0.0001758815,0.0003230609,0.00028174056,0.00006225199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015746639,0.0013032951,0.0010250102,0.0010941238,0.00074317504,0.00091876026,0.0010833911,0.0014293825,0.0013829713],"category_scores_gemma":[0.008280744,0.0008045431,0.0008113837,0.0014237284,0.00096830114,0.0014070261,0.0011750383,0.0017436369,0.00069331663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009211765,0.000024646873,0.00067855936,0.00017646045,0.00007602545,0.00021822273,0.00021223168,0.7984446,0.01646473,0.044637494,0.002020577,0.13695435],"study_design_scores_gemma":[0.000011967237,0.000008167961,0.00008091783,0.0000041140243,0.000004431684,0.000030662926,0.0000046541463,0.9863214,0.001867818,0.010305484,0.0013517163,0.00000875363],"about_ca_topic_score_codex":0.006432352,"about_ca_topic_score_gemma":0.006047181,"teacher_disagreement_score":0.006432352,"about_ca_system_score_codex":0.0008714022,"about_ca_system_score_gemma":0.0016192333,"threshold_uncertainty_score":0.0127898455},"labels":[],"label_agreement":null},{"id":"W2072158614","doi":"10.1016/j.neuroimage.2014.03.056","title":"Gray matter volume is associated with rate of subsequent skill learning after a long term training intervention","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"FP7 People: Marie-Curie Actions; University of Oxford; Fundação para a Ciência e a Tecnologia; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Term (time); Intervention (counseling); Training (meteorology); Volume (thermodynamics); Gray (unit); Psychology; Physical medicine and rehabilitation; Medicine; Psychiatry; Geography; Physics; Nuclear medicine","score_opus":0.0337410118784554,"score_gpt":0.3098381530670533,"score_spread":0.2760971411885979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072158614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993917,0.000108783664,0.00020053635,0.000014855138,0.000002238192,0.000005764427,0.000033474207,0.000011833116,0.00023092667],"genre_scores_gemma":[0.9990972,0.000043627093,0.0001389023,0.000006374338,0.0000029690618,0.000010864241,0.00006966897,0.0000032870505,0.00062709785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985385,0.000022416878,0.00001147477,0.00004321679,0.0000384355,0.00003063372],"domain_scores_gemma":[0.998917,0.0002681349,0.00045631212,0.00009907301,0.00010411984,0.00015539322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032597117,0.00018590945,0.00022187985,0.0002447489,0.00008702178,0.00022053822,0.00016761056,0.00036309424,0.00195517],"category_scores_gemma":[0.002029645,0.00010789348,0.00010739728,0.00010345233,0.00018862059,0.00018427378,0.0002677451,0.00034240083,0.00025129697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00856318,0.00287642,0.495516,0.00016549426,0.00038605338,0.00032393428,0.0007732515,0.001953708,0.41013795,0.00012932057,0.0004230887,0.078751706],"study_design_scores_gemma":[0.000008203254,0.0013422861,0.9933114,0.000004434115,0.000017093187,0.000077535085,0.000026893458,0.00048522418,0.0046101767,0.00003595412,0.00007720533,0.000003667309],"about_ca_topic_score_codex":0.00091288897,"about_ca_topic_score_gemma":0.0015753028,"teacher_disagreement_score":0.00195517,"about_ca_system_score_codex":0.00010994093,"about_ca_system_score_gemma":0.000073543844,"threshold_uncertainty_score":0.0065407157},"labels":[],"label_agreement":null},{"id":"W2072188503","doi":"10.1016/j.neuroimage.2013.06.033","title":"Locally linear embedding (LLE) for MRI based Alzheimer's disease classification","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; Genentech; IXICO; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Synarc; Bayer HealthCare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Medpace; AstraZeneca; Bristol-Myers Squibb; Eli Lilly and Company; Novartis Pharmaceuticals Corporation; National Center for Research Resources; F. Hoffmann-La Roche; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; University of California, San Diego; U.S. Department of Veterans Affairs","keywords":"Neuroimaging; Artificial intelligence; Linear discriminant analysis; Multivariate statistics; Pattern recognition (psychology); Logistic regression; Alzheimer's Disease Neuroimaging Initiative; Support vector machine; Medical diagnosis; Machine learning; Linear classifier; Computer science; Alzheimer's disease; Medicine; Disease; Psychology; Pathology; Neuroscience","score_opus":0.10974908995374599,"score_gpt":0.3852019442355012,"score_spread":0.2754528542817552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072188503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040861186,0.001963648,0.9535089,0.00055998453,0.00010045505,0.000061180726,0.0004221985,0.0016858992,0.00083658437],"genre_scores_gemma":[0.5866701,0.0012119351,0.4034585,0.0002795794,0.00018942275,0.0001932284,0.0013556423,0.0002984095,0.006343228],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948454,0.0002033053,0.00003994075,0.0001132577,0.00010669999,0.000052150262],"domain_scores_gemma":[0.99918586,0.00041452536,0.00008885636,0.00012094333,0.00015056522,0.000039191185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010684833,0.0006487438,0.0009409824,0.0010509102,0.00038622296,0.00079392956,0.00083109573,0.0009254087,0.0013143665],"category_scores_gemma":[0.0026105647,0.00029737837,0.0010064965,0.0007907942,0.00034292857,0.00080350845,0.00089581835,0.0011604058,0.0008145614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043700548,0.00028052842,0.0029614002,0.00023360163,0.00022884844,0.0001779751,0.00015335261,0.103910126,0.02198548,0.0061848243,0.010234784,0.85321206],"study_design_scores_gemma":[0.000011556455,0.000089342204,0.0010051056,0.00001934816,0.000038172744,0.00013827895,0.000043138305,0.9869431,0.004366873,0.0059251683,0.001398499,0.000021348535],"about_ca_topic_score_codex":0.0039713853,"about_ca_topic_score_gemma":0.0054216725,"teacher_disagreement_score":0.0039713853,"about_ca_system_score_codex":0.00034037075,"about_ca_system_score_gemma":0.0007216316,"threshold_uncertainty_score":0.007896543},"labels":[],"label_agreement":null},{"id":"W2072919309","doi":"10.1016/j.jad.2010.04.004","title":"MRI signal hyperintensities and treatment remission of geriatric depression","year":2010,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Center for Advanced Brain Imaging; National Institutes of Health; National Institute of Mental Health; University of Toronto; City University of New York","keywords":"Escitalopram; Depression (economics); Internal medicine; Placebo; Hamilton Rating Scale for Depression; Rating scale; Psychology; Psychiatry; Hyperintensity; Medicine; Major depressive disorder; Antidepressant; Magnetic resonance imaging; Pathology; Hippocampus; Cognition","score_opus":0.016451164568308387,"score_gpt":0.31600761588824366,"score_spread":0.2995564513199353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072919309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99676394,0.0014161183,0.000059868282,0.00015761463,0.000022758722,0.000015083652,0.00014279464,0.000009499469,0.0014122705],"genre_scores_gemma":[0.9988845,0.0003277803,0.000039799845,0.000059560614,0.000028418235,0.000005812552,0.0002951192,0.0000016318744,0.00035738177],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982244,0.000046858313,0.000032107146,0.000025467532,0.000036565365,0.000036614154],"domain_scores_gemma":[0.9991855,0.00016165197,0.00037508257,0.00005071947,0.0000921827,0.00013481201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045864328,0.00024486982,0.0005542905,0.00058355794,0.0003881266,0.00046997063,0.0002735393,0.0008215789,0.0012717242],"category_scores_gemma":[0.0027391217,0.00018035392,0.00029630438,0.0004468326,0.00024397261,0.00039242636,0.00016742718,0.0006621302,0.00022610989],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011969495,0.00073834794,0.94463724,0.00011959908,0.00047194908,0.001958321,0.00025220175,0.00017327853,0.007377877,0.000079098056,0.00066125434,0.031561393],"study_design_scores_gemma":[0.000052443083,0.0003080679,0.9983205,0.0000051830243,0.00005784511,0.0007996455,0.000045014647,0.00008091995,0.00016174246,0.00003531657,0.00012935573,0.0000038636795],"about_ca_topic_score_codex":0.0024994656,"about_ca_topic_score_gemma":0.0039595254,"teacher_disagreement_score":0.0024994656,"about_ca_system_score_codex":0.00035316896,"about_ca_system_score_gemma":0.00021048871,"threshold_uncertainty_score":0.0049698353},"labels":[],"label_agreement":null},{"id":"W2073169643","doi":"10.1002/1522-2594(200103)45:3<415::aid-mrm1054>3.0.co;2-m","title":"MR properties of rat sciatic nerve following trauma","year":2001,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Sciatic nerve; Fractional anisotropy; Magnetization transfer; Medicine; Histopathology; Degeneration (medical); Anatomy; Regeneration (biology); T2 relaxation; Nerve injury; Diffusion MRI; Axonal degeneration; Pathology; Magnetic resonance imaging; Anesthesia; Radiology; Biology","score_opus":0.0813412628426224,"score_gpt":0.34189166416312317,"score_spread":0.2605504013205008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073169643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98947984,0.006633955,0.0019503158,0.00006401258,0.000028856855,0.000015428177,0.00035342426,0.00007258197,0.001401559],"genre_scores_gemma":[0.97700614,0.008740037,0.0051488574,0.0001534,0.000043896558,0.00006808915,0.0017545283,0.000045255187,0.007039745],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999193,0.00001260325,0.0000048285715,0.000014608569,0.000025944673,0.000022666689],"domain_scores_gemma":[0.9997094,0.00003111443,0.00010601533,0.00001919491,0.00008027965,0.000053844033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031763504,0.00039872265,0.00031527606,0.00049370545,0.00016047113,0.0001912465,0.00017755982,0.00043105957,0.0013435718],"category_scores_gemma":[0.0002926376,0.00024112196,0.0002009804,0.0003802853,0.00024760913,0.0003201618,0.0001641828,0.0004418702,0.00039588998],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003732525,0.00001551669,0.00025174706,0.000088579596,0.000008959789,0.000079656245,0.000044509536,0.00005564812,0.99759287,0.000027180773,0.000040157902,0.001421819],"study_design_scores_gemma":[0.00007579716,0.005001225,0.063527964,0.000064442786,0.00020174039,0.0021398827,0.00030069065,0.0010162519,0.92334706,0.0002171245,0.0040619383,0.000045853674],"about_ca_topic_score_codex":0.00081525336,"about_ca_topic_score_gemma":0.0010195737,"teacher_disagreement_score":0.0013435718,"about_ca_system_score_codex":0.00015775108,"about_ca_system_score_gemma":0.00017012299,"threshold_uncertainty_score":0.0044947267},"labels":[],"label_agreement":null},{"id":"W2073715614","doi":"10.1016/j.rbmret.2007.12.012","title":"Développement clinique de l’IRM du tenseur de diffusion de la moelle épinière dans un contexte de lésion médullaire","year":2008,"lang":"fr","type":"article","venue":"IRBM","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institutes of Health Research; Université de Montréal","funders":"","keywords":"Physics; Humanities; Nuclear medicine; Medicine; Philosophy","score_opus":0.04400854159892869,"score_gpt":0.3520319567962167,"score_spread":0.308023415197288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073715614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8949447,0.013653376,0.047846638,0.008705858,0.00070631865,0.00077965454,0.0003607533,0.00068761205,0.03231486],"genre_scores_gemma":[0.9872269,0.002514274,0.007106999,0.0005261954,0.00059955067,0.00008316057,0.000059363756,0.000050463685,0.0018331358],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.999506,0.00008978501,0.00006358403,0.00013736876,0.00008821087,0.000114997216],"domain_scores_gemma":[0.9983918,0.00077686366,0.0002367936,0.0001474444,0.0003089894,0.00013804056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009256882,0.0012241994,0.00069902104,0.0030486304,0.0009827366,0.001053221,0.0012016011,0.0032145677,0.0030505657],"category_scores_gemma":[0.0074620987,0.00069013325,0.000616628,0.00087194954,0.0026926193,0.0042590336,0.0008125846,0.0028548124,0.0009924141],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014958885,0.00029278034,0.040288106,0.000797268,0.00007491243,0.7965791,0.0017669161,0.0010044903,0.09855572,0.0025763505,0.0012376292,0.055330887],"study_design_scores_gemma":[0.00020558287,0.0014217092,0.031874724,0.00022168366,0.00021873103,0.8606557,0.00066771795,0.009486091,0.08172533,0.003250133,0.010158492,0.00011419341],"about_ca_topic_score_codex":0.002483883,"about_ca_topic_score_gemma":0.001504268,"teacher_disagreement_score":0.0032145677,"about_ca_system_score_codex":0.00076265313,"about_ca_system_score_gemma":0.0007663636,"threshold_uncertainty_score":0.01020515},"labels":[],"label_agreement":null},{"id":"W2073864473","doi":"10.1002/ca.21190","title":"An anatomically based imaging sign to detect adventitial cyst derived from the superior tibiofibular joint","year":2011,"lang":"en","type":"article","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Sign (mathematics); Cyst; Joint (building); Anatomy; Radiology","score_opus":0.11539035306917172,"score_gpt":0.3994710658256264,"score_spread":0.2840807127564547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073864473","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945749,0.0011974379,0.0026894512,0.000066874294,0.000015242727,0.000026121703,0.000017349934,0.000039895083,0.0013727448],"genre_scores_gemma":[0.99642855,0.0004195708,0.0028969871,0.000047945035,0.000029056073,0.0000089075675,0.0000355716,0.0000047878666,0.00012864315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998349,0.00003660507,0.000037576632,0.000024339535,0.000033372904,0.00003322914],"domain_scores_gemma":[0.999059,0.00033652826,0.0002867596,0.00007936151,0.0001031745,0.00013512613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046662916,0.00042384295,0.00028651953,0.0019135653,0.0002516571,0.00051029975,0.00031746126,0.00059225055,0.0010769586],"category_scores_gemma":[0.002806254,0.00021739014,0.00017763738,0.00053123466,0.0008274797,0.0006427918,0.00044085475,0.00029974233,0.00039815786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031658073,0.00008181131,0.73489016,0.00027670048,0.000057229634,0.1110259,0.0008049565,0.00039842498,0.10988234,0.00029261695,0.0003127934,0.04166062],"study_design_scores_gemma":[0.000034037934,0.00043129807,0.30740255,0.00008979936,0.00009606157,0.6739686,0.000703144,0.0016866504,0.013982996,0.00021989363,0.001351353,0.00003361883],"about_ca_topic_score_codex":0.00057699764,"about_ca_topic_score_gemma":0.00087526545,"teacher_disagreement_score":0.0019135653,"about_ca_system_score_codex":0.00012729465,"about_ca_system_score_gemma":0.0003429315,"threshold_uncertainty_score":0.0036028028},"labels":[],"label_agreement":null},{"id":"W2073930583","doi":"10.1002/cne.22418","title":"Morphological patterns of the postcentral sulcus in the human brain","year":2010,"lang":"en","type":"article","venue":"The Journal of Comparative Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Postcentral gyrus; Sulcus; Intraparietal sulcus; Anatomy; Central sulcus; Biology; Gyrus; Parietal lobe; Superior temporal sulcus; Functional magnetic resonance imaging; Neuroscience; Motor cortex","score_opus":0.09557299371483786,"score_gpt":0.40270061112847916,"score_spread":0.3071276174136413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073930583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921342,0.0010123377,0.0041538747,0.000036048725,0.0000050636318,0.000031918764,0.00036772664,0.00004503646,0.002213724],"genre_scores_gemma":[0.99714357,0.00038238938,0.0017198205,0.000005902408,0.0000059260456,0.000014583225,0.00023064177,0.000012581527,0.00048449895],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998516,0.000024325138,0.00001567679,0.00004619416,0.00004425809,0.000017864908],"domain_scores_gemma":[0.99964535,0.00007754908,0.000121104,0.00004728758,0.00009062178,0.000018217743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022082479,0.00018132212,0.00014764504,0.0020559144,0.00014481059,0.0003447324,0.00014225011,0.00013623066,0.0015136313],"category_scores_gemma":[0.0010788605,0.00013321686,0.0001451342,0.0012755698,0.0006545166,0.00026289068,0.0002132811,0.00008931535,0.00030186336],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012351129,0.000045385492,0.39265695,0.00053433975,0.0003009694,0.0020897584,0.00443381,0.0016919604,0.39690915,0.0035139422,0.0010450237,0.19554347],"study_design_scores_gemma":[0.00000711488,0.00008341903,0.9896135,0.000011646818,0.00002310519,0.0020790894,0.00023452118,0.00068483915,0.005019229,0.0007478162,0.0014839954,0.000011838072],"about_ca_topic_score_codex":0.0026915094,"about_ca_topic_score_gemma":0.0060327044,"teacher_disagreement_score":0.0026915094,"about_ca_system_score_codex":0.00018268771,"about_ca_system_score_gemma":0.0003203517,"threshold_uncertainty_score":0.0053516626},"labels":[],"label_agreement":null},{"id":"W2074145542","doi":"10.1016/j.nicl.2013.06.012","title":"Intra-individual variability in information processing speed reflects white matter microstructure in multiple sclerosis","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Montreal Neurological Institute and Hospital; Health Sciences Centre; McGill University","funders":"Dalhousie University; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Genome Canada","keywords":"White matter; Neuropsychology; Medicine; Diffusion MRI; Multiple sclerosis; Audiology; Cognition; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.13430656742771432,"score_gpt":0.3834667417872672,"score_spread":0.24916017435955287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074145542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99953663,0.0000793336,0.00018615584,0.0000047201947,7.367933e-7,0.0000039336983,0.000051247374,0.0000048534403,0.00013248893],"genre_scores_gemma":[0.9996044,0.00003031787,0.00019769771,0.0000046762275,0.0000027905248,0.0000058702617,0.00007346997,0.0000027028439,0.00007800956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973506,0.000064327854,0.000038198104,0.0000780496,0.00006339587,0.00002089641],"domain_scores_gemma":[0.9978806,0.0005912883,0.0010316181,0.0002155654,0.00013948217,0.00014141868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005590296,0.0002999642,0.00026579786,0.00094058394,0.00016922186,0.0003500294,0.00017672121,0.00031344756,0.0005659749],"category_scores_gemma":[0.0033395344,0.00018998588,0.00014067408,0.00049771304,0.00027957905,0.00029443568,0.0003414389,0.0003402139,0.00015202245],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006020749,0.00009776573,0.98005575,0.000023403703,0.00016205391,0.00010778494,0.00030195666,0.0004165365,0.010042551,0.000027911663,0.00005217022,0.008109857],"study_design_scores_gemma":[0.0000021795283,0.00015715825,0.9988865,0.00000126178,0.00000928806,0.00018229775,0.000031500702,0.00027011888,0.00038774786,0.000045812318,0.000022745236,0.0000032340683],"about_ca_topic_score_codex":0.0008826492,"about_ca_topic_score_gemma":0.00087089965,"teacher_disagreement_score":0.00094058394,"about_ca_system_score_codex":0.00015111195,"about_ca_system_score_gemma":0.00009148868,"threshold_uncertainty_score":0.00295645},"labels":[],"label_agreement":null},{"id":"W2074890469","doi":"10.1016/j.jalz.2014.07.074","title":"P4‐303: COGNITIVE FUNCTION AND TRACTOGRAPHY OF WHITE MATTER TRACTS CROSSING HYPERINTENSITIES IN ELDERLY PERSONS","year":2014,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Queen's University","funders":"","keywords":"Memory span; Wechsler Adult Intelligence Scale; Fractional anisotropy; Stroop effect; Psychology; Hyperintensity; Diffusion MRI; Audiology; Dementia; White matter; Fluid-attenuated inversion recovery; Boston Naming Test; Neuropsychology; Cognition; Magnetic resonance imaging; Medicine; Neuroscience; Internal medicine; Working memory; Radiology","score_opus":0.04368040369058914,"score_gpt":0.3070907065569883,"score_spread":0.26341030286639916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074890469","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993375,0.000068937865,0.00014631773,0.000016869817,0.0000016208364,0.0000039891684,0.0001941307,0.0000050037147,0.00022552071],"genre_scores_gemma":[0.9993512,0.000034780944,0.00014675576,0.0000059728945,0.0000032630464,0.000004926884,0.00023504703,0.0000018453715,0.00021624925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999263,0.000016863458,0.000008775972,0.000017898117,0.000017747116,0.0000123083655],"domain_scores_gemma":[0.9995654,0.000088625005,0.00016300415,0.000043277152,0.00007039892,0.00006926084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031278812,0.00021818338,0.00015482624,0.00062096387,0.00027986363,0.00027053177,0.00015817613,0.00033812723,0.002359288],"category_scores_gemma":[0.0013008242,0.00012753825,0.00025075322,0.00037835372,0.00018667821,0.00029467436,0.00026369625,0.00016636714,0.00070379605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030547392,0.000042452997,0.9910575,0.000018103381,0.000040434326,0.00040876964,0.00013138745,0.0001300254,0.0029380585,0.00002626927,0.00019746761,0.0047041425],"study_design_scores_gemma":[0.000004054889,0.00009241558,0.99797577,0.0000031294453,0.0000091253805,0.0011427021,0.0000698257,0.00025369308,0.00029587795,0.000051866064,0.00009923098,0.0000023148523],"about_ca_topic_score_codex":0.004966273,"about_ca_topic_score_gemma":0.004535122,"teacher_disagreement_score":0.004966273,"about_ca_system_score_codex":0.00012850227,"about_ca_system_score_gemma":0.00020296837,"threshold_uncertainty_score":0.0098747015},"labels":[],"label_agreement":null},{"id":"W2075433159","doi":"10.1016/j.neuroimage.2007.01.006","title":"In vivo fiber tracking in the rat brain on a clinical 3T MRI system using a high strength insert gradient coil","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials","funders":"National Institute on Alcohol Abuse and Alcoholism; Heart and Stroke Foundation of Canada","keywords":"Splenium; Fractional anisotropy; Diffusion MRI; Corpus callosum; White matter; Biomedical engineering; Human brain; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Computer science; Neuroscience; Medicine; Physics; Psychology; Radiology","score_opus":0.11416610691376267,"score_gpt":0.4208602769058249,"score_spread":0.3066941699920622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075433159","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8906578,0.0008132617,0.10431596,0.00040971147,0.000100115074,0.00021274472,0.0006179772,0.0008876698,0.0019846857],"genre_scores_gemma":[0.88792413,0.0020640057,0.103251606,0.00016576663,0.00006061956,0.00021427976,0.00051410444,0.00034512227,0.0054603205],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981326,0.00004911563,0.000010004021,0.000051566043,0.00003212434,0.00004386674],"domain_scores_gemma":[0.9994659,0.00016950356,0.00010481924,0.000082590064,0.000112381735,0.00006479836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008183776,0.00046643283,0.00034116412,0.00040530073,0.0005805126,0.0004120855,0.0004944229,0.0008961137,0.00095939124],"category_scores_gemma":[0.0007746812,0.0004533592,0.0002335833,0.00047714994,0.0006737557,0.0008121336,0.0003754939,0.0005745698,0.00031171643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001057503,0.00011515197,0.00052567746,0.00008415881,0.000021492253,0.00006856028,0.0001846126,0.0020990153,0.9869933,0.00028902252,0.0003352261,0.008226221],"study_design_scores_gemma":[0.00023808023,0.0042630374,0.01195408,0.000042884225,0.00023346177,0.0006321715,0.00015255703,0.019231832,0.9597871,0.00046389297,0.0029351197,0.00006582147],"about_ca_topic_score_codex":0.009401357,"about_ca_topic_score_gemma":0.011681228,"teacher_disagreement_score":0.009401357,"about_ca_system_score_codex":0.0004084473,"about_ca_system_score_gemma":0.0015663898,"threshold_uncertainty_score":0.018693268},"labels":[],"label_agreement":null},{"id":"W2075738639","doi":"10.1016/j.pain.2012.04.003","title":"White matter brain and trigeminal nerve abnormalities in temporomandibular disorder","year":2012,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; White matter; Diffusion MRI; Internal capsule; Fractional anisotropy; Neuroscience; Medicine; Psychology; Prefrontal cortex; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.027414624017866887,"score_gpt":0.3166459926550091,"score_spread":0.2892313686371422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075738639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99474996,0.0030247644,0.00079912023,0.00009820248,0.000009277345,0.000014784253,0.00017003958,0.000015180126,0.0011186822],"genre_scores_gemma":[0.9982218,0.00090256316,0.0006256152,0.000026475274,0.000009255142,0.000007375345,0.00008295887,0.000002589676,0.00012126114],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.000016483655,0.000014612276,0.000032918408,0.00002800244,0.000015297739],"domain_scores_gemma":[0.9998271,0.00002942192,0.000104699844,0.000009915567,0.0000146485145,0.000014276141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017084443,0.00039333611,0.00015414259,0.00128079,0.0002789276,0.00029058746,0.00014204517,0.00028102618,0.0012475365],"category_scores_gemma":[0.00078651577,0.0001258717,0.00018647077,0.0009513643,0.0005541531,0.00028183893,0.00029248418,0.00020878571,0.00006450025],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013117993,0.00015215397,0.6684508,0.00075536,0.0004896416,0.013685535,0.0012449329,0.0011525864,0.21831863,0.001445116,0.00072279613,0.09227063],"study_design_scores_gemma":[0.000010563625,0.00007564088,0.9884672,0.000028956634,0.00005839803,0.007968181,0.00016144477,0.00048283205,0.0018619068,0.00050995476,0.0003667606,0.00000810769],"about_ca_topic_score_codex":0.005026749,"about_ca_topic_score_gemma":0.005075318,"teacher_disagreement_score":0.005026749,"about_ca_system_score_codex":0.0003581023,"about_ca_system_score_gemma":0.00024933473,"threshold_uncertainty_score":0.009994984},"labels":[],"label_agreement":null},{"id":"W2076609203","doi":"10.1371/journal.pone.0053678","title":"Reliable Identification of Deep Sulcal Pits: The Effects of Scan Session, Scanner, and Surface Extraction Tool","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Korea Science and Engineering Foundation; National Research Foundation of Korea; National Research Foundation","keywords":"Scanner; Neuroimaging; White matter; Artificial intelligence; Similarity (geometry); Pattern recognition (psychology); Nuclear medicine; Computer science; Magnetic resonance imaging; Biology; Medicine; Radiology; Neuroscience; Image (mathematics)","score_opus":0.03248149711368872,"score_gpt":0.2956015678760396,"score_spread":0.2631200707623509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076609203","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9542351,0.00094138115,0.04298051,0.0000975195,0.00008864402,0.00013149517,0.0002548206,0.00034256454,0.00092798396],"genre_scores_gemma":[0.99071527,0.000095076444,0.008322422,0.000031847532,0.000031349893,0.00005069583,0.00029547964,0.00017763433,0.0002803001],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99499714,0.0022790232,0.0005903801,0.0010306718,0.000918005,0.00018472318],"domain_scores_gemma":[0.9501534,0.030923659,0.0059687574,0.0074167363,0.005051889,0.00048553286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009808599,0.00074946607,0.000818307,0.0007572208,0.0005041471,0.0008425986,0.00053645,0.0007232832,0.0010951291],"category_scores_gemma":[0.04983279,0.00046785508,0.00061300053,0.00058457383,0.00085485773,0.0011152544,0.0009512089,0.0005397175,0.0003820287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0080336,0.00037490102,0.5071495,0.00091419276,0.0031896126,0.00095197634,0.0032746587,0.009707788,0.28007627,0.000425712,0.001157363,0.18474437],"study_design_scores_gemma":[0.000062755564,0.0017933577,0.93463814,0.000040855768,0.0005988889,0.0022143535,0.00038525535,0.014793807,0.043178827,0.0009248778,0.0012676284,0.000101244535],"about_ca_topic_score_codex":0.0009972707,"about_ca_topic_score_gemma":0.0022394205,"teacher_disagreement_score":0.009808599,"about_ca_system_score_codex":0.00016334442,"about_ca_system_score_gemma":0.00030495037,"threshold_uncertainty_score":0.051873446},"labels":[],"label_agreement":null},{"id":"W2076623026","doi":"10.1016/j.neuroimage.2011.04.068","title":"Wallerian degeneration after spinal cord lesions in cats detected with diffusion tensor imaging","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Christopher and Dana Reeve Foundation","keywords":"Wallerian degeneration; Diffusion MRI; CATS; Spinal cord; Degeneration (medical); Medicine; Pathology; Neuroscience; Anatomy; Psychology; Radiology; Magnetic resonance imaging; Internal medicine","score_opus":0.0766308467582226,"score_gpt":0.32317191193837425,"score_spread":0.24654106518015165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076623026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974482,0.00039461572,0.00035479196,0.00010035756,0.000014471645,0.000038513474,0.0002458133,0.00001629457,0.0013869368],"genre_scores_gemma":[0.99782145,0.00028374416,0.00026569082,0.000027102738,0.000008926886,0.000014953686,0.00019483847,0.000005240714,0.0013779878],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986434,0.00001766896,0.000014213746,0.00003046344,0.000028201683,0.000045130073],"domain_scores_gemma":[0.99931085,0.00010588983,0.00026471989,0.000079161975,0.00010159385,0.00013778747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003244968,0.0003627007,0.0004458213,0.0014153679,0.0004939123,0.000435295,0.0003504857,0.0008160329,0.0021606847],"category_scores_gemma":[0.0008803147,0.00044178052,0.00024654318,0.00034656006,0.0011040516,0.0006120711,0.00043006055,0.00096510554,0.00034389205],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01390221,0.0027668418,0.21837085,0.0008315436,0.00075966306,0.122250624,0.0014237319,0.0030483594,0.5837335,0.0022700587,0.0020035205,0.048639048],"study_design_scores_gemma":[0.0004968082,0.0072934977,0.7947311,0.00016329852,0.0005709895,0.08560286,0.00080858445,0.008380786,0.09765223,0.0014881004,0.0026826276,0.00012917112],"about_ca_topic_score_codex":0.0058712694,"about_ca_topic_score_gemma":0.007478379,"teacher_disagreement_score":0.0058712694,"about_ca_system_score_codex":0.0007284054,"about_ca_system_score_gemma":0.00047960115,"threshold_uncertainty_score":0.011674166},"labels":[],"label_agreement":null},{"id":"W2077459260","doi":"10.1016/j.neuroimage.2015.03.039","title":"Developmental synchrony of thalamocortical circuits in the neonatal brain","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Ministry of Education - Singapore; National Medical Research Council; National Research Foundation Singapore; Singapore Institute for Clinical Sciences; National University of Singapore; Ministry of Health -Singapore","keywords":"Thalamus; Neuroscience; Cortex (anatomy); Cerebral cortex; Diffusion MRI; Psychology; Temporal cortex; Functional magnetic resonance imaging; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.12667462552934863,"score_gpt":0.365192266885537,"score_spread":0.2385176413561884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077459260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97223127,0.0025384717,0.016967997,0.00043318348,0.000050139035,0.000019628233,0.00063093076,0.00012499122,0.007003289],"genre_scores_gemma":[0.9943252,0.0013303343,0.0032576555,0.0000321253,0.000016819946,0.000027878756,0.00015712183,0.000036219306,0.0008166086],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998159,0.0000381436,0.000013664028,0.00004347835,0.000061175415,0.00002769977],"domain_scores_gemma":[0.999298,0.00022611565,0.00021122294,0.000047118927,0.00014935742,0.000068138776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004593639,0.0002523818,0.00019553817,0.0009787593,0.00021289568,0.0007577235,0.0003423406,0.00032007816,0.0020009931],"category_scores_gemma":[0.0031836017,0.00019737144,0.0001427123,0.00050500676,0.0006223055,0.0006270754,0.00050200283,0.00056305673,0.00022022723],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010096446,0.0001501815,0.15859371,0.00031419113,0.00013408587,0.0073502967,0.0026470732,0.0055421363,0.5680398,0.025438333,0.0023530717,0.22842748],"study_design_scores_gemma":[0.000020560428,0.00027787595,0.8406744,0.00016111747,0.00008786084,0.0058064917,0.0014603783,0.0044900225,0.13081226,0.011323718,0.0048416117,0.00004373014],"about_ca_topic_score_codex":0.0022911667,"about_ca_topic_score_gemma":0.002739235,"teacher_disagreement_score":0.0022911667,"about_ca_system_score_codex":0.00065586634,"about_ca_system_score_gemma":0.000600393,"threshold_uncertainty_score":0.0066939592},"labels":[],"label_agreement":null},{"id":"W2078272321","doi":"10.1016/j.schres.2006.09.009","title":"Cerebral grey, white matter and csf in never-medicated, first-episode schizophrenia","year":2006,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":189,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Grey matter; White matter; Psychology; Internal capsule; Cingulum (brain); Lateral ventricles; Schizophrenia (object-oriented programming); Thalamus; Anterior cingulate cortex; Caudate nucleus; Insular cortex; Voxel-based morphometry; Psychosis; Limbic lobe; Parahippocampal gyrus; Cardiology; Neuroscience; Medicine; Fractional anisotropy; Magnetic resonance imaging; Temporal lobe; Psychiatry; Radiology; Cognition","score_opus":0.06080943112424795,"score_gpt":0.3661039390312939,"score_spread":0.30529450790704593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078272321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993863,0.0002846378,0.000007511038,0.000020952666,0.000003346453,0.0000022879992,0.00007699772,9.583698e-7,0.0002170585],"genre_scores_gemma":[0.9995216,0.00025184487,0.000026202099,0.000019118834,0.00000648297,0.000002019518,0.00008045171,9.900014e-7,0.00009133534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999081,0.000021147094,0.000013114086,0.000011533826,0.000021995456,0.000024017936],"domain_scores_gemma":[0.9994437,0.00020090208,0.00013594491,0.000020993513,0.000071113405,0.00012730424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003330069,0.000249071,0.00042484532,0.0010496356,0.0005052246,0.00045676567,0.0002146813,0.0005060394,0.00084257894],"category_scores_gemma":[0.0015437492,0.00030875343,0.00020706707,0.0005257419,0.00063554215,0.00047602103,0.00031679097,0.00043706747,0.000119172575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009452778,0.00022823589,0.9581141,0.00018367465,0.0002268923,0.0063164253,0.0018879198,0.0003292931,0.017277312,0.00011428365,0.00029677773,0.005572418],"study_design_scores_gemma":[0.000028696522,0.00020723717,0.9975635,0.000007884134,0.000045565357,0.0011532776,0.00039191678,0.00010922934,0.0003605842,0.00005650209,0.00006958391,0.0000059638587],"about_ca_topic_score_codex":0.02529724,"about_ca_topic_score_gemma":0.029737335,"teacher_disagreement_score":0.02529724,"about_ca_system_score_codex":0.00074504886,"about_ca_system_score_gemma":0.00054568297,"threshold_uncertainty_score":0.050299942},"labels":[],"label_agreement":null},{"id":"W2078369932","doi":"10.1016/j.mric.2009.02.001","title":"Diffusion and Perfusion MR Imaging of Acute Ischemic Stroke","year":2009,"lang":"en","type":"review","venue":"Magnetic Resonance Imaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Medicine; Diffusion imaging; Perfusion; Perfusion scanning; Stroke (engine); Diffusion MRI; Acute stroke; Ischemia; Radiology; Brain ischemia; Ischemic stroke; Magnetic resonance imaging; Cardiology; Internal medicine","score_opus":0.033716420910521065,"score_gpt":0.36830664241992006,"score_spread":0.334590221509399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078369932","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009910783,0.99885345,0.00009606152,0.00014336965,0.00012207664,0.000004125135,0.000010935425,0.000004595149,0.0006661734],"genre_scores_gemma":[0.00071126496,0.9982192,0.0001847519,0.00015774481,0.0003550799,0.0000041629123,0.000024060428,9.949333e-7,0.00034275284],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996965,0.000044168926,0.00008114137,0.000053936925,0.000101520876,0.00002277684],"domain_scores_gemma":[0.99914825,0.00038947703,0.00015521281,0.000024718529,0.00023020929,0.00005207384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008453304,0.0011665162,0.0020816023,0.0058018416,0.0002531339,0.001181593,0.0011493865,0.001350383,0.0020027128],"category_scores_gemma":[0.0017125052,0.00049185427,0.00058687554,0.004249045,0.00088742987,0.0020036697,0.00064845086,0.0013531935,0.0016605582],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007873193,0.000080834485,0.00045604043,0.013594314,0.00011770515,0.0006798512,0.00006512277,0.0002903495,0.0010151459,0.0012579018,0.03870978,0.9436542],"study_design_scores_gemma":[0.00006366508,0.00016648744,0.004199568,0.0072611906,0.00056004093,0.01019639,0.00016223389,0.00034273422,0.0007435707,0.0022026324,0.9740327,0.00006881204],"about_ca_topic_score_codex":0.0028896758,"about_ca_topic_score_gemma":0.004967708,"teacher_disagreement_score":0.0058018416,"about_ca_system_score_codex":0.00063749467,"about_ca_system_score_gemma":0.0015183946,"threshold_uncertainty_score":0.006699741},"labels":[],"label_agreement":null},{"id":"W2078510704","doi":"10.1097/wnr.0000000000000204","title":"The relationship between uncinate fasciculus white matter integrity and verbal memory proficiency in children","year":2014,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Population and Public Health","funders":"National Heart, Lung, and Blood Institute","keywords":"Uncinate fasciculus; Fractional anisotropy; Psychology; Fasciculus; White matter; Verbal memory; Diffusion MRI; Audiology; Inferior longitudinal fasciculus; Developmental psychology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.06031355565817511,"score_gpt":0.3418536438509589,"score_spread":0.2815400881927838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078510704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999765,0.00005264332,0.000024440036,0.000006520404,3.9489814e-7,8.262116e-7,0.000038564733,0.0000011361992,0.000110462686],"genre_scores_gemma":[0.99962306,0.00006855601,0.00010034941,0.0000035891705,0.0000017093907,0.0000033041974,0.00007373506,0.0000018330745,0.0001238095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997801,0.000026822854,0.0000305252,0.00006151165,0.00003617801,0.00006486783],"domain_scores_gemma":[0.9981207,0.00028016858,0.0012455506,0.00007359637,0.00014863389,0.00013128984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036275465,0.00032692973,0.00019223684,0.0010325551,0.00023593125,0.00043859964,0.00017371832,0.000335013,0.0012877574],"category_scores_gemma":[0.0022502365,0.0002063123,0.00013721823,0.00038892272,0.00044580852,0.00042959323,0.00029071548,0.00031192455,0.00016184738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001029256,0.000024033898,0.99413717,0.000009397425,0.000020596353,0.00020672382,0.00034248224,0.00005362133,0.0029232705,0.000020786161,0.000020234964,0.0021387131],"study_design_scores_gemma":[0.0000010258352,0.00004122669,0.99880433,0.000003349963,0.000006510182,0.0004544903,0.00019222108,0.00002989405,0.0004146499,0.000009617307,0.00004102103,0.0000015764396],"about_ca_topic_score_codex":0.0071367184,"about_ca_topic_score_gemma":0.008936079,"teacher_disagreement_score":0.0071367184,"about_ca_system_score_codex":0.00026018568,"about_ca_system_score_gemma":0.00020752226,"threshold_uncertainty_score":0.014190376},"labels":[],"label_agreement":null},{"id":"W2078989713","doi":"10.1523/jneurosci.3048-13.2013","title":"Motor Skill Learning Induces Changes in White Matter Microstructure and Myelination","year":2013,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":425,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"University of Oxford; National Institute for Health and Care Research; Oxford University Hospitals NHS Foundation Trust; Cancer Research UK; Wellcome Trust","keywords":"Fractional anisotropy; White matter; Psychology; Motor cortex; Motor learning; Neuroscience; Neuroplasticity; Lateralization of brain function; Cortex (anatomy); Myelin; Diffusion MRI; Medicine; Magnetic resonance imaging; Central nervous system","score_opus":0.030655539956320164,"score_gpt":0.3225949208676715,"score_spread":0.29193938091135135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078989713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99932957,0.000058494512,0.00040213772,0.00001078069,0.0000023977807,0.000004566739,0.000027519796,0.00001547345,0.00014906844],"genre_scores_gemma":[0.9980854,0.00013464317,0.00071096036,0.000019821968,0.000004450317,0.000019200937,0.00012040537,0.000008522607,0.00089672784],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982613,0.000011174108,0.000010790666,0.000049197362,0.00004803686,0.000054620563],"domain_scores_gemma":[0.9996475,0.000040841576,0.00016522124,0.00004355822,0.000023534587,0.00007949182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013381524,0.0003692614,0.00028960808,0.00025421625,0.00009638848,0.00021409648,0.00016328665,0.00021981103,0.0011188927],"category_scores_gemma":[0.00030314532,0.00016014402,0.00020551517,0.00010478142,0.00034795847,0.00017134576,0.0002814383,0.00048218647,0.00012172247],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003016297,0.00016460604,0.0025240686,0.000026677648,0.000020202304,0.00009349195,0.000025890322,0.00012941705,0.99286205,0.000033766828,0.000025514491,0.0037926638],"study_design_scores_gemma":[0.000041738585,0.0048869867,0.22045076,0.0000134621605,0.000053099662,0.0007300435,0.00008570084,0.0012391177,0.7716635,0.00021077771,0.00060715765,0.000017629513],"about_ca_topic_score_codex":0.0006628585,"about_ca_topic_score_gemma":0.0017697924,"teacher_disagreement_score":0.0011188927,"about_ca_system_score_codex":0.00023699312,"about_ca_system_score_gemma":0.00023022514,"threshold_uncertainty_score":0.003743112},"labels":[],"label_agreement":null},{"id":"W2079334797","doi":"10.1503/jpn.100041","title":"Complementary diffusion tensor imaging study of the corpus callosum in patients with first-episode and chronic schizophrenia","year":2011,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Xiangya Hospital, Central South University; Central South University","keywords":"Corpus callosum; Diffusion MRI; Schizophrenia (object-oriented programming); Fractional anisotropy; White matter; Psychology; Magnetic resonance imaging; Neuroimaging; Pathological; Neuroscience; Medicine; Psychiatry; Internal medicine; Radiology","score_opus":0.03079589462467696,"score_gpt":0.28912233874947996,"score_spread":0.258326444124803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079334797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996244,0.00009598826,0.00002001572,0.000025858086,0.0000016629186,0.000008083619,0.00005524878,0.0000014882158,0.00016718346],"genre_scores_gemma":[0.9996327,0.000070242306,0.00009561046,0.000013969637,0.0000031535312,0.000007465964,0.000117351025,9.378971e-7,0.000058668156],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998932,0.000016744743,0.000015562915,0.000024720166,0.000020140638,0.000029532717],"domain_scores_gemma":[0.9993048,0.00010331332,0.00027032298,0.000035096356,0.000102528,0.00018393947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046566027,0.00047781854,0.00040965728,0.0013414109,0.00072874874,0.00042049782,0.00023352739,0.00057527644,0.0014975943],"category_scores_gemma":[0.0020312588,0.00022541442,0.00023324235,0.0004989887,0.0005006156,0.00044792087,0.00039194926,0.00038723205,0.00016481648],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013266273,0.00026987062,0.96928465,0.00013188581,0.00012190174,0.005193191,0.0031057564,0.00014182013,0.01506663,0.00010547936,0.00025120043,0.0050009633],"study_design_scores_gemma":[0.00003652317,0.0002929576,0.9934395,0.000017833056,0.000031107065,0.0048291534,0.00068023405,0.00013167824,0.00034941192,0.00005396401,0.00012904087,0.000008484538],"about_ca_topic_score_codex":0.0098550245,"about_ca_topic_score_gemma":0.011219792,"teacher_disagreement_score":0.0098550245,"about_ca_system_score_codex":0.0007890261,"about_ca_system_score_gemma":0.000807666,"threshold_uncertainty_score":0.019595325},"labels":[],"label_agreement":null},{"id":"W2079501536","doi":"10.1016/j.neurobiolaging.2006.05.018","title":"Age and gender effects on human brain anatomy: A voxel-based morphometric study in healthy elderly","year":2006,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":325,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute on Aging; AGE-WELL; Deutsches Krebsforschungszentrum","keywords":"Corpus callosum; Grey matter; Voxel; White matter; Temporal lobe; Posterior cingulate; Magnetic resonance imaging; Basal ganglia; Brain size; Human brain; Parietal lobe; Psychology; Voxel-based morphometry; Anatomy; Brain mapping; Cingulate cortex; Frontal lobe; Cortex (anatomy); Medicine; Neuroscience; Central nervous system; Radiology","score_opus":0.06552498220250581,"score_gpt":0.3924909855949094,"score_spread":0.3269660033924036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079501536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991266,0.00019134251,0.0002850239,0.0000129100345,0.000004111909,0.0000038507355,0.0001367754,0.0000046907335,0.00023467149],"genre_scores_gemma":[0.9989785,0.00020812654,0.0003419669,0.00001335032,0.000009196776,0.0000049603564,0.00008966422,0.000009697376,0.00034465015],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993205,0.000012993296,0.0000068162863,0.000022658875,0.000014216675,0.000011274419],"domain_scores_gemma":[0.9997197,0.00008188721,0.00008210852,0.00004035366,0.000041908457,0.00003399889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027023634,0.000222602,0.00026977324,0.00049669977,0.00020065815,0.00025464757,0.00016842826,0.00022153444,0.0015723236],"category_scores_gemma":[0.0010115467,0.00019033653,0.0001915193,0.00040101516,0.0003445965,0.00049833726,0.00021845066,0.000120425844,0.000156726],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010530794,0.0004977505,0.5877329,0.0002892059,0.00060244615,0.003918473,0.0043227235,0.0016736699,0.30087474,0.0012776982,0.0011277477,0.087151885],"study_design_scores_gemma":[0.000020962334,0.00035816408,0.99416155,0.0000039321453,0.000085531414,0.0017850179,0.0003268371,0.00048736908,0.0021497828,0.00027157107,0.00033936868,0.000009878768],"about_ca_topic_score_codex":0.0025058913,"about_ca_topic_score_gemma":0.0051773004,"teacher_disagreement_score":0.0025058913,"about_ca_system_score_codex":0.00014112215,"about_ca_system_score_gemma":0.00016534583,"threshold_uncertainty_score":0.005259931},"labels":[],"label_agreement":null},{"id":"W2079848144","doi":"10.1016/j.jalz.2010.05.569","title":"P1‐022: Characterizing abnormal white matter structure in primary progressive aphasia","year":2010,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Health Sciences Centre; University Health Network; University of Toronto","funders":"","keywords":"Primary progressive aphasia; Diffusion MRI; White matter; Fractional anisotropy; Audiology; Arcuate fasciculus; Voxel; Nuclear medicine; Uncinate fasciculus; SMA*; Psychology; Boston Naming Test; Inferior longitudinal fasciculus; Medicine; Neuroscience; Dementia; Cognition; Pathology; Radiology; Neuropsychology; Mathematics; Magnetic resonance imaging; Frontotemporal dementia; Disease","score_opus":0.02388996777428627,"score_gpt":0.30671116162288425,"score_spread":0.282821193848598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079848144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996058,0.00015602772,0.0006881879,0.000045166653,0.0000070473993,0.000106822474,0.0003297394,0.000042663127,0.002566411],"genre_scores_gemma":[0.9969469,0.00011052308,0.0010786592,0.00003832028,0.000017850061,0.00005883511,0.00046723767,0.000021045355,0.0012606188],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985564,0.000020728603,0.000019313222,0.000044307344,0.000039176342,0.000020773563],"domain_scores_gemma":[0.9997961,0.000044936656,0.00004549407,0.00001735083,0.00003770253,0.00005847301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051383744,0.000704408,0.00037532425,0.0017144663,0.0004242031,0.0006539075,0.00035201284,0.00058928266,0.004063307],"category_scores_gemma":[0.001125117,0.00021016986,0.00017405175,0.0006351843,0.00049935555,0.00035855712,0.00036937898,0.0002640301,0.0009756344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043562492,0.00077052874,0.6270168,0.0004973468,0.00019408858,0.03667513,0.0013604576,0.00045207064,0.2611554,0.00037995828,0.0029938421,0.06414824],"study_design_scores_gemma":[0.00007406887,0.0013888908,0.95730215,0.000019921074,0.00004450908,0.031933587,0.00023318778,0.0009433615,0.0064885397,0.00027228871,0.0012879357,0.0000114945105],"about_ca_topic_score_codex":0.001872348,"about_ca_topic_score_gemma":0.002291773,"teacher_disagreement_score":0.004063307,"about_ca_system_score_codex":0.00022817553,"about_ca_system_score_gemma":0.0002824008,"threshold_uncertainty_score":0.013593137},"labels":[],"label_agreement":null},{"id":"W2079987516","doi":"10.1016/j.neuroimage.2005.09.068","title":"The NIH MRI study of normal brain development","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":538,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Generalizability theory; Voxel; Population; Protocol (science); Diffusion MRI; Medicine; Sample size determination; Neuroimaging; Database; Magnetic resonance imaging; Medical physics; Psychology; Pathology; Computer science; Radiology; Statistics; Developmental psychology; Psychiatry","score_opus":0.041257074273638845,"score_gpt":0.3354868080599654,"score_spread":0.29422973378632655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079987516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9262191,0.011466339,0.0027590059,0.0031590632,0.00023434624,0.00009250987,0.0014611135,0.00010881734,0.05449971],"genre_scores_gemma":[0.9882775,0.0049179113,0.0024306427,0.0001757249,0.00017588183,0.000021949352,0.00034927213,0.000026499769,0.003624572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980634,0.000069136826,0.000023716788,0.00002593719,0.0000502128,0.000024715944],"domain_scores_gemma":[0.9991898,0.00020461566,0.00010289831,0.00008038122,0.0002768846,0.00014540814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006084629,0.00033269115,0.00017975699,0.0027066052,0.00028978018,0.0004961629,0.00033694512,0.00039508395,0.0019992096],"category_scores_gemma":[0.0032123972,0.00018350809,0.00019044928,0.00079762784,0.0008759826,0.0007675333,0.00034087818,0.00042178872,0.0003706632],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023034706,0.0006737016,0.4671549,0.00083324034,0.00025955384,0.047731213,0.0021876695,0.0010182722,0.11628712,0.029553793,0.021399267,0.3105978],"study_design_scores_gemma":[0.00007198826,0.00096901145,0.82805306,0.00018880783,0.00016957082,0.09491082,0.0014444701,0.0011133455,0.027255477,0.012482816,0.033282943,0.000057708647],"about_ca_topic_score_codex":0.006184239,"about_ca_topic_score_gemma":0.004378907,"teacher_disagreement_score":0.006184239,"about_ca_system_score_codex":0.00039678146,"about_ca_system_score_gemma":0.0009926434,"threshold_uncertainty_score":0.012296498},"labels":[],"label_agreement":null},{"id":"W2080094149","doi":"10.3389/fninf.2014.00059","title":"Real-time multi-peak tractography for instantaneous connectivity display","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"Tractography; Computer science; Voxel; Diffusion MRI; Artificial intelligence; Pattern recognition (psychology); Human Connectome Project; Imaging phantom; Computer vision; Functional connectivity; Magnetic resonance imaging","score_opus":0.02914577916448745,"score_gpt":0.3089900371262589,"score_spread":0.2798442579617714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080094149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052283714,0.00007868028,0.9883931,0.000059445447,0.000019484489,0.000026921487,0.00015830017,0.005524626,0.00051096],"genre_scores_gemma":[0.087926775,0.0001922589,0.90883493,0.000058802638,0.000027671964,0.00012167771,0.000406775,0.0012977062,0.0011334225],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997938,0.00003995303,0.000014050966,0.00003697057,0.000099573626,0.000015712372],"domain_scores_gemma":[0.9992842,0.0003293867,0.00007789909,0.00014783791,0.000115422234,0.00004530975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054869597,0.00062089495,0.0003698984,0.0008430375,0.00018908028,0.00078826625,0.0008450711,0.00078131625,0.00990004],"category_scores_gemma":[0.0031000755,0.0003283585,0.00040526653,0.00068799837,0.00027335132,0.0008658263,0.000690657,0.0006358318,0.0017308507],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056929246,0.00009522973,0.0017231449,0.0004366237,0.000115085764,0.00068153645,0.00042692723,0.080684386,0.27608892,0.019105522,0.018366076,0.6017073],"study_design_scores_gemma":[0.000053295935,0.000120774086,0.001882912,0.00004991919,0.000029949815,0.0010687677,0.00004946755,0.84316576,0.124027155,0.008748788,0.020738712,0.00006441843],"about_ca_topic_score_codex":0.0007764979,"about_ca_topic_score_gemma":0.0011894687,"teacher_disagreement_score":0.00990004,"about_ca_system_score_codex":0.00030038774,"about_ca_system_score_gemma":0.000475916,"threshold_uncertainty_score":0.033118904},"labels":[],"label_agreement":null},{"id":"W2080329798","doi":"10.1063/1.4818797","title":"Some classes of renormalizable tensor models","year":2013,"lang":"en","type":"article","venue":"Journal of Mathematical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Tensor (intrinsic definition); Rank (graph theory); Physics; Mathematical physics; Function (biology); Tensor field; Tensor density; Simple (philosophy); Theoretical physics; Mathematics; Pure mathematics; Exact solutions in general relativity; Combinatorics; Quantum mechanics; Philosophy","score_opus":0.10338835903557786,"score_gpt":0.3527400115788212,"score_spread":0.24935165254324332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080329798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6636088,0.0013176551,0.21689282,0.00204838,0.00043882168,0.00022003076,0.00032052473,0.0018596045,0.11329341],"genre_scores_gemma":[0.94768864,0.00058238633,0.0316707,0.00059590396,0.0006129944,0.00021141524,0.0004376888,0.00039213934,0.017808173],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993382,0.00015737259,0.00003936349,0.00011849813,0.0002141825,0.00013233461],"domain_scores_gemma":[0.99904865,0.00017076527,0.00019049771,0.00024487393,0.0001356713,0.00020947475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072823325,0.0011473065,0.0006617176,0.0027905565,0.0013904977,0.0017755472,0.0013225449,0.0019444894,0.00608249],"category_scores_gemma":[0.0017544607,0.00041834638,0.0021261242,0.00052155677,0.0020908525,0.002601601,0.0013723111,0.0018353062,0.00068300293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002283275,0.00003590609,0.00029701876,0.000036974718,0.000016249749,0.0002855813,0.00028839157,0.0025762382,0.0054672854,0.98782235,0.0007297445,0.0024213756],"study_design_scores_gemma":[0.000031772302,0.000056717283,0.0005385354,0.000019787773,0.000018223232,0.0005186662,0.00013073189,0.046132512,0.0018903804,0.94757223,0.0030542207,0.000036170335],"about_ca_topic_score_codex":0.00094760547,"about_ca_topic_score_gemma":0.0007006961,"teacher_disagreement_score":0.00608249,"about_ca_system_score_codex":0.00077603926,"about_ca_system_score_gemma":0.0005690522,"threshold_uncertainty_score":0.020348012},"labels":[],"label_agreement":null},{"id":"W2080423736","doi":"10.1016/j.nurt.2007.05.004","title":"Magnetic Resonance Imaging of Myelin","year":2007,"lang":"en","type":"review","venue":"Neurotherapeutics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":324,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada","keywords":"Myelin; Diffusion imaging; Magnetic resonance imaging; Diffusion MRI; Magnetization transfer; Neuroscience; Nuclear magnetic resonance; Neurology; T2 relaxation; In vivo magnetic resonance spectroscopy; Relaxation (psychology); Medicine; Psychology; Physics; Radiology; Central nervous system","score_opus":0.19439852431245547,"score_gpt":0.44790907994188484,"score_spread":0.25351055562942937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080423736","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021503337,0.9971499,0.00034104078,0.00023187697,0.00015967782,0.000004991957,0.000011737708,0.000010696216,0.0018750886],"genre_scores_gemma":[0.0019627667,0.9953719,0.0005509671,0.00028375222,0.00039745177,0.000007406034,0.000035974175,0.0000027871781,0.0013870345],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99980253,0.00003961389,0.000028604712,0.000039982195,0.00006871541,0.000020569767],"domain_scores_gemma":[0.9996742,0.00013580352,0.00006508391,0.000016937785,0.00008800756,0.000019882722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005119843,0.0011334545,0.0013360083,0.0037604352,0.0002343205,0.00090980635,0.0009296285,0.0012954787,0.002460788],"category_scores_gemma":[0.0007915044,0.00031814846,0.00041006636,0.002360561,0.00091188663,0.0014380703,0.00067656074,0.0012539601,0.0026843676],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005801348,0.000054085496,0.0003130663,0.008824388,0.000081765866,0.0011816728,0.000064241045,0.00025347926,0.0036910113,0.0024344092,0.028177135,0.9548667],"study_design_scores_gemma":[0.000027667498,0.00009397628,0.0023572252,0.0044831038,0.0001947438,0.021672681,0.00010599423,0.00020624771,0.0033277203,0.0034912927,0.9639922,0.000047298694],"about_ca_topic_score_codex":0.0016951979,"about_ca_topic_score_gemma":0.0027102127,"teacher_disagreement_score":0.0037604352,"about_ca_system_score_codex":0.0007499601,"about_ca_system_score_gemma":0.0011878036,"threshold_uncertainty_score":0.008232117},"labels":[],"label_agreement":null},{"id":"W2081139805","doi":"10.1371/journal.pone.0072375","title":"White Matter Deficits in Psychopathic Offenders and Correlation with Factor Structure","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Community Safety and Correctional Services; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Alliance for Research on Schizophrenia and Depression; American Psychiatric Institute for Research and Education; AstraZeneca; Pfizer","keywords":"White matter; Fractional anisotropy; Psychology; Psychopathy; Diffusion MRI; Amygdala; Orbitofrontal cortex; Prefrontal cortex; Neuroscience; Voxel; Personality; Medicine; Magnetic resonance imaging; Artificial intelligence; Cognition; Computer science","score_opus":0.06043499436491861,"score_gpt":0.2714874023309725,"score_spread":0.2110524079660539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081139805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996037,0.000029397006,0.00009082357,0.00001556718,7.7547236e-7,0.000004988698,0.000055769222,0.0000048383117,0.00019409519],"genre_scores_gemma":[0.99958295,0.000032013304,0.00016278362,0.0000037666625,0.0000016453087,0.000003612928,0.0000697732,0.000003920248,0.0001395204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998431,0.000023196118,0.000018390934,0.000047256086,0.000033353834,0.000034701323],"domain_scores_gemma":[0.9990422,0.00009778398,0.0005964813,0.000078770005,0.00006798894,0.00011673548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026720372,0.00034496677,0.00021992192,0.0019003059,0.00038920424,0.00040432825,0.00015820026,0.00025416657,0.0029205128],"category_scores_gemma":[0.0017430136,0.00018871916,0.00015023212,0.0007007899,0.0006443506,0.0002868467,0.0006060361,0.00032816068,0.00016293903],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000468291,0.00008931402,0.9754023,0.000025214531,0.000084952204,0.0011187847,0.00053713156,0.00017303148,0.012238229,0.00017913498,0.0001149799,0.009568601],"study_design_scores_gemma":[0.0000041167436,0.00006973875,0.9979019,0.000005427109,0.000014675711,0.0010865239,0.00020048983,0.00014360755,0.00035856484,0.00014594113,0.00006639083,0.0000026617386],"about_ca_topic_score_codex":0.0029588172,"about_ca_topic_score_gemma":0.004318453,"teacher_disagreement_score":0.0029588172,"about_ca_system_score_codex":0.00029823926,"about_ca_system_score_gemma":0.0002253813,"threshold_uncertainty_score":0.009770095},"labels":[],"label_agreement":null},{"id":"W2081608119","doi":"10.1016/j.jmr.2006.09.008","title":"Anisotropic diffusion of metabolites in peripheral nerve using diffusion weighted magnetic resonance spectroscopy at ultra-high field","year":2006,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Nuclear magnetic resonance; Chemistry; Phosphocreatine; Anisotropy; Effective diffusion coefficient; Creatine; Diffusion; Diffusion MRI; Nuclear magnetic resonance spectroscopy; Fractional anisotropy; Choline; White matter; Taurine; Analytical Chemistry (journal); Magnetic resonance imaging; Biochemistry; Endocrinology; Physics; Amino acid","score_opus":0.016745045602997374,"score_gpt":0.28950365755501134,"score_spread":0.27275861195201395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081608119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.932544,0.004408579,0.06054635,0.00024503222,0.000034911413,0.000041571995,0.00014040856,0.000107586115,0.0019314955],"genre_scores_gemma":[0.94806576,0.0029587352,0.04780285,0.0000560012,0.00005580868,0.000028924735,0.00008866066,0.000038512047,0.0009048032],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99991,0.000032667383,0.0000069501943,0.000017711674,0.000021289186,0.0000113752685],"domain_scores_gemma":[0.9996823,0.00014058601,0.00004923074,0.000035028745,0.00006320623,0.000029739458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004999533,0.0002813208,0.00018157558,0.0005564168,0.00032421385,0.00073271844,0.00032253092,0.0004808632,0.00065284484],"category_scores_gemma":[0.001128395,0.0003377422,0.00014030877,0.000473343,0.00039165607,0.0013960308,0.00034543232,0.00047038434,0.00013813403],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069016626,0.000068102745,0.004578778,0.00035525157,0.0000871955,0.0004961713,0.00026715835,0.0013140932,0.9475306,0.0012709443,0.00028502723,0.043056518],"study_design_scores_gemma":[0.00013417621,0.00066086435,0.06707526,0.00007273589,0.0003326951,0.0051191817,0.00039818464,0.034425966,0.8827289,0.004596561,0.0043541268,0.00010134906],"about_ca_topic_score_codex":0.0008756429,"about_ca_topic_score_gemma":0.0015790602,"teacher_disagreement_score":0.0008756429,"about_ca_system_score_codex":0.0001198598,"about_ca_system_score_gemma":0.00022138114,"threshold_uncertainty_score":0.0026440024},"labels":[],"label_agreement":null},{"id":"W2081768396","doi":"10.1016/j.eplepsyres.2014.08.023","title":"Diffusion abnormalities of the corpus callosum in patients with malformations of cortical development and epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo; Canadian Institutes of Health Research; Alberta Innovates; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Alberta Innovates - Health Solutions","keywords":"Polymicrogyria; Corpus callosum; Cortical dysplasia; Epilepsy; Diffusion MRI; Fractional anisotropy; White matter; Splenium; Magnetic resonance imaging; Schizencephaly; Medicine; Psychology; Pathology; Neuroscience; Radiology","score_opus":0.06345972487955862,"score_gpt":0.35026828277603755,"score_spread":0.28680855789647897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081768396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99806863,0.00032658,0.000079452686,0.00012378804,0.00000542412,0.0000065155823,0.00009477798,0.0000069372304,0.0012879778],"genre_scores_gemma":[0.99954623,0.00016528962,0.00006677909,0.000023208502,0.000012677721,0.0000027981062,0.00007511907,0.0000028421318,0.00010508832],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997837,0.00003331946,0.000041956213,0.000053936124,0.000044296463,0.000042742042],"domain_scores_gemma":[0.9990791,0.00032022703,0.00031470094,0.000050163977,0.000086823835,0.00014894441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028450004,0.0006791578,0.0004049246,0.0022783666,0.0006761002,0.00053736474,0.00048695118,0.0010249956,0.0016688657],"category_scores_gemma":[0.0035508673,0.00032547553,0.00024385423,0.0013345769,0.00084485894,0.00074903085,0.00038124956,0.0005717057,0.00016192549],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006804767,0.00009885966,0.9049874,0.000069661284,0.00008859331,0.078351736,0.00090173114,0.00038022126,0.0073567866,0.00023801776,0.0003544995,0.006492],"study_design_scores_gemma":[0.000030005023,0.00017979782,0.85939825,0.00001911241,0.000091063506,0.13711828,0.00070104917,0.00048028046,0.0012799847,0.0003045185,0.00037162003,0.000026043372],"about_ca_topic_score_codex":0.0070317504,"about_ca_topic_score_gemma":0.006131969,"teacher_disagreement_score":0.0070317504,"about_ca_system_score_codex":0.0005152961,"about_ca_system_score_gemma":0.0007337994,"threshold_uncertainty_score":0.01398164},"labels":[],"label_agreement":null},{"id":"W2081828863","doi":"10.1016/j.neuroimage.2013.05.054","title":"Networks of anatomical covariance","year":2013,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":434,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Covariance; Neuroscience; Diffusion MRI; Neuroimaging; Cognition; Computer science; Neuroplasticity; Psychology; Functional connectivity; Artificial intelligence; Cognitive psychology; Mathematics; Magnetic resonance imaging; Medicine; Statistics","score_opus":0.16851715130382555,"score_gpt":0.42858435873199624,"score_spread":0.2600672074281707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081828863","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031901917,0.92404187,0.05480872,0.0019276286,0.00050575513,0.00003203435,0.00033581204,0.00019271634,0.014965279],"genre_scores_gemma":[0.049318668,0.92407703,0.01915029,0.00038693694,0.0010816527,0.00006816042,0.00043323069,0.000033621043,0.0054503484],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99979967,0.000048094673,0.000013346597,0.000066457294,0.00006000974,0.000012449583],"domain_scores_gemma":[0.99955815,0.00021933987,0.00007903942,0.00003218811,0.00009276892,0.00001848991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006149028,0.0010051711,0.00083419675,0.0016624429,0.00019526671,0.0012022159,0.0007513801,0.0007882975,0.0025084217],"category_scores_gemma":[0.0019890307,0.0003426789,0.0004279887,0.0020725313,0.00097305235,0.001789303,0.0008255686,0.0007537262,0.0009933491],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031858945,0.0000212535,0.0008889191,0.0022019378,0.00017688875,0.00011171395,0.00007029857,0.004778443,0.0012507843,0.04030666,0.013656793,0.9365045],"study_design_scores_gemma":[0.000030662755,0.000111820074,0.015325115,0.0033655723,0.00047194096,0.0027206386,0.0001938369,0.017315393,0.003986554,0.37003502,0.58628243,0.00016107388],"about_ca_topic_score_codex":0.0023080595,"about_ca_topic_score_gemma":0.0036411053,"teacher_disagreement_score":0.0025084217,"about_ca_system_score_codex":0.00073567,"about_ca_system_score_gemma":0.0009792971,"threshold_uncertainty_score":0.008391559},"labels":[],"label_agreement":null},{"id":"W2081903382","doi":"10.1109/jbhi.2014.2367026","title":"Multimodality Neurological Data Visualization With Multi-VOI-Based DTI Fiber Dynamic Integration","year":2014,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CancerCare Manitoba; University of Winnipeg; Centre for Imaging Technology Commercialization; Western University","funders":"Canadian Institutes of Health Research","keywords":"Multimodality; Visualization; Computer science; Data visualization; Medical imaging; Artificial intelligence; Computer vision; World Wide Web","score_opus":0.17133119978234487,"score_gpt":0.44995263127333024,"score_spread":0.2786214314909854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081903382","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012524021,0.00023737657,0.97906756,0.00015679868,0.000029965306,0.000058902435,0.00029514707,0.0064254752,0.0012047709],"genre_scores_gemma":[0.12798229,0.0004736653,0.8673132,0.000090540474,0.000040139137,0.00016955515,0.00083665363,0.0015085216,0.00158551],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978906,0.00003419594,0.00002104082,0.000040948693,0.0000916059,0.000023070112],"domain_scores_gemma":[0.999688,0.00008133003,0.00004535945,0.000049646776,0.000102093814,0.00003349972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043986726,0.0008837761,0.00040374394,0.0017080259,0.00029373835,0.0014094522,0.00086926756,0.0005907918,0.0041467417],"category_scores_gemma":[0.0014853163,0.00040907835,0.00074522285,0.00097082386,0.0002535484,0.0010352712,0.0013330659,0.0007230534,0.0007432661],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048507212,0.0001880705,0.0037935982,0.00053759245,0.00025636292,0.0007815143,0.0007936711,0.13096063,0.19262709,0.014602521,0.014369468,0.6406044],"study_design_scores_gemma":[0.000041280706,0.00007386933,0.0017745827,0.000048253245,0.000054403456,0.0005450223,0.00006952385,0.9175216,0.05550669,0.007412045,0.016870389,0.00008229559],"about_ca_topic_score_codex":0.0027393743,"about_ca_topic_score_gemma":0.0033946761,"teacher_disagreement_score":0.0041467417,"about_ca_system_score_codex":0.00044873822,"about_ca_system_score_gemma":0.0007532717,"threshold_uncertainty_score":0.013872266},"labels":[],"label_agreement":null},{"id":"W2082320904","doi":"10.1109/mmbia.2012.6164765","title":"Reconstruction of HARDI using compressed sensing and its application to contrast HARDI","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion imaging; Compressed sensing; Contrast (vision); Artificial intelligence; Diffusion MRI; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging","score_opus":0.08458415834292106,"score_gpt":0.36080407214977606,"score_spread":0.276219913806855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082320904","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034141872,0.00038002038,0.9625729,0.0005369951,0.000059673523,0.00006480101,0.00007819006,0.00017394785,0.0019917036],"genre_scores_gemma":[0.3670377,0.00094229885,0.62894595,0.00021540491,0.00013807841,0.0001092061,0.00033418866,0.000110176974,0.0021670153],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961495,0.00009256288,0.000019354073,0.000049955837,0.0001922269,0.000030944037],"domain_scores_gemma":[0.9987979,0.0006621755,0.00016457264,0.00015770731,0.00015703707,0.000060551145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084894185,0.0007426278,0.00044103048,0.00075003336,0.0002453482,0.0008552024,0.0005763524,0.00076670037,0.0010943067],"category_scores_gemma":[0.004619371,0.0002431197,0.0004317941,0.00059657235,0.00083537877,0.0008375116,0.0013117458,0.0013003796,0.00026868386],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058387767,0.00015713394,0.002198722,0.00058418483,0.000074592885,0.00093197066,0.00041174825,0.43880358,0.16797614,0.08788119,0.0028475362,0.2975493],"study_design_scores_gemma":[0.00001387447,0.000080181235,0.00033605422,0.000014045598,0.000007051539,0.00028415982,0.000022665063,0.9729906,0.01824411,0.00682956,0.0011587669,0.000019035762],"about_ca_topic_score_codex":0.0009448504,"about_ca_topic_score_gemma":0.00074108556,"teacher_disagreement_score":0.0010943067,"about_ca_system_score_codex":0.00029219515,"about_ca_system_score_gemma":0.0005135454,"threshold_uncertainty_score":0.00448972},"labels":[],"label_agreement":null},{"id":"W2082419792","doi":"10.1089/neu.2007.0462","title":"Characterizing White Matter Damage in Rat Spinal Cord with Quantitative MRI and Histology","year":2008,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada","keywords":"Luxol fast blue stain; White matter; Fractional anisotropy; Myelin; Anatomy; Corticospinal tract; Spinal cord; Pathology; Diffusion MRI; Superior longitudinal fasciculus; Axon; Fasciculus; Magnetic resonance imaging; Diffuse axonal injury; Spinal cord injury; Medicine; Biology; Central nervous system; Traumatic brain injury; Neuroscience; Internal medicine; Radiology","score_opus":0.14436926360356772,"score_gpt":0.3889712740701122,"score_spread":0.2446020104665445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082419792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97727203,0.0022045719,0.018090902,0.000048685135,0.000027705428,0.000083682375,0.000894291,0.00035893839,0.0010191213],"genre_scores_gemma":[0.95686775,0.0032806394,0.032755356,0.00006114964,0.000023560702,0.00029762098,0.0012152868,0.000083947205,0.005414591],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997471,0.000033234013,0.000024244411,0.00007007611,0.00007767621,0.000047705424],"domain_scores_gemma":[0.9993499,0.00004575845,0.00028069745,0.000055047985,0.00020556056,0.00006313347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005890948,0.0009054552,0.00030683167,0.0014367938,0.00019189916,0.00043353622,0.00027671162,0.00042254268,0.0010434531],"category_scores_gemma":[0.00033127549,0.00029384313,0.00030426498,0.00042883935,0.00044016782,0.00056879246,0.00024361927,0.00038145698,0.00040327312],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000136012,0.000037619586,0.0008672385,0.000059246882,0.000009257198,0.000031593183,0.000026402231,0.00014374034,0.9972275,0.00003830556,0.000013748284,0.0014092682],"study_design_scores_gemma":[0.00002817478,0.0020114917,0.041446637,0.00002682118,0.00008127297,0.00051221304,0.00011168492,0.002565749,0.95224303,0.00010870745,0.0008335609,0.00003071356],"about_ca_topic_score_codex":0.0027560925,"about_ca_topic_score_gemma":0.0041399733,"teacher_disagreement_score":0.0027560925,"about_ca_system_score_codex":0.00039594262,"about_ca_system_score_gemma":0.00033263187,"threshold_uncertainty_score":0.0054801702},"labels":[],"label_agreement":null},{"id":"W2083057497","doi":"10.1038/jcbfm.2012.37","title":"Changes in Callosal Motor Fiber Integrity after Subcortical Stroke of the Pyramidal Tract","year":2012,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Jewish General Hospital; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Pyramidal tracts; Corpus callosum; Stroke (engine); Fiber tract; Disinhibition; Medicine; Corticospinal tract; Fractional anisotropy; Motor cortex; Cardiology; Neuroscience; Internal medicine; Magnetic resonance imaging; Pathology; Anatomy; Psychology; Radiology; Stimulation; Psychiatry","score_opus":0.0344381441143804,"score_gpt":0.31213845907551646,"score_spread":0.27770031496113606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083057497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996743,0.00005848485,0.000096223666,0.000004123693,5.644389e-7,0.000002250904,0.00002238536,0.0000041970443,0.00013750188],"genre_scores_gemma":[0.9997428,0.000029029285,0.00007579754,0.0000026340588,0.0000012771862,0.0000025564718,0.000053362128,0.000001475292,0.000090914466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990416,0.000014483694,0.0000117878,0.000025036894,0.00001663791,0.000027806504],"domain_scores_gemma":[0.9994912,0.00006287968,0.0002615675,0.00004501503,0.000054979737,0.0000843903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018692562,0.00021052887,0.00021197346,0.00049069367,0.00020575045,0.00026137714,0.000095579744,0.00022123891,0.0007413964],"category_scores_gemma":[0.001118249,0.000118478245,0.0001550369,0.0001888846,0.00024391238,0.00024859505,0.00016488862,0.00016441169,0.0001667674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023337868,0.00013088048,0.78796613,0.000060059276,0.00022697044,0.0026490868,0.00091479474,0.00047260875,0.17414565,0.000081808226,0.00014248517,0.030875657],"study_design_scores_gemma":[0.0000049046357,0.00021679793,0.9965771,0.0000020181326,0.0000139588465,0.0012209495,0.00004123291,0.00014376089,0.0017035167,0.000024377745,0.000047261907,0.0000040925006],"about_ca_topic_score_codex":0.0030939395,"about_ca_topic_score_gemma":0.004062894,"teacher_disagreement_score":0.0030939395,"about_ca_system_score_codex":0.00026061025,"about_ca_system_score_gemma":0.00016579848,"threshold_uncertainty_score":0.006151855},"labels":[],"label_agreement":null},{"id":"W2083427562","doi":"10.1016/j.mri.2008.01.038","title":"Spatial normalization, bulk motion correction and coregistration for functional magnetic resonance imaging of the human cervical spinal cord and brainstem","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Brainstem; Functional magnetic resonance imaging; Spinal cord; Magnetic resonance imaging; Normalization (sociology); Spatial normalization; Region of interest; Computer science; Artificial intelligence; Neuroscience; Pattern recognition (psychology); Medicine; Psychology; Radiology","score_opus":0.03731751727197344,"score_gpt":0.3007095883055636,"score_spread":0.2633920710335902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083427562","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07094025,0.0016897224,0.92145336,0.0005279421,0.00014108166,0.00015431982,0.0005245892,0.0023197178,0.002248978],"genre_scores_gemma":[0.19574024,0.00096984993,0.7976533,0.00010927108,0.000055282704,0.00021859292,0.0005624517,0.00083935674,0.0038516375],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961346,0.00009516216,0.000042398522,0.00008215297,0.00013932254,0.000027472304],"domain_scores_gemma":[0.9994136,0.00019271548,0.0000709382,0.000120797864,0.00018263605,0.000019308993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010473701,0.00055996305,0.00043322516,0.0011117127,0.0005265335,0.0011702318,0.0008153687,0.0005263842,0.0020764768],"category_scores_gemma":[0.005234959,0.0004657351,0.0004950796,0.001552649,0.0005134534,0.0010107731,0.0008644126,0.00054005143,0.00087482645],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005759496,0.00008421095,0.0024753336,0.00052377133,0.00013788676,0.00025101242,0.00040748855,0.018020319,0.13650273,0.0138565935,0.0061682896,0.8209964],"study_design_scores_gemma":[0.00016595222,0.00045070975,0.04960449,0.00013907517,0.00058800506,0.0075197034,0.00060752203,0.40162125,0.40531015,0.060813654,0.07293594,0.00024351396],"about_ca_topic_score_codex":0.007838229,"about_ca_topic_score_gemma":0.015029634,"teacher_disagreement_score":0.007838229,"about_ca_system_score_codex":0.0005570257,"about_ca_system_score_gemma":0.0026144115,"threshold_uncertainty_score":0.015585184},"labels":[],"label_agreement":null},{"id":"W2084113628","doi":"10.1227/01.neu.0000367613.09324.da","title":"In Vivo Visualization of Cranial Nerve Pathways in Humans Using Diffusion-Based Tractography","year":2010,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Queen's University; University of Toronto","funders":"","keywords":"Tractography; Anatomy; Medicine; Cranial nerves; Diffusion MRI; Magnetic resonance imaging; Radiology","score_opus":0.0596501691124415,"score_gpt":0.3452522085990344,"score_spread":0.2856020394865929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084113628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58538675,0.0097843,0.39142752,0.0013531247,0.00008840861,0.00036512318,0.0011897491,0.001040536,0.009364489],"genre_scores_gemma":[0.8022185,0.0054036197,0.18828808,0.0002627334,0.00006245478,0.00027091065,0.0004701738,0.00020015077,0.0028234802],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99980444,0.00007362693,0.000016819597,0.000049565602,0.000041454627,0.000014083339],"domain_scores_gemma":[0.9996928,0.00013722721,0.000062779225,0.00003947868,0.000045670462,0.000022030517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073507184,0.0003953373,0.00022092441,0.00074544764,0.0002423333,0.0005788405,0.00024194639,0.0006460626,0.0036380275],"category_scores_gemma":[0.0015308063,0.00032386568,0.00019028246,0.00033109993,0.0004925557,0.0007944703,0.00030985303,0.00040575516,0.0005409087],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008714397,0.00012117119,0.009902625,0.00076550205,0.00014729267,0.0023445324,0.000569092,0.006635529,0.84694225,0.0019390793,0.0023131068,0.12744845],"study_design_scores_gemma":[0.00062957493,0.0042625573,0.22930443,0.0010280014,0.0005837172,0.07745839,0.0009057013,0.13740675,0.4563446,0.017141374,0.07449125,0.000443628],"about_ca_topic_score_codex":0.0015792518,"about_ca_topic_score_gemma":0.002342876,"teacher_disagreement_score":0.0036380275,"about_ca_system_score_codex":0.000196983,"about_ca_system_score_gemma":0.0004949117,"threshold_uncertainty_score":0.012170434},"labels":[],"label_agreement":null},{"id":"W2084169411","doi":"10.1002/jmri.22577","title":"Impact of outliers on diffusion tensor and Q‐ball imaging: Clinical implications and correction strategies","year":2011,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"European Commission","keywords":"Diffusion MRI; Outlier; Medicine; Radiology; Computer science; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Artificial intelligence","score_opus":0.08333704346863446,"score_gpt":0.4001292119955707,"score_spread":0.31679216852693626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084169411","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23989245,0.003638621,0.7507145,0.0022876158,0.00024839543,0.00025312311,0.00019869492,0.0016080872,0.0011586612],"genre_scores_gemma":[0.8293896,0.0010607642,0.16811632,0.00025137278,0.00012027137,0.00010938672,0.00015535575,0.00037077893,0.00042608683],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996563,0.0016203255,0.00030521964,0.0003503254,0.0010522846,0.00010878231],"domain_scores_gemma":[0.9705848,0.019360695,0.0044088797,0.0020665736,0.0031424908,0.00043657672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009047809,0.0009095381,0.0012157874,0.0013709227,0.00067376817,0.0017280945,0.000884391,0.0013453901,0.0012681385],"category_scores_gemma":[0.06885387,0.00045515187,0.00057654444,0.0009173803,0.0015067712,0.001505325,0.0012422511,0.00095831876,0.0005370155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035509649,0.00050488446,0.1229594,0.0014198963,0.0003928465,0.0044132587,0.0013215007,0.14872426,0.0558753,0.012433301,0.0044976226,0.64390683],"study_design_scores_gemma":[0.00025806174,0.0025161358,0.06369699,0.00057064235,0.00039056045,0.012244642,0.00065493764,0.7502045,0.12767619,0.033613656,0.007836825,0.00033688106],"about_ca_topic_score_codex":0.0014918043,"about_ca_topic_score_gemma":0.0012376298,"teacher_disagreement_score":0.009047809,"about_ca_system_score_codex":0.00057133666,"about_ca_system_score_gemma":0.0009605615,"threshold_uncertainty_score":0.047849953},"labels":[],"label_agreement":null},{"id":"W2084428331","doi":"10.1016/j.apmr.2008.08.211","title":"Use of Diffusion Tensor Imaging to Examine Subacute White Matter Injury Progression in Moderate to Severe Traumatic Brain Injury","year":2008,"lang":"en","type":"article","venue":"Archives of Physical Medicine and Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Glasgow Coma Scale; White matter; Traumatic brain injury; Medicine; Diffuse axonal injury; Anesthesia; Cardiology; Psychology; Magnetic resonance imaging; Radiology; Pathology; Psychiatry","score_opus":0.042605697692409884,"score_gpt":0.36168818275181747,"score_spread":0.31908248505940756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084428331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99830437,0.00030871076,0.00052781386,0.000047681664,0.000008650563,0.000045900775,0.000047971018,0.000007346603,0.00070160336],"genre_scores_gemma":[0.9982222,0.00033152718,0.0011860523,0.000019772571,0.000009309391,0.000020271757,0.000041350595,0.000002683742,0.00016680651],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972373,0.00010250224,0.000056777422,0.00003268632,0.000057897643,0.000026427482],"domain_scores_gemma":[0.99877197,0.00036930514,0.00028424858,0.00006300388,0.00035919162,0.00015223511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016649481,0.00042856167,0.0002893368,0.0019473083,0.00047352334,0.00062101125,0.00033782658,0.00045578208,0.0002776106],"category_scores_gemma":[0.004236348,0.00022692216,0.00029476258,0.0005774593,0.00047628634,0.0010028601,0.00034664746,0.0005241055,0.000105391075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023111056,0.0005653897,0.9422314,0.00011877207,0.00017472089,0.0008702816,0.0006015917,0.00056906464,0.018813327,0.000083641295,0.0001766222,0.033484086],"study_design_scores_gemma":[0.00008853853,0.002302633,0.98228925,0.000037497437,0.00019166004,0.0019391928,0.0010103609,0.003990432,0.007495487,0.0001954417,0.0004232691,0.000036231773],"about_ca_topic_score_codex":0.0067381603,"about_ca_topic_score_gemma":0.013375986,"teacher_disagreement_score":0.0067381603,"about_ca_system_score_codex":0.00030253062,"about_ca_system_score_gemma":0.0006535925,"threshold_uncertainty_score":0.013397872},"labels":[],"label_agreement":null},{"id":"W2084489466","doi":"10.1016/j.jelectrocard.2008.12.003","title":"Image-based models of cardiac structure with applications in arrhythmia and defibrillation studies","year":2009,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Heart, Lung, and Blood Institute; Biotechnology and Biological Sciences Research Council","keywords":"Defibrillation; Computer science; Diffusion MRI; Set (abstract data type); Computational model; Finite element method; Algorithm; Artificial intelligence; Magnetic resonance imaging; Medicine; Cardiology; Structural engineering; Engineering","score_opus":0.030540775169632745,"score_gpt":0.335656917742491,"score_spread":0.30511614257285824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084489466","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035128,0.00089139264,0.960757,0.0006046481,0.000086425774,0.000049556653,0.00031127184,0.00040629032,0.0017653496],"genre_scores_gemma":[0.7857597,0.0025879112,0.20419872,0.00028518136,0.00022909897,0.0002157467,0.0006709897,0.0002694024,0.0057832063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999269,0.000022944705,0.000005591666,0.000016060496,0.000022704788,0.0000057611155],"domain_scores_gemma":[0.99950635,0.00029901645,0.00005866074,0.000031282085,0.00007840232,0.000026287998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035708738,0.0005212193,0.00057672086,0.0005818562,0.00020437474,0.0009808196,0.00097200205,0.0017180387,0.0014319625],"category_scores_gemma":[0.0022030964,0.00049568614,0.0007548849,0.0006600111,0.0004352238,0.0007202022,0.00041207683,0.00081707275,0.00042759295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026921958,0.000022017237,0.00032492282,0.000032528107,0.000023719944,0.00006456179,0.000021991846,0.97960246,0.0018700049,0.002813754,0.00042464194,0.014772522],"study_design_scores_gemma":[0.0000037542602,0.00000599698,0.000095679556,0.0000026103744,0.0000038803623,0.00002207901,0.000001939651,0.9983394,0.0001961875,0.0011558932,0.00016945985,0.0000031169504],"about_ca_topic_score_codex":0.006920984,"about_ca_topic_score_gemma":0.005117027,"teacher_disagreement_score":0.006920984,"about_ca_system_score_codex":0.00041051832,"about_ca_system_score_gemma":0.00042346856,"threshold_uncertainty_score":0.013761401},"labels":[],"label_agreement":null},{"id":"W2084775462","doi":"10.1109/tpami.2012.184","title":"3D Stochastic Completion Fields for Mapping Connectivity in Diffusion MRI","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Spherical harmonics; Computer science; Artificial intelligence; Probability density function; Algorithm; Invariant (physics); Orientation (vector space); Imaging phantom; Computer vision; Mathematics; Geometry; Mathematical analysis; Physics","score_opus":0.06916264017012254,"score_gpt":0.34744422112829176,"score_spread":0.27828158095816924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084775462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003911866,0.00013544645,0.99533844,0.00008464664,0.000009572598,0.000020230531,0.00006492986,0.00013141622,0.0003034969],"genre_scores_gemma":[0.25972292,0.0009863656,0.735214,0.00012317002,0.00012936858,0.00036969705,0.00070098817,0.00030932383,0.002444223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995566,0.00017735962,0.000019524496,0.000057088517,0.0001620331,0.000027312048],"domain_scores_gemma":[0.9985494,0.0008299314,0.00017520406,0.00012124866,0.00022193114,0.00010233859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001854576,0.00069221837,0.0006729474,0.0016769576,0.00044817335,0.0008298525,0.0011880752,0.0010955991,0.0015175916],"category_scores_gemma":[0.0053480533,0.0005651016,0.0008292845,0.0012471315,0.0013923667,0.0012722925,0.0011684096,0.0015257841,0.0004542674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043764387,0.000028759858,0.00043083398,0.000067900066,0.000016880978,0.00006640495,0.00007411462,0.81342983,0.0022581138,0.14967722,0.0015966397,0.032309607],"study_design_scores_gemma":[0.0000032168853,0.000007861517,0.000061212755,0.000003918021,0.0000011394972,0.0000141542005,0.0000027482172,0.97225285,0.0002541739,0.026927063,0.000463469,0.000008244365],"about_ca_topic_score_codex":0.0043686996,"about_ca_topic_score_gemma":0.0032937324,"teacher_disagreement_score":0.0043686996,"about_ca_system_score_codex":0.0011084831,"about_ca_system_score_gemma":0.0010639055,"threshold_uncertainty_score":0.009808004},"labels":[],"label_agreement":null},{"id":"W2085683875","doi":"10.4236/jbise.2014.78060","title":"Assessment of Mechanical Properties of Muscles from Multi-Parametric Magnetic Resonance Imaging","year":2014,"lang":"en","type":"article","venue":"Journal of Biomedical Science and Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital Notre-Dame; Philips (Canada); Polytechnique Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Rigor mortis; Magnetic resonance imaging; Principal component analysis; Medicine; Biomedical engineering; Materials science; Anatomy; Radiology; Computer science; Artificial intelligence","score_opus":0.035716416079520565,"score_gpt":0.313309431973785,"score_spread":0.27759301589426444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085683875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.930145,0.0020275516,0.06626184,0.00006375921,0.000015461397,0.00008204288,0.0002003136,0.000057167606,0.0011468239],"genre_scores_gemma":[0.97347826,0.0010446141,0.024468115,0.00003024874,0.000019941763,0.00010750744,0.00014748746,0.000012449566,0.00069139496],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99962974,0.00010303142,0.00003378207,0.0000787153,0.000121158715,0.000033618355],"domain_scores_gemma":[0.99888045,0.00041685038,0.00034563383,0.00010176027,0.00018719505,0.00006803572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010831233,0.0004885363,0.000373388,0.0011268449,0.00015667401,0.0003436615,0.0003611496,0.0005433671,0.00080782676],"category_scores_gemma":[0.0019232514,0.00023333065,0.00023719344,0.00043360566,0.00045746242,0.00065602886,0.00042273107,0.0004455946,0.0002468014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018118667,0.000042932545,0.011128855,0.0001890209,0.000040559393,0.00011958451,0.00011124095,0.00039381813,0.97155267,0.00011270507,0.000020878144,0.01610661],"study_design_scores_gemma":[0.000019576195,0.0031367783,0.4650301,0.00006778226,0.00026002672,0.002346676,0.00036045525,0.015724037,0.510561,0.00097436353,0.0014355747,0.000083728024],"about_ca_topic_score_codex":0.00019348932,"about_ca_topic_score_gemma":0.000482144,"teacher_disagreement_score":0.0011268449,"about_ca_system_score_codex":0.000092565424,"about_ca_system_score_gemma":0.00013052039,"threshold_uncertainty_score":0.005728185},"labels":[],"label_agreement":null},{"id":"W2085715764","doi":"10.1073/pnas.1422824112","title":"Hydration water mobility is enhanced around tau amyloid fibers","year":2015,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche; European Molecular Biology Laboratory; Centre National de la Recherche Scientifique; European Commission; Engineering and Physical Sciences Research Council; French Infrastructure for Integrated Structural Biology","keywords":"Fiber; Molecular dynamics; Chemistry; Neutron scattering; Diffusion; Chemical physics; Molecule; Core (optical fiber); Biophysics; Crystallography; Scattering; Materials science; Computational chemistry; Composite material; Thermodynamics; Organic chemistry; Physics; Optics","score_opus":0.12171947923610736,"score_gpt":0.38347568506141116,"score_spread":0.2617562058253038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085715764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998108,0.00009289566,0.00149477,0.000021782795,0.0000037378409,0.0000031829252,0.000019051691,0.000014101864,0.0002424862],"genre_scores_gemma":[0.9990827,0.00009746198,0.0006636848,0.0000067068027,0.000001315676,0.0000028360796,0.000036697766,0.0000058906335,0.000102645296],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99996424,0.0000037113716,0.0000015035665,0.0000109441735,0.000009248168,0.0000102019185],"domain_scores_gemma":[0.99993014,0.000013970382,0.00002004469,0.000004938495,0.000010004998,0.000020877398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072633746,0.00018392553,0.00018195827,0.00015261052,0.00021931027,0.0002772186,0.00018376285,0.00018740962,0.00045039458],"category_scores_gemma":[0.0002386111,0.00017828202,0.00019850495,0.00009164323,0.00040720028,0.0004228016,0.00023791344,0.00023454202,0.000059286795],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037642347,0.000060842987,0.008841525,0.000073212046,0.00007024443,0.00034766734,0.00029498097,0.026607512,0.95815194,0.0010013678,0.00010263559,0.004071485],"study_design_scores_gemma":[0.00012936638,0.0006020477,0.06691593,0.000031485444,0.00010284844,0.0004731389,0.00034840693,0.40874898,0.5180732,0.0027847143,0.0016986307,0.00009119517],"about_ca_topic_score_codex":0.0020828617,"about_ca_topic_score_gemma":0.0009832731,"teacher_disagreement_score":0.0020828617,"about_ca_system_score_codex":0.00023201756,"about_ca_system_score_gemma":0.00022261005,"threshold_uncertainty_score":0.0041415095},"labels":[],"label_agreement":null},{"id":"W2086269292","doi":"10.1109/isbi.2013.6556459","title":"K-confidence: Assessing uncertainty in tractography using K optimal paths","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Johns Hopkins University","keywords":"Tractography; Computer science; Confidence interval; Artificial intelligence; Mathematics; Diffusion MRI; Statistics; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.0967022986631205,"score_gpt":0.3991294447365487,"score_spread":0.30242714607342824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086269292","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06958893,0.00078038184,0.9272437,0.00028495572,0.00003533807,0.00009033631,0.00033710452,0.0009274519,0.00071169354],"genre_scores_gemma":[0.6644507,0.00047699033,0.33283228,0.000113731505,0.00010034617,0.00014602594,0.00081486115,0.0005698921,0.0004951422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9908704,0.0029815,0.0012246897,0.0017143503,0.0028525447,0.00035649494],"domain_scores_gemma":[0.8627743,0.10830773,0.012020437,0.008746242,0.00683166,0.0013195724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015147017,0.0016174227,0.0020645582,0.005714462,0.0013561809,0.004046922,0.0029611378,0.0042892243,0.0018629052],"category_scores_gemma":[0.13814296,0.0011005144,0.0015027062,0.003767899,0.0032818567,0.0072378945,0.004209973,0.002592572,0.00051393005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014512097,0.00015302785,0.058239352,0.0008353695,0.00097025605,0.0006809464,0.0010276445,0.69964725,0.0063610594,0.020678973,0.002176557,0.20777847],"study_design_scores_gemma":[0.000058100653,0.00021349944,0.010274714,0.00014178225,0.00010197584,0.0009209575,0.00018811617,0.9300074,0.007425863,0.049043044,0.0014579941,0.00016656319],"about_ca_topic_score_codex":0.0040578246,"about_ca_topic_score_gemma":0.0038591763,"teacher_disagreement_score":0.015147017,"about_ca_system_score_codex":0.001242208,"about_ca_system_score_gemma":0.0017701767,"threshold_uncertainty_score":0.08010602},"labels":[],"label_agreement":null},{"id":"W2086568497","doi":"10.1016/j.neuroimage.2006.01.042","title":"Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":559,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Cerebral cortex; Cortex (anatomy); Correlation; Neuroscience; Tractography; Anterior cingulate cortex; Population; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Mathematics; Cognition; Geometry","score_opus":0.06033597840904665,"score_gpt":0.3592093956409723,"score_spread":0.2988734172319257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086568497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86480564,0.0033834954,0.12283401,0.00024343959,0.0001112428,0.00012428353,0.0017410134,0.0011410922,0.005615779],"genre_scores_gemma":[0.96396726,0.0011606601,0.032794055,0.00005922393,0.000115038514,0.00008980432,0.0004698581,0.00032028614,0.0010238556],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99962246,0.00009421422,0.000034130397,0.000093293565,0.00011343592,0.00004246847],"domain_scores_gemma":[0.9977325,0.0008357058,0.0007133121,0.00023246695,0.000396231,0.00008980263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001467857,0.0007137416,0.00035026338,0.0034564494,0.00039366525,0.0012012372,0.0004102243,0.0004987619,0.0017781926],"category_scores_gemma":[0.0072890013,0.00056183315,0.0003928199,0.002261666,0.00038423747,0.0013306324,0.0004795049,0.00045604803,0.00038795275],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018650447,0.00009422548,0.124342956,0.0010891685,0.0019853117,0.001429956,0.0016562458,0.013605178,0.52715164,0.0052508786,0.004459479,0.31706992],"study_design_scores_gemma":[0.00006465051,0.00032416912,0.8618133,0.00011897808,0.00090294203,0.0050146445,0.00046223,0.02899635,0.086060405,0.011958827,0.004132041,0.00015143347],"about_ca_topic_score_codex":0.004922513,"about_ca_topic_score_gemma":0.0072937957,"teacher_disagreement_score":0.004922513,"about_ca_system_score_codex":0.00027215615,"about_ca_system_score_gemma":0.00064285763,"threshold_uncertainty_score":0.009787738},"labels":[],"label_agreement":null},{"id":"W2087093896","doi":"10.1007/s00723-008-0095-7","title":"Quantitative Assessment of Injury in Rat Spinal Cords In Vivo by MRI of Water Diffusion Tensor","year":2008,"lang":"en","type":"article","venue":"Applied Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; White matter; Spinal cord; In vivo; Spinal cord injury; Pathology; Magnetic resonance imaging; Medicine; Anatomy; Radiology; Biology","score_opus":0.02979164940260054,"score_gpt":0.3440886748256232,"score_spread":0.3142970254230227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087093896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9550455,0.0034670446,0.038175795,0.0001666145,0.00007302237,0.00011916193,0.0005181431,0.00033801128,0.0020966742],"genre_scores_gemma":[0.96593964,0.0031809695,0.023928221,0.000064252104,0.00003305252,0.0001472907,0.0005358753,0.00011130328,0.0060593435],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996922,0.000042150605,0.000023750246,0.00006920993,0.00008166254,0.000091133916],"domain_scores_gemma":[0.99936,0.000081716265,0.00019219896,0.00008342132,0.00017561622,0.000107140426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076311745,0.0010152177,0.00042465056,0.001132439,0.00047732148,0.0005443305,0.00060864387,0.0007663841,0.0013720616],"category_scores_gemma":[0.0004995312,0.00049190305,0.00042173747,0.0005524924,0.0008963383,0.001590414,0.0005043814,0.0010966188,0.00038575585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019898068,0.00005414778,0.00016542885,0.00007828403,0.000011155106,0.000027339305,0.000057749174,0.00018032485,0.99754435,0.00016401816,0.000021766818,0.0014964683],"study_design_scores_gemma":[0.000017560325,0.0006090719,0.002979006,0.00001092252,0.000046069898,0.00011601604,0.000102477374,0.00195942,0.9936562,0.000109305074,0.0003817082,0.00001223066],"about_ca_topic_score_codex":0.0044756723,"about_ca_topic_score_gemma":0.004905222,"teacher_disagreement_score":0.0044756723,"about_ca_system_score_codex":0.00040362412,"about_ca_system_score_gemma":0.0006653532,"threshold_uncertainty_score":0.0088992715},"labels":[],"label_agreement":null},{"id":"W2088897607","doi":"10.1560/e0wu-7ffh-31m6-vlyt","title":"Diffusion MR in Biological Systems: Tissue Compartments and Exchange","year":2003,"lang":"en","type":"article","venue":"Israel Journal of Chemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Chemistry; Tortuosity; Diffusion; Effective diffusion coefficient; Extracellular; Intracellular; Permeability (electromagnetism); Anomalous diffusion; Biophysics; Membrane; Thermodynamics; Porosity; Innovation diffusion; Physics; Biochemistry; Magnetic resonance imaging","score_opus":0.0774085790768602,"score_gpt":0.3612994564860374,"score_spread":0.2838908774091772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088897607","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.065370254,0.077629,0.83730125,0.0032460408,0.0003409576,0.000053233063,0.000111516754,0.0005934832,0.015354298],"genre_scores_gemma":[0.86434215,0.027896618,0.08935749,0.00052372,0.00050128094,0.00013450152,0.000082886116,0.00015892679,0.017002407],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99975616,0.000109073226,0.000011268856,0.000042123,0.00005325141,0.000027999342],"domain_scores_gemma":[0.9996928,0.00017643343,0.000052473017,0.000033161734,0.000030515692,0.000014640346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091225817,0.0006088292,0.00065383204,0.00047916864,0.00031244062,0.000989714,0.0007427726,0.0012802948,0.0013057814],"category_scores_gemma":[0.0011129758,0.0002551453,0.00033427795,0.00048998225,0.0013511794,0.0030824433,0.0008638115,0.0005835746,0.00044699849],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014267744,0.000025520858,0.00042851054,0.0010076051,0.000061532344,0.0009612174,0.0004207177,0.07238686,0.11237503,0.76180035,0.0028626034,0.047527306],"study_design_scores_gemma":[0.000042692216,0.0002481312,0.0013669792,0.0001384434,0.000086700886,0.0032231065,0.00016870759,0.46275294,0.023302738,0.47030202,0.038290787,0.00007666965],"about_ca_topic_score_codex":0.0006560332,"about_ca_topic_score_gemma":0.0003546628,"teacher_disagreement_score":0.0013057814,"about_ca_system_score_codex":0.0006277861,"about_ca_system_score_gemma":0.00026927984,"threshold_uncertainty_score":0.0048245788},"labels":[],"label_agreement":null},{"id":"W2089346380","doi":"10.1016/j.neuroimage.2010.08.076","title":"Myelin water and T2 relaxation measurements in the healthy cervical spinal cord at 3.0T: Repeatability and changes with age","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC; University of British Columbia; Cervical Spine Research Society","keywords":"White matter; Grey matter; Myelin; Spinal cord; Cohort; Confidence interval; Repeatability; Medicine; Nuclear medicine; Population; T2 relaxation; Magnetic resonance imaging; Psychology; Internal medicine; Central nervous system; Chemistry; Neuroscience; Radiology","score_opus":0.11607692546983402,"score_gpt":0.368692942884262,"score_spread":0.252616017414428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089346380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987857,0.00035995524,0.00046131935,0.000022135315,0.0000062952818,0.0000041671938,0.00012468982,0.000019101899,0.0002165653],"genre_scores_gemma":[0.99903715,0.00013826737,0.00046778505,0.000014103727,0.000007670558,0.000004481281,0.00010679819,0.000012721962,0.00021099168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997527,0.000042625237,0.0000243406,0.00009014886,0.000056752164,0.00003345065],"domain_scores_gemma":[0.9989526,0.00031750972,0.00025993024,0.00011498322,0.00029674039,0.00005814592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006737518,0.00023058805,0.0002313928,0.0006140785,0.00026531983,0.0002875759,0.00029050658,0.0005728124,0.00044902452],"category_scores_gemma":[0.0034399994,0.00021488467,0.00014583796,0.00041336022,0.0003305064,0.00051979517,0.00023701235,0.0002806377,0.0001468292],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005314613,0.00016368607,0.4644753,0.0002687042,0.0004013881,0.001288407,0.004217379,0.0010287713,0.45628518,0.00025828026,0.00070543087,0.06559289],"study_design_scores_gemma":[0.000010802849,0.00034550938,0.9739057,0.000008640374,0.00009931804,0.0012661503,0.00027240237,0.0007862479,0.022833744,0.00012523825,0.00032687568,0.000019348254],"about_ca_topic_score_codex":0.0073700314,"about_ca_topic_score_gemma":0.011211533,"teacher_disagreement_score":0.0073700314,"about_ca_system_score_codex":0.00029661696,"about_ca_system_score_gemma":0.00028181984,"threshold_uncertainty_score":0.014654279},"labels":[],"label_agreement":null},{"id":"W2090877723","doi":"10.3389/fpsyt.2013.00175","title":"A Comparison of Neuroimaging Findings in Childhood Onset Schizophrenia and Autism Spectrum Disorder: A Review of the Literature","year":2013,"lang":"en","type":"review","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Ontario Brain Institute","keywords":"Neuroimaging; Autism spectrum disorder; White matter; Diffusion MRI; Psychology; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; Neuroscience; Autism; Brain size; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.024290084968578367,"score_gpt":0.3572098224094052,"score_spread":0.3329197374408268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090877723","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00092623394,0.9985524,0.000061735416,0.00016618548,0.0000583505,0.0000039963497,0.00003423102,0.00000402372,0.00019273588],"genre_scores_gemma":[0.010480325,0.9886015,0.0003152871,0.00020831414,0.0002599317,0.000012780031,0.00006999678,0.0000024663902,0.000049450216],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988489,0.00018549895,0.00046729745,0.00022717642,0.0002165536,0.000054557608],"domain_scores_gemma":[0.9961433,0.0023683456,0.00092416414,0.00005456696,0.0004048868,0.00010473075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017025087,0.0010196937,0.0018117591,0.011768666,0.00031650087,0.0014208381,0.0010740295,0.0013166299,0.0011210819],"category_scores_gemma":[0.00499398,0.00042556803,0.000980365,0.0069697564,0.0010354443,0.0016787059,0.0008323971,0.00072207977,0.0002585282],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026572053,0.00007530917,0.025930662,0.09946084,0.0011877838,0.0045025246,0.0007005659,0.00034190202,0.0015281686,0.00095724466,0.011923588,0.85312563],"study_design_scores_gemma":[0.000104018836,0.0004902486,0.3144042,0.24844873,0.008932741,0.14672345,0.004877525,0.00064978795,0.0017809336,0.0033595806,0.2698939,0.00033495526],"about_ca_topic_score_codex":0.0030123119,"about_ca_topic_score_gemma":0.0044081183,"teacher_disagreement_score":0.011768666,"about_ca_system_score_codex":0.0010626009,"about_ca_system_score_gemma":0.0015273917,"threshold_uncertainty_score":0.009003818},"labels":[],"label_agreement":null},{"id":"W2091142169","doi":"10.1523/jneurosci.0553-08.2008","title":"Thalamic Shape: A Possible Endophenotype","year":2008,"lang":"en","type":"letter","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"","keywords":"Endophenotype; Neuroscience; Schizophrenia (object-oriented programming); Thalamus; Mechanism (biology); Psychology; Sensory system; Cortex (anatomy); Cognition; Psychiatry","score_opus":0.10145203816079809,"score_gpt":0.3574402962795016,"score_spread":0.2559882581187035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091142169","genre_codex":"empirical","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6539859,0.005986586,0.007694219,0.28246143,0.0030307656,0.00022573226,0.0014234361,0.00034796612,0.044844013],"genre_scores_gemma":[0.9536591,0.0024231176,0.0026614976,0.031344183,0.0035977243,0.000081492544,0.0002193266,0.0000579552,0.0059555876],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99967027,0.00009641627,0.000022745247,0.00008204152,0.000079750906,0.000048801216],"domain_scores_gemma":[0.99898463,0.00056392286,0.00018674898,0.00008422824,0.0001052296,0.00007519294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003105048,0.0007319549,0.00080460747,0.00054151483,0.0004665122,0.0005140648,0.00091295154,0.0043103,0.0052185366],"category_scores_gemma":[0.0041380925,0.00016267777,0.0003120682,0.00071769796,0.0011766764,0.00080284406,0.00041140823,0.0017239429,0.000758038],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012644597,0.000112149275,0.07844488,0.000258729,0.00010736207,0.74351877,0.0009962291,0.0006324463,0.025625635,0.022821154,0.04212057,0.08409756],"study_design_scores_gemma":[0.00020995545,0.00032133632,0.06956291,0.00012501971,0.00008702614,0.88917285,0.0007746602,0.002595627,0.0019444779,0.017475337,0.017652296,0.000078437864],"about_ca_topic_score_codex":0.0009690172,"about_ca_topic_score_gemma":0.0014794194,"teacher_disagreement_score":0.0052185366,"about_ca_system_score_codex":0.0005671335,"about_ca_system_score_gemma":0.0003320128,"threshold_uncertainty_score":0.017457724},"labels":[],"label_agreement":null},{"id":"W2091333100","doi":"10.1007/bf02668216","title":"Evolution of β-amyloid induced neuropathology: magnetic resonance imaging and anatomical comparisons in the rodent hippocampus","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saskatoon City Hospital; University of Saskatchewan; Royal University Hospital","funders":"Medical Research Council Canada","keywords":"Hippocampus; Hippocampal formation; Pathology; Magnetic resonance imaging; Neuropathology; Edema; Medicine; Necrosis; Amyloid (mycology); Chemistry; Internal medicine; Radiology; Disease","score_opus":0.038701672800783744,"score_gpt":0.322324467651281,"score_spread":0.28362279485049724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091333100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99528056,0.0019074916,0.0014527638,0.000082173654,0.000008390518,0.000009240553,0.00013306236,0.000043550215,0.0010826141],"genre_scores_gemma":[0.9933467,0.0022480248,0.0025374193,0.00010584066,0.000008634061,0.00001537395,0.00024434584,0.000037219314,0.001456515],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999045,0.000010677359,0.000008462458,0.0000384192,0.000021901853,0.000015952139],"domain_scores_gemma":[0.99959177,0.000033176984,0.00015500725,0.000047150537,0.0001212186,0.00005170701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024727767,0.00019379659,0.00019493094,0.0010615527,0.00021741337,0.00044049058,0.00044501727,0.0004337063,0.0006200892],"category_scores_gemma":[0.0004306792,0.00030695807,0.0002075106,0.00032089217,0.00035426882,0.0005925007,0.0002485721,0.00056001986,0.00015586549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041564216,0.000060365142,0.012292536,0.00007223867,0.00007200062,0.00034643372,0.00009820505,0.00014316685,0.977132,0.00031369258,0.000086586915,0.008967196],"study_design_scores_gemma":[0.00003706503,0.00085566175,0.7731651,0.00004260418,0.00019996698,0.004920947,0.0003946832,0.00093089236,0.21534596,0.0012955926,0.002775532,0.000035905345],"about_ca_topic_score_codex":0.00126913,"about_ca_topic_score_gemma":0.0017907984,"teacher_disagreement_score":0.00126913,"about_ca_system_score_codex":0.00031756327,"about_ca_system_score_gemma":0.00017096911,"threshold_uncertainty_score":0.0025234222},"labels":[],"label_agreement":null},{"id":"W2091386625","doi":"10.1016/j.mri.2010.07.004","title":"Diffusion tensor fiber tractography of the olfactory tract","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Diffusion MRI; Tractography; Fiber tract; Olfactory system; Anatomy; Magnetic resonance imaging; Neuroscience; Medicine; Biology; Radiology","score_opus":0.027235621884554757,"score_gpt":0.2935040094184016,"score_spread":0.26626838753384685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091386625","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86965954,0.006638444,0.11304617,0.0009128091,0.00006238537,0.000077630364,0.0011986097,0.00025077126,0.008153659],"genre_scores_gemma":[0.95117563,0.0037023218,0.041496497,0.00006696268,0.000057610665,0.000019712768,0.00016531575,0.00005869474,0.0032572541],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993956,0.000012988661,0.0000046454047,0.000014885639,0.000019059386,0.000008784361],"domain_scores_gemma":[0.9997893,0.00006482786,0.00004000196,0.000022601127,0.00005388301,0.000029319497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003373586,0.00021996094,0.00016293219,0.00070818205,0.00028372562,0.0005036972,0.00016141016,0.0003303552,0.0010061375],"category_scores_gemma":[0.00097437983,0.00012875997,0.00014646312,0.0005203139,0.00034185106,0.00072406424,0.00017991131,0.00032488527,0.00015795292],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000991364,0.00008471708,0.08084279,0.0007322418,0.00022006614,0.0034863215,0.0008126913,0.011148948,0.6330693,0.015164021,0.0025107916,0.25093675],"study_design_scores_gemma":[0.00016923585,0.0006901721,0.46882704,0.00041118017,0.00041696124,0.028652363,0.0010653161,0.14902467,0.25321296,0.06282572,0.03445942,0.00024499698],"about_ca_topic_score_codex":0.015270712,"about_ca_topic_score_gemma":0.014348483,"teacher_disagreement_score":0.015270712,"about_ca_system_score_codex":0.00035221508,"about_ca_system_score_gemma":0.00086097413,"threshold_uncertainty_score":0.030363679},"labels":[],"label_agreement":null},{"id":"W2091741867","doi":"10.1088/0031-9155/52/6/n01","title":"Preservation of diffusion tensor properties during spatial normalization by use of tensor imaging and fibre tracking on a normal brain database","year":2007,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":114,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Spatial normalization; White matter; Normalization (sociology); Tractography; Scanner; Computer science; Artificial intelligence; Fractional anisotropy; Pattern recognition (psychology); Magnetic resonance imaging; Voxel; Nuclear magnetic resonance; Computer vision; Physics; Medicine; Radiology","score_opus":0.27148354941588937,"score_gpt":0.4017654255244735,"score_spread":0.1302818761085841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091741867","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17230418,0.0003247912,0.8218982,0.00011368932,0.00005281379,0.00024651806,0.00071453216,0.003364944,0.0009802805],"genre_scores_gemma":[0.2789954,0.0004748488,0.7160291,0.000026337766,0.00002111056,0.00035992937,0.0019120383,0.00089834863,0.0012829688],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982748,0.00039367023,0.00021090427,0.0006291912,0.00040957992,0.000081897946],"domain_scores_gemma":[0.9964768,0.0008386662,0.00042340826,0.0013499085,0.00083951646,0.00007175107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004850542,0.0009106593,0.001043881,0.0014379834,0.0007427219,0.0015254754,0.0009172168,0.00047795044,0.001460075],"category_scores_gemma":[0.012468609,0.00039622377,0.00070599135,0.001541617,0.00083228166,0.0016695141,0.0009499359,0.0006325467,0.0011144372],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008051391,0.00019658619,0.0054703993,0.00033218417,0.0001722404,0.00033432274,0.0006950025,0.027770093,0.22008014,0.006109377,0.0019166728,0.7361179],"study_design_scores_gemma":[0.00013867849,0.00073727936,0.06331596,0.00010215519,0.00039447352,0.004807634,0.00047143642,0.49354014,0.39724544,0.017764365,0.021269478,0.00021300453],"about_ca_topic_score_codex":0.0044867997,"about_ca_topic_score_gemma":0.005660249,"teacher_disagreement_score":0.004850542,"about_ca_system_score_codex":0.0005654085,"about_ca_system_score_gemma":0.0014156597,"threshold_uncertainty_score":0.025652409},"labels":[],"label_agreement":null},{"id":"W2092497652","doi":"10.1016/j.neuroimage.2009.01.002","title":"Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer's disease participants","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":596,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health","keywords":"White matter; Atlas (anatomy); Diffusion MRI; Spatial normalization; Fractional anisotropy; Image warping; Artificial intelligence; Segmentation; Pattern recognition (psychology); Brain atlas; Cartography; Nuclear medicine; Computer science; Medicine; Magnetic resonance imaging; Anatomy; Radiology; Voxel; Geography","score_opus":0.05788558248088984,"score_gpt":0.3439735161238967,"score_spread":0.2860879336430069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092497652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9043201,0.00031181236,0.0925116,0.00011100106,0.000030447145,0.00021736293,0.0008207452,0.00083475315,0.00084215036],"genre_scores_gemma":[0.9178633,0.00022563232,0.08003699,0.00003246846,0.000017687846,0.00010264474,0.0005088712,0.00017037876,0.0010420365],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998616,0.00006072985,0.000010163951,0.000030693584,0.00002620679,0.000010570369],"domain_scores_gemma":[0.9995684,0.00019640541,0.000025890837,0.00008155351,0.000088745706,0.000039021103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013388233,0.0003964569,0.00052274275,0.00090332027,0.00052843505,0.00056994025,0.0005258705,0.00043699998,0.001694305],"category_scores_gemma":[0.001771398,0.00019649453,0.0004538798,0.0006446209,0.00023828575,0.00029163685,0.00056955166,0.00027380153,0.00025833526],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008514202,0.001217876,0.057054397,0.00075259444,0.0012690359,0.005031558,0.0041792006,0.04434548,0.1930065,0.003677905,0.006217517,0.6747337],"study_design_scores_gemma":[0.0011709414,0.002844731,0.3640978,0.000057077687,0.001154841,0.012994077,0.002687759,0.49379814,0.092066504,0.018474491,0.01036425,0.0002894285],"about_ca_topic_score_codex":0.0053754714,"about_ca_topic_score_gemma":0.0077562737,"teacher_disagreement_score":0.0053754714,"about_ca_system_score_codex":0.00023647356,"about_ca_system_score_gemma":0.00048790243,"threshold_uncertainty_score":0.0106883645},"labels":[],"label_agreement":null},{"id":"W2092640753","doi":"10.1016/j.neuroimage.2012.03.062","title":"Brain white matter organisation in adolescence is related to childhood cerebral responses to facial expressions and harm avoidance","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec; Université Laval","funders":"","keywords":"Uncinate fasciculus; Inferior longitudinal fasciculus; Psychology; White matter; Fractional anisotropy; Superior longitudinal fasciculus; Tractography; Cingulum (brain); Fasciculus; N400; Neuroscience; Audiology; Event-related potential; Medicine; Electroencephalography; Magnetic resonance imaging","score_opus":0.031860111538509074,"score_gpt":0.3332742195678561,"score_spread":0.301414108029347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092640753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99928194,0.00011078924,0.000056311972,0.000019091516,0.0000018003253,0.0000027097908,0.000037933303,0.000002990143,0.0004864955],"genre_scores_gemma":[0.9990854,0.00016296194,0.00008371171,0.0000105739955,0.000002872333,0.0000075385533,0.000108604094,0.0000054906677,0.0005328314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999232,0.000011911825,0.000003558041,0.000017269747,0.000017434917,0.000026563886],"domain_scores_gemma":[0.9995372,0.000101901205,0.00022067472,0.00002175295,0.000049216087,0.00006926418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019862934,0.00017108521,0.00021365866,0.00046133774,0.0003051301,0.0004945101,0.0001248819,0.0002845337,0.001737156],"category_scores_gemma":[0.00080606056,0.00027190847,0.00015230624,0.00027062235,0.00039564213,0.00026967758,0.0003228087,0.0004512287,0.00017677496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022570835,0.00054986414,0.83630466,0.00009230564,0.000109026834,0.0013049544,0.0021515244,0.0002561758,0.1393535,0.00083814294,0.00040383174,0.016378937],"study_design_scores_gemma":[0.0000029655253,0.000050208644,0.9979386,0.000004414896,0.000008379727,0.00018154814,0.00017365359,0.000051787323,0.0013828477,0.00005668485,0.00014701977,0.0000018747156],"about_ca_topic_score_codex":0.0031840345,"about_ca_topic_score_gemma":0.0087454505,"teacher_disagreement_score":0.0031840345,"about_ca_system_score_codex":0.00027607233,"about_ca_system_score_gemma":0.00024111805,"threshold_uncertainty_score":0.006330967},"labels":[],"label_agreement":null},{"id":"W2092674859","doi":"10.3389/fnhum.2014.00507","title":"Investigating the contribution of ventral-lexical and dorsal-sublexical pathways during reading in bilinguals","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Arcuate fasciculus; Superior longitudinal fasciculus; Fasciculus; Psychology; Diffusion MRI; White matter; Inferior longitudinal fasciculus; Uncinate fasciculus; Lateralization of brain function; Reading (process); Dorsum; Neuroscience; Lexical decision task; Tractography; Cognitive psychology; Fractional anisotropy; Audiology; Anatomy; Cognition; Biology; Linguistics; Medicine; Magnetic resonance imaging","score_opus":0.046715731891005974,"score_gpt":0.33029396921269505,"score_spread":0.2835782373216891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092674859","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99944514,0.00008616189,0.00012768718,0.000010635266,9.4572937e-7,0.0000026678438,0.000022272532,0.000003867069,0.00030055825],"genre_scores_gemma":[0.99933296,0.00007751995,0.00024922553,0.000006515697,0.0000021792903,0.0000032447033,0.00003622223,0.0000030588824,0.00028917202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999923,0.000012762931,0.0000068810155,0.00002583933,0.000011885769,0.00001953616],"domain_scores_gemma":[0.99966955,0.000070760994,0.00013945626,0.000018278066,0.000046199668,0.00005578295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021603487,0.00024292646,0.0001974599,0.00054714177,0.00022688387,0.0003377913,0.00007461284,0.00021328761,0.0013279262],"category_scores_gemma":[0.00084914773,0.00010460002,0.00008687494,0.0001704882,0.00038512604,0.00032952384,0.0002712937,0.00016328244,0.00015171574],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002732359,0.00025822106,0.6541538,0.00021351055,0.0000817183,0.0020513956,0.0069433637,0.0002341404,0.29539755,0.00038257032,0.0001460187,0.037405398],"study_design_scores_gemma":[0.000014334917,0.00034262598,0.9901316,0.000008013424,0.000026330394,0.0011091031,0.0011324588,0.00032780846,0.0065156175,0.00018912287,0.00019568384,0.0000072958956],"about_ca_topic_score_codex":0.003887531,"about_ca_topic_score_gemma":0.008466492,"teacher_disagreement_score":0.003887531,"about_ca_system_score_codex":0.00021173025,"about_ca_system_score_gemma":0.0002519123,"threshold_uncertainty_score":0.0077298284},"labels":[],"label_agreement":null},{"id":"W2093104890","doi":"10.1002/hbm.20908","title":"Regional impact of field strength on voxel‐based morphometry results","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Voxel-based morphometry; Voxel; Context (archaeology); Grey matter; Psychology; Artificial intelligence; Computer science; Medicine; Magnetic resonance imaging; White matter; Biology; Radiology","score_opus":0.1310161375736174,"score_gpt":0.4094893649152951,"score_spread":0.2784732273416777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093104890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96300536,0.0013610221,0.033188973,0.000101773,0.000029264145,0.000066176966,0.0002273852,0.00031586023,0.0017042088],"genre_scores_gemma":[0.9958876,0.0001005741,0.0034925663,0.000032362794,0.000011095711,0.000021739956,0.00009927278,0.00012608623,0.00022872044],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980392,0.00095954345,0.00014805981,0.00036850348,0.00038592546,0.000098850396],"domain_scores_gemma":[0.98935807,0.007550287,0.0010258191,0.0012965701,0.00064611,0.00012307521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055860667,0.00040726745,0.00046844129,0.0010770931,0.00019460668,0.00056521775,0.00051138195,0.0003816496,0.0021947422],"category_scores_gemma":[0.018954964,0.00033658405,0.00033766558,0.00033653338,0.0007519897,0.0005527386,0.0006678973,0.00033673653,0.00030571857],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0058061993,0.00019749813,0.17627245,0.0008117692,0.0015569227,0.0013100804,0.0016922589,0.021305168,0.6616647,0.0011251565,0.0005603313,0.1276974],"study_design_scores_gemma":[0.00007690206,0.0017950342,0.8567201,0.00006081772,0.0005861154,0.00462981,0.0003034384,0.019328166,0.11217769,0.0028572408,0.0013760388,0.00008865897],"about_ca_topic_score_codex":0.00058684224,"about_ca_topic_score_gemma":0.00047847783,"teacher_disagreement_score":0.0055860667,"about_ca_system_score_codex":0.00017870273,"about_ca_system_score_gemma":0.00014644496,"threshold_uncertainty_score":0.029542327},"labels":[],"label_agreement":null},{"id":"W2093963221","doi":"10.1016/j.diii.2012.04.024","title":"3T tractography of the median nerve: Optimisation of acquisition parameters and normative diffusion values","year":2012,"lang":"en","type":"article","venue":"Diagnostic and Interventional Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Tractography; Diffusion MRI; Medicine; Fractional anisotropy; Wrist; Median nerve; Radiology; Nuclear medicine; Magnetic resonance imaging; Anatomy","score_opus":0.033812575761842115,"score_gpt":0.33169020221550183,"score_spread":0.2978776264536597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093963221","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34779733,0.0018057438,0.63728505,0.00088964973,0.00010787387,0.00047209125,0.0024617324,0.004425504,0.0047549955],"genre_scores_gemma":[0.53074414,0.0013796018,0.46121708,0.00014514364,0.00005283528,0.00077067094,0.001270017,0.0027900913,0.0016304743],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993955,0.00020973581,0.00009228318,0.00012991545,0.00013078527,0.000041691757],"domain_scores_gemma":[0.996554,0.0017720601,0.00027785654,0.00033502313,0.0009513501,0.000109728346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003313054,0.0009423938,0.0009323192,0.0017077675,0.0008537951,0.0023270252,0.0006817368,0.0019614543,0.003645249],"category_scores_gemma":[0.013532774,0.00062752323,0.0005997187,0.0011492393,0.00060675136,0.0016762129,0.0008238303,0.001085782,0.0008981635],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004210007,0.00040836536,0.025415163,0.0022485664,0.00041725326,0.0017715447,0.0018460888,0.08423224,0.42462537,0.0077191605,0.0063343607,0.44077188],"study_design_scores_gemma":[0.0005380896,0.0015960936,0.09793117,0.00086245703,0.0010409758,0.018119095,0.0009487928,0.38091835,0.45220393,0.023589555,0.021596251,0.00065520074],"about_ca_topic_score_codex":0.006005628,"about_ca_topic_score_gemma":0.0075634876,"teacher_disagreement_score":0.006005628,"about_ca_system_score_codex":0.0007066631,"about_ca_system_score_gemma":0.0020535178,"threshold_uncertainty_score":0.017521262},"labels":[],"label_agreement":null},{"id":"W2094458055","doi":"10.1016/j.neuroimage.2005.12.056","title":"Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"ZonMw","keywords":"White matter; Zygosity; Endophenotype; Voxel-based morphometry; Lateralization of brain function; Psychology; Voxel; Monozygotic twin; Twin study; Neuroscience; Medicine; Magnetic resonance imaging; Biology; Heritability; Genetics; Cognition","score_opus":0.04199888810913025,"score_gpt":0.31163004703146924,"score_spread":0.26963115892233896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094458055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99980897,0.000021529273,0.000034427543,0.00000747407,0.0000020197924,0.0000019250451,0.00005130251,0.0000014664371,0.00007094278],"genre_scores_gemma":[0.9995437,0.000028158727,0.0001783814,0.000009099181,0.0000016073589,0.000004059281,0.00009958271,0.000004981016,0.00013033893],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968946,0.00007106932,0.000046429344,0.00008175256,0.00006871891,0.000042473297],"domain_scores_gemma":[0.99926573,0.00015490587,0.00026023746,0.00009978903,0.00008537534,0.0001339115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044171984,0.00036237531,0.00046307434,0.0017251413,0.0006683837,0.00058150355,0.00039019965,0.00046573218,0.0012538418],"category_scores_gemma":[0.0022254856,0.0003830697,0.00035828684,0.0006652675,0.0005590317,0.00021232726,0.0006172539,0.0003648425,0.00012526212],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0062769414,0.00029272752,0.841015,0.00007285529,0.0005174777,0.0037178833,0.0038008597,0.00029882733,0.1351446,0.0007458194,0.00026152885,0.007855466],"study_design_scores_gemma":[0.000033570963,0.00013272345,0.9921691,0.000006076844,0.00009300266,0.0043366356,0.0006467212,0.00034959367,0.0019857187,0.00014338308,0.00009355402,0.000009978029],"about_ca_topic_score_codex":0.008524342,"about_ca_topic_score_gemma":0.0095787365,"teacher_disagreement_score":0.008524342,"about_ca_system_score_codex":0.00037967708,"about_ca_system_score_gemma":0.00026866642,"threshold_uncertainty_score":0.016949415},"labels":[],"label_agreement":null},{"id":"W2095347447","doi":"10.3389/fnhum.2014.01028","title":"Diffusion tensor imaging and white matter abnormalities in patients with disorders of consciousness","year":2015,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Neuroimaging; Diffusion MRI; Persistent vegetative state; White matter; Consciousness; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology; Minimally conscious state","score_opus":0.031144971538291762,"score_gpt":0.3251342267248881,"score_spread":0.29398925518659635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095347447","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002655457,0.998784,0.00012184114,0.0002424575,0.00006027623,0.0000030946055,0.000014772692,0.0000050186068,0.00050294044],"genre_scores_gemma":[0.001870337,0.9974946,0.00021029715,0.00008865488,0.00011923619,0.0000037772165,0.000026634842,8.0733577e-7,0.00018574912],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99980444,0.000033331336,0.000046366447,0.000040322728,0.000058822337,0.000016713602],"domain_scores_gemma":[0.9995976,0.00018146155,0.00010138845,0.000010315302,0.000087937726,0.000021330325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005202626,0.000743134,0.0011503778,0.00314966,0.00022657085,0.0008092403,0.00048668386,0.00087133254,0.0014453082],"category_scores_gemma":[0.0012026861,0.00017101018,0.00040725523,0.0022866826,0.00063946075,0.0010100227,0.0005834992,0.0010119635,0.000755022],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056366567,0.00003622792,0.0014735557,0.016338823,0.00013695621,0.00081815664,0.00014823658,0.00021478655,0.0013996896,0.002272731,0.011415097,0.9656893],"study_design_scores_gemma":[0.000035083503,0.0002513126,0.02954507,0.027600888,0.00092908775,0.038817424,0.0006398703,0.00042599498,0.0020869367,0.011539821,0.8880172,0.00011129406],"about_ca_topic_score_codex":0.001528641,"about_ca_topic_score_gemma":0.0020388404,"teacher_disagreement_score":0.00314966,"about_ca_system_score_codex":0.00039904076,"about_ca_system_score_gemma":0.001081759,"threshold_uncertainty_score":0.0048350096},"labels":[],"label_agreement":null},{"id":"W2095486621","doi":"10.1016/j.schres.2008.09.013","title":"Quetiapine alleviates the cuprizone-induced white matter pathology in the brain of C57BL/6 mouse","year":2008,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Manitoba","funders":"","keywords":"White matter; Myelin; Quetiapine; Myelin basic protein; Western blot; Internal medicine; Pharmacology; Schizophrenia (object-oriented programming); Endocrinology; Medicine; Pathology; Neuroscience; Chemistry; Central nervous system; Biology; Magnetic resonance imaging; Biochemistry; Psychiatry","score_opus":0.18268207295172567,"score_gpt":0.42693069997681654,"score_spread":0.24424862702509087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095486621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917778,0.0009327436,0.001903738,0.00070685917,0.00013869762,0.00004583543,0.0022424953,0.00065989525,0.0015921207],"genre_scores_gemma":[0.9797666,0.0017823732,0.0034059063,0.0003025812,0.000062590334,0.00009890115,0.0015112018,0.00020014128,0.012869658],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997272,0.000021829766,0.00002562472,0.00007445341,0.00007551144,0.0000753674],"domain_scores_gemma":[0.9995378,0.000033516095,0.0001838943,0.000046010155,0.000037889717,0.00016088218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018373394,0.0011032237,0.00065710925,0.0018835659,0.0004768367,0.0005709006,0.0008097879,0.0012673392,0.0025659623],"category_scores_gemma":[0.00020221966,0.0003562027,0.00051848753,0.00048926985,0.00090352766,0.0005523678,0.00027866176,0.0017857839,0.0007246096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006042896,0.0001063893,0.0001499773,0.00005011887,0.000015704038,0.00026606012,0.000039778024,0.00005554805,0.99726725,0.00018057466,0.00019202157,0.0010723824],"study_design_scores_gemma":[0.00016264735,0.0005983711,0.007486468,0.000019703984,0.0000879548,0.0005879906,0.0001013855,0.001069972,0.9876133,0.00018792898,0.0020575097,0.000026757758],"about_ca_topic_score_codex":0.007874128,"about_ca_topic_score_gemma":0.011581871,"teacher_disagreement_score":0.007874128,"about_ca_system_score_codex":0.0009063135,"about_ca_system_score_gemma":0.0008222966,"threshold_uncertainty_score":0.01565659},"labels":[],"label_agreement":null},{"id":"W2095552504","doi":"10.1016/s0028-3932(00)00048-8","title":"Comparison of overall brain volume and midsagittal corpus callosum surface area as obtained from NMR scans and direct anatomical measures: a within-subject study on autopsy brains","year":2000,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Magnetic resonance imaging; Volume (thermodynamics); Brain size; Psychology; Nuclear medicine; Displacement (psychology); Anatomy; Chemistry; Nuclear magnetic resonance; Neuroscience; Medicine; Radiology; Physics","score_opus":0.0745647637020618,"score_gpt":0.3801860399936065,"score_spread":0.3056212762915447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095552504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99943095,0.000066040324,0.00028227136,0.0000031410132,0.000003061783,0.000014046803,0.000058762693,0.0000065348877,0.00013527198],"genre_scores_gemma":[0.99840575,0.000118567776,0.00070347835,0.0000074829727,0.000014559258,0.000025282241,0.00018671661,0.000013294439,0.00052505254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998024,0.000043343633,0.000021480915,0.00007522838,0.0000371995,0.000020340321],"domain_scores_gemma":[0.9990459,0.00035723334,0.00013411333,0.00022291395,0.0001682723,0.000071520495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089854957,0.00043002778,0.0005159004,0.0008123496,0.0005273829,0.0004095462,0.00029940502,0.00034786112,0.001217044],"category_scores_gemma":[0.0021248457,0.00027888318,0.00021585802,0.0003370182,0.0010401238,0.00056700944,0.00035544438,0.00029615103,0.0002740533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.022243304,0.0023717375,0.472837,0.00034944416,0.0012679963,0.0063671963,0.010066905,0.001564282,0.42697364,0.00058220926,0.0005409263,0.05483535],"study_design_scores_gemma":[0.00009509469,0.0033512814,0.9698111,0.0000068476406,0.00026215005,0.0048043705,0.0014912066,0.0012526006,0.01793778,0.00028983262,0.00067074376,0.000026974938],"about_ca_topic_score_codex":0.0014682149,"about_ca_topic_score_gemma":0.0031175562,"teacher_disagreement_score":0.0014682149,"about_ca_system_score_codex":0.00014867706,"about_ca_system_score_gemma":0.0001901352,"threshold_uncertainty_score":0.00475204},"labels":[],"label_agreement":null},{"id":"W2095984111","doi":"10.1093/cercor/bhr361","title":"Axonal Fiber Terminations Concentrate on Gyri","year":2011,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Education and Early Childhood Development","funders":"National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute; National Institute on Aging","keywords":"Macaque; Neuroscience; Cerebral cortex; Cortex (anatomy); Diffusion MRI; Biology; Anatomy; Magnetic resonance imaging; Medicine","score_opus":0.13788488699399906,"score_gpt":0.3467944257352,"score_spread":0.2089095387412009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095984111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9747865,0.0021959462,0.015257694,0.00008898422,0.00002440978,0.000019425868,0.00026926986,0.0003028773,0.0070548765],"genre_scores_gemma":[0.9860654,0.0010917573,0.010140772,0.000025271316,0.000032096916,0.000025461191,0.00032450017,0.00004762528,0.0022472243],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99979025,0.000018629817,0.000014679888,0.00008459648,0.00005510061,0.000036818685],"domain_scores_gemma":[0.99928194,0.00013886069,0.00020609323,0.00009210961,0.00019382947,0.00008723092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023445014,0.00043244488,0.00049658096,0.0013383559,0.0008091581,0.0011798374,0.00014894383,0.00036765262,0.0025218918],"category_scores_gemma":[0.00087857636,0.00028148634,0.00022857204,0.0010154698,0.0008581517,0.0007614245,0.000580527,0.00034948473,0.0011140986],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027510538,0.00002160883,0.03377087,0.00024676308,0.00010207431,0.000484143,0.0008233504,0.00071822666,0.9212927,0.005065365,0.00043874388,0.036761116],"study_design_scores_gemma":[0.000042066644,0.00033961493,0.67054504,0.00020339995,0.00023542282,0.005791572,0.0011116626,0.0078752,0.27860966,0.00962022,0.025538277,0.0000877846],"about_ca_topic_score_codex":0.0021858073,"about_ca_topic_score_gemma":0.003504331,"teacher_disagreement_score":0.0025218918,"about_ca_system_score_codex":0.00042785998,"about_ca_system_score_gemma":0.0003461277,"threshold_uncertainty_score":0.00843662},"labels":[],"label_agreement":null},{"id":"W2097277305","doi":"10.1371/journal.pone.0133352","title":"Spatio-Temporal Regularization for Longitudinal Registration to Subject-Specific 3d Template","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute on Aging; University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; U.S. Food and Drug Administration; National Institutes of Health; Eisai; Genentech; Multiple Sclerosis Society; Foundation for the National Institutes of Health; Multiple Sclerosis Society of Canada; Northern California Institute for Research and Education; McGill University; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; Elan; Novartis; Medpace; GlaxoSmithKline; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Pfizer; Synarc; Alzheimer's Association","keywords":"Segmentation; Regularization (linguistics); Computer science; Artificial intelligence; Pattern recognition (psychology); Statistical power; Mathematics; Statistics","score_opus":0.27448312858531554,"score_gpt":0.35020603899020414,"score_spread":0.0757229104048886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097277305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003901316,0.00012862076,0.99473417,0.00007850718,0.000023549213,0.000037593585,0.00008482339,0.0007409567,0.00027055768],"genre_scores_gemma":[0.07245572,0.00025595084,0.92260057,0.00012820354,0.000040882165,0.0004274014,0.00089157774,0.0009519387,0.0022477228],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986078,0.000501302,0.0001375887,0.00029894,0.00038657937,0.000067816036],"domain_scores_gemma":[0.9975937,0.0008684018,0.00032776626,0.00072854303,0.0004141722,0.00006732992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038542794,0.0008056286,0.0006974473,0.0014942866,0.00067379896,0.0010131897,0.0016576761,0.0014199872,0.0027885193],"category_scores_gemma":[0.009153326,0.00076749566,0.0016890928,0.0021704363,0.0007842021,0.0009885563,0.0015757858,0.0016981838,0.0017266612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040855838,0.00026257537,0.0044766557,0.00045054546,0.00047414625,0.0003232647,0.0007658892,0.23403987,0.12029458,0.04385199,0.013201007,0.5814509],"study_design_scores_gemma":[0.000022197977,0.0000912648,0.002554253,0.00003134847,0.00005793039,0.00037499017,0.000060657978,0.9395843,0.024539057,0.018689381,0.013935771,0.000058751935],"about_ca_topic_score_codex":0.0054221326,"about_ca_topic_score_gemma":0.011389975,"teacher_disagreement_score":0.0054221326,"about_ca_system_score_codex":0.000945434,"about_ca_system_score_gemma":0.0024067997,"threshold_uncertainty_score":0.020383596},"labels":[],"label_agreement":null},{"id":"W2097840523","doi":"10.1109/hisb.2011.19","title":"Consistent Information Content Estimation for Diffusion Tensor MR Images","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Estimator; Diffusion MRI; Entropy estimation; Computer science; Artificial intelligence; Entropy (arrow of time); Tensor (intrinsic definition); Curse of dimensionality; Pattern recognition (psychology); Segmentation; Context (archaeology); Image segmentation; Image registration; Thresholding; Mathematics; Computer vision; Image (mathematics); Statistics","score_opus":0.19970581124354295,"score_gpt":0.34873286810613935,"score_spread":0.1490270568625964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097840523","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050741066,0.00016850456,0.99437153,0.00006357036,0.000010294835,0.000013223356,0.000040888506,0.000136443,0.00012141977],"genre_scores_gemma":[0.25246486,0.00070727983,0.7445593,0.00017322451,0.00014546956,0.00017330382,0.0006769685,0.0002831989,0.00081645325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982613,0.00058645435,0.00013184123,0.0003332288,0.0006137122,0.00007353924],"domain_scores_gemma":[0.9911016,0.0053736223,0.0010209053,0.0011681621,0.0011785463,0.00015714834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00420415,0.0007387189,0.0010992152,0.0028538487,0.00041433744,0.001547746,0.0014136046,0.0012969897,0.0006652698],"category_scores_gemma":[0.02231665,0.00063153106,0.000616158,0.0017512992,0.0013537788,0.0038470475,0.0015843908,0.0013992831,0.00048539543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034779997,0.00015967849,0.0058443313,0.0004075987,0.00025663732,0.00019929871,0.0003141961,0.4329651,0.045974247,0.12024602,0.0033713032,0.38991383],"study_design_scores_gemma":[0.000014824177,0.00005084702,0.0011249877,0.000024398505,0.000022405431,0.00007980941,0.000017163005,0.9293653,0.012517119,0.05560867,0.0011320431,0.00004236706],"about_ca_topic_score_codex":0.0009984144,"about_ca_topic_score_gemma":0.0011274065,"teacher_disagreement_score":0.00420415,"about_ca_system_score_codex":0.00072685006,"about_ca_system_score_gemma":0.0007581103,"threshold_uncertainty_score":0.022233963},"labels":[],"label_agreement":null},{"id":"W2098063347","doi":"10.1093/neuonc/nov113","title":"High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery","year":2015,"lang":"en","type":"review","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Fiber tract; Medicine; Glioma; Radiology; Magnetic resonance imaging","score_opus":0.28399379551971277,"score_gpt":0.44856462093393445,"score_spread":0.1645708254142217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098063347","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018764766,0.99869114,0.00023930473,0.0001415908,0.00006903653,0.0000047073854,0.000010646325,0.0000059543263,0.00064993865],"genre_scores_gemma":[0.0011876555,0.9979085,0.00046313976,0.00006703192,0.00008333622,0.000005834238,0.000022304088,0.0000018470848,0.0002603729],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998394,0.000027588165,0.000036648937,0.000025655328,0.00005897966,0.000011696971],"domain_scores_gemma":[0.9995018,0.00022550252,0.000093922965,0.000013957966,0.0001332343,0.000031629323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072331703,0.000874551,0.0010582771,0.0051216395,0.00023725766,0.0008391396,0.00071609864,0.0009012609,0.0023211807],"category_scores_gemma":[0.0010421675,0.0003191409,0.0006343636,0.0028883694,0.00063639286,0.0014155458,0.0006028894,0.0012382765,0.0017012948],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048784314,0.000048123482,0.0005776765,0.016392948,0.00010358206,0.00048304486,0.000062695275,0.00039587394,0.0014791889,0.0014364778,0.009786637,0.969185],"study_design_scores_gemma":[0.000033215474,0.0002035756,0.008143294,0.0145855425,0.00048443425,0.017271893,0.00021875558,0.00068742427,0.0022070282,0.004456679,0.95162,0.00008819243],"about_ca_topic_score_codex":0.0017767198,"about_ca_topic_score_gemma":0.0035788347,"teacher_disagreement_score":0.0051216395,"about_ca_system_score_codex":0.0004905206,"about_ca_system_score_gemma":0.0011335593,"threshold_uncertainty_score":0.0077651143},"labels":[],"label_agreement":null},{"id":"W2100031669","doi":"10.1002/hbm.20994","title":"Patterns of cortical degeneration in an elderly cohort with cerebral small vessel disease","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Psychology; White matter; Cerebral cortex; Temporal lobe; Neuroscience; Magnetic resonance imaging; Prefrontal cortex; Frontal lobe; Neuroimaging; Medicine; Cognition","score_opus":0.06349540230440086,"score_gpt":0.33181173404350434,"score_spread":0.26831633173910346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100031669","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996132,0.00010906189,0.00003113892,0.0000100297475,0.0000012549594,0.0000028645659,0.00010316166,0.0000023791338,0.00012686984],"genre_scores_gemma":[0.9996313,0.000070193724,0.000037481877,0.000009445214,0.000003605819,0.0000032358562,0.00014939312,0.0000011796665,0.00009422493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998222,0.00003230207,0.000020419322,0.000059782204,0.000030664436,0.0000346746],"domain_scores_gemma":[0.9994424,0.00007864607,0.00019603019,0.00006358914,0.00009358657,0.0001258591],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029079086,0.00022119968,0.00030566467,0.0012427819,0.00039571454,0.00044522417,0.0002239096,0.00039813583,0.00083965756],"category_scores_gemma":[0.0011448293,0.00024823318,0.00023015226,0.0008099353,0.00028624214,0.0002681347,0.00029401068,0.00028559443,0.0002251],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012185937,0.000013092047,0.9978946,0.0000033436927,0.000032894768,0.0002825614,0.0001124107,0.000026493313,0.0005994911,0.0000082014,0.000044360375,0.00086073973],"study_design_scores_gemma":[0.0000019685056,0.000033186778,0.9994178,0.0000010485259,0.000007734587,0.00037155877,0.000063628475,0.00003637059,0.00002517564,0.000009828872,0.000030108084,0.0000015297818],"about_ca_topic_score_codex":0.008485649,"about_ca_topic_score_gemma":0.009915987,"teacher_disagreement_score":0.008485649,"about_ca_system_score_codex":0.00017732262,"about_ca_system_score_gemma":0.00016533339,"threshold_uncertainty_score":0.016872525},"labels":[],"label_agreement":null},{"id":"W2100154344","doi":"10.1007/s10851-008-0071-8","title":"High Angular Resolution Diffusion MRI Segmentation Using Region-Based Statistical Surface Evolution","year":2008,"lang":"en","type":"article","venue":"Journal of Mathematical Imaging and Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften; McGill University","keywords":"Diffusion MRI; Segmentation; Angular resolution (graph drawing); Orientation (vector space); Computer science; Artificial intelligence; Tensor (intrinsic definition); Diffusion; Imaging phantom; Image resolution; Fiber; Synthetic data; Pattern recognition (psychology); Surface (topology); Image segmentation; Computer vision; Algorithm; Physics; Mathematics; Magnetic resonance imaging; Materials science; Optics; Geometry","score_opus":0.05149532651747536,"score_gpt":0.37590472275786785,"score_spread":0.3244093962403925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100154344","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015006465,0.0001580946,0.983414,0.00012951792,0.000014482076,0.000029454257,0.000050758998,0.00079583813,0.00040138705],"genre_scores_gemma":[0.19381285,0.0002957529,0.8038207,0.00007143201,0.000030910112,0.00006402495,0.00021678663,0.00054426555,0.0011432916],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997075,0.000070147275,0.000022697684,0.000057031833,0.00011727331,0.000025393258],"domain_scores_gemma":[0.99904937,0.0004287931,0.000117990545,0.00013226015,0.00023192642,0.000039623857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009439763,0.0006771972,0.0009176868,0.0015205685,0.00040176013,0.0015400384,0.00083734246,0.0011379069,0.00095638365],"category_scores_gemma":[0.003081951,0.0006770184,0.00090964814,0.0013610525,0.000473081,0.0011268331,0.0008752855,0.00090690877,0.0006292378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034813306,0.00010142696,0.0025144145,0.00029462128,0.00020668517,0.0003185072,0.0003934945,0.32186803,0.18744218,0.018090053,0.0036836956,0.4647387],"study_design_scores_gemma":[0.00000868623,0.000015477777,0.0004606568,0.000006582856,0.0000145514,0.000112361806,0.000010393904,0.98054403,0.013781491,0.004115543,0.000915893,0.0000143449415],"about_ca_topic_score_codex":0.002986832,"about_ca_topic_score_gemma":0.0034385566,"teacher_disagreement_score":0.002986832,"about_ca_system_score_codex":0.0005797316,"about_ca_system_score_gemma":0.0012310598,"threshold_uncertainty_score":0.0059388876},"labels":[],"label_agreement":null},{"id":"W2101143723","doi":"10.3389/fnhum.2013.00845","title":"Network efficiency in autism spectrum disorder and its relation to brain overgrowth","year":2013,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies; Compute Canada","keywords":"Autism spectrum disorder; Brain size; Autism; Tractography; Neuroscience; Psychology; Diffusion MRI; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.023411599221681373,"score_gpt":0.2995723087445292,"score_spread":0.2761607095228479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101143723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99573827,0.00043947162,0.0024473066,0.00008770655,0.000002139261,0.000009279665,0.00018274595,0.00002846755,0.001064591],"genre_scores_gemma":[0.99865735,0.00018734235,0.0008241232,0.0000044892217,0.0000030024623,0.000010501144,0.00013047956,0.000008994791,0.00017367146],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99965656,0.00007857843,0.000030321127,0.00008817798,0.00010408867,0.000042401687],"domain_scores_gemma":[0.9945639,0.0020888194,0.0022287008,0.00037447666,0.00036558343,0.00037860606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005910269,0.00039045475,0.00027448923,0.0024198028,0.00023174101,0.0004872067,0.00026978995,0.00036507403,0.0015184387],"category_scores_gemma":[0.0061689387,0.00018043701,0.00030533233,0.0009915611,0.00089834665,0.00079348404,0.0008490114,0.00036021383,0.00013992451],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037282813,0.000053750413,0.9404677,0.00008888531,0.00033355824,0.0006496185,0.00095866865,0.02036629,0.014753179,0.0025392224,0.00026488898,0.019151436],"study_design_scores_gemma":[0.0000053635085,0.00003853368,0.9854026,0.000010198496,0.0000262838,0.00080012664,0.0002450673,0.010228497,0.0008059946,0.0020811588,0.00034687054,0.0000093114995],"about_ca_topic_score_codex":0.0045270394,"about_ca_topic_score_gemma":0.0032006206,"teacher_disagreement_score":0.0045270394,"about_ca_system_score_codex":0.0005675723,"about_ca_system_score_gemma":0.00020583856,"threshold_uncertainty_score":0.009001374},"labels":[],"label_agreement":null},{"id":"W2101310005","doi":"10.3174/ajnr.a4312","title":"Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months","year":2015,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; Hospital for Sick Children; University of British Columbia; SickKids Foundation; BC Children's Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Canadian Child Health Clinician Scientist Program; Michael Smith Health Research BC; Child and Family Research Institute","keywords":"Medicine; Cognition; Pediatrics; Psychiatry","score_opus":0.05201122306081865,"score_gpt":0.3546413930039905,"score_spread":0.3026301699431718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101310005","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999464,0.00008872442,0.00015103891,0.000015653774,0.0000012158653,0.0000017955824,0.00014258461,0.0000064650867,0.00012863867],"genre_scores_gemma":[0.9992543,0.0000773981,0.00032718907,0.000003625724,0.0000016089605,0.000004718609,0.00023978678,0.0000039437155,0.00008735004],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985063,0.00003407905,0.000025888321,0.000033179564,0.00003237111,0.000023749524],"domain_scores_gemma":[0.9977629,0.00041791165,0.0012023759,0.00012053763,0.00029120396,0.00020511104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005327409,0.0002511789,0.00019882034,0.00067491084,0.0001698857,0.00035377906,0.00022310493,0.00037171273,0.0011745694],"category_scores_gemma":[0.0046284087,0.000101292455,0.0002320596,0.00030595827,0.0002598406,0.00023868095,0.0003704563,0.0002574977,0.0002567865],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001863356,0.000012256396,0.9935749,0.000010600919,0.000024743424,0.00027222218,0.00008083623,0.00028012463,0.0020398996,0.000040148105,0.00006764015,0.003410284],"study_design_scores_gemma":[0.0000018363398,0.00008829454,0.9963341,0.000014705121,0.000011863151,0.0012421828,0.0001274542,0.0009317236,0.001066623,0.00006878734,0.00010794843,0.0000044676735],"about_ca_topic_score_codex":0.0048281816,"about_ca_topic_score_gemma":0.005273954,"teacher_disagreement_score":0.0048281816,"about_ca_system_score_codex":0.0004249638,"about_ca_system_score_gemma":0.0003593524,"threshold_uncertainty_score":0.0096001625},"labels":[],"label_agreement":null},{"id":"W2101810272","doi":"10.1016/j.medengphy.2014.02.021","title":"Special Issue on Cerebral Autoregulation: Measurement and modelling","year":2014,"lang":"en","type":"editorial","venue":"Medical Engineering & Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Autoregulation; Cerebral autoregulation; Computer science; Neuroscience; Medicine; Engineering; Psychology; Internal medicine; Blood pressure","score_opus":0.03640128165501212,"score_gpt":0.29165094523028123,"score_spread":0.2552496635752691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101810272","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000018721395,0.010621856,0.00068408967,0.015154443,0.9726758,0.000012508754,0.00007197508,0.0000774252,0.000683276],"genre_scores_gemma":[0.00020021142,0.004323041,0.00023379466,0.0042117108,0.9877038,0.000021163012,0.000031446125,0.000041710395,0.0032330612],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9931203,0.0013610852,0.0010521333,0.001072539,0.0031331796,0.00026082442],"domain_scores_gemma":[0.9718983,0.014281776,0.0020716235,0.0010514539,0.008548589,0.00214824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010902532,0.0061298306,0.00799792,0.0060654827,0.002393313,0.008854546,0.0044178264,0.018523367,0.012400662],"category_scores_gemma":[0.031308055,0.0022242025,0.005457675,0.0022652866,0.002950731,0.004047689,0.0026965125,0.021441111,0.009294711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004714196,0.000015448579,0.000027879909,0.00033087743,0.0000608747,0.00007482135,0.000005819842,0.00013679815,0.00006228563,0.00036971108,0.990706,0.008162388],"study_design_scores_gemma":[0.00012811288,0.000051970368,0.00040252093,0.0008073157,0.00024972128,0.0003894482,0.000019733365,0.0015168015,0.00023380076,0.004660807,0.9914829,0.00005670933],"about_ca_topic_score_codex":0.0023353358,"about_ca_topic_score_gemma":0.005349796,"teacher_disagreement_score":0.018523367,"about_ca_system_score_codex":0.0032492727,"about_ca_system_score_gemma":0.003522486,"threshold_uncertainty_score":0.05765885},"labels":[],"label_agreement":null},{"id":"W2102318727","doi":"10.1109/nfsi-icfbi.2007.4387703","title":"Evaluating the Accuracy of an Anisotropic Finite-Volume Head Model for the EEG Forward Problem","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Head (geology); Finite volume method; Computer science; Magnitude (astronomy); Anisotropy; Electroencephalography; Physics; Mechanics; Optics; Geology","score_opus":0.22172727369997325,"score_gpt":0.4806607083890419,"score_spread":0.25893343468906865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102318727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36948577,0.0007026429,0.6204627,0.0008615802,0.00010815272,0.00012108106,0.00029176183,0.0010141591,0.006952152],"genre_scores_gemma":[0.8390574,0.00035477892,0.15861332,0.000073828865,0.000025000587,0.00007118297,0.00027677102,0.00015878578,0.0013689456],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999595,0.00016302825,0.000029681949,0.000029656852,0.00015502666,0.000027687605],"domain_scores_gemma":[0.99596006,0.0030400287,0.00020938313,0.00027976534,0.00043559173,0.00007505836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014734953,0.0005268305,0.00040508516,0.0004309842,0.0003599648,0.00077780685,0.00079101877,0.0011301893,0.0008925514],"category_scores_gemma":[0.0088805165,0.00027274582,0.000397088,0.0003427493,0.0005655915,0.00079699716,0.000512398,0.0006033591,0.00019209669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000119151635,0.000040773568,0.0014118745,0.00006489255,0.000020290161,0.00007719001,0.00008134406,0.976982,0.0056050643,0.003870243,0.00034519058,0.011381929],"study_design_scores_gemma":[0.000007329848,0.000019276891,0.00010798018,0.000004949365,0.0000023660643,0.000018598455,0.000011512021,0.9977464,0.0014969156,0.00039289138,0.00018666823,0.000005055461],"about_ca_topic_score_codex":0.014612718,"about_ca_topic_score_gemma":0.0068195607,"teacher_disagreement_score":0.014612718,"about_ca_system_score_codex":0.00056708837,"about_ca_system_score_gemma":0.0010292621,"threshold_uncertainty_score":0.029055297},"labels":[],"label_agreement":null},{"id":"W2102334389","doi":"10.1016/j.ccl.2012.10.011","title":"Syncope—Now in Its Golden Era","year":2012,"lang":"en","type":"article","venue":"Cardiology Clinics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Libin Cardiovascular Institute of Alberta","funders":"","keywords":"Medicine; Internuclear ophthalmoplegia; Medial longitudinal fasciculus; Midbrain; Diffusion MRI; Fractional anisotropy; Anatomy; Cardiology; Pathology; Internal medicine; Multiple sclerosis; Radiology; Magnetic resonance imaging; Central nervous system","score_opus":0.12880143680477668,"score_gpt":0.4324582693958911,"score_spread":0.3036568325911144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102334389","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064312587,0.3383335,0.004396986,0.49789858,0.1154419,0.000025772857,0.00032439388,0.0005492366,0.036598355],"genre_scores_gemma":[0.15108502,0.2550839,0.0059555247,0.19607994,0.36507338,0.0000753037,0.00056344736,0.0003122222,0.025771296],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99740773,0.0005475106,0.0004374541,0.00031532772,0.00096032606,0.00033163317],"domain_scores_gemma":[0.98516685,0.00551979,0.0012235759,0.00090289937,0.0034995293,0.0036873918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0071737734,0.0009545083,0.0018748698,0.0019122863,0.0021938237,0.007976343,0.0010896978,0.005208565,0.010305873],"category_scores_gemma":[0.015892023,0.00026736248,0.0005802346,0.0011595251,0.0046773297,0.012389093,0.0036576404,0.008787083,0.00399626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061853736,0.00010062095,0.0038257826,0.0011643044,0.000082407336,0.0013019822,0.00049515325,0.00016125834,0.0013027033,0.03782336,0.44618082,0.50694317],"study_design_scores_gemma":[0.00010899842,0.000372645,0.005268724,0.0022549948,0.00010578614,0.0046380777,0.0011123762,0.00038284803,0.00040091225,0.04257244,0.9426689,0.00011331708],"about_ca_topic_score_codex":0.0010038308,"about_ca_topic_score_gemma":0.0022069467,"teacher_disagreement_score":0.010305873,"about_ca_system_score_codex":0.0013344815,"about_ca_system_score_gemma":0.0030736874,"threshold_uncertainty_score":0.037939012},"labels":[],"label_agreement":null},{"id":"W2102604017","doi":"10.1016/j.jalz.2011.05.670","title":"P1‐389: Effect of Apolipoprotein E on cortical thickness and resting‐state brain function in Alzheimer's disease","year":2011,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Apolipoprotein E; Resting state fMRI; Medicine; Dementia; Cardiology; Internal medicine; Audiology; Psychology; Nuclear medicine; Disease; Radiology","score_opus":0.0604710601115722,"score_gpt":0.32822705156706145,"score_spread":0.26775599145548923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102604017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961156,0.00011088499,0.000033326778,0.000014087392,0.0000030793278,0.0000035383105,0.000058074736,0.0000021631588,0.00016320549],"genre_scores_gemma":[0.999161,0.000100184385,0.00011624651,0.000024590021,0.000008371425,0.000010133241,0.000166932,0.0000041164612,0.0004085761],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.00003756501,0.000010548501,0.000023947898,0.000021919648,0.000013511052],"domain_scores_gemma":[0.99963605,0.00014356397,0.00008669306,0.000031554264,0.000021344049,0.00008088322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033414253,0.00042881607,0.0003070441,0.00017466703,0.00023559069,0.00023750005,0.0002053851,0.00037488228,0.0016322861],"category_scores_gemma":[0.0009910937,0.00015964228,0.00019042894,0.00017149533,0.00020971186,0.00019433448,0.00019055173,0.00032059188,0.0002978335],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.08436787,0.003562484,0.6893488,0.00021549164,0.0010070483,0.004039301,0.0006682862,0.0004527782,0.16404277,0.00016893611,0.0006638588,0.05146234],"study_design_scores_gemma":[0.000088832276,0.0014988031,0.9959168,0.0000036462827,0.000061012026,0.00059246575,0.000040838204,0.00025069382,0.001304501,0.00009725669,0.00013969175,0.0000054795423],"about_ca_topic_score_codex":0.0012650519,"about_ca_topic_score_gemma":0.0011828792,"teacher_disagreement_score":0.0016322861,"about_ca_system_score_codex":0.000108848326,"about_ca_system_score_gemma":0.00009941413,"threshold_uncertainty_score":0.0054605007},"labels":[],"label_agreement":null},{"id":"W2103375347","doi":"10.1109/tmi.2011.2142189","title":"Spatially Regularized Compressed Sensing for High Angular Resolution Diffusion Imaging","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Compressed sensing; Computer science; Iterative reconstruction; Sampling (signal processing); Perspective (graphical); Diffusion; Minification; Artificial intelligence; Diffusion MRI; Image resolution; Computer vision; Encoding (memory); Algorithm; Reconstruction algorithm; Reduction (mathematics); Magnetic resonance imaging; Mathematics; Physics","score_opus":0.04798995004900583,"score_gpt":0.3162274920248334,"score_spread":0.2682375419758276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103375347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031839407,0.0005732186,0.99305725,0.0004798036,0.0000635308,0.000035684076,0.00006691166,0.00015946043,0.0023801276],"genre_scores_gemma":[0.17726085,0.0023761548,0.8144955,0.00027420203,0.00022831587,0.0002171238,0.00029487393,0.00014210539,0.0047108503],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99962103,0.00012391603,0.000020005098,0.000044461074,0.0001718767,0.000018740522],"domain_scores_gemma":[0.9994398,0.00034453,0.000056409666,0.000063513704,0.00007235882,0.000023471806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007560516,0.00053987774,0.0004838606,0.0004306819,0.00023904465,0.0006008762,0.00062237703,0.00079497806,0.0022417223],"category_scores_gemma":[0.0029090093,0.00022626236,0.0005287588,0.0006465819,0.00069574546,0.00073678547,0.0009914227,0.0016749159,0.00066171825],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014508831,0.000059405058,0.00031562336,0.00039393798,0.000042293595,0.00029853947,0.00022542229,0.46875465,0.047934502,0.33429387,0.0057870056,0.14174971],"study_design_scores_gemma":[0.0000073528304,0.000025179566,0.000059373928,0.000015761103,0.0000035081987,0.00005880377,0.000010290421,0.973565,0.0025222434,0.020370647,0.0033511806,0.000010645262],"about_ca_topic_score_codex":0.0015616608,"about_ca_topic_score_gemma":0.0015989329,"teacher_disagreement_score":0.0022417223,"about_ca_system_score_codex":0.00052771426,"about_ca_system_score_gemma":0.00072749454,"threshold_uncertainty_score":0.007499337},"labels":[],"label_agreement":null},{"id":"W2104545915","doi":"10.1016/j.neuroimage.2008.10.054","title":"Mathematical methods for diffusion MRI processing","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; U.S. Public Health Service","keywords":"Diffusion MRI; Focus (optics); Computer science; Diffusion; White matter; Image processing; Segmentation; Artificial intelligence; Magnetic resonance imaging; Computer vision; Physics; Image (mathematics); Medicine; Optics; Radiology","score_opus":0.14868572963379884,"score_gpt":0.46108824227450507,"score_spread":0.31240251264070623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104545915","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034312933,0.0020398742,0.9955663,0.0003400622,0.0001502648,0.000014394547,0.000059880236,0.0001586964,0.0013272709],"genre_scores_gemma":[0.030348208,0.0076051443,0.94399714,0.00027704972,0.0008771818,0.00026951765,0.00030882884,0.00061393966,0.015702937],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99926454,0.00026019668,0.000075911565,0.000120483026,0.00025132284,0.000027553668],"domain_scores_gemma":[0.9972698,0.001306655,0.00021483518,0.00045375372,0.00067748653,0.00007740981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019958767,0.0013926069,0.0012963674,0.0022257227,0.0006480863,0.00216576,0.002225601,0.0024346868,0.0055335066],"category_scores_gemma":[0.0077765244,0.00089899154,0.0014566206,0.0020984365,0.0015890654,0.0033178774,0.0018346937,0.004027368,0.0043457663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019170313,0.00003358023,0.00016178709,0.00047054832,0.000063350024,0.000108386725,0.00014065935,0.053700283,0.0039840867,0.7940293,0.013623535,0.13366528],"study_design_scores_gemma":[0.000013228305,0.000018380822,0.00020514775,0.00006910043,0.000034169465,0.00022939914,0.000029354464,0.43391553,0.0016041932,0.52327853,0.04055837,0.00004458724],"about_ca_topic_score_codex":0.0033971516,"about_ca_topic_score_gemma":0.00312451,"teacher_disagreement_score":0.0055335066,"about_ca_system_score_codex":0.0009208631,"about_ca_system_score_gemma":0.001281363,"threshold_uncertainty_score":0.018511474},"labels":[],"label_agreement":null},{"id":"W2105050326","doi":"10.1016/s0197-4580(02)00013-1","title":"A reliable MR measurement of medial temporal lobe width from the Sunnybrook Dementia Study","year":2002,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Women's College Hospital; University of Toronto","funders":"","keywords":"Temporal lobe; Hippocampus; Anterior commissure; Parahippocampal gyrus; Midbrain; Neuroscience; Hippocampal formation; Posterior commissure; Anatomy; Psychology; Medicine; Central nervous system; Epilepsy","score_opus":0.10307489958571628,"score_gpt":0.31592283895431383,"score_spread":0.21284793936859756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105050326","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909043,0.0017369593,0.0018031426,0.00019039307,0.000069150796,0.00007142185,0.0013633966,0.000042938136,0.0038183746],"genre_scores_gemma":[0.9961442,0.00035247594,0.0021362095,0.00006246302,0.00005064607,0.000038028287,0.00064226554,0.000025688218,0.0005480804],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991992,0.0002117571,0.00017070275,0.00014032831,0.00022293495,0.00005499063],"domain_scores_gemma":[0.99724126,0.0004359936,0.00065613165,0.00036331677,0.0010186823,0.00028466518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025463898,0.0006203824,0.0004742549,0.0029945127,0.0007092066,0.001152302,0.00072480337,0.0008192136,0.0015905458],"category_scores_gemma":[0.008686955,0.0003951868,0.00028046276,0.00085640687,0.0004455016,0.0009817573,0.0008018207,0.00045440538,0.00062369346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002268658,0.00008550862,0.9246262,0.0001819524,0.0003038786,0.0025818232,0.0009338379,0.00027165076,0.024233613,0.00042320715,0.0028949273,0.0411948],"study_design_scores_gemma":[0.000052681622,0.00016960599,0.9901225,0.00003944012,0.00013103236,0.002710454,0.00038488946,0.00035526472,0.0039076163,0.00029913508,0.00180071,0.000026665151],"about_ca_topic_score_codex":0.0056489427,"about_ca_topic_score_gemma":0.013072753,"teacher_disagreement_score":0.0056489427,"about_ca_system_score_codex":0.00035412883,"about_ca_system_score_gemma":0.00048581362,"threshold_uncertainty_score":0.013466716},"labels":[],"label_agreement":null},{"id":"W2105528651","doi":"10.1016/j.neuroimage.2007.11.033","title":"Complementary information from multi-exponential T2 relaxation and diffusion tensor imaging reveals differences between multiple sclerosis lesions","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Killam Trusts; Multiple Sclerosis Society","keywords":"Diffusion MRI; Fractional anisotropy; Multiple sclerosis; White matter; Nuclear magnetic resonance; T2 relaxation; Myelin; Lesion; Magnetic resonance imaging; Thermal diffusivity; Pathology; Medicine; Nuclear medicine; Neuroscience; Physics; Radiology; Psychology; Central nervous system","score_opus":0.1298048725404124,"score_gpt":0.33436079605896957,"score_spread":0.20455592351855717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105528651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98741865,0.0020244946,0.0078507,0.00039725058,0.000044588007,0.000024045465,0.00045393663,0.000101113525,0.0016851964],"genre_scores_gemma":[0.9877015,0.001457635,0.008638565,0.00020337952,0.00019286203,0.000038988917,0.0007236722,0.00010566295,0.0009377655],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998062,0.000045440374,0.000023597257,0.000041938674,0.000038141232,0.000044689023],"domain_scores_gemma":[0.99837744,0.0006917596,0.00034797008,0.00015963732,0.0002154429,0.00020770059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011432415,0.00078507466,0.00060310867,0.002962764,0.0004118595,0.0010302754,0.00045173737,0.0018647132,0.003238305],"category_scores_gemma":[0.0034119892,0.0006079731,0.00056863093,0.001084916,0.0005875825,0.0027113056,0.00074848643,0.0008575252,0.00068993197],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043505197,0.00024164043,0.017597506,0.0007114566,0.00053705456,0.0017866137,0.00049045135,0.0011555732,0.91530615,0.00082838046,0.0010081024,0.05598647],"study_design_scores_gemma":[0.0008635525,0.0018632538,0.5592695,0.00030393686,0.0025042808,0.022825519,0.0013376577,0.02633953,0.36393338,0.015990943,0.004453319,0.0003150834],"about_ca_topic_score_codex":0.00050994114,"about_ca_topic_score_gemma":0.0012104351,"teacher_disagreement_score":0.003238305,"about_ca_system_score_codex":0.00015562729,"about_ca_system_score_gemma":0.00030065246,"threshold_uncertainty_score":0.010833144},"labels":[],"label_agreement":null},{"id":"W2105728290","doi":"10.1111/j.1600-0447.2009.01389.x","title":"Morphology of the corpus callosum in treatment‐resistant schizophrenia and major depression","year":2009,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Medical Research Council; National Health and Medical Research Council; China Scholarship Council","keywords":"Corpus callosum; Depression (economics); Treatment-resistant depression; Schizophrenia (object-oriented programming); Psychology; Medicine; Major depressive disorder; Neuroscience; Psychiatry","score_opus":0.02488008501270776,"score_gpt":0.3194196018808942,"score_spread":0.2945395168681864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105728290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996209,0.000115472685,0.00005432097,0.000009149197,8.7355335e-7,0.0000034802356,0.000038342278,0.0000034397585,0.00015393546],"genre_scores_gemma":[0.999584,0.0000595784,0.0001997362,0.0000042851225,0.0000011244958,0.000005212415,0.00008587761,0.0000023166997,0.000057918656],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998797,0.000031829863,0.000018317616,0.000028412658,0.000028230856,0.000013450544],"domain_scores_gemma":[0.99955994,0.0000776222,0.00023672859,0.000038875463,0.00003575936,0.0000510832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002598307,0.0002643142,0.00015856407,0.0011755896,0.00025767603,0.0003359173,0.00018735601,0.0003022023,0.0013980384],"category_scores_gemma":[0.0012051471,0.00023796949,0.0001644032,0.00033670905,0.00043617803,0.00017882853,0.00022346836,0.00011519978,0.00013032452],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003621912,0.000100839105,0.8596535,0.00020802688,0.00037907154,0.0034392807,0.0019727903,0.0006029207,0.09893819,0.00025092426,0.00043019085,0.030402273],"study_design_scores_gemma":[0.000015931588,0.0001055553,0.996418,0.000007249401,0.000021086009,0.0025593324,0.00015182636,0.00013701594,0.00045101956,0.000030815816,0.0000993808,0.0000027602564],"about_ca_topic_score_codex":0.0028389937,"about_ca_topic_score_gemma":0.0044437298,"teacher_disagreement_score":0.0028389937,"about_ca_system_score_codex":0.00028575488,"about_ca_system_score_gemma":0.0001709251,"threshold_uncertainty_score":0.0056449175},"labels":[],"label_agreement":null},{"id":"W2105775214","doi":"10.1109/42.925291","title":"Penalized discriminant analysis of [/sup 15/O]-water PET brain images with prediction error selection of smoothness and regularization hyperparameters","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health","keywords":"Hyperparameter; Mathematics; Artificial intelligence; Covariance; Smoothness; Smoothing; Pattern recognition (psychology); Computer science; Covariance matrix; Regularization (linguistics); Algorithm; Statistics; Mathematical analysis","score_opus":0.025316644421795632,"score_gpt":0.31685698515474287,"score_spread":0.2915403407329472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105775214","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05209879,0.000055466084,0.9473989,0.00005624136,0.000005715594,0.000018823499,0.000026802622,0.00019588872,0.00014341588],"genre_scores_gemma":[0.40689927,0.000100794234,0.5916512,0.000059272414,0.000022438559,0.00010510931,0.00019836728,0.00015020116,0.00081331783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995129,0.00021676495,0.000027367118,0.00010663273,0.000101541154,0.00003480811],"domain_scores_gemma":[0.99886024,0.00047100493,0.00016157854,0.00024507582,0.00021926072,0.000042877018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016452176,0.00058885425,0.00055638177,0.00047154597,0.00019949806,0.00045542352,0.00062974595,0.0004310542,0.0004827676],"category_scores_gemma":[0.0029474783,0.0002542868,0.0005846569,0.00040767665,0.00062104885,0.00054072496,0.0007347966,0.0008477321,0.00019751149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004987659,0.00012477877,0.0053550736,0.00013081981,0.0001583371,0.00018531569,0.00015364673,0.55363977,0.13844414,0.0065571195,0.0009316876,0.29382056],"study_design_scores_gemma":[0.0000065583617,0.000051165276,0.0012330909,0.0000026547148,0.000009132516,0.000043760643,0.000007045388,0.9890238,0.007779322,0.0015780403,0.00025214904,0.000013256293],"about_ca_topic_score_codex":0.00094815955,"about_ca_topic_score_gemma":0.0014754323,"teacher_disagreement_score":0.0016452176,"about_ca_system_score_codex":0.0002796865,"about_ca_system_score_gemma":0.00041063613,"threshold_uncertainty_score":0.008700848},"labels":[],"label_agreement":null},{"id":"W2106003398","doi":"10.1093/cercor/12.11.1218","title":"Asymmetry of the Uncinate Fasciculus: A Post-mortem Study of Normal Subjects and Patients with Schizophrenia","year":2002,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":205,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; Wellcome Trust","keywords":"Uncinate fasciculus; Fasciculus; Inferior longitudinal fasciculus; Anatomy; Psychology; White matter; Neuroscience; Medicine; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.021300954928712566,"score_gpt":0.2541216520114659,"score_spread":0.23282069708275335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106003398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954575,0.00017735364,0.00005699542,0.000009369873,0.0000018616622,0.0000039385086,0.000053024643,0.0000018469333,0.00014981633],"genre_scores_gemma":[0.9994628,0.00012936424,0.00007302545,0.000010240481,0.0000038676717,0.000004908902,0.00012241385,0.0000024274334,0.00019106966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988246,0.000020453024,0.000013532064,0.00003286663,0.000021383747,0.000029244706],"domain_scores_gemma":[0.99963546,0.000071679424,0.00013743962,0.000038112106,0.000049498653,0.00006783042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002937039,0.00033256877,0.00034532842,0.0009842335,0.00043061495,0.00028698787,0.00011474995,0.000274196,0.0015722646],"category_scores_gemma":[0.0009316883,0.0002137958,0.00013326132,0.00023814493,0.0006955926,0.00020413831,0.00031793953,0.00019743468,0.0002756744],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005398187,0.00022045257,0.7980321,0.00016712151,0.00020428546,0.015631389,0.0058006593,0.0001494161,0.15307774,0.00029364016,0.00030355042,0.020721408],"study_design_scores_gemma":[0.000027400773,0.00030949622,0.9922774,0.000007733756,0.000020317832,0.0054188306,0.000505711,0.00006300919,0.0010412049,0.00006381281,0.00025820217,0.000006787298],"about_ca_topic_score_codex":0.0036795891,"about_ca_topic_score_gemma":0.00512274,"teacher_disagreement_score":0.0036795891,"about_ca_system_score_codex":0.0002683444,"about_ca_system_score_gemma":0.0001669596,"threshold_uncertainty_score":0.007316351},"labels":[],"label_agreement":null},{"id":"W2106241798","doi":"10.1016/s0720-048x(02)00305-4","title":"Diffusion weighted magnetic resonance imaging in stroke","year":2003,"lang":"en","type":"review","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canada Research Chairs","keywords":"Penumbra; Medicine; Magnetic resonance imaging; Diffusion MRI; Stroke (engine); Artifact (error); Effective diffusion coefficient; Radiology; Diffusion; Hyperintensity; Diffusion imaging; Ischemia; Artificial intelligence; Cardiology; Computer science","score_opus":0.05855231441885334,"score_gpt":0.35037951051591465,"score_spread":0.2918271960970613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106241798","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001266074,0.9984267,0.00015597543,0.0002470288,0.00028802725,0.0000053950025,0.000012099518,0.000006835517,0.0007313671],"genre_scores_gemma":[0.0007564877,0.9975865,0.00023930144,0.00022183007,0.00059995364,0.000006224517,0.000023085768,0.0000016285156,0.00056509505],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997054,0.00004424267,0.000090057634,0.000048605714,0.00009107907,0.00002062713],"domain_scores_gemma":[0.9991455,0.00032867238,0.00016354967,0.000030816827,0.0002704426,0.00006090616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009673145,0.0013338419,0.002787876,0.0047286586,0.00032868012,0.0011599085,0.0010893999,0.0016817428,0.0027955023],"category_scores_gemma":[0.0017672697,0.0004655165,0.0005413618,0.0048735603,0.0007980973,0.0023297223,0.00069162325,0.0013960175,0.0026651768],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012926388,0.00008346166,0.0002873983,0.013692209,0.00013526624,0.00082366634,0.00004391691,0.00029589335,0.0010292206,0.0009013451,0.034527272,0.94805104],"study_design_scores_gemma":[0.00009451534,0.00019930415,0.0027345528,0.0067012813,0.00062889827,0.010047662,0.00010743217,0.00020914144,0.0007167498,0.0019554899,0.97655565,0.000049313505],"about_ca_topic_score_codex":0.0022064585,"about_ca_topic_score_gemma":0.004677212,"teacher_disagreement_score":0.0047286586,"about_ca_system_score_codex":0.000672473,"about_ca_system_score_gemma":0.0018873608,"threshold_uncertainty_score":0.00935185},"labels":[],"label_agreement":null},{"id":"W2106440018","doi":"10.1109/iccv.2007.4409086","title":"On the Differential Geometry of 3D Flow Patterns: Generalized Helicoids and Diffusion MRI Analysis","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Curvature; Geometry; Helicoid; Differential geometry; Differential (mechanical device); Geometric analysis; Computer graphics; Computer science; Mathematics; Mathematical analysis; Artificial intelligence; Differential equation; Physics; Ordinary differential equation","score_opus":0.032409438905135486,"score_gpt":0.3280144220940771,"score_spread":0.29560498318894163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106440018","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13132003,0.00048116755,0.8653838,0.00028161163,0.0000244183,0.00003765235,0.00012703211,0.00012466825,0.0022197673],"genre_scores_gemma":[0.8544776,0.0010844906,0.14085425,0.00006122594,0.00010091795,0.000054458913,0.00023354198,0.000090421636,0.003043073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998646,0.00003796751,0.0000073944398,0.000032943175,0.000041351967,0.000015746278],"domain_scores_gemma":[0.9994715,0.00017087927,0.00013110593,0.00007258138,0.000091659625,0.00006235866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033428686,0.00045772718,0.0003203435,0.0018434199,0.0003039116,0.0008119267,0.00031768926,0.00041206626,0.0009967871],"category_scores_gemma":[0.0016033608,0.00018103552,0.00040788387,0.0008838607,0.0015238784,0.0013438873,0.00062586664,0.0003929422,0.0001983551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000714016,0.000024601763,0.002844,0.00011747515,0.000026971426,0.00047492987,0.00072867074,0.17925677,0.036725488,0.6836738,0.001494895,0.09456091],"study_design_scores_gemma":[0.0000063179527,0.000048680646,0.0029174427,0.000018923072,0.0000066252446,0.0004249994,0.00010592983,0.6962636,0.0037616575,0.29158124,0.0048276065,0.00003703573],"about_ca_topic_score_codex":0.0015467627,"about_ca_topic_score_gemma":0.0008516581,"teacher_disagreement_score":0.0018434199,"about_ca_system_score_codex":0.00049261743,"about_ca_system_score_gemma":0.00021489615,"threshold_uncertainty_score":0.0035741925},"labels":[],"label_agreement":null},{"id":"W2106610784","doi":"10.1093/schbul/sbr193","title":"The Incidence and Nature of Cerebellar Findings in Schizophrenia: A Quantitative Review of fMRI Literature","year":2012,"lang":"en","type":"review","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Institut universitaire en santé mentale de Montréal; Cegep de Sainte Foy; Home and Community Care Support Services; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Cerebellum; Neuroscience; Schizophrenia (object-oriented programming); Neuroimaging; Psychology; Functional magnetic resonance imaging; Functional neuroimaging; Cognition; Magnetic resonance imaging; Cerebellar hemisphere; Audiology; Medicine; Psychiatry; Radiology","score_opus":0.04360327085431317,"score_gpt":0.3700997363761323,"score_spread":0.32649646552181916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106610784","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013014226,0.9854188,0.00020502917,0.00025887974,0.00003426737,0.0000209509,0.00061275467,0.000009642043,0.0004255482],"genre_scores_gemma":[0.08289248,0.9151367,0.001061947,0.00017276722,0.0000840334,0.00004541159,0.0004937326,0.000010324802,0.0001026207],"study_design_codex":"design_other","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99755293,0.00050610414,0.0011048801,0.0003867812,0.0003829492,0.000066436],"domain_scores_gemma":[0.98028755,0.01271196,0.0050011636,0.00027637606,0.0015440282,0.00017891773],"candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.003841011,0.000625218,0.0014497732,0.034003858,0.00037697662,0.001501436,0.00071835524,0.00055493804,0.0013573173],"category_scores_gemma":[0.013908886,0.0004920175,0.0016256665,0.0249245,0.00088569726,0.0019249235,0.0008769258,0.00032709903,0.00021475172],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006254118,0.00003906781,0.064281106,0.35001016,0.0068238,0.0014632919,0.002230105,0.0003678879,0.004625327,0.0007683539,0.004326331,0.56443924],"study_design_scores_gemma":[0.000144988,0.0005371201,0.53658724,0.27225402,0.053677335,0.020653743,0.0049150814,0.00049196376,0.0033201887,0.0015582342,0.1056329,0.00022719304],"about_ca_topic_score_codex":0.003376237,"about_ca_topic_score_gemma":0.0085225655,"teacher_disagreement_score":0.996159,"about_ca_system_score_codex":0.0010736908,"about_ca_system_score_gemma":0.0022918547,"threshold_uncertainty_score":0.020313442},"labels":[],"label_agreement":null},{"id":"W2107019320","doi":"10.3174/ajnr.a1985","title":"Alteration of Human Fetal Subplate Layer and Intermediate Zone During Normal Development on MR and Diffusion Tensor Imaging","year":2010,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Subplate; White matter; Diffusion MRI; Intensity (physics); Medicine; Magnetic resonance imaging; Anatomy; Pathology; Cerebral cortex; Optics; Radiology; Internal medicine; Physics","score_opus":0.020538207827025694,"score_gpt":0.3140670428816063,"score_spread":0.2935288350545806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107019320","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987513,0.00046368942,0.00044641722,0.000009298004,0.0000024282788,0.0000041841536,0.000061984654,0.000009474819,0.00025135025],"genre_scores_gemma":[0.99873906,0.00021730557,0.0006618909,0.0000055123387,0.0000021427281,0.000005551214,0.00009136372,0.0000035997982,0.0002735784],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999012,0.000014907072,0.000010188752,0.000028821516,0.000030382334,0.000014552643],"domain_scores_gemma":[0.9996606,0.000051783216,0.00015418475,0.000037266407,0.00006204475,0.000034054574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002519195,0.00021501954,0.00011388388,0.00050737464,0.00011008747,0.00018535153,0.00013553372,0.00016814648,0.0007723826],"category_scores_gemma":[0.0008259345,0.00015133891,0.00010206112,0.00012109904,0.00029377727,0.00018035495,0.00014818156,0.00014629815,0.000158382],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020928239,0.000055855297,0.24507298,0.00013416621,0.00007231474,0.0040294672,0.00062793994,0.00038529575,0.7253308,0.00020612717,0.00018027371,0.021811884],"study_design_scores_gemma":[0.000011058645,0.0004028233,0.9264805,0.000017629549,0.000048028414,0.009173197,0.00018794222,0.0005433068,0.0623161,0.00010325743,0.0007042767,0.000011804177],"about_ca_topic_score_codex":0.0017419105,"about_ca_topic_score_gemma":0.0014851311,"teacher_disagreement_score":0.0017419105,"about_ca_system_score_codex":0.00022919706,"about_ca_system_score_gemma":0.00012885012,"threshold_uncertainty_score":0.0034635067},"labels":[],"label_agreement":null},{"id":"W2107294026","doi":"10.1016/j.neuroimage.2005.03.016","title":"Diffusion tensor imaging of neurodevelopment in children and young adults","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":355,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Splenium; Corpus callosum; Diffusion MRI; Caudate nucleus; Effective diffusion coefficient; Psychology; Magnetic resonance imaging; Putamen; Young adult; Internal capsule; Medicine; White matter; Nuclear magnetic resonance; Neuroscience; Developmental psychology; Radiology; Physics","score_opus":0.015803536626992305,"score_gpt":0.2876446576296194,"score_spread":0.2718411210026271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107294026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99039197,0.0064520678,0.000094679934,0.00033014352,0.000019800827,0.000014570338,0.0009080908,0.000009398107,0.0017793685],"genre_scores_gemma":[0.990378,0.0076721893,0.00048953464,0.00006399253,0.000022487602,0.000025573207,0.0006816339,0.0000046589817,0.0006620034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981564,0.00002960871,0.000036339745,0.00002685424,0.000050599705,0.000040926123],"domain_scores_gemma":[0.9992803,0.00012646332,0.00027095023,0.000021880332,0.0001898363,0.000110457164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066135445,0.00037475865,0.00042014648,0.0015782965,0.00043339282,0.0006072564,0.0002725974,0.00043980288,0.0006199813],"category_scores_gemma":[0.0030154926,0.00020911763,0.00027469787,0.0010255885,0.00037907186,0.00084251387,0.00043591345,0.00047961008,0.00018863335],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007930672,0.000051597406,0.9798989,0.00008778169,0.000055414886,0.0010503725,0.00076599396,0.0000904759,0.00063760736,0.00017170227,0.0010521626,0.016058732],"study_design_scores_gemma":[0.0000021532355,0.00005258134,0.99676967,0.000043498894,0.000024004486,0.0014926055,0.00050363666,0.000047640882,0.00024823492,0.00014284955,0.000669622,0.0000035888781],"about_ca_topic_score_codex":0.032172624,"about_ca_topic_score_gemma":0.040205903,"teacher_disagreement_score":0.032172624,"about_ca_system_score_codex":0.0007443708,"about_ca_system_score_gemma":0.0011858513,"threshold_uncertainty_score":0.063970685},"labels":[],"label_agreement":null},{"id":"W2107480447","doi":"10.1007/s11538-010-9589-1","title":"Restricted Diffusion in Cellular Media: (1+1)-Dimensional Model","year":2010,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Diffusion; Space (punctuation); Membrane; Biological system; Eigenfunction; Cellular compartment; Physics; Biophysics; Chemistry; Cell; Computer science; Biology; Eigenvalues and eigenvectors; Quantum mechanics","score_opus":0.04201676429705043,"score_gpt":0.3194109647560132,"score_spread":0.2773942004589628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107480447","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09445331,0.009480739,0.84040177,0.011262742,0.001191193,0.00024449118,0.0017266952,0.0007544912,0.040484574],"genre_scores_gemma":[0.8406805,0.01047183,0.06929201,0.002088242,0.001945765,0.0006777302,0.0011984168,0.00037215438,0.07327337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987425,0.00049457955,0.000068465575,0.00030321485,0.00021634313,0.00017496107],"domain_scores_gemma":[0.99593794,0.0018935172,0.000743639,0.0002980424,0.0006485962,0.0004781755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019279921,0.002384338,0.004374025,0.0031136554,0.0013038055,0.0042284243,0.0053996355,0.009944997,0.0038868685],"category_scores_gemma":[0.007279285,0.0015546511,0.0021161565,0.003064792,0.005128814,0.0064479928,0.0039085364,0.0036684093,0.0014918206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112924856,0.00013309556,0.0011331809,0.00037144232,0.000091114,0.00066443306,0.0002466247,0.5299415,0.0027844363,0.45550537,0.004255191,0.0047607133],"study_design_scores_gemma":[0.00003366814,0.000026025853,0.00016313636,0.000017666105,0.00002958358,0.0001816001,0.000024817566,0.9386226,0.000121864505,0.05980208,0.0009261711,0.00005066618],"about_ca_topic_score_codex":0.009941927,"about_ca_topic_score_gemma":0.0054284595,"teacher_disagreement_score":0.009944997,"about_ca_system_score_codex":0.002113003,"about_ca_system_score_gemma":0.0017356623,"threshold_uncertainty_score":0.019768119},"labels":[],"label_agreement":null},{"id":"W2107996484","doi":"10.1109/iembs.2006.260314","title":"A High-Resolution Anisotropic Finite-Volume Head Model for EEG Source Analysis","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Head (geology); Finite volume method; Electroencephalography; Source model; Computer science; Volume (thermodynamics); Geology; Mechanics; Physics; Theoretical computer science; Medicine","score_opus":0.05098986032001237,"score_gpt":0.33408588071218825,"score_spread":0.2830960203921759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107996484","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017228805,0.00012245601,0.9954324,0.00015004011,0.000040808725,0.00003245501,0.00012107195,0.00019978837,0.002178275],"genre_scores_gemma":[0.1829772,0.0011459283,0.80270225,0.0002246333,0.00013408044,0.0005301096,0.00080189825,0.00024693483,0.011237002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984634,0.00004377621,0.000010158291,0.000017254608,0.00007397764,0.0000084448675],"domain_scores_gemma":[0.9998379,0.00006426475,0.000020222089,0.000025940879,0.00004323185,0.000008356613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025495124,0.00036669528,0.00036441963,0.00036061616,0.00026409377,0.00053333206,0.0010344874,0.000976336,0.0024053345],"category_scores_gemma":[0.0011014664,0.00030005514,0.00061213673,0.00044207898,0.0002852347,0.00057715195,0.000479115,0.0007091046,0.0010637403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004188681,0.00003399841,0.00045046827,0.00014211633,0.00002589059,0.00040165902,0.00016097687,0.8046385,0.029027093,0.08226897,0.006596423,0.076212086],"study_design_scores_gemma":[0.0000059579174,0.000012548938,0.00012210212,0.000008539532,0.000006351455,0.00019010478,0.00001185348,0.97744715,0.0015809276,0.009333618,0.0112686,0.000012258568],"about_ca_topic_score_codex":0.0025073458,"about_ca_topic_score_gemma":0.0030263052,"teacher_disagreement_score":0.0025073458,"about_ca_system_score_codex":0.0002818916,"about_ca_system_score_gemma":0.0007467655,"threshold_uncertainty_score":0.008046687},"labels":[],"label_agreement":null},{"id":"W2108343092","doi":"10.1371/journal.pone.0073692","title":"Network Dynamics Underlying Speed-Accuracy Trade-Offs in Response to Errors","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health","keywords":"Diffusion MRI; Fractional anisotropy; Anterior cingulate cortex; Neuroscience; Reciprocal; Computer science; Intraparietal sulcus; Functional magnetic resonance imaging; Psychology; Medicine; Cognition; Magnetic resonance imaging","score_opus":0.1641656758659303,"score_gpt":0.35369675644844095,"score_spread":0.18953108058251064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108343092","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889149,0.00013433279,0.009465556,0.00013530972,0.000008619872,0.00001691243,0.00012806908,0.000068506844,0.0011278342],"genre_scores_gemma":[0.99827003,0.000040528776,0.0012582433,0.000011461358,0.000004625162,0.00001212053,0.000078663565,0.000013728599,0.0003105818],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999605,0.000093032766,0.000029223627,0.00012456653,0.00008322949,0.000065085726],"domain_scores_gemma":[0.997618,0.0009644719,0.0007875736,0.00019095195,0.00026914856,0.00016986938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007440758,0.00024434997,0.00025295248,0.0004930736,0.00015576922,0.00068955665,0.000289328,0.0003334733,0.0009851565],"category_scores_gemma":[0.008384068,0.00025665798,0.0002089831,0.00025886463,0.0003357785,0.0006622176,0.00047581122,0.00038202447,0.00014317888],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026632647,0.00039605514,0.38062277,0.00020192224,0.00057458255,0.001036491,0.002471467,0.13406166,0.3236335,0.009326565,0.0018877605,0.14312394],"study_design_scores_gemma":[0.00005627718,0.00025175157,0.76684487,0.000026387605,0.00007565112,0.00044799436,0.00025488852,0.20494018,0.01105659,0.015336997,0.0006511575,0.000057296264],"about_ca_topic_score_codex":0.0026985148,"about_ca_topic_score_gemma":0.0026900494,"teacher_disagreement_score":0.0026985148,"about_ca_system_score_codex":0.00041263996,"about_ca_system_score_gemma":0.0002475605,"threshold_uncertainty_score":0.0053656697},"labels":[],"label_agreement":null},{"id":"W2108677211","doi":"10.1215/15228517-2006-002","title":"Diffusion tensor imaging of white matter after cranial radiation in children for medulloblastoma: Correlation with IQ","year":2006,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":192,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; SickKids Foundation; Hospital for Sick Children; McMaster University; University of Toronto","funders":"","keywords":"White matter; Fractional anisotropy; Internal capsule; Diffusion MRI; Corpus callosum; Effective diffusion coefficient; Nuclear medicine; Medicine; Intelligence quotient; Correlation; Psychology; Magnetic resonance imaging; Pathology; Radiology; Neuroscience; Cognition","score_opus":0.008528242953704352,"score_gpt":0.28372072296481327,"score_spread":0.2751924800111089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108677211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996055,0.00011352393,0.000042743148,0.000019829298,0.0000011220775,0.000002249103,0.000048591584,0.000004133043,0.00016243805],"genre_scores_gemma":[0.99968994,0.00009215733,0.0000705907,0.000004748014,0.000002576996,0.0000024039284,0.00009414495,0.0000021404771,0.000041319083],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979323,0.000039621154,0.000030799594,0.00003852958,0.00005761535,0.000040360326],"domain_scores_gemma":[0.9987068,0.00015220964,0.0008521207,0.000049388196,0.00012500094,0.00011453176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003088167,0.00028975503,0.0002504531,0.0009009977,0.00021178093,0.00029412564,0.00021187385,0.0002033339,0.00041547118],"category_scores_gemma":[0.0027357568,0.0001648385,0.00022249887,0.0005012758,0.00034837003,0.00027581688,0.00027592762,0.0003450982,0.00008710223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006524069,0.000015430089,0.99630105,0.000007163337,0.000029985755,0.00027291343,0.00013711044,0.00009674417,0.00096597767,0.000013978078,0.000041393836,0.002053004],"study_design_scores_gemma":[0.0000019616662,0.00007092214,0.99860543,0.0000026649006,0.000015444393,0.00078923587,0.000080259466,0.000115921786,0.00024302132,0.0000085343545,0.000064816275,0.0000018668682],"about_ca_topic_score_codex":0.008136475,"about_ca_topic_score_gemma":0.006479058,"teacher_disagreement_score":0.008136475,"about_ca_system_score_codex":0.00035519912,"about_ca_system_score_gemma":0.00023300895,"threshold_uncertainty_score":0.01617825},"labels":[],"label_agreement":null},{"id":"W2109181684","doi":"10.1523/jneurosci.5302-10.2011","title":"Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1238,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Fondation pour la Recherche Médicale","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Brain size; Longitudinal study; Brain development; Psychology; Human brain; Neuroscience; Anatomy; Physiology; Internal medicine; Biology; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.10227087953948731,"score_gpt":0.3613307277025508,"score_spread":0.2590598481630635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109181684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975592,0.00087084103,0.00074627233,0.000060668182,0.0000022749862,0.0000052286896,0.000274969,0.000027701688,0.00045283826],"genre_scores_gemma":[0.9972608,0.0007154906,0.0011747727,0.000014746661,0.0000039292736,0.000008583582,0.00041224365,0.000008079216,0.0004012982],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980503,0.000038016045,0.000015678332,0.00007126548,0.000042339245,0.000027618386],"domain_scores_gemma":[0.99888283,0.00013925125,0.00054834073,0.00012686265,0.00021178434,0.000090923975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006501473,0.00016746916,0.00016791992,0.000535538,0.00037970298,0.0004294055,0.00014197287,0.00019741264,0.00070318126],"category_scores_gemma":[0.002174935,0.00021230093,0.00013645896,0.0004066504,0.0002851972,0.0006004886,0.0003449533,0.0002808186,0.00022839865],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011928575,0.000031304236,0.9609667,0.00003268333,0.00006957624,0.00014564188,0.0007627684,0.00024423152,0.006293596,0.00015888296,0.00022926388,0.030946147],"study_design_scores_gemma":[0.0000011633281,0.00007974701,0.9981279,0.000007700802,0.0000140750435,0.00031213198,0.000106230276,0.00012880492,0.00062604214,0.00009670606,0.0004960616,0.000003381227],"about_ca_topic_score_codex":0.007585683,"about_ca_topic_score_gemma":0.015026742,"teacher_disagreement_score":0.007585683,"about_ca_system_score_codex":0.00023239572,"about_ca_system_score_gemma":0.00028838063,"threshold_uncertainty_score":0.015083015},"labels":[],"label_agreement":null},{"id":"W2109345578","doi":"10.3389/fnins.2015.00396","title":"Assessing intracortical myelin in the living human brain using myelinated cortical thickness","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McMaster University; National Alliance for Research on Schizophrenia and Depression; Brain and Behavior Research Foundation","keywords":"Cortex (anatomy); Myelin; Neuroscience; Cerebral cortex; Magnetic resonance imaging; Gyrus; Medicine; Anatomy; Psychology; Central nervous system; Radiology","score_opus":0.1664601240308233,"score_gpt":0.42879533086726257,"score_spread":0.2623352068364393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109345578","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9255536,0.0034771103,0.06525812,0.00008303731,0.000034071556,0.000077328456,0.0011811107,0.00062919507,0.0037065044],"genre_scores_gemma":[0.95720404,0.0020768752,0.039078355,0.000045285058,0.000021942576,0.00005896779,0.0003301042,0.000093618306,0.0010908262],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998204,0.000047121535,0.000015522919,0.000051006344,0.00005179046,0.000014179817],"domain_scores_gemma":[0.99969745,0.0000836616,0.00009511417,0.000051085644,0.000048588226,0.0000240556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049857557,0.000408991,0.00018819662,0.0019741086,0.00026939568,0.0006160452,0.00027848702,0.00033173565,0.0015637118],"category_scores_gemma":[0.0008537836,0.00020783475,0.00016544267,0.00088990066,0.00033979432,0.00048218307,0.0003724415,0.00020172953,0.00026902888],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010424588,0.000054894783,0.07540673,0.000490336,0.0005791764,0.0008675554,0.0011191115,0.0030831061,0.7806872,0.0010929331,0.00067760964,0.13489902],"study_design_scores_gemma":[0.00003771538,0.0005742116,0.7413372,0.00010204717,0.00037354618,0.008774502,0.0008533006,0.012155648,0.22831802,0.003005952,0.0043537715,0.00011415548],"about_ca_topic_score_codex":0.0017752555,"about_ca_topic_score_gemma":0.0037041316,"teacher_disagreement_score":0.0019741086,"about_ca_system_score_codex":0.00012136572,"about_ca_system_score_gemma":0.00018395393,"threshold_uncertainty_score":0.0052310824},"labels":[],"label_agreement":null},{"id":"W2110036421","doi":"10.1093/cercor/bhs188","title":"Oligodendrocyte Genes, White Matter Tract Integrity, and Cognition in Schizophrenia","year":2012,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"White matter; Oligodendrocyte; Schizophrenia (object-oriented programming); Neuroscience; Cognition; Psychology; Biology; Medicine; Magnetic resonance imaging; Psychiatry; Central nervous system; Myelin","score_opus":0.053820338088351544,"score_gpt":0.33025606637381033,"score_spread":0.2764357282854588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110036421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997534,0.00007882435,0.000051149927,0.000009445522,5.5166083e-7,0.0000011992084,0.00004572265,0.0000013760142,0.00005829585],"genre_scores_gemma":[0.9996562,0.000063222724,0.00013217525,0.000004352494,0.0000013005101,0.0000017318508,0.00006933745,0.0000017757462,0.000069993795],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998486,0.000038617796,0.00002117419,0.00003277975,0.00003781593,0.000020942376],"domain_scores_gemma":[0.9992453,0.00016911485,0.00035236176,0.00006210729,0.000055896904,0.00011535073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052474416,0.00036876765,0.00029835245,0.0008028479,0.0003276861,0.0003429544,0.0001412258,0.00024394541,0.0010053775],"category_scores_gemma":[0.0015406772,0.00018359821,0.00021459431,0.00051111635,0.000541019,0.00020398734,0.00043712227,0.00024244863,0.00010151777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013580553,0.000079607744,0.97937155,0.000031055642,0.00020405797,0.00024303954,0.00037670875,0.00041572028,0.011724648,0.00009145955,0.000048917947,0.0060551297],"study_design_scores_gemma":[0.000007836707,0.00010061874,0.9988431,0.0000031196682,0.000033641205,0.0001934078,0.00005609085,0.00022947208,0.00039537094,0.00009942412,0.000034230605,0.0000037792292],"about_ca_topic_score_codex":0.0073941792,"about_ca_topic_score_gemma":0.010425803,"teacher_disagreement_score":0.0073941792,"about_ca_system_score_codex":0.00031579466,"about_ca_system_score_gemma":0.00033783817,"threshold_uncertainty_score":0.0147022605},"labels":[],"label_agreement":null},{"id":"W2110450380","doi":"10.1017/s1355617713001148","title":"Relations between White Matter Maturation and Reaction Time in Childhood","year":2013,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto; Hospital for Sick Children","funders":"National Cancer Institute","keywords":"White matter; White (mutation); Psychology; Developmental psychology; Cognitive science; Medicine; Biology; Magnetic resonance imaging; Genetics; Radiology","score_opus":0.028634120435631686,"score_gpt":0.3185484023873168,"score_spread":0.2899142819516851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110450380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99854374,0.00042532908,0.00020601366,0.000030548043,0.000004577544,0.000003329888,0.0001843383,0.00002118887,0.0005810455],"genre_scores_gemma":[0.99867463,0.00032988787,0.00037290307,0.00000943164,0.0000043658297,0.000006605756,0.00023944552,0.00001163379,0.00035104094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961406,0.000057970905,0.00004151834,0.00011292648,0.000090358066,0.00008328304],"domain_scores_gemma":[0.9962811,0.00079575746,0.0020156708,0.0002142271,0.00040537986,0.0002878889],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064666936,0.00039713967,0.00024587414,0.0010668921,0.00025209296,0.000533311,0.00021148128,0.00036456922,0.0011849626],"category_scores_gemma":[0.0050561805,0.0002564831,0.00027970385,0.00055527134,0.0006576706,0.00040219203,0.00032074106,0.00044606248,0.0002718258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006755371,0.00008639793,0.9709537,0.000056789573,0.000080510996,0.00073488615,0.0009912192,0.0006170338,0.011569086,0.0003158223,0.00024994253,0.013669038],"study_design_scores_gemma":[0.0000020777588,0.000083998944,0.99766076,0.00000791285,0.000012246876,0.00044635843,0.00007139273,0.00011653572,0.0013178926,0.00009195667,0.00018528641,0.0000035169028],"about_ca_topic_score_codex":0.008132629,"about_ca_topic_score_gemma":0.0061729723,"teacher_disagreement_score":0.008132629,"about_ca_system_score_codex":0.00047206762,"about_ca_system_score_gemma":0.00038045555,"threshold_uncertainty_score":0.01617062},"labels":[],"label_agreement":null},{"id":"W2110484413","doi":"10.1007/978-3-540-85988-8_17","title":"Streamline Flows for White Matter Fibre Pathway Segmentation in Diffusion MRI","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Voxel; Tractography; Computer science; Segmentation; Diffusion MRI; Artificial intelligence; White matter; Pairwise comparison; Consistency (knowledge bases); Algorithm; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging","score_opus":0.031290538802596725,"score_gpt":0.31535869955669005,"score_spread":0.2840681607540933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110484413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009302349,0.00027862954,0.98778766,0.000106997155,0.00002940276,0.00007802396,0.00022563418,0.0019155253,0.0002758034],"genre_scores_gemma":[0.081716575,0.0006108924,0.9148522,0.00003719739,0.00007563724,0.0001712105,0.00043447802,0.00056647055,0.0015353381],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976236,0.000065819615,0.000018433942,0.00005424686,0.00007046385,0.000028677121],"domain_scores_gemma":[0.9978656,0.0012927274,0.000177288,0.00013364661,0.0004129447,0.00011794992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015643047,0.0012472318,0.001134343,0.0033956135,0.0010638842,0.0019137347,0.0011762853,0.0017358771,0.0041619614],"category_scores_gemma":[0.0046441555,0.0010511867,0.0010286405,0.0020930008,0.0007153176,0.0019675358,0.0010649784,0.0014557268,0.0013255582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000770245,0.00014636615,0.002432035,0.00041339052,0.0001024809,0.00017301216,0.00042400623,0.20592485,0.026207624,0.022231814,0.010044083,0.7311301],"study_design_scores_gemma":[0.000019631556,0.000026842652,0.00026025614,0.000020043282,0.000012125556,0.000047534046,0.000022834462,0.98314637,0.006735139,0.008111931,0.0015815697,0.000015678412],"about_ca_topic_score_codex":0.012374014,"about_ca_topic_score_gemma":0.010201184,"teacher_disagreement_score":0.012374014,"about_ca_system_score_codex":0.0010743334,"about_ca_system_score_gemma":0.0021235875,"threshold_uncertainty_score":0.024603963},"labels":[],"label_agreement":null},{"id":"W2111438395","doi":"10.1016/j.clinimag.2004.08.001","title":"Diffusion and magnetization transfer MRI of brain infarct, infection, and tumor in children","year":2005,"lang":"en","type":"article","venue":"Clinical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre","funders":"","keywords":"Medicine; Magnetization transfer; Diffusion MRI; Parenchyma; Differential diagnosis; Magnetic resonance imaging; Pathology; Brain tumor; Effective diffusion coefficient; Radiology; Nuclear medicine","score_opus":0.03196621140562356,"score_gpt":0.3844727147642563,"score_spread":0.35250650335863276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111438395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99583745,0.0014751765,0.00021710446,0.00022804269,0.000013435972,0.000016220774,0.00014395274,0.000009002875,0.0020597235],"genre_scores_gemma":[0.997718,0.0013946138,0.0003515485,0.0000579603,0.000039047347,0.000015827476,0.000105696134,0.000008803716,0.0003086127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997162,0.00005958605,0.000040061946,0.000041583287,0.000042647996,0.0000998582],"domain_scores_gemma":[0.9993222,0.000210577,0.00020681052,0.000031714633,0.00009732075,0.00013141641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007061051,0.0005699524,0.0005064375,0.0021002067,0.0005989048,0.0004340254,0.00053469284,0.00090172986,0.00091202004],"category_scores_gemma":[0.0030894482,0.0005755792,0.00039100397,0.0009807439,0.0012817029,0.0011325673,0.00044985802,0.0009386972,0.000204426],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014327412,0.0004794962,0.8796024,0.00030050866,0.00010957313,0.09036511,0.001247025,0.0015516466,0.0097582145,0.0016634137,0.001569996,0.011919845],"study_design_scores_gemma":[0.000083022205,0.00082755217,0.833579,0.00010718072,0.00013918264,0.15251511,0.0013556501,0.0015190142,0.007133746,0.00067588146,0.0020230068,0.00004164316],"about_ca_topic_score_codex":0.010303811,"about_ca_topic_score_gemma":0.007161351,"teacher_disagreement_score":0.010303811,"about_ca_system_score_codex":0.0010319203,"about_ca_system_score_gemma":0.0010096466,"threshold_uncertainty_score":0.020487726},"labels":[],"label_agreement":null},{"id":"W2111508341","doi":"10.1002/mrm.21277","title":"Regularized, fast, and robust analytical Q‐ball imaging","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":847,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften; McGill University","keywords":"Unit sphere; Regularization (linguistics); Spherical harmonics; Imaging phantom; Tikhonov regularization; Mathematics; Laplace transform; Mathematical analysis; Algorithm; Computer science; Inverse problem; Artificial intelligence; Physics; Optics","score_opus":0.05022523487800512,"score_gpt":0.3508908641564233,"score_spread":0.30066562927841817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111508341","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010594276,0.00004822894,0.998345,0.00008516662,0.0000108678705,0.000015755068,0.000011302931,0.0001419948,0.00028230392],"genre_scores_gemma":[0.04131925,0.00023052264,0.9563537,0.000096791184,0.00003417289,0.00009158196,0.0000791504,0.00013442253,0.0016604351],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994499,0.00015819872,0.000030421437,0.00007824955,0.00023898963,0.000044200457],"domain_scores_gemma":[0.9989492,0.0003684268,0.00019021354,0.00017393974,0.00026690416,0.000051335057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015602569,0.0009360924,0.00093414827,0.00083730614,0.00038989217,0.0012041907,0.0016138154,0.0015480304,0.0017626908],"category_scores_gemma":[0.0042990795,0.00064076716,0.0008197731,0.0006556988,0.0010742613,0.0014137048,0.0014881841,0.0010989101,0.0013955036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002182213,0.00011671387,0.0011392275,0.00049126375,0.00011830089,0.0005676366,0.0003414495,0.45275328,0.0982104,0.18120113,0.008049037,0.25679338],"study_design_scores_gemma":[0.000009499425,0.000028416569,0.00006587164,0.000008289181,0.00000548139,0.00020510236,0.000009521591,0.9799891,0.007305319,0.009603856,0.0027503362,0.00001919319],"about_ca_topic_score_codex":0.0011405895,"about_ca_topic_score_gemma":0.0009961724,"teacher_disagreement_score":0.0017626908,"about_ca_system_score_codex":0.00054990017,"about_ca_system_score_gemma":0.0011640798,"threshold_uncertainty_score":0.008251548},"labels":[],"label_agreement":null},{"id":"W2111552401","doi":"10.1016/j.neurobiolaging.2014.07.045","title":"Cortical surface biomarkers for predicting cognitive outcomes using group l2,1 norm","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Division of Biological Infrastructure; National Center for Research Resources; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; National Institutes of Health; U.S. National Library of Medicine; IXICO; Genentech Foundation; Servier; Eisai; Elan; Division of Information and Intelligent Systems; Northern California Institute for Research and Education; Pfizer; Biogen; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb Foundation; U.S. Department of Defense; Eli Lilly and Company; Roche; Merck; Alzheimer's Drug Discovery Foundation; National Institute on Aging; Alzheimer's Association; National Institute of Biomedical Imaging and Bioengineering; Takeda Pharmaceuticals North America; Canadian Institutes of Health Research; National Science Foundation","keywords":"Neuroimaging; Cognition; Predictive power; Feature selection; Cognitive psychology; Machine learning; Correlation; Artificial intelligence; Regression; Psychology; Computer science; Set (abstract data type); Neuroscience; Mathematics","score_opus":0.07321909421608658,"score_gpt":0.37643393259099434,"score_spread":0.30321483837490776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111552401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9766506,0.00032417767,0.016718296,0.00027009938,0.000063243984,0.00008999401,0.0020674614,0.00026055213,0.003555609],"genre_scores_gemma":[0.9909322,0.00011747941,0.006327813,0.00008030126,0.000046995418,0.00012728393,0.0013347616,0.000053570016,0.0009795756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991984,0.00022621066,0.000075751566,0.00020159774,0.00022324666,0.000074811294],"domain_scores_gemma":[0.9975672,0.00071069633,0.0005306015,0.00047877964,0.00053312746,0.00017961636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002864511,0.00093138125,0.0007479549,0.0016252857,0.0006161964,0.0019054535,0.0009154349,0.0012319906,0.0021270227],"category_scores_gemma":[0.01000336,0.00014843483,0.0004579131,0.0009641631,0.00079939124,0.0012942497,0.0011810631,0.00072099536,0.000677838],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033139992,0.00057989993,0.84083086,0.00018532928,0.00072499213,0.00037871551,0.0007427743,0.005850038,0.01534525,0.0032949646,0.0050526666,0.12370059],"study_design_scores_gemma":[0.000121681784,0.0018280322,0.922049,0.00008629048,0.0003630539,0.0009686871,0.0010547898,0.039047427,0.011137551,0.020186547,0.003035113,0.00012185516],"about_ca_topic_score_codex":0.004838457,"about_ca_topic_score_gemma":0.0061571104,"teacher_disagreement_score":0.004838457,"about_ca_system_score_codex":0.00051043986,"about_ca_system_score_gemma":0.00079508795,"threshold_uncertainty_score":0.015149176},"labels":[],"label_agreement":null},{"id":"W2111627180","doi":"10.1016/j.media.2009.01.004","title":"Directional functions for orientation distribution estimation","year":2009,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Spherical harmonics; Orientation (vector space); Interpolation (computer graphics); Spherical coordinate system; Computer science; Unit sphere; Tractography; Geodesic; Algorithm; Diffusion MRI; Artificial intelligence; Mathematics; Computer vision; Mathematical analysis; Geometry; Image (mathematics)","score_opus":0.03070482850914545,"score_gpt":0.3971433175471677,"score_spread":0.36643848903802223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111627180","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012011859,0.00017296159,0.99805486,0.000035077406,0.000013137028,0.000007456867,0.000081485494,0.00017940004,0.0002544709],"genre_scores_gemma":[0.072142474,0.0013517879,0.9216782,0.000081459206,0.000079271354,0.0001341448,0.0010188097,0.00042892736,0.0030849553],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995346,0.00019179707,0.0000285483,0.00007743717,0.00013558542,0.000031986852],"domain_scores_gemma":[0.9983785,0.0007590863,0.000119512806,0.00029150234,0.00039656562,0.00005483072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012867164,0.00090329914,0.0009020736,0.0014926383,0.00033728287,0.000975865,0.00087983214,0.0009391838,0.002629297],"category_scores_gemma":[0.0062585487,0.0006244655,0.0008951302,0.0017441298,0.00039967557,0.0010812423,0.0008020866,0.0012610244,0.002041106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002514917,0.000094486284,0.0013740538,0.00022811112,0.000114811904,0.00009391188,0.00008325886,0.1382952,0.024782408,0.06703845,0.010133981,0.7575098],"study_design_scores_gemma":[0.00001780756,0.000029746692,0.0010039897,0.000040037598,0.000047759324,0.00019455471,0.00002541537,0.9546271,0.008013881,0.027324704,0.008642383,0.00003254652],"about_ca_topic_score_codex":0.0040433067,"about_ca_topic_score_gemma":0.0034670278,"teacher_disagreement_score":0.0040433067,"about_ca_system_score_codex":0.00040096047,"about_ca_system_score_gemma":0.0008541372,"threshold_uncertainty_score":0.008795917},"labels":[],"label_agreement":null},{"id":"W2112055941","doi":"10.1016/s0197-4580(03)00121-0","title":"Linear width of the medial temporal lobe can discriminate Alzheimer’s disease from normal aging: the Sunnybrook Dementia Study","year":2003,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"Ontario Mental Health Foundation","keywords":"Temporal lobe; Alzheimer's disease; Dementia; Parahippocampal gyrus; Audiology; Diagnostic accuracy; Psychology; Logistic regression; Hippocampus; Hippocampal sclerosis; Healthy aging; Medicine; Neuroscience; Disease; Nuclear medicine; Internal medicine; Gerontology; Epilepsy","score_opus":0.06874226434264971,"score_gpt":0.3363374797879582,"score_spread":0.2675952154453085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112055941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988361,0.00029058487,0.00006122145,0.000049829967,0.000013216276,0.000011768922,0.00012856767,0.0000036783563,0.0006049834],"genre_scores_gemma":[0.99899596,0.00016778364,0.00013640271,0.000042364692,0.000025566449,0.000011787374,0.00018217014,0.000007477093,0.00043050418],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996835,0.00008082228,0.000041463372,0.000069982896,0.00007864029,0.00004561584],"domain_scores_gemma":[0.9976246,0.0006154872,0.0007326088,0.00031189038,0.00025536964,0.00046012943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021688496,0.0012565426,0.0008121085,0.002126532,0.0011719413,0.0015178453,0.0008497864,0.0011131353,0.002306446],"category_scores_gemma":[0.00476813,0.00064753153,0.000621633,0.0011567986,0.0015082713,0.0018079473,0.0009210531,0.0009517881,0.0005194115],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006418335,0.00042090216,0.9790046,0.000060726863,0.00042029988,0.0013175585,0.0013873939,0.000115045754,0.0034426532,0.00020223726,0.0005723677,0.0066378815],"study_design_scores_gemma":[0.00015162815,0.00039355256,0.99573237,0.000012081975,0.00014160968,0.0014188472,0.0005948616,0.00026223445,0.0005838591,0.00028015065,0.00040582364,0.000023054818],"about_ca_topic_score_codex":0.015166284,"about_ca_topic_score_gemma":0.024681447,"teacher_disagreement_score":0.015166284,"about_ca_system_score_codex":0.00083748606,"about_ca_system_score_gemma":0.00083097693,"threshold_uncertainty_score":0.030156016},"labels":[],"label_agreement":null},{"id":"W2112080959","doi":"10.1016/j.jbiomech.2011.07.017","title":"Computational methods for quantifying in vivo muscle fascicle curvature from ultrasound images","year":2011,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fascicle; Curvature; In vivo; Ultrasound; Computer science; Biomedical engineering; Anatomy; Medicine; Biology; Radiology; Mathematics; Geometry","score_opus":0.1880739847070206,"score_gpt":0.44513381723734263,"score_spread":0.25705983253032205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112080959","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011671687,0.0001321116,0.98736274,0.00007942008,0.000015255695,0.000028843982,0.00004263462,0.0002881722,0.00037910292],"genre_scores_gemma":[0.3636385,0.0005389686,0.63228256,0.00010407727,0.00006377558,0.00024842148,0.00018932571,0.00033392664,0.0026004284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975055,0.00006191887,0.000020066069,0.000036600977,0.00011459177,0.00001626592],"domain_scores_gemma":[0.9987317,0.0008077995,0.00014017345,0.00010075347,0.00017943783,0.000040259376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007868384,0.0006523339,0.0007467605,0.0010312727,0.00039449832,0.0010329713,0.0010686768,0.0012762388,0.0013532072],"category_scores_gemma":[0.0037167983,0.00085293024,0.0007958482,0.0006014176,0.00061160105,0.00073641137,0.0010464491,0.0009691409,0.000454752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105542735,0.0000834911,0.0014347277,0.00019268267,0.00008850374,0.00012200524,0.00015949036,0.83228534,0.025038488,0.00794654,0.00086647854,0.13167682],"study_design_scores_gemma":[0.000002373212,0.0000046886335,0.00016710137,0.0000033286062,0.0000038847566,0.000025713469,0.000004572406,0.99807465,0.0007891282,0.000790622,0.00012944084,0.00000442268],"about_ca_topic_score_codex":0.005365329,"about_ca_topic_score_gemma":0.006958357,"teacher_disagreement_score":0.005365329,"about_ca_system_score_codex":0.0005052246,"about_ca_system_score_gemma":0.00089893065,"threshold_uncertainty_score":0.010668218},"labels":[],"label_agreement":null},{"id":"W2112277156","doi":"10.1371/journal.pone.0019698","title":"Negative Associations between Corpus Callosum Midsagittal Area and IQ in a Representative Sample of Healthy Children and Adolescents","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Douglas Mental Health University Institute; McGill University","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; University of California, Los Angeles; U.S. Department of Health and Human Services; Washington University in St. Louis; National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; University of Texas Health Science Center at Houston; McGill University","keywords":"Corpus callosum; Correlation; Intelligence quotient; Wechsler Adult Intelligence Scale; Psychology; Cohort; Population; Sample size determination; Developmental psychology; Audiology; Medicine; Cognition; Clinical psychology; Internal medicine; Psychiatry; Neuroscience","score_opus":0.1681180949783102,"score_gpt":0.34374196256376877,"score_spread":0.17562386758545856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112277156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99973375,0.000045059674,0.00003412524,0.000007732908,0.0000011097153,0.0000036210417,0.00007860157,0.0000017882702,0.000094320734],"genre_scores_gemma":[0.9995153,0.00005278474,0.00009323589,0.000011479694,0.0000060132347,0.000012919713,0.00022910154,0.0000029675662,0.000076223805],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961084,0.00011195396,0.000038226262,0.00011257954,0.000072776435,0.000053645093],"domain_scores_gemma":[0.9985815,0.00038970239,0.0004738496,0.00014345642,0.00018388928,0.00022748498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007251688,0.00039130083,0.00042822416,0.0015126142,0.00041595905,0.00049340085,0.00037175702,0.00036659092,0.0008810784],"category_scores_gemma":[0.0035836995,0.00030938254,0.00023464378,0.0006071748,0.00060567755,0.0003856748,0.00046866457,0.00040592617,0.00018855442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007789115,0.000025806527,0.9982993,0.0000058079277,0.000034341807,0.00010212608,0.00020805407,0.0000215361,0.0004673841,0.000017106171,0.000049334158,0.00069138984],"study_design_scores_gemma":[0.0000026069988,0.000042041338,0.99956566,0.0000012456376,0.000008742239,0.00015724922,0.00009761033,0.00004019478,0.000040546016,0.000007975538,0.000035014105,0.0000010059986],"about_ca_topic_score_codex":0.0069593354,"about_ca_topic_score_gemma":0.0069957743,"teacher_disagreement_score":0.0069593354,"about_ca_system_score_codex":0.00025821314,"about_ca_system_score_gemma":0.00022608877,"threshold_uncertainty_score":0.013837695},"labels":[],"label_agreement":null},{"id":"W2112492995","doi":"10.1093/brain/awv136","title":"Longitudinal changes in free-water within the substantia nigra of Parkinson’s disease","year":2015,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":220,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Movement Disorders","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke","keywords":"Substantia nigra; Parkinson's disease; Central nervous system disease; Internal medicine; Medicine; Psychology; Disease","score_opus":0.11004181301854678,"score_gpt":0.3445685490962396,"score_spread":0.2345267360776928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112492995","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99839324,0.00089888496,0.00029693873,0.000024390307,0.0000040019404,0.000006849684,0.00016019377,0.00001088357,0.000204576],"genre_scores_gemma":[0.9988971,0.00021733639,0.00029635624,0.000018248744,0.000004494013,0.0000072619296,0.00037182125,0.0000036531123,0.00018375626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973327,0.000051590396,0.000025475072,0.00009806695,0.00005753837,0.00003401226],"domain_scores_gemma":[0.9989672,0.00009245809,0.00048284503,0.00008589947,0.00023669202,0.00013480338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007232302,0.00025997392,0.00039468493,0.0005420284,0.00036496026,0.0005149669,0.0002511013,0.00040366486,0.000464753],"category_scores_gemma":[0.0012549112,0.00022313026,0.00032756088,0.00033405048,0.0002998744,0.0005596333,0.00039197245,0.00048025098,0.00011682372],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011638532,0.00014008144,0.9587316,0.000071011076,0.0005157746,0.00035571848,0.00064166624,0.0002257442,0.025713138,0.000047295183,0.00018667543,0.012207533],"study_design_scores_gemma":[0.0000061681003,0.00035887596,0.9978194,0.0000058429823,0.0000734556,0.00035751448,0.00008162983,0.00016017361,0.000880979,0.00006613876,0.00018254446,0.0000071949603],"about_ca_topic_score_codex":0.0046465495,"about_ca_topic_score_gemma":0.0068064714,"teacher_disagreement_score":0.0046465495,"about_ca_system_score_codex":0.00030190768,"about_ca_system_score_gemma":0.00017677716,"threshold_uncertainty_score":0.009238958},"labels":[],"label_agreement":null},{"id":"W2112875098","doi":"10.1002/mrm.20578","title":"Magnetic resonance imaging and mathematical modeling of progressive formalin fixation of the human brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Alberta Hospital; Alberta Hospital Edmonton","funders":"","keywords":"Fixation (population genetics); Magnetic resonance imaging; White matter; Nuclear magnetic resonance; Effective diffusion coefficient; T2 relaxation; Nuclear medicine; Human brain; Spin–lattice relaxation; Spin–spin relaxation; Diffusion imaging; Chemistry; Medicine; Physics; Radiology","score_opus":0.03702979127081108,"score_gpt":0.34881635186098475,"score_spread":0.3117865605901737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112875098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22795253,0.0021660738,0.76219636,0.0008554627,0.00007719209,0.00012668157,0.0005067021,0.00025830616,0.00586066],"genre_scores_gemma":[0.8755833,0.0032183854,0.11103975,0.00014721153,0.000055783406,0.0004136394,0.0003830259,0.00007011274,0.009088887],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999892,0.000032590153,0.000007727636,0.000025904432,0.000028663884,0.000013191468],"domain_scores_gemma":[0.9997254,0.00011856733,0.000089627174,0.000019008206,0.000037548052,0.000009811121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044264825,0.00062572886,0.0002866862,0.00046604016,0.00017807781,0.00045880114,0.0006034761,0.00076412596,0.000611876],"category_scores_gemma":[0.0012784646,0.0003016778,0.000642443,0.00027964704,0.0005398927,0.000506264,0.0003263172,0.00034778734,0.00023112555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012629433,0.000034649758,0.00081099354,0.00012932866,0.000034167715,0.00037730965,0.000093680945,0.9398056,0.038266946,0.013952945,0.00036322422,0.0060048765],"study_design_scores_gemma":[0.000019226725,0.00010647216,0.00092287804,0.000013889308,0.000024637837,0.00031079497,0.0000177887,0.9890454,0.0035895873,0.0047538728,0.0011770623,0.000018393115],"about_ca_topic_score_codex":0.0050397655,"about_ca_topic_score_gemma":0.0024927587,"teacher_disagreement_score":0.0050397655,"about_ca_system_score_codex":0.00063591904,"about_ca_system_score_gemma":0.0005299448,"threshold_uncertainty_score":0.010020852},"labels":[],"label_agreement":null},{"id":"W2113986781","doi":"10.1109/tmi.2007.907699","title":"Impact of an Improved Combination of Signals From Array Coils in Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"McGill University","keywords":"Diffusion MRI; Noise (video); Tensor (intrinsic definition); Computation; Noise reduction; SIGNAL (programming language); Diffusion; Signal-to-noise ratio (imaging); Anisotropic diffusion; Reduction (mathematics); Algorithm; Mathematics; Anisotropy; Computer science; Physics; Optics; Artificial intelligence; Image (mathematics); Magnetic resonance imaging; Geometry","score_opus":0.02657158651949947,"score_gpt":0.3661632366776523,"score_spread":0.33959165015815285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113986781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02798171,0.0009965764,0.9688854,0.00022787323,0.000108491164,0.00007110784,0.000058088306,0.0008799706,0.00079072715],"genre_scores_gemma":[0.08128995,0.0005068944,0.9165001,0.00014433508,0.00013883851,0.00009150964,0.0001705824,0.00024135,0.0009165366],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9971681,0.0010399403,0.0001738813,0.00043442895,0.0010768622,0.00010671465],"domain_scores_gemma":[0.9963534,0.0017662012,0.00036743504,0.0005069868,0.0008694023,0.0001364539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025505302,0.002171339,0.0013945352,0.0009485413,0.00044045487,0.0012656684,0.0010839006,0.0016499929,0.0022881243],"category_scores_gemma":[0.0083153695,0.0011774831,0.00076701783,0.001481355,0.0005579593,0.0025143202,0.00133042,0.0013258772,0.001268533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021465856,0.0003990867,0.002875893,0.0005937325,0.00039444322,0.00044843613,0.00015079563,0.0681783,0.381226,0.0037134762,0.0021564085,0.5377169],"study_design_scores_gemma":[0.0002447993,0.0020143026,0.008819325,0.00011348616,0.0007187631,0.0030690308,0.00004799142,0.5974852,0.3680163,0.0035716544,0.015652128,0.00024700098],"about_ca_topic_score_codex":0.0005856061,"about_ca_topic_score_gemma":0.0012430678,"teacher_disagreement_score":0.0025505302,"about_ca_system_score_codex":0.00031877722,"about_ca_system_score_gemma":0.0006790448,"threshold_uncertainty_score":0.01348865},"labels":[],"label_agreement":null},{"id":"W2114187925","doi":"10.1002/mrm.22292","title":"Tensor kernels for simultaneous fiber model estimation and tractography","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Diffusion MRI; Tractography; Orientation (vector space); Voxel; Tensor (intrinsic definition); Computer science; Fiber; Mathematics; Smoothness; Artificial intelligence; Biological system; Pattern recognition (psychology); Mathematical analysis; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.04190387894637874,"score_gpt":0.35813438768860023,"score_spread":0.31623050874222147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114187925","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00083795696,0.00006082538,0.9987552,0.000020385884,0.000009017369,0.0000058439123,0.000015065361,0.0001945204,0.0001011335],"genre_scores_gemma":[0.09784533,0.0005160673,0.89903384,0.00002966084,0.000086323445,0.000093608534,0.00023785801,0.00043522718,0.001722191],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985526,0.00042483487,0.00009743908,0.00028341237,0.0005340843,0.00010755715],"domain_scores_gemma":[0.9968612,0.0013416732,0.00045397764,0.00069096225,0.0005273294,0.00012493474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020967247,0.0013296244,0.0013200162,0.0016442656,0.00060974737,0.0016429862,0.0016757317,0.0012737372,0.0018343141],"category_scores_gemma":[0.007721471,0.0009629531,0.001538656,0.0016087061,0.0009815403,0.0032751972,0.0019289366,0.0019796519,0.0011638203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002264215,0.00008064465,0.0012424511,0.00023994537,0.00022077898,0.00021796027,0.00023469067,0.50392467,0.02836185,0.14707947,0.0030536514,0.31511754],"study_design_scores_gemma":[0.0000076255305,0.000022214863,0.0002062365,0.000008859718,0.000016394888,0.00007349543,0.000009107394,0.9728184,0.0025631506,0.021778893,0.0024710859,0.000024549405],"about_ca_topic_score_codex":0.006277373,"about_ca_topic_score_gemma":0.004858482,"teacher_disagreement_score":0.006277373,"about_ca_system_score_codex":0.0009796027,"about_ca_system_score_gemma":0.001585457,"threshold_uncertainty_score":0.012481689},"labels":[],"label_agreement":null},{"id":"W2114448824","doi":"10.1016/j.neuroimage.2013.05.022","title":"Diffusion imaging quality control via entropy of principal direction distribution","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; University of Washington","keywords":"Diffusion MRI; Computer science; Artificial intelligence; Voxel; Image quality; Entropy (arrow of time); Computer vision; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.03213628797906214,"score_gpt":0.33877909879691825,"score_spread":0.3066428108178561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114448824","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015015068,0.00025999724,0.98399854,0.00014969081,0.000023638537,0.000022608296,0.00006583064,0.0001905376,0.0002740478],"genre_scores_gemma":[0.52587694,0.0009023545,0.47018394,0.000108433764,0.00021891641,0.00011343318,0.0005521819,0.0004476514,0.0015961222],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974572,0.0009106585,0.00021778756,0.00050031365,0.00073227705,0.00018175517],"domain_scores_gemma":[0.9880922,0.0064991186,0.0012173698,0.0015140763,0.002295415,0.00038196964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0062326617,0.00094541366,0.0012359533,0.0020972146,0.00065775367,0.0025215573,0.0010447502,0.0009782917,0.001148744],"category_scores_gemma":[0.024015423,0.0006854466,0.000900804,0.0013691239,0.0015666166,0.003768123,0.0025121672,0.001974398,0.00031335224],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010482299,0.00021205432,0.008910809,0.000445024,0.0003989538,0.00017333846,0.00031004977,0.41600287,0.039615963,0.10290407,0.003066127,0.42691255],"study_design_scores_gemma":[0.000029140352,0.000096600095,0.002140492,0.000021859467,0.000035431607,0.000099867175,0.000019143397,0.9628703,0.008943384,0.025027698,0.00067454006,0.00004154627],"about_ca_topic_score_codex":0.002315137,"about_ca_topic_score_gemma":0.0025268232,"teacher_disagreement_score":0.0062326617,"about_ca_system_score_codex":0.0010330864,"about_ca_system_score_gemma":0.0023614538,"threshold_uncertainty_score":0.032961845},"labels":[],"label_agreement":null},{"id":"W2115624928","doi":"10.1371/journal.pone.0139897","title":"Myelination Is Associated with Processing Speed in Early Childhood: Preliminary Insights","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Corpus callosum; White matter; Occipital lobe; Magnetic resonance imaging; Myelin; Neuroimaging; Cerebellum; Working memory; Brain size; Neuroscience; Medicine; Audiology; Psychology; Central nervous system; Cognition; Radiology","score_opus":0.11173615169629753,"score_gpt":0.3044314697803395,"score_spread":0.192695318084042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115624928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989717,0.00033945116,0.00018872709,0.000020474363,0.0000014590291,0.000003633337,0.00018732074,0.000004325303,0.00028300667],"genre_scores_gemma":[0.99849236,0.00031829852,0.0006736593,0.000008387688,0.0000056237027,0.0000095811965,0.00019650857,0.0000049975624,0.0002905045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976915,0.000044098604,0.00001974852,0.00006765911,0.00004358692,0.00005570956],"domain_scores_gemma":[0.9982401,0.00043254116,0.0008243212,0.0001095026,0.00019224979,0.00020127842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069292786,0.0005266005,0.00029143618,0.0011874202,0.00026783193,0.0007031786,0.0003163449,0.00052823033,0.0012963915],"category_scores_gemma":[0.002280271,0.00028562112,0.00055997615,0.0010317955,0.00037432267,0.0004567176,0.00045136956,0.00045407476,0.00018630124],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004413193,0.00007436674,0.9880514,0.000045903973,0.000072377115,0.0003515068,0.0006747788,0.00017815274,0.0043434557,0.00012982883,0.00005915896,0.0055778436],"study_design_scores_gemma":[9.4795934e-7,0.00006819293,0.9989549,0.0000062599697,0.00002251356,0.00016594579,0.000119904056,0.00012079689,0.00041421296,0.000051050814,0.0000728405,0.0000024439018],"about_ca_topic_score_codex":0.0071636094,"about_ca_topic_score_gemma":0.007955425,"teacher_disagreement_score":0.0071636094,"about_ca_system_score_codex":0.0003424986,"about_ca_system_score_gemma":0.0005100345,"threshold_uncertainty_score":0.014243841},"labels":[],"label_agreement":null},{"id":"W2116129675","doi":"10.3389/fneur.2014.00216","title":"Beyond Crossing Fibers: Bootstrap Probabilistic Tractography Using Complex Subvoxel Fiber Geometries","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; Fiber; Computer science; Probabilistic logic; Artificial intelligence; Voxel; Fiber tract; Human Connectome Project; Pipeline (software); Pattern recognition (psychology); Magnetic resonance imaging; Neuroscience; Psychology; Functional connectivity; Materials science","score_opus":0.0797998667514669,"score_gpt":0.3461417527134482,"score_spread":0.26634188596198133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116129675","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019305987,0.00006704149,0.97991794,0.000059115402,0.0000035185863,0.000017215181,0.000039097195,0.00026127676,0.00032878807],"genre_scores_gemma":[0.4124942,0.00026287927,0.5859648,0.000040689665,0.000027498703,0.000079216545,0.000250641,0.00027382892,0.00060625654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993469,0.0002791954,0.000026815349,0.00011780056,0.00019046174,0.000038811842],"domain_scores_gemma":[0.9956989,0.0027095405,0.00049852446,0.000644764,0.000317097,0.00013116952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026131845,0.00057151204,0.0006257175,0.0010741184,0.0005093866,0.001076087,0.0010234427,0.0009914723,0.0009013626],"category_scores_gemma":[0.011782239,0.00053848553,0.0007143445,0.0008926892,0.0013346189,0.001758196,0.0015967498,0.0010631856,0.00040700822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017813887,0.000031472387,0.003916391,0.00010644099,0.00006958497,0.00035365895,0.00039992016,0.82310015,0.016231637,0.052019104,0.0007664135,0.10282696],"study_design_scores_gemma":[0.0000039156043,0.000021674163,0.00054874655,0.000008645774,0.000004573294,0.00007992523,0.0000105877925,0.9790172,0.0018458933,0.01795014,0.00049721025,0.000011598577],"about_ca_topic_score_codex":0.002753449,"about_ca_topic_score_gemma":0.0033694266,"teacher_disagreement_score":0.002753449,"about_ca_system_score_codex":0.0005966858,"about_ca_system_score_gemma":0.00086895295,"threshold_uncertainty_score":0.013819993},"labels":[],"label_agreement":null},{"id":"W2116280131","doi":"10.1109/iembs.2007.4352289","title":"Methodology for MR diffusion tensor imaging of the cat spinal cord","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Spinal cord; Diffusion MRI; Tractography; Echo-planar imaging; Magnetic resonance imaging; Lumbar Spinal Cord; Orientation (vector space); Nuclear magnetic resonance; Biomedical engineering; Materials science; Medicine; Radiology; Physics; Mathematics; Geometry","score_opus":0.22922831001119828,"score_gpt":0.4391316978561263,"score_spread":0.20990338784492804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116280131","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035963077,0.00017346248,0.99462116,0.000044790053,0.000037406648,0.0004113315,0.00010339384,0.00044750152,0.00056467194],"genre_scores_gemma":[0.008172914,0.00021223929,0.98937,0.000022914193,0.000006728734,0.0011717362,0.00013301522,0.0000749692,0.0008355092],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994661,0.00012451847,0.00006491503,0.00011261983,0.00019841375,0.00003348184],"domain_scores_gemma":[0.99939156,0.00009790805,0.00007567479,0.0001514763,0.00023730757,0.000046115652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019779294,0.0007875684,0.0005674203,0.0013538644,0.0006746298,0.0007983814,0.0009914445,0.0005861388,0.0066079763],"category_scores_gemma":[0.002011817,0.0006479726,0.0004839512,0.0008184774,0.0005156809,0.00053544436,0.0012605829,0.0012060783,0.0026323562],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015628024,0.00013516725,0.0013944908,0.000985477,0.000073600124,0.0006357853,0.00041024236,0.0046949307,0.7094559,0.03943079,0.0032030833,0.23942427],"study_design_scores_gemma":[0.00021688777,0.0019217603,0.0116791995,0.00045666844,0.0001694398,0.007787606,0.00036678102,0.13860515,0.4382034,0.036151573,0.36414453,0.00029701725],"about_ca_topic_score_codex":0.0010557108,"about_ca_topic_score_gemma":0.0029354724,"teacher_disagreement_score":0.0066079763,"about_ca_system_score_codex":0.0004722945,"about_ca_system_score_gemma":0.0017198569,"threshold_uncertainty_score":0.022105873},"labels":[],"label_agreement":null},{"id":"W2116458236","doi":"10.1503/jpn.110028","title":"Effects of early-life adversity on white matter diffusivity changes in patients at risk for major depression","year":2011,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Science Foundation Ireland","keywords":"Fractional anisotropy; Splenium; Corpus callosum; Fornix; Superior longitudinal fasciculus; Late life depression; White matter; Psychology; Tractography; Inferior longitudinal fasciculus; Uncinate fasciculus; Major depressive disorder; Depression (economics); Psychiatry; Clinical psychology; Medicine; Neuroscience; Magnetic resonance imaging; Cognition; Hippocampus","score_opus":0.024895342494898987,"score_gpt":0.2900436814675633,"score_spread":0.2651483389726643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116458236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997285,0.0001032146,0.000019780136,0.000019698437,0.0000013939825,0.0000017176162,0.000030761497,0.00000105669,0.00009378564],"genre_scores_gemma":[0.9998728,0.000025994063,0.00003454024,0.000004359636,0.0000013518137,9.410893e-7,0.000030051526,3.8258858e-7,0.000029618424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985147,0.000050051694,0.000015986867,0.000037983857,0.000019601046,0.000024996352],"domain_scores_gemma":[0.9994012,0.00010801567,0.00029176197,0.000034501667,0.000040613875,0.00012387318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025983911,0.00024659984,0.00021603469,0.00030233053,0.00037776394,0.00023857925,0.0001385579,0.00025685946,0.0013754121],"category_scores_gemma":[0.0014213983,0.00011805714,0.00018993081,0.00019519746,0.00021997036,0.00018732029,0.0002397127,0.00025725577,0.0001242942],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074914173,0.000059584243,0.99357915,0.000021392105,0.000085239204,0.000516418,0.00027126115,0.00006501841,0.0018132102,0.000014295595,0.00006344373,0.0027618336],"study_design_scores_gemma":[0.000002884655,0.000094385374,0.99926716,0.0000028549196,0.000012986439,0.00035964279,0.00008976056,0.000034859404,0.00009087156,0.0000118482185,0.000031282445,0.0000013260058],"about_ca_topic_score_codex":0.002433538,"about_ca_topic_score_gemma":0.004956908,"teacher_disagreement_score":0.002433538,"about_ca_system_score_codex":0.00026416482,"about_ca_system_score_gemma":0.00011825103,"threshold_uncertainty_score":0.0048387647},"labels":[],"label_agreement":null},{"id":"W2116470411","doi":"10.2522/ptj.20060164","title":"Answering the Call: The Influence of Neuroimaging and Electrophysiological Evidence on Rehabilitation","year":2007,"lang":"en","type":"review","venue":"Physical Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Neuroimaging; Magnetoencephalography; Neuroscience; Functional neuroimaging; Electrophysiology; Psychology; Rehabilitation; Diffusion MRI; Functional magnetic resonance imaging; Neuroplasticity; Modalities; Sensory system; Magnetic resonance imaging; Electroencephalography; Physical medicine and rehabilitation; Medicine; Radiology","score_opus":0.18520377911512395,"score_gpt":0.46857158022069806,"score_spread":0.28336780110557414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116470411","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001140275,0.99506,0.00021257074,0.002466801,0.0004779511,0.0000019512,0.000009239623,0.0000092725495,0.0016482355],"genre_scores_gemma":[0.0006620635,0.99627566,0.0003389587,0.0010683503,0.0008391253,0.0000044531535,0.000010548743,0.000003074849,0.0007979387],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996081,0.00011820187,0.000061495666,0.00005822515,0.0001315399,0.000022446382],"domain_scores_gemma":[0.9976198,0.0016411529,0.00016666675,0.00007904942,0.0003991521,0.00009425386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014484733,0.00076869567,0.0017296458,0.0031793825,0.0005133318,0.0015911676,0.000943035,0.0025714906,0.004444251],"category_scores_gemma":[0.003032658,0.00023956281,0.0003826151,0.0037345719,0.0020012646,0.004895709,0.001019771,0.0022965174,0.004142282],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003298024,0.00003206398,0.00022690161,0.0066102264,0.000037810732,0.0004390037,0.00017240262,0.00022750725,0.0009715936,0.0083273,0.045993768,0.9369286],"study_design_scores_gemma":[0.000009933229,0.000049358376,0.00137772,0.007242143,0.000043683835,0.004825467,0.0004636596,0.00009777145,0.00034075507,0.011339708,0.97417235,0.00003727205],"about_ca_topic_score_codex":0.0011028176,"about_ca_topic_score_gemma":0.0019748255,"teacher_disagreement_score":0.004444251,"about_ca_system_score_codex":0.00079192535,"about_ca_system_score_gemma":0.0016034562,"threshold_uncertainty_score":0.014867485},"labels":[],"label_agreement":null},{"id":"W2116949112","doi":"10.1002/hbm.22522","title":"Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Biogen Idec; Genentech; Takeda Pharmaceutical Company; IXICO; Servier; Eisai; Medpace; Eli Lilly and Company; Synarc; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; BioClinica; National Institute on Aging; Abbott Laboratories; Bayer HealthCare; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche","keywords":"Dementia; Atrophy; Frontotemporal dementia; Voxel; Neuroimaging; Region of interest; Medicine; Vascular dementia; Population; Cerebral blood flow; Magnetic resonance imaging; Pathology; Radiology; Psychology; Nuclear medicine; Internal medicine; Disease; Psychiatry","score_opus":0.06534631252162783,"score_gpt":0.34961993735697416,"score_spread":0.28427362483534635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116949112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991326,0.00022499695,0.00035152392,0.000013704578,0.0000058710953,0.000021083088,0.0000623053,0.000007652154,0.0001804317],"genre_scores_gemma":[0.9988919,0.00006906654,0.00071432214,0.000010029002,0.00000844409,0.000016933669,0.00022335663,0.000002284452,0.000063559026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984687,0.00065160065,0.000227751,0.00020102694,0.0002799035,0.00017105135],"domain_scores_gemma":[0.99489284,0.0021234124,0.001304311,0.00034617304,0.0008953735,0.00043787927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039537037,0.00053844624,0.00055287033,0.0026575702,0.0003422187,0.00081316236,0.00042355535,0.00070894277,0.00051250303],"category_scores_gemma":[0.010957257,0.00025746998,0.00028201874,0.00057626807,0.00042844095,0.0004111365,0.0006169154,0.00037315494,0.00022245052],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020066067,0.00012953415,0.9799699,0.000033600183,0.00009533749,0.00035706258,0.00022529191,0.00041413447,0.0037699102,0.000041794854,0.00016212938,0.012794728],"study_design_scores_gemma":[0.000057982048,0.0005866276,0.99207014,0.000019945934,0.000058933227,0.000845388,0.00022756706,0.0043915934,0.0014051597,0.00015980891,0.0001602784,0.000016605974],"about_ca_topic_score_codex":0.0015179788,"about_ca_topic_score_gemma":0.0030852377,"teacher_disagreement_score":0.0039537037,"about_ca_system_score_codex":0.00027914677,"about_ca_system_score_gemma":0.00030857098,"threshold_uncertainty_score":0.020909488},"labels":[],"label_agreement":null},{"id":"W2116953988","doi":"10.1109/isspit.2006.270854","title":"Bilateral Filtering of Diffusion Tensor MR Images","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Smoothing; Mathematics; Euclidean distance; Diffusion MRI; Tensor (intrinsic definition); Scalar (mathematics); Divergence (linguistics); Interpolation (computer graphics); Artificial intelligence; Mathematical analysis; Pattern recognition (psychology); Algorithm; Computer science; Image (mathematics); Geometry; Statistics","score_opus":0.03816979315600405,"score_gpt":0.3283772684908604,"score_spread":0.29020747533485636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116953988","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008652736,0.00016315206,0.98979026,0.00009941492,0.00004793072,0.000025039275,0.000057706802,0.00050343835,0.00066035456],"genre_scores_gemma":[0.13874553,0.00065302645,0.85519606,0.00011454726,0.00010858239,0.000074409334,0.0003398827,0.00036448656,0.004403528],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917775,0.00012244772,0.000062891624,0.00018424807,0.00038785645,0.00006475917],"domain_scores_gemma":[0.99841297,0.0006518045,0.0001783275,0.00032797412,0.00037457605,0.000054387638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017276545,0.0008174268,0.0008889752,0.0013700807,0.00060675456,0.0012420797,0.0006952308,0.0008504664,0.003448643],"category_scores_gemma":[0.006625258,0.0003913012,0.0010750178,0.0013924569,0.00061956135,0.001670845,0.0008757472,0.00090815517,0.0012290078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035538964,0.000092269576,0.0014154722,0.00034083324,0.00014919096,0.00032770782,0.0002874592,0.09325208,0.16101697,0.0360591,0.0031018972,0.70360154],"study_design_scores_gemma":[0.000037353977,0.00020582574,0.0033114247,0.000040593473,0.00009866336,0.0008054455,0.00009598488,0.81745064,0.104787596,0.051767427,0.021310722,0.00008835797],"about_ca_topic_score_codex":0.0021955443,"about_ca_topic_score_gemma":0.0026067249,"teacher_disagreement_score":0.003448643,"about_ca_system_score_codex":0.0005565884,"about_ca_system_score_gemma":0.00077508297,"threshold_uncertainty_score":0.011536837},"labels":[],"label_agreement":null},{"id":"W2117555148","doi":"10.1002/mrm.23292","title":"Somatotopic arrangement of thermal sensory regions in the healthy human spinal cord determined by means of spinal cord functional MRI","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Brainstem; Spinal cord; Sensory system; Neuroscience; Anatomy; Dermatome; Stimulus (psychology); Sensory stimulation therapy; Stimulation; Neurophysiology; Medicine; Psychology","score_opus":0.14372576778989582,"score_gpt":0.37612321436519336,"score_spread":0.23239744657529754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117555148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968183,0.000104545965,0.0025244849,0.000018339755,0.0000023178857,0.000018416802,0.00007332048,0.000017972174,0.00042222973],"genre_scores_gemma":[0.99852055,0.000047527672,0.0011425276,0.000012650215,0.0000034157813,0.000015346093,0.000051553667,0.0000040316695,0.00020232354],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986184,0.00003501613,0.000007269096,0.00004214919,0.00002937923,0.000024366482],"domain_scores_gemma":[0.9998561,0.00004354235,0.000034456792,0.000022178847,0.000023553332,0.000020084692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019559616,0.00018552781,0.0001705661,0.0005138495,0.00015298525,0.00017927993,0.0000886392,0.00019729599,0.0014982547],"category_scores_gemma":[0.0008459907,0.00015150843,0.00010751738,0.0001448523,0.000477207,0.00017493806,0.00017868076,0.000109399196,0.00013331941],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013425584,0.00010082242,0.038005088,0.00009925837,0.00006871349,0.0006993269,0.0003936493,0.0014687368,0.9388745,0.00022073872,0.00016225279,0.018564364],"study_design_scores_gemma":[0.000035182606,0.0010630781,0.95179325,0.000012906745,0.000045663783,0.0025061811,0.00023749383,0.005470295,0.037920583,0.00056068593,0.00032488626,0.000029784409],"about_ca_topic_score_codex":0.0012927466,"about_ca_topic_score_gemma":0.0032922407,"teacher_disagreement_score":0.0014982547,"about_ca_system_score_codex":0.00012248967,"about_ca_system_score_gemma":0.00014963423,"threshold_uncertainty_score":0.0050121546},"labels":[],"label_agreement":null},{"id":"W2118432137","doi":"10.1002/hbm.20828","title":"The rate of visuomotor adaptation correlates with cerebellar white‐matter microstructure","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; International Brain Research Organization; Wellcome Trust","keywords":"Cerebellum; Neuroscience; Psychology; White matter; Premotor cortex; Fractional anisotropy; Anatomy; Biology; Magnetic resonance imaging; Dorsum; Medicine","score_opus":0.03510674973222959,"score_gpt":0.3013756091440133,"score_spread":0.2662688594117837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118432137","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998273,0.00008874369,0.0011505741,0.000009373842,0.0000015256896,0.0000057071866,0.000040202376,0.000023622199,0.0004071712],"genre_scores_gemma":[0.99909854,0.0000555942,0.0005201466,0.000003726988,0.000002446707,0.000004070352,0.0000618412,0.000007962426,0.00024567542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998485,0.00002798644,0.000016290507,0.000053394037,0.00003437854,0.000019510595],"domain_scores_gemma":[0.9979843,0.0005582373,0.00097122305,0.00018944262,0.00017516217,0.00012157373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038126772,0.00022018,0.00018914322,0.00060486846,0.000077841854,0.00032323026,0.000119540775,0.0001994838,0.00086973945],"category_scores_gemma":[0.0029117186,0.00013019907,0.000100699595,0.00026292627,0.00027965638,0.000254442,0.0002240309,0.00023195343,0.00019403471],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006423528,0.00010090946,0.64998895,0.000050879877,0.00022318927,0.00025707285,0.00049837993,0.001985205,0.30032668,0.00017676818,0.00017639772,0.04557319],"study_design_scores_gemma":[0.0000017733566,0.000085010826,0.9937022,0.0000019150032,0.0000069441703,0.00024525615,0.000019548947,0.0007520307,0.00504044,0.00006491548,0.000075384116,0.0000046596906],"about_ca_topic_score_codex":0.0010948401,"about_ca_topic_score_gemma":0.0010673073,"teacher_disagreement_score":0.0010948401,"about_ca_system_score_codex":0.0001176456,"about_ca_system_score_gemma":0.000075481345,"threshold_uncertainty_score":0.0029096007},"labels":[],"label_agreement":null},{"id":"W2119543919","doi":"10.1109/tmi.2003.816961","title":"Retrospective evaluation of intersubject brain registration","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":202,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Cancer Institute","keywords":"Image registration; Artificial intelligence; Computer science; Normalization (sociology); Spatial normalization; Matching (statistics); Computer vision; Focus (optics); Transformation (genetics); Pattern recognition (psychology); Mathematics; Image (mathematics); Statistics; Voxel","score_opus":0.0647567008747169,"score_gpt":0.3928816999721583,"score_spread":0.3281249990974414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119543919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8136945,0.0047793747,0.17461868,0.00017421816,0.00015776524,0.00036271696,0.001527381,0.0011769701,0.003508525],"genre_scores_gemma":[0.9690267,0.00052859617,0.026887374,0.000037606555,0.00007179928,0.00011043203,0.0020139825,0.0002992513,0.001024303],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98858565,0.0061824108,0.0012831254,0.0017797009,0.0019466069,0.00022246949],"domain_scores_gemma":[0.9554374,0.02273617,0.0048870915,0.009416944,0.006974773,0.00054751907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019119542,0.00074890425,0.0007743303,0.002132288,0.00048521406,0.0010439234,0.00067723426,0.0007350749,0.0013757796],"category_scores_gemma":[0.057641342,0.0002647596,0.00053103163,0.0015104429,0.0007447508,0.0012287432,0.0013065209,0.0004209727,0.0005379182],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009316074,0.0003078014,0.22250712,0.001264585,0.0025485582,0.0007903011,0.0030065973,0.039911203,0.0738008,0.0031923156,0.003889982,0.6394647],"study_design_scores_gemma":[0.00026564425,0.005917822,0.7374643,0.00019378887,0.0015611275,0.0090146465,0.002004992,0.11376741,0.11078015,0.0046548317,0.014018415,0.00035678665],"about_ca_topic_score_codex":0.0007244653,"about_ca_topic_score_gemma":0.0015140632,"teacher_disagreement_score":0.019119542,"about_ca_system_score_codex":0.00026350902,"about_ca_system_score_gemma":0.00031651565,"threshold_uncertainty_score":0.10111505},"labels":[],"label_agreement":null},{"id":"W2120710153","doi":"10.1073/pnas.0407259102","title":"Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention","year":2005,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":365,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Cancer Institute; National Institute on Aging; GlaxoSmithKline","keywords":"Fractional anisotropy; Psychology; White matter; Corpus callosum; Superior parietal lobule; Neuroscience; Diffusion MRI; Precuneus; Working memory; Lateralization of brain function; Parietal lobe; Functional magnetic resonance imaging; Audiology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.03621497310292623,"score_gpt":0.3217695213953885,"score_spread":0.2855545482924623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120710153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988921,0.00006817121,0.00043107523,0.000014580985,0.000002767026,0.000004217617,0.00009558392,0.000018177474,0.00047329566],"genre_scores_gemma":[0.9991054,0.000050431325,0.00030770467,0.000011653635,0.0000045719753,0.0000051493103,0.00015807603,0.000011751736,0.00034532894],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979955,0.00003350806,0.000019417257,0.000087217435,0.000042839234,0.000017500857],"domain_scores_gemma":[0.99766135,0.0006468322,0.0011882926,0.0002213881,0.00011457827,0.00016763317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037169128,0.00024799022,0.00014487204,0.00043699105,0.00008789698,0.00046563277,0.00010918087,0.00031183622,0.0013851363],"category_scores_gemma":[0.0034959556,0.00013410393,0.0000940576,0.00019711471,0.00026251175,0.00020580755,0.00023057597,0.00026395055,0.00035546167],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016415251,0.00031372573,0.82432485,0.000069328235,0.00032707184,0.00024006712,0.0009348892,0.0015330917,0.1397776,0.00021755022,0.00040978583,0.030210515],"study_design_scores_gemma":[0.000005327851,0.00013956081,0.9969399,0.0000021296644,0.000011111229,0.00016702303,0.000032278167,0.0005444002,0.001982463,0.000081117825,0.000088186855,0.0000064932788],"about_ca_topic_score_codex":0.0012389395,"about_ca_topic_score_gemma":0.0015603097,"teacher_disagreement_score":0.0013851363,"about_ca_system_score_codex":0.00010145196,"about_ca_system_score_gemma":0.000076890225,"threshold_uncertainty_score":0.0046337247},"labels":[],"label_agreement":null},{"id":"W2121502050","doi":"10.1002/hbm.20779","title":"Lateralization of the arcuate fasciculus from childhood to adulthood and its relation to cognitive abilities in children","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":292,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Arcuate fasciculus; Lateralization of brain function; Psychology; Fractional anisotropy; Tractography; White matter; Cognition; Uncinate fasciculus; Inferior longitudinal fasciculus; Fasciculus; Audiology; Diffusion MRI; Developmental psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.03397784302624989,"score_gpt":0.31338961164840223,"score_spread":0.27941176862215233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121502050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99857616,0.0005004803,0.000070136346,0.00003665751,0.0000033066099,0.0000025937052,0.00022788721,0.0000072222656,0.0005754447],"genre_scores_gemma":[0.9981862,0.00062221894,0.00027019373,0.000018269142,0.000005344374,0.000011871168,0.00033727917,0.0000071572604,0.0005415276],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983335,0.000012199584,0.000017011975,0.00006445024,0.0000305628,0.000042467505],"domain_scores_gemma":[0.9992786,0.00007308535,0.00039773897,0.000041489962,0.00009863168,0.00011042063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029217036,0.00024780422,0.0002518333,0.0013190366,0.00036521902,0.00062401395,0.00016440118,0.0002875652,0.0010068412],"category_scores_gemma":[0.001120569,0.00021988418,0.00028286967,0.0005818423,0.0005210201,0.0005629792,0.00043984104,0.00034105955,0.00024563118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017203293,0.00003853167,0.9758296,0.000027283962,0.00003054106,0.0009829943,0.0013954849,0.0001409473,0.0075626737,0.00014852599,0.00021595674,0.013455482],"study_design_scores_gemma":[9.106772e-7,0.000036427,0.99847096,0.000008286565,0.000005233663,0.0007268696,0.0002056816,0.000020245969,0.0002541983,0.000032721036,0.00023560225,0.0000029136336],"about_ca_topic_score_codex":0.010049589,"about_ca_topic_score_gemma":0.011140983,"teacher_disagreement_score":0.010049589,"about_ca_system_score_codex":0.00037396047,"about_ca_system_score_gemma":0.00044519678,"threshold_uncertainty_score":0.01998216},"labels":[],"label_agreement":null},{"id":"W2121696795","doi":"10.1007/s00429-015-1078-8","title":"Blindness alters the microstructure of the ventral but not the dorsal visual stream","year":2015,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Visual system; Neuroscience; Inferior longitudinal fasciculus; Psychology; Visual cortex; Dorsum; Fasciculus; Anatomy; Medicine; Magnetic resonance imaging","score_opus":0.03405517960995518,"score_gpt":0.3140185209566567,"score_spread":0.27996334134670153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121696795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909827,0.0005980888,0.0057984847,0.00028180407,0.00009045606,0.000018755027,0.00036184565,0.000103625636,0.0017641659],"genre_scores_gemma":[0.99453664,0.00049179036,0.0020739587,0.00016916553,0.000033359436,0.000017955934,0.00018097689,0.000069119,0.0024270953],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998435,0.000018211798,0.000009652659,0.000047010228,0.000041295014,0.000040388808],"domain_scores_gemma":[0.9996456,0.000052970197,0.00013820006,0.000041990723,0.000049053473,0.000072054165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017442921,0.00039680986,0.00032899552,0.0008919894,0.00024580947,0.00054954883,0.00031006755,0.0005518303,0.0023878885],"category_scores_gemma":[0.00088102336,0.00029792124,0.0002092423,0.00026396566,0.00078018045,0.00076571363,0.00033114033,0.0007211053,0.0001347402],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009602794,0.00006106192,0.0033067313,0.000050388506,0.000054744636,0.00023249934,0.00006514249,0.00016960026,0.98477423,0.0009164924,0.00025838375,0.009150427],"study_design_scores_gemma":[0.000085215856,0.0008334459,0.41360626,0.00002709587,0.00020605008,0.0023741317,0.00027936517,0.0030499825,0.57265496,0.0048658373,0.0019572377,0.000060442253],"about_ca_topic_score_codex":0.0040568686,"about_ca_topic_score_gemma":0.0037182043,"teacher_disagreement_score":0.0040568686,"about_ca_system_score_codex":0.0004606483,"about_ca_system_score_gemma":0.00046477513,"threshold_uncertainty_score":0.008066535},"labels":[],"label_agreement":null},{"id":"W2121823099","doi":"10.1017/cjn.2014.34","title":"Greater Loss of White Matter Integrity in Postural Instability and Gait Difficulty Subtype of Parkinson's Disease","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Superior longitudinal fasciculus; Corpus callosum; Medicine; Voxel; Fasciculus; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.04805718819940654,"score_gpt":0.3013091439172459,"score_spread":0.25325195571783937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121823099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992378,0.00017177477,0.00006315926,0.000015225477,0.0000027447095,0.000011174148,0.00010796197,0.000002589616,0.00038765013],"genre_scores_gemma":[0.99949706,0.00005372971,0.00009613332,0.000017512073,0.000005480001,0.0000075816533,0.00019155735,0.0000011296409,0.0001297021],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998559,0.000014601542,0.000030801526,0.000050782986,0.00002765366,0.000020355148],"domain_scores_gemma":[0.99949455,0.000042218217,0.000298087,0.00002478338,0.00006301093,0.00007729513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023752543,0.00038453506,0.00048244905,0.0010162775,0.00045938228,0.00040312402,0.0002601532,0.00039790495,0.0025255159],"category_scores_gemma":[0.00070507964,0.00013500989,0.00023512347,0.0005690785,0.00028840595,0.00028622357,0.00038475852,0.0002568749,0.00027900818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070875074,0.000103912054,0.97824645,0.00008866328,0.00013757459,0.0022005283,0.00031931858,0.000059458023,0.010828928,0.00003356557,0.00018429228,0.0070886333],"study_design_scores_gemma":[0.0000073479546,0.00013364149,0.9962698,0.0000063706275,0.000016274531,0.0031150475,0.000092340095,0.000052254807,0.00020069348,0.00003176807,0.000072726514,0.0000016256854],"about_ca_topic_score_codex":0.002555618,"about_ca_topic_score_gemma":0.004506884,"teacher_disagreement_score":0.002555618,"about_ca_system_score_codex":0.00022083048,"about_ca_system_score_gemma":0.00015726552,"threshold_uncertainty_score":0.00844866},"labels":[],"label_agreement":null},{"id":"W2121839970","doi":"10.1109/isbi.2006.1624924","title":"The Biological Basis of Diffusion Tractography","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Tractography; White matter; Diffusion MRI; Diffusion; Anisotropic diffusion; Isotropy; Anisotropy; Diffusion imaging; Nuclear magnetic resonance; Computation; Magnetic resonance imaging; Physics; Computer science; Optics; Algorithm; Radiology; Medicine","score_opus":0.05916588426768305,"score_gpt":0.3382784821585658,"score_spread":0.2791125978908828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121839970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03735294,0.01784908,0.8804032,0.011612292,0.0005620467,0.00008942836,0.00051384734,0.00053093326,0.051086232],"genre_scores_gemma":[0.7883752,0.013569551,0.18651913,0.0008232755,0.0010149131,0.0002185843,0.0005412119,0.00018364527,0.008754478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99936634,0.00023011204,0.00003997207,0.00018969449,0.00013294387,0.000040831026],"domain_scores_gemma":[0.99774075,0.0011330767,0.00023790204,0.00032584465,0.000453691,0.00010876784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016771571,0.00033927508,0.00045583877,0.0017888424,0.0006580013,0.0023572731,0.00088938395,0.0016988993,0.0030996513],"category_scores_gemma":[0.007908687,0.00043288068,0.0004915998,0.000965277,0.0053940425,0.002696806,0.000947266,0.0014167629,0.0008057147],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030100106,0.000009537596,0.0013310016,0.00014326251,0.000042797772,0.0002217233,0.00021945321,0.023242798,0.0047426065,0.9372684,0.0011989529,0.031549577],"study_design_scores_gemma":[0.000016334916,0.000023809445,0.0020161974,0.000056499703,0.000010826672,0.00034023676,0.000043882996,0.036801707,0.00097019866,0.9489773,0.010709961,0.00003306144],"about_ca_topic_score_codex":0.0030322687,"about_ca_topic_score_gemma":0.0014905431,"teacher_disagreement_score":0.0030996513,"about_ca_system_score_codex":0.001185001,"about_ca_system_score_gemma":0.0009088546,"threshold_uncertainty_score":0.01036936},"labels":[],"label_agreement":null},{"id":"W2122506124","doi":"10.1503/jpn.110180","title":"Is depression a disconnection syndrome? Meta-analysis of diffusion tensor imaging studies in patients with MDD","year":2012,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":469,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Superior longitudinal fasciculus; Occipital lobe; Tractography; Voxel; Frontal lobe; Uncinate fasciculus; Psychology; Fasciculus; Neuroscience; Major depressive disorder; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.20798261876247473,"score_gpt":0.4386985490390744,"score_spread":0.23071593027659967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122506124","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058668584,0.93795604,0.0011829332,0.00062793575,0.00021123559,0.00014390914,0.0008059487,0.000034483295,0.00036891788],"genre_scores_gemma":[0.84072095,0.15467058,0.002056917,0.0007299368,0.00032296043,0.0002862047,0.0010375306,0.000030688345,0.00014421639],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.98568404,0.008052167,0.0030877828,0.0019171144,0.00096781726,0.00029107058],"domain_scores_gemma":[0.96515864,0.025464328,0.005731082,0.0020197143,0.0012275558,0.00039876264],"candidate_categories":["metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.017752081,0.0021279906,0.008813804,0.005322536,0.0007845998,0.0030244326,0.0018014199,0.0020432207,0.0019665097],"category_scores_gemma":[0.03604535,0.0011703188,0.028878989,0.005922481,0.0009732173,0.0011849671,0.0013940411,0.0014574176,0.00015598236],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002509419,0.000019168625,0.04723806,0.03265636,0.9094442,0.00024514625,0.00010840861,0.0005086471,0.00045775968,0.00012487278,0.00030067476,0.0063871727],"study_design_scores_gemma":[0.0005267744,0.00022400147,0.045399457,0.0036160904,0.9481385,0.0003076301,0.000069890666,0.00032733518,0.00019991488,0.00033600928,0.0008310811,0.000023329492],"about_ca_topic_score_codex":0.004279366,"about_ca_topic_score_gemma":0.007173278,"teacher_disagreement_score":0.9911862,"about_ca_system_score_codex":0.0015506062,"about_ca_system_score_gemma":0.0012861583,"threshold_uncertainty_score":0.0938831},"labels":[],"label_agreement":null},{"id":"W2122622288","doi":"10.1002/mds.22081","title":"Diffusion‐weighted imaging and magnetization transfer imaging of tardive and edentulous orodyskinesia","year":2008,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Putamen; Tardive dyskinesia; Basal ganglia; Globus pallidus; Magnetic resonance imaging; Caudate nucleus; Medicine; Dyskinesia; Neuroradiology; Diffusion MRI; Neurology; Psychology; Nuclear medicine; Internal medicine; Neuroscience; Radiology; Parkinson's disease; Central nervous system; Schizophrenia (object-oriented programming); Psychiatry; Disease","score_opus":0.013971641627157668,"score_gpt":0.2620241154697185,"score_spread":0.24805247384256082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122622288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994388,0.00023105608,0.00009617825,0.0000082349015,9.788802e-7,0.0000030808694,0.000010395743,0.000001727285,0.00020946466],"genre_scores_gemma":[0.99945635,0.00013156988,0.00023572774,0.000011210722,0.0000037683878,0.0000029332004,0.000021128977,8.6487216e-7,0.0001364687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999274,0.000018105331,0.000012727521,0.000018460807,0.000009416375,0.000013806017],"domain_scores_gemma":[0.99982893,0.00003743313,0.00007478116,0.000011656582,0.00002006504,0.00002723248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027674172,0.0003126003,0.0001963861,0.0009187256,0.00017094595,0.00019977237,0.00011632594,0.00025158154,0.00089476956],"category_scores_gemma":[0.00072073704,0.00017000025,0.00009635678,0.00018813544,0.00031130246,0.00021940711,0.00017472301,0.00013788295,0.00011129551],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024637762,0.0002075217,0.82110304,0.00017502016,0.00013410511,0.010522733,0.0010193163,0.00020245444,0.12961398,0.00018435865,0.00013954117,0.034234025],"study_design_scores_gemma":[0.00005878312,0.00063246896,0.9834695,0.000009402815,0.00004406248,0.0114880465,0.00031225957,0.00028194758,0.0034488814,0.000086537286,0.00016034505,0.000007834625],"about_ca_topic_score_codex":0.0009581886,"about_ca_topic_score_gemma":0.0014384318,"teacher_disagreement_score":0.0009581886,"about_ca_system_score_codex":0.00015333356,"about_ca_system_score_gemma":0.00008986484,"threshold_uncertainty_score":0.002993226},"labels":[],"label_agreement":null},{"id":"W2122735696","doi":"10.1016/j.brainres.2009.07.046","title":"The relations between white matter and declarative memory in older children and adolescents","year":2009,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; SickKids Foundation; Hospital for Sick Children; McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research; Sick Kids Foundation","keywords":"Uncinate fasciculus; White matter; Psychology; Cingulum (brain); Inferior longitudinal fasciculus; Diffusion MRI; Neuroscience; Cognitive psychology; Superior longitudinal fasciculus; Episodic memory; Recall; Audiology; Tractography; Cognition; Fractional anisotropy; Magnetic resonance imaging; Medicine","score_opus":0.07944380354018539,"score_gpt":0.4314518269975476,"score_spread":0.3520080234573622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122735696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954176,0.00025329905,0.0000121321655,0.000021378028,0.0000016275563,9.205565e-7,0.000030442749,4.970265e-7,0.0001379303],"genre_scores_gemma":[0.9993305,0.00031293364,0.000054934164,0.000016801496,0.0000061646942,0.0000030156418,0.00007834496,0.0000013987346,0.00019588304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998801,0.00002145077,0.000019437923,0.000026191456,0.000026280579,0.000026617996],"domain_scores_gemma":[0.9976078,0.0007895215,0.0010714241,0.0000868291,0.00024391616,0.00020054395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005352673,0.00026796781,0.000285482,0.0007150413,0.0003105359,0.0006587191,0.00038182698,0.0004209631,0.0009068758],"category_scores_gemma":[0.003394771,0.00025262497,0.00024053459,0.0006147927,0.00047191806,0.00082745444,0.0003207603,0.0006885694,0.00012676531],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013730736,0.00006961491,0.9952676,0.000019672505,0.000056253906,0.00033305524,0.00082530006,0.000043226406,0.0006320102,0.0000719202,0.000038122515,0.0025059753],"study_design_scores_gemma":[0.0000025667175,0.000065885135,0.99861646,0.000005683108,0.00002907894,0.00036760993,0.0005970843,0.000031114487,0.0001710202,0.000057048095,0.00005461273,0.0000017788833],"about_ca_topic_score_codex":0.0099441,"about_ca_topic_score_gemma":0.015546742,"teacher_disagreement_score":0.0099441,"about_ca_system_score_codex":0.0002780869,"about_ca_system_score_gemma":0.00035372545,"threshold_uncertainty_score":0.01977247},"labels":[],"label_agreement":null},{"id":"W2122954083","doi":"10.3174/ajnr.a2698","title":"Systematic Differences between Lean and Obese Adolescents in Brain Spin-Lattice Relaxation Time: A Quantitative Study","year":2011,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; School of Medicine, New York University; York University","keywords":"Medicine; Brain size; Obesity; Voxel; Internal medicine; Endocrinology; Magnetic resonance imaging; Radiology","score_opus":0.09885539507677374,"score_gpt":0.3763667851637285,"score_spread":0.2775113900869548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122954083","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990107,0.00023246992,0.00042502326,0.0000063383377,0.0000024794506,0.000014879911,0.00013066048,0.0000057136317,0.00017177455],"genre_scores_gemma":[0.99891675,0.00006826658,0.0007235493,0.000010671898,0.0000055289943,0.00002485087,0.0001788437,0.0000071024506,0.000064588705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99944943,0.00015543323,0.00006758214,0.00017433996,0.00011121986,0.00004204707],"domain_scores_gemma":[0.9972047,0.0008564686,0.0011539684,0.0002229913,0.00035435555,0.000207536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001251281,0.0002648275,0.0002192185,0.0010463364,0.00019124175,0.00039057352,0.00022692152,0.00032209823,0.00087544724],"category_scores_gemma":[0.003489055,0.0001560371,0.00018162094,0.0006508444,0.00050537055,0.00026902658,0.00033322317,0.00017723927,0.0001316442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007198936,0.00006250418,0.98520905,0.00007292496,0.00016122336,0.0001223245,0.0005164592,0.00007424133,0.0072517176,0.00006177916,0.00005915023,0.005688764],"study_design_scores_gemma":[0.000010128011,0.00024337243,0.99787605,0.0000068117556,0.00004561408,0.00050375715,0.00025599197,0.00016127038,0.0006838677,0.000032948185,0.00017555423,0.000004533944],"about_ca_topic_score_codex":0.00089633657,"about_ca_topic_score_gemma":0.0011359315,"teacher_disagreement_score":0.001251281,"about_ca_system_score_codex":0.00017123323,"about_ca_system_score_gemma":0.00014557522,"threshold_uncertainty_score":0.0066174865},"labels":[],"label_agreement":null},{"id":"W2125392828","doi":"","title":"Fluid-attenuated inversion recovery preparation: not an improvement over conventional diffusion-weighted imaging at 3T in acute ischemic stroke.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre","funders":"","keywords":"Fluid-attenuated inversion recovery; Medicine; Diffusion imaging; Nuclear medicine; Effective diffusion coefficient; Stroke (engine); Ischemic stroke; Magnetic resonance imaging; Diffusion MRI; Neuroimaging; Ischemia; Radiology; Cardiology","score_opus":0.028903660215779798,"score_gpt":0.29894726671571964,"score_spread":0.27004360649993986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125392828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772423,0.0088039655,0.008536735,0.001641058,0.00021513735,0.00016915546,0.00012400831,0.00026816924,0.0029994533],"genre_scores_gemma":[0.9813137,0.003091404,0.013109973,0.0006459885,0.00034890062,0.00005492504,0.00026455946,0.00005055253,0.0011200274],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99973375,0.000098576435,0.000027935075,0.000044732642,0.00006750306,0.000027564029],"domain_scores_gemma":[0.99915516,0.00028385286,0.0002163743,0.000085676795,0.00017096894,0.00008791147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016257842,0.00039897815,0.00036514242,0.0003549241,0.00014581751,0.00037833248,0.00033076992,0.00075507566,0.0015802718],"category_scores_gemma":[0.0052762013,0.00014231252,0.00018375723,0.00021450003,0.00028444175,0.00065796776,0.00018440561,0.0002856677,0.0007665049],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012488128,0.0008613603,0.09481542,0.0007930381,0.00032779374,0.004464281,0.000377384,0.0013933353,0.21034896,0.00020945554,0.0040372303,0.66988367],"study_design_scores_gemma":[0.0014233667,0.021562487,0.8068539,0.00034814604,0.0011725381,0.037694216,0.0005681586,0.017067092,0.091445625,0.002009094,0.019739868,0.000115641065],"about_ca_topic_score_codex":0.0005725078,"about_ca_topic_score_gemma":0.0014703366,"teacher_disagreement_score":0.0016257842,"about_ca_system_score_codex":0.00017330635,"about_ca_system_score_gemma":0.00028172365,"threshold_uncertainty_score":0.008598089},"labels":[],"label_agreement":null},{"id":"W2126026099","doi":"10.1016/j.neuroimage.2008.04.264","title":"A non-invasive method to relate the timing of neural activity to white matter microstructural integrity","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Mental Health","keywords":"White matter; Magnetoencephalography; Neuroscience; Saccadic masking; Diffusion MRI; Fractional anisotropy; Psychology; Visual cortex; Latency (audio); Neurophysiology; Electroencephalography; Eye movement; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.08420897776048947,"score_gpt":0.3782083580321031,"score_spread":0.29399938027161365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126026099","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.068337835,0.0023921484,0.92149717,0.00038704157,0.00058381207,0.00032785197,0.0009872277,0.0015503028,0.0039366335],"genre_scores_gemma":[0.32171133,0.002308742,0.6639787,0.00072075217,0.0005935136,0.000850079,0.00066946994,0.00068573863,0.008481683],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996377,0.00007214519,0.000017135313,0.00009787361,0.00015359989,0.00002153725],"domain_scores_gemma":[0.99887806,0.0005680533,0.0001681983,0.00012221897,0.00017807669,0.00008540189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008084784,0.0006086259,0.0005268392,0.0011717277,0.00039161372,0.0009853382,0.0006646405,0.0014551821,0.0029866304],"category_scores_gemma":[0.0027169278,0.0005169989,0.00032017037,0.0011191053,0.0005708669,0.0010159042,0.00057049457,0.0013893322,0.0010072083],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007628999,0.00017925925,0.0055632507,0.00048087785,0.000121811856,0.00032885422,0.00012313694,0.0012256743,0.77084345,0.0020913128,0.0039876993,0.21429186],"study_design_scores_gemma":[0.000787991,0.0027915826,0.15924977,0.00030682835,0.0008239697,0.018943725,0.00027191069,0.14939553,0.620295,0.014473304,0.032125503,0.00053489645],"about_ca_topic_score_codex":0.00085403095,"about_ca_topic_score_gemma":0.0036655401,"teacher_disagreement_score":0.0029866304,"about_ca_system_score_codex":0.0002185815,"about_ca_system_score_gemma":0.00059397076,"threshold_uncertainty_score":0.009991288},"labels":[],"label_agreement":null},{"id":"W2126390643","doi":"10.1139/jpn.0924","title":"Neuregulin 1 genetic variation and anterior cingulum integrity in patients with schizophrenia and healthy controls","year":2009,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Neuroscience; Medicine; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.016826759179006577,"score_gpt":0.30625820729598835,"score_spread":0.2894314481169818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126390643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997178,0.00006915945,0.000017030477,0.0000101888945,0.0000019106337,0.0000039049773,0.00006775855,0.0000015776902,0.00011073107],"genre_scores_gemma":[0.9997539,0.000036389727,0.00004602901,0.000008950198,0.000002501002,0.0000054585344,0.00008932629,0.0000010771694,0.000056414698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997515,0.00004672059,0.000033778328,0.00009241339,0.0000398225,0.000035821446],"domain_scores_gemma":[0.99962175,0.000064995394,0.00018753954,0.000024738381,0.000025695184,0.00007514402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035416428,0.00059797964,0.00032097477,0.001095595,0.00052006077,0.00042710267,0.00023459145,0.0005348001,0.0019198403],"category_scores_gemma":[0.0010089384,0.00024365669,0.00029762316,0.0007151803,0.00037872704,0.00019183493,0.00035563827,0.00023040168,0.00016030061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010882751,0.00009814532,0.98988146,0.000023434488,0.00017447707,0.00086690666,0.00037643817,0.00007459307,0.00498357,0.00006430569,0.000091955146,0.002276439],"study_design_scores_gemma":[0.000025025322,0.00012675751,0.9987293,0.000005041136,0.000041932275,0.0006347052,0.00012474759,0.000082325445,0.00012468729,0.000038450056,0.00006319339,0.000003711079],"about_ca_topic_score_codex":0.005882502,"about_ca_topic_score_gemma":0.0055962447,"teacher_disagreement_score":0.005882502,"about_ca_system_score_codex":0.0003390633,"about_ca_system_score_gemma":0.00018395516,"threshold_uncertainty_score":0.0116965175},"labels":[],"label_agreement":null},{"id":"W2127078620","doi":"10.1093/brain/awl111","title":"Unconscious vision: new insights into the neuronal correlate of blindsight using diffusion tractography","year":2006,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":176,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"University of Oxford; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Blindsight; Psychology; Neuroscience; Visual cortex; Stimulus (psychology); Cognitive psychology; Visual perception; Perception","score_opus":0.03215465323883735,"score_gpt":0.3285023049916865,"score_spread":0.2963476517528491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127078620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860384,0.00070591964,0.012687731,0.000053315067,0.0000030998096,0.000008817971,0.00005862074,0.00003874986,0.00040543682],"genre_scores_gemma":[0.9952673,0.00032148272,0.0041778395,0.000010699322,0.000006624008,0.000004678085,0.000047722115,0.000005986302,0.00015773813],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999136,0.000018283312,0.000010410854,0.000025441715,0.00001638071,0.000016025824],"domain_scores_gemma":[0.9997286,0.00006794033,0.00008620096,0.000050328887,0.000022026625,0.000044886812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031679915,0.000281139,0.00017063686,0.0010165365,0.000100439414,0.00027161313,0.00012835042,0.0002448782,0.00070088677],"category_scores_gemma":[0.0006340333,0.00013790582,0.00013772107,0.00027280278,0.00069560524,0.00063920696,0.00038906196,0.0002561058,0.000050035243],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052141544,0.000044547243,0.09366331,0.0002056801,0.00006415427,0.002141785,0.00088464736,0.0009769963,0.8587658,0.0017233897,0.000089148925,0.040919103],"study_design_scores_gemma":[0.000041245792,0.00045448216,0.89542633,0.000055826902,0.0000648291,0.013475041,0.000519882,0.00944149,0.0733425,0.005618379,0.0014953816,0.00006465253],"about_ca_topic_score_codex":0.00091258856,"about_ca_topic_score_gemma":0.0011856242,"teacher_disagreement_score":0.0010165365,"about_ca_system_score_codex":0.0001576571,"about_ca_system_score_gemma":0.00016354297,"threshold_uncertainty_score":0.0023447275},"labels":[],"label_agreement":null},{"id":"W2128207744","doi":"10.1002/mrm.20948","title":"Apparent diffusion coefficients from high angular resolution diffusion imaging: Estimation and applications","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":241,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA); McGill University; University of Minnesota; National Science Foundation","keywords":"Spherical harmonics; Diffusion MRI; Gaussian; Isotropy; Anisotropy; Tensor (intrinsic definition); Diffusion; Smoothing; Anisotropic diffusion; Mathematical analysis; Statistical physics; Mathematics; Physics; Computer science; Optics; Geometry; Computer vision","score_opus":0.017829009052379653,"score_gpt":0.3000969946516066,"score_spread":0.28226798559922694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128207744","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009198032,0.00073351956,0.9891549,0.00020306745,0.000011805569,0.000009875838,0.000041017447,0.00022910774,0.00041864614],"genre_scores_gemma":[0.2634945,0.0040012,0.7297017,0.00005435864,0.00008670777,0.00006472305,0.00031671333,0.00027938528,0.002000687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995271,0.0001702576,0.000026434813,0.000070415765,0.00018480353,0.000020945869],"domain_scores_gemma":[0.9977725,0.0013385314,0.0002810721,0.0003025482,0.0002545744,0.0000507978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016684359,0.00072314055,0.0005627397,0.0011057705,0.00026235613,0.00076265103,0.00073934003,0.0010209531,0.00074805116],"category_scores_gemma":[0.007364567,0.00047950333,0.000538855,0.0014196383,0.00083763775,0.0017006965,0.000663711,0.0011259624,0.0005702676],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010480717,0.00007123269,0.0024373569,0.00046822295,0.00009480385,0.00017557992,0.00024783253,0.5397508,0.043624245,0.0557596,0.0022618766,0.35500363],"study_design_scores_gemma":[0.000007749982,0.00002865584,0.001171168,0.000019647314,0.00001574517,0.00021005399,0.000023854782,0.95406145,0.011884168,0.028821431,0.0037159955,0.000040115894],"about_ca_topic_score_codex":0.0022711752,"about_ca_topic_score_gemma":0.0020945757,"teacher_disagreement_score":0.0022711752,"about_ca_system_score_codex":0.000570007,"about_ca_system_score_gemma":0.00062745204,"threshold_uncertainty_score":0.008823633},"labels":[],"label_agreement":null},{"id":"W2128224240","doi":"10.1016/j.jalz.2011.05.134","title":"IC‐P‐068: Declines in entorhinal cortex structural connectivity in amnestic mild cognitive impairment","year":2011,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University; Centre for Research on Brain Language and Music","funders":"","keywords":"Entorhinal cortex; Voxel; Probabilistic logic; Artificial intelligence; Pattern recognition (psychology); White matter; Hippocampus; Nuclear medicine; Computer science; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.10465410566856506,"score_gpt":0.3634386714035538,"score_spread":0.25878456573498876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128224240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975561,0.00010342299,0.00020554724,0.00004415736,0.000008104679,0.000026192703,0.00068680674,0.000065859254,0.0013037734],"genre_scores_gemma":[0.9978162,0.0000549732,0.0003282692,0.000037085083,0.000011458682,0.000035519166,0.00055553985,0.000019338233,0.0011416454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998708,0.000012308855,0.000015846523,0.000047573518,0.000033483673,0.0000200315],"domain_scores_gemma":[0.9995839,0.000039642033,0.00014107389,0.000055691802,0.00006770633,0.00011202047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026239513,0.0008712731,0.00050528074,0.0008512715,0.00044365725,0.00038722574,0.00039108467,0.0006139699,0.0046902313],"category_scores_gemma":[0.0010994215,0.00021900832,0.00018763794,0.00039499864,0.00040603528,0.00026490784,0.0005313815,0.0006453558,0.0008845171],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.023151059,0.0034405019,0.41841087,0.00040833515,0.0004913845,0.020379884,0.0019772358,0.001422598,0.41311345,0.00045864406,0.006681551,0.11006452],"study_design_scores_gemma":[0.0000726953,0.00095756,0.98801154,0.000010245195,0.000054392756,0.0053140353,0.000101629135,0.00046488646,0.004287837,0.00016051558,0.00055359583,0.000011148823],"about_ca_topic_score_codex":0.006451794,"about_ca_topic_score_gemma":0.0031783443,"teacher_disagreement_score":0.006451794,"about_ca_system_score_codex":0.00029626087,"about_ca_system_score_gemma":0.00022898997,"threshold_uncertainty_score":0.015690386},"labels":[],"label_agreement":null},{"id":"W2128297135","doi":"10.1007/s00429-013-0666-8","title":"Investigating the ventral-lexical, dorsal-sublexical model of basic reading processes using diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Saskatchewan; University of Alberta","funders":"","keywords":"Diffusion MRI; Dorsum; Reading (process); Neuroscience; Psychology; Neurology; Cognitive psychology; Cognitive science; Computer science; Linguistics; Biology; Medicine; Anatomy; Magnetic resonance imaging","score_opus":0.04938317891747021,"score_gpt":0.3053841916655988,"score_spread":0.2560010127481286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128297135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91595566,0.00084039697,0.07457682,0.0009475169,0.000040674127,0.00010768114,0.00030063745,0.00029967993,0.006930816],"genre_scores_gemma":[0.98517865,0.00036829602,0.012971477,0.000072232986,0.00001520013,0.000033585053,0.00018420252,0.00003794476,0.001138435],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998053,0.000041563526,0.000014215618,0.0000702279,0.000046823377,0.0000219641],"domain_scores_gemma":[0.99891984,0.0003461317,0.00029637627,0.0002250834,0.0001217945,0.00009071774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095947395,0.0006204368,0.00031065522,0.0008079011,0.00031424256,0.0027448733,0.00075116963,0.00072506105,0.0019036598],"category_scores_gemma":[0.003716172,0.0003699379,0.00038169124,0.0005134502,0.0012125515,0.0042412025,0.00052622095,0.0012689813,0.00042224798],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010850851,0.00071371015,0.12725286,0.0008725167,0.00057465385,0.0014096277,0.0044967295,0.016569197,0.58378273,0.091508165,0.0023835578,0.16935116],"study_design_scores_gemma":[0.00021130173,0.0016451787,0.43061697,0.00017448651,0.0004422488,0.0038938145,0.0043220995,0.2318982,0.12095198,0.20050056,0.005136768,0.00020647526],"about_ca_topic_score_codex":0.0030201424,"about_ca_topic_score_gemma":0.0049615786,"teacher_disagreement_score":0.0030201424,"about_ca_system_score_codex":0.00052819634,"about_ca_system_score_gemma":0.0008300838,"threshold_uncertainty_score":0.006368339},"labels":[],"label_agreement":null},{"id":"W2128462670","doi":"10.1177/1073858413513502","title":"The Language Connectome","year":2013,"lang":"en","type":"review","venue":"The Neuroscientist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":338,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Neuroscience; Uncinate fasciculus; Fasciculus; Superior longitudinal fasciculus; Medial longitudinal fasciculus; Inferior longitudinal fasciculus; Fiber tract; Psychology; Tractography; Diffusion MRI; Medicine; Central nervous system; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.16843741861229986,"score_gpt":0.45281744539152263,"score_spread":0.2843800267792228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128462670","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00072291784,0.98611414,0.00067646726,0.0017809636,0.00043060433,0.00001431763,0.00013102667,0.000023992296,0.010105596],"genre_scores_gemma":[0.0058161663,0.9880527,0.0009020668,0.00073393557,0.00047677208,0.00003857597,0.00024839022,0.0000073058104,0.0037241003],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988484,0.000024754476,0.000015668104,0.000028543138,0.00003217735,0.000014053719],"domain_scores_gemma":[0.99982256,0.0000919376,0.000027838434,0.000005492152,0.00003459144,0.000017583536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002829711,0.0007364868,0.00069831987,0.0025145651,0.00037341967,0.0013584503,0.0006058808,0.0011992313,0.011048971],"category_scores_gemma":[0.0006196975,0.00021390426,0.00034096203,0.002152659,0.0008164572,0.0017071188,0.0009684551,0.0014776798,0.0029387972],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005443672,0.000027515405,0.0005006758,0.0081696445,0.00011166485,0.0010033374,0.00016561046,0.00035851687,0.0024534366,0.02032245,0.03859838,0.92823434],"study_design_scores_gemma":[0.000014532947,0.0000305781,0.002856103,0.0034908191,0.000074707634,0.0074891974,0.00015394572,0.00012254523,0.0007751881,0.010718929,0.97424424,0.00002921467],"about_ca_topic_score_codex":0.0019745089,"about_ca_topic_score_gemma":0.0034378197,"teacher_disagreement_score":0.011048971,"about_ca_system_score_codex":0.00089276617,"about_ca_system_score_gemma":0.0014811857,"threshold_uncertainty_score":0.03696251},"labels":[],"label_agreement":null},{"id":"W2129393522","doi":"10.1111/j.1552-6569.2009.00430.x","title":"Investigating Agenesis of the Corpus Callosum Using Functional MRI: A Study Examining Interhemispheric Coordination of Motor Control","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; Ottawa Hospital; University of Toronto; Toronto Western Hospital; University of Ottawa","funders":"National Cancer Institute","keywords":"Corpus callosum; Medicine; Agenesis of the corpus callosum; Corpus Callosum Agenesis; Magnetic resonance imaging; Agenesis; White matter; Functional magnetic resonance imaging; Asymptomatic; Neuroscience; Anatomy; Psychology; Radiology; Pathology","score_opus":0.09708305232098167,"score_gpt":0.3415592975450382,"score_spread":0.24447624522405653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129393522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994716,0.00010907671,0.00016648129,0.000025143978,0.0000021189014,0.0000059976915,0.000006283741,0.000002506178,0.00021079717],"genre_scores_gemma":[0.99942124,0.00011909997,0.00029927253,0.0000279628,0.000011719742,0.000005356067,0.000021629916,0.0000036583563,0.00009016969],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974567,0.00005120879,0.00003235725,0.00008240403,0.000036967976,0.000051320745],"domain_scores_gemma":[0.9991054,0.00034614597,0.00022205217,0.00007935279,0.0000844511,0.00016263899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044372768,0.00054772047,0.00027895338,0.00091723347,0.0006126194,0.00032667207,0.00040249366,0.0008438222,0.0007169235],"category_scores_gemma":[0.0021035362,0.00027721256,0.0002540297,0.00034526852,0.0012297437,0.0004962615,0.00036374698,0.0004887671,0.00018939517],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012836986,0.0014707637,0.59991777,0.0002783587,0.00020534027,0.20323972,0.0113849575,0.00028792807,0.15503165,0.00030527962,0.00027302917,0.026321517],"study_design_scores_gemma":[0.00015132267,0.0037233096,0.6611531,0.000030102157,0.00018861744,0.3128494,0.002828504,0.0007627109,0.016480617,0.0004315862,0.001342471,0.000058188503],"about_ca_topic_score_codex":0.0018875235,"about_ca_topic_score_gemma":0.0021866842,"teacher_disagreement_score":0.0018875235,"about_ca_system_score_codex":0.00023030242,"about_ca_system_score_gemma":0.0003774155,"threshold_uncertainty_score":0.0037530065},"labels":[],"label_agreement":null},{"id":"W2130808757","doi":"10.1523/eneuro.0003-15.2015","title":"Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence","year":2015,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Institute on Drug Abuse; Alberta Children's Hospital Foundation; Universities Space Research Association; National Institutes of Health; Children's Hospital Foundation; Government of Canada; McGill University","keywords":"White matter; Gray (unit); Psychology; Voxel; Neuroscience; Anatomy; Developmental psychology; Magnetic resonance imaging; Biology; Medicine; Artificial intelligence; Computer science","score_opus":0.022789641840295485,"score_gpt":0.3077530727363132,"score_spread":0.2849634308960177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130808757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989379,0.00016077732,0.00034535342,0.000018221768,0.0000014952859,0.000003047865,0.00017741845,0.0000102115755,0.0003455548],"genre_scores_gemma":[0.999315,0.000102618564,0.00026969254,0.000004924831,0.0000017306127,0.000004754551,0.00013949763,0.000007871577,0.00015378698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999754,0.000060290422,0.000015929532,0.00008192181,0.000042609685,0.00004518387],"domain_scores_gemma":[0.9988331,0.00041928558,0.0003912583,0.00012236137,0.00014002348,0.00009395685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060312997,0.00018715675,0.00023479128,0.0006476148,0.0001433111,0.00042975892,0.00012412696,0.00020906143,0.0009580056],"category_scores_gemma":[0.002030184,0.00018986309,0.00022291378,0.0003675298,0.00022496909,0.00025630413,0.00038167305,0.00016739285,0.00015522595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008898262,0.000045486595,0.9481877,0.000046411347,0.00015146675,0.00024696565,0.001004234,0.00093139533,0.028560352,0.00023469052,0.00020308117,0.0194985],"study_design_scores_gemma":[7.558821e-7,0.00003242961,0.99883395,0.000002885806,0.000012544291,0.000077756915,0.00006762095,0.0002310709,0.0006035204,0.000043945773,0.00009146882,0.0000021051603],"about_ca_topic_score_codex":0.0033857299,"about_ca_topic_score_gemma":0.0053174207,"teacher_disagreement_score":0.0033857299,"about_ca_system_score_codex":0.00013824394,"about_ca_system_score_gemma":0.00017028302,"threshold_uncertainty_score":0.0067320466},"labels":[],"label_agreement":null},{"id":"W2130874647","doi":"10.1016/j.neuroimage.2006.02.046","title":"Clustered functional MRI of overt speech production","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Baycrest Hospital; University of Toronto; Sunnybrook Health Science Centre; Toronto Rehabilitation Institute; Health Sciences Centre","funders":"","keywords":"Speech production; Vowel; Psychology; Neurocomputational speech processing; Functional magnetic resonance imaging; Motor cortex; Neuroscience; Cerebellum; Audiology; Motor control; Speech recognition; Computer science; Speech perception; Medicine; Perception","score_opus":0.05686309059751046,"score_gpt":0.3182292509501781,"score_spread":0.2613661603526677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130874647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98485434,0.0007356694,0.010591644,0.0001396368,0.000033515837,0.00004178431,0.00060189405,0.00011985645,0.0028818406],"genre_scores_gemma":[0.9935907,0.00024852593,0.0039873193,0.000036273235,0.000041671155,0.00001905768,0.0003730882,0.00007212859,0.001631176],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999897,0.000022562792,0.000009621228,0.000031043375,0.000019465393,0.00002033505],"domain_scores_gemma":[0.9995241,0.00023035916,0.000061268656,0.000050274604,0.00009139464,0.000042571013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002664568,0.00033686592,0.00021103151,0.00074311806,0.000258303,0.00040359062,0.00030096594,0.00047191154,0.0027180507],"category_scores_gemma":[0.0016905972,0.0003312938,0.000149917,0.00048527395,0.00033966897,0.0004348369,0.00027312755,0.00041333443,0.0005422441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032728347,0.00018724464,0.018127698,0.00037689554,0.00019506473,0.0043312083,0.0012058592,0.006222879,0.8897672,0.0013842277,0.0017629582,0.07316589],"study_design_scores_gemma":[0.00015544055,0.0010603963,0.790152,0.00009193235,0.0002583022,0.012242624,0.0010126925,0.028098734,0.15880065,0.0034420725,0.004569382,0.00011576714],"about_ca_topic_score_codex":0.005030406,"about_ca_topic_score_gemma":0.006538568,"teacher_disagreement_score":0.005030406,"about_ca_system_score_codex":0.0002845258,"about_ca_system_score_gemma":0.00032974413,"threshold_uncertainty_score":0.010002255},"labels":[],"label_agreement":null},{"id":"W2131173886","doi":"10.1109/nebec.2013.92","title":"Entropic Framework for Nonrigid Registration of Diffusion Tensor Images","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Robustness (evolution); Diffusion MRI; Structure tensor; Image registration; Computer vision; Tensor (intrinsic definition); Distortion (music); Artificial intelligence; Computer science; Noise (video); Mathematics; Image (mathematics); Geometry","score_opus":0.054502831960675305,"score_gpt":0.36635368968041493,"score_spread":0.31185085771973964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131173886","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032912379,0.00024955827,0.99559927,0.00007681004,0.0000316279,0.000016975288,0.000021518736,0.00008113229,0.0006318234],"genre_scores_gemma":[0.38326228,0.001836817,0.60449064,0.00018766423,0.0003689574,0.00025783048,0.00026962074,0.00034519893,0.008980966],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933213,0.00022077656,0.00004334825,0.000119754,0.0002419021,0.000042027146],"domain_scores_gemma":[0.9994166,0.00018691867,0.00011248963,0.00013011893,0.0001001674,0.000053777876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011280559,0.0008857876,0.0008624882,0.001240835,0.00038527223,0.000971865,0.0014933704,0.00071725494,0.0013538935],"category_scores_gemma":[0.0019677905,0.0003602461,0.00089480914,0.00072909327,0.0010135967,0.001383651,0.0020807588,0.000982357,0.0005117096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010902535,0.00010785622,0.00048647332,0.00029244093,0.00017363532,0.00060511235,0.00018395309,0.48046547,0.04232757,0.3327787,0.0019266541,0.14054309],"study_design_scores_gemma":[0.0000042067513,0.000048198013,0.00021981794,0.0000084966305,0.000013897624,0.00010201146,0.000010049376,0.9537514,0.0031083785,0.04115898,0.0015481656,0.000026444935],"about_ca_topic_score_codex":0.0017401569,"about_ca_topic_score_gemma":0.0019351873,"teacher_disagreement_score":0.0017401569,"about_ca_system_score_codex":0.00056273915,"about_ca_system_score_gemma":0.0009271071,"threshold_uncertainty_score":0.005965829},"labels":[],"label_agreement":null},{"id":"W2132148195","doi":"10.1016/j.neuroimage.2012.02.083","title":"Very large fMRI study using the IMAGEN database: Sensitivity–specificity and population effect modeling in relation to the underlying anatomy","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto; Montreal Neurological Institute and Hospital","funders":"","keywords":"Voxel; Contrast (vision); Generalization; Artificial intelligence; Computer science; Gaussian; Population; Statistical model; Mixture model; Statistics; Pattern recognition (psychology); Mathematics; Medicine; Physics","score_opus":0.15176380843462187,"score_gpt":0.4096907333328081,"score_spread":0.25792692489818625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132148195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9513905,0.0018392378,0.042432725,0.00031100574,0.000044682372,0.00013950565,0.0025728534,0.00026859634,0.0010009169],"genre_scores_gemma":[0.97951424,0.00028103575,0.016744187,0.0001448216,0.000043916505,0.00014137833,0.0027388306,0.00013590987,0.00025560253],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977367,0.0012796238,0.00015045257,0.0005925857,0.00017973872,0.000060901017],"domain_scores_gemma":[0.9868879,0.009492875,0.0004270197,0.0025553321,0.000434795,0.00020204422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006886242,0.0006118996,0.001283476,0.0008203827,0.0007015179,0.00087902514,0.0010287557,0.0008845423,0.0015063717],"category_scores_gemma":[0.0154865105,0.0005647853,0.0009931164,0.00089139165,0.00075746037,0.00076333736,0.000764332,0.00055151765,0.00023326548],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021270147,0.0016048928,0.49298692,0.0023874938,0.01729221,0.004703692,0.0011386202,0.027095098,0.23271137,0.0056849197,0.012107472,0.18101713],"study_design_scores_gemma":[0.0016467157,0.0015416467,0.8555178,0.00009875189,0.0083527025,0.008481908,0.000313041,0.06788614,0.03741401,0.010391279,0.00806407,0.00029187146],"about_ca_topic_score_codex":0.0043003396,"about_ca_topic_score_gemma":0.010618002,"teacher_disagreement_score":0.006886242,"about_ca_system_score_codex":0.0003247261,"about_ca_system_score_gemma":0.00060775434,"threshold_uncertainty_score":0.03641838},"labels":[],"label_agreement":null},{"id":"W2132465749","doi":"10.1038/nm.3390","title":"Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging","year":2013,"lang":"en","type":"article","venue":"Nature Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":317,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Eye Institute","keywords":"Neuroimaging; Brain tissue; Robustness (evolution); Magnetic resonance imaging; Measure (data warehouse); Computer science; Population; Range (aeronautics); Artificial intelligence; Diffusion MRI; Neuroscience; Pattern recognition (psychology); Biology; Medicine; Data mining; Radiology; Materials science","score_opus":0.030104168357260323,"score_gpt":0.3416549283681054,"score_spread":0.3115507600108451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132465749","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7895207,0.0031228852,0.20374447,0.00026101418,0.000038818573,0.000050496983,0.00035118024,0.00074685854,0.0021636565],"genre_scores_gemma":[0.89098096,0.0023314063,0.10465711,0.00012317234,0.00006963958,0.00006519984,0.0002257067,0.00025479562,0.0012920267],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989986,0.000020407726,0.000005694168,0.000035383775,0.000029722622,0.000008982976],"domain_scores_gemma":[0.99980026,0.0000736484,0.000054829157,0.000029632803,0.000025156492,0.000016464506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004141838,0.00038199007,0.00035838882,0.001442543,0.00031118997,0.00074835523,0.0003741837,0.00058893627,0.0007253496],"category_scores_gemma":[0.00071325543,0.00037531496,0.00024020755,0.0006517848,0.0004777853,0.0012050081,0.0003948138,0.0003396183,0.00020244825],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000267598,0.00004909384,0.019726876,0.0003095771,0.00031917152,0.00030703074,0.00043932148,0.009353548,0.8578221,0.0012045488,0.0005891809,0.10961193],"study_design_scores_gemma":[0.00005341761,0.00044163395,0.2873226,0.00010603491,0.0008433468,0.006123811,0.001178432,0.13284354,0.5392147,0.023612771,0.00806605,0.00019367502],"about_ca_topic_score_codex":0.0012545766,"about_ca_topic_score_gemma":0.002830003,"teacher_disagreement_score":0.001442543,"about_ca_system_score_codex":0.00018742589,"about_ca_system_score_gemma":0.00027811024,"threshold_uncertainty_score":0.002494514},"labels":[],"label_agreement":null},{"id":"W2132888467","doi":"10.1002/hbm.21004","title":"Diffusion tensor‐based regional gray matter tissue segmentation using the international consortium for brain mapping atlases","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Diffusion MRI; White matter; Putamen; Fractional anisotropy; Statistical parametric mapping; Neuroimaging; Segmentation; Nuclear medicine; Magnetic resonance imaging; Medicine; Neuroscience; Artificial intelligence; Psychology; Computer science; Radiology","score_opus":0.12066255001764276,"score_gpt":0.388374009611986,"score_spread":0.2677114595943432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132888467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031986494,0.0004814043,0.9582854,0.00022456792,0.00016321249,0.00030278572,0.002039135,0.0036729395,0.0028441604],"genre_scores_gemma":[0.10016413,0.0005031128,0.891584,0.00008107456,0.00006500945,0.00061686017,0.0030084038,0.001476058,0.0025013639],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99865025,0.0002990799,0.00016636192,0.00041297826,0.0003730873,0.0000983445],"domain_scores_gemma":[0.99838555,0.0003279576,0.00028036453,0.00047988992,0.0004711752,0.000055024662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039792997,0.0012061341,0.00090450275,0.0037787203,0.001018775,0.0022111866,0.0010793847,0.000823341,0.0043177577],"category_scores_gemma":[0.0063381465,0.0006129923,0.0016296796,0.002645442,0.0006998846,0.0015522512,0.0015509549,0.0011664274,0.001988657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036290876,0.00013062816,0.023171514,0.0007229716,0.00071486837,0.0008774745,0.002001867,0.04839204,0.1654124,0.04284161,0.026674034,0.6886977],"study_design_scores_gemma":[0.00020454817,0.0005706836,0.11740546,0.0004330495,0.00084820064,0.0058709905,0.0005708192,0.45330763,0.19425577,0.043345973,0.18239324,0.000793629],"about_ca_topic_score_codex":0.009672002,"about_ca_topic_score_gemma":0.016074605,"teacher_disagreement_score":0.009672002,"about_ca_system_score_codex":0.0012151003,"about_ca_system_score_gemma":0.0031290771,"threshold_uncertainty_score":0.02104479},"labels":[],"label_agreement":null},{"id":"W2133479279","doi":"10.1139/jpn.0850","title":"Alterations of white matter integrity in adults with major depressive disorder: a magnetic resonance imaging study","year":2008,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; White matter; Internal capsule; Diffusion MRI; Magnetic resonance imaging; Major depressive disorder; Depression (economics); Psychology; Late life depression; Internal medicine; Cardiology; Medicine; Superior longitudinal fasciculus; Uncinate fasciculus; Radiology; Amygdala","score_opus":0.018899181319814138,"score_gpt":0.30794645292724077,"score_spread":0.2890472716074266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133479279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994906,0.0002601099,0.000054218668,0.000023756036,0.0000024471653,0.000007915315,0.000053681422,0.0000014917593,0.000105701314],"genre_scores_gemma":[0.99960345,0.00010485947,0.00010335771,0.000032269447,0.000008570531,0.000004450371,0.00008195331,5.3957314e-7,0.00006049564],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998872,0.000023121474,0.000019730332,0.000030465064,0.000021965776,0.000017413817],"domain_scores_gemma":[0.9997166,0.000027315768,0.00014592458,0.000016880835,0.000044923225,0.0000483755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032663377,0.00026398804,0.00025054364,0.00034816223,0.00024214578,0.0002900256,0.00013405674,0.0003814648,0.00069186755],"category_scores_gemma":[0.00073683856,0.0001773397,0.00014987984,0.00020163742,0.00020811273,0.00022874994,0.00021002581,0.00020155881,0.00021649533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007074363,0.00017547303,0.98333144,0.000058350306,0.00013229254,0.0007389537,0.0003602156,0.000040814753,0.00884975,0.00002081231,0.0001704762,0.00541403],"study_design_scores_gemma":[0.000027819975,0.00043432307,0.9975648,0.000005611336,0.000031231084,0.0013948325,0.00009493888,0.000044129127,0.00026240924,0.0000114451805,0.00012681406,0.0000017885372],"about_ca_topic_score_codex":0.0010989289,"about_ca_topic_score_gemma":0.0019445255,"teacher_disagreement_score":0.0010989289,"about_ca_system_score_codex":0.00012967967,"about_ca_system_score_gemma":0.00012195077,"threshold_uncertainty_score":0.002314508},"labels":[],"label_agreement":null},{"id":"W2135798489","doi":"10.1007/s10334-013-0424-1","title":"Assessment of diffusion tensor imaging indices in calf muscles following postural change from standing to supine position","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Supine position; Diffusion MRI; Position (finance); Medicine; Anatomy; Physical medicine and rehabilitation; Biomedical engineering; Radiology; Magnetic resonance imaging; Anesthesia","score_opus":0.04162330151471324,"score_gpt":0.37133367090713076,"score_spread":0.32971036939241755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135798489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987,0.00014940562,0.00044971547,0.000031694195,0.000022747237,0.00004410357,0.00018132782,0.000012624405,0.00040834516],"genre_scores_gemma":[0.99891603,0.00009848312,0.0002586966,0.000017611961,0.000013419933,0.000028810891,0.00018771355,0.0000025570948,0.0004766229],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988925,0.000015310796,0.00001040533,0.000022681641,0.00002938068,0.00003306693],"domain_scores_gemma":[0.9996037,0.00005081411,0.00007331313,0.000020005324,0.0001445679,0.000107692336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017385917,0.00031317485,0.00032807278,0.00040848623,0.00025085197,0.00027952497,0.00015025976,0.00032866228,0.0011405607],"category_scores_gemma":[0.0009590901,0.00010368135,0.00022502424,0.00027957,0.00023640637,0.00023637617,0.0002339707,0.00043050578,0.00018987432],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.038135495,0.002168894,0.32006228,0.00044354284,0.00043316078,0.0030537022,0.0025490425,0.0008026523,0.5222155,0.00018636446,0.0015604551,0.10838888],"study_design_scores_gemma":[0.00006713258,0.007371381,0.966831,0.00001870109,0.00013537223,0.0007188996,0.0006796821,0.0010698306,0.022521915,0.00006233228,0.0004951871,0.000028597404],"about_ca_topic_score_codex":0.0031628746,"about_ca_topic_score_gemma":0.004563873,"teacher_disagreement_score":0.0031628746,"about_ca_system_score_codex":0.00012977145,"about_ca_system_score_gemma":0.0002377164,"threshold_uncertainty_score":0.006288886},"labels":[],"label_agreement":null},{"id":"W2135993898","doi":"10.1161/strokeaha.115.008815","title":"Reduction of Diffusion-Weighted Imaging Contrast of Acute Ischemic Stroke at Short Diffusion Times","year":2015,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Diffusion MRI; Stroke (engine); Effective diffusion coefficient; Ischemia; Diffusion imaging; White matter; Diffusion; Magnetic resonance imaging; Cardiology; Nuclear magnetic resonance; Radiology","score_opus":0.027844593141929067,"score_gpt":0.31585404930161387,"score_spread":0.2880094561596848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135993898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97123015,0.00069730374,0.026794842,0.00011607572,0.0000144870455,0.000019585668,0.000058231883,0.00014364364,0.00092565705],"genre_scores_gemma":[0.9937092,0.00025167118,0.0057002883,0.000022825356,0.0000047126505,0.000017194225,0.000060849045,0.000018023808,0.0002150823],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999491,0.000008678758,0.0000048717097,0.00000855249,0.000017635759,0.000011166321],"domain_scores_gemma":[0.99970967,0.00014991195,0.000064906584,0.000017021426,0.000034662993,0.000023777133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021573478,0.00021490658,0.00018821169,0.00020009547,0.00010187571,0.00030897456,0.00018777236,0.0002939437,0.00067918235],"category_scores_gemma":[0.0014095892,0.00011027311,0.00017369662,0.00011781242,0.00028675783,0.000420729,0.00022178635,0.00026671196,0.0001345394],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007814057,0.000086259985,0.004698167,0.00023678834,0.00007897813,0.000550645,0.00015280744,0.0552105,0.9206329,0.001402393,0.00027771975,0.015891375],"study_design_scores_gemma":[0.00009138092,0.0008968596,0.03237516,0.000031173597,0.00015285483,0.0012974992,0.00008155166,0.24456725,0.7126895,0.005519456,0.0022470232,0.000050273815],"about_ca_topic_score_codex":0.0006225384,"about_ca_topic_score_gemma":0.00038910928,"teacher_disagreement_score":0.00067918235,"about_ca_system_score_codex":0.00026898913,"about_ca_system_score_gemma":0.00024426496,"threshold_uncertainty_score":0.002272129},"labels":[],"label_agreement":null},{"id":"W2137502570","doi":"10.1016/j.jagp.2014.09.008","title":"White Matter Microstructural Integrity Is Associated with Executive Function and Processing Speed in Older Adults with Coronary Artery Disease","year":2014,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Sunnybrook Health Science Centre; Heart and Stroke Foundation; Toronto Rehabilitation Institute; Health Sciences Centre; Sunnybrook Hospital; University of Toronto","funders":"National Institute on Aging; Canadian Institutes of Health Research; Pfizer Canada; National Institutes of Health; Elan Pharma International; Toronto Rehabilitation Institute; W. Garfield Weston Foundation; Ontario Ministry of Health and Long-Term Care; Canada Foundation for Innovation; Lundbeck Canada; Alzheimer Society; Pfizer; Heart and Stroke Foundation of Canada; Ontario Brain Institute; Alzheimer's Drug Discovery Foundation; F. Hoffmann-La Roche","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Cognitive decline; Diffusion MRI; Coronary artery disease; Cognition; Cardiology; Psychology; Neurocognitive; Medicine; Population; Executive dysfunction; Stroke (engine); Hyperintensity; Internal medicine; Audiology; Neuroscience; Dementia; Radiology; Disease; Neuropsychology; Magnetic resonance imaging","score_opus":0.007438545404216487,"score_gpt":0.25857659288771967,"score_spread":0.25113804748350316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137502570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99934524,0.00023296462,0.000045237,0.000040639654,0.000002605984,0.0000033689766,0.00008492209,0.0000029976588,0.00024195027],"genre_scores_gemma":[0.99963534,0.00008019235,0.0000643404,0.00001430555,0.000009867446,0.000002477275,0.000099009805,0.000001008024,0.00009338396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999841,0.0000256471,0.000029907389,0.00004172538,0.000034375757,0.000027426877],"domain_scores_gemma":[0.9987804,0.00015644613,0.00077803,0.00005990107,0.000113599,0.00011159436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043714498,0.00040408433,0.00026126902,0.00081013254,0.00029477748,0.0004569451,0.00020303689,0.00049393985,0.0012653803],"category_scores_gemma":[0.0022964333,0.00019497759,0.00022439433,0.0005549113,0.00024371453,0.0003490156,0.00031112827,0.00034444968,0.00019712957],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018504508,0.00004094212,0.9966853,0.000010106553,0.00008032216,0.00008682041,0.00008880947,0.00006343211,0.00080789806,0.000010854046,0.00005768635,0.0018828204],"study_design_scores_gemma":[0.000002194971,0.000032780965,0.9996921,0.000002378305,0.00001021269,0.00009358246,0.000021896993,0.000082051294,0.000033043172,0.000010952386,0.00001794644,8.967506e-7],"about_ca_topic_score_codex":0.0032242541,"about_ca_topic_score_gemma":0.005903707,"teacher_disagreement_score":0.0032242541,"about_ca_system_score_codex":0.00014273477,"about_ca_system_score_gemma":0.00012354598,"threshold_uncertainty_score":0.0064109564},"labels":[],"label_agreement":null},{"id":"W2137565679","doi":"10.1093/brain/awt370","title":"Inferring a dual-stream model of mentalizing from associative white matter fibres disconnection","year":2014,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mentalization; Arcuate fasciculus; Psychology; Neuroscience; Superior longitudinal fasciculus; Disconnection; Population; White matter; Cognitive psychology; Tractography; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.05117913465380517,"score_gpt":0.335571645426195,"score_spread":0.2843925107723898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137565679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9605353,0.00022394661,0.03552246,0.0006521312,0.00002030417,0.00009450655,0.00027528414,0.000104283994,0.0025718482],"genre_scores_gemma":[0.9952266,0.00011895396,0.0039619305,0.000043771863,0.0000142290855,0.000029839342,0.00014514304,0.000011984057,0.00044751697],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975973,0.00007107825,0.000014836791,0.00007706602,0.000031783366,0.000045479184],"domain_scores_gemma":[0.99909425,0.00039517067,0.00022729138,0.00012035777,0.00006516114,0.00009788527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008389345,0.0006534455,0.00048093108,0.0012535612,0.00028641327,0.0012575057,0.00069292163,0.00052991544,0.0029978715],"category_scores_gemma":[0.0031425222,0.00030577832,0.0007433727,0.00044491887,0.0014354966,0.0014563327,0.00089174294,0.0008478501,0.0003277855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022429675,0.00053603813,0.78189373,0.00038693825,0.0006201852,0.0044186935,0.0042762775,0.03369887,0.06094561,0.04098923,0.00091721356,0.06907436],"study_design_scores_gemma":[0.00027624567,0.00086181716,0.57833004,0.00008513929,0.0005291264,0.0048874887,0.0021208152,0.26232055,0.01153549,0.13762976,0.0013043068,0.00011915277],"about_ca_topic_score_codex":0.0035896844,"about_ca_topic_score_gemma":0.003453,"teacher_disagreement_score":0.0035896844,"about_ca_system_score_codex":0.0005384591,"about_ca_system_score_gemma":0.00054764264,"threshold_uncertainty_score":0.010028899},"labels":[],"label_agreement":null},{"id":"W2137788518","doi":"10.1007/s00259-002-0816-3","title":"Limbic system perfusion in Alzheimer's disease measured by MRI-coregistered HMPAO SPET","year":2002,"lang":"en","type":"article","venue":"European Journal of Nuclear Medicine and Molecular Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Limbic lobe; Limbic system; Posterior cingulate; Orbitofrontal cortex; Entorhinal cortex; Cingulate cortex; Basal forebrain; Hippocampus; Thalamus; Perfusion; Medicine; Anterior cingulate cortex; Parahippocampal gyrus; Cortex (anatomy); Internal medicine; Neuroscience; Temporal lobe; Pathology; Psychology; Prefrontal cortex; Central nervous system; Radiology","score_opus":0.05604775810994017,"score_gpt":0.29053013528331767,"score_spread":0.2344823771733775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137788518","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99493575,0.0010565375,0.0013399135,0.00006180111,0.000010160456,0.000035196088,0.00028658475,0.00003968359,0.0022342722],"genre_scores_gemma":[0.9972965,0.00062573433,0.001022428,0.000043588723,0.000012488974,0.00003141929,0.00013848094,0.000012854915,0.0008165255],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993443,0.000017114558,0.000005130706,0.000013391392,0.000011228339,0.00001869935],"domain_scores_gemma":[0.9998746,0.000045116463,0.000020036467,0.000011547242,0.00002628174,0.000022473081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042005695,0.0005268345,0.00036775536,0.00061651773,0.00029881133,0.00041754436,0.0002626354,0.0006708244,0.0028130768],"category_scores_gemma":[0.00081907935,0.000271696,0.00018236783,0.00044791147,0.00049454573,0.0006962363,0.00022254532,0.0005113549,0.00030369408],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.032961186,0.0008789908,0.13457961,0.0009426014,0.00064914784,0.01796931,0.0016507315,0.004005989,0.6968962,0.0018033708,0.0018930967,0.10576982],"study_design_scores_gemma":[0.0005208283,0.0034700716,0.833424,0.00008825447,0.00087857596,0.02343545,0.00049996556,0.017348306,0.115796916,0.0024340402,0.0020376963,0.00006601998],"about_ca_topic_score_codex":0.007851312,"about_ca_topic_score_gemma":0.0059184143,"teacher_disagreement_score":0.007851312,"about_ca_system_score_codex":0.00038123812,"about_ca_system_score_gemma":0.00037110285,"threshold_uncertainty_score":0.015611231},"labels":[],"label_agreement":null},{"id":"W2138296888","doi":"10.1109/isspit.2006.270855","title":"DTMRI Segmentation using DT-Snakes and DT-Livewire","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Smoothing; Segmentation; Interpolation (computer graphics); Tensor (intrinsic definition); Image segmentation; Diffusion MRI; Divergence (linguistics); Artificial intelligence; Mathematics; Scalar (mathematics); Computer vision; Computer science; Image (mathematics); Pattern recognition (psychology); Algorithm; Geometry; Magnetic resonance imaging","score_opus":0.08870102002145859,"score_gpt":0.3813279861171943,"score_spread":0.29262696609573574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138296888","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052360855,0.00012719313,0.99340147,0.00009665359,0.000022826469,0.000025292733,0.000027718614,0.0005518388,0.00051090505],"genre_scores_gemma":[0.07205386,0.00028028403,0.9255084,0.00010652432,0.0000348646,0.000059620957,0.00015870716,0.00038059542,0.0014171777],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992273,0.00017287635,0.0000790122,0.00015486933,0.00033261764,0.00003341187],"domain_scores_gemma":[0.9984578,0.0005597398,0.00022979103,0.00038121644,0.00029088088,0.00008056614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018911778,0.0007101274,0.0008775841,0.0016993282,0.00047744226,0.0015305331,0.0013219744,0.0016918879,0.0017968657],"category_scores_gemma":[0.0048134946,0.00060762174,0.0011823615,0.0012944476,0.0010116454,0.0021462669,0.0015242833,0.00095917005,0.0008462927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027451478,0.00008108926,0.0017474327,0.0003176435,0.00015718766,0.0002569982,0.00034541902,0.26435205,0.07632893,0.05023292,0.0035514643,0.60235435],"study_design_scores_gemma":[0.000022844932,0.00010572158,0.00077929866,0.000025932239,0.000027293036,0.00042091837,0.000037225906,0.93423635,0.027952647,0.025823914,0.01051163,0.000056246812],"about_ca_topic_score_codex":0.000963121,"about_ca_topic_score_gemma":0.0012425038,"teacher_disagreement_score":0.0018911778,"about_ca_system_score_codex":0.0007811036,"about_ca_system_score_gemma":0.0005679168,"threshold_uncertainty_score":0.010001659},"labels":[],"label_agreement":null},{"id":"W2138757700","doi":"10.1016/j.physd.2009.03.016","title":"Shocks and finite-time singularities in Hele-Shaw flow","year":2009,"lang":"en","type":"article","venue":"Physica D Nonlinear Phenomena","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Gravitational singularity; Hele-Shaw flow; Flow (mathematics); Mechanics; Computer science; Geology; Mathematics; Physics; Mathematical analysis; Open-channel flow","score_opus":0.03371506156988059,"score_gpt":0.3118802008721207,"score_spread":0.2781651393022401,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138757700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70576245,0.0067235217,0.25654858,0.004894061,0.0012755676,0.000101651094,0.00020523356,0.0006054064,0.023883518],"genre_scores_gemma":[0.9849744,0.0011812338,0.006648491,0.0002658799,0.0003131863,0.000024159615,0.00008699897,0.00008735613,0.006418476],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998079,0.00006631558,0.00001829146,0.000029408004,0.000042432217,0.00003571274],"domain_scores_gemma":[0.9985739,0.0006151811,0.0002452396,0.00008806576,0.00013613577,0.00034143386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008381335,0.00090234954,0.0009270457,0.0014151374,0.0006908285,0.0027533588,0.0011321192,0.002374093,0.0022747081],"category_scores_gemma":[0.0058437022,0.000630622,0.0008856196,0.00055401534,0.003424938,0.0033716366,0.0021305203,0.0023288834,0.00029894095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044454282,0.00012233348,0.0039512804,0.00028092996,0.00011144795,0.0034256242,0.0009226328,0.12439217,0.017876672,0.8340129,0.0031166237,0.011342871],"study_design_scores_gemma":[0.000095766,0.0000665081,0.0029394133,0.000046210498,0.000022565207,0.000692661,0.00025746165,0.3660981,0.0011135638,0.6275065,0.0010828765,0.00007833491],"about_ca_topic_score_codex":0.0009781598,"about_ca_topic_score_gemma":0.00034566506,"teacher_disagreement_score":0.0027533588,"about_ca_system_score_codex":0.0007638162,"about_ca_system_score_gemma":0.00040273007,"threshold_uncertainty_score":0.007609725},"labels":[],"label_agreement":null},{"id":"W2139009850","doi":"10.1002/mrm.20962","title":"Effects of temperature and aldehyde fixation on tissue water diffusion properties, studied in an erythrocyte ghost tissue model","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Ex vivo; Fixative; Glutaraldehyde; Fixation (population genetics); In vivo; Chemistry; Agarose; Biophysics; Permeability (electromagnetism); Membrane; Biomedical engineering; Chromatography; Biochemistry; Biology; In vitro","score_opus":0.024414676383765144,"score_gpt":0.30789144914706434,"score_spread":0.2834767727632992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139009850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934121,0.0016557844,0.004150116,0.000049060625,0.000025235515,0.000031377815,0.00014404257,0.00003476306,0.00049751706],"genre_scores_gemma":[0.9891066,0.0014670326,0.008228617,0.000036876132,0.000014991662,0.00004026834,0.00022974331,0.00003997022,0.0008359673],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981457,0.00004876309,0.00002332091,0.000047281337,0.00003623378,0.00002976774],"domain_scores_gemma":[0.9991573,0.0003612661,0.0002663098,0.000094426134,0.00006628658,0.000054381493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048474234,0.00057706784,0.0002631329,0.00019642373,0.00014221214,0.00026878226,0.00029918362,0.00027612815,0.00084318325],"category_scores_gemma":[0.0008812815,0.00026096057,0.00022875954,0.00018128184,0.00040009624,0.00045321937,0.00020805384,0.000409717,0.00018424023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034243093,0.000029694791,0.00015994141,0.00003787102,0.0000070003116,0.000034110795,0.000016724263,0.000158524,0.99876547,0.000027842994,0.0000063060065,0.00041402326],"study_design_scores_gemma":[0.000013076667,0.00063609873,0.0020091431,0.0000036438103,0.000030637715,0.00009202643,0.000011450793,0.00083372305,0.996097,0.000023835591,0.00024221491,0.000007166612],"about_ca_topic_score_codex":0.0012242771,"about_ca_topic_score_gemma":0.0018590213,"teacher_disagreement_score":0.0012242771,"about_ca_system_score_codex":0.00036918887,"about_ca_system_score_gemma":0.0002659966,"threshold_uncertainty_score":0.0028207898},"labels":[],"label_agreement":null},{"id":"W2139169840","doi":"10.1016/j.schres.2012.06.042","title":"White matter tract abnormalities in first-episode psychosis","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Royal Columbian Hospital","funders":"Canadian Institutes of Health Research; Fraser Health Authority","keywords":"Diffusion MRI; Fractional anisotropy; Internal capsule; White matter; Coronal plane; Psychosis; Psychology; Magnetic resonance imaging; External capsule; Audiology; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.14377782658362623,"score_gpt":0.4326362121774551,"score_spread":0.2888583855938289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139169840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977785,0.00094500504,0.00011482484,0.00013747651,0.00000685862,0.000006092724,0.00007374063,0.0000067852666,0.00093077257],"genre_scores_gemma":[0.99909794,0.0004931854,0.000121064586,0.000021056536,0.000008855343,0.0000025916725,0.000049664242,0.0000023277107,0.00020339573],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999398,0.000013448903,0.00000825679,0.000008300141,0.000013468027,0.000016780616],"domain_scores_gemma":[0.999617,0.000087905566,0.0001506381,0.000019937384,0.000038077396,0.000086429136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034691909,0.00028803057,0.00022166566,0.0013582464,0.00054780184,0.00058834744,0.0002925963,0.00056069554,0.0020311833],"category_scores_gemma":[0.001243754,0.00026827637,0.0001594182,0.0006593136,0.00055462815,0.00070384634,0.00037779493,0.00041888253,0.00015524046],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039227474,0.00024031186,0.85499907,0.00035159412,0.0002744487,0.02415203,0.0011660855,0.0011373727,0.07241998,0.000732993,0.00058602006,0.040017333],"study_design_scores_gemma":[0.00002664036,0.0001641366,0.9848409,0.000030571562,0.000045341116,0.010442356,0.00051506533,0.0004653261,0.002526532,0.0007256271,0.00020651998,0.000011025743],"about_ca_topic_score_codex":0.009646344,"about_ca_topic_score_gemma":0.01610656,"teacher_disagreement_score":0.009646344,"about_ca_system_score_codex":0.0006436549,"about_ca_system_score_gemma":0.00056917313,"threshold_uncertainty_score":0.019180417},"labels":[],"label_agreement":null},{"id":"W2139297841","doi":"10.1093/brain/aws222","title":"Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language","year":2012,"lang":"en","type":"review","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":489,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Fasciculus; Neuroscience; Uncinate fasciculus; Context (archaeology); Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Biology; Tractography; Medicine; Diffusion MRI","score_opus":0.08037340626828889,"score_gpt":0.42540054813581935,"score_spread":0.3450271418675305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139297841","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019359996,0.9516647,0.0031489397,0.038577642,0.0017608246,0.0000074582226,0.000029097848,0.000017717779,0.0028576604],"genre_scores_gemma":[0.039561335,0.93455046,0.0029076596,0.01656188,0.0054957406,0.00004414469,0.00006639746,0.00003702609,0.0007754047],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965635,0.0009740458,0.00063674996,0.0009881929,0.0006795339,0.00015796194],"domain_scores_gemma":[0.98100257,0.014381183,0.0010394576,0.00056054775,0.002683348,0.0003330419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011121248,0.000589679,0.0017676338,0.0032944023,0.0013246988,0.00461397,0.0031766575,0.005017866,0.0012774038],"category_scores_gemma":[0.020408077,0.0004062312,0.00083765696,0.0031334057,0.01583638,0.011974551,0.0028204892,0.007526885,0.0005859804],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002611905,0.000027256272,0.0018528088,0.0126607,0.00027637603,0.0015802404,0.00801805,0.0010123381,0.0017378484,0.29792836,0.021091256,0.6535536],"study_design_scores_gemma":[0.00003500361,0.00014704712,0.006055247,0.020736888,0.00022793321,0.0037280843,0.0072853607,0.00055952126,0.0012389253,0.41195405,0.54785556,0.00017640302],"about_ca_topic_score_codex":0.0036845081,"about_ca_topic_score_gemma":0.0033995933,"teacher_disagreement_score":0.011121248,"about_ca_system_score_codex":0.002489763,"about_ca_system_score_gemma":0.005853386,"threshold_uncertainty_score":0.05881548},"labels":[],"label_agreement":null},{"id":"W2139416445","doi":"10.1002/hbm.20117","title":"Visualization of thalamic nuclei on high resolution, multi‐averaged T<sub>1</sub> and T<sub>2</sub> maps acquired at 1.5 T","year":2005,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Heart and Stroke Foundation of Canada","keywords":"Thalamus; Hum; Visualization; Nuclear magnetic resonance; Magnetic resonance imaging; Resolution (logic); Physics; Neuroscience; Nucleus; Nuclear medicine; Artificial intelligence; Psychology; Medicine; Computer science; Radiology","score_opus":0.051634184724053726,"score_gpt":0.31657758807169245,"score_spread":0.2649434033476387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139416445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89439535,0.0009936312,0.100586206,0.00015250927,0.000014551835,0.00004169093,0.00033047414,0.00039696685,0.0030886887],"genre_scores_gemma":[0.9183824,0.00073572766,0.078824475,0.000058889575,0.000022417838,0.00004884972,0.00031312963,0.00010904613,0.0015049808],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999702,0.0000052717805,0.0000016903462,0.000007352114,0.000009351842,0.0000061743435],"domain_scores_gemma":[0.99985814,0.00004225686,0.000029410154,0.000016758679,0.00003282198,0.00002063595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002118084,0.00036861215,0.00015045547,0.0008349335,0.0001924683,0.00041293565,0.00020468539,0.0003268138,0.001854953],"category_scores_gemma":[0.0006110109,0.00024130526,0.00013390894,0.00030941083,0.00022086714,0.00047332657,0.00024550076,0.00021009851,0.0002412381],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030798255,0.000016888825,0.0021196287,0.00014318954,0.00004366339,0.00062993605,0.00021359061,0.0010268738,0.9603241,0.00030420726,0.00028774806,0.03458224],"study_design_scores_gemma":[0.00009188824,0.0009672711,0.23171978,0.000070696944,0.00034553313,0.021428853,0.00068565784,0.033444904,0.69760656,0.0050357473,0.008478449,0.0001247099],"about_ca_topic_score_codex":0.00089240505,"about_ca_topic_score_gemma":0.002302993,"teacher_disagreement_score":0.001854953,"about_ca_system_score_codex":0.000105497864,"about_ca_system_score_gemma":0.00015590458,"threshold_uncertainty_score":0.0062054396},"labels":[],"label_agreement":null},{"id":"W2139784227","doi":"10.1093/brain/awl256","title":"Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer's disease","year":2006,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":382,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Montreal Neurological Institute and Hospital; Hospital for Sick Children; Jewish General Hospital; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Atrophy; Temporal lobe; Magnetic resonance imaging; Dementia; Alzheimer's disease; Cortex (anatomy); Cerebral cortex; Frontal lobe; Neuroscience; Degenerative disease; Temporal cortex; Psychology; Disease; Medicine; Central nervous system disease; Pathology; Radiology; Epilepsy","score_opus":0.04068057329156473,"score_gpt":0.3452087382727024,"score_spread":0.30452816498113766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139784227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887425,0.00047372974,0.00024836152,0.0000068180752,0.0000013123929,0.000005127882,0.000059541715,0.000007950487,0.00032281707],"genre_scores_gemma":[0.99930155,0.00015104117,0.00032858233,0.0000071010545,0.0000040626846,0.0000046729388,0.000058911286,0.0000022069441,0.00014185824],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997986,0.00006106641,0.00002508793,0.00003527851,0.00005509229,0.000025026706],"domain_scores_gemma":[0.999191,0.00016382501,0.00038899403,0.00008161553,0.00009973562,0.000074803254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005330454,0.00022982818,0.0001975209,0.0020774652,0.00020134963,0.0002425402,0.00016050143,0.00018340348,0.00073926325],"category_scores_gemma":[0.0017993153,0.00023236958,0.00016637333,0.00066418963,0.00047938447,0.00022342212,0.00031292654,0.00015050941,0.00010952383],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003020171,0.00011303251,0.8503355,0.0002181264,0.00029234405,0.002141386,0.0011175055,0.0012020837,0.090915285,0.00027871557,0.00025024035,0.050115563],"study_design_scores_gemma":[0.0000031423388,0.000060215236,0.99790466,0.0000034090772,0.000010411759,0.0009412953,0.000046299177,0.00008609056,0.00080690085,0.00008799944,0.000046509034,0.0000030336928],"about_ca_topic_score_codex":0.0017915877,"about_ca_topic_score_gemma":0.0026264826,"teacher_disagreement_score":0.0020774652,"about_ca_system_score_codex":0.00012790118,"about_ca_system_score_gemma":0.00015252453,"threshold_uncertainty_score":0.0035623312},"labels":[],"label_agreement":null},{"id":"W2139854474","doi":"10.1503/jpn.090177","title":"White-matter abnormalities in adolescents with long-term inhalant and cannabis use: a diffusion magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"White matter; Intoxicative inhalant; Psychosocial; Cannabis; Fractional anisotropy; Diffusion MRI; Psychiatry; Psychology; Medicine; Pediatrics; Magnetic resonance imaging; Clinical psychology; Radiology","score_opus":0.017109069483508214,"score_gpt":0.30101840219703285,"score_spread":0.28390933271352464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139854474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998265,0.00005600943,0.000023556724,0.000008684111,8.957112e-7,0.0000044703206,0.00002018914,6.6329653e-7,0.00005895342],"genre_scores_gemma":[0.9997061,0.00008165807,0.00009426937,0.0000108150225,0.0000028966842,0.0000059463882,0.00004649082,8.5605404e-7,0.000051000607],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998472,0.000027070439,0.00002117955,0.000032860826,0.000038891125,0.00003279646],"domain_scores_gemma":[0.9993813,0.000087171975,0.00025314197,0.000023168186,0.00009331163,0.00016193379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031611364,0.00031763656,0.000314791,0.00077343354,0.00047503557,0.00038104283,0.00021710327,0.00046739017,0.00080020097],"category_scores_gemma":[0.00092846976,0.0002841111,0.00022162442,0.00043326066,0.00043114254,0.00038506326,0.00040791987,0.0003927879,0.00011252118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070991235,0.00008897614,0.99509454,0.000013869727,0.000019820023,0.0013758505,0.0003997715,0.000013376564,0.0017258982,0.000014762052,0.000023756009,0.0011584752],"study_design_scores_gemma":[0.0000057521006,0.00015461666,0.996323,0.000005913077,0.000020078298,0.0027256855,0.00045671134,0.000041789095,0.00018663565,0.000008356177,0.000069465445,0.0000020275131],"about_ca_topic_score_codex":0.0056288503,"about_ca_topic_score_gemma":0.011514633,"teacher_disagreement_score":0.0056288503,"about_ca_system_score_codex":0.00033337984,"about_ca_system_score_gemma":0.00048626025,"threshold_uncertainty_score":0.011192203},"labels":[],"label_agreement":null},{"id":"W2140306145","doi":"","title":"Diffusion tensor tractography of the limbic system.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":273,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fornix; Diffusion MRI; Tractography; White matter; Fractional anisotropy; Limbic system; Cingulum (brain); Medicine; Neuroscience; Subarachnoid space; Cerebrospinal fluid; Pathology; Psychology; Magnetic resonance imaging; Radiology; Central nervous system; Hippocampus","score_opus":0.04929022505852533,"score_gpt":0.27706968315224256,"score_spread":0.22777945809371725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140306145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6304983,0.03009946,0.30613238,0.0024275507,0.00027536874,0.0008771094,0.008863287,0.0017800893,0.019046444],"genre_scores_gemma":[0.8696481,0.005884529,0.11623016,0.00019643232,0.00006262376,0.00027008157,0.0019334534,0.00026112873,0.0055134986],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99986017,0.000040853385,0.00001448289,0.000041659623,0.00003113996,0.000011669047],"domain_scores_gemma":[0.9993537,0.00015886473,0.00021981134,0.000092310926,0.00011578969,0.000059491264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007389558,0.000542179,0.00030154956,0.001099407,0.0003132737,0.00056831364,0.00029313797,0.00043177346,0.0045150016],"category_scores_gemma":[0.0022482364,0.00020642819,0.00030832927,0.00081077317,0.00043439795,0.0006110694,0.00020779193,0.0003772493,0.0010861859],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013168362,0.00017284568,0.15270682,0.0033752471,0.0012485362,0.0040992205,0.00086963875,0.017344516,0.30243725,0.010588468,0.015903668,0.48993692],"study_design_scores_gemma":[0.00022315455,0.0007890584,0.698483,0.0006928209,0.0007183389,0.032943696,0.00031109105,0.0808252,0.07577786,0.04441269,0.064610824,0.00021237867],"about_ca_topic_score_codex":0.010203923,"about_ca_topic_score_gemma":0.01725192,"teacher_disagreement_score":0.010203923,"about_ca_system_score_codex":0.0007173981,"about_ca_system_score_gemma":0.0013446669,"threshold_uncertainty_score":0.020289063},"labels":[],"label_agreement":null},{"id":"W2140382254","doi":"10.1002/jmri.21166","title":"Minimum detectable difference of MR diffusion maps in acute ischemic stroke","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Diffusion MRI; Fractional anisotropy; Region of interest; Medicine; Effective diffusion coefficient; Nuclear medicine; Stroke (engine); White matter; Acute stroke; Magnetic resonance imaging; Radiology; Internal medicine; Physics","score_opus":0.02539094773858129,"score_gpt":0.29523405280556747,"score_spread":0.26984310506698617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140382254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97052616,0.0013585554,0.027277146,0.00006472283,0.000013304786,0.000048699756,0.00019440816,0.00013139019,0.00038563478],"genre_scores_gemma":[0.9893379,0.00011681241,0.010259474,0.000011091258,0.00001269214,0.000031279335,0.00015229311,0.00001746025,0.000060968247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978078,0.0010765403,0.00026206797,0.00034358405,0.00045015028,0.00005995173],"domain_scores_gemma":[0.98697066,0.008682997,0.0023576613,0.0007650994,0.0009768613,0.00024668535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003472149,0.0004024432,0.00044894574,0.0008482977,0.00018559098,0.000549782,0.000437777,0.00050973217,0.00045682333],"category_scores_gemma":[0.038748965,0.00019554581,0.00017077262,0.00035939933,0.000441679,0.0005305654,0.000488503,0.00032747688,0.00015295781],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010433096,0.00042829386,0.56974596,0.0012172193,0.0007886159,0.0012476164,0.0017311858,0.012593637,0.07846594,0.0009599949,0.0019504679,0.3204379],"study_design_scores_gemma":[0.00026239085,0.0025734163,0.9064736,0.0000884054,0.00023538692,0.006711343,0.00032468964,0.04497463,0.032356583,0.0042201853,0.001676035,0.00010334338],"about_ca_topic_score_codex":0.00044188095,"about_ca_topic_score_gemma":0.0004854748,"teacher_disagreement_score":0.003472149,"about_ca_system_score_codex":0.00025884734,"about_ca_system_score_gemma":0.00017616888,"threshold_uncertainty_score":0.018362701},"labels":[],"label_agreement":null},{"id":"W2141254413","doi":"10.1109/iembs.2008.4650072","title":"Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Hong Kong; School of Medicine, New York University; York University; University of Texas Southwestern Medical Center","keywords":"Kurtosis; Diffusion MRI; Diffusion; Tensor (intrinsic definition); Gaussian; Eigenvalues and eigenvectors; Nuclear magnetic resonance; Artificial intelligence; Algorithm; Mathematics; Physics; Computer science; Pattern recognition (psychology); Biological system; Statistics; Geometry; Medicine; Biology; Thermodynamics","score_opus":0.057458511628273215,"score_gpt":0.3444837264798528,"score_spread":0.2870252148515796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141254413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24562807,0.001233219,0.7502146,0.00013238669,0.00004260154,0.000095827236,0.00038409934,0.0004799122,0.0017893694],"genre_scores_gemma":[0.607075,0.0023441724,0.38823208,0.00003462292,0.00004235916,0.00012645674,0.00050060375,0.00010920149,0.0015355553],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998153,0.00003719604,0.000018670928,0.000039786057,0.00006858966,0.000020552246],"domain_scores_gemma":[0.99966,0.00007236496,0.00006552503,0.00004000655,0.00013996856,0.000022076316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060930237,0.0006524396,0.00039756313,0.0017911267,0.00015443008,0.0004901198,0.0002529554,0.00029996046,0.0007396057],"category_scores_gemma":[0.0013056458,0.00017135507,0.00037861842,0.00093852147,0.00039384468,0.0009927861,0.00039783193,0.0004143114,0.00024320617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013183216,0.000028827968,0.0031587847,0.00023065289,0.00005812923,0.00021991468,0.00015437645,0.008247352,0.8830829,0.0050900453,0.00036989467,0.099227294],"study_design_scores_gemma":[0.000033596025,0.00030618062,0.029874573,0.000039976596,0.00013615725,0.0020370143,0.00024994405,0.36449444,0.58179706,0.01233248,0.008474171,0.00022450976],"about_ca_topic_score_codex":0.0008247206,"about_ca_topic_score_gemma":0.0009464109,"teacher_disagreement_score":0.0017911267,"about_ca_system_score_codex":0.00021671756,"about_ca_system_score_gemma":0.0003481947,"threshold_uncertainty_score":0.0032223463},"labels":[],"label_agreement":null},{"id":"W2141293175","doi":"10.1017/s0317167100005801","title":"Tumor Effects on Cerebral White Matter as Characterized by Diffusion Tensor Tractography","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; Western University","funders":"","keywords":"White matter; Diffusion MRI; Corticospinal tract; Anaplastic astrocytoma; Astrocytoma; Corpus callosum; Tractography; Brain tumor; Pathology; Infiltration (HVAC); Fiber tract; Glioma; Medicine; Magnetic resonance imaging; Radiology; Materials science; Cancer research","score_opus":0.027948970278026657,"score_gpt":0.2981608682350211,"score_spread":0.2702118979569944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141293175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99553275,0.00033895802,0.0032451414,0.000028818049,0.0000026425403,0.000018672496,0.00011037505,0.0000342935,0.00068850035],"genre_scores_gemma":[0.9981623,0.00022724055,0.0013324448,0.0000040217224,0.0000017746761,0.000009292362,0.0001076608,0.00001101359,0.00014418979],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999068,0.000022320339,0.000006941627,0.000014217875,0.00003361581,0.00001613378],"domain_scores_gemma":[0.9995291,0.00011018899,0.00021825534,0.000038398182,0.00006620131,0.000037821224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033194255,0.00022796069,0.000097128184,0.0005542799,0.00016069975,0.0002895184,0.00008398915,0.00016519187,0.0005548225],"category_scores_gemma":[0.001494389,0.00010700474,0.00010591426,0.0003090877,0.0003717214,0.00025366544,0.00014181524,0.00016989783,0.00013427435],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014175607,0.00009675082,0.41606212,0.00023510023,0.00025402935,0.006962121,0.00087685394,0.0081013655,0.51729536,0.0012953631,0.0005381919,0.046865262],"study_design_scores_gemma":[0.00004229852,0.0006079389,0.812129,0.000031430325,0.00019669879,0.017111514,0.00021366464,0.013917328,0.15172982,0.0009325291,0.0030477338,0.000039976727],"about_ca_topic_score_codex":0.0058261706,"about_ca_topic_score_gemma":0.007455423,"teacher_disagreement_score":0.0058261706,"about_ca_system_score_codex":0.00050561223,"about_ca_system_score_gemma":0.00041756348,"threshold_uncertainty_score":0.01158452},"labels":[],"label_agreement":null},{"id":"W2142009729","doi":"10.1016/s0304-3940(02)01333-2","title":"Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins","year":2003,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; McMaster University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Heritability; Corpus callosum; Concordance; Dizygotic twins; Trait; Brain morphometry; Biology; Twin study; Magnetic resonance imaging; Dizygotic twin; Psychology; Audiology; Developmental psychology; Physiology; Evolutionary biology; Neuroscience; Genetics; Medicine","score_opus":0.05944971591487432,"score_gpt":0.35070261120484103,"score_spread":0.29125289528996673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142009729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996623,0.0000578164,0.00004918142,0.000016357224,0.0000036811773,0.000004920251,0.00004029908,0.0000012069914,0.00016424526],"genre_scores_gemma":[0.9994362,0.00009883943,0.00012931788,0.000020147261,0.000010800107,0.000008690089,0.000055341046,0.000009522194,0.00023103938],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99954236,0.000108721964,0.000049255406,0.00015087152,0.000087066044,0.00006177753],"domain_scores_gemma":[0.99847347,0.00059724,0.00034427145,0.00020306012,0.00012761318,0.00025441963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004897182,0.00083152857,0.0006729455,0.0023282452,0.0012506781,0.00061758986,0.0007890185,0.0010698604,0.0019981405],"category_scores_gemma":[0.0036988512,0.0006498772,0.00040773556,0.0011033078,0.0016135613,0.00042333716,0.0011561612,0.0007262196,0.00025423008],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011979467,0.001606975,0.63579535,0.00018508248,0.0006751337,0.04822316,0.013516313,0.00058944756,0.26721177,0.002047595,0.0005594563,0.01761027],"study_design_scores_gemma":[0.00013000687,0.0010150304,0.93950933,0.000024645204,0.00037280074,0.04527832,0.0019096573,0.00055772765,0.009956795,0.0004265695,0.000759187,0.00005988822],"about_ca_topic_score_codex":0.006262488,"about_ca_topic_score_gemma":0.0035546923,"teacher_disagreement_score":0.006262488,"about_ca_system_score_codex":0.00039699866,"about_ca_system_score_gemma":0.0003729396,"threshold_uncertainty_score":0.012452066},"labels":[],"label_agreement":null},{"id":"W2142154934","doi":"10.1002/mrm.25107","title":"Biomimetic phantom for the validation of diffusion magnetic resonance imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; University of Manchester; Cancer Research UK; European Commission; Ministère des relations internationales et de la Francophonie","keywords":"Imaging phantom; Diffusion MRI; Materials science; Fractional anisotropy; Scanner; White matter; Magnetic resonance imaging; Biomedical engineering; Nuclear magnetic resonance; Reproducibility; Diffusion; Nuclear medicine; Medicine; Optics; Physics; Chemistry; Radiology","score_opus":0.038696166987334316,"score_gpt":0.34343851739133896,"score_spread":0.30474235040400466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142154934","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2692473,0.007141867,0.7110074,0.00069185515,0.00068324135,0.0013982669,0.0013998174,0.0024739958,0.00595624],"genre_scores_gemma":[0.35213202,0.003050576,0.6371532,0.00030571566,0.00008604754,0.0017034531,0.0019017643,0.00022891379,0.0034383717],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998965,0.00025502138,0.0001030697,0.00019947605,0.00043736806,0.00004000421],"domain_scores_gemma":[0.99755824,0.0009331358,0.00050599774,0.00043057965,0.00046557028,0.000106489475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030935174,0.00096577103,0.00036590104,0.00076548086,0.000355683,0.00045007115,0.00065409014,0.0010740617,0.0023286906],"category_scores_gemma":[0.0036176818,0.00032012368,0.0003456021,0.00039882644,0.0006616987,0.00069158076,0.00048765788,0.0006149418,0.0009051916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057437377,0.00007146991,0.0002461653,0.00013681955,0.0000098574355,0.000040902458,0.000018522926,0.0004169628,0.9945866,0.00045025905,0.00014634148,0.00381868],"study_design_scores_gemma":[0.000027836155,0.00075701706,0.0021816308,0.00005423901,0.000051768257,0.0011008595,0.000024058707,0.0051287035,0.97878873,0.00032518338,0.011537018,0.000022954198],"about_ca_topic_score_codex":0.00024867425,"about_ca_topic_score_gemma":0.0004253083,"teacher_disagreement_score":0.0030935174,"about_ca_system_score_codex":0.00037717668,"about_ca_system_score_gemma":0.00053438003,"threshold_uncertainty_score":0.016360223},"labels":[],"label_agreement":null},{"id":"W2142285493","doi":"10.1002/mrm.21595","title":"Evidence for enhanced functional activity of cervical cord in relapsing multiple sclerosis","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; White matter; Multiple sclerosis; Cord; Diffusion MRI; Fractional anisotropy; Medicine; Proprioception; Corticospinal tract; Cervical spondylosis; Pyramidal tracts; Lesion; Magnetic resonance imaging; Neuroscience; Anatomy; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Surgery","score_opus":0.3082848132474972,"score_gpt":0.38552145026359746,"score_spread":0.07723663701610028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142285493","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995198,0.00021276872,0.000046382876,0.0000111922045,9.2019485e-7,0.00000357106,0.000024666015,0.0000031111183,0.00017750607],"genre_scores_gemma":[0.99972326,0.000073382136,0.00007381802,0.000012612561,0.0000030129424,0.000003064519,0.000042726053,9.2349194e-7,0.00006721765],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998568,0.000033088825,0.000018303,0.00004061391,0.000027314103,0.000023838717],"domain_scores_gemma":[0.99946326,0.00011894901,0.00024531738,0.00003236956,0.000065045475,0.000075012686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023678827,0.00022653026,0.00022592393,0.0007576062,0.00019033418,0.00018448212,0.00014916768,0.0003450051,0.0017190671],"category_scores_gemma":[0.0010467846,0.000106887455,0.0000933833,0.00020607145,0.00042630843,0.00012063526,0.0001880601,0.00014052916,0.00014921078],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031197655,0.00026391834,0.77086014,0.0003321594,0.00025434486,0.004292385,0.0009822749,0.00023276026,0.19823727,0.00008770062,0.00018991847,0.021147383],"study_design_scores_gemma":[0.000026942022,0.0004267,0.9941849,0.000008200757,0.00003028289,0.0032020358,0.00009257087,0.000108197615,0.0017633693,0.00003096826,0.000121728524,0.0000040455393],"about_ca_topic_score_codex":0.0024891153,"about_ca_topic_score_gemma":0.0035453814,"teacher_disagreement_score":0.0024891153,"about_ca_system_score_codex":0.00022010904,"about_ca_system_score_gemma":0.00013191512,"threshold_uncertainty_score":0.005750835},"labels":[],"label_agreement":null},{"id":"W2142415773","doi":"10.3109/02699052.2011.589791","title":"Focal thinning of the posterior corpus callosum: Normal variant or post-traumatic?","year":2011,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal","funders":"","keywords":"Corpus callosum; Traumatic brain injury; Medicine; Audiology; Anatomy; Psychiatry","score_opus":0.08515711006078454,"score_gpt":0.3405493260268062,"score_spread":0.2553922159660217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142415773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99809676,0.0009740175,0.0001984668,0.000067987654,0.000007343654,0.0000051756942,0.000055073993,0.000011891248,0.0005832663],"genre_scores_gemma":[0.9992155,0.00036244595,0.00015593381,0.000013834699,0.000013940494,0.000003418018,0.00007291921,0.000002751126,0.00015922556],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975854,0.000041555475,0.000033295368,0.00006476321,0.00005877926,0.00004318326],"domain_scores_gemma":[0.9984688,0.00022035243,0.0009424546,0.000111331035,0.00014730974,0.00010964254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039181477,0.00041499105,0.0003149714,0.0010464714,0.00034563077,0.00041081055,0.00044431514,0.00045746984,0.0020148493],"category_scores_gemma":[0.002434836,0.00014160768,0.00012527264,0.0008522625,0.0015201704,0.00061653217,0.00032099526,0.00032632687,0.0002955691],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011859488,0.00013588305,0.90110075,0.00031161925,0.00009658256,0.024671134,0.0012539861,0.000199916,0.030205127,0.00040669722,0.00043601377,0.039996255],"study_design_scores_gemma":[0.000006478409,0.0004231439,0.94716144,0.000035394653,0.000027820688,0.04810317,0.00068125565,0.00008013248,0.0027329253,0.00018950787,0.00054873875,0.0000100139],"about_ca_topic_score_codex":0.0019642368,"about_ca_topic_score_gemma":0.0024961934,"teacher_disagreement_score":0.0020148493,"about_ca_system_score_codex":0.00034105693,"about_ca_system_score_gemma":0.00032023326,"threshold_uncertainty_score":0.0067403316},"labels":[],"label_agreement":null},{"id":"W2142441078","doi":"10.25011/cim.v31i4.4830","title":"QUANTITATIVE EXAMINATION OF A NOVEL CLUSTERING METHOD USING MAGNETIC RESONANCE DIFFUSION TENSOR TRACTOGRAPHY","year":2008,"lang":"en","type":"article","venue":"Clinical and investigative medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Diffusion MRI; Tractography; Voxel; Artificial intelligence; Pattern recognition (psychology); Population; Computer science; Tensor (intrinsic definition); Mathematics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.5045214186943121,"score_gpt":0.47147405844462525,"score_spread":0.03304736024968685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142441078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53639215,0.0006904394,0.4578794,0.00021740646,0.000087338456,0.00036682773,0.0008539561,0.0014819287,0.0020306336],"genre_scores_gemma":[0.7502444,0.00014285538,0.24792008,0.00002029069,0.000038782026,0.0002102742,0.000620569,0.00021718915,0.0005854264],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973839,0.00064085657,0.0003018794,0.00059925346,0.00096600765,0.000108049186],"domain_scores_gemma":[0.9876622,0.004111283,0.0023792873,0.0012066141,0.004353603,0.00028701476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0061230483,0.00085916294,0.0004579382,0.0039252094,0.0008311076,0.0013864085,0.0007900688,0.0009991594,0.0017020523],"category_scores_gemma":[0.015678095,0.00033339922,0.0006925229,0.001841162,0.0007030978,0.000951048,0.00096841686,0.00046763237,0.00041073872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015919415,0.00032967396,0.2399178,0.0015354002,0.0020511292,0.0007235849,0.003751903,0.07479049,0.22017618,0.006272431,0.0040068096,0.44485265],"study_design_scores_gemma":[0.00014772193,0.00090716005,0.349917,0.00025879085,0.0006411745,0.0031647873,0.0007456575,0.54177976,0.090470865,0.005193801,0.0063566784,0.00041656557],"about_ca_topic_score_codex":0.0046196915,"about_ca_topic_score_gemma":0.0049170316,"teacher_disagreement_score":0.0061230483,"about_ca_system_score_codex":0.0009381527,"about_ca_system_score_gemma":0.0008522389,"threshold_uncertainty_score":0.03238219},"labels":[],"label_agreement":null},{"id":"W2143099998","doi":"10.1002/jmri.22101","title":"Human cervical spinal cord funiculi: Investigation with magnetic resonance diffusion tensor imaging","year":2010,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; National Research Council Institute for Biodiagnostics","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Spinal cord; Tractography; Magnetic resonance imaging; Anatomy; Region of interest; Dorsum; Medicine; Neuroscience; Biology; Radiology","score_opus":0.028948994662278654,"score_gpt":0.32143986664219054,"score_spread":0.29249087197991186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143099998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866731,0.0030085759,0.008654495,0.00014418173,0.000015877979,0.00015821817,0.00026540665,0.00006206871,0.0010180904],"genre_scores_gemma":[0.98412675,0.0016799372,0.012707671,0.0000561989,0.000017146383,0.00010554834,0.00032708127,0.000017986999,0.00096163835],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998791,0.000018162218,0.0000104796145,0.000039693692,0.000039833205,0.000012755314],"domain_scores_gemma":[0.99969757,0.00005113922,0.0000733764,0.000043036405,0.00010223987,0.00003264546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044997726,0.00038508239,0.00024476898,0.00065824843,0.00035909744,0.00037660825,0.00020820882,0.0005061209,0.0016617468],"category_scores_gemma":[0.0016785564,0.00017085942,0.00016082989,0.0003937328,0.00052592135,0.00043086626,0.00026629603,0.00020290278,0.0004483921],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018025729,0.000121475816,0.08589151,0.0010585478,0.00013975876,0.0028280807,0.001128036,0.0009387291,0.8368786,0.0004923608,0.0006368123,0.068083584],"study_design_scores_gemma":[0.00015967117,0.0019008867,0.7974859,0.00014061652,0.0001931769,0.022360539,0.0005830281,0.0062736953,0.1638047,0.0012233749,0.0057902825,0.00008414826],"about_ca_topic_score_codex":0.009901345,"about_ca_topic_score_gemma":0.011703203,"teacher_disagreement_score":0.009901345,"about_ca_system_score_codex":0.00047416403,"about_ca_system_score_gemma":0.00073053816,"threshold_uncertainty_score":0.019687414},"labels":[],"label_agreement":null},{"id":"W2143697715","doi":"10.3174/ajnr.a2224","title":"Abnormal Axial Diffusivity in the Deep Gray Nuclei and Dorsal Brain Stem in Infantile Spasm Treated with Vigabatrin","year":2010,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Dorsum; White matter; Anatomy; Magnetic resonance imaging; Radiology","score_opus":0.014277262608107117,"score_gpt":0.29000282609636463,"score_spread":0.2757255634882575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143697715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99983406,0.000036387617,0.000019930687,0.0000071873815,7.064162e-7,0.0000015567123,0.000010950443,0.0000016154337,0.00008762196],"genre_scores_gemma":[0.99986327,0.000033459673,0.000032261865,0.0000059778185,0.0000016259169,0.0000014033279,0.000024364124,5.0686106e-7,0.00003702815],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.9999243,0.000018507695,0.000011311562,0.000018014096,0.000012700805,0.000015085513],"domain_scores_gemma":[0.999814,0.00003332123,0.000090777205,0.000009318556,0.000015950312,0.0000366364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011188096,0.0003153488,0.00034573604,0.0006371205,0.00018386064,0.00019225592,0.00011359744,0.00022206674,0.00074462127],"category_scores_gemma":[0.0005772331,0.00013175824,0.00017076642,0.00020802011,0.00025469516,0.00011801459,0.00013377097,0.00017863543,0.00006859756],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019730306,0.00022451719,0.91753143,0.000043253403,0.00016093133,0.013456189,0.00055855606,0.0002837949,0.053770512,0.00007275914,0.000121875135,0.011803202],"study_design_scores_gemma":[0.000032733198,0.0006141978,0.9900289,0.000005847504,0.000055356428,0.0076721516,0.00010485287,0.00025307105,0.0011199916,0.000019372483,0.000089576766,0.0000040094824],"about_ca_topic_score_codex":0.0025763812,"about_ca_topic_score_gemma":0.0029449528,"teacher_disagreement_score":0.0025763812,"about_ca_system_score_codex":0.00028858855,"about_ca_system_score_gemma":0.00010580059,"threshold_uncertainty_score":0.0051228404},"labels":[],"label_agreement":null},{"id":"W2143815825","doi":"10.1016/j.jpsychires.2004.10.001","title":"Volumetric MRI measurement of caudate nuclei in antipsychotic-naïve patients suffering from a first episode of psychosis","year":2004,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychosis; Antipsychotic; Psychology; Psychiatry; Caudate nucleus; Schizophrenia (object-oriented programming); Medicine; Neuroscience","score_opus":0.13584859674759248,"score_gpt":0.4156573796592648,"score_spread":0.2798087829116723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143815825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99909234,0.00019764865,0.00006128484,0.000032729287,0.0000050760777,0.0000062479294,0.00005093528,0.0000038917933,0.0005498385],"genre_scores_gemma":[0.9997254,0.000058868754,0.00006354852,0.000021834725,0.0000046123905,0.0000024273602,0.000041266834,9.0070176e-7,0.00008114031],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991715,0.000016244927,0.00001081677,0.000013604635,0.000021672742,0.000020503612],"domain_scores_gemma":[0.9997073,0.00011290373,0.00007100988,0.000016970116,0.00003406916,0.000057737452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017116599,0.00018307693,0.00026605494,0.00042466354,0.00025284663,0.00029877658,0.0002529964,0.00037955606,0.0007325051],"category_scores_gemma":[0.0012696256,0.00022064234,0.00020490997,0.00020493302,0.00025395656,0.00021720989,0.00014434132,0.00037394156,0.00009582852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039410377,0.00034633654,0.9070009,0.00009958177,0.00015229132,0.015114382,0.0007314809,0.0006746077,0.058165625,0.00011974876,0.00021233759,0.013441791],"study_design_scores_gemma":[0.000042339292,0.0007887927,0.98731494,0.0000079715455,0.00005074502,0.00834405,0.00029616858,0.0003804398,0.0026147582,0.000055205837,0.00009325234,0.000011392868],"about_ca_topic_score_codex":0.004524753,"about_ca_topic_score_gemma":0.0064580473,"teacher_disagreement_score":0.004524753,"about_ca_system_score_codex":0.00031297098,"about_ca_system_score_gemma":0.00025241333,"threshold_uncertainty_score":0.008996844},"labels":[],"label_agreement":null},{"id":"W2143830079","doi":"10.1016/s0278-2626(02)00011-8","title":"Division of the corpus callosum into subregions","year":2002,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Percentile; Factor (programming language); Psychology; Division (mathematics); Artificial intelligence; Pattern recognition (psychology); Neuroscience; Statistics; Cognitive psychology; Computer science; Mathematics; Arithmetic","score_opus":0.07165951081883656,"score_gpt":0.3178279892003294,"score_spread":0.24616847838149283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143830079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6170525,0.018429838,0.27411473,0.0013711052,0.00035930873,0.00072399154,0.0015213168,0.0015638293,0.084863365],"genre_scores_gemma":[0.7733093,0.0032039955,0.2095101,0.00034073598,0.00011365694,0.0005054993,0.0006783146,0.0002744779,0.01206401],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998331,0.00003328979,0.000014939315,0.000061000115,0.00003326662,0.000024454477],"domain_scores_gemma":[0.9993973,0.00019537633,0.000090689275,0.00012527766,0.00014156653,0.00004981676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047372584,0.00056773896,0.0003473026,0.0019645623,0.00049572304,0.0014586311,0.0006533773,0.0005465661,0.0030785264],"category_scores_gemma":[0.0013139322,0.00022927443,0.0003673697,0.0011612567,0.001252267,0.0010028186,0.0006214189,0.00073867204,0.0007073797],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013499921,0.00009033726,0.019759756,0.0012947466,0.000247988,0.0007284784,0.0045571714,0.0038775946,0.2522463,0.071801014,0.0067146523,0.63733196],"study_design_scores_gemma":[0.00026103342,0.0010529151,0.32923177,0.0010336476,0.0010306467,0.012510457,0.0057674306,0.03903576,0.1849432,0.1440895,0.28082004,0.0002236267],"about_ca_topic_score_codex":0.008252742,"about_ca_topic_score_gemma":0.009922881,"teacher_disagreement_score":0.008252742,"about_ca_system_score_codex":0.00060712476,"about_ca_system_score_gemma":0.0014730126,"threshold_uncertainty_score":0.016409397},"labels":[],"label_agreement":null},{"id":"W2143997687","doi":"10.1016/j.neuroimage.2007.04.062","title":"Reduced microstructural integrity of the white matter underlying anterior cingulate cortex is associated with increased saccadic latency in schizophrenia","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; U.S. Public Health Service; GlaxoSmithKline","keywords":"White matter; Cingulum (brain); Anterior cingulate cortex; Psychology; Neuroscience; Fractional anisotropy; Diffusion MRI; Cingulate cortex; Saccadic masking; Schizophrenia (object-oriented programming); Posterior cingulate; Cortex (anatomy); Eye movement; Medicine; Magnetic resonance imaging; Central nervous system; Psychiatry; Cognition; Radiology","score_opus":0.040767312626619055,"score_gpt":0.3253026185730904,"score_spread":0.28453530594647136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143997687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993167,0.000102935424,0.00016725158,0.000065026135,0.0000027210049,0.0000030946208,0.00008232305,0.000010160059,0.0002497635],"genre_scores_gemma":[0.9995098,0.00009172785,0.00016233702,0.00001718734,0.0000047948465,0.0000030795165,0.00007344347,0.000005000556,0.00013264721],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989545,0.000018092445,0.00001651906,0.000021999876,0.000028671584,0.000019173396],"domain_scores_gemma":[0.9989998,0.00014812686,0.0006316994,0.00004130808,0.00007063998,0.00010855543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024000589,0.0005098957,0.00026207836,0.0013272478,0.0004064222,0.00042780556,0.0002658749,0.00038845788,0.0022192895],"category_scores_gemma":[0.0009137758,0.00037768003,0.00023480627,0.00053152617,0.00059269834,0.00030513504,0.0002885506,0.00044558907,0.00015979898],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048402473,0.00029150044,0.48380432,0.00027688133,0.00069874566,0.0054747136,0.0009866734,0.0013594837,0.4862857,0.00059346325,0.0005146621,0.014873643],"study_design_scores_gemma":[0.000019375893,0.00011191904,0.993856,0.0000068213,0.00009003493,0.0016055937,0.00016518697,0.000493176,0.003278283,0.00031028493,0.000054316322,0.000008996219],"about_ca_topic_score_codex":0.012107045,"about_ca_topic_score_gemma":0.015456013,"teacher_disagreement_score":0.012107045,"about_ca_system_score_codex":0.0003870145,"about_ca_system_score_gemma":0.00045583944,"threshold_uncertainty_score":0.024073124},"labels":[],"label_agreement":null},{"id":"W2144240799","doi":"10.1016/j.mri.2015.02.022","title":"In vivo 3T and ex vivo 7T diffusion tensor imaging of prostate cancer: Correlation with histology","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Ex vivo; In vivo; Prostate cancer; Fractional anisotropy; Diffusion MRI; Effective diffusion coefficient; Prostate; Prostatectomy; Medicine; Nuclear medicine; Magnetic resonance imaging; Histology; Pathology; Cancer; Nuclear magnetic resonance; Radiology; Internal medicine; Biology; Physics","score_opus":0.02095815390188491,"score_gpt":0.3002256656263203,"score_spread":0.27926751172443537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144240799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801358,0.0029645218,0.013684429,0.00026540036,0.00003416039,0.000036710666,0.00042956154,0.00014802653,0.002301369],"genre_scores_gemma":[0.9920304,0.0012701668,0.0055607506,0.00006471166,0.000053148895,0.000011552598,0.00022586568,0.00005955778,0.0007238155],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996989,0.00012151819,0.000029538696,0.000042421965,0.00006963478,0.00003805851],"domain_scores_gemma":[0.99846977,0.00051612814,0.00030071542,0.00020435826,0.0003869532,0.00012207912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017035924,0.00040472622,0.00030689224,0.0013325835,0.00028095144,0.0010260908,0.0004517615,0.00077138067,0.0013036988],"category_scores_gemma":[0.0033858388,0.00066878105,0.00023522529,0.0005836984,0.00047280872,0.0009259361,0.00035182378,0.00044795038,0.00033352574],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035440447,0.00036227403,0.23943599,0.0008793694,0.00063588837,0.0027392483,0.0012891232,0.0062658554,0.67673546,0.0012263908,0.0016355456,0.06525086],"study_design_scores_gemma":[0.00010091271,0.00094941165,0.73678386,0.00011093223,0.0009588357,0.021540044,0.0012881324,0.035305604,0.19588879,0.0021930935,0.004718423,0.00016191298],"about_ca_topic_score_codex":0.0024531563,"about_ca_topic_score_gemma":0.0031402826,"teacher_disagreement_score":0.0024531563,"about_ca_system_score_codex":0.00022686375,"about_ca_system_score_gemma":0.00037783774,"threshold_uncertainty_score":0.00900954},"labels":[],"label_agreement":null},{"id":"W2145381610","doi":"10.3389/fnhum.2014.00653","title":"A review of structural neuroimaging in schizophrenia: from connectivity to connectomics","year":2014,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":259,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Neuroimaging; Connectomics; Cingulum (brain); Corpus callosum; Neuroscience; Schizophrenia (object-oriented programming); White matter; Diffusion MRI; Uncinate fasciculus; Psychology; Thalamus; Functional connectivity; Connectome; Fractional anisotropy; Medicine; Magnetic resonance imaging; Psychiatry","score_opus":0.08628941262075396,"score_gpt":0.4099322611949404,"score_spread":0.32364284857418646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145381610","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000049022045,0.9991233,0.000115321905,0.00022693108,0.00008693737,0.0000035330997,0.000022859478,0.0000052065757,0.0003668806],"genre_scores_gemma":[0.00025622017,0.9991923,0.0001825028,0.00008647617,0.000120744386,0.00000442094,0.000021947266,0.0000012447924,0.00013421156],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99972695,0.0000624384,0.000058000347,0.000058460097,0.00007684699,0.000017275994],"domain_scores_gemma":[0.9991898,0.00048245548,0.00010145984,0.000022251686,0.00015303172,0.000051002375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010269246,0.001230782,0.0016473526,0.0053784805,0.00028004564,0.0010310158,0.00103508,0.001460822,0.0033490323],"category_scores_gemma":[0.0015392137,0.00047713015,0.0006740762,0.005772201,0.0008296161,0.0017892034,0.0008990595,0.0014507911,0.0020199134],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003851777,0.00003116445,0.00021320183,0.025431495,0.0001126748,0.00021016104,0.00008696245,0.00025224808,0.00066689687,0.002165347,0.02301333,0.94777805],"study_design_scores_gemma":[0.000017866618,0.00011288475,0.0033870756,0.01930119,0.00026448106,0.0025779211,0.00016079542,0.00012282259,0.0003548276,0.0042895223,0.9693578,0.000052861316],"about_ca_topic_score_codex":0.0027044371,"about_ca_topic_score_gemma":0.0045275115,"teacher_disagreement_score":0.0053784805,"about_ca_system_score_codex":0.0008533298,"about_ca_system_score_gemma":0.0015577675,"threshold_uncertainty_score":0.011203647},"labels":[],"label_agreement":null},{"id":"W2146011728","doi":"10.1109/isbi.2008.4541156","title":"Two novel methods for computing the 3D cardiac midwall","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Endocardium; Cardiac Ventricle; Computation; Streamlines, streaklines, and pathlines; Computer science; Visualization; Image processing; Diffusion MRI; Orientation (vector space); Artificial intelligence; Pipeline (software); Computer vision; Image (mathematics); Ventricle; Algorithm; Mathematics; Geometry; Physics; Cardiology; Medicine; Mechanics","score_opus":0.20091248527696082,"score_gpt":0.4897017434989566,"score_spread":0.2887892582219958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146011728","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011717866,0.00009336543,0.99800545,0.000056747504,0.000045417786,0.000021228523,0.000030121933,0.00027225455,0.00030359242],"genre_scores_gemma":[0.019718753,0.00023054551,0.978459,0.000045817866,0.000077086945,0.00010401584,0.00010494648,0.0001447259,0.0011150346],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992706,0.00007580952,0.00005101,0.00014804838,0.00041131416,0.0000431549],"domain_scores_gemma":[0.99887866,0.00030712245,0.00017446502,0.00016463791,0.00037889383,0.000096205324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083780615,0.0010378185,0.0006585634,0.001770229,0.00045631852,0.0017169219,0.0017464802,0.0011234912,0.0028356654],"category_scores_gemma":[0.003606691,0.0007323554,0.000940717,0.0011772313,0.00058207137,0.0017854738,0.0019281023,0.0014898912,0.0009560985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015323483,0.00011047558,0.0017971583,0.0003907294,0.000120159944,0.00015908165,0.00036694045,0.05592593,0.05469164,0.04522633,0.0057877973,0.83527064],"study_design_scores_gemma":[0.00007414791,0.00009497945,0.0016552922,0.000053936863,0.00004912548,0.00064247835,0.000113413254,0.93786484,0.021486636,0.015737254,0.022099799,0.00012808091],"about_ca_topic_score_codex":0.0021496466,"about_ca_topic_score_gemma":0.0041488176,"teacher_disagreement_score":0.0028356654,"about_ca_system_score_codex":0.00043005586,"about_ca_system_score_gemma":0.0009577824,"threshold_uncertainty_score":0.009486258},"labels":[],"label_agreement":null},{"id":"W2146726024","doi":"10.1038/mp.2013.44","title":"White-matter microstructure and gray-matter volumes in adolescents with subthreshold bipolar symptoms","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; University of Toronto; Toronto Rehabilitation Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Assistance publique-Hôpitaux de Paris; Institut National de la Santé et de la Recherche Médicale","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Psychology; Corpus callosum; Diffusion MRI; Bipolar disorder; Uncinate fasciculus; Population; Cardiology; Medicine; Internal medicine; Mood; Psychiatry; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.005979382664349936,"score_gpt":0.24881925806507507,"score_spread":0.24283987540072513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146726024","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99985325,0.000048932216,0.000015990661,0.0000036221586,6.738608e-7,0.000002259698,0.000030503947,8.669749e-7,0.000043886783],"genre_scores_gemma":[0.9997507,0.00005252577,0.000047575202,0.0000061114415,0.0000015155643,0.0000040229775,0.0000835181,8.3376517e-7,0.00005314295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999186,0.000013860142,0.000012553339,0.000022256112,0.00001620274,0.000016588969],"domain_scores_gemma":[0.9997552,0.000027805541,0.00012984662,0.000012204751,0.000026400377,0.000048509268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017460226,0.00023422335,0.00018434794,0.00064540934,0.00017678896,0.00025448835,0.00009999322,0.00021799168,0.0005960932],"category_scores_gemma":[0.0006909072,0.00021747268,0.00013157142,0.00029722447,0.0001859082,0.00016228131,0.00019362867,0.00016359179,0.00009543457],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002084521,0.00003462991,0.99446046,0.000011884794,0.000023305585,0.00036010728,0.00023105626,0.000040037266,0.0025222825,0.000022871036,0.00005378542,0.0020311486],"study_design_scores_gemma":[0.0000032137411,0.000057778616,0.999413,0.0000025191189,0.000006925236,0.00028126157,0.0000895568,0.000037689377,0.000076210694,0.0000069560806,0.000024161698,6.406601e-7],"about_ca_topic_score_codex":0.0036873275,"about_ca_topic_score_gemma":0.0057256245,"teacher_disagreement_score":0.0036873275,"about_ca_system_score_codex":0.00015826891,"about_ca_system_score_gemma":0.00010204555,"threshold_uncertainty_score":0.007331729},"labels":[],"label_agreement":null},{"id":"W2146949897","doi":"10.1016/j.neuroimage.2008.09.053","title":"Sensitivity of voxel-based morphometry analysis to choice of imaging protocol at 3 T","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Montreal Neurological Institute and Hospital","keywords":"Voxel; Contrast (vision); Mathematics; Population; Voxel-based morphometry; Artificial intelligence; Nuclear medicine; Pattern recognition (psychology); Statistics; White matter; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07714037351573723,"score_gpt":0.38587030552009705,"score_spread":0.30872993200435983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146949897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5277896,0.0060931174,0.4567797,0.0011610782,0.00043603015,0.00040012374,0.00079099636,0.0027406046,0.0038087778],"genre_scores_gemma":[0.911484,0.0008100973,0.083599396,0.0009329536,0.00007630534,0.00017745228,0.00056372496,0.001695119,0.0006609972],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9852669,0.010104899,0.0009240955,0.0018732693,0.0015052772,0.00032544532],"domain_scores_gemma":[0.8127978,0.16929851,0.0043382808,0.009590167,0.003254077,0.0007211768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038964633,0.0008745714,0.0019393731,0.0015659417,0.000767845,0.0026593516,0.0009558581,0.0013475708,0.00143806],"category_scores_gemma":[0.1368352,0.00153792,0.0011455815,0.0012466089,0.0012331101,0.0015737473,0.0018297248,0.0013752562,0.0005423638],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01719319,0.00046847854,0.13248895,0.0030560705,0.0072439974,0.001990734,0.002205967,0.06450564,0.5332185,0.0062630707,0.004726419,0.22663894],"study_design_scores_gemma":[0.00038395645,0.0024352865,0.40445438,0.00032467901,0.0055530486,0.01689639,0.0004435088,0.26376715,0.26998472,0.026461856,0.008703236,0.00059172016],"about_ca_topic_score_codex":0.0013251525,"about_ca_topic_score_gemma":0.0015820534,"teacher_disagreement_score":0.038964633,"about_ca_system_score_codex":0.00057970453,"about_ca_system_score_gemma":0.00070299866,"threshold_uncertainty_score":0.20606714},"labels":[],"label_agreement":null},{"id":"W2147009297","doi":"10.1093/brain/awp233","title":"Language networks in semantic dementia","year":2009,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":270,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"Fractional anisotropy; Arcuate fasciculus; Inferior longitudinal fasciculus; Uncinate fasciculus; Splenium; Corpus callosum; Superior longitudinal fasciculus; Diffusion MRI; Fasciculus; Psychology; White matter; Temporal lobe; Frontal lobe; Tractography; Neuroscience; Anatomy; Magnetic resonance imaging; Medicine; Radiology; Epilepsy","score_opus":0.029399449068715416,"score_gpt":0.35335782232605056,"score_spread":0.3239583732573351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147009297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966577,0.00033159435,0.0010261773,0.00013941345,0.0000034541702,0.0000055089363,0.00004422388,0.000019354819,0.0017725108],"genre_scores_gemma":[0.999238,0.000079317084,0.00037671265,0.000018062541,0.000002781278,0.000005044396,0.000054670436,0.0000018420751,0.00022371291],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997892,0.00007901088,0.0000109630955,0.00004590578,0.000029968165,0.00004503777],"domain_scores_gemma":[0.9996867,0.000078662444,0.00012632737,0.000024011153,0.000036662743,0.000047646074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004029582,0.00025396844,0.00018566569,0.0011293644,0.0005148148,0.0006517131,0.00019332797,0.0003250913,0.0011047655],"category_scores_gemma":[0.0015120462,0.00016601346,0.00016548843,0.0003794488,0.00084032223,0.00078896177,0.0008926794,0.00019860908,0.0001259178],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026644636,0.00022488736,0.68881494,0.00050657644,0.00043320731,0.011643903,0.017116353,0.00997845,0.07007302,0.025495876,0.0022906987,0.17075764],"study_design_scores_gemma":[0.00008581546,0.00029911404,0.90196073,0.00010142156,0.00014286373,0.008287056,0.00403075,0.010390838,0.004328278,0.0667429,0.0035920516,0.00003810388],"about_ca_topic_score_codex":0.0035385669,"about_ca_topic_score_gemma":0.005465707,"teacher_disagreement_score":0.0035385669,"about_ca_system_score_codex":0.00062738056,"about_ca_system_score_gemma":0.00037125676,"threshold_uncertainty_score":0.0070359707},"labels":[],"label_agreement":null},{"id":"W2147493105","doi":"10.1186/1471-2377-6-21","title":"Intrahemispheric dysfunction in primary motor cortex without corpus callosum: a transcranial magnetic stimulation study","year":2006,"lang":"en","type":"article","venue":"BMC Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Transcranial magnetic stimulation; Silent period; Primary motor cortex; Motor cortex; Neuroscience; Psychology; Evoked potential; Inhibitory postsynaptic potential; Pyramidal tracts; Cortex (anatomy); Stimulation; Medicine; Audiology","score_opus":0.026072855804647854,"score_gpt":0.2902690699066231,"score_spread":0.26419621410197525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147493105","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995357,0.000067152505,0.00012995426,0.000016061116,0.0000017945404,0.000011665894,0.000015572788,0.0000036169283,0.00021852588],"genre_scores_gemma":[0.9997428,0.000030408071,0.00008567137,0.000015387388,0.0000053898157,0.0000068738796,0.000026610001,0.0000013434262,0.00008561648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998253,0.000025991265,0.000020280006,0.00006750178,0.000030289768,0.000030688345],"domain_scores_gemma":[0.9994986,0.00018006386,0.00010767701,0.000057680492,0.00005448553,0.00010143382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002724467,0.0007320623,0.00046883372,0.00072834606,0.0005969077,0.00020805601,0.00027820995,0.0007431893,0.0023064404],"category_scores_gemma":[0.0011799268,0.00021883612,0.0001936911,0.00025975145,0.0009780974,0.00025712777,0.00027132995,0.00044553643,0.0002719624],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005024575,0.0027508147,0.47637394,0.0005261628,0.00041864408,0.20090792,0.005085507,0.00055554946,0.28044388,0.00057959434,0.00047705288,0.026856327],"study_design_scores_gemma":[0.00017071137,0.0037206535,0.7922134,0.000017145872,0.00013482157,0.19415984,0.00052360824,0.0004711007,0.007820192,0.00020891236,0.0005380583,0.000021573363],"about_ca_topic_score_codex":0.0014402329,"about_ca_topic_score_gemma":0.0015695564,"teacher_disagreement_score":0.0023064404,"about_ca_system_score_codex":0.0003214534,"about_ca_system_score_gemma":0.0003785547,"threshold_uncertainty_score":0.0077157617},"labels":[],"label_agreement":null},{"id":"W2147598339","doi":"10.1117/12.710417","title":"Tensor dissimilarity based adaptive seeding algorithm for DT-MRI visualization with streamtubes","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Seeding; Visualization; Diffusion MRI; Computer science; Tensor (intrinsic definition); Structure tensor; Artificial intelligence; Orientation (vector space); Algorithm; Computer vision; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Image (mathematics); Physics; Geometry","score_opus":0.026369610051325185,"score_gpt":0.2991909955680276,"score_spread":0.2728213855167024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147598339","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033382091,0.000053059935,0.9959345,0.00003510012,0.000014951778,0.000026771891,0.0000130408735,0.00041605422,0.00016828887],"genre_scores_gemma":[0.031831726,0.00009506226,0.9670748,0.000025905383,0.000011783907,0.000071046066,0.00008046445,0.00016067395,0.0006486065],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951637,0.00010139703,0.000040529132,0.00009027293,0.00022316932,0.000028238122],"domain_scores_gemma":[0.9984621,0.0006198382,0.00017667004,0.0002190187,0.0004193373,0.00010310313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009994516,0.0008553144,0.0008527085,0.0011731074,0.0005839549,0.001291297,0.0014036909,0.0011362999,0.0024955927],"category_scores_gemma":[0.0039785025,0.0004470699,0.0006789452,0.000970465,0.00058481237,0.0016277218,0.00124216,0.0011206751,0.00094654167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036370158,0.00009877979,0.0015317629,0.0002582551,0.00008661813,0.0004216134,0.00051231013,0.2268034,0.11032369,0.041368127,0.0049242973,0.6133074],"study_design_scores_gemma":[0.000026044878,0.0000429037,0.00017172597,0.000010591485,0.000008143108,0.00015180786,0.000021694152,0.9675981,0.018923175,0.0076452834,0.0053764516,0.000024178298],"about_ca_topic_score_codex":0.002193281,"about_ca_topic_score_gemma":0.0022072091,"teacher_disagreement_score":0.0024955927,"about_ca_system_score_codex":0.0009734515,"about_ca_system_score_gemma":0.00085615716,"threshold_uncertainty_score":0.008348584},"labels":[],"label_agreement":null},{"id":"W2147829144","doi":"10.1503/jpn.110132","title":"Impaired interhemispheric connectivity in medication-naive patients with major depressive disorder","year":2012,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health","keywords":"Fractional anisotropy; Major depressive disorder; Corpus callosum; Diffusion MRI; Psychology; Internal medicine; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology; Amygdala","score_opus":0.018805148923943193,"score_gpt":0.31266258975702876,"score_spread":0.29385744083308557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147829144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99951875,0.00012247561,0.000049214756,0.000030755364,0.0000021499975,0.0000055310556,0.00006611318,0.0000026635455,0.00020229397],"genre_scores_gemma":[0.99972934,0.00005790272,0.00007444591,0.000020769772,0.000004257628,0.0000044876288,0.00007571466,6.705638e-7,0.00003244373],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987173,0.000031539323,0.000020923417,0.000031050586,0.000027935415,0.000016777729],"domain_scores_gemma":[0.99952173,0.00009807032,0.00025647582,0.000023785453,0.000043143307,0.00005674154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017127879,0.00022043941,0.00028741965,0.00047715765,0.0003818035,0.00030765418,0.0001719251,0.0003662905,0.0014516459],"category_scores_gemma":[0.0011533096,0.00014796595,0.00010954368,0.00030473326,0.00020887372,0.00018310067,0.00015122106,0.00022369175,0.00016456224],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040541042,0.00011218861,0.9835564,0.00004600796,0.00010465279,0.0011177841,0.00041585788,0.000081617,0.0065643056,0.000044974688,0.00026763687,0.0072830766],"study_design_scores_gemma":[0.000009438077,0.00007930051,0.9982835,0.0000041027465,0.000019206396,0.0011789156,0.00008166616,0.00009684815,0.00014564427,0.000034777462,0.00006465989,0.0000019245479],"about_ca_topic_score_codex":0.0020292741,"about_ca_topic_score_gemma":0.006170103,"teacher_disagreement_score":0.0020292741,"about_ca_system_score_codex":0.00024036334,"about_ca_system_score_gemma":0.0001331592,"threshold_uncertainty_score":0.004856229},"labels":[],"label_agreement":null},{"id":"W2147848903","doi":"10.1002/hbm.20739","title":"Probabilistic topography of human corpus callosum using cytoarchitectural parcellation and high angular resolution diffusion imaging tractography","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":188,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Council","keywords":"Tractography; Corpus callosum; Diffusion MRI; Neuroscience; Population; Somatosensory system; Artificial intelligence; Computer science; Psychology; Pattern recognition (psychology); Computer vision; Cartography; Magnetic resonance imaging; Medicine; Geography","score_opus":0.055970219345086614,"score_gpt":0.3309406591190847,"score_spread":0.2749704397739981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147848903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9546045,0.00019747631,0.044227388,0.000053165993,0.0000037258535,0.000030939194,0.0002669254,0.00015824825,0.00045756114],"genre_scores_gemma":[0.9881572,0.00008980144,0.011297729,0.000004828942,0.0000040660125,0.000015110124,0.00018755304,0.000023354101,0.00022033598],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999894,0.00002953139,0.0000041107846,0.00004278057,0.000019647772,0.00000991103],"domain_scores_gemma":[0.99970394,0.0001256011,0.000058334226,0.000054927812,0.000041966792,0.000015244467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003188368,0.00019930795,0.00012185836,0.0008241919,0.0001661612,0.0003992365,0.00019611289,0.00020752089,0.0008792828],"category_scores_gemma":[0.0014485533,0.0001746204,0.00023062344,0.00047192845,0.00035856498,0.00042425728,0.00022584443,0.00012911111,0.00015065588],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008038156,0.000074788,0.20357352,0.00026866546,0.00036653355,0.00076578156,0.002343628,0.08013091,0.46142486,0.003602996,0.0011899472,0.24545456],"study_design_scores_gemma":[0.000022366077,0.000096008014,0.82014525,0.000012711459,0.00007242173,0.0009250668,0.00018529323,0.15828945,0.017055904,0.0021917932,0.00095523655,0.000048512255],"about_ca_topic_score_codex":0.018372359,"about_ca_topic_score_gemma":0.020001227,"teacher_disagreement_score":0.018372359,"about_ca_system_score_codex":0.000294773,"about_ca_system_score_gemma":0.00028776925,"threshold_uncertainty_score":0.036530852},"labels":[],"label_agreement":null},{"id":"W2147896272","doi":"10.1111/jgs.13644","title":"Resistance Training and White Matter Lesion Progression in Older Women: Exploratory Analysis of a 12‐Month Randomized Controlled Trial","year":2015,"lang":"en","type":"article","venue":"Journal of the American Geriatrics Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"Canadian Institutes of Health Research; Vancouver Foundation","keywords":"Medicine; Randomized controlled trial; Hyperintensity; Magnetic resonance imaging; Internal medicine; Physical therapy; Radiology","score_opus":0.047272915626346584,"score_gpt":0.3483704515841584,"score_spread":0.30109753595781186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147896272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9808601,0.010625077,0.0010696101,0.00040613505,0.00035575908,0.00515664,0.00069047266,0.00007983268,0.00075625343],"genre_scores_gemma":[0.9845517,0.002950074,0.0022950834,0.00038754198,0.00032728587,0.008152526,0.0004121002,0.000015305612,0.00090833794],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9953766,0.003272537,0.0003577504,0.00048607518,0.0002510321,0.00025590492],"domain_scores_gemma":[0.99370474,0.0032319466,0.0015768535,0.00046427228,0.00039752387,0.00062464183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007881419,0.0016281053,0.0048100627,0.0005339656,0.00046213088,0.0012911317,0.00091153313,0.0016147608,0.004018997],"category_scores_gemma":[0.009953654,0.0007072553,0.004488762,0.0008268637,0.0007863138,0.0009835458,0.00055752846,0.0017430475,0.0003516915],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.97974706,0.002692931,0.002087534,0.0012098858,0.007728824,0.00003665595,0.00005293419,0.00018445688,0.00057804736,0.000039970924,0.00020736178,0.0054344805],"study_design_scores_gemma":[0.8928523,0.08520232,0.010202724,0.00020293129,0.009955775,0.000035923942,0.00004756282,0.00067630445,0.00023265099,0.00014946556,0.00041979423,0.000022219125],"about_ca_topic_score_codex":0.0011303573,"about_ca_topic_score_gemma":0.0019259069,"teacher_disagreement_score":0.007881419,"about_ca_system_score_codex":0.000735983,"about_ca_system_score_gemma":0.0013937493,"threshold_uncertainty_score":0.04168141},"labels":[],"label_agreement":null},{"id":"W2148466603","doi":"10.1002/mds.25820","title":"Patterns of cortical thinning in idiopathic rapid eye movement sleep behavior disorder","year":2014,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal General Hospital; Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Institut Universitaire de Gériatrie de Montréal; Université du Québec à Montréal","funders":"Canadian Institutes of Health Research","keywords":"White matter; REM sleep behavior disorder; Parasomnia; Lingual gyrus; Psychology; Rapid eye movement sleep; Diffusion MRI; Polysomnography; Dementia with Lewy bodies; Neuroscience; Magnetic resonance imaging; Dementia; Eye movement; Medicine; Pathology; Electroencephalography; Functional magnetic resonance imaging; Disease; Radiology","score_opus":0.022996424498755066,"score_gpt":0.31647922209112866,"score_spread":0.2934827975923736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148466603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937516,0.00014121686,0.000103817416,0.000013502709,8.6295813e-7,0.000004757377,0.00003509287,0.000006046542,0.0003196771],"genre_scores_gemma":[0.99959046,0.00007643147,0.00014918287,0.000011683603,0.00000195655,0.0000032546334,0.000047262485,0.0000024179071,0.00011732066],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999007,0.00002011908,0.000012736542,0.000024258014,0.000021728969,0.000020525655],"domain_scores_gemma":[0.99963284,0.000067956826,0.00017239651,0.000035126468,0.00005066993,0.000040965413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020917866,0.00023710614,0.00019123865,0.0014705936,0.00019104691,0.0001852973,0.00014114274,0.00017338998,0.0010495526],"category_scores_gemma":[0.000885999,0.0002136929,0.00015272362,0.00042776397,0.00045343846,0.0001746354,0.00020095913,0.00016439318,0.000114412884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010219999,0.00008987185,0.8654952,0.000090710884,0.00021191985,0.010223104,0.0010539058,0.0005051072,0.10217161,0.00014453236,0.0002579533,0.018734064],"study_design_scores_gemma":[0.0000073816473,0.000059715017,0.99316216,0.0000045169086,0.000014323937,0.005541481,0.000082370105,0.0001032404,0.0009229436,0.0000397894,0.00005957622,0.00000254328],"about_ca_topic_score_codex":0.0029057567,"about_ca_topic_score_gemma":0.0060000597,"teacher_disagreement_score":0.0029057567,"about_ca_system_score_codex":0.00014828997,"about_ca_system_score_gemma":0.0001603997,"threshold_uncertainty_score":0.0057777166},"labels":[],"label_agreement":null},{"id":"W2148828979","doi":"10.1016/j.neuroimage.2007.12.035","title":"Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1889,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; University of California, Los Angeles; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"White matter; Diffusion MRI; Atlas (anatomy); Brain atlas; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Orientation (vector space); Magnetic resonance imaging; Medicine; Mathematics; Anatomy; Radiology","score_opus":0.060239750217129635,"score_gpt":0.3295501962829788,"score_spread":0.2693104460658492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148828979","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035582274,0.0002727712,0.9361734,0.0005395315,0.00038181277,0.00040840887,0.004295681,0.004978154,0.017367925],"genre_scores_gemma":[0.19669943,0.00041440886,0.7886131,0.00023847366,0.00007830089,0.0005328158,0.0034728055,0.0014533744,0.00849739],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997949,0.000033043387,0.000019192195,0.000068436086,0.000060134058,0.000024223753],"domain_scores_gemma":[0.99971277,0.000040615225,0.000031183656,0.00009781537,0.00009624105,0.000021264108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048420066,0.00045176366,0.0004200071,0.0011038013,0.00056152156,0.0017842879,0.00075002125,0.0008862667,0.0074576354],"category_scores_gemma":[0.0017405329,0.0003520254,0.00062316196,0.0014602148,0.00038133774,0.0007927914,0.00059036,0.0010970387,0.0033734802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009397911,0.00017225002,0.008725598,0.0007743298,0.00015885949,0.0014013695,0.0011533431,0.045309428,0.1293502,0.10662861,0.07887216,0.6265141],"study_design_scores_gemma":[0.00022061807,0.000494043,0.026579453,0.0003110246,0.00039515333,0.008636435,0.00063833874,0.4062138,0.14625555,0.076132566,0.33389166,0.0002314961],"about_ca_topic_score_codex":0.014727777,"about_ca_topic_score_gemma":0.018300056,"teacher_disagreement_score":0.014727777,"about_ca_system_score_codex":0.0007276197,"about_ca_system_score_gemma":0.002602976,"threshold_uncertainty_score":0.02928412},"labels":[],"label_agreement":null},{"id":"W2149314739","doi":"10.1016/j.media.2006.06.009","title":"3D curve inference for diffusion MRI regularization and fibre tractography☆","year":2006,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Tractography; Regularization (linguistics); Diffusion MRI; Inference; Artificial intelligence; Computer science; Mathematics; Pattern recognition (psychology); Magnetic resonance imaging; Medicine; Radiology","score_opus":0.019148141866167187,"score_gpt":0.3437552625796552,"score_spread":0.324607120713488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149314739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00097579154,0.00011295579,0.99810624,0.00011311392,0.000019836263,0.000014256532,0.000047947004,0.0004728018,0.0001370276],"genre_scores_gemma":[0.045446455,0.00029889977,0.95054823,0.000122717,0.000073560754,0.00013826,0.00038784818,0.00074107834,0.0022429363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897456,0.00040829365,0.000058745827,0.00022298965,0.00027527407,0.000060100534],"domain_scores_gemma":[0.9951107,0.0029720117,0.0003084033,0.0008182204,0.00063862687,0.0001520107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003888266,0.0012171796,0.001836027,0.0017200918,0.001120698,0.0019333563,0.0032732498,0.0043276045,0.0042401673],"category_scores_gemma":[0.014565035,0.0023125273,0.002403372,0.0015357439,0.0018160586,0.0024852704,0.0023887032,0.004117902,0.0019912745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024676305,0.00009691727,0.00087894493,0.00038982605,0.00027370424,0.00013974814,0.00018445347,0.5747792,0.009683801,0.08451291,0.010455748,0.31835794],"study_design_scores_gemma":[0.000009685023,0.000007868726,0.00006931208,0.0000118582375,0.000009275251,0.000023684073,0.0000044358057,0.9706917,0.0011015395,0.02655309,0.0015037203,0.000013855132],"about_ca_topic_score_codex":0.018171154,"about_ca_topic_score_gemma":0.022956932,"teacher_disagreement_score":0.018171154,"about_ca_system_score_codex":0.0015552931,"about_ca_system_score_gemma":0.00345909,"threshold_uncertainty_score":0.036130786},"labels":[],"label_agreement":null},{"id":"W2149542669","doi":"10.1109/isbi.2011.5872557","title":"Exact integration of diffusion orientation distribution functions for graph-based diffusion MRI analysis","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Graph; Weighting; Diffusion MRI; Weight function; Numerical integration; Algorithm; Applied mathematics; Computer science; Numerical analysis; Tractography; Probabilistic logic; Mathematical optimization; Mathematics; Theoretical computer science; Mathematical analysis; Artificial intelligence","score_opus":0.06433255133012311,"score_gpt":0.34262245062817825,"score_spread":0.27828989929805514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149542669","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016538658,0.00006777551,0.9976572,0.000034465284,0.000008538202,0.000008596031,0.000015443755,0.000115491086,0.00043856006],"genre_scores_gemma":[0.1130375,0.000581259,0.8835449,0.00007301186,0.00002641653,0.0000828955,0.00014786306,0.00036402038,0.0021420512],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966633,0.00008799789,0.000022095752,0.000039784452,0.00016390123,0.000020046933],"domain_scores_gemma":[0.9989299,0.00065349543,0.00009177541,0.00012855693,0.00015593176,0.000040302948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009498635,0.0007315274,0.00065866165,0.0010916517,0.00038252867,0.0008544807,0.0007321485,0.0009523896,0.002985895],"category_scores_gemma":[0.0054006903,0.00037617824,0.00057399645,0.0010845202,0.0007517833,0.0017370235,0.00093927473,0.0009848638,0.0010833492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028145101,0.00003338086,0.00047745864,0.00014188659,0.000033525957,0.00018496589,0.00014983637,0.72486496,0.010367067,0.16317032,0.001869738,0.098678656],"study_design_scores_gemma":[0.0000022637619,0.0000039840934,0.00005858012,0.00000542272,0.0000028185307,0.00003783364,0.0000070898545,0.97251576,0.0006208588,0.025814032,0.00092544133,0.0000059278245],"about_ca_topic_score_codex":0.0047708936,"about_ca_topic_score_gemma":0.0071657663,"teacher_disagreement_score":0.0047708936,"about_ca_system_score_codex":0.00089183304,"about_ca_system_score_gemma":0.0009587237,"threshold_uncertainty_score":0.009988785},"labels":[],"label_agreement":null},{"id":"W2150163312","doi":"10.1093/brain/awh454","title":"Diffusion-weighted and perfusion MRI demonstrates parenchymal changes in complex partial status epilepticus","year":2005,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":331,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Status epilepticus; Ictal; Effective diffusion coefficient; Epilepsy; Perfusion; Medicine; Magnetic resonance imaging; Nuclear medicine; Hippocampal formation; Thalamus; Diffusion MRI; Cortex (anatomy); Radiology; Psychology; Neuroscience; Internal medicine","score_opus":0.05183154374311538,"score_gpt":0.33663910558971083,"score_spread":0.28480756184659545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150163312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987835,0.00020460524,0.0002244673,0.000026127327,0.000002952402,0.000010690877,0.000021447322,0.000007724056,0.00071839226],"genre_scores_gemma":[0.99960095,0.00012623779,0.00010824332,0.000017568107,0.000008743698,0.000004483481,0.00003821229,0.0000015800113,0.00009399994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999187,0.000015171259,0.000011295534,0.000018793718,0.000013503406,0.000022506438],"domain_scores_gemma":[0.9997247,0.00007830003,0.00007712588,0.000019964955,0.00002931668,0.00007063813],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021095303,0.00042893627,0.00020680405,0.000679194,0.00009735129,0.00019916869,0.00010346644,0.00030400432,0.0011019806],"category_scores_gemma":[0.0015370959,0.00020882374,0.00012853646,0.00019639001,0.0005054951,0.00028146082,0.00019311665,0.00016772134,0.0002515928],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014219455,0.00026197926,0.6365096,0.00023426708,0.00015565146,0.09451144,0.0012813368,0.00070618745,0.20400074,0.00028331333,0.0006428865,0.059990644],"study_design_scores_gemma":[0.000097251635,0.0013408117,0.880875,0.000016304757,0.00005413979,0.10781474,0.0002558257,0.0009187759,0.0076621226,0.00017569249,0.0007741338,0.000015257435],"about_ca_topic_score_codex":0.00125206,"about_ca_topic_score_gemma":0.0008510055,"teacher_disagreement_score":0.00125206,"about_ca_system_score_codex":0.00015400583,"about_ca_system_score_gemma":0.00014223317,"threshold_uncertainty_score":0.0036864877},"labels":[],"label_agreement":null},{"id":"W2150217906","doi":"10.1007/978-3-540-69960-6_37","title":"BrainLab Image Guided System","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Vendor; Frame (networking); Neurosurgery; Medical physics; Computer science; Field (mathematics); Medicine; Radiology","score_opus":0.08059601785721211,"score_gpt":0.3538708462215804,"score_spread":0.2732748283643683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150217906","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025416063,0.0032863645,0.7840011,0.0008341982,0.0011251087,0.00016457605,0.0009112573,0.019734286,0.18740152],"genre_scores_gemma":[0.03690447,0.004827028,0.4494095,0.002017838,0.00039181847,0.00030516018,0.0021717895,0.002498311,0.50147414],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999044,0.000006486294,0.000004312771,0.00002149692,0.000057150333,0.000006169541],"domain_scores_gemma":[0.99990904,0.00001816754,0.000005280556,0.000021770487,0.000036708403,0.000009073169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016112368,0.0006084939,0.00033546347,0.00051467615,0.00022573552,0.00090505235,0.0008789662,0.0007872142,0.042622726],"category_scores_gemma":[0.00025061675,0.00027191886,0.00023780708,0.0003223612,0.00020757907,0.00071645767,0.0006542999,0.0006979899,0.029647788],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007183774,0.000019964686,0.000109360575,0.00015019394,0.000014927582,0.00016801589,0.000049657683,0.0011659956,0.027572611,0.012378772,0.1494364,0.80886227],"study_design_scores_gemma":[0.000022421842,0.00007643566,0.0007265471,0.00008547776,0.000039304377,0.0027279353,0.000029388977,0.015855903,0.03943312,0.011678701,0.9292676,0.000057162175],"about_ca_topic_score_codex":0.00080454384,"about_ca_topic_score_gemma":0.0015984542,"teacher_disagreement_score":0.042622726,"about_ca_system_score_codex":0.0002517171,"about_ca_system_score_gemma":0.00054134685,"threshold_uncertainty_score":0.14258718},"labels":[],"label_agreement":null},{"id":"W2150270487","doi":"10.1161/strokeaha.108.529958","title":"Corticospinal Tract Pre-Wallerian Degeneration","year":2009,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Medicine; Hemiparesis; Corticospinal tract; Cerebral peduncle; Stroke (engine); Wallerian degeneration; Abnormality; Diffusion MRI; Pediatric stroke; Physical medicine and rehabilitation; Cardiology; Radiology; Magnetic resonance imaging; Internal capsule; Ischemia; Ischemic stroke; Pathology; Angiography; Psychiatry","score_opus":0.05426073657291517,"score_gpt":0.3636700214783051,"score_spread":0.30940928490538994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150270487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997672,0.0008318187,0.00021934521,0.000042119256,0.000005096063,0.000011121457,0.0002719443,0.000014708154,0.00093185174],"genre_scores_gemma":[0.998395,0.00046381456,0.00048237247,0.000016204767,0.000009488156,0.000014819533,0.00030304602,0.0000023757768,0.00031273018],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998517,0.000020718679,0.000023383087,0.000037704234,0.000036057903,0.000030415562],"domain_scores_gemma":[0.9992331,0.000102522026,0.0004450577,0.00002581318,0.00009571371,0.0000978035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022653457,0.0004371133,0.00029619253,0.00072377006,0.00025587977,0.00037138845,0.0001813816,0.00019458776,0.0020225903],"category_scores_gemma":[0.0013665915,0.00009132507,0.000109431545,0.00047464293,0.0003782158,0.00023238818,0.00018049328,0.0002368987,0.0004002536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094673545,0.000035016685,0.9855202,0.000058246413,0.00003118735,0.0021883803,0.00006272362,0.000080432874,0.0036147144,0.0000455207,0.00018260225,0.008086402],"study_design_scores_gemma":[0.000003767551,0.00010666353,0.9908761,0.000023860348,0.000013342335,0.0072032707,0.000040810533,0.000093928655,0.0012909538,0.000035505935,0.000309692,0.0000022206707],"about_ca_topic_score_codex":0.0035370945,"about_ca_topic_score_gemma":0.0056003835,"teacher_disagreement_score":0.0035370945,"about_ca_system_score_codex":0.00043167718,"about_ca_system_score_gemma":0.00059319485,"threshold_uncertainty_score":0.0070329905},"labels":[],"label_agreement":null},{"id":"W2150487281","doi":"10.1684/epd.2012.0547","title":"White matter abnormalities revealed by DTI correlate with interictal grey matter FDG‐PET metabolism in focal childhood epilepsies","year":2012,"lang":"en","type":"article","venue":"Epileptic Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Fondation Pierre Deniker pour la Recherche et la Prévention en Santé Mentale","keywords":"White matter; Grey matter; Diffusion MRI; Fractional anisotropy; Ictal; Effective diffusion coefficient; Epilepsy; Psychology; Magnetic resonance imaging; Pathology; Medicine; Nuclear medicine; Neuroscience; Radiology","score_opus":0.011589455473755474,"score_gpt":0.2632453850574837,"score_spread":0.25165592958372823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150487281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976355,0.00006358399,0.00003462237,0.000004806659,4.797736e-7,0.0000013339517,0.000038503935,0.0000017359826,0.00009130362],"genre_scores_gemma":[0.9997583,0.00005836845,0.000064536376,0.0000040756004,0.0000010944387,0.0000018769238,0.00007287504,0.0000017588419,0.0000372358],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997874,0.000039021834,0.000032100324,0.00005773767,0.000035868397,0.000047914073],"domain_scores_gemma":[0.9989147,0.00013190074,0.0007136126,0.000055097265,0.00007269656,0.000112028574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027190355,0.00035251776,0.00019867005,0.0008502214,0.00019864886,0.00030303522,0.0001282303,0.00022879946,0.0007074367],"category_scores_gemma":[0.0015664345,0.0002444849,0.00016131367,0.0004910312,0.00039182097,0.0003155491,0.00023355747,0.00019546939,0.00012679143],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011948238,0.000011713758,0.9933895,0.000012146161,0.000017393826,0.0006563317,0.00013369836,0.00008429507,0.0039923955,0.00001451598,0.000029669673,0.0015388285],"study_design_scores_gemma":[0.0000016448759,0.0000505268,0.99847215,0.0000017672288,0.0000056313716,0.0010644644,0.000042598218,0.000040648552,0.00028172907,0.000005445961,0.000032123127,0.0000012584702],"about_ca_topic_score_codex":0.004360355,"about_ca_topic_score_gemma":0.007827004,"teacher_disagreement_score":0.004360355,"about_ca_system_score_codex":0.0003602753,"about_ca_system_score_gemma":0.00022566688,"threshold_uncertainty_score":0.008669913},"labels":[],"label_agreement":null},{"id":"W2150737561","doi":"10.1017/s0317167100004479","title":"Diffusion Tensor Imaging Abnormalities in Focal Cortical Dysplasia","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Alberta","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Cortical dysplasia; Hyperintensity; Magnetic resonance imaging; Medicine; Effective diffusion coefficient; Nuclear medicine; Lesion; Pathology; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.05064500833068652,"score_gpt":0.3202816174225774,"score_spread":0.26963660909189086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150737561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99651647,0.00086116785,0.0009425424,0.00013265961,0.0000047902163,0.000025412144,0.00016955195,0.000027154189,0.001320237],"genre_scores_gemma":[0.9986802,0.00026985197,0.0007590376,0.000014449625,0.0000036402942,0.000007685453,0.00010919998,0.0000031765385,0.00015273632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998956,0.000021116944,0.000019670677,0.000019284362,0.000025200121,0.00001921442],"domain_scores_gemma":[0.99964404,0.00004370612,0.00019305904,0.000021413334,0.000054081454,0.000043723045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027316247,0.0005575444,0.00017174061,0.0013739575,0.00021975256,0.00022864615,0.00014652654,0.00016408639,0.0013803403],"category_scores_gemma":[0.0011848747,0.000115078576,0.0001606688,0.00053357024,0.00037339155,0.00021352568,0.00025589173,0.00014443301,0.00016852416],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089755567,0.00010019992,0.80048645,0.0006484004,0.00028683717,0.035682984,0.0009092267,0.0009331078,0.11664964,0.0010810957,0.001037445,0.04128699],"study_design_scores_gemma":[0.000042144344,0.0002838325,0.9133973,0.00006872285,0.000116860705,0.075132854,0.00037150815,0.0014236467,0.007145982,0.00081094506,0.0011883153,0.000017891063],"about_ca_topic_score_codex":0.0029033138,"about_ca_topic_score_gemma":0.0030268708,"teacher_disagreement_score":0.0029033138,"about_ca_system_score_codex":0.00032868987,"about_ca_system_score_gemma":0.00031061316,"threshold_uncertainty_score":0.0057728887},"labels":[],"label_agreement":null},{"id":"W2151033012","doi":"10.1007/s00429-014-0956-9","title":"Puberty and testosterone shape the corticospinal tract during male adolescence","year":2014,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Université du Québec à Chicoutimi; Cégep de Jonquière; University of Toronto; Montreal Neurological Institute and Hospital; University of Calgary; McGill University; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"Testosterone (patch); White matter; Psychology; Mediation; Internal medicine; Young adult; Developmental psychology; Endocrinology; Physiology; Biology; Magnetic resonance imaging; Medicine","score_opus":0.021608274228481706,"score_gpt":0.27129703040430697,"score_spread":0.24968875617582525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151033012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969567,0.00065654085,0.00044099847,0.000091139635,0.000021806194,0.000006715554,0.00022561965,0.000017247025,0.0015832393],"genre_scores_gemma":[0.99813014,0.0002657424,0.00015071486,0.000029308634,0.000014315103,0.0000068545824,0.000124238,0.000030433435,0.0012482277],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999045,0.000020237387,0.0000027566803,0.000025209889,0.000019398583,0.000027895305],"domain_scores_gemma":[0.99972886,0.000082374674,0.000080750826,0.000018821267,0.000031776206,0.000057368372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013155436,0.00014217553,0.0002399695,0.0002727279,0.00018512069,0.00043782243,0.00015236261,0.0002490458,0.0030637167],"category_scores_gemma":[0.0009836991,0.00022617933,0.00015541997,0.00021668161,0.00033024876,0.0002464494,0.00023891771,0.0002664258,0.00028347742],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055525945,0.00040027336,0.4379742,0.00023231778,0.00024474526,0.0015254157,0.0023651416,0.0012994609,0.47952056,0.0017303745,0.0017100617,0.06744471],"study_design_scores_gemma":[0.0000071162226,0.00007070639,0.99693656,0.0000074189775,0.000011307563,0.00016147512,0.00017900858,0.00011377566,0.0020520235,0.0000915651,0.00036463563,0.000004398345],"about_ca_topic_score_codex":0.0039187265,"about_ca_topic_score_gemma":0.008492937,"teacher_disagreement_score":0.0039187265,"about_ca_system_score_codex":0.00021024984,"about_ca_system_score_gemma":0.0002780954,"threshold_uncertainty_score":0.010249138},"labels":[],"label_agreement":null},{"id":"W2151048581","doi":"10.1074/jbc.m113.515445","title":"Extracellular Monomeric Tau Protein Is Sufficient to Initiate the Spread of Tau Protein Pathology","year":2014,"lang":"en","type":"article","venue":"Journal of Biological Chemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Occupational Cancer Research Centre","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Wellcome Trust","keywords":"Extracellular; Endogeny; Tau protein; Tau pathology; Fibril; Protein aggregation; In vivo; Biophysics; Cell biology; Chemistry; Biology; Neuroscience; Biochemistry; Alzheimer's disease; Pathology; Medicine; Disease; Genetics","score_opus":0.062232143607083124,"score_gpt":0.3219237744916447,"score_spread":0.2596916308845616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151048581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995426,0.0008084204,0.0027636231,0.000058737794,0.000013345591,0.00001140175,0.000044155284,0.000046310804,0.00082809007],"genre_scores_gemma":[0.9966936,0.0003454476,0.0019520072,0.00002831472,0.000008215791,0.000008925525,0.000108118875,0.000012346697,0.00084293814],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998276,0.000030379986,0.0000145347485,0.000029659313,0.00006903827,0.00002876503],"domain_scores_gemma":[0.9996301,0.00011724791,0.00007777438,0.00006217839,0.000051724037,0.000060957205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018512688,0.00019799042,0.00019297807,0.00011572452,0.00010240966,0.00033436497,0.00011998112,0.0003663979,0.0007410523],"category_scores_gemma":[0.00034236067,0.000114106166,0.00015040411,0.00007393869,0.00018034327,0.0002466417,0.00023838802,0.00046592025,0.0002558749],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035377547,0.000012424754,0.0001429575,0.00001292172,0.000003218179,0.00006134919,0.000012565134,0.000039659877,0.99908435,0.00007401855,0.000013917571,0.0005072041],"study_design_scores_gemma":[0.000010295056,0.00031798362,0.0038485983,0.0000061160335,0.000015393136,0.0005152966,0.000042008734,0.0012597267,0.9928086,0.00013225792,0.0010400866,0.0000036523604],"about_ca_topic_score_codex":0.00029996017,"about_ca_topic_score_gemma":0.00042357677,"teacher_disagreement_score":0.0007410523,"about_ca_system_score_codex":0.00012443864,"about_ca_system_score_gemma":0.00019792662,"threshold_uncertainty_score":0.002479136},"labels":[],"label_agreement":null},{"id":"W2151103091","doi":"10.1109/tmi.2011.2111422","title":"Perception-Based Visualization of Manifold-Valued Medical Images Using Distance-Preserving Dimensionality Reduction","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; Johns Hopkins University","keywords":"Artificial intelligence; Pixel; Isomap; Mathematics; Nonlinear dimensionality reduction; Computer vision; Pattern recognition (psychology); Manifold (fluid mechanics); Euclidean distance; Similarity (geometry); Dimensionality reduction; Computer science; Image (mathematics)","score_opus":0.07963247697012278,"score_gpt":0.3814565320296012,"score_spread":0.30182405505947846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151103091","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0106736,0.00017374792,0.98759925,0.00019912452,0.000020663094,0.000034598164,0.00008093578,0.0007476354,0.00047049933],"genre_scores_gemma":[0.17567298,0.00045694303,0.8225169,0.000085232314,0.000047226047,0.000109329456,0.00025456736,0.0002284882,0.00062835397],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996227,0.00010980025,0.000020108593,0.00007349647,0.00014730652,0.00002650487],"domain_scores_gemma":[0.9992674,0.00028066922,0.000102220736,0.00010898674,0.0001810972,0.000059656566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006639365,0.0007124623,0.0007449396,0.0014141068,0.00028753834,0.0017293518,0.00078670017,0.00055077695,0.001822737],"category_scores_gemma":[0.002307551,0.00033929467,0.00082037796,0.0011073347,0.0005838589,0.0014250599,0.001582642,0.0011141606,0.00042830274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034459837,0.00012063707,0.0021146275,0.00058837543,0.00020287048,0.00053300365,0.0014982981,0.22011355,0.1491537,0.059220076,0.007557196,0.55855304],"study_design_scores_gemma":[0.000025120087,0.000108770815,0.0013712109,0.000035337544,0.000025653233,0.00066471536,0.00016915254,0.93744063,0.021500798,0.031724002,0.006861222,0.000073423944],"about_ca_topic_score_codex":0.0011644191,"about_ca_topic_score_gemma":0.00087585906,"teacher_disagreement_score":0.001822737,"about_ca_system_score_codex":0.00041859472,"about_ca_system_score_gemma":0.0005657368,"threshold_uncertainty_score":0.0060976744},"labels":[],"label_agreement":null},{"id":"W2151299940","doi":"10.1046/j.1528-1157.2003.55902.x","title":"Recurrent Nonstatus Generalized Seizures Alter the Developing Chicken Brain","year":2003,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Epilepsy; Magnetic resonance imaging; Psychology; Internal medicine; Medicine; Endocrinology; Neuroscience; Radiology","score_opus":0.07597483513792062,"score_gpt":0.37231616077027696,"score_spread":0.2963413256323563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151299940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99923456,0.00018305823,0.0003223993,0.000009485618,0.0000016907352,0.000004430751,0.000029415954,0.000013688734,0.00020120743],"genre_scores_gemma":[0.99886024,0.00017720817,0.00039087524,0.000011504743,0.0000019266809,0.000008466773,0.000083089624,0.0000048160937,0.0004619823],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99995756,0.0000053597387,0.0000040801115,0.000012520638,0.000010689194,0.000009775907],"domain_scores_gemma":[0.99987924,0.000012707151,0.000061620914,0.000009783403,0.0000160411,0.000020529875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005941522,0.00022736267,0.00009510733,0.00020999218,0.000055366825,0.00012333988,0.00007181327,0.00014563145,0.0005963242],"category_scores_gemma":[0.0001630769,0.0000821783,0.00008348888,0.00004502321,0.0002205008,0.00016603847,0.00010252241,0.00016055346,0.00011221901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014194741,0.000014893358,0.003434771,0.000026627898,0.000004653602,0.0002716483,0.000041485728,0.000032950535,0.99394,0.000026287751,0.000018095983,0.0020467027],"study_design_scores_gemma":[0.00004239888,0.0027333365,0.3769071,0.000021178254,0.000055229473,0.0056311795,0.00045117622,0.0010876594,0.6117808,0.00010869289,0.0011659616,0.000015307634],"about_ca_topic_score_codex":0.0006674245,"about_ca_topic_score_gemma":0.0013791878,"teacher_disagreement_score":0.0006674245,"about_ca_system_score_codex":0.00016475347,"about_ca_system_score_gemma":0.00008352288,"threshold_uncertainty_score":0.0019948483},"labels":[],"label_agreement":null},{"id":"W2151907388","doi":"10.1038/mp.2012.188","title":"Elevated serum measures of lipid peroxidation and abnormal prefrontal white matter in euthymic bipolar adults: toward peripheral biomarkers of bipolar disorder","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Center for Advancing Translational Sciences; Fogarty International Center; National Institute for Health and Care Research; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Fractional anisotropy; White matter; Bipolar disorder; Diffusion MRI; Psychology; Internal medicine; Lipid peroxidation; Analysis of variance; Biomarker; Endocrinology; Neuroscience; Medicine; Chemistry; Magnetic resonance imaging; Cognition; Oxidative stress; Biochemistry","score_opus":0.01313908495907106,"score_gpt":0.2599156324976838,"score_spread":0.24677654753861272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151907388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99693274,0.0013232097,0.00028441218,0.0001427596,0.000016552089,0.000019748068,0.0001458062,0.000012896216,0.0011218257],"genre_scores_gemma":[0.99882275,0.0003330641,0.0004687881,0.00009017364,0.0000143266625,0.000007919039,0.000089624176,0.0000015757607,0.00017178433],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998816,0.000026889944,0.000021885484,0.00002414264,0.000025989926,0.000019403598],"domain_scores_gemma":[0.9996165,0.000050348877,0.0001931974,0.000020876902,0.00005329711,0.00006578164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036944132,0.00043391454,0.0003211394,0.00077626744,0.0004608835,0.0008350254,0.00022377496,0.00059226045,0.0007272869],"category_scores_gemma":[0.0009689803,0.00025506454,0.00013592948,0.00057888904,0.000312527,0.00037777764,0.0003368324,0.00068518607,0.0001303275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008560724,0.00013998954,0.97985303,0.000045605342,0.0000824904,0.0003587831,0.00021903763,0.000074548036,0.011001212,0.00009234883,0.00017174025,0.007105237],"study_design_scores_gemma":[0.000017129256,0.00025685152,0.99701214,0.000019278916,0.000048367685,0.00076240866,0.00030565032,0.00026564303,0.0009653828,0.00018858984,0.00015417639,0.0000043427876],"about_ca_topic_score_codex":0.0020236445,"about_ca_topic_score_gemma":0.004585962,"teacher_disagreement_score":0.0020236445,"about_ca_system_score_codex":0.00024931095,"about_ca_system_score_gemma":0.00024591284,"threshold_uncertainty_score":0.0040237308},"labels":[],"label_agreement":null},{"id":"W2152024551","doi":"10.1139/jpn.0416","title":"Cotard’s syndrome with schizophreniform disorder can be successfully treated with electroconvulsive therapy: case report","year":2004,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Electroconvulsive therapy; Schizophreniform disorder; Medicine; Magnetic resonance imaging; Atrophy; Schizophrenia (object-oriented programming); Ventricle; Psychosis; Antipsychotic; Pediatrics; Psychiatry; Radiology; Cardiology; Internal medicine","score_opus":0.02057064078617056,"score_gpt":0.30333214825229476,"score_spread":0.2827615074661242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152024551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.985598,0.003235055,0.0014176153,0.0011417206,0.00026147906,0.00012830624,0.000071012226,0.00010310218,0.008043728],"genre_scores_gemma":[0.9967957,0.00095297577,0.000701032,0.00041427644,0.00029478135,0.00002509683,0.00004862545,0.000011251678,0.000756197],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9996917,0.000038829236,0.000031515396,0.000054084343,0.000055546257,0.00012833563],"domain_scores_gemma":[0.99919623,0.00022726756,0.00021677338,0.00006942713,0.00004316786,0.00024718666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017825466,0.0017043411,0.00082948327,0.0012771854,0.0019970282,0.0008765971,0.0006272822,0.0034728239,0.0015763553],"category_scores_gemma":[0.0021077832,0.00076582155,0.00073082506,0.0010804047,0.0013430172,0.0007956094,0.0010809586,0.0015450087,0.00042227434],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025454883,0.000018728577,0.005092902,0.000013730805,0.000007714111,0.9931096,0.000103129554,0.000029255754,0.0005846525,0.00010302505,0.00011424091,0.0007976522],"study_design_scores_gemma":[0.000020719393,0.00004263378,0.0034692602,0.000007429314,0.000009967799,0.9955778,0.00006071988,0.00015022383,0.00021477709,0.00009474155,0.0003434954,0.00000818176],"about_ca_topic_score_codex":0.0051908013,"about_ca_topic_score_gemma":0.0068881796,"teacher_disagreement_score":0.0051908013,"about_ca_system_score_codex":0.0006387551,"about_ca_system_score_gemma":0.000941953,"threshold_uncertainty_score":0.01032114},"labels":[],"label_agreement":null},{"id":"W2152573143","doi":"10.1002/hbm.22877","title":"Age‐related changes in the topological organization of the white matter structural connectome across the human lifespan","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":226,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Key Research and Development Program of China; National Science Fund for Distinguished Young Scholars; Fundamental Research Funds for the Central Universities; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Connectome; White matter; Neuroscience; Human brain; Psychology; Functional connectivity; Biology; Medicine; Magnetic resonance imaging","score_opus":0.10241650907414852,"score_gpt":0.3699829839895887,"score_spread":0.26756647491544017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152573143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99758863,0.00024946788,0.0013392161,0.000020006299,0.0000026449334,0.0000052874084,0.00044738242,0.000016888558,0.00033058206],"genre_scores_gemma":[0.9985629,0.00015408947,0.000805038,0.0000063728125,0.0000033012252,0.000005476357,0.00031496157,0.0000030893623,0.00014469115],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999193,0.000014063441,0.000007689972,0.00003561692,0.000013010265,0.000010260108],"domain_scores_gemma":[0.99947506,0.00008595527,0.0002314427,0.00007544317,0.00009297518,0.00003917211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036463438,0.00022354166,0.00015205928,0.0010628029,0.00016857543,0.00025344497,0.00012919547,0.00021988062,0.0007468249],"category_scores_gemma":[0.0014903587,0.00013463643,0.00017081625,0.00041540113,0.00023806798,0.00037189297,0.00029413545,0.00016283932,0.00010558471],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022470384,0.00003659283,0.92979336,0.000073827476,0.00031103994,0.00039832154,0.0007224096,0.0032146862,0.032157995,0.0008414409,0.0005873689,0.031638235],"study_design_scores_gemma":[0.0000013671969,0.00004652221,0.99649626,0.0000064991227,0.000027938455,0.0002821719,0.00007280773,0.0013685105,0.00086595945,0.0005495897,0.00027607498,0.000006358526],"about_ca_topic_score_codex":0.0031591873,"about_ca_topic_score_gemma":0.005250492,"teacher_disagreement_score":0.0031591873,"about_ca_system_score_codex":0.00016119974,"about_ca_system_score_gemma":0.00011424498,"threshold_uncertainty_score":0.0062816143},"labels":[],"label_agreement":null},{"id":"W2153291416","doi":"10.1109/fbit.2007.52","title":"Brain Differences Visualized in the Blind Using Tensor Manifold Statistics and Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Diffusion MRI; Fractional anisotropy; Tensor (intrinsic definition); Geodesic; Cartesian tensor; Mathematics; Scalar (mathematics); Tensor density; Symmetric tensor; Tensor field; Univariate; Euclidean distance; Manifold (fluid mechanics); Riemannian manifold; Metric (unit); Mathematical analysis; Artificial intelligence; Pattern recognition (psychology); Pure mathematics; Multivariate statistics; Statistics; Geometry; Computer science; Magnetic resonance imaging; Exact solutions in general relativity; Medicine","score_opus":0.09949310874390531,"score_gpt":0.4247981532152353,"score_spread":0.32530504447132996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153291416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9670409,0.0002530183,0.031647462,0.000068972615,0.000028641774,0.000042741365,0.00023432347,0.0001500348,0.0005339633],"genre_scores_gemma":[0.9790717,0.00011114443,0.020184644,0.00002109892,0.000022351202,0.000022137052,0.00011815591,0.000044243818,0.0004043813],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99913496,0.0002561427,0.00010781444,0.00020185194,0.00024053706,0.000058670543],"domain_scores_gemma":[0.99780184,0.00076411176,0.00052753615,0.00041588355,0.00028804198,0.00020247314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002935961,0.0007931499,0.000802872,0.0032736312,0.0004543538,0.0009863061,0.0002376799,0.000536519,0.0021760117],"category_scores_gemma":[0.009254174,0.00024483338,0.0004913679,0.00093314174,0.0020965093,0.0016911462,0.0011763957,0.00056418567,0.00021892336],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012321937,0.0007675131,0.18057387,0.00076738576,0.0012859844,0.0021996668,0.004373039,0.020917969,0.41178694,0.017101098,0.0029554549,0.34494913],"study_design_scores_gemma":[0.00030873908,0.0055252314,0.6999688,0.00008402877,0.00042248794,0.006600169,0.0017209608,0.10472081,0.112219416,0.064237624,0.0037224675,0.0004693008],"about_ca_topic_score_codex":0.0021871794,"about_ca_topic_score_gemma":0.0021306563,"teacher_disagreement_score":0.0032736312,"about_ca_system_score_codex":0.00033350443,"about_ca_system_score_gemma":0.00059788843,"threshold_uncertainty_score":0.01552701},"labels":[],"label_agreement":null},{"id":"W2153399392","doi":"10.1007/978-3-319-19992-4_5","title":"A Compressed-Sensing Approach for Super-Resolution Reconstruction of Diffusion MRI","year":2015,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Computer science; Compressed sensing; Diffusion; Computer vision; Artificial intelligence; Resolution (logic); Algorithm; Physics","score_opus":0.07223077402635684,"score_gpt":0.33255021830840115,"score_spread":0.2603194442820443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153399392","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014706437,0.00016551085,0.9975926,0.00015542627,0.000024524043,0.00001449363,0.00002892354,0.00007135049,0.00047647447],"genre_scores_gemma":[0.06949915,0.0010387902,0.92608804,0.0001899486,0.00016707843,0.00008389789,0.00021232839,0.000106813684,0.0026139675],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967384,0.00009657453,0.000023543467,0.000044386274,0.00014196226,0.000019675696],"domain_scores_gemma":[0.9990414,0.0006119915,0.000061059334,0.00010349038,0.00013317431,0.00004889281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007970671,0.0007389784,0.0006512959,0.0005684104,0.0002960251,0.0007580352,0.0010786087,0.0013251347,0.0031688458],"category_scores_gemma":[0.002982541,0.0004347724,0.0006630206,0.00080287736,0.00064270693,0.0012030327,0.0014491224,0.0016559638,0.00072106096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026376083,0.00014302158,0.0003276364,0.0006126605,0.00009892304,0.00042262083,0.00029640386,0.3592441,0.099343374,0.15150434,0.0059713647,0.38177177],"study_design_scores_gemma":[0.0000070446054,0.000032660555,0.00006399836,0.000010621811,0.000008464684,0.00014681778,0.000010723634,0.9797529,0.004834581,0.01333447,0.0017840785,0.000013632302],"about_ca_topic_score_codex":0.001666987,"about_ca_topic_score_gemma":0.0019314728,"teacher_disagreement_score":0.0031688458,"about_ca_system_score_codex":0.0002645396,"about_ca_system_score_gemma":0.000658796,"threshold_uncertainty_score":0.010600865},"labels":[],"label_agreement":null},{"id":"W2154288487","doi":"10.1016/j.neuroimage.2010.05.019","title":"Selective effects of aging on brain white matter microstructure: A diffusion tensor imaging tractography study","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Johns Hopkins University","keywords":"Diffusion MRI; Tractography; White matter; Psychology; Neuroscience; Nuclear magnetic resonance; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.010962183111987139,"score_gpt":0.30519724965844625,"score_spread":0.2942350665464591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154288487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988913,0.0003791598,0.00033537345,0.000026661377,0.00001048115,0.000013489608,0.000103107806,0.0000058331043,0.00023473529],"genre_scores_gemma":[0.9982181,0.00048177055,0.000459692,0.000047484198,0.000028902537,0.00001169064,0.00014168282,0.000017002758,0.00059356267],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988425,0.000019633793,0.000011738777,0.000045854667,0.000016501557,0.000022178056],"domain_scores_gemma":[0.99942636,0.00011201884,0.00015150699,0.00013637262,0.00008244154,0.00009125429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007296761,0.0006230782,0.0004907958,0.0005792083,0.00037357566,0.0003706676,0.00023937832,0.0005066475,0.0012398307],"category_scores_gemma":[0.0013203972,0.00029511072,0.00039705186,0.00048991037,0.00077625265,0.00073215197,0.00032506435,0.00035212206,0.00018427309],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.022424785,0.0016972532,0.25050285,0.0003330062,0.0009992729,0.0049114856,0.0017947641,0.00055032445,0.671922,0.00070888695,0.00079457974,0.043360826],"study_design_scores_gemma":[0.00019075949,0.003505313,0.9722855,0.000009496423,0.0007027733,0.0031163702,0.00027297402,0.00071627344,0.017694714,0.00061192835,0.0008648283,0.000029213184],"about_ca_topic_score_codex":0.0033673805,"about_ca_topic_score_gemma":0.003944157,"teacher_disagreement_score":0.0033673805,"about_ca_system_score_codex":0.00022546214,"about_ca_system_score_gemma":0.00041328438,"threshold_uncertainty_score":0.0066955686},"labels":[],"label_agreement":null},{"id":"W2154641379","doi":"10.1109/cvprw.2008.4563000","title":"Dealing with uncertainty in the principal directions of tensors","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Eigenvalues and eigenvectors; Tensor (intrinsic definition); Isotropy; Mathematics; Principal component analysis; Invariant (physics); Anisotropy; Tensor density; Monte Carlo method; Upper and lower bounds; Symmetric tensor; Principal axis theorem; Diffusion MRI; Multivariate statistics; Mathematical analysis; Cartesian tensor; Statistical physics; Tensor field; Geometry; Exact solutions in general relativity; Physics; Statistics; Quantum mechanics; Mathematical physics","score_opus":0.0950029987130292,"score_gpt":0.352952443618063,"score_spread":0.2579494449050338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154641379","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024064384,0.00059164345,0.97367316,0.00061364204,0.00005425853,0.00003297116,0.00007945478,0.00009689219,0.00079352816],"genre_scores_gemma":[0.6648017,0.0019334214,0.330301,0.0003434826,0.00060008944,0.00030395368,0.00033293045,0.00019656848,0.0011869654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98344696,0.006393746,0.0012189844,0.0033157337,0.0049430584,0.0006815555],"domain_scores_gemma":[0.84274876,0.12738347,0.011117802,0.012036949,0.0057096905,0.0010034287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027348341,0.0014327419,0.0024118102,0.004576229,0.0018946336,0.0046920236,0.002430025,0.003086062,0.0012549793],"category_scores_gemma":[0.13515392,0.0017534774,0.0018145612,0.003235159,0.006290215,0.006890124,0.003909216,0.004226728,0.00028167936],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035992332,0.00005984303,0.010903953,0.00054356654,0.00040666317,0.0009010419,0.001039805,0.5607753,0.004384196,0.31145632,0.001625743,0.107543565],"study_design_scores_gemma":[0.000026484619,0.000054285618,0.0031291172,0.00008589368,0.0000495802,0.00035561525,0.00014163554,0.61608905,0.0024449166,0.37564632,0.0018678738,0.000109282875],"about_ca_topic_score_codex":0.0031748158,"about_ca_topic_score_gemma":0.0020090884,"teacher_disagreement_score":0.027348341,"about_ca_system_score_codex":0.001865599,"about_ca_system_score_gemma":0.002004058,"threshold_uncertainty_score":0.14463359},"labels":[],"label_agreement":null},{"id":"W2155842404","doi":"10.1186/s12968-014-0087-8","title":"In vivo cardiovascular magnetic resonance diffusion tensor imaging shows evidence of abnormal myocardial laminar orientations and mobility in hypertrophic cardiomyopathy","year":2014,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":190,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Imperial College London; British Heart Foundation; School of Medicine, New York University; York University","keywords":"Diastole; Systole; Hypertrophic cardiomyopathy; Cardiology; Medicine; Internal medicine; Laminar flow; Diffusion MRI; Magnetic resonance imaging; Physics; Radiology; Mechanics; Blood pressure","score_opus":0.02008538652450102,"score_gpt":0.27364397560279036,"score_spread":0.2535585890782893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155842404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996075,0.00005980472,0.00019609979,0.000010140835,0.0000013815104,0.0000019253073,0.000014357541,0.0000035585156,0.00010520418],"genre_scores_gemma":[0.99964607,0.00003234409,0.00020621945,0.000010003281,0.000005239468,0.0000028008208,0.0000368317,0.0000016463229,0.000058735895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992657,0.000018850355,0.000008685957,0.000017951266,0.00001105022,0.000016808164],"domain_scores_gemma":[0.9996325,0.00006472504,0.00015473398,0.00003174261,0.000035058816,0.000081368555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035098323,0.0002550485,0.00012254095,0.0003377578,0.0001630598,0.0001757357,0.00007518459,0.00025329617,0.0009415999],"category_scores_gemma":[0.0006068795,0.00017374217,0.00007792155,0.00010099935,0.0003188,0.0001213228,0.00022977668,0.00016930224,0.00012420416],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016988175,0.00014186859,0.6919295,0.00006226483,0.00009970322,0.0019324749,0.00056381366,0.00029034115,0.29500678,0.0000929058,0.00017922293,0.008002346],"study_design_scores_gemma":[0.000019414365,0.00021532056,0.9939261,0.0000044279777,0.000015509542,0.0018462935,0.00008007193,0.00023094795,0.003529067,0.000049520422,0.00007956057,0.0000037548414],"about_ca_topic_score_codex":0.00043229095,"about_ca_topic_score_gemma":0.0006891602,"teacher_disagreement_score":0.0009415999,"about_ca_system_score_codex":0.000103265455,"about_ca_system_score_gemma":0.00009061124,"threshold_uncertainty_score":0.0031499863},"labels":[],"label_agreement":null},{"id":"W2156040424","doi":"10.3174/ajnr.a3553","title":"Novel White Matter Tract Integrity Metrics Sensitive to Alzheimer Disease Progression","year":2013,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":154,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; National Institute of Neurological Disorders and Stroke; York University","keywords":"White matter; Corpus callosum; Medicine; Diffusion MRI; Pathology; Neuroscience; Alzheimer's disease; Neurodegeneration; Magnetic resonance imaging; Disease; Biology; Radiology","score_opus":0.06452016962225685,"score_gpt":0.3792456606411035,"score_spread":0.3147254910188466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156040424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97863173,0.0007155436,0.018827805,0.00006465245,0.0000129036225,0.000039932045,0.00076619827,0.0002618177,0.00067943253],"genre_scores_gemma":[0.99012357,0.000121474994,0.008994299,0.00001551032,0.000012774489,0.000026028312,0.00052406924,0.000019212986,0.00016308237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996828,0.00007392436,0.000039591356,0.0000948984,0.0000774977,0.000031334606],"domain_scores_gemma":[0.9969927,0.0006768769,0.001399729,0.00021227327,0.00052131375,0.0001970979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012827544,0.00074804184,0.00048498312,0.0022612216,0.00023986085,0.0007978144,0.00034433545,0.0005386655,0.0007949826],"category_scores_gemma":[0.0054151225,0.00019801535,0.00030675123,0.00083880464,0.00046257753,0.0007844368,0.0005647444,0.0004421076,0.0002200742],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096889347,0.0001360841,0.8886219,0.00017420285,0.0004915996,0.0002290742,0.0002611707,0.010129588,0.03905157,0.00060780183,0.0009976937,0.058330435],"study_design_scores_gemma":[0.000041634234,0.000634089,0.8931083,0.00007228252,0.00023369561,0.0025335844,0.00020132147,0.07937439,0.01946103,0.003115769,0.0011411469,0.00008273981],"about_ca_topic_score_codex":0.0019310015,"about_ca_topic_score_gemma":0.0031261812,"teacher_disagreement_score":0.0022612216,"about_ca_system_score_codex":0.00046030965,"about_ca_system_score_gemma":0.00039040507,"threshold_uncertainty_score":0.0067839026},"labels":[],"label_agreement":null},{"id":"W2156127840","doi":"10.1016/j.neuroimage.2005.05.014","title":"Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":173,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University Health Centre; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Imaging phantom; Anisotropic diffusion; Tracking (education); Anisotropy; Tensor (intrinsic definition); Fiber; Diffusion; Computer science; Computer vision; Artificial intelligence; Physics; Mathematics; Geometry; Optics; Materials science","score_opus":0.07984183456497795,"score_gpt":0.3637643607038004,"score_spread":0.28392252613882246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156127840","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32636175,0.0017479805,0.6670467,0.00023896492,0.00019367218,0.00044413662,0.00084141485,0.002028869,0.0010965561],"genre_scores_gemma":[0.5776637,0.0013278866,0.4169323,0.00011624673,0.00006357797,0.00028373004,0.0011665192,0.0008512973,0.0015947879],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972459,0.0013871648,0.00022704534,0.0005375534,0.0005028332,0.000099496385],"domain_scores_gemma":[0.97572315,0.014118537,0.0016296942,0.0027306862,0.005411231,0.00038673045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015035289,0.0011858704,0.0013532257,0.0031230103,0.0011706003,0.0017085376,0.0012902324,0.0022899355,0.0015171291],"category_scores_gemma":[0.037857205,0.0007207223,0.0010373944,0.0020414868,0.0010740658,0.0032543081,0.0017713399,0.0014708934,0.00097575894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0066845426,0.0013613973,0.039723754,0.0019610657,0.0016898204,0.00030446547,0.0016022559,0.161732,0.07594901,0.004153035,0.002808051,0.7020306],"study_design_scores_gemma":[0.0005185177,0.00092929613,0.019187946,0.00017008846,0.0005781852,0.0007520015,0.00018654128,0.94194,0.029885296,0.0032156848,0.0024783309,0.0001579947],"about_ca_topic_score_codex":0.012597202,"about_ca_topic_score_gemma":0.008794001,"teacher_disagreement_score":0.015035289,"about_ca_system_score_codex":0.0006168225,"about_ca_system_score_gemma":0.0022837948,"threshold_uncertainty_score":0.07951516},"labels":[],"label_agreement":null},{"id":"W2156721104","doi":"10.1016/j.jad.2012.04.047","title":"Corpus callosal morphology in early onset adolescent depression","year":2012,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Calgary","funders":"","keywords":"Corpus callosum; Major depressive disorder; White matter; Depression (economics); Psychology; Diffusion MRI; Magnetic resonance imaging; Audiology; Age of onset; Psychiatry; Neuroscience; Medicine; Internal medicine; Cognition; Radiology; Disease","score_opus":0.02806847152146154,"score_gpt":0.34516273907371925,"score_spread":0.3170942675522577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156721104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997663,0.00035569898,0.00021043037,0.00006529138,0.0000051637194,0.0000074461664,0.00007352411,0.0000066057264,0.0016128611],"genre_scores_gemma":[0.99917847,0.00026172368,0.0001501321,0.000014353293,0.000006493693,0.0000037753246,0.00003171086,0.000006135547,0.00034707756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994004,0.00001332639,0.0000065047807,0.000009827145,0.000013536199,0.000016652666],"domain_scores_gemma":[0.99965477,0.00014934051,0.0000768951,0.000027484577,0.000048355538,0.000043111457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018708021,0.00019929197,0.00015213178,0.0011192278,0.00028858005,0.0005043737,0.00030417767,0.00047379945,0.0022165151],"category_scores_gemma":[0.0011595103,0.00022933653,0.00009513763,0.00043091454,0.00046006794,0.00033658824,0.0002555236,0.00033032463,0.000281206],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021161023,0.00017637506,0.5384197,0.00020402465,0.00010753722,0.20935473,0.0028175262,0.0010501402,0.17069332,0.0015271744,0.0010273645,0.072506145],"study_design_scores_gemma":[0.000029286024,0.00010176946,0.91246456,0.000033332042,0.00004017411,0.08046619,0.00085261534,0.0008137303,0.003983148,0.00037639783,0.0008251597,0.000013631973],"about_ca_topic_score_codex":0.004427144,"about_ca_topic_score_gemma":0.0072445753,"teacher_disagreement_score":0.004427144,"about_ca_system_score_codex":0.0003407394,"about_ca_system_score_gemma":0.00024691958,"threshold_uncertainty_score":0.008802712},"labels":[],"label_agreement":null},{"id":"W2157049741","doi":"10.1177/1550059413476031","title":"Neurofeedback Training Induces Changes in White and Gray Matter","year":2013,"lang":"en","type":"article","venue":"Clinical EEG and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":158,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fractional anisotropy; Neurofeedback; White matter; Diffusion MRI; Psychology; Neuroscience; Audiology; Gray (unit); Magnetic resonance imaging; Corpus callosum; Cognition; Neuroimaging; Electroencephalography; Medicine; Nuclear medicine","score_opus":0.1997951354628762,"score_gpt":0.42816003467488056,"score_spread":0.22836489921200437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157049741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987382,0.00016018754,0.0006746235,0.000036450725,0.000012420791,0.00003279838,0.000030025269,0.000019389654,0.00029601762],"genre_scores_gemma":[0.99826187,0.00017936932,0.0005972094,0.000043220876,0.000015193572,0.00009863343,0.00006337971,0.0000037896295,0.00073733984],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999249,0.000010845486,0.0000055517394,0.000019304543,0.000019002606,0.000020340582],"domain_scores_gemma":[0.99984956,0.000040076382,0.00005357558,0.000015517628,0.000018097518,0.000023182844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012436463,0.00028472554,0.0001883237,0.0001814482,0.00009282876,0.00009473387,0.00012496648,0.00024765826,0.0014225283],"category_scores_gemma":[0.00043902692,0.000095593685,0.000102265716,0.00007283364,0.00022806787,0.00012835042,0.00021111603,0.00020049348,0.00010099039],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003710124,0.0008586878,0.0017064346,0.00008703293,0.0000201634,0.0001008926,0.00010551474,0.0001650995,0.9704414,0.000041577496,0.000082754406,0.02268028],"study_design_scores_gemma":[0.0009364466,0.07659854,0.38744453,0.000055578075,0.00015286195,0.0011834307,0.00041782323,0.0037413735,0.52596396,0.00062357594,0.0028525558,0.000029434425],"about_ca_topic_score_codex":0.00048811996,"about_ca_topic_score_gemma":0.00085638807,"teacher_disagreement_score":0.0014225283,"about_ca_system_score_codex":0.00012235064,"about_ca_system_score_gemma":0.00015924303,"threshold_uncertainty_score":0.004758835},"labels":[],"label_agreement":null},{"id":"W2157436069","doi":"10.1016/j.bandl.2012.10.009","title":"Diffusion tensor imaging correlates of reading ability in dysfluent and non-impaired readers","year":2013,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Health Solutions","keywords":"Psychology; Reading (process); Diffusion MRI; Fractional anisotropy; Fluency; Cognitive psychology; White matter; Word recognition; Dyslexia; Audiology; Voxel; Neuroscience; Developmental psychology; Linguistics; Magnetic resonance imaging","score_opus":0.015969177001500072,"score_gpt":0.30021340216458997,"score_spread":0.2842442251630899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157436069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99946576,0.000058811045,0.000017987333,0.000011645237,0.0000016969117,0.000001956088,0.000086683496,0.0000024812284,0.00035296386],"genre_scores_gemma":[0.99961025,0.000031700638,0.000021132793,0.000006582751,0.000004625576,0.0000019085523,0.00008776265,0.0000015150509,0.00023450112],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997936,0.000029120241,0.00004261942,0.000050370094,0.000027365588,0.000056885296],"domain_scores_gemma":[0.9970432,0.0010990199,0.0010824911,0.00011407576,0.00030967515,0.00035150143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003683139,0.00044469433,0.0003671721,0.002184778,0.00039752427,0.0010643718,0.00036362233,0.00053333613,0.0031840405],"category_scores_gemma":[0.0046007195,0.00024058025,0.00025122895,0.0007886513,0.0006839083,0.0010087822,0.0005382918,0.00042720587,0.00047439578],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001151544,0.0001357658,0.98762137,0.000029637877,0.000070560694,0.0010971653,0.001322648,0.00009682159,0.0045615127,0.00006459816,0.00011119288,0.0037371847],"study_design_scores_gemma":[0.000005368771,0.000119762066,0.9981831,0.0000030205993,0.00001757338,0.00061181025,0.0006302859,0.000103979466,0.00023400623,0.000055127417,0.00003114013,0.000004757497],"about_ca_topic_score_codex":0.009434707,"about_ca_topic_score_gemma":0.009059583,"teacher_disagreement_score":0.009434707,"about_ca_system_score_codex":0.00027994075,"about_ca_system_score_gemma":0.00019750246,"threshold_uncertainty_score":0.018759549},"labels":[],"label_agreement":null},{"id":"W2157453960","doi":"10.1093/brain/awr099","title":"White matter damage in primary progressive aphasias: a diffusion tensor tractography study","year":2011,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":310,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"White matter; Diffusion MRI; Primary progressive aphasia; Tractography; Medicine; Psychology; Neuroscience; Magnetic resonance imaging; Pathology; Radiology; Dementia; Frontotemporal dementia; Disease","score_opus":0.06289204211024735,"score_gpt":0.33334876634951954,"score_spread":0.2704567242392722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157453960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997191,0.00004194486,0.00010611407,0.000008762748,5.7328e-7,0.000007059212,0.000032306994,0.000002243155,0.00008192903],"genre_scores_gemma":[0.9996427,0.000027936341,0.00017198652,0.000004445888,0.000002313184,0.0000056369036,0.000056041983,0.0000013071947,0.00008761564],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998306,0.000033510503,0.000024608917,0.000049558297,0.000034929955,0.000026794116],"domain_scores_gemma":[0.9995608,0.00009082703,0.00014602141,0.00006246542,0.00005602558,0.00008397836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038293493,0.00040848,0.00025432438,0.0010015992,0.00032422034,0.00026702747,0.00017085389,0.00038282803,0.0010738279],"category_scores_gemma":[0.001420629,0.00022333843,0.00023617521,0.00033030825,0.00057381374,0.00030715566,0.00034039447,0.00021295718,0.00020930455],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007848979,0.00020605863,0.9440777,0.00006462791,0.00017637623,0.006531774,0.0016558904,0.00024845722,0.038377814,0.00011295238,0.00010594656,0.0076575335],"study_design_scores_gemma":[0.00001438854,0.00021218079,0.99296194,0.0000033478248,0.000021940052,0.005811714,0.00014209744,0.0002635307,0.00044916256,0.000049360264,0.0000664727,0.0000038929],"about_ca_topic_score_codex":0.004500362,"about_ca_topic_score_gemma":0.0051723495,"teacher_disagreement_score":0.004500362,"about_ca_system_score_codex":0.00026593803,"about_ca_system_score_gemma":0.0002882267,"threshold_uncertainty_score":0.008948326},"labels":[],"label_agreement":null},{"id":"W2157938614","doi":"10.1523/jneurosci.3578-12.2013","title":"Early Musical Training and White-Matter Plasticity in the Corpus Callosum: Evidence for a Sensitive Period","year":2013,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":392,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Concordia University","funders":"Canadian Institutes of Health Research; McGill University","keywords":"Corpus callosum; White matter; Diffusion MRI; Period (music); Fractional anisotropy; Neuroscience; Neuroplasticity; Training (meteorology); Psychology; Audiology; Medicine; Magnetic resonance imaging; Physics","score_opus":0.15077021660382442,"score_gpt":0.37685208010264803,"score_spread":0.22608186349882362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157938614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99852824,0.00045628243,0.0002985663,0.000049321283,0.00000908336,0.0000065874447,0.000036402766,0.000009861849,0.0006056664],"genre_scores_gemma":[0.9984316,0.00025989625,0.00041335946,0.00003742786,0.000013534121,0.000019214027,0.00005488857,0.000006827616,0.0007631884],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99975616,0.000036351623,0.000015370784,0.000085722844,0.000054890203,0.000051504958],"domain_scores_gemma":[0.9986381,0.00019775123,0.0006346379,0.00007851565,0.000087836066,0.00036309083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041592316,0.00024941057,0.00022045978,0.0007569462,0.00026699668,0.0003664989,0.0002486522,0.00045803926,0.00171304],"category_scores_gemma":[0.0014436486,0.00015282327,0.00018363954,0.00019627207,0.00062766916,0.0003109634,0.00056508335,0.00038123337,0.00016948217],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019358243,0.0010474487,0.2574913,0.000301757,0.00023777517,0.0014588884,0.0012675617,0.0003778249,0.67483974,0.00067791744,0.0003919848,0.059972044],"study_design_scores_gemma":[0.0000051043785,0.00034498548,0.9936333,0.000023777384,0.000012863981,0.00017020268,0.00009516515,0.00007156844,0.00529254,0.00007535352,0.00027055017,0.0000047347235],"about_ca_topic_score_codex":0.0012318464,"about_ca_topic_score_gemma":0.0030219604,"teacher_disagreement_score":0.00171304,"about_ca_system_score_codex":0.000311477,"about_ca_system_score_gemma":0.00030774248,"threshold_uncertainty_score":0.0057306886},"labels":[],"label_agreement":null},{"id":"W2158262458","doi":"10.1016/j.mri.2008.01.015","title":"Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Stroke (engine); Medicine; Lesion; Magnetic resonance imaging; Cardiology; Nuclear medicine; Internal medicine; Nuclear magnetic resonance; Pathology; Radiology; Physics","score_opus":0.029512316993541083,"score_gpt":0.2961076474598769,"score_spread":0.2665953304663358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158262458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99857235,0.00019686834,0.00015031185,0.00006336007,0.000011363161,0.000015891887,0.00009307778,0.000009223607,0.00088759686],"genre_scores_gemma":[0.9988249,0.000184245,0.00017729723,0.000050488958,0.00009508247,0.000009755672,0.00027150172,0.0000062865297,0.00038045572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997799,0.000036396017,0.000044240656,0.00005376029,0.000040683626,0.000045152305],"domain_scores_gemma":[0.9986558,0.00028248742,0.0003900677,0.00018488208,0.00016584028,0.00032085663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005026799,0.00078927266,0.0005521754,0.0012331564,0.0005678508,0.0005918716,0.0005410742,0.0009327826,0.002209713],"category_scores_gemma":[0.002075815,0.00045984806,0.00048382048,0.0010114431,0.0006114449,0.0009404384,0.00029686396,0.0009361049,0.0007819061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004068303,0.0013429626,0.929076,0.000046358262,0.00017641862,0.033986613,0.00046943745,0.000109689354,0.023234975,0.00009246897,0.00033392117,0.007062697],"study_design_scores_gemma":[0.000100989106,0.0021131525,0.95241636,0.0000078198755,0.000117808304,0.041829742,0.00022321148,0.00032071111,0.0022169994,0.00010553673,0.00052648026,0.000021216649],"about_ca_topic_score_codex":0.0013663195,"about_ca_topic_score_gemma":0.000980656,"teacher_disagreement_score":0.002209713,"about_ca_system_score_codex":0.00020838519,"about_ca_system_score_gemma":0.0003366152,"threshold_uncertainty_score":0.0073922873},"labels":[],"label_agreement":null},{"id":"W2158459641","doi":"10.1007/s10618-015-0408-z","title":"Tractome: a visual data mining tool for brain connectivity analysis","year":2015,"lang":"en","type":"article","venue":"Data Mining and Knowledge Discovery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Visualization; Scalability; Artificial intelligence; Visual analytics; Process (computing); Set (abstract data type); Data visualization; Data set; Data mining; Machine learning; Human–computer interaction; Database","score_opus":0.27892127732114425,"score_gpt":0.467167125821036,"score_spread":0.18824584849989173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158459641","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010317909,0.00087279564,0.76057374,0.0006893969,0.00021204172,0.0004105578,0.05882861,0.16362342,0.004471512],"genre_scores_gemma":[0.110710725,0.0013713916,0.82819563,0.00043066128,0.0001438622,0.002161629,0.03960565,0.011712077,0.005668394],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996536,0.000059801372,0.000051197236,0.000097804535,0.00010770202,0.00002986613],"domain_scores_gemma":[0.998175,0.0010996439,0.00021354062,0.00021201144,0.00019479527,0.0001049829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010389468,0.001656798,0.00093193114,0.0050179637,0.00060085015,0.0019113363,0.0014702786,0.0009069865,0.026022153],"category_scores_gemma":[0.0071308548,0.00057014805,0.0015776422,0.003161358,0.00039962528,0.0015036402,0.0022032096,0.0012130777,0.004632767],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014396713,0.00023499229,0.0076881745,0.0042553716,0.0010579798,0.0015198732,0.0012351002,0.020105075,0.031427022,0.037833456,0.30852187,0.58468145],"study_design_scores_gemma":[0.00044860932,0.00040737068,0.01329636,0.00089682936,0.0006578374,0.0034415936,0.00055010524,0.43202683,0.05326079,0.18660375,0.30805203,0.000357892],"about_ca_topic_score_codex":0.0043129674,"about_ca_topic_score_gemma":0.007250422,"teacher_disagreement_score":0.026022153,"about_ca_system_score_codex":0.0005177675,"about_ca_system_score_gemma":0.0013152468,"threshold_uncertainty_score":0.08705282},"labels":[],"label_agreement":null},{"id":"W2159161559","doi":"10.1186/alzrt200","title":"Role of emerging neuroimaging modalities in patients with cognitive impairment: a review from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012","year":2013,"lang":"en","type":"review","venue":"Alzheimer s Research & Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Douglas College; Parkwood Institute; Université de Sherbrooke; Université Laval; Montreal Neurological Institute and Hospital; St Joseph's Health Care; Western University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Alzheimer's Association","keywords":"Neuroimaging; Dementia; Positron emission tomography; Modalities; Magnetic resonance imaging; Cognition; Medicine; Psychology; Medical physics; Disease; Psychiatry; Radiology; Pathology","score_opus":0.33295218630888307,"score_gpt":0.4519153971752655,"score_spread":0.11896321086638245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159161559","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000743518,0.99945825,0.000017411576,0.00026139233,0.00006912112,0.000010158553,0.000022289101,7.0410505e-7,0.00008630382],"genre_scores_gemma":[0.00085482636,0.9986337,0.0000867383,0.0002762714,0.00007148866,0.000017931237,0.000033472945,4.5860378e-7,0.000025040494],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973699,0.0005095337,0.000996716,0.00022074752,0.000777766,0.00012532997],"domain_scores_gemma":[0.99120224,0.00430136,0.0013268171,0.00009307699,0.0028908704,0.0001856242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052190293,0.0013065988,0.0039246366,0.011212574,0.0006259901,0.00187553,0.0017433688,0.001827929,0.0018688205],"category_scores_gemma":[0.014561188,0.0006143223,0.0030375277,0.011940844,0.0007248351,0.0020150093,0.0010494957,0.0013675686,0.00025805735],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033194575,0.00004079794,0.0012792293,0.39396504,0.0013930177,0.00052954414,0.00043345572,0.00021905215,0.00034178427,0.00070575345,0.027535543,0.5732248],"study_design_scores_gemma":[0.00020318692,0.0002596977,0.013741908,0.6689643,0.01125753,0.003117765,0.00066725316,0.00015533426,0.0003943181,0.00067018165,0.30043274,0.00013577224],"about_ca_topic_score_codex":0.043397877,"about_ca_topic_score_gemma":0.083450966,"teacher_disagreement_score":0.9942989,"about_ca_system_score_codex":0.005701137,"about_ca_system_score_gemma":0.014159361,"threshold_uncertainty_score":0.08629054},"labels":[],"label_agreement":null},{"id":"W2159251430","doi":"10.1038/npp.2013.93","title":"Alterations of Superficial White Matter in Schizophrenia and Relationship to Cognitive Performance","year":2013,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; National Alliance for Research on Schizophrenia and Depression; Centre for Addiction and Mental Health; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Cognition; Neuroscience; Effects of sleep deprivation on cognitive performance; Psychology; Diffusion MRI; Neuroimaging; Frontal lobe; Audiology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.0418119389417659,"score_gpt":0.3579025808085616,"score_spread":0.3160906418667957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159251430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991918,0.0002271504,0.00014203474,0.000027386151,0.0000016882815,0.0000043827913,0.000067833564,0.000004003694,0.0003337602],"genre_scores_gemma":[0.99941206,0.0001647662,0.00017051082,0.000011172081,0.0000033736646,0.0000034298919,0.000046386234,0.0000016270411,0.00018672735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999448,0.000011443856,0.000008674502,0.000010330109,0.000012992916,0.0000117444815],"domain_scores_gemma":[0.99958175,0.00007589939,0.00021207973,0.00002770348,0.000031814216,0.000070779824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002774701,0.0003551519,0.00019204502,0.0008098477,0.00023694569,0.0003352769,0.00018006096,0.0002879619,0.0013507574],"category_scores_gemma":[0.00069348514,0.00017987101,0.00014492552,0.00039395713,0.00042741912,0.00028278635,0.0003094787,0.0003659729,0.00010557545],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0058170254,0.0005183946,0.7910016,0.00018445963,0.0004924161,0.0025704708,0.00074597157,0.0008853535,0.16093877,0.00055899605,0.00013846913,0.03614806],"study_design_scores_gemma":[0.000013667679,0.00024378466,0.99609095,0.000004951852,0.00003439477,0.0006616034,0.00014492593,0.00025574956,0.00203723,0.00045995845,0.000047162375,0.0000057027873],"about_ca_topic_score_codex":0.0037959774,"about_ca_topic_score_gemma":0.0046250685,"teacher_disagreement_score":0.0037959774,"about_ca_system_score_codex":0.0002564337,"about_ca_system_score_gemma":0.00030943385,"threshold_uncertainty_score":0.007547796},"labels":[],"label_agreement":null},{"id":"W2159481232","doi":"10.1093/neuonc/nos160","title":"Clinical and neuroanatomical predictors of cerebellar mutism syndrome","year":2012,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; Pediatric Oncology Group; University of Toronto; SickKids Foundation; Hospital for Sick Children; University of Calgary","funders":"Pediatric Oncology Group of Ontario; C17 Council","keywords":"Cerebellum; Medicine; White matter; Medulloblastoma; Magnetic resonance imaging; Psychology; Pathology; Radiology; Internal medicine","score_opus":0.06592830632750624,"score_gpt":0.39698570053557347,"score_spread":0.33105739420806723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159481232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99959606,0.00008556637,0.000037669583,0.0000167259,0.0000014230471,0.0000032623489,0.000055919463,0.0000026056264,0.00020077353],"genre_scores_gemma":[0.9997267,0.00005803746,0.00006734011,0.0000052628675,0.0000045673773,0.0000048611273,0.00009681369,0.0000013283259,0.00003513771],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996989,0.000059276746,0.00004075372,0.00006770844,0.00007158847,0.000061747676],"domain_scores_gemma":[0.99766845,0.0006006235,0.0011072218,0.00005338234,0.00016743528,0.0004027914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027235423,0.00039730646,0.00022358494,0.0009917435,0.00036303158,0.000389488,0.00026826534,0.00042119308,0.0015227324],"category_scores_gemma":[0.003188584,0.00021054091,0.0001593334,0.0005772463,0.00052874617,0.00040275237,0.00042487917,0.0004166249,0.00017630079],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002606913,0.0000070674914,0.99898916,0.0000018477524,0.000004340258,0.00028641568,0.000015521258,0.000030598472,0.00022269113,0.000008126002,0.00002004505,0.00038820953],"study_design_scores_gemma":[0.0000023154396,0.000047649428,0.997776,0.000002996853,0.0000059175845,0.0018202466,0.00009284846,0.000120586345,0.00008271339,0.000015725525,0.000031180676,0.0000018069728],"about_ca_topic_score_codex":0.0031953186,"about_ca_topic_score_gemma":0.0040099295,"teacher_disagreement_score":0.0031953186,"about_ca_system_score_codex":0.00026452672,"about_ca_system_score_gemma":0.00045250388,"threshold_uncertainty_score":0.006353438},"labels":[],"label_agreement":null},{"id":"W2159593426","doi":"10.1007/978-3-642-15711-0_3","title":"Extraction of the Plane of Minimal Cross-Sectional Area of the Corpus Callosum Using Template-Driven Segmentation","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Western University; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Corpus callosum; Segmentation; Computer science; Artificial intelligence; Bottleneck; Plane (geometry); Pattern recognition (psychology); Cross section (physics); Magnetic resonance imaging; Artificial neural network; Computer vision; Anatomy; Mathematics; Physics; Geometry; Medicine; Radiology","score_opus":0.061906115286102466,"score_gpt":0.37233952337964477,"score_spread":0.3104334080935423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159593426","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057461053,0.0010460992,0.9294867,0.0003997262,0.000097874385,0.00034065443,0.0023323807,0.006298374,0.0025371097],"genre_scores_gemma":[0.15743382,0.00087829464,0.8365172,0.00011059963,0.000076188844,0.0002987999,0.002138412,0.001178008,0.0013686549],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956995,0.00005564473,0.000041321808,0.00012871943,0.00012731437,0.000077082186],"domain_scores_gemma":[0.99896073,0.00034705785,0.00011953495,0.0001713115,0.00034665925,0.000054724533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010696938,0.0012340712,0.0013585525,0.0042028264,0.0006925892,0.0028912975,0.0011963386,0.0023695922,0.0024220967],"category_scores_gemma":[0.0038509306,0.0010191144,0.0016981765,0.0030026624,0.00045860198,0.000850086,0.00088852213,0.0012083079,0.00207137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071307545,0.00013091527,0.008786119,0.000918338,0.00035967023,0.0016819276,0.0007158308,0.036906924,0.28501612,0.012052927,0.017609127,0.63510895],"study_design_scores_gemma":[0.00013316727,0.00020481671,0.02920666,0.00029072093,0.0005484055,0.006027677,0.00047077687,0.6639377,0.23987065,0.022618128,0.036410853,0.00028050685],"about_ca_topic_score_codex":0.009393721,"about_ca_topic_score_gemma":0.0073296167,"teacher_disagreement_score":0.009393721,"about_ca_system_score_codex":0.0005758516,"about_ca_system_score_gemma":0.0043154955,"threshold_uncertainty_score":0.01867807},"labels":[],"label_agreement":null},{"id":"W2160990082","doi":"10.1017/neu.2013.2","title":"Altered cingulum bundle microstructure in autism spectrum disorder","year":2013,"lang":"en","type":"article","venue":"Acta Neuropsychiatrica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Autism spectrum disorder; Cingulum (brain); Spectrum disorder; Microstructure; Spectrum (functional analysis); Autism; Nuclear magnetic resonance; Medicine; Materials science; Magnetic resonance imaging; Diffusion MRI; Radiology; Physics; Psychiatry; Composite material; Fractional anisotropy","score_opus":0.01670888438164793,"score_gpt":0.28807336737073463,"score_spread":0.2713644829890867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160990082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995204,0.00010989145,0.00013928169,0.000015775091,0.000001697613,0.0000029785374,0.00006785995,0.000008684036,0.00013341552],"genre_scores_gemma":[0.99915636,0.00007481749,0.00055954384,0.000009841081,0.0000029426124,0.000005522779,0.00008184583,0.0000049280893,0.00010410309],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998344,0.000023116196,0.000016282263,0.000058078098,0.00004633676,0.000021621692],"domain_scores_gemma":[0.9995467,0.00004907866,0.00028508966,0.000021327838,0.00004556608,0.000052196152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003323038,0.00038638743,0.00018306034,0.00088305847,0.00030679425,0.00039143045,0.00013325612,0.00028499903,0.0014817845],"category_scores_gemma":[0.0009770204,0.00014196934,0.00014997247,0.0002527777,0.00037060576,0.00030552366,0.00031738137,0.00017478465,0.000116256524],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000952186,0.000091447175,0.8446633,0.00010330442,0.00014621399,0.0014620117,0.0008795265,0.00038593097,0.13375096,0.00016699517,0.00022069486,0.017177373],"study_design_scores_gemma":[0.0000075818507,0.00010587,0.9961468,0.000008840915,0.000015455327,0.0012869942,0.0001114351,0.00018066341,0.0019168616,0.00006456754,0.00015214097,0.0000028458553],"about_ca_topic_score_codex":0.0025088512,"about_ca_topic_score_gemma":0.0038817415,"teacher_disagreement_score":0.0025088512,"about_ca_system_score_codex":0.0002831743,"about_ca_system_score_gemma":0.00024097395,"threshold_uncertainty_score":0.004988551},"labels":[],"label_agreement":null},{"id":"W2161083511","doi":"10.1038/srep05644","title":"A mechanical model predicts morphological abnormalities in the developing human brain","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":212,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Gyrification; Polymicrogyria; Neuroscience; Human brain; Lissencephaly; Epilepsy; Autism; Magnetic resonance imaging; Psychology; Biology; Medicine; Computer science; Cerebral cortex; Developmental psychology","score_opus":0.10402899669616991,"score_gpt":0.36289679983913736,"score_spread":0.2588678031429674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161083511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87758034,0.0005684255,0.11031535,0.0014483575,0.000050950148,0.000052969313,0.00028276598,0.0002709347,0.009429964],"genre_scores_gemma":[0.9935154,0.00032174977,0.0045405026,0.00007976848,0.000015043758,0.000037911006,0.000070217284,0.000033701577,0.0013857367],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999355,0.000015094375,0.0000032534476,0.000018643686,0.000015571235,0.00001197078],"domain_scores_gemma":[0.9997354,0.00009779315,0.000077508295,0.000023193817,0.000032406115,0.000033670425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023198416,0.00050181174,0.0002151196,0.0005527628,0.00018331011,0.00047933427,0.00042758763,0.0010399692,0.00092346605],"category_scores_gemma":[0.0012484471,0.0003207273,0.00035346323,0.00019601473,0.00085673505,0.00046562497,0.00035711887,0.0004267557,0.0002335735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007871706,0.00006760862,0.0075397273,0.000039005547,0.000027358301,0.00061196694,0.00008671222,0.94979537,0.02329276,0.013047304,0.00065344054,0.0047600283],"study_design_scores_gemma":[0.00001286201,0.0000398728,0.006197699,0.000006585971,0.000007100869,0.00023602988,0.000023680492,0.9828135,0.0010034504,0.009369698,0.0002740798,0.000015386266],"about_ca_topic_score_codex":0.0035400032,"about_ca_topic_score_gemma":0.0024680863,"teacher_disagreement_score":0.0035400032,"about_ca_system_score_codex":0.00049822143,"about_ca_system_score_gemma":0.00040041882,"threshold_uncertainty_score":0.0070388317},"labels":[],"label_agreement":null},{"id":"W2161345835","doi":"10.1093/cercor/bht334","title":"Gray- and White-Matter Anatomy of Absolute Pitch Possessors","year":2013,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Baycrest Hospital; Centre for Addiction and Mental Health","funders":"Danmarks Grundforskningsfond; National Research Foundation","keywords":"Gray (unit); White matter; Anatomy; Absolute (philosophy); White (mutation); Biology; Medicine; Magnetic resonance imaging; Philosophy; Nuclear medicine; Radiology","score_opus":0.02514172140313974,"score_gpt":0.3254385219395622,"score_spread":0.30029680053642244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161345835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990728,0.0000862017,0.00037409028,0.000012788591,0.0000013315816,0.0000022166428,0.000043871976,0.000004413259,0.00040229713],"genre_scores_gemma":[0.9991667,0.00006371265,0.00050963834,0.0000070234705,0.0000026293794,0.0000018022461,0.000028082712,0.0000024186784,0.00021806576],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999261,0.000009008503,0.0000065242543,0.000028838896,0.000014398843,0.000015055445],"domain_scores_gemma":[0.9997589,0.00003715778,0.0001198257,0.00003280007,0.000018307108,0.000032979297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001839841,0.0001584057,0.00012442417,0.001011964,0.0002507171,0.00032996738,0.000097876924,0.00015213715,0.0017130679],"category_scores_gemma":[0.00063604873,0.0001253717,0.00008234649,0.00031668076,0.0006518889,0.00039749837,0.00030530468,0.00016843998,0.0001300663],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011746293,0.00013547586,0.36516967,0.00015141483,0.0002002994,0.002850587,0.0052686404,0.00062984007,0.5556553,0.0024396004,0.00023901384,0.066085555],"study_design_scores_gemma":[0.0000043048744,0.000114423136,0.9917337,0.0000054296274,0.000014832264,0.0014225069,0.00046746494,0.00029988197,0.00514481,0.00055152737,0.00023464381,0.0000065492245],"about_ca_topic_score_codex":0.0018557796,"about_ca_topic_score_gemma":0.003263704,"teacher_disagreement_score":0.0018557796,"about_ca_system_score_codex":0.0001241317,"about_ca_system_score_gemma":0.0001195305,"threshold_uncertainty_score":0.005730808},"labels":[],"label_agreement":null},{"id":"W2161569157","doi":"10.1016/j.neuroimage.2012.08.071","title":"Predicting the location of human perirhinal cortex, Brodmann's area 35, from MRI","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Center for Research Resources; National Center for Complementary and Alternative Medicine; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Servier; Eisai; Dana Foundation; Bayer HealthCare; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; Genentech; Biogen Idec; Northern California Institute for Research and Education; Massachusetts General Hospital; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Novartis Pharmaceuticals Corporation; Boston University; BioClinica; Pfizer; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; National Center for Complementary and Integrative Health; National Institute on Aging; Abbott Laboratories; Ellison Medical Foundation; Foundation for the National Institutes of Health","keywords":"Perirhinal cortex; Neuroscience; Cortex (anatomy); Psychology; Temporal lobe","score_opus":0.07028257376445625,"score_gpt":0.34914359511337956,"score_spread":0.2788610213489233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161569157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94026625,0.0022474849,0.05179818,0.0004050847,0.00005909741,0.00006941516,0.0014389913,0.0012537364,0.0024617556],"genre_scores_gemma":[0.9850299,0.00055880134,0.012816738,0.000051347706,0.000023256489,0.00001033328,0.00052471075,0.000047476777,0.00093749806],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999505,0.0000080468,0.0000031803336,0.000017772665,0.000010065985,0.000010410295],"domain_scores_gemma":[0.99981195,0.00007589472,0.000033888497,0.000017970997,0.00004025606,0.0000201228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022776822,0.00043762676,0.00025693807,0.0012615961,0.00017307895,0.0005140817,0.0002567527,0.000641362,0.0011241115],"category_scores_gemma":[0.0014048397,0.00025810458,0.0002704263,0.00027319815,0.00019851365,0.0003258422,0.00014866685,0.00022965467,0.00082781014],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028454785,0.00016557088,0.16806546,0.0005841477,0.00032358582,0.0019040442,0.0003700604,0.02890949,0.50525177,0.0016018177,0.008772199,0.2812064],"study_design_scores_gemma":[0.0002005621,0.0004733862,0.5706734,0.00010724878,0.0006353053,0.0055462467,0.0005793283,0.24085367,0.16770178,0.0076996577,0.005405052,0.00012431956],"about_ca_topic_score_codex":0.011127154,"about_ca_topic_score_gemma":0.018464819,"teacher_disagreement_score":0.011127154,"about_ca_system_score_codex":0.00022836575,"about_ca_system_score_gemma":0.00046384658,"threshold_uncertainty_score":0.022124767},"labels":[],"label_agreement":null},{"id":"W2161773156","doi":"10.1176/appi.neuropsych.11080180","title":"Human Medial Forebrain Bundle (MFB) and Anterior Thalamic Radiation (ATR): Imaging of Two Major Subcortical Pathways and the Dynamic Balance of Opposite Affects in Understanding Depression","year":2012,"lang":"en","type":"article","venue":"Journal of Neuropsychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":344,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medial forebrain bundle; Neuroscience; Diffusion MRI; Forebrain; Psychology; Prefrontal cortex; Anatomy; Medicine; Magnetic resonance imaging; Cognition; Central nervous system; Dopaminergic","score_opus":0.027651643584099807,"score_gpt":0.3289981292353504,"score_spread":0.30134648565125055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161773156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90826774,0.0068432353,0.073921606,0.0015958336,0.00006141304,0.00011031736,0.00023745456,0.0001679358,0.008794459],"genre_scores_gemma":[0.96642935,0.0024078933,0.028136855,0.00024169499,0.00003265179,0.000036190806,0.00007869334,0.000016830143,0.002619795],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99996054,0.000010141322,0.0000030213873,0.000012656926,0.000008394568,0.0000052787277],"domain_scores_gemma":[0.99996555,0.0000090389885,0.000011401065,0.000004874081,0.0000045141546,0.0000045866686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017393162,0.00014982269,0.00008491673,0.00030308377,0.000111906025,0.0003204064,0.00014212957,0.0004410393,0.0012459649],"category_scores_gemma":[0.00029154177,0.00015498474,0.00009036523,0.00013099906,0.00040603703,0.0004347204,0.00020356764,0.0002661346,0.00022299819],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006734379,0.00007360028,0.026083788,0.00035545265,0.00005416133,0.0032270253,0.000626942,0.000953911,0.76667047,0.007818822,0.0012618811,0.19220056],"study_design_scores_gemma":[0.00022758286,0.0026193717,0.5160558,0.00049323996,0.0002582364,0.08385609,0.0013889371,0.026199076,0.29253468,0.043821827,0.032415066,0.00013010736],"about_ca_topic_score_codex":0.001260616,"about_ca_topic_score_gemma":0.002236549,"teacher_disagreement_score":0.001260616,"about_ca_system_score_codex":0.00028566795,"about_ca_system_score_gemma":0.00021078516,"threshold_uncertainty_score":0.0041682124},"labels":[],"label_agreement":null},{"id":"W2162089114","doi":"10.1109/cvprw.2009.5204044","title":"3D stochastic completion fields for fiber tractography","year":2009,"lang":"en","type":"article","venue":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Tractography; Random walk; Stochastic differential equation; Statistical physics; Brownian motion; Computer science; Monte Carlo method; Diffusion; Stochastic process; Voxel; Diffusion MRI; Anomalous diffusion; Algorithm; Mathematical optimization; Applied mathematics; Mathematics; Physics; Artificial intelligence; Statistics","score_opus":0.10372641488124447,"score_gpt":0.35089019035030916,"score_spread":0.2471637754690647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162089114","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023201993,0.00007083196,0.9968449,0.00011761169,0.000012234108,0.000015618409,0.000058969355,0.00017894262,0.0003807836],"genre_scores_gemma":[0.20395148,0.000600772,0.79013735,0.00014262511,0.00012200081,0.00038022047,0.0005340369,0.0003792192,0.0037522265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996216,0.00015419755,0.000018153713,0.000056374272,0.00012599048,0.000023691588],"domain_scores_gemma":[0.9982438,0.0009799517,0.00020876656,0.0002038908,0.00024356962,0.00011999069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015094278,0.0006915442,0.0007331022,0.001037257,0.0005553333,0.00093960407,0.0009911819,0.001367146,0.0026842619],"category_scores_gemma":[0.0046419343,0.0004956023,0.00093865837,0.0009058538,0.0012255424,0.0011718296,0.00133502,0.0015500165,0.0007242402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003246488,0.000022902184,0.0003010239,0.00005405349,0.000019071127,0.00006122389,0.00006137354,0.8072249,0.0023356075,0.16799463,0.001377142,0.020515604],"study_design_scores_gemma":[0.000003748931,0.000004386624,0.00003453106,0.0000039817746,0.0000011614975,0.00001038873,0.000002232155,0.9610999,0.00024628307,0.037809663,0.0007785487,0.0000051005395],"about_ca_topic_score_codex":0.005358381,"about_ca_topic_score_gemma":0.0038720919,"teacher_disagreement_score":0.005358381,"about_ca_system_score_codex":0.0012738906,"about_ca_system_score_gemma":0.0013108461,"threshold_uncertainty_score":0.01065433},"labels":[],"label_agreement":null},{"id":"W2162686834","doi":"10.1093/cercor/bhn102","title":"Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography","year":2008,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; University of Alberta","funders":"National Center for Research Resources","keywords":"Diffusion MRI; Tractography; Neuroscience; Cerebral cortex; Functional connectivity; Cortex (anatomy); Connectome; Connectomics; Human brain; Brain mapping; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.059787037910828435,"score_gpt":0.3299080363253019,"score_spread":0.27012099841447346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162686834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97034496,0.00010575569,0.029051889,0.000040386,0.0000016651467,0.000027635866,0.00014883182,0.00003905706,0.00023979966],"genre_scores_gemma":[0.9884471,0.00011100538,0.01118166,0.000004632353,0.0000028659679,0.000016733991,0.00013146046,0.000007746251,0.000096771866],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998952,0.000036752626,0.000007717705,0.000033084638,0.000016135671,0.0000110582005],"domain_scores_gemma":[0.9996371,0.00015582549,0.00010820534,0.000041299885,0.000034837874,0.000022754257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003024421,0.0002028873,0.00014512493,0.001115078,0.00015445848,0.0003143759,0.000128266,0.00015857935,0.00052619836],"category_scores_gemma":[0.0021316702,0.00014824318,0.00014672003,0.0006387454,0.00036585203,0.00039161093,0.000183496,0.00012787264,0.00006665681],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070964644,0.00018590013,0.25887448,0.00047670017,0.0004991732,0.0011918079,0.0019469213,0.072380364,0.5066491,0.0058080894,0.00090390566,0.150374],"study_design_scores_gemma":[0.000047106747,0.00024621867,0.7793711,0.000025919004,0.00014433345,0.0024442135,0.00034871884,0.17625228,0.03177265,0.007979243,0.0013103328,0.000057885347],"about_ca_topic_score_codex":0.004727427,"about_ca_topic_score_gemma":0.0084812045,"teacher_disagreement_score":0.004727427,"about_ca_system_score_codex":0.00024985184,"about_ca_system_score_gemma":0.00026667485,"threshold_uncertainty_score":0.009399831},"labels":[],"label_agreement":null},{"id":"W2162816954","doi":"10.1002/jmri.21297","title":"White matter microstructural abnormalities in children with spina bifida myelomeningocele and hydrocephalus: A diffusion tensor tractography study of the association pathways","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Hydrocephalus; Spina bifida; Tractography; Medicine; Psychology; Magnetic resonance imaging; Pediatrics; Radiology","score_opus":0.012804420850700734,"score_gpt":0.24395829573139563,"score_spread":0.2311538748806949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162816954","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99978644,0.000056607696,0.00003528117,0.0000071264453,7.622332e-7,0.000004013327,0.000052877316,0.0000015488018,0.000055475175],"genre_scores_gemma":[0.9992698,0.0001281917,0.000377229,0.0000103065895,0.0000034094332,0.000014024087,0.00013140815,0.0000029559756,0.00006260017],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997309,0.00003665062,0.000033174794,0.000074429554,0.000065811946,0.00005909644],"domain_scores_gemma":[0.9992756,0.00011387579,0.0003735061,0.00003135807,0.000074860836,0.00013086952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040978595,0.00056138803,0.00040357848,0.0014703667,0.00047913892,0.00037013015,0.0002367007,0.00041711592,0.00097485847],"category_scores_gemma":[0.0015786686,0.00031508916,0.00025774728,0.0008230018,0.00072479295,0.0005234034,0.00045448416,0.00032065116,0.00017236288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018619727,0.00006420125,0.9868976,0.00004714701,0.000042128384,0.003353741,0.00080463,0.00006358369,0.0053302348,0.000034506054,0.00007850019,0.003097491],"study_design_scores_gemma":[0.0000076406595,0.00013518553,0.99136555,0.000009496059,0.000017169514,0.00751647,0.00042725465,0.000056784058,0.00034385794,0.000014095,0.00010357031,0.0000030210017],"about_ca_topic_score_codex":0.006213991,"about_ca_topic_score_gemma":0.0077150543,"teacher_disagreement_score":0.006213991,"about_ca_system_score_codex":0.00040843795,"about_ca_system_score_gemma":0.0005353038,"threshold_uncertainty_score":0.012355626},"labels":[],"label_agreement":null},{"id":"W2162936913","doi":"10.1093/brain/awq040","title":"Diffusion tensor tractography findings in schizophrenia across the adult lifespan","year":2010,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":146,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of General Medical Sciences; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); White matter; Splenium; Diffusion MRI; Fasciculus; Corpus callosum; Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Tractography; Corticospinal tract; Schizophrenia (object-oriented programming); Arcuate fasciculus; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.02431946233022715,"score_gpt":0.34301939368738643,"score_spread":0.3186999313571593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162936913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986071,0.00044541663,0.0004310778,0.00005132976,0.000001700391,0.0000032532957,0.0002624563,0.000011831915,0.00018578666],"genre_scores_gemma":[0.99844354,0.00031967222,0.0006905928,0.000012503182,0.0000024461126,0.0000066077178,0.00029683535,0.0000053936997,0.00022228165],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990034,0.000018396828,0.000012121562,0.000031529817,0.000019008918,0.00001863059],"domain_scores_gemma":[0.99927944,0.00006518198,0.00038564668,0.00006421642,0.00010075528,0.000104783205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045288904,0.00019879248,0.00015594324,0.00078217435,0.00022413282,0.00023413784,0.00009647741,0.00018077523,0.0008856154],"category_scores_gemma":[0.0015899538,0.00015297066,0.00017312089,0.00043259544,0.00025409993,0.00024626666,0.00023150558,0.00012833769,0.00013747637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006310648,0.000036975376,0.8849563,0.0000833292,0.00024419234,0.0011049705,0.002127063,0.00073569996,0.079588905,0.00060942705,0.0006312334,0.02925066],"study_design_scores_gemma":[0.0000028666875,0.000036883444,0.998295,0.000007914317,0.000013348644,0.00056436076,0.000091637165,0.00020214921,0.0004391073,0.00015038192,0.00019294824,0.0000034515],"about_ca_topic_score_codex":0.012483502,"about_ca_topic_score_gemma":0.01797226,"teacher_disagreement_score":0.012483502,"about_ca_system_score_codex":0.00030800956,"about_ca_system_score_gemma":0.0003393424,"threshold_uncertainty_score":0.024821699},"labels":[],"label_agreement":null},{"id":"W2163195251","doi":"10.1109/iembs.2005.1615707","title":"Application of T1 and T2 Maps for Stereotactic Deep-Brain Neurosurgery Planning","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials","funders":"","keywords":"Neurosurgery; Computer science; Medical physics; Artificial intelligence; Medicine; Radiology","score_opus":0.06052932144412724,"score_gpt":0.36866807953033265,"score_spread":0.3081387580862054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163195251","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07367663,0.0007034179,0.9186528,0.00018259694,0.000056575278,0.00012440611,0.00027460288,0.001629665,0.004699188],"genre_scores_gemma":[0.48284298,0.0004414404,0.5147406,0.00004432151,0.000031582764,0.0001354895,0.00016861297,0.00047420274,0.0011208104],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996264,0.00013483923,0.000022950915,0.000048312682,0.00014544571,0.0000219862],"domain_scores_gemma":[0.9989942,0.000520596,0.0001130235,0.0000968816,0.00023772343,0.00003768458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010012754,0.00051104085,0.00020173512,0.0016157365,0.0003145216,0.00077359274,0.000397941,0.00032772924,0.002161357],"category_scores_gemma":[0.004685408,0.00032748905,0.00027879703,0.00059186487,0.00041847958,0.00078171905,0.0004018132,0.00029423193,0.0005068808],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008304246,0.000046994424,0.007100018,0.00041460732,0.000080745405,0.00052116375,0.0006079788,0.05779064,0.20405817,0.008428256,0.0025306684,0.7175903],"study_design_scores_gemma":[0.00016749249,0.00088775216,0.038837746,0.00009990508,0.00022440091,0.005753488,0.00056639395,0.48731437,0.41337436,0.018603057,0.033788297,0.00038273397],"about_ca_topic_score_codex":0.0027205197,"about_ca_topic_score_gemma":0.0025138715,"teacher_disagreement_score":0.0027205197,"about_ca_system_score_codex":0.00042846097,"about_ca_system_score_gemma":0.00072673504,"threshold_uncertainty_score":0.0072304606},"labels":[],"label_agreement":null},{"id":"W2163304592","doi":"10.3389/fnhum.2014.00589","title":"Functional MRI activation in white matter during the Symbol Digit Modalities Test","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Surrey Memorial Hospital; Fraser Health; Izaak Walton Killam Health Centre; Simon Fraser University; University of Calgary; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Nova Scotia Health Research Foundation","keywords":"Numerical digit; White matter; Modalities; Symbol (formal); Test (biology); Neuroscience; Psychology; Medicine; Arithmetic; Computer science; Magnetic resonance imaging; Biology; Mathematics; Radiology","score_opus":0.03062915196513463,"score_gpt":0.28595587735899664,"score_spread":0.25532672539386203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163304592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856156,0.00010620136,0.0005096445,0.000027764558,0.0000037785894,0.000016962555,0.00007179005,0.000007595889,0.0006946531],"genre_scores_gemma":[0.99896383,0.00005676647,0.00060721056,0.00003123435,0.0000075797043,0.000017394452,0.00006710102,0.000003009006,0.000245928],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998692,0.000038999584,0.0000097059865,0.00003698376,0.000027569105,0.000017572122],"domain_scores_gemma":[0.999366,0.00028374954,0.00018199864,0.000027557255,0.0000740731,0.00006664122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005141348,0.0002971083,0.00016756276,0.00047482984,0.00012336057,0.00026402858,0.00015591989,0.00034533732,0.0017770615],"category_scores_gemma":[0.0019038193,0.000075175405,0.000117818265,0.00016014051,0.00036194094,0.00021399648,0.00018601902,0.00024308446,0.00021127089],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048018093,0.00058326125,0.40169865,0.00040146662,0.00026902166,0.0038349095,0.0016083417,0.0010067606,0.52524245,0.00031015242,0.00060437643,0.05963884],"study_design_scores_gemma":[0.00007575447,0.0020986923,0.9398246,0.000027025982,0.0000876158,0.005410016,0.00021326885,0.0012511229,0.05009644,0.00038570445,0.0005119309,0.000017890225],"about_ca_topic_score_codex":0.0007215222,"about_ca_topic_score_gemma":0.001136471,"teacher_disagreement_score":0.0017770615,"about_ca_system_score_codex":0.00014598544,"about_ca_system_score_gemma":0.00015331748,"threshold_uncertainty_score":0.005944848},"labels":[],"label_agreement":null},{"id":"W2163397436","doi":"10.1016/j.media.2011.02.002","title":"Recent advances in diffusion MRI modeling: Angular and radial reconstruction","year":2011,"lang":"en","type":"review","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Diffusion MRI; Diffusion; Artificial intelligence; Bridge (graph theory); Sampling (signal processing); SIGNAL (programming language); Diffusion imaging; Emphasis (telecommunications); Magnetic resonance imaging; Computer vision; Machine learning; Physics","score_opus":0.07453154444029955,"score_gpt":0.39947682010072955,"score_spread":0.32494527566042997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163397436","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010166761,0.8968693,0.09736331,0.0010744395,0.00039947082,0.000027821625,0.00013917022,0.00031987714,0.0027899314],"genre_scores_gemma":[0.0059895143,0.9314921,0.059469476,0.00027101615,0.00090262934,0.000038602255,0.00024707618,0.00008058247,0.0015089874],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99959344,0.000092783775,0.000058310983,0.00009638036,0.00013994164,0.000019226227],"domain_scores_gemma":[0.9974371,0.0014931755,0.00018120876,0.00013913965,0.0006848478,0.00006438671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020955119,0.0017399373,0.0022060124,0.0025368747,0.00027422345,0.0016397396,0.001977761,0.0014778466,0.0023089985],"category_scores_gemma":[0.004174288,0.00082440395,0.0010193363,0.0037331053,0.0009523773,0.0018809204,0.0009485477,0.0018138853,0.0021834206],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005238348,0.000056937646,0.0004200055,0.0050892984,0.00012865393,0.000081018225,0.000043592998,0.007386491,0.0023698118,0.0069108065,0.010372455,0.9670885],"study_design_scores_gemma":[0.00007005157,0.00024207939,0.002571413,0.0040443493,0.0007962011,0.003817616,0.00015696502,0.0999416,0.01587402,0.048510894,0.8236621,0.0003126347],"about_ca_topic_score_codex":0.0040489063,"about_ca_topic_score_gemma":0.0036167176,"teacher_disagreement_score":0.0040489063,"about_ca_system_score_codex":0.0006308155,"about_ca_system_score_gemma":0.0016962958,"threshold_uncertainty_score":0.011082232},"labels":[],"label_agreement":null},{"id":"W2163622527","doi":"10.1007/978-1-84882-299-3_3","title":"A Variational Approach to the Registration of Tensor-Valued Images","year":2009,"lang":"en","type":"book-chapter","venue":"Advances in pattern recognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Compatibility (geochemistry); Tensor field; Tensor (intrinsic definition); Mathematics; Energy functional; Smoothness; Constraint (computer-aided design); Mathematical analysis; Computer science; Artificial intelligence; Applied mathematics; Geometry; Exact solutions in general relativity; Geology","score_opus":0.0761410596768305,"score_gpt":0.33942633749361084,"score_spread":0.26328527781678035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163622527","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00062313775,0.00082412676,0.9965833,0.00026075056,0.0000687383,0.000010492575,0.000044579683,0.00007059887,0.0015143801],"genre_scores_gemma":[0.04993643,0.0033976806,0.9294379,0.00020698695,0.0003651696,0.00012224233,0.0002852285,0.00047266192,0.01577583],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994147,0.00023870353,0.000041061325,0.000105554376,0.00016866672,0.00003130894],"domain_scores_gemma":[0.99915946,0.00050677947,0.00006372763,0.00008349905,0.00013424337,0.000052292897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017698144,0.0008015702,0.0012587508,0.0009503139,0.00051474385,0.0016876953,0.0023816593,0.0016851809,0.0027419145],"category_scores_gemma":[0.0025461318,0.0010250713,0.0014490733,0.0014517199,0.0021376985,0.0019919067,0.0022119253,0.0031468289,0.0008399124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025281955,0.000026910246,0.00016956168,0.00022336062,0.00009294272,0.00006981358,0.00017857776,0.14951292,0.006119579,0.7346382,0.007991844,0.10095106],"study_design_scores_gemma":[0.000008537805,0.00002737243,0.00017972376,0.00003388523,0.000020964428,0.00011306134,0.00002241177,0.6010046,0.0009602165,0.38173878,0.015855946,0.00003449633],"about_ca_topic_score_codex":0.006714092,"about_ca_topic_score_gemma":0.00892328,"teacher_disagreement_score":0.006714092,"about_ca_system_score_codex":0.0010171671,"about_ca_system_score_gemma":0.001356524,"threshold_uncertainty_score":0.0133500695},"labels":[],"label_agreement":null},{"id":"W2164021478","doi":"10.1186/1471-244x-13-264","title":"Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use","year":2013,"lang":"en","type":"article","venue":"BMC Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Western University; Dalhousie University","funders":"","keywords":"White matter; Diffusion MRI; Neuroimaging; Neuroscience; Schizophrenia (object-oriented programming); Psychology; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.026435281785758914,"score_gpt":0.33064953069887687,"score_spread":0.30421424891311794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164021478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993223,0.00016652374,0.00011350606,0.000048706785,0.0000010537434,0.000011283662,0.00008185169,0.0000017652773,0.000253044],"genre_scores_gemma":[0.99920756,0.00026666097,0.00030579476,0.00001437234,0.0000031137906,0.000010598995,0.00006499493,0.0000015465342,0.000125393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999496,0.000011031625,0.0000036036217,0.000010297031,0.000009742174,0.000015718777],"domain_scores_gemma":[0.99984074,0.00002684526,0.00006616904,0.0000075104986,0.000021898828,0.000036807975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024846167,0.00019510201,0.00012266627,0.00053521775,0.00024610918,0.00030344143,0.0000955535,0.00020736305,0.0012950327],"category_scores_gemma":[0.00053623423,0.00011465708,0.0001183616,0.00020342639,0.00023933407,0.00024077256,0.0002646922,0.00021184214,0.00007443212],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014564388,0.00030834143,0.89632857,0.00016464476,0.00011910907,0.0025490613,0.0010997158,0.000524533,0.07372723,0.00025409355,0.00022365757,0.023244634],"study_design_scores_gemma":[0.0000053329486,0.00011078897,0.9971252,0.000014165672,0.0000226802,0.00076330383,0.00030914732,0.00021007056,0.0012560993,0.00006901641,0.000111168505,0.0000030565054],"about_ca_topic_score_codex":0.007436741,"about_ca_topic_score_gemma":0.015629081,"teacher_disagreement_score":0.007436741,"about_ca_system_score_codex":0.00045174043,"about_ca_system_score_gemma":0.0004977503,"threshold_uncertainty_score":0.014786959},"labels":[],"label_agreement":null},{"id":"W2165564750","doi":"10.1016/j.clineuro.2006.06.005","title":"Magnetoencephalography and diffusion tensor imaging in gelastic seizures secondary to a cingulate gyrus lesion","year":2006,"lang":"en","type":"article","venue":"Clinical Neurology and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Ictal; Diffusion MRI; Lesion; Magnetoencephalography; Temporal lobe; Gelastic seizure; Gyrus; Neuroscience; Electroencephalography; Epilepsy; Magnetic resonance imaging; Radiology; Pathology; Psychology; Hypothalamic hamartoma; Internal medicine","score_opus":0.047973460715509876,"score_gpt":0.3575992250779697,"score_spread":0.3096257643624598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165564750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97938204,0.0014060742,0.00084677764,0.003035943,0.00018259627,0.00012371576,0.0003827831,0.000094042625,0.014546104],"genre_scores_gemma":[0.99800164,0.0002734627,0.0002210258,0.00044268437,0.00016744138,0.000012682793,0.00011659231,0.000012157925,0.0007524063],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.999767,0.000040853316,0.000050297327,0.000028591616,0.000027655868,0.00008559096],"domain_scores_gemma":[0.9991793,0.0003147478,0.00016793722,0.00006822275,0.000062545216,0.00020724232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000300244,0.0012088801,0.0005799239,0.0015505545,0.00078874035,0.0004729529,0.0009351675,0.0021715446,0.0032554253],"category_scores_gemma":[0.002897817,0.00051816663,0.00051708415,0.00081391435,0.0018341751,0.0014086484,0.00059996714,0.0020812438,0.00094617106],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011516751,0.00011580635,0.018937238,0.000073175645,0.000038740436,0.972344,0.00026092038,0.00026324083,0.0035265198,0.0003158513,0.00063610944,0.0023366986],"study_design_scores_gemma":[0.00033366622,0.00073723326,0.114647314,0.000033644534,0.00011022291,0.8738406,0.0007057886,0.0016238138,0.005402775,0.0012333519,0.0012601651,0.00007141375],"about_ca_topic_score_codex":0.013061008,"about_ca_topic_score_gemma":0.011456315,"teacher_disagreement_score":0.013061008,"about_ca_system_score_codex":0.0011121872,"about_ca_system_score_gemma":0.0009439317,"threshold_uncertainty_score":0.025969982},"labels":[],"label_agreement":null},{"id":"W2165848433","doi":"10.1186/1471-2202-13-107","title":"Both projection and commissural pathways are disrupted in individuals with chronic stroke: investigating microstructural white matter correlates of motor recovery","year":2012,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; Michael Smith Health Research BC; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Internal capsule; Fractional anisotropy; Corpus callosum; White matter; Stroke (engine); Diffusion MRI; Chronic stroke; Psychology; Sensory system; Physical medicine and rehabilitation; Corticospinal tract; Motor function; Medicine; Neuroscience; Magnetic resonance imaging; Rehabilitation","score_opus":0.052673132173399695,"score_gpt":0.3054686125792752,"score_spread":0.2527954804058755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165848433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998684,0.000028909046,0.000020722404,0.0000048191023,2.830796e-7,0.0000024651952,0.000020350259,7.533529e-7,0.000053334945],"genre_scores_gemma":[0.9997415,0.000032427237,0.000075112184,0.000005451527,0.0000016516683,0.0000049661908,0.00006235813,6.861429e-7,0.00007596648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999206,0.000009628027,0.000009112487,0.000023838213,0.000012107331,0.00002467675],"domain_scores_gemma":[0.9997676,0.00002799822,0.00010804333,0.000015596439,0.000039614166,0.000041126037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018946939,0.0002428827,0.00017085811,0.00066961977,0.00043390153,0.00023246664,0.00012722076,0.00029667097,0.0011969785],"category_scores_gemma":[0.0007022096,0.0001273533,0.00009645643,0.00036764648,0.00031741647,0.00021106833,0.0002490831,0.00016140753,0.00012182326],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048042275,0.00011628265,0.98053646,0.00003492081,0.00007971255,0.0004079249,0.0006127554,0.00006579368,0.011145641,0.000027010483,0.000086100925,0.0064070052],"study_design_scores_gemma":[0.0000035474934,0.00011602695,0.9991159,0.0000023720113,0.00001064004,0.00032033748,0.00011492581,0.00003476486,0.00023256891,0.000013039284,0.000034729834,0.0000010209621],"about_ca_topic_score_codex":0.0059518167,"about_ca_topic_score_gemma":0.012263365,"teacher_disagreement_score":0.0059518167,"about_ca_system_score_codex":0.00022933871,"about_ca_system_score_gemma":0.000203859,"threshold_uncertainty_score":0.011834383},"labels":[],"label_agreement":null},{"id":"W2166106056","doi":"10.1016/j.eplepsyres.2014.03.006","title":"Tractography of Meyer's Loop asymmetries","year":2014,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Alberta Innovates; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Uncinate fasciculus; Diffusion MRI; Temporal lobe; Anatomy; Nuclear medicine; Fasciculus; Epilepsy; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Radiology; Fractional anisotropy","score_opus":0.2188368223898774,"score_gpt":0.47567185241368376,"score_spread":0.25683503002380637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166106056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94047034,0.0008363076,0.04887402,0.00026365524,0.00002752937,0.000047437785,0.00091421325,0.00037863973,0.0081876945],"genre_scores_gemma":[0.99408746,0.0001508193,0.0047790282,0.000009625577,0.000011610065,0.000009757904,0.00007982659,0.00004571508,0.00082616776],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9999187,0.00002267928,0.000006651558,0.00002065697,0.000014473134,0.00001686225],"domain_scores_gemma":[0.99948835,0.00028722422,0.000080343605,0.00004841605,0.000056175006,0.000039511204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033816847,0.0002742376,0.00012656965,0.001129925,0.00026952566,0.00059750216,0.00014876087,0.00032908178,0.0034231348],"category_scores_gemma":[0.0028448596,0.00011554688,0.0001673153,0.00066496327,0.00023283398,0.00081092614,0.00020620176,0.00026902428,0.00028049405],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024986214,0.0001232421,0.10567693,0.00037362086,0.0002872891,0.0054547405,0.0018112021,0.02705215,0.34634298,0.051500697,0.0036708012,0.45520774],"study_design_scores_gemma":[0.00018795092,0.00072342367,0.51995564,0.00020559512,0.0003981286,0.031482942,0.0009499182,0.19916233,0.16341756,0.06760052,0.015733372,0.00018267106],"about_ca_topic_score_codex":0.0034797746,"about_ca_topic_score_gemma":0.0031372327,"teacher_disagreement_score":0.0034797746,"about_ca_system_score_codex":0.00026676335,"about_ca_system_score_gemma":0.00044149105,"threshold_uncertainty_score":0.011451483},"labels":[],"label_agreement":null},{"id":"W2166238599","doi":"10.71781/27554","title":"Étude de la substance blanche par diffusion tensiorelle : tractographie des fibres d'association de la région temporo-pariéto-occipitale","year":2007,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.03907964895021424,"score_gpt":0.38250335156357795,"score_spread":0.3434237026133637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166238599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9205124,0.0119212065,0.05682998,0.0011820305,0.000079355385,0.00032946139,0.0016399869,0.00032031286,0.0071852123],"genre_scores_gemma":[0.96165234,0.0039803954,0.02585214,0.00009628185,0.00006712562,0.00022304602,0.00030154767,0.00009197561,0.0077351257],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998185,0.000027232036,0.00000950938,0.000058635313,0.000043465327,0.000042667943],"domain_scores_gemma":[0.99954885,0.00020192344,0.000083588726,0.000039302573,0.0000844732,0.000041768042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012433021,0.0006858141,0.0004188879,0.001896445,0.0008025289,0.0016655744,0.0006594053,0.0011717489,0.003813829],"category_scores_gemma":[0.002265377,0.0004907362,0.0004102992,0.0014753304,0.0014881515,0.0016304586,0.0005876653,0.0008875689,0.000559456],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020543006,0.000103618666,0.06430001,0.0014846419,0.0005302157,0.007517509,0.0074784877,0.0035067399,0.74052227,0.008654502,0.0015960308,0.16225167],"study_design_scores_gemma":[0.0003053419,0.00060073374,0.746725,0.00049979996,0.00055657636,0.019795058,0.0026165405,0.016849456,0.1759128,0.00851938,0.027451271,0.0001680365],"about_ca_topic_score_codex":0.0775364,"about_ca_topic_score_gemma":0.079456046,"teacher_disagreement_score":0.0775364,"about_ca_system_score_codex":0.0012142869,"about_ca_system_score_gemma":0.001570917,"threshold_uncertainty_score":0.15417016},"labels":[],"label_agreement":null},{"id":"W2166318116","doi":"10.3233/jad-140519","title":"Tract Based Spatial Statistic Reveals No Differences in White Matter Microstructural Organization between Carriers and Non-Carriers of the APOE ɛ4 and ɛ2 Alleles in Young Healthy Adolescents","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; SickKids Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Hospital for Sick Children; Université de Montréal","funders":"IXICO; King's College London; National Institute for Health and Care Research; South London and Maudsley NHS Foundation Trust","keywords":"Apolipoprotein E; Allele; White matter; Diffusion MRI; Psychology; Neuroimaging; Genetics; Biology; Medicine; Internal medicine; Magnetic resonance imaging; Neuroscience; Disease; Gene","score_opus":0.03557124961063087,"score_gpt":0.3120112037721963,"score_spread":0.27643995416156547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166318116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961424,0.00003060057,0.00020531807,0.000003546059,4.849243e-7,0.0000013763108,0.00007713185,0.0000043474165,0.00006290901],"genre_scores_gemma":[0.9994518,0.000024520261,0.00023699233,0.000002732712,0.0000010478418,0.0000028965328,0.00018173085,0.0000058734026,0.0000924399],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998975,0.0000202701,0.000013805182,0.000034738776,0.000017882398,0.000015823902],"domain_scores_gemma":[0.9995078,0.00014752506,0.00015833287,0.00006806553,0.000057458117,0.000060840273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025745403,0.00013992758,0.00020947545,0.0003900727,0.000109381996,0.00023173259,0.00010211478,0.00014154112,0.0010916512],"category_scores_gemma":[0.0010877833,0.00010984682,0.00018473259,0.0002344155,0.00021048391,0.00014484013,0.00016135107,0.00010199934,0.00014235718],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007821922,0.000057638703,0.93969715,0.000035513833,0.00017684179,0.0004483967,0.0004890495,0.00029625994,0.047040045,0.00018777716,0.00017624191,0.010612876],"study_design_scores_gemma":[0.0000043661726,0.00007393743,0.9979619,0.0000022664178,0.000027464317,0.00043090034,0.00009806615,0.000338446,0.00091638614,0.000041994103,0.00010227945,0.0000020446812],"about_ca_topic_score_codex":0.0032605224,"about_ca_topic_score_gemma":0.0034316613,"teacher_disagreement_score":0.0032605224,"about_ca_system_score_codex":0.00009402325,"about_ca_system_score_gemma":0.00016946069,"threshold_uncertainty_score":0.006483078},"labels":[],"label_agreement":null},{"id":"W2166628049","doi":"10.1016/j.neuroimage.2008.01.028","title":"Labeling of ambiguous subvoxel fibre bundle configurations in high angular resolution diffusion MRI","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Fiber bundle; Tractography; Bundle; Diffusion MRI; Orientation (vector space); Computer science; Artificial intelligence; Inference; Tracking (education); Computer vision; Mathematics; Algorithm; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.05627328459219187,"score_gpt":0.315476799707365,"score_spread":0.2592035151151731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166628049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64860386,0.0012303237,0.34356946,0.00050663756,0.00005890743,0.00011201055,0.00025524208,0.00055028626,0.0051132655],"genre_scores_gemma":[0.7889407,0.0006449864,0.208214,0.00010105371,0.00006281506,0.00007007787,0.00016752249,0.00022991022,0.0015689268],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99955434,0.00012622397,0.00005133158,0.00008636506,0.00010266193,0.0000789558],"domain_scores_gemma":[0.9983032,0.0005134574,0.00036455062,0.00033509303,0.00030936414,0.00017433258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018371493,0.0006297235,0.0003718134,0.0025072144,0.0010341022,0.0026125158,0.0006534997,0.0016637612,0.0028144403],"category_scores_gemma":[0.0059044096,0.0006456274,0.00020311182,0.0011166411,0.0010688661,0.0024787146,0.0010206739,0.0009865622,0.00076018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028895244,0.00016210625,0.0289858,0.00095050025,0.00015314035,0.005158759,0.002245064,0.017659368,0.6536171,0.039701402,0.0020144046,0.24646291],"study_design_scores_gemma":[0.00030857284,0.00069372763,0.06178016,0.00080316025,0.00039653006,0.035089053,0.0020722924,0.20890188,0.54117817,0.13293272,0.015561693,0.00028206475],"about_ca_topic_score_codex":0.0009251028,"about_ca_topic_score_gemma":0.0020386502,"teacher_disagreement_score":0.0028144403,"about_ca_system_score_codex":0.00028949243,"about_ca_system_score_gemma":0.0006219225,"threshold_uncertainty_score":0.009715915},"labels":[],"label_agreement":null},{"id":"W2167776784","doi":"10.1016/j.jneumeth.2011.07.026","title":"A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Scanning electron microscope; Electron microscope; Microscope; Materials science; Computer science; Artificial intelligence; Biomedical engineering; Optics; Physics; Medicine; Composite material","score_opus":0.2303427529505041,"score_gpt":0.5002429240959286,"score_spread":0.26990017114542453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167776784","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013499155,0.00023404406,0.97986686,0.0000532916,0.000041731277,0.00038089821,0.0003840935,0.00480278,0.000737162],"genre_scores_gemma":[0.017953694,0.000118405704,0.9800726,0.000021888818,0.000012191633,0.00025355045,0.00030931967,0.00026867853,0.0009896087],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99756444,0.00030137884,0.00027467927,0.00042346108,0.0012989757,0.0001371333],"domain_scores_gemma":[0.9928934,0.0021723597,0.00076622725,0.0009671528,0.003006881,0.00019388508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027695666,0.0014573281,0.0013365034,0.0069865687,0.0011767357,0.0026133785,0.0025177798,0.0013662921,0.0055781077],"category_scores_gemma":[0.0048726955,0.0012593163,0.000880673,0.0028556364,0.00085521874,0.0016446797,0.0018863227,0.001274546,0.002611813],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041729078,0.00021339302,0.0044071097,0.001095989,0.00024452523,0.0002713067,0.0004116125,0.00385714,0.34785855,0.003166171,0.004952118,0.6331048],"study_design_scores_gemma":[0.00015048668,0.0005357691,0.048951156,0.000273517,0.00041617246,0.006953269,0.000532415,0.41725785,0.4887573,0.005721971,0.029887883,0.0005622086],"about_ca_topic_score_codex":0.0037353225,"about_ca_topic_score_gemma":0.010536168,"teacher_disagreement_score":0.0069865687,"about_ca_system_score_codex":0.000834611,"about_ca_system_score_gemma":0.00229158,"threshold_uncertainty_score":0.018660605},"labels":[],"label_agreement":null},{"id":"W2167908150","doi":"10.1016/j.media.2012.07.002","title":"Symmetric positive semi-definite Cartesian Tensor fiber orientation distributions (CT-FOD)","year":2012,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute on Aging; National Center for Research Resources; McGill University; Johns Hopkins University","keywords":"Tensor (intrinsic definition); Diffusion MRI; Cartesian coordinate system; Mathematics; Tensor field; Cartesian tensor; Mathematical analysis; Orientation (vector space); Convolution (computer science); Artificial intelligence; Geometry; Computer science; Tensor density; Magnetic resonance imaging; Exact solutions in general relativity; Artificial neural network","score_opus":0.029280580250433053,"score_gpt":0.35686157417974923,"score_spread":0.32758099392931617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167908150","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011414636,0.00028992858,0.98355526,0.0002530114,0.000078075565,0.00006432717,0.0007894021,0.0005676526,0.0029876414],"genre_scores_gemma":[0.21869014,0.0011446356,0.7701923,0.00027400634,0.00013318176,0.00019249013,0.001518012,0.00049322133,0.0073619364],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971026,0.000074437245,0.000025000047,0.000061642124,0.000104553714,0.000024104962],"domain_scores_gemma":[0.9985361,0.00028782705,0.00034363833,0.00024762368,0.00047082713,0.0001140155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010441621,0.0008369532,0.0003078675,0.0011109128,0.0003445479,0.0014956725,0.0007359091,0.00094916555,0.0048383446],"category_scores_gemma":[0.0038930194,0.00025471215,0.00036641592,0.0009344933,0.0008515862,0.0014810496,0.000584673,0.00082270656,0.0018036962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005398088,0.00019719718,0.006658602,0.0010862796,0.00010104071,0.0011689354,0.00042701195,0.08748921,0.080192655,0.21183331,0.031339172,0.57896674],"study_design_scores_gemma":[0.00004188348,0.00016739113,0.006797374,0.00015898456,0.00005537759,0.0045276345,0.00027174357,0.7805145,0.03303435,0.123347215,0.05094163,0.0001419456],"about_ca_topic_score_codex":0.0015816912,"about_ca_topic_score_gemma":0.0017455575,"teacher_disagreement_score":0.0048383446,"about_ca_system_score_codex":0.0002907723,"about_ca_system_score_gemma":0.0010617322,"threshold_uncertainty_score":0.01618588},"labels":[],"label_agreement":null},{"id":"W2168301017","doi":"10.1017/s1461145712000314","title":"Striatal glutamate and the conversion to psychosis: a prospective 1H-MRS imaging study","year":2012,"lang":"en","type":"article","venue":"The International Journal of Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Instituto Carlos Slim de la Salud; Consejo Nacional de Ciencia y Tecnología; University of California Institute for Mexico and the United States; Sistema Nacional de Investigadores; Eli Lilly and Company","keywords":"Psychosis; Striatum; Glutamate receptor; Psychology; Abnormality; Internal medicine; Proton magnetic resonance; Psychiatry; Medicine; Audiology; Neuroscience; Nuclear magnetic resonance; Dopamine","score_opus":0.03647671716841642,"score_gpt":0.40207527755291245,"score_spread":0.365598560384496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168301017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99966955,0.00009216186,0.000039864986,0.000010678913,0.0000015767297,0.000012158446,0.000041658073,0.000002045207,0.00013032068],"genre_scores_gemma":[0.99970007,0.00005018606,0.000056484012,0.000014044906,0.0000030770905,0.000004547493,0.00007571093,0.0000010854577,0.00009491733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982446,0.000048416903,0.000015295996,0.00004420332,0.000032885917,0.000034802026],"domain_scores_gemma":[0.9996062,0.000062259496,0.00011993774,0.000050743245,0.000033683737,0.00012710024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004243677,0.0005437052,0.00042017148,0.0006426013,0.0008917451,0.0006603134,0.00031450661,0.00070645945,0.0011707894],"category_scores_gemma":[0.00095830776,0.00069797924,0.00036963687,0.0004755469,0.0006174922,0.0003572151,0.0005704633,0.0008451939,0.00030001882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028315927,0.0011026696,0.9817769,0.000031631007,0.00018455036,0.0032451635,0.0006529277,0.00013641648,0.0064337845,0.0000654863,0.000077726945,0.0034611674],"study_design_scores_gemma":[0.000045526096,0.001466179,0.9952933,0.000003859973,0.000050829265,0.002335736,0.00020317246,0.00015498673,0.0002921802,0.000048933147,0.0000957564,0.000009459102],"about_ca_topic_score_codex":0.0035033536,"about_ca_topic_score_gemma":0.004099939,"teacher_disagreement_score":0.0035033536,"about_ca_system_score_codex":0.00028435688,"about_ca_system_score_gemma":0.00021935713,"threshold_uncertainty_score":0.006965935},"labels":[],"label_agreement":null},{"id":"W2168389179","doi":"10.1016/j.media.2009.10.003","title":"A filtered approach to neural tractography using the Watson directional function","year":2009,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Mental Health; Fogarty International Center; National Institutes of Health","keywords":"Tractography; Computer science; Diffusion MRI; Noise (video); Fiber; Artificial intelligence; Kalman filter; SIGNAL (programming language); Noise reduction; Algorithm; Mathematics; Computer vision","score_opus":0.072124928754897,"score_gpt":0.37745874984233835,"score_spread":0.30533382108744134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168389179","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020001626,0.00011030572,0.9972481,0.0000412963,0.000025169546,0.0000094644665,0.000036975496,0.00011525529,0.0004132224],"genre_scores_gemma":[0.044432476,0.00076629024,0.94823015,0.000064612745,0.000112692,0.00009249719,0.00027208016,0.00034450207,0.0056846263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996774,0.00009845072,0.000023174145,0.00007342238,0.0001003296,0.000027208986],"domain_scores_gemma":[0.9993175,0.00026711333,0.00005113787,0.00010510647,0.0002104381,0.000048802147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011466356,0.0008856319,0.0008107191,0.0019987149,0.0007103281,0.0020117625,0.0011166247,0.0014249682,0.003316944],"category_scores_gemma":[0.0027842103,0.0006332389,0.0014412949,0.0014063301,0.0007289196,0.0021946523,0.000988945,0.0015096716,0.0016935848],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023916895,0.000115374954,0.0011761603,0.00027459874,0.00027165076,0.00037596395,0.00023970808,0.14477989,0.052566443,0.51227814,0.005548603,0.28213423],"study_design_scores_gemma":[0.000022839702,0.000088731926,0.0007653093,0.000037494472,0.000058083486,0.00039720425,0.00004841038,0.8323045,0.0072175236,0.14476037,0.014232077,0.000067332025],"about_ca_topic_score_codex":0.004476061,"about_ca_topic_score_gemma":0.0052947653,"teacher_disagreement_score":0.004476061,"about_ca_system_score_codex":0.0005239442,"about_ca_system_score_gemma":0.0013479866,"threshold_uncertainty_score":0.011096239},"labels":[],"label_agreement":null},{"id":"W2168728070","doi":"10.1017/s0317167100009756","title":"Damage of White Matter in the Parietal Lobe Results in Anomic Alexia of Kana","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kana; Parietal lobe; Psychology; White matter; Action (physics); White (mutation); Neuroscience; Medicine; Computer science; Physics; Biology; Artificial intelligence; Kanji","score_opus":0.05302311584205827,"score_gpt":0.3208565431386705,"score_spread":0.26783342729661225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168728070","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993404,0.00027151508,0.0010856657,0.0003161303,0.000059515132,0.000047150534,0.00027597838,0.0002508911,0.004289162],"genre_scores_gemma":[0.9979075,0.00021872073,0.0005232217,0.000110791225,0.000028827404,0.000022798962,0.00013146523,0.000028950943,0.0010278444],"study_design_codex":"bench_or_experimental","study_design_gemma":"case_report","domain_scores_codex":[0.99973184,0.00003742867,0.000034961697,0.00007990922,0.00006606883,0.00004992243],"domain_scores_gemma":[0.99958163,0.00008678106,0.00014764728,0.00006424062,0.000035900885,0.00008382417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002730513,0.0014203049,0.00057339994,0.0021119246,0.00059398037,0.0003940871,0.00038544083,0.0006356787,0.006429823],"category_scores_gemma":[0.0008836906,0.00050413236,0.00034897734,0.0005696768,0.0015871171,0.0005013881,0.00060618145,0.0010461012,0.0008912431],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0070079057,0.001922198,0.038823154,0.0005226723,0.0008153288,0.219525,0.00069140876,0.0011004499,0.6718377,0.0024513926,0.0038866072,0.05141619],"study_design_scores_gemma":[0.00077852106,0.004630565,0.49601647,0.00009219356,0.0007027026,0.40392652,0.0005187829,0.0021139048,0.084201165,0.0031452917,0.0037819531,0.00009188625],"about_ca_topic_score_codex":0.0013897921,"about_ca_topic_score_gemma":0.0016160535,"teacher_disagreement_score":0.006429823,"about_ca_system_score_codex":0.0003017897,"about_ca_system_score_gemma":0.00040579675,"threshold_uncertainty_score":0.021509886},"labels":[],"label_agreement":null},{"id":"W2169459006","doi":"10.1177/1352458506070928","title":"Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology","year":2006,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":492,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Myelin; Luxol fast blue stain; Multiple sclerosis; Pathology; Relaxometry; Magnetic resonance imaging; Histopathology; Remyelination; Nuclear magnetic resonance; Chemistry; Medicine; Nuclear medicine; Central nervous system; Radiology; Physics; Internal medicine; Immunology; Spin echo","score_opus":0.1417452837391413,"score_gpt":0.3052127361807104,"score_spread":0.16346745244156907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169459006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97918737,0.007429019,0.011996978,0.000086679225,0.000014866393,0.000024529525,0.00017470903,0.00012526599,0.0009605502],"genre_scores_gemma":[0.9948738,0.0008421875,0.003889045,0.000021534783,0.000019152738,0.000013596228,0.00009349475,0.000013518575,0.00023374014],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993844,0.00020206472,0.00004815711,0.00011008501,0.0002236661,0.000031650256],"domain_scores_gemma":[0.9973367,0.00087710057,0.0010086973,0.00024172712,0.00042141072,0.000114413255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019650066,0.00037056726,0.00027098897,0.0014477003,0.00013466454,0.0003965283,0.00023547548,0.00042007654,0.0006489172],"category_scores_gemma":[0.004800991,0.0002884733,0.00011006616,0.00067247136,0.00058842084,0.0008001358,0.0003862587,0.0003312695,0.00028416308],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001572667,0.00014032275,0.5269713,0.0003900716,0.00037887215,0.0004405582,0.0002912123,0.00284514,0.40873876,0.000393056,0.00038249863,0.057455566],"study_design_scores_gemma":[0.000025351243,0.0010312103,0.90595686,0.000038346796,0.00014080551,0.0044227634,0.00017060689,0.0056771045,0.07998802,0.0013435854,0.0011616313,0.00004360309],"about_ca_topic_score_codex":0.0003574755,"about_ca_topic_score_gemma":0.0003717285,"teacher_disagreement_score":0.0019650066,"about_ca_system_score_codex":0.00016126462,"about_ca_system_score_gemma":0.00013175634,"threshold_uncertainty_score":0.01039207},"labels":[],"label_agreement":null},{"id":"W2169504979","doi":"10.1007/978-3-642-15705-9_80","title":"Biomarkers for Identifying First-Episode Schizophrenia Patients Using Diffusion Weighted Imaging","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Diffusion MRI; Classifier (UML); Support vector machine; Affine transformation; Feature selection; Population; Kernel (algebra); Magnetic resonance imaging; Mathematics; Medicine","score_opus":0.03512895276646575,"score_gpt":0.3378100518769688,"score_spread":0.302681099110503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169504979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98804736,0.0058184257,0.0020076316,0.00065320346,0.00017849503,0.00013976259,0.0017159848,0.00008776701,0.0013514602],"genre_scores_gemma":[0.9909033,0.0018749519,0.0047263536,0.00015999757,0.000110679306,0.0000959541,0.0013779735,0.00000968495,0.00074108737],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996562,0.0000710965,0.00007783525,0.000055656852,0.00008002116,0.000059289203],"domain_scores_gemma":[0.9978064,0.0006507823,0.00084214914,0.000069737725,0.00032086848,0.00031007276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008104275,0.001470175,0.0014948444,0.0026396334,0.0006522882,0.0016478044,0.0005341379,0.0014133562,0.001858074],"category_scores_gemma":[0.0038936888,0.000398526,0.00092180906,0.0010886327,0.0002694694,0.0010691895,0.0004449136,0.0010184422,0.0004584442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016467646,0.00038132697,0.95668465,0.0001537581,0.00032941383,0.00043767784,0.00010647435,0.0005262216,0.012986753,0.00021695302,0.0009780037,0.025551908],"study_design_scores_gemma":[0.00034929896,0.0026612612,0.961465,0.00034655075,0.0013136453,0.002645176,0.0009414771,0.009218543,0.016086986,0.0020860727,0.0027780011,0.00010795235],"about_ca_topic_score_codex":0.0020467143,"about_ca_topic_score_gemma":0.0032984712,"teacher_disagreement_score":0.0026396334,"about_ca_system_score_codex":0.0005651515,"about_ca_system_score_gemma":0.0010581268,"threshold_uncertainty_score":0.00621593},"labels":[],"label_agreement":null},{"id":"W2170383010","doi":"10.1007/s00256-008-0577-6","title":"Diffusion tensor imaging and fiber tractography of the median nerve at 1.5T: optimization of b value","year":2008,"lang":"en","type":"article","venue":"Skeletal Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University Health Network; Mount Sinai Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Medicine; Fractional anisotropy; Effective diffusion coefficient; Nuclear medicine; Nerve fiber; Image quality; Median nerve; Tractography; Nuclear magnetic resonance; Magnetic resonance imaging; Radiology; Image (mathematics); Anatomy; Physics","score_opus":0.02166906536808541,"score_gpt":0.2826039610703224,"score_spread":0.26093489570223694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170383010","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24348047,0.0021317517,0.7478795,0.0013571753,0.000059593847,0.00015523651,0.0007716869,0.0009156413,0.0032489188],"genre_scores_gemma":[0.35162413,0.0011742513,0.64315426,0.00009429784,0.00004446726,0.0001399297,0.0003086065,0.00067122397,0.0027888785],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979943,0.000081046084,0.000017199945,0.000040461007,0.00004194379,0.00001993705],"domain_scores_gemma":[0.9994105,0.00027659652,0.00010342116,0.000049923718,0.00011423076,0.000045253677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013136626,0.00079385843,0.00061121304,0.000890909,0.00047603785,0.0014636201,0.00047941355,0.00089737395,0.0017504425],"category_scores_gemma":[0.004734331,0.0005989927,0.00044509512,0.000745642,0.00036337785,0.0011412036,0.0005865098,0.0009116586,0.00048681564],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001532848,0.00030215216,0.015949998,0.0007661546,0.00035175704,0.00066217576,0.0005498516,0.16655067,0.18594658,0.015628474,0.006718506,0.60504085],"study_design_scores_gemma":[0.00018405476,0.00045778407,0.028457133,0.0001657584,0.00034857015,0.002634436,0.00026351633,0.8329741,0.10181832,0.021422,0.011055257,0.00021902534],"about_ca_topic_score_codex":0.007744279,"about_ca_topic_score_gemma":0.012628861,"teacher_disagreement_score":0.007744279,"about_ca_system_score_codex":0.00053087756,"about_ca_system_score_gemma":0.0018074577,"threshold_uncertainty_score":0.015398383},"labels":[],"label_agreement":null},{"id":"W2170628400","doi":"10.1109/iembs.2007.4353343","title":"Analysis of Cardiac Diffusion Tensor Magnetic Resonance Images Using Sparse Representation","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Diffusion MRI; Heaviside step function; Sparse approximation; Representation (politics); Tensor (intrinsic definition); Artificial intelligence; Noise reduction; Noise (video); Magnetic resonance imaging; Pattern recognition (psychology); Structure tensor; Computer science; Diffusion; Signal-to-noise ratio (imaging); Basis (linear algebra); Algorithm; Mathematics; Image (mathematics); Physics; Mathematical analysis; Geometry; Radiology","score_opus":0.09405092578367139,"score_gpt":0.3739980428284507,"score_spread":0.27994711704477937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170628400","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028455978,0.00024237964,0.97048587,0.00012952766,0.000014508257,0.000022708273,0.0000558416,0.00023307932,0.0003600929],"genre_scores_gemma":[0.27451828,0.0010052967,0.7224978,0.000060377013,0.00005765167,0.000052098047,0.00037527306,0.00011362799,0.001319612],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998826,0.000023122337,0.0000071347813,0.000020143365,0.00005638678,0.000010565169],"domain_scores_gemma":[0.99968624,0.00013251117,0.000050773884,0.000029250428,0.00008849652,0.000012728213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039781563,0.00044364098,0.00042969768,0.0007582783,0.00016345753,0.00047048705,0.00027356175,0.00046329905,0.00065852137],"category_scores_gemma":[0.0013025835,0.00019223776,0.00047356213,0.00053566,0.00023604148,0.0005797001,0.00034254233,0.0004325884,0.0002807482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018270985,0.00008816737,0.0017720496,0.00029789182,0.00010727537,0.0002731455,0.00014517266,0.1728365,0.30445722,0.0074472926,0.0017596751,0.51063293],"study_design_scores_gemma":[0.000010995129,0.00006692306,0.0014596522,0.000009855312,0.000027798886,0.00025433648,0.000024780738,0.96613634,0.026909247,0.0036128839,0.0014677092,0.000019548273],"about_ca_topic_score_codex":0.00078254903,"about_ca_topic_score_gemma":0.0009644341,"teacher_disagreement_score":0.00078254903,"about_ca_system_score_codex":0.00016683387,"about_ca_system_score_gemma":0.0003235682,"threshold_uncertainty_score":0.002202928},"labels":[],"label_agreement":null},{"id":"W2170975082","doi":"10.1016/j.neuroimage.2010.03.072","title":"Age-related regional variations of the corpus callosum identified by diffusion tensor tractography","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":215,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Corpus callosum; Diffusion MRI; Tractography; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.033527946524591165,"score_gpt":0.3067254980784151,"score_spread":0.2731975515538239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170975082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966503,0.0010862054,0.0010918702,0.00003975872,0.000015954689,0.000010160761,0.00031966035,0.000022159367,0.00076397666],"genre_scores_gemma":[0.9979488,0.00057455426,0.00068954297,0.000011186064,0.000027954029,0.0000070971387,0.00020242398,0.000017813303,0.0005205601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998728,0.000024958583,0.000017208446,0.000041704272,0.000027032742,0.00001627202],"domain_scores_gemma":[0.99903345,0.00022367308,0.00042722048,0.00010611555,0.00015593201,0.000053675194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055097206,0.0002968294,0.00029008338,0.0011854977,0.00020335232,0.00035733037,0.00016904155,0.00042368175,0.001140664],"category_scores_gemma":[0.0027712411,0.0001769718,0.0001919978,0.0006995641,0.00030588213,0.0007354298,0.00023199257,0.00026899812,0.00022429871],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053087673,0.00018791137,0.49167427,0.00036410862,0.00064260355,0.00886152,0.0019230639,0.0039037063,0.39054656,0.0016195289,0.0018925348,0.09307537],"study_design_scores_gemma":[0.000014547921,0.00029261858,0.9812112,0.000017749779,0.00011501621,0.00526109,0.00015682518,0.0012976533,0.009653297,0.00058097474,0.0013754753,0.000023598162],"about_ca_topic_score_codex":0.0024540771,"about_ca_topic_score_gemma":0.0024687075,"teacher_disagreement_score":0.0024540771,"about_ca_system_score_codex":0.00021901354,"about_ca_system_score_gemma":0.00020212251,"threshold_uncertainty_score":0.0048796535},"labels":[],"label_agreement":null},{"id":"W2171152497","doi":"10.1007/s00429-011-0321-1","title":"Structural organization of the prefrontal white matter pathways in the adult and aging brain measured by diffusion tensor imaging","year":2011,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Neuroscience; Psychology; Prefrontal cortex; Tractography; Magnetic resonance imaging; Medicine; Cognition; Radiology","score_opus":0.017907791253062827,"score_gpt":0.23075747573004704,"score_spread":0.2128496844769842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171152497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987128,0.0004722459,0.00039745407,0.000033654855,0.0000017043668,0.0000025962306,0.00014576263,0.0000047061944,0.00022906718],"genre_scores_gemma":[0.99856454,0.0003179647,0.00072043965,0.000012747768,0.000003904455,0.0000035487462,0.000096671356,0.0000025389916,0.00027766987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999527,0.000006541979,0.0000042952393,0.000016022432,0.000010320718,0.000010103969],"domain_scores_gemma":[0.9997713,0.000029089504,0.00011172297,0.000019728912,0.00003754573,0.000030627278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027839115,0.00015951948,0.00011575576,0.0005190953,0.0001422493,0.0002958316,0.00017459992,0.00021990975,0.0006615928],"category_scores_gemma":[0.0007010842,0.00015319194,0.00009193487,0.0002793803,0.0002610367,0.00047870047,0.00016325474,0.00020723537,0.00006965502],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002511715,0.00027994628,0.57267517,0.00022318498,0.0006892023,0.0014636551,0.0024418144,0.0024172387,0.29968962,0.002248918,0.0012973066,0.11406227],"study_design_scores_gemma":[0.000010155705,0.00011467042,0.9947001,0.000005856644,0.00003277139,0.00095129694,0.00015548443,0.00082975184,0.0024126726,0.00043132037,0.00034880955,0.0000070755186],"about_ca_topic_score_codex":0.006529533,"about_ca_topic_score_gemma":0.009874031,"teacher_disagreement_score":0.006529533,"about_ca_system_score_codex":0.00025130608,"about_ca_system_score_gemma":0.00029140813,"threshold_uncertainty_score":0.012983084},"labels":[],"label_agreement":null},{"id":"W2171212208","doi":"10.1016/j.schres.2012.04.011","title":"Compassionate allowance for people with schizophrenia?","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; White matter; Psychology; Schizophrenia (object-oriented programming); Fractional anisotropy; Toronto Alexithymia Scale; Corpus callosum; Clinical psychology; Psychiatry; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.16402728078681908,"score_gpt":0.4408004998953637,"score_spread":0.2767732191085446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171212208","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60825354,0.022602683,0.0025481465,0.25882196,0.002919714,0.000043089276,0.0001588187,0.0001021676,0.10454988],"genre_scores_gemma":[0.98472834,0.0023944122,0.00077155733,0.009302698,0.00017715321,0.000017274762,0.000023247154,0.000012270781,0.0025730035],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991074,0.0005113831,0.000021601893,0.00006280305,0.00011431194,0.00018247339],"domain_scores_gemma":[0.9976859,0.0004501951,0.0005275266,0.00019889924,0.00025866745,0.0008788389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014825058,0.0002666123,0.00031016365,0.00030508763,0.0027960301,0.0020872927,0.00054179155,0.001694191,0.0052594547],"category_scores_gemma":[0.0076395054,0.00016226784,0.00029506287,0.00023164798,0.005535818,0.0027542936,0.0024257286,0.0030818824,0.0005069692],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017240379,0.00073729263,0.13573445,0.0010938803,0.000486207,0.008716065,0.14329876,0.00028635294,0.011502904,0.11714391,0.09577238,0.48350373],"study_design_scores_gemma":[0.00031780417,0.0009117502,0.1872431,0.0016585848,0.00030248746,0.018562457,0.27481732,0.0004621541,0.003712969,0.22910112,0.28263706,0.0002731967],"about_ca_topic_score_codex":0.0037461803,"about_ca_topic_score_gemma":0.0085381605,"teacher_disagreement_score":0.0052594547,"about_ca_system_score_codex":0.0017402173,"about_ca_system_score_gemma":0.0023534948,"threshold_uncertainty_score":0.017594635},"labels":[],"label_agreement":null},{"id":"W2171548242","doi":"10.3174/ajnr.a3283","title":"Evaluation of a Practical Visual MRI Rating Scale of Brain White Matter Hyperintensities for Clinicians Based on Largest Lesion Size Regardless of Location","year":2012,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health","keywords":"Hyperintensity; Medicine; Rating scale; Reproducibility; Cognition; White matter; Visual analogue scale; Audiology; Montreal Cognitive Assessment; Magnetic resonance imaging; Cognitive impairment; Radiology; Physical therapy; Psychology; Psychiatry; Developmental psychology; Statistics","score_opus":0.1209894688439421,"score_gpt":0.4572396465836188,"score_spread":0.3362501777396767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171548242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9173792,0.0009356749,0.06922821,0.00059248996,0.00030346916,0.0016991247,0.0023966595,0.0006815601,0.006783619],"genre_scores_gemma":[0.9137183,0.00019788308,0.08240566,0.00012732588,0.00011618256,0.0010740991,0.0012056519,0.000052207466,0.0011026647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972475,0.0011688612,0.0004685132,0.00034277403,0.0007060353,0.000066289365],"domain_scores_gemma":[0.98831147,0.0041019795,0.0025569324,0.0010550555,0.0035069166,0.00046765397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055554593,0.00052504655,0.00062439084,0.0016756768,0.0002824024,0.0007274266,0.00089089153,0.0007739452,0.0031219001],"category_scores_gemma":[0.021114511,0.00018850461,0.00056527945,0.0006885874,0.00038038465,0.0008010093,0.00071800547,0.00036660352,0.000867301],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021186178,0.00055607373,0.75678235,0.0006789425,0.00036177886,0.00026950068,0.0006188625,0.0016347391,0.020360108,0.00049147924,0.008833179,0.20729433],"study_design_scores_gemma":[0.00043701814,0.0026679009,0.9682557,0.00014480531,0.00017782401,0.0022087237,0.0006107596,0.013548822,0.008086699,0.000863508,0.0028805651,0.000117762145],"about_ca_topic_score_codex":0.00069502444,"about_ca_topic_score_gemma":0.0021717285,"teacher_disagreement_score":0.0055554593,"about_ca_system_score_codex":0.0002880517,"about_ca_system_score_gemma":0.00060146005,"threshold_uncertainty_score":0.02938044},"labels":[],"label_agreement":null},{"id":"W2172252744","doi":"10.1002/ana.20030","title":"Diffusion tensor fiber tracking shows distinct corticostriatal circuits in humans","year":2004,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":550,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; W. M. Keck Foundation","keywords":"Neuroscience; Diffusion MRI; Striatum; Tracing; Functional magnetic resonance imaging; Psychology; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.1683074227627158,"score_gpt":0.3952873803303854,"score_spread":0.22697995756766962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172252744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9693764,0.0010826607,0.022360055,0.00044394992,0.000040817304,0.000026536347,0.0005088103,0.00035174048,0.0058091753],"genre_scores_gemma":[0.9899346,0.0005030788,0.00810369,0.00012767782,0.000015165334,0.000013128747,0.00035784952,0.000051382645,0.00089333096],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982244,0.000021186865,0.000012062108,0.00009392747,0.000034401422,0.000015966216],"domain_scores_gemma":[0.99965036,0.00007554763,0.00009199606,0.000107111264,0.000044726054,0.00003034524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004549454,0.0002779162,0.00028734788,0.00069779536,0.00022572563,0.0004675925,0.00010827389,0.0005152514,0.0014539383],"category_scores_gemma":[0.0010645372,0.00022173623,0.00015204621,0.00025070587,0.00077334436,0.0004371896,0.00020828804,0.00032849907,0.0002913134],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021472673,0.0003678425,0.1550048,0.00027917765,0.00051340804,0.0044145165,0.0025667732,0.0040915436,0.49715278,0.012370272,0.008517131,0.31257454],"study_design_scores_gemma":[0.0001284484,0.00074516656,0.89633495,0.00010239061,0.00018899303,0.017051283,0.00032088728,0.010452182,0.04908055,0.0083157765,0.01715609,0.00012335293],"about_ca_topic_score_codex":0.0033120592,"about_ca_topic_score_gemma":0.004573337,"teacher_disagreement_score":0.0033120592,"about_ca_system_score_codex":0.00023100284,"about_ca_system_score_gemma":0.0002605556,"threshold_uncertainty_score":0.0065855384},"labels":[],"label_agreement":null},{"id":"W2175900216","doi":"10.1016/j.media.2015.10.012","title":"Sparse Reconstruction Challenge for diffusion MRI: Validation on a physical phantom to determine which acquisition scheme and analysis method to use?","year":2015,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Computer science; Imaging phantom; Diffusion MRI; Artificial intelligence; Set (abstract data type); Data set; Iterative reconstruction; Neuroimaging; Pattern recognition (psychology); Protocol (science); Data mining; Machine learning; Medical physics; Magnetic resonance imaging; Nuclear medicine; Medicine; Radiology","score_opus":0.10680281640726129,"score_gpt":0.42206878803914777,"score_spread":0.31526597163188647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2175900216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16597266,0.0014953399,0.8205068,0.0042119436,0.0002940464,0.00054103934,0.0013734757,0.002294167,0.003310493],"genre_scores_gemma":[0.3542077,0.0012302252,0.63908094,0.00070952385,0.000075353986,0.00039259897,0.0020435525,0.00040780994,0.0018523323],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99863786,0.00067295413,0.000079033096,0.00017124845,0.00039092114,0.000047961425],"domain_scores_gemma":[0.99005425,0.0070026345,0.00042481895,0.0008418566,0.0014803278,0.00019609634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059024454,0.000568906,0.0006721616,0.00042036615,0.0005463098,0.0011561216,0.0009795597,0.0019353706,0.0018372473],"category_scores_gemma":[0.036216777,0.00040560568,0.00044151905,0.00048192436,0.00086359965,0.0010423587,0.0009701877,0.0015684845,0.0009403568],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002596846,0.0014786622,0.008598,0.0032920323,0.0005404733,0.0010223014,0.0009827336,0.37376085,0.15942027,0.02104219,0.03033684,0.39692876],"study_design_scores_gemma":[0.0003196926,0.0006754423,0.0022327977,0.00022858102,0.00008055906,0.0011756724,0.00019598783,0.9387535,0.039145555,0.009581454,0.007541049,0.00006972963],"about_ca_topic_score_codex":0.0039770366,"about_ca_topic_score_gemma":0.0037143484,"teacher_disagreement_score":0.0059024454,"about_ca_system_score_codex":0.00040227346,"about_ca_system_score_gemma":0.0014803559,"threshold_uncertainty_score":0.03121543},"labels":[],"label_agreement":null},{"id":"W2178761095","doi":"10.1016/j.neuroimage.2015.10.061","title":"A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Stiftelsen för Strategisk Forskning; Vetenskapsrådet; Stiftelsen för Strategisk Forskning","keywords":"Computer science; Voxel; Diffusion MRI; Compressed sensing; Algorithm; Artificial intelligence; Image resolution; Regularization (linguistics); Computer vision; Pattern recognition (psychology); Magnetic resonance imaging","score_opus":0.10546400796500113,"score_gpt":0.32256278767892554,"score_spread":0.2170987797139244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2178761095","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018439873,0.00025828695,0.9970613,0.00020903454,0.00002664077,0.000015064659,0.00003546942,0.000091244256,0.00045894913],"genre_scores_gemma":[0.08908921,0.0011293903,0.90646976,0.0002291334,0.0002007718,0.00009236483,0.00024499197,0.00012408772,0.0024202683],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995307,0.00013422269,0.000031623054,0.00006577399,0.00020552265,0.0000322711],"domain_scores_gemma":[0.99887854,0.0005759946,0.00009660976,0.0001552815,0.00022344141,0.000070235845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010047212,0.000927555,0.00086322735,0.0006919499,0.000345924,0.0008277506,0.0013020899,0.0014737899,0.0022161407],"category_scores_gemma":[0.003557218,0.00051165157,0.0007046789,0.0010130217,0.00074456196,0.0019789238,0.0017447826,0.0015965551,0.0006227731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042882893,0.00019140713,0.0006043765,0.0007069699,0.00020955257,0.0004973713,0.0002866385,0.36689085,0.11761034,0.12576312,0.007878331,0.37893218],"study_design_scores_gemma":[0.000009544881,0.00003133092,0.00009268936,0.000009601009,0.000014422777,0.00016148409,0.0000100450125,0.9790902,0.0049712835,0.013859057,0.0017301474,0.000020140333],"about_ca_topic_score_codex":0.0021257661,"about_ca_topic_score_gemma":0.0032116966,"teacher_disagreement_score":0.0022161407,"about_ca_system_score_codex":0.0003004857,"about_ca_system_score_gemma":0.0009607039,"threshold_uncertainty_score":0.0074136853},"labels":[],"label_agreement":null},{"id":"W2180021448","doi":"","title":"Rapid alterations in diffusion-weighted images with anatomic correlates in a rodent model of status epilepticus.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital","funders":"","keywords":"Piriform cortex; Status epilepticus; Retrosplenial cortex; Hippocampal formation; Medicine; Entorhinal cortex; Neuroscience; Hippocampus; Effective diffusion coefficient; Cortex (anatomy); Pilocarpine; Temporal lobe; Epilepsy; Epileptogenesis; Amygdala; Pathology; Magnetic resonance imaging; Psychology; Internal medicine; Radiology","score_opus":0.038755409744673223,"score_gpt":0.2804857950530955,"score_spread":0.24173038530842228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180021448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946688,0.0017710523,0.0019636808,0.00015850905,0.000039403643,0.000098534234,0.0002938672,0.00020318445,0.00080296234],"genre_scores_gemma":[0.99303657,0.0015818821,0.0026480665,0.00007671659,0.000013118666,0.00014432866,0.00057780213,0.00003210907,0.0018894348],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987996,0.000018194303,0.000010969069,0.000025078249,0.000032252377,0.000033469296],"domain_scores_gemma":[0.9996207,0.000021288792,0.0002241818,0.000037877755,0.000030385227,0.00006562815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002359929,0.0008321128,0.00025805068,0.0006933011,0.00015558857,0.00023575292,0.00030439033,0.00038164813,0.0009220638],"category_scores_gemma":[0.0002617904,0.00032125763,0.00027773264,0.00018130448,0.00060781173,0.0005684846,0.00023510645,0.00074994867,0.00029724688],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011122018,0.00028357428,0.0010641468,0.00009621886,0.000020696887,0.0006237239,0.000045455687,0.00011566597,0.99311924,0.00015755913,0.00014207904,0.0032194585],"study_design_scores_gemma":[0.00032469572,0.017468793,0.048667565,0.000057429774,0.0001741872,0.0076377615,0.00019914783,0.0019016698,0.919709,0.0005334318,0.003285067,0.00004117698],"about_ca_topic_score_codex":0.00053916377,"about_ca_topic_score_gemma":0.0012081071,"teacher_disagreement_score":0.0009220638,"about_ca_system_score_codex":0.0004799046,"about_ca_system_score_gemma":0.00024893496,"threshold_uncertainty_score":0.0034819841},"labels":[],"label_agreement":null},{"id":"W2181270872","doi":"10.3389/fnhum.2015.00585","title":"Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study","year":2015,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Manitoba; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"Diffusion MRI; Default mode network; White matter; Tractography; Resting state fMRI; Neuroscience; Human Connectome Project; Salience (neuroscience); Artificial intelligence; Task-positive network; Psychology; Neuroimaging; Computer science; Pattern recognition (psychology); Functional magnetic resonance imaging; Medicine; Functional connectivity; Magnetic resonance imaging; Radiology","score_opus":0.0468302688176115,"score_gpt":0.3404702059645135,"score_spread":0.293639937146902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181270872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51446646,0.00046704034,0.47759646,0.00012306863,0.000014875897,0.00022570924,0.002289012,0.0005512194,0.004266097],"genre_scores_gemma":[0.85740614,0.00034847422,0.13887183,0.000026635265,0.00001687819,0.00027905763,0.0016660424,0.00012394944,0.0012609814],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99956435,0.000108968095,0.000033216027,0.00013775488,0.00012681186,0.000028895487],"domain_scores_gemma":[0.9992694,0.00023762096,0.00012290927,0.00022559246,0.000104424624,0.000039965867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012176278,0.00027488466,0.00027838294,0.0015183764,0.0003657019,0.0007557999,0.00047957004,0.00032063344,0.0015193744],"category_scores_gemma":[0.0029132613,0.00035877115,0.000557546,0.0012608988,0.0005461336,0.0007130743,0.00067146047,0.00036420656,0.0003468597],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012429131,0.00030867525,0.19621165,0.00050107867,0.00068113743,0.0018620508,0.0047555664,0.229445,0.15806341,0.10060674,0.0050048954,0.3013169],"study_design_scores_gemma":[0.00012447243,0.00047782913,0.43823954,0.00010723196,0.00024173624,0.0056074695,0.00070704555,0.44267547,0.0363504,0.055480346,0.01974574,0.00024267705],"about_ca_topic_score_codex":0.0053042546,"about_ca_topic_score_gemma":0.0065225363,"teacher_disagreement_score":0.0053042546,"about_ca_system_score_codex":0.0006638732,"about_ca_system_score_gemma":0.00087129173,"threshold_uncertainty_score":0.010546744},"labels":[],"label_agreement":null},{"id":"W2182563485","doi":"10.1016/j.nicl.2015.11.019","title":"Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI","year":2015,"lang":"en","type":"review","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":225,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; McMaster University; University of Toronto","funders":"","keywords":"Spinal cord; Medicine; Neuroscience; Diffusion MRI; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.5799579797304347,"score_gpt":0.6054766709107983,"score_spread":0.02551869118036354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182563485","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014481525,0.9963735,0.00028406156,0.00031549894,0.00011635627,0.00066823134,0.00051808695,0.000011014924,0.000265085],"genre_scores_gemma":[0.014476692,0.98156756,0.0016059623,0.0005514336,0.000076979035,0.0012603569,0.00034001298,0.000009383324,0.00011165339],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.97596836,0.0070374096,0.011889267,0.0013217366,0.0033266027,0.0004566068],"domain_scores_gemma":[0.89764833,0.07596651,0.01570666,0.0012724828,0.008693599,0.0007125583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023698036,0.0021849682,0.010591725,0.02560761,0.0010928743,0.004124194,0.0033722124,0.002592794,0.0039593354],"category_scores_gemma":[0.09662882,0.0017098165,0.0070789484,0.0245251,0.0016101472,0.0041491156,0.0024883896,0.0012937888,0.00044226335],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011947572,0.000008962559,0.00045611447,0.9731093,0.004021603,0.00012020992,0.00023790401,0.00005475352,0.00014819516,0.00013438155,0.00064390246,0.02094515],"study_design_scores_gemma":[0.0001389642,0.00014550438,0.0021938304,0.95002985,0.03746041,0.00027697277,0.00044360658,0.00007310644,0.00022698168,0.00018737842,0.008790017,0.0000333473],"about_ca_topic_score_codex":0.009274004,"about_ca_topic_score_gemma":0.032072134,"teacher_disagreement_score":0.02560761,"about_ca_system_score_codex":0.0058553433,"about_ca_system_score_gemma":0.02196344,"threshold_uncertainty_score":0.12532866},"labels":[],"label_agreement":null},{"id":"W2182991436","doi":"10.1007/978-3-642-22092-0_23","title":"Anisotropic Diffusion of Tensor Fields for Fold Shape Analysis on Surfaces","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Diffusion MRI; Sulcus; Anisotropy; Isotropy; Geometry; Anisotropic diffusion; Surface (topology); Fold (higher-order function); Tractography; Computer science; Physics; Anatomy; Mathematics; Optics; Biology; Magnetic resonance imaging","score_opus":0.06319671666251693,"score_gpt":0.3342538968793565,"score_spread":0.2710571802168396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182991436","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008220218,0.00037793876,0.9902862,0.0001939078,0.000037260772,0.000022323791,0.0000887999,0.0002159498,0.0005575145],"genre_scores_gemma":[0.14438802,0.0018339198,0.8477454,0.000083738785,0.000109575274,0.00009143533,0.00049589796,0.00051054737,0.004741477],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996896,0.00009326309,0.000025264417,0.000054013148,0.00010935822,0.000028516479],"domain_scores_gemma":[0.99840003,0.0006580851,0.00016936948,0.0002885045,0.00034478662,0.00013927318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010300443,0.00093957,0.0010693336,0.0019436807,0.00053119037,0.0021335273,0.0011422591,0.0012108006,0.0022769407],"category_scores_gemma":[0.0046274643,0.00058419956,0.0012767749,0.0015840182,0.00096701214,0.0020128933,0.0014813337,0.0020412782,0.0007932407],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032126013,0.00011162778,0.001845103,0.0005857247,0.00015595942,0.00021251176,0.00045951334,0.16465722,0.10039777,0.26207754,0.0085903555,0.46058547],"study_design_scores_gemma":[0.000010749954,0.00003501125,0.0005009334,0.000023844446,0.000018876546,0.00016899724,0.000058493795,0.91754997,0.006217916,0.07066294,0.0047174287,0.00003483802],"about_ca_topic_score_codex":0.0036477507,"about_ca_topic_score_gemma":0.004190002,"teacher_disagreement_score":0.0036477507,"about_ca_system_score_codex":0.00067383685,"about_ca_system_score_gemma":0.0011380033,"threshold_uncertainty_score":0.0076170564},"labels":[],"label_agreement":null},{"id":"W2184177600","doi":"10.62721/diffusion-fundamentals.18.669","title":"Velocity-sensitised Magnetic Resonance Imaging of foams","year":2013,"lang":"en","type":"article","venue":"Diffusion fundamentals.","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Venturi effect; Magnetic resonance imaging; Magnetic field; Rheology; Optics; Nuclear magnetic resonance; Mechanics; Physics; Composite material","score_opus":0.028707815078479876,"score_gpt":0.30339981011966,"score_spread":0.27469199504118014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184177600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86850333,0.001408933,0.12731627,0.00018578865,0.000034252596,0.000054079803,0.000070593785,0.0004121035,0.0020145513],"genre_scores_gemma":[0.906351,0.0010042416,0.09044412,0.00009961039,0.00003617637,0.000057529574,0.000114426286,0.00006857865,0.0018243211],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99987507,0.00003241404,0.000005517993,0.000027553337,0.000038156482,0.000021323269],"domain_scores_gemma":[0.9996172,0.0001501645,0.00009657477,0.00003183544,0.00006456099,0.000039680042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042913464,0.00026134204,0.00020251873,0.0005440408,0.00015411292,0.00030445275,0.0003206811,0.00051290944,0.00073055417],"category_scores_gemma":[0.0012976464,0.00021808835,0.0001114446,0.00016467588,0.00056302187,0.000558,0.00039960872,0.00041138937,0.0001458819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007451426,0.0000063680955,0.00023470994,0.000043623455,0.0000030366393,0.000087913715,0.00003563775,0.00027232256,0.99529666,0.00022322782,0.00003302523,0.0036889066],"study_design_scores_gemma":[0.00001836755,0.0003833756,0.0038220412,0.00002116359,0.000017426053,0.0009209095,0.00004395284,0.008878092,0.9840687,0.0004216442,0.0013863813,0.000017868264],"about_ca_topic_score_codex":0.0002668516,"about_ca_topic_score_gemma":0.0003734925,"teacher_disagreement_score":0.00073055417,"about_ca_system_score_codex":0.00015448117,"about_ca_system_score_gemma":0.00018095855,"threshold_uncertainty_score":0.0024439096},"labels":[],"label_agreement":null},{"id":"W2186454342","doi":"10.1503/jpn.130079","title":"Cognitive impairment with and without depression history: an analysis of white matter microstructure","year":2014,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Late life depression; White matter; Corpus callosum; Fractional anisotropy; Cingulum (brain); Depression (economics); Superior longitudinal fasciculus; Psychology; Internal capsule; Diffusion MRI; Medicine; Internal medicine; Hyperintensity; Corona radiata (embryology); Cardiology; Psychiatry; Magnetic resonance imaging; Cognition; Neuroscience; Radiology","score_opus":0.018963606810451044,"score_gpt":0.31604544411668034,"score_spread":0.2970818373062293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186454342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99945563,0.00018189037,0.000031053118,0.000008679457,0.000002426159,0.000009732479,0.00010408125,0.0000011834184,0.00020542393],"genre_scores_gemma":[0.9996799,0.000042865493,0.000055988512,0.000008500518,0.0000047568815,0.0000067641163,0.00014636411,5.149439e-7,0.000054370776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982506,0.00002797111,0.000028981576,0.000049572296,0.000038038354,0.000030456897],"domain_scores_gemma":[0.9996247,0.000038008828,0.0001654395,0.00002849636,0.000044534823,0.000098781085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042723664,0.0003235537,0.0003028622,0.0012967694,0.00041295867,0.00050730427,0.0002539953,0.0003562202,0.0009980686],"category_scores_gemma":[0.0009402932,0.00014448067,0.0003536688,0.0006859724,0.00026758917,0.00026836616,0.0005467065,0.0002487589,0.00015717138],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055860914,0.000043462245,0.99638295,0.000015709024,0.000117665535,0.00019158528,0.00010871309,0.000021797325,0.00070202927,0.000014828265,0.00005233566,0.001790313],"study_design_scores_gemma":[0.0000069106422,0.00011128774,0.99933964,0.000002750576,0.00002408849,0.0003035026,0.00006186463,0.000048673406,0.000038175276,0.000014893742,0.00004687089,0.0000013145228],"about_ca_topic_score_codex":0.003193052,"about_ca_topic_score_gemma":0.005528069,"teacher_disagreement_score":0.003193052,"about_ca_system_score_codex":0.00029909206,"about_ca_system_score_gemma":0.00022565697,"threshold_uncertainty_score":0.006348908},"labels":[],"label_agreement":null},{"id":"W2188887891","doi":"10.1007/978-3-642-38899-6_52","title":"Atlases of Cardiac Fiber Differential Geometry","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Helicoid; Normalization (sociology); Curvature; Computer science; Artificial intelligence; Geometry; Algorithm; Mathematics; Pattern recognition (psychology)","score_opus":0.03304658311309931,"score_gpt":0.30185528153546654,"score_spread":0.2688086984223672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188887891","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036171523,0.002071896,0.9649729,0.00025857103,0.00017550388,0.00006397794,0.0013009856,0.0014769686,0.026061926],"genre_scores_gemma":[0.09825336,0.008396833,0.8560406,0.00019370143,0.00035663965,0.00016254169,0.0030157347,0.0012525296,0.03232811],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998666,0.000021979322,0.000009283989,0.000032551397,0.00005901834,0.000010511744],"domain_scores_gemma":[0.99973184,0.00007709754,0.000021520345,0.00005946884,0.00008937775,0.00002060487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003359911,0.00061204424,0.00041857458,0.0015605399,0.00032574096,0.0016681325,0.00075307034,0.00056418753,0.009774124],"category_scores_gemma":[0.000969043,0.00048933417,0.00040070005,0.0014031142,0.0004694432,0.0010458376,0.00077423954,0.0011530344,0.003946715],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059522317,0.000016830014,0.0006745969,0.00045620571,0.000041630024,0.00033866992,0.0003832255,0.040597305,0.014502821,0.38675693,0.040244084,0.51592815],"study_design_scores_gemma":[0.000022801549,0.00006816477,0.002003192,0.0002744932,0.000049238755,0.003898559,0.0001828662,0.20920706,0.016399745,0.35244662,0.4153594,0.000087805114],"about_ca_topic_score_codex":0.0014057403,"about_ca_topic_score_gemma":0.0023077137,"teacher_disagreement_score":0.009774124,"about_ca_system_score_codex":0.00043169796,"about_ca_system_score_gemma":0.00052325224,"threshold_uncertainty_score":0.032697678},"labels":[],"label_agreement":null},{"id":"W2193227159","doi":"10.3233/jad-150049","title":"Non-Linear Association between Cerebral Amyloid Deposition and White Matter Microstructure in Cognitively Healthy Older Adults","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; U.S. Department of Defense","keywords":"Fractional anisotropy; White matter; Pittsburgh compound B; Diffusion MRI; Amyloid (mycology); Neuroimaging; Psychology; Cognition; Medicine; Internal medicine; Neuroscience; Pathology; Magnetic resonance imaging; Cognitive impairment","score_opus":0.035232916105586674,"score_gpt":0.334160483947288,"score_spread":0.2989275678417013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2193227159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996898,0.00009776183,0.00006103408,0.000010269255,8.412829e-7,0.0000017721347,0.00005328958,0.000002147298,0.0000832279],"genre_scores_gemma":[0.9996898,0.000039055813,0.00009341478,0.0000080207255,0.0000033177407,0.000002582191,0.00009245864,8.3786404e-7,0.0000704551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983764,0.000028377424,0.000027216149,0.000051120784,0.000034278284,0.00002130434],"domain_scores_gemma":[0.9989127,0.0001836696,0.00055453397,0.00010300318,0.00015910811,0.00008704862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005121815,0.00031795134,0.0002538539,0.0006013073,0.00024201999,0.00038438753,0.00019707732,0.0004045185,0.00061926886],"category_scores_gemma":[0.0022583695,0.0002126212,0.00023047815,0.00038165468,0.00022415056,0.0003393791,0.00030187,0.00024363602,0.0001372079],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022901931,0.000023752897,0.99573493,0.000011782592,0.0001110673,0.00009522648,0.00015526442,0.00007393479,0.0016963617,0.0000151851455,0.000033257267,0.0018202724],"study_design_scores_gemma":[0.0000027419417,0.000043423435,0.99954104,0.0000011069131,0.000013046389,0.00011100202,0.000030497766,0.00014654335,0.00006408186,0.000024414714,0.000020987049,0.0000011656665],"about_ca_topic_score_codex":0.0039313105,"about_ca_topic_score_gemma":0.005409673,"teacher_disagreement_score":0.0039313105,"about_ca_system_score_codex":0.00015500764,"about_ca_system_score_gemma":0.00012578507,"threshold_uncertainty_score":0.007816851},"labels":[],"label_agreement":null},{"id":"W2194834710","doi":"10.3171/2015.6.jns142203","title":"Identifying preoperative language tracts and predicting postoperative functional recovery using HARDI q-ball fiber tractography in patients with gliomas","year":2015,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Cancer Institute; National Defense Science and Engineering Graduate; National Institutes of Health; U.S. Department of Defense","keywords":"Diffusion MRI; Medicine; Tractography; White matter; Segmentation; Glioma; Fiber tract; Surgical planning; Brain mapping; Neuroscience; Radiology; Magnetic resonance imaging; Artificial intelligence; Computer science; Psychology","score_opus":0.08442622157027459,"score_gpt":0.3243280770015919,"score_spread":0.2399018554313173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2194834710","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997414,0.000034346675,0.00008582203,0.000010685456,8.346373e-7,0.0000026170608,0.000025103245,0.0000044574585,0.00009470397],"genre_scores_gemma":[0.9996295,0.000045459128,0.00015777827,0.0000052806304,0.0000013899656,0.0000034225272,0.00007607165,0.0000012251463,0.00007982214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999367,0.000010183033,0.0000098888795,0.000016566408,0.000013224884,0.000013461796],"domain_scores_gemma":[0.99958366,0.00012743188,0.0001243347,0.00003261523,0.00005517129,0.00007684022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001975196,0.00023575046,0.0001619695,0.00062749686,0.00018567807,0.00025336185,0.00012676604,0.00026629958,0.0005379828],"category_scores_gemma":[0.0014324193,0.000107747896,0.0001361804,0.00022731215,0.00024035967,0.00033945224,0.00018256983,0.00022152344,0.00018351928],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025072935,0.000055201133,0.9881577,0.000009720052,0.000012365869,0.00033878657,0.00018231018,0.00041463718,0.0014058051,0.000010979307,0.00008978667,0.009071904],"study_design_scores_gemma":[0.000011749664,0.00034553427,0.9962883,0.000006049628,0.000018656538,0.00074824755,0.00035877008,0.0013042142,0.00076261157,0.000033198026,0.0001144864,0.000008128485],"about_ca_topic_score_codex":0.0062295347,"about_ca_topic_score_gemma":0.010974498,"teacher_disagreement_score":0.0062295347,"about_ca_system_score_codex":0.00023056497,"about_ca_system_score_gemma":0.00020585072,"threshold_uncertainty_score":0.012386501},"labels":[],"label_agreement":null},{"id":"W2198859253","doi":"10.1371/journal.pone.0138122","title":"Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Maastricht Universitair Medisch Centrum; Universiteit Maastricht","keywords":"Tractography; Deconvolution; Imaging phantom; Human Connectome Project; Computer science; Voxel; Artificial intelligence; Diffusion MRI; Probabilistic logic; Pattern recognition (psychology); Algorithm; Magnetic resonance imaging; Physics; Optics; Functional connectivity","score_opus":0.09028309085164263,"score_gpt":0.2916264425202657,"score_spread":0.20134335166862308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198859253","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017139932,0.00014296203,0.98186034,0.00009244215,0.000014459832,0.000024442272,0.000025330257,0.00041257887,0.0002876286],"genre_scores_gemma":[0.15910561,0.00024999597,0.83949506,0.000077372715,0.000043032953,0.00004988688,0.00014360182,0.00023403295,0.0006014176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993704,0.00013901238,0.000040555264,0.00014094885,0.0002584098,0.0000508118],"domain_scores_gemma":[0.99876153,0.00049595756,0.00022373423,0.00025711456,0.00017402883,0.00008757724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016649853,0.0013254875,0.0008122245,0.0010811754,0.00032860745,0.001072669,0.00097308884,0.0010340869,0.00073658966],"category_scores_gemma":[0.0038640024,0.0005244656,0.0008483031,0.0006044086,0.0008926896,0.0011700278,0.0019433496,0.0011213212,0.0003416888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029506368,0.00016607133,0.0029653609,0.00030945995,0.00013375435,0.00029170842,0.00031595453,0.51562184,0.17397217,0.016091524,0.00082759914,0.2890096],"study_design_scores_gemma":[0.000018333018,0.00009908335,0.00083874905,0.000013140609,0.000023793707,0.00013012864,0.000011823238,0.957357,0.03571053,0.0041669663,0.0015962393,0.00003421223],"about_ca_topic_score_codex":0.0030833827,"about_ca_topic_score_gemma":0.003482342,"teacher_disagreement_score":0.0030833827,"about_ca_system_score_codex":0.0007500223,"about_ca_system_score_gemma":0.0011223867,"threshold_uncertainty_score":0.008805394},"labels":[],"label_agreement":null},{"id":"W2206916168","doi":"10.1159/000439045","title":"Cognitive Function and 3-Tesla Magnetic Resonance Imaging Tractography of White Matter Hyperintensities in Elderly Persons","year":2015,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Toronto; Kingston General Hospital","funders":"","keywords":"Hyperintensity; Magnetic resonance imaging; White matter; Cognition; Tractography; Psychology; Diffusion MRI; Medicine; Neuroscience; Radiology","score_opus":0.020355807171047888,"score_gpt":0.2756507647423577,"score_spread":0.2552949575713098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2206916168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965966,0.00007402537,0.0001223026,0.000005533829,6.531189e-7,0.0000022482452,0.000041355128,0.000003620863,0.000090640104],"genre_scores_gemma":[0.99962115,0.0000301305,0.0002234306,0.000004194225,0.0000016309938,0.0000025655097,0.00006235027,9.612353e-7,0.00005348662],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999279,0.000018029801,0.00000829187,0.000019235704,0.000012395542,0.000014134138],"domain_scores_gemma":[0.99938214,0.000091800146,0.0003022749,0.00004260956,0.000097004486,0.00008422063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004496291,0.00024968895,0.00011196216,0.0005624276,0.00023174276,0.00032223307,0.00010300827,0.0002965969,0.00061375205],"category_scores_gemma":[0.001197814,0.00009637093,0.00018264748,0.00025159377,0.00019544142,0.0002043654,0.00014850477,0.00015323533,0.00015150872],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037660103,0.000065669956,0.99009484,0.000018690818,0.00006156221,0.00022463288,0.00020678763,0.00015793175,0.004302141,0.000021852054,0.000052192932,0.0044172034],"study_design_scores_gemma":[0.0000030197054,0.00010895008,0.99870265,0.000002703214,0.000010924707,0.00043544904,0.00004969073,0.00016610368,0.00045143158,0.000024495783,0.000042546533,0.0000021289197],"about_ca_topic_score_codex":0.0034831727,"about_ca_topic_score_gemma":0.0048468793,"teacher_disagreement_score":0.0034831727,"about_ca_system_score_codex":0.00019796511,"about_ca_system_score_gemma":0.00018789092,"threshold_uncertainty_score":0.0069258213},"labels":[],"label_agreement":null},{"id":"W2218066725","doi":"10.1161/strokeaha.115.011229","title":"Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects","year":2015,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Medical Research Council","keywords":"Medicine; Brain size; Hyperintensity; Magnetic resonance imaging; White matter; Longitudinal study; Cross-sectional study; Cardiology; Pathology; Radiology","score_opus":0.0683254785697802,"score_gpt":0.3635266156793527,"score_spread":0.29520113710957246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2218066725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995034,0.00012863356,0.00007813696,0.000015229974,0.0000027314643,0.0000037378047,0.00010500227,0.0000036052475,0.00015956943],"genre_scores_gemma":[0.99956423,0.000048593243,0.000077479504,0.000013134805,0.000005335583,0.0000051598668,0.00015127435,0.0000012450303,0.00013342279],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978536,0.00004042719,0.000021320664,0.0000765091,0.000039707425,0.000036640842],"domain_scores_gemma":[0.9988955,0.0001511413,0.0005430635,0.00013105536,0.00012819002,0.0001508858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000597991,0.0002769872,0.00023834778,0.0006361336,0.00045748425,0.00034716143,0.00030775394,0.0004967819,0.0013782142],"category_scores_gemma":[0.0021223875,0.00026520653,0.00021882338,0.00066844077,0.0003603799,0.00035098192,0.00031520842,0.00044356508,0.0002288049],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001686709,0.00003103373,0.99772626,0.000006400923,0.000061169994,0.00008333754,0.000103845385,0.00003565953,0.0005871256,0.000016250551,0.00003631537,0.00114391],"study_design_scores_gemma":[0.0000023776195,0.00003356268,0.999747,0.0000014695465,0.000008749672,0.00006652919,0.000020566036,0.000038277038,0.00003834887,0.000015078236,0.000027000666,0.0000010126482],"about_ca_topic_score_codex":0.009340447,"about_ca_topic_score_gemma":0.010851938,"teacher_disagreement_score":0.009340447,"about_ca_system_score_codex":0.00026596262,"about_ca_system_score_gemma":0.0002804408,"threshold_uncertainty_score":0.018572152},"labels":[],"label_agreement":null},{"id":"W2220266781","doi":"10.1007/978-3-319-24574-4_3","title":"Multimodal Cortical Parcellation Based on Anatomical and Functional Brain Connectivity","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Human Connectome Project; Functional magnetic resonance imaging; Spurious relationship; Robustness (evolution); Pattern recognition (psychology); Cluster analysis; Connectome; Weighting; Functional connectivity; Machine learning; Neuroscience; Psychology","score_opus":0.06352721780385819,"score_gpt":0.330669639901175,"score_spread":0.2671424220973168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2220266781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04493168,0.0019302631,0.9395496,0.00037143848,0.00013447597,0.00011236101,0.0009987878,0.002763032,0.009208262],"genre_scores_gemma":[0.49452302,0.0036577429,0.486814,0.00018841596,0.0004047822,0.00027458186,0.002370741,0.001347732,0.0104190055],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977595,0.000036664893,0.000009125213,0.000066110326,0.00006998422,0.000042205986],"domain_scores_gemma":[0.99970967,0.000113560665,0.000031372707,0.00005313094,0.00007180435,0.000020376487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005353461,0.0010587822,0.0007247329,0.0015965269,0.00033500599,0.0017271438,0.00080913724,0.00066731765,0.0062123393],"category_scores_gemma":[0.0016652801,0.000348991,0.0009287613,0.0021867736,0.0004886234,0.0012892976,0.0009110607,0.0004950617,0.0029639516],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040427182,0.00004189955,0.00240163,0.00029380588,0.00025450095,0.00038722582,0.00030192616,0.020060698,0.19472864,0.007835388,0.010356925,0.7629331],"study_design_scores_gemma":[0.000065312626,0.00032745645,0.04864909,0.00015200766,0.0007841129,0.0038120502,0.0006158733,0.6631434,0.1836388,0.06537725,0.03322865,0.00020604683],"about_ca_topic_score_codex":0.001472142,"about_ca_topic_score_gemma":0.003118662,"teacher_disagreement_score":0.0062123393,"about_ca_system_score_codex":0.00031071092,"about_ca_system_score_gemma":0.00026394476,"threshold_uncertainty_score":0.020782411},"labels":[],"label_agreement":null},{"id":"W2222869326","doi":"10.1016/j.media.2015.10.011","title":"Strengths and weaknesses of state of the art fiber tractography pipelines – A comprehensive in-vivo and phantom evaluation study using Tractometer","year":2015,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; Deutsche Forschungsgemeinschaft","keywords":"Tractography; Metric (unit); Imaging phantom; Computer science; Consistency (knowledge bases); Artificial intelligence; Machine learning; Data mining; Diffusion MRI; Magnetic resonance imaging; Engineering; Medicine; Nuclear medicine; Radiology","score_opus":0.0852731398949972,"score_gpt":0.4298637285706721,"score_spread":0.34459058867567494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222869326","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17316635,0.003154247,0.8067753,0.00062400865,0.0001692292,0.00046703406,0.0012132857,0.011063931,0.0033666978],"genre_scores_gemma":[0.45313057,0.0022831948,0.53640586,0.00021398481,0.000059827544,0.00028865825,0.0021727697,0.0027878105,0.0026572759],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953566,0.0013734379,0.0003137336,0.0006499818,0.0020924162,0.00021380984],"domain_scores_gemma":[0.98002267,0.009639743,0.0013576563,0.003569257,0.0050202184,0.0003904466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01036063,0.0015937178,0.001038231,0.0021975562,0.0010481736,0.0032718235,0.002551502,0.002207289,0.0024402207],"category_scores_gemma":[0.03155112,0.0012623336,0.0009407278,0.0018440456,0.0010343136,0.004616018,0.0018787063,0.0013228517,0.0013597762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003001854,0.00081237446,0.029756706,0.0029976957,0.0016238752,0.00054461655,0.0017859213,0.124960266,0.102533706,0.005555168,0.006929274,0.7194986],"study_design_scores_gemma":[0.00014826744,0.0022182663,0.031115312,0.00072925625,0.00081264356,0.003161344,0.0005397817,0.8096465,0.11869141,0.006162103,0.026374409,0.00040072014],"about_ca_topic_score_codex":0.006868652,"about_ca_topic_score_gemma":0.010504846,"teacher_disagreement_score":0.01036063,"about_ca_system_score_codex":0.0010327022,"about_ca_system_score_gemma":0.0022732865,"threshold_uncertainty_score":0.05479288},"labels":[],"label_agreement":null},{"id":"W2229909148","doi":"10.6084/m9.figshare.1216667.v1","title":"CST Mask in ICBM152 space","year":2014,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Space (punctuation); Computer science; Mathematics","score_opus":0.11457397241012524,"score_gpt":0.3683917273883437,"score_spread":0.25381775497821846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2229909148","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074811415,0.0005325605,0.03731128,0.0007546694,0.00079467526,0.00067293877,0.86383414,0.047069512,0.041549094],"genre_scores_gemma":[0.049709328,0.0005736934,0.09963405,0.00089754566,0.00039279019,0.0036409546,0.7699461,0.037884355,0.037321217],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999647,0.000038326794,0.00005456429,0.00008319529,0.00011665097,0.000060249487],"domain_scores_gemma":[0.9980451,0.00061323703,0.000113615875,0.0005231711,0.00059790764,0.000107011496],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005531167,0.0011098117,0.0009293411,0.0015451786,0.0006051545,0.0016610356,0.0014549452,0.0011530113,0.49030438],"category_scores_gemma":[0.0064379564,0.0006266665,0.0005985946,0.0021107614,0.00021202357,0.0012241569,0.0013276037,0.000894819,0.17289051],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000609218,0.000030886873,0.00064292515,0.00049363653,0.000033126762,0.00018890521,0.00011585876,0.00043134057,0.0034791671,0.0018015081,0.9340908,0.05808266],"study_design_scores_gemma":[0.0004185637,0.00012635322,0.008504895,0.0002864488,0.000059697788,0.001589895,0.00012022652,0.0033845992,0.017081803,0.004955898,0.96339047,0.000081234604],"about_ca_topic_score_codex":0.0033629204,"about_ca_topic_score_gemma":0.0040116077,"teacher_disagreement_score":0.49030438,"about_ca_system_score_codex":0.00058262615,"about_ca_system_score_gemma":0.0013236337,"threshold_uncertainty_score":0.72701895},"labels":[],"label_agreement":null},{"id":"W2231927503","doi":"10.1155/2016/6029241","title":"Simultaneous Assessment of White Matter Changes in Microstructure and Connectedness in the Blind Brain","year":2016,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"H. Lundbeck A/S; Danmarks Frie Forskningsfond; Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"White matter; Corpus callosum; Diffusion MRI; Fractional anisotropy; Neuroscience; Voxel; Social connectedness; Psychology; Magnetic resonance imaging; Blindness; Medicine; Radiology","score_opus":0.03530728386644837,"score_gpt":0.34566196415317535,"score_spread":0.31035468028672697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2231927503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986638,0.00011290728,0.0009625974,0.000009301056,0.0000015473076,0.0000062785425,0.00006016836,0.000013811759,0.00016962002],"genre_scores_gemma":[0.9984322,0.000082654435,0.0012907825,0.000007422353,0.0000020396021,0.0000067829556,0.000044728164,0.000004621702,0.00012870137],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986947,0.00002331932,0.000015508556,0.000046797322,0.000030176927,0.000014797508],"domain_scores_gemma":[0.99954516,0.00007468775,0.0002251749,0.000047322763,0.000046630517,0.00006103748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002872468,0.00035984794,0.00019481592,0.0014540864,0.00022756589,0.00030687056,0.00010080461,0.00021628261,0.00090814044],"category_scores_gemma":[0.0010185844,0.00014802213,0.0001275632,0.0003345483,0.00044154326,0.00033587712,0.00044257398,0.00021797669,0.000051603867],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013749945,0.00013931209,0.19280668,0.0002015208,0.00027822153,0.00090125855,0.0013596215,0.0007026868,0.76415485,0.00060982583,0.00014242415,0.03732859],"study_design_scores_gemma":[0.0000137421275,0.0005242419,0.955049,0.000011953073,0.000058039222,0.0019282299,0.00030434108,0.0009512206,0.040221415,0.00069898955,0.00021771133,0.000021130072],"about_ca_topic_score_codex":0.0014911033,"about_ca_topic_score_gemma":0.0022080578,"teacher_disagreement_score":0.0014911033,"about_ca_system_score_codex":0.00014987784,"about_ca_system_score_gemma":0.00013011096,"threshold_uncertainty_score":0.0030379891},"labels":[],"label_agreement":null},{"id":"W2236225132","doi":"10.1002/mrm.26071","title":"Q‐space truncation and sampling in diffusion spectrum imaging","year":2016,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Consortia for Improving Medicine with Innovation and Technology","keywords":"Sampling (signal processing); Truncation (statistics); Spectrum (functional analysis); Diffusion; Nuclear magnetic resonance; Diffusion MRI; k-space; Space (punctuation); Physics; Statistical physics; Computer science; Mathematics; Mathematical analysis; Statistics; Medicine; Magnetic resonance imaging; Optics; Radiology; Fourier transform; Quantum mechanics","score_opus":0.04134616623408731,"score_gpt":0.34313900023516963,"score_spread":0.3017928340010823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2236225132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3573099,0.0006385079,0.6403896,0.000149504,0.00002347254,0.00007704457,0.000101446785,0.00029615193,0.0010142977],"genre_scores_gemma":[0.8476399,0.0006682589,0.15029156,0.00009501928,0.000024954761,0.000089553534,0.00023451561,0.0001636507,0.00079248537],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995964,0.000141637,0.000029051094,0.00006190419,0.00012909326,0.00004197048],"domain_scores_gemma":[0.9962924,0.0023305828,0.00047285215,0.00044374666,0.0003423494,0.000118037526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024854736,0.0005417748,0.0004047999,0.00032255394,0.00034226375,0.00049862906,0.00041265335,0.0003916619,0.0005802891],"category_scores_gemma":[0.011631135,0.00032208196,0.00028575733,0.00030956723,0.0011727521,0.001330517,0.00057692203,0.00047337354,0.00019980111],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014352497,0.0001603395,0.014302002,0.0005758746,0.000107958775,0.001268958,0.0008644655,0.16258018,0.675964,0.02373133,0.0007051047,0.11830456],"study_design_scores_gemma":[0.000093014176,0.0007578918,0.026809761,0.000077340796,0.00006319949,0.0024498808,0.000117785974,0.604052,0.34382248,0.018572673,0.0030807233,0.00010328045],"about_ca_topic_score_codex":0.0014228873,"about_ca_topic_score_gemma":0.0007874761,"teacher_disagreement_score":0.0024854736,"about_ca_system_score_codex":0.0005381766,"about_ca_system_score_gemma":0.00063969026,"threshold_uncertainty_score":0.013144553},"labels":[],"label_agreement":null},{"id":"W2253627718","doi":"10.1016/j.mri.2015.12.032","title":"Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Quantitative susceptibility mapping; Globus pallidus; Computer science; Neuroscience; Gray (unit); Physics; Psychology; Magnetic resonance imaging; Basal ganglia; Medicine; Nuclear medicine","score_opus":0.0532588597182677,"score_gpt":0.3459175589204995,"score_spread":0.2926586992022318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2253627718","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24008131,0.005618724,0.7464017,0.0007278617,0.00007993696,0.00006762948,0.00047058577,0.0009611037,0.00559118],"genre_scores_gemma":[0.8059771,0.0026762984,0.18893695,0.00026058947,0.00012443302,0.0001534835,0.00037991663,0.00033302006,0.0011581096],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980694,0.0000812703,0.000015104789,0.000037862454,0.000044218228,0.000014558558],"domain_scores_gemma":[0.99754745,0.0015506983,0.00015983626,0.00038714643,0.00025247756,0.00010244653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012157526,0.00045740616,0.00034607723,0.00061658566,0.00026144643,0.0010876469,0.00037264868,0.00060547004,0.0015205548],"category_scores_gemma":[0.0065374807,0.00036352008,0.00016500833,0.0003415406,0.0005564826,0.0015598878,0.0010445208,0.00059072394,0.00028834626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079875387,0.00008742882,0.008286806,0.0009374956,0.00027088655,0.0011200152,0.00045472232,0.027009184,0.78310645,0.0152993845,0.0016007844,0.1610281],"study_design_scores_gemma":[0.00016279191,0.0008778386,0.08068073,0.00048396213,0.0006520122,0.01720344,0.00048686183,0.23087765,0.5390497,0.10038353,0.028926203,0.00021529169],"about_ca_topic_score_codex":0.0006230792,"about_ca_topic_score_gemma":0.0011013913,"teacher_disagreement_score":0.0015205548,"about_ca_system_score_codex":0.00014917323,"about_ca_system_score_gemma":0.00048594357,"threshold_uncertainty_score":0.0064296126},"labels":[],"label_agreement":null},{"id":"W2257429363","doi":"","title":"Novel Decomposition of Tensor Distance into Shape and Orientation Distances","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Orientation (vector space); Anisotropy; Tensor (intrinsic definition); Scalar (mathematics); Interpolation (computer graphics); Mathematics; Fractional anisotropy; Geometry; Measure (data warehouse); White noise; Mathematical analysis; Physics; White matter; Computer science; Artificial intelligence; Optics; Image (mathematics); Statistics","score_opus":0.03504798679884674,"score_gpt":0.38034551748719764,"score_spread":0.3452975306883509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2257429363","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006765939,0.00012163303,0.9918127,0.000087778004,0.000057837788,0.000017476004,0.000054353684,0.00011914447,0.0009630903],"genre_scores_gemma":[0.18415344,0.00047910507,0.81100905,0.00010090493,0.00022172056,0.00009407051,0.00030725627,0.00026742616,0.0033670713],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990139,0.0002831358,0.00006764927,0.00021001093,0.0003596986,0.000065599954],"domain_scores_gemma":[0.9984345,0.0002876567,0.00027726512,0.00029841074,0.00053484226,0.0001672184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001328274,0.0011122831,0.00067652983,0.0015466698,0.00038661587,0.0015340274,0.00097347423,0.0007572359,0.002145096],"category_scores_gemma":[0.0032403234,0.00031754392,0.00075896183,0.001041136,0.0012903786,0.0023217117,0.0015990242,0.0016741857,0.0009349986],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020980259,0.00011774855,0.0014656684,0.00030344486,0.000086405445,0.00023975113,0.00025953655,0.12938745,0.084736235,0.51627296,0.0053153154,0.26160562],"study_design_scores_gemma":[0.000013352141,0.00023241188,0.0008295398,0.00002471294,0.000027894628,0.0003511526,0.000054097683,0.886794,0.012919798,0.08756779,0.011122452,0.00006284473],"about_ca_topic_score_codex":0.00073010835,"about_ca_topic_score_gemma":0.0007248313,"teacher_disagreement_score":0.002145096,"about_ca_system_score_codex":0.0007051955,"about_ca_system_score_gemma":0.00076405314,"threshold_uncertainty_score":0.0071760416},"labels":[],"label_agreement":null},{"id":"W2259452444","doi":"10.1089/brain.2014.0237","title":"Structure, Integrity, and Function of the Hypoplastic Corpus Callosum in Spina Bifida Myelomeningocele","year":2014,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health","keywords":"Corpus callosum; Dichotic listening; Spina bifida; Fractional anisotropy; Diffusion MRI; Psychology; Anatomy; Neuroscience; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.037596026441725376,"score_gpt":0.3017971270643748,"score_spread":0.2642011006226494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259452444","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961394,0.00015002015,0.000062215586,0.000016419543,9.105024e-7,0.0000020600621,0.000025142883,0.0000023835048,0.00012688374],"genre_scores_gemma":[0.9996275,0.000077505465,0.00019824678,0.0000041861513,0.000001731195,0.0000023136188,0.00004831301,0.0000014120967,0.000038763472],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981874,0.000040924377,0.00002128223,0.000041024643,0.000052960782,0.00002502695],"domain_scores_gemma":[0.99929094,0.00016663846,0.00032125122,0.000057031124,0.00007367345,0.00009049044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042222688,0.000454685,0.00025019632,0.0022345644,0.0003439952,0.0004181953,0.00029107212,0.00035470608,0.00066384824],"category_scores_gemma":[0.0033022936,0.00022871548,0.00014735475,0.0006458767,0.00075716013,0.00039210194,0.0003653275,0.0002644836,0.000082976454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062864996,0.00008576599,0.9416024,0.0000716357,0.000083722756,0.004831255,0.0012811275,0.0005458465,0.028394336,0.00017012953,0.00012858066,0.022176525],"study_design_scores_gemma":[0.0000026598366,0.00006080475,0.99537694,0.000008347017,0.00001611325,0.003257429,0.00019124406,0.00027030965,0.000659274,0.00010438355,0.000048330738,0.0000041575922],"about_ca_topic_score_codex":0.008024616,"about_ca_topic_score_gemma":0.009705896,"teacher_disagreement_score":0.008024616,"about_ca_system_score_codex":0.00041364445,"about_ca_system_score_gemma":0.00039415472,"threshold_uncertainty_score":0.015955806},"labels":[],"label_agreement":null},{"id":"W2261986951","doi":"10.1007/978-3-319-15090-1_10","title":"Visualization of Diffusion Propagator and Multiple Parameter Diffusion Signal","year":2015,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Visualization; Diffusion MRI; Voxel; Computer science; Glyph (data visualization); Tractography; Diffusion; Diffusion imaging; Artificial intelligence; Diffusion map; Computer vision; Dimensionality reduction; Physics; Magnetic resonance imaging; Nonlinear dimensionality reduction","score_opus":0.09585173528790579,"score_gpt":0.3656442987827219,"score_spread":0.2697925634948161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2261986951","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039763907,0.015064386,0.88637257,0.0017245531,0.00090541993,0.00004946087,0.00043545142,0.0026875772,0.0887842],"genre_scores_gemma":[0.09429675,0.02933182,0.7010537,0.0005886757,0.0011466629,0.00016500775,0.000864681,0.0017776653,0.17077501],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999019,0.00002039071,0.000005403819,0.000020798134,0.000044203243,0.000007316954],"domain_scores_gemma":[0.9997726,0.00011185127,0.000014172569,0.000027389922,0.00005199013,0.000021960575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028538023,0.0008408958,0.0004892106,0.0010904964,0.00023754763,0.0019445237,0.0007579796,0.0008484275,0.019854598],"category_scores_gemma":[0.0007747658,0.00032541537,0.0004344752,0.00091789046,0.0006325675,0.0019898717,0.0006905319,0.0013344187,0.004996262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005561277,0.000019488712,0.0001407848,0.00067810796,0.000027479691,0.00036081814,0.00038674878,0.01178786,0.039965115,0.55253404,0.06207213,0.3319718],"study_design_scores_gemma":[0.000020333078,0.000034067576,0.0004425414,0.0002609934,0.000026545118,0.0016300906,0.00012633676,0.10092314,0.019971505,0.46344107,0.41306216,0.00006120905],"about_ca_topic_score_codex":0.0005584038,"about_ca_topic_score_gemma":0.0006109131,"teacher_disagreement_score":0.019854598,"about_ca_system_score_codex":0.00041508046,"about_ca_system_score_gemma":0.0004437262,"threshold_uncertainty_score":0.06642026},"labels":[],"label_agreement":null},{"id":"W2262750511","doi":"10.1161/str.43.suppl_1.a4033","title":"Abstract 4033: Structural Integrity of the Corticospinal Tract Correlated with the Degree of Hand Recovery in Pediatric Patients Following Stroke","year":2012,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network","funders":"","keywords":"Cerebral peduncle; Corticospinal tract; Diffusion MRI; Medicine; Fractional anisotropy; Tractography; Stroke (engine); Pyramidal tracts; Region of interest; Pediatric stroke; Nuclear medicine; Internal capsule; Ischemic stroke; Magnetic resonance imaging; Radiology; Anatomy; White matter; Cardiology; Ischemia","score_opus":0.05015838496368698,"score_gpt":0.30796162488125134,"score_spread":0.2578032399175644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2262750511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994337,0.00008510181,0.00007014312,0.000020271327,0.0000016672823,0.000003689888,0.00017995895,0.000004947967,0.00020049524],"genre_scores_gemma":[0.99934644,0.000117658135,0.000120787896,0.000007170132,0.000005393601,0.0000062328468,0.0002665968,0.0000027627275,0.00012701137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986506,0.000014695302,0.000020082494,0.000041419476,0.000029634299,0.00002908807],"domain_scores_gemma":[0.9992632,0.00010997849,0.0004370445,0.000027029355,0.00008258978,0.00008019738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027920134,0.0003319479,0.0003378691,0.0005947786,0.00027205682,0.00027722813,0.00019119999,0.00025631246,0.0035808503],"category_scores_gemma":[0.0014082206,0.000117299365,0.00016815946,0.00049173244,0.00031469736,0.00032419778,0.00019164571,0.0002280459,0.00044911954],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014077743,0.000022884791,0.99256027,0.000025188594,0.000015800018,0.0013105861,0.0001473233,0.00007378366,0.0023537301,0.000014934882,0.00011571635,0.0032190783],"study_design_scores_gemma":[0.00000411264,0.00014711572,0.9946359,0.0000066217062,0.00001698918,0.0042198948,0.000110363355,0.000086593805,0.0006018146,0.000018046501,0.000150003,0.0000025059733],"about_ca_topic_score_codex":0.0019764625,"about_ca_topic_score_gemma":0.0017741092,"teacher_disagreement_score":0.0035808503,"about_ca_system_score_codex":0.00017720954,"about_ca_system_score_gemma":0.00027989352,"threshold_uncertainty_score":0.011979103},"labels":[],"label_agreement":null},{"id":"W2263537162","doi":"10.1161/str.45.suppl_1.tmp118","title":"Abstract T MP118: Microinfarct Disruption of Cerebral White Matter: A Longitudinal Diffusion Tractography Analysis","year":2014,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Titan Medical (Canada)","funders":"","keywords":"Medicine; Diffusion MRI; Lesion; Fractional anisotropy; Region of interest; White matter; Nuclear medicine; Effective diffusion coefficient; Magnetic resonance imaging; Hyperintensity; Radiology; Pathology","score_opus":0.02616798143469206,"score_gpt":0.31649176128136297,"score_spread":0.2903237798466709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2263537162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854536,0.00028486009,0.010541917,0.00013024146,0.000013801463,0.00006285219,0.0021955885,0.00024171405,0.001075463],"genre_scores_gemma":[0.9894265,0.00010221998,0.0059162006,0.00001463045,0.000027032465,0.000044379878,0.002783258,0.000053886237,0.00163199],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990535,0.000017648197,0.000014630268,0.00002784868,0.000022687804,0.000011813585],"domain_scores_gemma":[0.99945587,0.00014439771,0.00014734866,0.000040020586,0.00011908819,0.00009322919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045103754,0.0003331447,0.00021636944,0.001009436,0.0002235538,0.00040841397,0.00022175699,0.0003732213,0.008871179],"category_scores_gemma":[0.0016247326,0.00009781002,0.00032942928,0.00045284998,0.0001571107,0.00023865113,0.00023141596,0.00019318369,0.0013100099],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026252905,0.00037427142,0.78418505,0.00032347598,0.00052040647,0.0048407773,0.0003146211,0.0035037608,0.10009993,0.00039013496,0.004889888,0.097932346],"study_design_scores_gemma":[0.00009404134,0.0007181789,0.9481582,0.00004784906,0.00023046295,0.012741346,0.00012882336,0.020354167,0.013476654,0.00047180895,0.0035546604,0.000023756565],"about_ca_topic_score_codex":0.0026961595,"about_ca_topic_score_gemma":0.0017031959,"teacher_disagreement_score":0.008871179,"about_ca_system_score_codex":0.00020382772,"about_ca_system_score_gemma":0.00032031906,"threshold_uncertainty_score":0.029677033},"labels":[],"label_agreement":null},{"id":"W2266699239","doi":"10.1093/cercor/bhv308","title":"The Corticocortical Structural Connectivity of the Human Insula","year":2015,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":312,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Hôpital Notre-Dame; Institut Universitaire de Gériatrie de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Insula; Neuroscience; Tractography; Posterior cingulate; Precuneus; Cytoarchitecture; Psychology; Supramarginal gyrus; Entorhinal cortex; Human brain; Functional magnetic resonance imaging; Diffusion MRI; Hippocampus; Magnetic resonance imaging; Medicine","score_opus":0.09143753737255118,"score_gpt":0.37280994357773595,"score_spread":0.2813724062051848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2266699239","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99119776,0.0004985169,0.0056911735,0.000052381743,0.000003895653,0.000013354204,0.0006315971,0.000044230874,0.0018670902],"genre_scores_gemma":[0.9975643,0.00012247544,0.0016522796,0.000007536428,0.000002524965,0.000007835801,0.00026626507,0.000008161638,0.0003686374],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99990964,0.000023203436,0.000003867335,0.00003975905,0.000014693743,0.000008897497],"domain_scores_gemma":[0.9998776,0.000055271685,0.000017398228,0.000025427726,0.000013262256,0.000011125344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012567188,0.00013945047,0.0001277749,0.00046120625,0.00017887235,0.00030905177,0.000077198354,0.00010370666,0.0021044381],"category_scores_gemma":[0.0007362394,0.00011867204,0.00010560626,0.00025760283,0.0003294519,0.0001686185,0.0001834827,0.00009333381,0.0002325633],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010978937,0.000115233684,0.32937402,0.00036869312,0.00082221767,0.00267349,0.004917514,0.0144412415,0.4203278,0.006648544,0.0028388621,0.21637455],"study_design_scores_gemma":[0.000011396846,0.000047054094,0.9785467,0.000011610994,0.000058825863,0.0021777023,0.0002396585,0.004422729,0.009468321,0.0021898113,0.0028057909,0.000020511996],"about_ca_topic_score_codex":0.008402407,"about_ca_topic_score_gemma":0.015393277,"teacher_disagreement_score":0.008402407,"about_ca_system_score_codex":0.0002054805,"about_ca_system_score_gemma":0.00022438406,"threshold_uncertainty_score":0.016707003},"labels":[],"label_agreement":null},{"id":"W2271674807","doi":"","title":"Microstructural white matter changes mediated age- related cognitive decline in the Montreal Cognitive Assessment (MoCA)","year":2016,"lang":"en","type":"article","venue":"Scientific Repository (Petra Christian University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Cognitive decline; White matter; Cognition; Diffusion MRI; Psychology; Effects of sleep deprivation on cognitive performance; Gerontology; Medicine; Cardiology; Internal medicine; Magnetic resonance imaging; Psychiatry; Cognitive impairment; Disease; Radiology; Dementia","score_opus":0.02178047862863062,"score_gpt":0.2782523756910521,"score_spread":0.25647189706242146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2271674807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973917,0.00044597493,0.00059479574,0.00008918963,0.0000122287765,0.000044643304,0.00037608616,0.00002251152,0.0010227261],"genre_scores_gemma":[0.99886096,0.00008904069,0.00033841963,0.000021062346,0.0000137435145,0.000017321847,0.00023501733,0.0000038157123,0.00042068932],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995679,0.00009532249,0.000028202761,0.00012395874,0.00010585193,0.000078685356],"domain_scores_gemma":[0.9972398,0.00060458423,0.0010545001,0.0003141794,0.00053622125,0.0002506618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015621054,0.0006942053,0.00038968207,0.00065262214,0.00034419695,0.0006142117,0.00061624026,0.000557469,0.0020347356],"category_scores_gemma":[0.0075632446,0.00029597688,0.00058159424,0.00048129517,0.000288787,0.00085820525,0.0008393647,0.0006798163,0.00021069314],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009656575,0.00024945047,0.97975165,0.000045691995,0.00043368706,0.00012605621,0.00046687198,0.00055161945,0.0021577878,0.00014376274,0.0003702113,0.01473762],"study_design_scores_gemma":[0.000003898577,0.00012382098,0.99901426,0.000004201712,0.00003644509,0.000034393026,0.000025629315,0.00047041802,0.00012539876,0.00007639374,0.000081999184,0.000003078034],"about_ca_topic_score_codex":0.05463287,"about_ca_topic_score_gemma":0.051122878,"teacher_disagreement_score":0.05463287,"about_ca_system_score_codex":0.0005107577,"about_ca_system_score_gemma":0.0008332474,"threshold_uncertainty_score":0.10862976},"labels":[],"label_agreement":null},{"id":"W2273155963","doi":"10.1007/978-3-642-38868-2_31","title":"Group-Wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Spherical harmonics; Correspondence problem; Computer science; Entropy (arrow of time); Minification; Algorithm; Artificial intelligence; Mathematics; Pattern recognition (psychology); Mathematical analysis; Mathematical optimization; Physics","score_opus":0.025309178946464592,"score_gpt":0.3097011722853255,"score_spread":0.2843919933388609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273155963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009945874,0.00006850739,0.9882825,0.00010532628,0.00001527094,0.000037019923,0.000089857036,0.00048323165,0.0009724683],"genre_scores_gemma":[0.3605219,0.00025164516,0.63217795,0.000107049294,0.00008829845,0.00020243335,0.0006446489,0.0012537169,0.004752364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995372,0.0001224955,0.000020962425,0.000111198766,0.00016031646,0.000047822665],"domain_scores_gemma":[0.999025,0.00046786547,0.00013024746,0.00014831494,0.00016326894,0.00006521282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089326646,0.00083199464,0.0011946942,0.0016245284,0.0005934649,0.0015187279,0.0013741134,0.0012718351,0.0042217956],"category_scores_gemma":[0.0035841577,0.00065658276,0.00125011,0.001451478,0.0009121039,0.001362801,0.0022386687,0.0012532795,0.0015285312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038997954,0.00015406884,0.001353951,0.0004078521,0.00020429453,0.00024351092,0.00031623428,0.45315653,0.034421418,0.055889234,0.007824202,0.44563878],"study_design_scores_gemma":[0.00001615126,0.000038994032,0.00031534347,0.000011794469,0.000016216607,0.000101141755,0.000032593663,0.96778095,0.004915403,0.025505941,0.0012480726,0.000017449274],"about_ca_topic_score_codex":0.0019005825,"about_ca_topic_score_gemma":0.0033471163,"teacher_disagreement_score":0.0042217956,"about_ca_system_score_codex":0.000587713,"about_ca_system_score_gemma":0.0014916671,"threshold_uncertainty_score":0.014123321},"labels":[],"label_agreement":null},{"id":"W2273771579","doi":"10.1089/brain.2015.0387","title":"Plasticity of Interhemispheric Temporal Lobe White Matter Pathways Due to Early Disruption of Corpus Callosum Development in Spina Bifida","year":2015,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Corpus callosum; Anterior commissure; White matter; Diffusion MRI; Neuroscience; Psychology; Anatomy; Fractional anisotropy; Cingulum (brain); Decussation; Temporal lobe; Commissure; Tractography; Biology; Epilepsy; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.07007561285151678,"score_gpt":0.3199479911161679,"score_spread":0.2498723782646511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273771579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996909,0.00005159126,0.0000915659,0.0000106072775,6.937339e-7,0.0000021087478,0.000033319924,0.000005937344,0.00011331793],"genre_scores_gemma":[0.99957913,0.000060910395,0.00021157433,0.0000037868615,0.0000010436995,0.0000029249932,0.000055772638,0.0000019685738,0.00008280007],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998909,0.000014546402,0.0000106813595,0.000033445544,0.00002738243,0.00002288095],"domain_scores_gemma":[0.99965143,0.000053154654,0.00018592278,0.000028087896,0.000024397135,0.00005704022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015406354,0.00037307118,0.00021991228,0.00091977057,0.00034824168,0.0002543307,0.00016313646,0.0002869635,0.00074272905],"category_scores_gemma":[0.00096687727,0.0002539992,0.00019225023,0.0004516457,0.0005631515,0.0001956581,0.00029559026,0.00029143758,0.00008364546],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000602539,0.00013249335,0.8285446,0.00006360485,0.00011046454,0.01611163,0.0011370421,0.00087456254,0.1220669,0.00021061316,0.00020973322,0.029935934],"study_design_scores_gemma":[0.0000035086903,0.000065518,0.9926721,0.0000036874635,0.000015345322,0.005175603,0.00011685361,0.0002305886,0.0015790998,0.0000653959,0.000068139314,0.0000042232127],"about_ca_topic_score_codex":0.011171945,"about_ca_topic_score_gemma":0.015643906,"teacher_disagreement_score":0.011171945,"about_ca_system_score_codex":0.0004939867,"about_ca_system_score_gemma":0.0003921586,"threshold_uncertainty_score":0.022213817},"labels":[],"label_agreement":null},{"id":"W2274502676","doi":"10.1038/tp.2015.216","title":"Conduct disorder in females is associated with reduced corpus callosum structural integrity independent of comorbid disorders and exposure to maltreatment","year":2016,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"VINNOVA; Vetenskapsrådet; Stockholms Läns Landsting; Karolinska Institutet; Stiftelsen för Strategisk Forskning","keywords":"Fractional anisotropy; Corpus callosum; White matter; Psychology; Diffusion MRI; Psychiatry; Internal medicine; Clinical psychology; Physiology; Medicine; Magnetic resonance imaging; Neuroscience","score_opus":0.05934138757850891,"score_gpt":0.3486620478158702,"score_spread":0.28932066023736125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274502676","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989365,0.00022931589,0.00005106083,0.000045578974,0.000005092566,0.0000033504798,0.00010040058,0.0000060852108,0.00062259455],"genre_scores_gemma":[0.99902475,0.00025018989,0.00009652001,0.00002234135,0.00001749175,0.000003837202,0.00016331514,0.000004126681,0.00041746322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998746,0.000020073037,0.0000095212845,0.000045112592,0.000022687238,0.000028053766],"domain_scores_gemma":[0.9993272,0.00004918599,0.00046016191,0.000028190405,0.000032956443,0.00010225737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013207018,0.0002828899,0.00021964553,0.00077389803,0.0003078804,0.00033280186,0.000088465924,0.00025111018,0.0024199756],"category_scores_gemma":[0.0006614065,0.00021658474,0.0001742824,0.0003480273,0.00027926976,0.00017504986,0.00023352918,0.00024314821,0.00027417328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033666307,0.000042751446,0.98628265,0.000017573977,0.000044520908,0.0011255319,0.00010545061,0.000023962093,0.0064543276,0.000035052002,0.00016971157,0.0053618005],"study_design_scores_gemma":[0.0000021881433,0.00006489882,0.99659085,0.000004029688,0.000008426703,0.0030050252,0.00007127877,0.000021211883,0.00010556928,0.000011916968,0.000113302085,0.0000012327454],"about_ca_topic_score_codex":0.002933211,"about_ca_topic_score_gemma":0.0058373623,"teacher_disagreement_score":0.002933211,"about_ca_system_score_codex":0.00017275463,"about_ca_system_score_gemma":0.00015033587,"threshold_uncertainty_score":0.008095622},"labels":[],"label_agreement":null},{"id":"W2274948889","doi":"10.1001/jamapsychiatry.2015.3375","title":"Mediation of Developmental Risk Factors for Psychosis by White Matter Microstructure in Young Adults With Psychotic Experiences","year":2016,"lang":"en","type":"article","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Medical Research Council; Cardiff University; Wellcome Trust","keywords":"Psychosis; Psychology; Young adult; White matter; Mediation; Developmental psychology; Psychiatry; Clinical psychology; Medicine; Magnetic resonance imaging; Sociology","score_opus":0.009802066465755217,"score_gpt":0.2799803194094808,"score_spread":0.2701782529437256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274948889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999749,0.00006975365,0.000034897574,0.000029737299,0.0000012120529,0.0000035663986,0.00003101011,0.0000012865399,0.000079437836],"genre_scores_gemma":[0.9998086,0.000040513965,0.000055998444,0.00000614912,0.0000014341109,0.000003900129,0.000041356358,5.832025e-7,0.00004146496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995846,0.00014915697,0.000038052203,0.00008518344,0.00007248762,0.00007053771],"domain_scores_gemma":[0.9983968,0.00036730777,0.0008294688,0.00010581748,0.00009737836,0.00020328422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009658663,0.00042721545,0.00024373266,0.00058312924,0.0005146693,0.00072826765,0.0004317741,0.0004794791,0.0016009538],"category_scores_gemma":[0.0057808496,0.000509973,0.00040625074,0.0003835515,0.0005211247,0.0006305841,0.0008165844,0.0005088785,0.00013461152],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006848574,0.000031721574,0.9978369,0.00000603106,0.00002214438,0.00024731294,0.00048206927,0.000020112027,0.00025855197,0.00003549099,0.000024357727,0.00096676947],"study_design_scores_gemma":[0.000004478687,0.00007839712,0.99883395,0.000008396433,0.000013807224,0.00033372885,0.0004778959,0.000112981026,0.000052477455,0.000054061285,0.000027520213,0.000002368684],"about_ca_topic_score_codex":0.008042487,"about_ca_topic_score_gemma":0.010462331,"teacher_disagreement_score":0.008042487,"about_ca_system_score_codex":0.00034507635,"about_ca_system_score_gemma":0.0004885673,"threshold_uncertainty_score":0.01599133},"labels":[],"label_agreement":null},{"id":"W2278001415","doi":"10.3389/fnana.2016.00012","title":"A Digital Atlas of Middle to Large Brain Vessels and Their Relation to Cortical and Subcortical Structures","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Universität Ulm; Bundesministerium für Bildung und Forschung","keywords":"Neuroscience; Cortex (anatomy); Temporal lobe; Cytoarchitecture; Anatomy; Cerebral cortex; Neuroimaging; Lobe; Psychology; Medicine","score_opus":0.021203535322260755,"score_gpt":0.2903973633769404,"score_spread":0.2691938280546796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278001415","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20415612,0.0033926412,0.5239335,0.0014777092,0.00055642816,0.0015797754,0.10602287,0.009986826,0.14889413],"genre_scores_gemma":[0.4414862,0.0033455468,0.48100638,0.00030185943,0.00014903388,0.001544286,0.028303154,0.0015381819,0.042325307],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998561,0.000026502918,0.000016366777,0.000030514071,0.00004673702,0.00002374207],"domain_scores_gemma":[0.9997073,0.00009311756,0.000036493264,0.00006073206,0.000077544704,0.000024816445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003063558,0.00048518798,0.00027740662,0.0040656114,0.0005177366,0.001333476,0.0004739388,0.00041698435,0.02650224],"category_scores_gemma":[0.0009776535,0.00030345673,0.00030725144,0.0032693024,0.00047041615,0.00042263075,0.00062678946,0.0006269326,0.0038894557],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010941875,0.00021851719,0.025612954,0.0015988606,0.0002729957,0.0023508566,0.0027458346,0.017938249,0.11637942,0.051523678,0.1524042,0.62786025],"study_design_scores_gemma":[0.00012923428,0.00033377513,0.24011807,0.00023525719,0.00021920477,0.012593525,0.0011645459,0.021769674,0.017591394,0.02226536,0.6833695,0.00021049498],"about_ca_topic_score_codex":0.013445106,"about_ca_topic_score_gemma":0.033217825,"teacher_disagreement_score":0.02650224,"about_ca_system_score_codex":0.00050173065,"about_ca_system_score_gemma":0.0015581562,"threshold_uncertainty_score":0.08865887},"labels":[],"label_agreement":null},{"id":"W2278559975","doi":"10.3389/fnana.2016.00009","title":"Maturation Along White Matter Tracts in Human Brain Using a Diffusion Tensor Surface Model Tract-Specific Analysis","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"White matter; Fasciculus; Diffusion MRI; Corpus callosum; Corticospinal tract; Superior longitudinal fasciculus; Fractional anisotropy; Uncinate fasciculus; Anatomy; Neuroscience; Pyramidal tracts; Inferior longitudinal fasciculus; Biology; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.03785058414571119,"score_gpt":0.3192626039099383,"score_spread":0.28141201976422714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278559975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6964308,0.0003108786,0.29999518,0.0001225763,0.000014268741,0.00014516509,0.0011611596,0.0009608759,0.0008591323],"genre_scores_gemma":[0.8644221,0.000391256,0.13160303,0.000015357427,0.000011819444,0.0001667506,0.001868366,0.00013488212,0.0013863745],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99989974,0.000025307785,0.000007857853,0.000041658328,0.000017412938,0.000007993542],"domain_scores_gemma":[0.9998128,0.00005733545,0.00004708865,0.000031443346,0.000041273393,0.0000101932155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005250843,0.00040597472,0.00033815138,0.0010957965,0.00018092421,0.0005472095,0.00021686907,0.00035894732,0.00097360084],"category_scores_gemma":[0.0011042621,0.00021941903,0.001103242,0.00079998944,0.00019797834,0.0003655564,0.00030865657,0.00023878996,0.0003534612],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005329452,0.00014232352,0.14078782,0.00032114415,0.0008640944,0.0011856138,0.0013370261,0.512419,0.11667199,0.0073067686,0.0023813404,0.21605001],"study_design_scores_gemma":[0.000010893311,0.00015370171,0.057064284,0.000019887093,0.00007876367,0.0005095868,0.000112289825,0.9336593,0.004100347,0.0025558437,0.0017032296,0.000031817028],"about_ca_topic_score_codex":0.009500464,"about_ca_topic_score_gemma":0.008927638,"teacher_disagreement_score":0.009500464,"about_ca_system_score_codex":0.00034538851,"about_ca_system_score_gemma":0.00059892534,"threshold_uncertainty_score":0.018890321},"labels":[],"label_agreement":null},{"id":"W2279592394","doi":"10.1371/journal.pone.0113081.t005","title":"Tract-based spatial statistics results showing regions of white matter integrity decrease in each of the patient groups compared with Controls&lt;sup&gt;a&lt;/sup&gt;","year":2015,"lang":"en","type":"paratext","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Statistics; Medicine; Biology; Mathematics; Magnetic resonance imaging","score_opus":0.08369833103386917,"score_gpt":0.32193233914679176,"score_spread":0.23823400811292259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2279592394","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3665545,0.0028117024,0.07942088,0.002025906,0.0012078034,0.00086667464,0.47238287,0.016288657,0.05844103],"genre_scores_gemma":[0.7468898,0.0014552182,0.05827084,0.00049415644,0.00023063553,0.0013932202,0.12570092,0.0069081536,0.05865707],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99968886,0.000035537738,0.000042767388,0.00011174861,0.00008429212,0.000036780068],"domain_scores_gemma":[0.9989697,0.00038804128,0.00022181142,0.00017760947,0.00015121321,0.00009159212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005530622,0.0010977199,0.00076300214,0.0016377852,0.0005874688,0.0007451817,0.00067665684,0.0007598816,0.20404452],"category_scores_gemma":[0.0030104395,0.0003552076,0.00074712426,0.0011908181,0.00055578497,0.0010794197,0.0007515788,0.000657622,0.01602302],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009506861,0.0006511153,0.05152586,0.0043188566,0.0028213183,0.003151619,0.00207572,0.008054479,0.1638212,0.0091490345,0.54150105,0.20342286],"study_design_scores_gemma":[0.0012608172,0.0018310593,0.7641962,0.00091908406,0.001685751,0.014516048,0.0015413287,0.022238888,0.054350946,0.025052166,0.11204401,0.00036367885],"about_ca_topic_score_codex":0.0079401005,"about_ca_topic_score_gemma":0.011029829,"teacher_disagreement_score":0.20404452,"about_ca_system_score_codex":0.00044153337,"about_ca_system_score_gemma":0.00090162107,"threshold_uncertainty_score":0.6825969},"labels":[],"label_agreement":null},{"id":"W2283128416","doi":"10.1093/cercor/bhv180","title":"Altered Human Memory Modification in the Presence of Normal Consolidation","year":2015,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Center for Neuroscience and Regenerative Medicine; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Israel National Road Safety Authority","keywords":"Memory consolidation; Neuroscience; Consolidation (business); Engram; Dissociation (chemistry); Human memory; Psychology; Human brain; Cognition; Hippocampus; Chemistry","score_opus":0.16406319875743555,"score_gpt":0.39272486988972,"score_spread":0.22866167113228444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283128416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991126,0.0004212405,0.0069123968,0.00006582134,0.000013272287,0.000010459249,0.000115534705,0.00007695625,0.0012583777],"genre_scores_gemma":[0.9984693,0.00009720496,0.0011059316,0.00001414381,0.0000025874026,0.0000047792414,0.00007550848,0.000006629703,0.00022386786],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99988127,0.000019115576,0.000011493243,0.00004055522,0.000030437295,0.000017251146],"domain_scores_gemma":[0.99956936,0.000072142866,0.00013534723,0.00014420546,0.000041217132,0.00003773095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025237387,0.00020948885,0.00023358152,0.00036885944,0.00011682963,0.00040405814,0.00026080685,0.00022430171,0.0013396625],"category_scores_gemma":[0.0011252096,0.00011382796,0.00010868829,0.00014802834,0.00077099266,0.00044222083,0.00032548577,0.00032363203,0.0001710552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012926977,0.00018897414,0.032093916,0.00020530014,0.00023510565,0.00083021214,0.0006214498,0.0031196943,0.9022313,0.0033082755,0.0005773706,0.055295747],"study_design_scores_gemma":[0.00006226967,0.0030685435,0.37940606,0.000061724655,0.00025001395,0.006463959,0.0004189874,0.017217604,0.56760705,0.018284116,0.007085664,0.000073991505],"about_ca_topic_score_codex":0.0008733661,"about_ca_topic_score_gemma":0.0010077783,"teacher_disagreement_score":0.0013396625,"about_ca_system_score_codex":0.0001873144,"about_ca_system_score_gemma":0.00017009446,"threshold_uncertainty_score":0.0044816732},"labels":[],"label_agreement":null},{"id":"W2284206694","doi":"10.1016/j.media.2016.01.002","title":"The application of a new sampling theorem for non-bandlimited signals on the sphere: Improving the recovery of crossing fibers for low b-value acquisitions","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; Washington University in St. Louis","keywords":"Deconvolution; Bandlimiting; Sampling (signal processing); Mathematics; Algorithm; Convolution (computer science); Kernel (algebra); Nonuniform sampling; Computer science; Mathematical analysis; Fourier transform; Artificial intelligence; Computer vision; Discrete mathematics; Artificial neural network","score_opus":0.038154558591240596,"score_gpt":0.36350859537872743,"score_spread":0.3253540367874868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284206694","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026750013,0.00011745684,0.99653363,0.00008407665,0.000044303,0.000011273798,0.00001682019,0.000123473,0.0003938274],"genre_scores_gemma":[0.07865921,0.0006766258,0.9175039,0.00019450655,0.0002469323,0.000059450038,0.0001508461,0.00033533006,0.00217323],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895215,0.00036380126,0.0000703234,0.00016994041,0.00039392983,0.000049760245],"domain_scores_gemma":[0.9959182,0.002263136,0.00026367605,0.0006213771,0.0007117549,0.0002218138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026852207,0.0010528057,0.00069146574,0.0011184366,0.00042786894,0.0014388093,0.0013068719,0.0012096985,0.002901818],"category_scores_gemma":[0.009422999,0.00037177705,0.0007443931,0.00095403247,0.0013475406,0.0026810851,0.0017646378,0.001478216,0.0010611174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072338636,0.00023225867,0.0017051547,0.0005452962,0.00015062802,0.00044930945,0.00046163664,0.117523335,0.19964983,0.18905754,0.007440135,0.4820615],"study_design_scores_gemma":[0.000022981583,0.00012629111,0.00049190054,0.00002025145,0.000020794943,0.0004959061,0.000021916676,0.95121497,0.022619538,0.020112544,0.004812745,0.000040145853],"about_ca_topic_score_codex":0.0012010994,"about_ca_topic_score_gemma":0.0013065689,"teacher_disagreement_score":0.002901818,"about_ca_system_score_codex":0.0004822088,"about_ca_system_score_gemma":0.00089664327,"threshold_uncertainty_score":0.014200985},"labels":[],"label_agreement":null},{"id":"W2284226518","doi":"10.1007/s10803-016-2744-2","title":"Widespread White Matter Differences in Children and Adolescents with Autism Spectrum Disorder","year":2016,"lang":"en","type":"article","venue":"Journal of Autism and Developmental Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Institute for Christian Studies; University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Sick Kids Foundation","keywords":"Corpus callosum; Fractional anisotropy; Autism spectrum disorder; Psychology; Autism; White matter; Diffusion MRI; Neurodevelopmental disorder; Audiology; Developmental psychology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.009518566486734784,"score_gpt":0.24509901106574214,"score_spread":0.23558044457900734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284226518","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957484,0.000092919305,0.000022277929,0.000022404958,0.0000022246452,0.000002155524,0.000048273065,0.0000017286491,0.00023318622],"genre_scores_gemma":[0.9995347,0.00010296623,0.00006191412,0.00002102139,0.000003897105,0.0000050013864,0.000092972834,0.0000029504608,0.00017457196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998399,0.000019849354,0.000020011674,0.000052498453,0.000033181168,0.000034578457],"domain_scores_gemma":[0.99939716,0.00012233533,0.00027949343,0.000020750953,0.00007054849,0.00010977097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026028792,0.00035218854,0.00026216533,0.0011940076,0.00042487145,0.0005045009,0.00025287317,0.000431137,0.0018328924],"category_scores_gemma":[0.0012349819,0.00023997088,0.00019798325,0.0005383521,0.00052488147,0.00047793105,0.00052351016,0.0003892757,0.00019620117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002371563,0.00008609916,0.98196584,0.000037961545,0.00007356385,0.0016965024,0.0013727157,0.000071856804,0.009237774,0.00015505461,0.00017395112,0.004891489],"study_design_scores_gemma":[0.0000024432838,0.000029685463,0.9982918,0.0000029600724,0.00000874308,0.0009430049,0.00045888664,0.000023044791,0.00013907478,0.000035414974,0.000063650434,0.0000012527341],"about_ca_topic_score_codex":0.0069628824,"about_ca_topic_score_gemma":0.014442755,"teacher_disagreement_score":0.0069628824,"about_ca_system_score_codex":0.0003114069,"about_ca_system_score_gemma":0.00025712384,"threshold_uncertainty_score":0.0138447285},"labels":[],"label_agreement":null},{"id":"W2288592143","doi":"10.1007/s11682-015-9495-0","title":"Correlating quantitative tractography at 3T MRI and cognitive tests in healthy older adults","year":2015,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; Queen's University; University of Toronto","funders":"","keywords":"Fractional anisotropy; Stroop effect; Corpus callosum; Psychology; White matter; Tractography; Diffusion MRI; Wechsler Adult Intelligence Scale; Cerebral peduncle; Neuroscience; Audiology; Cognition; Medicine; Magnetic resonance imaging; Internal capsule; Radiology","score_opus":0.0685035506087787,"score_gpt":0.3993114726856923,"score_spread":0.33080792207691356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288592143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99949324,0.00012577503,0.0000778066,0.000018406865,0.000002277967,0.0000033117526,0.00007806749,0.0000027562587,0.00019836711],"genre_scores_gemma":[0.9995722,0.00006943763,0.0000932123,0.0000145628455,0.0000070633528,0.000003117691,0.000085649226,0.0000015071339,0.00015324132],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985445,0.000025476364,0.000024522678,0.00003931995,0.00002338061,0.00003277947],"domain_scores_gemma":[0.99902105,0.00024289884,0.00038486475,0.00005814724,0.00018115377,0.00011187009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049449294,0.00045394927,0.00037163758,0.00094906514,0.00031760355,0.00069086766,0.00021292552,0.0007183285,0.0008792493],"category_scores_gemma":[0.0036174378,0.00020879427,0.0002258018,0.0006212282,0.00038927604,0.000721436,0.00036048557,0.00028667718,0.00020163761],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004912881,0.00010882279,0.9918139,0.000020525069,0.00008808083,0.00063419255,0.0003812062,0.00018530119,0.0019843928,0.000047979003,0.00010566666,0.0041386466],"study_design_scores_gemma":[0.0000059158747,0.00017440593,0.99858886,0.0000047729177,0.000029580899,0.00040466624,0.00018164392,0.00029340584,0.00015364577,0.00011325683,0.000045960685,0.000003841154],"about_ca_topic_score_codex":0.010732332,"about_ca_topic_score_gemma":0.018434137,"teacher_disagreement_score":0.010732332,"about_ca_system_score_codex":0.00029032494,"about_ca_system_score_gemma":0.00033577578,"threshold_uncertainty_score":0.021339715},"labels":[],"label_agreement":null},{"id":"W2290984633","doi":"10.1093/schbul/sbv180","title":"Limited Evidence for Association of Genome-Wide Schizophrenia Risk Variants on Cortical Neuroimaging Phenotypes","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Corpus callosum; White matter; Neuroimaging; Splenium; Schizophrenia (object-oriented programming); Fractional anisotropy; Genome-wide association study; Neuroscience; Genetic association; Diffusion MRI; Single-nucleotide polymorphism; Psychology; Biology; Genetics; Medicine; Magnetic resonance imaging; Psychiatry; Genotype; Gene","score_opus":0.08618003780891856,"score_gpt":0.3389441491555898,"score_spread":0.2527641113466712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290984633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99018455,0.0039396016,0.0016982988,0.00065117475,0.000028657823,0.000016212962,0.001610165,0.000039501163,0.0018317417],"genre_scores_gemma":[0.99782073,0.0007489916,0.00059025054,0.0001847696,0.000029073146,0.000012671403,0.00051237445,0.00001540799,0.00008573683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99746084,0.0006358226,0.00042942286,0.00086576876,0.0004282816,0.00017981332],"domain_scores_gemma":[0.9802151,0.012008132,0.004186047,0.0018205977,0.0011674889,0.0006026481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043129222,0.0006553262,0.0006032225,0.0011896606,0.00040635688,0.0010575827,0.0009327763,0.001113628,0.0053756856],"category_scores_gemma":[0.011953228,0.00027279573,0.000984761,0.001173673,0.0011601781,0.00045651168,0.000864196,0.0005624107,0.00041750874],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010892316,0.00003643554,0.9690531,0.0004892935,0.0026623504,0.00092298735,0.0004133021,0.0003967076,0.010458393,0.00028205794,0.00038668167,0.013809398],"study_design_scores_gemma":[0.00003497434,0.00016156831,0.99481297,0.00012693914,0.0008668008,0.0014717825,0.00016716366,0.00022459624,0.0008724111,0.0005570175,0.0006893279,0.000014293854],"about_ca_topic_score_codex":0.0030638217,"about_ca_topic_score_gemma":0.005067128,"teacher_disagreement_score":0.0053756856,"about_ca_system_score_codex":0.00022913612,"about_ca_system_score_gemma":0.0005304969,"threshold_uncertainty_score":0.022809148},"labels":[],"label_agreement":null},{"id":"W2295505655","doi":"10.1007/978-3-319-27929-9_6","title":"A Graph Based Classification Method for Multiple Sclerosis Clinical Forms Using Support Vector Machine","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche","keywords":"Support vector machine; Computer science; Diffusion MRI; Pattern recognition (psychology); Artificial intelligence; Multiple sclerosis; Graph theory; Graph; Artificial neural network; Kernel (algebra); Machine learning; Data mining; Theoretical computer science; Magnetic resonance imaging; Mathematics; Medicine","score_opus":0.3312701000338951,"score_gpt":0.4433715667412938,"score_spread":0.11210146670739868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295505655","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048541907,0.00094924535,0.9419299,0.00055586046,0.0003522096,0.00024268268,0.0013344353,0.0040148813,0.0020788743],"genre_scores_gemma":[0.31198838,0.00069282,0.67749935,0.00022641229,0.00023391192,0.00033444597,0.0031064476,0.00024038956,0.0056778924],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996213,0.000082422855,0.000038795704,0.00008878443,0.00013268451,0.00003601166],"domain_scores_gemma":[0.99901724,0.00047457562,0.00006078241,0.0000759289,0.00032653954,0.000044975575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006333164,0.00061760255,0.0007027227,0.0023452144,0.00041706284,0.00085773476,0.0011054308,0.0008716011,0.0038534245],"category_scores_gemma":[0.0020476962,0.00017752714,0.0009096252,0.0016113879,0.00017352826,0.0006763641,0.00063393934,0.00097427913,0.002014096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002282531,0.0001316185,0.0035463425,0.00008741591,0.000080179794,0.00014268424,0.000048667553,0.015940327,0.0071267495,0.0016977324,0.0098541,0.9611159],"study_design_scores_gemma":[0.000029087621,0.0001185746,0.0037500937,0.000034346496,0.00007515742,0.00034589693,0.000086816246,0.97965837,0.00476172,0.0066670333,0.0044403267,0.000032517797],"about_ca_topic_score_codex":0.0038822114,"about_ca_topic_score_gemma":0.00441403,"teacher_disagreement_score":0.0038822114,"about_ca_system_score_codex":0.00031401496,"about_ca_system_score_gemma":0.00052998087,"threshold_uncertainty_score":0.012890935},"labels":[],"label_agreement":null},{"id":"W2296626252","doi":"10.14288/1.0066854","title":"Myelin water imaging : development at 3.0T, application to the study of multiple sclerosis, and comparison to diffusion tensor imaging","year":2008,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; Multiple sclerosis; Diffusion imaging; Myelin; Neuroscience; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Psychology; Physics; Radiology; Central nervous system","score_opus":0.03655666054394428,"score_gpt":0.24008213335775522,"score_spread":0.20352547281381095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296626252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35932988,0.029768908,0.6000895,0.0018928212,0.00027301017,0.0007198583,0.0008944986,0.003107086,0.0039244746],"genre_scores_gemma":[0.29751223,0.0155076245,0.68258977,0.00034418525,0.00015944519,0.00058721175,0.00065692136,0.00065241614,0.0019902303],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996014,0.00015796567,0.000021458192,0.00007983863,0.000107271626,0.000032061285],"domain_scores_gemma":[0.99901795,0.00026588087,0.000121196514,0.00009904769,0.00040354635,0.00009227498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051474557,0.00072813785,0.0006117588,0.001220722,0.00031387102,0.0009312402,0.00091945945,0.0010779405,0.0008972833],"category_scores_gemma":[0.003377993,0.000670006,0.00041784023,0.0010980357,0.0006273486,0.0012789872,0.0007263764,0.0008058494,0.0005166592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010674974,0.00018323123,0.005046977,0.0007858414,0.000077984376,0.0007212813,0.00061326066,0.0053172056,0.69695073,0.0025511172,0.0014080071,0.28527686],"study_design_scores_gemma":[0.00029590327,0.0046100696,0.057695355,0.000397489,0.00032750197,0.0116840275,0.000643477,0.08515082,0.7755075,0.007850661,0.055483013,0.00035420238],"about_ca_topic_score_codex":0.0022320864,"about_ca_topic_score_gemma":0.0022523906,"teacher_disagreement_score":0.0051474557,"about_ca_system_score_codex":0.00039438685,"about_ca_system_score_gemma":0.0009527149,"threshold_uncertainty_score":0.027222693},"labels":[],"label_agreement":null},{"id":"W2298552625","doi":"10.1016/j.media.2016.02.010","title":"Non Local Spatial and Angular Matching: Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Noise reduction; Noise (video); Computer science; Artificial intelligence; Rician fading; Spatial analysis; Pattern recognition (psychology); Gaussian noise; Noise measurement; Algorithm; Computer vision; Mathematics; Statistics","score_opus":0.029768578420550303,"score_gpt":0.3345688220668706,"score_spread":0.3048002436463203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2298552625","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01247687,0.0002414003,0.985246,0.00028488322,0.00003871056,0.000030797153,0.00010004806,0.000509732,0.0010715921],"genre_scores_gemma":[0.1261269,0.0007264575,0.86853564,0.00024630586,0.0000819096,0.00006388441,0.00043796748,0.00040860742,0.003372275],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993641,0.00015244294,0.000052315376,0.00011997286,0.0002628194,0.00004835429],"domain_scores_gemma":[0.99829143,0.00063264644,0.00019176469,0.00051402993,0.00029123516,0.00007894919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017545335,0.0007583563,0.00076579634,0.0009896453,0.00034337526,0.0015967587,0.00111501,0.0012928402,0.0028132815],"category_scores_gemma":[0.0063342107,0.00060917693,0.0006144842,0.0016060905,0.0006395153,0.0018514908,0.0019313726,0.0014231565,0.0012102044],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064219494,0.00027924977,0.0022444634,0.0006271286,0.00023223329,0.0002581144,0.00036170366,0.0766334,0.34697482,0.034440383,0.0065868683,0.5307194],"study_design_scores_gemma":[0.000048128186,0.00012076139,0.002169264,0.00005107569,0.00009838901,0.00085659063,0.00009562902,0.796645,0.15708824,0.029001692,0.013756804,0.00006845916],"about_ca_topic_score_codex":0.0015234983,"about_ca_topic_score_gemma":0.003385432,"teacher_disagreement_score":0.0028132815,"about_ca_system_score_codex":0.00033189665,"about_ca_system_score_gemma":0.0010575675,"threshold_uncertainty_score":0.009411335},"labels":[],"label_agreement":null},{"id":"W2303032580","doi":"10.3389/fnint.2016.00015","title":"Pre-Surgical Integration of fMRI and DTI of the Sensorimotor System in Transcortical Resection of a High-Grade Insular Astrocytoma","year":2016,"lang":"en","type":"article","venue":"Frontiers in Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Saskatchewan Health Research Foundation","keywords":"Astrocytoma; Internal capsule; Functional magnetic resonance imaging; Diffusion MRI; Middle frontal gyrus; Magnetic resonance imaging; Psychology; Medicine; Neuroscience; White matter; Radiology; Glioma","score_opus":0.03135172242304888,"score_gpt":0.31621968094846553,"score_spread":0.28486795852541663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2303032580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991046,0.0006056082,0.0048740013,0.00046546207,0.000018779636,0.000036612193,0.00005318347,0.0000538627,0.0028463386],"genre_scores_gemma":[0.9972989,0.0003237911,0.0019072883,0.00008586051,0.000019047813,0.0000072775842,0.000035135574,0.0000086907285,0.0003141417],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.9999403,0.000009476641,0.0000064306364,0.000012460493,0.000012887322,0.000018433215],"domain_scores_gemma":[0.99988663,0.000035330064,0.000023871595,0.000009853553,0.000013609202,0.000030739116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012659813,0.00036361313,0.00019943836,0.00052183995,0.00028536338,0.00021792475,0.00017486984,0.00051078614,0.0004333026],"category_scores_gemma":[0.00049007544,0.00018188368,0.0002162756,0.00014657684,0.0004356721,0.00025162927,0.00020365734,0.00047468435,0.00014495483],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049518247,0.00018918408,0.054485824,0.00016600812,0.00006769701,0.77472,0.0007582852,0.0018573995,0.12105822,0.00033672908,0.00054828543,0.045317177],"study_design_scores_gemma":[0.000027871567,0.00080133433,0.12970096,0.00005173154,0.00016544387,0.80881137,0.00048095535,0.006939565,0.049218766,0.0009161772,0.0028257826,0.000060089005],"about_ca_topic_score_codex":0.0018390811,"about_ca_topic_score_gemma":0.0076645766,"teacher_disagreement_score":0.0018390811,"about_ca_system_score_codex":0.00029343017,"about_ca_system_score_gemma":0.00041321368,"threshold_uncertainty_score":0.0036568046},"labels":[],"label_agreement":null},{"id":"W2308601713","doi":"10.1016/j.neuroimage.2016.03.042","title":"Complex interplay between brain function and structure during cerebral amyloidosis in APP transgenic mouse strains revealed by multi-parametric MRI comparison","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Genetically modified mouse; Cerebral amyloid angiopathy; Pathology; Amyloid (mycology); Neuroscience; Parenchyma; Population; Perivascular space; Amyloidosis; Intracellular; Neuroimaging; Amyloid precursor protein; Biology; Transgene; Alzheimer's disease; Medicine; Cell biology; Disease; Gene; Biochemistry","score_opus":0.05762622994255563,"score_gpt":0.3560699535394426,"score_spread":0.298443723596887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2308601713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963825,0.00021675973,0.0029141337,0.00003443267,0.000005806154,0.0000064366222,0.00013335027,0.000041785137,0.00026473825],"genre_scores_gemma":[0.99629825,0.00026063024,0.0022669076,0.000033217042,0.000007747091,0.000037007874,0.00025846073,0.000077833,0.0007599413],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980146,0.000029309818,0.000021015114,0.000055778448,0.000047016325,0.000045587083],"domain_scores_gemma":[0.9995364,0.000069367234,0.0002132354,0.00005388135,0.0000613684,0.000065745706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044274173,0.00040508865,0.00031957112,0.001165872,0.0002038695,0.00045983773,0.0003010038,0.0003940099,0.0007189425],"category_scores_gemma":[0.0006203041,0.00033086893,0.00031857486,0.00027767653,0.00046183183,0.00048305254,0.00036214374,0.0007129401,0.000110083594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036370964,0.00003247298,0.0019952029,0.000014720179,0.000028325248,0.00023415068,0.000065894805,0.00008238061,0.99524873,0.00010871679,0.000030061597,0.0017954942],"study_design_scores_gemma":[0.000032094267,0.00066698244,0.31605193,0.000020910684,0.00026004913,0.0057219956,0.00039306786,0.0034902215,0.6711155,0.0010653175,0.0011153684,0.00006652428],"about_ca_topic_score_codex":0.0004999833,"about_ca_topic_score_gemma":0.0007463038,"teacher_disagreement_score":0.001165872,"about_ca_system_score_codex":0.00016962831,"about_ca_system_score_gemma":0.00011351308,"threshold_uncertainty_score":0.002405107},"labels":[],"label_agreement":null},{"id":"W2309119811","doi":"10.3171/2016.1.peds15580","title":"Vulnerability of white matter to insult during childhood: evidence from patients treated for medulloblastoma","year":2016,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research; Pediatric Oncology Group","funders":"Brain Tumour Research; Hospital for Sick Children; Garron Family Cancer Centre; Genome British Columbia; Fondation Brain Canada; Pediatric Oncology Group of Ontario; Children's Hospital Foundation; Canadian Institutes of Health Research; Genome Canada","keywords":"Medicine; Fractional anisotropy; Medulloblastoma; White matter; Nuclear medicine; Diffusion MRI; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.04148133429304946,"score_gpt":0.3146477158787259,"score_spread":0.27316638158567647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2309119811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992187,0.00044611725,0.000029631528,0.000023407318,0.0000014733253,0.0000035242897,0.00008151908,0.0000012075137,0.00019453885],"genre_scores_gemma":[0.99944836,0.00035741134,0.00004436158,0.000011173093,0.00000420598,0.0000026729253,0.000102335034,0.0000011717103,0.000028368215],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996934,0.00008565414,0.00003791152,0.000084811305,0.000052956464,0.00004537034],"domain_scores_gemma":[0.998248,0.00035420703,0.0010547031,0.0001054581,0.000103149265,0.00013445273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036621702,0.0001990618,0.00029271265,0.00069001253,0.00044644196,0.0003794274,0.0002294531,0.00023082254,0.0009668137],"category_scores_gemma":[0.0027130884,0.00017059504,0.00033012408,0.00077669363,0.0005642301,0.00030343648,0.00039430487,0.00021296428,0.00012906163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025029093,0.000023687906,0.99655294,0.000025757769,0.00008241849,0.00022229705,0.00025270713,0.000032850603,0.0006472969,0.000013299831,0.00003741527,0.0018590839],"study_design_scores_gemma":[0.00000698443,0.00013856294,0.99840206,0.000009801901,0.000051685973,0.00080326735,0.00025214645,0.000024634715,0.00015754667,0.000013453292,0.00013763184,0.0000022057043],"about_ca_topic_score_codex":0.006752648,"about_ca_topic_score_gemma":0.007971602,"teacher_disagreement_score":0.006752648,"about_ca_system_score_codex":0.00027463527,"about_ca_system_score_gemma":0.00032542186,"threshold_uncertainty_score":0.0134266615},"labels":[],"label_agreement":null},{"id":"W2314099791","doi":"10.1177/0271678x15606718","title":"Exploring the use of shape and texture descriptors of positron emission tomography tracer distribution in imaging studies of neurodegenerative disease","year":2015,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Positron emission tomography; Artificial intelligence; Pattern recognition (psychology); Nuclear medicine; Raclopride; Parkinson's disease; Mathematics; Computer science; Biological system; Medicine; Striatum; Disease; Pathology; Dopamine; Internal medicine; Biology","score_opus":0.23844535160093902,"score_gpt":0.34282599972479105,"score_spread":0.10438064812385203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314099791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8434261,0.001971056,0.15255517,0.00020329404,0.000023484634,0.00009573715,0.00049512566,0.00022331913,0.0010066392],"genre_scores_gemma":[0.9476677,0.0008265652,0.050904967,0.000031018328,0.00002625211,0.000038374914,0.0003155742,0.000033288154,0.00015625231],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992686,0.0003646172,0.00004727341,0.00010686247,0.00016777679,0.00004493514],"domain_scores_gemma":[0.99663514,0.0021348435,0.00061904517,0.00024228591,0.00026737803,0.00010135236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021815484,0.00068574946,0.0007864217,0.002629002,0.00017250478,0.0013090277,0.0003427228,0.000581768,0.0003355073],"category_scores_gemma":[0.007858513,0.00021607116,0.0005583394,0.002118403,0.00064211554,0.00090815907,0.00047697077,0.00037285427,0.00013475459],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020372507,0.00032676125,0.2252541,0.0007149732,0.00069961813,0.000538758,0.0004794448,0.08511177,0.21272554,0.0027950185,0.0005986565,0.46871814],"study_design_scores_gemma":[0.000069390946,0.0017764564,0.36492714,0.0000874394,0.00034136107,0.002229906,0.0005323944,0.5654728,0.053761378,0.008512906,0.002100997,0.00018778791],"about_ca_topic_score_codex":0.0016561757,"about_ca_topic_score_gemma":0.002401324,"teacher_disagreement_score":0.002629002,"about_ca_system_score_codex":0.000322669,"about_ca_system_score_gemma":0.0003587421,"threshold_uncertainty_score":0.011537254},"labels":[],"label_agreement":null},{"id":"W2314151980","doi":"10.1038/srep22161","title":"Multimodal Image Analysis in Alzheimer’s Disease via Statistical Modelling of Non-local Intensity Correlations","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Information and Communication Technologies; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Southern California; University College London; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University College London Hospitals NHS Foundation Trust; Eli Lilly and Company; U.S. Department of Defense; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Magnetic resonance imaging; Positron emission tomography; Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; Cerebral atrophy; Posterior cortical atrophy; Partial least squares regression; Fluorodeoxyglucose; Pathology; Disease; Artificial intelligence; Alzheimer's disease; Neuroscience; Computer science; Pattern recognition (psychology); Medicine; Psychology; Dementia; Radiology; Machine learning","score_opus":0.058192720159185266,"score_gpt":0.348394349798752,"score_spread":0.29020162963956675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314151980","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16533579,0.0011874143,0.8314401,0.00058905844,0.000024414723,0.000046134006,0.00028232922,0.00051164086,0.0005831951],"genre_scores_gemma":[0.9258155,0.00090755307,0.07014616,0.00012639404,0.00009770374,0.00012545935,0.00048250693,0.000118557764,0.002180113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9992009,0.00045925504,0.000025836065,0.0001830526,0.000082812076,0.000048165857],"domain_scores_gemma":[0.99759454,0.0016994633,0.00038741183,0.00014709051,0.00011618653,0.000055294626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033403896,0.0007284415,0.00089545693,0.00086705683,0.00019957114,0.0009891655,0.000825278,0.00067225867,0.00072784995],"category_scores_gemma":[0.005567593,0.0004978302,0.0013780737,0.00076879316,0.000826236,0.00087344757,0.00084779074,0.0010060741,0.00030880168],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013226905,0.00008014044,0.0074308706,0.00008246087,0.00025372187,0.00028041122,0.00015808431,0.9281386,0.0032367068,0.00888327,0.0008531409,0.050470185],"study_design_scores_gemma":[0.0000036141666,0.000021563184,0.0011191746,0.0000033485398,0.0000131280185,0.000029482966,0.0000057055017,0.9937331,0.00015109012,0.004799269,0.00011353647,0.000006990314],"about_ca_topic_score_codex":0.0044688317,"about_ca_topic_score_gemma":0.004346887,"teacher_disagreement_score":0.0044688317,"about_ca_system_score_codex":0.00048819513,"about_ca_system_score_gemma":0.00057965616,"threshold_uncertainty_score":0.017665923},"labels":[],"label_agreement":null},{"id":"W2314790700","doi":"10.1136/archdischild-2014-307384.1078","title":"PO-0436 Postnatal Development Of The Auditory Thalamocortical Connexions","year":2014,"lang":"en","type":"article","venue":"Archives of Disease in Childhood","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Temporal lobe; Thalamus; White matter; Temporal cortex; Tractography; Neuroscience; Cortex (anatomy); Medicine; Fractional anisotropy; Auditory cortex; Diffusion MRI; Anatomy; Audiology; Magnetic resonance imaging; Psychology; Epilepsy; Radiology","score_opus":0.01942967463543542,"score_gpt":0.29409045366156633,"score_spread":0.2746607790261309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314790700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871022,0.000746027,0.0029582535,0.00019865263,0.00006966796,0.000046801677,0.00093988,0.00017003785,0.0077684987],"genre_scores_gemma":[0.9834145,0.0005633167,0.0023021633,0.00007191725,0.000015403666,0.0001829823,0.00078028487,0.00010180129,0.012567653],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998636,0.000015343203,0.000012517348,0.00004611711,0.000036043726,0.000026427273],"domain_scores_gemma":[0.99964786,0.000049921477,0.000100868005,0.000034775872,0.000059460785,0.00010721647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024770998,0.00020922655,0.00028020082,0.00030338558,0.00022112313,0.00038905643,0.00022654494,0.0003357396,0.011285792],"category_scores_gemma":[0.0004641352,0.00017137811,0.00017354116,0.00013685574,0.0004501287,0.00023334245,0.00039177126,0.0005345879,0.0018054518],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019671454,0.00033548402,0.029121805,0.00019163635,0.000029120221,0.0030824007,0.0005908095,0.00015674591,0.90037894,0.0015963523,0.0014750679,0.0610746],"study_design_scores_gemma":[0.00010682791,0.002577127,0.74395776,0.00012961852,0.000070908274,0.009378282,0.00085013115,0.0011199329,0.2163498,0.0017093573,0.023717409,0.00003287562],"about_ca_topic_score_codex":0.00083550735,"about_ca_topic_score_gemma":0.0006305355,"teacher_disagreement_score":0.011285792,"about_ca_system_score_codex":0.00015210277,"about_ca_system_score_gemma":0.0003837583,"threshold_uncertainty_score":0.037754714},"labels":[],"label_agreement":null},{"id":"W2315856334","doi":"10.1515/ins-2014-0012","title":"Part II: an evaluation of an integrated systems approach using diffusion-weighted, image-guided, exoscopic-assisted, transulcal radial corridors","year":2015,"lang":"en","type":"article","venue":"Innovative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Diffusion; Image (mathematics); Computer science; Computer vision; Artificial intelligence; Physics","score_opus":0.285184818469056,"score_gpt":0.40616575064967037,"score_spread":0.12098093218061434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315856334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987834,0.00022203485,0.010706945,0.000029909857,0.000018161794,0.00034469448,0.000076854834,0.00014229039,0.0006251405],"genre_scores_gemma":[0.96318793,0.00043850372,0.034081895,0.00006810225,0.000035535588,0.0005494522,0.0003189498,0.000041841457,0.0012778371],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995617,0.0001405929,0.00003963038,0.000084153704,0.0001267315,0.00004710126],"domain_scores_gemma":[0.9994043,0.0001413928,0.00009262549,0.00009492537,0.00014694702,0.00011993684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097346073,0.00091614306,0.00036593244,0.00074111205,0.0002315387,0.0004140157,0.0005282993,0.0004185161,0.002549166],"category_scores_gemma":[0.00144836,0.0002189745,0.0004067171,0.0002709538,0.00045117814,0.00055115164,0.0005739885,0.00036079084,0.00045437456],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011778329,0.019217085,0.042283975,0.0012592945,0.0008730625,0.001703484,0.0011917314,0.019971889,0.2786019,0.00053964835,0.0011978103,0.6213818],"study_design_scores_gemma":[0.005178893,0.41820422,0.2656545,0.0002337002,0.0011792233,0.010589194,0.00092124497,0.06329342,0.22080302,0.0005842146,0.012986527,0.00037184937],"about_ca_topic_score_codex":0.0013135656,"about_ca_topic_score_gemma":0.0016159104,"teacher_disagreement_score":0.002549166,"about_ca_system_score_codex":0.00043373316,"about_ca_system_score_gemma":0.0005474887,"threshold_uncertainty_score":0.008527815},"labels":[],"label_agreement":null},{"id":"W2315964472","doi":"10.1016/j.jpain.2012.01.385","title":"White matter alterations in long-term yoga practitioners: a diffusion-tensor imaging study","year":2012,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Anterior cingulate cortex; Medicine; Insula; Internal capsule; Psychology; Cingulum (brain); Cingulate cortex; Neuroscience; Magnetic resonance imaging; Radiology; Central nervous system; Cognition","score_opus":0.04234693114602367,"score_gpt":0.371311472149703,"score_spread":0.32896454100367933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315964472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999514,0.00015698382,0.000023781979,0.000041147377,0.0000025722359,0.000008389338,0.0000260334,8.681499e-7,0.00022617723],"genre_scores_gemma":[0.9992649,0.00018114962,0.000057403195,0.000039868766,0.000011348248,0.000011228067,0.000062025225,0.0000010251617,0.00037110658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999013,0.000017060005,0.00001280342,0.000023913004,0.000016393871,0.000028470069],"domain_scores_gemma":[0.999579,0.00008206769,0.00014884876,0.00001710988,0.00006185773,0.00011119154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025841632,0.00032201686,0.00033296118,0.0006884939,0.0008612416,0.0003739988,0.00026188302,0.00080034474,0.0016944162],"category_scores_gemma":[0.001017611,0.00031706897,0.00031129236,0.0006428822,0.00034349525,0.00048153588,0.00036449725,0.0005356748,0.0002578778],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022427435,0.0022552426,0.9611042,0.00010431711,0.00014823282,0.01000303,0.0025580567,0.0000630901,0.014383218,0.000045372242,0.00015064931,0.006941804],"study_design_scores_gemma":[0.000021204738,0.000581288,0.99696904,0.0000063453895,0.00004424094,0.0014722579,0.0006476255,0.00007176912,0.00009354247,0.000014177265,0.00007276139,0.000005790439],"about_ca_topic_score_codex":0.01520402,"about_ca_topic_score_gemma":0.018674534,"teacher_disagreement_score":0.01520402,"about_ca_system_score_codex":0.00038724867,"about_ca_system_score_gemma":0.00039326408,"threshold_uncertainty_score":0.030231059},"labels":[],"label_agreement":null},{"id":"W2316328502","doi":"10.1097/rct.0b013e3182ab60ea","title":"Diffusion Tensor Imaging of the Normal Foot at 3 T","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Foot (prosody); Anatomy; Effective diffusion coefficient; Magnetic resonance imaging; Nuclear magnetic resonance; Nuclear medicine; Asymptomatic; Thigh; Radiology; Pathology; Physics","score_opus":0.02167771018270286,"score_gpt":0.2837120542004462,"score_spread":0.26203434401774334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316328502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9443898,0.0019518846,0.04646547,0.0003344082,0.00006392692,0.000085690896,0.0017043093,0.00032168292,0.0046827765],"genre_scores_gemma":[0.9769722,0.0010454536,0.019800294,0.00013111523,0.000048741967,0.00005761277,0.0008521704,0.00007959606,0.0010126792],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997389,0.000060986167,0.000027415235,0.000057623976,0.000088936744,0.00002617847],"domain_scores_gemma":[0.9992131,0.00011235373,0.00018213382,0.00007748375,0.0003534759,0.00006140059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008401933,0.00042046537,0.00026142225,0.001790778,0.00030542753,0.0010000565,0.00035309017,0.00044878336,0.0014594439],"category_scores_gemma":[0.0035515204,0.00020249248,0.00026161873,0.00089993083,0.00040094787,0.0007491122,0.00027356122,0.0002694098,0.0004438954],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020086966,0.00038813113,0.28375968,0.0014235602,0.0007081507,0.0067579267,0.0011668941,0.006907648,0.41950965,0.003306949,0.009832513,0.26423025],"study_design_scores_gemma":[0.00023684485,0.0014134812,0.82916373,0.000439294,0.0004966633,0.031189885,0.0009349572,0.039529946,0.069541596,0.013714061,0.013156215,0.00018330912],"about_ca_topic_score_codex":0.0043415907,"about_ca_topic_score_gemma":0.005688509,"teacher_disagreement_score":0.0043415907,"about_ca_system_score_codex":0.0003006106,"about_ca_system_score_gemma":0.00049154705,"threshold_uncertainty_score":0.00863266},"labels":[],"label_agreement":null},{"id":"W2318362526","doi":"10.1227/neu.0000000000000271","title":"Anatomic Study of the Central Core of the Cerebrum Correlating 7-T Magnetic Resonance Imaging and Fiber Dissection With the Aid of a Neuronavigation System","year":2013,"lang":"en","type":"article","venue":"Operative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Neuronavigation; Medicine; Magnetic resonance imaging; White matter; Dissection (medical); Anatomy; Tractography; Radiology","score_opus":0.02083046362942726,"score_gpt":0.27779662753778067,"score_spread":0.2569661639083534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318362526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85584986,0.0013972016,0.1381532,0.00006861524,0.000037162783,0.00021764492,0.00018837611,0.00022874735,0.003859214],"genre_scores_gemma":[0.8082828,0.0013895996,0.18829258,0.00005903706,0.00002875818,0.000116622025,0.00034321754,0.00007143321,0.0014160208],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997719,0.00003545869,0.000024721507,0.00007889108,0.00006023627,0.00002893044],"domain_scores_gemma":[0.99922085,0.00014107379,0.0001680421,0.00018994854,0.00022718408,0.00005283158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011249342,0.00047875702,0.0002063898,0.001275842,0.00035588568,0.00031953945,0.00043349696,0.000488578,0.0014128577],"category_scores_gemma":[0.0006499543,0.00045810323,0.0002025398,0.00027262882,0.001056082,0.0005508528,0.00043380517,0.00043151138,0.0005238186],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020531338,0.000067890476,0.009511058,0.00016305738,0.00005068543,0.0025431048,0.0002342502,0.0010357646,0.97129816,0.00090642355,0.00012867853,0.0138555365],"study_design_scores_gemma":[0.00014008426,0.0034420788,0.17064159,0.0001666659,0.0003141252,0.08656767,0.0005702189,0.011853447,0.71445847,0.0012038861,0.01054555,0.00009619535],"about_ca_topic_score_codex":0.0011505948,"about_ca_topic_score_gemma":0.0025838409,"teacher_disagreement_score":0.0014128577,"about_ca_system_score_codex":0.0002476011,"about_ca_system_score_gemma":0.0008501946,"threshold_uncertainty_score":0.005949259},"labels":[],"label_agreement":null},{"id":"W2319216091","doi":"10.1177/1545968315584004","title":"Dynamic Changes in White Matter Abnormalities Correlate With Late Improvement and Deterioration Following TBI","year":2015,"lang":"en","type":"article","venue":"Neurorehabilitation and neural repair","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Academy of Medical Sciences; National Institute for Health and Care Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Traumatic brain injury; Magnetic resonance imaging; Corpus callosum; Medicine; Corticospinal tract; Neuroimaging; Tractography; Neuroscience; Psychology; Physical medicine and rehabilitation; Radiology; Psychiatry","score_opus":0.027938809501586406,"score_gpt":0.3095742834121778,"score_spread":0.2816354739105914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319216091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994054,0.00012202092,0.00014772307,0.000034330056,0.0000019056336,0.0000072432163,0.00007558294,0.000006956877,0.00019880626],"genre_scores_gemma":[0.999385,0.000059313377,0.00015822468,0.000011038095,0.000007555902,0.000007990493,0.00019100562,0.0000024310434,0.00017751784],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999897,0.000017180442,0.0000150419755,0.00002289772,0.000021521335,0.000026266041],"domain_scores_gemma":[0.9990113,0.000093215276,0.0005771781,0.000044596378,0.0001388158,0.00013481191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030662667,0.00025606868,0.00019660435,0.0005329377,0.0003067603,0.00039844812,0.00020189617,0.0003279602,0.001406852],"category_scores_gemma":[0.0021653932,0.000107197964,0.00015707579,0.0003779291,0.00035411547,0.00044703303,0.00037955024,0.00040074743,0.0002834828],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082803686,0.00013408136,0.97773063,0.000031657553,0.000054838387,0.00042200045,0.00034755858,0.0002940287,0.00810705,0.00003063408,0.00020783371,0.011811618],"study_design_scores_gemma":[0.000008217091,0.00033615885,0.9977101,0.0000066431544,0.000016415657,0.0006610872,0.00013301219,0.00022643447,0.00074181275,0.0000443526,0.000111018475,0.0000048141924],"about_ca_topic_score_codex":0.0018372638,"about_ca_topic_score_gemma":0.0027356916,"teacher_disagreement_score":0.0018372638,"about_ca_system_score_codex":0.00027261945,"about_ca_system_score_gemma":0.00023676344,"threshold_uncertainty_score":0.0047063828},"labels":[],"label_agreement":null},{"id":"W2320710418","doi":"10.1097/rct.0b013e3182772d66","title":"Quantitative DTI Assessment in Human Lumbar Stabilization Muscles at 3 T","year":2013,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; McMaster University Medical Centre","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; Medicine; Diffusion MRI; Lumbar; Magnetic resonance imaging; Low back pain; Body mass index; Oswestry Disability Index; Nuclear medicine; Anatomy; Radiology; Pathology","score_opus":0.06766996994943697,"score_gpt":0.380726403764135,"score_spread":0.31305643381469805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320710418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9643609,0.0019187044,0.031071987,0.00011514379,0.000014624378,0.000058371344,0.000636415,0.00016838312,0.0016555694],"genre_scores_gemma":[0.98199534,0.0005994175,0.01617679,0.000042894542,0.000017696802,0.00006020141,0.00032464936,0.000031544652,0.00075138966],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998752,0.000041193467,0.000010777127,0.000033169305,0.000030267687,0.0000094148345],"domain_scores_gemma":[0.999582,0.00010355162,0.0001191123,0.000027374988,0.00013891894,0.000029031926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007797527,0.00029544963,0.0001571471,0.00078562286,0.00019736485,0.00036642866,0.0001737526,0.00043046454,0.0014229945],"category_scores_gemma":[0.0017785759,0.00014415632,0.00012452423,0.00032509936,0.00022613103,0.00035529872,0.00013053695,0.00011935454,0.0003290203],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001761597,0.00011326941,0.060006958,0.00081630313,0.00017006251,0.0005032137,0.0007143247,0.0029981367,0.8400949,0.00045554593,0.0010703075,0.0912954],"study_design_scores_gemma":[0.00017538106,0.0017370145,0.78128743,0.00016738202,0.00032643796,0.0071596876,0.00069539115,0.033481628,0.16891824,0.0015955635,0.0043376046,0.000118299264],"about_ca_topic_score_codex":0.0018301924,"about_ca_topic_score_gemma":0.0024531493,"teacher_disagreement_score":0.0018301924,"about_ca_system_score_codex":0.00017189953,"about_ca_system_score_gemma":0.00018568941,"threshold_uncertainty_score":0.0047603846},"labels":[],"label_agreement":null},{"id":"W2321691898","doi":"10.3174/ajnr.a2844","title":"A Validation Study of Multicenter Diffusion Tensor Imaging: Reliability of Fractional Anisotropy and Diffusivity Values","year":2011,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":149,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Neurological Disorders and Stroke; Genentech; National Institutes of Health; Teva Pharmaceutical Industries; Biogen; National Multiple Sclerosis Society","keywords":"Fractional anisotropy; Concordance; Diffusion MRI; White matter; Medicine; Corpus callosum; Nuclear medicine; Magnetic resonance imaging; Intraclass correlation; Nuclear magnetic resonance; Pulse sequence; Concordance correlation coefficient; Radiology; Physics; Pathology; Statistics; Mathematics; Internal medicine","score_opus":0.0484040084854849,"score_gpt":0.3402699345200311,"score_spread":0.2918659260345462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321691898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99145633,0.0003090196,0.006894568,0.000038408132,0.000039651455,0.00014813423,0.00020753738,0.00006147274,0.00084490405],"genre_scores_gemma":[0.99636,0.000031439642,0.0030552775,0.00001555461,0.000023273846,0.00006951693,0.000304855,0.00002732206,0.000112688715],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9895912,0.0056798635,0.0010692517,0.002018772,0.0013973748,0.00024364992],"domain_scores_gemma":[0.9455672,0.023052653,0.008446454,0.009280328,0.012634274,0.0010190336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020451626,0.00077331706,0.00050145,0.0013264846,0.0010262384,0.0009421123,0.001158897,0.0011049113,0.0009223739],"category_scores_gemma":[0.050462052,0.00039982345,0.00069580314,0.0006887843,0.0014048564,0.00093817053,0.0012738591,0.0005040908,0.0006710936],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029607979,0.00038762082,0.94784945,0.00017261281,0.0008884621,0.00024195868,0.0024056109,0.0012749288,0.0139981555,0.00037690526,0.0006217579,0.028821727],"study_design_scores_gemma":[0.000282844,0.0036366794,0.96845365,0.000088287576,0.00044737465,0.0019679118,0.0006194863,0.0116830375,0.009898113,0.000553759,0.0022995484,0.00006933367],"about_ca_topic_score_codex":0.0013880982,"about_ca_topic_score_gemma":0.0013060849,"teacher_disagreement_score":0.020451626,"about_ca_system_score_codex":0.00042215196,"about_ca_system_score_gemma":0.00058236386,"threshold_uncertainty_score":0.10815978},"labels":[],"label_agreement":null},{"id":"W2322861895","doi":"10.1002/hbm.23139","title":"Effects of change in FreeSurfer version on classification accuracy of patients with Alzheimer's disease and mild cognitive impairment","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroRx Research (Canada)","funders":"DoD Alzheimer's Disease Neuroimaging Initiative; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; National Institutes of Health; Foundation for the National Institutes of Health; Norges Forskningsråd; Northern California Institute for Research and Education; University of California, San Diego; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Eisai; National Institute on Aging; Alzheimer's Association","keywords":"Neuroimaging; Cognition; Alzheimer's Disease Neuroimaging Initiative; Cognitive impairment; Entorhinal cortex; Disease; Psychology; Alzheimer's disease; Dementia; Audiology; Magnetic resonance imaging; Neuroscience; Medicine; Pathology; Radiology; Hippocampus","score_opus":0.10049862533979845,"score_gpt":0.34839473308590335,"score_spread":0.2478961077461049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2322861895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99878985,0.00022226441,0.0004321187,0.000059760474,0.000022235674,0.000011317105,0.00015034502,0.000028257991,0.00028379646],"genre_scores_gemma":[0.99898225,0.000036463007,0.00049743557,0.000027161868,0.000010627757,0.000010961353,0.0002962611,0.000023034308,0.000115756375],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9920094,0.0035042474,0.001321785,0.0015373253,0.0012955271,0.00033179586],"domain_scores_gemma":[0.9433405,0.03932617,0.007187034,0.005139718,0.004024888,0.0009817161],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01064712,0.00047238747,0.0007228815,0.0016281937,0.00038491705,0.0012006739,0.0004851736,0.0007717413,0.00087026745],"category_scores_gemma":[0.05652091,0.0002930592,0.00075447286,0.00093002716,0.0009888611,0.0010668901,0.0009020894,0.0006887649,0.00032337697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008551981,0.00016746673,0.9577817,0.00006421936,0.00065332185,0.00024648596,0.00081439107,0.0014173059,0.0034496319,0.00006787064,0.0004625102,0.02632303],"study_design_scores_gemma":[0.000041232088,0.0010140766,0.9934457,0.000013512178,0.000121636396,0.00045514992,0.0002100186,0.0025121353,0.0017989986,0.0001552876,0.00020609556,0.00002615707],"about_ca_topic_score_codex":0.0013534378,"about_ca_topic_score_gemma":0.0016358739,"teacher_disagreement_score":0.9893529,"about_ca_system_score_codex":0.00035432065,"about_ca_system_score_gemma":0.0002255348,"threshold_uncertainty_score":0.05630803},"labels":[],"label_agreement":null},{"id":"W2324703134","doi":"10.1109/embc.2014.6944098","title":"Optimized methodology for neonatal diffusion tensor imaging processing and study-specific template construction","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Template; Computer science; White matter; Modular design; Population; Pipeline (software); Artificial intelligence; Medicine; Magnetic resonance imaging; Programming language","score_opus":0.12621877826627628,"score_gpt":0.39593935126441127,"score_spread":0.269720572998135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2324703134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023615235,0.0000791515,0.9917745,0.00005794399,0.000037731996,0.00010147747,0.00058872957,0.004666891,0.00033202747],"genre_scores_gemma":[0.01406589,0.00010550464,0.98025507,0.000068000976,0.000028545439,0.0003975687,0.0023621395,0.001540653,0.0011767378],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99878746,0.00025007586,0.00016969653,0.00031172583,0.00038255492,0.00009858518],"domain_scores_gemma":[0.99715024,0.0006451474,0.00026160845,0.0007546128,0.001041591,0.00014683206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030903926,0.0016309764,0.00089826365,0.0014281003,0.00058280944,0.0016435354,0.0018427796,0.001023723,0.009409909],"category_scores_gemma":[0.009679838,0.0008786789,0.0014576252,0.0013774525,0.00042762983,0.0009844435,0.002239996,0.0020544473,0.0066873087],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043130238,0.00012936135,0.00537466,0.0004256483,0.00029893825,0.0006808486,0.0003873004,0.029360967,0.10511323,0.011259154,0.035568465,0.81097007],"study_design_scores_gemma":[0.00014107565,0.0004287738,0.016620187,0.00015448403,0.0003372019,0.0038184498,0.0002677592,0.5544454,0.24783504,0.04140335,0.13424931,0.00029906956],"about_ca_topic_score_codex":0.003840484,"about_ca_topic_score_gemma":0.0061948746,"teacher_disagreement_score":0.009409909,"about_ca_system_score_codex":0.0006475812,"about_ca_system_score_gemma":0.0038201606,"threshold_uncertainty_score":0.03147924},"labels":[],"label_agreement":null},{"id":"W2328218730","doi":"10.1017/s0317167100000627","title":"MRI Techniques: Bilateral Findings and “Normal Findings”","year":2000,"lang":"en","type":"review","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre","funders":"","keywords":"Magnetic resonance imaging; Fluid-attenuated inversion recovery; Coronal plane; Temporal lobe; Hippocampal sclerosis; Medicine; Nuclear medicine; Radiology; Creatine; Magnetic resonance spectroscopic imaging; Epilepsy; Internal medicine","score_opus":0.08788210174650572,"score_gpt":0.3591172914560427,"score_spread":0.271235189709537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328218730","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004222283,0.95824456,0.0026163976,0.0016762621,0.0014035379,0.00005073898,0.00013169291,0.00021504193,0.031439424],"genre_scores_gemma":[0.059761234,0.91466266,0.004373311,0.003810494,0.003572095,0.00006905473,0.0003462814,0.00006709566,0.013337891],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993374,0.00011349835,0.00012575745,0.00013460945,0.0002217725,0.000066843],"domain_scores_gemma":[0.9993591,0.00019467997,0.0001536725,0.000058435577,0.0001626263,0.00007155458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061308814,0.0018755775,0.0019581544,0.0046076123,0.00037119712,0.0010276493,0.0010610406,0.0016499739,0.00419526],"category_scores_gemma":[0.0021120491,0.00030562415,0.00044463226,0.0027896133,0.0028664528,0.0018785613,0.00079288357,0.0012857622,0.0063449466],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020475325,0.00014900691,0.0031866631,0.0082298145,0.00014378807,0.023099765,0.0003844502,0.00032319644,0.008460983,0.0065825456,0.06324534,0.88598967],"study_design_scores_gemma":[0.0000770099,0.00018289791,0.0141833015,0.006903486,0.00017488962,0.34976485,0.00061578234,0.000361535,0.0029479726,0.010465588,0.61421555,0.00010708951],"about_ca_topic_score_codex":0.0013055631,"about_ca_topic_score_gemma":0.001493657,"teacher_disagreement_score":0.0046076123,"about_ca_system_score_codex":0.00054984726,"about_ca_system_score_gemma":0.0007166389,"threshold_uncertainty_score":0.014034569},"labels":[],"label_agreement":null},{"id":"W2328558547","doi":"10.1097/wnr.0000000000000044","title":"Functional reorganization of the corticospinal tract in a pediatric patient with an arteriovenous malformation","year":2013,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McMaster University; Hospital for Sick Children","funders":"","keywords":"Corticospinal tract; Magnetoencephalography; Precentral gyrus; White matter; Neuroscience; Tractography; Lateralization of brain function; Diffusion MRI; Psychology; Anatomy; Motor system; Medicine; Magnetic resonance imaging; Electroencephalography; Radiology","score_opus":0.028410600197774163,"score_gpt":0.26388390662875194,"score_spread":0.23547330643097777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328558547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99831223,0.0001769094,0.00051648635,0.0003101107,0.000011371853,0.000016176125,0.00006702644,0.000036744375,0.0005529545],"genre_scores_gemma":[0.99886787,0.00020271941,0.0006397501,0.00006803447,0.000022850498,0.000007264897,0.000037024252,0.000007858058,0.00014658032],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9997993,0.000020318777,0.000025267816,0.00005699857,0.00003640492,0.00006173616],"domain_scores_gemma":[0.99939144,0.00024017539,0.00013503696,0.000026226335,0.00004268732,0.00016450012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001853383,0.00085671816,0.0007378999,0.001488566,0.0011273829,0.00044554428,0.00048634998,0.0014512484,0.00094653934],"category_scores_gemma":[0.0014412674,0.000533946,0.00036946035,0.0008713557,0.001152604,0.000561323,0.00040064182,0.0011729432,0.00016099514],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095943455,0.00007093992,0.046278596,0.000039223174,0.000016037322,0.9423485,0.00048681884,0.00023949487,0.007161833,0.00012062292,0.00015109593,0.0029909005],"study_design_scores_gemma":[0.00002194742,0.00036621586,0.08112863,0.000012905926,0.000042448388,0.9137063,0.00031211696,0.00085449975,0.003171659,0.00011722768,0.00024456333,0.000021530412],"about_ca_topic_score_codex":0.0050343336,"about_ca_topic_score_gemma":0.007238419,"teacher_disagreement_score":0.0050343336,"about_ca_system_score_codex":0.0008016534,"about_ca_system_score_gemma":0.0007359452,"threshold_uncertainty_score":0.010010064},"labels":[],"label_agreement":null},{"id":"W2330281932","doi":"10.1017/s0317167100006120","title":"Wallerian-Like Degeneration After Ischemic Stroke Revealed by Diffusion - Weighted Imaging","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Magnetic resonance imaging; Middle cerebral artery; Radiology; Anterior cerebral artery; Dysarthria; Wallerian degeneration; Effective diffusion coefficient; Cardiology; Ischemia; Anatomy","score_opus":0.03063846124426548,"score_gpt":0.29841350257407073,"score_spread":0.26777504132980523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330281932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9653237,0.006574791,0.0012374542,0.0023346376,0.00023672485,0.0003129623,0.0004193534,0.00008023752,0.023480153],"genre_scores_gemma":[0.993141,0.0022839743,0.00042418664,0.00061671896,0.00037428163,0.000024215235,0.00024351719,0.00000814657,0.0028840331],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99977046,0.000022012111,0.000028304032,0.000056052835,0.00004689642,0.00007637586],"domain_scores_gemma":[0.9997489,0.000038489237,0.000059978083,0.000019297611,0.000038356367,0.00009496679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023215586,0.0011435879,0.00077283493,0.001645101,0.0012154684,0.00059463154,0.0006331837,0.0015335162,0.0021982936],"category_scores_gemma":[0.0010540406,0.000504422,0.00034856205,0.0012378267,0.0007085084,0.0010645924,0.0005635566,0.0014620605,0.00074085675],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010262497,0.00009156442,0.017208755,0.000032350483,0.000010561845,0.9796244,0.00012281114,0.00003571115,0.00095620827,0.00010711256,0.00026624603,0.0014417062],"study_design_scores_gemma":[0.000046318866,0.00041785216,0.088397264,0.00006136722,0.00003988498,0.90801847,0.00022794532,0.00037524814,0.00059658237,0.000379697,0.0014159556,0.000023369083],"about_ca_topic_score_codex":0.0061315824,"about_ca_topic_score_gemma":0.00807384,"teacher_disagreement_score":0.0061315824,"about_ca_system_score_codex":0.0008220318,"about_ca_system_score_gemma":0.00085531984,"threshold_uncertainty_score":0.012191772},"labels":[],"label_agreement":null},{"id":"W2332641582","doi":"10.1017/s0317167100000846","title":"Callosal Atrophy Correlates with Temporal Lobe Volume and Mental Status in Alzheimer's Disease","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Atrophy; Corpus callosum; Temporal lobe; Alzheimer's disease; Commissure; Neuroscience; Psychology; Dementia; Medicine; Pathology; Disease","score_opus":0.03592678515444098,"score_gpt":0.2942231187294774,"score_spread":0.2582963335750364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2332641582","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927145,0.00021122457,0.000029114139,0.00002210034,0.0000015455819,0.0000028260954,0.00007210238,0.0000048460024,0.00038474286],"genre_scores_gemma":[0.9995572,0.00009573854,0.0000857389,0.00000914447,0.00000452776,0.0000035867781,0.00013482358,0.0000015463512,0.000107716296],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994254,0.0000098989385,0.0000072083235,0.000011894415,0.000020794676,0.000007771544],"domain_scores_gemma":[0.9993899,0.000111149726,0.0002950011,0.000034986788,0.00008822309,0.00008074031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020240426,0.000237592,0.00014330455,0.000740554,0.00024684094,0.000345908,0.00019713915,0.00022186992,0.0014806837],"category_scores_gemma":[0.0011453873,0.00008807452,0.00013222896,0.0003572108,0.00037634486,0.00019468149,0.00023862177,0.00020957775,0.0001700544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004983726,0.000042925192,0.98426616,0.000033568667,0.000091519265,0.0005923067,0.00038450386,0.00010570423,0.0074011474,0.00004516736,0.00017608191,0.0063625644],"study_design_scores_gemma":[0.0000027757717,0.000028586792,0.9992028,0.000002638374,0.000012183451,0.00042558668,0.00005099525,0.000057759797,0.00012483256,0.00003445405,0.00005585174,0.0000015685533],"about_ca_topic_score_codex":0.004269167,"about_ca_topic_score_gemma":0.006403515,"teacher_disagreement_score":0.004269167,"about_ca_system_score_codex":0.00025552872,"about_ca_system_score_gemma":0.00014236206,"threshold_uncertainty_score":0.0084885955},"labels":[],"label_agreement":null},{"id":"W2337241400","doi":"10.1016/j.neuroimage.2016.04.048","title":"Dance and music training have different effects on white matter diffusivity in sensorimotor pathways","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; International Laboratory for Brain, Music and Sound Research; Cégep Marie-Victorin; Université de Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dance; Psychology; Corpus callosum; White matter; Cognitive psychology; Diffusion MRI; Neuroscience; Visual arts; Medicine; Art","score_opus":0.07154916855905313,"score_gpt":0.3019285371522233,"score_spread":0.23037936859317015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2337241400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99618953,0.0012594514,0.00037170423,0.00018371349,0.000102819016,0.000030488582,0.00014648314,0.00003298432,0.0016828895],"genre_scores_gemma":[0.9948624,0.0006685979,0.00046486105,0.00016105344,0.00007097528,0.00010906102,0.0001429708,0.00004054735,0.0034796088],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99981123,0.000042728832,0.000016351287,0.000050299266,0.000019413688,0.00006002646],"domain_scores_gemma":[0.9994572,0.00023237427,0.00008178954,0.000060065435,0.00003223772,0.0001363391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025282567,0.0005263867,0.0006103003,0.00025809597,0.00028646353,0.0003805629,0.00022936058,0.0005911171,0.0068427664],"category_scores_gemma":[0.0011500107,0.0003046609,0.00043728,0.00020141223,0.00071515853,0.00037732394,0.0003414135,0.0005259048,0.00039082437],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.15269774,0.005129665,0.011427584,0.00094351324,0.0011307419,0.0005259657,0.0006701884,0.00058763183,0.73248297,0.00030500098,0.000826727,0.09327227],"study_design_scores_gemma":[0.004415104,0.028912216,0.86472505,0.0001350074,0.0016647888,0.0005167168,0.0011471689,0.0013010325,0.09318232,0.00080921897,0.0031198692,0.00007147202],"about_ca_topic_score_codex":0.0014708022,"about_ca_topic_score_gemma":0.0026523771,"teacher_disagreement_score":0.0068427664,"about_ca_system_score_codex":0.00020405327,"about_ca_system_score_gemma":0.00029698538,"threshold_uncertainty_score":0.022891343},"labels":[],"label_agreement":null},{"id":"W2337594561","doi":"10.1037/neu0000258","title":"White matter and information processing speed following treatment with cranial-spinal radiation for pediatric brain tumor.","year":2016,"lang":"en","type":"article","venue":"Neuropsychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; Princess Margaret Cancer Centre; Hospital for Sick Children; University of British Columbia; Ontario Institute for Cancer Research; BC Children's Hospital; Children's Hospital of Eastern Ontario; University of Calgary","funders":"","keywords":"White matter; Optic radiation; Psychology; Diffusion MRI; Visual processing; Audiology; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.02670042228463997,"score_gpt":0.33940743535808293,"score_spread":0.31270701307344295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2337594561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974126,0.00009547942,0.000026575191,0.000009983057,0.0000013773183,0.0000031683321,0.000040598225,0.0000014687997,0.00007992095],"genre_scores_gemma":[0.999602,0.00008612858,0.00008232967,0.000005918529,0.0000028108063,0.000007752792,0.00012597526,0.00000162835,0.00008547064],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981505,0.00003264662,0.000013271992,0.000039561222,0.000057370697,0.00004220844],"domain_scores_gemma":[0.99887866,0.00015854937,0.0007380438,0.000027457634,0.00007856019,0.00011871606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025758587,0.00020227808,0.00020538372,0.00030145267,0.00016955248,0.00016910282,0.00015763514,0.00018927672,0.0007446781],"category_scores_gemma":[0.0019364615,0.00006946843,0.00021128196,0.00030702274,0.00027830148,0.00018358859,0.00013982273,0.00027852948,0.00008825569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004996154,0.00015466206,0.9850348,0.000040787978,0.000083563325,0.0004126344,0.00023509855,0.000209032,0.0030100336,0.000020177536,0.00012309187,0.010176541],"study_design_scores_gemma":[0.000007480043,0.0004677059,0.9978702,0.0000036739266,0.000019231686,0.0007350647,0.000081398735,0.00007041954,0.00063399173,0.000008056592,0.00010103434,0.0000018563413],"about_ca_topic_score_codex":0.0033908014,"about_ca_topic_score_gemma":0.0047572968,"teacher_disagreement_score":0.0033908014,"about_ca_system_score_codex":0.00037853772,"about_ca_system_score_gemma":0.00035370336,"threshold_uncertainty_score":0.00674212},"labels":[],"label_agreement":null},{"id":"W2340818140","doi":"10.1016/j.neuroimage.2016.04.038","title":"Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Research and Development; National Institute of Nursing Research; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Biogen Idec; Genentech; National Institutes of Health; Servier; Eisai; Pfizer; BioClinica; Synarc; National Center for Complementary and Integrative Health; National Institute on Aging; Fonds Québécois de la Recherche sur la Nature et les Technologies; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Research Resources; F. Hoffmann-La Roche; Ellison Medical Foundation; Alzheimer's Drug Discovery Foundation; Merck; NIH Blueprint for Neuroscience Research; Fujirebio Europe; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics","keywords":"Diffusion MRI; Univariate; Fractional anisotropy; Multivariate statistics; Population; White matter; Pattern recognition (psychology); Voxel; Artificial intelligence; Partial least squares regression; Multivariate analysis; Magnetic resonance imaging; Computer science; Statistics; Mathematics; Medicine; Radiology","score_opus":0.050328048339124805,"score_gpt":0.3634823989638484,"score_spread":0.3131543506247236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340818140","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061298285,0.00050456444,0.9365864,0.00027114205,0.000028823104,0.000050973395,0.00013989818,0.0009015548,0.00021835174],"genre_scores_gemma":[0.30235222,0.00063242624,0.69545144,0.00005110478,0.00006314318,0.00013770344,0.00015209273,0.00039901823,0.00076086196],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991002,0.00055696844,0.000052661675,0.0001180346,0.00014266097,0.00002946228],"domain_scores_gemma":[0.99583876,0.0031130242,0.00026491648,0.00030797653,0.00040861944,0.000066729976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036445893,0.00057800196,0.00091032183,0.00093483785,0.00048728942,0.0005814296,0.0005434497,0.00037448545,0.0007175704],"category_scores_gemma":[0.010936689,0.0003352542,0.0011189486,0.0014267334,0.0004529566,0.0004749539,0.0006789248,0.001073293,0.00015492844],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045517448,0.00021823063,0.013060154,0.00031728862,0.00072111434,0.00026059026,0.00040804574,0.10793916,0.03393396,0.006800234,0.0027176407,0.8331683],"study_design_scores_gemma":[0.000046783338,0.00023758902,0.021665366,0.000014889417,0.00020159516,0.000459245,0.00007941132,0.9510585,0.00953735,0.014417928,0.002219633,0.000061673265],"about_ca_topic_score_codex":0.004669595,"about_ca_topic_score_gemma":0.008272587,"teacher_disagreement_score":0.004669595,"about_ca_system_score_codex":0.00027132247,"about_ca_system_score_gemma":0.001494532,"threshold_uncertainty_score":0.019274652},"labels":[],"label_agreement":null},{"id":"W2342252618","doi":"10.3174/ajnr.a4772","title":"Gray Matter Growth Is Accompanied by Increasing Blood Flow and Decreasing Apparent Diffusion Coefficient during Childhood","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Globus pallidus; Putamen; Cerebral blood flow; Medicine; Effective diffusion coefficient; Thalamus; Caudate nucleus; Basal ganglia; Grey matter; Nuclear medicine; Cerebral cortex; Internal medicine; Cardiology; Magnetic resonance imaging; Central nervous system; Radiology; White matter","score_opus":0.011479287923401625,"score_gpt":0.26901416842542986,"score_spread":0.2575348805020282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342252618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968777,0.0011155648,0.0006609664,0.000032594166,0.000005786696,0.00000673401,0.0006377889,0.000048508922,0.00061442435],"genre_scores_gemma":[0.9979328,0.00059832743,0.00084876176,0.0000095103915,0.000007214316,0.0000071938766,0.00047643785,0.000011191956,0.00010853499],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974126,0.000036864938,0.000042106985,0.00007810206,0.000052513304,0.00004918282],"domain_scores_gemma":[0.998137,0.00031317782,0.0011731022,0.0000873637,0.0001965224,0.00009283362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037883307,0.00038031445,0.0002691433,0.0015015154,0.00029238773,0.00036263518,0.00022861935,0.00028960616,0.0009366321],"category_scores_gemma":[0.0020715403,0.00021346012,0.00019947429,0.0008496807,0.00059473806,0.000474273,0.0003075844,0.00023605411,0.00018422284],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023604448,0.000012737367,0.98238695,0.00008321029,0.00003306223,0.001376593,0.00020985822,0.00029007593,0.005624011,0.00010777591,0.0002249497,0.009414742],"study_design_scores_gemma":[0.0000023917614,0.00005982735,0.9908025,0.000015074563,0.000025795453,0.0059871217,0.00010951108,0.00014211252,0.0024209556,0.000056225057,0.00037466665,0.0000037956383],"about_ca_topic_score_codex":0.0069107525,"about_ca_topic_score_gemma":0.0064439736,"teacher_disagreement_score":0.0069107525,"about_ca_system_score_codex":0.0004082795,"about_ca_system_score_gemma":0.0004563222,"threshold_uncertainty_score":0.013741016},"labels":[],"label_agreement":null},{"id":"W2343783019","doi":"10.3174/ajnr.a4788","title":"Tractography at 3T MRI of Corpus Callosum Tracts Crossing White Matter Hyperintensities","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; University of Toronto; Queen's University","funders":"","keywords":"Corpus callosum; White matter; Hyperintensity; Diffusion MRI; Cingulum (brain); Fractional anisotropy; Tractography; Fluid-attenuated inversion recovery; Medicine; Magnetic resonance imaging; Anatomy; Radiology","score_opus":0.03429017887771286,"score_gpt":0.31555428671333197,"score_spread":0.2812641078356191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343783019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844283,0.00033746177,0.014214333,0.00004403105,0.000005093067,0.00002843281,0.00028218262,0.00014601307,0.0005141994],"genre_scores_gemma":[0.986434,0.00019946416,0.0126819555,0.00001512735,0.000005319754,0.000026991705,0.00028128875,0.000060384424,0.00029550106],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982005,0.00005070775,0.0000139650865,0.00006601043,0.000035464593,0.000013790232],"domain_scores_gemma":[0.9989825,0.00026726074,0.0003649786,0.00013122073,0.00019710536,0.000056960693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006656868,0.0003403281,0.00024604323,0.0011671365,0.00036962784,0.0007565951,0.00019774516,0.00042990173,0.0013099924],"category_scores_gemma":[0.0023907095,0.00021886971,0.00037057078,0.00058268366,0.00046710332,0.00044486547,0.00019227462,0.00023675531,0.0002354351],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020775371,0.00012261831,0.3544864,0.0006144322,0.0011185557,0.0027321696,0.0036291126,0.016332652,0.5066919,0.0016071672,0.0015216477,0.109065875],"study_design_scores_gemma":[0.000060922157,0.0003345677,0.910072,0.00009416724,0.00023300436,0.006905493,0.0004658461,0.026966417,0.05095843,0.0016816345,0.002142927,0.00008452874],"about_ca_topic_score_codex":0.007675892,"about_ca_topic_score_gemma":0.012580696,"teacher_disagreement_score":0.007675892,"about_ca_system_score_codex":0.0005164896,"about_ca_system_score_gemma":0.0004567515,"threshold_uncertainty_score":0.015262425},"labels":[],"label_agreement":null},{"id":"W2344067133","doi":"10.1016/j.pscychresns.2016.04.014","title":"White matter integrity in major depressive disorder: Implications of childhood trauma, 5-HTTLPR and BDNF polymorphisms","year":2016,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; University of Calgary; McMaster University","funders":"","keywords":"5-HTTLPR; White matter; Major depressive disorder; Medicine; Psychology; Internal medicine; Clinical psychology; Genetics; Biology; Polymorphism (computer science); Allele; Gene","score_opus":0.06373267162740659,"score_gpt":0.3913081380794589,"score_spread":0.3275754664520523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344067133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987154,0.00056570244,0.000061614264,0.00011721326,0.0000074396467,0.0000022016568,0.0001329309,0.0000016859339,0.000395811],"genre_scores_gemma":[0.99945,0.00015723852,0.000080649894,0.000034466717,0.000008784902,0.0000019323284,0.00008640597,0.0000016769093,0.00017883851],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982303,0.00004327576,0.000023864204,0.0000569909,0.000020755619,0.000032181746],"domain_scores_gemma":[0.99947006,0.000093656214,0.0002807941,0.000043032847,0.000038124952,0.00007427819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002643994,0.000238846,0.0002446073,0.0003900459,0.00035293895,0.00048597154,0.00033894487,0.0005564783,0.0021922844],"category_scores_gemma":[0.0011096685,0.00025501152,0.00033240553,0.0005056315,0.00031859492,0.00027025773,0.00027579506,0.0005232649,0.00014505202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012568483,0.00010578745,0.9835194,0.00004290429,0.0005736611,0.00068258174,0.00025710187,0.00014568583,0.0067188875,0.00013115258,0.00018394578,0.0063820845],"study_design_scores_gemma":[0.000004256644,0.000025279489,0.9993992,0.0000037520856,0.000046924764,0.00025262826,0.000044678625,0.00004450525,0.000101772246,0.000042562566,0.000033312615,0.0000010938255],"about_ca_topic_score_codex":0.00606156,"about_ca_topic_score_gemma":0.010453395,"teacher_disagreement_score":0.00606156,"about_ca_system_score_codex":0.00031608835,"about_ca_system_score_gemma":0.0001827027,"threshold_uncertainty_score":0.012052536},"labels":[],"label_agreement":null},{"id":"W2344337444","doi":"10.1016/j.neuroimage.2016.04.041","title":"Inter-site and inter-scanner diffusion MRI data harmonization","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vetenskapsrådet","keywords":"Diffusion MRI; Scanner; Spherical harmonics; Fractional anisotropy; Pattern recognition (psychology); Computer science; Artificial intelligence; Invariant (physics); Rotation (mathematics); SIGNAL (programming language); Computer vision; Algorithm; Mathematics; Magnetic resonance imaging; Mathematical analysis","score_opus":0.07737868940764157,"score_gpt":0.3476584246011658,"score_spread":0.2702797351935242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344337444","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053692795,0.0010119161,0.92945796,0.00044702494,0.00040702627,0.00045059374,0.0038006485,0.005556036,0.0051760124],"genre_scores_gemma":[0.37587208,0.001116092,0.5905549,0.0006004262,0.00021614393,0.0012555167,0.015829487,0.0078310445,0.006724284],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954294,0.00134969,0.000743718,0.0012034986,0.00097341073,0.00030028215],"domain_scores_gemma":[0.98865104,0.0015293149,0.00068910467,0.005692568,0.0033323641,0.00010561063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065733884,0.0011222151,0.0014113816,0.0026615923,0.0009119474,0.0029722138,0.002177505,0.0012220371,0.0053157993],"category_scores_gemma":[0.018115057,0.0009563563,0.0017124213,0.003932922,0.0007512845,0.002700913,0.0031370958,0.0011506102,0.004083731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002343201,0.0004993014,0.019131757,0.0013303774,0.0017334813,0.0006988095,0.002238703,0.026203008,0.12170877,0.01252006,0.034111526,0.777481],"study_design_scores_gemma":[0.0003114731,0.0007081591,0.071442954,0.00032172338,0.0027755098,0.0072187874,0.0026380548,0.179662,0.4738321,0.052906185,0.2076073,0.00057573913],"about_ca_topic_score_codex":0.0013893275,"about_ca_topic_score_gemma":0.0024653806,"teacher_disagreement_score":0.0065733884,"about_ca_system_score_codex":0.00041612124,"about_ca_system_score_gemma":0.001951395,"threshold_uncertainty_score":0.034763873},"labels":[],"label_agreement":null},{"id":"W2345039138","doi":"10.1002/jmri.25269","title":"MRI in the evaluation of localization‐related epilepsy","year":2016,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; University Health Network; Hospital for Sick Children","funders":"","keywords":"Epilepsy; Diffusion MRI; Neuroimaging; Epilepsy surgery; Medicine; White matter; Magnetic resonance imaging; Radiology; Lesion; Medical physics; Pathology; Psychiatry","score_opus":0.09849419431217071,"score_gpt":0.42647568063472696,"score_spread":0.32798148632255625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345039138","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015979464,0.9975616,0.00021238791,0.00031068388,0.00017532376,0.0000036860754,0.0000074137797,0.000010160512,0.001559022],"genre_scores_gemma":[0.0026679726,0.99549747,0.00055001385,0.00036485645,0.0004926337,0.0000062459353,0.000020017153,0.0000046402,0.0003961014],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9995472,0.00011527724,0.00008391702,0.00006537795,0.00015319248,0.00003499163],"domain_scores_gemma":[0.9988696,0.0006421427,0.00017161193,0.000031954172,0.00022929769,0.000055373483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008895218,0.0010959092,0.0013118215,0.00498669,0.00031483392,0.0010944809,0.00085081864,0.0016462159,0.0023392644],"category_scores_gemma":[0.0019318978,0.000323824,0.0005428748,0.003287494,0.0013648382,0.0021214788,0.0008717099,0.0022477969,0.0023510924],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048694015,0.000045302582,0.0011839758,0.0104825795,0.00007636085,0.0017825373,0.0001907246,0.00029306294,0.0013729043,0.0032252579,0.02484872,0.9564499],"study_design_scores_gemma":[0.000024380766,0.00013076254,0.006742235,0.017956918,0.00020156533,0.063711144,0.0004082954,0.00028023918,0.0010073261,0.0061611766,0.90330726,0.000068629335],"about_ca_topic_score_codex":0.001482995,"about_ca_topic_score_gemma":0.0021992454,"teacher_disagreement_score":0.00498669,"about_ca_system_score_codex":0.0006015469,"about_ca_system_score_gemma":0.0009135729,"threshold_uncertainty_score":0.007825673},"labels":[],"label_agreement":null},{"id":"W2345819060","doi":"10.1016/j.nicl.2016.04.013","title":"Integrity of the arcuate fasciculus in patients with schizophrenia with auditory verbal hallucinations: A DTI-tractography study","year":2016,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Canadian Institutes of Health Research; Brain and Behavior Research Foundation","keywords":"Arcuate fasciculus; Fasciculus; Fractional anisotropy; Schizophrenia (object-oriented programming); Tractography; White matter; Psychology; Diffusion MRI; Audiology; Psychosis; Neuroscience; Uncinate fasciculus; Medicine; Anatomy; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.06868667258836783,"score_gpt":0.37374370511709815,"score_spread":0.3050570325287303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345819060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999759,0.000046649617,0.00006738854,0.000008566928,5.220639e-7,0.0000036682266,0.000038672788,0.0000014078207,0.00007410011],"genre_scores_gemma":[0.99977666,0.000033125383,0.000083818144,0.000004546991,0.0000015689827,0.0000028905192,0.000049996237,9.915043e-7,0.00004638754],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998884,0.000022135548,0.00001883009,0.000029146591,0.000019803196,0.000021708753],"domain_scores_gemma":[0.99958485,0.00006763205,0.00021530925,0.000028230956,0.000035218396,0.00006875046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022497274,0.0002852113,0.00021871534,0.00072309957,0.0002657051,0.00029977862,0.00009562834,0.00024740832,0.0010523635],"category_scores_gemma":[0.00094983773,0.00018320912,0.00016993932,0.0003029942,0.0003583596,0.0002710143,0.0002543176,0.00016326454,0.00016035748],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007635519,0.000060512826,0.9753921,0.00003284348,0.00007220755,0.0017167103,0.0007444632,0.00013580814,0.016400622,0.000045221288,0.00004524885,0.004590719],"study_design_scores_gemma":[0.000010691641,0.00014955224,0.99688303,0.0000042018833,0.000016720624,0.0020302245,0.00023672816,0.00023025146,0.00032524773,0.000040151608,0.000068920344,0.000004270398],"about_ca_topic_score_codex":0.0033128243,"about_ca_topic_score_gemma":0.0039972602,"teacher_disagreement_score":0.0033128243,"about_ca_system_score_codex":0.00023335447,"about_ca_system_score_gemma":0.00022473327,"threshold_uncertainty_score":0.006587088},"labels":[],"label_agreement":null},{"id":"W2346434957","doi":"10.1111/adb.12363","title":"Characterization of white matter integrity deficits in cocaine‐dependent individuals with substance‐induced psychosis compared with non‐psychotic cocaine users","year":2016,"lang":"en","type":"article","venue":"Addiction Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; AstraZeneca","keywords":"White matter; Psychosis; Fractional anisotropy; Diffusion MRI; Psychology; Corpus callosum; Schizophrenia (object-oriented programming); Neuroscience; Corona radiata (embryology); Voxel; Internal medicine; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04531289078426361,"score_gpt":0.31965017137040164,"score_spread":0.27433728058613804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346434957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997439,0.000030390798,0.00002807943,0.000006582865,5.3460235e-7,0.000004399577,0.000027044522,0.000001464504,0.00015772396],"genre_scores_gemma":[0.99973065,0.000029442801,0.00009357,0.000007468447,0.000001514368,0.0000050761923,0.000050338684,0.0000013654363,0.00008044229],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999063,0.000014943102,0.000015206573,0.000027207352,0.000017770592,0.000018502049],"domain_scores_gemma":[0.9996921,0.000041251373,0.00014307449,0.000018940964,0.000024603936,0.00008003799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023001296,0.0002556374,0.00021028452,0.0013204443,0.000319266,0.00031768167,0.0001377212,0.0002663341,0.0015558721],"category_scores_gemma":[0.00082588807,0.00016227821,0.00014147542,0.00037441796,0.00037096793,0.00025678868,0.0004345292,0.00019590561,0.00014981383],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008150454,0.0001279457,0.95436764,0.000041828393,0.00008354162,0.0012262638,0.0009813742,0.000085330576,0.034607228,0.00009638581,0.00009017932,0.007477202],"study_design_scores_gemma":[0.0000038723742,0.00013657608,0.99847966,0.000002751272,0.00000793806,0.0007682925,0.00015388105,0.000067447,0.00031645302,0.000025663036,0.00003591148,0.0000014834045],"about_ca_topic_score_codex":0.00206525,"about_ca_topic_score_gemma":0.003248825,"teacher_disagreement_score":0.00206525,"about_ca_system_score_codex":0.00019067021,"about_ca_system_score_gemma":0.00014226856,"threshold_uncertainty_score":0.0052048564},"labels":[],"label_agreement":null},{"id":"W2347466196","doi":"10.1371/journal.pone.0155557","title":"ZOOM or Non-ZOOM? Assessing Spinal Cord Diffusion Tensor Imaging Protocols for Multi-Centre Studies","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"National Institute of Neurological Disorders and Stroke; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds de recherche du Québec – Nature et technologies; International Spinal Research Trust; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Multiple Sclerosis Society; Wings for Life","keywords":"Diffusion MRI; Scanner; Echo-planar imaging; Reproducibility; Spinal cord; White matter; Computer science; Zoom; Biomedical engineering; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Mathematics; Radiology; Optics","score_opus":0.4180598378084749,"score_gpt":0.4811919151031335,"score_spread":0.06313207729465864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2347466196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5140462,0.010984597,0.46263295,0.0015465331,0.0009179948,0.0027232368,0.00063905923,0.0019633088,0.0045460383],"genre_scores_gemma":[0.59968585,0.0014439048,0.39412582,0.00051356765,0.00016015246,0.0023904326,0.0004386008,0.0006818384,0.00055985013],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99051756,0.005820037,0.0009679154,0.001025602,0.0015159613,0.00015290572],"domain_scores_gemma":[0.97895765,0.006530193,0.0044146897,0.004842858,0.004674834,0.0005797888],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.023036597,0.00075505546,0.00075006916,0.0009627637,0.00067119114,0.0016033814,0.0011612931,0.0012016984,0.0016144563],"category_scores_gemma":[0.049982782,0.000643551,0.0006900708,0.0008583594,0.0008177337,0.0017464054,0.0014363261,0.000736611,0.0005368034],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0077898013,0.0011942761,0.08095606,0.0034546223,0.0024773164,0.0007704542,0.0037931728,0.014657448,0.25615805,0.0054969564,0.006619418,0.6166324],"study_design_scores_gemma":[0.0024584911,0.017756568,0.5923527,0.0026095014,0.003327117,0.008181735,0.0021365895,0.10283659,0.19006257,0.0146292085,0.06259045,0.0010585098],"about_ca_topic_score_codex":0.00080627913,"about_ca_topic_score_gemma":0.0018649145,"teacher_disagreement_score":0.9769634,"about_ca_system_score_codex":0.0005987843,"about_ca_system_score_gemma":0.0009865133,"threshold_uncertainty_score":0.12183064},"labels":[],"label_agreement":null},{"id":"W2350722100","doi":"","title":"Change of MR diffusion tensor imaging and its correlation with cognitive impairment in patients with cerebral small vessel disease","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Caudate nucleus; Dementia; Frontal lobe; White matter; Medicine; Neuropsychology; Internal medicine; Cardiology; Psychology; Cognition; Correlation; Magnetic resonance imaging; Neuroscience; Radiology; Disease","score_opus":0.024709243266931583,"score_gpt":0.2699094831966479,"score_spread":0.24520023992971635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2350722100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99921286,0.0003701467,0.000068124915,0.000033956738,0.0000045938973,0.0000050350127,0.000049001428,0.000003148337,0.00025315848],"genre_scores_gemma":[0.99965453,0.00011096518,0.00008240619,0.0000100517655,0.000012802263,0.0000031650825,0.000061117375,5.7281017e-7,0.000064456595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998161,0.000033628472,0.00003364342,0.0000377335,0.00004282663,0.00003617907],"domain_scores_gemma":[0.9993793,0.000094198665,0.00030961313,0.000023321943,0.00008532618,0.00010819269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029402022,0.00034312316,0.0003202424,0.0008875165,0.00028652308,0.0003531141,0.00015853187,0.00032003943,0.0008129544],"category_scores_gemma":[0.0016865958,0.00012535663,0.00023488577,0.0005302719,0.00030147625,0.0003226376,0.00021378092,0.00030700988,0.00014172873],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018877909,0.000045535213,0.99518037,0.000020822326,0.000049506412,0.00058326416,0.00009593601,0.000051843403,0.00070826936,0.000012010879,0.000063243984,0.0030003286],"study_design_scores_gemma":[0.0000093440785,0.00017133752,0.9974227,0.000005874596,0.000028294793,0.0017567532,0.00012937984,0.00020879884,0.00013637531,0.000031077558,0.00009558915,0.000004420313],"about_ca_topic_score_codex":0.0018047713,"about_ca_topic_score_gemma":0.0018686363,"teacher_disagreement_score":0.0018047713,"about_ca_system_score_codex":0.00016653887,"about_ca_system_score_gemma":0.0001785537,"threshold_uncertainty_score":0.0035885572},"labels":[],"label_agreement":null},{"id":"W2351131966","doi":"","title":"The Changes of Cerebral White Matter MR Diffusion Tensor Imaging of Brain on Patients of Mild Cognitive Impairment and Its Relationship with Cognitive Dysfunction","year":2015,"lang":"en","type":"article","venue":"Medical Innovation of China","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Montreal Cognitive Assessment; Diffusion MRI; Internal medicine; Cognition; Ischemia; Parahippocampal gyrus; Magnetic resonance imaging; Cardiology; Cognitive impairment; Radiology; Psychiatry; Temporal lobe","score_opus":0.04715136043640825,"score_gpt":0.32559953937687075,"score_spread":0.2784481789404625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2351131966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999218,0.00034468411,0.000040484705,0.00002952609,0.000006125476,0.000007368883,0.000065444365,0.0000019122663,0.00028662203],"genre_scores_gemma":[0.9995962,0.00010955101,0.000032957803,0.000013313172,0.000014645467,0.0000056305107,0.0001049894,3.6218987e-7,0.00012242518],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980766,0.000025357782,0.000028575794,0.000039661878,0.00004183196,0.00005689412],"domain_scores_gemma":[0.99953544,0.000040250685,0.00022483003,0.00001806814,0.00006985724,0.00011163677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002406369,0.00041772134,0.00033140593,0.0007274408,0.0003408559,0.00034019072,0.00018500829,0.0002931472,0.0012129032],"category_scores_gemma":[0.0011441561,0.00012610138,0.00027796763,0.00032962655,0.0002481579,0.0002744345,0.0002892957,0.00031584283,0.00015312842],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003962236,0.00008645356,0.9947937,0.000034210054,0.00008884362,0.00051359856,0.00012216743,0.00004434678,0.00066522806,0.000016853613,0.00013468697,0.0031036746],"study_design_scores_gemma":[0.000012890115,0.0002231493,0.99817216,0.000009313036,0.000034131197,0.0010198685,0.00013131964,0.00009500129,0.00012621409,0.000027543974,0.00014482805,0.0000035040516],"about_ca_topic_score_codex":0.0014954759,"about_ca_topic_score_gemma":0.0024058118,"teacher_disagreement_score":0.0014954759,"about_ca_system_score_codex":0.0002384237,"about_ca_system_score_gemma":0.00022563674,"threshold_uncertainty_score":0.0040575266},"labels":[],"label_agreement":null},{"id":"W2358442394","doi":"","title":"A magnetic resonance diffusion tensor imaging analysis of the hippocampus in patients with mild cognitive impairment","year":2012,"lang":"en","type":"article","venue":"Journal of Shandong University","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Montreal Cognitive Assessment; Cognitive impairment; Magnetic resonance imaging; Correlation; Medicine; Hippocampus; Effective diffusion coefficient; Internal medicine; Nuclear medicine; Cognition; Psychology; Audiology; Radiology; Psychiatry; Geometry; Mathematics","score_opus":0.013895819982988614,"score_gpt":0.25166539471123855,"score_spread":0.23776957472824994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2358442394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937975,0.00018930883,0.00005589611,0.000020679334,0.0000036944493,0.000009348272,0.000065981796,0.0000028690636,0.00027251997],"genre_scores_gemma":[0.9996544,0.00005457437,0.0001036696,0.000015371537,0.000007814947,0.0000044228454,0.000075617856,5.256571e-7,0.00008366335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999049,0.000014426357,0.00001675582,0.000024335806,0.00002211884,0.00001737481],"domain_scores_gemma":[0.9996902,0.000037706373,0.00012504375,0.0000138744435,0.000057544727,0.000075731485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025134705,0.00037662478,0.00029533135,0.0009490227,0.00035741468,0.00027953056,0.00013590837,0.00022749431,0.0007809317],"category_scores_gemma":[0.0011289611,0.0001211278,0.00020517193,0.0002821379,0.00020773825,0.00027943598,0.00021252372,0.00015674243,0.00014773094],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006792426,0.00008332948,0.9871662,0.000046541347,0.000071253526,0.0011167888,0.00019974935,0.00006848269,0.0048632203,0.000020354117,0.00015028272,0.0055346065],"study_design_scores_gemma":[0.000026074069,0.00034279033,0.99586403,0.0000069283196,0.000031025324,0.0028794792,0.00017008625,0.00018489663,0.00030934255,0.00004565519,0.00013546627,0.000004127296],"about_ca_topic_score_codex":0.0030666455,"about_ca_topic_score_gemma":0.004141761,"teacher_disagreement_score":0.0030666455,"about_ca_system_score_codex":0.00020557376,"about_ca_system_score_gemma":0.00022069577,"threshold_uncertainty_score":0.0060976148},"labels":[],"label_agreement":null},{"id":"W2359665709","doi":"10.1155/2016/7526135","title":"Motor Skill Acquisition Promotes Human Brain Myelin Plasticity","year":2016,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Myelin; White matter; Neuroplasticity; Neuroscience; Psychology; Diffusion MRI; Intraparietal sulcus; Motor skill; Central sulcus; Human brain; Motor learning; Coactivation; Dreyfus model of skill acquisition; Motor cortex; Medicine; Magnetic resonance imaging; Functional magnetic resonance imaging; Central nervous system; Electromyography; Stimulation","score_opus":0.04988203912802484,"score_gpt":0.34109551376306313,"score_spread":0.29121347463503827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2359665709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994856,0.0000613241,0.00018183791,0.000008456906,5.6988347e-7,0.0000029370428,0.000011070202,0.0000032043827,0.00024492192],"genre_scores_gemma":[0.99936765,0.000060401482,0.0002269788,0.0000050974077,0.0000012429442,0.0000030706155,0.000020200861,0.0000010860421,0.0003142981],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994206,0.000012334845,0.0000031266468,0.000014610935,0.000012434126,0.0000154667],"domain_scores_gemma":[0.9998523,0.0000376491,0.00005662822,0.0000105243425,0.000013845364,0.000029023828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015248629,0.00011297423,0.00009719119,0.00012964456,0.000062178144,0.00011602761,0.000055443754,0.00011531738,0.0019498772],"category_scores_gemma":[0.00051305053,0.00006359038,0.00004955422,0.00005178172,0.00011713784,0.00012334141,0.00021113957,0.00012027586,0.00014280446],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010560072,0.00060760125,0.06754388,0.0001583977,0.000048854155,0.00039607263,0.0005452732,0.0003866022,0.8663684,0.00015988166,0.00019510061,0.062533885],"study_design_scores_gemma":[0.000017713408,0.0021941108,0.9546093,0.00001145822,0.000011202188,0.0005959301,0.00010503815,0.0005530982,0.04106607,0.00015391519,0.0006764891,0.000005685721],"about_ca_topic_score_codex":0.00055686245,"about_ca_topic_score_gemma":0.0013112138,"teacher_disagreement_score":0.0019498772,"about_ca_system_score_codex":0.000082035884,"about_ca_system_score_gemma":0.00009703866,"threshold_uncertainty_score":0.006523013},"labels":[],"label_agreement":null},{"id":"W2369402140","doi":"","title":"Correlation Between Deep Brain White Matter Ischemia and MR Diffusion Tensor Imaging of Mild Cognitive Impairment","year":2013,"lang":"en","type":"article","venue":"Zhongguo yixue yingxiangxue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Montreal Cognitive Assessment; White matter; Fractional anisotropy; Medicine; Cognitive impairment; Magnetic resonance imaging; Nuclear medicine; Internal medicine; Cognition; Cardiology; Radiology; Psychiatry","score_opus":0.021722185593413632,"score_gpt":0.29931712714328856,"score_spread":0.2775949415498749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2369402140","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99912304,0.00038118678,0.00008664029,0.00003683765,0.0000062327135,0.00000771933,0.00005865323,0.0000037318528,0.00029592504],"genre_scores_gemma":[0.9995572,0.00009451367,0.000080666396,0.000015538766,0.000016213698,0.0000046106384,0.000084743646,6.718257e-7,0.0001458789],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981266,0.000030770014,0.000029700986,0.00004617012,0.00003821058,0.00004244201],"domain_scores_gemma":[0.99923635,0.00007432551,0.0003953586,0.0000344865,0.0000809257,0.00017861518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031485793,0.00047082079,0.00037383658,0.00083856215,0.0003663586,0.00034408557,0.00020367715,0.0003323206,0.001600318],"category_scores_gemma":[0.0013639514,0.00014680484,0.0002677709,0.0002842582,0.00033172074,0.00022066211,0.00033341764,0.0003454949,0.00019372729],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038730595,0.00008418385,0.9937085,0.000031770913,0.00009207248,0.00051759987,0.00008096554,0.000058658992,0.0015204926,0.000029082676,0.0000834048,0.003406112],"study_design_scores_gemma":[0.000010118262,0.00024172828,0.99788386,0.00000605644,0.00002935404,0.0013208481,0.00006507698,0.00012348828,0.00016289063,0.000050961127,0.00010180087,0.0000038110375],"about_ca_topic_score_codex":0.0017574581,"about_ca_topic_score_gemma":0.002084088,"teacher_disagreement_score":0.0017574581,"about_ca_system_score_codex":0.0001769485,"about_ca_system_score_gemma":0.00021773326,"threshold_uncertainty_score":0.0053536296},"labels":[],"label_agreement":null},{"id":"W2370336172","doi":"","title":"The Observation of Water Compartmentalization In-Vivo in the Feline Lumbar Spinal Cord","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Grey matter; White matter; Spinal cord; Compartmentalization (fire protection); In vivo; Myelin; Anatomy; Pathology; Neuroscience; Chemistry; Nuclear medicine; Medicine; Nuclear magnetic resonance; Biology; Central nervous system; Magnetic resonance imaging; Physics; Radiology","score_opus":0.12227924569488281,"score_gpt":0.3881954848884261,"score_spread":0.2659162391935433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2370336172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886713,0.0023288112,0.007351918,0.00013659622,0.000012463593,0.000015004971,0.00018152321,0.000080468744,0.0012219192],"genre_scores_gemma":[0.99077046,0.0013439478,0.005010444,0.000058677466,0.0000081925455,0.000017588756,0.00017515199,0.000021196029,0.0025943706],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999745,0.000003410998,0.0000011377342,0.0000074795644,0.0000048337497,0.000008554208],"domain_scores_gemma":[0.9999081,0.000024456636,0.00002158274,0.000006467744,0.000024826235,0.000014564267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015658679,0.00014569187,0.00011275124,0.0002818916,0.00022760798,0.00019007121,0.00018046008,0.0002713201,0.0007679065],"category_scores_gemma":[0.00019577995,0.000112654205,0.00006767047,0.000111457564,0.00027701596,0.00025373147,0.00014168277,0.00031407125,0.00018026523],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009895227,0.0000044517456,0.00054291246,0.000033815606,0.000003033251,0.00012491764,0.000039967443,0.000047827285,0.996738,0.00004478588,0.00003686685,0.0022843336],"study_design_scores_gemma":[0.000013619546,0.0003313071,0.054611705,0.000024124227,0.00003653954,0.0013351963,0.00022165278,0.001854127,0.9390689,0.00017777346,0.0023091903,0.000015789115],"about_ca_topic_score_codex":0.004917053,"about_ca_topic_score_gemma":0.008339224,"teacher_disagreement_score":0.004917053,"about_ca_system_score_codex":0.00034816936,"about_ca_system_score_gemma":0.0001367158,"threshold_uncertainty_score":0.00977689},"labels":[],"label_agreement":null},{"id":"W2375759623","doi":"","title":"Quantitative research of diffusion tensor imaging in cognitive impairment of Parkinson's disease","year":2015,"lang":"en","type":"article","venue":"Chinese Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Putamen; White matter; Caudate nucleus; Diffusion MRI; Substantia nigra; Medicine; Globus pallidus; Parkinson's disease; Striatum; Neuroscience; Magnetic resonance imaging; Internal medicine; Psychology; Basal ganglia; Dopamine; Radiology; Central nervous system; Disease","score_opus":0.10400253968027091,"score_gpt":0.4360482739120871,"score_spread":0.3320457342318162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2375759623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844232,0.0046363357,0.008144636,0.00014524984,0.00003206517,0.000092385686,0.0007272785,0.00007091912,0.0017279346],"genre_scores_gemma":[0.9945446,0.0005352227,0.0042354222,0.000014830932,0.000032031698,0.00004966075,0.00025967398,0.000006618182,0.00032197314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949896,0.0001643676,0.00006564801,0.000086779924,0.00015038547,0.00003381591],"domain_scores_gemma":[0.99882597,0.00023644179,0.00049784227,0.00006578204,0.00028582537,0.00008822899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001518879,0.0005254438,0.00021654055,0.0020123052,0.00020126595,0.0005749747,0.0002692868,0.00029117038,0.00079278497],"category_scores_gemma":[0.0036194941,0.00011100234,0.00025538623,0.00077551807,0.00039941465,0.00045803422,0.00030597052,0.00018099634,0.00015438325],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020593142,0.00028631932,0.74195474,0.001619847,0.0008856358,0.001244132,0.0017858424,0.0038216142,0.0639578,0.0013733973,0.0013939366,0.17961738],"study_design_scores_gemma":[0.0000729727,0.000795908,0.9749531,0.00011438995,0.000212363,0.0032294735,0.00061991106,0.01007559,0.006402947,0.0014538695,0.0020218138,0.000047608395],"about_ca_topic_score_codex":0.0015251262,"about_ca_topic_score_gemma":0.0014590764,"teacher_disagreement_score":0.0020123052,"about_ca_system_score_codex":0.0003379279,"about_ca_system_score_gemma":0.0002196139,"threshold_uncertainty_score":0.00803268},"labels":[],"label_agreement":null},{"id":"W2377901611","doi":"","title":"A diffusion tensor imaging study of white matter lesion in amnesic mild cognitive impairment","year":2010,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Fractional anisotropy; Audiology; Diffusion MRI; White matter; Psychology; Cognition; Verbal fluency test; Cognitive impairment; Neuropsychology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.26431484410636186,"score_gpt":0.5768198277249041,"score_spread":0.3125049836185423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2377901611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988318,0.0004277127,0.00022911349,0.000049580514,0.0000059352865,0.000021704745,0.000054829146,0.0000053279014,0.00037390162],"genre_scores_gemma":[0.998965,0.00019748046,0.0005152792,0.000016484075,0.000013536561,0.00001132072,0.00007794561,0.0000015407156,0.0002013881],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999057,0.000019234965,0.000017891995,0.000017868124,0.000019646202,0.000019584751],"domain_scores_gemma":[0.9997845,0.000017271948,0.000086170774,0.000013330672,0.000043907963,0.000054795888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042153813,0.0004104303,0.00017436985,0.0011804703,0.00028162808,0.00019981351,0.0001793355,0.00022163182,0.0006908983],"category_scores_gemma":[0.0009555434,0.00015618624,0.00018655081,0.00036455793,0.00038683115,0.0003634466,0.0002640993,0.00019891912,0.00014919371],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024868727,0.0006733981,0.8427474,0.00030924287,0.0002741274,0.010559078,0.0017683154,0.0003434972,0.101823986,0.0003517396,0.0006352342,0.038027037],"study_design_scores_gemma":[0.00005021369,0.00077907735,0.9870776,0.0000132987825,0.0000435346,0.00946015,0.00026899495,0.00044840545,0.0013241966,0.00016600467,0.00035887957,0.000009612604],"about_ca_topic_score_codex":0.0035385115,"about_ca_topic_score_gemma":0.0023512477,"teacher_disagreement_score":0.0035385115,"about_ca_system_score_codex":0.00029789397,"about_ca_system_score_gemma":0.00029632048,"threshold_uncertainty_score":0.0070358515},"labels":[],"label_agreement":null},{"id":"W2386694087","doi":"","title":"The application of diffusion tensor imaging on 3.0T MR in amnestic mild cognitive impairment","year":2012,"lang":"en","type":"article","venue":"Journal of China Clinic Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Splenium; Medicine; Fractional anisotropy; Cognitive impairment; White matter; Montreal Cognitive Assessment; Parahippocampal gyrus; Cognition; Magnetic resonance imaging; Audiology; Nuclear medicine; Radiology; Temporal lobe; Psychiatry; Epilepsy","score_opus":0.04121147298681041,"score_gpt":0.4130964285146729,"score_spread":0.3718849555278625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2386694087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990546,0.00045297935,0.00013421674,0.00004002887,0.0000035173857,0.0000070508477,0.000037761583,0.00000584036,0.00026388458],"genre_scores_gemma":[0.9993253,0.00019704741,0.00036037015,0.000011073062,0.000006992169,0.000004795836,0.00003551462,7.41006e-7,0.000058260768],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998987,0.000028244855,0.000016978822,0.00002083547,0.000019425517,0.000015886004],"domain_scores_gemma":[0.9997224,0.000035886118,0.0001261347,0.000016755317,0.000057192814,0.00004158581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047270683,0.00034388748,0.00016236272,0.00080707663,0.00024276183,0.0002469996,0.00012530011,0.00022999191,0.00032265543],"category_scores_gemma":[0.0012759063,0.00008787108,0.00015290255,0.00023175779,0.00024629646,0.00028484745,0.00019868085,0.00014170048,0.000060475537],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012057591,0.00012918776,0.93192655,0.000111602734,0.000088884924,0.0021338852,0.00051015924,0.00032415616,0.02572818,0.000055130306,0.00026752145,0.03751905],"study_design_scores_gemma":[0.000028211713,0.00032511007,0.9927751,0.000019435949,0.000058541274,0.0025710266,0.00028622785,0.00091172074,0.002608544,0.00013388658,0.00027218007,0.000010019759],"about_ca_topic_score_codex":0.0034444716,"about_ca_topic_score_gemma":0.0032055625,"teacher_disagreement_score":0.0034444716,"about_ca_system_score_codex":0.00023117493,"about_ca_system_score_gemma":0.00018374252,"threshold_uncertainty_score":0.006848812},"labels":[],"label_agreement":null},{"id":"W2388595031","doi":"","title":"Study of microstructural white matter lesions in patients with mild cognitive impairment and mild and moderate Alzheimer disease","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Splenium; Fractional anisotropy; Corpus callosum; White matter; Internal capsule; Diffusion MRI; Cognitive impairment; Internal medicine; Parietal lobe; Medicine; Psychology; Audiology; Cardiology; Pathology; Disease; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.03113333164979861,"score_gpt":0.32048516422925916,"score_spread":0.28935183257946057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2388595031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99932194,0.00024829968,0.00004014216,0.000022782773,0.0000041108465,0.000008837256,0.00006351076,0.0000020739192,0.00028829378],"genre_scores_gemma":[0.99956244,0.000075178046,0.00007982531,0.000022891478,0.000013792675,0.000008131883,0.00011103403,6.8546416e-7,0.00012600668],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998534,0.000024907213,0.000024192525,0.00004004605,0.000028349034,0.000029035902],"domain_scores_gemma":[0.99963117,0.000040936953,0.00015162463,0.000014979578,0.000049204664,0.00011215447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000298998,0.00040014068,0.00040696398,0.0007405691,0.00046983248,0.00036170677,0.00017888872,0.00041472667,0.0013567351],"category_scores_gemma":[0.0009793582,0.00016770215,0.00019993873,0.0003688728,0.0002355204,0.00035487657,0.00027513847,0.00022386157,0.00023444364],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009546917,0.00017213843,0.9888362,0.00005896827,0.00012477726,0.0008490297,0.00034165406,0.00004921817,0.0029818788,0.000027803548,0.0001564974,0.0054470827],"study_design_scores_gemma":[0.000020574824,0.0003426187,0.997741,0.0000048187694,0.00002065939,0.0013294973,0.0001877692,0.000057715515,0.000097874596,0.00002892012,0.00016553878,0.0000029749704],"about_ca_topic_score_codex":0.0021921915,"about_ca_topic_score_gemma":0.0029579576,"teacher_disagreement_score":0.0021921915,"about_ca_system_score_codex":0.00016625122,"about_ca_system_score_gemma":0.00017849395,"threshold_uncertainty_score":0.0045386553},"labels":[],"label_agreement":null},{"id":"W2389283394","doi":"","title":"Diffusion Tensor Imaging in Acute Ischemic Stroke: Usefulness of Fractional Anisotropy","year":2006,"lang":"en","type":"article","venue":"Journal of the Korean Neurological Association","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; Modified Rankin Scale; Cardiology; Stroke (engine); Internal medicine; Penumbra; Magnetic resonance imaging; Infarction; Ischemic stroke; Anesthesia; Ischemia; Radiology; Myocardial infarction","score_opus":0.02168075310410963,"score_gpt":0.2859440296971228,"score_spread":0.2642632765930132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2389283394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9605623,0.03059194,0.005589026,0.0008137442,0.00006302813,0.00005702002,0.00031427928,0.000065056774,0.0019436197],"genre_scores_gemma":[0.99090075,0.0052428287,0.0033845294,0.000032069176,0.00014093494,0.000015974658,0.00012465012,0.0000047457293,0.00015359667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997389,0.00011713001,0.000036373083,0.000032399363,0.00005596742,0.000019221212],"domain_scores_gemma":[0.99884427,0.00039622845,0.00050500507,0.000052920517,0.00012070406,0.00008080882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012084013,0.0005253104,0.00026027998,0.001147928,0.00012901155,0.00040983345,0.0002142045,0.00029225615,0.00058992556],"category_scores_gemma":[0.002988886,0.00008112855,0.00018252057,0.000642409,0.0004797621,0.00050607795,0.00020053975,0.00031889882,0.00018731064],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006865236,0.00015041912,0.86526525,0.00042297554,0.0002662026,0.0007871018,0.00014624099,0.0013261597,0.012699478,0.00045690528,0.0009959391,0.116796784],"study_design_scores_gemma":[0.000046271885,0.00072380574,0.9796012,0.00013144237,0.00021555343,0.005846197,0.00016051205,0.005353913,0.0032042982,0.002060436,0.0026240747,0.000032298576],"about_ca_topic_score_codex":0.0006127467,"about_ca_topic_score_gemma":0.0005380148,"teacher_disagreement_score":0.0012084013,"about_ca_system_score_codex":0.0001853503,"about_ca_system_score_gemma":0.00026455926,"threshold_uncertainty_score":0.006390691},"labels":[],"label_agreement":null},{"id":"W2397498493","doi":"10.1111/jon.12359","title":"Neurite Orientation Dispersion and Density Imaging Color Maps to Characterize Brain Diffusion in Neurologic Disorders","year":2016,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"White matter; Diffusion MRI; Medicine; Diffusion imaging; Orientation (vector space); Multiple sclerosis; Pathology; Neurite; Artificial intelligence; Magnetic resonance imaging; Radiology; Computer science; Biology","score_opus":0.028421646163467092,"score_gpt":0.3131157431984131,"score_spread":0.284694097034946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397498493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34307337,0.0033825152,0.6457249,0.0003142676,0.00007332381,0.00020061631,0.0008769524,0.0013633813,0.0049907262],"genre_scores_gemma":[0.66129017,0.0021312481,0.333899,0.00008404373,0.000039509054,0.00020444131,0.0005300686,0.00024515463,0.0015763883],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998808,0.000036323578,0.0000074911127,0.000020294347,0.000042268177,0.000012695664],"domain_scores_gemma":[0.9995647,0.00014154406,0.000067272136,0.00005207577,0.00013409907,0.00004023843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006312952,0.00058140885,0.00023500223,0.0014465511,0.00017737673,0.0005281055,0.00033135252,0.00032503245,0.0011904524],"category_scores_gemma":[0.0015248292,0.00016318719,0.00022952135,0.000797773,0.00027697187,0.0006893271,0.0004682906,0.0003770494,0.00024388678],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093958364,0.00019292634,0.024689367,0.0010993319,0.00018356144,0.00046964848,0.00040983202,0.04471993,0.56059545,0.008061718,0.002225295,0.35641325],"study_design_scores_gemma":[0.00005519527,0.00036909137,0.036041934,0.00016403831,0.00017248989,0.0026568156,0.00023630395,0.5760826,0.36441705,0.0086401,0.011028536,0.00013584543],"about_ca_topic_score_codex":0.0012208447,"about_ca_topic_score_gemma":0.0014873919,"teacher_disagreement_score":0.0014465511,"about_ca_system_score_codex":0.00043967905,"about_ca_system_score_gemma":0.00046011244,"threshold_uncertainty_score":0.0039824843},"labels":[],"label_agreement":null},{"id":"W2399008936","doi":"10.1002/nbm.3549","title":"Differences in iron and manganese concentration may confound the measurement of myelin from <i>R</i><sub>1</sub> and <i>R</i><sub>2</sub> relaxation rates in studies of dysmyelination","year":2016,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre; University of Toronto; McMaster University; Sunnybrook Hospital; Sunnybrook Health Science Centre","funders":"Diamond Light Source","keywords":"White matter; Chemistry; Myelin; Manganese; Analytical Chemistry (journal); Nuclear magnetic resonance; Relaxation (psychology); Magnetic resonance imaging; Biology; Physics; Chromatography; Central nervous system","score_opus":0.07151617025963065,"score_gpt":0.3341724110686814,"score_spread":0.26265624080905076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399008936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90184563,0.002721101,0.09067212,0.00041641458,0.00016928787,0.0001856526,0.0005721086,0.0005814803,0.0028362444],"genre_scores_gemma":[0.9182292,0.0015080268,0.075714886,0.00054827525,0.000038783495,0.00036950182,0.00042057034,0.00031809125,0.0028526692],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863714,0.000338103,0.0001507257,0.00047122248,0.00028806293,0.0001147131],"domain_scores_gemma":[0.99859625,0.00047173645,0.0003993196,0.00019159853,0.000242179,0.00009898408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029874241,0.000655552,0.000712407,0.0008102248,0.0006885785,0.0006446304,0.00094941293,0.0007879253,0.0012540347],"category_scores_gemma":[0.0028819456,0.0005648717,0.00026876328,0.00045016236,0.0013894949,0.000705947,0.00072558975,0.0008893458,0.0003804512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000244162,0.00004491497,0.005517873,0.00021806746,0.000059779377,0.0001445469,0.00017318566,0.00015309796,0.9879529,0.0005119327,0.00012565436,0.004853862],"study_design_scores_gemma":[0.000026443156,0.00068078755,0.05924473,0.000055925735,0.00019875879,0.0014505195,0.00029067742,0.0021088556,0.93021274,0.0014435471,0.0042584357,0.000028736367],"about_ca_topic_score_codex":0.002679288,"about_ca_topic_score_gemma":0.009260148,"teacher_disagreement_score":0.0029874241,"about_ca_system_score_codex":0.00061095116,"about_ca_system_score_gemma":0.00041242034,"threshold_uncertainty_score":0.015799224},"labels":[],"label_agreement":null},{"id":"W2399294503","doi":"10.1007/978-3-319-19992-4_63","title":"Functional Nonlinear Mixed Effects Models for Longitudinal Image Data","year":2015,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Covariance operator; Computer science; Nonlinear system; Covariance; Functional data analysis; Artificial intelligence; Random effects model; Covariate; Algorithm; Machine learning; Data mining; Statistics; Mathematics","score_opus":0.1640109882639426,"score_gpt":0.38354205146568476,"score_spread":0.21953106320174218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399294503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0053645945,0.0010596284,0.99147207,0.00047114227,0.000116508956,0.00006809576,0.00069344696,0.00048837246,0.00026618774],"genre_scores_gemma":[0.27438384,0.0041397004,0.6927731,0.0005852839,0.00083953503,0.0025473787,0.00577514,0.0009589098,0.017997127],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99570763,0.0027191353,0.00020690866,0.00084154954,0.00027062418,0.00025413165],"domain_scores_gemma":[0.9801853,0.016141113,0.001020534,0.0013839591,0.0009706174,0.00029839823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013861262,0.0022412818,0.0028307107,0.0020014027,0.0008670412,0.0024064952,0.0050838604,0.0038519243,0.0064711403],"category_scores_gemma":[0.029755592,0.0027998376,0.004217316,0.0028078547,0.00173841,0.0030355353,0.00279399,0.0044434112,0.0019135544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013706641,0.00034814837,0.0069162147,0.00087296375,0.002431404,0.00058841694,0.0006332204,0.65199816,0.0032759157,0.1654305,0.008357375,0.15777707],"study_design_scores_gemma":[0.0000645027,0.000083974526,0.00085124205,0.000044268938,0.00017653467,0.00010577257,0.000026665104,0.9331301,0.0004102173,0.062136177,0.0029196779,0.00005078422],"about_ca_topic_score_codex":0.016791865,"about_ca_topic_score_gemma":0.023684371,"teacher_disagreement_score":0.016791865,"about_ca_system_score_codex":0.0020788694,"about_ca_system_score_gemma":0.0027592487,"threshold_uncertainty_score":0.07330626},"labels":[],"label_agreement":null},{"id":"W2404527239","doi":"10.3389/fnins.2016.00247","title":"Microstructure Informed Tractography: Pitfalls and Open Challenges","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Diffusion MRI; Data science; Artificial intelligence; Medicine; Magnetic resonance imaging","score_opus":0.07275986416428372,"score_gpt":0.3553850544133283,"score_spread":0.2826251902490446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404527239","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052662212,0.030199038,0.8966009,0.06256436,0.00079154887,0.000077768564,0.00027513198,0.0007549066,0.0034701074],"genre_scores_gemma":[0.18389125,0.046593316,0.7555846,0.005044383,0.00454864,0.0006283751,0.0006183909,0.0009010806,0.002190051],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.985421,0.009421317,0.00078552426,0.0016418763,0.0025417597,0.0001885909],"domain_scores_gemma":[0.83725244,0.14166735,0.0032704235,0.010301292,0.0066373716,0.00087113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.029972516,0.0013359777,0.0024558182,0.0024978062,0.0015043819,0.0038884068,0.0041354485,0.004634438,0.0031507441],"category_scores_gemma":[0.11794894,0.0011335101,0.0011114373,0.0026894442,0.008926102,0.010351228,0.0040573273,0.0066273613,0.0019833078],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017588184,0.000067225956,0.004395663,0.0022712266,0.00031245392,0.000926773,0.0019383968,0.09572521,0.0020103403,0.4714325,0.027211843,0.39353245],"study_design_scores_gemma":[0.000022354912,0.000033989203,0.0009493235,0.00054452056,0.000022906705,0.00096038735,0.00038487755,0.12560685,0.0008015698,0.8502584,0.02031514,0.00009972982],"about_ca_topic_score_codex":0.0074556028,"about_ca_topic_score_gemma":0.0050630453,"teacher_disagreement_score":0.029972516,"about_ca_system_score_codex":0.0019577239,"about_ca_system_score_gemma":0.0028846187,"threshold_uncertainty_score":0.1585117},"labels":[],"label_agreement":null},{"id":"W2406164791","doi":"10.1503/jpn.150030","title":"Frontal fasciculi and psychotic symptoms in antipsychotic-naive patients with schizophrenia before and after 6 weeks of selective dopamine D2/3 receptor blockade","year":2016,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Lundbeckfonden","keywords":"Dopamine receptor D2; Schizophrenia (object-oriented programming); Dopamine; Antipsychotic; Blockade; Psychology; Psychosis; Medicine; Psychiatry; Neuroscience; Receptor; Internal medicine","score_opus":0.00842308945023912,"score_gpt":0.26742311113302825,"score_spread":0.2590000216827891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406164791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99979895,0.00008110922,0.000008776997,0.000010382316,0.0000018840553,0.000003568598,0.000023448667,0.0000011820447,0.00007068651],"genre_scores_gemma":[0.99977523,0.00003112897,0.00003354398,0.00001085599,0.0000027343028,0.0000040669834,0.00007051221,4.5248953e-7,0.00007152092],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981374,0.000046172197,0.000022335124,0.000039785995,0.00003536514,0.000042645082],"domain_scores_gemma":[0.9993794,0.000069293936,0.00031523177,0.000028920518,0.000044807883,0.00016238255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037028865,0.00033590783,0.00047420312,0.00031764898,0.0003642496,0.00031800772,0.00014405149,0.00044639705,0.00063287537],"category_scores_gemma":[0.0011035637,0.00020454668,0.00030668455,0.00019827965,0.00026835004,0.00022932845,0.00019601399,0.0003672666,0.000107915905],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009070958,0.00062071945,0.9753753,0.000026597967,0.00015421706,0.0009078309,0.00031985008,0.00017221904,0.0076975008,0.000022234712,0.00010425031,0.0055282298],"study_design_scores_gemma":[0.00008469493,0.0013424029,0.99766016,0.0000034350517,0.000028620423,0.0004684135,0.00007513415,0.00007929265,0.00017626438,0.000013160304,0.00006309787,0.000005164045],"about_ca_topic_score_codex":0.0030748113,"about_ca_topic_score_gemma":0.0059209736,"teacher_disagreement_score":0.0030748113,"about_ca_system_score_codex":0.0006273456,"about_ca_system_score_gemma":0.00025577002,"threshold_uncertainty_score":0.006113827},"labels":[],"label_agreement":null},{"id":"W2410277926","doi":"10.1017/cjn.2015.398","title":"Nε-(carboxymethyl)-lysine, White Matter, and Cognitive Function in Diabetes Patients","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Montreal Cognitive Assessment; Fractional anisotropy; Internal medicine; White matter; Fasciculus; Corpus callosum; Medicine; Cognition; Psychology; Cognitive impairment; Cardiology; Psychiatry; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.038058508760774545,"score_gpt":0.29062967376360704,"score_spread":0.2525711650028325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2410277926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99921703,0.00047919084,0.000026265157,0.000019649378,0.0000038904377,0.000003188468,0.00007144739,0.0000014855042,0.00017784041],"genre_scores_gemma":[0.99944764,0.00019118743,0.000078465935,0.00003010195,0.0000110675965,0.00000437176,0.00011678463,6.469752e-7,0.00011977836],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999002,0.000019173212,0.000018221655,0.000026796135,0.000019481928,0.000016124352],"domain_scores_gemma":[0.9996768,0.000042974974,0.0001627126,0.000013135032,0.0000312879,0.000073046096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027323826,0.00036039707,0.00031038496,0.0005400327,0.00035662405,0.00039790856,0.00015612044,0.0003882491,0.0009514109],"category_scores_gemma":[0.00062405376,0.00014911903,0.00021540304,0.0006883174,0.00014452614,0.00026108575,0.00018215667,0.0003287052,0.0001395887],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007281761,0.00014203328,0.9958377,0.00002070552,0.000092698676,0.00019172528,0.000055970526,0.00003181298,0.00096651557,0.000007641482,0.000049649883,0.0018755737],"study_design_scores_gemma":[0.000019381147,0.00032701288,0.9988085,0.00000548879,0.000041867665,0.00042447267,0.00007319762,0.000098141856,0.00011016416,0.000014028915,0.0000753705,0.0000023592183],"about_ca_topic_score_codex":0.0018373643,"about_ca_topic_score_gemma":0.0021288728,"teacher_disagreement_score":0.0018373643,"about_ca_system_score_codex":0.00015037112,"about_ca_system_score_gemma":0.00012425154,"threshold_uncertainty_score":0.0036533475},"labels":[],"label_agreement":null},{"id":"W2410342480","doi":"10.1007/s00406-016-0702-9","title":"The 5-HTTLPR and BDNF polymorphisms moderate the association between uncinate fasciculus connectivity and antidepressants treatment response in major depression","year":2016,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McMaster University","funders":"Mathison Centre for Mental Health Research and Education","keywords":"Uncinate fasciculus; Fractional anisotropy; 5-HTTLPR; Citalopram; Psychology; Internal medicine; Superior longitudinal fasciculus; Serotonin transporter; White matter; Sertraline; Antidepressant; Medicine; Fasciculus; Oncology; Psychiatry; Magnetic resonance imaging; Hippocampus; Serotonin","score_opus":0.05212781065193478,"score_gpt":0.36329858358076667,"score_spread":0.3111707729288319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2410342480","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99921405,0.00027371972,0.000098441225,0.00007123076,0.0000053648882,0.0000016793906,0.00007613924,0.0000022284771,0.00025709812],"genre_scores_gemma":[0.99964917,0.000059383397,0.00007671156,0.000020670395,0.00000457985,0.0000017531806,0.000049445924,0.0000011161667,0.0001371235],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998584,0.00004644658,0.000016503365,0.000039658855,0.000014512895,0.000024455703],"domain_scores_gemma":[0.9994367,0.00015710587,0.00027838827,0.0000388947,0.000030180267,0.00005870063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001938158,0.00020110117,0.00025816855,0.00019500659,0.0001916132,0.0002934327,0.00016998031,0.00041616627,0.0022277175],"category_scores_gemma":[0.0010764468,0.00017034067,0.00026631152,0.00021446342,0.0001788125,0.00020527763,0.0001836793,0.00030983117,0.00013194984],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049801664,0.00018384123,0.950964,0.000073243886,0.0012473961,0.00046903655,0.00033302777,0.00055791123,0.021446688,0.00027340275,0.00037245287,0.019098887],"study_design_scores_gemma":[0.00002857206,0.00009454438,0.9985555,0.0000072234316,0.00012530065,0.00021615888,0.000049691465,0.0004363301,0.00024245521,0.00013933392,0.00010160471,0.0000033249323],"about_ca_topic_score_codex":0.004081271,"about_ca_topic_score_gemma":0.008681898,"teacher_disagreement_score":0.004081271,"about_ca_system_score_codex":0.00015878618,"about_ca_system_score_gemma":0.00011019575,"threshold_uncertainty_score":0.008115053},"labels":[],"label_agreement":null},{"id":"W2411482138","doi":"10.1016/j.bandl.2016.05.008","title":"Treatment of dysphasia with rTMS and language therapy after childhood stroke: Multimodal imaging of plastic change","year":2016,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Alberta Children's Hospital","funders":"Alberta Children's Hospital Foundation; Health Research Board; Heart and Stroke Foundation of Canada","keywords":"Aphasia; Psychology; Stroke (engine); Neuroimaging; Inferior frontal gyrus; Neuroplasticity; White matter; Neuroscience; Audiology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.018115668307559663,"score_gpt":0.3040748849272598,"score_spread":0.28595921661970014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2411482138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96457845,0.010419929,0.0040095113,0.0017813015,0.00016397437,0.00016422149,0.00012681608,0.00015907211,0.018596845],"genre_scores_gemma":[0.99411666,0.0026840954,0.0013445662,0.0003794135,0.000115897914,0.000036339883,0.00005082207,0.000011463611,0.0012606776],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998981,0.000029460793,0.000013127055,0.000011803532,0.000012937178,0.0000344923],"domain_scores_gemma":[0.99992716,0.000029510971,0.000017890334,0.000006936984,0.0000077235245,0.000010729547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001714878,0.00038207986,0.00048144063,0.00043821012,0.0004010912,0.0003226536,0.00021682275,0.0008007872,0.0016683087],"category_scores_gemma":[0.00048598574,0.00012109593,0.00033732693,0.00025262206,0.00044071107,0.00046514676,0.00021016346,0.0005723071,0.00038062184],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012514636,0.0015706175,0.03162014,0.0011334618,0.00031363347,0.15622054,0.0009693973,0.0021140815,0.2036989,0.002562617,0.0037043411,0.5835776],"study_design_scores_gemma":[0.0022773328,0.020951776,0.32492146,0.000672799,0.0011330179,0.40025964,0.0017321863,0.0106514925,0.20186926,0.0038751469,0.03148335,0.00017255443],"about_ca_topic_score_codex":0.001844387,"about_ca_topic_score_gemma":0.002748998,"teacher_disagreement_score":0.001844387,"about_ca_system_score_codex":0.0004675085,"about_ca_system_score_gemma":0.00060250424,"threshold_uncertainty_score":0.0055810213},"labels":[],"label_agreement":null},{"id":"W2413345301","doi":"","title":"Pulse: The brain drain: a statistical snapshot","year":2000,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Snapshot (computer storage); Brain drain; Computer science; Data science; Operating system","score_opus":0.021846170528829558,"score_gpt":0.32110566153287556,"score_spread":0.29925949100404603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2413345301","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3668586,0.016324276,0.5254487,0.03199332,0.0019592205,0.0002437314,0.035784725,0.0042908182,0.017096702],"genre_scores_gemma":[0.93616796,0.004469494,0.043064397,0.0015084399,0.002272778,0.00014333458,0.008596049,0.00079923804,0.0029782252],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975648,0.0010303773,0.0002233236,0.00039418036,0.0006311661,0.00015613697],"domain_scores_gemma":[0.962755,0.025445791,0.0024251377,0.0036387546,0.004894411,0.00084072456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006359866,0.00059627456,0.0009867821,0.0021571468,0.00036706062,0.0033506863,0.00091841584,0.0009958574,0.004512881],"category_scores_gemma":[0.040719796,0.00030981968,0.0006187426,0.0028220853,0.00071635353,0.0031767827,0.001140764,0.0024816568,0.00091537955],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002965045,0.00020420224,0.31907487,0.0007778897,0.0019492661,0.001354986,0.00044388085,0.03402893,0.0018793693,0.03593574,0.11854858,0.4828372],"study_design_scores_gemma":[0.00028505802,0.0019765478,0.29144788,0.00071215286,0.0020681424,0.0071506323,0.0018878534,0.414586,0.0065941866,0.17429048,0.09848134,0.0005197314],"about_ca_topic_score_codex":0.008180346,"about_ca_topic_score_gemma":0.007358762,"teacher_disagreement_score":0.99950314,"about_ca_system_score_codex":0.0004968821,"about_ca_system_score_gemma":0.0019156483,"threshold_uncertainty_score":0.033634543},"labels":[],"label_agreement":null},{"id":"W2415288600","doi":"10.1016/j.schres.2016.05.025","title":"Corrigendum to “abnormal white matter integrity in antipsychotic-naïve first-episode psychosis patients assessed by a DTI principal component analysis” [Schizophr. Res. 162 (1–3) (march 2015) 14–21]","year":2016,"lang":"en","type":"erratum","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychosis; White matter; Antipsychotic; Schizophrenia (object-oriented programming); Psychology; Psychiatry; Principal component analysis; Medicine; Magnetic resonance imaging; Computer science; Radiology","score_opus":0.09695297960127922,"score_gpt":0.4141474399166557,"score_spread":0.31719446031537646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2415288600","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000111132525,0.0011400783,0.00023648249,0.07228716,0.92233306,0.000042746637,0.0007876592,0.00026412267,0.0027975123],"genre_scores_gemma":[0.0063319313,0.0082496265,0.0020016083,0.23963241,0.5072981,0.00028967546,0.0026422278,0.00060262636,0.23295175],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970878,0.0004391857,0.0006359644,0.00044007433,0.001072795,0.0003242243],"domain_scores_gemma":[0.9863772,0.0035146836,0.000834557,0.0007755766,0.007698997,0.00079907285],"candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0025679804,0.002394839,0.0029742392,0.0029838942,0.0030209909,0.002529371,0.0036808478,0.010077887,0.047824666],"category_scores_gemma":[0.034218322,0.0014774428,0.002567404,0.0015569511,0.0023982215,0.0017466564,0.002304509,0.010602854,0.034685913],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013913688,0.000006923588,0.000040221294,0.000042050855,0.0000070310366,0.0002613871,0.000010391168,0.000018960116,0.0000231157,0.000110675835,0.99712485,0.002340514],"study_design_scores_gemma":[0.00009890261,0.000057421254,0.0026094583,0.00043940012,0.000061438026,0.0011792379,0.00007803043,0.00035632506,0.00039623893,0.0012517415,0.9933983,0.0000735075],"about_ca_topic_score_codex":0.03517422,"about_ca_topic_score_gemma":0.05389518,"teacher_disagreement_score":0.997432,"about_ca_system_score_codex":0.0039928756,"about_ca_system_score_gemma":0.0044925497,"threshold_uncertainty_score":0.15998942},"labels":[],"label_agreement":null},{"id":"W241994552","doi":"10.1016/j.neuroimage.2015.05.016","title":"Robust and efficient linear registration of white-matter fascicles in the space of streamlines","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":93,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Max-Planck-Institut für Kognitions- und Neurowissenschaften","keywords":"Streamlines, streaklines, and pathlines; Artificial intelligence; Computer science; Diffusion MRI; Tractography; Jaccard index; Arcuate fasciculus; White matter; Computer vision; Pattern recognition (psychology); Physics","score_opus":0.11651302412537339,"score_gpt":0.34401294845725133,"score_spread":0.22749992433187793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W241994552","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03628853,0.00050740736,0.9602396,0.00023444822,0.000053013577,0.0000754806,0.0002602466,0.0015793978,0.0007617774],"genre_scores_gemma":[0.31770846,0.001024421,0.67531246,0.00010963847,0.00014993035,0.00021278228,0.0008973895,0.0011188629,0.0034660045],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927634,0.00019580238,0.000052010233,0.00020526903,0.00019077404,0.000079822246],"domain_scores_gemma":[0.99872464,0.00040995935,0.00029634748,0.00024133995,0.00026986038,0.000057861078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014146934,0.0009307279,0.0008288232,0.0021755188,0.00052576273,0.0024845197,0.0008002472,0.0010266555,0.0015274195],"category_scores_gemma":[0.0064099985,0.0006682803,0.0009572233,0.001980776,0.00068203994,0.0021811489,0.0018778578,0.00134672,0.0013719904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010174685,0.00017127563,0.005498697,0.000586307,0.0003080939,0.00032587105,0.00061254326,0.11150751,0.14775336,0.016390195,0.009603566,0.7062252],"study_design_scores_gemma":[0.00009813609,0.0001647497,0.007604499,0.000083044084,0.00012835958,0.0011631903,0.00022471802,0.85506094,0.089758344,0.03528407,0.0103134755,0.00011647073],"about_ca_topic_score_codex":0.0024747823,"about_ca_topic_score_gemma":0.0033463228,"teacher_disagreement_score":0.0024845197,"about_ca_system_score_codex":0.0005057614,"about_ca_system_score_gemma":0.0016976335,"threshold_uncertainty_score":0.007481694},"labels":[],"label_agreement":null},{"id":"W2423712451","doi":"10.18632/oncotarget.10091","title":"White matter degeneration in subjective cognitive decline: a diffusion tensor imaging study","year":2016,"lang":"en","type":"article","venue":"Oncotarget","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Medicine; Beijing; Cognitive decline; Neurology; Montreal Cognitive Assessment; China; Cognitive impairment; Disease; Internal medicine; Dementia; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.030354010026129082,"score_gpt":0.34816708322534795,"score_spread":0.31781307319921887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2423712451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990435,0.00029800108,0.00013961569,0.00005543697,0.000010283091,0.00002342916,0.00009068831,0.0000024040244,0.00033650605],"genre_scores_gemma":[0.9992162,0.00017077436,0.00013001967,0.000043673415,0.00003395935,0.000010920114,0.00018811625,0.0000023133396,0.00020399544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980384,0.000030144918,0.000035693934,0.000054450004,0.000042901644,0.000033075085],"domain_scores_gemma":[0.99921715,0.00007749028,0.00029314446,0.000059830698,0.00013468508,0.00021770045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000926105,0.00086150464,0.0005201141,0.0017238919,0.00073816086,0.0009302766,0.00035341046,0.0006803329,0.0010878086],"category_scores_gemma":[0.0020492265,0.0004208375,0.00062782917,0.0011297481,0.0006838219,0.0010870901,0.00074091466,0.00059786165,0.00025646327],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010291312,0.0004762043,0.9864761,0.00006939633,0.00023340655,0.003487444,0.00079324667,0.0001410603,0.0025129,0.00013108738,0.0002580962,0.004391979],"study_design_scores_gemma":[0.000047838494,0.00045813827,0.99431205,0.000020837755,0.00013877185,0.0031255025,0.0004669504,0.00076533895,0.00018838103,0.00021885827,0.00023511704,0.00002221955],"about_ca_topic_score_codex":0.004676233,"about_ca_topic_score_gemma":0.004684754,"teacher_disagreement_score":0.004676233,"about_ca_system_score_codex":0.00034440536,"about_ca_system_score_gemma":0.00038066666,"threshold_uncertainty_score":0.009298027},"labels":[],"label_agreement":null},{"id":"W2423914761","doi":"10.1002/ana.24111","title":"Reply","year":2014,"lang":"en","type":"letter","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Annals; Biostatistics; Citation; Medicine; Library science; Psychology; Humanities; Classics; Art; Computer science; Public health; Pathology","score_opus":0.2168970704524688,"score_gpt":0.4189773543611998,"score_spread":0.202080283908731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2423914761","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021955468,0.0006204657,0.000059504095,0.97210026,0.024909845,0.000009719624,0.000032515716,0.000023590199,0.0020245316],"genre_scores_gemma":[0.0011882465,0.00023354153,0.000050228307,0.9803625,0.013092925,0.000017346852,0.000011092524,0.000010340187,0.005033771],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953625,0.0008307135,0.00048573207,0.00078353233,0.0013042405,0.0012331909],"domain_scores_gemma":[0.9880293,0.004859703,0.0012438045,0.00038317902,0.0030580724,0.0024259742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042486135,0.0010483119,0.002040538,0.0014009939,0.007667115,0.008457127,0.003222259,0.11261001,0.014858929],"category_scores_gemma":[0.04254272,0.0013452568,0.0018680824,0.0010397393,0.004570958,0.004836648,0.0039935126,0.06548816,0.011912523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019861416,0.000010134375,0.0004646794,0.00003025153,0.000018211022,0.0011627193,0.0001532961,0.00003463169,0.00005839126,0.0014504167,0.99419206,0.002405403],"study_design_scores_gemma":[0.000090274894,0.000040074065,0.0014841348,0.0003950724,0.000069087626,0.0024374523,0.0010377573,0.00029834686,0.0002126805,0.008852738,0.98495805,0.00012431291],"about_ca_topic_score_codex":0.010244366,"about_ca_topic_score_gemma":0.014800885,"teacher_disagreement_score":0.11261001,"about_ca_system_score_codex":0.006775663,"about_ca_system_score_gemma":0.008980314,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2428473372","doi":"10.1371/journal.pone.0157218","title":"Progression of Microstructural Degeneration in Progressive Supranuclear Palsy and Corticobasal Syndrome: A Longitudinal Diffusion Tensor Imaging Study","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; Tau Consortium; National Institute on Aging; National Institutes of Health; U.S. Department of Veterans Affairs","keywords":"Progressive supranuclear palsy; Fractional anisotropy; Diffusion MRI; Corticobasal degeneration; Medicine; Tauopathy; Pathology; White matter; Magnetic resonance imaging; Radiology; Neurodegeneration; Disease","score_opus":0.06790541763405622,"score_gpt":0.3297950096081705,"score_spread":0.26188959197411427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2428473372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992933,0.00031242732,0.00014797185,0.000015326512,0.0000021301628,0.000013642126,0.00006710357,0.0000042195566,0.00014386856],"genre_scores_gemma":[0.9994106,0.000097063516,0.00015500783,0.000009896201,0.0000067081214,0.000010216633,0.00017904871,0.0000016528973,0.00012981858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997305,0.000073614465,0.000037274775,0.00006554291,0.000051777854,0.00004131761],"domain_scores_gemma":[0.9988617,0.00014383195,0.0005157249,0.000087971,0.00018596415,0.00020478503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011227785,0.00034189652,0.00026692668,0.00081077,0.00030424644,0.00034704228,0.00020651007,0.00044232598,0.0005579535],"category_scores_gemma":[0.0020913351,0.00023729476,0.00041739337,0.00031234682,0.00031203637,0.00044303387,0.0003329977,0.00037187757,0.00019165229],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021717309,0.00035276546,0.97838414,0.000040823827,0.00029845358,0.00081381644,0.00049174775,0.00025392356,0.009021939,0.0000338263,0.00007509332,0.008061701],"study_design_scores_gemma":[0.000020847394,0.0010574558,0.997004,0.0000058541973,0.00006909581,0.0009816937,0.00007032555,0.0003381929,0.00031619513,0.000025348772,0.00010457671,0.0000064391256],"about_ca_topic_score_codex":0.0030461329,"about_ca_topic_score_gemma":0.0024739725,"teacher_disagreement_score":0.0030461329,"about_ca_system_score_codex":0.00030751489,"about_ca_system_score_gemma":0.0003425809,"threshold_uncertainty_score":0.0060567856},"labels":[],"label_agreement":null},{"id":"W2429763096","doi":"10.1097/wnr.0000000000000488","title":"A study of brain white matter plasticity in early blinds using tract-based spatial statistics and tract statistical analysis","year":2015,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"White matter; Diffusion MRI; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11209336524505895,"score_gpt":0.3995146119130394,"score_spread":0.2874212466679804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2429763096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989999,0.00021005979,0.009290162,0.00001566089,0.0000021420549,0.000021811775,0.00013689371,0.000043330103,0.00028092813],"genre_scores_gemma":[0.99236614,0.00013625917,0.007113047,0.0000057630677,0.000004043352,0.00001672195,0.00008473783,0.000012875813,0.00026034637],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997607,0.00005876207,0.000028090562,0.00007152848,0.000055778888,0.000025086405],"domain_scores_gemma":[0.9989987,0.0003233978,0.00030456507,0.00014123692,0.0001338969,0.00009835433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010090206,0.00038272748,0.00034355375,0.0021669464,0.00032262164,0.00032194259,0.00014892635,0.00029141505,0.0009884791],"category_scores_gemma":[0.0028159893,0.00017444817,0.00034051665,0.0008243659,0.0006457671,0.00039571623,0.00041326843,0.00021541434,0.00012504838],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020395794,0.00021463627,0.49013862,0.0003700739,0.0006091722,0.0024483134,0.001978987,0.0061328174,0.3810566,0.001502635,0.00028706336,0.113221474],"study_design_scores_gemma":[0.000013091934,0.00057594164,0.9691288,0.00001619249,0.0000745052,0.002642977,0.00028256275,0.0066935914,0.01935745,0.000778049,0.0004047304,0.000032202548],"about_ca_topic_score_codex":0.004358573,"about_ca_topic_score_gemma":0.0041968757,"teacher_disagreement_score":0.004358573,"about_ca_system_score_codex":0.00024175202,"about_ca_system_score_gemma":0.0004537098,"threshold_uncertainty_score":0.008666396},"labels":[],"label_agreement":null},{"id":"W2438513049","doi":"10.1109/isbi.2016.7493414","title":"A sparse coding approach for the efficient representation and segmentation of white matter fibers","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Embedding; Computer science; Neural coding; Segmentation; Artificial intelligence; Pattern recognition (psychology); Sparse approximation; Pairwise comparison; Centroid; Representation (politics); Fiber bundle; Coding (social sciences); Fiber; Mathematics","score_opus":0.08784135663455689,"score_gpt":0.36222850187348543,"score_spread":0.27438714523892854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2438513049","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011900245,0.000071491515,0.9982907,0.00006396259,0.0000149696525,0.000012105049,0.000037836813,0.000101140366,0.00021776927],"genre_scores_gemma":[0.057942934,0.0006015791,0.938423,0.00011585985,0.00011839967,0.00015836647,0.00041072123,0.00009223895,0.0021370598],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995944,0.00008552836,0.000024453115,0.00007434604,0.00017808734,0.00004314497],"domain_scores_gemma":[0.9993154,0.00028662372,0.00008155325,0.00009519785,0.00018274093,0.00003849016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006512043,0.0006412905,0.00073736813,0.0013866561,0.00041914056,0.0007201229,0.0010478141,0.0009917425,0.0015879839],"category_scores_gemma":[0.0021305995,0.00043726148,0.00075124804,0.0016386462,0.0006847232,0.001164945,0.0011500223,0.0016434251,0.00076574495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011742266,0.00010318511,0.0008133929,0.00027036513,0.000077747434,0.00020910807,0.00029732182,0.23705332,0.0925856,0.06767937,0.00827783,0.5925153],"study_design_scores_gemma":[0.0000094593,0.000052134274,0.00034862495,0.00001895232,0.000012307133,0.00016498956,0.000020516769,0.9745393,0.007464836,0.013322873,0.0040235086,0.00002255431],"about_ca_topic_score_codex":0.003732639,"about_ca_topic_score_gemma":0.0038702937,"teacher_disagreement_score":0.003732639,"about_ca_system_score_codex":0.0004481936,"about_ca_system_score_gemma":0.001146617,"threshold_uncertainty_score":0.007421851},"labels":[],"label_agreement":null},{"id":"W2444358503","doi":"10.1017/s0954579416000444","title":"Anxious/depressed symptoms are related to microstructural maturation of white matter in typically developing youths","year":2016,"lang":"en","type":"article","venue":"Development and Psychopathology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Psychology; Typically developing; White matter; Depression (economics); Developing country; Clinical psychology; Developmental psychology; Anxiety; White (mutation); Psychiatry; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.024052250900980475,"score_gpt":0.31504260550905033,"score_spread":0.2909903546080699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2444358503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997054,0.00009718728,0.000035467798,0.000008595471,9.023688e-7,0.0000019591075,0.000035304867,0.000003352333,0.00011176644],"genre_scores_gemma":[0.99971956,0.0000832688,0.000077657336,0.0000060220623,0.0000021746619,0.0000025477457,0.00006178247,0.0000014042681,0.00004559822],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980897,0.000037947953,0.00003085406,0.00004706495,0.00004461948,0.000030647392],"domain_scores_gemma":[0.99840635,0.00021559342,0.0010305927,0.00005414446,0.00011109827,0.000182244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032321303,0.00020696918,0.00015143519,0.0011543483,0.0001850914,0.00038540375,0.00015573997,0.00025156283,0.0007311186],"category_scores_gemma":[0.002614863,0.0002146336,0.00017032867,0.00044098002,0.00025117578,0.00020514357,0.00027424202,0.00028260416,0.00007929471],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008768245,0.000016711634,0.99470747,0.000011226233,0.000024065812,0.00026854713,0.00020780867,0.00002899742,0.001840336,0.000015785996,0.000041447736,0.002749878],"study_design_scores_gemma":[5.5951693e-7,0.000019616258,0.99958676,0.0000015244824,0.000003892594,0.0002373564,0.000047420694,0.000019921672,0.000065911176,0.000004541387,0.000011877444,6.062255e-7],"about_ca_topic_score_codex":0.005671363,"about_ca_topic_score_gemma":0.007283228,"teacher_disagreement_score":0.005671363,"about_ca_system_score_codex":0.00021000039,"about_ca_system_score_gemma":0.00015047297,"threshold_uncertainty_score":0.011276662},"labels":[],"label_agreement":null},{"id":"W2460472596","doi":"10.1016/b978-0-12-396460-1.00014-7","title":"Individual Differences in White Matter Microstructure in the Healthy Brain","year":2014,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Neuroscience; Human brain; Psychology; Cognition; Neuroimaging; Relevance (law); Medicine; Magnetic resonance imaging; Political science","score_opus":0.043391977386875495,"score_gpt":0.31279904332294567,"score_spread":0.26940706593607017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460472596","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2794338,0.292322,0.090540215,0.007264034,0.0027423603,0.00007638225,0.004385988,0.0016325804,0.32160267],"genre_scores_gemma":[0.4618689,0.1673271,0.057452425,0.0014546306,0.001965972,0.000064858854,0.0020887763,0.00045492337,0.30732244],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99995947,0.0000050680565,0.000002597105,0.000016816413,0.000012965207,0.00000304266],"domain_scores_gemma":[0.99993145,0.00004382722,0.000006350651,0.000006173992,0.0000070656893,0.0000052358037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018364619,0.0002961914,0.00022948615,0.00041506684,0.00008545685,0.00063545344,0.0001938788,0.0003916572,0.010127931],"category_scores_gemma":[0.00034075795,0.000150192,0.00016696533,0.00043498512,0.00030432653,0.0005239517,0.00025928157,0.00036346653,0.0013760496],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014802905,0.00003793378,0.0059937737,0.0005327577,0.00011645891,0.00040104822,0.00037644574,0.0013999827,0.037284873,0.021589601,0.029818904,0.9023002],"study_design_scores_gemma":[0.000026459855,0.0004459194,0.39696756,0.00068773783,0.00023757207,0.0069199284,0.00070816965,0.004776256,0.020691754,0.2634485,0.30495268,0.00013743219],"about_ca_topic_score_codex":0.0011430363,"about_ca_topic_score_gemma":0.0024907936,"teacher_disagreement_score":0.010127931,"about_ca_system_score_codex":0.00014678553,"about_ca_system_score_gemma":0.00019166015,"threshold_uncertainty_score":0.033881307},"labels":[],"label_agreement":null},{"id":"W2460496408","doi":"10.18632/oncotarget.10601","title":"Abnormal organization of white matter networks in patients with subjective cognitive decline and mild cognitive impairment","year":2016,"lang":"en","type":"article","venue":"Oncotarget","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Diffusion MRI; Medicine; Beijing; Montreal Cognitive Assessment; White matter; Cognitive impairment; Dementia; China; Cognition; Neurology; Disease; Internal medicine; Psychiatry; Magnetic resonance imaging; Political science; Radiology","score_opus":0.010186497445157245,"score_gpt":0.27076311483646104,"score_spread":0.2605766173913038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460496408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99826485,0.0004943897,0.0003101158,0.00007101591,0.000011116853,0.000010589823,0.0002166153,0.00000855627,0.00061284355],"genre_scores_gemma":[0.99939203,0.000121915546,0.00014589223,0.000014670374,0.0000126664845,0.000008001362,0.00016827602,0.0000018900573,0.00013470158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998598,0.00002384138,0.000022755483,0.00004789662,0.00002011321,0.000025490011],"domain_scores_gemma":[0.9992793,0.00008793598,0.00041057117,0.000031953383,0.000077301345,0.00011288662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030521184,0.00040120957,0.00035962605,0.0013515179,0.00030872782,0.00051074673,0.0002697298,0.0003394134,0.0012541172],"category_scores_gemma":[0.0019461439,0.0001535911,0.00025809376,0.0009139129,0.00021581234,0.0006618176,0.0004481859,0.00031299813,0.00013844603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055154145,0.000061668856,0.9869696,0.000059409325,0.0002523133,0.00057928415,0.00027319952,0.0003797491,0.0016566722,0.00011446774,0.00026374537,0.0088383155],"study_design_scores_gemma":[0.000008889739,0.00006470861,0.997387,0.000010021267,0.000067205314,0.00049636204,0.00019448377,0.0011363552,0.0001478123,0.00035247946,0.00012717185,0.0000074463355],"about_ca_topic_score_codex":0.0032830425,"about_ca_topic_score_gemma":0.005868754,"teacher_disagreement_score":0.0032830425,"about_ca_system_score_codex":0.00025677303,"about_ca_system_score_gemma":0.00017772886,"threshold_uncertainty_score":0.0065279007},"labels":[],"label_agreement":null},{"id":"W2460521385","doi":"10.1002/ana.24712","title":"Development of White Matter Hyperintensity Is Preceded by Reduced Cerebrovascular Reactivity","year":2016,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Health Sciences Centre; University Health Network","funders":"Canadian Stroke Network; Campbell Foundation","keywords":"Fractional anisotropy; White matter; Hyperintensity; Diffusion MRI; Cardiology; Magnetic resonance imaging; Medicine; Internal medicine; Neuroimaging; Radiology; Psychiatry","score_opus":0.11353973132076414,"score_gpt":0.36128746957404045,"score_spread":0.2477477382532763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460521385","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995461,0.00014859112,0.00007712961,0.000012115233,0.0000017793716,0.000003843219,0.000027669463,0.00000436428,0.00017826923],"genre_scores_gemma":[0.99965894,0.000062816674,0.000112726135,0.000009660315,0.00001060081,0.0000028003922,0.00006251851,0.0000010639312,0.000078779325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987745,0.000024610752,0.000014700586,0.00003749404,0.000025320765,0.000020472007],"domain_scores_gemma":[0.9989059,0.00015721454,0.0007092512,0.000047982303,0.000072206174,0.0001075634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031596364,0.00021732466,0.00027130407,0.0003607984,0.00016988147,0.00024578345,0.00013718486,0.00028836195,0.0010226298],"category_scores_gemma":[0.0011481713,0.00018653127,0.00014299633,0.00024292181,0.00032483265,0.00020977625,0.00023536889,0.00030081073,0.00018068597],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000995689,0.00013477774,0.94348466,0.00008137255,0.00012663503,0.0013934139,0.000228282,0.00015431727,0.047386322,0.000039435825,0.000110183806,0.005864828],"study_design_scores_gemma":[0.0000038580733,0.00017548434,0.9982553,0.0000027944552,0.000009221373,0.0006580406,0.000026338808,0.00004713211,0.0007669356,0.0000139744625,0.00003976196,0.0000011553321],"about_ca_topic_score_codex":0.00086138974,"about_ca_topic_score_gemma":0.0011065708,"teacher_disagreement_score":0.0010226298,"about_ca_system_score_codex":0.00010850076,"about_ca_system_score_gemma":0.00011175768,"threshold_uncertainty_score":0.0034210682},"labels":[],"label_agreement":null},{"id":"W2462313590","doi":"10.3174/ajnr.a4870","title":"DTI Analysis of Presbycusis Using Voxel-Based Analysis","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Presbycusis; Fractional anisotropy; Diffusion MRI; Medicine; Voxel; Thermal diffusivity; White matter; Audiology; Magnetic resonance imaging; Radiology; Physics; Hearing loss","score_opus":0.08403468295634334,"score_gpt":0.3970112409590346,"score_spread":0.3129765580026913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2462313590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4382127,0.0012503348,0.5522193,0.00023471832,0.00005568752,0.0004049586,0.0022542193,0.0030940536,0.0022741067],"genre_scores_gemma":[0.623971,0.00031687794,0.37288687,0.000029658306,0.000024473342,0.00034885376,0.0015502082,0.00025083215,0.00062117947],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99977547,0.00006230414,0.000032153126,0.0000507898,0.000059615788,0.000019689502],"domain_scores_gemma":[0.9994529,0.00019286407,0.00011364134,0.000056070203,0.00015763896,0.000026844882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071962486,0.00048086088,0.00039951177,0.0034713869,0.00032756774,0.0006542821,0.00036751264,0.0002831438,0.0018181709],"category_scores_gemma":[0.0021377616,0.00015158083,0.00049440336,0.0017566251,0.00023018826,0.00029278634,0.00031273594,0.00032097567,0.00033199758],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011031564,0.00028687512,0.06674061,0.0008650058,0.0012350113,0.0016919945,0.00073647633,0.04354689,0.28562084,0.007356112,0.0058547,0.58496225],"study_design_scores_gemma":[0.0001361105,0.00061233103,0.2986892,0.0001199709,0.00058961957,0.0059082364,0.00047256987,0.5475342,0.11308286,0.017397366,0.015279363,0.00017809657],"about_ca_topic_score_codex":0.0041163107,"about_ca_topic_score_gemma":0.0064566345,"teacher_disagreement_score":0.0041163107,"about_ca_system_score_codex":0.0004808563,"about_ca_system_score_gemma":0.0008200036,"threshold_uncertainty_score":0.008184671},"labels":[],"label_agreement":null},{"id":"W2466746677","doi":"10.1159/000446770","title":"Altered Superficial White Matter on Tractography MRI in Alzheimer's Disease","year":2016,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Kingston General Hospital; Queen's University; University of Toronto","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Tractography; Hyperintensity; Psychology; Stroop effect; Magnetic resonance imaging; Cognitive decline; Alzheimer's disease; Frontal lobe; Pathology; Neuroscience; Medicine; Cognition; Disease; Dementia; Radiology","score_opus":0.02363189521748272,"score_gpt":0.30127741748287973,"score_spread":0.277645522265397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2466746677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998609,0.00029747744,0.00070734957,0.000012986677,0.0000012852813,0.000006503251,0.00008457231,0.0000124351845,0.00026846924],"genre_scores_gemma":[0.99861467,0.00017775677,0.0009399738,0.000007834489,0.0000036037495,0.0000052838895,0.00009059044,0.0000038209646,0.0001565131],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993575,0.000012198809,0.000009956881,0.000018988121,0.000012425963,0.0000106407815],"domain_scores_gemma":[0.99956566,0.0000624007,0.00024862922,0.00004001384,0.000045362292,0.000037777838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042943767,0.0003308415,0.0001955555,0.0007760611,0.00018191298,0.00043212847,0.000113879854,0.0002460289,0.0015914488],"category_scores_gemma":[0.00078836764,0.00014708185,0.00015436808,0.00041159062,0.00036697788,0.00031934603,0.0002315157,0.0001246567,0.00017440792],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016334032,0.00007912422,0.85210085,0.00018485606,0.0002879855,0.0016900685,0.0009246555,0.0007018102,0.11065647,0.00035007496,0.00022563405,0.031165078],"study_design_scores_gemma":[0.0000117274885,0.00012383288,0.9926588,0.000017875993,0.000060498853,0.0027166246,0.00009996734,0.000666544,0.0029240637,0.0005080883,0.00020524257,0.000006706036],"about_ca_topic_score_codex":0.002955634,"about_ca_topic_score_gemma":0.0043800385,"teacher_disagreement_score":0.002955634,"about_ca_system_score_codex":0.00021756352,"about_ca_system_score_gemma":0.00019737294,"threshold_uncertainty_score":0.0058768988},"labels":[],"label_agreement":null},{"id":"W2467810590","doi":"10.1007/s10334-016-0575-y","title":"Assessing the accuracy of using oscillating gradient spin echo sequences with AxCaliber to infer micron-sized axon diameters","year":2016,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Canadian Institute for Theoretical Astrophysics; University of Toronto; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Echo (communications protocol); Axon; Physics; Spin (aerodynamics); Nuclear magnetic resonance; Acoustics; Computer science; Neuroscience; Biology","score_opus":0.07362427929021703,"score_gpt":0.4014896194416566,"score_spread":0.3278653401514396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2467810590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92417246,0.0036823244,0.06759634,0.00035798663,0.000207118,0.000062115854,0.00036283827,0.000472336,0.00308636],"genre_scores_gemma":[0.97163105,0.0006121582,0.026727853,0.00016258445,0.000033036264,0.000019536377,0.00017958364,0.000091504706,0.0005427178],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99724674,0.00089396996,0.00038486108,0.00070693553,0.00062594947,0.00014161112],"domain_scores_gemma":[0.9379745,0.043899268,0.004685446,0.003610355,0.009024396,0.00080606516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009748147,0.000649088,0.00035697932,0.0017371114,0.0004308769,0.001669623,0.001095464,0.0024808731,0.0008849571],"category_scores_gemma":[0.05441634,0.00056101626,0.0002795876,0.0005322927,0.00091428123,0.0017687238,0.0006915382,0.0007984678,0.0005442659],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00885107,0.00029336556,0.63211644,0.0007090695,0.0014065026,0.00052254443,0.0012511882,0.016692584,0.15108985,0.0015412042,0.0011340812,0.18439214],"study_design_scores_gemma":[0.00023168261,0.0026753151,0.57908905,0.00042789613,0.0018641904,0.003834709,0.0010853327,0.2460424,0.1552874,0.0045223595,0.004676431,0.00026329013],"about_ca_topic_score_codex":0.0029513328,"about_ca_topic_score_gemma":0.005772494,"teacher_disagreement_score":0.009748147,"about_ca_system_score_codex":0.00040016355,"about_ca_system_score_gemma":0.0005137275,"threshold_uncertainty_score":0.051553726},"labels":[],"label_agreement":null},{"id":"W2470264972","doi":"10.1109/tip.2016.2588328","title":"Multi-Tissue Decomposition of Diffusion MRI Signals via L0 Sparse-Group Estimation","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Aging; University of North Carolina at Chapel Hill; National Institutes of Health; Simon Fraser University","keywords":"Deconvolution; Algorithm; Voxel; Diffusion MRI; Robustness (evolution); Matrix decomposition; Computer science; Mathematics; Mathematical optimization; Artificial intelligence; Magnetic resonance imaging","score_opus":0.04059078803748986,"score_gpt":0.3646835081929801,"score_spread":0.3240927201554903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2470264972","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012096341,0.000057917427,0.99828726,0.000065874534,0.000009218776,0.000015452742,0.000018495004,0.00011828131,0.00021790956],"genre_scores_gemma":[0.036061358,0.00027734358,0.96140164,0.00007712505,0.000050485673,0.000096229945,0.00022726171,0.00011093812,0.0016975313],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99938965,0.00019716086,0.000035610345,0.00012114567,0.00021237126,0.000044029177],"domain_scores_gemma":[0.99902177,0.00049228227,0.00012685597,0.00013711823,0.00017508877,0.000046946963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016895586,0.001212995,0.00083766045,0.001076791,0.0004241857,0.0007479,0.00102388,0.001125438,0.0020725755],"category_scores_gemma":[0.0040634573,0.0004935666,0.0011396675,0.0012575616,0.000808104,0.0016752875,0.0016880037,0.0016709467,0.0014858574],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014534978,0.00011338717,0.00074755785,0.00032454784,0.00010560988,0.00017127059,0.0004147443,0.3404291,0.04328639,0.05149175,0.0062245126,0.55654573],"study_design_scores_gemma":[0.000013473106,0.00005874634,0.00025280935,0.000015375652,0.000014724464,0.0000917748,0.000035769175,0.96731466,0.007167336,0.02006388,0.004951493,0.000020020936],"about_ca_topic_score_codex":0.0022326973,"about_ca_topic_score_gemma":0.0030312468,"teacher_disagreement_score":0.0022326973,"about_ca_system_score_codex":0.0005203915,"about_ca_system_score_gemma":0.0011788646,"threshold_uncertainty_score":0.008935332},"labels":[],"label_agreement":null},{"id":"W2471565160","doi":"10.1093/brain/aww167","title":"The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions","year":2016,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Savoy Foundation","keywords":"White matter; Temporal lobe; Magnetic resonance imaging; Fractional anisotropy; Neuroscience; Diffusion MRI; Grey matter; Epilepsy; Cortex (anatomy); Frontal lobe; Psychology; Anatomy; Medicine; Radiology","score_opus":0.03960624551264561,"score_gpt":0.31723039288946575,"score_spread":0.2776241473768201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471565160","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99848026,0.00022303006,0.0010259628,0.000050593364,8.384295e-7,0.0000033020385,0.000040950697,0.000007380661,0.00016758096],"genre_scores_gemma":[0.9994604,0.000120214405,0.00032433597,0.000006901538,0.0000021321287,0.0000020785906,0.00003330554,0.0000013664818,0.000049220234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995494,0.000010330204,0.000004830411,0.000015262685,0.0000071518457,0.0000074098693],"domain_scores_gemma":[0.9997516,0.00006397396,0.0001265371,0.000023263978,0.0000149770985,0.00001950132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017313672,0.000181892,0.00013253596,0.0004073828,0.00011974681,0.00028023394,0.00008699192,0.00014156192,0.00045268572],"category_scores_gemma":[0.00095026125,0.000090751324,0.00008899695,0.0003692531,0.00041671988,0.0003197994,0.00026265843,0.0001739759,0.00004628466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013514245,0.00008501673,0.71719676,0.00018752001,0.00021811074,0.0022612503,0.0012537271,0.003425341,0.21699665,0.0014650107,0.00024014477,0.055319015],"study_design_scores_gemma":[0.00000545289,0.00009977594,0.99125427,0.000007671328,0.00004002791,0.0013741046,0.00016988216,0.002404255,0.0029193917,0.0015552087,0.0001626121,0.000007296398],"about_ca_topic_score_codex":0.002420285,"about_ca_topic_score_gemma":0.0036817382,"teacher_disagreement_score":0.002420285,"about_ca_system_score_codex":0.00017650245,"about_ca_system_score_gemma":0.00018902405,"threshold_uncertainty_score":0.0048124194},"labels":[],"label_agreement":null},{"id":"W2472551679","doi":"10.1088/0031-9155/61/15/5768","title":"Automated PET-only quantification of amyloid deposition with adaptive template and empirically pre-defined ROI","year":2016,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Spatial normalization; Voxel; Region of interest; Artificial intelligence; Normalization (sociology); Nuclear medicine; Computer science; Pittsburgh compound B; Segmentation; Pattern recognition (psychology); Positron emission tomography; Medicine; Alzheimer's disease; Pathology; Disease","score_opus":0.21797642221013058,"score_gpt":0.4287588403691964,"score_spread":0.21078241815906584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2472551679","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37222722,0.0010754272,0.62183976,0.00007149335,0.000040376755,0.00034653113,0.00040347525,0.0022829943,0.0017127276],"genre_scores_gemma":[0.48170087,0.00029974186,0.51562804,0.000047846042,0.000019533865,0.00036332538,0.0006443721,0.00038105017,0.0009152354],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900925,0.00028786404,0.00007682273,0.00030810403,0.00025425872,0.000063690415],"domain_scores_gemma":[0.99888104,0.0003502583,0.00015992956,0.0002978117,0.00028012437,0.000030885865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002073857,0.0005922528,0.0008191679,0.0008424729,0.00022290974,0.0007067608,0.000735145,0.00074069796,0.0009967041],"category_scores_gemma":[0.0041145105,0.00052355207,0.0005119048,0.0005733414,0.00035728863,0.0006958044,0.00047966608,0.00031141227,0.00064640807],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084514666,0.00016790717,0.023758912,0.00037472122,0.0002070628,0.00060465233,0.0003403103,0.014382219,0.68106943,0.0014886103,0.0010208872,0.27574012],"study_design_scores_gemma":[0.00018685652,0.0013590342,0.15122885,0.000075884345,0.00043709218,0.011719899,0.00020608981,0.38553888,0.4386082,0.002937351,0.007455499,0.00024633444],"about_ca_topic_score_codex":0.0012186076,"about_ca_topic_score_gemma":0.0022184849,"teacher_disagreement_score":0.002073857,"about_ca_system_score_codex":0.00030070206,"about_ca_system_score_gemma":0.00048187957,"threshold_uncertainty_score":0.0109677315},"labels":[],"label_agreement":null},{"id":"W2483278632","doi":"10.1007/s00429-016-1274-1","title":"Transcallosal connectivity of the human cortical motor network","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Department of Education and Learning, Northern Ireland; Atlantic Philanthropies","keywords":"Neuroscience; Corpus callosum; White matter; Diffusion MRI; Tractography; Premotor cortex; Human brain; Motor cortex; Primary motor cortex; Supplementary motor area; Cortex (anatomy); Psychology; Biology; Anatomy; Dorsum; Magnetic resonance imaging; Functional magnetic resonance imaging; Medicine","score_opus":0.02681806880911118,"score_gpt":0.2955183435411584,"score_spread":0.2687002747320472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2483278632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94321775,0.00059329433,0.048498955,0.00012550337,0.000008475481,0.000040145773,0.00033556283,0.00018936621,0.006990993],"genre_scores_gemma":[0.98913026,0.00029843685,0.009140132,0.00001397029,0.000005653073,0.00003251289,0.00023395778,0.00001430797,0.0011306313],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99990714,0.000023942195,0.0000035291,0.000041324038,0.000017051825,0.0000069955795],"domain_scores_gemma":[0.99988997,0.00005016946,0.00002153882,0.000013506302,0.000016571386,0.000008179246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010452156,0.00014815641,0.000094897245,0.00065922557,0.00016063632,0.0002836853,0.00015064265,0.00016621049,0.0014306239],"category_scores_gemma":[0.00081514264,0.000099207966,0.00010135942,0.00039977938,0.00037774252,0.00029704714,0.0003023014,0.00012259226,0.00023351448],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008126947,0.00012155275,0.05438544,0.0003929189,0.0002525696,0.002331628,0.0029551801,0.07220865,0.41853002,0.02709786,0.0029739614,0.41793752],"study_design_scores_gemma":[0.000044940694,0.00041759445,0.60057926,0.000064309286,0.00015871409,0.006217809,0.00079882564,0.28413394,0.049467426,0.04265443,0.015379584,0.00008314957],"about_ca_topic_score_codex":0.0039999057,"about_ca_topic_score_gemma":0.006833893,"teacher_disagreement_score":0.0039999057,"about_ca_system_score_codex":0.00020679894,"about_ca_system_score_gemma":0.00025752373,"threshold_uncertainty_score":0.007953286},"labels":[],"label_agreement":null},{"id":"W2485969200","doi":"10.1093/brain/aww195","title":"Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia","year":2016,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"Primary progressive aphasia; Frontotemporal dementia; Aphasia; Psychology; Neuroscience; Semantic dementia; Dementia; Atrophy; Frontal lobe; Middle frontal gyrus; Grey matter; White matter; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Pathology","score_opus":0.03239517832150831,"score_gpt":0.357791396281009,"score_spread":0.3253962179595007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2485969200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99975353,0.000016076403,0.000082711595,0.00000637737,5.0356687e-7,0.0000020813907,0.000024730412,0.0000037183902,0.00011028721],"genre_scores_gemma":[0.99974936,0.000011913946,0.00009257894,0.000002921652,0.000001248032,0.0000023387013,0.00007230616,0.0000012112861,0.00006619089],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999372,0.000012235855,0.000007974166,0.000023685441,0.000009292192,0.00000957643],"domain_scores_gemma":[0.99955994,0.0001297459,0.00017284174,0.000034645473,0.00003925899,0.00006353068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001803916,0.00023579902,0.00016311313,0.0005763807,0.00021940691,0.00023947693,0.0001230962,0.0002676767,0.0013630956],"category_scores_gemma":[0.0011257424,0.00012137083,0.00017046317,0.00015864907,0.00025941388,0.00023267661,0.00018431456,0.00021579092,0.0001358217],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073496054,0.00010586031,0.959125,0.000023226276,0.00012730963,0.0014161217,0.00048690187,0.0008821588,0.028044816,0.00009791169,0.00017715928,0.008778753],"study_design_scores_gemma":[0.0000038501184,0.00007876876,0.99854076,0.0000011659823,0.000010243667,0.0005738285,0.000033553435,0.00041916364,0.00025982008,0.00005562148,0.000021741673,0.0000014970167],"about_ca_topic_score_codex":0.0034872964,"about_ca_topic_score_gemma":0.007712415,"teacher_disagreement_score":0.0034872964,"about_ca_system_score_codex":0.00015942154,"about_ca_system_score_gemma":0.000110585665,"threshold_uncertainty_score":0.006933987},"labels":[],"label_agreement":null},{"id":"W2487395641","doi":"10.1016/j.neuroimage.2016.07.048","title":"Optimal DSI reconstruction parameter recommendations: Better ODFs and better connectivity","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Computation; Diffusion MRI; Software; Algorithm; Data mining; Orientation (vector space); Artificial intelligence; Mathematics","score_opus":0.05842319150817775,"score_gpt":0.3335125303600374,"score_spread":0.27508933885185965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2487395641","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04643368,0.002000222,0.9410281,0.0031567118,0.00024715424,0.000098607685,0.0008950936,0.0025509791,0.0035893486],"genre_scores_gemma":[0.29775003,0.0018675536,0.694516,0.00062841503,0.00029124226,0.00012404047,0.0010975824,0.0015364913,0.0021886711],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99949956,0.0001921116,0.000058476464,0.00008915116,0.00010899179,0.00005164818],"domain_scores_gemma":[0.99758124,0.001243143,0.00018060638,0.00037885524,0.000498969,0.000117141804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012847786,0.0015181712,0.0011437688,0.0016364245,0.0005001966,0.002336653,0.0007551638,0.0017883197,0.006760412],"category_scores_gemma":[0.017555973,0.0006724201,0.0005604586,0.0011311986,0.0004056192,0.002639395,0.0008516594,0.0023386634,0.0025056421],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012639785,0.0003646655,0.01077795,0.0006543859,0.00019331365,0.00036585503,0.00025137272,0.16303097,0.04055563,0.00887321,0.022790447,0.7508782],"study_design_scores_gemma":[0.00044076907,0.0001841546,0.005546134,0.0004053326,0.00031364703,0.0013811878,0.00039054055,0.8628455,0.05998617,0.047922995,0.020389112,0.00019441849],"about_ca_topic_score_codex":0.0048592063,"about_ca_topic_score_gemma":0.0069244425,"teacher_disagreement_score":0.006760412,"about_ca_system_score_codex":0.00037325098,"about_ca_system_score_gemma":0.0020039177,"threshold_uncertainty_score":0.02261585},"labels":[],"label_agreement":null},{"id":"W2496475229","doi":"10.1007/978-1-4939-3995-4_20","title":"Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-oncology and Neurotraumatology","year":2016,"lang":"en","type":"book-chapter","venue":"Springer series in computational neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"Susceptibility weighted imaging; Neuroimaging; Magnetic resonance imaging; Medicine; Biomarker; Radiology; Glioma; Diffusion MRI; Fractal analysis; Fractal dimension; Pathology; Fractal; Biology; Cancer research","score_opus":0.042439371411067725,"score_gpt":0.3441250715068095,"score_spread":0.30168570009574175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2496475229","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011684145,0.018664395,0.95095944,0.0015285042,0.0005963319,0.000029069073,0.00035286255,0.0006393511,0.015545859],"genre_scores_gemma":[0.230027,0.03052172,0.70425236,0.00045894468,0.0018782872,0.00011128918,0.00087532966,0.000631962,0.031243214],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998956,0.000019096991,0.0000062639883,0.00001897239,0.000053203246,0.0000068890668],"domain_scores_gemma":[0.9994617,0.00032749618,0.000040389754,0.000044052973,0.000100694684,0.00002571568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036514594,0.0005271462,0.00056394323,0.00089560065,0.00021884864,0.0012067597,0.00071905245,0.0007883733,0.0023717969],"category_scores_gemma":[0.0012265963,0.00026597304,0.00062558515,0.00067330827,0.00063625886,0.0010675128,0.0006189384,0.0009622602,0.0007558535],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038824575,0.00004059281,0.000669547,0.0006110416,0.00008103327,0.00020477924,0.00022918596,0.2445891,0.018324427,0.3804374,0.032663036,0.32211113],"study_design_scores_gemma":[0.0000034823329,0.000022191667,0.0008301338,0.000068822905,0.000015040872,0.0002877549,0.00002524721,0.79749846,0.0022542987,0.1716598,0.027293872,0.000040918178],"about_ca_topic_score_codex":0.00074757193,"about_ca_topic_score_gemma":0.0010069943,"teacher_disagreement_score":0.0023717969,"about_ca_system_score_codex":0.00043223036,"about_ca_system_score_gemma":0.00037113414,"threshold_uncertainty_score":0.007934451},"labels":[],"label_agreement":null},{"id":"W2499587845","doi":"10.1016/j.neuroimage.2016.07.053","title":"Corrigendum to “A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging”","year":2016,"lang":"en","type":"erratum","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Compressed sensing; Joint (building); Resolution (logic); High resolution; Diffusion; Computer science; Diffusion imaging; Diffusion MRI; Artificial intelligence; Remote sensing; Geology; Medicine; Physics; Radiology; Engineering; Magnetic resonance imaging","score_opus":0.07265784918326551,"score_gpt":0.3106696367758546,"score_spread":0.23801178759258906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2499587845","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000059472197,0.0018064053,0.000772818,0.05188702,0.9418251,0.000029038578,0.0003373889,0.00018937483,0.0030934631],"genre_scores_gemma":[0.0053580524,0.010750572,0.0056999335,0.17163739,0.46582994,0.0002182165,0.0016217163,0.0009654093,0.33791876],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964104,0.00054741633,0.000593011,0.0005347204,0.0016292795,0.00028521114],"domain_scores_gemma":[0.9830503,0.0036243252,0.00071237586,0.00089213037,0.011050516,0.000670271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003075465,0.0018547579,0.0019446478,0.003216296,0.002997035,0.002934056,0.0031873053,0.008931887,0.04302812],"category_scores_gemma":[0.03996687,0.0010107091,0.0020982227,0.001665365,0.0021100934,0.0018942135,0.0019624252,0.010607117,0.031836964],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001258979,0.0000037226669,0.000016944661,0.000043576816,0.0000051165784,0.00008645581,0.0000064065835,0.00002661649,0.000040604697,0.00037123237,0.9963407,0.0030460046],"study_design_scores_gemma":[0.000027112521,0.000018960725,0.0005275718,0.00017682133,0.00003473908,0.0002877556,0.000029362522,0.00038694838,0.0004688311,0.0018227267,0.9961817,0.000037455447],"about_ca_topic_score_codex":0.029651804,"about_ca_topic_score_gemma":0.053050015,"teacher_disagreement_score":0.04302812,"about_ca_system_score_codex":0.0040092687,"about_ca_system_score_gemma":0.0042176084,"threshold_uncertainty_score":0.14394337},"labels":[],"label_agreement":null},{"id":"W2502730944","doi":"10.1002/hbm.23339","title":"New insights in the homotopic and heterotopic connectivity of the frontal portion of the human corpus callosum revealed by microdissection and diffusion tractography","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Superior frontal gyrus; Neuroscience; Frontal lobe; Corpus callosum; Middle frontal gyrus; Diffusion MRI; Anatomy; Inferior frontal gyrus; Psychology; Medial frontal gyrus; Biology; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.03283729647112223,"score_gpt":0.2918627210989834,"score_spread":0.2590254246278612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2502730944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9609438,0.0031373678,0.034185894,0.00012838017,0.0000093067665,0.000022050479,0.0002050492,0.00008080451,0.0012874706],"genre_scores_gemma":[0.98168737,0.0014298531,0.015857935,0.00003266406,0.000014142734,0.000020373209,0.00017151733,0.00002062286,0.00076544227],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994266,0.000009427474,0.0000039243155,0.000025160723,0.0000099898025,0.000008773187],"domain_scores_gemma":[0.999928,0.000023187338,0.000016333368,0.000017436847,0.0000071221953,0.00000785612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017956785,0.0002423465,0.000115927076,0.00075440423,0.00019401492,0.00024236612,0.00015176073,0.0002610407,0.0008592309],"category_scores_gemma":[0.00024259131,0.00018846849,0.00016897598,0.00020029648,0.00052827614,0.0003177971,0.00028125054,0.00021960803,0.000113668844],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008625239,0.000008898757,0.004043359,0.00007431678,0.00003208801,0.00056581886,0.0003234022,0.00047394502,0.97991574,0.0009937957,0.000048258735,0.013434142],"study_design_scores_gemma":[0.00003477174,0.00034040955,0.58203846,0.00006198106,0.0002042871,0.012777359,0.0007582004,0.015726153,0.36877215,0.008016366,0.011203307,0.000066460976],"about_ca_topic_score_codex":0.0014258628,"about_ca_topic_score_gemma":0.0030552188,"teacher_disagreement_score":0.0014258628,"about_ca_system_score_codex":0.000171574,"about_ca_system_score_gemma":0.00014248985,"threshold_uncertainty_score":0.002874434},"labels":[],"label_agreement":null},{"id":"W2504994530","doi":"10.1101/066647","title":"The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Striatum; Addiction; Thalamus; Nucleus accumbens; Kurtosis; Psychology; Cocaine dependence; Neuroscience; Ventral striatum; Dopamine; Mathematics","score_opus":0.015220829807030028,"score_gpt":0.2683196317622078,"score_spread":0.25309880195517775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2504994530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992067,0.00017134714,0.0003743062,0.000008122317,0.0000017868366,0.000007096637,0.00006235653,0.0000040812606,0.0001641704],"genre_scores_gemma":[0.99888486,0.000116917625,0.0006708548,0.000007920422,0.0000021589842,0.0000058684977,0.00005374593,0.0000045127003,0.00025320018],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999925,0.000015131747,0.000007213348,0.000022785263,0.000021036038,0.000008803942],"domain_scores_gemma":[0.999696,0.000055765548,0.00012726948,0.000024412166,0.00005598199,0.000040531275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018132332,0.0001840592,0.00013609926,0.0004835256,0.000107245614,0.00022185425,0.00007642771,0.00018427783,0.0009920001],"category_scores_gemma":[0.0004998039,0.00011546615,0.0001280403,0.00017635542,0.00019554133,0.00019677858,0.00020705009,0.00013497629,0.00006104098],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025789253,0.00021350922,0.43954512,0.0001428732,0.0002554887,0.0009659392,0.00060937175,0.0005119979,0.52841884,0.00016466608,0.00017267921,0.026420536],"study_design_scores_gemma":[0.000004886133,0.0002701209,0.98763406,0.0000057758434,0.00003503889,0.000690039,0.000111014066,0.001173515,0.009871151,0.000048467387,0.00014803406,0.000007917834],"about_ca_topic_score_codex":0.0027222254,"about_ca_topic_score_gemma":0.0059518,"teacher_disagreement_score":0.0027222254,"about_ca_system_score_codex":0.00014551666,"about_ca_system_score_gemma":0.00010257375,"threshold_uncertainty_score":0.005412698},"labels":[],"label_agreement":null},{"id":"W2505695543","doi":"10.1016/j.jad.2016.07.026","title":"Corpus callosum integrity is affected by mood disorders and also by the suicide attempt history: A diffusion tensor imaging study","year":2016,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Major depressive disorder; Suicide attempt; Bipolar disorder; Psychology; Mood disorders; Diffusion MRI; Poison control; Mood; Psychiatry; Clinical psychology; Internal medicine; Medicine; Injury prevention; Magnetic resonance imaging; Neuroscience; Anxiety","score_opus":0.021605041082241174,"score_gpt":0.3131748482433767,"score_spread":0.29156980716113556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505695543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99938166,0.000113950875,0.00005118233,0.000024815887,0.0000030710892,0.000005652488,0.000056813937,0.0000020502239,0.0003608486],"genre_scores_gemma":[0.999564,0.00007272501,0.00007193768,0.00001887773,0.000010540793,0.000004228544,0.00007889853,0.0000026156558,0.00017626185],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998816,0.000024416651,0.000014694872,0.000036301757,0.000021126538,0.000021887905],"domain_scores_gemma":[0.99928623,0.00013422864,0.00029467416,0.000086688095,0.00007332243,0.00012473909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029213805,0.000648968,0.00043168745,0.0011607385,0.00058188697,0.00058590923,0.000381547,0.00063535076,0.002253871],"category_scores_gemma":[0.0013219184,0.00049454643,0.0003840487,0.00057843735,0.00073512574,0.0004331989,0.00041117158,0.0004889973,0.00029764528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036221982,0.0007071157,0.90674794,0.00009109098,0.00075415627,0.01515621,0.0014945638,0.00016591202,0.061193645,0.00017020403,0.00032481362,0.009572044],"study_design_scores_gemma":[0.000022420152,0.00021318521,0.9927867,0.000005710297,0.00012369186,0.005784721,0.00016241522,0.00010852679,0.0005988168,0.000067800625,0.000118225085,0.000007860792],"about_ca_topic_score_codex":0.0032698992,"about_ca_topic_score_gemma":0.0031220764,"teacher_disagreement_score":0.0032698992,"about_ca_system_score_codex":0.00023267952,"about_ca_system_score_gemma":0.00022831939,"threshold_uncertainty_score":0.007539928},"labels":[],"label_agreement":null},{"id":"W2508153689","doi":"10.1016/j.media.2016.09.001","title":"Conformal invariants for multiply connected surfaces: Application to landmark curve-based brain morphometry analysis","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; U.S. Department of Defense; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"Brain morphometry; Landmark; Invariant (physics); Conformal map; Neuroimaging; Computation; Mathematics; Artificial intelligence; Shape analysis (program analysis); Pattern recognition (psychology); Surface (topology); Geometry; Computer science; Algorithm; Neuroscience; Magnetic resonance imaging; Psychology; Medicine","score_opus":0.03491847557675011,"score_gpt":0.37055534472712737,"score_spread":0.33563686915037727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2508153689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017291058,0.00011990034,0.9806433,0.00008744441,0.000028325408,0.000053796186,0.00006975346,0.0009695816,0.00073680707],"genre_scores_gemma":[0.38407785,0.0005104007,0.6123063,0.000047475543,0.00010126289,0.000091929614,0.00026502897,0.0009962288,0.001603505],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953806,0.000084061714,0.000027440436,0.00008374932,0.00022162292,0.00004508141],"domain_scores_gemma":[0.998582,0.00060842297,0.00017537878,0.00024988592,0.00029096202,0.00009337412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083551655,0.00060656806,0.0010417755,0.00366678,0.000585723,0.0020881977,0.001071423,0.00089190825,0.0023413629],"category_scores_gemma":[0.005643562,0.00046280117,0.0011670147,0.0028364516,0.0011533079,0.0010576139,0.0018879304,0.0016407367,0.00069572724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013248688,0.00011841554,0.0026428897,0.00024598828,0.00008976582,0.00025843448,0.0004951861,0.15052488,0.033486374,0.076961935,0.0037705791,0.731273],"study_design_scores_gemma":[0.000011830092,0.000055114637,0.0012809321,0.000012999173,0.000023102239,0.00020858287,0.000077544406,0.9537772,0.006668636,0.034203716,0.003648691,0.00003157382],"about_ca_topic_score_codex":0.0025177666,"about_ca_topic_score_gemma":0.0022327122,"teacher_disagreement_score":0.00366678,"about_ca_system_score_codex":0.000658822,"about_ca_system_score_gemma":0.0009451268,"threshold_uncertainty_score":0.007832646},"labels":[],"label_agreement":null},{"id":"W2509368961","doi":"10.7717/peerj.2632","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model","year":2016,"lang":"en","type":"article","venue":"PeerJ","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"Medical Research Council","keywords":"Corpus callosum; Ex vivo; Magnetic resonance imaging; Diffusion MRI; Myelin; Relaxometry; Pathology; White matter; Neuroscience; Hippocampus; Central nervous system; Biology; Medicine; In vivo; Spin echo; Radiology","score_opus":0.09114219249002782,"score_gpt":0.37491447792262694,"score_spread":0.28377228543259914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509368961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83870184,0.0074091502,0.12543523,0.0014782831,0.0006537514,0.0007277915,0.013409192,0.0040710615,0.008113656],"genre_scores_gemma":[0.79377365,0.008341749,0.14592324,0.00065195933,0.00017640807,0.0019763203,0.010161963,0.0019040928,0.037090585],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991917,0.00008399781,0.00010376263,0.00028383755,0.00024977225,0.00008695204],"domain_scores_gemma":[0.9981875,0.00019545999,0.00067679904,0.0002828139,0.0003200319,0.00033740653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013750002,0.0019191534,0.00090997934,0.004601995,0.0007479357,0.0009372097,0.0012572573,0.001704914,0.0039323187],"category_scores_gemma":[0.0005934242,0.00065761793,0.00073452207,0.00087035244,0.0013699157,0.0012355102,0.0007097807,0.002088317,0.0018240139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032486964,0.00011327484,0.00026540895,0.00017200698,0.000029928753,0.00032546412,0.00013869899,0.00016189719,0.99556476,0.0005673094,0.0003390575,0.0019973502],"study_design_scores_gemma":[0.00005323314,0.00056746014,0.005424641,0.00011155543,0.00015269197,0.0018806776,0.0001307549,0.0017281265,0.9782395,0.00043813197,0.011218726,0.00005454305],"about_ca_topic_score_codex":0.0015170628,"about_ca_topic_score_gemma":0.0023814982,"teacher_disagreement_score":0.004601995,"about_ca_system_score_codex":0.0006443107,"about_ca_system_score_gemma":0.00041009663,"threshold_uncertainty_score":0.013154924},"labels":[],"label_agreement":null},{"id":"W2510336237","doi":"10.1016/j.neuroimage.2016.08.053","title":"Functional activity and white matter microstructure reveal the independent effects of age of acquisition and proficiency on second-language learning","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Age of Acquisition; Diffusion MRI; Functional magnetic resonance imaging; White matter; Superior temporal gyrus; Parahippocampal gyrus; Inferior frontal gyrus; Language proficiency; Mandarin Chinese; Cognitive psychology; Cognition; Linguistics; Neuroscience; Temporal lobe; Magnetic resonance imaging; Medicine","score_opus":0.0134870159044191,"score_gpt":0.27883595711147147,"score_spread":0.2653489412070524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510336237","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990575,0.000076250966,0.0004209555,0.000015338377,0.000001340618,0.0000015990715,0.000052051335,0.000006588516,0.00036837268],"genre_scores_gemma":[0.9992723,0.000044773693,0.00032632402,0.000008263303,0.0000017573028,0.0000031418776,0.00005339045,0.0000034965808,0.00028652174],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998952,0.000012864122,0.0000072079893,0.000045164317,0.000020822683,0.000018775003],"domain_scores_gemma":[0.99967945,0.000056785684,0.00014229881,0.00002973804,0.000034271354,0.00005739788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025394786,0.00020192315,0.00015559925,0.00046171987,0.00011768926,0.0002926677,0.00009221505,0.00021307926,0.0013096081],"category_scores_gemma":[0.0005506623,0.00014674313,0.0001452383,0.00016545261,0.00036996082,0.0002977781,0.00027020593,0.00019920687,0.0001315999],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047042393,0.00007531772,0.22168046,0.000056768065,0.000113370006,0.0004055232,0.00069071184,0.0001307761,0.7618507,0.00018873237,0.000086202366,0.014250999],"study_design_scores_gemma":[0.0000024507904,0.000077937926,0.9855117,0.000002349895,0.000013351014,0.00024717135,0.00010232288,0.00020587911,0.013657299,0.00009138897,0.00008476686,0.0000033541999],"about_ca_topic_score_codex":0.0019174672,"about_ca_topic_score_gemma":0.005401029,"teacher_disagreement_score":0.0019174672,"about_ca_system_score_codex":0.00015492164,"about_ca_system_score_gemma":0.00023964618,"threshold_uncertainty_score":0.0043810606},"labels":[],"label_agreement":null},{"id":"W2511678394","doi":"10.1093/cercor/bhw221","title":"Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm","year":2016,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Gestational age; Internal capsule; Pediatrics; Psychology; Medicine; Magnetic resonance imaging; Biology; Pregnancy; Radiology; Genetics","score_opus":0.03852160220448467,"score_gpt":0.31879269295294693,"score_spread":0.28027109074846224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2511678394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99956554,0.00008779555,0.000091964386,0.000010297318,0.0000012083337,0.0000020536777,0.00015979134,0.0000024413787,0.00007886367],"genre_scores_gemma":[0.99884796,0.00017207627,0.00029125443,0.000007767843,0.0000020505677,0.000012157958,0.000535608,0.0000028737843,0.00012820605],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971384,0.00007013528,0.000027765653,0.00006396581,0.00006802985,0.00005619974],"domain_scores_gemma":[0.9985625,0.0002266072,0.00056239025,0.00012265249,0.00031880484,0.00020709308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095197867,0.00017989946,0.000224693,0.00071563607,0.00043974695,0.0004368282,0.00025146836,0.0003055895,0.00034877562],"category_scores_gemma":[0.0034143154,0.00019105166,0.00026244292,0.00054174016,0.00022598359,0.00038861955,0.0005961395,0.000527614,0.00013504556],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010265076,0.000029623163,0.9950099,0.000009525161,0.000041958145,0.00014861386,0.00038961982,0.00006212145,0.0012330908,0.000038691454,0.000056953464,0.0028772939],"study_design_scores_gemma":[0.0000011342514,0.00006946737,0.9992292,0.000005025519,0.000011122286,0.00017710279,0.00013473321,0.000053421303,0.00019826932,0.000016226119,0.000102006874,0.0000024255723],"about_ca_topic_score_codex":0.010148627,"about_ca_topic_score_gemma":0.010636316,"teacher_disagreement_score":0.010148627,"about_ca_system_score_codex":0.00033582523,"about_ca_system_score_gemma":0.0003898725,"threshold_uncertainty_score":0.020179093},"labels":[],"label_agreement":null},{"id":"W2515079814","doi":"10.1016/j.neurobiolaging.2016.08.006","title":"Age-related white-matter correlates of motor sequence learning and consolidation","year":2016,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Western University; Hôpital du Sacré-Cœur de Montréal; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Corpus callosum; Psychology; Consolidation (business); Young adult; Memory consolidation; Corticospinal tract; Motor learning; Developmental psychology; Audiology; Neuroscience; Physical medicine and rehabilitation; Magnetic resonance imaging; Medicine","score_opus":0.033700747211780055,"score_gpt":0.3210379763784704,"score_spread":0.28733722916669036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515079814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99862313,0.00036919693,0.00041185008,0.000025339068,0.0000068994536,0.000006618443,0.00021816464,0.000006046995,0.00033275783],"genre_scores_gemma":[0.9985273,0.00024732688,0.00037193447,0.000014739333,0.000013249311,0.000009366362,0.0003030816,0.0000059161757,0.00050711085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993,0.000009301098,0.000010423353,0.000024289791,0.000013971739,0.000012122267],"domain_scores_gemma":[0.99902153,0.00013130673,0.00052153575,0.00009103587,0.00015113989,0.00008342925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038608236,0.00019127894,0.00020190985,0.0006367936,0.00013252169,0.00029636285,0.00019538759,0.00029199047,0.0011432611],"category_scores_gemma":[0.0014917814,0.00015232018,0.00009772006,0.0003620426,0.000320062,0.00056289387,0.00029134366,0.00035395246,0.00016052928],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037331202,0.00050461834,0.6006828,0.00015644918,0.0004479847,0.0006866265,0.0007965607,0.0012240921,0.33486608,0.0010106086,0.00080457877,0.055086486],"study_design_scores_gemma":[0.0000066212096,0.00019617166,0.99437547,0.0000037885627,0.00002493724,0.00026255727,0.000061799365,0.00031567324,0.004162941,0.00042244908,0.00016282554,0.000004825599],"about_ca_topic_score_codex":0.0012885757,"about_ca_topic_score_gemma":0.0023919654,"teacher_disagreement_score":0.0012885757,"about_ca_system_score_codex":0.00014905777,"about_ca_system_score_gemma":0.00014053639,"threshold_uncertainty_score":0.003824532},"labels":[],"label_agreement":null},{"id":"W2515350692","doi":"10.1007/s00429-016-1298-6","title":"Revisiting the human uncinate fasciculus, its subcomponents and asymmetries with stem-based tractography and microdissection validation","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Agence Nationale de la Recherche","keywords":"Tractography; Microdissection; Uncinate fasciculus; Psychology; Neuroscience; Diffusion MRI; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.029715552549711397,"score_gpt":0.28316871332772997,"score_spread":0.25345316077801855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515350692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8247615,0.0033203019,0.16719674,0.00026968014,0.00004462767,0.00006596335,0.00048098658,0.00024379608,0.0036163523],"genre_scores_gemma":[0.9591094,0.00103815,0.038206346,0.00006279245,0.000015776157,0.000039063754,0.00028762425,0.00013032532,0.0011104709],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995683,0.000096641896,0.00003988243,0.00011713762,0.0001338264,0.00004414431],"domain_scores_gemma":[0.9983138,0.0006145093,0.00019629906,0.00044623233,0.00036602022,0.00006315035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018227762,0.00040790878,0.000410444,0.0013005226,0.0005996893,0.0011035238,0.00043012307,0.00050371257,0.0013764821],"category_scores_gemma":[0.0036040721,0.00026543697,0.0002787545,0.000779362,0.0014284035,0.0011684458,0.00060442876,0.000462108,0.00042256305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058095914,0.00004550437,0.047629647,0.00051041297,0.0001495457,0.0009035805,0.0013178553,0.0064313714,0.7734741,0.012316677,0.000631031,0.15600933],"study_design_scores_gemma":[0.00006953013,0.00054209103,0.39786607,0.0006207741,0.0004895306,0.013506478,0.0015703316,0.074800186,0.44153962,0.024919469,0.04394247,0.00013347893],"about_ca_topic_score_codex":0.005536249,"about_ca_topic_score_gemma":0.012696859,"teacher_disagreement_score":0.005536249,"about_ca_system_score_codex":0.0004406779,"about_ca_system_score_gemma":0.0010520723,"threshold_uncertainty_score":0.011008084},"labels":[],"label_agreement":null},{"id":"W2515401228","doi":"10.3791/53759","title":"Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography","year":2016,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lateral geniculate nucleus; Tractography; Diffusion MRI; Optic radiation; Neuroscience; Visual cortex; Decussation; Albinism; Optic chiasm; Retinotopy; White matter; Biology; Artificial intelligence; Physics; Computer science; Optic nerve; Magnetic resonance imaging; Medicine","score_opus":0.10341913999359678,"score_gpt":0.452052485913231,"score_spread":0.34863334591963424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515401228","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953909,0.00020176424,0.0037959456,0.000049939816,0.0000021498715,0.000041680778,0.00017550807,0.000039700113,0.00030240978],"genre_scores_gemma":[0.98679525,0.0003533411,0.0121429395,0.0000125457145,0.0000057329016,0.00004362516,0.00022135573,0.000018210907,0.00040700118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986196,0.00003289082,0.000015112277,0.000048151876,0.000028644443,0.000013240528],"domain_scores_gemma":[0.99961346,0.00012493784,0.00012926078,0.000042303203,0.000046436042,0.000043588065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003589008,0.00044584632,0.00019592131,0.0013488131,0.00025361465,0.0004201869,0.0001568154,0.0002846943,0.0010526107],"category_scores_gemma":[0.0016159435,0.00013207473,0.0002021115,0.0005328064,0.00037966625,0.0003318321,0.0002527765,0.00016136968,0.00011259653],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002399479,0.00029310654,0.51237565,0.0005299306,0.00050562737,0.004394785,0.003077204,0.011946907,0.24133538,0.0018179026,0.0012849765,0.22003904],"study_design_scores_gemma":[0.00004847319,0.000387159,0.9582256,0.000030166164,0.00010046906,0.0039535887,0.00041172418,0.020586638,0.013866826,0.0013669694,0.0009766862,0.000045736724],"about_ca_topic_score_codex":0.0059971167,"about_ca_topic_score_gemma":0.0077680713,"teacher_disagreement_score":0.0059971167,"about_ca_system_score_codex":0.00039933377,"about_ca_system_score_gemma":0.00023849623,"threshold_uncertainty_score":0.011924446},"labels":[],"label_agreement":null},{"id":"W2517974079","doi":"10.1093/cercor/bhw250","title":"Impaired Frontal-Limbic White Matter Maturation in Children at Risk for Major Depression","year":2016,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health; Canadian Institutes of Health Research; Tommy Fuss Fund","keywords":"Depression (economics); Fractional anisotropy; White matter; Psychology; Corpus callosum; Cingulum (brain); Anterior cingulate cortex; Pathological; Limbic system; Risk factor; Neuroscience; Mood disorders; Clinical psychology; Anxiety; Internal medicine; Medicine; Psychiatry; Central nervous system; Magnetic resonance imaging; Cognition","score_opus":0.017751103400360176,"score_gpt":0.28944592070922104,"score_spread":0.27169481730886086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2517974079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99971896,0.000097157,0.000022197157,0.000012258947,0.0000013411093,0.0000013206799,0.000041244297,0.0000019482452,0.00010352463],"genre_scores_gemma":[0.99966705,0.000114489136,0.00007912413,0.000007097774,0.0000019135855,0.0000019916254,0.000059266666,9.842444e-7,0.00006815692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991167,0.000016616406,0.000007875503,0.000028039023,0.000016135475,0.00001969412],"domain_scores_gemma":[0.999708,0.000033487227,0.00017839334,0.000014700997,0.000022335915,0.000043073193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019029535,0.00027471883,0.00016614459,0.0005995133,0.00022256549,0.00026555924,0.00014429522,0.0002572006,0.0010476749],"category_scores_gemma":[0.0008182118,0.00022463342,0.00015716927,0.0003132008,0.0002678766,0.00018924352,0.0002045073,0.00029663337,0.00011603302],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019183251,0.000043561846,0.9903515,0.000015667407,0.000032734122,0.0005370628,0.00026078027,0.000042991356,0.0048410255,0.00002967132,0.000108463755,0.0035447262],"study_design_scores_gemma":[0.0000015332805,0.000035282676,0.9991504,0.0000026406094,0.000007912024,0.0005211668,0.0000626434,0.000022339898,0.00015681346,0.000008239727,0.000030399186,6.488858e-7],"about_ca_topic_score_codex":0.00520984,"about_ca_topic_score_gemma":0.0069196015,"teacher_disagreement_score":0.00520984,"about_ca_system_score_codex":0.00026967167,"about_ca_system_score_gemma":0.00016028868,"threshold_uncertainty_score":0.010358989},"labels":[],"label_agreement":null},{"id":"W2518385205","doi":"10.3389/fnhum.2016.00410","title":"Identification of Reliable Sulcal Patterns of the Human Rolandic Region","year":2016,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital de l'Enfant-Jésus","funders":"","keywords":"Concordance; Lateralization of brain function; Segmentation; Magnetic resonance imaging; Human brain; Nuclear medicine; Anatomy; Medicine; Cartography; Psychology; Computer science; Radiology; Neuroscience; Artificial intelligence; Audiology; Geography","score_opus":0.04754164539441399,"score_gpt":0.3288227069448095,"score_spread":0.2812810615503955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518385205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98786795,0.00045308698,0.010730502,0.000014468333,0.000008630015,0.000044064884,0.00013998931,0.000078147816,0.00066328153],"genre_scores_gemma":[0.9924964,0.00014436273,0.0068387147,0.000004605596,0.000008621816,0.000025027457,0.00024171527,0.000036227546,0.00020427196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99857974,0.00042657592,0.0002073945,0.0004128294,0.00029727304,0.00007621843],"domain_scores_gemma":[0.9931973,0.0021583254,0.0015745955,0.001573992,0.0013179835,0.00017779325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022424315,0.00040718148,0.00041648615,0.0014081092,0.00027669422,0.00055308593,0.00028283516,0.00032228068,0.0007719131],"category_scores_gemma":[0.010425774,0.00020977948,0.00022732063,0.00045034883,0.0007916601,0.000383785,0.000606625,0.00016141092,0.00038788357],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002277687,0.00010773123,0.42125207,0.000783912,0.0003604632,0.0013411851,0.004772505,0.0025158306,0.3779999,0.0005357104,0.0005873263,0.18746571],"study_design_scores_gemma":[0.000028723965,0.00050706975,0.9419845,0.000047960217,0.0001121178,0.0036309615,0.00060285436,0.003623085,0.047845464,0.0004739059,0.0010999246,0.00004340744],"about_ca_topic_score_codex":0.00090074487,"about_ca_topic_score_gemma":0.0017220818,"teacher_disagreement_score":0.0022424315,"about_ca_system_score_codex":0.00011315007,"about_ca_system_score_gemma":0.00029176867,"threshold_uncertainty_score":0.011859238},"labels":[],"label_agreement":null},{"id":"W2520118764","doi":"10.1007/s00406-016-0730-5","title":"Altered intracortical myelin staining in the dorsolateral prefrontal cortex in severe mental illness","year":2016,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Sunnybrook Health Science Centre","funders":"Stanley Medical Research Institute; Brain and Behavior Research Foundation","keywords":"White matter; Myelin; Luxol fast blue stain; Dorsolateral prefrontal cortex; Neuroscience; Major depressive disorder; Cortex (anatomy); Anterior cingulate cortex; Prefrontal cortex; Schizophrenia (object-oriented programming); Psychology; Medicine; Central nervous system; Psychiatry; Magnetic resonance imaging; Cognition","score_opus":0.048367836148668214,"score_gpt":0.3728467860560255,"score_spread":0.32447894990735726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2520118764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99909985,0.00020704945,0.00018953794,0.000035833753,0.0000021342294,0.0000020017208,0.00002734287,0.0000041975627,0.00043205518],"genre_scores_gemma":[0.9997274,0.00007497643,0.00007607518,0.000007825123,0.0000024071044,0.0000010193681,0.000018072284,0.0000012741131,0.000090973954],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993825,0.000012394772,0.0000061075716,0.000009558228,0.000014005525,0.000019737043],"domain_scores_gemma":[0.99977595,0.00004374938,0.00009907672,0.000014708209,0.00002466391,0.000041944644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016426391,0.00023520802,0.00011664584,0.00068554725,0.00025752155,0.0002471603,0.0001883562,0.0002574108,0.0016108588],"category_scores_gemma":[0.00045663878,0.00015988006,0.000111540925,0.00023408448,0.0006046817,0.0002026433,0.00032247,0.00030127828,0.00009585511],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004288149,0.00013712917,0.21920335,0.0004117887,0.0003165793,0.014976092,0.0019891742,0.0006829533,0.7262389,0.00054050324,0.00031013723,0.030905193],"study_design_scores_gemma":[0.00002136859,0.00016366916,0.9768689,0.000015047807,0.000053894233,0.009208086,0.0007225142,0.00042492812,0.011871209,0.0004764907,0.00016488285,0.000009061736],"about_ca_topic_score_codex":0.003912952,"about_ca_topic_score_gemma":0.005598777,"teacher_disagreement_score":0.003912952,"about_ca_system_score_codex":0.00021878855,"about_ca_system_score_gemma":0.00017538197,"threshold_uncertainty_score":0.007780373},"labels":[],"label_agreement":null},{"id":"W2520475080","doi":"10.82308/26415","title":"Perceptual organisation in diffusion MRI: curves and streamline flows","year":2009,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Tangent; Artificial intelligence; Inference; Orientation (vector space); Computer science; Computer vision; Diffusion MRI; Algorithm; Geometry; Mathematics","score_opus":0.07893361469951948,"score_gpt":0.38806300680384137,"score_spread":0.3091293921043219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2520475080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038569715,0.0012035046,0.9564184,0.00068248337,0.00005635935,0.000045408357,0.0001457788,0.00015964286,0.0027187224],"genre_scores_gemma":[0.57312834,0.0033553469,0.41612986,0.00017343753,0.0003348447,0.00014528958,0.00041052367,0.00026248585,0.006059812],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954873,0.000146938,0.00002252368,0.00013280922,0.000105993844,0.000042980737],"domain_scores_gemma":[0.9973334,0.0013630317,0.0004986195,0.00024782357,0.0003297667,0.00022732158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013195291,0.00058295,0.0005569564,0.0020540857,0.00070051017,0.0024957482,0.00081025454,0.0011498082,0.0023794158],"category_scores_gemma":[0.007847502,0.0006135575,0.0008856133,0.0011365814,0.0024396705,0.0043390966,0.0015595885,0.0015106867,0.0003814328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094895775,0.000029561692,0.0014970319,0.00015791313,0.000028630844,0.00015343273,0.0010441443,0.18999358,0.0060790023,0.7304543,0.00157553,0.06889211],"study_design_scores_gemma":[0.000013648672,0.00004499342,0.0010866266,0.000046779012,0.000009570621,0.00010948723,0.000102755104,0.6027726,0.0011686604,0.388791,0.0058142245,0.000039595],"about_ca_topic_score_codex":0.003153095,"about_ca_topic_score_gemma":0.0015387146,"teacher_disagreement_score":0.003153095,"about_ca_system_score_codex":0.0011032904,"about_ca_system_score_gemma":0.00069096114,"threshold_uncertainty_score":0.008005023},"labels":[],"label_agreement":null},{"id":"W2521607924","doi":"10.1016/j.neuroimage.2016.08.027","title":"Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Fujirebio Europe; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; Lundbeckfonden; Alzheimer's Drug Discovery Foundation; Chinese Academy of Sciences; National Natural Science Foundation of China; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Wellcome Trust; Roche; Merck; Takeda Pharmaceutical Company; AbbVie; National Institute on Aging; Queen Mary University of London; Wellcome; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Covariate; Overfitting; Nonparametric statistics; Neuroimaging; Computer science; Artificial intelligence; Imaging genetics; Interpretability; Dimensionality reduction; Curse of dimensionality; Machine learning; Mathematics; Econometrics; Psychology","score_opus":0.056628162743357746,"score_gpt":0.33561193653538707,"score_spread":0.2789837737920293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521607924","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052667195,0.0015531668,0.99100786,0.0009900054,0.000066173176,0.000030221576,0.00022684825,0.000303024,0.00055601547],"genre_scores_gemma":[0.096865475,0.004013551,0.8909512,0.0002771666,0.00045935786,0.00020776763,0.0007717844,0.00035722172,0.006096433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981041,0.0011781277,0.00008952766,0.00031561742,0.0002364591,0.00007621751],"domain_scores_gemma":[0.9906872,0.0056517352,0.0010470214,0.0011774774,0.001120849,0.00031565802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00563018,0.0019988471,0.0014537195,0.001774507,0.0006680214,0.0019716488,0.0018572923,0.0020057363,0.0033954263],"category_scores_gemma":[0.02384476,0.0007761114,0.0014725926,0.0025216774,0.0023831541,0.0028514562,0.0018058763,0.003032397,0.0011654416],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019447887,0.00023299504,0.0033020019,0.00064137374,0.0003408713,0.00044605584,0.00044414672,0.30947387,0.008361986,0.44667378,0.016755737,0.21313265],"study_design_scores_gemma":[0.000024184683,0.000041583997,0.000764841,0.000058222275,0.00003455433,0.0001537629,0.000055000608,0.7329441,0.0010492386,0.26025224,0.004560348,0.0000618874],"about_ca_topic_score_codex":0.010145562,"about_ca_topic_score_gemma":0.013869203,"teacher_disagreement_score":0.010145562,"about_ca_system_score_codex":0.0011272368,"about_ca_system_score_gemma":0.002846034,"threshold_uncertainty_score":0.02977562},"labels":[],"label_agreement":null},{"id":"W2523274259","doi":"10.1002/hbm.23399","title":"Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET)","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Tractography; Voxel; Diffusion MRI; Prior probability; Optic radiation; Artificial intelligence; Computer science; Loop (graph theory); White matter; Pattern recognition (psychology); Magnetic resonance imaging; Bayesian probability; Mathematics; Radiology; Medicine","score_opus":0.11054802625502137,"score_gpt":0.37362930450917187,"score_spread":0.2630812782541505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523274259","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023325348,0.00016170793,0.9754419,0.00005815099,0.000010806936,0.00004505102,0.00006553817,0.000571352,0.00032002904],"genre_scores_gemma":[0.22038117,0.0002467821,0.7781031,0.00005922618,0.000026939158,0.00012067366,0.00023129479,0.00021558697,0.0006151712],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996451,0.00010195964,0.0000271844,0.00011578138,0.00008350507,0.00002639425],"domain_scores_gemma":[0.9988943,0.0006178969,0.00023517538,0.000107685926,0.000107110915,0.00003776892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012453693,0.0009282367,0.00065060845,0.0013427289,0.00040107116,0.0010373895,0.000756846,0.0008565093,0.0007104527],"category_scores_gemma":[0.0034750488,0.0005446663,0.0008796703,0.00071247143,0.0007360707,0.0012313735,0.0008632236,0.00087223254,0.00024747578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052869046,0.000099437755,0.005298684,0.00034835754,0.00022753868,0.00044499466,0.0007607199,0.34027553,0.075301,0.028096307,0.0024138354,0.5462049],"study_design_scores_gemma":[0.00003304319,0.00011535748,0.0018757173,0.00003340914,0.000057549587,0.00028384392,0.000038568418,0.95507306,0.025706101,0.013699144,0.003041035,0.000043227465],"about_ca_topic_score_codex":0.0037901627,"about_ca_topic_score_gemma":0.005110193,"teacher_disagreement_score":0.0037901627,"about_ca_system_score_codex":0.0005991483,"about_ca_system_score_gemma":0.0010523184,"threshold_uncertainty_score":0.0075362325},"labels":[],"label_agreement":null},{"id":"W2523445319","doi":"10.1016/j.neuroimage.2016.09.018","title":"g-Ratio weighted imaging of the human spinal cord in vivo","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Axon; Spinal cord; Anatomy; Surface-area-to-volume ratio; Chemistry; Biology; Magnetic resonance imaging; Central nervous system; Medicine; Neuroscience; Radiology","score_opus":0.0545877705470188,"score_gpt":0.3621916563437483,"score_spread":0.3076038857967295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523445319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92799336,0.006512199,0.04917333,0.0016222525,0.0000739587,0.00013644974,0.0008616605,0.0005524271,0.013074303],"genre_scores_gemma":[0.9751024,0.0032077832,0.015888548,0.00031500048,0.00006713006,0.000050228486,0.00035175632,0.00013286721,0.0048842067],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999459,0.000019103854,0.00000381309,0.0000125158585,0.000009097982,0.000009649993],"domain_scores_gemma":[0.99988115,0.000054462114,0.000015782936,0.000011875425,0.000021474885,0.000015314321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027572145,0.00031300532,0.00018591722,0.00062251044,0.00031249216,0.00049490953,0.00036530208,0.0010731723,0.004310048],"category_scores_gemma":[0.0008110506,0.0002634191,0.00010937417,0.00039385242,0.00048453815,0.00074924575,0.0003081133,0.0004509507,0.00061710563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017363415,0.00013255129,0.0017243003,0.0006358825,0.000075934506,0.0014034032,0.00029680526,0.0018984126,0.953181,0.0012259965,0.0016452699,0.036044165],"study_design_scores_gemma":[0.00052927126,0.0042150393,0.099901564,0.0003188595,0.00073244935,0.027162572,0.0012035187,0.025978748,0.81425196,0.0075615756,0.01801478,0.00012959173],"about_ca_topic_score_codex":0.0023448628,"about_ca_topic_score_gemma":0.002153205,"teacher_disagreement_score":0.004310048,"about_ca_system_score_codex":0.00015565014,"about_ca_system_score_gemma":0.00039335896,"threshold_uncertainty_score":0.014418542},"labels":[],"label_agreement":null},{"id":"W2526156408","doi":"10.3389/fnana.2016.00092","title":"An In vivo Multi-Modal Structural Template for Neonatal Piglets Using High Angular Resolution and Population-Based Whole-Brain Tractography","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Hospital for Sick Children; Toronto Rehabilitation Institute; SickKids Foundation; University Health Network; University of Toronto; Ontario Brain Institute","funders":"Fondation Brain Canada","keywords":"White matter; Diffusion MRI; Neuroimaging; Population; Metric (unit); Tractography; Segmentation; Artificial intelligence; Computer science; Pattern recognition (psychology); Neuroscience; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.028897425410416795,"score_gpt":0.33080834011038973,"score_spread":0.30191091469997294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526156408","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036842827,0.00016216579,0.96046907,0.00013272355,0.000019807847,0.000074352036,0.00047614024,0.001022094,0.0008007191],"genre_scores_gemma":[0.15376666,0.00053985266,0.842419,0.00007931125,0.00001807029,0.00028415496,0.0009698971,0.0004272256,0.0014958485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998845,0.000026236523,0.000010227054,0.000035440848,0.000034606455,0.000009063356],"domain_scores_gemma":[0.9996834,0.00009127959,0.00006992364,0.00007691072,0.000058651658,0.00001988258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074201555,0.00032935204,0.00029597123,0.0007544423,0.00020022278,0.00064730324,0.0004269058,0.00083479827,0.0019350797],"category_scores_gemma":[0.0016723267,0.00039130097,0.00059959927,0.0005230024,0.0002570861,0.0004580513,0.0003887524,0.0005274563,0.000589133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029847646,0.00009832445,0.008019485,0.000342297,0.0001830481,0.0014250195,0.00040434927,0.09916753,0.53026044,0.0122189745,0.005775276,0.34180668],"study_design_scores_gemma":[0.000027629938,0.00040673555,0.02625748,0.00011359463,0.00017060121,0.004594624,0.00013958407,0.7544949,0.176964,0.013301447,0.023404075,0.00012529489],"about_ca_topic_score_codex":0.002958236,"about_ca_topic_score_gemma":0.005588936,"teacher_disagreement_score":0.002958236,"about_ca_system_score_codex":0.00035754248,"about_ca_system_score_gemma":0.0009463098,"threshold_uncertainty_score":0.0064735413},"labels":[],"label_agreement":null},{"id":"W2526742587","doi":"10.1007/978-3-319-46720-7_21","title":"Predictive Subnetwork Extraction with Structural Priors for Infant Connectomes","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hospital for Sick Children; University of Toronto; Child and Family Research Institute; Simon Fraser University","funders":"","keywords":"Connectome; Subnetwork; Computer science; Prior probability; Artificial intelligence; Constraint (computer-aided design); Diffusion MRI; Pattern recognition (psychology); Machine learning; Functional connectivity; Neuroscience; Mathematics; Psychology; Bayesian probability","score_opus":0.029243037323431285,"score_gpt":0.3256026376107184,"score_spread":0.2963596002872871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526742587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017963324,0.0011870669,0.9733462,0.00034493863,0.000052806467,0.00006727744,0.001214557,0.0037454076,0.002078521],"genre_scores_gemma":[0.35802713,0.0022432879,0.6176298,0.00020810959,0.00032379944,0.00034080984,0.008610574,0.0011590329,0.011457438],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996625,0.000073279705,0.000017295188,0.00012511245,0.00007532322,0.00004653297],"domain_scores_gemma":[0.9989091,0.0006363209,0.00008824323,0.00021236876,0.00010759277,0.000046347464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010690774,0.0015983057,0.001209574,0.002778102,0.00053341006,0.0012031954,0.0016604444,0.0019525227,0.004190026],"category_scores_gemma":[0.0036636998,0.0010289502,0.0018506215,0.0020152654,0.00049936556,0.0015135694,0.0015717197,0.002158839,0.0027468044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039282918,0.00014493882,0.0031985037,0.0003165548,0.0002341284,0.00042949646,0.00017019727,0.156836,0.023378989,0.013628792,0.018452741,0.7828168],"study_design_scores_gemma":[0.000019200514,0.000029744406,0.0016408246,0.000060118422,0.00007573223,0.00022555626,0.000025698444,0.9643396,0.0054233596,0.025097284,0.0030454628,0.000017512119],"about_ca_topic_score_codex":0.004245776,"about_ca_topic_score_gemma":0.010611492,"teacher_disagreement_score":0.004245776,"about_ca_system_score_codex":0.00048905675,"about_ca_system_score_gemma":0.00094859645,"threshold_uncertainty_score":0.0140170455},"labels":[],"label_agreement":null},{"id":"W2527824541","doi":"","title":"Group sparse kernelized dictionary learning for the clustering of white matter fibers","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Kernel (algebra); Cluster analysis; Outlier; Fiber bundle; Feature (linguistics); Sparse approximation; Dictionary learning; Feature learning; Fiber; Mathematics","score_opus":0.04612359615896681,"score_gpt":0.32267024458182375,"score_spread":0.2765466484228569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527824541","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042162356,0.00011831488,0.99486536,0.00006639732,0.000016355403,0.000021172813,0.000039682935,0.000303504,0.0003529578],"genre_scores_gemma":[0.1417147,0.00024900417,0.85490125,0.00011170788,0.000080661455,0.00013163158,0.0005715231,0.00027265362,0.001966895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990151,0.0003200725,0.0000442557,0.00025984933,0.00028125205,0.00007931845],"domain_scores_gemma":[0.9984225,0.0004919117,0.00018066114,0.00040072712,0.00042035026,0.00008378232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012139591,0.000828621,0.0012409089,0.0013155513,0.0006969865,0.00091226125,0.0015741296,0.0012482122,0.0016975778],"category_scores_gemma":[0.0047288043,0.00044390175,0.0009003476,0.0016958906,0.00086787064,0.0015524722,0.001423866,0.0015177809,0.0012485238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026001135,0.00020020537,0.002107589,0.0002784912,0.00023703018,0.00014298607,0.00037662114,0.3699968,0.026905237,0.035248265,0.011917399,0.5523293],"study_design_scores_gemma":[0.000014540399,0.000034839344,0.000227658,0.000008856451,0.000011701692,0.000045858782,0.000021719994,0.9838833,0.0032652235,0.010498366,0.0019748819,0.00001309187],"about_ca_topic_score_codex":0.0041620247,"about_ca_topic_score_gemma":0.0051625785,"teacher_disagreement_score":0.0041620247,"about_ca_system_score_codex":0.00075687555,"about_ca_system_score_gemma":0.0013380941,"threshold_uncertainty_score":0.0082755685},"labels":[],"label_agreement":null},{"id":"W2528727157","doi":"10.1016/j.neuroimage.2016.10.009","title":"SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":628,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Spinal cord; Computer science; Software; Neuroimaging; Standardization; Medicine; Toolbox","score_opus":0.21217250137722327,"score_gpt":0.44659657430929695,"score_spread":0.23442407293207368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528727157","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009919501,0.0015714159,0.48627564,0.0005805779,0.00042032864,0.0005032261,0.044621773,0.44873962,0.007367882],"genre_scores_gemma":[0.08256727,0.0016729999,0.7361822,0.0009884315,0.0003137844,0.002352729,0.049822617,0.10939989,0.01670001],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99965155,0.00004345649,0.0000717472,0.00008722399,0.00010564375,0.00004029184],"domain_scores_gemma":[0.99858934,0.00069933705,0.00013583363,0.00017108767,0.00028467673,0.00011973747],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0010419685,0.0016927641,0.0010842099,0.0026590226,0.0005676105,0.0017484747,0.0021458513,0.0011400334,0.08502798],"category_scores_gemma":[0.0061335242,0.0008748598,0.0013129908,0.0017425565,0.0003945653,0.0014285152,0.001982381,0.001696617,0.022343151],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013453141,0.00013960019,0.002907166,0.003003968,0.0005507666,0.00096671435,0.00046985617,0.005837275,0.023692748,0.0054886322,0.46785787,0.4877401],"study_design_scores_gemma":[0.0017897867,0.00061036355,0.021017166,0.0012707197,0.000763855,0.009393633,0.0004135302,0.259229,0.14430618,0.056546777,0.5039401,0.0007187613],"about_ca_topic_score_codex":0.003288683,"about_ca_topic_score_gemma":0.0073033585,"teacher_disagreement_score":0.9978542,"about_ca_system_score_codex":0.0005550333,"about_ca_system_score_gemma":0.0024527758,"threshold_uncertainty_score":0.2844469},"labels":[],"label_agreement":null},{"id":"W2528967587","doi":"10.1016/j.artmed.2016.09.003","title":"Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm","year":2016,"lang":"en","type":"article","venue":"Artificial Intelligence in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Computer science; Artificial intelligence; Segmentation; Pattern recognition (psychology); Diffusion MRI; Spectral clustering; DBSCAN; Fiber bundle; Fuzzy clustering; Algorithm; CURE data clustering algorithm; Bundle","score_opus":0.15710639887640207,"score_gpt":0.4112737736595068,"score_spread":0.2541673747831047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528967587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01349456,0.00012963699,0.9850327,0.00009290042,0.00003039551,0.000060551043,0.00006153797,0.00081312476,0.00028471183],"genre_scores_gemma":[0.037870783,0.00011939834,0.960703,0.000025230254,0.000020852045,0.00006516733,0.00020348186,0.0001882589,0.00080380344],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99911255,0.0001339367,0.00007437635,0.00024896394,0.00035605207,0.00007419295],"domain_scores_gemma":[0.9981085,0.0004694063,0.0001920097,0.00023419214,0.0009111984,0.00008466635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012127131,0.0009580635,0.0014283513,0.00345206,0.0012131967,0.001749105,0.0017166343,0.0014266736,0.0013935043],"category_scores_gemma":[0.0031469571,0.0010157184,0.001421512,0.0019806724,0.0006988931,0.0018678984,0.0012703938,0.0011351552,0.0010631492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033317626,0.00026529646,0.0028120396,0.00027196243,0.00023501688,0.00014250119,0.00035092767,0.124319755,0.09749433,0.007783833,0.00511606,0.7608752],"study_design_scores_gemma":[0.000029282688,0.00003428315,0.0018877119,0.00001695709,0.0000476779,0.0001818806,0.000037506205,0.9761261,0.016154442,0.0035318297,0.0019045497,0.000047914695],"about_ca_topic_score_codex":0.018602435,"about_ca_topic_score_gemma":0.02323607,"teacher_disagreement_score":0.018602435,"about_ca_system_score_codex":0.0012348538,"about_ca_system_score_gemma":0.0028493595,"threshold_uncertainty_score":0.036988318},"labels":[],"label_agreement":null},{"id":"W2528977329","doi":"10.1038/srep32833","title":"In-vivo Dynamics of the Human Hippocampus across the Menstrual Cycle","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":167,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; Douglas Mental Health University Institute","funders":"Max-Planck-Gesellschaft","keywords":"Hippocampal formation; Menstrual cycle; Estrogen; Hippocampus; Neuroimaging; Hormone; Neuroscience; Neuroplasticity; Fractional anisotropy; Sexual dimorphism; Ovulation; Physiology; Human brain; Biology; Medicine; Endocrinology; Internal medicine; Psychology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.027306205042633737,"score_gpt":0.3493622372302128,"score_spread":0.32205603218757906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528977329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962606,0.00091630913,0.0018407517,0.000058202644,0.00000695459,0.00001000286,0.00022857927,0.000020086616,0.0006583708],"genre_scores_gemma":[0.99761236,0.00049663545,0.0013734427,0.00002568617,0.0000072628955,0.000012024224,0.00012160817,0.00000889117,0.00034216593],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999697,0.00000909243,0.0000020262682,0.00000801196,0.0000059283843,0.00000513428],"domain_scores_gemma":[0.9999013,0.000023854103,0.000026103737,0.000015622285,0.000021238304,0.000011844119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015728336,0.00007864993,0.000102533755,0.00026749328,0.00012033218,0.00019980018,0.00009479794,0.00013913473,0.00076174526],"category_scores_gemma":[0.00051298644,0.00010972307,0.000053602955,0.00014744315,0.00017764873,0.00014122821,0.0001151105,0.000100123376,0.00015966585],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016675335,0.000087644614,0.078417,0.00014809909,0.0001260009,0.0006870896,0.0008350902,0.0009202591,0.86322534,0.0003005731,0.0009032535,0.052682128],"study_design_scores_gemma":[0.00005254248,0.00080164114,0.90206194,0.000028618195,0.00013623052,0.0029781244,0.0007141448,0.0038884017,0.08440029,0.0008245772,0.004087524,0.000026010066],"about_ca_topic_score_codex":0.0016509072,"about_ca_topic_score_gemma":0.0031627482,"teacher_disagreement_score":0.0016509072,"about_ca_system_score_codex":0.00007116326,"about_ca_system_score_gemma":0.00011518002,"threshold_uncertainty_score":0.0032826662},"labels":[],"label_agreement":null},{"id":"W2529768151","doi":"10.7759/cureus.817","title":"Interhemispheric Difference Images from Postoperative Diffusion Tensor Imaging of Gliomas","year":2016,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Organisation Canadienne des Physiciens Médicaux; Canadian Association of Radiation Oncology; American Association of Physicists in Medicine","keywords":"Medicine; Diffusion MRI; Nuclear medicine; Fractional anisotropy; Magnetic resonance imaging; Voxel; Glioma; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.036998995925060334,"score_gpt":0.3273018284625544,"score_spread":0.29030283253749406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529768151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9467177,0.0007358506,0.04957475,0.00008786135,0.00003148043,0.000064910935,0.00069736305,0.00032691623,0.0017630385],"genre_scores_gemma":[0.95867294,0.0002449381,0.04000254,0.000013551148,0.000012297533,0.000037589634,0.00042242953,0.00007039049,0.0005232302],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99987876,0.000023074823,0.000015737733,0.000024182573,0.000045002387,0.000013168391],"domain_scores_gemma":[0.9995431,0.000115132396,0.00013479032,0.00005050339,0.0001253129,0.000031251926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042809173,0.00029343046,0.00013590758,0.0011196262,0.00014085368,0.00041631627,0.00019964897,0.00020357754,0.0012359428],"category_scores_gemma":[0.0020535882,0.00010934226,0.00019130959,0.00040537084,0.00015576773,0.0003204742,0.00018401165,0.00017691813,0.0002745049],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015440937,0.00009798331,0.12417327,0.0006127895,0.00026111444,0.00094575033,0.00068057043,0.007916133,0.37225547,0.0015699654,0.0020062493,0.48793662],"study_design_scores_gemma":[0.00006609362,0.00050519366,0.6945776,0.00006529975,0.00018156317,0.008273759,0.0005252712,0.064032055,0.22078322,0.0035531411,0.007339048,0.000097704535],"about_ca_topic_score_codex":0.0020885447,"about_ca_topic_score_gemma":0.0031733478,"teacher_disagreement_score":0.0020885447,"about_ca_system_score_codex":0.0002760347,"about_ca_system_score_gemma":0.00034689013,"threshold_uncertainty_score":0.004152775},"labels":[],"label_agreement":null},{"id":"W2531143546","doi":"10.3389/fnana.2016.00096","title":"Merged Group Tractography Evaluation with Selective Automated Group Integrated Tractography","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; Krembil Foundation; University of Toronto","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; European Genomic Institute for Diabetes","keywords":"Tractography; Decussation; Artificial intelligence; Diffusion MRI; Computer science; Human Connectome Project; Neuroanatomy; Pattern recognition (psychology); Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.022463696182611948,"score_gpt":0.3081746143063434,"score_spread":0.28571091812373145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531143546","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11482704,0.00033864361,0.87840843,0.00012060284,0.000032273012,0.00029900877,0.0005670746,0.004491801,0.00091516436],"genre_scores_gemma":[0.33624947,0.00016250786,0.6598932,0.000053470867,0.000034440254,0.0004532756,0.0011496707,0.0012601165,0.0007438496],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976458,0.0009259757,0.0002766408,0.0004307195,0.00060220493,0.000118626886],"domain_scores_gemma":[0.9917024,0.0032417304,0.0014845354,0.0014760384,0.0018001079,0.00029519523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075364695,0.0012501434,0.00097596075,0.0038770884,0.000646495,0.0019879672,0.001022983,0.0010955689,0.0046589514],"category_scores_gemma":[0.018414516,0.0004916977,0.001244132,0.0018833114,0.0010646892,0.0016592962,0.0018837588,0.0006225589,0.000850716],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002247917,0.00024824624,0.0746088,0.0015115964,0.0024118745,0.00088476867,0.0024094686,0.094061464,0.12080429,0.010290252,0.0068556913,0.6836657],"study_design_scores_gemma":[0.00018832803,0.0012674376,0.0688832,0.00016829037,0.00060501357,0.0023633505,0.00054440345,0.8013131,0.09480379,0.01834853,0.011320171,0.00019442929],"about_ca_topic_score_codex":0.002653269,"about_ca_topic_score_gemma":0.005603611,"teacher_disagreement_score":0.0075364695,"about_ca_system_score_codex":0.00074383867,"about_ca_system_score_gemma":0.0014533022,"threshold_uncertainty_score":0.03985715},"labels":[],"label_agreement":null},{"id":"W2531371400","doi":"10.1111/adb.12466","title":"Progressive white matter impairment as a predictor of outcome in a cohort of opioid‐dependent patient's post‐detoxification","year":2016,"lang":"en","type":"article","venue":"Addiction Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"Trinity College Dublin","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Grey matter; Psychology; Internal medicine; Opioid; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.020075453226041734,"score_gpt":0.3270657382763677,"score_spread":0.306990285050326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531371400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998988,0.000023119668,0.0000087392245,0.0000067345177,6.843817e-7,0.0000014660123,0.00002170666,4.1934877e-7,0.00003837485],"genre_scores_gemma":[0.9997776,0.000036736357,0.000018915722,0.0000066122325,0.0000026381726,0.000002711709,0.000078965226,4.6613792e-7,0.00007549754],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999217,0.00001318361,0.000008558522,0.000016391345,0.000015830201,0.000024262847],"domain_scores_gemma":[0.999617,0.000047053756,0.00016402181,0.000023594881,0.00003870843,0.000109655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016613111,0.00022228852,0.00027519854,0.00044685687,0.0005322344,0.00038091277,0.00016058027,0.00028905942,0.0011564405],"category_scores_gemma":[0.0007799285,0.00017427742,0.00016839933,0.0003304103,0.0002390998,0.00022757391,0.00028538867,0.00044081104,0.00020579108],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014639455,0.000053650187,0.9980825,0.0000033352705,0.000012477796,0.0002463972,0.00011075615,0.000016474225,0.0005398433,0.00000567695,0.000026645585,0.0007557142],"study_design_scores_gemma":[0.0000029108623,0.00010210783,0.99928087,0.0000016770092,0.000006483127,0.00035098396,0.0001209711,0.000054493816,0.000041141313,0.000009402115,0.000027613516,0.0000013660788],"about_ca_topic_score_codex":0.0028528096,"about_ca_topic_score_gemma":0.004411939,"teacher_disagreement_score":0.0028528096,"about_ca_system_score_codex":0.00015172572,"about_ca_system_score_gemma":0.00018315847,"threshold_uncertainty_score":0.005672395},"labels":[],"label_agreement":null},{"id":"W2534746602","doi":"10.1016/j.jalz.2016.06.1901","title":"P3‐239: Asymmetrically Low White Matter Integrity in Seniors with Mci and POOR GAIT","year":2016,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials; Parkwood Institute","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Corticospinal tract; Gait; Population; Tractography; Medicine; Neuroscience; Radiology","score_opus":0.03327758752587061,"score_gpt":0.3056207425326355,"score_spread":0.27234315500676487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534746602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99936455,0.000043856715,0.00003535876,0.000028034294,0.000005758084,0.000008910686,0.00012520619,0.0000050147187,0.00038335758],"genre_scores_gemma":[0.9995863,0.00002017434,0.000046975107,0.00002034937,0.000009950687,0.000006630477,0.000121015335,0.0000017662622,0.00018667676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998491,0.000013549561,0.000022544698,0.000037395057,0.000040578132,0.000036853733],"domain_scores_gemma":[0.9995647,0.000031445466,0.00016908035,0.000021322463,0.00006546664,0.0001480637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023031802,0.0007737292,0.0004986704,0.0013904382,0.00094615703,0.0005820586,0.00032384778,0.0007635534,0.0037507853],"category_scores_gemma":[0.001062065,0.00033130642,0.00035892613,0.0005983194,0.00046235273,0.00036820595,0.00054310536,0.00040888597,0.00096455315],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084756815,0.00025398796,0.977471,0.00004696589,0.000072498275,0.0075524705,0.0005322527,0.00007768011,0.0065996214,0.000045480938,0.00056784746,0.005932597],"study_design_scores_gemma":[0.000010896106,0.00028985526,0.99364674,0.0000056094923,0.000014530475,0.005395685,0.00016725025,0.00010301896,0.00019339133,0.00006452759,0.00010381437,0.0000047385465],"about_ca_topic_score_codex":0.0042566257,"about_ca_topic_score_gemma":0.0036244192,"teacher_disagreement_score":0.0042566257,"about_ca_system_score_codex":0.0002459133,"about_ca_system_score_gemma":0.00026333923,"threshold_uncertainty_score":0.012547553},"labels":[],"label_agreement":null},{"id":"W2537773907","doi":"10.1088/0031-9155/61/21/7765","title":"On the averaging of cardiac diffusion tensor MRI data: the effect of distance function selection","year":2016,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Biological and Environmental Research; National Institute of Biomedical Imaging and Bioengineering; Imperial College London; Office of Science; National Institutes of Health; National Institute for Health and Care Research; U.S. Department of Energy","keywords":"Diffusion MRI; Tensor (intrinsic definition); Euclidean distance; Context (archaeology); Mathematics; Voxel; Function (biology); Mathematical analysis; Computer science; Magnetic resonance imaging; Algorithm; Artificial intelligence; Geometry; Medicine; Radiology","score_opus":0.16060116566896776,"score_gpt":0.405546470237325,"score_spread":0.24494530456835722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2537773907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5411908,0.002907912,0.4518784,0.00040726198,0.00023325197,0.00022183516,0.00024471723,0.0009346859,0.0019812223],"genre_scores_gemma":[0.74412876,0.0012646368,0.25202656,0.00016581734,0.00013520355,0.0001317817,0.00072917,0.00052862597,0.00088954],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99433446,0.0032735614,0.00040653555,0.0008959742,0.0008854995,0.00020404399],"domain_scores_gemma":[0.9777369,0.016203957,0.0014837607,0.0020617037,0.0021027362,0.0004109412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01634761,0.0012880107,0.001240194,0.0015989398,0.00065700716,0.0013687427,0.0007983947,0.0010472004,0.00074500305],"category_scores_gemma":[0.035490915,0.00023577946,0.00091947615,0.0019012215,0.001021526,0.0016529056,0.0014029138,0.000935413,0.00034307622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003113581,0.0003341414,0.023837274,0.0010491585,0.0009673664,0.0006894416,0.00084481324,0.14814523,0.1301531,0.006939191,0.0018629236,0.68206376],"study_design_scores_gemma":[0.000115480194,0.0040183254,0.051073,0.00016936571,0.0007908764,0.0010905968,0.0003915772,0.8175407,0.11140706,0.008393127,0.0047527384,0.0002570785],"about_ca_topic_score_codex":0.0016193058,"about_ca_topic_score_gemma":0.0020219781,"teacher_disagreement_score":0.01634761,"about_ca_system_score_codex":0.0003409461,"about_ca_system_score_gemma":0.0009605615,"threshold_uncertainty_score":0.086455405},"labels":[],"label_agreement":null},{"id":"W2538167484","doi":"","title":"Loss of callosal fibre integrity in healthy elderly with age-related white matter changes Martin GriebeAlex ForsterMichele WessaChristina RossmanithHansjorg Bazner • Tamara SauerKathrin ZohselChristian BlahakAndrea V. KingJulia Linke • Michael G. HennericiAchim GassKristina Szabo","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Corpus callosum; Magnetic resonance imaging; Psychology; Fractional anisotropy; Cognition; Diffusion MRI; Atrophy; Cognitive impairment; Audiology; Medicine; Cardiology; Neuroscience; Internal medicine; Radiology","score_opus":0.05316479166702132,"score_gpt":0.30253032504803157,"score_spread":0.24936553338101025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2538167484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982337,0.0012049881,0.000118368174,0.000033708457,0.000010856921,0.000010856041,0.00008476439,0.000008325482,0.00029437305],"genre_scores_gemma":[0.99789315,0.0009316326,0.0002496152,0.00005236317,0.000027223023,0.000012815587,0.00021218878,0.0000058323017,0.0006150758],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998877,0.000012830994,0.000012939721,0.000035018773,0.000034539607,0.000016883534],"domain_scores_gemma":[0.99974257,0.000035188463,0.00010216133,0.000019345398,0.000060520273,0.000040210445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038551065,0.00047404566,0.0003795629,0.0012014855,0.00026970688,0.0004840763,0.00021174984,0.00039718868,0.0017753046],"category_scores_gemma":[0.0011249803,0.00026107978,0.00017889198,0.00038470794,0.0003428704,0.0003210843,0.0003993046,0.0002123643,0.00045948985],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0046266736,0.00047049279,0.87804,0.00032009208,0.00049405976,0.005199689,0.0016677801,0.00047325925,0.039666828,0.0001634102,0.0024738633,0.06640373],"study_design_scores_gemma":[0.000015429046,0.00023783604,0.9961739,0.000018678567,0.000049244805,0.0022346785,0.00013228394,0.00013549342,0.00052013923,0.00007670273,0.0003988158,0.0000067695373],"about_ca_topic_score_codex":0.0035570662,"about_ca_topic_score_gemma":0.002802651,"teacher_disagreement_score":0.0035570662,"about_ca_system_score_codex":0.00017291284,"about_ca_system_score_gemma":0.00013269707,"threshold_uncertainty_score":0.007072687},"labels":[],"label_agreement":null},{"id":"W2539797428","doi":"10.1212/wnl.0000000000003373","title":"Cerebrovascular reactivity and white matter integrity","year":2016,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Sunnybrook Health Science Centre","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Cerebral blood flow; Medicine; Leukoaraiosis; Bonferroni correction; Perfusion; Cardiology; Magnetic resonance imaging; Internal medicine; Nuclear medicine; Radiology; Mathematics","score_opus":0.03989864370391906,"score_gpt":0.3173514247816232,"score_spread":0.27745278107770416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2539797428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991831,0.00026292747,0.00014557684,0.000012825438,0.000002159227,0.000007535754,0.000059320286,0.000004351625,0.0003221842],"genre_scores_gemma":[0.9996209,0.000047439775,0.0001645652,0.000006533525,0.000004903428,0.0000056484955,0.000059943817,0.0000015198485,0.000088556415],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973446,0.00005949674,0.000023161216,0.00008057896,0.000061322055,0.000040983727],"domain_scores_gemma":[0.99843675,0.00023562115,0.0009450632,0.000070615926,0.00017268061,0.00013930644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007779574,0.00032612658,0.00026042096,0.00046885046,0.00030239654,0.00044946687,0.00016538227,0.00033788584,0.0014207204],"category_scores_gemma":[0.0028061487,0.00013573884,0.00018032642,0.00028215026,0.00027408256,0.00025091582,0.0002388141,0.00025782717,0.00016714723],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017696113,0.00021411073,0.9702721,0.000092745715,0.00033980826,0.0003855217,0.0003217191,0.0002115662,0.015683811,0.00005604471,0.00012735107,0.010525621],"study_design_scores_gemma":[0.0000072297535,0.0002800278,0.99802834,0.0000050909844,0.00004273827,0.0005428291,0.000046179102,0.0001059039,0.0008348302,0.000027501032,0.00007589846,0.0000034476375],"about_ca_topic_score_codex":0.0015410138,"about_ca_topic_score_gemma":0.0018130541,"teacher_disagreement_score":0.0015410138,"about_ca_system_score_codex":0.00019097571,"about_ca_system_score_gemma":0.00016855211,"threshold_uncertainty_score":0.004752755},"labels":[],"label_agreement":null},{"id":"W2541603500","doi":"10.1016/b978-0-12-801942-9.00003-3","title":"Imaging Approaches to Cerebral Cortex Pathology","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Centre; Western University","funders":"","keywords":"Positron emission tomography; Neurodegeneration; Disease; Magnetic resonance imaging; Neuroscience; Neuroimaging; Medicine; Drug development; Drug trial; Pathology; Clinical trial; Psychology; Drug; Radiology; Pharmacology","score_opus":0.1395140268724563,"score_gpt":0.3275713256474919,"score_spread":0.18805729877503563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2541603500","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009724472,0.18970715,0.06437446,0.0042552655,0.0062521636,0.00006231076,0.00027735526,0.0008773786,0.7332215],"genre_scores_gemma":[0.006067359,0.19129865,0.034515813,0.0020033708,0.0038916937,0.00010494909,0.00036556847,0.00041278935,0.7613397],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988544,0.000013980525,0.000006301661,0.000017683122,0.000067926885,0.000008663165],"domain_scores_gemma":[0.9998084,0.00009542347,0.000009174392,0.000017102418,0.000050633902,0.000019235184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026760576,0.001202681,0.0005491415,0.0020962728,0.00042478804,0.0018638036,0.0009563272,0.0013610966,0.05475943],"category_scores_gemma":[0.00059448107,0.00042354947,0.00039539818,0.0013424226,0.0010709107,0.0021599375,0.0011100892,0.002248124,0.030471625],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013290502,0.000027723356,0.000067916044,0.0007476921,0.000012638371,0.00040952468,0.00019099383,0.00085217133,0.00302112,0.09342522,0.24414651,0.65708524],"study_design_scores_gemma":[0.0000023165187,0.00000830486,0.00017640516,0.00038624043,0.0000072704665,0.0013583183,0.00004850027,0.00031732934,0.00064255606,0.05714401,0.9398986,0.000010249736],"about_ca_topic_score_codex":0.0012522271,"about_ca_topic_score_gemma":0.0042081825,"teacher_disagreement_score":0.05475943,"about_ca_system_score_codex":0.00076925446,"about_ca_system_score_gemma":0.0009929461,"threshold_uncertainty_score":0.18318856},"labels":[],"label_agreement":null},{"id":"W2542536236","doi":"10.1503/jpn.150341","title":"Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging","year":2017,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":154,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Yale University","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Superior longitudinal fasciculus; Major depressive disorder; Medicine; Internal medicine; Cardiology; Meta-analysis; Neuroscience; Audiology; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Magnetic resonance imaging","score_opus":0.05634473385502789,"score_gpt":0.37672600299123216,"score_spread":0.32038126913620424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2542536236","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009505589,0.9888719,0.0004056613,0.00021835629,0.00008729667,0.000092255024,0.00065609545,0.000016582728,0.00014627656],"genre_scores_gemma":[0.32761702,0.66670823,0.0024430454,0.0007577699,0.00026708294,0.0005748159,0.0014285692,0.000031228137,0.00017227777],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9936172,0.00272039,0.0018802601,0.001006244,0.0005765149,0.00019942269],"domain_scores_gemma":[0.98501325,0.0101316525,0.0028782184,0.00062905194,0.0011565777,0.00019120432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0093771005,0.0017655098,0.010755371,0.0050246385,0.00064339524,0.0021487654,0.0016253315,0.0015715506,0.0018434918],"category_scores_gemma":[0.023633456,0.0011889571,0.021482673,0.0064033386,0.0005667536,0.0010392289,0.001104747,0.0010202286,0.00016351396],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016233755,0.000027515349,0.021423955,0.31672406,0.63623196,0.000254788,0.00015353138,0.0006104006,0.00055766053,0.00016959713,0.001174347,0.021048656],"study_design_scores_gemma":[0.00037458603,0.00015317896,0.021603154,0.022349697,0.9528958,0.00021295245,0.000061133345,0.00021698426,0.00018650813,0.00022315119,0.0016933889,0.00002949763],"about_ca_topic_score_codex":0.007327393,"about_ca_topic_score_gemma":0.018019889,"teacher_disagreement_score":0.010755371,"about_ca_system_score_codex":0.0015101819,"about_ca_system_score_gemma":0.002693157,"threshold_uncertainty_score":0.04959148},"labels":[],"label_agreement":null},{"id":"W2543407163","doi":"10.1089/neu.2016.4591","title":"Microstructural Integrity of Hippocampal Subregions Is Impaired after Mild Traumatic Brain Injury","year":2016,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital du Sacré-Cœur de Montréal; Western University; McGill University; Douglas Mental Health University Institute; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Traumatic brain injury; Hippocampal formation; Neuroscience; Psychology; Structural integrity; Medicine; Psychiatry","score_opus":0.14861186423520872,"score_gpt":0.39846187009210043,"score_spread":0.2498500058568917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2543407163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995858,0.00011125127,0.000053211417,0.000011003251,0.0000014048517,0.0000031452562,0.000060497285,0.0000045524494,0.00016911296],"genre_scores_gemma":[0.999574,0.00007666739,0.00007647447,0.000011615717,0.0000043526347,0.0000030821561,0.000105475396,0.0000024299177,0.0001457993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998952,0.000010770407,0.000014236978,0.00002928295,0.000026951258,0.000023563238],"domain_scores_gemma":[0.9995931,0.000033381384,0.00024024812,0.000038630686,0.00003580661,0.000058989197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017480565,0.00025060933,0.00030444257,0.00074507407,0.0002621803,0.00032592705,0.00018332619,0.00027612763,0.0010675326],"category_scores_gemma":[0.0007472827,0.00020088346,0.00018731046,0.00027163743,0.0004120741,0.00023742329,0.0003536799,0.00023773387,0.0002357527],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017729404,0.00015495237,0.9028525,0.00006958196,0.00025632035,0.0016042833,0.0010780509,0.00020246272,0.07456742,0.000062250336,0.00027855515,0.017100845],"study_design_scores_gemma":[0.0000032129597,0.00010645728,0.9982462,0.0000029518717,0.00001124348,0.00064705964,0.00008114738,0.00003946161,0.0007900855,0.00002462751,0.000045583198,0.0000020003256],"about_ca_topic_score_codex":0.0029819785,"about_ca_topic_score_gemma":0.0045158444,"teacher_disagreement_score":0.0029819785,"about_ca_system_score_codex":0.00019777118,"about_ca_system_score_gemma":0.00013002103,"threshold_uncertainty_score":0.0059292912},"labels":[],"label_agreement":null},{"id":"W2544700523","doi":"10.1109/iembs.1996.652733","title":"Improved T/sub 2/ and diffusion maps from wavelet de-noised magnetic resonance imaging data","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital","funders":"","keywords":"Wavelet; Noise (video); Diffusion; Magnetic resonance imaging; Relaxation (psychology); Artificial intelligence; Image (mathematics); Base (topology); Computer science; Wavelet transform; Nuclear magnetic resonance; Diffusion MRI; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Physics; Mathematical analysis","score_opus":0.053766825350059805,"score_gpt":0.30204886396288044,"score_spread":0.24828203861282064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2544700523","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059185874,0.0006230817,0.93581474,0.0003798335,0.0002047589,0.00006232882,0.00047661384,0.0015231569,0.0017296184],"genre_scores_gemma":[0.06727858,0.0010300489,0.92891246,0.00005720123,0.00008361092,0.00003941989,0.0005224464,0.00033139033,0.0017448644],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977845,0.00003617505,0.000019821688,0.000042045114,0.00009701251,0.00002648411],"domain_scores_gemma":[0.9989899,0.00036265646,0.00011442424,0.00016976394,0.00031964405,0.000043560958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007368638,0.0010212098,0.0006590132,0.0012602018,0.00024515693,0.0011908074,0.0005613289,0.0007884808,0.0020900648],"category_scores_gemma":[0.0053546242,0.00039172327,0.0006181637,0.0014975829,0.00046165095,0.0014665639,0.0007224428,0.0011351261,0.0011121077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058035733,0.00010464874,0.0011969345,0.00052224664,0.000100503414,0.00093497016,0.00030708092,0.046964295,0.4855873,0.010781603,0.004046695,0.44887325],"study_design_scores_gemma":[0.00008125121,0.00027767898,0.008697461,0.0000936747,0.00021517216,0.003228458,0.0002066752,0.5697438,0.37087327,0.020460125,0.02595723,0.00016513522],"about_ca_topic_score_codex":0.0006365084,"about_ca_topic_score_gemma":0.0008041407,"teacher_disagreement_score":0.0020900648,"about_ca_system_score_codex":0.00021097658,"about_ca_system_score_gemma":0.0003257307,"threshold_uncertainty_score":0.0069919825},"labels":[],"label_agreement":null},{"id":"W254543832","doi":"10.1016/j.neuroimage.2015.05.034","title":"A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; Aix-Marseille Université","keywords":"White matter; Gray (unit); Grey matter; Segmentation; Spinal cord; Artificial intelligence; Cartography; Neuroscience; Pattern recognition (psychology); Computer science; Psychology; Medicine; Nuclear medicine; Magnetic resonance imaging; Radiology; Geography","score_opus":0.06169969129582981,"score_gpt":0.3493579809373288,"score_spread":0.287658289641499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W254543832","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07061592,0.00083340623,0.92429763,0.00027979404,0.00006359593,0.00018876573,0.0008736617,0.002017303,0.0008298773],"genre_scores_gemma":[0.23533145,0.0007064777,0.76066387,0.00006374875,0.00003775299,0.00017771665,0.00076420663,0.00073653006,0.0015182288],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974185,0.000051732484,0.000025265714,0.00007681494,0.00008605647,0.00001829423],"domain_scores_gemma":[0.9994336,0.000099735196,0.00010449588,0.00011817672,0.00020702678,0.00003693931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001087793,0.00050705165,0.00056368345,0.0013600327,0.0004575084,0.0011630883,0.0008202263,0.0010221851,0.0017794075],"category_scores_gemma":[0.0031760384,0.0005811235,0.00051856757,0.0013774413,0.00043878218,0.0007868561,0.00066040276,0.00048526682,0.000981422],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000638198,0.00013780089,0.0065239756,0.00055247184,0.00014686114,0.00045114578,0.0003750517,0.0347662,0.43883264,0.006743476,0.005113151,0.50571907],"study_design_scores_gemma":[0.00009118171,0.00044057035,0.045545295,0.000110438516,0.00029852815,0.0051485277,0.00027239372,0.68132323,0.2373717,0.013440319,0.0157915,0.00016626761],"about_ca_topic_score_codex":0.005903369,"about_ca_topic_score_gemma":0.009246794,"teacher_disagreement_score":0.005903369,"about_ca_system_score_codex":0.00047323617,"about_ca_system_score_gemma":0.0019268034,"threshold_uncertainty_score":0.011738002},"labels":[],"label_agreement":null},{"id":"W2550828940","doi":"10.1101/084137","title":"Tractography-based connectomes are dominated by false-positive connections","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sleep & Circadian Network; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; China Scholarship Council; Deutsche Forschungsgemeinschaft; Université de Sherbrooke","keywords":"Tractography; Human Connectome Project; Ground truth; Diffusion MRI; Connectome; White matter; Computer science; Human brain; Artificial intelligence; Connectomics; Pattern recognition (psychology); Neuroscience; Functional connectivity; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.024448664433080247,"score_gpt":0.280448739986918,"score_spread":0.25600007555383775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550828940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6094007,0.0069646463,0.3603966,0.0033255771,0.0012502918,0.00038277343,0.0038874208,0.0055845054,0.008807379],"genre_scores_gemma":[0.9622336,0.000567659,0.031264275,0.0005030538,0.000264837,0.000121660436,0.002475316,0.0011526672,0.0014168641],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9690109,0.014006704,0.002849427,0.006361907,0.006805198,0.0009658733],"domain_scores_gemma":[0.75892603,0.18227476,0.016232653,0.02624956,0.014620228,0.0016967874],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02723983,0.0013914017,0.0015519238,0.0040097316,0.0019268219,0.0042118724,0.0015536427,0.0026006496,0.0033279813],"category_scores_gemma":[0.19773185,0.00086815923,0.0011047734,0.0032003347,0.0036834525,0.0037071542,0.0025861103,0.0017156752,0.0019503383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060880915,0.00041399154,0.30249268,0.0049101473,0.0039867247,0.008113779,0.005498763,0.11121531,0.059850194,0.04153981,0.07369845,0.382192],"study_design_scores_gemma":[0.00035570754,0.00054539816,0.20306306,0.0013981741,0.0014543646,0.0176963,0.0013988976,0.42068636,0.07695621,0.23366004,0.04243181,0.0003536397],"about_ca_topic_score_codex":0.001284214,"about_ca_topic_score_gemma":0.0018391465,"teacher_disagreement_score":0.9727602,"about_ca_system_score_codex":0.0013095009,"about_ca_system_score_gemma":0.0012067708,"threshold_uncertainty_score":0.14405972},"labels":[],"label_agreement":null},{"id":"W2551579479","doi":"10.1016/j.jpeds.2016.10.034","title":"Cerebellar Microstructural Organization is Altered by Complications of Premature Birth: A Case-Control Study","year":2016,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canadian Institutes of Health Research","keywords":"Splenium; Fractional anisotropy; Medicine; Corpus callosum; Diffusion MRI; Cerebellum; Cerebellar vermis; Anatomy; Cardiology; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.023529074554977183,"score_gpt":0.3055935792693921,"score_spread":0.28206450471441497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551579479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994843,0.00016472579,0.00012261675,0.00001099411,0.000005330208,0.000017801958,0.00006127503,0.0000038141004,0.00012911571],"genre_scores_gemma":[0.9994198,0.0001092274,0.00013748142,0.00001460676,0.000012088948,0.0000200988,0.000118395066,0.000006141338,0.00016212778],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99819,0.00041691953,0.0002447363,0.00069498125,0.00024650482,0.00020674079],"domain_scores_gemma":[0.9967332,0.0008580236,0.0009921945,0.00064675976,0.0003553912,0.00041456067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014287859,0.0013466014,0.0014419911,0.0023315994,0.0022871003,0.0012916956,0.001295235,0.0016473368,0.0026405049],"category_scores_gemma":[0.0051776688,0.0015429623,0.0013243203,0.0018787296,0.0017918429,0.000946296,0.0010043221,0.0010749733,0.0003675829],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018337944,0.0012708848,0.9818494,0.000060721624,0.0005894554,0.008139824,0.0014135264,0.000053015003,0.001960175,0.00012515158,0.00016371123,0.0025402622],"study_design_scores_gemma":[0.00011069137,0.001345577,0.9876703,0.000013035163,0.00032276232,0.009155579,0.0006941712,0.0001801992,0.00019686704,0.000074612784,0.00020889423,0.000027285701],"about_ca_topic_score_codex":0.008035415,"about_ca_topic_score_gemma":0.005849958,"teacher_disagreement_score":0.008035415,"about_ca_system_score_codex":0.000713145,"about_ca_system_score_gemma":0.000533716,"threshold_uncertainty_score":0.015977323},"labels":[],"label_agreement":null},{"id":"W2551844768","doi":"10.1007/s00429-016-1336-4","title":"Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Thalamus; Segmentation; Voxel; Neuroscience; Anatomy; Diffusion MRI; Cluster analysis; Robustness (evolution); Magnetic resonance imaging; Pattern recognition (psychology); Computer science; Artificial intelligence; Biology; Medicine","score_opus":0.03718634432736501,"score_gpt":0.2825612260279025,"score_spread":0.2453748817005375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551844768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04849865,0.00060763117,0.9480351,0.000104,0.00002795739,0.00013579715,0.00029506555,0.0014260567,0.0008696373],"genre_scores_gemma":[0.34141096,0.000562974,0.6537322,0.00008074824,0.00004610756,0.00023647946,0.001062676,0.00065669295,0.0022112739],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996344,0.00006016157,0.000023448429,0.00012275488,0.00011730467,0.000041983443],"domain_scores_gemma":[0.99973696,0.00006715078,0.000048005466,0.00003761476,0.00008881359,0.000021469803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056411687,0.00089908525,0.000844869,0.0017160501,0.0004013754,0.0010276082,0.00090964994,0.00081742596,0.0014025391],"category_scores_gemma":[0.0013753788,0.00045943685,0.0010204425,0.0008125559,0.0004408535,0.00059568003,0.00073799095,0.00054619496,0.00070865767],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053716364,0.0000842069,0.004551023,0.00040562882,0.0003590808,0.00068611326,0.00056596217,0.10111845,0.45315453,0.0053251977,0.0031021002,0.43011057],"study_design_scores_gemma":[0.00008792527,0.00016029012,0.011844696,0.000052992636,0.00021986297,0.0011715144,0.00016896203,0.8834016,0.093271896,0.0051071797,0.004402639,0.00011056691],"about_ca_topic_score_codex":0.008036243,"about_ca_topic_score_gemma":0.011171413,"teacher_disagreement_score":0.008036243,"about_ca_system_score_codex":0.00076928345,"about_ca_system_score_gemma":0.0011037703,"threshold_uncertainty_score":0.015978932},"labels":[],"label_agreement":null},{"id":"W2553481210","doi":"10.1007/s10237-020-01346-z","title":"La metafisica di trascendenza come saturazione dell'orizzonte fenomenologico","year":2014,"lang":"en","type":"article","venue":"Biomechanics and Modeling in Mechanobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Humanities; Philosophy","score_opus":0.11141502329864984,"score_gpt":0.34253917770151515,"score_spread":0.23112415440286532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553481210","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22837359,0.0405253,0.6914008,0.003065719,0.0013319048,0.00015561948,0.00052684837,0.0016537566,0.03296636],"genre_scores_gemma":[0.8246728,0.01702144,0.13095665,0.00096796616,0.00028713717,0.00026626955,0.0002338435,0.00036930514,0.025224637],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995906,0.000042853815,0.000016016753,0.00014902548,0.00014191064,0.000059705002],"domain_scores_gemma":[0.99949884,0.00022151152,0.0000636215,0.00010209435,0.00008597961,0.000027876065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086985755,0.0004945592,0.0006285964,0.00064193964,0.00047830385,0.00095918647,0.00079193444,0.001088319,0.0048496146],"category_scores_gemma":[0.0012968897,0.0004408863,0.00046192258,0.00058148004,0.0009464546,0.0014080663,0.0009813228,0.0010267034,0.0012368584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016579266,0.000049540533,0.0014205504,0.0009366673,0.00006358668,0.00039924853,0.00045446798,0.0109571135,0.87194645,0.022261523,0.002509191,0.088835746],"study_design_scores_gemma":[0.00005313792,0.00031001933,0.003331735,0.00031980505,0.00016229822,0.0012589734,0.00026910746,0.076601595,0.79893047,0.016836574,0.101804666,0.00012167312],"about_ca_topic_score_codex":0.001773286,"about_ca_topic_score_gemma":0.0022565757,"teacher_disagreement_score":0.0048496146,"about_ca_system_score_codex":0.00087604346,"about_ca_system_score_gemma":0.00061432936,"threshold_uncertainty_score":0.01622355},"labels":[],"label_agreement":null},{"id":"W2554475177","doi":"10.1371/journal.pone.0165637","title":"A Novel Approach for Studying the Physiology and Pathophysiology of Myelinated and Non-Myelinated Axons in the CNS White Matter","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"Ontario Brain Institute","keywords":"White matter; Connectomics; Corpus callosum; Neuroscience; Axon; Electrophysiology; Optic nerve; Population; Anatomy; Biology; Central nervous system; Chemistry; Medicine; Magnetic resonance imaging; Functional connectivity; Connectome","score_opus":0.10019311582913289,"score_gpt":0.30288387083637935,"score_spread":0.20269075500724648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2554475177","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47308478,0.028001793,0.48054457,0.0017175537,0.00091014645,0.0005995357,0.00178308,0.0014812748,0.011877381],"genre_scores_gemma":[0.66277164,0.022236427,0.29480112,0.0011220679,0.00044162208,0.0011483955,0.0012920934,0.00023145732,0.015955102],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998318,0.000019688921,0.000011072062,0.00007961248,0.000039896062,0.000017822776],"domain_scores_gemma":[0.9998596,0.000018412347,0.00003336116,0.000025995281,0.000023547394,0.000039019593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030817435,0.0005876542,0.00041193032,0.0006924483,0.00041558727,0.000530534,0.0005644129,0.00077935454,0.0016178316],"category_scores_gemma":[0.00017743086,0.0002581624,0.00036033697,0.00026528898,0.00068751327,0.00091122393,0.0006555242,0.001587503,0.00043934907],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026671672,0.000012216971,0.00011768027,0.000073494746,0.000008149783,0.000060382634,0.000019511104,0.00002886936,0.9951885,0.00079267623,0.00007899029,0.003592845],"study_design_scores_gemma":[0.00003712779,0.001455878,0.018044231,0.00014855096,0.00014615433,0.0032347844,0.00018538277,0.0023385773,0.9397988,0.0035347806,0.031025227,0.000050497016],"about_ca_topic_score_codex":0.00057536666,"about_ca_topic_score_gemma":0.001400639,"teacher_disagreement_score":0.0016178316,"about_ca_system_score_codex":0.0003098291,"about_ca_system_score_gemma":0.00040832406,"threshold_uncertainty_score":0.0054121614},"labels":[],"label_agreement":null},{"id":"W2555769692","doi":"10.15353/vsnl.v1i1.63","title":"Superpixel-based Prostate Cancer Detection from Diffusion Magnetic Resonance Imaging","year":2015,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Magnetic resonance imaging; Prostate cancer; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion MRI; Cancer; Cancer detection; Prostate; Computer science; Computation; Medicine; Artificial intelligence; Radiology; Internal medicine; Algorithm","score_opus":0.028822922260031043,"score_gpt":0.33677633269411783,"score_spread":0.3079534104340868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555769692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013834079,0.0017121511,0.9817259,0.00018298821,0.000049750295,0.00007507301,0.00020736942,0.0012665683,0.00094610924],"genre_scores_gemma":[0.17689003,0.0021991923,0.8167946,0.0003002649,0.00016022038,0.00013296006,0.0007395827,0.00030455043,0.002478542],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994722,0.0000852866,0.00001887461,0.00011378918,0.00026181212,0.00004814178],"domain_scores_gemma":[0.9995484,0.0001758466,0.000064191336,0.00007417365,0.00010686405,0.000030472811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005301183,0.0011205518,0.0010378392,0.0019952937,0.0003064376,0.00084803393,0.0012878096,0.0010673623,0.001842741],"category_scores_gemma":[0.001505451,0.0006611894,0.0009420315,0.001218744,0.00037739714,0.0010153939,0.0010670912,0.00082870154,0.00092673226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032117811,0.000114821734,0.002117976,0.0005664537,0.00016995595,0.00042213072,0.00012378741,0.07851309,0.18703495,0.004952552,0.005184353,0.7204788],"study_design_scores_gemma":[0.00002142307,0.000097300814,0.003000976,0.000030947962,0.000078418096,0.0010593211,0.000023592542,0.91418666,0.07095008,0.0053716507,0.0051200045,0.000059450722],"about_ca_topic_score_codex":0.0024515921,"about_ca_topic_score_gemma":0.0051792213,"teacher_disagreement_score":0.0024515921,"about_ca_system_score_codex":0.00044505467,"about_ca_system_score_gemma":0.00054491893,"threshold_uncertainty_score":0.006164551},"labels":[],"label_agreement":null},{"id":"W2556879144","doi":"10.1016/j.neuroimage.2016.11.003","title":"CERES: A new cerebellum lobule segmentation method","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":197,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Centre for Addiction and Mental Health; Western University; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council; Centre National de la Recherche Scientifique; Ministerio de Economía y Competitividad; Agence Nationale de la Recherche","keywords":"Cerebellum; Segmentation; Computer science; Neuroscience; Artificial intelligence; Anatomy; Medicine; Psychology","score_opus":0.0907674934808323,"score_gpt":0.39978312090164203,"score_spread":0.30901562742080974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2556879144","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055455435,0.00085705845,0.9778432,0.00018802653,0.00022812611,0.00012685209,0.0008322485,0.012623422,0.0017554824],"genre_scores_gemma":[0.037169218,0.00072168495,0.9470611,0.0002553794,0.00019389443,0.0001778088,0.0027638825,0.0037171133,0.007939905],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992467,0.00008522118,0.00004993496,0.00025241778,0.00029039424,0.00007536582],"domain_scores_gemma":[0.9994172,0.00014836297,0.0000575906,0.00013193299,0.00018092064,0.000063988795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001138166,0.002303689,0.001814,0.003616283,0.0008605365,0.0023881155,0.0026557206,0.0028401874,0.008059864],"category_scores_gemma":[0.0019548594,0.0013724994,0.0024035424,0.0020889232,0.0005584182,0.0018245296,0.0022055872,0.0019857055,0.0050625075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064228364,0.00012301962,0.0013146782,0.00040315161,0.000479091,0.00033658743,0.00010629468,0.023152724,0.050612777,0.0055715763,0.02963029,0.8876276],"study_design_scores_gemma":[0.00031489722,0.00019247565,0.0032189325,0.000116136194,0.00039727153,0.0018046005,0.00008094255,0.8653868,0.05899255,0.011801121,0.057527002,0.00016711494],"about_ca_topic_score_codex":0.008402944,"about_ca_topic_score_gemma":0.019108618,"teacher_disagreement_score":0.008402944,"about_ca_system_score_codex":0.00077942107,"about_ca_system_score_gemma":0.0024742656,"threshold_uncertainty_score":0.026962936},"labels":[],"label_agreement":null},{"id":"W2556951263","doi":"10.3233/bpl-160033","title":"Magnetic Resonance of Myelin Water: An <i>in vivo</i> Marker for Myelin","year":2016,"lang":"en","type":"review","venue":"Brain Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":298,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Multiple Sclerosis Society of Canada","keywords":"Myelin; Magnetic resonance imaging; Multiple sclerosis; Relaxometry; White matter; Diffusion MRI; Neuroscience; Magnetization transfer; Medicine; Pathology; Chemistry; Biology; Central nervous system; Radiology; Spin echo; Immunology","score_opus":0.07084405338574562,"score_gpt":0.3746824336317408,"score_spread":0.3038383802459952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2556951263","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22398302,0.29838476,0.3976055,0.0071583176,0.003434916,0.00028244732,0.004034186,0.0041814945,0.060935263],"genre_scores_gemma":[0.651936,0.15522303,0.14603849,0.0045296843,0.002195001,0.0005621006,0.0028387497,0.001100358,0.035576623],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957985,0.00011856929,0.000024518235,0.00010197652,0.00012465657,0.00005046509],"domain_scores_gemma":[0.99953187,0.00011173905,0.0001862409,0.000030290526,0.00010644577,0.000033440803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008037423,0.0007758589,0.0006577483,0.0014098268,0.0003645515,0.0011571997,0.00059235527,0.0013598074,0.0027288715],"category_scores_gemma":[0.0009061633,0.0002683751,0.00039187475,0.0012895279,0.0008680104,0.0015938052,0.00072114106,0.00092136295,0.0020896152],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033630797,0.000053050164,0.0030496616,0.002509185,0.00021023808,0.0008724288,0.00025901588,0.0006808181,0.86428314,0.004349097,0.009183063,0.114213906],"study_design_scores_gemma":[0.00003020034,0.0007975255,0.017920878,0.0007563363,0.00041357917,0.009511477,0.0005524008,0.0039874073,0.77868664,0.007075553,0.18008241,0.00018568053],"about_ca_topic_score_codex":0.00076954195,"about_ca_topic_score_gemma":0.0008355133,"teacher_disagreement_score":0.0027288715,"about_ca_system_score_codex":0.00040727467,"about_ca_system_score_gemma":0.00040318933,"threshold_uncertainty_score":0.009128988},"labels":[],"label_agreement":null},{"id":"W2558110624","doi":"10.1371/journal.pone.0167274","title":"Assessing White Matter Microstructure in Brain Regions with Different Myelin Architecture Using MRI","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft","keywords":"White matter; Myelin; Diffusion MRI; Fractional anisotropy; Magnetization transfer; Nuclear magnetic resonance; Relaxometry; Magnetic resonance imaging; Materials science; Biomedical engineering; Nuclear medicine; Neuroscience; Biology; Medicine; Physics; Radiology; Central nervous system; Spin echo","score_opus":0.08225228573317421,"score_gpt":0.3212132745469855,"score_spread":0.23896098881381128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558110624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99789256,0.00035245356,0.0014818872,0.000010733132,0.0000018815607,0.000014549375,0.00009043907,0.000013004144,0.00014245593],"genre_scores_gemma":[0.99635017,0.00020451886,0.003188753,0.0000072624907,0.0000043712566,0.000011697934,0.00006307484,0.0000059401536,0.00016419703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998723,0.000025594247,0.000012022237,0.0000529711,0.000021037959,0.00001597571],"domain_scores_gemma":[0.9997136,0.00006701665,0.00013059516,0.000018218361,0.000041994943,0.000028553657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047622545,0.00038110896,0.00016686856,0.0008095842,0.00014081366,0.00028279552,0.00013116868,0.00033940873,0.00094880385],"category_scores_gemma":[0.0008170615,0.00013149968,0.00012632669,0.0003004055,0.00031307814,0.00034898982,0.00021589032,0.00012626081,0.00017608456],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011599656,0.00024219594,0.60083014,0.00040163528,0.00018418812,0.0013141839,0.001085569,0.00082984904,0.34828228,0.00024668084,0.00012745764,0.0452958],"study_design_scores_gemma":[0.000019436196,0.0013534417,0.9534108,0.0000283711,0.00011457546,0.0032101672,0.00044189775,0.0012363321,0.03953512,0.00015294358,0.00048395217,0.000012881198],"about_ca_topic_score_codex":0.00075916864,"about_ca_topic_score_gemma":0.0012545497,"teacher_disagreement_score":0.00094880385,"about_ca_system_score_codex":0.00010824582,"about_ca_system_score_gemma":0.00014950402,"threshold_uncertainty_score":0.0031741261},"labels":[],"label_agreement":null},{"id":"W2559255072","doi":"10.1089/brain.2016.0451","title":"Using CForest to Analyze Diffusion Tensor Imaging Data: A Study of White Matter Integrity in Healthy Aging","year":2016,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton; Saint Mary's University; Dalhousie University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Cognitive decline; Psychology; Tractography; Neuroimaging; Neuroscience; Developmental psychology; Internal medicine; Medicine; Magnetic resonance imaging; Disease; Dementia","score_opus":0.1458535999089755,"score_gpt":0.4289856862583005,"score_spread":0.283132086349325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559255072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57848513,0.000681117,0.41873512,0.0002046851,0.000019964185,0.00011494853,0.00064980466,0.00033560622,0.00077365385],"genre_scores_gemma":[0.8127082,0.00043324244,0.1856381,0.00004339261,0.00003238129,0.00008915949,0.00069541356,0.000055540397,0.00030466513],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999148,0.00041471148,0.000056656692,0.00022688888,0.00011264779,0.00004095367],"domain_scores_gemma":[0.9963607,0.0019416854,0.000893929,0.00041752277,0.00028234214,0.00010378528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042712283,0.00069108495,0.00044149088,0.0015320326,0.0004507704,0.0006283862,0.00024452826,0.0004180247,0.00038640216],"category_scores_gemma":[0.0096238665,0.00015442139,0.00055383367,0.0010310678,0.00069643237,0.00095855433,0.00042928435,0.00046348368,0.00013521912],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071562297,0.00043891394,0.38326555,0.00055555505,0.0013198988,0.0007087871,0.0019002219,0.055128455,0.09988251,0.0088468725,0.0015743226,0.4456633],"study_design_scores_gemma":[0.000049195074,0.0015805636,0.6069142,0.00016084376,0.00028430263,0.0027143979,0.0005279948,0.3303059,0.029345488,0.023955941,0.003970171,0.00019091072],"about_ca_topic_score_codex":0.0056773894,"about_ca_topic_score_gemma":0.0150311375,"teacher_disagreement_score":0.0056773894,"about_ca_system_score_codex":0.0002671599,"about_ca_system_score_gemma":0.0009780192,"threshold_uncertainty_score":0.02258867},"labels":[],"label_agreement":null},{"id":"W2559740506","doi":"10.1007/s11682-016-9657-8","title":"Age and gender interactions in white matter of schizophrenia and obsessive compulsive disorder compared to non-psychiatric controls: commonalities across disorders","year":2016,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Temerty Family Foundation; Canadian HIV Trials Network, Canadian Institutes of Health Research; BrainsWay; Campbell Institute; Eli Lilly and Company","keywords":"White matter; Fractional anisotropy; Psychology; Schizophrenia (object-oriented programming); Corpus callosum; Diffusion MRI; Comorbidity; Psychiatry; Clinical psychology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.03721346790613547,"score_gpt":0.36441410040761807,"score_spread":0.32720063250148257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559740506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994973,0.0001398828,0.000025042295,0.000018458622,0.00000404284,9.079225e-7,0.00006754292,0.0000011837736,0.0002457376],"genre_scores_gemma":[0.99952364,0.000074045936,0.000026089572,0.000014335404,0.0000065280437,0.0000015248646,0.00007907507,0.0000028934885,0.000271766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998559,0.000024915687,0.000018911789,0.00004420867,0.000022592418,0.000033371856],"domain_scores_gemma":[0.9992843,0.00018371463,0.0003190937,0.000031157186,0.00004299614,0.00013865103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021041006,0.00021817049,0.000255302,0.0007563738,0.00025035546,0.00040562017,0.00016785157,0.00033044902,0.003069564],"category_scores_gemma":[0.0009941042,0.0001542286,0.00022266165,0.00036801572,0.00020300767,0.00041029003,0.0003504229,0.00024070735,0.00024730407],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019137652,0.00011856282,0.96983624,0.00002987757,0.0001423522,0.00096590066,0.00071982254,0.0000500897,0.021433445,0.000109796885,0.00009443282,0.0045857974],"study_design_scores_gemma":[0.000002937621,0.00006882618,0.9992029,0.0000017574272,0.000013038517,0.00033450607,0.0001595595,0.000024313087,0.00012769972,0.000031518946,0.000031389445,0.0000015098477],"about_ca_topic_score_codex":0.0026379293,"about_ca_topic_score_gemma":0.0044195866,"teacher_disagreement_score":0.003069564,"about_ca_system_score_codex":0.00018316876,"about_ca_system_score_gemma":0.00015762252,"threshold_uncertainty_score":0.010268688},"labels":[],"label_agreement":null},{"id":"W2559779481","doi":"10.1016/j.biopsych.2016.12.005","title":"Gray Matter Neuritic Microstructure Deficits in Schizophrenia and Bipolar Disorder","year":2016,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Bipolar disorder; Magnetic resonance imaging; Schizophrenia (object-oriented programming); Parahippocampal gyrus; Psychology; Neuroscience; Functional magnetic resonance imaging; White matter; Neuroimaging; Neurocognitive; Medicine; Cardiology; Psychiatry; Radiology; Cognition; Temporal lobe","score_opus":0.02652682464387103,"score_gpt":0.30247878792194444,"score_spread":0.2759519632780734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559779481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994223,0.0001420785,0.000045736415,0.00003405688,0.0000028525837,0.0000030859555,0.00005378526,0.0000015200915,0.00029466147],"genre_scores_gemma":[0.99960047,0.00010673619,0.00007347388,0.0000125522065,0.0000025634904,0.0000024629555,0.00006478812,0.0000012904552,0.0001356303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993587,0.000011915203,0.000009717581,0.000011754281,0.00001549773,0.000015144183],"domain_scores_gemma":[0.9997271,0.00003091774,0.000128945,0.000015852045,0.00002267554,0.00007456041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003050379,0.0002965828,0.00018943092,0.0007549141,0.0004549198,0.00041226074,0.00018336081,0.00029907838,0.0017593146],"category_scores_gemma":[0.0009004673,0.00025607354,0.00013654448,0.0003396452,0.00047427663,0.00035820503,0.0005875489,0.00026499448,0.00010979539],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006113255,0.00028936405,0.8747699,0.00017478193,0.0004358114,0.0024529959,0.0015651216,0.0007327026,0.09176346,0.0007284793,0.00036208023,0.020612072],"study_design_scores_gemma":[0.0000141528935,0.000078223944,0.99810386,0.000008512432,0.00002349112,0.00044270206,0.00035648234,0.0001582384,0.0004406854,0.00032696174,0.000043452277,0.0000033097078],"about_ca_topic_score_codex":0.0150079215,"about_ca_topic_score_gemma":0.025961453,"teacher_disagreement_score":0.0150079215,"about_ca_system_score_codex":0.000537638,"about_ca_system_score_gemma":0.00040244265,"threshold_uncertainty_score":0.029841125},"labels":[],"label_agreement":null},{"id":"W2561965437","doi":"10.1503/jpn.150291","title":"Shape analysis of the cingulum, uncinate and arcuate fasciculi in patients with bipolar disorder","year":2016,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Agence Nationale de la Recherche","keywords":"Cingulum (brain); Tractography; Uncinate fasciculus; White matter; Inferior longitudinal fasciculus; Arcuate fasciculus; Temporal lobe; Diffusion MRI; Superior longitudinal fasciculus; Anatomy; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Fractional anisotropy; Radiology","score_opus":0.016301129963002592,"score_gpt":0.28771793684706753,"score_spread":0.27141680688406494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561965437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991253,0.00015247223,0.00032109628,0.00002095275,0.0000033150925,0.0000062397276,0.00015112215,0.000008043089,0.00021137604],"genre_scores_gemma":[0.9989911,0.00008430609,0.0005799102,0.000009537361,0.0000043381892,0.0000070470846,0.0002420099,0.0000060371144,0.000075735494],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998454,0.000030258303,0.00002423362,0.000042285916,0.00003428103,0.000023553393],"domain_scores_gemma":[0.99946886,0.000082662016,0.0002587477,0.000049549344,0.00008912573,0.00005103282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003967898,0.00032866508,0.00023471001,0.0016997027,0.00032850693,0.0004269142,0.00017152952,0.00032929424,0.000986394],"category_scores_gemma":[0.0015543781,0.00016912798,0.0002642119,0.0007077351,0.00028084457,0.0002268906,0.00028267098,0.00015178157,0.00015052491],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009992201,0.000033643722,0.95412534,0.00007384371,0.00015291217,0.0010091164,0.0006631847,0.00069481204,0.013567852,0.0001335703,0.0005248114,0.028021632],"study_design_scores_gemma":[0.0000119796405,0.000050947932,0.9963163,0.0000136205645,0.000036460813,0.0013251987,0.00020946503,0.0011377805,0.00055925985,0.00014767378,0.00018424168,0.000007007095],"about_ca_topic_score_codex":0.0042593735,"about_ca_topic_score_gemma":0.0088538425,"teacher_disagreement_score":0.0042593735,"about_ca_system_score_codex":0.0002719121,"about_ca_system_score_gemma":0.00014459561,"threshold_uncertainty_score":0.008469164},"labels":[],"label_agreement":null},{"id":"W2565838431","doi":"10.1016/j.neuroimage.2016.12.017","title":"Multivariate dynamical modelling of structural change during development","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Mental Health; Medical Research Council; Deutscher Akademischer Austauschdienst; Jacobs Foundation; Wellcome Trust; McGill University","keywords":"Multivariate statistics; Bayesian probability; Bayesian inference; Neuroscience; Neuroimaging; Computer science; Psychology; Artificial intelligence; Machine learning","score_opus":0.14419327794513073,"score_gpt":0.3499756302418245,"score_spread":0.20578235229669375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565838431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037917748,0.000721815,0.957043,0.00060625834,0.000056366694,0.000036482827,0.0013538956,0.0002872617,0.0019772244],"genre_scores_gemma":[0.8508907,0.0022306093,0.12998708,0.0002879209,0.00021588686,0.0004553379,0.0024187004,0.00033511815,0.013178743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944764,0.00020024677,0.000023096747,0.000179027,0.00007506125,0.00007491036],"domain_scores_gemma":[0.99856573,0.0007966085,0.00030630882,0.0001098575,0.00012524136,0.00009633261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013178694,0.00089198735,0.00085318956,0.0010984689,0.00029127146,0.0012139544,0.0013649442,0.001070315,0.0034135235],"category_scores_gemma":[0.004391867,0.00071763434,0.0015028786,0.0008385486,0.0010740791,0.0010625254,0.0013951862,0.001565452,0.0004546606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050733204,0.000020833895,0.0050723483,0.000064005384,0.00010620013,0.00016756932,0.00012232282,0.9112222,0.0022842968,0.068896905,0.001077375,0.010915192],"study_design_scores_gemma":[0.000006252985,0.000014500228,0.0015909742,0.000007555815,0.000012996098,0.000035842197,0.000011669431,0.9761653,0.00014131065,0.020748245,0.0012514567,0.000013924984],"about_ca_topic_score_codex":0.0145062655,"about_ca_topic_score_gemma":0.009816578,"teacher_disagreement_score":0.0145062655,"about_ca_system_score_codex":0.0009377594,"about_ca_system_score_gemma":0.0009013553,"threshold_uncertainty_score":0.0288437},"labels":[],"label_agreement":null},{"id":"W2566061819","doi":"10.1016/j.nicl.2016.12.012","title":"Longitudinal changes in microstructural white matter metrics in Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; University of Manitoba; University of Calgary; University of Victoria","funders":"National Institute on Aging; National Institutes of Health; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"White matter; Alzheimer's disease; Neuroscience; Disease; Psychology; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.16508872100979347,"score_gpt":0.433411103769093,"score_spread":0.26832238275929954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566061819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99699855,0.00083423767,0.00055565056,0.00007657136,0.000007134184,0.000014154745,0.00095696,0.000020521276,0.0005363122],"genre_scores_gemma":[0.9980058,0.0002471452,0.0007153266,0.000018436438,0.000007878812,0.000016180014,0.0007988508,0.000004537916,0.00018590158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998449,0.000026317502,0.00001792698,0.00005030393,0.000034769033,0.000025726522],"domain_scores_gemma":[0.99861276,0.00014516072,0.0006266468,0.00012499085,0.00036307122,0.0001273024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012403121,0.00023602348,0.00018789146,0.0010044364,0.00036508378,0.00051094295,0.00023009062,0.0003170747,0.00085087534],"category_scores_gemma":[0.0022405388,0.00013573768,0.000220821,0.0007603829,0.00018131433,0.0005428784,0.00035571711,0.00039354496,0.00018890765],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032677,0.000061651444,0.9815414,0.000046236848,0.00024290738,0.000086414104,0.00028632596,0.00037628846,0.0044201445,0.00009362252,0.0003980221,0.012120128],"study_design_scores_gemma":[0.0000022641573,0.0000863274,0.99869746,0.000008092184,0.00002970979,0.0001316037,0.000054269913,0.00024130395,0.00036841084,0.00012538745,0.00025171644,0.0000034672194],"about_ca_topic_score_codex":0.006368116,"about_ca_topic_score_gemma":0.010159832,"teacher_disagreement_score":0.006368116,"about_ca_system_score_codex":0.00036892007,"about_ca_system_score_gemma":0.00031592685,"threshold_uncertainty_score":0.012662113},"labels":[],"label_agreement":null},{"id":"W2568307873","doi":"10.1016/j.jneumeth.2016.12.020","title":"Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; BioClinica; Biogen; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Roche; Merck; Alzheimer's Drug Discovery Foundation; Takeda Pharmaceutical Company; AbbVie; Fujirebio Europe; Alzheimer's Association","keywords":"Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; White matter; Diffusion MRI; Context (archaeology); Voxel; Dementia; Computer science; Artificial intelligence; Psychology; Neuroscience; Disease; Magnetic resonance imaging; Medicine; Pathology; Radiology","score_opus":0.25053591682464693,"score_gpt":0.5517588206324406,"score_spread":0.3012229038077937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2568307873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999169,0.00018561377,0.00016425441,0.000023842409,0.000004027722,0.000012678957,0.00025192197,0.0000060625857,0.00018265439],"genre_scores_gemma":[0.997971,0.00022863067,0.0005145056,0.000030041143,0.000021116717,0.000020187392,0.0008081444,0.0000116962765,0.00039455981],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998498,0.000029819137,0.000015597217,0.00005783326,0.000021489186,0.00002551157],"domain_scores_gemma":[0.999337,0.00008984606,0.00016355295,0.00014338612,0.00014992655,0.00011612493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009470689,0.00060043077,0.00044618902,0.0011000554,0.0006629596,0.0007335526,0.0003764261,0.00049562193,0.0006935192],"category_scores_gemma":[0.002028473,0.00027041804,0.00033548236,0.00067365775,0.00054668955,0.0008122428,0.00035477694,0.00032032334,0.000236617],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041522854,0.0008274676,0.9583966,0.00008619537,0.0004652315,0.0013899338,0.0012264297,0.00031028865,0.011359465,0.00026243777,0.0010679654,0.020455549],"study_design_scores_gemma":[0.000045103927,0.0003013527,0.99567693,0.0000091482425,0.00015640847,0.001339323,0.00036034637,0.0006788019,0.00057742686,0.00030317856,0.0005369074,0.00001504443],"about_ca_topic_score_codex":0.009480302,"about_ca_topic_score_gemma":0.013706105,"teacher_disagreement_score":0.009480302,"about_ca_system_score_codex":0.0004935363,"about_ca_system_score_gemma":0.0006220793,"threshold_uncertainty_score":0.018850207},"labels":[],"label_agreement":null},{"id":"W2571211835","doi":"10.1016/b978-0-12-800756-3.00041-7","title":"Neuroimaging Findings in Adolescent Cannabis Use and Early Phase Psychosis","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Psychosis; Cannabis; Neuroimaging; Psychology; Psychiatry; Effects of cannabis; Neuroscience; Mechanism (biology); Clinical psychology; Cannabidiol","score_opus":0.08783188676811546,"score_gpt":0.3627047429250566,"score_spread":0.2748728561569411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2571211835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6082632,0.1504808,0.0031287926,0.010655206,0.0006545387,0.00016991534,0.0005346381,0.00016795161,0.22594482],"genre_scores_gemma":[0.8837903,0.08455411,0.0035210392,0.001239368,0.00080686173,0.000056802197,0.00023404142,0.000034286684,0.02576319],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99996376,0.000007644772,0.0000049266278,0.0000046356836,0.000009181263,0.000009878071],"domain_scores_gemma":[0.9998617,0.00008389092,0.000019929112,0.000004338353,0.000011027164,0.000019098821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000110651585,0.00031167277,0.00012336987,0.0008428689,0.00021161562,0.00039444363,0.0003887437,0.0008301779,0.0052785994],"category_scores_gemma":[0.0005872407,0.00020099804,0.00014147758,0.0003573532,0.0004265672,0.00049218495,0.00029299493,0.0006120553,0.0005892947],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021917332,0.00023738472,0.064386874,0.000857859,0.00007237263,0.62297446,0.0015548565,0.00090452726,0.026651615,0.010714665,0.01815165,0.25327456],"study_design_scores_gemma":[0.000023066643,0.00015622527,0.16101418,0.0009875606,0.000054330234,0.7816545,0.0013595868,0.0010147383,0.0043076705,0.007070011,0.042322643,0.000035498022],"about_ca_topic_score_codex":0.004209769,"about_ca_topic_score_gemma":0.008868337,"teacher_disagreement_score":0.0052785994,"about_ca_system_score_codex":0.0003430404,"about_ca_system_score_gemma":0.00042261803,"threshold_uncertainty_score":0.01765865},"labels":[],"label_agreement":null},{"id":"W2576872718","doi":"10.1016/j.nicl.2017.01.009","title":"Hemispheric asymmetry in myelin after stroke is related to motor impairment and function","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Health and Medical Research Council; Medical Research Council; Canadian Institutes of Health Research; Michael Smith Health Research BC; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Stroke (engine); Myelin; Physical medicine and rehabilitation; Magnetic resonance imaging; Motor impairment; Chronic stroke; Psychology; Neuroscience; Medicine; Cardiology; Rehabilitation; Radiology; Central nervous system","score_opus":0.06965723557771637,"score_gpt":0.42084157966511526,"score_spread":0.3511843440873989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576872718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99977154,0.00004370273,0.000038053007,0.00000510119,3.812765e-7,0.0000013833311,0.000020306124,0.0000017064193,0.00011786894],"genre_scores_gemma":[0.9998227,0.000024651754,0.000032587144,0.0000029981989,0.0000017319691,0.0000015889335,0.000037829774,7.443603e-7,0.000075059696],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998795,0.00002173145,0.000015026887,0.000026332118,0.00003259795,0.000024871026],"domain_scores_gemma":[0.999175,0.00016120289,0.00044918444,0.000042819785,0.000065531734,0.00010623438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021931405,0.00016349136,0.00024792782,0.00069936214,0.00015622006,0.00022000939,0.00009749427,0.00020025924,0.0013492891],"category_scores_gemma":[0.0015838855,0.00007578289,0.00010489748,0.0002943896,0.00022756481,0.00019251365,0.00029467125,0.00016711648,0.00019911991],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071952137,0.0000812887,0.97867936,0.000017351655,0.00007583692,0.00025869542,0.00019158701,0.00017957782,0.010545154,0.000030037467,0.000049001836,0.00917262],"study_design_scores_gemma":[0.0000010801577,0.000069745554,0.99940693,9.733484e-7,0.0000038453527,0.00019294332,0.00002791295,0.000086307205,0.00017293332,0.000023441686,0.000012985283,9.660382e-7],"about_ca_topic_score_codex":0.0012770212,"about_ca_topic_score_gemma":0.0015393831,"teacher_disagreement_score":0.0013492891,"about_ca_system_score_codex":0.0001309099,"about_ca_system_score_gemma":0.000110668785,"threshold_uncertainty_score":0.0045138597},"labels":[],"label_agreement":null},{"id":"W2577018854","doi":"10.1016/j.dadm.2016.12.011","title":"Peripheral inflammatory markers indicate microstructural damage within periventricular white matter hyperintensities in Alzheimer's disease: A preliminary report","year":2017,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia; McMaster University; Health Sciences Centre; Centre for Addiction and Mental Health; Sunnybrook Health Science Centre; Heart and Stroke Foundation; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Cognoptix; Canadian Institutes of Health Research; Alzheimer Society; Sunnybrook Research Institute; University of Toronto; Biogen; Heart and Stroke Foundation of Canada; Pfizer; Eli Lilly and Company","keywords":"Hyperintensity; White matter; Diffusion MRI; Pathology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Peripheral; Inflammation; Disease; Lesion; Dementia; Internal medicine; Radiology","score_opus":0.04145832636965725,"score_gpt":0.34864103449007655,"score_spread":0.3071827081204193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577018854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978877,0.0014904718,0.00021578844,0.000019497138,0.0000049700757,0.0000169894,0.00005419716,0.0000033234885,0.00030701532],"genre_scores_gemma":[0.99902034,0.00029415303,0.00038068043,0.0000116053425,0.00002176176,0.000011806495,0.000057594312,8.5423414e-7,0.00020110751],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998616,0.000039323906,0.00001698987,0.000035945508,0.000023721355,0.000022346334],"domain_scores_gemma":[0.9992699,0.00018717929,0.00024094403,0.00004956079,0.00017175326,0.00008059707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088343804,0.00048514307,0.00032392403,0.0006811098,0.0003077305,0.0005234106,0.0001934342,0.00032708532,0.0018008874],"category_scores_gemma":[0.0017542312,0.00022538433,0.0001980922,0.00040041865,0.0003924733,0.00039599132,0.000336663,0.0002593115,0.00021871117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0076663936,0.00030416547,0.9336584,0.00034321612,0.00028194574,0.0010486655,0.00079344976,0.00015216318,0.031686556,0.00008083437,0.00022722596,0.023756964],"study_design_scores_gemma":[0.00007349448,0.0012908424,0.9915623,0.000029873827,0.00021510798,0.0019010705,0.00035453253,0.000259193,0.0037969775,0.00012531197,0.0003799357,0.000011469672],"about_ca_topic_score_codex":0.0013289466,"about_ca_topic_score_gemma":0.0017472127,"teacher_disagreement_score":0.0018008874,"about_ca_system_score_codex":0.00014704048,"about_ca_system_score_gemma":0.00017835936,"threshold_uncertainty_score":0.006024599},"labels":[],"label_agreement":null},{"id":"W2580611812","doi":"10.1016/j.compbiomed.2017.01.016","title":"3D-SSF: A bio-inspired approach for dynamic multi-subject clustering of white matter tracts","year":2017,"lang":"en","type":"review","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Outlier; Computer science; Flocking (texture); Cluster analysis; Artificial intelligence; Pattern recognition (psychology); Population; Data mining","score_opus":0.20114477447282839,"score_gpt":0.47394949576067724,"score_spread":0.27280472128784883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580611812","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050947163,0.4825225,0.5032626,0.0009877143,0.00081304094,0.00014240506,0.0009308737,0.0017936524,0.004452555],"genre_scores_gemma":[0.050985828,0.5145985,0.4226986,0.00082044705,0.0009501718,0.0003450522,0.0022067665,0.00049327366,0.00690137],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996942,0.0000474844,0.000025011735,0.00006885129,0.00014616114,0.000018279772],"domain_scores_gemma":[0.99957556,0.00019468945,0.00004917612,0.000030479046,0.00013014968,0.00001999942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089525693,0.0012244992,0.0015242796,0.003365525,0.00032710057,0.0012929542,0.0014809516,0.0015078764,0.0019126593],"category_scores_gemma":[0.0015601522,0.00041446503,0.0013495989,0.0035181474,0.00050645316,0.00094695657,0.00078798993,0.00097624573,0.0015179696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003854385,0.00003499571,0.00054697,0.0027650525,0.00027868987,0.00012991378,0.000061742394,0.009706729,0.005866551,0.004735139,0.008333582,0.9675021],"study_design_scores_gemma":[0.00010150719,0.00037301247,0.01357986,0.004178645,0.0014444728,0.008092041,0.00033429096,0.2553507,0.03530241,0.06921069,0.61153805,0.0004943059],"about_ca_topic_score_codex":0.0038738525,"about_ca_topic_score_gemma":0.0064121946,"teacher_disagreement_score":0.0038738525,"about_ca_system_score_codex":0.000596629,"about_ca_system_score_gemma":0.0013221438,"threshold_uncertainty_score":0.007702589},"labels":[],"label_agreement":null},{"id":"W2581789148","doi":"10.3389/fninf.2017.00005","title":"AxonPacking: An Open-Source Software to Simulate Arrangements of Axons in White Matter","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Open source; Open source software; Computer science; White matter; White (mutation); Software; Programming language; Biology; Medicine","score_opus":0.0682076722942466,"score_gpt":0.3653725144846666,"score_spread":0.29716484219042005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2581789148","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043792527,0.001667611,0.70556176,0.00045864968,0.0004042246,0.0004639251,0.009674587,0.22701062,0.010966079],"genre_scores_gemma":[0.15328255,0.0022579245,0.7638505,0.00062382664,0.00011395554,0.0025888146,0.017230388,0.04750612,0.012545927],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967515,0.00005726324,0.000041270978,0.00005981378,0.00012346846,0.000043073913],"domain_scores_gemma":[0.99862206,0.00094618695,0.00011188504,0.000089318215,0.00015128765,0.000079242265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011013021,0.0015300127,0.0011381443,0.00084525597,0.0007642268,0.0012206841,0.0031684057,0.001969581,0.015949577],"category_scores_gemma":[0.004045454,0.0012389353,0.0014196289,0.00084664114,0.00057441456,0.0014481926,0.0019420709,0.0023530738,0.0043724985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012267223,0.00060479384,0.009115903,0.005579978,0.0013349154,0.0012538421,0.0018466484,0.4753626,0.04661187,0.037650675,0.14466584,0.2747462],"study_design_scores_gemma":[0.00022556674,0.00015392498,0.0016804881,0.00024904276,0.000116234994,0.00039318082,0.00008079114,0.8835462,0.021079335,0.01312474,0.07920584,0.00014468523],"about_ca_topic_score_codex":0.0063071405,"about_ca_topic_score_gemma":0.008435187,"teacher_disagreement_score":0.015949577,"about_ca_system_score_codex":0.00079955085,"about_ca_system_score_gemma":0.0024694814,"threshold_uncertainty_score":0.053356647},"labels":[],"label_agreement":null},{"id":"W2582496673","doi":"10.1016/j.nicl.2017.01.026","title":"Independent value added by diffusion MRI for prediction of cognitive function in older adults","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Canadian Institutes of Health Research; California Department of Public Health; National Institute on Aging; Alzheimer's Association","keywords":"Dementia; White matter; Alzheimer's Disease Neuroimaging Initiative; Cognitive decline; Psychology; Neuroimaging; Diffusion MRI; Magnetic resonance imaging; Brain size; Internal medicine; Cognition; Medicine; Cardiology; Neuroscience; Disease; Radiology","score_opus":0.08883776844937022,"score_gpt":0.41924321603563136,"score_spread":0.3304054475862611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582496673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906646,0.0033584742,0.002060712,0.0004292595,0.00011259966,0.00004850297,0.001654296,0.00010823688,0.0015635284],"genre_scores_gemma":[0.99653804,0.00053496077,0.0015292179,0.000052081938,0.00010735652,0.000014648081,0.0007751802,0.000009164183,0.0004392847],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998944,0.00048109156,0.00010271849,0.00020002201,0.00018927158,0.000082957],"domain_scores_gemma":[0.99297184,0.003443604,0.0014796089,0.00061597914,0.0009500169,0.0005388935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002769281,0.001673013,0.0009990714,0.0020686719,0.00034169192,0.00145169,0.0008418999,0.001235519,0.0012938023],"category_scores_gemma":[0.016059183,0.00038419885,0.0011846387,0.0009352286,0.000348572,0.001123862,0.0009347457,0.0012575621,0.00060771615],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012622243,0.00015418426,0.97894156,0.00005093052,0.00061732373,0.00011928102,0.000043230273,0.0018554929,0.0003122096,0.00006652273,0.000370158,0.016207002],"study_design_scores_gemma":[0.000120000484,0.0008777468,0.94958,0.00008881649,0.00075598306,0.0003879286,0.00010369431,0.04498889,0.0007722997,0.0014933097,0.00076937315,0.00006188941],"about_ca_topic_score_codex":0.0065776273,"about_ca_topic_score_gemma":0.013204307,"teacher_disagreement_score":0.0065776273,"about_ca_system_score_codex":0.00041964886,"about_ca_system_score_gemma":0.00058145146,"threshold_uncertainty_score":0.014645517},"labels":[],"label_agreement":null},{"id":"W2584408557","doi":"10.1101/104190","title":"Fiber tractography using machine learning","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Deutsche Forschungsgemeinschaft","keywords":"Tractography; Computer science; Random forest; Artificial intelligence; Imaging phantom; Fiber; Diffusion MRI; Machine learning; Pattern recognition (psychology); Physics; Medicine; Chemistry","score_opus":0.0603398396589757,"score_gpt":0.3155699989317103,"score_spread":0.25523015927273457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584408557","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027558056,0.00012176544,0.9950831,0.000071591494,0.000022765458,0.000032180465,0.00010002015,0.0013976377,0.00041519402],"genre_scores_gemma":[0.13674007,0.00027341343,0.8586673,0.00007691495,0.00008888912,0.00011960381,0.00076647976,0.00068315794,0.0025841668],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990637,0.00027720103,0.000047675723,0.000276025,0.00026949128,0.000065993016],"domain_scores_gemma":[0.9980716,0.0006676072,0.00026300998,0.00046499696,0.0004448703,0.000087849134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018706218,0.00092384097,0.0009979303,0.002482801,0.0006284707,0.0018676344,0.0012312304,0.0014846369,0.0044416776],"category_scores_gemma":[0.004898746,0.0005105496,0.001163736,0.0015661616,0.0008102364,0.0013079759,0.0012467792,0.001347334,0.0025956181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001707024,0.00007967733,0.0019285697,0.00028160465,0.00022859681,0.00019029198,0.0001124842,0.46848342,0.039983362,0.03141893,0.0076895687,0.4494328],"study_design_scores_gemma":[0.0000068740314,0.000020004316,0.00029219457,0.000015469346,0.000008676192,0.00006423139,0.000004998385,0.9776072,0.005723105,0.013785194,0.0024595198,0.000012483307],"about_ca_topic_score_codex":0.0037192446,"about_ca_topic_score_gemma":0.0048374604,"teacher_disagreement_score":0.0044416776,"about_ca_system_score_codex":0.000848863,"about_ca_system_score_gemma":0.0013228316,"threshold_uncertainty_score":0.0148589015},"labels":[],"label_agreement":null},{"id":"W2584704508","doi":"10.1101/105270","title":"Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Ikerbasque, Basque Foundation for Science; Eisai; National Institute on Aging; Eusko Jaurlaritza; AstraZeneca; Bristol-Myers Squibb; Amorfix Life Sciences; European Commission; Alzheimer's Disease Neuroimaging Initiative; Biogen","keywords":"Parahippocampal gyrus; Neuroscience; Diffusion MRI; Entorhinal cortex; Middle temporal gyrus; Hippocampus; Neuroimaging; Psychology; Hippocampal formation; Cognition; Dementia; Disease; Temporal lobe; Medicine; Internal medicine; Epilepsy; Magnetic resonance imaging","score_opus":0.05181560930956387,"score_gpt":0.3354240008034575,"score_spread":0.28360839149389366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584704508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992494,0.000082550374,0.0003700845,0.000021658641,0.000001984057,0.00000647691,0.00013449752,0.00000591722,0.00012730704],"genre_scores_gemma":[0.99938893,0.000032914977,0.00030841376,0.000005323324,0.0000028340528,0.0000065046193,0.00016011407,0.0000018183348,0.00009301301],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998696,0.000029822346,0.000012733473,0.000036958812,0.000020706248,0.00003008337],"domain_scores_gemma":[0.99944466,0.00009750008,0.00022975705,0.00007739078,0.000055238903,0.00009540431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005444314,0.00028527767,0.0002883776,0.0010581793,0.00020902735,0.00036191544,0.00018460353,0.00029448618,0.00086367904],"category_scores_gemma":[0.001369092,0.00010393804,0.00029103106,0.00046488634,0.0003453956,0.00046969252,0.00042894096,0.0003427374,0.00008492029],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003560926,0.0002500903,0.85871875,0.00013206362,0.00062480825,0.0005531808,0.0017897086,0.002072929,0.107918754,0.00061098504,0.00066063803,0.02310708],"study_design_scores_gemma":[0.000011515333,0.00019020474,0.99657553,0.0000049201626,0.00004408553,0.00012945365,0.00017187171,0.0010176203,0.0012937831,0.00045771478,0.00009545806,0.000007807359],"about_ca_topic_score_codex":0.002224555,"about_ca_topic_score_gemma":0.0031962986,"teacher_disagreement_score":0.002224555,"about_ca_system_score_codex":0.00021487258,"about_ca_system_score_gemma":0.00014381089,"threshold_uncertainty_score":0.0044232607},"labels":[],"label_agreement":null},{"id":"W2586729820","doi":"10.1016/j.pscychresns.2017.02.002","title":"Corpus callosum volumes in bipolar disorders and suicidal vulnerability","year":2017,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Corpus callosum; Bipolar disorder; Psychology; Bipolar I disorder; Psychiatry; Magnetic resonance imaging; Internal medicine; Suicide attempt; Audiology; Medicine; Clinical psychology; Poison control; Neuroscience; Injury prevention; Lithium (medication); Radiology; Mania","score_opus":0.1409115750582966,"score_gpt":0.46194309760321134,"score_spread":0.32103152254491474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586729820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99731064,0.0008051119,0.000044390476,0.00020539458,0.000008510203,0.000004255408,0.00013544354,0.000003782756,0.0014824178],"genre_scores_gemma":[0.99909496,0.00029374775,0.00010865859,0.00002831211,0.000018392375,0.0000045869865,0.00011132343,0.000002421782,0.00033767126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998976,0.000034090626,0.000011999999,0.000019362391,0.000020801994,0.000016034572],"domain_scores_gemma":[0.9992993,0.00019080189,0.0003023478,0.000041571657,0.000050803967,0.000115282506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004546991,0.0003988086,0.00025003462,0.0014630599,0.00052274327,0.0010025835,0.00043657384,0.0007698448,0.0026396562],"category_scores_gemma":[0.002439538,0.00032698805,0.00022495794,0.0008440676,0.00055374496,0.0006875425,0.0006086186,0.0006268647,0.00015734292],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008248291,0.00008669629,0.98234254,0.000054632532,0.00023765239,0.0011936364,0.00066520233,0.00027441417,0.0020112663,0.0006615055,0.00050945394,0.011138253],"study_design_scores_gemma":[0.000010184252,0.00003592704,0.997399,0.000021788546,0.00005111378,0.000880428,0.0003844244,0.00023869603,0.00012724772,0.00069183623,0.00015264282,0.0000066924867],"about_ca_topic_score_codex":0.007148374,"about_ca_topic_score_gemma":0.012340435,"teacher_disagreement_score":0.007148374,"about_ca_system_score_codex":0.0004527671,"about_ca_system_score_gemma":0.00034692732,"threshold_uncertainty_score":0.014213562},"labels":[],"label_agreement":null},{"id":"W2587656219","doi":"10.1007/s11682-016-9670-y","title":"Multi-site harmonization of diffusion MRI data in a registration framework","year":2017,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; University of Cincinnati","keywords":"Fractional anisotropy; Diffusion MRI; Computer science; Harmonization; Artificial intelligence; Pattern recognition (psychology); Image registration; Data mining; Statistics; Mathematics; Radiology; Medicine; Magnetic resonance imaging; Image (mathematics); Physics","score_opus":0.1189248562493965,"score_gpt":0.42021924601030924,"score_spread":0.3012943897609127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587656219","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040415307,0.0001246522,0.9949114,0.0000757925,0.000019780688,0.000030531897,0.000055656914,0.0003552169,0.00038552328],"genre_scores_gemma":[0.19009027,0.0005258069,0.8038328,0.00013081805,0.00013833304,0.0002746339,0.0006881702,0.00079496304,0.0035241586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983,0.00077519595,0.00011338929,0.00035925396,0.00034859494,0.00010356982],"domain_scores_gemma":[0.9987104,0.0003643534,0.0001889835,0.0004564523,0.00022629928,0.000053582764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003189486,0.00078603474,0.0014229274,0.0015655675,0.00056670903,0.0018537343,0.002259243,0.0016109662,0.0020305454],"category_scores_gemma":[0.005084934,0.00082590146,0.0023006848,0.0024628465,0.0009223032,0.002359032,0.0026907837,0.0015784957,0.0013542932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037505856,0.00023906607,0.0011552628,0.00033302454,0.00043670842,0.00022207122,0.00031589816,0.46686128,0.028796759,0.05585455,0.0056028687,0.43980742],"study_design_scores_gemma":[0.000023983408,0.00013675718,0.0007260394,0.000016100254,0.00009434909,0.00019716562,0.000060621664,0.9626331,0.007038748,0.023930484,0.0051078363,0.00003485554],"about_ca_topic_score_codex":0.002223097,"about_ca_topic_score_gemma":0.0037748325,"teacher_disagreement_score":0.003189486,"about_ca_system_score_codex":0.00037698846,"about_ca_system_score_gemma":0.0013865973,"threshold_uncertainty_score":0.016867816},"labels":[],"label_agreement":null},{"id":"W2589870402","doi":"10.1038/nn.4501","title":"Studying neuroanatomy using MRI","year":2017,"lang":"en","type":"review","venue":"Nature Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":335,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Hospital for Sick Children; University of Toronto","funders":"Engineering and Physical Sciences Research Council; Wellcome Trust","keywords":"Neuroanatomy; Neuroscience; Key (lock); Computer science; Neuroimaging; Brain function; Artificial intelligence; Cognitive science; Psychology","score_opus":0.334178582928508,"score_gpt":0.5299279926264469,"score_spread":0.19574940969793886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2589870402","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006613578,0.9983064,0.00022084145,0.00030293188,0.00023049535,0.000004557692,0.00001619687,0.000008356315,0.0008441005],"genre_scores_gemma":[0.00051840773,0.9979007,0.00038000187,0.00030618277,0.00043716657,0.000007098103,0.00003140081,0.0000025633665,0.00041650946],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997693,0.000036891157,0.000045905705,0.000047739934,0.00007927309,0.000020913412],"domain_scores_gemma":[0.9991854,0.0004263267,0.000108283384,0.00002630393,0.00019415909,0.000059562648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010238137,0.001610092,0.0015895624,0.0041339993,0.00026411796,0.0014017499,0.0010220079,0.0015572084,0.0028340088],"category_scores_gemma":[0.0019445838,0.00043229986,0.00054061285,0.002943276,0.0010465528,0.0024399837,0.0010975954,0.0018852163,0.0017882184],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004903176,0.000036817208,0.00025488154,0.015969517,0.000088377856,0.00019591559,0.000041036856,0.0002787115,0.0011051685,0.0032270662,0.027225832,0.9515278],"study_design_scores_gemma":[0.000027884738,0.00007516676,0.001158352,0.008191318,0.00032145972,0.0026041802,0.00010793934,0.00019215292,0.0007725374,0.007035872,0.97946715,0.000046059824],"about_ca_topic_score_codex":0.0016332926,"about_ca_topic_score_gemma":0.0036147009,"teacher_disagreement_score":0.0041339993,"about_ca_system_score_codex":0.0007280633,"about_ca_system_score_gemma":0.0021746412,"threshold_uncertainty_score":0},"labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"grok","categories":[],"domain":null,"study_design":"not_applicable","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"opus","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W2590116164","doi":"10.1088/1361-6560/aa5dbe","title":"DTI measurements for Alzheimer’s classification","year":2017,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Engineering and Physical Sciences Research Council; University of California, San Francisco; National Institute on Aging; Alzheimer's Disease Neuroimaging Initiative","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Neuroimaging; Feature selection; Alzheimer's Disease Neuroimaging Initiative; Artificial intelligence; Computer science; Alzheimer's disease; Psychology; Pattern recognition (psychology); Medicine; Disease; Neuroscience; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.8816298606038262,"score_gpt":0.5812535583468126,"score_spread":0.3003763022570136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590116164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25208503,0.016395792,0.66598207,0.0014504147,0.0013315493,0.0014595978,0.03958335,0.005414436,0.016297804],"genre_scores_gemma":[0.48030922,0.0035988328,0.4913466,0.0002530941,0.00036907365,0.0015458589,0.017541293,0.000804084,0.0042319354],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99753845,0.00066672644,0.00036187924,0.0005666115,0.0007582646,0.000108120366],"domain_scores_gemma":[0.9946361,0.001770773,0.0010565104,0.0011092183,0.0012618446,0.0001656482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039413855,0.0011705484,0.0013453793,0.0038675386,0.0006583742,0.0014636528,0.0007791121,0.00085123256,0.005631053],"category_scores_gemma":[0.018580375,0.00035530122,0.0007952535,0.0041802386,0.00043480186,0.0006893625,0.000821182,0.0011791768,0.0027733846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018209313,0.00040968065,0.15379114,0.0016595998,0.001048989,0.0005669402,0.00045350712,0.02044444,0.035698257,0.009693733,0.05181378,0.72259897],"study_design_scores_gemma":[0.00031715288,0.0017868081,0.42632705,0.00085330626,0.0008991631,0.0050418205,0.00050900603,0.34412625,0.05090426,0.040683173,0.12806599,0.0004859953],"about_ca_topic_score_codex":0.0027635123,"about_ca_topic_score_gemma":0.002375339,"teacher_disagreement_score":0.005631053,"about_ca_system_score_codex":0.00062650663,"about_ca_system_score_gemma":0.0011302459,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2590185774","doi":"10.1016/j.neuroimage.2017.02.056","title":"Structural properties of the human corpus callosum: Multimodal assessment and sex differences","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital; University of Calgary","funders":"National Institute of Mental Health; Medical Research Council; National Institutes of Health; European Commission; Wellcome Trust","keywords":"Corpus callosum; Psychology; Natural language processing; Artificial intelligence; Computer science; Neuroscience","score_opus":0.13050249486350834,"score_gpt":0.3855794944059545,"score_spread":0.25507699954244617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590185774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955537,0.0011211082,0.0011464418,0.00010119354,0.000007196966,0.000007285747,0.00029843528,0.000017679742,0.0017468318],"genre_scores_gemma":[0.99844825,0.00035056061,0.00045870763,0.000018181632,0.000013027079,0.0000065228483,0.00009655755,0.000028651528,0.00057956524],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988616,0.000025838108,0.0000088029865,0.000041462205,0.000028026387,0.000009643217],"domain_scores_gemma":[0.9991566,0.00032806568,0.00023574514,0.00012493732,0.00009648664,0.00005821706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053685094,0.00021635026,0.00016963447,0.0010087917,0.00018728957,0.0005099973,0.00021794658,0.00034774488,0.0027623866],"category_scores_gemma":[0.0026862768,0.000174733,0.00012776369,0.00046697157,0.00046716057,0.000469631,0.0003146209,0.00017912751,0.00025851413],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023187383,0.00012920125,0.3156457,0.00032336323,0.00059548253,0.0013707825,0.0027765483,0.0011246366,0.51867515,0.0022203354,0.0010540286,0.15376602],"study_design_scores_gemma":[0.0000129302825,0.00015755674,0.9761153,0.000025293146,0.000109583576,0.0031532198,0.00045004077,0.0010543431,0.016596314,0.0012173677,0.0010851341,0.000022870881],"about_ca_topic_score_codex":0.00084673223,"about_ca_topic_score_gemma":0.0013237352,"teacher_disagreement_score":0.0027623866,"about_ca_system_score_codex":0.00016831988,"about_ca_system_score_gemma":0.00018233183,"threshold_uncertainty_score":0.0092410445},"labels":[],"label_agreement":null},{"id":"W2590918729","doi":"","title":"Cleaning output of tractography via fiber to bundle coherence, a new open source implementation","year":2016,"lang":"en","type":"article","venue":"TU/e Research Portal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Coherence (philosophical gambling strategy); Tractography; Bundle; Computer science; Open source; Physics; Medicine; Materials science; Diffusion MRI; Radiology; Programming language; Software","score_opus":0.23658491046603872,"score_gpt":0.5110103378283268,"score_spread":0.27442542736228814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590918729","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002750885,0.000058395795,0.93528277,0.000096689415,0.00006736606,0.000042743,0.0005570102,0.060662303,0.00048192064],"genre_scores_gemma":[0.0392945,0.00009112471,0.9433636,0.000085952066,0.00008203598,0.0001355697,0.0030901711,0.010878487,0.0029785014],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99778914,0.0003722047,0.00018914421,0.00059293286,0.0009303312,0.00012631],"domain_scores_gemma":[0.9938451,0.0022298319,0.00036591562,0.0020463082,0.0012867681,0.0002260306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028935047,0.0017529691,0.001293925,0.002341892,0.0011205,0.0027774824,0.002647136,0.0022170965,0.021670856],"category_scores_gemma":[0.017784214,0.0013703026,0.0015635825,0.001958312,0.000741348,0.0031094,0.003231526,0.0021526231,0.011099799],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010217546,0.00031617907,0.0022998536,0.0005371974,0.0007000351,0.00046877697,0.00048566237,0.02820122,0.035951737,0.009992366,0.054464925,0.8655603],"study_design_scores_gemma":[0.00027552122,0.00017354003,0.0036121968,0.000079395904,0.00014129117,0.0005734174,0.00011006411,0.87333184,0.049706884,0.02596613,0.045862917,0.00016685521],"about_ca_topic_score_codex":0.005148249,"about_ca_topic_score_gemma":0.00790058,"teacher_disagreement_score":0.021670856,"about_ca_system_score_codex":0.0004358391,"about_ca_system_score_gemma":0.0018197014,"threshold_uncertainty_score":0.072496235},"labels":[],"label_agreement":null},{"id":"W2592582590","doi":"10.1159/000456710","title":"White Matter Disruption and Connected Speech in Non-Fluent and Semantic Variants of Primary Progressive Aphasia","year":2017,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; Sunnybrook Health Science Centre; Mount Sinai Hospital; Toronto Western Hospital; Hôpital du Sacré-Cœur de Montréal; University of Ottawa; Sinai Health System; Baycrest Hospital; Université de Montréal; Health Sciences Centre; University Health Network; University of Toronto; Heart and Stroke Foundation; Toronto Rehabilitation Institute","funders":"University of Toronto; Eli Lilly Canada; Morris Kerzner Memorial Fund; Canadian Institutes of Health Research; Toronto Rehabilitation Institute; Sunnybrook Research Institute","keywords":"Primary progressive aphasia; Diffusion MRI; White matter; Psychology; Natural language processing; Aphasia; Artificial intelligence; Computer science; Audiology; Medicine; Cognitive psychology; Pathology; Frontotemporal dementia","score_opus":0.017182474040084075,"score_gpt":0.30963321771317864,"score_spread":0.2924507436730946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592582590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954295,0.00004918221,0.00024497547,0.0000046449177,0.0000012050533,0.0000064205765,0.000021708189,0.0000045002057,0.00012450073],"genre_scores_gemma":[0.99942315,0.000033195498,0.0003793503,0.0000052984146,0.000003173386,0.00000784701,0.00006871069,0.0000030475255,0.000076104196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996722,0.00007260329,0.000047593338,0.00011453341,0.00006423902,0.000028872873],"domain_scores_gemma":[0.99883467,0.000389957,0.00048566464,0.00010282222,0.00008258421,0.000104219944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046152092,0.000525546,0.0002486361,0.0019276317,0.0003361768,0.00044977485,0.00016246988,0.0004034504,0.0010948235],"category_scores_gemma":[0.0025693572,0.00018368647,0.00023153427,0.00046670478,0.00092932343,0.00039555895,0.0005868795,0.0002462838,0.00013836382],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002008912,0.00026940843,0.74560964,0.0002452648,0.0004019257,0.010795748,0.008350312,0.00070826244,0.19012137,0.00042938875,0.00019088568,0.040868815],"study_design_scores_gemma":[0.0000073659535,0.0001640369,0.99367976,0.000006502453,0.000021369555,0.003622387,0.00046121696,0.00030001288,0.0014604334,0.00021945286,0.000050277427,0.0000070687197],"about_ca_topic_score_codex":0.0017049003,"about_ca_topic_score_gemma":0.0032037469,"teacher_disagreement_score":0.0019276317,"about_ca_system_score_codex":0.00017186266,"about_ca_system_score_gemma":0.00018617038,"threshold_uncertainty_score":0.0036625266},"labels":[],"label_agreement":null},{"id":"W2592815600","doi":"10.1117/12.2254418","title":"Automatic classification of patients with idiopathic Parkinson's disease and progressive supranuclear palsy using diffusion MRI datasets","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Calgary","funders":"","keywords":"Progressive supranuclear palsy; Diffusion MRI; Support vector machine; Effective diffusion coefficient; Magnetic resonance imaging; Computer science; Parkinson's disease; Context (archaeology); Artificial intelligence; Pattern recognition (psychology); Medicine; Disease; Radiology; Pathology","score_opus":0.024586228229855636,"score_gpt":0.28678156296573015,"score_spread":0.26219533473587453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592815600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701591,0.0009659478,0.023632208,0.00022789704,0.00007563348,0.00012970452,0.0033866863,0.00064618414,0.0007766051],"genre_scores_gemma":[0.9762807,0.0001999161,0.017248759,0.000040017017,0.00003630321,0.00006144864,0.00588027,0.000017330896,0.00023525947],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934584,0.00013621594,0.0001327868,0.00019248787,0.0001200833,0.00007252147],"domain_scores_gemma":[0.99898356,0.00039372663,0.00015877363,0.00013155506,0.00024897594,0.00008334068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001124924,0.0006728477,0.00072838593,0.0023969484,0.0002494641,0.00078734325,0.0005100656,0.00081560336,0.00046071064],"category_scores_gemma":[0.0028794897,0.000116552335,0.0005586535,0.00075674395,0.00019539689,0.00039276187,0.00061345054,0.0004001878,0.0003409768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028714756,0.0009286292,0.45089903,0.00047641172,0.0007729438,0.0031509048,0.00046217703,0.024861673,0.04725854,0.000812605,0.008442362,0.45906326],"study_design_scores_gemma":[0.00018655401,0.00063952093,0.44320035,0.00014449899,0.00035363,0.0049317125,0.0008467122,0.511967,0.03066596,0.002432983,0.004524767,0.00010628808],"about_ca_topic_score_codex":0.0022950124,"about_ca_topic_score_gemma":0.0026009057,"teacher_disagreement_score":0.0023969484,"about_ca_system_score_codex":0.00030852685,"about_ca_system_score_gemma":0.0004324987,"threshold_uncertainty_score":0.005949199},"labels":[],"label_agreement":null},{"id":"W2593343929","doi":"10.1016/j.neuroimage.2017.08.038","title":"Promise and pitfalls of g-ratio estimation with MRI","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; McGill University; University of Calgary; Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec","keywords":"Estimation; Computer science; Medicine; Economics","score_opus":0.20888363962043036,"score_gpt":0.4534811352873786,"score_spread":0.24459749566694824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593343929","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018293309,0.9956151,0.0017977533,0.0012973378,0.00025089193,0.0000041520802,0.000027184537,0.000024483437,0.00080011965],"genre_scores_gemma":[0.0028025343,0.9893762,0.0048539084,0.0010812338,0.0013676989,0.0000108733575,0.00005703625,0.000016665701,0.00043387318],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991679,0.00023226581,0.00009995089,0.00018812275,0.0002694806,0.000042353848],"domain_scores_gemma":[0.9946138,0.003927813,0.00034330192,0.00015396446,0.00084777747,0.0001133428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037475778,0.0014245429,0.0025329937,0.003698041,0.00028085636,0.0024459392,0.0022866728,0.0026712029,0.002423664],"category_scores_gemma":[0.0076059597,0.0005787279,0.0009262198,0.003055547,0.0024035436,0.0035760913,0.0010295052,0.0032111043,0.0016679696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007840393,0.000032148444,0.00080960616,0.0066738585,0.00020930536,0.00023560546,0.0000615922,0.00068215054,0.0010899463,0.008673423,0.01661086,0.96484315],"study_design_scores_gemma":[0.00008062534,0.0002105133,0.005117511,0.010853507,0.0010078942,0.008823455,0.00034547644,0.0027473096,0.0036282875,0.05749086,0.90946186,0.00023278242],"about_ca_topic_score_codex":0.003201611,"about_ca_topic_score_gemma":0.0044456436,"teacher_disagreement_score":0.0037475778,"about_ca_system_score_codex":0.0008855137,"about_ca_system_score_gemma":0.0022556183,"threshold_uncertainty_score":0.01981932},"labels":[],"label_agreement":null},{"id":"W2593832538","doi":"10.17975/sfj-2017-006","title":"Comparison of Tractography in Mouse Models of Multiple Sclerosis and Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"STEM Fellowship Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Tractography; Corpus callosum; Neuroscience; Multiple sclerosis; Magnetic resonance imaging; Biology; Diffusion MRI; Artificial intelligence; Pathology; Psychology; Computer science; Medicine; Radiology","score_opus":0.3294660013029526,"score_gpt":0.407705977781786,"score_spread":0.0782399764788334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593832538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90865153,0.0015317927,0.08387539,0.00022100042,0.00013248023,0.00019688188,0.0023159308,0.0011893569,0.0018857352],"genre_scores_gemma":[0.8791836,0.0026678317,0.10270968,0.00014453789,0.00003114356,0.0009152825,0.0053287325,0.00077021215,0.008248899],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993236,0.00014836097,0.00010114339,0.00017130886,0.00018296285,0.0000725687],"domain_scores_gemma":[0.9985898,0.00032697245,0.00040041335,0.0002305278,0.00026370547,0.0001885605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013373182,0.0010047293,0.00067607866,0.0028608048,0.0003950668,0.00063489133,0.000432023,0.0008473748,0.0017147027],"category_scores_gemma":[0.0010283089,0.00053072954,0.0008505823,0.0008430085,0.0006950486,0.00060536707,0.00044178998,0.0011797324,0.0004970218],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005030527,0.00016424837,0.0015039764,0.00011709735,0.00009368001,0.00013815517,0.00011779682,0.0011656226,0.99202555,0.000641684,0.00018873185,0.003340312],"study_design_scores_gemma":[0.00011979488,0.0027563968,0.033488866,0.00009031974,0.00029470734,0.0016582641,0.00017757497,0.016110504,0.9380329,0.0011343677,0.0060679954,0.00006834996],"about_ca_topic_score_codex":0.0027951128,"about_ca_topic_score_gemma":0.0040668454,"teacher_disagreement_score":0.0028608048,"about_ca_system_score_codex":0.0006697512,"about_ca_system_score_gemma":0.0004317068,"threshold_uncertainty_score":0.0070725083},"labels":[],"label_agreement":null},{"id":"W2594251290","doi":"10.1007/s00429-016-1356-0","title":"Magnetic resonance diffusion tensor imaging for the pedunculopontine nucleus: proof of concept and histological correlation","year":2017,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute on Aging; Sociedade Beneficente Israelita Brasileira Albert Einstein; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Pedunculopontine nucleus; Fractional anisotropy; Medial lemniscus; Diffusion MRI; White matter; Anatomy; Magnetic resonance imaging; Brainstem; Lateral lemniscus; Neuroscience; Nuclear magnetic resonance; Nucleus; Chemistry; Inferior colliculus; Medicine; Pathology; Physics; Psychology; Deep brain stimulation; Parkinson's disease; Radiology","score_opus":0.02637555752708965,"score_gpt":0.29535414324876114,"score_spread":0.2689785857216715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594251290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55708426,0.009370301,0.4166184,0.0034120074,0.0010550761,0.0017312233,0.0011900181,0.00078014494,0.008758575],"genre_scores_gemma":[0.7921135,0.0052336426,0.19628324,0.00047933968,0.00033414256,0.0008357477,0.0011510216,0.00018727315,0.003382121],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99929214,0.00015808493,0.000048395006,0.00016276295,0.00024683226,0.00009175976],"domain_scores_gemma":[0.9968637,0.00081814005,0.00057509926,0.0005795849,0.00090119126,0.0002623166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004410884,0.0010439005,0.00066827994,0.0010012815,0.0008847749,0.0013234207,0.0013777274,0.0015903072,0.0026985302],"category_scores_gemma":[0.005380394,0.0005729792,0.0007126297,0.00038040295,0.002480144,0.0025147423,0.001038773,0.0017282147,0.0010354073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018044726,0.001404949,0.009072988,0.0010019791,0.00017794363,0.00418453,0.00037437893,0.001275198,0.9211,0.011179876,0.0024201775,0.04600335],"study_design_scores_gemma":[0.0009238707,0.005675506,0.029891927,0.0003194307,0.0008021092,0.02522138,0.00053964555,0.018247034,0.88458246,0.008466599,0.025148023,0.00018197646],"about_ca_topic_score_codex":0.0016382118,"about_ca_topic_score_gemma":0.0016992092,"teacher_disagreement_score":0.004410884,"about_ca_system_score_codex":0.00085183093,"about_ca_system_score_gemma":0.0023727799,"threshold_uncertainty_score":0.023327231},"labels":[],"label_agreement":null},{"id":"W2594651183","doi":"10.1016/j.jagp.2017.02.021","title":"Stage-Dependent Significance of Subjective Memory Complaints: Responding to the Worried Well … and to the Unworried Unwell","year":2017,"lang":"en","type":"letter","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Dementia; Neuropsychology; Psychology; Fractional anisotropy; Neurocognitive; Cognitive decline; Psychiatry; Cognition; Clinical psychology; Disease; Montreal Cognitive Assessment; Medicine; Cognitive impairment; White matter; Internal medicine","score_opus":0.027396020033645097,"score_gpt":0.32928781890592185,"score_spread":0.30189179887227674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594651183","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34144887,0.0029225328,0.0007097936,0.62909585,0.009637812,0.00006511777,0.0005144217,0.00005953739,0.015546169],"genre_scores_gemma":[0.8403839,0.0011561852,0.00068429817,0.1302395,0.023468371,0.00005705485,0.00015244517,0.00002963045,0.0038286773],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994623,0.00016497905,0.00007985995,0.00008053698,0.00010699445,0.000105397856],"domain_scores_gemma":[0.99468297,0.003381573,0.00041610503,0.00016072782,0.0008572907,0.0005013535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011167694,0.0003058057,0.0007626205,0.00036367294,0.0006790477,0.0008484356,0.0006773336,0.0046829935,0.0016663158],"category_scores_gemma":[0.012402658,0.0001964522,0.000436035,0.00036324761,0.0010045216,0.00082410045,0.00033770423,0.0050961715,0.000523891],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035066693,0.00043571836,0.51799154,0.0002221297,0.00025827327,0.11990445,0.0030264398,0.0003925613,0.003953083,0.00504403,0.26673952,0.07852565],"study_design_scores_gemma":[0.00089784537,0.0011269955,0.7573788,0.0004104331,0.0003564793,0.12946112,0.005682708,0.0059426874,0.0019120061,0.018875346,0.07769803,0.00025750737],"about_ca_topic_score_codex":0.0046534752,"about_ca_topic_score_gemma":0.009746218,"teacher_disagreement_score":0.0046829935,"about_ca_system_score_codex":0.00092040526,"about_ca_system_score_gemma":0.0009735897,"threshold_uncertainty_score":0.009252787},"labels":[],"label_agreement":null},{"id":"W2597202272","doi":"10.1155/2017/9807512","title":"Thalamocortical Connectivity and Microstructural Changes in Congenital and Late Blindness","year":2017,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"H. Lundbeck A/S; Danmarks Frie Forskningsfond; Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"Tractography; Neuroscience; Diffusion MRI; Thalamus; Cortex (anatomy); White matter; Fractional anisotropy; Connectomics; Visual cortex; Psychology; Magnetic resonance imaging; Connectome; Functional connectivity; Medicine","score_opus":0.06990996027466524,"score_gpt":0.35359893949321963,"score_spread":0.2836889792185544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597202272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99899274,0.00014375111,0.0006003303,0.0000149210655,0.0000010505607,0.0000031248824,0.00005742413,0.000009842623,0.00017689902],"genre_scores_gemma":[0.9993837,0.00005167599,0.00042435515,0.0000041028716,0.0000012491065,0.0000037501281,0.000040548148,0.0000035831167,0.00008709366],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982315,0.00002699536,0.000019685278,0.000050949555,0.000041206175,0.000038061862],"domain_scores_gemma":[0.9992386,0.00015032996,0.00036444011,0.000074385665,0.000059293547,0.00011300868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033630728,0.00025058782,0.00019110869,0.0017418077,0.00021183019,0.00036087894,0.00014590917,0.0002555677,0.0012338755],"category_scores_gemma":[0.0014996721,0.00018903884,0.00019535796,0.00038894368,0.0006489927,0.00035547029,0.00047398827,0.0002446129,0.00007493128],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021094435,0.00011159828,0.4216562,0.00023611628,0.00037428597,0.0048440504,0.0027015586,0.00183091,0.5195786,0.0014512714,0.00023069736,0.04487524],"study_design_scores_gemma":[0.0000053667422,0.000122054604,0.988241,0.000007784741,0.000031511277,0.003426678,0.00024029751,0.00091192295,0.0065614916,0.00036012774,0.00008219992,0.000009457215],"about_ca_topic_score_codex":0.0031412991,"about_ca_topic_score_gemma":0.0033967285,"teacher_disagreement_score":0.0031412991,"about_ca_system_score_codex":0.0002662267,"about_ca_system_score_gemma":0.00016495027,"threshold_uncertainty_score":0.0062460303},"labels":[],"label_agreement":null},{"id":"W2598029772","doi":"10.3389/fneur.2017.00097","title":"Investigating Microstructural Abnormalities and Neurocognition in Sub-Acute and Chronic Traumatic Brain Injury Patients with Normal-Appearing White Matter: A Preliminary Diffusion Tensor Imaging Study","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; Ontario Neurotrauma Foundation","keywords":"Fractional anisotropy; Diffusion MRI; Traumatic brain injury; White matter; Neuropsychology; Neurocognitive; Neuroimaging; Medicine; Psychology; Physical medicine and rehabilitation; Cardiology; Audiology; Internal medicine; Cognition; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.01456521141226421,"score_gpt":0.2795929995735592,"score_spread":0.265027788161295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598029772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999673,0.00012634302,0.00003913319,0.00001179309,0.0000014649015,0.000008623634,0.00003000921,9.770798e-7,0.000108653876],"genre_scores_gemma":[0.9996055,0.00009851633,0.000088458066,0.000014321981,0.000010317449,0.000007223073,0.00009618529,9.0126554e-7,0.000078532685],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998815,0.000016606828,0.000024690402,0.000027579174,0.000017055065,0.000032520576],"domain_scores_gemma":[0.9996643,0.000047396607,0.000107237254,0.000022169264,0.000053471842,0.00010536779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028878864,0.00044178157,0.00028780245,0.0010904175,0.00047823344,0.000349967,0.00014526212,0.00037924896,0.0012579216],"category_scores_gemma":[0.00077017065,0.0001841814,0.0001914658,0.0004174192,0.0005396589,0.00031503296,0.00033933527,0.00024801577,0.0002274017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012483293,0.000343222,0.97366977,0.00006703283,0.000084595005,0.0023763028,0.0009907571,0.00005215576,0.015993534,0.000021345744,0.00007240302,0.0050805844],"study_design_scores_gemma":[0.000026447986,0.0009378007,0.9954218,0.0000046290365,0.00003415525,0.0023864605,0.00040886496,0.000068446694,0.00057647243,0.000018183693,0.00011303425,0.0000034983211],"about_ca_topic_score_codex":0.0031904443,"about_ca_topic_score_gemma":0.003548398,"teacher_disagreement_score":0.0031904443,"about_ca_system_score_codex":0.00021674359,"about_ca_system_score_gemma":0.00028897016,"threshold_uncertainty_score":0.006343782},"labels":[],"label_agreement":null},{"id":"W2598260296","doi":"","title":"Structural connectivity reproducibility through multiple acquisitions","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Reproducibility; Tractography; Probabilistic logic; Computer science; Artificial intelligence; Pattern recognition (psychology); Diffusion MRI; Mathematics; Statistics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.08295902571810543,"score_gpt":0.33597663976552244,"score_spread":0.253017614047417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598260296","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30558842,0.00552561,0.65998137,0.004243903,0.001000302,0.00018780668,0.003232074,0.0038230766,0.016417418],"genre_scores_gemma":[0.8788564,0.0018315731,0.10737376,0.00033300425,0.0012450326,0.00013884489,0.0022818688,0.0017604864,0.006178999],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99613523,0.0012138481,0.00030730444,0.0015235655,0.00069016614,0.00012987987],"domain_scores_gemma":[0.97312254,0.013418962,0.0022732,0.0063264756,0.004348505,0.0005103043],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009960973,0.0011299911,0.0011551308,0.0027297684,0.0010147044,0.0034589549,0.0011755314,0.0019308452,0.008018621],"category_scores_gemma":[0.060966585,0.0010132128,0.000877151,0.0024801062,0.0015309032,0.0036627043,0.0016960099,0.0014537403,0.0021946358],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002966604,0.00032059054,0.052387092,0.0016459237,0.0027393866,0.0015522635,0.0019422271,0.047148883,0.2635803,0.03238174,0.02164741,0.5716876],"study_design_scores_gemma":[0.00028236498,0.0009417836,0.21227361,0.00045326786,0.0025041522,0.012146706,0.0006226828,0.34051636,0.19357947,0.20562515,0.03057378,0.00048077176],"about_ca_topic_score_codex":0.0013143121,"about_ca_topic_score_gemma":0.0020052209,"teacher_disagreement_score":0.99003905,"about_ca_system_score_codex":0.00063347945,"about_ca_system_score_gemma":0.0010556912,"threshold_uncertainty_score":0.0526793},"labels":[],"label_agreement":null},{"id":"W2598379557","doi":"10.15353/vsnl.v2i1.107","title":"Sparse Correlated Diffusion Imaging: A New Computational Diffusion MRI Modality for Prostate Cancer Detection","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto; Sunnybrook Health Science Centre","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Diffusion MRI; Modality (human–computer interaction); Prostate cancer; Magnetic resonance imaging; Diffusion; Computer science; Radiology; Artificial intelligence; Medicine; Cancer; Physics; Internal medicine","score_opus":0.028915644810776697,"score_gpt":0.34722755198007604,"score_spread":0.31831190716929936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598379557","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013289199,0.0010577613,0.9831693,0.0005178662,0.00006324758,0.00004831039,0.00017852538,0.000394247,0.0012815442],"genre_scores_gemma":[0.1893714,0.0023499154,0.80377346,0.000458664,0.00027079633,0.00013126365,0.00058682205,0.00011566941,0.0029420678],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997855,0.000049922637,0.000010529964,0.000040625077,0.000094882445,0.000018666044],"domain_scores_gemma":[0.9996791,0.000093734685,0.000056728233,0.00005655279,0.000081695754,0.00003215653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004324243,0.0005661759,0.00057941675,0.00077569543,0.00026110615,0.0006923909,0.0007290214,0.00076890783,0.0014411996],"category_scores_gemma":[0.0010461804,0.00026091206,0.00049571524,0.0008872933,0.0005514491,0.0010338392,0.00089873705,0.0007415801,0.00040049784],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032571628,0.00016431026,0.0025093479,0.00060402654,0.00017582449,0.000387895,0.00018461922,0.122752674,0.23017411,0.024840157,0.010969587,0.6069117],"study_design_scores_gemma":[0.000031820637,0.00014298687,0.0014158207,0.000029348757,0.00006090588,0.0009501011,0.000031905234,0.926876,0.04665117,0.008111647,0.015637288,0.00006091796],"about_ca_topic_score_codex":0.0008634474,"about_ca_topic_score_gemma":0.0018000596,"teacher_disagreement_score":0.0014411996,"about_ca_system_score_codex":0.00027243994,"about_ca_system_score_gemma":0.00062198204,"threshold_uncertainty_score":0.0048213005},"labels":[],"label_agreement":null},{"id":"W2599979438","doi":"10.1093/schbul/sbx024.081","title":"SU85. The Behavioral and Neural Correlates of Social Cognition in Youth With Mental Illness","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychology; Neurocognitive; Social cognition; Cognition; Schizophrenia (object-oriented programming); Autism spectrum disorder; Bipolar disorder; Fractional anisotropy; Autism; White matter; Psychiatry; Clinical psychology; Medicine; Magnetic resonance imaging","score_opus":0.04380205161097011,"score_gpt":0.3247954440957202,"score_spread":0.2809933924847501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2599979438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99890935,0.00009138592,0.000060709346,0.000031201565,0.0000023205362,0.0000061935925,0.00016187661,0.000004501386,0.0007325561],"genre_scores_gemma":[0.99958915,0.00002969344,0.00009307424,0.00000731113,0.0000014926507,0.000005938439,0.00014961795,0.0000011654836,0.00012250221],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998678,0.000028040307,0.000010389599,0.00002354121,0.000038098497,0.000032038068],"domain_scores_gemma":[0.999666,0.0000427753,0.00015606065,0.0000130759345,0.000040518004,0.00008154305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032404542,0.00026721312,0.00019376444,0.00061291904,0.00039122658,0.00037119517,0.00015597358,0.00020485975,0.0023056231],"category_scores_gemma":[0.0010977089,0.000086973916,0.00020801673,0.0005974131,0.00021304858,0.00023632658,0.0005179506,0.00022015774,0.00018790399],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002439511,0.000063774416,0.98281705,0.0000197113,0.000037368074,0.00012229907,0.00034506683,0.000097830205,0.0011996883,0.00007539155,0.00024781405,0.014730028],"study_design_scores_gemma":[0.0000024273484,0.0000503556,0.99929726,0.000004212192,0.000007684806,0.00009123206,0.00017071608,0.00016493576,0.000069270594,0.000042322103,0.00009861603,9.446224e-7],"about_ca_topic_score_codex":0.010108297,"about_ca_topic_score_gemma":0.018318042,"teacher_disagreement_score":0.010108297,"about_ca_system_score_codex":0.00046742137,"about_ca_system_score_gemma":0.00031322442,"threshold_uncertainty_score":0.020098925},"labels":[],"label_agreement":null},{"id":"W2599999445","doi":"10.1093/schbul/sbx021.111","title":"72. Behavioral and Neurobiological Correlates of Attention in Schizophrenia in a Virtual Environment","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Fractional anisotropy; Cognition; Neurocognitive; Schizophrenia (object-oriented programming); Effects of sleep deprivation on cognitive performance; Diffusion MRI; Cognitive psychology; Audiology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04149820874313977,"score_gpt":0.3130314617268467,"score_spread":0.27153325298370695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2599999445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996952,0.000031100484,0.000059049373,0.000006577029,4.8773677e-7,0.0000051485335,0.000024133627,0.0000018150866,0.00017654494],"genre_scores_gemma":[0.9998273,0.00002037702,0.00006065866,0.0000031236834,3.4812282e-7,0.0000042193446,0.000028620132,5.6041637e-7,0.000054775766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998565,0.000025946605,0.00001662278,0.000023266726,0.000051410254,0.000026315245],"domain_scores_gemma":[0.99961346,0.00004645903,0.00017978717,0.000022636214,0.000043066404,0.000094663956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039256556,0.00030369233,0.00015785776,0.00046948373,0.0002789757,0.00036053092,0.0001296751,0.00019165887,0.001401641],"category_scores_gemma":[0.0011223466,0.00012122752,0.0001374343,0.0001544012,0.00042805722,0.00021348536,0.00053558574,0.00019232962,0.00011184415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002684024,0.00046395152,0.8648885,0.00014328561,0.00012116791,0.0007322422,0.0010872096,0.0013137616,0.10711344,0.00024314524,0.00018830822,0.021021007],"study_design_scores_gemma":[0.000014179527,0.00046475814,0.9972337,0.00000743099,0.0000197403,0.00024940647,0.00029615633,0.00042738955,0.0011426324,0.00009040617,0.00004916536,0.0000050398216],"about_ca_topic_score_codex":0.0078966,"about_ca_topic_score_gemma":0.007514189,"teacher_disagreement_score":0.0078966,"about_ca_system_score_codex":0.00045995784,"about_ca_system_score_gemma":0.00032985667,"threshold_uncertainty_score":0.015701294},"labels":[],"label_agreement":null},{"id":"W2600405717","doi":"10.1101/120857","title":"Anatomical and functional organization of the human substantia nigra and its connections","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Substantia nigra; Salience (neuroscience); Human brain; Impulsivity; Striatum; Psychology; Human Connectome Project; Functional connectivity; Ventral striatum; Functional organization; Dopamine; Dopaminergic; Developmental psychology","score_opus":0.041946824727498215,"score_gpt":0.2840982228182877,"score_spread":0.2421513980907895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2600405717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98876023,0.000826668,0.008007789,0.0001292768,0.0000027537078,0.000007543846,0.00035639244,0.00006386728,0.0018456287],"genre_scores_gemma":[0.99474597,0.0001997222,0.004228329,0.000023646533,0.0000024569692,0.000008202741,0.00016916837,0.0000076035262,0.0006148205],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999136,0.000019222647,0.0000034486336,0.000028076565,0.00002663354,0.000009099648],"domain_scores_gemma":[0.9998555,0.000036395057,0.00003873491,0.000023225693,0.000032900927,0.000013238511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018064083,0.00007741037,0.000116534226,0.00065610517,0.00031206195,0.0004496291,0.0001494178,0.00026985994,0.00079051236],"category_scores_gemma":[0.00053143594,0.00014386575,0.000108927234,0.00039343434,0.0003457672,0.0001887224,0.00024757962,0.00012068278,0.00014646466],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036769442,0.0000538485,0.14302756,0.00019697544,0.00036928602,0.0012828205,0.0016638557,0.00570656,0.7299982,0.006398835,0.00092765305,0.1100068],"study_design_scores_gemma":[0.0000134651855,0.00010864377,0.93159205,0.00004037455,0.00009500456,0.0046039014,0.00055429013,0.015832968,0.03587079,0.00578869,0.0054600383,0.000039858336],"about_ca_topic_score_codex":0.011361019,"about_ca_topic_score_gemma":0.021759339,"teacher_disagreement_score":0.011361019,"about_ca_system_score_codex":0.00021366884,"about_ca_system_score_gemma":0.0002543079,"threshold_uncertainty_score":0.022589803},"labels":[],"label_agreement":null},{"id":"W2602101619","doi":"10.1016/j.neuroimage.2017.03.065","title":"Validating myelin water imaging with transmission electron microscopy in a rat spinal cord injury model","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Myelin; Spinal cord; Spinal cord injury; White matter; Chemistry; Electron microscope; Pathology; Biophysics; Anatomy; Neuroscience; Biology; Central nervous system; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.05049683749905037,"score_gpt":0.3986401592412709,"score_spread":0.3481433217422205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2602101619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9039195,0.0015185813,0.08958716,0.00041954932,0.00016599415,0.00047390567,0.0007806944,0.0006021031,0.0025325348],"genre_scores_gemma":[0.9222355,0.0032851687,0.06661463,0.00017432355,0.000032712218,0.00046436323,0.00077044737,0.00026924524,0.0061536175],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995443,0.000087230685,0.0000353176,0.00009230546,0.00014224891,0.00009852816],"domain_scores_gemma":[0.99905056,0.00010308619,0.00018133664,0.00015464654,0.00042577577,0.000084518986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015262542,0.0011731795,0.00044626178,0.0010336398,0.0008609544,0.0006395638,0.001006286,0.0011000643,0.0014231788],"category_scores_gemma":[0.000930355,0.0004277452,0.00050746434,0.0003922156,0.0009375392,0.0012987921,0.0006569195,0.0011781893,0.00048441094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026872216,0.00027139235,0.000457376,0.00012948857,0.000024348516,0.00010651337,0.000088329805,0.0006513973,0.9946392,0.00039654988,0.000101312726,0.002865376],"study_design_scores_gemma":[0.000026288237,0.0014256225,0.0014288543,0.0000253792,0.000098872064,0.00020675563,0.00010014176,0.0034490789,0.9918997,0.00019537126,0.0011280307,0.000015926355],"about_ca_topic_score_codex":0.008774081,"about_ca_topic_score_gemma":0.011854372,"teacher_disagreement_score":0.008774081,"about_ca_system_score_codex":0.0007557573,"about_ca_system_score_gemma":0.0013618298,"threshold_uncertainty_score":0.017445982},"labels":[],"label_agreement":null},{"id":"W2604506905","doi":"10.3390/brainsci7040037","title":"Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Meso Scale Diagnostics; F. Hoffmann-La Roche; University of Southern California; Biogen; BioClinica; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Tractography; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Psychology; Fractional anisotropy; Artificial intelligence; Cognitive impairment; Computer science; Cognition; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.14223717141486394,"score_gpt":0.42844495725609366,"score_spread":0.28620778584122974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604506905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99924767,0.000061683386,0.00045508333,0.0000102883705,0.0000025137158,0.0000036881424,0.000060622628,0.000006821021,0.00015170066],"genre_scores_gemma":[0.99933606,0.000024384626,0.00042454383,0.000007397124,0.00000223264,0.000004818866,0.00012164393,0.000004243276,0.00007460322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999561,0.00012131652,0.00004286342,0.00019158039,0.000049089565,0.000034100285],"domain_scores_gemma":[0.9987779,0.0005331963,0.000323712,0.00017654248,0.0000868061,0.000101854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008994692,0.00027481027,0.0002888173,0.0006591574,0.00023294186,0.00047274737,0.00015084949,0.0003351654,0.00086539786],"category_scores_gemma":[0.0036475307,0.00016834988,0.00027968784,0.00027689346,0.00038042545,0.0006574901,0.00049335946,0.00018021606,0.000100889134],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004897909,0.00025728915,0.8425017,0.00017399447,0.0011140138,0.00092103565,0.003022194,0.0038581693,0.11405016,0.0012710328,0.00044133945,0.027491277],"study_design_scores_gemma":[0.000043686465,0.0004480859,0.98922753,0.000014555135,0.00015260075,0.00042748012,0.00048214564,0.003679034,0.0042051882,0.0010281634,0.000278958,0.0000124701055],"about_ca_topic_score_codex":0.002248198,"about_ca_topic_score_gemma":0.0052426104,"teacher_disagreement_score":0.002248198,"about_ca_system_score_codex":0.000277427,"about_ca_system_score_gemma":0.00016465061,"threshold_uncertainty_score":0.004756868},"labels":[],"label_agreement":null},{"id":"W2604855401","doi":"10.1007/s00234-017-1816-0","title":"Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke","year":2017,"lang":"en","type":"review","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":146,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Diffusion MRI; Medicine; Stroke recovery; Corticospinal tract; Stroke (engine); Physical medicine and rehabilitation; Rehabilitation; Neurology; Neuroradiology; White matter; Biomarker; Neuroplasticity; Clinical trial; Physical therapy; Magnetic resonance imaging; Radiology; Internal medicine","score_opus":0.11026459000338917,"score_gpt":0.42646614135719596,"score_spread":0.3162015513538068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604855401","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013177295,0.99911064,0.0000963487,0.00021322834,0.000105091225,0.00000276133,0.000019202631,0.0000032779317,0.000317692],"genre_scores_gemma":[0.0016184746,0.997384,0.00019886372,0.00022411173,0.00034676827,0.000006894238,0.00003288875,0.000001138404,0.0001868984],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996209,0.00005795212,0.00009358757,0.0000781074,0.00012226673,0.000027181592],"domain_scores_gemma":[0.99883336,0.0005931157,0.000235528,0.000026113235,0.00026994638,0.000041940362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013526651,0.0012553936,0.002249606,0.003978565,0.00025384157,0.0016030762,0.0008979274,0.0012141,0.0014405986],"category_scores_gemma":[0.0027861716,0.00032901968,0.0007365275,0.003122667,0.0008538573,0.0015185644,0.0008818683,0.0014723521,0.00078165723],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012812542,0.00007254906,0.0014096748,0.017452765,0.00037613395,0.00017561119,0.000046375724,0.00025624433,0.0005841204,0.0019573132,0.015834194,0.9617068],"study_design_scores_gemma":[0.00014069698,0.0005622402,0.012348719,0.032555707,0.0036921543,0.0043436987,0.00034507437,0.000852003,0.0020943577,0.010828145,0.9320467,0.0001904064],"about_ca_topic_score_codex":0.0017113268,"about_ca_topic_score_gemma":0.0032081231,"teacher_disagreement_score":0.003978565,"about_ca_system_score_codex":0.0005762044,"about_ca_system_score_gemma":0.0021024223,"threshold_uncertainty_score":0.00715369},"labels":[],"label_agreement":null},{"id":"W2605823361","doi":"10.1002/hbm.23622","title":"Contributions of imprecision in<scp>PET</scp>‐<scp>MRI</scp>rigid registration to imprecision in amyloid<scp>PET</scp><scp>SUVR</scp>measurements","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Genentech; IXICO; Elsie and Marvin Dekelboum Family Foundation; Canadian Institutes of Health Research; GHR Foundation; F. Hoffmann-La Roche; Biogen; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Hum; White matter; Orientation (vector space); Artificial intelligence; Positron emission tomography; Image registration; Pattern recognition (psychology); Nuclear medicine; Computer science; Magnetic resonance imaging; Mathematics; Medicine; Radiology; Image (mathematics)","score_opus":0.10033635084873678,"score_gpt":0.38027108839224305,"score_spread":0.2799347375435063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605823361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7639455,0.0014251901,0.2303162,0.00051128224,0.00016118556,0.00020574639,0.00053563114,0.0011743291,0.0017248709],"genre_scores_gemma":[0.97367,0.00019482823,0.02486652,0.00013997838,0.000013626409,0.00010838396,0.0003500581,0.0003038851,0.00035287146],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9932387,0.003173579,0.0006065651,0.0014183328,0.0012034364,0.00035938714],"domain_scores_gemma":[0.9784243,0.014734044,0.0018249506,0.0035611086,0.0011520388,0.00030364082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010128944,0.0011642199,0.0012423795,0.0010325207,0.00078812585,0.0016262656,0.0013914527,0.0011131066,0.0008253149],"category_scores_gemma":[0.04871273,0.0012416756,0.0012370293,0.001249648,0.0017795304,0.0011821807,0.0016778567,0.0015183201,0.000330856],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027663787,0.00021220992,0.061948057,0.0007378132,0.0013325638,0.0013989249,0.001961578,0.79081535,0.07432259,0.0047858767,0.0012121059,0.05850652],"study_design_scores_gemma":[0.0002782797,0.0012737792,0.10690392,0.0002130986,0.00073208846,0.0030781997,0.00091425324,0.73213404,0.12886894,0.018480398,0.0065808874,0.00054213684],"about_ca_topic_score_codex":0.00697145,"about_ca_topic_score_gemma":0.0052132714,"teacher_disagreement_score":0.010128944,"about_ca_system_score_codex":0.0013676481,"about_ca_system_score_gemma":0.001155559,"threshold_uncertainty_score":0.053567648},"labels":[],"label_agreement":null},{"id":"W2605983219","doi":"10.2214/ajr.17.18064","title":"Hallway Conversations in Physics","year":2017,"lang":"en","type":"article","venue":"American Journal of Roentgenology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Tractography; White matter; Radiology; Magnetic resonance imaging","score_opus":0.07514372012561657,"score_gpt":0.39176554367246197,"score_spread":0.3166218235468454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605983219","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010968515,0.006359205,0.0023437373,0.57613266,0.23541434,0.000060710405,0.0018644189,0.0013534869,0.17537461],"genre_scores_gemma":[0.018452978,0.002704352,0.0015653932,0.11983006,0.07656889,0.00016015048,0.00064525136,0.002451803,0.7776211],"study_design_codex":"not_applicable","study_design_gemma":"qualitative","domain_scores_codex":[0.99519,0.0016292576,0.00014267268,0.0007467819,0.0015838483,0.0007074338],"domain_scores_gemma":[0.98480266,0.0034926885,0.0005558016,0.00092595496,0.0027212438,0.007501713],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006101135,0.0013226464,0.0008673419,0.0015062476,0.00977183,0.011537069,0.0016045145,0.006772535,0.33559093],"category_scores_gemma":[0.03057687,0.0007719998,0.00089875114,0.0011485716,0.0028331669,0.008303534,0.009402254,0.015205948,0.08474018],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024232866,0.000011667209,0.000028657967,0.000011795197,0.0000024295493,0.000048559257,0.00018430162,0.000012431886,0.00006991673,0.0019642543,0.99251443,0.0051273443],"study_design_scores_gemma":[0.0000065300196,0.000009206397,0.00012239508,0.000024010587,0.0000015738547,0.000045935118,0.00031162833,0.000020017755,0.000056630306,0.0012626738,0.9981285,0.000010923113],"about_ca_topic_score_codex":0.0053915926,"about_ca_topic_score_gemma":0.014656669,"teacher_disagreement_score":0.9902282,"about_ca_system_score_codex":0.0038636758,"about_ca_system_score_gemma":0.0042813052,"threshold_uncertainty_score":0.9476989},"labels":[],"label_agreement":null},{"id":"W2606128815","doi":"10.3174/ajnr.a5162","title":"A Novel MRI Biomarker of Spinal Cord White Matter Injury: T2*-Weighted White Matter to Gray Matter Signal Intensity Ratio","year":2017,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; AOSpine; Rick Hansen Institute; Christopher and Dana Reeve Foundation","keywords":"Medicine; Nuclear medicine; White matter; Fractional anisotropy; Magnetic resonance imaging; Magnetization transfer; Radiology","score_opus":0.046102369390599654,"score_gpt":0.35636721979096503,"score_spread":0.3102648504003654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606128815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9793423,0.004149446,0.012235853,0.000257707,0.00007819025,0.000118785865,0.001530077,0.00030499883,0.0019825818],"genre_scores_gemma":[0.9861394,0.0006305272,0.011514599,0.00012508982,0.000110631896,0.00010334285,0.0006962404,0.000028857301,0.00065128156],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978834,0.000036156027,0.000028263052,0.00005957842,0.00006589128,0.000021840242],"domain_scores_gemma":[0.9990797,0.00016903023,0.000411582,0.000055653887,0.00020621782,0.0000778288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008571114,0.00058583805,0.00053502806,0.0015334571,0.0002401352,0.00081159285,0.00044452804,0.0008779688,0.0015297062],"category_scores_gemma":[0.0019033806,0.00016729791,0.00035475736,0.00089481304,0.0004788958,0.0007604542,0.00033122653,0.00038112784,0.0004569194],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00135068,0.0003676969,0.8105404,0.00060436054,0.000871855,0.0005891314,0.00023360117,0.0016095047,0.0862022,0.00050675316,0.0023456318,0.0947782],"study_design_scores_gemma":[0.000063309206,0.0011225475,0.95890176,0.000051250096,0.0003485196,0.003964616,0.00021551966,0.007657354,0.025097957,0.0007008209,0.0018170734,0.000059336056],"about_ca_topic_score_codex":0.0011639589,"about_ca_topic_score_gemma":0.0017043849,"teacher_disagreement_score":0.0015334571,"about_ca_system_score_codex":0.00033692902,"about_ca_system_score_gemma":0.0003226093,"threshold_uncertainty_score":0.005117357},"labels":[],"label_agreement":null},{"id":"W2606631943","doi":"10.3174/ajnr.a5163","title":"Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability","year":2017,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Université de Montréal; Toronto Western Hospital; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; AOSpine; Rick Hansen Institute; Christopher and Dana Reeve Foundation","keywords":"Magnetization transfer; Fractional anisotropy; Medicine; Magnetic resonance imaging; Nuclear medicine; Coefficient of variation; Reliability (semiconductor); Radiology; Diffusion MRI; Statistics; Mathematics; Physics","score_opus":0.12360889887312501,"score_gpt":0.50474400880697,"score_spread":0.38113510993384503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606631943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9095865,0.0030418811,0.082610354,0.00022052153,0.000083974366,0.00088185776,0.00088009005,0.0005710791,0.0021237475],"genre_scores_gemma":[0.9501715,0.00029904212,0.04738201,0.00008157203,0.000051593106,0.00079805544,0.00087558967,0.00008151417,0.00025916466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960006,0.0014923658,0.00057664834,0.0006549333,0.0011878128,0.000087561726],"domain_scores_gemma":[0.98908687,0.003024911,0.0019386165,0.002163761,0.0034410644,0.00034479695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009823477,0.0010284622,0.000516256,0.0016120111,0.00060602167,0.0009175281,0.001102451,0.0011509154,0.0006913758],"category_scores_gemma":[0.019418376,0.00036641784,0.0003778084,0.0007503183,0.0008894675,0.0008259793,0.00073747046,0.0005641731,0.00040619422],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018604599,0.0008663435,0.774314,0.00048592506,0.00075247086,0.0003356394,0.0012331392,0.004071285,0.07371283,0.00087351305,0.0018442766,0.13965012],"study_design_scores_gemma":[0.00016011093,0.0026496674,0.9479243,0.00013578152,0.00028896533,0.0020865374,0.00049985165,0.019182231,0.02356075,0.0010860601,0.0023268706,0.00009885601],"about_ca_topic_score_codex":0.0010968184,"about_ca_topic_score_gemma":0.002393962,"teacher_disagreement_score":0.009823477,"about_ca_system_score_codex":0.000439294,"about_ca_system_score_gemma":0.0006912486,"threshold_uncertainty_score":0.051952124},"labels":[],"label_agreement":null},{"id":"W2607432848","doi":"10.1016/j.neuroimage.2017.03.027","title":"Multi-center machine learning in imaging psychiatry: A meta-model approach","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Central European Institute of Technology; Ministry of Health, British Columbia; Ministry of Education, Youth and Science; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Generalizability theory; Support vector machine; Artificial intelligence; Machine learning; Computer science; Raw data; Similarity (geometry); Data sharing; Sample (material); Schizophrenia (object-oriented programming); Sample size determination; Data mining; Image (mathematics); Medicine; Mathematics; Statistics","score_opus":0.16009223452309757,"score_gpt":0.3899819900185808,"score_spread":0.22988975549548324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607432848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06513463,0.088757984,0.83107185,0.0062124124,0.0011694415,0.00045088874,0.0034746665,0.002202917,0.0015252089],"genre_scores_gemma":[0.7719376,0.0147954,0.20302482,0.0016667792,0.0009932156,0.0012503098,0.0035139504,0.00059331313,0.0022246095],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.96956784,0.02489657,0.0011089798,0.003275674,0.00075374276,0.0003971979],"domain_scores_gemma":[0.9155791,0.07525374,0.0022445787,0.004333803,0.0017961031,0.0007926868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.051419653,0.0046144337,0.0096913045,0.008515489,0.0019860552,0.0054352293,0.008114862,0.0044755554,0.00419575],"category_scores_gemma":[0.057736345,0.002628886,0.022127822,0.0069844415,0.0012048549,0.0051974906,0.003281451,0.0053664795,0.0010688753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050782356,0.0009435099,0.04011478,0.0040992415,0.38276294,0.0007478427,0.00044056558,0.4256862,0.0006254743,0.01072436,0.007908288,0.12086862],"study_design_scores_gemma":[0.00077233574,0.0006029752,0.0061603375,0.00097232097,0.103062816,0.00036760984,0.00021296574,0.8238815,0.00050799915,0.060070425,0.0031622865,0.00022652058],"about_ca_topic_score_codex":0.017439919,"about_ca_topic_score_gemma":0.01762231,"teacher_disagreement_score":0.051419653,"about_ca_system_score_codex":0.0023195513,"about_ca_system_score_gemma":0.002981176,"threshold_uncertainty_score":0.27193642},"labels":[],"label_agreement":null},{"id":"W2608502883","doi":"10.1016/j.neuroimage.2017.04.057","title":"A tract-specific approach to assessing white matter in preterm infants","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Programme Grants for Applied Research; Biotechnology and Biological Sciences Research Council; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Medical Research Council; Directorate for Biological Sciences; Medical Research Council Canada","keywords":"Tractography; Diffusion MRI; White matter; Population; Computer science; Artificial intelligence; Cartography; Medicine; Geography; Magnetic resonance imaging; Radiology","score_opus":0.11095673463104096,"score_gpt":0.3848755421898771,"score_spread":0.27391880755883613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608502883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20423974,0.0015423456,0.78647333,0.00022907686,0.000046194662,0.0005707637,0.0021157954,0.0020128826,0.0027698448],"genre_scores_gemma":[0.38851312,0.0017328258,0.60314995,0.00008192861,0.00003348772,0.0011023916,0.0015045522,0.0007309408,0.0031508326],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999383,0.0001923427,0.00008411194,0.00017203286,0.0001385254,0.000029930887],"domain_scores_gemma":[0.9987935,0.00031480816,0.00032722947,0.00021140886,0.00028853037,0.000064579996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018062287,0.00087726087,0.00055735896,0.003430745,0.0006410925,0.0012045589,0.00066182704,0.0006847819,0.003359564],"category_scores_gemma":[0.0057263793,0.00033036145,0.00087388343,0.0020832731,0.0005327828,0.000596016,0.00097133784,0.0005303106,0.00069081236],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006342865,0.000121127865,0.09855151,0.0013146069,0.0009027624,0.0016220467,0.0019282473,0.024539562,0.23378542,0.007020677,0.0035303547,0.62604946],"study_design_scores_gemma":[0.00006085415,0.0019814793,0.5261534,0.00049351197,0.0009520579,0.014520876,0.0018875015,0.21721773,0.17445028,0.026824063,0.035158537,0.00029965834],"about_ca_topic_score_codex":0.0060539544,"about_ca_topic_score_gemma":0.015335583,"teacher_disagreement_score":0.0060539544,"about_ca_system_score_codex":0.00065782166,"about_ca_system_score_gemma":0.0012689722,"threshold_uncertainty_score":0.012037456},"labels":[],"label_agreement":null},{"id":"W2608872009","doi":"10.1093/schbul/sbx049","title":"Sex and Diffusion Tensor Imaging of White Matter in Schizophrenia: A Systematic Review Plus Meta-analysis of the Corpus Callosum","year":2017,"lang":"en","type":"review","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Centre of Excellence for Child and Youth Mental Health; University of Toronto; Western University; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Health Canada; National Institutes of Health","keywords":"Corpus callosum; Splenium; Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Meta-analysis; Diffusion MRI; Psychology; Neuropathology; Clinical psychology; Medicine; Psychiatry; Disease; Neuroscience; Pathology; Magnetic resonance imaging","score_opus":0.11040003168301936,"score_gpt":0.37133684010968426,"score_spread":0.2609368084266649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608872009","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003415266,0.99565107,0.00024021893,0.00018305086,0.00008047125,0.000074733485,0.0002334436,0.000008760353,0.00011298062],"genre_scores_gemma":[0.11598752,0.8804248,0.0017198517,0.0004740663,0.00026667348,0.00044692194,0.00050666777,0.000018296058,0.00015530855],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9924476,0.0036422655,0.0021320963,0.0007444378,0.0007778729,0.00025573437],"domain_scores_gemma":[0.9820472,0.012761822,0.0029599562,0.00065894495,0.0013417688,0.00023035283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013059312,0.0021304414,0.011501311,0.006506202,0.0006740691,0.0028819866,0.0012886702,0.001749369,0.0022114527],"category_scores_gemma":[0.031509317,0.0012095568,0.03028435,0.0071416358,0.0006175016,0.0015225607,0.0013838506,0.0013614369,0.00021081389],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016913014,0.000034128298,0.011940085,0.35109493,0.60266036,0.00024276845,0.00014307891,0.0005533859,0.0004318924,0.00019479061,0.0010291283,0.029984144],"study_design_scores_gemma":[0.00043560105,0.00021661153,0.013108192,0.03726263,0.945806,0.0002382779,0.000062855775,0.0001783338,0.0001590895,0.00032969314,0.0021687602,0.000033926455],"about_ca_topic_score_codex":0.006948318,"about_ca_topic_score_gemma":0.016381098,"teacher_disagreement_score":0.013059312,"about_ca_system_score_codex":0.0020752165,"about_ca_system_score_gemma":0.0046482375,"threshold_uncertainty_score":0.069065094},"labels":[],"label_agreement":null},{"id":"W2609432052","doi":"10.1002/sim.7300","title":"Constructing longitudinal disease progression curves using sparse, short‐term individual data with an application to Alzheimer's disease","year":2017,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Department of Health, Government of Western Australia; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; University of Southern California; F. Hoffmann-La Roche; Australian Government; Novartis Pharmaceuticals Corporation; Government of Western Australia; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Australian Institute of Health and Welfare, Australian Government; Foundation for the National Institutes of Health","keywords":"Term (time); Trajectory; Construct (python library); Regression; Computer science; Longitudinal data; Disease; Regression analysis; Statistics; Algorithm; Mathematics; Applied mathematics; Machine learning; Medicine; Data mining; Pathology","score_opus":0.2365476554198065,"score_gpt":0.48871271654198184,"score_spread":0.25216506112217535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2609432052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09368449,0.00028023202,0.904322,0.0003072903,0.000021401765,0.00011510728,0.00033347745,0.0005167742,0.00041926425],"genre_scores_gemma":[0.5495142,0.0005056954,0.44766057,0.000076611825,0.000027758475,0.00024716355,0.0010025135,0.00016139784,0.00080413016],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971283,0.0018792021,0.00012865434,0.00040588286,0.00035996595,0.00009806604],"domain_scores_gemma":[0.97205293,0.020446666,0.0025283983,0.0031068716,0.0015628062,0.00030220515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011088007,0.00060372864,0.0007400894,0.0016970607,0.0005732649,0.0011725371,0.0012599701,0.0011977553,0.0012826596],"category_scores_gemma":[0.04872779,0.0005450719,0.0016428712,0.0021027036,0.00083952997,0.0015163168,0.001583755,0.0018180808,0.00041136175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025863256,0.00014438282,0.030876556,0.00031837964,0.00027689835,0.00026166064,0.0014898926,0.77173495,0.0035968476,0.025288355,0.0008538575,0.16489957],"study_design_scores_gemma":[0.000020650852,0.0001605863,0.010223957,0.00006936382,0.00003444411,0.00014558114,0.00018393286,0.96258074,0.0012751501,0.022883287,0.0023402611,0.00008209865],"about_ca_topic_score_codex":0.011049513,"about_ca_topic_score_gemma":0.0103985155,"teacher_disagreement_score":0.011088007,"about_ca_system_score_codex":0.0008395015,"about_ca_system_score_gemma":0.0015067841,"threshold_uncertainty_score":0.058639705},"labels":[],"label_agreement":null},{"id":"W2609585001","doi":"10.1097/md.0000000000006703","title":"Correlation between prefrontal-striatal pathway impairment and cognitive impairment in patients with leukoaraiosis","year":2017,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Leukoaraiosis; Fractional anisotropy; Diffusion MRI; Medicine; Corpus callosum; Hyperintensity; Montreal Cognitive Assessment; Internal capsule; Neuropsychology; Magnetic resonance imaging; Cardiology; Internal medicine; Pathology; Cognition; Cognitive impairment; Radiology; Psychiatry","score_opus":0.03408362052617913,"score_gpt":0.3183947547624304,"score_spread":0.28431113423625126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2609585001","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993401,0.0002750352,0.00004901024,0.000030375104,0.0000026664086,0.000004702823,0.000037875867,0.0000035763,0.00025671767],"genre_scores_gemma":[0.9997378,0.00008606827,0.00005115274,0.000013048782,0.000006557236,0.000002149386,0.000050559254,6.777083e-7,0.000052063933],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998141,0.000036550107,0.00003483132,0.0000535342,0.000030178422,0.000030920255],"domain_scores_gemma":[0.99930537,0.00008525228,0.00037103365,0.000029630452,0.00007911927,0.00012956362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030561307,0.0004745742,0.000429125,0.0010596501,0.00053271296,0.00046868582,0.00023699946,0.00042356466,0.0012288088],"category_scores_gemma":[0.0012901034,0.0002651671,0.00018676226,0.00055322534,0.0003239188,0.0003476297,0.00033768747,0.00037998977,0.00013227815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023254124,0.00005296275,0.99523526,0.000018119235,0.000050695257,0.0011561048,0.000117612755,0.00005341949,0.0011480787,0.000018452713,0.00004422562,0.0018725612],"study_design_scores_gemma":[0.0000106388,0.00012877904,0.9962717,0.000006769369,0.000034640318,0.0029772234,0.00015725414,0.00015182405,0.00010881369,0.000053669217,0.00009445796,0.000004349544],"about_ca_topic_score_codex":0.0023152637,"about_ca_topic_score_gemma":0.0036666356,"teacher_disagreement_score":0.0023152637,"about_ca_system_score_codex":0.00019908269,"about_ca_system_score_gemma":0.00020465185,"threshold_uncertainty_score":0.0046036243},"labels":[],"label_agreement":null},{"id":"W2610161052","doi":"10.1002/hbm.23624","title":"Age‐related mapping of intracortical myelin from late adolescence to middle adulthood using T<sub>1</sub>‐weighted MRI","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McGill University; Douglas Mental Health University Institute; McMaster University","funders":"","keywords":"White matter; Neuroscience; Premotor cortex; Psychology; Magnetic resonance imaging; Cortex (anatomy); Myelin; Trajectory; Ventromedial prefrontal cortex; Prefrontal cortex; Medicine; Physics; Central nervous system; Anatomy; Cognition; Radiology","score_opus":0.1049593143279976,"score_gpt":0.34335855877965493,"score_spread":0.23839924445165733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610161052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99184096,0.000845285,0.0062898644,0.00003619513,0.000004247438,0.0000074482396,0.0002660769,0.000042427848,0.0006674538],"genre_scores_gemma":[0.9951292,0.00047876948,0.003816155,0.000010630381,0.000005406541,0.000005542513,0.00020393851,0.0000133589265,0.00033691534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99996305,0.0000071209643,0.000001993648,0.00001609358,0.0000053390963,0.000006339971],"domain_scores_gemma":[0.9998118,0.00003523795,0.000090787486,0.000013852701,0.000026864256,0.000021430373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024367364,0.00022446517,0.000087238215,0.00066565024,0.00009288232,0.00023571876,0.00010726893,0.0001470039,0.0005273819],"category_scores_gemma":[0.0005551393,0.00008813047,0.00008882492,0.0003835345,0.00014131497,0.00022213215,0.00014656791,0.00012294979,0.00015334132],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084192335,0.00007180316,0.63800305,0.0001687826,0.00020360232,0.0005068804,0.00073119666,0.0023806302,0.24476857,0.00047863732,0.00075792364,0.11108709],"study_design_scores_gemma":[0.0000031227553,0.0001477721,0.989042,0.0000110940855,0.0000279017,0.00054151134,0.00012808174,0.0026369002,0.006659525,0.00028725923,0.0005074159,0.0000075089747],"about_ca_topic_score_codex":0.0035145683,"about_ca_topic_score_gemma":0.008535348,"teacher_disagreement_score":0.0035145683,"about_ca_system_score_codex":0.00012139201,"about_ca_system_score_gemma":0.00014990984,"threshold_uncertainty_score":0.0069882274},"labels":[],"label_agreement":null},{"id":"W2610383986","doi":"10.1111/bdi.12489","title":"Longitudinal differences in white matter integrity in youth at high familial risk for bipolar disorder","year":2017,"lang":"en","type":"article","venue":"Bipolar Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Seventh Framework Programme; University of Edinburgh; Scottish Funding Council; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Royal College of Physicians; Health Foundation; Fonds de Recherche du Québec-Société et Culture; Dr Mortimer and Theresa Sackler Foundation; Brain and Behavior Research Foundation; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Bipolar disorder; Psychology; White matter; Clinical psychology; Psychiatry; Medicine; Mood; Magnetic resonance imaging","score_opus":0.05621888127931756,"score_gpt":0.3247170914896752,"score_spread":0.26849821021035764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610383986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999754,0.00005723478,0.000020627032,0.000011161949,0.0000011955868,0.0000017073189,0.000069678346,0.0000014523529,0.000082947656],"genre_scores_gemma":[0.99958426,0.000048749254,0.00004833608,0.0000070269816,0.0000020782081,0.00000275472,0.0002087385,0.0000010528682,0.0000971328],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998497,0.000028497772,0.000014166052,0.000034805893,0.000031736457,0.00004112529],"domain_scores_gemma":[0.99934727,0.000056772446,0.00032940088,0.00003866047,0.000109343186,0.00011846846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000494075,0.00021066058,0.00020878851,0.0006491554,0.00046911486,0.0005083241,0.00016310581,0.00033129475,0.0009834676],"category_scores_gemma":[0.0013361896,0.00018914395,0.00022230209,0.00043165166,0.00019396294,0.00025934065,0.00029967204,0.00044062265,0.00016054306],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080464946,0.000026653446,0.99768984,0.0000027844044,0.000021660338,0.00011265988,0.00027960492,0.000017972676,0.00062726496,0.00000930062,0.000044450913,0.001087319],"study_design_scores_gemma":[0.0000012645107,0.000032925258,0.9996784,0.0000017882836,0.000005774286,0.00009541834,0.000094019866,0.000020076524,0.000037770067,0.0000056438657,0.000026205209,7.0432395e-7],"about_ca_topic_score_codex":0.0115603395,"about_ca_topic_score_gemma":0.018003134,"teacher_disagreement_score":0.0115603395,"about_ca_system_score_codex":0.00025049443,"about_ca_system_score_gemma":0.00019617386,"threshold_uncertainty_score":0.022986114},"labels":[],"label_agreement":null},{"id":"W2611301338","doi":"10.1002/mrm.26711","title":"Choice of reference measurements affects quantification of long diffusion time behaviour using stimulated echoes","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"Medical Research Council; Cancer Research UK; Wellcome Trust; Wellcome","keywords":"Diffusion; Nuclear magnetic resonance; Diffusion MRI; Effective diffusion coefficient; Chemistry; Magnetic resonance imaging; Physics; Thermodynamics; Radiology; Medicine","score_opus":0.2281639196815763,"score_gpt":0.4299483690553256,"score_spread":0.2017844493737493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611301338","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72908854,0.0063312957,0.26077724,0.0003282527,0.00015766597,0.00007810289,0.000227492,0.0008444473,0.0021669453],"genre_scores_gemma":[0.91057724,0.0015564587,0.085624725,0.00021004368,0.00003588294,0.00013907316,0.0003329974,0.0005403396,0.0009831063],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978155,0.0009098473,0.00016776,0.00050146785,0.0004952258,0.000110303976],"domain_scores_gemma":[0.99239993,0.0049057757,0.0008540132,0.00083362794,0.0008573327,0.00014926924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004195563,0.00091430574,0.00048630082,0.0005211453,0.00038687745,0.0012268189,0.00079044123,0.0009978603,0.000986745],"category_scores_gemma":[0.019146867,0.0005034481,0.00026925726,0.0005753074,0.001068235,0.0013241482,0.0009952926,0.00074224646,0.00036707934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005507634,0.000054706106,0.003382401,0.00037460105,0.00006381413,0.00029819438,0.00024194646,0.0030731056,0.9725281,0.0013423848,0.00019553117,0.017894492],"study_design_scores_gemma":[0.000030015079,0.00059902517,0.009624361,0.000055786444,0.0001071189,0.00069441495,0.00007780598,0.016413625,0.9684683,0.0012056464,0.002668054,0.0000558678],"about_ca_topic_score_codex":0.0008480521,"about_ca_topic_score_gemma":0.0008788929,"teacher_disagreement_score":0.004195563,"about_ca_system_score_codex":0.0005648892,"about_ca_system_score_gemma":0.00046522505,"threshold_uncertainty_score":0.022188485},"labels":[],"label_agreement":null},{"id":"W2611398135","doi":"","title":"Reducing Invalid Connections with Microstructure-Driven Tractography","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; Streamlines, streaklines, and pathlines; White matter; Computer science; Artificial intelligence; Neuroscience; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Psychology; Physics; Radiology; Medicine","score_opus":0.030784716112358022,"score_gpt":0.2849209317116451,"score_spread":0.2541362155992871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611398135","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015849298,0.00025171452,0.9818424,0.00035629302,0.00008582209,0.000036936828,0.00013604113,0.0010534745,0.0003880681],"genre_scores_gemma":[0.41729158,0.00059166906,0.5749064,0.00031686653,0.00029916922,0.00017597048,0.0012803206,0.0011974033,0.003940582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975375,0.00074729015,0.00015703165,0.0004377733,0.0009461193,0.00017430341],"domain_scores_gemma":[0.9813976,0.011077609,0.0015087754,0.0030805005,0.002413236,0.00052234164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031728563,0.0020900965,0.0025875745,0.002367949,0.001279004,0.002199822,0.0024168224,0.004058763,0.0039288797],"category_scores_gemma":[0.038511824,0.0016826246,0.0016603115,0.0022779484,0.0015141626,0.0035061399,0.0034784141,0.003230603,0.0012774573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011423284,0.00018171548,0.0042742784,0.00063776056,0.00047947248,0.00086630107,0.00041207793,0.5832677,0.027967615,0.0451805,0.0105807725,0.32500952],"study_design_scores_gemma":[0.000028613993,0.00004598115,0.00049602723,0.00001812954,0.000033304743,0.00021608792,0.00001768417,0.95381725,0.004932185,0.039130956,0.0012450648,0.000018698238],"about_ca_topic_score_codex":0.006852933,"about_ca_topic_score_gemma":0.012432803,"teacher_disagreement_score":0.006852933,"about_ca_system_score_codex":0.0012938775,"about_ca_system_score_gemma":0.0032461965,"threshold_uncertainty_score":0.0167799},"labels":[],"label_agreement":null},{"id":"W2612184340","doi":"10.1007/s11538-017-0271-8","title":"A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread","year":2017,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; Alberta Cancer Foundation; American Brain Tumor Association","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Anisotropy; Magnetic resonance imaging; Fiber tract; Tractography; Anisotropic diffusion; Grey matter; Physics; Glioma; Neuroscience; Nuclear magnetic resonance; Pathology; Medicine; Biology; Radiology; Optics","score_opus":0.07374728929369659,"score_gpt":0.3533821802579183,"score_spread":0.27963489096422167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612184340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052892074,0.0025629322,0.93448883,0.0034302562,0.00025573422,0.000119761615,0.0012461571,0.00041119108,0.004593106],"genre_scores_gemma":[0.89328575,0.004250911,0.07026436,0.0006935224,0.0004070281,0.00040696483,0.0014860177,0.00028710376,0.028918343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996388,0.00012342252,0.000023106935,0.00009770809,0.000064560234,0.000052394025],"domain_scores_gemma":[0.99879646,0.000622708,0.00019379037,0.00007341549,0.0002121325,0.0001014082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010829191,0.0012917356,0.0015500003,0.0010669256,0.0004621304,0.0016096114,0.0021930304,0.0045625134,0.0019112108],"category_scores_gemma":[0.0048549566,0.0010163762,0.0014054807,0.0015168685,0.001055992,0.0015555723,0.001101758,0.0024825449,0.00084356824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007917427,0.00003708566,0.0011658127,0.00009571367,0.000062717365,0.00055695465,0.00010597883,0.9606842,0.0021734536,0.026204335,0.0020125273,0.0068220575],"study_design_scores_gemma":[0.000020923293,0.000018321973,0.00029254917,0.000009903324,0.000031927557,0.00021251196,0.000010506975,0.99377316,0.0001615069,0.0048052836,0.0006429422,0.000020384956],"about_ca_topic_score_codex":0.020250997,"about_ca_topic_score_gemma":0.012203762,"teacher_disagreement_score":0.020250997,"about_ca_system_score_codex":0.001356854,"about_ca_system_score_gemma":0.0015967983,"threshold_uncertainty_score":0.040266275},"labels":[],"label_agreement":null},{"id":"W2612583120","doi":"10.1042/cs20170146","title":"Using DTI to assess white matter microstructure in cerebral small vessel disease (SVD) in multicentre studies","year":2017,"lang":"en","type":"article","venue":"Clinical Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NIHR Newcastle Biomedical Research Centre; University of Cambridge; Cambridge University Hospitals; Stroke Association; British Heart Foundation; National Institute for Health and Care Research","keywords":"Hyperintensity; Fractional anisotropy; White matter; Diffusion MRI; Neuropsychology; Montreal Cognitive Assessment; Cognition; Medicine; Psychology; Internal medicine; Magnetic resonance imaging; Radiology; Cognitive impairment; Neuroscience","score_opus":0.4690996578450013,"score_gpt":0.5580194649050302,"score_spread":0.08891980706002889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612583120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98853904,0.0032099264,0.0059530875,0.00012695874,0.00006197621,0.000453693,0.00067119487,0.000032540655,0.00095152477],"genre_scores_gemma":[0.98966134,0.00050694065,0.008516861,0.00006378761,0.000044383807,0.00050481403,0.00057494984,0.000015905938,0.000111082714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9806991,0.012457551,0.0030748604,0.0022187326,0.0011347842,0.0004149261],"domain_scores_gemma":[0.97569627,0.00599761,0.009842024,0.005021385,0.0023717692,0.0010710771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038788456,0.0010112402,0.0012364656,0.005646075,0.0010515657,0.0020308576,0.0011834183,0.0009120791,0.00043789338],"category_scores_gemma":[0.045152765,0.00069937384,0.0018260448,0.006090766,0.00092368387,0.0014563036,0.0024106014,0.0007017864,0.00010783146],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010995208,0.00008092087,0.98010224,0.00023483594,0.003072551,0.00016526286,0.0007886115,0.00059847935,0.0012998616,0.00016478931,0.00030381887,0.012089062],"study_design_scores_gemma":[0.00008359368,0.0006488007,0.9959086,0.00006682407,0.00076507573,0.00022934057,0.00022041443,0.0008707061,0.000318608,0.00028880156,0.0005700206,0.000029230969],"about_ca_topic_score_codex":0.0063158367,"about_ca_topic_score_gemma":0.0153786065,"teacher_disagreement_score":0.038788456,"about_ca_system_score_codex":0.0008873127,"about_ca_system_score_gemma":0.0009631705,"threshold_uncertainty_score":0.2051354},"labels":[],"label_agreement":null},{"id":"W2613834872","doi":"10.1016/j.neuroimage.2017.05.012","title":"Concurrent white matter bundles and grey matter networks using independent component analysis","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; McDonnell Center for Systems Neuroscience; NIH Blueprint for Neuroscience Research; Sackler Institute for Translational Neurodevelopment, King's College London; Medical Research Council Canada; National Institutes of Health; King's College London","keywords":"White matter; Tractography; Grey matter; Diffusion MRI; Neuroscience; Artificial intelligence; Pattern recognition (psychology); Computer science; Component (thermodynamics); Independent component analysis; Brain mapping; Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.20894823415073066,"score_gpt":0.43722122718067336,"score_spread":0.2282729930299427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613834872","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027834333,0.9961355,0.001836573,0.00032045157,0.00010724646,0.000015003265,0.000032321645,0.000025687654,0.001248904],"genre_scores_gemma":[0.002716126,0.9936992,0.002344241,0.00011656817,0.00019274511,0.000026815687,0.00009921706,0.000007227966,0.0007979134],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99970263,0.000045552242,0.000048044076,0.00008515898,0.00010208509,0.00001641519],"domain_scores_gemma":[0.99945706,0.00023096622,0.00009520309,0.000024476958,0.00015912652,0.000033098],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010106879,0.0013360357,0.0014936045,0.0051164567,0.00026993817,0.001442296,0.0012629981,0.001220375,0.0029089774],"category_scores_gemma":[0.0015300645,0.0004846208,0.00093715213,0.0032897508,0.0009860167,0.002055431,0.0008755249,0.0014265418,0.0018774994],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036492038,0.000034940298,0.0005156979,0.013285222,0.00022974769,0.00021671692,0.000088537105,0.0009124119,0.0011148283,0.0070614605,0.008340709,0.96816325],"study_design_scores_gemma":[0.000039351493,0.00016128326,0.007774642,0.00836867,0.00065810216,0.005842017,0.00021173149,0.0022561776,0.0032393,0.029767746,0.9415209,0.00016008844],"about_ca_topic_score_codex":0.002812875,"about_ca_topic_score_gemma":0.0035390495,"teacher_disagreement_score":0.0051164567,"about_ca_system_score_codex":0.0008674717,"about_ca_system_score_gemma":0.0017016869,"threshold_uncertainty_score":0.009731472},"labels":[],"label_agreement":null},{"id":"W2614686673","doi":"10.1007/s11060-017-2462-4","title":"Analysis of surgical and MRI factors associated with cerebellar mutism","year":2017,"lang":"en","type":"article","venue":"Journal of Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster Children's Hospital; Impact; McMaster University","funders":"","keywords":"Medicine; Calcification; Odds ratio; Medulloblastoma; Pathological; Pilocytic astrocytoma; Magnetic resonance imaging; Ventricle; Hemosiderin; Cohort; Fourth ventricle; Radiology; Astrocytoma; Surgery; Internal medicine; Pathology; Glioma","score_opus":0.08692544639285024,"score_gpt":0.39442740323993564,"score_spread":0.30750195684708537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614686673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987023,0.00029450224,0.00012139451,0.000050348906,0.000009456932,0.000004957188,0.00014811213,0.0000052512964,0.00066371285],"genre_scores_gemma":[0.9996191,0.00007462513,0.000054426608,0.000007778875,0.000013724949,0.00000238259,0.00009033974,0.0000021214003,0.0001354374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959654,0.000086385924,0.000073888026,0.000076268974,0.00007050284,0.00009643049],"domain_scores_gemma":[0.99756646,0.0006842465,0.0010050868,0.000120093755,0.0001856513,0.00043852878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003395288,0.00034673885,0.00034015081,0.0017463737,0.00049795076,0.00056710077,0.00043011652,0.0005175999,0.0030389994],"category_scores_gemma":[0.0029435628,0.00022409287,0.00059415336,0.0015648364,0.00054129085,0.0005435476,0.0003639818,0.0005693069,0.00033614764],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001645452,0.000029105011,0.9978527,0.0000066284274,0.000042763524,0.0005452331,0.000023478759,0.00004253441,0.00030077586,0.000017559572,0.000042285752,0.0009325478],"study_design_scores_gemma":[0.000003275971,0.00012385979,0.99709606,0.000004816426,0.000054469965,0.0018530617,0.00024861857,0.0002627634,0.00015967865,0.00004865499,0.00013901477,0.000005676826],"about_ca_topic_score_codex":0.0029945327,"about_ca_topic_score_gemma":0.0031105147,"teacher_disagreement_score":0.0030389994,"about_ca_system_score_codex":0.00031929705,"about_ca_system_score_gemma":0.00071057485,"threshold_uncertainty_score":0.010166466},"labels":[],"label_agreement":null},{"id":"W2615056316","doi":"10.1371/journal.pone.0177466","title":"Exploring the role of white matter connectivity in cortex maturation","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Connectomics; White matter; Neuroscience; Diffusion MRI; Connectome; Biology; Cerebral cortex; Sensory system; Brain development; Functional connectivity; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.20100170113064128,"score_gpt":0.3231630553389885,"score_spread":0.1221613542083472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615056316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95226663,0.00049012416,0.044846576,0.00027105332,0.0000068714853,0.000016200165,0.000107695174,0.00006657579,0.0019281887],"genre_scores_gemma":[0.9899311,0.00034161785,0.009441682,0.000014749047,0.0000058770697,0.0000148439585,0.00005287275,0.0000099172485,0.00018723917],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999236,0.000027324731,0.0000030061865,0.000026785827,0.000007913073,0.0000114453605],"domain_scores_gemma":[0.99961436,0.00021589235,0.00009333757,0.000025129757,0.000016067743,0.000035229783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000340437,0.0002172737,0.00015006817,0.00037474776,0.00015597223,0.0005503081,0.00026237886,0.00036214822,0.0006967142],"category_scores_gemma":[0.0020028308,0.00013977342,0.00023612026,0.00028930564,0.00044815667,0.0011025975,0.00038331904,0.00033537092,0.00008093715],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054139417,0.00015590843,0.1377026,0.0005506842,0.00030894356,0.0012409405,0.0012858852,0.11472578,0.54276913,0.09576032,0.00058112066,0.104377255],"study_design_scores_gemma":[0.000028146953,0.0005259388,0.30180076,0.000070678885,0.0001684778,0.0008802091,0.0004993332,0.50707304,0.06677217,0.119496316,0.0026132315,0.0000716655],"about_ca_topic_score_codex":0.0013414992,"about_ca_topic_score_gemma":0.001284776,"teacher_disagreement_score":0.0013414992,"about_ca_system_score_codex":0.00025617686,"about_ca_system_score_gemma":0.00037146528,"threshold_uncertainty_score":0.002667427},"labels":[],"label_agreement":null},{"id":"W2615393412","doi":"10.1097/wnr.0000000000000813","title":"Radiation-induced cerebellar–cerebral functional connectivity alterations in nasopharyngeal carcinoma patients","year":2017,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Task-positive network; Cerebellum; Neuroscience; Superior frontal gyrus; Middle frontal gyrus; Nasopharyngeal carcinoma; Cognition; Medicine; Montreal Cognitive Assessment; Default mode network; Psychology; Radiation therapy; Cognitive impairment; Internal medicine","score_opus":0.08435529029233034,"score_gpt":0.3428243763137724,"score_spread":0.25846908602144203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615393412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999228,0.00023229241,0.00010879044,0.000018852463,0.0000025001775,0.000011186909,0.00009534098,0.000004305138,0.0002987898],"genre_scores_gemma":[0.99971026,0.00007052196,0.00005909894,0.0000066508314,0.0000022913089,0.0000062669383,0.000080160135,0.000001055268,0.00006364988],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998927,0.000018584327,0.000010329117,0.000040330095,0.000018529377,0.000019492152],"domain_scores_gemma":[0.99980766,0.000022374386,0.00010731872,0.000014119587,0.000023393388,0.00002522741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011064483,0.0002596722,0.00027898396,0.00038300068,0.0003070397,0.00025439108,0.0001745976,0.00023451897,0.0010239419],"category_scores_gemma":[0.0008887342,0.0001164287,0.00022539572,0.00037771894,0.00019805877,0.00022688994,0.000232599,0.00019594484,0.00008751026],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009459297,0.00010034556,0.9607093,0.00010524823,0.0002971389,0.0030168549,0.00054703833,0.0004419329,0.014934153,0.00011704987,0.00025155567,0.018533444],"study_design_scores_gemma":[0.000009138449,0.00011920838,0.9975635,0.0000037391555,0.000052683925,0.0012036387,0.0001215162,0.00023109015,0.0004492343,0.000060035214,0.00018113409,0.0000049995506],"about_ca_topic_score_codex":0.00825868,"about_ca_topic_score_gemma":0.015953874,"teacher_disagreement_score":0.00825868,"about_ca_system_score_codex":0.00039270724,"about_ca_system_score_gemma":0.000295921,"threshold_uncertainty_score":0.016421199},"labels":[],"label_agreement":null},{"id":"W2615453098","doi":"10.1161/str.47.suppl_1.wmp40","title":"Abstract WMP40: Intra-arterial Mesenchymal Stem Cells in a Large Animal Endovascular Canine Stroke Model: Findings on Serial Diffusion Tensor Imaging","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Adidas (Canada)","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; White matter; Effective diffusion coefficient; Stroke (engine); Stroke recovery; Magnetic resonance imaging; Pathology; Nuclear medicine; Radiology","score_opus":0.025339264564449158,"score_gpt":0.28994046482040026,"score_spread":0.2646012002559511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615453098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941117,0.00081843726,0.0028826466,0.00023065033,0.000085369036,0.00010794457,0.0006349914,0.00012630402,0.0010019754],"genre_scores_gemma":[0.9828545,0.0012885532,0.0042558727,0.00013490078,0.000052228872,0.0003429321,0.0021149516,0.000053455617,0.008902547],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979335,0.000018651868,0.0000207249,0.00006197451,0.00005627061,0.000049032467],"domain_scores_gemma":[0.9997882,0.000015336778,0.000065708475,0.000021899454,0.00002602587,0.000082905965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038967832,0.00063953514,0.00038658085,0.0007487351,0.0002139763,0.00030237867,0.00025503826,0.0005539287,0.0026318994],"category_scores_gemma":[0.00017665046,0.00018650031,0.0002721253,0.00021395324,0.0005770601,0.0004019507,0.00020155862,0.0008176017,0.0007088134],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001286807,0.0010224615,0.00075224746,0.00014608595,0.000030044248,0.00048574398,0.00012823238,0.00017609015,0.99033165,0.0002729263,0.0005993675,0.0047684247],"study_design_scores_gemma":[0.0002773289,0.01684304,0.014014105,0.000059519203,0.00016023235,0.0029155277,0.00021742129,0.002796596,0.951274,0.00032874628,0.011086254,0.000027192425],"about_ca_topic_score_codex":0.0009449359,"about_ca_topic_score_gemma":0.0011620396,"teacher_disagreement_score":0.0026318994,"about_ca_system_score_codex":0.0003739029,"about_ca_system_score_gemma":0.00028569682,"threshold_uncertainty_score":0.008804619},"labels":[],"label_agreement":null},{"id":"W2619324736","doi":"10.1007/978-3-319-59448-4_4","title":"Cartan Frames for Heart Wall Fiber Motion","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Motion (physics); Frame (networking); Fiber; Artificial intelligence; Mechanics; Computer vision; Physics; Materials science; Telecommunications","score_opus":0.05562735939141506,"score_gpt":0.3494575874783898,"score_spread":0.29383022808697473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619324736","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017959174,0.0023290478,0.9824426,0.0002446427,0.00061150495,0.000030823543,0.00038352126,0.001417222,0.010744654],"genre_scores_gemma":[0.03366797,0.0057564527,0.917703,0.00022371311,0.00084283686,0.000100601515,0.0015200484,0.0012483441,0.03893709],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997967,0.00003757409,0.000011491657,0.000054063614,0.00008293032,0.000017313254],"domain_scores_gemma":[0.9996977,0.00008066803,0.000022327677,0.000070529815,0.00010799848,0.000020945648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004913487,0.0012383868,0.00059479586,0.0012455786,0.00042582286,0.0013001411,0.0008524464,0.0010344534,0.018125974],"category_scores_gemma":[0.0012979469,0.0004788536,0.0005376583,0.001249137,0.00041731796,0.0013510089,0.0008318068,0.0013368961,0.008446853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008918796,0.000023433571,0.00015235876,0.00028490165,0.00003871875,0.00013520192,0.00014396067,0.013249764,0.016980516,0.16891275,0.057014003,0.74297523],"study_design_scores_gemma":[0.000026216414,0.00009712899,0.0011519298,0.00024586587,0.00006287084,0.00060942373,0.00010997637,0.44787255,0.02110436,0.17256431,0.3560704,0.000085020445],"about_ca_topic_score_codex":0.002334595,"about_ca_topic_score_gemma":0.003906541,"teacher_disagreement_score":0.018125974,"about_ca_system_score_codex":0.00035701558,"about_ca_system_score_gemma":0.00045059877,"threshold_uncertainty_score":0.060637474},"labels":[],"label_agreement":null},{"id":"W2619834707","doi":"10.1016/j.neuroimage.2017.05.052","title":"Brain grey and white matter predictors of verbal ability traits in older age: The Lothian Birth Cohort 1936","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Medical Research Council; Directorate for Biological Sciences; Centre for Cognitive Ageing and Cognitive Epidemiology; University of Edinburgh; Scottish Funding Council; Age UK; Medical Research Council Canada; Wellcome Trust","keywords":"Psychology; Grey matter; Fractional anisotropy; White matter; Cognition; Developmental psychology; Cognitive psychology; Semantic memory; Brain size; Arcuate fasciculus; Audiology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.029191684035404775,"score_gpt":0.3194922356273708,"score_spread":0.290300551591966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619834707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991505,0.0001213463,0.000039069713,0.00005237273,0.000003324871,0.0000029001424,0.00037155524,0.0000021278038,0.00025668857],"genre_scores_gemma":[0.9991498,0.00006621217,0.000048139333,0.000026894337,0.0000063489006,0.000006204757,0.000343564,0.0000015937869,0.00035121365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998727,0.000022663407,0.000011670884,0.000040590356,0.000027104119,0.000025248883],"domain_scores_gemma":[0.9995117,0.00007014624,0.00018199046,0.00006579031,0.00006565517,0.00010475669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053453184,0.00025068055,0.00027014903,0.000704358,0.00049258105,0.0004441521,0.00030908122,0.0005100821,0.0020047266],"category_scores_gemma":[0.00093308976,0.00030551493,0.00040869828,0.00066035555,0.0003105421,0.00035840573,0.00038038244,0.00046787964,0.000309223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097345335,0.00002466252,0.9975406,0.0000055097685,0.0000672796,0.00013929867,0.00034106852,0.00003562013,0.00068470166,0.000044071905,0.00017802646,0.0008418859],"study_design_scores_gemma":[0.0000017501159,0.000012223495,0.9997563,0.0000017823886,0.0000074390528,0.00004364488,0.00005864335,0.000048286525,0.000014245334,0.000009836711,0.000044405853,0.0000013768505],"about_ca_topic_score_codex":0.046484906,"about_ca_topic_score_gemma":0.0526372,"teacher_disagreement_score":0.046484906,"about_ca_system_score_codex":0.00035354056,"about_ca_system_score_gemma":0.00022806092,"threshold_uncertainty_score":0.092428684},"labels":[],"label_agreement":null},{"id":"W2619945508","doi":"","title":"Microstructure driven tractography in the human brain","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Human brain; Fascicle; Magnetic resonance imaging; Axon; Neocortex; Neuroimaging; Neuroscience; Nuclear magnetic resonance; Computer science; Anatomy; Physics; Psychology; Biology; Medicine; Radiology","score_opus":0.030523102029129626,"score_gpt":0.3074304985296007,"score_spread":0.2769073965004711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619945508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22548634,0.004891098,0.7552874,0.0031465306,0.00024296343,0.000060978535,0.00092313375,0.001680806,0.008280716],"genre_scores_gemma":[0.8689225,0.0037367358,0.116479725,0.0002513567,0.00030687128,0.00003842428,0.00036815053,0.000427268,0.009468884],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991715,0.000027920489,0.0000031585587,0.000025633648,0.000020202817,0.000006063805],"domain_scores_gemma":[0.9995382,0.00026003894,0.000059071528,0.000039923925,0.00006671414,0.000036092966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004251281,0.00025257366,0.00028463732,0.0005808023,0.00017397258,0.0010294484,0.00030142826,0.0008169229,0.0023620888],"category_scores_gemma":[0.0026848759,0.00025941883,0.0003137262,0.00069913425,0.0005214362,0.0007172002,0.00037991515,0.0004094449,0.00042532306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054011337,0.000084646985,0.0086945025,0.00093562756,0.0003405794,0.0015331703,0.00073676085,0.33855423,0.2173169,0.13724269,0.011979048,0.2820417],"study_design_scores_gemma":[0.000039672104,0.000116871095,0.03149581,0.00008723548,0.00006309017,0.0016711048,0.000082219995,0.7046534,0.024126017,0.22622399,0.011355665,0.000084970015],"about_ca_topic_score_codex":0.0032034318,"about_ca_topic_score_gemma":0.004913932,"teacher_disagreement_score":0.0032034318,"about_ca_system_score_codex":0.0004631483,"about_ca_system_score_gemma":0.0008755862,"threshold_uncertainty_score":0.007902026},"labels":[],"label_agreement":null},{"id":"W2620158492","doi":"10.1136/bjsports-2016-097270.86","title":"Eye movement and white matter integrity in patients with post-concussion syndrome","year":2017,"lang":"en","type":"article","venue":"British Journal of Sports Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University Health Network; Toronto Western Hospital; Hospital for Sick Children; Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"White matter; Uncinate fasciculus; Superior longitudinal fasciculus; Fractional anisotropy; Diffusion MRI; Tractography; Psychology; Cingulum (brain); Physical medicine and rehabilitation; Medicine; Audiology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.015165644709323564,"score_gpt":0.29299318400881375,"score_spread":0.27782753929949017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620158492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995448,0.0001436544,0.000031441028,0.000020721289,0.000002038847,0.000008584424,0.00007982961,0.0000024976143,0.00016633476],"genre_scores_gemma":[0.9995265,0.00007421122,0.00007010101,0.000014514486,0.0000058890587,0.00000867155,0.00017574114,0.0000010967749,0.00012335347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996972,0.000044149245,0.00006187637,0.00007100111,0.000080314734,0.00004544829],"domain_scores_gemma":[0.99827707,0.00024055273,0.0010289842,0.000050171722,0.0002021743,0.00020101039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040514002,0.0005251639,0.00047851162,0.0013283442,0.0004979921,0.0004465939,0.00025264325,0.00079578,0.0021841729],"category_scores_gemma":[0.0027339424,0.00025871486,0.00025828453,0.0007830275,0.00039432256,0.0005477413,0.00047819602,0.0003764966,0.00042802887],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002642955,0.000060902676,0.9964954,0.00001873277,0.00003280431,0.00041332914,0.000114616516,0.00004435546,0.0010000214,0.000009457865,0.000043318298,0.0015027642],"study_design_scores_gemma":[0.000008456145,0.00022253761,0.9986842,0.0000041272924,0.000010096822,0.00079767767,0.000085179716,0.00006195213,0.00008742418,0.000009772959,0.000026332364,0.000002354313],"about_ca_topic_score_codex":0.0032645634,"about_ca_topic_score_gemma":0.004274785,"teacher_disagreement_score":0.0032645634,"about_ca_system_score_codex":0.0002953018,"about_ca_system_score_gemma":0.00024759097,"threshold_uncertainty_score":0.007306814},"labels":[],"label_agreement":null},{"id":"W2620311529","doi":"10.1002/hbm.23658","title":"White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI)","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; Siemens Canada; Canadian Institute for Military and Veteran Health Research; Defence Research and Development Canada","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Concussion; Athletes; Magnetic resonance imaging; Psychology; Neurite; Neuroscience; Medicine; Chemistry; Physical therapy; Poison control; Radiology; Injury prevention","score_opus":0.03303363302585623,"score_gpt":0.2934358046874379,"score_spread":0.2604021716615817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620311529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998118,0.000049451803,0.000023135059,0.0000053357644,0.000001758458,0.0000041019916,0.000029745011,6.644948e-7,0.00007387745],"genre_scores_gemma":[0.9997414,0.000036698642,0.00005231886,0.0000068597574,0.000007222526,0.0000044596613,0.00006963807,6.3009173e-7,0.000080774254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977916,0.000031214266,0.00003131343,0.000056476576,0.000036603593,0.00006518983],"domain_scores_gemma":[0.9993819,0.00006946865,0.0002800249,0.00002422964,0.00009571591,0.00014873188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042469974,0.00030432068,0.00031320172,0.0010634653,0.0004672305,0.00048419717,0.00019166764,0.00053816923,0.0009340116],"category_scores_gemma":[0.0012400623,0.0002185765,0.00022670225,0.00044822885,0.0003684061,0.00037151665,0.00050928706,0.00021483385,0.00019686471],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035221514,0.000062056235,0.99640155,0.000012136788,0.0000369551,0.0001952607,0.00024510475,0.00002713809,0.0010414321,0.00001014233,0.000024224308,0.0015917749],"study_design_scores_gemma":[0.000004476211,0.00024959265,0.9987722,0.0000046828713,0.000014572077,0.0003417134,0.00036502967,0.00008408266,0.00010924703,0.00000787019,0.000044155575,0.0000022685697],"about_ca_topic_score_codex":0.0056471084,"about_ca_topic_score_gemma":0.0061284825,"teacher_disagreement_score":0.0056471084,"about_ca_system_score_codex":0.0003012961,"about_ca_system_score_gemma":0.00022061246,"threshold_uncertainty_score":0.011228502},"labels":[],"label_agreement":null},{"id":"W2620852117","doi":"","title":"Human Statistical Atlas of Cardiac Fiber Architecture from DT-MRI","year":2011,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Atlas (anatomy); Diffusion MRI; Segmentation; Human heart; Population; Orientation (vector space); Computer science; Artificial intelligence; Computer vision; Anatomy; Mathematics; Biology; Medicine; Geometry; Cardiology; Radiology; Magnetic resonance imaging","score_opus":0.03629853074752196,"score_gpt":0.28755465957508936,"score_spread":0.25125612882756737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620852117","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07085624,0.0021179006,0.8572993,0.001343685,0.00048702932,0.00043323936,0.029028151,0.018823627,0.0196108],"genre_scores_gemma":[0.47123,0.002974343,0.47166514,0.0007905727,0.00036826383,0.0008720534,0.019718692,0.004484762,0.027896171],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998171,0.000039427447,0.00001252418,0.00007038965,0.000039097533,0.000021529078],"domain_scores_gemma":[0.99924207,0.00031735798,0.000072375005,0.00017611875,0.00014448818,0.000047510108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011183582,0.0005408324,0.00039603267,0.0014021618,0.00049738435,0.0015929351,0.0004978561,0.0008811762,0.018421596],"category_scores_gemma":[0.0026599877,0.00036405484,0.0005447429,0.0012619195,0.00038352498,0.0005313415,0.00052475237,0.0006347455,0.0048807785],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007915189,0.00012684011,0.005517131,0.0007641563,0.00022553846,0.0010313479,0.00049617636,0.072896816,0.058404543,0.021522714,0.116417706,0.72180545],"study_design_scores_gemma":[0.00019694063,0.00048557526,0.056499314,0.0006728872,0.000265171,0.010512218,0.00037454886,0.47516754,0.07476876,0.088044636,0.29263481,0.0003776013],"about_ca_topic_score_codex":0.008262208,"about_ca_topic_score_gemma":0.015272764,"teacher_disagreement_score":0.018421596,"about_ca_system_score_codex":0.00046238714,"about_ca_system_score_gemma":0.0019894398,"threshold_uncertainty_score":0.061626375},"labels":[],"label_agreement":null},{"id":"W2621188631","doi":"10.1017/cjn.2017.166","title":"P.082 Neural Reorganization Following Compression of the Motor Cortex: An fMRI and DTI Case Report","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Saskatoon Medical Imaging","funders":"","keywords":"Functional magnetic resonance imaging; Motor cortex; Diffusion MRI; Psychology; Supplementary motor area; Magnetic resonance imaging; Neuroscience; Cortex (anatomy); White matter; Subthalamic nucleus; Medicine; Anatomy; Deep brain stimulation; Radiology; Parkinson's disease; Pathology","score_opus":0.08188633804923962,"score_gpt":0.35428019309251807,"score_spread":0.27239385504327845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621188631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9749517,0.0015919791,0.003763897,0.00445033,0.00022578762,0.0002491298,0.00029730157,0.00016593724,0.014303941],"genre_scores_gemma":[0.994046,0.00042734685,0.0017864341,0.00082118076,0.00039788647,0.000052895073,0.00009505526,0.000023517196,0.0023495709],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9996685,0.000028403296,0.000032892705,0.00007726222,0.000058925893,0.00013414216],"domain_scores_gemma":[0.99926656,0.00025106582,0.00016645745,0.00007816852,0.000053343832,0.0001843852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002959334,0.0014890713,0.0006512481,0.0023282175,0.0018157286,0.00089031796,0.001061974,0.004424671,0.0034998246],"category_scores_gemma":[0.0017407748,0.0007776683,0.0007930823,0.0009473419,0.002096184,0.001057565,0.0009760002,0.002956705,0.0012106934],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002539368,0.000033161603,0.001713423,0.000012133162,0.0000056643175,0.9959015,0.00008459984,0.00004217909,0.0009475975,0.0000900625,0.00016396274,0.0009803724],"study_design_scores_gemma":[0.000014015823,0.00008649267,0.0039117127,0.000009648195,0.000010670082,0.9941292,0.00004713422,0.00041795638,0.0008430303,0.0001418168,0.00037850736,0.00000984766],"about_ca_topic_score_codex":0.0051467405,"about_ca_topic_score_gemma":0.005863273,"teacher_disagreement_score":0.0051467405,"about_ca_system_score_codex":0.0016663744,"about_ca_system_score_gemma":0.0009096924,"threshold_uncertainty_score":0.012090385},"labels":[],"label_agreement":null},{"id":"W2621380256","doi":"10.1017/cjn.2017.167","title":"P.083 Characterization of an arteriovenous malformation using 7T structural and functional imaging: A case report","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Arteriovenous malformation; Digital subtraction angiography; Neuroimaging; Radiology; Abnormality; Intracranial Arteriovenous Malformations; Functional imaging; Magnetic resonance imaging; Angiography; Cerebral angiography","score_opus":0.08718711268704743,"score_gpt":0.33898033115505327,"score_spread":0.25179321846800584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621380256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754596,0.002102437,0.005699841,0.0037901998,0.00028229973,0.00019741763,0.00031092827,0.00017200231,0.011985387],"genre_scores_gemma":[0.99298745,0.0007536601,0.0033224688,0.00061206403,0.00058385485,0.000043426426,0.0001236164,0.000039754374,0.0015337262],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99942017,0.000046910893,0.00007498578,0.0001587732,0.000112342736,0.00018688494],"domain_scores_gemma":[0.9987165,0.0003927533,0.0002975821,0.000119140896,0.00010024511,0.0003737242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031738196,0.0017672452,0.000877151,0.0032725735,0.0023842722,0.001578277,0.0013228285,0.005513892,0.0035931177],"category_scores_gemma":[0.00244912,0.0010086717,0.0012141012,0.0016278,0.0020376125,0.0018238235,0.001497173,0.0036927795,0.0012061445],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011769742,0.000016940525,0.0022631106,0.000010731792,0.0000048163224,0.99593794,0.00007668931,0.000034426008,0.0006322309,0.00011799452,0.000114373586,0.000778883],"study_design_scores_gemma":[0.0000049847686,0.000025339383,0.0016059926,0.000009500701,0.000009749312,0.99722123,0.000042643882,0.00032899715,0.00037950653,0.00014183644,0.00022321497,0.0000071061404],"about_ca_topic_score_codex":0.0050515193,"about_ca_topic_score_gemma":0.004180427,"teacher_disagreement_score":0.005513892,"about_ca_system_score_codex":0.0014238011,"about_ca_system_score_gemma":0.001114931,"threshold_uncertainty_score":0.012020171},"labels":[],"label_agreement":null},{"id":"W2621699596","doi":"10.1101/146878","title":"Unfolding the hippocampus: an intrinsic coordinate system for subfield segmentations and quantitative mapping","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Fondation Brain Canada; Ontario Brain Institute","keywords":"Hippocampal formation; Central sulcus; Neuroscience; Hippocampus; Grey matter; Neocortex; Computer science; Coordinate system; Anatomy; Artificial intelligence; Biology; Magnetic resonance imaging; White matter; Medicine; Radiology; Motor cortex","score_opus":0.07299884844012966,"score_gpt":0.331262584607385,"score_spread":0.25826373616725534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621699596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03498595,0.000035759353,0.9636418,0.00005025617,0.000009969249,0.000031459225,0.00013738808,0.000836038,0.0002713599],"genre_scores_gemma":[0.22040434,0.000058964073,0.7782992,0.000019857198,0.000014555003,0.000102367645,0.00027850503,0.0003244152,0.00049776706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996592,0.00010828308,0.00002113673,0.000113151065,0.00007221254,0.00002609428],"domain_scores_gemma":[0.999395,0.00019198145,0.000103355866,0.0001278632,0.00015053686,0.000031104522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007522308,0.00057199376,0.00043172122,0.00081156543,0.00039109774,0.001084372,0.0005601403,0.0004267807,0.0018348912],"category_scores_gemma":[0.002330058,0.00024079115,0.0005094594,0.0006494017,0.0006349797,0.00058100553,0.0008524363,0.0005900785,0.00043280533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003631447,0.00009210371,0.0052567325,0.00025288132,0.00014125848,0.0003292352,0.0010285142,0.3217549,0.26425,0.03895198,0.003161045,0.3644182],"study_design_scores_gemma":[0.00001267001,0.000091741866,0.0034814947,0.000013060959,0.000014222009,0.000107353095,0.0000873165,0.9496739,0.034108166,0.008613479,0.003760957,0.000035595614],"about_ca_topic_score_codex":0.002457259,"about_ca_topic_score_gemma":0.002363042,"teacher_disagreement_score":0.002457259,"about_ca_system_score_codex":0.0005522936,"about_ca_system_score_gemma":0.0007073561,"threshold_uncertainty_score":0.0061383247},"labels":[],"label_agreement":null},{"id":"W2621911999","doi":"10.1101/146688","title":"Learn to Track: Deep Learning for Tractography","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Ground truth; Artificial intelligence; Deep learning; Diffusion MRI; Trajectory; Track (disk drive); Imaging phantom; Tracking (education); Process (computing); Artificial neural network; Deep neural networks; White matter; Fiber tract; Machine learning; Magnetic resonance imaging; Psychology; Physics","score_opus":0.04752977220672326,"score_gpt":0.31785915994131053,"score_spread":0.27032938773458726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621911999","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013641909,0.00047493962,0.98157334,0.00053501996,0.000055859746,0.000029160577,0.00028499353,0.0024288087,0.00097597676],"genre_scores_gemma":[0.49875695,0.000825709,0.48903978,0.00034735742,0.00012137379,0.0001940778,0.0014260517,0.0004563311,0.008832308],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997832,0.000053264375,0.000009967579,0.00006183928,0.000064567284,0.000027106165],"domain_scores_gemma":[0.9992236,0.0003918566,0.00009844489,0.00012102624,0.000111472065,0.00005368694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009721742,0.0009036078,0.00046821157,0.00051504176,0.00027369455,0.0008959336,0.0009945001,0.0013422614,0.0028349024],"category_scores_gemma":[0.0038547227,0.0004864865,0.00048785875,0.00063870364,0.00059105427,0.0012176561,0.0013201935,0.0019502874,0.001008318],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098541714,0.00006848725,0.0012083474,0.000077443045,0.00007061182,0.00007866147,0.000043034583,0.7793747,0.004462266,0.014612382,0.0048924424,0.19501303],"study_design_scores_gemma":[0.0000036308381,0.000006414298,0.000048048827,0.0000032183184,0.000001983187,0.0000070676147,0.0000013832366,0.993749,0.0006813551,0.0051190504,0.00037695977,0.000001926513],"about_ca_topic_score_codex":0.0070025325,"about_ca_topic_score_gemma":0.008589979,"teacher_disagreement_score":0.0070025325,"about_ca_system_score_codex":0.00093910727,"about_ca_system_score_gemma":0.0010352924,"threshold_uncertainty_score":0.013923526},"labels":[],"label_agreement":null},{"id":"W2622626023","doi":"10.1002/mrm.26689","title":"The effect of realistic geometries on the susceptibility‐weighted MR signal in white matter","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; University of Toronto","keywords":"White matter; SIGNAL (programming language); Magnetic resonance imaging; Diffusion MRI; Nuclear magnetic resonance; Physics; Geometry; Diffusion; Work (physics); Mathematics; Computer science; Medicine; Radiology","score_opus":0.03430550830802002,"score_gpt":0.3434914899147198,"score_spread":0.30918598160669974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622626023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9200163,0.0010762835,0.07617429,0.00045855343,0.000044903176,0.000092315895,0.00021197321,0.00030866856,0.001616741],"genre_scores_gemma":[0.9907342,0.00036060082,0.008487433,0.0000654148,0.000011710937,0.000028166098,0.00007628513,0.000048274665,0.0001878665],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995054,0.0002538608,0.000025719994,0.000072241586,0.00009586496,0.000046800455],"domain_scores_gemma":[0.99539137,0.0032339639,0.00080775266,0.00024499313,0.0002068749,0.000115100185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009037477,0.0009575161,0.00032245528,0.000345582,0.00031361077,0.0008016794,0.00051036495,0.0010777351,0.0005615877],"category_scores_gemma":[0.011297541,0.0004976708,0.00041344416,0.0001939219,0.00081266434,0.0011462595,0.0006642371,0.0004495039,0.0001646332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056112505,0.000110748435,0.0057547437,0.00031285078,0.000119647484,0.0008910665,0.000306934,0.8534203,0.12949479,0.0025187242,0.00022749016,0.0062815347],"study_design_scores_gemma":[0.000112648355,0.0010542439,0.011499785,0.000111927235,0.00021713889,0.001683182,0.00019769666,0.8861288,0.09297407,0.0043102745,0.0015955664,0.00011467793],"about_ca_topic_score_codex":0.0023449075,"about_ca_topic_score_gemma":0.0013256087,"teacher_disagreement_score":0.0023449075,"about_ca_system_score_codex":0.0007585088,"about_ca_system_score_gemma":0.000546977,"threshold_uncertainty_score":0.005503416},"labels":[],"label_agreement":null},{"id":"W2622868629","doi":"10.1101/148502","title":"Harmonization of cortical thickness measurements across scanners and sites","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"Scanner; Spurious relationship; Neuroimaging; Computer science; Statistical power; Artificial intelligence; Variance (accounting); Modalities; Reproducibility; Diffusion MRI; Data set; Set (abstract data type); Computer vision; Pattern recognition (psychology); Data mining; Magnetic resonance imaging; Machine learning; Statistics; Mathematics; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.09371964326403137,"score_gpt":0.3415614789768183,"score_spread":0.24784183571278695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622868629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.759109,0.0008442873,0.23394111,0.00034068237,0.00011775138,0.00024183445,0.001949579,0.00080342096,0.0026523236],"genre_scores_gemma":[0.91462535,0.00013439824,0.0825465,0.000115316405,0.000055950288,0.00023857273,0.0013200883,0.00038559502,0.00057820784],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9935759,0.0031728828,0.0005619495,0.001511957,0.0010038554,0.00017354629],"domain_scores_gemma":[0.9803017,0.005599403,0.0040673558,0.0070053847,0.0027112628,0.00031486328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008796362,0.0006594116,0.0009090183,0.0022732443,0.00057487714,0.001601671,0.001103477,0.00075384334,0.0021180152],"category_scores_gemma":[0.026002614,0.00058011967,0.0009408246,0.0021630866,0.0010154305,0.00083251286,0.0019807091,0.00083726353,0.0003331584],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030138325,0.00031963206,0.3973069,0.0013361371,0.0059920065,0.0012622423,0.0037347344,0.02873586,0.27261382,0.0057071694,0.005232635,0.27474508],"study_design_scores_gemma":[0.00024788454,0.0009792614,0.8139609,0.00015984295,0.001902363,0.0046943286,0.0017771596,0.034490064,0.11546536,0.014415174,0.011701584,0.00020607127],"about_ca_topic_score_codex":0.0012940839,"about_ca_topic_score_gemma":0.0021150522,"teacher_disagreement_score":0.008796362,"about_ca_system_score_codex":0.00033247937,"about_ca_system_score_gemma":0.00051791506,"threshold_uncertainty_score":0.046520174},"labels":[],"label_agreement":null},{"id":"W2624422566","doi":"10.1016/j.neurobiolaging.2017.05.023","title":"Long-term changes in time spent walking and subsequent cognitive and structural brain changes in older adults","year":2017,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health Research Institute; University of British Columbia; Vancouver Coastal Health","funders":"National Institute of Nursing Research; National Institute on Aging; Canadian Institutes of Health Research","keywords":"Cognition; Cognitive decline; White matter; Brain size; Effects of sleep deprivation on cognitive performance; Diffusion MRI; Psychology; Neuroimaging; Gerontology; Physical medicine and rehabilitation; Demographics; Medicine; Magnetic resonance imaging; Physical therapy; Dementia; Demography; Internal medicine; Psychiatry","score_opus":0.03544485928355749,"score_gpt":0.3413519391574788,"score_spread":0.3059070798739213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624422566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999198,0.00035636805,0.000041995947,0.000015917774,0.000004040789,0.0000036785627,0.00017609974,0.0000016524448,0.00020224815],"genre_scores_gemma":[0.99898297,0.00020800089,0.00006271957,0.00001697261,0.000007804427,0.00000873381,0.00027872695,8.9959e-7,0.00043307926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999236,0.00001001895,0.000010216205,0.00002428549,0.000011131185,0.000020779295],"domain_scores_gemma":[0.99969447,0.000024436678,0.00012973254,0.00001481145,0.00004965297,0.00008678192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020823085,0.0002862817,0.0002690884,0.00046344305,0.00030643292,0.00039415472,0.0001970993,0.0005104496,0.0008074867],"category_scores_gemma":[0.0008201141,0.0001446425,0.00022887037,0.00048737583,0.00015930939,0.00039646085,0.00037430288,0.0004176664,0.00019139827],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001291188,0.00028897362,0.9847947,0.000056455803,0.00022331344,0.0003191355,0.0004933806,0.00013139643,0.0025166983,0.000027933713,0.00014302025,0.009713818],"study_design_scores_gemma":[0.0000020487034,0.000115778246,0.99957997,0.0000027371811,0.000017336662,0.000060947634,0.000091268135,0.000034406563,0.000039474675,0.000019139108,0.000035024157,0.0000018314892],"about_ca_topic_score_codex":0.008927009,"about_ca_topic_score_gemma":0.018957766,"teacher_disagreement_score":0.008927009,"about_ca_system_score_codex":0.00019314354,"about_ca_system_score_gemma":0.00014306493,"threshold_uncertainty_score":0.017750084},"labels":[],"label_agreement":null},{"id":"W2624604555","doi":"10.1007/978-3-319-46293-6_10","title":"Spinal Cord Imaging","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Magnetic resonance imaging; Spinal cord; Diffusion MRI; Medicine; White matter; Spinal cord injury; Radiology; Functional magnetic resonance imaging; Neuroscience; Psychology","score_opus":0.13466672986164469,"score_gpt":0.4122790765283925,"score_spread":0.27761234666674783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624604555","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00067552243,0.072954856,0.02833528,0.0042043584,0.008847087,0.00008596129,0.0005007906,0.0011288914,0.8832672],"genre_scores_gemma":[0.003288916,0.040100776,0.009730578,0.0021743644,0.002938585,0.000066568675,0.00055013696,0.00030538067,0.9408447],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99980944,0.000020367446,0.000008740436,0.000029655266,0.000116013085,0.000015848906],"domain_scores_gemma":[0.999694,0.00007808794,0.000014265858,0.000034402903,0.00013362271,0.000045651832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002944775,0.0009554502,0.00066368346,0.0016650282,0.0006080733,0.0015901271,0.00088653865,0.0012891239,0.10797252],"category_scores_gemma":[0.0010634632,0.0003400654,0.0003838688,0.0010643956,0.00067587406,0.0017044523,0.0013799276,0.0023946774,0.073166855],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012275557,0.000018415303,0.00006497833,0.00033934767,0.0000071015465,0.00017388341,0.00006579038,0.00027815654,0.001071376,0.015937945,0.4624235,0.5196072],"study_design_scores_gemma":[0.0000020160846,0.000009267155,0.00015261807,0.00027453495,0.000004987317,0.0011501061,0.000022660737,0.00013349942,0.0003577928,0.00866322,0.9892229,0.000006499113],"about_ca_topic_score_codex":0.001372255,"about_ca_topic_score_gemma":0.005893591,"teacher_disagreement_score":0.10797252,"about_ca_system_score_codex":0.00063382485,"about_ca_system_score_gemma":0.0012535964,"threshold_uncertainty_score":0.36120403},"labels":[],"label_agreement":null},{"id":"W2624760699","doi":"10.1152/jn.00259.2017","title":"Diffusion-weighted tractography in the common marmoset monkey at 9.4T","year":2017,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Marmoset; Callithrix; White matter; Diffusion MRI; Neuroscience; Tractography; Fiber tract; Biology; Primate; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.06347437753438777,"score_gpt":0.3643572958683328,"score_spread":0.30088291833394504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624760699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97345734,0.00043532418,0.0235533,0.00028479545,0.000013123449,0.000033898003,0.00023081835,0.00010520563,0.0018862467],"genre_scores_gemma":[0.9632139,0.0005085968,0.03451298,0.00005403747,0.000011699783,0.000058510966,0.0002903856,0.000047677535,0.0013020983],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999946,0.000016605572,0.000003494593,0.00001582675,0.000009944788,0.000008264601],"domain_scores_gemma":[0.99992585,0.00001337244,0.00001606181,0.000012220976,0.000018035336,0.000014418887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033165785,0.00012769182,0.00018323376,0.00030089106,0.00041343019,0.0002506791,0.00021933245,0.00033233358,0.0007149881],"category_scores_gemma":[0.00045078134,0.00015110013,0.00013274718,0.00020410736,0.0002611953,0.000263601,0.0003528809,0.00036648387,0.0001811329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034758676,0.000042041618,0.0064958786,0.00007232087,0.000049184735,0.0011834275,0.00041276557,0.002365622,0.9688751,0.0016457966,0.00031802198,0.018192291],"study_design_scores_gemma":[0.000106419066,0.002084134,0.45505744,0.0001854948,0.0004712265,0.0165256,0.0008739793,0.058526143,0.43245718,0.014760187,0.018809555,0.00014258655],"about_ca_topic_score_codex":0.0028771576,"about_ca_topic_score_gemma":0.004783753,"teacher_disagreement_score":0.0028771576,"about_ca_system_score_codex":0.00022152872,"about_ca_system_score_gemma":0.0002343804,"threshold_uncertainty_score":0.005720854},"labels":[],"label_agreement":null},{"id":"W2625813974","doi":"10.1016/j.nicl.2017.06.017","title":"Predicting pain relief: Use of pre-surgical trigeminal nerve diffusion metrics in trigeminal neuralgia","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; Toronto Western Hospital; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Trigeminal Neuralgia Association of Canada","keywords":"Trigeminal neuralgia; Diffusion MRI; Medicine; Fractional anisotropy; Trigeminal nerve; Anesthesia; Radiology; Magnetic resonance imaging","score_opus":0.21252290911907837,"score_gpt":0.45670683316170824,"score_spread":0.24418392404262987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625813974","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961901,0.0005080869,0.0025071288,0.00008170992,0.000011578624,0.00003192576,0.00015043869,0.000038011,0.0004810114],"genre_scores_gemma":[0.9990356,0.00006024486,0.0007062242,0.000006946316,0.0000055840715,0.000010022555,0.00007870858,0.0000017661783,0.00009488202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972516,0.00011223499,0.000028517085,0.000042784934,0.000059127786,0.00003216482],"domain_scores_gemma":[0.99909055,0.0004766807,0.00016600902,0.000054862867,0.00011193507,0.00009987073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00126116,0.0003786998,0.00035354914,0.0006381594,0.00014506406,0.0002788196,0.00015998955,0.0002463789,0.0006893921],"category_scores_gemma":[0.0027781231,0.000056163055,0.00020293993,0.00020139513,0.00021775154,0.000257939,0.00024484203,0.00040187832,0.00014833777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055993106,0.00043837828,0.734467,0.0002695296,0.0002819647,0.00028340117,0.000246335,0.008141697,0.04744127,0.0001298758,0.0006558117,0.20204541],"study_design_scores_gemma":[0.00006121357,0.0032785127,0.93770504,0.000038750404,0.00014091391,0.0006820878,0.00029615872,0.043794904,0.012852242,0.00047951413,0.000639079,0.00003158737],"about_ca_topic_score_codex":0.00097641733,"about_ca_topic_score_gemma":0.0020559095,"teacher_disagreement_score":0.00126116,"about_ca_system_score_codex":0.00018529782,"about_ca_system_score_gemma":0.00023624998,"threshold_uncertainty_score":0.0066697598},"labels":[],"label_agreement":null},{"id":"W2627002953","doi":"10.1016/j.bandc.2017.05.001","title":"Diffusion tensor MRI tractography reveals increased fractional anisotropy (FA) in arcuate fasciculus following music-cued motor training","year":2017,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"FP7 People: Marie-Curie Actions; Wellcome Trust","keywords":"Arcuate fasciculus; Fractional anisotropy; Psychology; Diffusion MRI; Superior longitudinal fasciculus; Neuroscience; Audiology; White matter; Tractography; Motor learning; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.07908599173559543,"score_gpt":0.3464124446228678,"score_spread":0.26732645288727236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2627002953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993063,0.000073417454,0.0004331901,0.000021612106,0.0000026790808,0.000006420354,0.00001904908,0.000011863925,0.00012551332],"genre_scores_gemma":[0.99910694,0.000061906285,0.00045666142,0.0000109544235,0.0000028508707,0.000014541264,0.000025866251,0.0000024463752,0.00031791237],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999205,0.000014446848,0.000007643924,0.000021381806,0.00001654748,0.000019444848],"domain_scores_gemma":[0.99975044,0.000047987436,0.00010356957,0.000022848211,0.000019977162,0.00005519608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019380488,0.00016852592,0.00022140268,0.00020148771,0.00011841081,0.00011744643,0.00009737143,0.00020917087,0.0012386398],"category_scores_gemma":[0.00059886195,0.00011744744,0.00010090069,0.00008762541,0.0003548529,0.00012377261,0.00016293982,0.00022910048,0.00011695101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0047544423,0.00046234336,0.020616502,0.000101239886,0.00006775361,0.0008239823,0.00030760784,0.0003937089,0.94726634,0.000057038043,0.00013343545,0.025015628],"study_design_scores_gemma":[0.00015889632,0.0055000125,0.8477446,0.000018133094,0.00008570219,0.002764305,0.0002628366,0.0020559798,0.14056036,0.00021893776,0.0006130721,0.000017245982],"about_ca_topic_score_codex":0.0018688,"about_ca_topic_score_gemma":0.0025054966,"teacher_disagreement_score":0.0018688,"about_ca_system_score_codex":0.00017082604,"about_ca_system_score_gemma":0.00014799136,"threshold_uncertainty_score":0.0041436553},"labels":[],"label_agreement":null},{"id":"W2633513078","doi":"10.1101/153924","title":"Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; University College London; Alberta Children's Hospital Foundation; Norges Forskningsråd; Universitetet i Oslo; Children's Hospital Foundation","keywords":"Diffusion MRI; Neuroimaging; White matter; Brain development; Psychology; Popularity; Data science; Computer science; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.02907968211941895,"score_gpt":0.30838032152459577,"score_spread":0.2793006394051768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2633513078","genre_codex":"review","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011560352,0.86419135,0.08710472,0.029058697,0.0015279622,0.00017570853,0.0007715678,0.0002640879,0.005345496],"genre_scores_gemma":[0.06417994,0.7660107,0.15728837,0.005018719,0.0037540104,0.000689399,0.0006953722,0.00030167817,0.002061777],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99467564,0.0028608076,0.0004347183,0.0009159645,0.0009551165,0.00015773985],"domain_scores_gemma":[0.96919256,0.019903105,0.0016591178,0.0018750828,0.0067181583,0.00065199536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03505314,0.0010691136,0.0017720028,0.003742399,0.0005431548,0.0041209282,0.0019730492,0.0024193907,0.0020206075],"category_scores_gemma":[0.026913343,0.0008950901,0.0008897344,0.0031539942,0.0032778443,0.004651649,0.0025778704,0.0037816328,0.0010923559],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002471001,0.00014584581,0.024998337,0.010822429,0.00063180603,0.00035239646,0.001588193,0.0020236552,0.008427489,0.03326032,0.02081029,0.8966923],"study_design_scores_gemma":[0.0001413891,0.001104,0.10496652,0.0354449,0.0011232597,0.006718464,0.004757875,0.014876845,0.019281548,0.20471296,0.60613614,0.0007360618],"about_ca_topic_score_codex":0.0046503865,"about_ca_topic_score_gemma":0.0056794323,"teacher_disagreement_score":0.03505314,"about_ca_system_score_codex":0.0018942135,"about_ca_system_score_gemma":0.0037493638,"threshold_uncertainty_score":0.185381},"labels":[],"label_agreement":null},{"id":"W2638045955","doi":"10.3389/fnhum.2017.00306","title":"Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks","year":2017,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Boniface Hospital; Health Sciences Centre; University of Manitoba","funders":"Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"White matter; Diffusion MRI; Precuneus; Tractography; Artificial intelligence; Computer science; Region of interest; Fractional anisotropy; Spatial normalization; Pattern recognition (psychology); Brain mapping; Neuroscience; Psychology; Functional magnetic resonance imaging; Magnetic resonance imaging; Voxel; Medicine","score_opus":0.028165057815306205,"score_gpt":0.35485452185098354,"score_spread":0.32668946403567733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2638045955","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1799895,0.00047987254,0.7958677,0.0003360488,0.000048429734,0.00039753667,0.008921989,0.0031210734,0.010837783],"genre_scores_gemma":[0.47101653,0.00071097334,0.5148176,0.000065938846,0.00003927866,0.0009450282,0.006797649,0.00086089014,0.0047461484],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99979466,0.000038805687,0.000019173895,0.00006750524,0.00006167619,0.00001827664],"domain_scores_gemma":[0.99954104,0.00013394443,0.00008461501,0.00010358699,0.0001126373,0.000024206336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006715264,0.00036910654,0.00018746126,0.0017995748,0.0004090029,0.00073401415,0.00052804785,0.00036545444,0.005144275],"category_scores_gemma":[0.0014527783,0.00032052587,0.00049332256,0.0011229139,0.00040795715,0.00054157263,0.00048314303,0.00040256197,0.001194148],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010086212,0.00017300053,0.04019028,0.0009260294,0.00033952988,0.001492857,0.0035477628,0.22762138,0.16456632,0.09005188,0.029716015,0.44036645],"study_design_scores_gemma":[0.0001815437,0.00048266668,0.20768307,0.00022202381,0.00030412478,0.009836701,0.0006951408,0.47134128,0.094154075,0.07856181,0.13621916,0.00031845993],"about_ca_topic_score_codex":0.0073915473,"about_ca_topic_score_gemma":0.011475855,"teacher_disagreement_score":0.0073915473,"about_ca_system_score_codex":0.0007442289,"about_ca_system_score_gemma":0.001253729,"threshold_uncertainty_score":0.017209291},"labels":[],"label_agreement":null},{"id":"W266018641","doi":"10.1093/oxfordhb/9780199764228.013.5","title":"White Matter Connectivity","year":2014,"lang":"en","type":"book","venue":"Oxford University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Psychology; Frontotemporal dementia; Dementia; White matter; Diffusion MRI; Aphasia; Schizophrenia (object-oriented programming); Agnosia; Neuropsychology; Depression (economics); Psychiatry; Neuroscience; Disease; Clinical psychology; Cognition; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.042216648225983325,"score_gpt":0.26783251262986846,"score_spread":0.22561586440388515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W266018641","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030518507,0.23918568,0.059224527,0.010341818,0.008374657,0.00018703108,0.0027517953,0.0016344714,0.6752482],"genre_scores_gemma":[0.013421407,0.17524128,0.049009096,0.0022609152,0.0036817708,0.00015953384,0.0019300051,0.00063886546,0.7536572],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998462,0.00001536676,0.000008209115,0.00004666926,0.000075368545,0.00000819799],"domain_scores_gemma":[0.99988365,0.000045689372,0.00000764311,0.000015903046,0.00003309221,0.000013970078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024347301,0.00085615274,0.0004603048,0.0020589905,0.00046355708,0.0016166538,0.00057354174,0.0009003111,0.048952904],"category_scores_gemma":[0.00060262746,0.00031962077,0.0003633522,0.0015006628,0.0007016918,0.0014402323,0.00066178886,0.0010869012,0.023857795],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019143445,0.000013939869,0.00018467705,0.00045957128,0.000023453138,0.00014528545,0.0001248388,0.0005179159,0.00418557,0.058056254,0.2688571,0.6674122],"study_design_scores_gemma":[0.0000026909704,0.000018291794,0.00062282704,0.00022653266,0.0000073961864,0.001061758,0.000023121562,0.00028903648,0.001025572,0.024063868,0.97264695,0.000012007187],"about_ca_topic_score_codex":0.0015734253,"about_ca_topic_score_gemma":0.0045871157,"teacher_disagreement_score":0.048952904,"about_ca_system_score_codex":0.00070107554,"about_ca_system_score_gemma":0.0005704848,"threshold_uncertainty_score":0.16376376},"labels":[],"label_agreement":null},{"id":"W2666006491","doi":"10.1503/jpn.160090","title":"Hemispheric lateralization abnormalities of the white matter microstructure in patients with schizophrenia and bipolar disorder","year":2017,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Biomedical Research Council; National Medical Research Council; Medical Research Council; National Healthcare Group; Duke-NUS Medical School","keywords":"Lateralization of brain function; Bipolar disorder; Schizophrenia (object-oriented programming); Laterality; Psychology; White matter; Fractional anisotropy; Psychosis; Neuroscience; Audiology; Psychiatry; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.009839823075723788,"score_gpt":0.26573112413209254,"score_spread":0.25589130105636876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2666006491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992803,0.00019595241,0.000035383,0.00002561996,0.0000022528811,0.0000050140284,0.000098477896,0.0000023480875,0.00035468105],"genre_scores_gemma":[0.9996662,0.00008021289,0.000054045533,0.000012441181,0.0000033604178,0.000004337641,0.00011644658,9.983216e-7,0.00006198402],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983585,0.00002925291,0.000027761678,0.00004619753,0.000033462526,0.000027404434],"domain_scores_gemma":[0.99932635,0.00007412973,0.00045003332,0.00003114593,0.00005342054,0.00006490187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030771666,0.0003900305,0.00024200106,0.0010077644,0.0003922147,0.00035359783,0.0001236958,0.00028056971,0.0019243648],"category_scores_gemma":[0.0011280312,0.00019625713,0.00021156599,0.000527747,0.0003269974,0.00025051375,0.00029189445,0.0002098751,0.00016379046],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026577196,0.000017383829,0.9937087,0.000020403471,0.0000648541,0.00062073657,0.0002140415,0.000052635678,0.0025958938,0.000043295564,0.00010539687,0.0022907546],"study_design_scores_gemma":[0.000005164671,0.000038222322,0.9984475,0.0000066399475,0.000017219087,0.0011085398,0.00012479888,0.000051122737,0.000095062394,0.000052753396,0.00005021102,0.0000026639811],"about_ca_topic_score_codex":0.0042300588,"about_ca_topic_score_gemma":0.0084793605,"teacher_disagreement_score":0.0042300588,"about_ca_system_score_codex":0.0002809876,"about_ca_system_score_gemma":0.0003163998,"threshold_uncertainty_score":0.008410871},"labels":[],"label_agreement":null},{"id":"W2679766784","doi":"10.3389/fninf.2017.00042","title":"Visualization, Interaction and Tractometry: Dealing with Millions of Streamlines from Diffusion MRI Tractography","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Hospitalier Universitaire de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Visualization; Streamlines, streaklines, and pathlines; Diffusion MRI; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Medicine; Radiology; Mechanics","score_opus":0.035425939507643625,"score_gpt":0.3413802033523625,"score_spread":0.3059542638447189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2679766784","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018396331,0.00054558436,0.97355837,0.0008004763,0.000100669,0.000067508474,0.0005022381,0.005433934,0.0005948657],"genre_scores_gemma":[0.09570503,0.0013234048,0.8969132,0.00014184628,0.00020980122,0.00025708842,0.0019041323,0.0023126826,0.0012328604],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981901,0.0005515981,0.00018759449,0.00030474082,0.0006577118,0.00010821514],"domain_scores_gemma":[0.9894978,0.0059256246,0.0011336831,0.002064636,0.0010647363,0.00031358658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024317512,0.0016758419,0.0013272694,0.0028162168,0.0009933913,0.0042824904,0.0015552923,0.0016425445,0.0053036655],"category_scores_gemma":[0.020579727,0.0009823696,0.0011107647,0.0036180601,0.0012699232,0.005474137,0.0033607013,0.0023218268,0.0015792331],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080946455,0.00013419788,0.0043116906,0.0011698229,0.0002702856,0.0010724916,0.0016836061,0.07227979,0.104827024,0.032876603,0.02175594,0.75880915],"study_design_scores_gemma":[0.0000939872,0.00019439062,0.0064575234,0.00018323922,0.00012182152,0.0018502501,0.00039720908,0.75101405,0.1022055,0.0878182,0.04945945,0.00020432028],"about_ca_topic_score_codex":0.0022014114,"about_ca_topic_score_gemma":0.0019764898,"teacher_disagreement_score":0.0053036655,"about_ca_system_score_codex":0.0008031601,"about_ca_system_score_gemma":0.0013046353,"threshold_uncertainty_score":0.017742455},"labels":[],"label_agreement":null},{"id":"W2704183690","doi":"10.1007/s00415-017-8550-8","title":"Higher blood–brain barrier permeability is associated with higher white matter hyperintensities burden","year":2017,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; National Natural Science Foundation of China","keywords":"Hyperintensity; Medicine; White matter; Neurology; Leukoaraiosis; Magnetic resonance imaging; Montreal Cognitive Assessment; Internal medicine; Cardiology; Cognitive impairment; Psychiatry; Radiology; Disease","score_opus":0.04596272256702478,"score_gpt":0.3219293559223865,"score_spread":0.2759666333553617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2704183690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960861,0.0012929591,0.00073084276,0.00025017225,0.000030864805,0.000008485427,0.00016165603,0.00002881873,0.0014101168],"genre_scores_gemma":[0.9983047,0.000415912,0.0004128976,0.000054952718,0.00006235469,0.0000060678067,0.00014615161,0.00001925346,0.00057768484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996258,0.00007211654,0.000053404907,0.0001041227,0.00007177203,0.00007277822],"domain_scores_gemma":[0.9949679,0.0006160213,0.003547046,0.00022062074,0.000259572,0.00038900413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004908866,0.00053186266,0.0005676973,0.0011389235,0.0005609668,0.0012336752,0.00041792847,0.001008248,0.0052777077],"category_scores_gemma":[0.003012631,0.00040800133,0.00066283543,0.0010921416,0.00049679395,0.0009838546,0.0005508938,0.0012609714,0.0005586684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026933944,0.00047261122,0.94803476,0.0003108198,0.0013223297,0.0035208256,0.000334611,0.00028259607,0.029020201,0.00084595283,0.00073014904,0.012431583],"study_design_scores_gemma":[0.000013165982,0.00014020737,0.9927498,0.000022118393,0.00025793765,0.003562416,0.00011977062,0.00040777717,0.001306097,0.0010348241,0.0003706761,0.000015212799],"about_ca_topic_score_codex":0.001416137,"about_ca_topic_score_gemma":0.0009717557,"teacher_disagreement_score":0.0052777077,"about_ca_system_score_codex":0.0002921918,"about_ca_system_score_gemma":0.00034961553,"threshold_uncertainty_score":0.01765567},"labels":[],"label_agreement":null},{"id":"W2727983075","doi":"10.1016/j.neuroimage.2017.06.083","title":"Fiberprint: A subject fingerprint based on sparse code pooling for white matter fiber analysis","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Eastern Washington University","keywords":"Fiber bundle; Artificial intelligence; Pattern recognition (psychology); Pooling; Computer science; Feature vector; Diffusion MRI; Fingerprint (computing); Human Connectome Project; Bundle; Biology; Magnetic resonance imaging","score_opus":0.0788378342822814,"score_gpt":0.3710360669902838,"score_spread":0.2921982327080024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2727983075","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028608356,0.00045764202,0.9636055,0.00017490122,0.00008761092,0.00008905223,0.0012824653,0.004776914,0.00091761537],"genre_scores_gemma":[0.19565523,0.000735955,0.79153764,0.00022362192,0.00023246484,0.00021445422,0.002853987,0.0010475414,0.0074991668],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99977654,0.000032266697,0.0000101271335,0.00005784595,0.00008147713,0.000041688763],"domain_scores_gemma":[0.9996661,0.000055631772,0.0000403684,0.000086648455,0.00010124485,0.000049983937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005684686,0.00079481065,0.00080259197,0.0013757043,0.0004026867,0.0007573514,0.0006984607,0.0008217002,0.005029848],"category_scores_gemma":[0.0011028548,0.0003423341,0.0006901941,0.0013572889,0.0002772937,0.0009690482,0.0013625512,0.0006253032,0.002401867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009056586,0.00016073034,0.00224948,0.00015872148,0.00018751717,0.00016791243,0.0001310065,0.012922624,0.15265404,0.0028431672,0.014928607,0.81269056],"study_design_scores_gemma":[0.00015936847,0.00037918566,0.014961849,0.0000461095,0.00028916195,0.0012954688,0.00012008845,0.8080348,0.14361666,0.013706027,0.017223734,0.00016768242],"about_ca_topic_score_codex":0.0039071143,"about_ca_topic_score_gemma":0.0080494825,"teacher_disagreement_score":0.005029848,"about_ca_system_score_codex":0.0002535818,"about_ca_system_score_gemma":0.0010799684,"threshold_uncertainty_score":0.01682657},"labels":[],"label_agreement":null},{"id":"W2732416206","doi":"10.1016/j.neuroimage.2017.06.047","title":"Thalamus segmentation using multi-modal feature classification: Validation and pilot study of an age-matched cohort","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Thalamus; Voxel; Fractional anisotropy; Pattern recognition (psychology); Diffusion MRI; Artificial intelligence; Segmentation; Feature (linguistics); Computer science; Neuroscience; Medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.2382049101604581,"score_gpt":0.43425491782629133,"score_spread":0.19605000766583322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732416206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977082,0.000047040336,0.0015353751,0.000016896078,0.000012297376,0.00007333186,0.0003709453,0.000025507767,0.00021045697],"genre_scores_gemma":[0.9956766,0.0001068538,0.00163764,0.000031627365,0.000027297381,0.00009919223,0.001666341,0.00004688549,0.0007076693],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996431,0.0000747908,0.000027694772,0.00014723215,0.00006386827,0.000043370957],"domain_scores_gemma":[0.998632,0.00023988579,0.00009299257,0.00045940874,0.00043525035,0.00014041847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015947775,0.00061537715,0.0005370478,0.0007363362,0.0008057127,0.0005555795,0.00053427485,0.00058222126,0.0020043862],"category_scores_gemma":[0.0027171064,0.00025571857,0.00061796466,0.00035563877,0.0007013899,0.0004449151,0.0004332049,0.0005075207,0.00092775567],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007139225,0.0053702667,0.84058094,0.00016657935,0.00078290654,0.0040565967,0.0051881718,0.0013283417,0.071783826,0.00032099916,0.0033753137,0.059906717],"study_design_scores_gemma":[0.0003320552,0.004485001,0.97574824,0.000022865137,0.00042035716,0.0047356933,0.0017847504,0.003793524,0.005907926,0.0002979659,0.0024240296,0.000047500856],"about_ca_topic_score_codex":0.0063543934,"about_ca_topic_score_gemma":0.0076149595,"teacher_disagreement_score":0.0063543934,"about_ca_system_score_codex":0.00035115107,"about_ca_system_score_gemma":0.00046534566,"threshold_uncertainty_score":0.012634814},"labels":[],"label_agreement":null},{"id":"W2733738172","doi":"10.1016/j.eurpsy.2017.01.2122","title":"Classification of first-episode schizophrenia spectrum disorders and controls from whole brain white matter fractional anisotropy using machine learning","year":2017,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fractional anisotropy; Support vector machine; White matter; Schizophrenia (object-oriented programming); Artificial intelligence; Psychology; Machine learning; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Computer science","score_opus":0.029833558692052956,"score_gpt":0.31109454678328896,"score_spread":0.281260988091236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2733738172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998582,0.000109722234,0.0010343348,0.0000152761,0.000005985945,0.000016676728,0.00012367748,0.000016992013,0.00009539099],"genre_scores_gemma":[0.99873716,0.000026573807,0.0009173443,0.0000035124606,0.0000048594843,0.000011144834,0.00024337765,0.0000023828866,0.000053723175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995328,0.00015266234,0.00007844314,0.000118217875,0.00006069257,0.000057267593],"domain_scores_gemma":[0.9990847,0.00042000055,0.00020424499,0.000116369636,0.00009048186,0.00008415293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013144873,0.00043211898,0.00040072357,0.0016882247,0.00019658166,0.0005185241,0.00017844017,0.00042389365,0.0011287051],"category_scores_gemma":[0.0032164229,0.0000853033,0.00033925634,0.00024318021,0.000267989,0.00020074312,0.0002872835,0.00016721466,0.0001879735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036855466,0.00030707862,0.89607406,0.00009673136,0.00041586463,0.00045677717,0.00034920583,0.002688788,0.020312494,0.00024084117,0.0005005046,0.074872136],"study_design_scores_gemma":[0.00008565106,0.0008536964,0.95586413,0.000027956185,0.00012397906,0.000922007,0.0003108892,0.034962475,0.0056749117,0.00081532635,0.00033179342,0.00002727274],"about_ca_topic_score_codex":0.0017824798,"about_ca_topic_score_gemma":0.0016086049,"teacher_disagreement_score":0.0017824798,"about_ca_system_score_codex":0.00026868333,"about_ca_system_score_gemma":0.00018314781,"threshold_uncertainty_score":0.0069517493},"labels":[],"label_agreement":null},{"id":"W2735032522","doi":"10.1161/str.47.suppl_1.214","title":"Abstract 214: Corticospinal Tract Integrity is Acutely Maintained Within Perihematoma Edema","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Edema; Corticospinal tract; Fractional anisotropy; Hematoma; White matter; Intracerebral hemorrhage; Anesthesia; Diffusion MRI; Stroke (engine); Magnetic resonance imaging; Nuclear medicine; Glasgow Coma Scale; Radiology; Surgery","score_opus":0.06869884978146984,"score_gpt":0.3671000579202947,"score_spread":0.29840120813882487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735032522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991806,0.00015590055,0.00009578611,0.00005073625,0.0000042009974,0.000005255164,0.000077857745,0.000006304249,0.00042333812],"genre_scores_gemma":[0.9994887,0.00006950563,0.000068288675,0.000032395026,0.000022344906,0.0000041737558,0.00015972268,0.0000017385433,0.00015294208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999279,0.00000940388,0.000009173712,0.000016353584,0.000017241508,0.00001990678],"domain_scores_gemma":[0.99959844,0.000069723465,0.00018514892,0.000026294885,0.00005116991,0.00006931692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014035935,0.00016293903,0.0002598322,0.0002080459,0.00023546044,0.00038716284,0.00015811551,0.00030685216,0.0033309811],"category_scores_gemma":[0.0006583645,0.00007454706,0.000103699145,0.0002123222,0.0004067076,0.00025921312,0.00015371694,0.00027686942,0.0005589845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051531848,0.00027704582,0.85350835,0.0002159243,0.00014010479,0.014298248,0.00026811237,0.0003623442,0.10242846,0.00013950189,0.0015818563,0.021626806],"study_design_scores_gemma":[0.00007625537,0.0009634853,0.97457916,0.000015030385,0.000051121857,0.015514743,0.00010447533,0.00037150696,0.0075840848,0.00016788529,0.0005649612,0.0000073176],"about_ca_topic_score_codex":0.00069681054,"about_ca_topic_score_gemma":0.00081053906,"teacher_disagreement_score":0.0033309811,"about_ca_system_score_codex":0.00032488868,"about_ca_system_score_gemma":0.0002523765,"threshold_uncertainty_score":0.011143208},"labels":[],"label_agreement":null},{"id":"W2735700022","doi":"10.1016/j.neuroimage.2017.07.015","title":"Recognition of white matter bundles using local and global streamline-based registration and clustering","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":317,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Indiana University; State Corporation Commission","keywords":"Computer science; Bundle; Artificial intelligence; Tractography; Cluster analysis; Diffusion MRI; Process (computing); White matter; Streamlines, streaklines, and pathlines; Pipeline (software); Pattern recognition (psychology)","score_opus":0.2521597257101989,"score_gpt":0.4376269879966907,"score_spread":0.1854672622864918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735700022","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024830273,0.9658247,0.02747584,0.0005873896,0.0003157456,0.0000691754,0.00023180264,0.00032209596,0.0026901825],"genre_scores_gemma":[0.01444428,0.94557285,0.03633287,0.00025028182,0.0004782529,0.00007191507,0.00067508075,0.00005907984,0.0021154166],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996631,0.000036287594,0.000046984453,0.000092898445,0.00014188969,0.000018769035],"domain_scores_gemma":[0.99944013,0.00019725093,0.00010056421,0.000038335602,0.00020087165,0.000022850401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010663621,0.0011593717,0.001717191,0.0034973694,0.00022018483,0.0012734436,0.00149965,0.0009738402,0.0013781328],"category_scores_gemma":[0.001604769,0.00038573472,0.00087251764,0.0032114096,0.0007208486,0.0014187294,0.00059851905,0.0010370159,0.0016777545],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005091053,0.000040212788,0.00043315857,0.0048954436,0.00016619469,0.00008492241,0.000033329816,0.00076542975,0.0031759087,0.0015794142,0.0052946857,0.9834803],"study_design_scores_gemma":[0.00014090528,0.0006759226,0.01963523,0.00843073,0.0023667905,0.01220021,0.00041360327,0.020440048,0.043343447,0.03324056,0.8586115,0.0005009805],"about_ca_topic_score_codex":0.0029981423,"about_ca_topic_score_gemma":0.0038759415,"teacher_disagreement_score":0.0034973694,"about_ca_system_score_codex":0.0004477971,"about_ca_system_score_gemma":0.0013091107,"threshold_uncertainty_score":0.0059613585},"labels":[],"label_agreement":null},{"id":"W2736256711","doi":"10.1093/scan/nsx070","title":"White matter correlates of psychopathic traits in a female community sample","year":2017,"lang":"en","type":"article","venue":"Social Cognitive and Affective Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Stiftelsen för Strategisk Forskning","keywords":"Uncinate fasciculus; Psychology; Cingulum (brain); Psychopathy; White matter; Facet (psychology); Diffusion MRI; Fornix; Fractional anisotropy; Fasciculus; Big Five personality traits; Neuroscience; Personality; Medicine; Magnetic resonance imaging; Social psychology","score_opus":0.09969603128901235,"score_gpt":0.402511471614359,"score_spread":0.3028154403253467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736256711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996493,0.000024245694,0.000029504261,0.00001387168,9.689152e-7,0.000008536971,0.000088256,0.0000014717112,0.00018389165],"genre_scores_gemma":[0.999337,0.00004668332,0.00006829185,0.000018749552,0.000006518632,0.000010886817,0.0001600598,0.0000025591073,0.00034913345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985695,0.000024087769,0.0000100123025,0.00004904588,0.000031703505,0.000028237859],"domain_scores_gemma":[0.9998123,0.00001549611,0.0000655084,0.000019984858,0.000040087507,0.000046686997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017622969,0.0003655414,0.00031425545,0.0010101724,0.0009734222,0.00037715473,0.00022101184,0.00030347295,0.0026942322],"category_scores_gemma":[0.0007298649,0.00028557103,0.00012488727,0.00045519482,0.00031612482,0.00024629553,0.0005423142,0.00028135485,0.00040233618],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023539962,0.00019084963,0.9912034,0.00001234153,0.000029406621,0.00082335033,0.000728465,0.000017587148,0.003217785,0.000033870707,0.00019543551,0.0033121884],"study_design_scores_gemma":[0.000009533534,0.00011183378,0.99780005,0.0000041267544,0.000009314893,0.0012123297,0.00055717083,0.000047035915,0.00009590798,0.000018454168,0.00013197627,0.0000021790604],"about_ca_topic_score_codex":0.007333872,"about_ca_topic_score_gemma":0.014389373,"teacher_disagreement_score":0.007333872,"about_ca_system_score_codex":0.00017417359,"about_ca_system_score_gemma":0.00013208971,"threshold_uncertainty_score":0.014582396},"labels":[],"label_agreement":null},{"id":"W2737094118","doi":"10.1002/hbm.23743","title":"Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":286,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Drug Abuse; Engineering and Physical Sciences Research Council; National Institutes of Health; Genentech; Dana Foundation; Agence Nationale de la Recherche; Canadian Institutes of Health Research; National Health and Medical Research Council; Leon Levy Foundation; GlaxoSmithKline; Alzheimer's Drug Discovery Foundation; Medical Research Council; Centre National de la Recherche Scientifique; National Institute on Aging; Alzheimer's Association","keywords":"Brain size; White matter; Neuroimaging; Encephalization; Neuroscience; Aging brain; Hum; Brain aging; Amygdala; Senescence; Psychology; Hippocampus; Magnetic resonance imaging; Cognition; Medicine; Internal medicine; History","score_opus":0.08566485548572217,"score_gpt":0.4056353312085949,"score_spread":0.31997047572287274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737094118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59753853,0.009901127,0.37379164,0.0007869839,0.000086160486,0.00019809647,0.012248105,0.0029996617,0.0024496773],"genre_scores_gemma":[0.8343727,0.0034305155,0.14389437,0.0001882832,0.00016981151,0.00031357602,0.015635889,0.00051264453,0.0014822747],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99941015,0.0000997224,0.0000530731,0.0003102064,0.00007014199,0.00005677353],"domain_scores_gemma":[0.9988319,0.0002541193,0.00027896478,0.00024849243,0.00026446208,0.000121971156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024397608,0.0010883796,0.001015212,0.0050838394,0.00033229846,0.0011296722,0.00072866475,0.00085908565,0.0009112787],"category_scores_gemma":[0.0034346485,0.00036358574,0.0015863873,0.0018541913,0.000592099,0.00095437333,0.0014294942,0.0008019201,0.0006892328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012781507,0.00032235615,0.41684023,0.0013661336,0.0030195788,0.0025136485,0.0019216605,0.054715518,0.12479738,0.0065212944,0.014256517,0.37244746],"study_design_scores_gemma":[0.000044416865,0.00064356334,0.710364,0.00038670297,0.0014809866,0.0032720629,0.0009154616,0.23285334,0.01422551,0.01944255,0.01623822,0.00013317811],"about_ca_topic_score_codex":0.007919166,"about_ca_topic_score_gemma":0.0070237247,"teacher_disagreement_score":0.007919166,"about_ca_system_score_codex":0.00053425675,"about_ca_system_score_gemma":0.00079390995,"threshold_uncertainty_score":0.015746117},"labels":[],"label_agreement":null},{"id":"W2737984394","doi":"10.1523/jneurosci.0560-17.2017","title":"Changes in White Matter Microstructure Impact Cognition by Disrupting the Ability of Neural Assemblies to Synchronize","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Pediatric Oncology Group of Ontario; Garron Family Cancer Centre; Fondation Brain Canada","keywords":"White matter; Neuroscience; Cognition; Psychology; Cuneus; Diffusion MRI; Audiology; Visual cortex; Medicine; Magnetic resonance imaging; Precuneus","score_opus":0.05281792820267213,"score_gpt":0.39681723200265046,"score_spread":0.34399930379997834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737984394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978928,0.000044843026,0.0017133632,0.00003286454,0.0000032533692,0.000005986213,0.00011833689,0.000017423541,0.00017120819],"genre_scores_gemma":[0.999079,0.000030793977,0.0007021016,0.000005037104,0.0000017463003,0.0000052056994,0.00007365284,0.0000032397236,0.000099150624],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991524,0.000016380021,0.000009453991,0.000029236462,0.000012340963,0.000017295932],"domain_scores_gemma":[0.99969363,0.00008133863,0.00014994814,0.000035069188,0.000013083918,0.000026973234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021066683,0.0003662771,0.00015587932,0.00028988323,0.00015459905,0.00044424378,0.0001749891,0.00023586131,0.0016143873],"category_scores_gemma":[0.0010429263,0.00010734465,0.00023913493,0.00016688478,0.00046529734,0.0002495378,0.00037525914,0.00021530344,0.00013012275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008408536,0.00020313183,0.7925727,0.00015765599,0.00037024418,0.00071164104,0.0006358883,0.020144165,0.15164822,0.0034713338,0.0003409971,0.028903188],"study_design_scores_gemma":[0.000024745403,0.00071296334,0.929607,0.000020845133,0.00012489391,0.0008207934,0.00056364684,0.029002672,0.036112137,0.0021636186,0.00082760735,0.000019075756],"about_ca_topic_score_codex":0.0034527718,"about_ca_topic_score_gemma":0.003637749,"teacher_disagreement_score":0.0034527718,"about_ca_system_score_codex":0.00035567654,"about_ca_system_score_gemma":0.00038807886,"threshold_uncertainty_score":0.006865382},"labels":[],"label_agreement":null},{"id":"W2738800716","doi":"10.1002/hbm.23741","title":"Ax<scp>T</scp>ract: Toward microstructure informed tractography","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"H2020 European Research Council; Horizon 2020; Natural Sciences and Engineering Research Council of Canada; Centre d'Imagerie BioMédicale","keywords":"Tractography; White matter; Diffusion MRI; Streamlines, streaklines, and pathlines; Computer science; Connectomics; Artificial intelligence; Magnetic resonance imaging; Neuroscience; Microstructure; Geology; Computer vision; Physics; Psychology; Connectome; Materials science; Medicine; Radiology; Functional connectivity","score_opus":0.11000815081223125,"score_gpt":0.3775074931784151,"score_spread":0.26749934236618383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738800716","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0100931525,0.00039706452,0.9835976,0.00042777054,0.000057954152,0.0000485212,0.0004577471,0.0033570463,0.0015631298],"genre_scores_gemma":[0.09650321,0.0010079405,0.89595747,0.0002891874,0.00014263825,0.00015608808,0.0010899021,0.0013301566,0.0035234722],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964964,0.00012325248,0.000019244038,0.00006701441,0.000120990124,0.000019941232],"domain_scores_gemma":[0.9985702,0.00048469866,0.00027567588,0.000260564,0.0003101095,0.00009873006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011363643,0.00076629134,0.00047985747,0.0013210796,0.00032749402,0.0015682532,0.00079064653,0.0010526894,0.004808461],"category_scores_gemma":[0.0037464437,0.000325034,0.0005735781,0.0011894691,0.00067088864,0.0010802489,0.0011200844,0.0009397719,0.0030084462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005319009,0.00012594723,0.0037175121,0.0006721835,0.0003094562,0.0014184235,0.00026980852,0.26461986,0.104597926,0.05341129,0.037789218,0.5325365],"study_design_scores_gemma":[0.000031316427,0.00008205018,0.0019590135,0.000052624004,0.000030729872,0.00052478595,0.0000266383,0.93854153,0.021397976,0.022193776,0.0151153635,0.000044232238],"about_ca_topic_score_codex":0.0026759913,"about_ca_topic_score_gemma":0.003651109,"teacher_disagreement_score":0.004808461,"about_ca_system_score_codex":0.00042656637,"about_ca_system_score_gemma":0.00096912903,"threshold_uncertainty_score":0.016085863},"labels":[],"label_agreement":null},{"id":"W2739042028","doi":"10.1007/978-3-319-73839-0_4","title":"A Generalized SMT-Based Framework for Diffusion MRI Microstructural Model Estimation","year":2018,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Orientation (vector space); Biological system; Axial symmetry; Computer science; Estimation theory; Diffusion MRI; Spherical harmonics; Algorithm; Ellipsoid; Physics; Mathematics; Magnetic resonance imaging; Mathematical analysis; Geometry","score_opus":0.08106635121994765,"score_gpt":0.3953394343880638,"score_spread":0.31427308316811614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739042028","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024138321,0.0002427179,0.99876547,0.00006763529,0.00002942439,0.0000069605894,0.000052528387,0.00019409673,0.00039992333],"genre_scores_gemma":[0.01754526,0.0011592462,0.9754765,0.00013306606,0.00019351416,0.00011082473,0.0005242684,0.0004431506,0.0044142185],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941826,0.00025236508,0.000040671817,0.000095524425,0.00016593223,0.00002734045],"domain_scores_gemma":[0.9990742,0.00038661464,0.00007003134,0.00014959065,0.00026802727,0.000051505227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015546378,0.0013012859,0.0011672861,0.001008504,0.00041045982,0.0014007537,0.0023663547,0.0018163777,0.0057591926],"category_scores_gemma":[0.003793679,0.0007447188,0.0018825101,0.0018665325,0.0007121341,0.0015402839,0.002054729,0.0025608514,0.0033637485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009114878,0.000059049315,0.00035482642,0.0003849111,0.00019763203,0.00026851415,0.00010212785,0.39743575,0.013075862,0.16853945,0.020875031,0.39861566],"study_design_scores_gemma":[0.0000042531906,0.000020551392,0.00010287649,0.000021744368,0.00001733642,0.00014857425,0.00000778933,0.9337011,0.0010833021,0.05589354,0.008981002,0.000017996552],"about_ca_topic_score_codex":0.004630705,"about_ca_topic_score_gemma":0.007245612,"teacher_disagreement_score":0.0057591926,"about_ca_system_score_codex":0.00056415825,"about_ca_system_score_gemma":0.0011999655,"threshold_uncertainty_score":0.019266367},"labels":[],"label_agreement":null},{"id":"W2739464459","doi":"10.1016/j.nicl.2017.07.020","title":"A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":175,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Neuroscience; Putamen; Diffusion MRI; Thalamus; Tractography; Parkinson's disease; Basal ganglia; Psychology; Deep brain stimulation; Essential tremor; Neurology; Medicine; Magnetic resonance imaging; Pathology; Disease; Central nervous system; Radiology","score_opus":0.2194016638390161,"score_gpt":0.47843130508799625,"score_spread":0.25902964124898015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739464459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94917816,0.0027972287,0.03353115,0.00023682551,0.00040030925,0.00038691112,0.009627393,0.0018540198,0.0019879465],"genre_scores_gemma":[0.95623237,0.00029241428,0.01906261,0.0001261135,0.00008317529,0.0003147834,0.02182963,0.00038951257,0.0016692475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99450314,0.0012004692,0.0005639468,0.0027657493,0.0007678019,0.00019889935],"domain_scores_gemma":[0.98078096,0.0067651644,0.0016884956,0.005706845,0.00455973,0.000498747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007920822,0.0011035091,0.0010953717,0.0011596793,0.0010872191,0.001315503,0.0009976983,0.0011021344,0.0010540762],"category_scores_gemma":[0.023723971,0.0003220436,0.0010131076,0.0008478868,0.00092562335,0.0008313912,0.0014057384,0.0010277202,0.0010863609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004197915,0.001503177,0.5839049,0.0015227289,0.007975471,0.0015816459,0.0029735484,0.015982164,0.10444708,0.000915451,0.022595173,0.25240085],"study_design_scores_gemma":[0.00019791964,0.0025436624,0.9017449,0.00012111502,0.0017343063,0.0040449887,0.0005953162,0.03181503,0.03697813,0.0024432635,0.017550724,0.00023073088],"about_ca_topic_score_codex":0.0033306568,"about_ca_topic_score_gemma":0.008263442,"teacher_disagreement_score":0.007920822,"about_ca_system_score_codex":0.0004436602,"about_ca_system_score_gemma":0.00048317574,"threshold_uncertainty_score":0.041889787},"labels":[],"label_agreement":null},{"id":"W2739790172","doi":"10.1055/b-0034-91424","title":"Diffusion Tensor Imaging","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Child Health and Human Development; Michael Smith Health Research BC; U.S. Department of Energy","keywords":"Diffusion MRI; Diffusion; Tensor (intrinsic definition); Physics; Medicine; Mathematics; Geometry; Radiology; Magnetic resonance imaging","score_opus":0.05355543596820343,"score_gpt":0.3266532703954651,"score_spread":0.27309783442726165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739790172","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01584402,0.039685573,0.8186334,0.004043846,0.001310871,0.00056287856,0.018415963,0.007458597,0.094044946],"genre_scores_gemma":[0.13603476,0.041210297,0.7098382,0.0014898865,0.0012114217,0.0010723046,0.017335836,0.0028704132,0.0889368],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99954504,0.000093006696,0.000050181912,0.00012443477,0.00015945027,0.000027915848],"domain_scores_gemma":[0.9990909,0.0001847384,0.00013733568,0.00019130392,0.0003392976,0.00005640692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009704272,0.0011166906,0.00078852026,0.0027907516,0.0005681195,0.0028628008,0.0010345427,0.0011323834,0.03868706],"category_scores_gemma":[0.0032736466,0.0005239939,0.00065888575,0.0031190058,0.0004458289,0.0019443063,0.0016318028,0.0010233906,0.015635457],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014406058,0.000050568287,0.0036543794,0.002238188,0.00046019006,0.0007107132,0.0004332942,0.006888387,0.020102443,0.053983144,0.1600863,0.75124836],"study_design_scores_gemma":[0.000070527436,0.0001311951,0.0069606197,0.00063947827,0.00025474123,0.005586943,0.00026830498,0.049043637,0.01122594,0.08495349,0.84067917,0.0001859771],"about_ca_topic_score_codex":0.0018035724,"about_ca_topic_score_gemma":0.0027787401,"teacher_disagreement_score":0.03868706,"about_ca_system_score_codex":0.00046435156,"about_ca_system_score_gemma":0.0012875188,"threshold_uncertainty_score":0.12942106},"labels":[],"label_agreement":null},{"id":"W2741653274","doi":"","title":"Effects of mid sagittal plane selection on corpus callosal area","year":2006,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sagittal plane; Corpus callosum; Selection (genetic algorithm); Medicine; Artificial intelligence; Anatomy; Computer science","score_opus":0.06509693910491117,"score_gpt":0.2850036577089702,"score_spread":0.21990671860405903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741653274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97983927,0.00108116,0.01462092,0.00023645096,0.000112792986,0.00004493373,0.0013278333,0.00074263726,0.0019938443],"genre_scores_gemma":[0.9926916,0.0002716204,0.004690739,0.000045639095,0.00001542478,0.000031305488,0.0007329839,0.00046686188,0.0010539441],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994904,0.00018785552,0.000031160223,0.00007640202,0.00014435589,0.00006976987],"domain_scores_gemma":[0.99300283,0.005531804,0.00048138853,0.00036280847,0.00044488182,0.00017624664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009159484,0.00046488058,0.00037877256,0.00043644736,0.00019492835,0.00059867674,0.00022834093,0.00035107543,0.003946254],"category_scores_gemma":[0.012441636,0.00020825844,0.00028274886,0.0007619431,0.00037203994,0.0002766462,0.0003894297,0.0005454607,0.0006677016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.04736753,0.0005385873,0.04391485,0.00065852545,0.00043600053,0.0009121179,0.0006027234,0.04709527,0.6612256,0.0007341732,0.0038423103,0.1926724],"study_design_scores_gemma":[0.0003258944,0.0031964465,0.60641915,0.000076016084,0.00047997938,0.0015276737,0.00031118147,0.123280495,0.26014626,0.0008872128,0.0032229933,0.00012664968],"about_ca_topic_score_codex":0.004952425,"about_ca_topic_score_gemma":0.0032016553,"teacher_disagreement_score":0.004952425,"about_ca_system_score_codex":0.00031019532,"about_ca_system_score_gemma":0.0005140067,"threshold_uncertainty_score":0.013201475},"labels":[],"label_agreement":null},{"id":"W2742736294","doi":"10.1016/j.cortex.2017.07.021","title":"Processing speed and the relationship between Trail Making Test-B performance, cortical thinning and white matter microstructure in older adults","year":2017,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Biotechnology and Biological Sciences Research Council; Centre for Cognitive Ageing and Cognitive Epidemiology; Medical Research Council; University of Edinburgh; Age UK; Scottish Funding Council","keywords":"White matter; Psychology; Insula; Diffusion MRI; Grey matter; Trail Making Test; Audiology; Superior longitudinal fasciculus; Neuroscience; Fractional anisotropy; Cognition; Magnetic resonance imaging; Medicine","score_opus":0.04840686680783762,"score_gpt":0.34533061655337793,"score_spread":0.2969237497455403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2742736294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997774,0.00006727791,0.000031938318,0.000004667563,0.0000012449027,0.0000015381939,0.000046947847,0.000001435392,0.000067528796],"genre_scores_gemma":[0.9995832,0.00005239131,0.0000994568,0.0000042953143,0.000004041225,0.0000027554265,0.00010419128,0.0000012472809,0.00014852792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998822,0.000020521207,0.000026219152,0.000028425899,0.000023266128,0.00001936294],"domain_scores_gemma":[0.9985214,0.00027521138,0.0008184938,0.00010862045,0.0001346632,0.0001416621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005426094,0.000391478,0.00021430949,0.00076623727,0.00022978477,0.00041367696,0.0001578251,0.0003156156,0.00097307726],"category_scores_gemma":[0.0034799501,0.0002419879,0.00020902198,0.0004750503,0.00019872803,0.00040530553,0.00031145028,0.0003216781,0.00015839332],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030342562,0.000036889585,0.99718803,0.000006400284,0.00006185849,0.000043662065,0.000095327356,0.000074452946,0.00048239206,0.000013356266,0.000026871088,0.0016673219],"study_design_scores_gemma":[0.0000037308218,0.00010610628,0.9994789,0.0000017255464,0.000014084017,0.00009395306,0.000038370446,0.00013928545,0.00006727175,0.00003135709,0.000023563269,0.0000016627939],"about_ca_topic_score_codex":0.0029623697,"about_ca_topic_score_gemma":0.003655179,"teacher_disagreement_score":0.0029623697,"about_ca_system_score_codex":0.00012610307,"about_ca_system_score_gemma":0.00013088994,"threshold_uncertainty_score":0.00589025},"labels":[],"label_agreement":null},{"id":"W2744387978","doi":"10.1049/htl.2017.0073","title":"Multimodal connectivity based eloquence score computation and visualisation for computer‐aided neurosurgical path planning","year":2017,"lang":"en","type":"article","venue":"Healthcare Technology Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Modalities; Artificial intelligence; Heuristics; Neuroimaging; Visualization; Machine learning; Pattern recognition (psychology); Neuroscience","score_opus":0.1292244648341827,"score_gpt":0.42820420481652344,"score_spread":0.29897973998234073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2744387978","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034013588,0.00029124925,0.9602698,0.00025834772,0.000022037535,0.00009300224,0.00036595194,0.0031447918,0.0015412597],"genre_scores_gemma":[0.46764845,0.00050371786,0.5292148,0.00006201909,0.000036586905,0.00025172363,0.00047429564,0.00035294495,0.0014554724],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998921,0.000034469766,0.000007669329,0.000015339427,0.000038630118,0.0000117847685],"domain_scores_gemma":[0.9996562,0.00020591417,0.00003657983,0.000024697814,0.000057181827,0.000019450259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034199678,0.0006896868,0.00031077754,0.0017707725,0.00022086775,0.001070979,0.00042182472,0.0005516412,0.005108693],"category_scores_gemma":[0.002350324,0.00026152623,0.00035582614,0.0006723342,0.00019784586,0.0005398137,0.00074822584,0.0003966922,0.00041527182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034285334,0.000095492825,0.0030856626,0.0003110553,0.00010758358,0.0005697699,0.00044718722,0.35679895,0.03695999,0.013401928,0.00923604,0.5786435],"study_design_scores_gemma":[0.0000098536075,0.00003085283,0.0010595673,0.00002510466,0.000014579863,0.00013949594,0.000040319534,0.9849368,0.005419097,0.005861827,0.0024433252,0.000019274477],"about_ca_topic_score_codex":0.0039421064,"about_ca_topic_score_gemma":0.0054097855,"teacher_disagreement_score":0.005108693,"about_ca_system_score_codex":0.00044303175,"about_ca_system_score_gemma":0.0006333593,"threshold_uncertainty_score":0.017090261},"labels":[],"label_agreement":null},{"id":"W2745760221","doi":"10.1371/journal.pone.0182340","title":"Detailing neuroanatomical development in late childhood and early adolescence using NODDI","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":134,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; University of Calgary","keywords":"White matter; Diffusion MRI; Neurite; Neuroscience; Fractional anisotropy; Grey matter; Brain mapping; Axon; Gray (unit); Biology; Psychology; Magnetic resonance imaging; Medicine; Nuclear medicine; Radiology","score_opus":0.12787531040316102,"score_gpt":0.3233294250417209,"score_spread":0.19545411463855988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2745760221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849886,0.0009217778,0.008946152,0.00006687392,0.00001196491,0.00005010546,0.0021555559,0.00010534158,0.0027536016],"genre_scores_gemma":[0.97167754,0.0010213072,0.023734612,0.00002336919,0.0000064045257,0.00009033134,0.0021261189,0.000052979634,0.0012672754],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984944,0.000026093621,0.00002024212,0.0000431433,0.000029980749,0.00003098706],"domain_scores_gemma":[0.9996202,0.00008004063,0.00010986952,0.000035991194,0.00011554641,0.000038254046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006090544,0.000326668,0.00023703108,0.0018561542,0.00023108855,0.0005393886,0.00019560306,0.00017701078,0.00091100176],"category_scores_gemma":[0.0012287257,0.00016763547,0.00021871201,0.0011310617,0.00017907645,0.00029891872,0.00040193138,0.00027159834,0.00024044495],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021813762,0.00006073544,0.86153394,0.00028451893,0.00009916987,0.0009052839,0.0018617827,0.001052833,0.06391312,0.0009786562,0.0008858535,0.06820599],"study_design_scores_gemma":[0.0000027416245,0.000051085095,0.98585063,0.000036401092,0.000030301746,0.00079643447,0.0007448537,0.0019124738,0.007219497,0.00038670556,0.002954828,0.000013965968],"about_ca_topic_score_codex":0.007854083,"about_ca_topic_score_gemma":0.025616217,"teacher_disagreement_score":0.007854083,"about_ca_system_score_codex":0.00027210687,"about_ca_system_score_gemma":0.00046907619,"threshold_uncertainty_score":0.015616715},"labels":[],"label_agreement":null},{"id":"W2747350130","doi":"10.1503/jpn.170137","title":"The neurobiology of transition to psychosis: clearing the cache","year":2017,"lang":"en","type":"letter","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Psychosis; Endophenotype; Psychology; Neuroscience; Schizophrenia (object-oriented programming); Prodrome; Psychiatry; Cognition","score_opus":0.05652825236951737,"score_gpt":0.35981618978687224,"score_spread":0.3032879374173549,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747350130","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004434415,0.00802828,0.00011893139,0.97410077,0.016513012,0.000004510346,0.000009718101,0.0000140186685,0.00076720136],"genre_scores_gemma":[0.010999734,0.020247655,0.00050923036,0.7890445,0.1758613,0.000027705513,0.000022578704,0.000018116321,0.003269218],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998922,0.00039739464,0.00016102473,0.00013012154,0.00028558288,0.00010399206],"domain_scores_gemma":[0.99340326,0.0038753496,0.0004046258,0.00028264412,0.0012529279,0.000781226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021066412,0.0005430277,0.001322756,0.0005671946,0.0020818044,0.002088642,0.0017977254,0.024860736,0.0023794863],"category_scores_gemma":[0.013863055,0.00033821713,0.00060788647,0.0003513413,0.0041739037,0.0058374866,0.0015147597,0.029639818,0.0023381882],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007942684,0.00006721136,0.0007681197,0.00032387226,0.000024919176,0.009423333,0.00043411745,0.00012114797,0.0006188684,0.009023816,0.9383867,0.04072844],"study_design_scores_gemma":[0.00014068572,0.00012978338,0.0017009885,0.0012749485,0.00003633745,0.01938987,0.0014891534,0.00075581175,0.0005297225,0.05826219,0.9161898,0.00010066808],"about_ca_topic_score_codex":0.0021415325,"about_ca_topic_score_gemma":0.004316591,"teacher_disagreement_score":0.024860736,"about_ca_system_score_codex":0.0024861523,"about_ca_system_score_gemma":0.00252238,"threshold_uncertainty_score":0.018038392},"labels":[],"label_agreement":null},{"id":"W2748010953","doi":"10.1002/hbm.23768","title":"Changes to white matter microstructure in transient ischemic attack: A longitudinal diffusion tensor imaging study","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Campbell Scientific (Canada); Heart and Stroke Foundation; Sunnybrook Health Science Centre; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Cingulum (brain); Fractional anisotropy; Diffusion MRI; White matter; Corticospinal tract; Superior longitudinal fasciculus; Fasciculus; Medicine; Cardiology; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.08835072668025683,"score_gpt":0.3771940305671938,"score_spread":0.28884330388693696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748010953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99941313,0.00014543536,0.0001257599,0.000033409287,0.000002704263,0.000011099178,0.000094679024,0.0000036458437,0.00017017002],"genre_scores_gemma":[0.9992723,0.00009039206,0.0001758272,0.000013794064,0.0000070339797,0.000009263211,0.00024872768,0.0000020639236,0.0001806334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987435,0.000022005059,0.000016537344,0.0000382814,0.000022194192,0.000026555825],"domain_scores_gemma":[0.9990926,0.00004974513,0.00043208007,0.00008916978,0.0001757369,0.00016068095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078805257,0.00023765361,0.00019313066,0.00057537813,0.0005043658,0.0004488377,0.0002025763,0.00043306904,0.0009116356],"category_scores_gemma":[0.0017647714,0.00023628738,0.0003098941,0.000400495,0.00024871243,0.000564594,0.00035432674,0.00039730797,0.00025320225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006361016,0.00023432462,0.98568267,0.000024971916,0.00017359157,0.00039548991,0.000784034,0.00009148907,0.0078097596,0.00004329071,0.00014156828,0.0039827717],"study_design_scores_gemma":[0.000007687146,0.00025403002,0.9987877,0.000004517618,0.00003790435,0.00032224163,0.00012361757,0.0001352672,0.00016043935,0.000028986817,0.00013300407,0.000004719565],"about_ca_topic_score_codex":0.005986961,"about_ca_topic_score_gemma":0.0074915006,"teacher_disagreement_score":0.005986961,"about_ca_system_score_codex":0.0002721572,"about_ca_system_score_gemma":0.00038169505,"threshold_uncertainty_score":0.01190424},"labels":[],"label_agreement":null},{"id":"W2748088957","doi":"10.3233/jad-170341","title":"White Matter Degradation is Associated with Reduced Financial Capacity in Mild Cognitive Impairment and Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; McGill University","keywords":"Cognitive impairment; White matter; Disease; Medicine; Psychology; Internal medicine; Magnetic resonance imaging","score_opus":0.09728137444753973,"score_gpt":0.344950787508043,"score_spread":0.24766941306050325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748088957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99944156,0.00022694688,0.000029399751,0.0000201649,0.0000021899677,0.000004680864,0.000053461357,0.000002014052,0.0002196647],"genre_scores_gemma":[0.9996841,0.000066397726,0.00005487719,0.000013237945,0.000005689466,0.0000023417044,0.000085628104,8.793661e-7,0.00008681942],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978656,0.00003152578,0.000044824475,0.000058863934,0.000044521224,0.000033658507],"domain_scores_gemma":[0.9984415,0.00014491037,0.0010062881,0.00008821993,0.0001364149,0.00018266802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046854754,0.00042327226,0.00041507615,0.0014134881,0.0005983265,0.0004542432,0.00028948305,0.00046257998,0.0010611498],"category_scores_gemma":[0.0028690365,0.00026848412,0.00029529026,0.00091551215,0.0005275918,0.00047932187,0.0004970739,0.00040311727,0.0001319345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075766165,0.00008924541,0.99330395,0.000025239242,0.00010899387,0.00042767383,0.0003276532,0.00007108781,0.0014860752,0.00004143321,0.000086738524,0.003274205],"study_design_scores_gemma":[0.0000027020226,0.000054054315,0.9994684,0.0000022542895,0.000010873243,0.00025803543,0.00004477065,0.00004054524,0.000053293377,0.00003462737,0.000028923838,0.0000014746297],"about_ca_topic_score_codex":0.008839844,"about_ca_topic_score_gemma":0.010276708,"teacher_disagreement_score":0.008839844,"about_ca_system_score_codex":0.0003099718,"about_ca_system_score_gemma":0.00023236692,"threshold_uncertainty_score":0.017576814},"labels":[],"label_agreement":null},{"id":"W2748573512","doi":"10.1007/s00247-017-3955-1","title":"Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children","year":2017,"lang":"en","type":"article","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Cancer Institute; Foundation for the National Institutes of Health","keywords":"Corpus callosum; Diffusion MRI; White matter; Medicine; Neuroradiology; Term (time); Neurology; Radiology; Magnetic resonance imaging; Pathology; Psychiatry; Physics; Astronomy","score_opus":0.0172452671509386,"score_gpt":0.3154845928209104,"score_spread":0.2982393256699718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748573512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99935323,0.00033155514,0.000035816287,0.000031079384,0.0000033788979,0.0000027459403,0.000070967806,0.000001402382,0.00016982488],"genre_scores_gemma":[0.9990821,0.00044955814,0.0000634627,0.000016868353,0.000012070361,0.000007208078,0.0001573225,0.000005630621,0.00020585481],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997689,0.000045806806,0.00001830537,0.00004963744,0.000035200166,0.00008211091],"domain_scores_gemma":[0.99907047,0.000291381,0.00029833385,0.00006511387,0.00009388225,0.0001808941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040132413,0.00040497055,0.00053240836,0.0005419478,0.0005746903,0.00040515742,0.0004224487,0.00060409616,0.00056565594],"category_scores_gemma":[0.0015732679,0.00028604732,0.00068475,0.0007894536,0.0010516308,0.00050470745,0.00038761413,0.00073561457,0.00017096194],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003887786,0.0012358258,0.94818836,0.00018464826,0.00044234828,0.014921065,0.001364269,0.0011644805,0.016008507,0.00019364373,0.00048415392,0.011924899],"study_design_scores_gemma":[0.00002818727,0.0013822505,0.99027133,0.000014425497,0.00017663561,0.004943389,0.000628747,0.00013732017,0.0018436289,0.000041087405,0.00051044085,0.000022652264],"about_ca_topic_score_codex":0.011833121,"about_ca_topic_score_gemma":0.0102536045,"teacher_disagreement_score":0.011833121,"about_ca_system_score_codex":0.00083311443,"about_ca_system_score_gemma":0.00079664297,"threshold_uncertainty_score":0.023528516},"labels":[],"label_agreement":null},{"id":"W2749066460","doi":"10.1016/j.neulet.2017.08.036","title":"A structural motor network correlates with motor function and not impairment post stroke","year":2017,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Heart and Stroke Foundation of Canada","keywords":"Motor function; Physical medicine and rehabilitation; Motor impairment; Stroke (engine); Psychology; Neuroscience; Medicine; Physics","score_opus":0.03164887749764121,"score_gpt":0.2926759741412607,"score_spread":0.26102709664361945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749066460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970348,0.00014035175,0.0007683644,0.00018169431,0.000008368114,0.0000098848095,0.00017526928,0.000011733611,0.0016696639],"genre_scores_gemma":[0.99898213,0.00008395833,0.00021884916,0.000020521982,0.000019749092,0.000007849279,0.00015070474,0.0000035612748,0.0005126339],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999876,0.000020156493,0.000013728986,0.000035305206,0.000017193654,0.000037643316],"domain_scores_gemma":[0.998863,0.00026720148,0.0005367819,0.0001022201,0.000120246405,0.00011056287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025330004,0.00026765678,0.00020031826,0.00070393557,0.00031978477,0.0005215143,0.00030628862,0.0004609428,0.0036462294],"category_scores_gemma":[0.0021942307,0.00016525599,0.00018008087,0.00055361516,0.0004621582,0.0009063805,0.00044770594,0.0003418641,0.00042979783],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017405461,0.00024095865,0.91823447,0.0000786297,0.00034900688,0.001654847,0.00033075293,0.0013095387,0.03690727,0.0010345526,0.00084527634,0.037274145],"study_design_scores_gemma":[0.00000719952,0.00014244104,0.9943895,0.000010077389,0.000054335425,0.0012203327,0.00013840741,0.0013475794,0.0012948624,0.0011998486,0.00019013368,0.0000052664427],"about_ca_topic_score_codex":0.0025071262,"about_ca_topic_score_gemma":0.005923722,"teacher_disagreement_score":0.0036462294,"about_ca_system_score_codex":0.0002901686,"about_ca_system_score_gemma":0.0003111541,"threshold_uncertainty_score":0.012197852},"labels":[],"label_agreement":null},{"id":"W2749107595","doi":"10.3389/fninf.2017.00054","title":"Fiberweb: Diffusion Visualization and Processing in the Browser","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Diffusion; Computer graphics (images); World Wide Web; Data mining; Physics","score_opus":0.047445804040137055,"score_gpt":0.35520976726546644,"score_spread":0.3077639632253294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749107595","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004220367,0.0005110597,0.77530324,0.0004398633,0.00015156234,0.00015021146,0.0025482133,0.21341737,0.0032581736],"genre_scores_gemma":[0.08187327,0.0014645223,0.827144,0.0006305564,0.0002268434,0.00073062436,0.011533783,0.06436932,0.012026921],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991744,0.00017141073,0.00010266001,0.00015890272,0.0003009635,0.000091588176],"domain_scores_gemma":[0.9971898,0.0009404152,0.000122054655,0.00071040203,0.0006880195,0.0003492066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001991282,0.0020088905,0.0010056166,0.0019884175,0.0005085599,0.0028681445,0.0018589683,0.0017444661,0.028086388],"category_scores_gemma":[0.006585559,0.0009169984,0.0012565074,0.0010316544,0.00058011967,0.003839495,0.0035240331,0.0018247736,0.010193527],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002049012,0.00041396296,0.0061163222,0.0012618097,0.00057699485,0.001669146,0.0016519921,0.014775669,0.07159764,0.04183253,0.30827752,0.5497773],"study_design_scores_gemma":[0.00075839076,0.00028563602,0.003616038,0.0004006708,0.00016378154,0.0025120932,0.00028985174,0.32980374,0.117016256,0.06432272,0.4804175,0.00041342218],"about_ca_topic_score_codex":0.0036008628,"about_ca_topic_score_gemma":0.002944359,"teacher_disagreement_score":0.028086388,"about_ca_system_score_codex":0.0004698056,"about_ca_system_score_gemma":0.0016485292,"threshold_uncertainty_score":0.09395838},"labels":[],"label_agreement":null},{"id":"W2749609967","doi":"10.1002/nbm.3793","title":"User‐independent diffusion tensor imaging analysis pipelines in a rat model presenting ventriculomegalia: A comparison study","year":2017,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal","funders":"Institute of Human Development, Child and Youth Health; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Tensor (intrinsic definition); Pipeline transport; Computer science; Geology; Magnetic resonance imaging; Mathematics; Chemistry; Medicine; Radiology; Geometry","score_opus":0.07894206902046202,"score_gpt":0.42113731132863275,"score_spread":0.3421952423081707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749609967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98761415,0.00062138133,0.010670723,0.000048111255,0.000060220398,0.00012846672,0.0003783861,0.00022909712,0.0002493323],"genre_scores_gemma":[0.96489334,0.0019037399,0.029143574,0.00007819266,0.000041119212,0.00044127015,0.0014148805,0.00022933888,0.0018545853],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99939275,0.00011051953,0.00007311001,0.00014786483,0.00017485271,0.000100762954],"domain_scores_gemma":[0.99855775,0.00021434593,0.00029756318,0.00034030358,0.00041748103,0.0001725379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014597796,0.0010073829,0.0007509771,0.0011519371,0.00026202438,0.0006114338,0.00067810225,0.0007859812,0.0007704998],"category_scores_gemma":[0.0017837886,0.00043147788,0.0010767991,0.00039380055,0.0005953937,0.0008081571,0.00051603763,0.00084870006,0.00038188393],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012777911,0.0068323677,0.012807538,0.0011368844,0.0011356462,0.00078336056,0.0007212033,0.016126525,0.85395896,0.0007519742,0.001503146,0.09146449],"study_design_scores_gemma":[0.00084483763,0.13616282,0.079171784,0.000200678,0.0028423977,0.0029238998,0.00088710216,0.104610674,0.6638108,0.0010574117,0.0070065754,0.00048111606],"about_ca_topic_score_codex":0.0028167337,"about_ca_topic_score_gemma":0.00290545,"teacher_disagreement_score":0.0028167337,"about_ca_system_score_codex":0.00047624003,"about_ca_system_score_gemma":0.00059469446,"threshold_uncertainty_score":0.007720113},"labels":[],"label_agreement":null},{"id":"W2749934906","doi":"10.1007/s11682-017-9758-z","title":"Abnormal relationships between local and global brain measures in subjects at clinical high risk for psychosis: a pilot study","year":2017,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Gender and Health","funders":"National Center for Research Resources; National Institute of Mental Health; Harvard University","keywords":"Brain size; White matter; Psychology; Psychosis; Lateral ventricles; Grey matter; Magnetic resonance imaging; Temporal lobe; Amygdala; Neuropsychology; Lateralization of brain function; Neuroscience; Cardiology; Internal medicine; Medicine; Cognition; Radiology; Psychiatry","score_opus":0.197856411745396,"score_gpt":0.4484658028593476,"score_spread":0.25060939111395164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749934906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997004,0.000023321161,0.000049566115,0.000008449765,0.0000017448021,0.000019544948,0.000036611218,0.0000019054,0.00015836173],"genre_scores_gemma":[0.9996598,0.000020871375,0.00008521301,0.000009912943,0.0000051712973,0.000021901358,0.00006823128,0.0000017254933,0.00012712028],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997104,0.00011276333,0.000018492443,0.000063403975,0.0000475927,0.00004738772],"domain_scores_gemma":[0.9987702,0.0004319435,0.00022983378,0.00014027434,0.00011993312,0.0003079278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061330263,0.0005761571,0.0005876239,0.00072471524,0.0010757365,0.00058485003,0.00033479018,0.0005546554,0.0018998076],"category_scores_gemma":[0.0020865342,0.00031683056,0.0002946359,0.00050499715,0.0009632541,0.00057385286,0.00070724625,0.00072710676,0.00036928497],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007911065,0.002985869,0.95971984,0.000054404056,0.00014293904,0.0028680314,0.0028939983,0.00011949976,0.0156321,0.00010976661,0.00017505445,0.0073873005],"study_design_scores_gemma":[0.00014059723,0.0041838954,0.99264526,0.0000029966536,0.000058218353,0.001179571,0.0009600172,0.00015365328,0.00044971032,0.00010534423,0.00011004882,0.000010569407],"about_ca_topic_score_codex":0.0038290243,"about_ca_topic_score_gemma":0.0048827613,"teacher_disagreement_score":0.0038290243,"about_ca_system_score_codex":0.0003643934,"about_ca_system_score_gemma":0.00039478592,"threshold_uncertainty_score":0.00761348},"labels":[],"label_agreement":null},{"id":"W2750443165","doi":"10.1016/j.nicl.2017.08.020","title":"Emotion detection deficits and changes in personality traits linked to loss of white matter integrity in primary progressive aphasia","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Occupational Cancer Research Centre; Toronto Western Hospital; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Larry L. Hillblom Foundation","keywords":"White matter; Uncinate fasciculus; Inferior longitudinal fasciculus; Psychology; Diffusion MRI; Audiology; Inferior frontal gyrus; Frontotemporal lobar degeneration; Neuroscience; Frontotemporal dementia; Medicine; Fractional anisotropy; Cognition; Internal medicine; Dementia; Magnetic resonance imaging; Radiology","score_opus":0.13711604485848117,"score_gpt":0.4352336571927776,"score_spread":0.29811761233429646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750443165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974185,0.00003793748,0.000045804256,0.0000059163267,0.0000010101496,0.0000041408234,0.000029950888,0.0000032567657,0.00013013672],"genre_scores_gemma":[0.9997625,0.000021597345,0.000066667024,0.000006116534,0.0000025217885,0.000004064458,0.000053603926,0.0000010576031,0.000081831924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998259,0.00002831073,0.000030618292,0.000059739,0.00003264156,0.000022828264],"domain_scores_gemma":[0.9995053,0.000100348785,0.00020906505,0.00004340019,0.00003833788,0.000103471815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025303452,0.00045235036,0.0002801207,0.0010951995,0.0004146269,0.0004124113,0.00019890662,0.00032211145,0.001450854],"category_scores_gemma":[0.0013119589,0.00025164607,0.00024625962,0.0003328244,0.0005642742,0.00029645354,0.00043408168,0.000316765,0.00022124355],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011735891,0.00019800909,0.95888853,0.00004901812,0.00016415169,0.006047454,0.0007230797,0.00020070803,0.021046534,0.00007255526,0.00013414625,0.01130206],"study_design_scores_gemma":[0.000011193864,0.0002449204,0.9938259,0.0000035639275,0.000019239014,0.0052273064,0.00011425159,0.00013573756,0.00030456198,0.00007583917,0.000034444234,0.0000029921744],"about_ca_topic_score_codex":0.0022531054,"about_ca_topic_score_gemma":0.002637617,"teacher_disagreement_score":0.0022531054,"about_ca_system_score_codex":0.00024471275,"about_ca_system_score_gemma":0.00017789299,"threshold_uncertainty_score":0.004853606},"labels":[],"label_agreement":null},{"id":"W2750953308","doi":"10.1167/17.10.584","title":"Model-based functional segmentation of the human lateral geniculate nucleus","year":2017,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Lateral geniculate nucleus; Neuroscience; Parvocellular cell; Receptive field; Visual cortex; Thalamus; Geniculate; Functional magnetic resonance imaging; Psychology; Computer science; Nucleus","score_opus":0.08630416084600195,"score_gpt":0.40165920521147247,"score_spread":0.3153550443654705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750953308","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17442772,0.00080754294,0.80800956,0.0008036302,0.00010908965,0.00011699214,0.0007161274,0.0016109563,0.013398372],"genre_scores_gemma":[0.890857,0.00032455803,0.10486048,0.00013412158,0.000028546197,0.00012322451,0.00061959855,0.00021125235,0.0028411015],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991286,0.000019990739,0.0000036865135,0.000029880857,0.000019824787,0.00001377608],"domain_scores_gemma":[0.9999211,0.000032746066,0.000011180095,0.00001228596,0.000014853018,0.000007742319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018484589,0.00040745852,0.00034650124,0.00037950755,0.00024078702,0.00058968016,0.0007980448,0.00089735474,0.002604421],"category_scores_gemma":[0.00055537745,0.0002579946,0.00080803584,0.00024058895,0.00044413857,0.00033380982,0.00047485813,0.0003610348,0.00034855024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011861466,0.000023167935,0.0009539391,0.00005810415,0.00003518895,0.00011087748,0.00008500072,0.9593928,0.014833263,0.0069697457,0.0010067167,0.01641271],"study_design_scores_gemma":[0.000009143028,0.000010967021,0.00029726385,0.0000033905271,0.000004391553,0.00002687816,0.000006718912,0.99563533,0.00081211247,0.0026520775,0.0005367037,0.0000049805026],"about_ca_topic_score_codex":0.024130253,"about_ca_topic_score_gemma":0.023202453,"teacher_disagreement_score":0.024130253,"about_ca_system_score_codex":0.0013434195,"about_ca_system_score_gemma":0.0011991422,"threshold_uncertainty_score":0.047979593},"labels":[],"label_agreement":null},{"id":"W2751461426","doi":"10.1101/184978","title":"Brain white matter structure and language ability in preschool-aged children","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Psychology; Tractography; Lateralization of brain function; Developmental psychology; Corticospinal tract; Cognitive psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.015150891212742457,"score_gpt":0.2788213697264617,"score_spread":0.2636704785137193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751461426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99922836,0.0002750729,0.000035404522,0.000016772578,0.0000026769433,0.0000029538635,0.00021039665,0.000010133712,0.00021827001],"genre_scores_gemma":[0.9989806,0.00022721093,0.00018908638,0.00001647817,0.0000029042403,0.0000069625994,0.0002532317,0.0000046131318,0.00031886288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984944,0.000013079657,0.000018178105,0.000040473144,0.000028015309,0.000050755883],"domain_scores_gemma":[0.9994209,0.00008875935,0.000272199,0.000030134348,0.0000805616,0.00010751452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004335042,0.00041453834,0.00048554214,0.0019437611,0.0004254946,0.0007521689,0.00023224752,0.00054035115,0.0016057173],"category_scores_gemma":[0.0013105209,0.00029648523,0.00038996522,0.0006748063,0.0005309081,0.0005080299,0.0003483219,0.00046197276,0.000308341],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000379509,0.00013433448,0.9713371,0.000077224904,0.000071555936,0.0031782705,0.0015474358,0.00014144221,0.015069591,0.00009430092,0.00031366234,0.007655553],"study_design_scores_gemma":[0.0000025103734,0.000063421474,0.9984511,0.000006935575,0.000011880457,0.00056843413,0.00030235722,0.00002213326,0.0004566594,0.000023164906,0.00008905867,0.00000230525],"about_ca_topic_score_codex":0.019617254,"about_ca_topic_score_gemma":0.018127058,"teacher_disagreement_score":0.019617254,"about_ca_system_score_codex":0.0005458018,"about_ca_system_score_gemma":0.0003897075,"threshold_uncertainty_score":0.039006174},"labels":[],"label_agreement":null},{"id":"W2752410508","doi":"10.1002/nbm.3778","title":"A review of diffusion MRI of typical white matter development from early childhood to young adulthood","year":2017,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":414,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Calgary","funders":"Canada Research Chairs; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Diffusion imaging; Brain development; Psychology; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.08690828425249522,"score_gpt":0.4145742153961112,"score_spread":0.327665931143616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752410508","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012942641,0.9989537,0.00015275134,0.00024784397,0.00011968662,0.0000057500383,0.000061135186,0.000007354839,0.00032235758],"genre_scores_gemma":[0.0006446601,0.99842215,0.00032881615,0.00019322749,0.00019249234,0.0000114822615,0.0000659721,0.0000029454206,0.00013831898],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931455,0.00014035212,0.00022711592,0.00016219607,0.00012009168,0.00003574185],"domain_scores_gemma":[0.9976707,0.0014410401,0.00041229668,0.000044941393,0.00036366394,0.000067297115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012998311,0.0014843585,0.0020459527,0.008339484,0.00036128375,0.0011075104,0.0011782848,0.0012288925,0.0029848674],"category_scores_gemma":[0.0035965438,0.0007441974,0.0011463069,0.0067505282,0.0008332617,0.0022419014,0.0007005796,0.001255982,0.0014613695],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017647525,0.0000524779,0.0013970344,0.0947634,0.00039605692,0.00061364373,0.0003466942,0.0004473088,0.0012778328,0.002334779,0.045608707,0.8525856],"study_design_scores_gemma":[0.000023039578,0.0002271519,0.013142526,0.062361542,0.0009475021,0.009106891,0.00028291464,0.00021594291,0.00082939793,0.0027243388,0.9100347,0.00010403154],"about_ca_topic_score_codex":0.0043344395,"about_ca_topic_score_gemma":0.005245724,"teacher_disagreement_score":0.008339484,"about_ca_system_score_codex":0.0012171072,"about_ca_system_score_gemma":0.0020134107,"threshold_uncertainty_score":0.009985447},"labels":[],"label_agreement":null},{"id":"W2753002091","doi":"10.1007/978-3-319-66182-7_71","title":"q-Space Upsampling Using x-q Space Regularization","year":2017,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism","keywords":"Upsampling; Computer science; Interpolation (computer graphics); Regularization (linguistics); Algorithm; Space (punctuation); ENCODE; Diffusion MRI; Graph; Artificial intelligence; Pattern recognition (psychology); Theoretical computer science; Image (mathematics)","score_opus":0.07985640111280169,"score_gpt":0.3800472213559094,"score_spread":0.3001908202431077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753002091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030127943,0.000101013444,0.99595463,0.000079720056,0.00003991745,0.000023658518,0.000034629855,0.00023062066,0.0005230261],"genre_scores_gemma":[0.094736144,0.0002587866,0.90106153,0.00019401974,0.00008092019,0.000089311776,0.00027684087,0.00018461655,0.0031178256],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994537,0.00017341244,0.000032004526,0.00008112012,0.00020031176,0.0000593813],"domain_scores_gemma":[0.999094,0.00031974353,0.000055650275,0.00025107828,0.00021911177,0.000060413222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001659169,0.0007147633,0.0008668148,0.00066712435,0.00043524726,0.0010691432,0.0011085264,0.0014193193,0.00428009],"category_scores_gemma":[0.0031001964,0.00045291212,0.0010646366,0.00092920737,0.0007093533,0.00096326927,0.0016428134,0.0016577999,0.0011829817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005582932,0.00031157274,0.002019438,0.00041034239,0.00022910199,0.00022244963,0.00025958478,0.2698912,0.06191754,0.13468671,0.012972742,0.5165211],"study_design_scores_gemma":[0.000017332228,0.000024668341,0.00018040283,0.00000985518,0.000016952312,0.00006385824,0.0000136648405,0.98083717,0.005663118,0.009951719,0.0032118752,0.000009482453],"about_ca_topic_score_codex":0.00458282,"about_ca_topic_score_gemma":0.0050119986,"teacher_disagreement_score":0.00458282,"about_ca_system_score_codex":0.00043278388,"about_ca_system_score_gemma":0.0013791445,"threshold_uncertainty_score":0.014318347},"labels":[],"label_agreement":null},{"id":"W2753319834","doi":"10.7759/cureus.1637","title":"Ischemic Stroke of Midbrain and Cerebellum Involving Reticular Activating System&#x0D;","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Abbott (Canada)","funders":"","keywords":"Reticular activating system; Medicine; Midbrain; Midbrain reticular formation; Reticular connective tissue; Cerebellum; Stroke (engine); Neuroscience; Sleep (system call); Reticular formation; Central nervous system; Anatomy; Internal medicine; Psychology","score_opus":0.07133301111960438,"score_gpt":0.35184238681472607,"score_spread":0.2805093756951217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753319834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9420092,0.005948754,0.004342769,0.0033641167,0.00018928092,0.0002465799,0.00038569255,0.00031349823,0.043199997],"genre_scores_gemma":[0.99423933,0.00096154696,0.0007261668,0.00075079355,0.00017837535,0.000018926716,0.000117006966,0.000013848176,0.0029939446],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99982315,0.000014033567,0.000018837569,0.00004204675,0.000024050642,0.00007784476],"domain_scores_gemma":[0.9997956,0.00003363766,0.00007976676,0.000020859068,0.000020295733,0.00004989744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000091368274,0.0008482869,0.00044938677,0.0009961306,0.0011244027,0.00053363456,0.0005725384,0.0012876146,0.004128487],"category_scores_gemma":[0.0005622454,0.00033459326,0.00033932622,0.00071800925,0.0010033567,0.0009430332,0.0004336629,0.0009964491,0.0008868352],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068762805,0.000049156482,0.012495838,0.00006478905,0.000027029506,0.97597927,0.00013003929,0.00008258275,0.0031756344,0.00079392333,0.00090044155,0.0062325443],"study_design_scores_gemma":[0.00001901994,0.00008298803,0.016076546,0.000017775055,0.00001599466,0.9807567,0.00007193923,0.00022069462,0.0012696533,0.00038126032,0.0010773167,0.000010114004],"about_ca_topic_score_codex":0.007104382,"about_ca_topic_score_gemma":0.010540473,"teacher_disagreement_score":0.007104382,"about_ca_system_score_codex":0.0011326519,"about_ca_system_score_gemma":0.00080230716,"threshold_uncertainty_score":0.014126062},"labels":[],"label_agreement":null},{"id":"W2753663815","doi":"10.1523/eneuro.0164-17.2017","title":"Defining an Analytic Framework to Evaluate Quantitative MRI Markers of Traumatic Axonal Injury: Preliminary Results in a Mouse Closed Head Injury Model","year":2017,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; Center for Neuroscience and Regenerative Medicine; National Institutes of Health; W. Garfield Weston Foundation; Weston Brain Institute","keywords":"Diffusion MRI; Gliosis; Fractional anisotropy; Diffuse axonal injury; Magnetic resonance imaging; Traumatic brain injury; Pathology; White matter; Histology; Neuroscience; Medicine; Radiology; Biology","score_opus":0.13491145599568424,"score_gpt":0.45354494014850644,"score_spread":0.3186334841528222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753663815","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047227744,0.00056519755,0.94979185,0.00017021496,0.000015289092,0.00026207286,0.00033145974,0.00028932234,0.0013468921],"genre_scores_gemma":[0.3654292,0.0009589969,0.63092613,0.000085756765,0.00003276418,0.0009061586,0.0006997718,0.0001622335,0.00079902576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99865144,0.00042772968,0.00010480297,0.00020143665,0.0005275891,0.00008700337],"domain_scores_gemma":[0.9968623,0.0013693796,0.0007015316,0.00024152207,0.00073439436,0.00009090332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054069953,0.0012837914,0.0008992785,0.0026547331,0.00040561205,0.0014428735,0.0008874041,0.0007044543,0.0009424471],"category_scores_gemma":[0.008388319,0.0003160097,0.00090964296,0.0012248935,0.0010319208,0.0010113964,0.0013070729,0.0012286964,0.0003567036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005046522,0.0006870592,0.010407243,0.0008789389,0.000248749,0.00060570514,0.00037289358,0.56316805,0.19864301,0.07685341,0.0015800063,0.14605021],"study_design_scores_gemma":[0.000015250737,0.0005113536,0.002746445,0.00006255755,0.000054103635,0.00016812209,0.00008515821,0.963123,0.017594337,0.013541572,0.0020462603,0.000051914576],"about_ca_topic_score_codex":0.002411324,"about_ca_topic_score_gemma":0.0015403712,"teacher_disagreement_score":0.0054069953,"about_ca_system_score_codex":0.0011222109,"about_ca_system_score_gemma":0.0010371953,"threshold_uncertainty_score":0.028595269},"labels":[],"label_agreement":null},{"id":"W2753814260","doi":"10.1007/978-3-319-67159-8_5","title":"Interactive Computation and Visualization of Structural Connectomes in Real-Time","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Medical Research Council","keywords":"Visualization; Computer science; Graph drawing; Connectome; GRASP; Connectomics; Computation; Theoretical computer science; Graph; Node (physics); Enhanced Data Rates for GSM Evolution; On the fly; Graph theory; Perspective (graphical); Artificial intelligence; Algorithm; Functional connectivity; Mathematics; Engineering","score_opus":0.03936564957441193,"score_gpt":0.37807853417676957,"score_spread":0.33871288460235766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753814260","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024417743,0.0008115485,0.95073664,0.00089286134,0.00016378149,0.00008737654,0.0016161046,0.015702736,0.0055712187],"genre_scores_gemma":[0.20621847,0.0019843678,0.77591896,0.00030499644,0.0001862009,0.00032147602,0.002082973,0.0038431084,0.0091395285],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983084,0.000032687014,0.00001043511,0.000032503733,0.00006972691,0.00002371506],"domain_scores_gemma":[0.9990491,0.00064879877,0.00004455581,0.00008821588,0.00009192144,0.00007735897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006292783,0.0010015635,0.0006072147,0.0013417574,0.0004452341,0.0028716922,0.001497824,0.0011463286,0.025700014],"category_scores_gemma":[0.0023692101,0.0005770136,0.0008579137,0.0012085151,0.00048275533,0.0012406483,0.0016904507,0.0012305441,0.002539049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009746511,0.00018555528,0.0016917629,0.0017045772,0.0003393414,0.0012758204,0.0014946494,0.17913885,0.13806829,0.04451901,0.07123437,0.5593731],"study_design_scores_gemma":[0.00013931369,0.00008334111,0.002259366,0.00015758107,0.00008686765,0.0009407294,0.0002780059,0.85836554,0.035784084,0.060858034,0.04093576,0.00011136543],"about_ca_topic_score_codex":0.0026469901,"about_ca_topic_score_gemma":0.0063008936,"teacher_disagreement_score":0.025700014,"about_ca_system_score_codex":0.00048781643,"about_ca_system_score_gemma":0.00065573264,"threshold_uncertainty_score":0.08597505},"labels":[],"label_agreement":null},{"id":"W2754530470","doi":"10.1017/cjn.2017.221","title":"Corpus Callosum Impingement Syndrome: A Callosal or Colossal Problem?","year":2017,"lang":"fr","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Content (measure theory); Computer science; Medicine; Psychology; Neuroscience; Mathematics","score_opus":0.10535488708823874,"score_gpt":0.35991612036807624,"score_spread":0.2545612332798375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754530470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84594643,0.0170288,0.006388522,0.05212625,0.0022390722,0.00024802948,0.0008644358,0.0011938045,0.07396465],"genre_scores_gemma":[0.98344547,0.0032584167,0.001962624,0.0037036412,0.001481715,0.00004995688,0.00018557355,0.00012932434,0.0057831993],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.99958736,0.000026514477,0.00003898509,0.000120128236,0.000094374576,0.00013261751],"domain_scores_gemma":[0.998156,0.0008840443,0.00038809038,0.0001109601,0.00008422277,0.0003766336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002143324,0.002475988,0.0016924709,0.0027200668,0.002272602,0.0019012737,0.0021087313,0.008647767,0.015629468],"category_scores_gemma":[0.006743204,0.0006303107,0.0005666691,0.0031251975,0.0037267741,0.0038649107,0.0012042932,0.0044195675,0.0016859384],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033561504,0.000019759165,0.0016181552,0.000052984422,0.000011774939,0.9928397,0.000098396864,0.000085507345,0.0007227474,0.0007561201,0.0009997933,0.0027616262],"study_design_scores_gemma":[0.00005012078,0.000039930932,0.004985782,0.000072084775,0.00003727517,0.99004644,0.00028012344,0.00048744053,0.00063514174,0.0021726165,0.0011640558,0.00002897644],"about_ca_topic_score_codex":0.009641252,"about_ca_topic_score_gemma":0.011547657,"teacher_disagreement_score":0.015629468,"about_ca_system_score_codex":0.0018608113,"about_ca_system_score_gemma":0.0020354872,"threshold_uncertainty_score":0.05228579},"labels":[],"label_agreement":null},{"id":"W2755098915","doi":"10.1007/978-3-319-67675-3_9","title":"White Matter Fiber Segmentation Using Functional Varifolds","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Fiber; Computer science; Artificial intelligence; Materials science; Composite material","score_opus":0.06946542090999351,"score_gpt":0.33812976724214705,"score_spread":0.2686643463321535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755098915","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055026277,0.0005891506,0.99029505,0.00012927315,0.000055500095,0.000021107488,0.00021988008,0.0018283881,0.0013590369],"genre_scores_gemma":[0.0468121,0.0012910728,0.9425971,0.000070309936,0.000100748155,0.000043079817,0.0005938586,0.001142302,0.007349411],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998368,0.000019669707,0.000013378111,0.000061038634,0.000049549057,0.000019486712],"domain_scores_gemma":[0.99958295,0.00013289193,0.00004577322,0.00009293832,0.00011867633,0.000026795911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007414628,0.0010159832,0.00080083875,0.0022178718,0.0004710637,0.0017467254,0.00086760975,0.0011753248,0.0058244504],"category_scores_gemma":[0.00095437333,0.0007510139,0.0012302739,0.0017956285,0.0005073879,0.001908375,0.0009317948,0.0009245459,0.0033943567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112643975,0.000029218445,0.0012118391,0.00036201926,0.00014835563,0.00014389602,0.00017068595,0.03299826,0.07903085,0.015120575,0.008580907,0.8620907],"study_design_scores_gemma":[0.000017504375,0.00007953257,0.004012181,0.00021189702,0.00014348296,0.0013162632,0.00013576017,0.7896801,0.099472836,0.07330973,0.031527206,0.00009349517],"about_ca_topic_score_codex":0.0021230762,"about_ca_topic_score_gemma":0.0033640824,"teacher_disagreement_score":0.0058244504,"about_ca_system_score_codex":0.0003996167,"about_ca_system_score_gemma":0.0007039913,"threshold_uncertainty_score":0.019484699},"labels":[],"label_agreement":null},{"id":"W2755475577","doi":"10.1016/j.neuroimage.2017.09.019","title":"A comparison of inhomogeneous magnetization transfer, myelin volume fraction, and diffusion tensor imaging measures in healthy children","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arkansas Children’s Hospital Research Institute; University of Calgary","keywords":"Magnetization transfer; Diffusion MRI; Nuclear magnetic resonance; Tensor (intrinsic definition); Diffusion; Magnetization; Physics; Volume fraction; Myelin; Condensed matter physics; Materials science; Medicine; Psychology; Mathematics; Magnetic resonance imaging; Neuroscience; Radiology; Magnetic field; Thermodynamics; Quantum mechanics; Geometry","score_opus":0.05793730415032883,"score_gpt":0.3752019245705948,"score_spread":0.317264620420266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755475577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99910516,0.00021358475,0.000099993136,0.000032348114,0.000004963248,0.00000623416,0.00024859645,0.000006945613,0.0002820295],"genre_scores_gemma":[0.99897754,0.0002014665,0.00031401333,0.000017249302,0.0000060484203,0.0000107876995,0.00027074342,0.0000074260665,0.00019467247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994593,0.00008011832,0.00007434783,0.00019529849,0.00007845323,0.00011252009],"domain_scores_gemma":[0.99892944,0.0003281172,0.0003100374,0.000090271045,0.0001687592,0.00017327884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008680112,0.0007096701,0.0007079347,0.0022568323,0.00059672113,0.00085598347,0.00045921837,0.00070541195,0.00128026],"category_scores_gemma":[0.0029336112,0.0004009993,0.00047164346,0.00090734044,0.0010847849,0.0011602443,0.00064677413,0.00044997915,0.0002917684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013495815,0.00032240766,0.97874486,0.000096797405,0.000167102,0.001222685,0.0015646538,0.00029420518,0.0059605646,0.00033284348,0.0004171535,0.009527181],"study_design_scores_gemma":[0.000032359214,0.00043983085,0.9953702,0.000016542119,0.000078131874,0.0012213051,0.0009764893,0.00024389302,0.00116726,0.00014123227,0.00030026658,0.00001247578],"about_ca_topic_score_codex":0.017449008,"about_ca_topic_score_gemma":0.012683996,"teacher_disagreement_score":0.017449008,"about_ca_system_score_codex":0.0007748123,"about_ca_system_score_gemma":0.00081234454,"threshold_uncertainty_score":0.03469491},"labels":[],"label_agreement":null},{"id":"W2755700757","doi":"10.1007/978-3-319-73839-0_17","title":"Multi-Modal Analysis of Genetically-Related Subjects Using SIFT Descriptors in Brain MRI","year":2018,"lang":"en","type":"preprint","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Human Connectome Project; Scale-invariant feature transform; Similarity measure; Artificial intelligence; Computer science; Similarity (geometry); Diffusion MRI; Pattern recognition (psychology); Modality (human–computer interaction); Connectome; Modal; Measure (data warehouse); Modalities; Data mining; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Feature extraction; Radiology; Functional connectivity; Image (mathematics)","score_opus":0.1152558743178228,"score_gpt":0.4248246109812118,"score_spread":0.309568736663389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755700757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65687597,0.0012773527,0.33675146,0.00040248176,0.00007209005,0.00007442967,0.0016921012,0.0010130638,0.0018410201],"genre_scores_gemma":[0.91327727,0.0006073908,0.08340406,0.000057052308,0.00007145467,0.000042012805,0.0009750726,0.00012619449,0.0014395419],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990964,0.000015359692,0.0000050267645,0.00002924667,0.000019229265,0.000021572076],"domain_scores_gemma":[0.99976474,0.000059081365,0.000048601418,0.00004233903,0.0000536509,0.00003153883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038506402,0.00031437742,0.00032651454,0.0018163424,0.00018424989,0.00054546766,0.00023518268,0.00046009992,0.0013610953],"category_scores_gemma":[0.0008721481,0.00012789923,0.0004590912,0.0010021763,0.00018606726,0.00034887405,0.00036810437,0.00027124124,0.00033129854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012979872,0.00026385186,0.030419355,0.00034167623,0.00030575116,0.001013757,0.00047933395,0.018473258,0.5157385,0.004149338,0.005596243,0.42192104],"study_design_scores_gemma":[0.00006370999,0.0003838113,0.39319283,0.00009479733,0.00042129756,0.0046110167,0.0008324034,0.4686767,0.106992505,0.019220995,0.005382061,0.00012777536],"about_ca_topic_score_codex":0.0021996892,"about_ca_topic_score_gemma":0.0031456545,"teacher_disagreement_score":0.0021996892,"about_ca_system_score_codex":0.00016894843,"about_ca_system_score_gemma":0.00025811713,"threshold_uncertainty_score":0.004553318},"labels":[],"label_agreement":null},{"id":"W2756068656","doi":"10.1117/1.jmi.4.3.036001","title":"Ex vivo tissue imaging for radiology–pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin","year":2017,"lang":"en","type":"article","venue":"Journal of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Medical Service Foundation","keywords":"Hemosiderin; Medicine; Ex vivo; Magnetic resonance imaging; Pathology; Diffusion MRI; In vivo; Melanin; Radiology; Biology","score_opus":0.07248924691438242,"score_gpt":0.35460723132288585,"score_spread":0.28211798440850344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756068656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9940627,0.00029130702,0.004717964,0.00018715941,0.0000249941,0.00013933133,0.000041096533,0.000045600515,0.0004899082],"genre_scores_gemma":[0.9921233,0.00044941428,0.006476412,0.00017251114,0.000080748,0.000107621454,0.00015660338,0.000032929038,0.00040035674],"study_design_codex":"bench_or_experimental","study_design_gemma":"case_report","domain_scores_codex":[0.9996195,0.00017076966,0.000033919896,0.00008485067,0.000038366514,0.000052511317],"domain_scores_gemma":[0.9991874,0.00025354562,0.00007360086,0.0001920366,0.00009074497,0.00020261879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014597914,0.0009841326,0.00061614387,0.00053542777,0.0004944828,0.00032961243,0.0006044224,0.0011818745,0.0011554736],"category_scores_gemma":[0.0012960747,0.0004210911,0.00054626924,0.00018345316,0.00095138326,0.0008537946,0.0005868465,0.0008465903,0.0005900928],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021634263,0.005914185,0.008279585,0.00017876271,0.000081878585,0.047130786,0.0010079262,0.000848901,0.9256056,0.00016792612,0.00015643497,0.008464621],"study_design_scores_gemma":[0.0017974377,0.2035268,0.12867802,0.00008079384,0.0008927317,0.2862899,0.0021919203,0.014158122,0.3533017,0.0008867158,0.007968863,0.0002269637],"about_ca_topic_score_codex":0.00042686146,"about_ca_topic_score_gemma":0.00053939916,"teacher_disagreement_score":0.0014597914,"about_ca_system_score_codex":0.0002239786,"about_ca_system_score_gemma":0.0002460029,"threshold_uncertainty_score":0.007720232},"labels":[],"label_agreement":null},{"id":"W2756259711","doi":"10.1016/j.neuroscience.2017.09.011","title":"Pathways of the inferior frontal occipital fasciculus in overt speech and reading","year":2017,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Uncinate fasciculus; Psychology; Inferior longitudinal fasciculus; Diffusion MRI; Rapid automatized naming; Reading (process); Fractional anisotropy; Superior longitudinal fasciculus; Fasciculus; White matter; Context (archaeology); Tractography; Corticospinal tract; Cognitive psychology; Neuroscience; Phonological awareness; Linguistics; Magnetic resonance imaging; Medicine","score_opus":0.07105586257299687,"score_gpt":0.34937235447152787,"score_spread":0.278316491898531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756259711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94849634,0.007491146,0.020171091,0.0024344558,0.00017500804,0.00011723282,0.0005151548,0.00010117914,0.020498404],"genre_scores_gemma":[0.9891011,0.0016172566,0.0044405884,0.000117834046,0.000077101446,0.00006620577,0.00009235679,0.000016379548,0.0044711283],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997814,0.00006750442,0.00001060314,0.000032406304,0.00003919548,0.00006889283],"domain_scores_gemma":[0.99935466,0.00029142443,0.00012583773,0.000040470168,0.00007820039,0.00010954982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045855017,0.0006053947,0.00021335471,0.0006929325,0.0007935291,0.0011132593,0.00031368615,0.00070366764,0.0031179755],"category_scores_gemma":[0.0021492182,0.00027418608,0.00025890386,0.00052136014,0.0015020423,0.0021742182,0.000809413,0.001087666,0.0003081441],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0072139553,0.00053320435,0.06806575,0.0010674007,0.00034313733,0.017625796,0.0091635855,0.0065504713,0.3819334,0.13223526,0.0044959118,0.37077212],"study_design_scores_gemma":[0.00062689104,0.0021325233,0.5952686,0.0006362453,0.0002792322,0.013729466,0.0072503337,0.01853162,0.14474145,0.1954197,0.021207593,0.00017632364],"about_ca_topic_score_codex":0.010910372,"about_ca_topic_score_gemma":0.0131415585,"teacher_disagreement_score":0.010910372,"about_ca_system_score_codex":0.0010423572,"about_ca_system_score_gemma":0.001863825,"threshold_uncertainty_score":0.021693707},"labels":[],"label_agreement":null},{"id":"W2756436797","doi":"10.1002/hbm.23799","title":"A pediatric structural MRI analysis of healthy brain development from newborns to young adults","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Canada Foundation for Innovation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"White matter; Magnetic resonance imaging; Brain development; Brain morphometry; Neuroimaging; Hum; Medicine; Brain size; Pathological; Neuroscience; Psychology; Pathology; Radiology","score_opus":0.07595107030098333,"score_gpt":0.38110838037630673,"score_spread":0.30515731007532343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756436797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9940333,0.00051973085,0.002214094,0.000033409935,0.0000063821653,0.00002379072,0.002157939,0.00004205133,0.0009693081],"genre_scores_gemma":[0.99209964,0.0006566573,0.0045862594,0.00002111371,0.000008170852,0.000037418722,0.0023425631,0.00003014692,0.0002181207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971455,0.000047937094,0.000046431127,0.00010529373,0.000056800352,0.00002889148],"domain_scores_gemma":[0.99907804,0.00018375818,0.00029504322,0.00012847317,0.00025372222,0.000061008774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069757324,0.00032367645,0.00018713177,0.0016966455,0.00025716086,0.00031720774,0.00019110503,0.00017861756,0.0009926175],"category_scores_gemma":[0.002137903,0.00012993476,0.00026160278,0.0009254475,0.00023195562,0.00029675558,0.00031515225,0.00016044297,0.00023182563],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002441409,0.000025386214,0.9404595,0.00007267181,0.00011158989,0.0007028279,0.000407043,0.00043339873,0.015950436,0.0001927185,0.0006455597,0.04075476],"study_design_scores_gemma":[0.0000015862162,0.00008794883,0.9939959,0.000010192065,0.000040390594,0.0015048652,0.00015342279,0.00027766073,0.0029584428,0.000060631613,0.0009052998,0.000003680937],"about_ca_topic_score_codex":0.004048762,"about_ca_topic_score_gemma":0.0062080664,"teacher_disagreement_score":0.004048762,"about_ca_system_score_codex":0.00023745206,"about_ca_system_score_gemma":0.00036830356,"threshold_uncertainty_score":0.008050382},"labels":[],"label_agreement":null},{"id":"W2757204155","doi":"10.1007/978-3-319-73839-0_15","title":"Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players","year":2018,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fiber bundle; Diffusion MRI; Fiber; Diffusion; Anisotropy; Mathematics; Physics; Optics; Materials science","score_opus":0.03743149619188727,"score_gpt":0.34174117214212896,"score_spread":0.30430967595024166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757204155","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02307688,0.0024779055,0.96674705,0.0005823408,0.0001411723,0.00005578308,0.00073932187,0.0015710441,0.0046085673],"genre_scores_gemma":[0.09820654,0.005162492,0.8755497,0.00008830647,0.00022103553,0.00009087532,0.0007679743,0.00071241875,0.019200733],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99993134,0.000014289345,0.000005155942,0.00002003665,0.000024924339,0.0000043236982],"domain_scores_gemma":[0.99965394,0.00019919698,0.000020023335,0.000021225234,0.0000898281,0.000015772594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005686596,0.0006074848,0.00050881447,0.0009245265,0.00025654814,0.0008293229,0.0005175846,0.00062937965,0.0051730582],"category_scores_gemma":[0.001649751,0.00022734034,0.00054469303,0.00093760935,0.00027751428,0.0005586205,0.0004392268,0.0005410951,0.0014427259],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014945483,0.0001061913,0.0044640703,0.0004409004,0.000087226465,0.00049571315,0.0003576493,0.04937539,0.031233057,0.037961844,0.02507572,0.85025275],"study_design_scores_gemma":[0.000020093741,0.00009773721,0.011518214,0.00011867508,0.00011156895,0.0018358922,0.00018587425,0.87332135,0.01949554,0.056352533,0.036871888,0.00007073584],"about_ca_topic_score_codex":0.004581365,"about_ca_topic_score_gemma":0.0058627953,"teacher_disagreement_score":0.0051730582,"about_ca_system_score_codex":0.00035828137,"about_ca_system_score_gemma":0.0005469181,"threshold_uncertainty_score":0.017305613},"labels":[],"label_agreement":null},{"id":"W2758054168","doi":"10.7759/cureus.1722","title":"Tractography for Optic Radiation Preservation in Transcortical Approaches to Intracerebral Lesions","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Tractography; Optic radiation; Neuroscience; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.4468942478928639,"score_gpt":0.41873300207780717,"score_spread":0.028161245815056746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758054168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8435278,0.06149619,0.060335077,0.0020633542,0.00040215193,0.00016165,0.00027181665,0.0011451016,0.030596865],"genre_scores_gemma":[0.9751159,0.010379301,0.012098066,0.0003444478,0.00029294833,0.000023701956,0.00008184699,0.00007317264,0.0015906156],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.999863,0.000023032599,0.000025533644,0.000022241635,0.000035315923,0.00003084916],"domain_scores_gemma":[0.99957365,0.00014782265,0.00013204213,0.00007362237,0.00002822757,0.00004468579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019121313,0.0006095788,0.00024627653,0.0011876136,0.00039435882,0.0005239465,0.00038575658,0.0009437986,0.0010262898],"category_scores_gemma":[0.0008537584,0.00022785399,0.00042481028,0.0006947447,0.0007522632,0.0007475274,0.00032377525,0.00085908966,0.00067481113],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015754277,0.00004697233,0.01818706,0.00077451335,0.000119203614,0.829238,0.00040486135,0.0007199636,0.03466118,0.001010167,0.00086629944,0.113814265],"study_design_scores_gemma":[0.00001695716,0.000094523806,0.007278547,0.00009163947,0.00007560916,0.9756443,0.00008399804,0.00067282724,0.009806011,0.00050067296,0.0057168123,0.000018072644],"about_ca_topic_score_codex":0.0013768892,"about_ca_topic_score_gemma":0.0039576264,"teacher_disagreement_score":0.0013768892,"about_ca_system_score_codex":0.00035809443,"about_ca_system_score_gemma":0.00064212654,"threshold_uncertainty_score":0.0034333467},"labels":[],"label_agreement":null},{"id":"W2758085132","doi":"","title":"Studying white matter tractography reproducibility through connectivity matrices","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; Reproducibility; White matter; Computer science; Grey matter; Connectome; Artificial intelligence; Pattern recognition (psychology); Functional connectivity; Neuroscience; Magnetic resonance imaging; Mathematics; Psychology; Medicine; Radiology; Statistics","score_opus":0.07567469515517751,"score_gpt":0.3302137052561688,"score_spread":0.2545390101009913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758085132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7083417,0.0009120079,0.2842515,0.0007435603,0.00014328667,0.00007771246,0.0009527716,0.0009225868,0.003654965],"genre_scores_gemma":[0.96940887,0.0002296542,0.027745355,0.00006014559,0.00014973384,0.00004939681,0.0006501462,0.0005145828,0.0011921282],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940222,0.0028539265,0.00044795006,0.0018090648,0.00070291135,0.0001640216],"domain_scores_gemma":[0.8870833,0.08628789,0.0070296153,0.013087173,0.0056887786,0.00082326285],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.011325697,0.00084326486,0.00083004066,0.0022127389,0.0007641525,0.0028736277,0.0012078189,0.001630052,0.0042925305],"category_scores_gemma":[0.13020353,0.0006061751,0.0009172304,0.002571899,0.0018298519,0.0027709643,0.0012106922,0.0009834301,0.0009919183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032322633,0.0003863283,0.42518356,0.0011157914,0.0056249234,0.0015465427,0.0037224526,0.06603985,0.17137621,0.027696885,0.0055625653,0.28851265],"study_design_scores_gemma":[0.00021104042,0.0013004098,0.41937977,0.00019471234,0.0017376408,0.0043925475,0.00093222817,0.37561294,0.08623759,0.10473024,0.005062563,0.00020833759],"about_ca_topic_score_codex":0.0015417073,"about_ca_topic_score_gemma":0.0013631774,"teacher_disagreement_score":0.9886743,"about_ca_system_score_codex":0.00048638936,"about_ca_system_score_gemma":0.0007641988,"threshold_uncertainty_score":0.059896767},"labels":[],"label_agreement":null},{"id":"W2758113150","doi":"10.1002/nbm.3785","title":"Diffusion MRI fiber tractography of the brain","year":2017,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":600,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Fonds Wetenschappelijk Onderzoek; McDonnell Center for Systems Neuroscience; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Tractography; Connectomics; Diffusion MRI; White matter; Neuroscience; Computer science; Fiber tract; Human Connectome Project; Tracking (education); Data science; Artificial intelligence; Psychology; Connectome; Medicine; Magnetic resonance imaging; Functional connectivity; Radiology","score_opus":0.17918645848264028,"score_gpt":0.4685740191986128,"score_spread":0.2893875607159725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758113150","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030017763,0.03321609,0.914355,0.003795431,0.00034138752,0.00015057604,0.0014986123,0.0012426155,0.015382548],"genre_scores_gemma":[0.37249708,0.060468458,0.5549697,0.0007178893,0.00041186987,0.00023773247,0.001139514,0.00051908864,0.009038716],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997273,0.00007178371,0.000030413748,0.00008522226,0.000068194255,0.000017099725],"domain_scores_gemma":[0.9994753,0.00019831871,0.0000898148,0.00007541456,0.0001320737,0.000029178454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010185689,0.00052148616,0.00046971987,0.0020720037,0.0003513324,0.0011314583,0.0004820704,0.0008187727,0.0017841044],"category_scores_gemma":[0.0026727582,0.00032603394,0.00039576698,0.0017502351,0.0010073445,0.0017922967,0.00057826255,0.0011039601,0.00095836807],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014344175,0.000040049104,0.010850096,0.0024790622,0.00025380077,0.0013070588,0.0017456494,0.02849098,0.12805198,0.16362956,0.016348444,0.6466599],"study_design_scores_gemma":[0.00006875738,0.0002852647,0.048062235,0.0016948644,0.0002909159,0.012597414,0.00076993235,0.14158458,0.059877608,0.35701296,0.37735492,0.00040053175],"about_ca_topic_score_codex":0.005226156,"about_ca_topic_score_gemma":0.0058912057,"teacher_disagreement_score":0.005226156,"about_ca_system_score_codex":0.0007788378,"about_ca_system_score_gemma":0.0011269029,"threshold_uncertainty_score":0.010391474},"labels":[],"label_agreement":null},{"id":"W2758471796","doi":"10.1161/str.47.suppl_1.tp373","title":"Abstract TP373: Tracts Enfolded by Small Hematomas Remain Intact in Acute Intracerebral Hemorrhage","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Basal ganglia; Hematoma; Intracerebral hemorrhage; White matter; Corticospinal tract; Tractography; Diffusion MRI; Magnetic resonance imaging; Pyramidal tracts; Lesion; Nuclear medicine; Surgery; Radiology; Anatomy; Glasgow Coma Scale; Internal medicine; Central nervous system","score_opus":0.0342844207898849,"score_gpt":0.31662762216759693,"score_spread":0.282343201377712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758471796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99938416,0.00010279041,0.000112905895,0.000025770642,0.0000021590522,0.000005301665,0.00006158388,0.0000034354462,0.00030184913],"genre_scores_gemma":[0.9997359,0.00003710392,0.00006197911,0.000008308997,0.000007437454,0.0000024274946,0.00007350024,0.0000012467079,0.00007215302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992836,0.000009950134,0.000010580353,0.000012789671,0.000020946325,0.000017269622],"domain_scores_gemma":[0.9995726,0.00009367555,0.00016343695,0.000018637525,0.000039697727,0.000111904956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017872847,0.0001839164,0.0001507513,0.00041894524,0.00026734592,0.0003186958,0.00016160126,0.0002206194,0.0024636374],"category_scores_gemma":[0.0010977006,0.00008970415,0.000110226654,0.00032398273,0.00056120346,0.00029407517,0.00023342301,0.00024440378,0.00037122917],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013462986,0.000050477145,0.9718839,0.000047386522,0.000027900436,0.009904921,0.00013330956,0.00020900437,0.00877145,0.00006473141,0.00027418794,0.0072863554],"study_design_scores_gemma":[0.000019360012,0.00032285464,0.9809677,0.000011102611,0.00001852156,0.01622423,0.00014452619,0.0003723212,0.0015252552,0.0002040684,0.00018366637,0.0000063378043],"about_ca_topic_score_codex":0.0016342571,"about_ca_topic_score_gemma":0.0017123456,"teacher_disagreement_score":0.0024636374,"about_ca_system_score_codex":0.00028387283,"about_ca_system_score_gemma":0.0002835601,"threshold_uncertainty_score":0.008241713},"labels":[],"label_agreement":null},{"id":"W2759664261","doi":"10.1002/hbm.23831","title":"Altered white matter structure in the visual system following early monocular enucleation","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Enucleation; Lateral geniculate nucleus; Fractional anisotropy; White matter; Monocular; Diffusion MRI; Visual cortex; Optic tract; Psychology; Visual system; Tractography; Eye Enucleation; Anatomy; Optic radiation; Neuroscience; Ophthalmology; Optic nerve; Biology; Magnetic resonance imaging; Medicine; Optics; Surgery; Physics","score_opus":0.06478154638342154,"score_gpt":0.36307098968075013,"score_spread":0.2982894432973286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759664261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998874,0.00038419134,0.00046030513,0.000016235565,0.0000027727447,0.0000067321594,0.0000765996,0.000009851989,0.00016934359],"genre_scores_gemma":[0.99876887,0.00018497814,0.00043702935,0.000024828241,0.0000017582628,0.000011587548,0.00011088136,0.00000382558,0.00045611936],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998635,0.0000144177,0.000011211812,0.000047854246,0.000034700282,0.00002831263],"domain_scores_gemma":[0.99965596,0.000035674668,0.000204057,0.000023258823,0.000034537232,0.00004657822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022217938,0.00026216081,0.00024067776,0.00042851164,0.00016695306,0.00017811228,0.000117792435,0.00021555342,0.00064865354],"category_scores_gemma":[0.0004360589,0.000110951856,0.0001603081,0.00012114997,0.00034602772,0.000186421,0.0003196147,0.00019661074,0.00006334852],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012539222,0.00005684731,0.052329376,0.00012222916,0.00007199749,0.002845356,0.0004093231,0.00017516316,0.92735904,0.00014613659,0.000102075166,0.015128507],"study_design_scores_gemma":[0.000011546083,0.00062289246,0.9348812,0.000013243307,0.000030447247,0.0045069843,0.0001970258,0.00020597092,0.058987282,0.00011073141,0.00042156636,0.000010983925],"about_ca_topic_score_codex":0.003816417,"about_ca_topic_score_gemma":0.0079259155,"teacher_disagreement_score":0.003816417,"about_ca_system_score_codex":0.00045843696,"about_ca_system_score_gemma":0.00028605497,"threshold_uncertainty_score":0.007588446},"labels":[],"label_agreement":null},{"id":"W2760517586","doi":"10.7759/cureus.1721","title":"Diffusion Tensor Imaging for Ruptured Cerebral Arteriovenous Malformation","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Neuroradiologist; Diffusion MRI; White matter; Tractography; Arteriovenous malformation; Fractional anisotropy; Radiology; Neurological deficit; Neuronavigation; Intracranial Arteriovenous Malformations; Nuclear medicine; Magnetic resonance imaging; Surgery; Cerebral angiography; Angiography","score_opus":0.0809561197386152,"score_gpt":0.3817563610082013,"score_spread":0.3008002412695861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760517586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96367955,0.023324598,0.0036680545,0.0010747601,0.00010777321,0.000114661954,0.0003325198,0.000065596054,0.0076324837],"genre_scores_gemma":[0.99206585,0.004578203,0.0022310358,0.00010124131,0.00009692295,0.00001895421,0.00019681716,0.000011887265,0.00069910655],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.99963593,0.00010124855,0.0000944357,0.00003830455,0.00007679948,0.00005335612],"domain_scores_gemma":[0.99916077,0.00025351226,0.0002916837,0.00007325061,0.0001192901,0.00010148718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009098484,0.00041091733,0.00034427093,0.0032409134,0.00043764574,0.00041159082,0.00039833513,0.00041356598,0.0021382703],"category_scores_gemma":[0.0035033105,0.00017074004,0.00031307575,0.0009382939,0.0005414186,0.0008730058,0.00041924047,0.00044492568,0.00041663725],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004823273,0.000105322804,0.6798804,0.00052623195,0.000100721925,0.24610808,0.0006985726,0.00029678975,0.012121552,0.0008550386,0.001969695,0.056855347],"study_design_scores_gemma":[0.000030373634,0.00026891413,0.43908054,0.00023581482,0.00007898211,0.55034924,0.00047378382,0.0010675081,0.0031929545,0.00091866805,0.004273094,0.000030164983],"about_ca_topic_score_codex":0.0017886576,"about_ca_topic_score_gemma":0.002099734,"teacher_disagreement_score":0.0032409134,"about_ca_system_score_codex":0.0004863917,"about_ca_system_score_gemma":0.00055684015,"threshold_uncertainty_score":0.0071531534},"labels":[],"label_agreement":null},{"id":"W2760605084","doi":"10.1016/j.schres.2017.09.030","title":"The influence of MIR137 on white matter fractional anisotropy and cortical surface area in individuals with familial risk for psychosis","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Rheinische Friedrich-Wilhelms-Universität Bonn; Deutsche Forschungsgemeinschaft","keywords":"Schizophrenia (object-oriented programming); Genotype; Psychosis; Allele; Medicine; Internal medicine; Biology; Genetics; Psychiatry; Gene","score_opus":0.08393412983607419,"score_gpt":0.42153832978966566,"score_spread":0.3376041999535915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760605084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992231,0.00015728708,0.00011382593,0.00006695637,0.000007075149,0.000001180356,0.000090916445,0.000008353076,0.00033121274],"genre_scores_gemma":[0.9996469,0.000028700128,0.00008657684,0.000014431536,0.0000045117954,0.000001363503,0.00003859307,0.0000052456667,0.00017373466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959856,0.00013343463,0.000040893636,0.00010774397,0.000057657773,0.00006176774],"domain_scores_gemma":[0.99869835,0.00043456457,0.0005120082,0.000118571195,0.000098114186,0.00013827915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045056827,0.00041623253,0.0004181861,0.0004675201,0.0005259637,0.00066320953,0.00032005957,0.0006802898,0.0022232747],"category_scores_gemma":[0.0026441554,0.00027810148,0.00060996274,0.00044472024,0.0003394655,0.00032481903,0.00037256276,0.0005814723,0.0002387408],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006185316,0.0002347042,0.96144205,0.000049039936,0.0008227421,0.00095777673,0.0006278348,0.00037591494,0.020009765,0.00036653198,0.00027986345,0.008648419],"study_design_scores_gemma":[0.000033105567,0.00023556154,0.99583375,0.000012493273,0.0003126519,0.00073661195,0.00024197128,0.0009974741,0.0010484194,0.0003237464,0.00020890962,0.000015319243],"about_ca_topic_score_codex":0.005712561,"about_ca_topic_score_gemma":0.0045979624,"teacher_disagreement_score":0.005712561,"about_ca_system_score_codex":0.00038946554,"about_ca_system_score_gemma":0.0002574545,"threshold_uncertainty_score":0.011358619},"labels":[],"label_agreement":null},{"id":"W2761140693","doi":"10.3389/fnins.2017.00554","title":"Comparison of Diffusion-Weighted MRI Reconstruction Methods for Visualization of Cranial Nerves in Posterior Fossa Surgery","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Western Hospital; University Health Network","funders":"Mitacs","keywords":"Tractography; Diffusion MRI; Visualization; Deconvolution; Artificial intelligence; Computer science; Computer vision; Medicine; Radiology; Magnetic resonance imaging; Algorithm","score_opus":0.10952893873970326,"score_gpt":0.4683709639523552,"score_spread":0.35884202521265196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761140693","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7424946,0.008479298,0.24302171,0.00052917737,0.0001555146,0.00040069298,0.00059397315,0.0012184585,0.0031065124],"genre_scores_gemma":[0.6127242,0.006699902,0.3772857,0.00009506334,0.00006411288,0.00031834745,0.000733554,0.00092890294,0.0011502956],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99824846,0.0008979446,0.00020122081,0.00012434661,0.0004508583,0.00007711121],"domain_scores_gemma":[0.99141663,0.0059297425,0.0005696805,0.0005438229,0.0013568242,0.00018343217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045919996,0.0010793816,0.000539042,0.0025684652,0.000316637,0.0014290002,0.000666573,0.00087338476,0.001739155],"category_scores_gemma":[0.017756255,0.0007563867,0.0008129168,0.0012341535,0.00036755367,0.0012543538,0.00084541464,0.00061537395,0.0006427431],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010325535,0.00041965838,0.032904264,0.0020610187,0.0010749168,0.00077764335,0.0016721148,0.09229816,0.073118314,0.0033752113,0.0016980645,0.78027517],"study_design_scores_gemma":[0.0010038756,0.0041264035,0.08194423,0.0006658448,0.0008722675,0.0058190366,0.0009185439,0.8076249,0.08597343,0.0032848017,0.0071722455,0.0005945294],"about_ca_topic_score_codex":0.0031266627,"about_ca_topic_score_gemma":0.0043403497,"teacher_disagreement_score":0.0045919996,"about_ca_system_score_codex":0.00050994696,"about_ca_system_score_gemma":0.0009133349,"threshold_uncertainty_score":0.024285138},"labels":[],"label_agreement":null},{"id":"W2762036029","doi":"10.1002/hbm.23836","title":"Development of short‐range white matter in healthy children and adolescents","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Centre for Addiction and Mental Health; Hospital for Sick Children; University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Cohort; Psychology; Lateralization of brain function; Neuroscience; Hum; Tractography; Magnetic resonance imaging; Medicine; Pathology","score_opus":0.0854100442372943,"score_gpt":0.36677229395114175,"score_spread":0.28136224971384743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762036029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99929094,0.00025385377,0.000047319256,0.000024829991,0.0000037229418,0.0000047877925,0.00019219884,0.000004215199,0.00017809357],"genre_scores_gemma":[0.99891615,0.0003726736,0.00020842717,0.000025140263,0.000004981835,0.000015474248,0.00032284018,0.000003933034,0.0001304356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974865,0.000024039999,0.00003221491,0.000097712866,0.000049997507,0.000047392652],"domain_scores_gemma":[0.9994036,0.000060276878,0.00032665586,0.000025931637,0.000080774305,0.00010274802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055366266,0.0003721414,0.00037319565,0.0012851268,0.00048183525,0.0006456416,0.00026205988,0.00041658065,0.00097004534],"category_scores_gemma":[0.0014154366,0.00039228587,0.00031340215,0.0006566003,0.0005008104,0.0008193225,0.0005059822,0.00041143785,0.00021154017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000533489,0.000027027167,0.99450123,0.000021792623,0.000023538581,0.00030286648,0.00077621895,0.000029688603,0.0010712526,0.00006049397,0.00012284137,0.003009669],"study_design_scores_gemma":[0.0000011495358,0.000029279958,0.99911827,0.000007853659,0.000006541746,0.0003069823,0.00028786415,0.000025534633,0.00009109279,0.000018893083,0.000105081206,0.0000015344572],"about_ca_topic_score_codex":0.011531416,"about_ca_topic_score_gemma":0.0147679625,"teacher_disagreement_score":0.011531416,"about_ca_system_score_codex":0.00036786948,"about_ca_system_score_gemma":0.00044366784,"threshold_uncertainty_score":0.022928596},"labels":[],"label_agreement":null},{"id":"W2762896436","doi":"10.1016/j.neuroimage.2017.10.013","title":"Imaging microstructure in the living human brain: A viewpoint","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"National Institutes of Health; University of Toronto; Canadian Institutes of Health Research; Child Mind Institute","keywords":"Human brain; Neuroscience; Magnetic resonance imaging; White matter; Bridge (graph theory); Neuroimaging; Grey matter; Computer science; Ex vivo; Microstructure; In vivo; Psychology; Medicine; Materials science; Biology; Anatomy; Radiology","score_opus":0.06539384090682576,"score_gpt":0.38726362304611056,"score_spread":0.3218697821392848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762896436","genre_codex":"review","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02082629,0.5475732,0.22402644,0.12767005,0.003551544,0.00008346897,0.00050156016,0.00044883863,0.07531867],"genre_scores_gemma":[0.46582887,0.3501682,0.11541125,0.02538182,0.028705306,0.00025211988,0.00022914784,0.00028716907,0.013736073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994715,0.00018944794,0.000034371442,0.00013783196,0.00013988186,0.000027032487],"domain_scores_gemma":[0.997985,0.0011762864,0.00012828832,0.00021658081,0.00036687107,0.00012694034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024599265,0.0009683459,0.0012580953,0.0031225143,0.0009480223,0.0036433497,0.002356791,0.0049748663,0.0022576142],"category_scores_gemma":[0.005039833,0.000734568,0.0007092394,0.0008429648,0.015034901,0.0074833534,0.0019016505,0.0049744747,0.0005897679],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055930548,0.000061678285,0.0008229718,0.0008677986,0.00008203675,0.00044831206,0.00049337145,0.0034072318,0.0041443547,0.9423923,0.005986771,0.041237123],"study_design_scores_gemma":[0.000026740925,0.000111170455,0.001829784,0.00036949647,0.00005803144,0.0011046792,0.00026463522,0.0055099935,0.0015492254,0.9435861,0.045537453,0.000052671247],"about_ca_topic_score_codex":0.0042496086,"about_ca_topic_score_gemma":0.0038204398,"teacher_disagreement_score":0.0049748663,"about_ca_system_score_codex":0.0022787817,"about_ca_system_score_gemma":0.0014401397,"threshold_uncertainty_score":0.016533732},"labels":[],"label_agreement":null},{"id":"W2763277880","doi":"10.5281/zenodo.1007149","title":"Tractography Challenge ISMRM 2015 b=3000s/mm² Data.","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.20731157691122631,"score_gpt":0.40304209479875874,"score_spread":0.19573051788753243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763277880","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015332022,0.00042728533,0.002979272,0.0003017169,0.00012811171,0.00007541995,0.9850013,0.0076728724,0.0018807638],"genre_scores_gemma":[0.0024617908,0.00013059755,0.0022361153,0.00008119967,0.00001812589,0.00014714623,0.99311334,0.0007270675,0.001084661],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99877876,0.00025973708,0.00011817883,0.00032293095,0.00035902968,0.00016130964],"domain_scores_gemma":[0.9972722,0.0007526989,0.00022243967,0.00089944666,0.0006140556,0.00023922992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018410112,0.003692946,0.002026898,0.0026812982,0.00097595935,0.002785099,0.00483523,0.0040952126,0.04279158],"category_scores_gemma":[0.008087374,0.0012523946,0.0025493926,0.0036875603,0.0008999861,0.0014007264,0.0026164863,0.0026855273,0.09452933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001771804,0.00007531545,0.00097565365,0.0009753755,0.00012765039,0.00011500072,0.000036336667,0.0029693337,0.0005159187,0.00079456664,0.98500526,0.008232451],"study_design_scores_gemma":[0.0010141673,0.00016592539,0.0068710246,0.0007215458,0.00022767596,0.0015054764,0.0001216843,0.014366892,0.0047641583,0.010729395,0.9593397,0.00017251534],"about_ca_topic_score_codex":0.019484276,"about_ca_topic_score_gemma":0.04268334,"teacher_disagreement_score":0.04279158,"about_ca_system_score_codex":0.0018056124,"about_ca_system_score_gemma":0.0031608138,"threshold_uncertainty_score":0.14315206},"labels":[],"label_agreement":null},{"id":"W2763631887","doi":"10.1002/jnr.24142","title":"Age‐ and sex‐related effects in children with mild traumatic brain injury on diffusion magnetic resonance imaging properties: A comparison of voxelwise and tractography methods","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health","keywords":"Uncinate fasciculus; Tractography; Fractional anisotropy; Corticospinal tract; Corpus callosum; White matter; Diffusion MRI; Superior longitudinal fasciculus; Cingulum (brain); Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Radiology","score_opus":0.17543774200190432,"score_gpt":0.49676812004678206,"score_spread":0.32133037804487774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763631887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99842983,0.00054453616,0.0004681233,0.000025728654,0.00000777415,0.000007549379,0.00025276476,0.000012324592,0.00025141414],"genre_scores_gemma":[0.99847156,0.00028039835,0.0006734028,0.00001523256,0.000010058011,0.000014723998,0.00028830458,0.000019579598,0.00022664468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993156,0.00018708345,0.00007535176,0.00018825376,0.00016618217,0.00006741688],"domain_scores_gemma":[0.99614763,0.0016409026,0.001340631,0.00029667915,0.00038348633,0.00019065922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015774088,0.00038261348,0.0003654933,0.0010527229,0.00018629646,0.00045332982,0.0002392396,0.00038067918,0.0018802555],"category_scores_gemma":[0.005931699,0.00018283931,0.00069595175,0.0006115481,0.00032430785,0.0005072658,0.00044156387,0.00028861305,0.00027076996],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072844967,0.00003980073,0.9833112,0.000052153377,0.00021547753,0.00020634536,0.00058235833,0.000117621945,0.0020060192,0.000058532467,0.00008376381,0.012598228],"study_design_scores_gemma":[0.0000043817668,0.00022789788,0.9984773,0.000008804721,0.000053414966,0.00032077022,0.0002546398,0.00021734847,0.00027229206,0.000024281697,0.00013372916,0.000005218754],"about_ca_topic_score_codex":0.0034334997,"about_ca_topic_score_gemma":0.005209343,"teacher_disagreement_score":0.0034334997,"about_ca_system_score_codex":0.00022286958,"about_ca_system_score_gemma":0.00029042212,"threshold_uncertainty_score":0.0083422065},"labels":[],"label_agreement":null},{"id":"W2763784867","doi":"10.1002/mrm.26945","title":"Scan–rescan of axcaliber, macromolecular tissue volume, and g‐ratio in the spinal cord","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec; Canadian Institutes of Health Research; National Institutes of Health; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada; Canada Foundation for Innovation","keywords":"Intraclass correlation; Magnetic resonance imaging; White matter; Spinal cord; Repeatability; Artifact (error); Medicine; Nuclear medicine; Relaxometry; Partial volume; Radiology; Chemistry; Biology; Neuroscience; Spin echo","score_opus":0.0554028314702005,"score_gpt":0.389358564859911,"score_spread":0.3339557333897105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763784867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.981615,0.0008859917,0.015552466,0.00006116262,0.000007539804,0.00005235798,0.00038844897,0.00024289571,0.0011941723],"genre_scores_gemma":[0.99005413,0.00016318295,0.008817117,0.00001804245,0.0000074823724,0.00002820233,0.0003642455,0.00005045121,0.00049707014],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993449,0.00023106631,0.00005744415,0.00011964605,0.00021584939,0.00003112145],"domain_scores_gemma":[0.99755174,0.0007400731,0.00042798868,0.000450165,0.0007579912,0.000072031384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020506997,0.00031432766,0.000335916,0.0015339486,0.0004760596,0.0005230458,0.00048813925,0.00041845607,0.0012811926],"category_scores_gemma":[0.006804128,0.00024992687,0.00022402556,0.0006271878,0.00044233652,0.00050417206,0.00040840427,0.00029589393,0.0003238845],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034563811,0.0003138734,0.41674474,0.00084457383,0.0009794486,0.0007282681,0.0018108303,0.007384162,0.2931291,0.0009364026,0.0019886678,0.27168366],"study_design_scores_gemma":[0.000024625106,0.0004271911,0.9306031,0.00003479466,0.00017654216,0.0021306926,0.00020753045,0.014877612,0.049541563,0.00056582596,0.001372519,0.000038039776],"about_ca_topic_score_codex":0.0056298194,"about_ca_topic_score_gemma":0.009905435,"teacher_disagreement_score":0.0056298194,"about_ca_system_score_codex":0.0003790397,"about_ca_system_score_gemma":0.0004670223,"threshold_uncertainty_score":0.01119405},"labels":[],"label_agreement":null},{"id":"W2763963518","doi":"10.1016/j.neuropsychologia.2017.09.032","title":"Erratum to “A watershed model of individual differences in fluid intelligence” [Neuropsychologia 91 (2016) 186–198]","year":2017,"lang":"en","type":"erratum","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"Biotechnology and Biological Sciences Research Council; Wellcome Trust","keywords":"Psychology; Watershed; Fluid intelligence; Neuroscience; Cognition; Computer science; Machine learning","score_opus":0.16385716162347208,"score_gpt":0.3883942908832086,"score_spread":0.2245371292597365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763963518","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020812508,0.005195221,0.07397977,0.11676486,0.74214286,0.00013568962,0.0068704267,0.0018226552,0.051007256],"genre_scores_gemma":[0.043354623,0.017784528,0.1116888,0.052760314,0.12197449,0.00044680265,0.012757871,0.004682405,0.63455015],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991666,0.00016738218,0.00015602821,0.00016544554,0.0003106059,0.00003386956],"domain_scores_gemma":[0.99441224,0.0022460246,0.0002641092,0.0004294502,0.002403929,0.00024428742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020660402,0.0010997227,0.0008775155,0.0017923776,0.0014157413,0.0027140507,0.0026087603,0.0028511444,0.06705412],"category_scores_gemma":[0.024334798,0.0006525988,0.0011680801,0.0015346155,0.0016450281,0.0027752644,0.0014297978,0.004395547,0.022948908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027370123,0.000006413628,0.0001221244,0.00009121712,0.0000125799515,0.00018798199,0.000053130872,0.00040255443,0.000101371166,0.020183448,0.9605918,0.018220106],"study_design_scores_gemma":[0.00006069784,0.000029439834,0.00083335896,0.00031134946,0.000051052688,0.00077261805,0.00009908919,0.005530382,0.00068170816,0.059992637,0.9315604,0.000077419674],"about_ca_topic_score_codex":0.008954536,"about_ca_topic_score_gemma":0.011563707,"teacher_disagreement_score":0.06705412,"about_ca_system_score_codex":0.0012827347,"about_ca_system_score_gemma":0.0026632624,"threshold_uncertainty_score":0.22431839},"labels":[],"label_agreement":null},{"id":"W2764143201","doi":"10.1161/str.48.suppl_1.14","title":"Abstract 14: Effects of Lesion Laterality on Post-Stroke Motor Performance: An ENIGMA Stroke Recovery Analysis","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Laterality; Stroke (engine); Lesion; Lateralization of brain function; Physical medicine and rehabilitation; Stroke recovery; Physical therapy; Audiology; Pathology; Rehabilitation","score_opus":0.04431299141442506,"score_gpt":0.3541423515475729,"score_spread":0.3098293601331478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764143201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9139178,0.0008990234,0.011623476,0.00066500145,0.00016955967,0.0005281448,0.06890259,0.0010571942,0.0022373726],"genre_scores_gemma":[0.9292301,0.00012915113,0.005693649,0.00034329252,0.000087960776,0.001442067,0.058507986,0.00062191207,0.003943892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99410456,0.0025249878,0.00048662847,0.0017299426,0.0007371008,0.00041682672],"domain_scores_gemma":[0.9841241,0.009143985,0.0019940734,0.002976555,0.0012104239,0.00055089465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009985757,0.0011671381,0.0016855154,0.0013184274,0.0005858794,0.0014067971,0.0018251401,0.0010922883,0.013154959],"category_scores_gemma":[0.018492477,0.00031986772,0.0034928187,0.001255088,0.0008555969,0.000989938,0.0019855269,0.0015690423,0.0031901244],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.030137096,0.0019404277,0.791994,0.0018272613,0.033821374,0.00092996116,0.0009738704,0.006610481,0.009338049,0.0010742935,0.06655019,0.054803],"study_design_scores_gemma":[0.0008831316,0.0026682895,0.96599936,0.00012459491,0.003354575,0.00063741906,0.00035567858,0.011057822,0.0021188236,0.0009603834,0.011750213,0.000089786095],"about_ca_topic_score_codex":0.0038120633,"about_ca_topic_score_gemma":0.0037937167,"teacher_disagreement_score":0.013154959,"about_ca_system_score_codex":0.0004774102,"about_ca_system_score_gemma":0.0009145409,"threshold_uncertainty_score":0.05281037},"labels":[],"label_agreement":null},{"id":"W2764303658","doi":"10.1109/access.2017.2761701","title":"Data-Driven Corpus Callosum Parcellation Method Through Diffusion Tensor Imaging","year":2017,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Diffusion MRI; Artificial intelligence; Corpus callosum; Pattern recognition (psychology); Computer science; Tractography; Sørensen–Dice coefficient; Data set; Computer vision; Image segmentation; Segmentation; Psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.2846180431202832,"score_gpt":0.5028456206158834,"score_spread":0.21822757749560023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764303658","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011480073,0.00016540918,0.98644966,0.00010937155,0.000028960323,0.000095548516,0.00014136301,0.0012410445,0.0002885456],"genre_scores_gemma":[0.06808341,0.00027055803,0.92960894,0.000055777877,0.000037419864,0.00023415472,0.00062020804,0.00034586652,0.00074360153],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99931943,0.00013054218,0.00005000207,0.00018690477,0.00025701273,0.000056102188],"domain_scores_gemma":[0.9987244,0.0003795356,0.00019254547,0.00019802972,0.00045445023,0.000051034218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001086603,0.0010290178,0.0009077486,0.002114542,0.0005771063,0.0012178834,0.0012129361,0.00083226775,0.0011250093],"category_scores_gemma":[0.002944579,0.0004769583,0.0010919647,0.0015990073,0.00051671313,0.0011001728,0.0010777813,0.0011288857,0.00075083214],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028116693,0.00010844779,0.0028886353,0.0004212524,0.00032200493,0.00030632326,0.0005472491,0.0970391,0.12434819,0.0063714553,0.006023252,0.761343],"study_design_scores_gemma":[0.000041636493,0.000115921066,0.0034587393,0.000024782295,0.00011193647,0.00049379363,0.00011968374,0.89857596,0.08077099,0.004153817,0.012037732,0.000094929426],"about_ca_topic_score_codex":0.0052933316,"about_ca_topic_score_gemma":0.0063127102,"teacher_disagreement_score":0.0052933316,"about_ca_system_score_codex":0.0006601703,"about_ca_system_score_gemma":0.0017286077,"threshold_uncertainty_score":0.010525048},"labels":[],"label_agreement":null},{"id":"W2765232463","doi":"10.1038/s41598-018-22181-4","title":"AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Compute Canada; McGill University; Nvidia","keywords":"Convolutional neural network; Segmentation; Computer science; Artificial intelligence; Axon; Myelin; Pattern recognition (psychology); Image segmentation; Deep learning; Pixel; Magnetic resonance imaging; Artificial neural network; Computer vision; Neuroscience; Anatomy; Biology; Central nervous system; Medicine; Radiology","score_opus":0.11562764753880364,"score_gpt":0.3972882005873601,"score_spread":0.2816605530485564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765232463","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06341854,0.0014511144,0.79157406,0.0004068505,0.00020662116,0.00038103317,0.019087961,0.119397454,0.0040764087],"genre_scores_gemma":[0.14405932,0.00094422145,0.8050851,0.00042356976,0.00005070102,0.0008437616,0.03323465,0.0061104232,0.009248236],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997701,0.000019291763,0.000014729684,0.00008207022,0.00007616046,0.00003758545],"domain_scores_gemma":[0.99969506,0.000107310225,0.00004972441,0.000058134112,0.00006788417,0.000021937272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000696226,0.0016391799,0.00064829603,0.0017017428,0.0004689385,0.001047962,0.0015047787,0.00120705,0.0055431994],"category_scores_gemma":[0.0014853391,0.0008451652,0.0010150882,0.0008220409,0.0002973061,0.00092239195,0.0014270025,0.0010629051,0.002517502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008292111,0.0003067569,0.0064846063,0.0014173681,0.0009633761,0.00065015204,0.00029782555,0.12026412,0.12368001,0.007028419,0.12372408,0.61435413],"study_design_scores_gemma":[0.000088209614,0.00012911027,0.004646514,0.00011757574,0.00011448957,0.0005477668,0.000057066085,0.87767243,0.085410796,0.008912012,0.022220595,0.00008344671],"about_ca_topic_score_codex":0.009380973,"about_ca_topic_score_gemma":0.022898838,"teacher_disagreement_score":0.009380973,"about_ca_system_score_codex":0.0010618899,"about_ca_system_score_gemma":0.0017848101,"threshold_uncertainty_score":0.018652737},"labels":[],"label_agreement":null},{"id":"W2765503737","doi":"10.3171/2017.7.peds17137","title":"Corticospinal tract atrophy and motor fMRI predict motor preservation after functional cerebral hemispherectomy","year":2017,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; SickKids Foundation; Hospital for Sick Children; Toronto Western Hospital","funders":"University of California, Los Angeles; National Institutes of Health; Seattle Children's Research Institute","keywords":"Corticospinal tract; Medicine; Hemispherectomy; Neuroscience; Fractional anisotropy; Pyramidal tracts; Diffusion MRI; Atrophy; Motor cortex; Functional magnetic resonance imaging; Magnetic resonance imaging; Epilepsy; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Anatomy; Internal medicine; Stimulation","score_opus":0.056140547754351684,"score_gpt":0.3090965300936073,"score_spread":0.25295598233925565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765503737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997528,0.0006863962,0.0011751766,0.000033397067,0.000015178016,0.000024001201,0.000050318922,0.000020654114,0.00046677253],"genre_scores_gemma":[0.9992092,0.00007918744,0.0005927578,0.000008181195,0.000009338996,0.0000066989196,0.000038560873,0.000003436572,0.000052675005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981262,0.00067866937,0.0004318495,0.00029340497,0.00034070812,0.00012925731],"domain_scores_gemma":[0.9839516,0.0076282853,0.0039039315,0.00097143697,0.0030320717,0.0005125617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049460847,0.000387543,0.0005009348,0.0010629066,0.00032439968,0.0006228924,0.00039558028,0.0004764334,0.00059761637],"category_scores_gemma":[0.027434817,0.00023644783,0.00054750434,0.00031165848,0.00058224116,0.00057077385,0.00067581225,0.0002669427,0.0001607454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060234865,0.00002617534,0.98021394,0.00009306313,0.00018549814,0.0005948873,0.00048703517,0.0007057828,0.004384868,0.00002336847,0.00014340066,0.012539661],"study_design_scores_gemma":[0.000019928815,0.00036948634,0.9911374,0.0000440138,0.00011565178,0.0026621404,0.0005013883,0.0024489826,0.0023272375,0.0001044253,0.0002475756,0.000021871747],"about_ca_topic_score_codex":0.0013660964,"about_ca_topic_score_gemma":0.0027283449,"teacher_disagreement_score":0.0049460847,"about_ca_system_score_codex":0.00022309365,"about_ca_system_score_gemma":0.00036530624,"threshold_uncertainty_score":0.026157677},"labels":[],"label_agreement":null},{"id":"W2766009055","doi":"10.1007/s11011-017-0135-9","title":"Prenatal methamphetamine exposure is associated with corticostriatal white matter changes in neonates","year":2017,"lang":"en","type":"article","venue":"Metabolic Brain Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health; University of Cape Town; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"White matter; Methamphetamine; Diffusion MRI; Fractional anisotropy; Orbitofrontal cortex; Tractography; Striatum; Neuroscience; Psychology; Medicine; Psychiatry; Dopamine; Magnetic resonance imaging; Prefrontal cortex; Cognition","score_opus":0.03816196029757842,"score_gpt":0.3215380286692689,"score_spread":0.2833760683716905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766009055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987527,0.00053768244,0.00013749201,0.000086892614,0.000008751788,0.0000034356667,0.00011887487,0.000008316396,0.00034575135],"genre_scores_gemma":[0.99836165,0.00085400365,0.0002977608,0.000031817293,0.000016022008,0.000009046411,0.00014362467,0.000007915442,0.00027806388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979347,0.00004034925,0.000032639568,0.00005167446,0.00004643674,0.000035355217],"domain_scores_gemma":[0.9987072,0.00029499445,0.0007524239,0.000056091612,0.0000725007,0.00011682461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020204445,0.00044535362,0.0003085963,0.0009002451,0.0003049082,0.00033097083,0.0003714081,0.00056300306,0.0016529087],"category_scores_gemma":[0.001778997,0.00032613092,0.00030004085,0.00053701963,0.00038838532,0.00031143276,0.0004072191,0.0005662366,0.00015053898],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078416424,0.00014637849,0.9182252,0.0001387816,0.00012771,0.026318751,0.0005782428,0.00011966276,0.042600773,0.00016278528,0.0002210774,0.010576389],"study_design_scores_gemma":[0.0000032810938,0.000100741716,0.9823459,0.00004343107,0.000062314146,0.013152272,0.00034131255,0.00014769049,0.003451969,0.00009225045,0.00025030397,0.000008570585],"about_ca_topic_score_codex":0.004269554,"about_ca_topic_score_gemma":0.0036444159,"teacher_disagreement_score":0.004269554,"about_ca_system_score_codex":0.0002798855,"about_ca_system_score_gemma":0.00034229815,"threshold_uncertainty_score":0.00848937},"labels":[],"label_agreement":null},{"id":"W2766181796","doi":"10.1016/j.cortex.2017.10.022","title":"Short parietal lobe connections of the human and monkey brain","year":2017,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; King's College London; Wellcome Trust","keywords":"Supramarginal gyrus; Postcentral gyrus; Angular gyrus; Inferior parietal lobule; Superior parietal lobule; Neuroscience; Parietal lobe; Human brain; Psychology; Posterior parietal cortex; Middle temporal gyrus; Anatomy; Inferior temporal gyrus; Limbic lobe; Cortex (anatomy); Macaque; Superior temporal gyrus; Middle frontal gyrus; Temporal lobe; Cognition; Biology; Functional magnetic resonance imaging","score_opus":0.08919821177536608,"score_gpt":0.3927691679658896,"score_spread":0.30357095619052354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766181796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8602488,0.019553073,0.07647846,0.0017149963,0.00025297716,0.000037799156,0.0008965335,0.0004608777,0.040356513],"genre_scores_gemma":[0.98891187,0.0014662348,0.0058317618,0.0000963387,0.0000693182,0.000019709525,0.00016419835,0.00004483902,0.003395723],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99991655,0.000032644395,0.000003626833,0.000016702663,0.0000206653,0.000009937299],"domain_scores_gemma":[0.99951804,0.00029622388,0.000049817314,0.000048684928,0.00004646585,0.0000407296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023984643,0.00017325381,0.000118482756,0.00045540338,0.00021165011,0.0008175124,0.00023720157,0.00052177405,0.0050871707],"category_scores_gemma":[0.0023384632,0.00017656726,0.00014238256,0.00052710774,0.00061344175,0.0011798217,0.00046943763,0.0003878198,0.00043984668],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001094404,0.000063744126,0.022908552,0.00073411665,0.00038190675,0.003461411,0.0023626685,0.0064626485,0.48473412,0.12768051,0.0050627994,0.34505317],"study_design_scores_gemma":[0.00014062488,0.000517057,0.5426787,0.00014189606,0.0002322511,0.012108846,0.00160859,0.030231876,0.07462592,0.28620866,0.05141343,0.00009202215],"about_ca_topic_score_codex":0.0013263399,"about_ca_topic_score_gemma":0.002655267,"teacher_disagreement_score":0.0050871707,"about_ca_system_score_codex":0.00024434182,"about_ca_system_score_gemma":0.00030495616,"threshold_uncertainty_score":0.017018259},"labels":[],"label_agreement":null},{"id":"W2766426594","doi":"10.1016/j.neuroimage.2017.10.041","title":"PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":254,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Centre National de la Recherche Scientifique","keywords":"Spinal cord; Brainstem; Medicine; Computer science; White matter; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Radiology; Internal medicine","score_opus":0.07279584564477942,"score_gpt":0.3629979640391347,"score_spread":0.2902021183943553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766426594","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1829557,0.0028571254,0.7529369,0.0019060784,0.00044958686,0.00037788347,0.024086084,0.01386535,0.020565344],"genre_scores_gemma":[0.5553143,0.0016984416,0.40811962,0.0014938071,0.00029464555,0.0008419302,0.01743537,0.0037203592,0.011081602],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985766,0.00002227055,0.000008062044,0.00003975459,0.000036406174,0.00003587071],"domain_scores_gemma":[0.9998271,0.0000387152,0.000020873873,0.000030297797,0.000057263536,0.000025810205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005065652,0.00055155944,0.00038003357,0.0010529602,0.00039979257,0.000993174,0.0005968863,0.0014026666,0.00935711],"category_scores_gemma":[0.002035768,0.0004196361,0.00048137407,0.0009009646,0.00026558252,0.0006005289,0.0008511778,0.00068923115,0.003009213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014660055,0.00019787913,0.008319729,0.00093364395,0.00038564397,0.0010511982,0.0005050455,0.03134243,0.29307303,0.0123350555,0.13662934,0.513761],"study_design_scores_gemma":[0.00028731968,0.0006606232,0.09087127,0.000437496,0.0008263995,0.01091354,0.0005704247,0.34575304,0.32288188,0.039053783,0.18723334,0.0005108719],"about_ca_topic_score_codex":0.005655611,"about_ca_topic_score_gemma":0.011814189,"teacher_disagreement_score":0.00935711,"about_ca_system_score_codex":0.00038567,"about_ca_system_score_gemma":0.0016666419,"threshold_uncertainty_score":0.03130269},"labels":[],"label_agreement":null},{"id":"W2766639217","doi":"10.1038/s41467-017-01285-x","title":"The challenge of mapping the human connectome based on diffusion tractography","year":2017,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1432,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MaRS; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Centre d'Imagerie BioMédicale; National Natural Science Foundation of China; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; École Polytechnique Fédérale de Lausanne; Deutsche Forschungsgemeinschaft; China Scholarship Council; National Institute for Health and Care Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; National Cancer Institute; Université de Sherbrooke; National Science Foundation","keywords":"Connectome; Tractography; Diffusion MRI; Human Connectome Project; Connectomics; Computer science; Neuroscience; Diffusion; Computational biology; Functional connectivity; Medicine; Biology; Magnetic resonance imaging; Physics; Radiology","score_opus":0.1387769546426739,"score_gpt":0.4102983062435371,"score_spread":0.2715213516008632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766639217","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0791158,0.005285465,0.902613,0.0068871393,0.00022416729,0.00010789054,0.0008872858,0.0011422371,0.003736979],"genre_scores_gemma":[0.5836711,0.00389222,0.40861496,0.00074467243,0.00044586742,0.00023345102,0.0008282211,0.0009092222,0.0006602386],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9804387,0.01291222,0.0011465829,0.002662163,0.0025767968,0.00026355436],"domain_scores_gemma":[0.85452205,0.10960926,0.009014599,0.020070687,0.0059307655,0.00085254223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.026583545,0.00073562335,0.0015000484,0.0040383176,0.0010786004,0.0049659875,0.0015885449,0.0019942143,0.0012736408],"category_scores_gemma":[0.17392285,0.000749274,0.00088475674,0.003717469,0.0042240135,0.004894801,0.0025023192,0.0020493465,0.0010662596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039442568,0.0000925281,0.062456492,0.0032427958,0.0012084045,0.000811279,0.004347575,0.17681023,0.03970598,0.099073224,0.014969426,0.59688765],"study_design_scores_gemma":[0.000054005817,0.00017402876,0.048430894,0.0009171568,0.0001878723,0.0024460547,0.0013205219,0.35624805,0.013225346,0.54687995,0.029894706,0.00022149013],"about_ca_topic_score_codex":0.0029432229,"about_ca_topic_score_gemma":0.0032755611,"teacher_disagreement_score":0.026583545,"about_ca_system_score_codex":0.0010350376,"about_ca_system_score_gemma":0.0028404074,"threshold_uncertainty_score":0.14058888},"labels":[],"label_agreement":null},{"id":"W2766986295","doi":"10.1016/j.mri.2017.07.027","title":"A novel DTI-QA tool: Automated metric extraction exploiting the sphericity of an agar filled phantom","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Sphericity; Imaging phantom; Metric (unit); Extraction (chemistry); Computer science; Biomedical engineering; Mathematics; Chromatography; Nuclear medicine; Chemistry; Medicine; Engineering; Geometry","score_opus":0.06488995868777386,"score_gpt":0.3745805827896747,"score_spread":0.30969062410190085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766986295","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023816486,0.000100504694,0.9876816,0.00006492191,0.000028671002,0.00005955399,0.0002938958,0.008843621,0.0005455809],"genre_scores_gemma":[0.029566495,0.0001539932,0.96653104,0.00011833197,0.000023842458,0.00011310898,0.00063894904,0.0015547778,0.0012994967],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995827,0.000057510126,0.000037951522,0.000064689724,0.00022436792,0.00003282671],"domain_scores_gemma":[0.9985495,0.00049216225,0.00017234965,0.00019557173,0.00048966124,0.00010065538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011345721,0.0016431622,0.0009438409,0.0021733823,0.00047217635,0.0021059457,0.001702947,0.0017391201,0.0112901665],"category_scores_gemma":[0.004968031,0.0008033794,0.00066129107,0.0014548558,0.00034675605,0.0014674657,0.0018643554,0.0011080977,0.00481807],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053202506,0.00015833198,0.0013873224,0.0008533403,0.0001419938,0.00042461962,0.0002158634,0.025130125,0.16652265,0.007372358,0.023263032,0.77399826],"study_design_scores_gemma":[0.000087358094,0.00015175647,0.0017480978,0.000092052855,0.00006133025,0.0014404261,0.00007632585,0.7977171,0.16531666,0.008059838,0.025107326,0.0001417897],"about_ca_topic_score_codex":0.0012743317,"about_ca_topic_score_gemma":0.00204996,"teacher_disagreement_score":0.0112901665,"about_ca_system_score_codex":0.000414391,"about_ca_system_score_gemma":0.0014818884,"threshold_uncertainty_score":0.037769377},"labels":[],"label_agreement":null},{"id":"W2767050687","doi":"10.1038/mp.2017.170","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":736,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Norges Forskningsråd; National Health and Medical Research Council; Helse Sør-Øst RHF; Medical Research Council; NSW Ministry of Health; National Institute of Mental Health; Ministero della Salute; Office of Health and Medical Research; Hunter Medical Research Institute; Wellcome Trust; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Schizophrenia (object-oriented programming); Corpus callosum; White matter; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04207327760869915,"score_gpt":0.3272838972083747,"score_spread":0.28521061959967553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767050687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96950275,0.017013038,0.0017401995,0.00012831751,0.000022703427,0.00012082822,0.010971351,0.000052733565,0.00044824427],"genre_scores_gemma":[0.9865866,0.0031239875,0.0017681587,0.00009676997,0.000019609639,0.00020331566,0.0079374,0.000058664125,0.00020544212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959462,0.0014518879,0.0007894207,0.0012134587,0.000430466,0.00016853979],"domain_scores_gemma":[0.99445677,0.0018826737,0.0016778192,0.0010652426,0.0006261583,0.00029125914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070076897,0.0011000826,0.0016610547,0.0031713347,0.0008547682,0.0013091193,0.0007375491,0.0005444662,0.0013995931],"category_scores_gemma":[0.010139156,0.0006431993,0.002919201,0.0046942467,0.0005596554,0.00046753968,0.001975071,0.00038195294,0.0003192103],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038240012,0.00010140101,0.9067348,0.0022063565,0.049565013,0.000347689,0.0014505534,0.0006628339,0.0049431985,0.00022725087,0.0020863104,0.027850665],"study_design_scores_gemma":[0.0002471999,0.0002643485,0.9758099,0.00022958673,0.019714119,0.0003336365,0.00034218113,0.00016181845,0.0005483528,0.00022622163,0.0020870895,0.00003542294],"about_ca_topic_score_codex":0.015447306,"about_ca_topic_score_gemma":0.019892257,"teacher_disagreement_score":0.015447306,"about_ca_system_score_codex":0.00063691684,"about_ca_system_score_gemma":0.00093728915,"threshold_uncertainty_score":0.03706062},"labels":[],"label_agreement":null},{"id":"W2767073388","doi":"10.1016/j.neuroimage.2017.10.033","title":"Associations between prenatal, childhood, and adolescent stress and variations in white-matter properties in young men","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Economic and Social Research Council; National Institute of Mental Health; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; University of Bristol; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Prenatal stress; Psychology; Developmental psychology; White matter; Stress (linguistics); Clinical psychology; Medicine; Pregnancy; Biology; Genetics; Gestation; Philosophy; Magnetic resonance imaging","score_opus":0.12000149264979423,"score_gpt":0.3781422829021788,"score_spread":0.25814079025238457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767073388","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002687536,0.99655354,0.00008024127,0.00023952809,0.000061212,0.000002683127,0.0000942381,0.000003835321,0.00027711777],"genre_scores_gemma":[0.00834155,0.99082315,0.00024139408,0.0001334565,0.00017825852,0.0000054425036,0.00010911637,0.0000015145073,0.0001661023],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9999008,0.000015550751,0.00001790331,0.00003494234,0.000022885977,0.000007906844],"domain_scores_gemma":[0.9996462,0.00018646108,0.00009132738,0.000009837927,0.00005128599,0.000014947937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045203287,0.00059979246,0.00092233793,0.00094614626,0.00015821084,0.00058539456,0.00055108155,0.00060377124,0.0010397646],"category_scores_gemma":[0.0010162847,0.00021205633,0.0005064737,0.0013575442,0.0002923947,0.00046548454,0.0003972595,0.0006022852,0.0002469824],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037981878,0.000081004015,0.035468027,0.019867802,0.002090851,0.00057644316,0.0001965699,0.00034763856,0.0018429203,0.0010300641,0.007432978,0.9306859],"study_design_scores_gemma":[0.0001339808,0.00052709045,0.55914885,0.023984443,0.009685769,0.00862533,0.0010220205,0.00041628422,0.0025128159,0.0073352614,0.38639355,0.00021450476],"about_ca_topic_score_codex":0.0040664207,"about_ca_topic_score_gemma":0.00764055,"teacher_disagreement_score":0.0040664207,"about_ca_system_score_codex":0.00021991899,"about_ca_system_score_gemma":0.000752494,"threshold_uncertainty_score":0.008085489},"labels":[],"label_agreement":null},{"id":"W2767236431","doi":"10.1016/j.neuroscience.2017.10.050","title":"White Matter Changes Correlates of Peripheral Neuroinflammation in Patients with Parkinson’s Disease","year":2017,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael J. Fox Foundation for Parkinson's Research","keywords":"White matter; Corpus callosum; Splenium; Fornix; Cingulum (brain); Neuroinflammation; Diffusion MRI; Pathology; Neuroscience; Parkinson's disease; Neurodegeneration; Corticospinal tract; Psychology; Medicine; Disease; Magnetic resonance imaging; Fractional anisotropy; Hippocampus; Radiology","score_opus":0.029635594694023246,"score_gpt":0.29967394629913907,"score_spread":0.2700383516051158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767236431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987232,0.00057121273,0.000046204335,0.000034509543,0.0000043260375,0.0000037431028,0.00006213744,0.000002602989,0.00055210135],"genre_scores_gemma":[0.99949515,0.00017593603,0.000049419265,0.000019960979,0.000013772229,0.000003142111,0.000087242704,8.6734906e-7,0.00015436312],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998636,0.000026240026,0.000028456292,0.000036603753,0.000021076694,0.000023981347],"domain_scores_gemma":[0.9993783,0.00011571428,0.00034272618,0.000021631133,0.00006775125,0.000073746254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020969028,0.0003302714,0.0003851885,0.00067771133,0.0004342876,0.0005078026,0.00015918171,0.0004493707,0.0012400552],"category_scores_gemma":[0.001162987,0.00018698926,0.00019227607,0.000641764,0.0003249745,0.000385624,0.0002802262,0.00035993714,0.00016482639],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010162906,0.000090185145,0.9886302,0.000047341706,0.00013869628,0.0016010446,0.00019407042,0.00009417797,0.0032637597,0.000035163324,0.000102160324,0.00478693],"study_design_scores_gemma":[0.0000057067887,0.00010486081,0.99803406,0.0000061537617,0.000030448937,0.0013597838,0.00009910834,0.000079834936,0.0001760191,0.00003912537,0.00006244285,0.0000025001116],"about_ca_topic_score_codex":0.001574014,"about_ca_topic_score_gemma":0.0026043272,"teacher_disagreement_score":0.001574014,"about_ca_system_score_codex":0.00021801576,"about_ca_system_score_gemma":0.00015765829,"threshold_uncertainty_score":0.004148364},"labels":[],"label_agreement":null},{"id":"W2768007735","doi":"10.1177/0271678x17740501","title":"Lesion location matters: The relationships between white matter hyperintensities on cognition in the healthy elderly","year":2017,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Hyperintensity; Cognition; Lesion; Psychology; White matter; Cognitive aging; Medicine; Cognitive psychology; Audiology; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.1131383849703217,"score_gpt":0.35109328363517933,"score_spread":0.23795489866485764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768007735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987136,0.0005789742,0.00019061261,0.00003377062,0.00000354356,0.0000034788015,0.00007756691,0.0000044707135,0.00039396874],"genre_scores_gemma":[0.9995833,0.00009132207,0.00009926142,0.000016374832,0.000012686864,0.0000015015825,0.00004426512,0.0000015760721,0.00014976827],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986136,0.000033377262,0.000015505297,0.000046386074,0.000025780782,0.000017663584],"domain_scores_gemma":[0.9994443,0.00012896399,0.00025825127,0.0000726499,0.000045651796,0.000050111004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004258099,0.00033882307,0.00030547474,0.0006597973,0.0002009051,0.00041986257,0.00020518289,0.0003912234,0.0013582801],"category_scores_gemma":[0.001394848,0.0001305377,0.00019097826,0.0004428044,0.0003307349,0.0005104652,0.00037728602,0.00020219496,0.0002620054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007079087,0.00007368253,0.97571915,0.00005980786,0.00022927199,0.00035693074,0.00023169954,0.00011235384,0.009071525,0.000060863294,0.00010652035,0.013270251],"study_design_scores_gemma":[0.0000025600734,0.000089409856,0.9989291,0.0000035169974,0.000030301922,0.0002882706,0.00006603864,0.00007379181,0.0003676277,0.000082766266,0.00006476937,0.0000018269867],"about_ca_topic_score_codex":0.001532318,"about_ca_topic_score_gemma":0.0031652746,"teacher_disagreement_score":0.001532318,"about_ca_system_score_codex":0.000095010255,"about_ca_system_score_gemma":0.00016390969,"threshold_uncertainty_score":0.004543841},"labels":[],"label_agreement":null},{"id":"W2768161353","doi":"10.1002/hbm.23900","title":"Integration of routine QA data into mega‐analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Fractional anisotropy; Diffusion MRI; Principal component analysis; Multivariate statistics; Statistics; Explained variation; White matter; Mathematics; Regression; Variance (accounting); Nuclear medicine; Artificial intelligence; Psychology; Pattern recognition (psychology); Computer science; Medicine; Magnetic resonance imaging","score_opus":0.2754570418686222,"score_gpt":0.4852983870692898,"score_spread":0.2098413452006676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768161353","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08316744,0.0012644536,0.90464437,0.0013549225,0.00027630496,0.00076398364,0.0014772532,0.005180333,0.0018709614],"genre_scores_gemma":[0.3346984,0.00028195497,0.6601005,0.0004840563,0.00018686485,0.0008066348,0.0016198917,0.0013282865,0.0004934488],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.93711483,0.05034881,0.004536386,0.0040262523,0.0035141332,0.00045950248],"domain_scores_gemma":[0.7452737,0.15101397,0.016633771,0.061822277,0.024058344,0.001198007],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.13160716,0.0014320005,0.0020576594,0.003639763,0.0008580241,0.0037917113,0.002046536,0.0011253082,0.0038481476],"category_scores_gemma":[0.24046935,0.0013025544,0.00241041,0.004162499,0.0012391602,0.0028140296,0.0034505036,0.001580785,0.0010906762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055294605,0.0009574121,0.18641925,0.00375952,0.012653666,0.0003915461,0.0034186596,0.040289167,0.05471029,0.018182486,0.023501905,0.65018654],"study_design_scores_gemma":[0.001296033,0.003209916,0.3543053,0.000791017,0.005148483,0.0008203881,0.001057036,0.44726133,0.057660554,0.079683125,0.04813205,0.00063470355],"about_ca_topic_score_codex":0.001770149,"about_ca_topic_score_gemma":0.0037156544,"teacher_disagreement_score":0.8683928,"about_ca_system_score_codex":0.00065780664,"about_ca_system_score_gemma":0.0018089458,"threshold_uncertainty_score":0.6960135},"labels":[],"label_agreement":null},{"id":"W2768632892","doi":"10.1016/j.eplepsyres.2017.11.010","title":"Histological and MRI markers of white matter damage in focal epilepsy","year":2017,"lang":"en","type":"review","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"White matter; Epilepsy; Diffusion MRI; Cortical dysplasia; Neuroscience; Neuroimaging; Magnetic resonance imaging; Pathology; Medicine; Temporal lobe; Psychology; Radiology","score_opus":0.3585299072192049,"score_gpt":0.5228600838039462,"score_spread":0.1643301765847413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768632892","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009322281,0.99942744,0.000056397137,0.00008598512,0.000049292692,0.0000021564642,0.000012674292,0.0000022534923,0.00027058314],"genre_scores_gemma":[0.0006453184,0.99887997,0.00011908644,0.000078606834,0.00010549086,0.000002285872,0.000019993415,5.159933e-7,0.00014882511],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9998233,0.000022351893,0.00004543742,0.00003720897,0.00005829825,0.000013527779],"domain_scores_gemma":[0.9995528,0.0002166715,0.0001023347,0.000010827089,0.00009479616,0.000022450085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057834963,0.0009883379,0.0015617976,0.0029179202,0.00017270606,0.000996331,0.00080063,0.0008090194,0.001723398],"category_scores_gemma":[0.0010861254,0.00029405864,0.00049884245,0.0025200765,0.0006188582,0.0013511073,0.00063796266,0.0010923264,0.00081875507],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009773757,0.00004519419,0.000597343,0.025481349,0.00019456726,0.00030717193,0.000054689666,0.00022726551,0.0013521237,0.0013771835,0.011964625,0.9583008],"study_design_scores_gemma":[0.00007288926,0.00023903801,0.008251493,0.023146285,0.0016079413,0.0069965483,0.00033287384,0.00028120846,0.0015547025,0.006006782,0.9514082,0.00010195483],"about_ca_topic_score_codex":0.0016257787,"about_ca_topic_score_gemma":0.003380702,"teacher_disagreement_score":0.0029179202,"about_ca_system_score_codex":0.00038190561,"about_ca_system_score_gemma":0.0010857561,"threshold_uncertainty_score":0.0057653785},"labels":[],"label_agreement":null},{"id":"W2769873747","doi":"10.1016/j.neuropsychologia.2017.11.017","title":"More than blindsight: Case report of a child with extraordinary visual capacity following perinatal bilateral occipital lobe injury","year":2017,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; State Government of Victoria; Australian Government","keywords":"Blindsight; Psychology; Occipital lobe; Visual cortex; Neuroscience; Visual field; Cortical blindness; N2pc; Cortex (anatomy); Temporal lobe; Visual perception; Extrastriate cortex; Audiology; Perception; Blindness; Medicine; Epilepsy; Optometry","score_opus":0.05564976656072537,"score_gpt":0.39066700030885576,"score_spread":0.3350172337481304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769873747","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96636224,0.0043230485,0.0037738748,0.008963846,0.0016897928,0.0003523527,0.00089514244,0.000539034,0.013100709],"genre_scores_gemma":[0.9865394,0.0025093323,0.0034594212,0.0023601297,0.0015510113,0.0000681176,0.00023432505,0.00015150648,0.003126707],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9981281,0.00013740119,0.00024667082,0.0005811525,0.00029613008,0.00061050337],"domain_scores_gemma":[0.9931477,0.0019840838,0.0016170593,0.0006254519,0.00042489334,0.0022009255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006188768,0.0046265023,0.002723397,0.0051801745,0.0059243087,0.003046931,0.0043289075,0.009194193,0.003493038],"category_scores_gemma":[0.007649844,0.00231896,0.0027881449,0.0038060884,0.005325957,0.0033152262,0.004430258,0.008614668,0.0011377259],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000065386535,0.000017367303,0.0006799325,0.000007120977,0.0000023319,0.9988764,0.00005272168,0.000014281595,0.00011703577,0.000036853184,0.00004713491,0.00014238303],"study_design_scores_gemma":[0.0000035318221,0.00003208894,0.0011386411,0.0000066804096,0.000010734057,0.9982383,0.00011957217,0.000056613102,0.00018633046,0.00008939116,0.0001085588,0.000009500339],"about_ca_topic_score_codex":0.007958206,"about_ca_topic_score_gemma":0.010071386,"teacher_disagreement_score":0.009194193,"about_ca_system_score_codex":0.003172039,"about_ca_system_score_gemma":0.0031266313,"threshold_uncertainty_score":0.023014843},"labels":[],"label_agreement":null},{"id":"W276996006","doi":"10.1007/978-3-319-10443-0_22","title":"Automatic Method for Thalamus Parcellation Using Multi-modal Feature Classification","year":2014,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Computer science; Modal; Artificial intelligence; Pattern recognition (psychology); Feature (linguistics)","score_opus":0.1041728978129066,"score_gpt":0.4138508495461696,"score_spread":0.30967795173326296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W276996006","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018539958,0.00068542064,0.97273016,0.00016165702,0.00012873704,0.0001679448,0.0008544466,0.00546143,0.0012702403],"genre_scores_gemma":[0.16408812,0.000651915,0.8273411,0.00016731308,0.00013649798,0.00034294682,0.0026024042,0.0007977635,0.0038720355],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994085,0.000055618282,0.00003520896,0.000207296,0.00016500417,0.00012831176],"domain_scores_gemma":[0.99932826,0.00013849179,0.00005701248,0.00010591106,0.00031763033,0.000052715357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068633497,0.0013043458,0.001294825,0.0023442493,0.0006589451,0.0014808013,0.001551502,0.0013003151,0.004716695],"category_scores_gemma":[0.0012097383,0.00048115847,0.0013713078,0.0018938772,0.00030157343,0.00081887026,0.0011797767,0.0011248817,0.0033368769],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003985924,0.000111610905,0.0027339594,0.0002229864,0.00012084451,0.0001891254,0.00012112153,0.0038323686,0.15224367,0.0012418906,0.008408881,0.83037496],"study_design_scores_gemma":[0.00014178304,0.00026214434,0.027964141,0.00007984801,0.0004290416,0.0018000556,0.00031951786,0.7129375,0.22717111,0.007307869,0.021388117,0.00019881174],"about_ca_topic_score_codex":0.0065347846,"about_ca_topic_score_gemma":0.01143804,"teacher_disagreement_score":0.0065347846,"about_ca_system_score_codex":0.00039267988,"about_ca_system_score_gemma":0.0012898307,"threshold_uncertainty_score":0.0157789},"labels":[],"label_agreement":null},{"id":"W2770851226","doi":"10.1016/j.neuroimage.2017.11.038","title":"Effects of bilingualism on white matter integrity in older adults","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; York University","funders":"National Institute on Aging; National Institutes of Health","keywords":"Fractional anisotropy; Neuroscience of multilingualism; White matter; Psychology; Cognitive reserve; Diffusion MRI; Dementia; Mechanism (biology); Cognition; Audiology; Neuroscience; Medicine; Cognitive impairment; Physics; Magnetic resonance imaging; Pathology","score_opus":0.03388399414908069,"score_gpt":0.35974322054175445,"score_spread":0.32585922639267373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770851226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992749,0.00017352153,0.000020745072,0.000048440437,0.0000045974743,0.0000017341017,0.000049595885,0.0000016851145,0.00042479625],"genre_scores_gemma":[0.9995153,0.000086560736,0.000039414117,0.000027464708,0.000009845179,0.0000017308555,0.000050304807,0.0000019543163,0.00026738617],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999175,0.000016665923,0.000012722637,0.00002344474,0.000013526757,0.00001619818],"domain_scores_gemma":[0.99938655,0.00015729737,0.00026234976,0.000033058852,0.0000627467,0.00009795435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024564686,0.00026905607,0.00029046394,0.00029376944,0.00033930386,0.00036705134,0.000088499495,0.00039296877,0.0025930235],"category_scores_gemma":[0.0015707308,0.00015000909,0.00016650601,0.00019812412,0.00032667923,0.00041323298,0.00033273146,0.0002900154,0.0002043161],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.025268504,0.0007211473,0.882519,0.00019553729,0.0006725503,0.0037985346,0.0020475488,0.00022946247,0.060580656,0.00023830304,0.0004698853,0.02325881],"study_design_scores_gemma":[0.000046871486,0.00059044745,0.99707234,0.000008881088,0.00010132191,0.000650543,0.00024490608,0.00007320842,0.00095481786,0.00014683684,0.00010552021,0.000004248512],"about_ca_topic_score_codex":0.004870902,"about_ca_topic_score_gemma":0.011935985,"teacher_disagreement_score":0.004870902,"about_ca_system_score_codex":0.00024210193,"about_ca_system_score_gemma":0.00022060383,"threshold_uncertainty_score":0.009685099},"labels":[],"label_agreement":null},{"id":"W2771176174","doi":"10.2967/jnumed.117.200006","title":"Flortaucipir F 18 Quantitation Using Parametric Estimation of Reference Signal Intensity","year":2017,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Avid Radiopharmaceuticals; Eli Lilly and Company","keywords":"White matter; Partial volume; Nuclear medicine; Voxel; Spatial normalization; Alzheimer's disease; Medicine; Magnetic resonance imaging; Pathology; Radiology; Disease","score_opus":0.3348029175542141,"score_gpt":0.4658599099119657,"score_spread":0.1310569923577516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771176174","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33551452,0.0017942186,0.6556921,0.00014363718,0.000051865987,0.000104986226,0.00041414856,0.0030133838,0.0032712298],"genre_scores_gemma":[0.58788395,0.00094545353,0.40692154,0.00006778055,0.000028094271,0.0003374148,0.00062820496,0.00090311,0.002284556],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994246,0.00014186178,0.000038978,0.00019333519,0.00014396955,0.00005739365],"domain_scores_gemma":[0.99908733,0.00025299273,0.00029247254,0.0001993799,0.00013385325,0.000033948007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014048865,0.000924541,0.00043469868,0.0015020245,0.0003202656,0.0012515199,0.0009362364,0.0007610273,0.001138225],"category_scores_gemma":[0.004053025,0.000549124,0.0004890057,0.00080024864,0.0007469723,0.0010823961,0.0005363965,0.00073557143,0.00042967926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008076359,0.00010593019,0.010168605,0.00023980028,0.00018691718,0.00036565348,0.0002525555,0.0082077775,0.80597293,0.0024095199,0.00086886814,0.1704139],"study_design_scores_gemma":[0.00005437408,0.00085155206,0.053482402,0.00004564805,0.00019162416,0.0041431123,0.00013788763,0.122002065,0.80852604,0.002845136,0.0075302846,0.00018982292],"about_ca_topic_score_codex":0.0015767013,"about_ca_topic_score_gemma":0.002589857,"teacher_disagreement_score":0.0015767013,"about_ca_system_score_codex":0.00067001645,"about_ca_system_score_gemma":0.0004837665,"threshold_uncertainty_score":0.007429838},"labels":[],"label_agreement":null},{"id":"W2771290777","doi":"10.1002/hbm.23908","title":"Cerebral sex dimorphism and sexual orientation","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Vetenskapsrådet; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; Alberta Foundation for the Arts","keywords":"Sexual dimorphism; Sexual orientation; Psychology; Precuneus; Sex characteristics; Fractional anisotropy; Cerebral cortex; Developmental psychology; Heterosexuality; Sexual differentiation; Homosexuality; White matter; Neuroscience; Biology; Cognition; Zoology; Genetics; Social psychology; Medicine; Magnetic resonance imaging; Psychoanalysis","score_opus":0.13840602051202386,"score_gpt":0.3929665288813349,"score_spread":0.254560508369311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771290777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99634844,0.0013073976,0.00019008035,0.000039405,0.000007929076,0.000004571847,0.00010044539,0.000003567121,0.001998081],"genre_scores_gemma":[0.9989311,0.00043712766,0.00008044475,0.00001974296,0.0000081970975,0.0000034451925,0.00006795577,0.0000020972893,0.0004498901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991107,0.00002518074,0.0000045972874,0.000025629653,0.000017090835,0.00001647566],"domain_scores_gemma":[0.9997632,0.000059158345,0.00009390856,0.00002141209,0.000021576732,0.000040711784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017010061,0.00013502984,0.00015120592,0.00043097552,0.00013623106,0.0002898769,0.00011847474,0.00013254152,0.0021899128],"category_scores_gemma":[0.00065802515,0.0000675626,0.00008324061,0.00024012101,0.00032433812,0.00013927756,0.0001668213,0.00012555666,0.00015504667],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012281552,0.00009166541,0.871482,0.00012563479,0.00023394192,0.0022192914,0.0014557502,0.00014642978,0.051408105,0.0022432504,0.0005527905,0.068812855],"study_design_scores_gemma":[0.0000048331376,0.000089445595,0.9959203,0.000007758197,0.000014457058,0.0015648183,0.0002268599,0.00008100967,0.0011012818,0.0004681258,0.0005155654,0.0000053923454],"about_ca_topic_score_codex":0.0006189697,"about_ca_topic_score_gemma":0.00065421575,"teacher_disagreement_score":0.0021899128,"about_ca_system_score_codex":0.000102219994,"about_ca_system_score_gemma":0.000078990044,"threshold_uncertainty_score":0.0073259473},"labels":[],"label_agreement":null},{"id":"W2771937409","doi":"10.1089/neu.2017.5274","title":"Decreased Number of Self-Paced Saccades in Post-Concussion Syndrome Associated with Higher Symptom Burden and Reduced White Matter Integrity","year":2017,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network; Toronto Western Hospital; Hospital for Sick Children; Occupational Cancer Research Centre","funders":"","keywords":"Post-concussion syndrome; Concussion; Traumatic brain injury; White matter; Medicine; Psychology; Physical medicine and rehabilitation; Poison control; Injury prevention; Psychiatry; Audiology; Medical emergency; Magnetic resonance imaging","score_opus":0.05738284679522208,"score_gpt":0.3627935700725841,"score_spread":0.305410723277362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771937409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998227,0.000054287393,0.00003125542,0.0000073387014,7.2473773e-7,0.0000023125635,0.000027844622,0.0000013908921,0.000052151645],"genre_scores_gemma":[0.99972266,0.000036439433,0.00007174641,0.0000050491244,0.0000026939142,0.0000036141187,0.00008978109,8.962539e-7,0.000067097586],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997414,0.00005214422,0.000045052497,0.00006499809,0.0000623177,0.000034065415],"domain_scores_gemma":[0.99783367,0.00022636492,0.0014435457,0.000085638494,0.00024755494,0.0001632082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003048547,0.00039874643,0.00039704028,0.0010374201,0.00032246448,0.00041237354,0.00027624954,0.0004512117,0.0015541117],"category_scores_gemma":[0.0028643026,0.0002222563,0.00024228179,0.00054345466,0.00037758407,0.00034286611,0.00051273685,0.00033252404,0.00022626907],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002458224,0.000031948028,0.99534875,0.0000165285,0.00004946636,0.00021151984,0.00020355635,0.000043013944,0.0019948182,0.000008102677,0.000022880726,0.0018235141],"study_design_scores_gemma":[0.000002789767,0.00006255096,0.99935395,0.0000024185686,0.0000098072705,0.00027971706,0.000099591154,0.00005870361,0.000103043276,0.000008575633,0.000017237282,0.0000014836377],"about_ca_topic_score_codex":0.0042512873,"about_ca_topic_score_gemma":0.0053874515,"teacher_disagreement_score":0.0042512873,"about_ca_system_score_codex":0.00021677336,"about_ca_system_score_gemma":0.00025655524,"threshold_uncertainty_score":0.008453131},"labels":[],"label_agreement":null},{"id":"W2775461784","doi":"10.1016/j.neuroimage.2017.12.036","title":"Surface-enhanced tractography (SET)","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Streamlines, streaklines, and pathlines; Connectomics; Artificial intelligence; Computer science; Diffusion MRI; Human Connectome Project; Pattern recognition (psychology); Computer vision; Neuroscience; Connectome; Magnetic resonance imaging; Physics; Psychology; Radiology; Medicine; Functional connectivity","score_opus":0.11706797726663845,"score_gpt":0.40060523113589525,"score_spread":0.28353725386925677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775461784","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037275817,0.0016100637,0.94373846,0.0004688402,0.00016884872,0.00017519204,0.003137841,0.0059085377,0.0075164177],"genre_scores_gemma":[0.2333615,0.0024433057,0.74918187,0.000513326,0.00020823449,0.0005147806,0.0030805515,0.0022070794,0.008489407],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996542,0.000101920414,0.000034185457,0.00006722416,0.00010793488,0.00003451491],"domain_scores_gemma":[0.99919087,0.00032582288,0.00010544371,0.0001686341,0.00015278674,0.00005648621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081450754,0.0009969805,0.00067353225,0.0020232708,0.00058527716,0.0024576855,0.0009361035,0.0022035346,0.0132748],"category_scores_gemma":[0.00328803,0.00064048904,0.0014604303,0.0022855243,0.0005234822,0.0013609359,0.0011060818,0.0012896336,0.0035239542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010209917,0.00023422064,0.009244979,0.0023023197,0.0012140283,0.0018463898,0.0005764809,0.069244936,0.10955739,0.02755317,0.033944603,0.74326044],"study_design_scores_gemma":[0.00027750764,0.000843595,0.017529672,0.0005694082,0.0011612237,0.016133139,0.00030586423,0.59437686,0.17380075,0.09162046,0.102911286,0.00047014924],"about_ca_topic_score_codex":0.0032951839,"about_ca_topic_score_gemma":0.0053044325,"teacher_disagreement_score":0.0132748,"about_ca_system_score_codex":0.000419355,"about_ca_system_score_gemma":0.0017365773,"threshold_uncertainty_score":0.04440862},"labels":[],"label_agreement":null},{"id":"W2776173315","doi":"10.3389/fnana.2017.00129","title":"Axon and Myelin Morphology in Animal and Human Spinal Cord","year":2017,"lang":"en","type":"review","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation","keywords":"Axon; Neuroscience; Spinal cord; White matter; Myelin; Segmentation; Myelin sheath; Biology; Computer science; Anatomy; Artificial intelligence; Magnetic resonance imaging; Central nervous system; Medicine","score_opus":0.1548428791220594,"score_gpt":0.4555201286528816,"score_spread":0.3006772495308222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2776173315","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96694124,0.017015833,0.007320325,0.00021534269,0.000040212457,0.000030631,0.0014266497,0.00014888213,0.0068608127],"genre_scores_gemma":[0.9759798,0.009960347,0.008888947,0.00009329903,0.000019606867,0.00003429106,0.0012105072,0.000052342257,0.003760916],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99981946,0.00003644435,0.000013902983,0.00005578536,0.000061654144,0.0000128233905],"domain_scores_gemma":[0.99973863,0.00006690543,0.000070519854,0.000032552416,0.000069439455,0.00002181345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004501036,0.00010763975,0.00013003963,0.0012973777,0.00019408634,0.00034928988,0.00017717473,0.00032240056,0.0017638946],"category_scores_gemma":[0.0006406472,0.00009542974,0.000105681815,0.0005853516,0.00051121064,0.00035365584,0.00019190683,0.00017558679,0.00045852698],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020186454,0.00022310385,0.12908132,0.002246055,0.00030752076,0.0033891513,0.0028655888,0.0034773604,0.641782,0.006111647,0.0040478646,0.20444976],"study_design_scores_gemma":[0.000014026688,0.0009947062,0.91667414,0.00027558647,0.0001002156,0.011892988,0.0012122348,0.0029405325,0.042101424,0.00259702,0.02113731,0.00005993822],"about_ca_topic_score_codex":0.0028996125,"about_ca_topic_score_gemma":0.0058501074,"teacher_disagreement_score":0.0028996125,"about_ca_system_score_codex":0.00033678935,"about_ca_system_score_gemma":0.00026391583,"threshold_uncertainty_score":0.0059007406},"labels":[],"label_agreement":null},{"id":"W2779764073","doi":"10.1016/j.schres.2017.11.038","title":"Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Alzheimer's Society; Consejo Nacional de Ciencia y Tecnología; Weston Brain Institute; Centre for Addiction and Mental Health Foundation; Canadian Institutes of Health Research; National Alliance for Research on Schizophrenia and Depression; Alzheimer Society; Natural Sciences and Engineering Research Council of Canada; Ontario Mental Health Foundation; Sistema Nacional de Investigadores; Michael J. Fox Foundation for Parkinson's Research","keywords":"Support vector machine; Artificial intelligence; Machine learning; Linear discriminant analysis; Pattern recognition (psychology); Computer science; Logistic regression; Cross-validation; Data set; Regression; Magnetic resonance imaging; Feature (linguistics); Mathematics; Statistics; Medicine; Radiology","score_opus":0.24079170290325963,"score_gpt":0.47929969308049564,"score_spread":0.238507990177236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779764073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854893,0.0019137538,0.0076977722,0.0008289313,0.00017090702,0.00009413185,0.003078344,0.00013703121,0.00058976666],"genre_scores_gemma":[0.9883824,0.00035584526,0.004895024,0.00027386862,0.00010618102,0.00005480554,0.0055129714,0.000059483813,0.0003593531],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99562055,0.002210112,0.0004460159,0.00090705574,0.00052578683,0.00029046953],"domain_scores_gemma":[0.98832846,0.005631736,0.0014445953,0.0025799794,0.0015661535,0.0004490422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012567067,0.001638569,0.0016374189,0.002172822,0.0009718376,0.0025855901,0.0016643172,0.0026350792,0.0010062889],"category_scores_gemma":[0.01701641,0.00063229265,0.0024481462,0.00077908655,0.0009619078,0.0028641338,0.0019026208,0.0013738883,0.0006007765],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008125822,0.0010595149,0.8847462,0.0004702363,0.008070472,0.00033104332,0.0006440646,0.0038227462,0.012386353,0.0005429338,0.007222615,0.07257799],"study_design_scores_gemma":[0.0008664215,0.0018173925,0.8907766,0.00020534049,0.004620238,0.002297521,0.0018027449,0.07918035,0.008148039,0.0042816824,0.005713847,0.00028983844],"about_ca_topic_score_codex":0.006596058,"about_ca_topic_score_gemma":0.0110388165,"teacher_disagreement_score":0.012567067,"about_ca_system_score_codex":0.0009166835,"about_ca_system_score_gemma":0.0008574978,"threshold_uncertainty_score":0.0664618},"labels":[],"label_agreement":null},{"id":"W2780737922","doi":"10.1038/s41596-021-00588-0","title":"Generic acquisition protocol for quantitative MRI of the spinal cord","year":2021,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Centre Hospitalier Universitaire de Sherbrooke; International Collaboration On Repair Discoveries; University of British Columbia; Université de Montréal; Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute","funders":"National Institute of Neurological Disorders and Stroke; Staatssekretariat für Bildung, Forschung und Innovation; Economic and Social Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; CRIS Cancer Foundation; Regione Puglia; University College London Hospitals NHS Foundation Trust; Ministero dell’Istruzione, dell’Università e della Ricerca; Ministero della Salute; Concordia University; Agentura Pro Zdravotnický Výzkum České Republiky; National Institutes of Health; Rosetrees Trust; European Commission; Multiple Sclerosis Society; Bundesministerium für Bildung und Forschung; National Imaging Facility; National Institute for Health and Care Research; University of Pennsylvania; SpinalCure Australia; University of Minnesota; National Science Foundation; Compute Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Polytechnique Montréal; Wellcome Trust; Institut de Valorisation des Données; AstraZeneca; National Center for Advancing Translational Sciences; Craig H. Neilsen Foundation; McGill University; Canada First Research Excellence Fund; Max-Planck-Gesellschaft","keywords":"Protocol (science); Magnetic resonance imaging; Computer science; Diffusion MRI; Medicine; Spinal cord; Neuroimaging; Medical physics; Nuclear medicine; Radiology; Pathology","score_opus":0.14861896995219095,"score_gpt":0.51340233755156,"score_spread":0.364783367599369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2780737922","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015615026,0.0020170186,0.82389736,0.0024009475,0.002038159,0.07890834,0.028313754,0.014595811,0.032213654],"genre_scores_gemma":[0.033093464,0.0020186985,0.7285882,0.0037998417,0.00065205316,0.17590508,0.030308524,0.005433691,0.02020036],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99551255,0.0017363542,0.0011015293,0.0006070685,0.0008603105,0.00018217959],"domain_scores_gemma":[0.9886763,0.0025933431,0.0005247432,0.003131651,0.0047837826,0.00029020698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011797966,0.0013933562,0.0012702758,0.0020069994,0.0013945983,0.0017231585,0.002115332,0.0021028486,0.072044596],"category_scores_gemma":[0.016839348,0.0012475966,0.0009904592,0.0016946122,0.0010634272,0.0014718993,0.0016905303,0.0035121976,0.030644977],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007472332,0.0014415301,0.004898076,0.0048140627,0.0002985574,0.0023314247,0.001567758,0.004777383,0.12166696,0.020833801,0.4274267,0.40247148],"study_design_scores_gemma":[0.0018920422,0.0027415752,0.018199068,0.0021911894,0.00030136644,0.0049876305,0.0003492023,0.0103009725,0.04474543,0.016031718,0.8978357,0.0004240654],"about_ca_topic_score_codex":0.0011366843,"about_ca_topic_score_gemma":0.0017524601,"teacher_disagreement_score":0.072044596,"about_ca_system_score_codex":0.0008521078,"about_ca_system_score_gemma":0.0037276805,"threshold_uncertainty_score":0.24101317},"labels":[],"label_agreement":null},{"id":"W2781188568","doi":"10.1186/s12880-017-0236-2","title":"Improving the evaluation of cardiac function in rats at 7T with denoising filters: a comparison study","year":2017,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Hôpital Fleurimont","funders":"Fonds de Recherche du Québec - Santé","keywords":"Noise reduction; Ejection fraction; Segmentation; Computer science; Ventricle; Filter (signal processing); Cardiac function curve; Pattern recognition (psychology); Medicine; Biomedical engineering; Artificial intelligence; Cardiology; Computer vision; Heart failure","score_opus":0.15102675773463192,"score_gpt":0.43331228315720466,"score_spread":0.28228552542257274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781188568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9195346,0.002754518,0.076093696,0.0001319882,0.0000359612,0.000069586,0.00009802031,0.00021076977,0.0010708673],"genre_scores_gemma":[0.8779719,0.0039608553,0.11542034,0.00014462073,0.000070976,0.00011756619,0.00033632736,0.00016262426,0.0018148044],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997981,0.000053360804,0.000012519334,0.00004937012,0.00005806674,0.00002857037],"domain_scores_gemma":[0.9994055,0.00017026222,0.00012069785,0.00006506145,0.00019403562,0.00004436746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012295786,0.00056571903,0.00039207132,0.00049369206,0.00015618432,0.00026025093,0.00025169333,0.0006252642,0.0006221309],"category_scores_gemma":[0.000951663,0.00016786516,0.00035675784,0.00020793504,0.00033896393,0.00029562716,0.00021779409,0.00029661416,0.000223696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046437245,0.000098722296,0.0018287749,0.00012341478,0.00005859828,0.00007123746,0.000070014336,0.00081286475,0.9727801,0.00007637316,0.00006823773,0.023547402],"study_design_scores_gemma":[0.00003761796,0.0051411577,0.03748298,0.000041324267,0.00048600425,0.0013564387,0.000093515126,0.014403389,0.93826467,0.00021216348,0.0024266273,0.000054212236],"about_ca_topic_score_codex":0.00071400387,"about_ca_topic_score_gemma":0.0013082493,"teacher_disagreement_score":0.0012295786,"about_ca_system_score_codex":0.00020045755,"about_ca_system_score_gemma":0.00021152182,"threshold_uncertainty_score":0.0065027475},"labels":[],"label_agreement":null},{"id":"W2781983970","doi":"10.1016/j.eplepsyres.2018.01.008","title":"Longitudinal hippocampal and extra-hippocampal microstructural and macrostructural changes following temporal lobe epilepsy surgery","year":2018,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; University of Alberta","keywords":"Fornix; Mammillary body; Temporal lobe; Fractional anisotropy; Diffusion MRI; Epilepsy surgery; Hippocampus; Hippocampal formation; Epilepsy; Hippocampal sclerosis; Medicine; Psychology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.16147041313139757,"score_gpt":0.4221222310652415,"score_spread":0.26065181793384395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781983970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99910176,0.00017731087,0.000094459705,0.000038471695,0.000007981954,0.000005653433,0.00010743449,0.000004257537,0.00046267192],"genre_scores_gemma":[0.9989361,0.0001551026,0.000042580108,0.000018625231,0.000008851537,0.000007662917,0.0002018645,0.000002607758,0.0006266094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989855,0.00001103182,0.0000086488235,0.000017625369,0.000021486732,0.000042638043],"domain_scores_gemma":[0.9993747,0.00007948863,0.00026430088,0.000049358863,0.00010237972,0.00012977964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025816855,0.00014121449,0.00026596492,0.0005616808,0.00025551266,0.0003024499,0.00021638782,0.00029434136,0.0019581367],"category_scores_gemma":[0.000980656,0.00014310026,0.00024859532,0.00051862694,0.000435853,0.00062490493,0.00034819223,0.00048260557,0.00038160192],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.015259293,0.0010223107,0.7883305,0.00014383401,0.0003921121,0.0093278345,0.0012010547,0.0010879477,0.12859054,0.00025554866,0.00079331285,0.05359583],"study_design_scores_gemma":[0.000013153241,0.0006602729,0.9946753,0.0000070509986,0.00003966556,0.0011798447,0.0002812764,0.0001849821,0.0025467325,0.0001217693,0.00027735493,0.000012695005],"about_ca_topic_score_codex":0.0044303695,"about_ca_topic_score_gemma":0.009859413,"teacher_disagreement_score":0.0044303695,"about_ca_system_score_codex":0.00030251822,"about_ca_system_score_gemma":0.00046920724,"threshold_uncertainty_score":0.008809209},"labels":[],"label_agreement":null},{"id":"W2782258118","doi":"10.1007/s11548-017-1699-x","title":"Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection","year":2018,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Tractography; Diffusion MRI; Medicine; Brain tumor; Craniotomy; Radiology; Neuronavigation; Surgical planning; Intraoperative MRI; Magnetic resonance imaging; Pathology; Interventional magnetic resonance imaging","score_opus":0.051637209771576036,"score_gpt":0.35072452097686196,"score_spread":0.2990873112052859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782258118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93699384,0.00076594204,0.059967317,0.00032413474,0.000029269217,0.00003115662,0.00013761531,0.00015389183,0.0015968308],"genre_scores_gemma":[0.9942094,0.000264896,0.0047073183,0.000017451868,0.000010786169,0.00000994624,0.000054010416,0.000038675484,0.00068735564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987817,0.000053776857,0.000008274236,0.000015513042,0.00002968464,0.0000146307775],"domain_scores_gemma":[0.9994868,0.00031544518,0.000074630836,0.000036536883,0.000053149502,0.000033433844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003039797,0.00020502624,0.00014776221,0.00035355688,0.00015598578,0.000602892,0.00019400753,0.00049345655,0.0006753072],"category_scores_gemma":[0.0028581833,0.00018163999,0.00019737029,0.00037628837,0.0003316392,0.00047329385,0.00029045728,0.00027432153,0.00018052287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031955333,0.00021185387,0.058427203,0.00044366962,0.00016199387,0.0030557984,0.0012987881,0.3637066,0.33158192,0.004093266,0.0016757072,0.2321477],"study_design_scores_gemma":[0.000026332724,0.0002766092,0.09080315,0.00004343085,0.00006792656,0.0021337199,0.00025684352,0.8635783,0.039135225,0.0023149801,0.001309107,0.00005436555],"about_ca_topic_score_codex":0.0048839315,"about_ca_topic_score_gemma":0.0053821984,"teacher_disagreement_score":0.0048839315,"about_ca_system_score_codex":0.00035172887,"about_ca_system_score_gemma":0.00047406892,"threshold_uncertainty_score":0.009711027},"labels":[],"label_agreement":null},{"id":"W2782477562","doi":"10.1016/j.neuroimage.2017.12.097","title":"The development of brain white matter microstructure","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":637,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; National Institute of Mental Health; Alberta Children's Hospital Research Institute; National Institutes of Health; Bill and Melinda Gates Foundation","keywords":"White matter; Microstructure; Brain development; Neuroscience; Psychology; Medicine; Materials science; Metallurgy; Magnetic resonance imaging; Radiology","score_opus":0.08773591416304627,"score_gpt":0.39908749152442524,"score_spread":0.311351577361379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782477562","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026140863,0.99762076,0.00040765054,0.0006052658,0.00018634487,0.0000041458134,0.000029928216,0.000007927443,0.00087660976],"genre_scores_gemma":[0.0019327822,0.9963877,0.0005688588,0.00023994822,0.00039071622,0.0000059662902,0.000038877202,0.000002759404,0.00043244465],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997669,0.000035806795,0.000036583075,0.00005792831,0.00008037305,0.000022492894],"domain_scores_gemma":[0.99921155,0.00037239012,0.000116067065,0.000030617077,0.00022444721,0.00004495525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010195854,0.0008945926,0.0010602969,0.0027695233,0.00025612803,0.0016111493,0.0009069817,0.0014658029,0.0023783613],"category_scores_gemma":[0.0019998394,0.0003073897,0.00051108125,0.002251317,0.0010688977,0.0017756317,0.0010870058,0.0014663592,0.0010051797],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000514577,0.00003358279,0.00077829225,0.009943978,0.00010470435,0.00024918714,0.00006653954,0.000309549,0.00196582,0.0064051785,0.011481459,0.9686102],"study_design_scores_gemma":[0.000016897353,0.00012324867,0.006390534,0.0071881954,0.00032788236,0.003996694,0.00017252548,0.00035220414,0.0024080414,0.013726503,0.9652365,0.000060794195],"about_ca_topic_score_codex":0.0024759301,"about_ca_topic_score_gemma":0.0032106221,"teacher_disagreement_score":0.0027695233,"about_ca_system_score_codex":0.0008070936,"about_ca_system_score_gemma":0.0022588463,"threshold_uncertainty_score":0.007956445},"labels":[],"label_agreement":null},{"id":"W2782642508","doi":"10.1159/000480766","title":"Diffusion Tensor Imaging of the Basal Ganglia for Functional Neurosurgery Applications","year":2018,"lang":"en","type":"review","venue":"Progress in neurological surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Medicine; Tractography; Neuroscience; Deep brain stimulation; Neurosurgery; White matter; Basal ganglia; Medical physics; Radiology; Magnetic resonance imaging; Pathology; Psychology; Central nervous system; Internal medicine","score_opus":0.1638321474368537,"score_gpt":0.3919044344635699,"score_spread":0.22807228702671617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782642508","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014974743,0.9969797,0.00058606215,0.0004769,0.00027162553,0.000007772348,0.00003274079,0.000014084672,0.001481461],"genre_scores_gemma":[0.0011101507,0.99701464,0.00076201296,0.00016121371,0.00031516858,0.000008622111,0.000044196284,0.000005161934,0.0005788085],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997185,0.000049882266,0.00005611956,0.0000483647,0.000105198094,0.000021867352],"domain_scores_gemma":[0.99915314,0.00045225653,0.00011623352,0.00002689199,0.00020828405,0.00004309352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009602637,0.0011248565,0.0012240363,0.0045368294,0.00033634686,0.0014247348,0.00075106364,0.0013250307,0.004953626],"category_scores_gemma":[0.0016809097,0.00033826908,0.0007707921,0.0029845708,0.0008383959,0.0018476661,0.0008693823,0.0019511414,0.0030850822],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004354914,0.00004506345,0.00044439314,0.016429493,0.00012353034,0.00031876258,0.00010604915,0.00043570597,0.0021556702,0.00771907,0.025753787,0.946425],"study_design_scores_gemma":[0.000011260555,0.00007964877,0.0018514438,0.0071665,0.00015093408,0.0045286417,0.00011694021,0.00030674075,0.0014161249,0.0064905477,0.97783285,0.0000484355],"about_ca_topic_score_codex":0.0019462466,"about_ca_topic_score_gemma":0.0032402065,"teacher_disagreement_score":0.004953626,"about_ca_system_score_codex":0.000694278,"about_ca_system_score_gemma":0.0019246415,"threshold_uncertainty_score":0.016571522},"labels":[],"label_agreement":null},{"id":"W2783800543","doi":"10.1002/nbm.3868","title":"Can <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratio be used as a myelin‐specific measure in subcortical structures? Comparisons between FSE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios, GRASE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios and multi‐echo GRASE‐based myelin water fractions","year":2018,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Manitoba Health; Health Sciences Centre","funders":"Canadian Institutes of Health Research","keywords":"White matter; Nuclear medicine; Nuclear magnetic resonance; Linear regression; Magnetic resonance imaging; Physics; Mathematics; Medicine; Statistics; Radiology","score_opus":0.06212933630555088,"score_gpt":0.32809298493096456,"score_spread":0.26596364862541366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783800543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9721624,0.0034187573,0.021280318,0.0004205819,0.000096661905,0.00006129976,0.0002498726,0.00023969817,0.0020704246],"genre_scores_gemma":[0.9841458,0.0012656503,0.013540717,0.00018378862,0.000052473253,0.000055505894,0.00022489043,0.00012481207,0.00040625347],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992005,0.00024340164,0.00010733961,0.00027571735,0.000112313544,0.000060760176],"domain_scores_gemma":[0.99703753,0.0011666307,0.0007825146,0.00041806526,0.00048568667,0.00010953906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004625064,0.00096809084,0.00076959725,0.0014431903,0.00040357673,0.0019470461,0.0006769242,0.0016867057,0.00069906935],"category_scores_gemma":[0.014783144,0.0005115014,0.00042585476,0.0006944282,0.0010311676,0.0022496693,0.00055639056,0.0004075395,0.0005418006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026323544,0.00035732327,0.33677465,0.001892207,0.0019607234,0.0010515916,0.0022620363,0.0029430855,0.4671613,0.00086232345,0.0011784749,0.18092397],"study_design_scores_gemma":[0.00012346846,0.0020489837,0.8442188,0.0002731275,0.0012461676,0.0032872513,0.0025750836,0.011697533,0.12572923,0.004244852,0.004350708,0.000204825],"about_ca_topic_score_codex":0.0014351446,"about_ca_topic_score_gemma":0.0051580546,"teacher_disagreement_score":0.004625064,"about_ca_system_score_codex":0.00015533909,"about_ca_system_score_gemma":0.0002933927,"threshold_uncertainty_score":0.024459958},"labels":[],"label_agreement":null},{"id":"W2784595116","doi":"10.1177/1759091417753802","title":"Stuck in a State of Inattention? Functional Hyperconnectivity as an Indicator of Disturbed Intrinsic Brain Dynamics in Adolescents with Concussion: A Pilot Study","year":2018,"lang":"en","type":"article","venue":"ASN NEURO","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Concussion; Functional magnetic resonance imaging; Resting state fMRI; Psychology; Diffusion MRI; Neuroscience; Brain activity and meditation; Poison control; Brain Structure and Function; Physical medicine and rehabilitation; Neuroimaging; Medicine; Magnetic resonance imaging; Electroencephalography; Injury prevention","score_opus":0.03877808274899654,"score_gpt":0.334348101531653,"score_spread":0.2955700187826565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784595116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99975294,0.00003916664,0.0000894493,0.000007908367,0.0000016717131,0.000018677973,0.000031582193,0.0000010050151,0.000057541918],"genre_scores_gemma":[0.9992648,0.00009010933,0.00038210116,0.000015004623,0.000008650731,0.000046063742,0.00010543271,0.0000018391227,0.000085937674],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981946,0.000053215943,0.000019365605,0.00003992583,0.000029258203,0.0000389263],"domain_scores_gemma":[0.9994012,0.00009308,0.0001623019,0.00004087827,0.00015578738,0.00014678312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046576015,0.00026443822,0.00036344814,0.00053912704,0.0003396293,0.00037397366,0.0002025392,0.00033392917,0.0006972765],"category_scores_gemma":[0.0011556443,0.00013584942,0.00024693087,0.00025009757,0.00032554567,0.00027682615,0.00036228207,0.00038067266,0.000120861965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005075375,0.0007063399,0.980011,0.000082912826,0.000053420652,0.0013868143,0.002149649,0.00007309157,0.006886603,0.000069137066,0.00015446063,0.007919139],"study_design_scores_gemma":[0.00002045054,0.001433727,0.99385756,0.000018934357,0.000049427315,0.0012924614,0.0021288155,0.00026330215,0.0005775672,0.000036977643,0.00031558707,0.0000051364495],"about_ca_topic_score_codex":0.0021827165,"about_ca_topic_score_gemma":0.003318833,"teacher_disagreement_score":0.0021827165,"about_ca_system_score_codex":0.00017452687,"about_ca_system_score_gemma":0.0002869022,"threshold_uncertainty_score":0.0043400526},"labels":[],"label_agreement":null},{"id":"W2785040294","doi":"","title":"Relevance of exosomes with structural changes of white matter and cognitive impairment in patients with PD","year":2017,"lang":"en","type":"article","venue":"Biomedical Research-tokyo","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; White matter; Fractional anisotropy; Diffusion MRI; Internal medicine; Montreal Cognitive Assessment; Medicine; Parkinson's disease; Exacerbation; Rating scale; Atrophy; Cognition; Psychology; Cardiology; Dementia; Gastroenterology; Pathology; Magnetic resonance imaging; Disease; Psychiatry; Radiology; Developmental psychology","score_opus":0.06808585921757733,"score_gpt":0.4094118734857848,"score_spread":0.34132601426820747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785040294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981281,0.0012357248,0.00005760223,0.000055470904,0.000009196505,0.0000071346412,0.0001153108,0.0000031178724,0.00038840054],"genre_scores_gemma":[0.99930704,0.000280462,0.00007694279,0.000022730392,0.000025311341,0.0000046963837,0.00013211383,9.898284e-7,0.00014969446],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980813,0.000036481983,0.0000331562,0.000049733404,0.00003955115,0.000032936605],"domain_scores_gemma":[0.9992993,0.00009762686,0.0003971093,0.000023860575,0.000092071336,0.00009001212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031775044,0.0003331517,0.00039453144,0.00081066653,0.0005622976,0.00059122156,0.00018372764,0.0004959378,0.0012382064],"category_scores_gemma":[0.0015318607,0.0001739036,0.0003344249,0.000629425,0.00023634122,0.000499782,0.00052145234,0.0003719316,0.00016272477],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006642339,0.000069239446,0.99393433,0.000043260567,0.00008475066,0.0010224934,0.00010758578,0.00004189896,0.00092845585,0.000019619712,0.00010930804,0.0029748252],"study_design_scores_gemma":[0.000013400304,0.00023047783,0.9963492,0.00001377377,0.00005978713,0.0023815471,0.00021537502,0.00015685402,0.00020171884,0.000054989574,0.00031688614,0.0000058731944],"about_ca_topic_score_codex":0.0008264813,"about_ca_topic_score_gemma":0.00086714857,"teacher_disagreement_score":0.0012382064,"about_ca_system_score_codex":0.00019247142,"about_ca_system_score_gemma":0.00018675513,"threshold_uncertainty_score":0.004142165},"labels":[],"label_agreement":null},{"id":"W2787874265","doi":"10.1007/s11548-018-1706-x","title":"Correction to: Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection","year":2018,"lang":"en","type":"erratum","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Acknowledgement; Tractography; Computer science; Medical physics; Medicine; Diffusion MRI; Radiology; Computer security; Magnetic resonance imaging","score_opus":0.041925504605143826,"score_gpt":0.3450086749760189,"score_spread":0.30308317037087507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787874265","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030706394,0.0042452146,0.012198917,0.07553676,0.8964868,0.00010144854,0.0010429765,0.0021630768,0.0051541445],"genre_scores_gemma":[0.117105685,0.016101265,0.07396058,0.07064383,0.40814948,0.0004613045,0.0023273225,0.00418408,0.3070666],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984565,0.00018817822,0.0003800826,0.00021398597,0.0006389002,0.00012235688],"domain_scores_gemma":[0.9898358,0.0034602785,0.0007639711,0.00079203275,0.004711479,0.00043644407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014739732,0.0016185496,0.0010858891,0.002418026,0.0012835095,0.002015045,0.0020992295,0.0075429566,0.031881925],"category_scores_gemma":[0.027067237,0.00075706816,0.0008440567,0.0014423605,0.0017069718,0.0015016054,0.0011510733,0.005408752,0.013158873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021537651,0.00001758203,0.000605947,0.00050893414,0.00002997243,0.0048714057,0.00009681015,0.00052894646,0.0008726868,0.0018981884,0.9294352,0.060918923],"study_design_scores_gemma":[0.00017442594,0.000101627236,0.00372281,0.0006311614,0.00010673544,0.022287453,0.00024180644,0.0068335477,0.006729262,0.0057961917,0.95320857,0.00016650287],"about_ca_topic_score_codex":0.0062263976,"about_ca_topic_score_gemma":0.009944782,"teacher_disagreement_score":0.031881925,"about_ca_system_score_codex":0.0017344028,"about_ca_system_score_gemma":0.0019484774,"threshold_uncertainty_score":0.10665566},"labels":[],"label_agreement":null},{"id":"W2788141036","doi":"10.1016/j.nicl.2018.01.033","title":"Telomere length and advanced diffusion MRI as biomarkers for repetitive mild traumatic brain injury in adolescent rats","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"National Health and Medical Research Council; Medical Research Council; Alberta Children's Hospital Foundation; National Imaging Facility; Children's Hospital Foundation","keywords":"Traumatic brain injury; Medicine; Diffusion MRI; Corpus callosum; Pathology; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.14806788697070153,"score_gpt":0.4690715258704526,"score_spread":0.32100363889975103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788141036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99191743,0.0016073904,0.004277413,0.00019199774,0.00007171996,0.00007322496,0.0010304108,0.00015030746,0.0006800643],"genre_scores_gemma":[0.97695655,0.0033751812,0.008909756,0.00019426818,0.0000312226,0.00060755695,0.0013927671,0.00007737372,0.008455434],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996935,0.000029445608,0.000030567822,0.000099957884,0.00007982512,0.000066634464],"domain_scores_gemma":[0.9994265,0.000027813585,0.00026258902,0.00005023859,0.00008538533,0.00014745678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004052503,0.0007155573,0.0004374322,0.0015595024,0.00033810415,0.00033851166,0.00039309188,0.00057997805,0.0016975843],"category_scores_gemma":[0.0002617944,0.0003644356,0.0005371783,0.00040660833,0.00058608013,0.00048100032,0.00036756886,0.0017234448,0.0003700649],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016863509,0.0007881278,0.0047117015,0.00012089639,0.00004121759,0.00021269478,0.00025172715,0.00016556852,0.9849021,0.00021653868,0.00016622669,0.0067369053],"study_design_scores_gemma":[0.00022792764,0.014531176,0.08260344,0.00008845889,0.00028382233,0.0007498997,0.0010003732,0.0026395426,0.8920781,0.0005164431,0.005170633,0.00011024688],"about_ca_topic_score_codex":0.0023207346,"about_ca_topic_score_gemma":0.004052923,"teacher_disagreement_score":0.0023207346,"about_ca_system_score_codex":0.0004646965,"about_ca_system_score_gemma":0.0005152296,"threshold_uncertainty_score":0.0056789517},"labels":[],"label_agreement":null},{"id":"W2788415044","doi":"10.1101/251108","title":"A population-based atlas of the human pyramidal tract in 410 healthy participants","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Pyramidal tracts; Atlas (anatomy); Diffusion MRI; Fiber tract; Corticospinal tract; Brain atlas","score_opus":0.07034661507362043,"score_gpt":0.3413616496605835,"score_spread":0.2710150345869631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788415044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93102926,0.00021940627,0.043932002,0.00011502958,0.000019111922,0.00015048843,0.019931136,0.000685966,0.00391763],"genre_scores_gemma":[0.9569337,0.00017655641,0.02417706,0.00004170438,0.000014394201,0.00028060333,0.0146868685,0.00012439069,0.0035647776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998672,0.000024387582,0.000011041052,0.000070492344,0.000015256615,0.0000116159335],"domain_scores_gemma":[0.9997141,0.00006437935,0.000032056854,0.000090944806,0.00007534019,0.000023237293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038790354,0.00022204364,0.00023560619,0.0007992877,0.00034249452,0.0003535198,0.00030877255,0.00035592893,0.006579342],"category_scores_gemma":[0.0012144395,0.00015881177,0.00019455604,0.00077699457,0.00031131934,0.00021741295,0.0004446719,0.0001727026,0.0014195688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020979517,0.00035692976,0.48224193,0.0007454495,0.00047179637,0.0055024107,0.008484823,0.018685818,0.07853732,0.0077468483,0.049348056,0.34578073],"study_design_scores_gemma":[0.000100555255,0.00046799015,0.91956,0.00006644991,0.00016351145,0.010083351,0.0014239522,0.017770668,0.0062438985,0.009586969,0.034429844,0.00010283036],"about_ca_topic_score_codex":0.0065260627,"about_ca_topic_score_gemma":0.01058227,"teacher_disagreement_score":0.006579342,"about_ca_system_score_codex":0.00023109606,"about_ca_system_score_gemma":0.00048228487,"threshold_uncertainty_score":0.022010088},"labels":[],"label_agreement":null},{"id":"W2789296617","doi":"10.1101/282434","title":"Axons morphometry in the human spinal cord","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Axon; Spinal cord; Anatomy; Myelin; Neuroscience; Magnetic resonance imaging; Biology; Central nervous system; Medicine; Radiology","score_opus":0.071882110216865,"score_gpt":0.3414459069492006,"score_spread":0.26956379673233555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789296617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8828614,0.0017676128,0.1077874,0.0002492126,0.00004108537,0.00009013702,0.0030021116,0.0019328883,0.0022682599],"genre_scores_gemma":[0.9229213,0.00070794474,0.072435595,0.00006759425,0.000014015374,0.00005274125,0.0015019263,0.00016503024,0.002134007],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998573,0.000016179081,0.000009532048,0.000057561538,0.000046277233,0.0000132075],"domain_scores_gemma":[0.99983406,0.000033829732,0.00003578056,0.000026759171,0.00005701931,0.000012611048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026443644,0.0002451319,0.00014483117,0.00085846375,0.00020336162,0.00043742845,0.00016506026,0.00035283228,0.0014460497],"category_scores_gemma":[0.00060005893,0.00014631668,0.00017277144,0.00045488184,0.0002619372,0.0002570942,0.00027094944,0.00016460806,0.0005045723],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065231964,0.000097562865,0.032763317,0.0005167379,0.00016448958,0.00086146814,0.00055779045,0.023505429,0.65717864,0.0014984712,0.003910836,0.27829292],"study_design_scores_gemma":[0.00003898886,0.0007508576,0.45531076,0.000253468,0.00020847988,0.008490734,0.000598824,0.17296739,0.34312028,0.0048200865,0.013320596,0.00011950632],"about_ca_topic_score_codex":0.004488941,"about_ca_topic_score_gemma":0.007454661,"teacher_disagreement_score":0.004488941,"about_ca_system_score_codex":0.00028148553,"about_ca_system_score_gemma":0.00052987883,"threshold_uncertainty_score":0.008925617},"labels":[],"label_agreement":null},{"id":"W2789780381","doi":"10.1002/dev.21610","title":"Auditory structural connectivity in preterm and healthy term infants during the first postnatal year","year":2018,"lang":"en","type":"article","venue":"Developmental Psychobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children’s Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Canada Excellence Research Chairs, Government of Canada; Health Research Board; Natural Sciences and Engineering Research Council of Canada; Children's Health Research Institute","keywords":"Magnetic resonance imaging; Gestational age; White matter; Fractional anisotropy; Diffusion MRI; Brainstem; Tractography; Psychology; Audiology; Language development; Auditory pathways; Medicine; Pediatrics; Developmental psychology; Neuroscience; Pregnancy; Biology; Radiology","score_opus":0.029052862095500377,"score_gpt":0.34578539565578503,"score_spread":0.31673253356028463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789780381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997702,0.000054184256,0.000026959973,0.000004107117,4.783294e-7,0.0000017937055,0.000052722728,0.000001863411,0.00008755664],"genre_scores_gemma":[0.99956614,0.00008350571,0.00009310744,0.0000044651606,0.0000019103838,0.000011046321,0.00010496221,0.000002565109,0.00013231378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998635,0.000020458216,0.000011219226,0.000043313637,0.000024884102,0.000036645593],"domain_scores_gemma":[0.9994517,0.000166827,0.00018142589,0.000038037055,0.00006531762,0.0000966852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002469238,0.00019609064,0.00027634174,0.00090439164,0.00022429593,0.0002680401,0.00024814208,0.00032947923,0.0008135666],"category_scores_gemma":[0.0016903204,0.00018584616,0.00012781036,0.00031000937,0.0003501365,0.000247276,0.00039274932,0.00020019738,0.00012941728],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00264042,0.00018886641,0.9280065,0.00007516671,0.000070695205,0.0071445405,0.0028187695,0.0003646329,0.039625637,0.00017508397,0.00019298014,0.018696764],"study_design_scores_gemma":[0.0000032454664,0.0001631786,0.9977717,0.0000029417927,0.000010147553,0.0012029466,0.00021137009,0.00011992205,0.0004255973,0.000032277716,0.000053338597,0.0000033642175],"about_ca_topic_score_codex":0.0053590215,"about_ca_topic_score_gemma":0.0049944418,"teacher_disagreement_score":0.0053590215,"about_ca_system_score_codex":0.00034228136,"about_ca_system_score_gemma":0.00017096355,"threshold_uncertainty_score":0.010655642},"labels":[],"label_agreement":null},{"id":"W2789795746","doi":"10.3389/fmed.2018.00031","title":"Quantitative Ex Vivo MRI Changes due to Progressive Formalin Fixation in Whole Human Brain Specimens: Longitudinal Characterization of Diffusion, Relaxometry, and Myelin Water Fraction Measurements at 3T","year":2018,"lang":"en","type":"article","venue":"Frontiers in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"Siemens Healthineers; University of Memphis; University of Manitoba; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Health Sciences Centre Foundation","keywords":"Relaxometry; Myelin; Ex vivo; Nuclear magnetic resonance; Diffusion MRI; Fixation (population genetics); Characterization (materials science); Pathology; Magnetic resonance imaging; In vivo; Chemistry; Medicine; Materials science; Biology; Central nervous system; Radiology; Internal medicine; Spin echo; Biochemistry","score_opus":0.07882573708557716,"score_gpt":0.3678608864943389,"score_spread":0.28903514940876174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789795746","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772555,0.004099531,0.01698488,0.000118263575,0.00004865173,0.00006847503,0.0003497187,0.00009526155,0.0009797727],"genre_scores_gemma":[0.98098993,0.0023208426,0.014113756,0.00011492275,0.000027626555,0.00015105071,0.0005928401,0.00006738959,0.0016215],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979836,0.000042936364,0.000020960786,0.000053072148,0.000055429988,0.000029272629],"domain_scores_gemma":[0.99944717,0.00009607802,0.00020317695,0.00008428155,0.00013717505,0.000032246407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008074316,0.0006620015,0.00027464028,0.0004302514,0.0002518777,0.00034893127,0.00031545525,0.0004538776,0.0013781913],"category_scores_gemma":[0.0010418796,0.0002944755,0.0002659654,0.00030334684,0.00053049665,0.0004641648,0.00025258522,0.0004151121,0.0003992304],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036634138,0.000023281176,0.0015624039,0.00007730964,0.00002151404,0.00014218998,0.00006856241,0.00011017274,0.9952207,0.000029388433,0.000034046407,0.0023441722],"study_design_scores_gemma":[0.000032689317,0.0023144996,0.103392966,0.000049615046,0.00018780607,0.0025607306,0.00030338878,0.0018112449,0.88752925,0.0001641392,0.0016186769,0.000034985333],"about_ca_topic_score_codex":0.0012296495,"about_ca_topic_score_gemma":0.0018972016,"teacher_disagreement_score":0.0013781913,"about_ca_system_score_codex":0.00027775226,"about_ca_system_score_gemma":0.0002611044,"threshold_uncertainty_score":0.004610479},"labels":[],"label_agreement":null},{"id":"W2790018820","doi":"10.1101/256933","title":"Relationships between Human Brain Structural Connectomes and Traits","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Connectome; Human Connectome Project; Human brain; Computer science; Artificial intelligence; Neuroscience; Psychology; Resting state fMRI; Pattern recognition (psychology); Cognitive psychology; Functional connectivity","score_opus":0.07574890596280866,"score_gpt":0.3235845401569406,"score_spread":0.24783563419413196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790018820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99529076,0.00018827122,0.0025164408,0.00012495532,0.000005428158,0.0000051759407,0.001442814,0.000043285825,0.00038281863],"genre_scores_gemma":[0.9973285,0.000077446115,0.0014258561,0.000018961186,0.000008940816,0.000009856183,0.0009644573,0.000014896607,0.00015107483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99966,0.00010067549,0.000022010601,0.00013675005,0.000049559763,0.000030976167],"domain_scores_gemma":[0.99701023,0.0012293503,0.0008891747,0.0005245875,0.00021412276,0.00013254749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074477564,0.00023854512,0.00027023893,0.0011350223,0.00023316499,0.00056829094,0.00017768821,0.00031718082,0.00213351],"category_scores_gemma":[0.005514648,0.00020418465,0.00022748196,0.00084293424,0.00044249656,0.0003557719,0.00044680169,0.000425722,0.00023175312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004620679,0.000069120215,0.94665724,0.0000820912,0.0011697165,0.0002602732,0.00032398212,0.00395736,0.024368567,0.0012570427,0.0016738597,0.019718606],"study_design_scores_gemma":[0.0000053385397,0.000025392914,0.9943673,0.000006116051,0.000035252044,0.00031908572,0.00005064742,0.002595836,0.0010232202,0.00130915,0.0002536565,0.000009019701],"about_ca_topic_score_codex":0.0017117237,"about_ca_topic_score_gemma":0.00261892,"teacher_disagreement_score":0.00213351,"about_ca_system_score_codex":0.00017069366,"about_ca_system_score_gemma":0.00011043233,"threshold_uncertainty_score":0.007137358},"labels":[],"label_agreement":null},{"id":"W2790175756","doi":"10.1111/ejn.13841","title":"White matter microstructural organisation of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults","year":2018,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek","keywords":"White matter; Motor learning; Psychology; Premotor cortex; Fractional anisotropy; Primary motor cortex; Neuroscience; Tractography; Motor cortex; Diffusion MRI; Dorsum; Cortex (anatomy); Young adult; Physical medicine and rehabilitation; Developmental psychology; Medicine; Magnetic resonance imaging; Anatomy","score_opus":0.020959953705917047,"score_gpt":0.276564203888547,"score_spread":0.25560425018263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790175756","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994573,0.00008243874,0.000089745015,0.000015269221,0.000002075718,0.00000408165,0.00014539796,0.000004112843,0.0001995481],"genre_scores_gemma":[0.99898046,0.00004971778,0.00016784457,0.000014573253,0.0000042318347,0.000008261197,0.00028555872,0.0000024002645,0.00048697903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999155,0.000005728124,0.000013751701,0.000035878154,0.000012123271,0.0000170336],"domain_scores_gemma":[0.9995704,0.00005077265,0.00018474423,0.000045002413,0.000059064532,0.000089970286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003719137,0.00034997304,0.00027073637,0.00053781027,0.00022357471,0.00043111338,0.00018893881,0.00053114805,0.0017132994],"category_scores_gemma":[0.0011100644,0.0002174366,0.0002732737,0.00018003091,0.00020914157,0.00046917144,0.00037890457,0.000305753,0.00035535847],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007349894,0.000117309864,0.97670835,0.000029946683,0.00011070636,0.00027628182,0.0008256847,0.0004381792,0.011238643,0.000117847434,0.00030731596,0.009094718],"study_design_scores_gemma":[0.0000028310633,0.00006794111,0.9992453,0.0000033728797,0.000010484634,0.000090825735,0.000070482834,0.00023152368,0.00016805374,0.000051129446,0.00005588278,0.0000021106318],"about_ca_topic_score_codex":0.007079988,"about_ca_topic_score_gemma":0.010858594,"teacher_disagreement_score":0.007079988,"about_ca_system_score_codex":0.00020126614,"about_ca_system_score_gemma":0.00014124587,"threshold_uncertainty_score":0.014077544},"labels":[],"label_agreement":null},{"id":"W2790520416","doi":"10.1007/s10334-018-0680-1","title":"Toward faster inference of micron-scale axon diameters using Monte Carlo simulations","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Monte Carlo method; Scale (ratio); Cylinder; Axon; Materials science; Diffusion; Physics; Geometry; Mathematics; Statistics; Anatomy","score_opus":0.08719405476780663,"score_gpt":0.38342536726532556,"score_spread":0.29623131249751894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790520416","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028220596,0.00026548354,0.9661708,0.00034598148,0.00009007469,0.000052957686,0.00016603872,0.0026318212,0.0020561626],"genre_scores_gemma":[0.3670833,0.00022833077,0.6281775,0.00038874615,0.00011056887,0.00022555553,0.00040046975,0.0009175534,0.0024678817],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993536,0.00019789576,0.00003918648,0.00014493075,0.0002067145,0.000057726713],"domain_scores_gemma":[0.98210377,0.014415572,0.00058478134,0.0012188714,0.0012104257,0.0004665501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024032302,0.0010185388,0.0020467804,0.0016310713,0.0010775719,0.0016686877,0.0037315162,0.0028500368,0.0058151362],"category_scores_gemma":[0.016988432,0.0019345004,0.0013561113,0.0011033078,0.001381316,0.0028580856,0.0021047255,0.0030941188,0.0013323812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011359031,0.000049678147,0.0011593947,0.00008289634,0.000088819776,0.00007833476,0.00007152889,0.9587613,0.0016974792,0.0150303,0.0011386487,0.021728126],"study_design_scores_gemma":[0.000005612207,0.0000025295042,0.0000447313,0.0000037510606,0.0000029308976,0.0000072114003,0.0000032383039,0.99471563,0.00022015459,0.0048898174,0.0001012057,0.0000030683952],"about_ca_topic_score_codex":0.01915203,"about_ca_topic_score_gemma":0.02488286,"teacher_disagreement_score":0.01915203,"about_ca_system_score_codex":0.0017146008,"about_ca_system_score_gemma":0.0025682554,"threshold_uncertainty_score":0.03808111},"labels":[],"label_agreement":null},{"id":"W2790987263","doi":"10.3389/fnana.2018.00021","title":"Alterations of White Matter Integrity and Hippocampal Functional Connectivity in Type 2 Diabetes Without Mild Cognitive Impairment","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Corpus callosum; White matter; Splenium; Hippocampal formation; Diffusion MRI; Psychology; Montreal Cognitive Assessment; Neuroscience; Audiology; Resting state fMRI; Medicine; Cognition; Magnetic resonance imaging; Internal medicine; Cognitive impairment; Radiology","score_opus":0.030012893694276697,"score_gpt":0.3125346215064711,"score_spread":0.2825217278121944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790987263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99942625,0.00019856804,0.000057191635,0.000013286354,0.0000029529976,0.000006117761,0.00008979154,0.0000025937604,0.00020324848],"genre_scores_gemma":[0.99932206,0.00012260422,0.00014191745,0.000027540542,0.000010641758,0.0000090036965,0.00018866692,0.0000013038635,0.00017636445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999089,0.000013295357,0.00001545575,0.000031789474,0.000015097227,0.000015349093],"domain_scores_gemma":[0.9997702,0.00002636213,0.00011424975,0.000013283781,0.000021531907,0.000054290966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021146999,0.00042213788,0.0002941161,0.00047968506,0.00033122557,0.00036231606,0.00019074877,0.0003491434,0.0011319963],"category_scores_gemma":[0.0005120524,0.0001535217,0.0001957331,0.0003961403,0.00017228861,0.00020427734,0.00016669983,0.00023551502,0.00012512949],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015038013,0.00026965863,0.98488486,0.00006217659,0.00017642128,0.0011485522,0.00017773276,0.00009735143,0.0058393516,0.000020539515,0.00011146027,0.005708151],"study_design_scores_gemma":[0.000023375223,0.00023749456,0.9983399,0.000004036006,0.000040226547,0.0008489149,0.000071993476,0.000105866064,0.0002376339,0.000019589492,0.00006801868,0.000002835904],"about_ca_topic_score_codex":0.0027036178,"about_ca_topic_score_gemma":0.0040543242,"teacher_disagreement_score":0.0027036178,"about_ca_system_score_codex":0.00015323226,"about_ca_system_score_gemma":0.000121748475,"threshold_uncertainty_score":0.005375743},"labels":[],"label_agreement":null},{"id":"W2791053909","doi":"10.1016/j.jneumeth.2018.03.001","title":"Extraction of corticospinal tract microstructural properties in chronic stroke","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Corticospinal tract; Motor impairment; Diffusion MRI; Stroke (engine); Fractional anisotropy; Physical medicine and rehabilitation; Medicine; Structural integrity; Chronic stroke; Magnetic resonance imaging; Physical therapy; Rehabilitation; Radiology","score_opus":0.197772134622818,"score_gpt":0.5022585865306397,"score_spread":0.3044864519078217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791053909","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9145401,0.0019818756,0.078402445,0.00025732943,0.00004581576,0.00009130288,0.0025159912,0.00041317596,0.0017521362],"genre_scores_gemma":[0.9758336,0.00084057904,0.02023797,0.000028740958,0.000051181505,0.00004145006,0.0012735468,0.00006938025,0.0016234355],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999242,0.0000138818605,0.000010792198,0.000016328137,0.000016313863,0.000018455152],"domain_scores_gemma":[0.9996773,0.00014043978,0.00004932646,0.000033317883,0.000071789495,0.000027831176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039754531,0.00047856657,0.00030933178,0.0018885145,0.00033936228,0.0008077225,0.00020696483,0.0004910537,0.0013006211],"category_scores_gemma":[0.0015483703,0.00021107799,0.00037341524,0.0010705364,0.00021167332,0.000486998,0.0002865463,0.00022172378,0.00043653825],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028182073,0.00019403116,0.07205392,0.00077191123,0.00046444245,0.0018189988,0.0004324545,0.01252562,0.33654678,0.0013613541,0.0035031806,0.5675091],"study_design_scores_gemma":[0.00008043867,0.00043383086,0.6880207,0.0001312525,0.00065186375,0.005185652,0.0006410614,0.18639605,0.11015275,0.0038855858,0.004332415,0.00008843784],"about_ca_topic_score_codex":0.004816093,"about_ca_topic_score_gemma":0.010249192,"teacher_disagreement_score":0.004816093,"about_ca_system_score_codex":0.00018979955,"about_ca_system_score_gemma":0.00063454016,"threshold_uncertainty_score":0.009576082},"labels":[],"label_agreement":null},{"id":"W2791224996","doi":"10.1016/j.neuroimage.2018.01.034","title":"High resolution in-vivo diffusion imaging of the human hippocampus","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Hippocampus; Hippocampal formation; Diffusion; Diffusion imaging; Nuclear magnetic resonance; Neuroscience; Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.03556724292426493,"score_gpt":0.33003583117118174,"score_spread":0.2944685882469168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791224996","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90894216,0.010798509,0.07018584,0.00164821,0.00006255508,0.000101296384,0.00093345926,0.00024831644,0.0070797894],"genre_scores_gemma":[0.9575914,0.0043451767,0.034167994,0.0001181561,0.00004249569,0.000026536021,0.00026903633,0.000050604547,0.003388674],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99995816,0.000012107012,0.0000037685975,0.0000070611018,0.00000999679,0.000008855281],"domain_scores_gemma":[0.99986875,0.000057410718,0.000018983646,0.00001725651,0.000024765694,0.000012784008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031597627,0.0002098887,0.00016764874,0.00051426055,0.00027239523,0.00048784062,0.0002712596,0.0005789354,0.0017625919],"category_scores_gemma":[0.00087375136,0.00029962746,0.00010596537,0.0003708185,0.0002888217,0.0006378019,0.00026412754,0.00034025445,0.00029982065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008060524,0.00008661852,0.0028060696,0.00063757825,0.00009117922,0.00091729785,0.0003101307,0.0027222398,0.95223343,0.0015290055,0.0011915006,0.036668986],"study_design_scores_gemma":[0.0003967231,0.00101196,0.093692824,0.00023474196,0.0004902073,0.025328059,0.0009721232,0.02625698,0.82415557,0.008617979,0.01873118,0.00011168926],"about_ca_topic_score_codex":0.003011344,"about_ca_topic_score_gemma":0.004708864,"teacher_disagreement_score":0.003011344,"about_ca_system_score_codex":0.00016372318,"about_ca_system_score_gemma":0.00044152766,"threshold_uncertainty_score":0.005987644},"labels":[],"label_agreement":null},{"id":"W2791409461","doi":"10.1016/j.neuroimage.2017.12.064","title":"Mapping population-based structural connectomes","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; National Science Foundation; National Institutes of Health; Cancer Prevention and Research Institute of Texas","keywords":"Connectome; Human Connectome Project; Connectomics; Tractography; Computer science; Population; Artificial intelligence; Outlier; Robustness (evolution); Pattern recognition (psychology); Diffusion MRI; Neuroscience; Functional connectivity; Biology; Magnetic resonance imaging","score_opus":0.06870418740974009,"score_gpt":0.367364929209922,"score_spread":0.2986607418001819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791409461","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18409272,0.0006563024,0.81035703,0.00056740147,0.000043365188,0.00008492078,0.00066640467,0.00089939503,0.0026324575],"genre_scores_gemma":[0.84009117,0.0007689863,0.15582485,0.000116966236,0.00007708637,0.00019476637,0.00077383954,0.00020720478,0.0019450336],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99985325,0.00005509709,0.0000050047274,0.000050646417,0.000024435152,0.000011528224],"domain_scores_gemma":[0.99958926,0.00024658497,0.000053042633,0.00005279514,0.000040679435,0.00001775327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079807604,0.00043070756,0.00035922122,0.0020862482,0.00035795686,0.0010521725,0.00063776236,0.00075134035,0.0018342913],"category_scores_gemma":[0.0032538625,0.00039054092,0.00083222456,0.0014609923,0.00045731,0.0008521602,0.0006362943,0.0007172457,0.000496495],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006611449,0.0003458881,0.031010529,0.0005843047,0.0014263798,0.0012997831,0.0006836956,0.2602234,0.14841764,0.05068513,0.008367644,0.4962945],"study_design_scores_gemma":[0.0001067413,0.00017245214,0.034681637,0.00007280701,0.00037338934,0.0022573604,0.00023194843,0.73979455,0.024690783,0.19249304,0.0050524613,0.00007278604],"about_ca_topic_score_codex":0.0025361774,"about_ca_topic_score_gemma":0.004756577,"teacher_disagreement_score":0.0025361774,"about_ca_system_score_codex":0.00033107627,"about_ca_system_score_gemma":0.0006569004,"threshold_uncertainty_score":0.006136358},"labels":[],"label_agreement":null},{"id":"W2791545517","doi":"10.1117/12.2293566","title":"Design and evaluation of a diffusion MRI fibre phantom using 3D printing","year":2018,"lang":"en","type":"article","venue":"Medical Imaging 2018: Physics of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Imaging phantom; 3D printing; Diffusion; Computer science; Biomedical engineering; Materials science; Engineering; Optics; Physics; Composite material","score_opus":0.09184233710314892,"score_gpt":0.4189484282336127,"score_spread":0.3271060911304638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791545517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19677171,0.0010995881,0.7945771,0.0003608766,0.00019789253,0.0016913794,0.0007122623,0.0021216976,0.002467513],"genre_scores_gemma":[0.31822336,0.0014303137,0.67389596,0.00014858681,0.00003527066,0.0020340618,0.0007255448,0.00032135396,0.0031854634],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993212,0.00011701824,0.000056042394,0.00012758092,0.0003353585,0.00004281025],"domain_scores_gemma":[0.99813336,0.00075130916,0.00026578733,0.00025882418,0.00044520004,0.00014548036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022043167,0.00080025056,0.0004328751,0.0007487365,0.00022534154,0.0006720937,0.000859551,0.0012206715,0.0013966458],"category_scores_gemma":[0.0029421567,0.0005313823,0.00041255853,0.00045100055,0.0004644784,0.0006002262,0.0005207818,0.00040465585,0.0007287036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029781618,0.00019013957,0.0007259028,0.00038011218,0.00002336243,0.00032432168,0.00016454628,0.014991428,0.955187,0.0011764129,0.00035881836,0.02618029],"study_design_scores_gemma":[0.000058713613,0.0013335175,0.0020334006,0.000052926604,0.000059941227,0.00084993214,0.000042534415,0.04524093,0.9390503,0.0004168562,0.0107728625,0.00008823049],"about_ca_topic_score_codex":0.00042270086,"about_ca_topic_score_gemma":0.00033752364,"teacher_disagreement_score":0.0022043167,"about_ca_system_score_codex":0.00039089908,"about_ca_system_score_gemma":0.00059543055,"threshold_uncertainty_score":0.011657655},"labels":[],"label_agreement":null},{"id":"W2791687065","doi":"10.1016/j.media.2018.03.004","title":"Riemannian metric optimization on surfaces (RMOS) for intrinsic brain mapping in the Laplace–Beltrami embedding space","year":2018,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; Foundation of the American Society of Neuroradiology; National Institutes of Health; BioClinica; National Eye Institute; National Institute on Aging; Alzheimer's Association; AbbVie; Biogen; American Society of Neuroradiology; Northern California Institute for Research and Education; Alzheimer's Drug Discovery Foundation; U.S. Department of Defense","keywords":"Embedding; Mathematics; Surface (topology); Riemannian geometry; Metric (unit); Polygon mesh; Artificial intelligence; Mathematical analysis; Topology (electrical circuits); Computer science; Algorithm; Geometry; Combinatorics","score_opus":0.04481816951865586,"score_gpt":0.39064356498760916,"score_spread":0.3458253954689533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791687065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01773744,0.0007321853,0.97764105,0.00061056303,0.00006761221,0.000054425116,0.00013416601,0.00019807057,0.002824451],"genre_scores_gemma":[0.46936902,0.0022876502,0.50677115,0.00043072374,0.000494454,0.00045805288,0.0009827279,0.0010271926,0.018178983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999201,0.0003510997,0.000045015095,0.00016443804,0.00019107046,0.0000473694],"domain_scores_gemma":[0.9982482,0.00090384815,0.00021078101,0.00017837458,0.00029464724,0.00016418163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014144138,0.0012884107,0.0012849548,0.0013064855,0.0004212443,0.0015865171,0.00127885,0.0015801099,0.0025810343],"category_scores_gemma":[0.0062685683,0.0004925196,0.0011539469,0.0007636325,0.0016074077,0.0023605027,0.0031307628,0.0024946565,0.0008152836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010243661,0.00008771215,0.00082811643,0.00044067885,0.00010472582,0.00013592381,0.0003325029,0.18415026,0.007928184,0.69030154,0.008267406,0.10732047],"study_design_scores_gemma":[0.0000066430125,0.000058564667,0.0003120643,0.00001788136,0.000011423962,0.00006661521,0.00003466012,0.7749272,0.00070108275,0.22090265,0.0029376892,0.000023419087],"about_ca_topic_score_codex":0.0025266008,"about_ca_topic_score_gemma":0.002016027,"teacher_disagreement_score":0.0025810343,"about_ca_system_score_codex":0.00097357534,"about_ca_system_score_gemma":0.0010494696,"threshold_uncertainty_score":0.008634388},"labels":[],"label_agreement":null},{"id":"W2791791346","doi":"10.4103/0366-6999.226060","title":"Brain Impairment in Chronic Schizophrenia Patients with Depressive Symptoms Differs from Brain Impairment in Chronic Depression Patients with Psychotic Symptoms","year":2018,"lang":"en","type":"article","venue":"Chinese Medical Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Depression (economics); Schizophrenia (object-oriented programming); Depressive symptoms; Psychiatry; Medicine; Psychosis; Chronic depression; Psychology; Internal medicine; Clinical psychology; Anxiety; Cognition","score_opus":0.007124780128962359,"score_gpt":0.2965348584193956,"score_spread":0.28941007829043325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791791346","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996811,0.00007690519,0.000012166579,0.000008997351,0.0000013877514,0.0000060808566,0.000045339508,5.041791e-7,0.00016738009],"genre_scores_gemma":[0.999706,0.00006272684,0.00003062785,0.000017104725,0.000004261806,0.000005888184,0.0001123289,4.2706085e-7,0.000060542767],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985695,0.000019976396,0.000023956318,0.00003297096,0.000028527455,0.00003761877],"domain_scores_gemma":[0.9997423,0.00002482463,0.00010751116,0.000009203062,0.000024897417,0.00009121135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016932645,0.00024404451,0.00027143318,0.00080524065,0.00046329794,0.00033293356,0.0001303116,0.0002757059,0.0015501627],"category_scores_gemma":[0.00057351607,0.00015437603,0.00017155861,0.00040741713,0.0002938647,0.00023306962,0.00037016757,0.00018172314,0.00015501326],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005178357,0.00008973406,0.9912766,0.000026263506,0.000034624016,0.00086732284,0.0003040442,0.000020503352,0.0044146776,0.00003319999,0.00006444271,0.002350731],"study_design_scores_gemma":[0.0000099526615,0.00010745626,0.9989365,0.0000033040353,0.000005851549,0.0006834024,0.00014205412,0.000016727414,0.00003992014,0.000010511023,0.000043066106,0.00000126462],"about_ca_topic_score_codex":0.004494482,"about_ca_topic_score_gemma":0.00862027,"teacher_disagreement_score":0.004494482,"about_ca_system_score_codex":0.00028016395,"about_ca_system_score_gemma":0.00023282842,"threshold_uncertainty_score":0.008936644},"labels":[],"label_agreement":null},{"id":"W2791995825","doi":"10.1111/jcpp.12879","title":"Diffusion tensor imaging correlates of early markers of depression in youth at high‐familial risk for bipolar disorder","year":2018,"lang":"en","type":"article","venue":"Journal of Child Psychology and Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Medical Research Council; Fonds de Recherche du Québec - Santé; University of Edinburgh; European Commission; Seventh Framework Programme; Alzheimer Society; Wellcome Trust","keywords":"Fractional anisotropy; Major depressive disorder; Psychology; Bipolar disorder; Mood disorders; Depression (economics); Mood; Psychiatry; Diffusion MRI; Clinical psychology; White matter; Internal medicine; Medicine; Magnetic resonance imaging; Anxiety","score_opus":0.01354712241150179,"score_gpt":0.31979865715293326,"score_spread":0.30625153474143146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791995825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999592,0.00013493338,0.00002298605,0.00002768525,0.0000020509174,0.0000033768474,0.000072312294,0.0000013857656,0.00014320116],"genre_scores_gemma":[0.99965954,0.00007545234,0.00006917725,0.00000740566,0.0000031567874,0.000003697465,0.00011695208,7.95854e-7,0.00006393245],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999833,0.000036843685,0.00002035542,0.00003408508,0.000034066,0.00004154169],"domain_scores_gemma":[0.9987676,0.00010788298,0.00073668273,0.000042123793,0.00012581801,0.00021994615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000430104,0.0002957915,0.00025532316,0.0006972858,0.00038433,0.0004795945,0.0002048248,0.00035630257,0.0009933686],"category_scores_gemma":[0.0019285299,0.00022359197,0.00019312624,0.0004903011,0.00020561689,0.0002308604,0.0003172755,0.00052029704,0.00012859162],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004995528,0.0000251533,0.99861,0.0000043547366,0.000017329718,0.00009554826,0.00010239753,0.000017753086,0.00023528298,0.000014345922,0.00004845855,0.0007793059],"study_design_scores_gemma":[0.000001611825,0.000025195688,0.9996786,0.000003127711,0.0000069780444,0.00014266449,0.00006463285,0.000029425406,0.000020205183,0.0000087918315,0.000018021234,7.585189e-7],"about_ca_topic_score_codex":0.0055027623,"about_ca_topic_score_gemma":0.0110087935,"teacher_disagreement_score":0.0055027623,"about_ca_system_score_codex":0.00028457327,"about_ca_system_score_gemma":0.00021033926,"threshold_uncertainty_score":0.010941446},"labels":[],"label_agreement":null},{"id":"W2792160103","doi":"10.1016/j.mri.2018.03.010","title":"T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; University of Alberta; Western University; University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Wellcome Trust; Canada Foundation for Innovation; Research Manitoba","keywords":"Diffusion MRI; Magnetization transfer; White matter; Hippocampus; Hippocampal formation; Magnetic resonance imaging; Pathology; Nuclear magnetic resonance; Neuroscience; Medicine; Biology; Radiology; Physics","score_opus":0.03846721745761758,"score_gpt":0.32534317293207915,"score_spread":0.28687595547446154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792160103","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97376055,0.0031886548,0.014491107,0.0014429319,0.00032400875,0.00015940158,0.0040729973,0.0005521865,0.0020081596],"genre_scores_gemma":[0.9461933,0.004331583,0.028262665,0.0005214584,0.00011792206,0.00053014525,0.0025161065,0.00030418084,0.0172228],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99950516,0.000060036302,0.000070203205,0.00015599717,0.00010579271,0.00010281276],"domain_scores_gemma":[0.9990533,0.00006761582,0.00036795528,0.000089739806,0.00017399933,0.00024730788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010766966,0.0018679118,0.0006298357,0.0033596058,0.00091868226,0.0007273663,0.0010442476,0.0018434154,0.0016772529],"category_scores_gemma":[0.00035259925,0.00084448827,0.00090103754,0.00082024466,0.0012905808,0.001304262,0.00048545972,0.0027403566,0.00053126324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014354979,0.00038700458,0.00030338325,0.000095916505,0.000041590603,0.00029611975,0.00009499027,0.00021294887,0.99484044,0.0005220378,0.00031907012,0.001450906],"study_design_scores_gemma":[0.0004004464,0.0021395907,0.007349568,0.00006394964,0.00032313156,0.001718013,0.00026846526,0.0036795794,0.97938985,0.0010199655,0.0035848697,0.00006262034],"about_ca_topic_score_codex":0.00464414,"about_ca_topic_score_gemma":0.0071765254,"teacher_disagreement_score":0.00464414,"about_ca_system_score_codex":0.0010388097,"about_ca_system_score_gemma":0.0007485335,"threshold_uncertainty_score":0.00923419},"labels":[],"label_agreement":null},{"id":"W2792230481","doi":"10.1101/282145","title":"Topographic diversity of structural connectivity in schizophrenia","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Taipei Veterans General Hospital; National Health Research Institutes; Janssen Canada; Academia Sinica; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Schizophrenia (object-oriented programming); Diffusion MRI; Neuroscience; Similarity (geometry); Psychology; Biology; Medicine; Magnetic resonance imaging; Artificial intelligence; Computer science; Psychiatry","score_opus":0.03556129631042174,"score_gpt":0.2820594888935082,"score_spread":0.24649819258308645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792230481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987122,0.0000707866,0.0008050878,0.000024409945,8.869463e-7,0.0000032237401,0.00012874004,0.000007942407,0.00024680153],"genre_scores_gemma":[0.99965835,0.000020157158,0.00022301485,0.0000021935973,0.0000014510773,0.0000013670052,0.00007283419,0.0000012714459,0.000019300962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975735,0.000083347826,0.000022992943,0.000056855897,0.000050555132,0.000028931898],"domain_scores_gemma":[0.9990833,0.00030119848,0.0003357434,0.00012555953,0.000080493846,0.00007364781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047565319,0.00022391879,0.0002754952,0.0016586763,0.00021648087,0.0004288087,0.00015315061,0.00020838297,0.0011809174],"category_scores_gemma":[0.0020150898,0.00019343584,0.00018935543,0.0007552851,0.0005027777,0.00035018276,0.0005580848,0.00018739514,0.00008061855],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009816185,0.00004805864,0.8677121,0.00010215091,0.00037943677,0.0007807829,0.0009293267,0.0067884484,0.0898716,0.0010646653,0.00032664542,0.031015174],"study_design_scores_gemma":[0.0000072227845,0.00004588812,0.9928108,0.0000057952193,0.000023388971,0.00065666536,0.00013774466,0.0040112906,0.0010406044,0.001192037,0.00005938064,0.0000091203165],"about_ca_topic_score_codex":0.0021404284,"about_ca_topic_score_gemma":0.0031115126,"teacher_disagreement_score":0.0021404284,"about_ca_system_score_codex":0.00019932658,"about_ca_system_score_gemma":0.00015129952,"threshold_uncertainty_score":0.004255891},"labels":[],"label_agreement":null},{"id":"W2792269733","doi":"10.1101/253443","title":"A structural equation model for imaging genetics using spatial transcriptomics","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Stichting voor de Technische Wetenschappen; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; European Commission; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Imaging genetics; Interpretability; Neuroimaging; Context (archaeology); Structural equation modeling; Artificial intelligence; Computer science; Machine learning; Computational biology; Biology; Neuroscience","score_opus":0.09471566155556396,"score_gpt":0.32280967976409014,"score_spread":0.22809401820852618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792269733","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.104827784,0.0014008803,0.8717611,0.009901912,0.00030410473,0.00031468793,0.0069224746,0.0009781125,0.0035890148],"genre_scores_gemma":[0.7426529,0.0017512153,0.23006295,0.00092528877,0.00048024615,0.0019228889,0.0070809233,0.00023637767,0.0148871755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99598,0.00258313,0.00011299715,0.00081493374,0.00028617974,0.00022273802],"domain_scores_gemma":[0.9826795,0.015129083,0.000970478,0.00035093236,0.00063631934,0.00023370293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007196987,0.0015893204,0.0021779889,0.0029054845,0.0009286237,0.0027280943,0.003254132,0.0038551532,0.012457113],"category_scores_gemma":[0.018127725,0.0013256642,0.0028998526,0.00350548,0.001778726,0.0020024392,0.0019672557,0.00382601,0.0011693715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002808218,0.00024682417,0.022931837,0.00017350787,0.00073886174,0.0010183037,0.0005466845,0.7538073,0.0005307519,0.18937166,0.006674869,0.023678653],"study_design_scores_gemma":[0.00010216687,0.00004267072,0.0017604149,0.00003160346,0.00010170326,0.000083346335,0.000055267952,0.93881375,0.00005350438,0.0574986,0.0014233172,0.000033649856],"about_ca_topic_score_codex":0.03909237,"about_ca_topic_score_gemma":0.029948974,"teacher_disagreement_score":0.03909237,"about_ca_system_score_codex":0.0028742205,"about_ca_system_score_gemma":0.0027499578,"threshold_uncertainty_score":0.07772964},"labels":[],"label_agreement":null},{"id":"W2792428439","doi":"10.1002/mrm.27112","title":"Diffusion MRI monitoring of specific structures in the irradiated rat brain","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Astrogliosis; Corpus callosum; Hippocampus; Nuclear medicine; Medicine; Pathology; Magnetic resonance imaging; Internal medicine; Central nervous system; Radiology","score_opus":0.055476362538311105,"score_gpt":0.35731721185641563,"score_spread":0.3018408493181045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792428439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97529376,0.0038383154,0.018841457,0.00006667067,0.000023307608,0.000050633378,0.00047998692,0.00021258534,0.0011933444],"genre_scores_gemma":[0.9732517,0.0039353454,0.019352132,0.00006789623,0.000016865704,0.000106818006,0.0005511758,0.00005759883,0.002660435],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999354,0.0000062914246,0.0000036839922,0.000026438702,0.000014762497,0.000013364128],"domain_scores_gemma":[0.9998745,0.000012526668,0.000058574322,0.000009341694,0.000026831141,0.00001834544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019066803,0.00063014973,0.00028761046,0.0005191955,0.00015033298,0.00023387502,0.00017899724,0.00032999192,0.00076043175],"category_scores_gemma":[0.00019736786,0.00019353825,0.00017735356,0.00015864364,0.00029581776,0.00032024606,0.00023779985,0.0004107389,0.00021381721],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040977622,0.0000067636065,0.00031152213,0.000040164927,0.000005930234,0.00001921295,0.000013608737,0.000075549295,0.9981414,0.0000266421,0.000015697688,0.0013025394],"study_design_scores_gemma":[0.000007925951,0.0008497501,0.01877048,0.000017343167,0.000076120305,0.00050203194,0.00007351411,0.0013635625,0.97710234,0.00011014094,0.0011100617,0.000016762317],"about_ca_topic_score_codex":0.0008223045,"about_ca_topic_score_gemma":0.0011743193,"teacher_disagreement_score":0.0008223045,"about_ca_system_score_codex":0.00019820934,"about_ca_system_score_gemma":0.00018546009,"threshold_uncertainty_score":0.0025439262},"labels":[],"label_agreement":null},{"id":"W2792811499","doi":"10.1002/jmri.26013","title":"Novel connectivity map normalization procedure for improved quantitative investigation of structural thalamic connectivity in temporal lobe epilepsy patients","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Temporal lobe; Diffusion MRI; Tractography; Parahippocampal gyrus; Thalamus; Epilepsy; Normalization (sociology); Neuroscience; Medicine; Nuclear medicine; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.034724177122954225,"score_gpt":0.3304289340590972,"score_spread":0.29570475693614295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792811499","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43183985,0.00033494594,0.561427,0.00033035746,0.000073134535,0.00037975312,0.0021169921,0.001806095,0.0016918399],"genre_scores_gemma":[0.65451455,0.000189784,0.34128022,0.00004390884,0.000052317875,0.00071337016,0.0021039012,0.00033611973,0.0007658068],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996654,0.00012769656,0.000027092477,0.000076368706,0.000079328,0.00002409193],"domain_scores_gemma":[0.9991099,0.00037172742,0.00017088653,0.00009563795,0.00021488333,0.000036898342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009624308,0.00044109416,0.0003805442,0.001150196,0.0002823868,0.00047020614,0.00034630013,0.0002774947,0.0019038717],"category_scores_gemma":[0.0045535173,0.00017330024,0.00041800816,0.00088946236,0.00027374882,0.00043821163,0.00047936485,0.0003456387,0.0002850849],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001986639,0.00034330957,0.08038017,0.00046177706,0.0006343389,0.000873032,0.00076684845,0.032944467,0.20141156,0.00716177,0.0061168782,0.6669193],"study_design_scores_gemma":[0.0002810044,0.00093507837,0.35764816,0.00008850269,0.00045745514,0.0044257995,0.00035835526,0.5234274,0.08913089,0.009421207,0.013620289,0.00020591627],"about_ca_topic_score_codex":0.0030045786,"about_ca_topic_score_gemma":0.005384657,"teacher_disagreement_score":0.0030045786,"about_ca_system_score_codex":0.0003883107,"about_ca_system_score_gemma":0.00084890384,"threshold_uncertainty_score":0.0063690543},"labels":[],"label_agreement":null},{"id":"W2793249164","doi":"10.1093/cercor/bhx363","title":"Diversity of Cortico-descending Projections: Histological and Diffusion MRI Characterization in the Monkey","year":2017,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Tractography; Neuroscience; Somatosensory system; Diffusion MRI; Anatomy; White matter; SMA*; Spinal cord; Internal capsule; Axon; Electrophysiology; Biology; Magnetic resonance imaging; Medicine; Computer science","score_opus":0.09689226681129072,"score_gpt":0.34613012875158367,"score_spread":0.24923786194029296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793249164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959817,0.00050221157,0.0021182194,0.000054044653,0.00000309408,0.000008096688,0.00014549604,0.000026111045,0.0011611175],"genre_scores_gemma":[0.989279,0.0014489648,0.0063867983,0.00006550698,0.000007866572,0.000028821685,0.00035045762,0.000027616856,0.002404795],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999502,0.000004759883,0.0000031737122,0.00001981001,0.0000096358635,0.000012382538],"domain_scores_gemma":[0.99981326,0.000034637007,0.000044383953,0.000031853833,0.00004001696,0.000035902183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017640185,0.00016344896,0.00017104116,0.0007547659,0.00029756784,0.00037389752,0.00013955234,0.00028578265,0.00074523996],"category_scores_gemma":[0.00035165492,0.00026662045,0.000094363946,0.00034674135,0.00043122334,0.00038437013,0.0002642492,0.0002346476,0.00025214898],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002925794,0.000040893152,0.014524765,0.00008366168,0.000037653037,0.00050343043,0.00031052856,0.00025554886,0.9632636,0.00064794713,0.00008335801,0.019956095],"study_design_scores_gemma":[0.00008914015,0.0014780817,0.7376967,0.000107134794,0.00023963039,0.010770346,0.0012393122,0.008499244,0.22617401,0.0045597297,0.009069835,0.00007676912],"about_ca_topic_score_codex":0.0035251332,"about_ca_topic_score_gemma":0.007019346,"teacher_disagreement_score":0.0035251332,"about_ca_system_score_codex":0.00026291475,"about_ca_system_score_gemma":0.0002285823,"threshold_uncertainty_score":0.007009268},"labels":[],"label_agreement":null},{"id":"W2793560073","doi":"10.1093/cercor/bhy031","title":"Global White Matter Diffusion Characteristics Predict Longitudinal Cognitive Change Independently of Amyloid Status in Clinically Normal Older Adults","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institutes of Health; Canadian Institutes of Health Research; Centre d'Imagerie BioMédicale; Massachusetts General Hospital","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Cognitive decline; Cognition; Episodic memory; Psychology; Effects of sleep deprivation on cognitive performance; Neuroscience; Internal medicine; Medicine; Dementia; Magnetic resonance imaging; Radiology","score_opus":0.03980957992377172,"score_gpt":0.341549975888084,"score_spread":0.3017403959643123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793560073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99968207,0.000113300404,0.00007026393,0.000012747353,0.0000012246886,0.0000021211777,0.000041273586,0.0000019457189,0.0000750689],"genre_scores_gemma":[0.9997191,0.000040162824,0.000082040446,0.0000068857294,0.0000037054301,0.000001966151,0.00007765952,6.8947287e-7,0.00006782898],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998679,0.00003572561,0.000019114044,0.00003946722,0.000017871214,0.000019875899],"domain_scores_gemma":[0.9989538,0.00028359168,0.00043065168,0.00011339108,0.00008298741,0.00013560022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007016239,0.00047449887,0.00028834955,0.00054030196,0.00023673411,0.00041532252,0.00017150317,0.00053941587,0.00066144933],"category_scores_gemma":[0.002570105,0.00024189081,0.00035033855,0.0002996212,0.0003113805,0.0005465413,0.00034672828,0.00037265866,0.00017408842],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023709037,0.00003549249,0.99754035,0.00000537153,0.000056721758,0.00004496523,0.00007374195,0.000094142066,0.00040217856,0.000011365024,0.000022246224,0.0014763891],"study_design_scores_gemma":[0.0000060363905,0.00009384778,0.9992562,0.0000018254947,0.00002502346,0.00009428736,0.000042416526,0.00030973562,0.0000875163,0.00005811973,0.000023332239,0.0000017104883],"about_ca_topic_score_codex":0.0022939437,"about_ca_topic_score_gemma":0.005538016,"teacher_disagreement_score":0.0022939437,"about_ca_system_score_codex":0.00014407208,"about_ca_system_score_gemma":0.00017015723,"threshold_uncertainty_score":0.004561186},"labels":[],"label_agreement":null},{"id":"W2794587673","doi":"10.1002/jmri.26016","title":"Myocardial fibrosis evaluated by diffusion‐weighted imaging and its relationship to 3D contractile function in patients with hypertrophic cardiomyopathy","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Circle Cardiovascular Imaging","funders":"National Natural Science Foundation of China","keywords":"Medicine; Hypertrophic cardiomyopathy; Myocardial fibrosis; Cardiology; Internal medicine; Effective diffusion coefficient; Intraclass correlation; Diffusion MRI; Fibrosis; Cardiomyopathy; Magnetic resonance imaging; Population; Ventricle; Nuclear medicine; Heart failure; Radiology","score_opus":0.015548300847582927,"score_gpt":0.2734621996068646,"score_spread":0.25791389875928167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794587673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99970776,0.00009986728,0.000032851956,0.000015782533,0.0000028873446,0.0000028839102,0.000023113245,9.32469e-7,0.00011394556],"genre_scores_gemma":[0.9998332,0.000026059799,0.000034874094,0.00001059732,0.0000074910135,0.0000030535539,0.000034672004,4.5637293e-7,0.000049533905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982446,0.000042829597,0.000022276334,0.00003812571,0.00003367972,0.000038560407],"domain_scores_gemma":[0.99913627,0.00021565621,0.00034835548,0.000033933673,0.00007923757,0.00018653968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005016111,0.0002799872,0.0002702031,0.0006666623,0.00031545406,0.00030319445,0.00013842134,0.0004222355,0.0011896357],"category_scores_gemma":[0.0017415532,0.00019984,0.00020285402,0.00031488074,0.00029826115,0.00026251876,0.00024587696,0.00037603034,0.00017877806],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001977609,0.00003101382,0.9981071,0.00000486913,0.000016111131,0.00020882876,0.000059316564,0.000028064836,0.0004960948,0.0000070751776,0.000023792323,0.0008198646],"study_design_scores_gemma":[0.0000075760345,0.00014644659,0.999025,0.0000026859414,0.000011062822,0.00053421827,0.0000698147,0.000098677956,0.000060980874,0.00001245297,0.000029236071,0.0000018692293],"about_ca_topic_score_codex":0.0007792421,"about_ca_topic_score_gemma":0.0010996835,"teacher_disagreement_score":0.0011896357,"about_ca_system_score_codex":0.00013920109,"about_ca_system_score_gemma":0.00012712472,"threshold_uncertainty_score":0.003979802},"labels":[],"label_agreement":null},{"id":"W2794660696","doi":"10.3389/fpsyg.2018.00330","title":"Openness to Changing Religious Views Is Related to Radial Diffusivity in the Genu of the Corpus Callosum in an Initial Study of Healthy Young Adults","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Institute on Drug Abuse; National Institutes of Health; National Center for Responsible Gaming","keywords":"Corpus callosum; Psychology; White matter; Splenium; Diffusion MRI; Superior longitudinal fasciculus; Openness to experience; Inferior longitudinal fasciculus; Neuroscience; Social psychology; Fractional anisotropy; Medicine","score_opus":0.06200635574306377,"score_gpt":0.42748605235321224,"score_spread":0.36547969661014845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794660696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997912,0.000034467732,0.000027008044,0.0000108805625,0.0000013512988,0.0000036920317,0.00002717733,9.848587e-7,0.00010326055],"genre_scores_gemma":[0.9996542,0.000023581317,0.000050420833,0.0000094831585,0.0000022996437,0.000004060299,0.000046327794,7.279964e-7,0.00020887794],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990964,0.0000141149685,0.000010606179,0.00003100498,0.000015925589,0.00001859466],"domain_scores_gemma":[0.99940383,0.00010526663,0.00022909566,0.00004168487,0.00007752323,0.00014253838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031489125,0.00018826823,0.0001818521,0.0005121173,0.000367728,0.00035902916,0.00012948629,0.00039589923,0.0017109424],"category_scores_gemma":[0.0015241425,0.00023889152,0.00020270246,0.00019556949,0.00030893538,0.0003207123,0.00030906385,0.0004273647,0.0001688832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034184588,0.00019160453,0.9875815,0.000023698696,0.00006364409,0.00037841,0.0016417925,0.000038049347,0.006203063,0.00004413301,0.000106052285,0.003386079],"study_design_scores_gemma":[0.0000042095703,0.00008550083,0.9992574,0.000002433043,0.000008829955,0.00020795963,0.00020029992,0.00004099215,0.00013567804,0.000014192118,0.00004096077,0.0000016576602],"about_ca_topic_score_codex":0.0037215708,"about_ca_topic_score_gemma":0.0073483447,"teacher_disagreement_score":0.0037215708,"about_ca_system_score_codex":0.00014757495,"about_ca_system_score_gemma":0.00015977674,"threshold_uncertainty_score":0.0073997974},"labels":[],"label_agreement":null},{"id":"W2794674174","doi":"10.1093/schbul/sby016.443","title":"T167. ABERRANT MYELINATION OF THE CINGULUM BUNDLE IN PATIENTS WITH SCHIZOPHRENIA: A 7T MTI/DTI STUDY","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Fractional anisotropy; Cingulum (brain); Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Radiology; Psychiatry","score_opus":0.019380576258406425,"score_gpt":0.2791227404122939,"score_spread":0.25974216415388746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794674174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992374,0.00010250564,0.00015759596,0.00004088588,0.00000655793,0.000013030005,0.00009882741,0.000007096645,0.00033599092],"genre_scores_gemma":[0.9992054,0.00006938885,0.00026144882,0.000028476912,0.000008751055,0.000008876676,0.00014596141,0.0000072724683,0.00026460868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998233,0.000018800278,0.00003195986,0.000052984058,0.00004594138,0.000027090065],"domain_scores_gemma":[0.99955827,0.00004337733,0.00016361661,0.00003872303,0.00008556737,0.000110442066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004108644,0.00075955625,0.000495582,0.0010755735,0.001063758,0.00042205202,0.00023576483,0.00062815327,0.0027528533],"category_scores_gemma":[0.0010318141,0.0004006699,0.00039214944,0.0005481764,0.00050987746,0.00033965326,0.00043013928,0.0003832222,0.0005452784],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0053081843,0.0009801154,0.785894,0.00021195512,0.00031895214,0.040297747,0.00320429,0.00038028666,0.14186123,0.00037877733,0.00063492544,0.02052964],"study_design_scores_gemma":[0.000086472835,0.0016192326,0.9772136,0.000024347719,0.00017478141,0.01621944,0.0005783791,0.0005554923,0.002651731,0.00016878631,0.00067570247,0.00003204219],"about_ca_topic_score_codex":0.0070793875,"about_ca_topic_score_gemma":0.0055937907,"teacher_disagreement_score":0.0070793875,"about_ca_system_score_codex":0.00038498951,"about_ca_system_score_gemma":0.0004797205,"threshold_uncertainty_score":0.014076352},"labels":[],"label_agreement":null},{"id":"W2794907560","doi":"10.3897/rio.4.e25312","title":"FIIND: Ferret Interactive Integrated Neurodevelopment Atlas","year":2018,"lang":"en","type":"article","venue":"Research Ideas and Outcomes","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; European Commission","keywords":"Neocortex; Neuroscience; Brain development; Neuroimaging; Regionalisation; Diffusion MRI; Human Connectome Project; Brain size; Fiber tract; Biology; Brain atlas; Human brain; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Geography","score_opus":0.17726212184635556,"score_gpt":0.4973078213687,"score_spread":0.3200456995223444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794907560","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021845136,0.003368627,0.20716621,0.00080466253,0.00033455488,0.00044990348,0.54274553,0.1928603,0.030425023],"genre_scores_gemma":[0.10568327,0.0033808306,0.2527019,0.0007758488,0.000110915025,0.0034956322,0.57907504,0.03357195,0.021204688],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999718,0.000037981175,0.0000298197,0.00009215314,0.00008127043,0.000040759398],"domain_scores_gemma":[0.99964213,0.000107547654,0.00006394164,0.00007919637,0.00006666898,0.000040493163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008363034,0.001390111,0.0009221766,0.0032168543,0.00052264886,0.0016268279,0.0024156843,0.0012933151,0.035133272],"category_scores_gemma":[0.0016068943,0.00065896433,0.0008843034,0.0013214817,0.00033706494,0.0011658608,0.001880797,0.0012042291,0.015732192],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012689114,0.000113384536,0.008826701,0.0028735686,0.0004545505,0.0013752155,0.0005316987,0.010397772,0.048847236,0.017207896,0.7378377,0.17026545],"study_design_scores_gemma":[0.00011794665,0.00016723505,0.016314806,0.00045075675,0.00021030496,0.0027645186,0.00009624515,0.018348655,0.024386331,0.017323628,0.9196943,0.00012519093],"about_ca_topic_score_codex":0.0038366034,"about_ca_topic_score_gemma":0.0071471157,"teacher_disagreement_score":0.035133272,"about_ca_system_score_codex":0.0011017496,"about_ca_system_score_gemma":0.0010692807,"threshold_uncertainty_score":0.11753249},"labels":[],"label_agreement":null},{"id":"W2794971544","doi":"10.1093/schbul/sby016.454","title":"T178. PRIOR SUB-THRESHOLD PSYCHOTIC SYMPTOMS ASSOCIATED WITH THICKER RIGHT INFERIOR FRONTAL GYRUS AMONG PATIENTS IN A FIRST EPISODE OF PSYCHOSIS","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"","keywords":"Psychosis; Psychology; Psychiatry; Schizophrenia (object-oriented programming); Neuroimaging; Recall; Clinical psychology","score_opus":0.013774802396196429,"score_gpt":0.26684695601873193,"score_spread":0.2530721536225355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794971544","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961984,0.000019883875,0.00001652626,0.00003721268,0.0000028022862,0.0000053037147,0.00007240533,0.0000015622348,0.00022438802],"genre_scores_gemma":[0.999721,0.000016780847,0.00003439527,0.00001932499,0.000005165955,0.0000040361083,0.000068926245,0.000001119364,0.0001293065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987626,0.000013823214,0.000013701405,0.000042921944,0.000025034142,0.000028275108],"domain_scores_gemma":[0.9993923,0.0000819099,0.00031205325,0.000023906987,0.000035688223,0.00015414687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014608403,0.00043524225,0.00034393504,0.000762263,0.000945597,0.0004325692,0.00034747247,0.00061243173,0.0052338713],"category_scores_gemma":[0.0008789662,0.0003147355,0.00029324,0.0005871419,0.0004611467,0.00043667667,0.00033015115,0.0005862821,0.0003200849],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052861404,0.00017822944,0.9831078,0.000024154157,0.00004615024,0.0063134157,0.00077649154,0.00007352807,0.006132644,0.00009321689,0.0002716757,0.002454056],"study_design_scores_gemma":[0.000012133468,0.00014769133,0.9939558,0.0000054318075,0.000011259239,0.005205162,0.00033553314,0.000084872685,0.00012058964,0.000049187667,0.00006847069,0.0000038923836],"about_ca_topic_score_codex":0.0109918555,"about_ca_topic_score_gemma":0.01607849,"teacher_disagreement_score":0.0109918555,"about_ca_system_score_codex":0.00040705415,"about_ca_system_score_gemma":0.0003826649,"threshold_uncertainty_score":0.021855712},"labels":[],"label_agreement":null},{"id":"W2795037714","doi":"10.1093/schbul/sby018.797","title":"S10. ASTROGLIAL PATHOLOGY IN SCHIZOPHRENIA: A META-ANALYSIS OF MRS STUDIES OF ANTERIOR CINGULATE MYOINOSITOL","year":2018,"lang":"es","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Care; London Health Sciences Centre; Western University","funders":"","keywords":"Schizophrenia (object-oriented programming); Anterior cingulate cortex; Meta-analysis; Inositol; Psychosis; Psychiatry; Medicine; Neuroscience; Internal medicine; Psychology; Cognition","score_opus":0.09390195899340781,"score_gpt":0.3813231331694894,"score_spread":0.2874211741760816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795037714","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022501137,0.9715549,0.00067601434,0.0006192442,0.0002613504,0.00020025135,0.0036092144,0.000052719843,0.0005251839],"genre_scores_gemma":[0.6272295,0.36173028,0.0030828284,0.0017098737,0.00052254787,0.0011445781,0.003552187,0.00010621936,0.0009219187],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9938625,0.002338231,0.0020716842,0.0008885018,0.0005067994,0.0003321723],"domain_scores_gemma":[0.9848008,0.011098635,0.0024276904,0.0005355466,0.0008990752,0.00023839348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007598459,0.0019928985,0.009579343,0.0053238887,0.0007336942,0.0028579782,0.0016561466,0.0020972376,0.0064323037],"category_scores_gemma":[0.01942458,0.0010504783,0.030619577,0.008531257,0.00058549276,0.0016100507,0.0015899704,0.0015617015,0.0005110138],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032255359,0.0000244886,0.027911602,0.28040588,0.67476326,0.00038582433,0.00019064386,0.00039580194,0.0007629144,0.00017385739,0.0014873167,0.010272923],"study_design_scores_gemma":[0.0005075441,0.00017149866,0.027977692,0.019164033,0.9484986,0.00021247697,0.00012007217,0.00021623091,0.00019809337,0.0003117451,0.0025912272,0.00003075106],"about_ca_topic_score_codex":0.007915544,"about_ca_topic_score_gemma":0.015806628,"teacher_disagreement_score":0.009579343,"about_ca_system_score_codex":0.0014406177,"about_ca_system_score_gemma":0.0022347567,"threshold_uncertainty_score":0.040184975},"labels":[],"label_agreement":null},{"id":"W2795150941","doi":"10.1016/j.nicl.2018.03.029","title":"Postmortem diffusion MRI of the entire human spinal cord at microscopic resolution","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Spinal cord; Magnetic resonance imaging; Diffusion MRI; Cord; Medicine; Magnetic resonance microscopy; Anatomy; Ex vivo; Biomedical engineering; Pathology; Neuroscience; Radiology; In vivo; Biology; Spin echo; Surgery","score_opus":0.16271483131394815,"score_gpt":0.47911206556944236,"score_spread":0.3163972342554942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795150941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8083727,0.008467431,0.15504244,0.0010313604,0.0001804818,0.0003493315,0.014618058,0.0018061121,0.010132023],"genre_scores_gemma":[0.85858595,0.006198398,0.11858397,0.00029419537,0.00011917294,0.0001645148,0.010804347,0.0004911357,0.0047584516],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990034,0.000009638021,0.000012488153,0.000029980414,0.000036584333,0.000010876624],"domain_scores_gemma":[0.99967074,0.00004784931,0.000054811288,0.000077631994,0.0001225149,0.00002642384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000286622,0.00032223153,0.00027674093,0.0012566299,0.0003276271,0.00043417624,0.00021008431,0.00047521133,0.00172692],"category_scores_gemma":[0.00081224815,0.0003500893,0.00018338337,0.00073366164,0.00034071412,0.00037368108,0.00040565015,0.00047396365,0.00064917153],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002419662,0.00009160445,0.0058540585,0.00063831854,0.0000962231,0.0014508665,0.00036822906,0.0030021481,0.9275519,0.00089069724,0.0035983922,0.05621571],"study_design_scores_gemma":[0.0001045716,0.0015030511,0.29932195,0.00059729116,0.0005947907,0.04234497,0.0011365087,0.022112463,0.5585941,0.0043770014,0.06912054,0.0001928174],"about_ca_topic_score_codex":0.0025469929,"about_ca_topic_score_gemma":0.0057993284,"teacher_disagreement_score":0.0025469929,"about_ca_system_score_codex":0.00020551439,"about_ca_system_score_gemma":0.0004570442,"threshold_uncertainty_score":0.0057771206},"labels":[],"label_agreement":null},{"id":"W2795442880","doi":"10.1016/j.neuroimage.2018.04.009","title":"Microstructural imaging in the spinal cord and validation strategies","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Canada Foundation for Innovation; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec","keywords":"Magnetic resonance imaging; Spinal cord; Myelin; Medicine; Neuroscience; Biomedical engineering; Pathology; Computer science; Radiology; Psychology; Central nervous system","score_opus":0.14215483030592915,"score_gpt":0.447487751245612,"score_spread":0.3053329209396829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795442880","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013546142,0.9979674,0.00049093895,0.000482019,0.00012323285,0.0000075691696,0.000027571305,0.000007570642,0.00075817585],"genre_scores_gemma":[0.0015213067,0.99627507,0.0010914055,0.00036344017,0.0003339403,0.000015962287,0.00005271925,0.000005522609,0.00034068341],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993538,0.00015192802,0.0001187919,0.00014124454,0.00019010538,0.000044112876],"domain_scores_gemma":[0.99599385,0.0026383179,0.0003634005,0.00012860604,0.0007915429,0.00008418778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003447873,0.0013342509,0.0018624169,0.0048224595,0.00030165736,0.0023781452,0.0017129455,0.002250321,0.0030281455],"category_scores_gemma":[0.0076671876,0.00058644806,0.0008347681,0.0031740903,0.0019384846,0.0027115224,0.0012204482,0.0017839175,0.0015120173],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008399695,0.000038390725,0.0006442184,0.020492284,0.00017114735,0.0002606126,0.000084601925,0.00046231603,0.0009082882,0.005966655,0.012230224,0.9586573],"study_design_scores_gemma":[0.00004531331,0.00018636184,0.0046548424,0.03926595,0.0009899581,0.0055940473,0.00027361693,0.0006520921,0.0027588462,0.019357458,0.92608947,0.00013214101],"about_ca_topic_score_codex":0.0044764136,"about_ca_topic_score_gemma":0.0064920294,"teacher_disagreement_score":0.0048224595,"about_ca_system_score_codex":0.0011639938,"about_ca_system_score_gemma":0.0044790134,"threshold_uncertainty_score":0.018234313},"labels":[],"label_agreement":null},{"id":"W2795505299","doi":"10.1101/277087","title":"Comparison of different methods for average anatomical templates creation: do we really gain anything from a diffeomorphic framework?","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Diffeomorphism; Computer science; Computation; Population; Template; Artificial intelligence; Mathematics; Algorithm; Pure mathematics; Medicine; Programming language","score_opus":0.06948087597698725,"score_gpt":0.39353280889160874,"score_spread":0.3240519329146215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795505299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0561658,0.0062044957,0.9285229,0.0005657385,0.00050672685,0.000409226,0.00048760363,0.0045071114,0.0026303853],"genre_scores_gemma":[0.27863494,0.0021830185,0.71261847,0.0002551337,0.0001726349,0.00028601073,0.0015236647,0.0026092012,0.0017169409],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9936394,0.002409315,0.00059159985,0.0011346337,0.0019667952,0.00025833328],"domain_scores_gemma":[0.9862555,0.006805373,0.0007919628,0.0031864808,0.002552857,0.00040790532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0107589895,0.0018244784,0.00159385,0.0035139471,0.0007684306,0.0027476156,0.0029253464,0.0018208459,0.004290316],"category_scores_gemma":[0.034352843,0.00071255735,0.002000343,0.0021164052,0.0009358538,0.0033082408,0.0024414314,0.0019613039,0.0020680153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014870069,0.00035604433,0.0056946347,0.0015205371,0.0015601491,0.00021116465,0.0004268785,0.08235094,0.021212412,0.015661798,0.009896759,0.8596216],"study_design_scores_gemma":[0.00032122197,0.0013409598,0.011899557,0.00061521126,0.0006160444,0.0020353345,0.00043798928,0.86689854,0.06743813,0.026342973,0.02174998,0.0003040006],"about_ca_topic_score_codex":0.0035271724,"about_ca_topic_score_gemma":0.0042932113,"teacher_disagreement_score":0.0107589895,"about_ca_system_score_codex":0.000735968,"about_ca_system_score_gemma":0.001487183,"threshold_uncertainty_score":0.056899667},"labels":[],"label_agreement":null},{"id":"W2795722583","doi":"10.1007/s00415-018-8846-3","title":"Alterations in white matter network topology contribute to freezing of gait in Parkinson’s disease","year":2018,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Western Sydney University; National Health and Medical Research Council; Parkinson Canada","keywords":"Connectome; White matter; Diffusion MRI; Neuroscience; Parkinson's disease; Modularity (biology); Psychology; Neuroradiology; Neurology; Gait; Disease; Medicine; Physical medicine and rehabilitation; Biology; Functional connectivity; Magnetic resonance imaging; Pathology","score_opus":0.030902479770605187,"score_gpt":0.3386517814299037,"score_spread":0.30774930165929854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795722583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99837625,0.00017993902,0.0010439713,0.000044448036,0.0000058859628,0.0000052253026,0.00009531596,0.000011011789,0.00023789084],"genre_scores_gemma":[0.99930656,0.00011053699,0.00036755993,0.000007835417,0.0000061591345,0.0000046463797,0.000087416025,0.0000027894912,0.00010655796],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992716,0.000020580359,0.000010390255,0.000016415559,0.000012112988,0.000013280253],"domain_scores_gemma":[0.99951935,0.000105649015,0.00025115904,0.000033605156,0.00004786935,0.000042345357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024225986,0.00026918846,0.0001846273,0.0006039934,0.00023630021,0.0004595899,0.00023929958,0.0002553609,0.00081100606],"category_scores_gemma":[0.0015012423,0.00022123978,0.00019138039,0.000399575,0.00031199117,0.0005323919,0.0003193144,0.00027129968,0.000071611605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022421123,0.00024396926,0.83991235,0.00019970365,0.0010911162,0.0031376847,0.00083140563,0.017123349,0.07523237,0.0012717886,0.00084490684,0.05786925],"study_design_scores_gemma":[0.000009482678,0.00012077312,0.9844647,0.000019845871,0.00010429798,0.0013289498,0.00019776863,0.009629599,0.0019513657,0.0019993384,0.00016135434,0.000012561214],"about_ca_topic_score_codex":0.0031387168,"about_ca_topic_score_gemma":0.00454825,"teacher_disagreement_score":0.0031387168,"about_ca_system_score_codex":0.0002593639,"about_ca_system_score_gemma":0.00013459894,"threshold_uncertainty_score":0.0062409043},"labels":[],"label_agreement":null},{"id":"W2797006568","doi":"","title":"Effects of Formalin Fixation on Myelin Water Fraction MRI Measurements in Human White Matter: a Novel Ex Vivo Study","year":2017,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Ex vivo; White matter; Fixation (population genetics); Myelin; Chemistry; Fraction (chemistry); Pathology; Biomedical engineering; Magnetic resonance imaging; Medicine; Chromatography; Internal medicine; Biochemistry; Central nervous system; In vitro; Radiology","score_opus":0.07328939495328274,"score_gpt":0.3671232300828864,"score_spread":0.29383383512960365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797006568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895858,0.0018910435,0.0076894904,0.000058694113,0.000055340835,0.000044412725,0.000107814034,0.00002642452,0.00054098247],"genre_scores_gemma":[0.9934057,0.0016277188,0.0035634215,0.000068694084,0.00004224519,0.00004690189,0.00013844702,0.000035114426,0.0010715573],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998166,0.000059647296,0.000014605898,0.000054015833,0.000026647216,0.000028379747],"domain_scores_gemma":[0.99942964,0.0002678752,0.00009487401,0.00011130892,0.00006735741,0.000028977853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057627086,0.00057062646,0.00022115413,0.0002113309,0.00035078154,0.00028372862,0.00034429083,0.0005499405,0.0014741268],"category_scores_gemma":[0.0010447811,0.0003103861,0.00025972372,0.00016532345,0.00067220547,0.000631752,0.00035145032,0.00034664333,0.00027983668],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002700153,0.00014292775,0.00081808504,0.00006355907,0.000022055014,0.00013626482,0.000102966136,0.00011571871,0.9930227,0.000033982582,0.000028839628,0.00281272],"study_design_scores_gemma":[0.000102264814,0.0068319375,0.018700149,0.000021961436,0.00022942293,0.0011993573,0.00024071812,0.0015231726,0.97014004,0.00012382849,0.0008578364,0.0000293052],"about_ca_topic_score_codex":0.0009389074,"about_ca_topic_score_gemma":0.0011759789,"teacher_disagreement_score":0.0014741268,"about_ca_system_score_codex":0.00013817698,"about_ca_system_score_gemma":0.00021999324,"threshold_uncertainty_score":0.0049313903},"labels":[],"label_agreement":null},{"id":"W2797202872","doi":"10.1016/j.biopsych.2018.02.679","title":"F66. The Effect of Traumatic Brain Injury on Superficial White Matter in Youth: Towards a Personalized Injury Profile","year":2018,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; SickKids Foundation; Hospital for Sick Children; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"White matter; Traumatic brain injury; Diffusion MRI; Medicine; Cortex (anatomy); Neuroscience; Cerebral cortex; Psychology; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.06872475749452366,"score_gpt":0.3769164492771213,"score_spread":0.30819169178259764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797202872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8148949,0.014010212,0.0076796617,0.051098697,0.002535832,0.0003232839,0.015589219,0.00025907182,0.09360918],"genre_scores_gemma":[0.95980275,0.005713518,0.0049636355,0.007318895,0.0016008224,0.000094948395,0.003361268,0.00005319036,0.01709104],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998332,0.000033305227,0.000020164953,0.000021499161,0.00005842345,0.000033362856],"domain_scores_gemma":[0.99929214,0.0001671212,0.000157558,0.000025227171,0.00023953988,0.00011828356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006940441,0.0001797042,0.00018558885,0.00042610936,0.00039511916,0.00035183734,0.00019510405,0.00088488834,0.008145667],"category_scores_gemma":[0.0027969263,0.00005133421,0.0003763671,0.0004314974,0.00018117833,0.00042282016,0.00027787965,0.00033548207,0.00129847],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018317293,0.00034404738,0.4665337,0.00096620223,0.00037146115,0.0032494634,0.00075428886,0.0006918689,0.0057992563,0.0037999984,0.06529561,0.4503623],"study_design_scores_gemma":[0.00004931379,0.000479504,0.96733475,0.00055119663,0.00024805815,0.003716356,0.00023463351,0.00027656235,0.0013649301,0.0026912529,0.023027975,0.000025447727],"about_ca_topic_score_codex":0.006898988,"about_ca_topic_score_gemma":0.012602916,"teacher_disagreement_score":0.008145667,"about_ca_system_score_codex":0.00034077422,"about_ca_system_score_gemma":0.0007608178,"threshold_uncertainty_score":0.027249932},"labels":[],"label_agreement":null},{"id":"W2797379939","doi":"10.1016/j.biopsych.2018.02.845","title":"F231. Microstructural Changes in White Matter Associated With Alcohol Use in Early Phase Psychosis: A Diffusion Tensor Imaging (DTI) and Relaxometry Study","year":2018,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Psychosis; Relaxometry; Psychology; Medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.07058778630286348,"score_gpt":0.36415259528452115,"score_spread":0.29356480898165765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797379939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99905723,0.000059729056,0.00008613297,0.000048600705,0.000006341602,0.000014381132,0.00012552753,0.0000026773914,0.0005994233],"genre_scores_gemma":[0.9986093,0.000050976,0.00010158781,0.000042223608,0.000011508831,0.000010436066,0.00013454862,0.000006246452,0.0010330412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999261,0.000012569174,0.0000062601425,0.000018227689,0.000015324651,0.000021437689],"domain_scores_gemma":[0.9997187,0.000043288906,0.00008365612,0.000012519031,0.00004235489,0.00009945691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025177805,0.00039891654,0.00024093514,0.00048472104,0.0007646475,0.0002929854,0.00028135674,0.00045821702,0.0042850897],"category_scores_gemma":[0.00061034213,0.0002459344,0.00029068667,0.000398148,0.0003311542,0.00029179206,0.0003199159,0.00045615237,0.0006546963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01319473,0.0031977503,0.73191667,0.00022084793,0.00037925548,0.04043206,0.0026030648,0.0003547649,0.18386286,0.00047168173,0.001097811,0.02226856],"study_design_scores_gemma":[0.000062763254,0.0010682347,0.98846185,0.000011582353,0.00005999258,0.007070516,0.00033438252,0.00023051874,0.0020840466,0.00009209681,0.0005090657,0.000015015648],"about_ca_topic_score_codex":0.013748825,"about_ca_topic_score_gemma":0.008192806,"teacher_disagreement_score":0.013748825,"about_ca_system_score_codex":0.00034679094,"about_ca_system_score_gemma":0.00031234056,"threshold_uncertainty_score":0.02733761},"labels":[],"label_agreement":null},{"id":"W2797747717","doi":"10.1101/300806","title":"The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in <i>Nrxn2</i> deletion mice","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Biotechnology and Biological Sciences Research Council; National Institutes of Health; Innovative Medicines Initiative; European Commission; University of Leeds; Alzheimer's Society; Medical Research Council; European Federation of Pharmaceutical Industries and Associations; British Pharmacological Society; International Seafood Sustainability Foundation; Wellcome Trust","keywords":"Orbitofrontal cortex; Diffusion MRI; Anterior cingulate cortex; Amygdala; Fractional anisotropy; Thalamus; Cortex (anatomy); Hippocampus; Cingulate cortex","score_opus":0.02203914396760065,"score_gpt":0.2819932292458216,"score_spread":0.25995408527822095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797747717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97530997,0.00028818953,0.020715818,0.00022451632,0.000044079756,0.00007223094,0.0017151355,0.0005299824,0.001100095],"genre_scores_gemma":[0.93594193,0.00067833153,0.052473497,0.00024873376,0.000037167392,0.0004324145,0.001975222,0.0008937349,0.0073190117],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995704,0.00005240528,0.000040801133,0.00018691641,0.00008820091,0.000061296276],"domain_scores_gemma":[0.99900013,0.00009777249,0.00051841524,0.00010316793,0.00009871748,0.00018180939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075280305,0.00097295915,0.0005688147,0.0012225943,0.00038105683,0.0006372809,0.00044200502,0.00062563404,0.0021547752],"category_scores_gemma":[0.000498272,0.0006321887,0.00054036995,0.0003182798,0.0010385618,0.00040409568,0.00059479306,0.0011607934,0.00030566962],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003044228,0.000060819042,0.0006447486,0.000036513407,0.00003905645,0.00014593042,0.00006888225,0.0002858321,0.9966427,0.00021393424,0.00012142813,0.0014356526],"study_design_scores_gemma":[0.00014922721,0.0018732722,0.091319755,0.000095419105,0.00035245577,0.0031674379,0.00029070518,0.010437782,0.8865654,0.0008781267,0.0047664484,0.00010398849],"about_ca_topic_score_codex":0.0023541488,"about_ca_topic_score_gemma":0.0047646444,"teacher_disagreement_score":0.0023541488,"about_ca_system_score_codex":0.0003975531,"about_ca_system_score_gemma":0.0003330326,"threshold_uncertainty_score":0.007208407},"labels":[],"label_agreement":null},{"id":"W2797939012","doi":"10.1016/j.patcog.2019.06.002","title":"White matter fiber analysis using kernel dictionary learning and sparsity priors","year":2019,"lang":"en","type":"preprint","venue":"Pattern Recognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Prior probability; occam; Streamlines, streaklines, and pathlines; Tractography; Human Connectome Project; Artificial intelligence; Computer science; Regularization (linguistics); Fiber bundle; Pattern recognition (psychology); Kernel (algebra); Set (abstract data type); Parallelizable manifold; Bundle; Machine learning; Diffusion MRI; Mathematics; Algorithm; Bayesian probability; Magnetic resonance imaging; Physics","score_opus":0.0824439340404125,"score_gpt":0.34516872211839905,"score_spread":0.26272478807798655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797939012","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033744017,0.00003891287,0.99604034,0.0000785474,0.000010444061,0.00000803757,0.000049206752,0.00014568833,0.0002544783],"genre_scores_gemma":[0.13982001,0.00035531406,0.85348535,0.00007094519,0.000065719854,0.000057933266,0.0005238587,0.00033872924,0.0052821063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978703,0.000059068767,0.000012673872,0.000058451962,0.00006332635,0.000019584631],"domain_scores_gemma":[0.999111,0.0003438883,0.00009834737,0.00020977511,0.00017901688,0.000057935154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079951546,0.00062050985,0.00072113145,0.0007253316,0.00026203814,0.0010459089,0.00078323984,0.0009418663,0.0020134759],"category_scores_gemma":[0.0033873194,0.0005655664,0.0007608856,0.0008333169,0.0006140048,0.0016457817,0.0013423427,0.0015092159,0.0009522738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034526622,0.00015424837,0.0022516784,0.00024724766,0.00022248937,0.00015370666,0.00018238481,0.42869234,0.04652448,0.11862154,0.009284296,0.39332032],"study_design_scores_gemma":[0.000011797457,0.000013508385,0.00023399826,0.0000064354767,0.000009183016,0.00004753922,0.000008703165,0.9716907,0.003134809,0.023751989,0.0010827433,0.000008494684],"about_ca_topic_score_codex":0.0032915557,"about_ca_topic_score_gemma":0.0038191734,"teacher_disagreement_score":0.0032915557,"about_ca_system_score_codex":0.00034617473,"about_ca_system_score_gemma":0.0010986128,"threshold_uncertainty_score":0.006735742},"labels":[],"label_agreement":null},{"id":"W2798240981","doi":"10.1016/j.mri.2018.04.001","title":"Effect of cardiac-related translational motion in diffusion MRI of the spinal cord","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation","keywords":"Diffusion MRI; Spinal cord; Imaging phantom; SIGNAL (programming language); Cord; Diffusion; Medicine; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Nuclear medicine; Computer science; Radiology; Surgery","score_opus":0.014704282529158853,"score_gpt":0.3213850486417121,"score_spread":0.30668076611255324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798240981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98378086,0.003595793,0.0098786615,0.00027751678,0.00011491168,0.000053068958,0.00017913713,0.00015452618,0.0019655884],"genre_scores_gemma":[0.9961093,0.000988848,0.0016506873,0.000100464,0.000068111534,0.000014291966,0.00013096367,0.000111667294,0.0008255921],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998348,0.00007239259,0.0000126674195,0.000022206843,0.000026166454,0.000031789332],"domain_scores_gemma":[0.99852484,0.0010794824,0.000120344026,0.00008153032,0.00008988765,0.000103980456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007415766,0.00038413788,0.00025178673,0.00033184065,0.00033416293,0.0006070331,0.0002566105,0.0005944938,0.0028683043],"category_scores_gemma":[0.00587258,0.00023238396,0.00024595036,0.00029754313,0.00044424908,0.000491299,0.00032930085,0.0005217601,0.00026443772],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006094488,0.00028708196,0.004490484,0.0004454566,0.00022146157,0.0014402036,0.00046192599,0.009311907,0.94756585,0.0007856662,0.00049097516,0.028404485],"study_design_scores_gemma":[0.00053990155,0.0059591066,0.25544053,0.00017827052,0.0016001364,0.0037418813,0.0004658261,0.07061973,0.6553337,0.0015123895,0.004467299,0.00014119853],"about_ca_topic_score_codex":0.002514832,"about_ca_topic_score_gemma":0.00248331,"teacher_disagreement_score":0.0028683043,"about_ca_system_score_codex":0.0002735289,"about_ca_system_score_gemma":0.00042173953,"threshold_uncertainty_score":0.009595394},"labels":[],"label_agreement":null},{"id":"W2798489997","doi":"10.1101/311050","title":"Physical activity predicts population-level age-related differences in frontal white matter","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Medical Research Council; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; European Commission; Wellcome Trust","keywords":"Fractional anisotropy; Internal capsule; White matter; Diffusion MRI; Corpus callosum; Uncinate fasciculus; Population; Psychology; Superior longitudinal fasciculus; Disconnection; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.04906034224454509,"score_gpt":0.29188653369696754,"score_spread":0.24282619145242246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798489997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988154,0.00017044494,0.00023530534,0.00003879553,0.000006185184,0.0000039741094,0.00035822834,0.0000069034154,0.00036473732],"genre_scores_gemma":[0.9992761,0.00007731068,0.00008840885,0.000013181834,0.0000076165124,0.0000040409122,0.0002650972,0.0000027856127,0.00026537318],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999861,0.00003519102,0.000012305131,0.000058770263,0.00001285836,0.00001991287],"domain_scores_gemma":[0.9992772,0.00012605642,0.00034523764,0.00010594726,0.000053109932,0.000092475224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004617348,0.00027068166,0.0002116481,0.00043742405,0.00019630669,0.00058446854,0.000182578,0.00051143,0.002022957],"category_scores_gemma":[0.0016249911,0.00015597315,0.00018806173,0.00040838245,0.00022177705,0.00033670102,0.00027587396,0.00030824606,0.00034234484],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020556072,0.000078184574,0.99535406,0.000013292994,0.0001480645,0.00006063368,0.00010319449,0.00011808469,0.0015415724,0.000050803774,0.00017779571,0.0021488413],"study_design_scores_gemma":[0.0000014833732,0.000026716703,0.9996295,0.0000015307919,0.000010993327,0.000047379413,0.000023646493,0.00009804546,0.000059458896,0.000045883222,0.00005433439,0.0000010563476],"about_ca_topic_score_codex":0.0025473237,"about_ca_topic_score_gemma":0.0032362938,"teacher_disagreement_score":0.0025473237,"about_ca_system_score_codex":0.00009360414,"about_ca_system_score_gemma":0.00006816198,"threshold_uncertainty_score":0.0067674518},"labels":[],"label_agreement":null},{"id":"W2800290738","doi":"10.2316/j.2010.216.680-0051","title":"Extraction of Human Heart Conduction Network from Diffusion Tensor MRI","year":2010,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Human heart; Diffusion; Extraction (chemistry); Tensor (intrinsic definition); Nuclear magnetic resonance; Thermal conduction; Computer science; Physics; Medicine; Cardiology; Mathematics; Chemistry; Radiology; Magnetic resonance imaging; Geometry; Chromatography; Thermodynamics","score_opus":0.027360868665930637,"score_gpt":0.32170254667316617,"score_spread":0.29434167800723554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800290738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23118596,0.003233303,0.7558388,0.000707567,0.00016561056,0.00021497185,0.0028325873,0.0023498265,0.0034714043],"genre_scores_gemma":[0.6745666,0.0035592937,0.31206182,0.00015034176,0.0002829825,0.00014686273,0.003003296,0.00030232058,0.00592655],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999392,0.000009349242,0.0000038573053,0.000021328682,0.000014052902,0.000012286534],"domain_scores_gemma":[0.9998323,0.000056073834,0.000025883994,0.00002752873,0.00004060064,0.000017530963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029650924,0.0006435196,0.00035346352,0.0011956237,0.00024119004,0.00055146695,0.0002911643,0.0006591301,0.0015327404],"category_scores_gemma":[0.001005539,0.00034171014,0.00048636872,0.00073375396,0.00019607416,0.0004346848,0.000247289,0.0005321304,0.0010033485],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004599667,0.00010920144,0.006825924,0.0004987653,0.00012797686,0.00092357036,0.00024072149,0.020998215,0.35110706,0.0025217258,0.006748835,0.609438],"study_design_scores_gemma":[0.00012426078,0.0003502001,0.10040088,0.00019829678,0.0004914544,0.006508165,0.00034056936,0.65507454,0.1965178,0.017488137,0.02237082,0.00013489641],"about_ca_topic_score_codex":0.0031752144,"about_ca_topic_score_gemma":0.0054508774,"teacher_disagreement_score":0.0031752144,"about_ca_system_score_codex":0.00015849606,"about_ca_system_score_gemma":0.00056628196,"threshold_uncertainty_score":0.006313503},"labels":[],"label_agreement":null},{"id":"W2800823087","doi":"10.1101/319863","title":"Superoanterior Fasciculus (SAF): Novel fiber tract revealed by diffusion MRI fiber tractography","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Arcuate fasciculus; Fractional anisotropy; White matter; Diffusion MRI; Fiber tract; Superior longitudinal fasciculus; Neuroscience; Inferior longitudinal fasciculus; Uncinate fasciculus; Artificial intelligence; Computer science; Anatomy; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.025978256114191342,"score_gpt":0.2760881515939531,"score_spread":0.25010989547976176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800823087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911011,0.00031654944,0.007583987,0.00003145652,0.0000067926803,0.000034879846,0.00053927815,0.000046744644,0.0003393668],"genre_scores_gemma":[0.992531,0.0001837794,0.0062470417,0.000011543964,0.000008431476,0.000029111223,0.00045018567,0.000021012667,0.0005180094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998493,0.000023434086,0.000016295337,0.00006182319,0.000025366457,0.000023734528],"domain_scores_gemma":[0.99942315,0.0001393174,0.00018789555,0.0001135003,0.000078752404,0.00005745172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006562321,0.00044703303,0.00034511252,0.0011580951,0.00038869437,0.0003503185,0.0001693087,0.00025551117,0.0023772956],"category_scores_gemma":[0.0012391325,0.00019951063,0.00032149907,0.0006088443,0.00051562116,0.00040534785,0.00033506379,0.0001769328,0.0003017569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025955224,0.00014638594,0.59988743,0.00042116933,0.00047229812,0.005107971,0.0016085011,0.0019154014,0.29580888,0.0014425856,0.0012110842,0.0893828],"study_design_scores_gemma":[0.000038082595,0.00037156555,0.9601121,0.000033008284,0.00015115833,0.008726588,0.00025234837,0.0044259597,0.022097722,0.0015182929,0.0022386066,0.000034509518],"about_ca_topic_score_codex":0.005267926,"about_ca_topic_score_gemma":0.011295821,"teacher_disagreement_score":0.005267926,"about_ca_system_score_codex":0.00024009032,"about_ca_system_score_gemma":0.00037473452,"threshold_uncertainty_score":0.010474503},"labels":[],"label_agreement":null},{"id":"W2801233903","doi":"10.1016/j.nicl.2018.04.029","title":"Connectome-derived diffusion characteristics of the fornix in Alzheimer's disease","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Health Canada; University of Oxford; Canadian Institutes of Health Research; National Institute for Health and Care Research; Massachusetts General Hospital; National Institutes of Health; Pfizer","keywords":"Fornix; Diffusion MRI; Hippocampus; Alzheimer's disease; Neuroscience; White matter; Temporal lobe; Psychology; Medicine; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.14411964394659818,"score_gpt":0.4306195358969989,"score_spread":0.2864998919504007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801233903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992119,0.00013333047,0.00045721015,0.000009664048,0.0000012650638,0.0000064068977,0.00007829839,0.000004569712,0.000097178316],"genre_scores_gemma":[0.9989236,0.00007327247,0.0007479251,0.000004760096,0.000003091979,0.000007741667,0.00015430458,0.0000036895176,0.00008155977],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986744,0.000032887485,0.000019878202,0.000042751333,0.000024217288,0.000012791661],"domain_scores_gemma":[0.99949265,0.00011204112,0.00022091123,0.000059114143,0.00007064115,0.000044646553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067172834,0.00034146802,0.0002930723,0.0010459203,0.00020796122,0.00038976176,0.00014310805,0.00034514215,0.00061478943],"category_scores_gemma":[0.0023453538,0.00014072841,0.00015741735,0.0004362928,0.00024754304,0.00048884,0.00031589405,0.00018282275,0.000089421024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010829434,0.00009318616,0.91093516,0.00014042002,0.00031720175,0.000589541,0.0019475367,0.0014392578,0.058720343,0.0002648045,0.00023548177,0.024234122],"study_design_scores_gemma":[0.000013801515,0.00009185049,0.9955219,0.000008009665,0.000029147728,0.0007981974,0.00018879725,0.00118726,0.00174128,0.0002613557,0.00014844678,0.000009907609],"about_ca_topic_score_codex":0.0028152918,"about_ca_topic_score_gemma":0.0055616065,"teacher_disagreement_score":0.0028152918,"about_ca_system_score_codex":0.00017949152,"about_ca_system_score_gemma":0.00011716119,"threshold_uncertainty_score":0.00559783},"labels":[],"label_agreement":null},{"id":"W2801394998","doi":"10.1093/cercor/bhy074","title":"Mapping Cortical Laminar Structure in the 3D BigBrain","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Wellcome Trust","keywords":"Cytoarchitecture; Laminar flow; Laminar organization; Neuroimaging; White matter; Anatomy; Neuroscience; Cerebral cortex; Cortex (anatomy); Geology; Computer science; Biology; Physics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.05488904631452847,"score_gpt":0.34345049515007975,"score_spread":0.2885614488355513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801394998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6013419,0.00038807202,0.3952585,0.000065583714,0.000017539274,0.00006242943,0.0004715138,0.0010668302,0.001327707],"genre_scores_gemma":[0.7115916,0.00045293514,0.28636506,0.000040117095,0.0000074166073,0.000101122016,0.000526196,0.00019698928,0.00071854284],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99990666,0.000013718387,0.000006880188,0.000021103911,0.000040145504,0.000011443922],"domain_scores_gemma":[0.9997682,0.00007241759,0.000051641426,0.000042139898,0.00005194812,0.0000136933795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002629338,0.00026864494,0.00017001484,0.0010666557,0.0001886535,0.0007938467,0.00023435602,0.00024797558,0.00058494613],"category_scores_gemma":[0.0006402654,0.00033976385,0.00026163147,0.00031843034,0.00040901906,0.00037310866,0.0004911689,0.00026988954,0.00022748084],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012217928,0.00003539046,0.019499592,0.00023039569,0.00008897645,0.0003444038,0.0008259502,0.02692828,0.85603744,0.0034761648,0.00044420903,0.09196705],"study_design_scores_gemma":[0.000022085338,0.00016716031,0.28868553,0.0000993421,0.00009870729,0.0022368266,0.0006494942,0.28375313,0.4047179,0.010623577,0.008794779,0.00015143298],"about_ca_topic_score_codex":0.0020504293,"about_ca_topic_score_gemma":0.006044144,"teacher_disagreement_score":0.0020504293,"about_ca_system_score_codex":0.0002340144,"about_ca_system_score_gemma":0.00062974903,"threshold_uncertainty_score":0.0040769577},"labels":[],"label_agreement":null},{"id":"W2802026893","doi":"10.1007/s11682-018-9873-5","title":"DTI-derived indexes of brain WM correlate with cognitive performance in vascular MCI and small-vessel disease. A TBSS study","year":2018,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Regione Toscana","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Psychology; Corpus callosum; Cognition; Audiology; Cardiology; Neuroscience; Medicine; Magnetic resonance imaging; Cognitive impairment; Radiology","score_opus":0.036890063358661566,"score_gpt":0.3254143038895997,"score_spread":0.2885242405309381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802026893","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99903214,0.00019706195,0.00015036127,0.0000149624375,0.0000051174115,0.000005171225,0.00017285939,0.0000040310047,0.00041824218],"genre_scores_gemma":[0.99939215,0.000056382727,0.00014265598,0.0000065126537,0.000008323459,0.000003820571,0.000213652,0.0000028775996,0.00017353774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998745,0.000025707417,0.000018420755,0.000032012256,0.000027764976,0.000021578395],"domain_scores_gemma":[0.99929893,0.00012593035,0.0002383945,0.00012954326,0.000096010925,0.00011118827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085806916,0.0006233402,0.0002444257,0.001045608,0.00024908833,0.00063563394,0.00038836623,0.00037795646,0.0015217563],"category_scores_gemma":[0.0022596086,0.0002917681,0.00027669236,0.00077304227,0.00044647494,0.0005176214,0.0004362843,0.0004251802,0.0003675976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060556745,0.00045065492,0.94451797,0.000089830304,0.00090655294,0.0004885773,0.00073773356,0.00038275064,0.025475675,0.0004074379,0.00044293047,0.02004412],"study_design_scores_gemma":[0.00002054466,0.00027002778,0.9970728,0.00000658233,0.000106796586,0.0005113029,0.00013744114,0.00044399258,0.0009941823,0.00023727074,0.00019311362,0.0000058945698],"about_ca_topic_score_codex":0.003322469,"about_ca_topic_score_gemma":0.004004945,"teacher_disagreement_score":0.003322469,"about_ca_system_score_codex":0.0002699572,"about_ca_system_score_gemma":0.00023393633,"threshold_uncertainty_score":0.006606281},"labels":[],"label_agreement":null},{"id":"W2802608235","doi":"10.1002/hbm.24186","title":"Effects of<i>SYN1<sub>Q555X</sub></i>mutation on cortical gray matter microstructure","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université du Québec à Trois-Rivières; Philips (Canada); Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Savoy Foundation; Réseau en Bio-Imagerie du Quebec","keywords":"Fractional anisotropy; Diffusion MRI; Autism spectrum disorder; Psychology; Epilepsy; Nuclear magnetic resonance; Dyslexia; Autism; Connectome; Neuroscience; Medicine; Magnetic resonance imaging; Developmental psychology; Functional connectivity; Physics; Radiology","score_opus":0.02709015434167398,"score_gpt":0.32038294578242515,"score_spread":0.29329279144075115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802608235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997025,0.000025127347,0.00016748809,0.000004962967,8.0512785e-7,0.000003257765,0.000016904714,0.000005834769,0.00007304492],"genre_scores_gemma":[0.9997509,0.000012573877,0.00015989078,0.0000043264195,9.632212e-7,0.000002909941,0.000016272768,0.000004078984,0.000048194623],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998204,0.00004459995,0.000016268887,0.000055419794,0.000037420883,0.000025940275],"domain_scores_gemma":[0.99965763,0.000111593035,0.00010589021,0.000030936124,0.00004118608,0.000052625222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030603382,0.00051826175,0.00024971704,0.0005165467,0.00021951823,0.00019720683,0.00013041825,0.000334884,0.0009720303],"category_scores_gemma":[0.0005965951,0.00015767934,0.00024385493,0.00011663672,0.00060511066,0.0001511546,0.0002751941,0.00016202495,0.000059820974],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013899592,0.00012508435,0.042783402,0.000029783667,0.00011979649,0.0028734342,0.00027882063,0.00054228294,0.9466911,0.00008035044,0.000052151863,0.0050338325],"study_design_scores_gemma":[0.0000758115,0.0035088249,0.8077902,0.000011222002,0.0002554043,0.008602034,0.00031586233,0.003294283,0.17565191,0.00016574602,0.00030095273,0.000027751952],"about_ca_topic_score_codex":0.0017819267,"about_ca_topic_score_gemma":0.0014793152,"teacher_disagreement_score":0.0017819267,"about_ca_system_score_codex":0.000180753,"about_ca_system_score_gemma":0.000098666984,"threshold_uncertainty_score":0.0035431385},"labels":[],"label_agreement":null},{"id":"W2802754793","doi":"10.1161/str.49.suppl_1.wmp16","title":"Abstract WMP16: Elevated Cerebral Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Values Are Associated With Poor Neurologic Outcome in Comatose Cardiac Arrest Patients","year":2018,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Kurtosis; Coma (optics); Cardiology; Anesthesia; Internal medicine; Nuclear medicine; Magnetic resonance imaging; Radiology; Physics","score_opus":0.02124783518267544,"score_gpt":0.2911026425681579,"score_spread":0.26985480738548245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802754793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996648,0.000047436923,0.000044028155,0.000016643527,0.0000022241836,0.0000033683446,0.0000774873,0.0000021938854,0.00014176263],"genre_scores_gemma":[0.9996284,0.000023016237,0.0000519746,0.000008001057,0.000007691672,0.0000046442874,0.00015740342,0.000001488963,0.00011722736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999076,0.000012261448,0.000019842671,0.000025395142,0.00001579469,0.00001903783],"domain_scores_gemma":[0.999052,0.00008011729,0.0006092913,0.000032694086,0.000079796264,0.0001460862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002083071,0.0004906808,0.0002726356,0.00068038114,0.0003969203,0.00039521503,0.00020357268,0.0003421179,0.0031976115],"category_scores_gemma":[0.00094041636,0.00013955169,0.0002033364,0.00042062954,0.00036273611,0.00028396538,0.00035520302,0.0003071252,0.0003467519],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005801761,0.00006220148,0.9912724,0.000021863172,0.0000671504,0.0011511,0.00008950275,0.000072025236,0.004779352,0.000029646504,0.00013136519,0.0017432187],"study_design_scores_gemma":[0.000010972143,0.00017262652,0.99667525,0.0000071215127,0.000019088733,0.0023657356,0.00010973028,0.000137588,0.00037625694,0.00004768937,0.00007424467,0.0000036587364],"about_ca_topic_score_codex":0.0011066045,"about_ca_topic_score_gemma":0.0009266219,"teacher_disagreement_score":0.0031976115,"about_ca_system_score_codex":0.00019921789,"about_ca_system_score_gemma":0.00018852079,"threshold_uncertainty_score":0.010697067},"labels":[],"label_agreement":null},{"id":"W2803132175","doi":"10.1097/md.0000000000010858","title":"Cortical thickness contributes to cognitive heterogeneity in patients with type 2 diabetes mellitus","year":2018,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Medicine; Parahippocampal gyrus; Gyrus; Posterior cingulate; Middle frontal gyrus; Magnetic resonance imaging; Cardiology; Internal medicine; Temporal lobe; Cognition; Radiology; Psychiatry","score_opus":0.03729879803978029,"score_gpt":0.3477954183252305,"score_spread":0.31049662028545016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803132175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988379,0.0005328981,0.00009586437,0.00003547594,0.000007218656,0.00000614873,0.000087850196,0.0000048796196,0.0003917573],"genre_scores_gemma":[0.9995441,0.00014427459,0.00008159471,0.000016500819,0.000017985984,0.000003900272,0.000096542106,0.0000018286869,0.00009328153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997409,0.000057743026,0.000042608805,0.00006770515,0.000053665837,0.00003731019],"domain_scores_gemma":[0.99900395,0.00019338768,0.00056298537,0.000063455016,0.0000762271,0.0001000953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004013574,0.00060475577,0.0004462337,0.0014521928,0.00042744822,0.0007018841,0.00033841483,0.00041251862,0.001396828],"category_scores_gemma":[0.0018229003,0.0002619964,0.0004458648,0.0010991812,0.0002882017,0.0003490725,0.00045244806,0.00049949007,0.0001450238],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006805878,0.00006307266,0.990873,0.00003386542,0.00028281554,0.0013061803,0.00017247755,0.0001284321,0.0014893571,0.00003671982,0.00010063511,0.004832895],"study_design_scores_gemma":[0.000007842876,0.000055997745,0.9981785,0.000005920384,0.00005552415,0.0011746937,0.00010349087,0.00015124555,0.00012806758,0.000067721805,0.00006647703,0.0000045106876],"about_ca_topic_score_codex":0.0024902828,"about_ca_topic_score_gemma":0.0025341264,"teacher_disagreement_score":0.0024902828,"about_ca_system_score_codex":0.00019971369,"about_ca_system_score_gemma":0.00014473425,"threshold_uncertainty_score":0.0049515963},"labels":[],"label_agreement":null},{"id":"W2803143819","doi":"10.1186/s12888-018-1678-y","title":"Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy","year":2018,"lang":"en","type":"article","venue":"BMC Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Institute of Mental Health; National Institutes of Health; Otto von Guericke University Magdeburg; Grantová Agentura České Republiky; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Fractional anisotropy; Support vector machine; White matter; Artificial intelligence; Diffusion MRI; Machine learning; Voxel; Psychology; Medicine; Internal medicine; Psychiatry; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.031311570315625106,"score_gpt":0.32043863614544926,"score_spread":0.28912706582982417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803143819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99757534,0.00010500682,0.0020738228,0.000029178756,0.000009618775,0.000016231195,0.000066950335,0.00003213945,0.00009170945],"genre_scores_gemma":[0.99834144,0.000024075884,0.0014004534,0.000006451221,0.0000049107466,0.000008744365,0.00016007779,0.00000277115,0.000051171886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959224,0.00012433043,0.000055434102,0.0001232487,0.000048138194,0.000056585046],"domain_scores_gemma":[0.99896777,0.0005255351,0.00020588622,0.000108017644,0.000112739544,0.00008003593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001910817,0.0004828267,0.00045466315,0.00095447706,0.00022924645,0.00059689145,0.00022957587,0.0004880069,0.00084748986],"category_scores_gemma":[0.003920443,0.00010158865,0.00043255166,0.00022106158,0.0003110663,0.00023285439,0.0002606413,0.00029663678,0.00015024444],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050963117,0.00069676654,0.79555535,0.00014062934,0.0008383563,0.00038463657,0.00044226457,0.01330009,0.056149613,0.00039863776,0.00084395637,0.12615335],"study_design_scores_gemma":[0.00015703011,0.001503325,0.7766509,0.000048334674,0.00022063656,0.00072814967,0.0003487683,0.20300323,0.015679749,0.0012164363,0.00039767628,0.000045794477],"about_ca_topic_score_codex":0.0028198147,"about_ca_topic_score_gemma":0.0017879527,"teacher_disagreement_score":0.0028198147,"about_ca_system_score_codex":0.00044684962,"about_ca_system_score_gemma":0.0002889415,"threshold_uncertainty_score":0.010105491},"labels":[],"label_agreement":null},{"id":"W2803268487","doi":"10.1002/brb3.1010","title":"Altered white matter connectivity associated with visual hallucinations following occipital stroke","year":2018,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"White matter; Neuroscience; Visual cortex; Diffusion MRI; Tractography; Psychology; Visual system; Occipital lobe; Visual Hallucination; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.040264455028883525,"score_gpt":0.3596213435639656,"score_spread":0.31935688853508204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803268487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993437,0.000072840296,0.00029644577,0.000033727472,9.985004e-7,0.000004752262,0.000025570323,0.0000057326665,0.0002162039],"genre_scores_gemma":[0.9997271,0.00005741945,0.00008441392,0.000006063057,0.0000037356012,0.0000023816272,0.000047629143,0.0000015090429,0.00006987789],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993706,0.000006893401,0.0000070045944,0.0000151436525,0.000012459585,0.00002131288],"domain_scores_gemma":[0.9995813,0.00005324397,0.00026728425,0.000020532254,0.000024090568,0.000053610263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011529331,0.00025519784,0.00015703941,0.0005165115,0.0003093082,0.0002657548,0.00016262455,0.00024450495,0.0009083923],"category_scores_gemma":[0.0006817556,0.00013447308,0.0001200103,0.000313025,0.00047699417,0.00029330797,0.00029702813,0.00022273234,0.00011867634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020581535,0.00017146906,0.6910346,0.00017700184,0.00021295532,0.09341385,0.0020917635,0.0016119069,0.17592995,0.00041570317,0.00043251566,0.03245021],"study_design_scores_gemma":[0.000016870094,0.00034737858,0.9240327,0.00001258552,0.000045003006,0.06779256,0.00037576756,0.0011897938,0.005528701,0.00040787066,0.0002358351,0.000015001409],"about_ca_topic_score_codex":0.0018843102,"about_ca_topic_score_gemma":0.0022970526,"teacher_disagreement_score":0.0018843102,"about_ca_system_score_codex":0.00028268527,"about_ca_system_score_gemma":0.00014401742,"threshold_uncertainty_score":0.0037466288},"labels":[],"label_agreement":null},{"id":"W2803916235","doi":"10.1016/j.neuroimage.2018.05.047","title":"Microstructural imaging of the human brain with a ‘super-scanner’: 10 key advantages of ultra-strong gradients for diffusion MRI","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":206,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Medical Research Council Canada; Wellcome Trust; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Cancer Research UK","keywords":"Diffusion MRI; Scanner; Diffusion; Tractography; Materials science; Anisotropic diffusion; Computer science; Biomedical engineering; Nuclear magnetic resonance; Anisotropy; Magnetic resonance imaging; Artificial intelligence; Optics; Physics; Radiology; Medicine","score_opus":0.051943621094670954,"score_gpt":0.3765746836947506,"score_spread":0.3246310626000797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803916235","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012285798,0.9981781,0.00052403286,0.00038050357,0.00013972788,0.0000037082102,0.000014621552,0.00001040531,0.00062610616],"genre_scores_gemma":[0.0009749751,0.9970349,0.0009791019,0.00027689547,0.0003627045,0.000006977381,0.00002963548,0.000006158445,0.0003287011],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997025,0.00005510938,0.00003926384,0.00005681408,0.000118773074,0.000027460032],"domain_scores_gemma":[0.99888116,0.0006903923,0.00010485768,0.000036910802,0.00023479962,0.00005178638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013418384,0.0012220267,0.0013682565,0.0029472287,0.0002523984,0.0015707982,0.0013783218,0.0019191745,0.0018774191],"category_scores_gemma":[0.0015805855,0.0005079272,0.0005597496,0.002422213,0.0013665004,0.0030101931,0.0011689796,0.0027417461,0.0014100033],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007569559,0.000051653886,0.00021799134,0.017994702,0.00009998758,0.00021790114,0.0000825859,0.00035201435,0.0045051887,0.007713877,0.019718045,0.9489703],"study_design_scores_gemma":[0.000020532545,0.00011452473,0.0015408562,0.0041093617,0.00017305983,0.0032520795,0.00008953327,0.00032169957,0.003299352,0.0077313604,0.97927296,0.00007470532],"about_ca_topic_score_codex":0.0013713517,"about_ca_topic_score_gemma":0.0024825518,"teacher_disagreement_score":0.0029472287,"about_ca_system_score_codex":0.0005852551,"about_ca_system_score_gemma":0.0015374194,"threshold_uncertainty_score":0.00709641},"labels":[],"label_agreement":null},{"id":"W2804787479","doi":"10.1038/s41593-019-0379-2","title":"The spatial correspondence and genetic influence of interhemispheric connectivity with white matter microstructure","year":2019,"lang":"en","type":"article","venue":"Nature Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Wellcome Trust","keywords":"White matter; Functional connectivity; Neuroscience; Diffusion MRI; Genome-wide association study; Multivariate statistics; Biobank; Microstructure; Biology; Psychology; Magnetic resonance imaging; Genetics; Computer science; Medicine; Gene; Single-nucleotide polymorphism; Genotype","score_opus":0.006549790310904288,"score_gpt":0.2794167238913519,"score_spread":0.2728669335804476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804787479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970823,0.00014221216,0.0017390375,0.00011024259,0.000010647192,0.0000039367983,0.00025748886,0.000017991219,0.000636118],"genre_scores_gemma":[0.99857426,0.000068222675,0.0008678931,0.000019857112,0.00001192547,0.000005353243,0.00006301923,0.000032805227,0.00035675],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99899906,0.00033447644,0.000071186914,0.00036315143,0.00014778334,0.00008430452],"domain_scores_gemma":[0.9977398,0.00095688226,0.0006624184,0.00036685122,0.00013527767,0.00013882661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085661083,0.00036283248,0.00022669208,0.00096407253,0.00032141633,0.0005157047,0.00044959973,0.0005105048,0.002021322],"category_scores_gemma":[0.0026103922,0.00035533003,0.00035912977,0.0008626838,0.0007233232,0.00048030363,0.00051378016,0.0005746656,0.00015442462],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020650106,0.00020210422,0.5546642,0.000104051396,0.0022598645,0.0022043844,0.0014342698,0.0047205095,0.39288485,0.00957603,0.0009625706,0.028922176],"study_design_scores_gemma":[0.000017745428,0.000068209025,0.9860554,0.000011493063,0.0001883466,0.00082401396,0.00013015395,0.0030806412,0.0071788407,0.0020240038,0.00039521276,0.000026028829],"about_ca_topic_score_codex":0.004354571,"about_ca_topic_score_gemma":0.0053530624,"teacher_disagreement_score":0.004354571,"about_ca_system_score_codex":0.00025221487,"about_ca_system_score_gemma":0.00027483096,"threshold_uncertainty_score":0.008658469},"labels":[],"label_agreement":null},{"id":"W2805168298","doi":"10.1101/342436","title":"Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer’s Disease","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; University of Cape Town; Alzheimer's Disease Neuroimaging Initiative; Organization for Women in Science for the Developing World; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; University of Southern California; F. Hoffmann-La Roche; Styrelsen för Internationellt Utvecklingssamarbete; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Genome-wide association study; Neuroimaging; Disease; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Genetic association; Single-nucleotide polymorphism; Imaging genetics; Neuroscience; Biology; Computational biology; Medicine; Gene; Genetics; Genotype; Pathology","score_opus":0.06245420533810141,"score_gpt":0.31945832743342933,"score_spread":0.2570041220953279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805168298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99655294,0.00029960932,0.001490447,0.00024613456,0.000019791645,0.0000076132633,0.001006967,0.00003056831,0.00034598203],"genre_scores_gemma":[0.99793386,0.0000838396,0.0011432511,0.00003408847,0.00001803838,0.000011842411,0.000636359,0.000012344519,0.00012630725],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988794,0.00045067412,0.00007486134,0.000405692,0.00010585672,0.00008354644],"domain_scores_gemma":[0.9964741,0.0016564172,0.0008294048,0.0005068902,0.00020635725,0.00032687705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019667812,0.0003536233,0.00043666395,0.001029902,0.0005200102,0.0005376191,0.00037113202,0.0005244506,0.0025181992],"category_scores_gemma":[0.0046540694,0.00022964198,0.0007423529,0.001549191,0.00047607208,0.00027711003,0.00047593823,0.0008216892,0.00014431738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083432224,0.00016256329,0.9778177,0.00004391811,0.0029582328,0.0004756133,0.00015802658,0.0008355597,0.010986284,0.0005711798,0.0006870092,0.0044696294],"study_design_scores_gemma":[0.000030472384,0.00008946335,0.99654275,0.0000057137268,0.00033468113,0.0002719517,0.00004247177,0.0012616469,0.0006018059,0.00046427516,0.00034647397,0.000008084757],"about_ca_topic_score_codex":0.0035144612,"about_ca_topic_score_gemma":0.004528112,"teacher_disagreement_score":0.0035144612,"about_ca_system_score_codex":0.00021177669,"about_ca_system_score_gemma":0.00037148566,"threshold_uncertainty_score":0.010401428},"labels":[],"label_agreement":null},{"id":"W2805311321","doi":"10.1016/j.neuroimage.2018.05.077","title":"A supervised learning approach for diffusion MRI quality control with minimal training data","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; EPSRC Centre for Doctoral Training in Medical Imaging; NIH Blueprint for Neuroscience Research; Medical Research Council; Seventh Framework Programme; Medical Research Council Canada; McDonnell Center for Systems Neuroscience; Leverhulme Trust; European Research Council; National Institutes of Health; Royal Academy of Engineering; Engineering and Physical Sciences Research Council; University of Washington","keywords":"Computer science; Artificial intelligence; Classifier (UML); Machine learning; Convolutional neural network; Calibration; Process (computing); Pattern recognition (psychology); Data mining; Mathematics","score_opus":0.2173156371708592,"score_gpt":0.4026729381350168,"score_spread":0.18535730096415762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805311321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009368519,0.00018887297,0.9886065,0.00012089426,0.00002517262,0.000105096384,0.00007511895,0.0010199118,0.00048998825],"genre_scores_gemma":[0.29658943,0.0002530077,0.6971452,0.0002990455,0.00015653949,0.0005773388,0.00096112344,0.0003215718,0.0036967392],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974015,0.0008496859,0.00018077664,0.00080188975,0.00063208124,0.00013416383],"domain_scores_gemma":[0.9942194,0.00255066,0.00061024446,0.0009241473,0.0015661855,0.00012923927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004950755,0.0010768863,0.0012140631,0.0010557852,0.00071362226,0.0009699672,0.0023846782,0.0016224125,0.0014472606],"category_scores_gemma":[0.010393036,0.00060644175,0.0009877839,0.0008376274,0.0011173008,0.0010175325,0.0015055606,0.002123468,0.0007180876],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004839796,0.00041178355,0.002502356,0.00034615916,0.000259978,0.00019694795,0.00021276413,0.31093153,0.022937236,0.009145346,0.0064086127,0.6461634],"study_design_scores_gemma":[0.000022397027,0.00012762751,0.00060115336,0.000014884053,0.000021237482,0.00006998755,0.000013071636,0.9878539,0.004411282,0.0055514444,0.0012945334,0.000018434312],"about_ca_topic_score_codex":0.0040251403,"about_ca_topic_score_gemma":0.005273016,"teacher_disagreement_score":0.004950755,"about_ca_system_score_codex":0.0011731683,"about_ca_system_score_gemma":0.0018410296,"threshold_uncertainty_score":0.026182473},"labels":[],"label_agreement":null},{"id":"W2805625726","doi":"10.1109/isbi.2018.8363534","title":"Connectome priors in deep neural networks to predict autism","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Connectome; Computer science; Prior probability; Regularization (linguistics); Artificial intelligence; Connectomics; Autism; Artificial neural network; Human Connectome Project; Deep learning; Machine learning; Pattern recognition (psychology); Functional connectivity; Neuroscience; Psychology; Bayesian probability","score_opus":0.040013126448416224,"score_gpt":0.35073741450536466,"score_spread":0.31072428805694846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805625726","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11728172,0.000724611,0.87646145,0.0011434099,0.0000625014,0.000058704158,0.0006853005,0.0017707936,0.0018114792],"genre_scores_gemma":[0.7759468,0.0005021553,0.21736036,0.00038765545,0.00008893422,0.0002104315,0.0017769228,0.00022457878,0.0035022805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961156,0.00012695944,0.000018096334,0.000108684915,0.000099452795,0.000035160272],"domain_scores_gemma":[0.9992192,0.00039953555,0.00012548096,0.00009837669,0.00011077214,0.00004663581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012121905,0.001077384,0.00058841915,0.0010808392,0.00035961097,0.000550486,0.0012165688,0.0014515104,0.0013777877],"category_scores_gemma":[0.0048896265,0.00055512163,0.0006164531,0.0005316546,0.00071894075,0.0014000249,0.0015450234,0.0019301617,0.00041157118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033955023,0.00016933984,0.007974617,0.000119046745,0.00018008913,0.0002299944,0.000115540315,0.8458515,0.015374049,0.020834615,0.0060800062,0.10273158],"study_design_scores_gemma":[0.000014300588,0.000023380775,0.0010374197,0.00001661467,0.000015494003,0.000057577316,0.0000068643244,0.98307854,0.0026511783,0.012364396,0.0007227349,0.000011532541],"about_ca_topic_score_codex":0.0034579544,"about_ca_topic_score_gemma":0.007528221,"teacher_disagreement_score":0.0034579544,"about_ca_system_score_codex":0.00077793404,"about_ca_system_score_gemma":0.00085086847,"threshold_uncertainty_score":0.006875694},"labels":[],"label_agreement":null},{"id":"W2805700032","doi":"10.1038/s41598-018-26627-7","title":"Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Office of AIDS Research; National Institute of Allergy and Infectious Diseases; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; University of Alabama; Center for AIDS Research, University of Washington; National Institutes of Health; International AIDS Society; University of Alabama at Birmingham","keywords":"Confounding; Artificial intelligence; Functional magnetic resonance imaging; Machine learning; Cohort; Diffusion MRI; Magnetic resonance imaging; Psychology; Computer science; Medicine; Neuroscience; Pathology","score_opus":0.09894950361852398,"score_gpt":0.36577180731774067,"score_spread":0.26682230369921667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805700032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98783034,0.00018813564,0.011211231,0.0000698875,0.000007661543,0.000016585622,0.0003389506,0.000044427223,0.00029270336],"genre_scores_gemma":[0.99098223,0.00009540811,0.0082078865,0.000016706053,0.0000056131335,0.000020924652,0.0005367543,0.000012968494,0.00012146954],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994386,0.00024312297,0.00003749982,0.00017286146,0.00006268974,0.00004521392],"domain_scores_gemma":[0.99853206,0.0005899662,0.00035985993,0.00034344624,0.00012838581,0.00004629596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018271732,0.0003858723,0.00031620078,0.0008315353,0.00025531198,0.0003981233,0.00024528714,0.00023454025,0.0004826574],"category_scores_gemma":[0.004532025,0.00015024873,0.0005523428,0.00045914788,0.0004182471,0.0004004742,0.0005564131,0.00041471698,0.00009001743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044959024,0.00012151405,0.8802219,0.000103340084,0.0005290036,0.00014221139,0.00040363258,0.006109242,0.01507983,0.00088182447,0.0006566939,0.09530126],"study_design_scores_gemma":[0.000012700071,0.0002473914,0.9465282,0.00003359023,0.00024053258,0.0003541259,0.00028069768,0.03991753,0.008637209,0.0024248222,0.0013076202,0.00001546798],"about_ca_topic_score_codex":0.005334014,"about_ca_topic_score_gemma":0.014769587,"teacher_disagreement_score":0.005334014,"about_ca_system_score_codex":0.00025503148,"about_ca_system_score_gemma":0.00043416113,"threshold_uncertainty_score":0.010605931},"labels":[],"label_agreement":null},{"id":"W2806680184","doi":"10.1038/s41598-018-22985-4","title":"Altered Insulin/Insulin-Like Growth Factor Signaling in a Comorbid Rat model of Ischemia and β-Amyloid Toxicity","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research","keywords":"Insulin receptor; Internal medicine; Endocrinology; Basal forebrain; Insulin; Medicine; Striatum; Neuroscience; Psychology; Biology; Insulin resistance; Central nervous system; Dopamine","score_opus":0.06719222394954029,"score_gpt":0.32899416086149297,"score_spread":0.2618019369119527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806680184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99717283,0.00048528356,0.0012818093,0.00008773437,0.000055376768,0.000058983576,0.00018720127,0.00006248352,0.0006082929],"genre_scores_gemma":[0.9920534,0.001093499,0.0032139842,0.0000756497,0.000024373197,0.00017388593,0.000402135,0.000019789397,0.0029433554],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997733,0.000028364426,0.000023498522,0.000059613612,0.000052567753,0.000062671636],"domain_scores_gemma":[0.9996977,0.0000166446,0.00010894782,0.0000426185,0.000021190648,0.00011295047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002517255,0.0011960366,0.00061190315,0.0011986633,0.00037378815,0.0003484544,0.00042808766,0.00058542023,0.0016978249],"category_scores_gemma":[0.00015297854,0.000436423,0.0004034781,0.00047064538,0.0006170668,0.00047468726,0.00039088863,0.0015180252,0.00029314778],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005941537,0.0029727723,0.0032587661,0.00012665514,0.00007412168,0.0011185318,0.00011594189,0.00032408073,0.97938854,0.0005436671,0.00020125855,0.005934077],"study_design_scores_gemma":[0.0005917884,0.035145745,0.0472951,0.00007643458,0.00031077315,0.0042488105,0.0003668183,0.005123058,0.902754,0.0008241893,0.0032004442,0.0000627847],"about_ca_topic_score_codex":0.0015250026,"about_ca_topic_score_gemma":0.003077998,"teacher_disagreement_score":0.0016978249,"about_ca_system_score_codex":0.00050488714,"about_ca_system_score_gemma":0.00051869417,"threshold_uncertainty_score":0.005679846},"labels":[],"label_agreement":null},{"id":"W2807651809","doi":"10.1007/s10334-018-0685-9","title":"Inferring diameters of spheres and cylinders using interstitial water","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba; Canadian Institutes of Health Research; University of Winnipeg; Canada Foundation for Innovation; Research Manitoba","keywords":"Diffusion; Volume (thermodynamics); Analytical Chemistry (journal); SPHERES; Materials science; Bead; Tube (container); Surface-area-to-volume ratio; RADIUS; Chemistry; Nuclear magnetic resonance; Composite material; Chromatography; Physics; Thermodynamics","score_opus":0.06763640712481932,"score_gpt":0.37534931229469465,"score_spread":0.3077129051698753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807651809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33284125,0.0011032578,0.6595728,0.0002209514,0.00006031098,0.000048928552,0.0007333195,0.0025218239,0.0028973948],"genre_scores_gemma":[0.8218111,0.00040022025,0.17625609,0.000043389235,0.00004574965,0.000029139186,0.0005203926,0.00031124303,0.00058258814],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994747,0.00009360557,0.000023969184,0.00021203517,0.0001386338,0.000057026165],"domain_scores_gemma":[0.99761474,0.0013847074,0.00030061553,0.00021138703,0.00033843864,0.00015003215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069375685,0.0008893378,0.0006929513,0.0017250814,0.00046848727,0.0011053929,0.0011560407,0.0011459499,0.0006023739],"category_scores_gemma":[0.006637169,0.00094086805,0.0005063021,0.0009523927,0.00068081415,0.002342017,0.0012935558,0.0007655767,0.00054494647],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019367981,0.00022872862,0.06962322,0.0006552323,0.00023726038,0.0012541879,0.0010802639,0.30485484,0.31324935,0.025971826,0.0047764652,0.27613184],"study_design_scores_gemma":[0.000029546367,0.00006934122,0.004344263,0.000020551994,0.000054414304,0.0003284198,0.000174257,0.9171778,0.06136749,0.014120857,0.002264258,0.000048717342],"about_ca_topic_score_codex":0.0043834685,"about_ca_topic_score_gemma":0.005525024,"teacher_disagreement_score":0.0043834685,"about_ca_system_score_codex":0.00050408527,"about_ca_system_score_gemma":0.0006181658,"threshold_uncertainty_score":0.008715928},"labels":[],"label_agreement":null},{"id":"W2807820258","doi":"10.1038/sdata.2018.107","title":"Warping an atlas derived from serial histology to 5 high-resolution MRIs","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Western University; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Atlas (anatomy); Image warping; Histology; Computer science; High resolution; Artificial intelligence; Computer vision; Medicine; Anatomy; Pathology; Remote sensing; Geology","score_opus":0.1620349504297906,"score_gpt":0.3946804462657199,"score_spread":0.2326454958359293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807820258","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039562073,0.00039713466,0.9393072,0.00034496206,0.00032561997,0.0004896051,0.0038746106,0.008237179,0.0074616335],"genre_scores_gemma":[0.14042842,0.0007281491,0.84325016,0.00019981198,0.00007045348,0.0006803962,0.005386339,0.0027771643,0.0064790975],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906164,0.00013854903,0.000105804276,0.00028821098,0.00033100732,0.0000748221],"domain_scores_gemma":[0.9984666,0.00036022346,0.00016624143,0.0004564593,0.0004853019,0.000065130385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023131226,0.0008530815,0.0006872631,0.0027625128,0.00091207,0.0026159785,0.001126259,0.0012208638,0.010420418],"category_scores_gemma":[0.003995907,0.00093729806,0.0017769776,0.0026800525,0.00080654345,0.0011457583,0.0017054805,0.0017160224,0.0038531227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000996544,0.00026004226,0.009145962,0.001641314,0.00057430146,0.0014615741,0.0022042915,0.09810767,0.19534138,0.046991386,0.036515146,0.6067604],"study_design_scores_gemma":[0.00015174809,0.001110378,0.033890463,0.000412218,0.00061117753,0.005585765,0.0008759683,0.32154623,0.322941,0.06580077,0.24657808,0.00049622275],"about_ca_topic_score_codex":0.0046248706,"about_ca_topic_score_gemma":0.009782291,"teacher_disagreement_score":0.010420418,"about_ca_system_score_codex":0.0015208189,"about_ca_system_score_gemma":0.0030866312,"threshold_uncertainty_score":0.034859776},"labels":[],"label_agreement":null},{"id":"W2808538832","doi":"10.1111/jon.12531","title":"Yakovlev's Basolateral Limbic Circuit in Multiple Sclerosis Related Cognitive Impairment","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; John S. Dunn Foundation","keywords":"Fractional anisotropy; Medicine; Diffusion MRI; Neuroscience; Cognition; Montreal Cognitive Assessment; Audiology; Magnetic resonance imaging; Cognitive impairment; Psychology; Psychiatry; Radiology","score_opus":0.13577067389362377,"score_gpt":0.3400989525921899,"score_spread":0.20432827869856615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808538832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99595934,0.0012010989,0.00035560277,0.00022679158,0.000008029945,0.00001061043,0.00010982331,0.000014859836,0.0021138443],"genre_scores_gemma":[0.99952507,0.000115606395,0.00016671358,0.000028965866,0.000005713265,0.000004843702,0.000043706834,0.0000010329826,0.00010828858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988484,0.000021060465,0.000011497318,0.000027817901,0.00003269255,0.000022177583],"domain_scores_gemma":[0.99968016,0.000052214273,0.00015771284,0.000017276403,0.000044129592,0.00004862619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028732183,0.00021378194,0.00023120051,0.00052091456,0.00035376812,0.00044263323,0.00024678212,0.00022082691,0.0011350336],"category_scores_gemma":[0.0010972514,0.000058642127,0.00010031355,0.0002699029,0.0005098279,0.0002857979,0.00039134856,0.0002643999,0.0001427522],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001100817,0.00013925887,0.9522705,0.00010712729,0.000077981145,0.0016818801,0.00036683035,0.000607261,0.011132701,0.0008832542,0.00049325434,0.031139208],"study_design_scores_gemma":[0.000029693361,0.000193939,0.9885592,0.00003823,0.000040084644,0.0057798815,0.00021211026,0.0009447355,0.0016146757,0.0017346358,0.0008458811,0.0000068398103],"about_ca_topic_score_codex":0.0046523954,"about_ca_topic_score_gemma":0.0054280064,"teacher_disagreement_score":0.0046523954,"about_ca_system_score_codex":0.0004514597,"about_ca_system_score_gemma":0.0005283638,"threshold_uncertainty_score":0.009250581},"labels":[],"label_agreement":null},{"id":"W2809233735","doi":"10.1016/j.mri.2018.06.009","title":"Voxel-Wise Logistic Regression and Leave-One-Source-Out Cross Validation for white matter hyperintensity segmentation","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Vector Institute; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Segmentation; Computer science; Voxel; Fluid-attenuated inversion recovery; Pattern recognition (psychology); Hyperintensity; Logistic regression; Artificial intelligence; Similarity (geometry); Algorithm; Magnetic resonance imaging; Machine learning; Image (mathematics); Medicine","score_opus":0.07407320815730728,"score_gpt":0.3759359318396396,"score_spread":0.3018627236823323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809233735","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0949966,0.0021908283,0.86951023,0.00050703296,0.00079157593,0.0011369565,0.0041201585,0.025464198,0.0012823654],"genre_scores_gemma":[0.27830303,0.00037234518,0.6892123,0.00039895315,0.00017492424,0.0015860667,0.013636999,0.008484006,0.007831307],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9910492,0.003716691,0.00090454577,0.0026105696,0.00083713036,0.0008818983],"domain_scores_gemma":[0.9862178,0.0063653444,0.00065920653,0.0029336473,0.0034351952,0.00038883858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02804918,0.0035346632,0.0056444956,0.0035087683,0.0038672101,0.003157165,0.007686356,0.00503803,0.0073774303],"category_scores_gemma":[0.03589626,0.0017075642,0.0049757827,0.0032649033,0.0019976357,0.0020215057,0.00321664,0.007147761,0.0051362184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0076627946,0.0020877982,0.017390667,0.001159052,0.0039483355,0.00094910554,0.0016580049,0.1862606,0.030911716,0.0070726234,0.040160045,0.70073926],"study_design_scores_gemma":[0.0002054248,0.0004699455,0.0069015445,0.00013849828,0.00061117625,0.00039675328,0.00028028936,0.9618534,0.016440168,0.0059146774,0.006630243,0.00015795398],"about_ca_topic_score_codex":0.029116431,"about_ca_topic_score_gemma":0.04824062,"teacher_disagreement_score":0.029116431,"about_ca_system_score_codex":0.0017719176,"about_ca_system_score_gemma":0.0069176746,"threshold_uncertainty_score":0.14834005},"labels":[],"label_agreement":null},{"id":"W2810277203","doi":"10.1093/schbul/sby091","title":"Classification of First-Episode Schizophrenia Using Multimodal Brain Features: A Combined Structural and Diffusion Imaging Study","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Neuroimaging; Gyrification; Diffusion MRI; Artificial intelligence; Discriminative model; Fractional anisotropy; Pattern recognition (psychology); Parahippocampal gyrus; Psychology; Magnetic resonance imaging; Neuroscience; Computer science; Medicine; Radiology; Temporal lobe; Cerebral cortex","score_opus":0.030564212612422904,"score_gpt":0.32534361633564535,"score_spread":0.2947794037232224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810277203","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989982,0.00008585709,0.0007824567,0.000019000012,0.0000020047744,0.000007083426,0.000047675145,0.000007825616,0.000049725397],"genre_scores_gemma":[0.9989581,0.00003717284,0.0008449767,0.0000044887197,0.0000047925428,0.0000032469216,0.00011623244,0.0000016342966,0.00002926703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995845,0.00015199817,0.000046034293,0.00008292047,0.00007480502,0.00005977335],"domain_scores_gemma":[0.99899286,0.00040142855,0.0002068988,0.00012314801,0.00014709904,0.00012864293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017840262,0.0005558597,0.0006237966,0.0012989709,0.00031763627,0.0005049107,0.00019581486,0.00042499704,0.0003808476],"category_scores_gemma":[0.0029899862,0.00014660829,0.00057870144,0.0003565061,0.00030659977,0.00038011622,0.0004891626,0.0003022504,0.00012049351],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017367653,0.00037447005,0.8887767,0.000087916786,0.00054246647,0.0005128701,0.00036339782,0.0082323365,0.033256106,0.000098752804,0.00032126467,0.06569694],"study_design_scores_gemma":[0.00004695498,0.0009099754,0.8876786,0.000031103085,0.00022362014,0.00092237815,0.00033377027,0.10413539,0.0052368087,0.00026101866,0.00018255453,0.000037880236],"about_ca_topic_score_codex":0.002815929,"about_ca_topic_score_gemma":0.0035122745,"teacher_disagreement_score":0.002815929,"about_ca_system_score_codex":0.00031768318,"about_ca_system_score_gemma":0.0003059918,"threshold_uncertainty_score":0.009434938},"labels":[],"label_agreement":null},{"id":"W2810325419","doi":"10.1016/j.neuroimage.2018.06.045","title":"High-resolution 3D diffusion tensor MRI of anesthetized rhesus macaque brain at 3T","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Association Nationale de la Recherche et de la Technologie; Agence Nationale de la Recherche","keywords":"Diffusion MRI; White matter; Human Connectome Project; Macaque; Neuroscience; Magnetic resonance imaging; Connectome; Human brain; Computer science; Psychology; Medicine; Functional connectivity; Radiology","score_opus":0.03682248071453918,"score_gpt":0.3237640249850234,"score_spread":0.2869415442704842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810325419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9128249,0.0024019324,0.06971363,0.0024060947,0.00016460157,0.00018707025,0.0025318656,0.00088444696,0.008885485],"genre_scores_gemma":[0.9105137,0.0041666795,0.07148043,0.0010643606,0.00011193314,0.00027010395,0.0021523365,0.0005670532,0.009673505],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999583,0.000005123343,0.000003359131,0.000010353564,0.000012144596,0.000010712091],"domain_scores_gemma":[0.9998592,0.00003301338,0.000024907882,0.000023186825,0.00004326956,0.000016376414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000338031,0.00030432653,0.00018549597,0.00054648245,0.00057346304,0.00044961044,0.00032108647,0.00085202616,0.0020811893],"category_scores_gemma":[0.00048713706,0.0004016401,0.0002520728,0.00030022138,0.00040719993,0.00057917763,0.0003365956,0.0008282962,0.00043598493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026024884,0.00008318878,0.0014971575,0.00015374008,0.000050353294,0.0007790764,0.00041560625,0.0016271349,0.97682357,0.0012580684,0.0017800375,0.015271887],"study_design_scores_gemma":[0.0001892639,0.001741419,0.16519603,0.00024816446,0.0006729354,0.015725072,0.001163539,0.026936864,0.72751933,0.014470497,0.045870934,0.00026601471],"about_ca_topic_score_codex":0.0061811097,"about_ca_topic_score_gemma":0.012337268,"teacher_disagreement_score":0.0061811097,"about_ca_system_score_codex":0.00026475757,"about_ca_system_score_gemma":0.0007927056,"threshold_uncertainty_score":0.012290299},"labels":[],"label_agreement":null},{"id":"W2810948267","doi":"10.1016/j.neuroimage.2018.06.072","title":"In vivo manganese tract tracing of frontal eye fields in rhesus macaques with ultra-high field MRI: Comparison with DWI tractography","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Neuroscience; Tracing; Diffusion MRI; In vivo; Saccadic masking; Tractography; Computer science; Magnetic resonance imaging; Biology; Eye movement; Medicine; Radiology","score_opus":0.02671317543621853,"score_gpt":0.33373560398211854,"score_spread":0.3070224285459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810948267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96310824,0.0006498584,0.033517614,0.00022522078,0.0000151563745,0.000044301087,0.00035439347,0.0001641649,0.0019210776],"genre_scores_gemma":[0.9636665,0.0010575092,0.03131575,0.000047133875,0.000011301896,0.0000331782,0.00020774576,0.00012600813,0.0035349769],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999604,0.000008217101,0.0000036630186,0.000011972311,0.000007128855,0.000008512568],"domain_scores_gemma":[0.9997887,0.00006128475,0.000040491457,0.000043333657,0.00004958988,0.000016638862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028485368,0.00020738856,0.00013172181,0.00068659824,0.00031373696,0.00041928442,0.0002349675,0.00038506935,0.0008041396],"category_scores_gemma":[0.00083157106,0.00019483265,0.00010649587,0.00026659758,0.00029081444,0.00046201897,0.00022062864,0.00021862028,0.00018670048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003416307,0.00007343066,0.01820133,0.0001867166,0.00006443331,0.00073071936,0.00077809044,0.0027060518,0.9277648,0.0014430727,0.00035705595,0.047352653],"study_design_scores_gemma":[0.000069395945,0.00071347965,0.3624426,0.00013852153,0.00030800002,0.009316034,0.0011186007,0.07414013,0.5348275,0.006049489,0.010791569,0.00008470009],"about_ca_topic_score_codex":0.016936319,"about_ca_topic_score_gemma":0.027012609,"teacher_disagreement_score":0.016936319,"about_ca_system_score_codex":0.00033243213,"about_ca_system_score_gemma":0.00045477282,"threshold_uncertainty_score":0.03367549},"labels":[],"label_agreement":null},{"id":"W2811003555","doi":"10.1159/000489491","title":"The Relationship between White Matter and Reading Acquisition, Refinement and Maintenance","year":2018,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"National Institute on Drug Abuse","keywords":"White matter; Neuroscience; Reading (process); Psychology; White (mutation); Cognitive psychology; Biology; Medicine; Linguistics; Genetics; Philosophy; Magnetic resonance imaging","score_opus":0.07529957441823172,"score_gpt":0.342031578114362,"score_spread":0.2667320036961303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811003555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986192,0.00046488774,0.00025095942,0.000033600805,0.0000030815268,0.0000042572137,0.00020432727,0.0000099430135,0.0004096298],"genre_scores_gemma":[0.998262,0.00029615514,0.00061092427,0.000013730662,0.0000070148226,0.000005711261,0.00026897807,0.0000050772023,0.00053040846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973387,0.00004248292,0.000029354664,0.00011087698,0.00005440348,0.000029056753],"domain_scores_gemma":[0.9968855,0.0005400527,0.0018245181,0.00015858136,0.0003869375,0.00020439431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006329073,0.0002780116,0.00014852206,0.00073211436,0.00023616778,0.0005589816,0.00022841671,0.00042291972,0.0012414284],"category_scores_gemma":[0.0027507152,0.00017499978,0.00015858191,0.00041154452,0.00039467137,0.0006537364,0.00033777184,0.00039767098,0.0003208432],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001323793,0.00009022594,0.98353255,0.000031419277,0.00008374136,0.00021507576,0.00029062197,0.00009319661,0.008148104,0.00009868753,0.00008039171,0.007203597],"study_design_scores_gemma":[4.803077e-7,0.00006276707,0.9991466,0.0000026372218,0.0000079711435,0.0001984557,0.000027338441,0.000035955443,0.0004185818,0.000035652134,0.000062294406,0.000001289129],"about_ca_topic_score_codex":0.0027229837,"about_ca_topic_score_gemma":0.0042119604,"teacher_disagreement_score":0.0027229837,"about_ca_system_score_codex":0.00021243557,"about_ca_system_score_gemma":0.00024187444,"threshold_uncertainty_score":0.0054142475},"labels":[],"label_agreement":null},{"id":"W2811045425","doi":"10.1101/356576","title":"Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; James S. McDonnell Foundation","keywords":"Connectome; Tractography; Macaque; Betweenness centrality; Human Connectome Project; Diffusion MRI; Modularity (biology); Connectomics; Computer science; Neuroscience; Network topology; Artificial intelligence; Topology (electrical circuits); Centrality; Pattern recognition (psychology); Psychology; Functional connectivity; Biology; Mathematics; Medicine; Magnetic resonance imaging; Evolutionary biology","score_opus":0.18416910244361595,"score_gpt":0.35850793081213295,"score_spread":0.174338828368517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811045425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8806033,0.0017112894,0.11407737,0.0011862445,0.00001612874,0.000017536273,0.00010971946,0.00025248367,0.0020258606],"genre_scores_gemma":[0.98213404,0.00038895672,0.017096242,0.0000551295,0.0000122500605,0.000018796945,0.00005628722,0.00003746349,0.00020080367],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990759,0.00051338924,0.00003658168,0.00019556213,0.00013652776,0.00004210839],"domain_scores_gemma":[0.9871809,0.008617655,0.0012608046,0.0017550171,0.0008158187,0.00036990235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004978012,0.00047559582,0.00058634277,0.0020838354,0.000618742,0.0018843488,0.0005845276,0.00075567054,0.0006154317],"category_scores_gemma":[0.029270161,0.00034430146,0.00027547628,0.0008227438,0.0023447727,0.0030919972,0.001402893,0.0009741692,0.00014281536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083180243,0.00017580044,0.18811709,0.00096265494,0.00074520847,0.0019619514,0.008582658,0.173988,0.29221094,0.1365505,0.0016256876,0.19424772],"study_design_scores_gemma":[0.000027139016,0.00033408776,0.17570154,0.00034892763,0.00014702657,0.0017686393,0.0015598276,0.51945496,0.03830187,0.25638348,0.0058568898,0.00011564331],"about_ca_topic_score_codex":0.0090060625,"about_ca_topic_score_gemma":0.0074798404,"teacher_disagreement_score":0.0090060625,"about_ca_system_score_codex":0.00089944084,"about_ca_system_score_gemma":0.00068910734,"threshold_uncertainty_score":0.026326597},"labels":[],"label_agreement":null},{"id":"W2811225418","doi":"10.1017/cjn.2018.166","title":"P.064 Preoperative mapping using fMRI and DTI: a multimodal approach to assessing language dominance","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Saskatoon Medical Imaging","funders":"","keywords":"Arcuate fasciculus; Lateralization of brain function; Diffusion MRI; Precentral gyrus; Psychology; Wada test; Medicine; Neuroscience; Tractography; Radiology; Epilepsy surgery; Magnetic resonance imaging; Epilepsy","score_opus":0.1050975204146551,"score_gpt":0.3665366888966896,"score_spread":0.2614391684820345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811225418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6503435,0.0120553635,0.10188161,0.030087782,0.0015979591,0.0008976535,0.0012682091,0.0008701494,0.20099777],"genre_scores_gemma":[0.93113655,0.002645288,0.044587772,0.0013626484,0.0007480653,0.00018664857,0.00022233829,0.00008531763,0.019025477],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9999132,0.000019808562,0.00001041072,0.000015954742,0.000027900896,0.000012741524],"domain_scores_gemma":[0.9998186,0.000061151135,0.000030853178,0.000013082971,0.000044063327,0.000032242955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003184282,0.00042770364,0.00014160674,0.000906165,0.00030642768,0.0004731369,0.00025488538,0.00065299915,0.012295655],"category_scores_gemma":[0.0008082103,0.000107109685,0.0001294516,0.00026697302,0.0007923782,0.00045809755,0.00031321874,0.0006731296,0.002447876],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013399243,0.0002863595,0.059280176,0.00048791966,0.0000878999,0.1542005,0.0006533116,0.00096309953,0.105422,0.0096196635,0.03796489,0.6296943],"study_design_scores_gemma":[0.00024169177,0.0017749598,0.13509189,0.0008334196,0.00015522537,0.640777,0.0013924581,0.016096437,0.06784583,0.038341857,0.09734305,0.0001061754],"about_ca_topic_score_codex":0.0011819701,"about_ca_topic_score_gemma":0.0020347696,"teacher_disagreement_score":0.012295655,"about_ca_system_score_codex":0.00029643718,"about_ca_system_score_gemma":0.00054129167,"threshold_uncertainty_score":0.041133106},"labels":[],"label_agreement":null},{"id":"W2811480054","doi":"10.1016/j.neuroimage.2018.08.012","title":"A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology","year":2018,"lang":"en","type":"preprint","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Universidad de Castilla-La Mancha; NIH Blueprint for Neuroscience Research; Fujirebio Europe; Eisai; Bristol-Myers Squibb; Ministerio de Economía y Competitividad; Lundbeckfonden; U.S. Department of Defense; Eli Lilly and Company; Eusko Jaurlaritza; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; National Center for Research Resources; F. Hoffmann-La Roche; National Institute of Neurological Disorders and Stroke; IXICO; Takeda Pharmaceutical Company; European Commission; AbbVie; European Research Council; Northern California Institute for Research and Education; Massachusetts General Hospital; Novartis Pharmaceuticals Corporation; University of Southern California; Roche; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics","keywords":"Thalamus; Ex vivo; Neuroimaging; Putamen; Atlas (anatomy); Segmentation; Neuroscience; Brain atlas; Human brain; Magnetic resonance imaging; Diffusion MRI; Computer science; In vivo; Artificial intelligence; Medicine; Anatomy; Biology; Radiology","score_opus":0.06383799917899072,"score_gpt":0.34536827674136117,"score_spread":0.2815302775623705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811480054","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020943806,0.00040195364,0.96911967,0.00011265271,0.000043985376,0.00021170665,0.0030379868,0.0025111602,0.003616988],"genre_scores_gemma":[0.16725029,0.0011955991,0.818779,0.000088872766,0.000057557765,0.0006187922,0.0061480636,0.0015201541,0.004341613],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99944586,0.00012202272,0.0000523507,0.00013799242,0.0001982688,0.00004356929],"domain_scores_gemma":[0.9994542,0.0001306628,0.000082607374,0.00016843565,0.00013281185,0.000031280542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009434876,0.00078827713,0.0005777114,0.0024091112,0.00063389615,0.001936784,0.0012044561,0.0010706517,0.004608699],"category_scores_gemma":[0.0016194183,0.0009843033,0.0010330653,0.0022379956,0.00082515966,0.000794869,0.001385325,0.00090507173,0.0017149518],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056276546,0.00018302111,0.009531805,0.0014405668,0.00036138756,0.0015606158,0.0012802042,0.24421217,0.35453176,0.042121474,0.017596053,0.3266182],"study_design_scores_gemma":[0.00017849043,0.000615007,0.05837954,0.00044258824,0.00048563266,0.011000688,0.0005040014,0.5956282,0.13093954,0.06411416,0.1371902,0.0005219457],"about_ca_topic_score_codex":0.0070399796,"about_ca_topic_score_gemma":0.011784277,"teacher_disagreement_score":0.0070399796,"about_ca_system_score_codex":0.0008431363,"about_ca_system_score_gemma":0.0023482877,"threshold_uncertainty_score":0.015417635},"labels":[],"label_agreement":null},{"id":"W2847223726","doi":"10.1002/acn3.601","title":"Presymptomatic white matter integrity loss in familial frontotemporal dementia in the <scp>GENFI</scp> cohort: A cross‐sectional diffusion tensor imaging study","year":2018,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Occupational Cancer Research Centre; University of Toronto; Western University; Sunnybrook Health Science Centre","funders":"Medical Research Council; Stichting Dioraphte; Ministero della Salute; Erasmus Medisch Centrum; Alzheimer’s Research UK; Brain Research Trust; Wolfson Foundation; National Institute for Health and Care Research; Alzheimer Nederland; EU Joint Programme – Neurodegenerative Disease Research; ZonMw; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Canadian Institutes of Health Research; Wellcome","keywords":"C9orf72; Splenium; Corpus callosum; Medicine; White matter; Diffusion MRI; Internal capsule; Uncinate fasciculus; Fractional anisotropy; Frontotemporal dementia; Pathology; Dementia; Radiology; Magnetic resonance imaging; Disease","score_opus":0.1382471159744504,"score_gpt":0.4537488345202032,"score_spread":0.3155017185457528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2847223726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99960977,0.000057590056,0.000025518462,0.000008682684,0.0000025187403,0.0000041322646,0.00017482598,0.0000016462992,0.000115348346],"genre_scores_gemma":[0.99927956,0.00004778709,0.000057840803,0.000012692459,0.000007023681,0.0000070828332,0.00046815924,0.0000025543593,0.000117243915],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99966955,0.0000519062,0.000030708245,0.00014024542,0.000062337,0.00004520242],"domain_scores_gemma":[0.9992768,0.00008122869,0.00026908316,0.00010322052,0.00011145844,0.0001581383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006707374,0.00073547295,0.00044823225,0.0011746035,0.0010794362,0.0007611579,0.00043348063,0.000702258,0.0015217469],"category_scores_gemma":[0.0014946666,0.0004414591,0.0005855712,0.0008823868,0.0003676302,0.00043875017,0.0005235813,0.00052976876,0.0002808352],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036176998,0.000051018884,0.9963498,0.000008305943,0.00017554953,0.000693701,0.00022708418,0.000037135866,0.0009324157,0.000020034042,0.00014844335,0.0009947256],"study_design_scores_gemma":[0.0000102416525,0.000065252956,0.99882907,0.0000031312013,0.000046038913,0.00075100653,0.00008731537,0.0000709812,0.000051003415,0.000012091242,0.0000707071,0.000003157626],"about_ca_topic_score_codex":0.01636474,"about_ca_topic_score_gemma":0.019048529,"teacher_disagreement_score":0.01636474,"about_ca_system_score_codex":0.0003781347,"about_ca_system_score_gemma":0.00033225058,"threshold_uncertainty_score":0.03253901},"labels":[],"label_agreement":null},{"id":"W28615604","doi":"10.1007/978-3-642-38868-2_44","title":"Moving Frames for Heart Fiber Geometry","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Geometry; Computer graphics (images); Fiber; Computer vision; Engineering drawing; Artificial intelligence; Mathematics; Engineering; Composite material; Materials science","score_opus":0.031902053099422636,"score_gpt":0.33720562827644507,"score_spread":0.30530357517702245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28615604","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003053576,0.00058048323,0.99489576,0.0001369092,0.00010179315,0.000016850683,0.00019369223,0.00032064485,0.00070037774],"genre_scores_gemma":[0.13456388,0.0034767892,0.8470253,0.00014704015,0.0008103494,0.00013975994,0.0017172383,0.0007080262,0.011411608],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999716,0.000073061994,0.000014217237,0.000100378835,0.000071270886,0.000025082078],"domain_scores_gemma":[0.9992988,0.00026517757,0.00008605271,0.00013471342,0.00015129319,0.00006397341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007145059,0.001092253,0.00096085895,0.0017990215,0.0004541451,0.0011542784,0.0014381915,0.0014845676,0.0061461194],"category_scores_gemma":[0.0028944472,0.0007239408,0.0008944072,0.0012490805,0.0007396826,0.0015889549,0.0011008553,0.0021595703,0.0024598446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021348648,0.00006428333,0.00058981974,0.00027210193,0.000093885414,0.00023650321,0.00022284115,0.12832989,0.019617515,0.42898664,0.02056695,0.40080604],"study_design_scores_gemma":[0.000013738232,0.00004116063,0.00041002448,0.000024397985,0.000017617778,0.00008578914,0.000034177458,0.8761972,0.0014976497,0.111415595,0.01023879,0.000023894298],"about_ca_topic_score_codex":0.00798654,"about_ca_topic_score_gemma":0.0059338617,"teacher_disagreement_score":0.00798654,"about_ca_system_score_codex":0.00057797355,"about_ca_system_score_gemma":0.0005292781,"threshold_uncertainty_score":0.02056086},"labels":[],"label_agreement":null},{"id":"W286640797","doi":"10.1007/978-3-319-11182-7_13","title":"Diffusion Propagator Estimation Using Gaussians Scattered in q-Space","year":2014,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Propagator; Gaussian; Basis (linear algebra); Diffusion; Basis function; Diffusion MRI; Radial basis function; Statistical physics; Orientation (vector space); Mathematics; Mathematical analysis; Physics; Computer science; Geometry; Artificial intelligence","score_opus":0.08375704491233274,"score_gpt":0.37670314711074593,"score_spread":0.2929461021984132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W286640797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006277018,0.00019322547,0.9983298,0.000085305546,0.000030255484,0.0000047207723,0.000011112414,0.00011036957,0.0006076159],"genre_scores_gemma":[0.04627731,0.0014529394,0.94342875,0.00011430018,0.00011698217,0.000034084554,0.00013360266,0.00031622834,0.008125862],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997445,0.00009500604,0.000018238254,0.000049855265,0.00007902664,0.000013421499],"domain_scores_gemma":[0.99891174,0.00071289897,0.000055183024,0.00009743509,0.00018814286,0.00003460109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012023122,0.0008102784,0.0006619665,0.0007088316,0.0002916199,0.001220139,0.00094249926,0.001261449,0.0024918562],"category_scores_gemma":[0.0036573592,0.00053692335,0.0007722316,0.0010075518,0.00087171694,0.0021258844,0.0010696306,0.0015155857,0.0013856046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110649715,0.000058929712,0.00064525503,0.00045853716,0.00011694353,0.0001851167,0.00033908282,0.24999046,0.021437665,0.3109992,0.009582351,0.4060759],"study_design_scores_gemma":[0.00000979593,0.000017699002,0.00015212012,0.00003715321,0.000015718775,0.00017994353,0.00002620727,0.889511,0.0052845664,0.0976524,0.0070843156,0.000029140816],"about_ca_topic_score_codex":0.0013493391,"about_ca_topic_score_gemma":0.0012281833,"teacher_disagreement_score":0.0024918562,"about_ca_system_score_codex":0.00047313442,"about_ca_system_score_gemma":0.0006589065,"threshold_uncertainty_score":0.008336127},"labels":[],"label_agreement":null},{"id":"W28703433","doi":"10.1002/chem.201703215","title":"22 DWI volume color-coded mapとDTI tractographyによる白質神経線維走行可視化結果の比較(北日本脳神経外科連合会第30回学術集会)","year":2007,"lang":"en","type":"article","venue":"新潟医学会雑誌","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Volume (thermodynamics); Artificial intelligence; Computer vision; Computer science; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging; Physics","score_opus":0.05908910226020175,"score_gpt":0.37028104855537053,"score_spread":0.3111919462951688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28703433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51271063,0.0054298965,0.42840144,0.0020098812,0.00020334031,0.00041662782,0.010257962,0.0037911558,0.036779027],"genre_scores_gemma":[0.806271,0.0061272522,0.15579246,0.0005083271,0.000114218,0.0006155071,0.006224246,0.00081189774,0.023535116],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999516,0.0000066530333,0.000005188983,0.000015539797,0.000011989104,0.000008943947],"domain_scores_gemma":[0.99983466,0.0000355045,0.00004183277,0.000025558695,0.000044645694,0.000017723858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038106245,0.00042583668,0.00021216576,0.0008771064,0.00034899614,0.0009370793,0.00023860927,0.00038279608,0.008500489],"category_scores_gemma":[0.0005702711,0.00023717986,0.00015243149,0.0008919226,0.0003642133,0.000621729,0.00020012735,0.0004027266,0.0014519016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007440032,0.000074909054,0.018225646,0.0009255993,0.00031377925,0.001293042,0.00041102417,0.005439357,0.5827079,0.011130134,0.013702059,0.36503252],"study_design_scores_gemma":[0.00008143583,0.0005230562,0.14339867,0.0002448835,0.0005978579,0.013242928,0.00071361434,0.045911796,0.66259927,0.032203525,0.10028521,0.00019776105],"about_ca_topic_score_codex":0.003839229,"about_ca_topic_score_gemma":0.0052329255,"teacher_disagreement_score":0.008500489,"about_ca_system_score_codex":0.0006374962,"about_ca_system_score_gemma":0.00068429037,"threshold_uncertainty_score":0.028436959},"labels":[],"label_agreement":null},{"id":"W2883037454","doi":"10.1016/j.mri.2018.07.011","title":"Scan-rescan repeatability and cross-scanner comparability of DTI metrics in healthy subjects in the SPRINT-MS multicenter trial","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroRx Research (Canada); Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Repeatability; Scanner; Siemens; Nuclear medicine; Diffusion MRI; Fractional anisotropy; Medicine; Mathematics; Physics; Magnetic resonance imaging; Artificial intelligence; Computer science; Statistics; Radiology","score_opus":0.07056010756874385,"score_gpt":0.3980813807907984,"score_spread":0.32752127322205454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883037454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99628013,0.0008451259,0.0012174386,0.000088574896,0.00006631316,0.00009170129,0.0006464152,0.00004061652,0.0007235922],"genre_scores_gemma":[0.9979978,0.00007098764,0.0005181742,0.000048441918,0.000054384313,0.00011075614,0.0008151119,0.00003203951,0.00035232483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9892211,0.0061706323,0.0011144199,0.002070455,0.00093408104,0.00048937614],"domain_scores_gemma":[0.98129785,0.007182306,0.0027336457,0.0052991114,0.0030296426,0.00045740345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01947929,0.0007291811,0.0020168773,0.0005744655,0.0011261388,0.0013993524,0.0009704895,0.0013491773,0.0012633529],"category_scores_gemma":[0.02921277,0.0006356645,0.0012725003,0.00071538717,0.0010188562,0.0015969693,0.0008145354,0.00095380883,0.00044219213],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.18600091,0.0019276061,0.7082417,0.0006364659,0.019690253,0.00072346325,0.0029559569,0.0026943572,0.0132468175,0.001179453,0.005644317,0.057058748],"study_design_scores_gemma":[0.003556153,0.010233675,0.96925485,0.000058439462,0.0046706693,0.0008027924,0.00044021057,0.0034787576,0.0031248308,0.0014185217,0.0028522164,0.000108878376],"about_ca_topic_score_codex":0.0026157298,"about_ca_topic_score_gemma":0.004622365,"teacher_disagreement_score":0.01947929,"about_ca_system_score_codex":0.00042239373,"about_ca_system_score_gemma":0.000736795,"threshold_uncertainty_score":0.10301757},"labels":[],"label_agreement":null},{"id":"W2883215471","doi":"10.3389/fninf.2018.00057","title":"Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Aging; National Institutes of Health; National Natural Science Foundation of China","keywords":"Upsampling; Diffusion MRI; Spherical harmonics; Diffusion; Regularization (linguistics); Interpolation (computer graphics); Computer science; Algorithm; Matching (statistics); Scanner; Mathematics; Artificial intelligence; Mathematical analysis; Physics; Magnetic resonance imaging; Statistics","score_opus":0.03758903992502172,"score_gpt":0.3275924135135114,"score_spread":0.2900033735884897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883215471","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030905437,0.00022829624,0.96792644,0.00006418233,0.000017105862,0.000034083467,0.000031454605,0.00026354258,0.00052941864],"genre_scores_gemma":[0.24378656,0.00046841791,0.7538745,0.00007818528,0.00003682137,0.00007672659,0.00017415,0.0001604469,0.0013442147],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997416,0.000081349346,0.000016789007,0.000044481705,0.000098247125,0.00001748668],"domain_scores_gemma":[0.99952257,0.00021522521,0.00007269981,0.00007638408,0.0000862786,0.000026912814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010210989,0.00031241024,0.00041131428,0.00052831596,0.00022482991,0.00042251655,0.0005397782,0.00047040833,0.0010831724],"category_scores_gemma":[0.0026949546,0.00022541227,0.00045391137,0.00046881134,0.00034811356,0.0005243844,0.0006711269,0.00048934843,0.00031740466],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004755626,0.00013982187,0.004058541,0.00033466154,0.00010102766,0.000503336,0.00058996695,0.2638976,0.14727055,0.034486145,0.0025038938,0.545639],"study_design_scores_gemma":[0.000014506327,0.00007945375,0.001053812,0.000012627642,0.00002175171,0.0002339466,0.000037873484,0.9654387,0.025159812,0.0050390456,0.002889511,0.000018896088],"about_ca_topic_score_codex":0.0022691037,"about_ca_topic_score_gemma":0.0025791102,"teacher_disagreement_score":0.0022691037,"about_ca_system_score_codex":0.0002428702,"about_ca_system_score_gemma":0.0004940331,"threshold_uncertainty_score":0.005400181},"labels":[],"label_agreement":null},{"id":"W2883730994","doi":"10.1007/s00234-018-2053-x","title":"Impact of white matter hyperintensities on surrounding white matter tracts","year":2018,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Hyperintensity; White matter; Neuroradiology; Medicine; Neurology; White (mutation); Magnetic resonance imaging; Neurosurgery; Pathology; Radiology; Biology; Psychiatry","score_opus":0.06462821543391545,"score_gpt":0.3667525050291711,"score_spread":0.30212428959525567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883730994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97838724,0.004343722,0.002555506,0.0009294553,0.000120108154,0.000034205466,0.0003280305,0.0000968309,0.0132049965],"genre_scores_gemma":[0.9955668,0.0011565429,0.00070417015,0.00009974083,0.000111252484,0.0000045250827,0.00012324855,0.000045470995,0.0021882432],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996742,0.00007193422,0.000027456581,0.000049638424,0.00010976015,0.0000670745],"domain_scores_gemma":[0.9983398,0.0006156334,0.0003878913,0.00014081612,0.0002898226,0.00022606585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007778743,0.00053628505,0.00029299603,0.0008181444,0.0005431519,0.0011496394,0.00034550362,0.00053006195,0.007946019],"category_scores_gemma":[0.0040759984,0.00018133438,0.00037078105,0.00059469073,0.0006055116,0.0008471007,0.0005107375,0.0005805456,0.00062029343],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007795641,0.00076922233,0.52281743,0.0007852831,0.0020552934,0.03826994,0.000682124,0.0067395363,0.20577963,0.005068035,0.0030106697,0.20622726],"study_design_scores_gemma":[0.00009055229,0.00087124406,0.94120806,0.0001603622,0.000969801,0.013589835,0.00057979143,0.0040098005,0.028999638,0.004429026,0.00505071,0.000041205316],"about_ca_topic_score_codex":0.003878219,"about_ca_topic_score_gemma":0.0057229567,"teacher_disagreement_score":0.007946019,"about_ca_system_score_codex":0.0004040629,"about_ca_system_score_gemma":0.0006437138,"threshold_uncertainty_score":0.026582062},"labels":[],"label_agreement":null},{"id":"W2885277692","doi":"10.2147/ndt.s169583","title":"Abnormal white matter integrity in Chinese young adults with first-episode medication-free anxious depression: a possible neurological biomarker of subtype major depressive disorder","year":2018,"lang":"en","type":"article","venue":"Neuropsychiatric Disease and Treatment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Uncinate fasciculus; Fractional anisotropy; Major depressive disorder; White matter; Medicine; Diffusion MRI; Depression (economics); Anxiety; Superior longitudinal fasciculus; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology; Mood","score_opus":0.01220636934380843,"score_gpt":0.2826764052142453,"score_spread":0.2704700358704369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885277692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997037,0.00009619539,0.00002027077,0.0000149746365,0.000001459,0.0000058384444,0.000054656077,9.055535e-7,0.00010206406],"genre_scores_gemma":[0.99972624,0.00006937876,0.00004286891,0.000016286122,0.0000032093692,0.0000042409674,0.00008993695,2.9282216e-7,0.000047580026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993396,0.0000071093505,0.000011100134,0.000019697995,0.000014331853,0.000013898158],"domain_scores_gemma":[0.99978703,0.000018809855,0.000113719565,0.000011751928,0.000024749907,0.00004389149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015662904,0.00025693464,0.00023091763,0.00078666944,0.0003936574,0.0002852532,0.00014664521,0.0002930726,0.00073620543],"category_scores_gemma":[0.00050139625,0.00017004435,0.00017430766,0.0004987058,0.00021061339,0.00017706276,0.00016935391,0.00014135931,0.000086084096],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007880019,0.000020569103,0.9954917,0.000018011991,0.000030508221,0.00033944283,0.0002260422,0.000020772799,0.002254318,0.000012922836,0.00004753073,0.0014593797],"study_design_scores_gemma":[0.0000016458599,0.000020389596,0.9996567,0.0000011400431,0.000007762695,0.0001786934,0.000054570955,0.000026258727,0.00003281527,0.0000048794573,0.00001448265,6.93865e-7],"about_ca_topic_score_codex":0.010685136,"about_ca_topic_score_gemma":0.01911344,"teacher_disagreement_score":0.010685136,"about_ca_system_score_codex":0.0002905246,"about_ca_system_score_gemma":0.00024419787,"threshold_uncertainty_score":0.021245897},"labels":[],"label_agreement":null},{"id":"W2885417691","doi":"10.1016/j.nicl.2018.08.021","title":"Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Tractography; Diffusion MRI; Siemens; Protocol (science); Variance (accounting); Epilepsy surgery; Temporal lobe; Nuclear medicine; Computer science; Artificial intelligence; Psychology; Medicine; Radiology; Physics; Magnetic resonance imaging; Neuroscience; Electroencephalography; Epilepsy; Pathology","score_opus":0.23602589910635866,"score_gpt":0.5001529943187989,"score_spread":0.26412709521244027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885417691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70642966,0.0029660177,0.28433514,0.00046111803,0.00013869682,0.00047356368,0.0003936339,0.0008723577,0.0039297994],"genre_scores_gemma":[0.84684736,0.00090065197,0.14994545,0.00013429149,0.00009369347,0.0004223941,0.00036001354,0.0003578896,0.00093829783],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99837756,0.0008037982,0.00015871515,0.00027474147,0.00034407395,0.00004105511],"domain_scores_gemma":[0.9920953,0.004573674,0.0009566584,0.0014370645,0.0008231922,0.00011422495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055986177,0.00052689755,0.00028161707,0.0004069832,0.0002551516,0.0009535576,0.00062311057,0.0004984071,0.003080561],"category_scores_gemma":[0.017739398,0.0003169357,0.00027390858,0.00037091097,0.0007073231,0.00083249074,0.00045109427,0.00036011118,0.00063229474],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003139543,0.00031345172,0.14690787,0.00179134,0.0005460416,0.00082605454,0.0010615353,0.009974332,0.2939641,0.0036896374,0.0024523835,0.53533375],"study_design_scores_gemma":[0.00034912504,0.0035681347,0.67004925,0.0010828492,0.0009172782,0.011225536,0.0005136859,0.0724797,0.20887478,0.013550383,0.017141908,0.00024738925],"about_ca_topic_score_codex":0.0009338394,"about_ca_topic_score_gemma":0.0019553876,"teacher_disagreement_score":0.0055986177,"about_ca_system_score_codex":0.00042207554,"about_ca_system_score_gemma":0.00068674714,"threshold_uncertainty_score":0.029608667},"labels":[],"label_agreement":null},{"id":"W2885904423","doi":"10.3389/fneur.2018.00575","title":"Pathological Insights From Quantitative Susceptibility Mapping and Diffusion Tensor Imaging in Ice Hockey Players Pre and Post-concussion","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Vertex Pharmaceuticals; Canadian Institutes of Health Research; Teva Pharmaceutical Industries; Biogen; Celgene; Sanofi","keywords":"Myelin; Diffusion MRI; White matter; Fractional anisotropy; Concussion; Voxel; Chemistry; Biophysics; Neuroscience; Magnetic resonance imaging; Medicine; Psychology; Biology; Radiology; Poison control; Central nervous system","score_opus":0.027008619643349708,"score_gpt":0.30872483542783874,"score_spread":0.281716215784489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885904423","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975727,0.00029220383,0.0013463969,0.00003561387,0.0000060010325,0.000023380171,0.00013980063,0.0000107041615,0.0005733206],"genre_scores_gemma":[0.99867517,0.00013704791,0.0005937928,0.000015281283,0.000007818423,0.000018063318,0.00011704322,0.000008859891,0.00042674647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99955314,0.000104154264,0.000057166773,0.00011474979,0.000095530115,0.00007512653],"domain_scores_gemma":[0.99848783,0.00036231763,0.0006170573,0.00019559247,0.00023233272,0.00010479519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014150558,0.00040977309,0.00030786043,0.002601403,0.00034232574,0.0011119304,0.00030594424,0.00047981009,0.000952307],"category_scores_gemma":[0.003551878,0.00033897508,0.00031033315,0.000912246,0.0012704132,0.0005662363,0.00037576928,0.00030018963,0.00030727545],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025205251,0.0002226665,0.866002,0.00025002044,0.00037705366,0.0063063633,0.0038072518,0.0017584284,0.08917901,0.0008134109,0.0003266655,0.028436705],"study_design_scores_gemma":[0.000008908092,0.00031048842,0.9906722,0.00002364642,0.000049131322,0.0029911194,0.0011183289,0.0010034625,0.0031276178,0.00030567535,0.00037214684,0.00001720988],"about_ca_topic_score_codex":0.0046861973,"about_ca_topic_score_gemma":0.0047572698,"teacher_disagreement_score":0.0046861973,"about_ca_system_score_codex":0.00038967203,"about_ca_system_score_gemma":0.00035425666,"threshold_uncertainty_score":0.009317875},"labels":[],"label_agreement":null},{"id":"W2885963010","doi":"10.1016/j.nicl.2018.101650","title":"Girls' internalizing symptoms and white matter tracts in Cortico-Limbic circuitry","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Western University; Canada Foundation for Innovation; Fondation Brain Canada; Children's Health Research Institute","keywords":"Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); White matter; Psychology; Diffusion MRI; Limbic system; Fasciculus; Psychopathology; Neuroscience; Audiology; Developmental psychology; Medicine; Clinical psychology; Magnetic resonance imaging; Central nervous system","score_opus":0.12614242268611708,"score_gpt":0.4423561381816067,"score_spread":0.3162137154954896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885963010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996897,0.000034228822,0.000039947765,0.000007641336,5.5217095e-7,9.750725e-7,0.000069120055,0.0000022523366,0.00015567044],"genre_scores_gemma":[0.99952066,0.000052148618,0.00012613909,0.000003713134,9.41968e-7,0.00000207411,0.00011302151,0.0000025547245,0.00017874918],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999895,0.0000131344395,0.000008795654,0.000041487056,0.000019424184,0.000022145809],"domain_scores_gemma":[0.99952126,0.000055514916,0.00029419077,0.00002737865,0.00003248109,0.00006911658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016360472,0.00027336413,0.0001691462,0.0005806078,0.00019738272,0.0004533216,0.00012717163,0.00020453129,0.0015505835],"category_scores_gemma":[0.00073715136,0.0001661479,0.00019015333,0.00023934522,0.0002628799,0.0002023975,0.00026617115,0.00031493837,0.00014285732],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007407288,0.000020886819,0.99059063,0.000005528527,0.000022550486,0.0001907622,0.00024391785,0.00004593013,0.006611505,0.000056693963,0.000032458825,0.0021049622],"study_design_scores_gemma":[8.220301e-7,0.000028259929,0.9989793,0.000002159421,0.000005140183,0.0002876205,0.0000973099,0.000035258236,0.0005072934,0.000018452029,0.000037610345,7.069494e-7],"about_ca_topic_score_codex":0.004255044,"about_ca_topic_score_gemma":0.0076077883,"teacher_disagreement_score":0.004255044,"about_ca_system_score_codex":0.00023670113,"about_ca_system_score_gemma":0.0001964389,"threshold_uncertainty_score":0.008460581},"labels":[],"label_agreement":null},{"id":"W2886571235","doi":"10.1097/md.0000000000011803","title":"Cognitive decline and white matter changes in mesial temporal lobe epilepsy","year":2018,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Fractional anisotropy; Fasciculus; Uncinate fasciculus; Superior longitudinal fasciculus; Diffusion MRI; Hippocampal sclerosis; Corpus callosum; Epilepsy; Voxel-based morphometry; Temporal lobe; Cardiology; Magnetic resonance imaging; Anatomy; Radiology; Psychiatry","score_opus":0.060242372306823694,"score_gpt":0.38086392421319853,"score_spread":0.32062155190637487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886571235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996487,0.00013419733,0.00002856899,0.000010087102,0.0000010386344,0.000002416158,0.000027710857,0.000002481893,0.0001447329],"genre_scores_gemma":[0.99965477,0.00007941996,0.000045700963,0.0000116085275,0.0000065745803,0.0000044698168,0.00008513997,9.425312e-7,0.00011139293],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992764,0.00001396651,0.000011496121,0.000016793601,0.000017549883,0.00001268216],"domain_scores_gemma":[0.9997713,0.00003199821,0.000119719254,0.000016305723,0.000020259966,0.000040418407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021177022,0.00033663365,0.00019026214,0.0006535679,0.00024910067,0.00026534614,0.00013212283,0.0002752227,0.00064338505],"category_scores_gemma":[0.00065063074,0.00011591314,0.00012626768,0.00025705103,0.0003352044,0.00027620688,0.00018526654,0.00017518578,0.000146024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011937171,0.00016843631,0.9766,0.000037383645,0.00009318629,0.0016418253,0.0002850524,0.00013853211,0.009152537,0.000031512984,0.00012315405,0.0105347065],"study_design_scores_gemma":[0.000009687954,0.00021402082,0.9984029,0.0000013608623,0.000008877569,0.00095263665,0.000047100613,0.00006936149,0.00021781678,0.000023877285,0.00005032354,0.0000019647052],"about_ca_topic_score_codex":0.0019661037,"about_ca_topic_score_gemma":0.0025444478,"teacher_disagreement_score":0.0019661037,"about_ca_system_score_codex":0.00017007256,"about_ca_system_score_gemma":0.0001281132,"threshold_uncertainty_score":0.0039093494},"labels":[],"label_agreement":null},{"id":"W2886832730","doi":"10.1093/schbul/sby016.418","title":"T142. PARIETAL CONNECTIVITY IN SCHIZOPHRENIA AND PSYCHOTIC BIPOLAR DISORDER: A COMBINED STRUCTURAL AND DYNAMIC FUNCTIONAL CONNECTIVITY STUDY","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Supramarginal gyrus; Parietal lobe; Psychology; Schizophrenia (object-oriented programming); Resting state fMRI; Bipolar disorder; Neuroscience; Psychosis; Temporal lobe; Fractional anisotropy; Middle frontal gyrus; Superior temporal gyrus; Angular gyrus; Diffusion MRI; Functional magnetic resonance imaging; Psychiatry; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.021794763789255628,"score_gpt":0.3014564537811058,"score_spread":0.27966168999185015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886832730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927646,0.00009759204,0.00012367807,0.000020267038,0.0000021339413,0.0000091550155,0.000114062284,0.0000022865286,0.0003544114],"genre_scores_gemma":[0.9993697,0.000044191176,0.00017372576,0.000010612044,0.000006323267,0.000011651538,0.0002074246,0.000002048843,0.00017445878],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993455,0.0000145220865,0.000006555188,0.000018035458,0.000012945659,0.000013375247],"domain_scores_gemma":[0.99985564,0.000022877392,0.000053751035,0.000009250374,0.000014868924,0.000043582164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023477852,0.00025151414,0.00020497365,0.00060692575,0.00030666232,0.00027766352,0.00011963861,0.00027162503,0.0030430355],"category_scores_gemma":[0.00046671144,0.0001953753,0.00020700332,0.00040592713,0.00022006391,0.00017674766,0.00035548437,0.00017762113,0.00020119727],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004198665,0.00029681154,0.9256196,0.00015046855,0.00053950935,0.0037825864,0.0010264651,0.0004488941,0.047027104,0.00044921527,0.0004728499,0.015987856],"study_design_scores_gemma":[0.000049671253,0.00024286725,0.9971009,0.0000070230135,0.000051932453,0.0015598513,0.00013932055,0.00032374347,0.00023247447,0.00012901054,0.00015880831,0.00000435203],"about_ca_topic_score_codex":0.004783129,"about_ca_topic_score_gemma":0.007882276,"teacher_disagreement_score":0.004783129,"about_ca_system_score_codex":0.00019364123,"about_ca_system_score_gemma":0.0002484638,"threshold_uncertainty_score":0.010179937},"labels":[],"label_agreement":null},{"id":"W2887072805","doi":"10.1016/j.neuroimage.2018.10.029","title":"Limits to anatomical accuracy of diffusion tractography using modern approaches","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":282,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Vanderbilt Institute for Clinical and Translational Research; National Institute on Aging; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University","keywords":"Tractography; Diffusion MRI; Computer science; White matter; Artificial intelligence; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.220788248719264,"score_gpt":0.3910391396846636,"score_spread":0.17025089096539958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887072805","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03449526,0.03927862,0.90027475,0.010923196,0.0009039736,0.000075131284,0.0005936346,0.0022105721,0.011244883],"genre_scores_gemma":[0.4422862,0.027380077,0.5214506,0.0020709473,0.0015693228,0.00015555792,0.0005986307,0.0010481208,0.0034406248],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9846864,0.0056864456,0.0010190379,0.002134641,0.0061140005,0.0003595216],"domain_scores_gemma":[0.8150078,0.15394624,0.0039460277,0.015522345,0.01075903,0.0008185717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027020859,0.0010231818,0.0021723155,0.0028619259,0.0008078857,0.0049480563,0.0034148167,0.0036375073,0.0032193488],"category_scores_gemma":[0.118182994,0.0016284101,0.0009059764,0.0019461095,0.0042369915,0.007658373,0.003773253,0.0047066994,0.0028065597],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094238133,0.00012532748,0.010543904,0.004852907,0.0013785807,0.0003308407,0.0016068337,0.05407667,0.05442746,0.16160457,0.014223048,0.6958875],"study_design_scores_gemma":[0.00014022666,0.0004149077,0.03444308,0.0020239132,0.00067646545,0.0057005677,0.00063420273,0.30518982,0.06076209,0.50832146,0.08116945,0.00052376866],"about_ca_topic_score_codex":0.0035310593,"about_ca_topic_score_gemma":0.0035558767,"teacher_disagreement_score":0.027020859,"about_ca_system_score_codex":0.0016229308,"about_ca_system_score_gemma":0.0018769376,"threshold_uncertainty_score":0.14290166},"labels":[],"label_agreement":null},{"id":"W2887719417","doi":"10.1016/j.neurobiolaging.2018.07.018","title":"Re-examining age-related differences in white matter microstructure with free-water corrected diffusion tensor imaging","year":2018,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":124,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Nursing Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"White matter; Diffusion MRI; Free water; Myelin; Cohort; Neuroscience; Medicine; Psychology; Magnetic resonance imaging; Pathology; Radiology; Geology; Central nervous system","score_opus":0.024024038761350237,"score_gpt":0.2752394576277168,"score_spread":0.25121541886636656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887719417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9310956,0.0058567217,0.053826205,0.001267837,0.001198056,0.00013081652,0.0023143247,0.00059503474,0.0037154718],"genre_scores_gemma":[0.95030063,0.0030320927,0.0377938,0.00044432582,0.00022099719,0.00008536802,0.0012630636,0.00031238832,0.00654726],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997054,0.00003902329,0.00004844698,0.000113693255,0.00005974644,0.00003365102],"domain_scores_gemma":[0.99858475,0.00013341184,0.00020838881,0.000460049,0.0005419327,0.00007132623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002058864,0.0007666817,0.000472058,0.00087702443,0.00047407747,0.00090513774,0.000603569,0.00066257996,0.001428511],"category_scores_gemma":[0.0040997365,0.00022840734,0.00055523985,0.0006053991,0.00040474645,0.0017563157,0.00038131844,0.0007503226,0.0004988458],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016534309,0.00032098618,0.17138031,0.001201833,0.0018025131,0.001686497,0.0018437089,0.0033587627,0.548182,0.0022904433,0.013374909,0.25290462],"study_design_scores_gemma":[0.00006737205,0.0011117922,0.793488,0.00023604919,0.0017373792,0.0043832688,0.0014203042,0.012053633,0.13472323,0.008935251,0.041703295,0.00014047622],"about_ca_topic_score_codex":0.008440992,"about_ca_topic_score_gemma":0.020280786,"teacher_disagreement_score":0.008440992,"about_ca_system_score_codex":0.00024500152,"about_ca_system_score_gemma":0.00069315743,"threshold_uncertainty_score":0.016783714},"labels":[],"label_agreement":null},{"id":"W2888278728","doi":"10.1186/s13742-016-0147-0-w","title":"DIPY: Brain tissue classification","year":2016,"lang":"en","type":"article","venue":"GigaScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Brain tissue; Computer science; Computational biology; Artificial intelligence; Neuroscience; Biology","score_opus":0.11838140739627466,"score_gpt":0.4176493103567173,"score_spread":0.29926790296044264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888278728","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009303508,0.0024003286,0.6017347,0.0014131118,0.0013102675,0.0005397053,0.05177254,0.31326228,0.018263593],"genre_scores_gemma":[0.070703104,0.0017702231,0.7552211,0.0014042803,0.0005592469,0.0012440807,0.10937375,0.019338323,0.040385876],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993512,0.00004685106,0.000039388826,0.00019899408,0.00027120393,0.00009231087],"domain_scores_gemma":[0.9994293,0.00011671635,0.000046338442,0.00020242156,0.000114935545,0.000090222544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007411061,0.0016259622,0.0010456936,0.0024811176,0.0005493124,0.0020400002,0.0020623165,0.001422794,0.040197026],"category_scores_gemma":[0.0024572168,0.0006072538,0.0011723812,0.0018051886,0.00034484925,0.0017145707,0.0036812224,0.0014643109,0.033867937],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002477238,0.000064312255,0.0014039146,0.0003940678,0.00008958153,0.00022052097,0.00006313358,0.0039300513,0.011429985,0.0051910724,0.39739877,0.5795669],"study_design_scores_gemma":[0.00028386808,0.00018497383,0.0069699464,0.00023386117,0.00014432425,0.0024944977,0.00014883972,0.2822153,0.07390467,0.05391905,0.5793519,0.00014878793],"about_ca_topic_score_codex":0.0024061392,"about_ca_topic_score_gemma":0.0029496723,"teacher_disagreement_score":0.040197026,"about_ca_system_score_codex":0.00058178854,"about_ca_system_score_gemma":0.001144427,"threshold_uncertainty_score":0.13447243},"labels":[],"label_agreement":null},{"id":"W2889179699","doi":"10.1093/cercor/bhy204","title":"Maturation of the Human Cerebral Cortex During Adolescence: Myelin or Dendritic Arbor?","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; Medical Research Council; National Institutes of Health; Vetenskapsrådet; Svenska Forskningsrådet Formas; Fondation pour la Recherche Médicale; EU Joint Programme – Neurodegenerative Disease Research; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft; National Institute for Health and Care Research; Mission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives; European Commission","keywords":"Myelin; Neuroscience; Cortex (anatomy); Biology; Cerebral cortex; White matter; Human brain; Oligodendrocyte; Central nervous system; Magnetic resonance imaging; Medicine","score_opus":0.04529827670135839,"score_gpt":0.3405659199363404,"score_spread":0.295267643234982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889179699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990595,0.0026107547,0.005156795,0.00011697209,0.000006106798,0.0000116842375,0.00018977486,0.0000361658,0.0012767543],"genre_scores_gemma":[0.9969505,0.0013530325,0.0012528641,0.000022206052,0.0000054961893,0.000007249202,0.00009548623,0.000012229045,0.0003008856],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994206,0.0000130349545,0.0000029949874,0.000018703111,0.000012435561,0.000010836429],"domain_scores_gemma":[0.9998658,0.000027155056,0.00005589722,0.000013070057,0.000022725626,0.000015289046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017964681,0.000105363346,0.00011323611,0.00038435785,0.00010951328,0.00025801084,0.00011357729,0.00017616803,0.00064844463],"category_scores_gemma":[0.00048344475,0.00011244343,0.00009193312,0.00019043367,0.00026559064,0.0002927012,0.00015566201,0.00016472803,0.00019495939],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005755545,0.000046364727,0.13358527,0.00026392264,0.00007752111,0.0010452872,0.00091095606,0.00086408627,0.78658897,0.0012538848,0.00040239442,0.07438584],"study_design_scores_gemma":[0.000005753623,0.00018414378,0.9334803,0.000038624486,0.000049633807,0.00323988,0.00045467817,0.0018624283,0.057032995,0.0012060486,0.0024272408,0.000018208759],"about_ca_topic_score_codex":0.001989847,"about_ca_topic_score_gemma":0.0031393317,"teacher_disagreement_score":0.001989847,"about_ca_system_score_codex":0.00015495798,"about_ca_system_score_gemma":0.00017960125,"threshold_uncertainty_score":0.0039564967},"labels":[],"label_agreement":null},{"id":"W2889302022","doi":"10.3389/fpsyt.2018.00391","title":"Associations Among Suicidal Ideation, White Matter Integrity and Cognitive Deficit in First-Episode Schizophrenia","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Xiangya Hospital, Central South University; Natural Science Foundation of Hunan Province; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Psychology; Working memory; Cognitive deficit; Fractional anisotropy; Cognition; Corona radiata (embryology); Suicidal ideation; Schizophrenia (object-oriented programming); Precuneus; Clinical psychology; Wechsler Adult Intelligence Scale; White matter; Psychiatry; Poison control; Medicine; Injury prevention; Internal medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.019359267026921596,"score_gpt":0.30792116874827413,"score_spread":0.28856190172135254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889302022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99977857,0.00007993835,0.00001444951,0.000012231499,7.446611e-7,0.0000022815486,0.00004262691,8.198283e-7,0.00006841454],"genre_scores_gemma":[0.9997652,0.00005680312,0.00004378351,0.0000049416653,0.0000013684323,0.0000019305096,0.00007605985,3.8853423e-7,0.000049423663],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999076,0.000017623513,0.000020747757,0.000015216893,0.000021724807,0.000017159353],"domain_scores_gemma":[0.99936944,0.000058177782,0.00039576212,0.00002389705,0.000056491022,0.00009628179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034116604,0.00028178733,0.000200147,0.00077040074,0.0002380689,0.0003493923,0.00014092663,0.00030906973,0.0013817173],"category_scores_gemma":[0.0010008075,0.00013901116,0.00023275227,0.00035273746,0.00019115079,0.00021543837,0.00028730487,0.0002500544,0.00011670759],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020133331,0.000053410735,0.9963664,0.000021941076,0.000059445374,0.00014120761,0.000095763506,0.000046335157,0.0012122088,0.000014759537,0.000023834556,0.0017634337],"study_design_scores_gemma":[0.0000043503806,0.0000690548,0.9993462,0.0000056734257,0.000012758513,0.0002916491,0.00008259773,0.00007630494,0.0000715336,0.000018841623,0.000019512587,0.0000015838081],"about_ca_topic_score_codex":0.0025537359,"about_ca_topic_score_gemma":0.0046139807,"teacher_disagreement_score":0.0025537359,"about_ca_system_score_codex":0.00022936211,"about_ca_system_score_gemma":0.00021843505,"threshold_uncertainty_score":0.0050777793},"labels":[],"label_agreement":null},{"id":"W2889789314","doi":"10.1002/jmri.26269","title":"Evaluation of Intra‐ and Interscanner Reliability of MRI Protocols for Spinal Cord Gray Matter and Total Cross‐Sectional Area Measurements","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"School of Medicine, University of California, San Francisco; University of California, San Francisco; Polytechnique Montréal","keywords":"Gray (unit); Medicine; Spinal cord; Reliability (semiconductor); Cross-sectional study; Nuclear medicine; Radiology; Pathology; Physics","score_opus":0.12262668503511116,"score_gpt":0.4348650783346461,"score_spread":0.31223839329953496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889789314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98000205,0.0012974857,0.015747579,0.000041479667,0.00014468248,0.0006001141,0.0004702542,0.0002535462,0.0014429403],"genre_scores_gemma":[0.9815547,0.00016452138,0.016147101,0.00004702548,0.000057650464,0.0006077242,0.0005922894,0.00011779968,0.0007111768],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9934325,0.0029388973,0.00081244245,0.0016294775,0.0010046754,0.00018194428],"domain_scores_gemma":[0.96467775,0.0147119975,0.0044695428,0.005524944,0.009916455,0.0006993041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012294137,0.00080367574,0.00056561927,0.0010847858,0.00057580275,0.00086518266,0.0008852033,0.0010104212,0.001303194],"category_scores_gemma":[0.034017988,0.0006030523,0.0007217041,0.000517652,0.00074496266,0.00070479815,0.0009453474,0.0005937195,0.00060476497],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.032825124,0.0022523773,0.65321684,0.0012128875,0.009550477,0.00035139453,0.004433479,0.008512958,0.116376236,0.00071466115,0.0026251192,0.16792837],"study_design_scores_gemma":[0.0005904659,0.008187213,0.94501597,0.00008895399,0.0013266087,0.0009629072,0.00048592943,0.015480265,0.024329403,0.0005340177,0.0028493197,0.00014887274],"about_ca_topic_score_codex":0.0011669496,"about_ca_topic_score_gemma":0.003125325,"teacher_disagreement_score":0.012294137,"about_ca_system_score_codex":0.00039375797,"about_ca_system_score_gemma":0.00040645877,"threshold_uncertainty_score":0.065018415},"labels":[],"label_agreement":null},{"id":"W2889989509","doi":"10.1111/jon.12559","title":"Multicenter Measurements of T<sub>1</sub> Relaxation and Diffusion Tensor Imaging: Intra and Intersite Reproducibility","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Fractional anisotropy; Reproducibility; Diffusion MRI; Intraclass correlation; Medicine; White matter; Nuclear medicine; Corpus callosum; Magnetic resonance imaging; Pathology; Radiology; Mathematics; Statistics","score_opus":0.07068274961811168,"score_gpt":0.3370152020516118,"score_spread":0.2663324524335001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889989509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97116446,0.0008191429,0.025106061,0.000071146416,0.000056698747,0.0001539369,0.0005724716,0.00023250454,0.0018235712],"genre_scores_gemma":[0.99313086,0.000056632765,0.0060413964,0.000024485287,0.000030163956,0.00008283621,0.00036113997,0.00005228861,0.00022011093],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9910069,0.004425124,0.0008659725,0.002259896,0.0012318449,0.00021027224],"domain_scores_gemma":[0.97220165,0.010617954,0.0050191954,0.0050646774,0.0065837554,0.0005127423],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.013951505,0.00061926735,0.0005436083,0.00085043925,0.0005824163,0.00093964254,0.0005615058,0.0007347472,0.0006513564],"category_scores_gemma":[0.023521956,0.000296667,0.00048138603,0.00062815537,0.0007087839,0.0005610909,0.000851577,0.00051796366,0.00032961965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038566797,0.00041545977,0.7947204,0.00039240878,0.0026938834,0.00021611823,0.0025067322,0.004498839,0.112593055,0.0006309799,0.0015503736,0.07592493],"study_design_scores_gemma":[0.00008227737,0.0017504035,0.9577944,0.000048012702,0.00063985016,0.0006865428,0.00034181817,0.007608818,0.02848525,0.0006336535,0.001850781,0.00007800145],"about_ca_topic_score_codex":0.0013831701,"about_ca_topic_score_gemma":0.0017787801,"teacher_disagreement_score":0.9860485,"about_ca_system_score_codex":0.00025380455,"about_ca_system_score_gemma":0.00031458668,"threshold_uncertainty_score":0.07378352},"labels":[],"label_agreement":null},{"id":"W2890034454","doi":"10.1016/j.neuroimage.2018.09.004","title":"Corpus callosum microstructure is associated with motor function in preschool children","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Alberta Children's Hospital Foundation; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Corticospinal tract; Motor skill; White matter; Psychology; Motor function; Physical medicine and rehabilitation; Audiology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.021710149441484045,"score_gpt":0.28807220158875935,"score_spread":0.2663620521472753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890034454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99926084,0.00021481252,0.000077863326,0.000039717223,0.0000025730562,0.0000025835902,0.0001342287,0.000012071277,0.00025523122],"genre_scores_gemma":[0.9984074,0.00025393936,0.0003600443,0.000018715362,0.000004598111,0.000012567571,0.00023498546,0.000012368363,0.00069545285],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998111,0.00001899262,0.00002030352,0.000067670466,0.000030393681,0.000051652212],"domain_scores_gemma":[0.9990214,0.00015943531,0.0005663053,0.000055072676,0.00011149107,0.00008630839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037189614,0.0005471741,0.0003777528,0.0013192558,0.0004879518,0.0008070029,0.00048674742,0.0007105407,0.002549743],"category_scores_gemma":[0.0019763815,0.00047039238,0.00036108246,0.0007832783,0.00075158454,0.0007506222,0.00063588633,0.00059178,0.00029087352],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007594382,0.00014177007,0.95865184,0.00012557066,0.00014993224,0.002292249,0.0017498716,0.00035907925,0.023109764,0.00041766156,0.0004603235,0.01178249],"study_design_scores_gemma":[0.0000024069502,0.000040086124,0.9980307,0.000012649582,0.000024495885,0.00044321243,0.0003854556,0.000087771085,0.0007910065,0.00007465343,0.000102884165,0.000004519591],"about_ca_topic_score_codex":0.030422742,"about_ca_topic_score_gemma":0.035766177,"teacher_disagreement_score":0.030422742,"about_ca_system_score_codex":0.0007741595,"about_ca_system_score_gemma":0.0007744093,"threshold_uncertainty_score":0.060491323},"labels":[],"label_agreement":null},{"id":"W2890400814","doi":"10.1038/s41393-018-0191-y","title":"Decreased white matter fractional anisotropy is associated with poorer functional motor skills following spinal cord injury: a pilot study","year":2018,"lang":"en","type":"article","venue":"Spinal Cord","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"GF Strong Rehabilitation Centre; University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries; University of New Brunswick","funders":"International Collaboration on Repair Discoveries","keywords":"Fractional anisotropy; White matter; Corpus callosum; Corticospinal tract; Diffusion MRI; Medicine; Superior longitudinal fasciculus; Spinal cord injury; Physical medicine and rehabilitation; Grip strength; Spinal cord; Physical therapy; Neuroscience; Anatomy; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.06935069524829889,"score_gpt":0.378778178087942,"score_spread":0.3094274828396431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890400814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99979395,0.00002985059,0.00003829245,0.000008344524,0.0000029608673,0.000020387652,0.000023050517,0.0000012702184,0.00008183459],"genre_scores_gemma":[0.9995017,0.000048450092,0.00008605812,0.0000151455215,0.000016447208,0.00003069155,0.00008340275,0.0000016048543,0.0002165365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996086,0.00011891491,0.00004010794,0.00009535228,0.00005408768,0.00008291029],"domain_scores_gemma":[0.9974452,0.0006392393,0.0008002949,0.0002347937,0.00025836617,0.00062198925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011415733,0.0009367361,0.0007980429,0.0009458875,0.0010390689,0.00055545,0.0006656934,0.00096888014,0.0024425827],"category_scores_gemma":[0.0021535738,0.0005147056,0.00075363857,0.00085906184,0.0013621612,0.0008276555,0.0006118763,0.0011225962,0.00046139912],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02270155,0.015087039,0.9365193,0.000107472224,0.0004933564,0.0037795124,0.0010288333,0.00014962237,0.014061539,0.000078299934,0.00017371814,0.0058198147],"study_design_scores_gemma":[0.0002673398,0.017686486,0.97870535,0.000008722371,0.00019116375,0.0014913208,0.00054644747,0.00021555851,0.00071020535,0.000046616904,0.00011586234,0.000014947022],"about_ca_topic_score_codex":0.0037548714,"about_ca_topic_score_gemma":0.0033422923,"teacher_disagreement_score":0.0037548714,"about_ca_system_score_codex":0.00039493162,"about_ca_system_score_gemma":0.00067630515,"threshold_uncertainty_score":0.008171201},"labels":[],"label_agreement":null},{"id":"W2890509943","doi":"10.1017/s0033291718002647","title":"Aberrant myelination of the cingulum and Schneiderian delusions in schizophrenia: a 7T magnetization transfer study","year":2018,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Cingulum (brain); Schizophrenia (object-oriented programming); Psychology; Neuroscience; Audiology; White matter; Medicine; Psychiatry; Magnetic resonance imaging; Fractional anisotropy; Radiology","score_opus":0.09328243376669865,"score_gpt":0.40815789258830815,"score_spread":0.3148754588216095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890509943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99958354,0.00006258299,0.00018907063,0.0000140275815,0.000001062251,0.0000046762284,0.000020029873,0.000003290564,0.00012160607],"genre_scores_gemma":[0.9994885,0.00005129903,0.00032393707,0.0000065257664,0.000004046851,0.0000036547733,0.000041258354,0.0000031665822,0.00007756108],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999002,0.000026578758,0.000010897139,0.000021605225,0.00002427464,0.00001646937],"domain_scores_gemma":[0.9995585,0.00007653434,0.00018496433,0.00005261408,0.00005144108,0.00007592833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006079496,0.00032571892,0.00015674708,0.00080515014,0.00031609496,0.00026371886,0.00018027038,0.00031082053,0.0014464112],"category_scores_gemma":[0.0010826127,0.0002201972,0.00017067525,0.00026710946,0.00042475303,0.00022222748,0.0003058492,0.00027775808,0.00016416432],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044598714,0.00046407245,0.6742123,0.00017617077,0.0003729343,0.0066092173,0.0026831494,0.00059389294,0.28093395,0.00045647655,0.00026961722,0.028768323],"study_design_scores_gemma":[0.00004388971,0.0006717942,0.98852134,0.000010864128,0.00009191825,0.0043318113,0.00030231208,0.00089532067,0.0047132843,0.00018365592,0.00022186307,0.000012044903],"about_ca_topic_score_codex":0.0017507726,"about_ca_topic_score_gemma":0.0019829,"teacher_disagreement_score":0.0017507726,"about_ca_system_score_codex":0.00023225395,"about_ca_system_score_gemma":0.00019836456,"threshold_uncertainty_score":0.0048387647},"labels":[],"label_agreement":null},{"id":"W2891370352","doi":"10.1016/j.nicl.2018.09.005","title":"Early changes in white matter predict intellectual outcome in children treated for posterior fossa tumors","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children's & Women's Health Centre of British Columbia; SickKids Foundation; Alberta Children's Hospital; Hospital for Sick Children","funders":"Canadian Cancer Society Research Institute; Canadian Cancer Society","keywords":"White matter; Diffusion MRI; Medicine; Tractography; Voxel; Optic radiation; Neuroimaging; Magnetic resonance imaging; Radiology; Nuclear medicine; Psychology; Psychiatry","score_opus":0.11640286118457063,"score_gpt":0.4216149981999025,"score_spread":0.3052121370153319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891370352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996518,0.00014049606,0.000024932442,0.00001235105,0.0000015233927,0.000002548885,0.00008090763,0.000001495731,0.00008389011],"genre_scores_gemma":[0.999519,0.000099133,0.00004955986,0.0000047972594,0.0000037462103,0.0000044413714,0.00022625993,9.796862e-7,0.000092143324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983716,0.000035020243,0.000013214012,0.000030604362,0.0000409834,0.000042951586],"domain_scores_gemma":[0.9986002,0.0002080747,0.00090655504,0.00003950042,0.00009645572,0.00014934938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035286054,0.00026981518,0.00022040431,0.00044994787,0.0002941565,0.00035762787,0.00021461213,0.0003098879,0.0009679095],"category_scores_gemma":[0.0019242476,0.00012913179,0.0002811079,0.0003916124,0.00031123002,0.0003282818,0.00026284007,0.00039931928,0.0001693271],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013068753,0.000027076103,0.9977738,0.000005384893,0.0000146639795,0.00014861567,0.00006180611,0.000030005118,0.00024392907,0.0000028731233,0.00003228761,0.0015287994],"study_design_scores_gemma":[0.0000024427384,0.00010210184,0.9993814,0.0000021451576,0.000008417146,0.00028772806,0.00006029187,0.00002347995,0.00008563974,0.0000031826426,0.00004205207,0.0000010531336],"about_ca_topic_score_codex":0.0057629235,"about_ca_topic_score_gemma":0.0066863843,"teacher_disagreement_score":0.0057629235,"about_ca_system_score_codex":0.00031166174,"about_ca_system_score_gemma":0.00033269307,"threshold_uncertainty_score":0.011458755},"labels":[],"label_agreement":null},{"id":"W2891372289","doi":"10.1101/415158","title":"Uncovering a role for the dorsal hippocampal commissure in episodic memory","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut du Savoir Montfort; Montreal Neurological Institute and Hospital","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Medical Research Council; Centre d'Imagerie BioMédicale; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Wellcome Trust; University of California, Los Angeles; University of Minnesota; Massachusetts General Hospital","keywords":"Diffusion MRI; White matter; Neuroscience; Anterior commissure; Episodic memory; Tractography; Corpus callosum; Hippocampal formation; Fractional anisotropy; Commissure; Psychology; Human Connectome Project; Temporal lobe; Hippocampus; Cingulum (brain); Anatomy; Biology; Medicine; Functional connectivity; Magnetic resonance imaging; Cognition; Epilepsy","score_opus":0.03211149104441389,"score_gpt":0.2911100686521923,"score_spread":0.2589985776077784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891372289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9665758,0.0020012285,0.027688336,0.00071213103,0.00003894867,0.000020234225,0.00038180166,0.0001298222,0.0024516524],"genre_scores_gemma":[0.9900489,0.0003524491,0.008709418,0.00006251989,0.000019642102,0.000006349955,0.00011701347,0.000020691956,0.0006630566],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992764,0.000011829396,0.000004067123,0.000033006858,0.000014662734,0.000008763388],"domain_scores_gemma":[0.9995709,0.00011645235,0.00012311543,0.00010102871,0.00004519792,0.000043321408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036315518,0.00024217856,0.00018118473,0.00053145725,0.00027763177,0.0007088458,0.0002449721,0.0005069132,0.0018978356],"category_scores_gemma":[0.0011028544,0.00014748223,0.00012814032,0.0003288986,0.0009777569,0.0005408966,0.0003563671,0.00043508544,0.00024569136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009213946,0.00017715576,0.1389861,0.000588582,0.00032814758,0.002241043,0.0014891217,0.0056952117,0.69349146,0.01254184,0.0021061967,0.14143385],"study_design_scores_gemma":[0.00007516889,0.000591925,0.6921946,0.0002691687,0.0002796997,0.006455073,0.0012188567,0.041318476,0.20641099,0.034419503,0.016678717,0.000087808876],"about_ca_topic_score_codex":0.003742399,"about_ca_topic_score_gemma":0.0075597307,"teacher_disagreement_score":0.003742399,"about_ca_system_score_codex":0.00024924296,"about_ca_system_score_gemma":0.0004376593,"threshold_uncertainty_score":0.0074412227},"labels":[],"label_agreement":null},{"id":"W2891444336","doi":"10.3389/fpsyt.2018.00438","title":"Putative Astroglial Dysfunction in Schizophrenia: A Meta-Analysis of 1H-MRS Studies of Medial Prefrontal Myo-Inositol","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"Instituto de Salud Carlos III; Canadian Institutes of Health Research","keywords":"Schizophrenia (object-oriented programming); Inositol; Prefrontal cortex; Meta-analysis; DISC1; Internal medicine; Psychosis; Psychology; Sample size determination; Psychiatry; Medicine; Chemistry; Cognition; Biochemistry; Receptor","score_opus":0.09004497261632373,"score_gpt":0.38765712489573645,"score_spread":0.29761215227941273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891444336","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031278726,0.9662653,0.00091076177,0.00035772446,0.00015593173,0.0001195415,0.000626018,0.0000369246,0.00024911144],"genre_scores_gemma":[0.6699558,0.3240249,0.002895238,0.0009351779,0.00028663978,0.00040459118,0.0011435398,0.000051330997,0.00030281866],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9935035,0.0030824475,0.0015909384,0.0010300181,0.0005103371,0.00028271417],"domain_scores_gemma":[0.9878143,0.008726991,0.0018540681,0.000599221,0.0007898998,0.00021546295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010309681,0.0022653241,0.011061911,0.004866738,0.00082334573,0.0032404836,0.0015486755,0.0020496089,0.0024027354],"category_scores_gemma":[0.0190866,0.0012846672,0.03343646,0.0049611176,0.00073597673,0.0011799836,0.0015041219,0.0015510264,0.00018801386],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003329828,0.00003195639,0.019919693,0.082942694,0.88316363,0.00031076669,0.00010101281,0.00062339084,0.0009503213,0.000119424105,0.00037708314,0.008130157],"study_design_scores_gemma":[0.00030375915,0.00016818102,0.013940597,0.0039897594,0.98017603,0.00016213162,0.00003989019,0.00019036735,0.00015782249,0.0002094872,0.00064573967,0.000016320271],"about_ca_topic_score_codex":0.0050896914,"about_ca_topic_score_gemma":0.009456372,"teacher_disagreement_score":0.011061911,"about_ca_system_score_codex":0.0015230363,"about_ca_system_score_gemma":0.0017938116,"threshold_uncertainty_score":0.054523468},"labels":[],"label_agreement":null},{"id":"W2891919159","doi":"10.1002/jmri.26328","title":"Characterizing Structural Changes With Evolving Remyelination Following Experimental Demyelination Using High Angular Resolution Diffusion MRI and Texture Analysis","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; University of Calgary","funders":"Alberta Innovates; Health Research Board; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Remyelination; Diffusion imaging; Diffusion MRI; Texture (cosmology); High resolution; Diffusion; Medicine; Computer science; Magnetic resonance imaging; Physics; Radiology; Artificial intelligence; Geology; Myelin; Internal medicine","score_opus":0.01985293469802128,"score_gpt":0.3191306368759522,"score_spread":0.2992777021779309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891919159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98902786,0.0006440051,0.009647261,0.000026578933,0.0000058377927,0.00004035279,0.00026409232,0.00005864631,0.00028537386],"genre_scores_gemma":[0.9857701,0.00067337655,0.012335563,0.000027986403,0.000009461482,0.00006126022,0.00039581067,0.000019326508,0.00070701964],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99987376,0.000015463771,0.000013751403,0.000025486599,0.00004546551,0.000026202582],"domain_scores_gemma":[0.9995264,0.000050631883,0.00020455112,0.00003438441,0.00012274068,0.00006134521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004781892,0.0002876291,0.00022933325,0.000858377,0.0001291622,0.00031460408,0.00014589984,0.00025777653,0.0007194195],"category_scores_gemma":[0.00036996452,0.0001300725,0.00020097505,0.0003630821,0.00024721544,0.00034947426,0.00017731382,0.0003207383,0.00014777729],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066550466,0.000108158485,0.014647374,0.00010836374,0.000047482677,0.00010638685,0.000067087814,0.00042993826,0.97306234,0.000045394834,0.00005837145,0.010653681],"study_design_scores_gemma":[0.00004154615,0.0018285173,0.39496174,0.000034011227,0.00016858686,0.0015248838,0.00025238327,0.008809227,0.59124285,0.00021217401,0.0008886247,0.0000354312],"about_ca_topic_score_codex":0.0008376712,"about_ca_topic_score_gemma":0.0016384849,"teacher_disagreement_score":0.000858377,"about_ca_system_score_codex":0.000210564,"about_ca_system_score_gemma":0.00015610034,"threshold_uncertainty_score":0.0025289655},"labels":[],"label_agreement":null},{"id":"W2892140621","doi":"10.1101/423459","title":"Bundle-specific fornix reconstruction for dual-tracer PET-tractometry","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Fornix; Tractography; Diffusion MRI; Positron emission tomography; Neuroscience; Partial volume; Voxel; Human Connectome Project; White matter; Medicine; Nuclear medicine; Psychology; Hippocampus; Radiology; Magnetic resonance imaging","score_opus":0.05268890752959248,"score_gpt":0.30640840972062744,"score_spread":0.25371950219103495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892140621","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065045916,0.0000873501,0.9919119,0.00009271433,0.000018715804,0.000032670432,0.00010243748,0.0010263912,0.00022331084],"genre_scores_gemma":[0.07947992,0.00017793954,0.9178615,0.00004914335,0.000024241108,0.00012483662,0.00054935395,0.0006309836,0.0011020598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999464,0.00022798151,0.000040704137,0.00010182447,0.00012366471,0.000041838484],"domain_scores_gemma":[0.99854857,0.0005118121,0.00024234789,0.00034021834,0.00027078876,0.0000862339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019123143,0.0010317636,0.00079567,0.0010296705,0.0005721832,0.0017227386,0.0010484033,0.0016864329,0.0032585845],"category_scores_gemma":[0.0057774796,0.0008462359,0.0010821956,0.0012415024,0.000599932,0.0010190625,0.0011192898,0.0014360189,0.0017324763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043266916,0.0001708883,0.008134742,0.0005729769,0.00048226898,0.0005780063,0.0005893688,0.43123016,0.09711274,0.029021911,0.012114045,0.41956022],"study_design_scores_gemma":[0.000017044504,0.00004004582,0.0011479482,0.00002664718,0.00002092465,0.00024532562,0.000031032134,0.9697272,0.014196313,0.009461565,0.0050605363,0.00002534678],"about_ca_topic_score_codex":0.003957715,"about_ca_topic_score_gemma":0.0056781294,"teacher_disagreement_score":0.003957715,"about_ca_system_score_codex":0.00079719775,"about_ca_system_score_gemma":0.0019348356,"threshold_uncertainty_score":0.010901034},"labels":[],"label_agreement":null},{"id":"W2893406291","doi":"10.1007/s00429-018-1759-1","title":"Topological principles and developmental algorithms might refine diffusion tractography","year":2018,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Tractography; Computer science; Diffusion; Topology (electrical circuits); Diffusion MRI; Cognitive science; Artificial intelligence; Algorithm; Psychology; Mathematics; Physics; Medicine; Combinatorics; Magnetic resonance imaging","score_opus":0.10554750883450897,"score_gpt":0.36201536571622606,"score_spread":0.2564678568817171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893406291","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028413152,0.7433354,0.22537051,0.008638416,0.0016771446,0.00007184097,0.0002597263,0.0005172056,0.017288366],"genre_scores_gemma":[0.048672173,0.7855522,0.15431716,0.0012027036,0.0013839285,0.00012942625,0.00050495815,0.0002554395,0.0079819895],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997081,0.00010046979,0.00003066228,0.0000721116,0.000071121016,0.00001749807],"domain_scores_gemma":[0.99884063,0.00066144636,0.0000789799,0.00010710088,0.0002746192,0.00003728779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015368791,0.0009689817,0.00088471384,0.003152353,0.0003716739,0.0016639513,0.0011924289,0.0014762909,0.004257812],"category_scores_gemma":[0.0032629024,0.0003845587,0.0010488678,0.0024396111,0.0023073317,0.0028140093,0.0008144264,0.002266386,0.0029037776],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033764674,0.000027683041,0.0007755665,0.0051087122,0.00013375115,0.00016366542,0.00017334669,0.0078096306,0.0020834708,0.21124719,0.014119078,0.7583242],"study_design_scores_gemma":[0.00003007379,0.000108300286,0.002040386,0.0031536485,0.00015953321,0.0015459667,0.00018113792,0.012879125,0.0034431303,0.29636648,0.67996603,0.00012622066],"about_ca_topic_score_codex":0.0022607828,"about_ca_topic_score_gemma":0.0033038335,"teacher_disagreement_score":0.004257812,"about_ca_system_score_codex":0.0009899447,"about_ca_system_score_gemma":0.0014812096,"threshold_uncertainty_score":0.014243782},"labels":[],"label_agreement":null},{"id":"W2893628403","doi":"10.1115/1.4041541","title":"Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture","year":2018,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Sunnybrook Research Institute","keywords":"Diffusion MRI; Voxel; Tractography; Biomedical engineering; Orientation (vector space); Magnetic resonance imaging; Anatomy; Materials science; Computer science; Nuclear magnetic resonance; Artificial intelligence; Physics; Mathematics; Geometry; Medicine; Radiology","score_opus":0.03342880551342237,"score_gpt":0.3108715339195204,"score_spread":0.277442728406098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893628403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76867205,0.0025693849,0.22458558,0.00023347019,0.000057675497,0.00019501697,0.0001816777,0.00034354505,0.003161745],"genre_scores_gemma":[0.79804176,0.0029345881,0.19747478,0.000058970632,0.000028558303,0.000099158686,0.00016761037,0.00013094592,0.001063563],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996124,0.00012441288,0.000043368345,0.00008304909,0.0001123846,0.000024476745],"domain_scores_gemma":[0.99910635,0.00042573537,0.00019566697,0.00014434376,0.00009463823,0.00003321943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002418369,0.00062284846,0.00026784826,0.001556745,0.00015987121,0.0011709477,0.0003542946,0.00047080914,0.0012023333],"category_scores_gemma":[0.005690028,0.00049760466,0.00028979013,0.00095519715,0.00058772694,0.0010809215,0.00047219163,0.00034896456,0.00030092662],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012455613,0.00009511103,0.053297125,0.0006718809,0.00019206488,0.0006633263,0.0013265514,0.030254683,0.35360852,0.004874619,0.00045219547,0.55331844],"study_design_scores_gemma":[0.00022277734,0.0019235915,0.28501725,0.00037551593,0.00092445954,0.007835143,0.0019414397,0.45066065,0.23001464,0.006952281,0.013851578,0.0002806081],"about_ca_topic_score_codex":0.003365896,"about_ca_topic_score_gemma":0.007322373,"teacher_disagreement_score":0.003365896,"about_ca_system_score_codex":0.00033628946,"about_ca_system_score_gemma":0.00054647616,"threshold_uncertainty_score":0.012789726},"labels":[],"label_agreement":null},{"id":"W2894095668","doi":"10.1111/acps.12964","title":"Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity","year":2018,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministerstvo Zdravotnictví Ceské Republiky; Agence Nationale de la Recherche","keywords":"Schizophrenia (object-oriented programming); Machine learning; Artificial intelligence; Signature (topology); Psychosis; Psychology; Computer science; Pattern recognition (psychology); Psychiatry; Mathematics","score_opus":0.05515447275850306,"score_gpt":0.3596134905246516,"score_spread":0.30445901776614853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894095668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9307583,0.00017494307,0.06804797,0.00016041314,0.000010420214,0.00006397018,0.00031804084,0.00014917039,0.00031676196],"genre_scores_gemma":[0.97773015,0.000051091818,0.02153445,0.000019795556,0.000015674845,0.00003675057,0.0005119613,0.00001465895,0.00008551595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99932384,0.00027476487,0.00007074489,0.0002000931,0.00008349629,0.00004702148],"domain_scores_gemma":[0.99627644,0.0017572849,0.0010384436,0.000522838,0.00027624398,0.00012864267],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003105859,0.0004645765,0.0004096512,0.0011125416,0.0003009602,0.0006824697,0.00036516905,0.0004354589,0.0005759526],"category_scores_gemma":[0.008190163,0.00020275696,0.0006822265,0.0005850677,0.0006079725,0.0006118136,0.0007216659,0.00047035565,0.00016297943],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001169615,0.00038007722,0.7185655,0.00023493137,0.0007012648,0.0004330977,0.00038189645,0.05985228,0.04841115,0.0011763687,0.001129914,0.16756381],"study_design_scores_gemma":[0.00008595584,0.0006321058,0.48831055,0.00007379089,0.00023842197,0.00080720364,0.00016120334,0.48961556,0.011805828,0.007810063,0.00039980139,0.000059516427],"about_ca_topic_score_codex":0.0011980194,"about_ca_topic_score_gemma":0.0019404689,"teacher_disagreement_score":0.9968941,"about_ca_system_score_codex":0.00034333012,"about_ca_system_score_gemma":0.0007420933,"threshold_uncertainty_score":0.01642555},"labels":[],"label_agreement":null},{"id":"W2894333093","doi":"10.1016/j.neuroimage.2018.09.076","title":"Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Foulkes Foundation; Natural Sciences and Engineering Research Council of Canada; Royal College of Psychiatrists","keywords":"Monte Carlo method; Human Connectome Project; Diffusion MRI; Computer science; Ground truth; Voxel; Algorithm; Diffusion; Statistical physics; Artificial intelligence; Biological system; Magnetic resonance imaging; Physics; Mathematics; Statistics; Radiology; Neuroscience; Biology","score_opus":0.04307607797040159,"score_gpt":0.3293704997543542,"score_spread":0.2862944217839526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894333093","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007903244,0.000080095975,0.99142766,0.00008398855,0.000010319401,0.000020971982,0.000048183443,0.00020965154,0.00021579952],"genre_scores_gemma":[0.21600644,0.0006920904,0.7809153,0.00013554911,0.00006713419,0.00016339714,0.00040618243,0.00030140718,0.0013125179],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996847,0.00011142782,0.000023983708,0.00005664816,0.00009333505,0.000029938155],"domain_scores_gemma":[0.9980135,0.0009568185,0.00023315306,0.00034097812,0.00032418876,0.00013124167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012474653,0.0006809835,0.0011213378,0.0011087005,0.0003781307,0.0010935612,0.001394423,0.0017272178,0.0011074677],"category_scores_gemma":[0.006587206,0.0010478616,0.00093552173,0.00090919243,0.00084517495,0.001378148,0.001268118,0.0018371554,0.00078417896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019625248,0.00011322273,0.0019923507,0.00021017523,0.00009100132,0.00008970298,0.00014960632,0.8077125,0.022280237,0.026199834,0.0020339822,0.13893127],"study_design_scores_gemma":[0.0000058599776,0.000009284312,0.00009734149,0.00000661965,0.0000048956063,0.000018890332,0.000004153686,0.9944958,0.0009049862,0.0040860637,0.00036066727,0.0000053333824],"about_ca_topic_score_codex":0.004286453,"about_ca_topic_score_gemma":0.0045544854,"teacher_disagreement_score":0.004286453,"about_ca_system_score_codex":0.000497214,"about_ca_system_score_gemma":0.0017796627,"threshold_uncertainty_score":0.008523047},"labels":[],"label_agreement":null},{"id":"W2894533856","doi":"10.3389/fphar.2018.01172","title":"Confused Connections? Targeting White Matter to Address Treatment Resistant Schizophrenia","year":2018,"lang":"en","type":"review","venue":"Frontiers in Pharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Nova Scotia Health Authority","funders":"Canadian Institutes of Health Research","keywords":"Psychosis; Schizophrenia (object-oriented programming); Antipsychotic; Medicine; Pharmacotherapy; Serotonergic; Psychiatry; Psychology; Internal medicine; Serotonin; Receptor","score_opus":0.08410181325738236,"score_gpt":0.4174358491086453,"score_spread":0.3333340358512629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894533856","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034689235,0.9738627,0.0011961358,0.014092418,0.0015860231,0.000027755475,0.000060292758,0.00008074166,0.005625061],"genre_scores_gemma":[0.020377781,0.96664,0.0021141048,0.0054938593,0.0017412523,0.000039171377,0.000070065,0.000018189596,0.0035055815],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998865,0.000033245367,0.000014924193,0.000014308354,0.000031313895,0.000019661122],"domain_scores_gemma":[0.9998011,0.00007404325,0.00004434259,0.0000044171925,0.000047214187,0.00002887891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046080834,0.00027922,0.00046463072,0.0005089132,0.00018766103,0.00063416624,0.00037372508,0.0008004035,0.0032871268],"category_scores_gemma":[0.00056533766,0.00008586782,0.00033670827,0.00017683364,0.00038972887,0.00069398235,0.00039124113,0.0013437651,0.0008833072],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036575948,0.000148091,0.0006823714,0.009268836,0.00015285035,0.00085879583,0.00026536483,0.00028979714,0.01032486,0.009460805,0.060096134,0.9080863],"study_design_scores_gemma":[0.00021176873,0.00092607905,0.0035563468,0.0074156197,0.00031542496,0.003263061,0.0004352028,0.00033746278,0.0039707604,0.013274594,0.9662546,0.00003913179],"about_ca_topic_score_codex":0.0006631511,"about_ca_topic_score_gemma":0.002898397,"teacher_disagreement_score":0.0032871268,"about_ca_system_score_codex":0.00043926074,"about_ca_system_score_gemma":0.00060501526,"threshold_uncertainty_score":0.01099658},"labels":[],"label_agreement":null},{"id":"W2894670374","doi":"10.1093/cercor/bhy231","title":"Altered White Matter Organization in the TUBB3 E410K Syndrome","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hamilton Health Sciences","funders":"Boston Children's Hospital; Intellectual and Developmental Disabilities Research Center; National Institutes of Health; National Eye Institute; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Howard Hughes Medical Institute","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Corticospinal tract; Neuroimaging; Psychology; Endophenotype; Neuroscience; Magnetic resonance imaging; Pyramidal tracts; Medicine; Cognition; Radiology","score_opus":0.03665468334787248,"score_gpt":0.3163464266729352,"score_spread":0.27969174332506275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894670374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996829,0.000033180197,0.00013247976,0.0000059631334,6.289755e-7,0.0000027016488,0.000035750596,0.0000067548535,0.00009960332],"genre_scores_gemma":[0.99936527,0.000054439308,0.0003672385,0.000009949711,0.0000026133857,0.0000040048667,0.00006981458,0.000006467575,0.00012020949],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983764,0.000022531756,0.000021898968,0.00006323149,0.00003060788,0.000023992574],"domain_scores_gemma":[0.99982494,0.000040920106,0.000075186326,0.000014497981,0.000014683071,0.000029854475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015529642,0.00075979985,0.00028047932,0.0011862648,0.00043928274,0.00025928306,0.00016328602,0.0004483579,0.0016503928],"category_scores_gemma":[0.00062605663,0.00033079198,0.00014516574,0.0005086678,0.0006816124,0.00019676657,0.00037436656,0.00017887559,0.0001607655],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009810975,0.0001554131,0.6655548,0.00011498438,0.00018423337,0.07460567,0.002585824,0.0009766739,0.23114352,0.00044150167,0.00033615076,0.022920014],"study_design_scores_gemma":[0.000034730627,0.00036976713,0.9012506,0.000013545089,0.00007573665,0.0903745,0.00042133097,0.00078320777,0.0059208237,0.0002057603,0.00053302053,0.00001691677],"about_ca_topic_score_codex":0.0025657387,"about_ca_topic_score_gemma":0.003224473,"teacher_disagreement_score":0.0025657387,"about_ca_system_score_codex":0.0002274531,"about_ca_system_score_gemma":0.00015492579,"threshold_uncertainty_score":0.0055211186},"labels":[],"label_agreement":null},{"id":"W2894959679","doi":"10.1016/j.nicl.2018.09.028","title":"Widespread diffusion changes differentiate Parkinson's disease and progressive supranuclear palsy","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Calgary","funders":"","keywords":"Progressive supranuclear palsy; Diffusion MRI; Fractional anisotropy; Parkinson's disease; Artificial intelligence; Psychology; Nuclear medicine; Medicine; Pathology; Computer science; Disease; Magnetic resonance imaging; Radiology","score_opus":0.1195562695030688,"score_gpt":0.42324322796270725,"score_spread":0.30368695845963845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894959679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969817,0.00076890504,0.001741679,0.00002916968,0.0000050465305,0.000011139588,0.00010406252,0.000020569754,0.00033779483],"genre_scores_gemma":[0.9975878,0.00027934604,0.0017538748,0.000013805948,0.000006654977,0.000007127115,0.00023784673,0.0000026574492,0.00011089788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977344,0.000055087177,0.000041891133,0.00006290871,0.000042936972,0.000023872217],"domain_scores_gemma":[0.9994605,0.00019734152,0.00018751055,0.000049112445,0.0000690328,0.00003656346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062277843,0.00040767528,0.00042781045,0.0009864451,0.0001898736,0.00037024912,0.00015598162,0.00039491014,0.0005678112],"category_scores_gemma":[0.001263359,0.00014340214,0.00022008638,0.0003911574,0.0003515036,0.00030875576,0.0003625633,0.00018547139,0.00015724573],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018506438,0.00021069539,0.63769543,0.00038949816,0.0003878633,0.0025738329,0.00052316126,0.0018559019,0.17860602,0.0003640993,0.0006407565,0.17490216],"study_design_scores_gemma":[0.000020858291,0.00029195947,0.9834854,0.000028701383,0.000070635,0.0039685573,0.0003279832,0.0033322715,0.007603337,0.00034420253,0.00051255495,0.00001349039],"about_ca_topic_score_codex":0.001182295,"about_ca_topic_score_gemma":0.0028344928,"teacher_disagreement_score":0.001182295,"about_ca_system_score_codex":0.00013695314,"about_ca_system_score_gemma":0.00017025071,"threshold_uncertainty_score":0.0032936335},"labels":[],"label_agreement":null},{"id":"W2896133725","doi":"10.1002/acn3.667","title":"Diffusion <scp>MRI</scp> abnormalities in adolescent rats given repeated mild traumatic brain injury","year":2018,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Cummings Foundation","keywords":"Medicine; Traumatic brain injury; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Concussion; Population; Neuroscience; Radiology; Poison control; Injury prevention; Psychiatry; Psychology; Emergency medicine","score_opus":0.26504683664408674,"score_gpt":0.46885978822287316,"score_spread":0.20381295157878643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896133725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994433,0.00071544695,0.0023410495,0.00021971119,0.0000924385,0.00007188127,0.0008832821,0.00017138872,0.0010717426],"genre_scores_gemma":[0.98425865,0.0014123957,0.0041159107,0.00023762074,0.000034158224,0.00034409162,0.0011518324,0.00007543305,0.0083699245],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99962497,0.000020943124,0.00003311145,0.00008665151,0.00011585095,0.00011845043],"domain_scores_gemma":[0.9993605,0.00002773274,0.00026979588,0.00004812327,0.00012666345,0.00016722718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002941318,0.00087270763,0.00062894524,0.0012414119,0.00037667216,0.00035151432,0.00047153875,0.0007020051,0.00280364],"category_scores_gemma":[0.000239603,0.0003440134,0.00061901245,0.0003173977,0.0009563171,0.00054830255,0.0004008506,0.0019644988,0.0005965679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083729846,0.00055071485,0.0026548356,0.00013231205,0.000032952197,0.0008398156,0.00017186828,0.00009750666,0.99060035,0.00015023019,0.00025512086,0.003676958],"study_design_scores_gemma":[0.00007763256,0.0077368338,0.057940803,0.00006885667,0.00012020021,0.0020396868,0.00095468835,0.0011916949,0.9271699,0.00017599827,0.0024723832,0.00005127491],"about_ca_topic_score_codex":0.0038756963,"about_ca_topic_score_gemma":0.006341718,"teacher_disagreement_score":0.0038756963,"about_ca_system_score_codex":0.00059727137,"about_ca_system_score_gemma":0.00070235244,"threshold_uncertainty_score":0.0093791485},"labels":[],"label_agreement":null},{"id":"W2896255880","doi":"10.1038/s41598-018-34219-8","title":"Allostatic load and disordered white matter microstructure in overweight adults","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Universitat de Barcelona; Generalitat de Catalunya","keywords":"Allostatic load; Overweight; White matter; Medicine; Gerontology; Psychology; Obesity; Endocrinology; Magnetic resonance imaging","score_opus":0.013815243343114505,"score_gpt":0.2955988558445625,"score_spread":0.281783612501448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896255880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99950564,0.00021835287,0.00004094122,0.000014321671,0.0000025389425,0.0000039333886,0.000038529703,0.00000125086,0.00017458203],"genre_scores_gemma":[0.99968207,0.00009809812,0.000054289285,0.000008263972,0.0000052287446,0.0000027164997,0.00004219953,5.48461e-7,0.00010651508],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999194,0.00001453356,0.000013571906,0.000021370182,0.000016999331,0.000014028588],"domain_scores_gemma":[0.99974066,0.000020189602,0.00015612948,0.000016172104,0.000016923668,0.000049937345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019560139,0.00025022612,0.00022492105,0.0007985073,0.0003043561,0.00033931457,0.00009710865,0.00029300974,0.001289862],"category_scores_gemma":[0.0006538034,0.00019714686,0.00015570491,0.0004932609,0.00020500983,0.00027378168,0.00033005202,0.00024637656,0.00012765896],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041726037,0.000082266546,0.9928429,0.000024544132,0.00007148661,0.00018680286,0.00024041338,0.00002819672,0.0023806193,0.00004028934,0.000040677885,0.003644554],"study_design_scores_gemma":[0.0000022297959,0.00007500188,0.99950135,0.000003182542,0.000014108168,0.0001598396,0.000089252215,0.000030184694,0.000060020564,0.000025463334,0.00003824304,0.0000011294884],"about_ca_topic_score_codex":0.001995195,"about_ca_topic_score_gemma":0.003274934,"teacher_disagreement_score":0.001995195,"about_ca_system_score_codex":0.00009668389,"about_ca_system_score_gemma":0.00009616401,"threshold_uncertainty_score":0.0043150783},"labels":[],"label_agreement":null},{"id":"W2896736741","doi":"10.1101/439836","title":"Novel use of Diffusion Tensor Imaging to Delineate the Rat Basolateral Amygdala","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Neuroscience; Diffusion MRI; Basolateral amygdala; Amygdala; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.052795566163076096,"score_gpt":0.29377080010411555,"score_spread":0.24097523394103945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896736741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44446844,0.0020282061,0.54821664,0.00055868196,0.00010190511,0.00023773072,0.0009407388,0.00093366764,0.0025139598],"genre_scores_gemma":[0.49011064,0.0018658239,0.5043908,0.00012523688,0.00002758445,0.00023665499,0.00059360405,0.00023694563,0.0024127706],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989045,0.00002034159,0.000011050854,0.000028783385,0.000036124664,0.000013268867],"domain_scores_gemma":[0.9996524,0.000044519158,0.00010816283,0.000052474898,0.00009978681,0.000042719275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062475126,0.00049701874,0.00020611823,0.00089004607,0.00030600085,0.0005494627,0.00034165118,0.0004659438,0.00083476247],"category_scores_gemma":[0.0006482228,0.00032895475,0.00020145236,0.0002673138,0.00037078245,0.0006528918,0.00045841973,0.0007154653,0.0004400952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005653003,0.00001755859,0.0010870256,0.000069409885,0.000010897721,0.00007249751,0.00004608635,0.000564543,0.98814166,0.00073624257,0.00011712467,0.009080396],"study_design_scores_gemma":[0.000031957446,0.00036873933,0.014678641,0.000053265125,0.00006749261,0.0017080778,0.00011330276,0.034835268,0.9405268,0.0015460878,0.006017545,0.00005282542],"about_ca_topic_score_codex":0.0018494696,"about_ca_topic_score_gemma":0.0036949993,"teacher_disagreement_score":0.0018494696,"about_ca_system_score_codex":0.00029301865,"about_ca_system_score_gemma":0.0006492,"threshold_uncertainty_score":0.0036774278},"labels":[],"label_agreement":null},{"id":"W2897068525","doi":"10.1016/j.mri.2018.10.003","title":"Fiber orientation distribution function from non-negative sparse recovery with quantitative analysis of local fiber orientations and tractography using DW-MRI datasets","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"H2020 European Research Council; Horizon 2020","keywords":"Tractography; Voxel; Diffusion MRI; Computer science; Artificial intelligence; Orientation (vector space); Pattern recognition (psychology); Human Connectome Project; Population; Noise (video); Mathematics; Magnetic resonance imaging; Image (mathematics); Biology","score_opus":0.029898547542991143,"score_gpt":0.3302889309628341,"score_spread":0.300390383419843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897068525","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14330094,0.00035291546,0.8538757,0.00026083452,0.000027127711,0.00007788235,0.00077495934,0.0007380278,0.0005916538],"genre_scores_gemma":[0.5925477,0.00052948296,0.40263718,0.000055536853,0.00004954227,0.00011927764,0.0023718819,0.00031720873,0.0013722235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998056,0.00006795704,0.00001299086,0.0000492147,0.000049179325,0.000015015463],"domain_scores_gemma":[0.9987853,0.0004881911,0.00021914812,0.0002355933,0.00022226255,0.000049383503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013733958,0.0006157391,0.00045273517,0.0011806351,0.00028029087,0.0007709676,0.00055197784,0.00069167797,0.0006815542],"category_scores_gemma":[0.004314977,0.00032692475,0.0005242477,0.0012369816,0.00055011275,0.0010236542,0.0006471657,0.00087329943,0.00031739136],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074752094,0.00032177623,0.00856847,0.00061785127,0.000299737,0.00041189557,0.00032001932,0.46277338,0.10083736,0.015085586,0.00570824,0.40430814],"study_design_scores_gemma":[0.000014317921,0.000043508964,0.0035719632,0.000016329544,0.00002915646,0.0002006781,0.000030650735,0.9803412,0.00825587,0.0066040503,0.00086897146,0.00002333903],"about_ca_topic_score_codex":0.0035641345,"about_ca_topic_score_gemma":0.0048421873,"teacher_disagreement_score":0.0035641345,"about_ca_system_score_codex":0.0003388431,"about_ca_system_score_gemma":0.00078013696,"threshold_uncertainty_score":0.007263303},"labels":[],"label_agreement":null},{"id":"W2897519381","doi":"10.1016/j.jalz.2018.06.491","title":"P1‐481: DEFAULT MODE NETWORK CONNECTIVITY CHANGE DETECTED BY DIFFUSION TENSOR IMAGING CONTRIBUTES TO COGNITIVE IMPAIRMENTS IN VASCULAR COGNITIVE IMPAIRMENT, NO DEMENTIA","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Default mode network; Montreal Cognitive Assessment; Diffusion MRI; White matter; Cognition; Dementia; Psychology; Prefrontal cortex; Audiology; Posterior cingulate; Vascular dementia; Neuroscience; Cardiology; Medicine; Cognitive impairment; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.036583717660380266,"score_gpt":0.3328418265583878,"score_spread":0.2962581088980075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897519381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985676,0.00014239276,0.00022234659,0.000056868987,0.0000064728115,0.00001283995,0.00019183841,0.000005544584,0.0007942523],"genre_scores_gemma":[0.99937147,0.000047648267,0.00014451238,0.000011691017,0.000008848801,0.00000805611,0.00015966252,0.00000134511,0.000246858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999217,0.000013555069,0.00000897758,0.000026787768,0.000013868713,0.000015237554],"domain_scores_gemma":[0.9995907,0.000086188746,0.00016412389,0.000029371038,0.000053963577,0.0000756662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000248711,0.00035219025,0.0002273939,0.00060990744,0.00038261805,0.000381057,0.0002560677,0.00031000405,0.004592671],"category_scores_gemma":[0.0012438773,0.00012530835,0.00021458532,0.00027626113,0.00025095674,0.0003528824,0.0003788518,0.0003542933,0.00026450504],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018264357,0.00032699193,0.9560859,0.00010289134,0.0001876608,0.0021026907,0.00035644654,0.00024527597,0.011453439,0.00018700532,0.0009909464,0.026134422],"study_design_scores_gemma":[0.000019678166,0.00014550585,0.99617517,0.000010255738,0.000043730717,0.0018614752,0.00007857316,0.0007162033,0.00050359487,0.00026485714,0.00017661708,0.0000042759984],"about_ca_topic_score_codex":0.0023154765,"about_ca_topic_score_gemma":0.00301959,"teacher_disagreement_score":0.004592671,"about_ca_system_score_codex":0.00021636387,"about_ca_system_score_gemma":0.00015192434,"threshold_uncertainty_score":0.015363991},"labels":[],"label_agreement":null},{"id":"W2897543276","doi":"10.1002/jmri.26290","title":"Diffusion tensor imaging of white matter in patients with prediabetes by trace‐based spatial statistics","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Prediabetes; Medicine; White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Superior longitudinal fasciculus; Internal medicine; Magnetic resonance imaging; Radiology; Type 2 diabetes; Diabetes mellitus; Pathology; Endocrinology","score_opus":0.009361816085818807,"score_gpt":0.2686683266081283,"score_spread":0.25930651052230946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897543276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945544,0.0006944402,0.0037025474,0.000089164525,0.0000099146455,0.000026852797,0.00038961624,0.000036583035,0.00049646775],"genre_scores_gemma":[0.99500895,0.00025164467,0.004204144,0.000008936829,0.000013569044,0.000019036692,0.00033750798,0.000007636781,0.0001486143],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998085,0.00006644204,0.00003014661,0.0000431724,0.000034495457,0.0000173676],"domain_scores_gemma":[0.99914706,0.00021935423,0.00035591837,0.00007186571,0.00014165544,0.0000642522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012113837,0.0003893477,0.00031807413,0.0014302492,0.00015769423,0.00049360236,0.00022061056,0.00018407677,0.0011584687],"category_scores_gemma":[0.0027609132,0.00015152547,0.00030998155,0.0010033523,0.00021215806,0.00040770273,0.00032192143,0.0002952289,0.00014993345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015708669,0.00015919034,0.93949646,0.00015650649,0.00040197704,0.00056789,0.00038847618,0.0021582565,0.005395812,0.0005831527,0.00072764483,0.0483937],"study_design_scores_gemma":[0.00009496165,0.0004872655,0.96120733,0.000052273183,0.00021504152,0.0019559944,0.00035427365,0.031161878,0.0014608878,0.0020506561,0.00092459505,0.000034867768],"about_ca_topic_score_codex":0.0017179381,"about_ca_topic_score_gemma":0.0019675086,"teacher_disagreement_score":0.0017179381,"about_ca_system_score_codex":0.00017988987,"about_ca_system_score_gemma":0.00032418975,"threshold_uncertainty_score":0.0064065456},"labels":[],"label_agreement":null},{"id":"W2897772899","doi":"10.1016/j.jalz.2018.06.2057","title":"IC‐06‐04: ANTEMORTEM LONGITUDINAL MRI METRICS AS A BIOMARKER OF POSTMORTEM BRAAK NFT STAGING","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Temporal lobe; Atrophy; Pathology; Neuropathology; Medicine; Magnetic resonance imaging; Neurofibrillary tangle; Senile plaques; Alzheimer's disease; Psychology; Neuroscience; Radiology; Disease","score_opus":0.10347928492331174,"score_gpt":0.3790310302017456,"score_spread":0.27555174527843385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897772899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95404947,0.0006833102,0.006089618,0.00007447424,0.00004207895,0.0005708916,0.029943679,0.0008079398,0.0077385493],"genre_scores_gemma":[0.9388939,0.0002662398,0.014566745,0.000065771324,0.000058716934,0.0009338417,0.03774399,0.0002868801,0.0071837734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996306,0.000059812544,0.000041656247,0.000110252724,0.000097869,0.000059767837],"domain_scores_gemma":[0.9982722,0.00018481759,0.0004863823,0.00032019918,0.00053956034,0.00019685816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015653364,0.0006996302,0.0005210959,0.0025318724,0.00040436117,0.0012519868,0.00087810145,0.0006267208,0.005605372],"category_scores_gemma":[0.0033496625,0.00030029324,0.00023377045,0.0013695387,0.00032008978,0.00039637715,0.00061661797,0.00042015663,0.0023417852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048051192,0.00034616675,0.8870727,0.00043540323,0.00041334121,0.0005020643,0.0008396948,0.0018828001,0.022519141,0.0006236173,0.018956382,0.06160357],"study_design_scores_gemma":[0.000042051885,0.00034101435,0.9900709,0.000024465291,0.00007570711,0.0008853333,0.000097191405,0.0014239197,0.0021279664,0.00021504636,0.0046733054,0.000023199926],"about_ca_topic_score_codex":0.00728458,"about_ca_topic_score_gemma":0.01675441,"teacher_disagreement_score":0.00728458,"about_ca_system_score_codex":0.00039439023,"about_ca_system_score_gemma":0.0004510646,"threshold_uncertainty_score":0.01875186},"labels":[],"label_agreement":null},{"id":"W2897779915","doi":"10.1016/j.jalz.2018.06.1327","title":"P2‐631: JAZZERCISE AS AN INTERVENTION FOR SUBJECTIVE COGNITIVE DECLINE IN POSTMENOPAUSAL WOMEN: PILOT STUDY RATIONALE AND FEASIBILITY","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Guenther Dermatology Research Centre; Western University; Robarts Clinical Trials; Parkwood Institute","funders":"","keywords":"Cognition; Physical therapy; Psychology; Cognitive decline; Physical medicine and rehabilitation; Cardiovascular fitness; Gait; Neuropsychology; Diffusion MRI; Posterior cingulate; Medicine; Magnetic resonance imaging; Physical fitness; Dementia; Internal medicine; Psychiatry","score_opus":0.11880431243032989,"score_gpt":0.418394331533933,"score_spread":0.2995900191036031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897779915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87444496,0.0006672354,0.0012202874,0.00056216493,0.00019862878,0.11886031,0.0015493934,0.00013125293,0.0023657961],"genre_scores_gemma":[0.71990186,0.0018061111,0.010650945,0.0013577773,0.0007020422,0.25543785,0.0009244678,0.000051884825,0.009167103],"study_design_codex":"nonrandomized_trial","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.9988803,0.00045885952,0.00009917326,0.00017832727,0.00016181867,0.00022142597],"domain_scores_gemma":[0.99884534,0.0002749976,0.000119754695,0.00012078433,0.00018451677,0.00045456685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030559595,0.0014176888,0.0019715577,0.00086660584,0.0016481268,0.0008229978,0.00167301,0.0024320476,0.0099071],"category_scores_gemma":[0.0020953196,0.0008494014,0.0012626414,0.0006459659,0.0012863654,0.00088390615,0.00092687213,0.0023201318,0.0025395874],"study_design_candidate":"nonrandomized_trial","study_design_consensus":"nonrandomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.4207298,0.49398795,0.0061222804,0.0024059643,0.00049249316,0.00059631903,0.0010029074,0.0004464611,0.023257483,0.00030235355,0.0013247698,0.049331304],"study_design_scores_gemma":[0.122506686,0.8609617,0.011948948,0.00006782686,0.00027287734,0.00005925795,0.00021299068,0.00019980343,0.0018640874,0.00015512433,0.0017281151,0.000022690117],"about_ca_topic_score_codex":0.0021319978,"about_ca_topic_score_gemma":0.0029037583,"teacher_disagreement_score":0.0099071,"about_ca_system_score_codex":0.0004318204,"about_ca_system_score_gemma":0.002956071,"threshold_uncertainty_score":0.033142567},"labels":[],"label_agreement":null},{"id":"W2897798352","doi":"10.1016/j.jalz.2018.06.2291","title":"IC‐P‐224: HETEROGENEOUS TAU‐PET SIGNAL IN THE HIPPOCAMPUS HELPS RESOLVE DISCREPANCIES BETWEEN IMAGING AND PATHOLOGY","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; McGill University Health Centre","funders":"","keywords":"Hippocampus; Entorhinal cortex; Hippocampal formation; Neuroscience; Positron emission tomography; Neuroimaging; Alzheimer's disease; Psychology; Voxel; Pittsburgh compound B; Dementia; Medicine; Pathology; Disease; Cognitive impairment; Cognition; Radiology","score_opus":0.051867200182784026,"score_gpt":0.33499694428727145,"score_spread":0.28312974410448744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897798352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923259,0.0005524673,0.0048611816,0.000028095523,0.000007869818,0.00003714995,0.0008694055,0.00020307407,0.0011148641],"genre_scores_gemma":[0.99096256,0.00027870605,0.0064236782,0.000025934505,0.000011468203,0.000035015273,0.0013247681,0.00011398024,0.00082398555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999859,0.000018997442,0.000014712572,0.000055495762,0.000028767165,0.000023183924],"domain_scores_gemma":[0.99972516,0.00007608393,0.00006782428,0.000052647498,0.000047125945,0.00003125559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005390692,0.00045300796,0.00037227216,0.001523428,0.0003168263,0.00095826347,0.00024409268,0.000495242,0.0013585039],"category_scores_gemma":[0.0012203905,0.00020885801,0.00024256634,0.00075727346,0.00030969828,0.00032203805,0.0003698113,0.0001983846,0.0003506077],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004643845,0.00018308245,0.45696476,0.0008140405,0.0011006544,0.0020121401,0.0012579742,0.004744187,0.3642406,0.0009139485,0.0043148925,0.15880983],"study_design_scores_gemma":[0.000058171147,0.00032606217,0.94262844,0.000050501418,0.00032987987,0.003645086,0.00037843807,0.0070145014,0.041090347,0.0012067799,0.003228411,0.000043368404],"about_ca_topic_score_codex":0.0039054074,"about_ca_topic_score_gemma":0.0094226515,"teacher_disagreement_score":0.0039054074,"about_ca_system_score_codex":0.00020844955,"about_ca_system_score_gemma":0.00018553967,"threshold_uncertainty_score":0.0077653527},"labels":[],"label_agreement":null},{"id":"W2898273293","doi":"10.1002/hbm.24435","title":"Developmental origins of depression‐related white matter properties: Findings from a prenatal birth cohort","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Psychology; Young adult; White matter; Depression (economics); Cingulum (brain); Cohort; Prenatal stress; Longitudinal study; Diffusion MRI; Uncinate fasciculus; Cohort study; Pediatrics; Medicine; Pregnancy; Developmental psychology; Offspring; Internal medicine; Magnetic resonance imaging; Pathology","score_opus":0.053580519763796124,"score_gpt":0.30489348037053304,"score_spread":0.2513129606067369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898273293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996661,0.00008726545,0.000059403832,0.000008311753,0.0000011658112,0.0000026897728,0.000118912685,7.3256683e-7,0.000055435765],"genre_scores_gemma":[0.99960285,0.00011435161,0.00007790825,0.0000063439884,0.0000013495903,0.0000039885003,0.00012837588,0.0000012248846,0.000063638545],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999785,0.000042836975,0.000023039234,0.00007526868,0.000036268695,0.000037632926],"domain_scores_gemma":[0.999524,0.000098798635,0.00016139429,0.00007276747,0.00005817979,0.000084817315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003505801,0.00024166834,0.0002307486,0.00049163494,0.0003533665,0.0003298051,0.00023985765,0.00029014284,0.0008816276],"category_scores_gemma":[0.0014919896,0.00026461628,0.0002296271,0.00046219784,0.00019871855,0.00019876176,0.0004338128,0.00028114812,0.0001185544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060760856,0.000014122062,0.99681985,0.000004444823,0.0000354444,0.00019193122,0.0002921802,0.000014275398,0.0010767722,0.000021208723,0.000031908126,0.0014370385],"study_design_scores_gemma":[9.756808e-7,0.00002110358,0.99952483,0.0000022006147,0.000010551452,0.00018724454,0.00010642066,0.000023794692,0.00007144472,0.0000081819135,0.000042249423,0.0000010432695],"about_ca_topic_score_codex":0.012768368,"about_ca_topic_score_gemma":0.013795014,"teacher_disagreement_score":0.012768368,"about_ca_system_score_codex":0.00019371694,"about_ca_system_score_gemma":0.00020621868,"threshold_uncertainty_score":0.025388062},"labels":[],"label_agreement":null},{"id":"W2898476585","doi":"10.1016/j.neuroimage.2018.10.067","title":"Diffusion tensor imaging shows mechanism-specific differences in injury pattern and progression in rat models of acute spinal cord injury","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; Wings for Life","keywords":"Diffusion MRI; White matter; Spinal cord injury; Spinal cord; Anatomy; Medicine; Corticospinal tract; Cord; Diffuse axonal injury; Superior longitudinal fasciculus; Magnetic resonance imaging; Traumatic brain injury; Radiology; Fractional anisotropy; Surgery","score_opus":0.06474475424370242,"score_gpt":0.3664488663145007,"score_spread":0.3017041120707983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898476585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921767,0.001647773,0.00423967,0.00030209342,0.000089125184,0.00004416095,0.00047471139,0.00014805411,0.00087766396],"genre_scores_gemma":[0.989238,0.0022056529,0.0023040108,0.00011028759,0.00002028951,0.000070410395,0.0006506463,0.00004660194,0.005354087],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978775,0.000019282466,0.0000180357,0.000047417925,0.000046280104,0.000081293314],"domain_scores_gemma":[0.99956554,0.000022927337,0.00017378648,0.000047411773,0.0000817655,0.000108640015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003447914,0.00086701795,0.0005364916,0.0012312294,0.0003520526,0.0005180358,0.00040771128,0.00061159703,0.0015089185],"category_scores_gemma":[0.00034410378,0.00043437368,0.0006518473,0.0005396941,0.0006744569,0.000909851,0.0003244897,0.0016425092,0.0003324369],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001379708,0.00041310495,0.0010274384,0.00011743711,0.00006212977,0.0001981535,0.000092143346,0.00022240424,0.9920919,0.00030548582,0.00021244783,0.0038777392],"study_design_scores_gemma":[0.00005559224,0.0033459945,0.021551067,0.000033265238,0.00018869762,0.0006141655,0.00028226848,0.0017975954,0.9708202,0.00035422805,0.00092232507,0.000034679557],"about_ca_topic_score_codex":0.0061828787,"about_ca_topic_score_gemma":0.009914353,"teacher_disagreement_score":0.0061828787,"about_ca_system_score_codex":0.00054389023,"about_ca_system_score_gemma":0.0007641274,"threshold_uncertainty_score":0.012293756},"labels":[],"label_agreement":null},{"id":"W2898573652","doi":"10.1002/hbm.24437","title":"Corticospinal tract degeneration in ALS unmasked in T1‐weighted images using texture analysis","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Canadian Institutes of Health Research; Fondation Brain Canada; ALS Society of Canada; ALS Association","keywords":"Corticospinal tract; Medicine; Diffusion MRI; Voxel; Magnetic resonance imaging; Amyotrophic lateral sclerosis; Nuclear medicine; Internal capsule; Radiology; Pathology; White matter","score_opus":0.12037111040865021,"score_gpt":0.40619548992288373,"score_spread":0.2858243795142335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898573652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981798,0.00013029571,0.0014743425,0.000015418105,0.000003967821,0.000007269626,0.000032548123,0.000011812514,0.00014461135],"genre_scores_gemma":[0.9988682,0.00006391791,0.00093327294,0.000004918908,0.0000068154663,0.0000037778614,0.00004701143,0.000002891266,0.00006917545],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998288,0.00004434606,0.000015846796,0.00003424387,0.000045618686,0.000031073516],"domain_scores_gemma":[0.9994777,0.00016506169,0.00018896481,0.000052082167,0.00007043008,0.00004583672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005886938,0.00026398778,0.00025031177,0.0012640198,0.00016989427,0.00054707896,0.00014198032,0.00022853131,0.00057880214],"category_scores_gemma":[0.0018806359,0.00014133775,0.00020300767,0.000506375,0.0002849955,0.00036137606,0.00033481474,0.0001270692,0.00012737601],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031584592,0.00012261659,0.7509441,0.00017361656,0.00024404156,0.0015236448,0.00067317934,0.0015947965,0.13876678,0.0002498465,0.00037479922,0.10217411],"study_design_scores_gemma":[0.000025591695,0.0003064536,0.9783366,0.00001734872,0.00007893607,0.0024117897,0.00029685738,0.010678253,0.0070549906,0.00045553764,0.00031671597,0.00002094548],"about_ca_topic_score_codex":0.0011359217,"about_ca_topic_score_gemma":0.0016273778,"teacher_disagreement_score":0.0012640198,"about_ca_system_score_codex":0.00013605061,"about_ca_system_score_gemma":0.00010795934,"threshold_uncertainty_score":0.003113389},"labels":[],"label_agreement":null},{"id":"W2899191342","doi":"10.1016/j.nicl.2018.10.026","title":"Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Ministry of Education; Ministry of Education - Singapore; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Alzheimer's Drug Discovery Foundation; AbbVie; Alzheimer's Association; Foundation for the National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Precuneus; Psychology; White matter; Neuroscience; Apolipoprotein E; Cognitive decline; Temporal lobe; Corpus callosum; Cognition; Dementia; Disease; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.242862737418475,"score_gpt":0.4746921061407849,"score_spread":0.2318293687223099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899191342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94826347,0.0016052154,0.046040855,0.00020823698,0.000024955772,0.000085541746,0.0023934774,0.0001690159,0.0012092507],"genre_scores_gemma":[0.9910568,0.00019053517,0.006647731,0.000026403875,0.000024758205,0.000049150352,0.0017096003,0.000027241816,0.00026770245],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99899143,0.00031363522,0.0001026794,0.00033466244,0.00013187679,0.00012574258],"domain_scores_gemma":[0.9976871,0.001136952,0.000495643,0.0003205784,0.00023369823,0.00012606196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021569715,0.0007200008,0.00076525327,0.0037554244,0.00037263022,0.0013178154,0.00034529186,0.0005779953,0.001219101],"category_scores_gemma":[0.006130676,0.00017780869,0.0010537845,0.002268701,0.00043663481,0.00073640957,0.0009307217,0.000490594,0.00034934032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011830973,0.00016583131,0.87374395,0.00020086287,0.001275722,0.00044836538,0.0009966713,0.011147205,0.011057214,0.0017802025,0.0021094892,0.095891275],"study_design_scores_gemma":[0.00004342998,0.00021184329,0.8795148,0.00008958101,0.00053084886,0.00090043904,0.0007044103,0.09938064,0.002543246,0.012911347,0.0030760777,0.000093273426],"about_ca_topic_score_codex":0.004636658,"about_ca_topic_score_gemma":0.0043358207,"teacher_disagreement_score":0.004636658,"about_ca_system_score_codex":0.00042573377,"about_ca_system_score_gemma":0.0004760421,"threshold_uncertainty_score":0.011407316},"labels":[],"label_agreement":null},{"id":"W2899606321","doi":"10.1371/journal.pone.0206607","title":"Data-driven, voxel-based analysis of brain PET images: Application of PCA and LASSO methods to visualize and quantify patterns of neurodegeneration","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Lasso (programming language); Voxel; Principal component analysis; Pattern recognition (psychology); Artificial intelligence; Functional principal component analysis; Positron emission tomography; Computer science; Covariate; Mathematics; Nuclear medicine; Medicine; Machine learning","score_opus":0.1882450430924438,"score_gpt":0.44988884250456906,"score_spread":0.26164379941212523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899606321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023262557,0.0002237745,0.9753237,0.00017919588,0.000022681934,0.000033387183,0.00018876817,0.0005361714,0.00022962647],"genre_scores_gemma":[0.47912398,0.0006534067,0.51663256,0.00018529192,0.00009006716,0.00037342447,0.0013316828,0.0003173967,0.0012922168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992931,0.00029331996,0.000047245678,0.0001629383,0.0001607152,0.000042607102],"domain_scores_gemma":[0.99856704,0.0007853235,0.00027027287,0.00012629185,0.00020831618,0.000042860425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00197853,0.0009885776,0.00093968865,0.00083190826,0.00024703,0.0010647415,0.0006647792,0.00074567576,0.0004897376],"category_scores_gemma":[0.0035913084,0.00042742075,0.001176493,0.0008389978,0.00060548366,0.00055591424,0.00064028095,0.0012461678,0.00021378683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001833455,0.00014203775,0.00543609,0.0002705684,0.00039706627,0.00023166106,0.00021338504,0.76550084,0.04025724,0.0069214036,0.002529969,0.17791642],"study_design_scores_gemma":[0.0000036960223,0.000022536273,0.001288281,0.0000053587432,0.000009107083,0.000037798385,0.00001080695,0.993658,0.0021285494,0.002357901,0.00046112968,0.000016756196],"about_ca_topic_score_codex":0.0018437656,"about_ca_topic_score_gemma":0.0017903254,"teacher_disagreement_score":0.00197853,"about_ca_system_score_codex":0.0003275106,"about_ca_system_score_gemma":0.00079682184,"threshold_uncertainty_score":0.010463595},"labels":[],"label_agreement":null},{"id":"W2900068659","doi":"10.1007/s12035-018-1405-1","title":"Regional Amyloid-β Load and White Matter Abnormalities Contribute to Hypometabolism in Alzheimer’s Dementia","year":2018,"lang":"en","type":"article","venue":"Molecular Neurobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute","funders":"National Institute on Aging","keywords":"Fractional anisotropy; Precuneus; Diffusion MRI; White matter; Standardized uptake value; Dementia; Psychology; Positron emission tomography; Neuroscience; Posterior cingulate; Neuroimaging; Pathology; Magnetic resonance imaging; Internal medicine; Medicine; Disease; Cognition; Radiology","score_opus":0.038701346181607706,"score_gpt":0.31713659956393536,"score_spread":0.27843525338232766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900068659","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965491,0.0021983958,0.00028598245,0.00009341938,0.000015471833,0.0000052325745,0.000047975354,0.00001428838,0.0007900937],"genre_scores_gemma":[0.9983504,0.0008298787,0.00033105916,0.00003940259,0.000051038365,0.0000051384263,0.00007596141,0.000004117391,0.00031296382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998946,0.000024182636,0.000021723718,0.00002138478,0.000023952101,0.000014176326],"domain_scores_gemma":[0.9995621,0.00009075502,0.00019865925,0.00002858611,0.000064763575,0.00005512645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005188556,0.0007583827,0.00047472463,0.001498396,0.00032427936,0.0008905352,0.00040509002,0.000592169,0.0011122725],"category_scores_gemma":[0.001175845,0.00050976814,0.00026838787,0.00075357576,0.00046156804,0.00070030324,0.00036489448,0.00056376617,0.00022668947],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0058897026,0.00071174593,0.8328554,0.00041129751,0.0007630481,0.014872419,0.00095489965,0.0009212974,0.07482766,0.00066246616,0.0007186974,0.06641135],"study_design_scores_gemma":[0.000030695144,0.00023827983,0.98580337,0.000026052121,0.00021478639,0.007903306,0.00029811493,0.00080913486,0.002499989,0.0018407368,0.0003223071,0.0000132069545],"about_ca_topic_score_codex":0.00091743807,"about_ca_topic_score_gemma":0.0010402377,"teacher_disagreement_score":0.001498396,"about_ca_system_score_codex":0.0002094982,"about_ca_system_score_gemma":0.00016856786,"threshold_uncertainty_score":0.0037209392},"labels":[],"label_agreement":null},{"id":"W2900602020","doi":"10.3389/fncel.2018.00428","title":"White Matter Plasticity Keeps the Brain in Tune: Axons Conduct While Glia Wrap","year":2018,"lang":"en","type":"review","venue":"Frontiers in Cellular Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Neuroscience; Glutamatergic; Neuroplasticity; Context (archaeology); Biology; White matter; Oligodendrocyte; Myelin; Plasticity; Diffusion MRI; Psychology; Central nervous system; Glutamate receptor; Physics; Medicine","score_opus":0.1321283382690935,"score_gpt":0.36998595918111293,"score_spread":0.23785762091201942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900602020","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020659037,0.9965814,0.0005120578,0.0006520551,0.00033501972,0.0000043989003,0.000025131425,0.000016834927,0.001666549],"genre_scores_gemma":[0.0013456609,0.99683595,0.00042384572,0.00026198334,0.0001781948,0.0000070601313,0.000027486518,0.0000033980523,0.00091650564],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99986744,0.000021092459,0.000022452465,0.00002810096,0.00004768187,0.0000132196055],"domain_scores_gemma":[0.999783,0.00009357883,0.000030366518,0.000010542276,0.000064368134,0.000018197328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038890124,0.0007477675,0.0008658576,0.0017652233,0.0003142207,0.0011003688,0.0006602936,0.0012795213,0.002537594],"category_scores_gemma":[0.0006044564,0.00020747598,0.00035750994,0.0013640145,0.00078619167,0.0016616866,0.00075253984,0.001367174,0.001983198],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043232867,0.00002757791,0.00016136136,0.015237184,0.00006593948,0.00030773468,0.00014995874,0.00037880885,0.0070328168,0.0130699705,0.020745965,0.9427793],"study_design_scores_gemma":[0.000004140994,0.000047028512,0.0005323891,0.0019325761,0.000043191114,0.0014035836,0.00007384166,0.00005282069,0.0011704006,0.004495897,0.99022955,0.000014552297],"about_ca_topic_score_codex":0.0008842748,"about_ca_topic_score_gemma":0.0015162186,"teacher_disagreement_score":0.002537594,"about_ca_system_score_codex":0.0006523541,"about_ca_system_score_gemma":0.0012844213,"threshold_uncertainty_score":0.008489132},"labels":[],"label_agreement":null},{"id":"W2900804267","doi":"10.1016/j.neuroimage.2018.11.015","title":"Arterial stiffness and white matter integrity in the elderly: A diffusion tensor and magnetization transfer imaging study","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Clinical Research Institute; Université de Montréal; Polytechnique Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Arterial stiffness; Corpus callosum; Internal capsule; Myelin; Corona radiata (embryology); External capsule; Pulse wave velocity; Internal medicine; Cardiology; Medicine; Anatomy; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.036469752460684284,"score_gpt":0.32324278488670943,"score_spread":0.28677303242602514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900804267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995142,0.00017545765,0.000049981874,0.000022364491,0.000004086556,0.0000040284913,0.000048177884,0.0000012466407,0.00018036865],"genre_scores_gemma":[0.9993537,0.0001348697,0.0001304171,0.00003588181,0.000023574252,0.000004434915,0.00006336649,0.0000011786598,0.0002525705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998679,0.000022277363,0.00001956973,0.000037792684,0.0000261197,0.000026361264],"domain_scores_gemma":[0.99946624,0.0001019696,0.00013663895,0.00005705854,0.000083759114,0.00015434953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064670725,0.00050821464,0.00040332752,0.0006756844,0.00054018764,0.0004424774,0.00023500381,0.0007704874,0.0009764987],"category_scores_gemma":[0.0012767245,0.0004967265,0.00043394824,0.0007949637,0.00043991525,0.00076816336,0.00041103814,0.0004981777,0.00028948305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00347177,0.000674072,0.9698145,0.00007501402,0.00047479363,0.003828706,0.0013081748,0.00012742839,0.013416547,0.000075127704,0.00018642013,0.0065475116],"study_design_scores_gemma":[0.000038254246,0.0007208066,0.9961547,0.000005259831,0.00014270056,0.0017108554,0.0004320319,0.0001690566,0.00038937363,0.000073324445,0.00015343638,0.000010111022],"about_ca_topic_score_codex":0.0042638006,"about_ca_topic_score_gemma":0.005379465,"teacher_disagreement_score":0.0042638006,"about_ca_system_score_codex":0.00020891834,"about_ca_system_score_gemma":0.00029341984,"threshold_uncertainty_score":0.008477926},"labels":[],"label_agreement":null},{"id":"W2900930986","doi":"10.1016/j.nicl.2018.11.006","title":"White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; Canada Research Chairs; SickKids Foundation; University of Toronto; Children's Hospital of Western Ontario; Hospital for Sick Children; Western University","funders":"Canadian Institutes of Health Research; Ontario Brain Institute","keywords":"White matter; Corpus callosum; Fractional anisotropy; Corona radiata (embryology); Diffusion MRI; Interquartile range; Fasciculus; Medicine; Magnetic resonance imaging; Connectome; Diffuse axonal injury; Anatomy; Neuroscience; Functional connectivity; Internal medicine; Psychology; Traumatic brain injury; Radiology","score_opus":0.060511695163842416,"score_gpt":0.3845515843053998,"score_spread":0.3240398891415574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900930986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995938,0.000100541605,0.00013723143,0.00001897191,0.0000016669452,0.0000025052893,0.000059762617,0.000002963393,0.00008252804],"genre_scores_gemma":[0.99951696,0.00009060072,0.00020946724,0.000008648376,0.000002846845,0.000007879259,0.00010961204,0.0000023206571,0.00005156718],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997584,0.00005153401,0.000036021887,0.00007185677,0.000049456234,0.000032759228],"domain_scores_gemma":[0.9981019,0.0003915851,0.0010939158,0.0000942612,0.00014783377,0.00017059418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006026045,0.0003720412,0.00027107785,0.00067436305,0.00019722148,0.00045302504,0.0004074519,0.0005799273,0.0009987835],"category_scores_gemma":[0.005334356,0.0002021699,0.0003564814,0.00035655283,0.0004196125,0.00032755337,0.0005550629,0.00039876084,0.00014651536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013727466,0.000015773261,0.99464273,0.000017927936,0.00004927008,0.0006445458,0.0001304872,0.00022369728,0.002030479,0.000039936862,0.000041023413,0.0020268147],"study_design_scores_gemma":[0.0000020718078,0.00007337646,0.99778014,0.0000149051,0.000015850834,0.0010400888,0.00013809894,0.00041367084,0.00042000235,0.00006431299,0.000034151224,0.0000033082147],"about_ca_topic_score_codex":0.0031612995,"about_ca_topic_score_gemma":0.0027812675,"teacher_disagreement_score":0.0031612995,"about_ca_system_score_codex":0.0003381696,"about_ca_system_score_gemma":0.0003040585,"threshold_uncertainty_score":0.0062858462},"labels":[],"label_agreement":null},{"id":"W2900990031","doi":"10.3389/fnins.2018.00854","title":"Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; University of Manitoba; University of British Columbia","funders":"National Research Foundation of Korea; National Research Foundation","keywords":"White matter; Corpus callosum; Reproducibility; Myelin; Magnetic resonance imaging; Nuclear magnetic resonance; Nuclear medicine; Splenium; T2 relaxation; Coefficient of variation; Relaxometry; Spin echo; Chemistry; Medicine; Radiology; Physics; Pathology; Internal medicine; Central nervous system","score_opus":0.08428072625631944,"score_gpt":0.3744385856514024,"score_spread":0.290157859395083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900990031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87995285,0.0010469911,0.11530896,0.00009346738,0.00014803452,0.00029136293,0.00058356975,0.00064684084,0.0019279293],"genre_scores_gemma":[0.952502,0.00012124267,0.04560519,0.00006482861,0.000023800694,0.00022933554,0.0006082565,0.0002722487,0.00057311717],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9874544,0.0051560914,0.0016704277,0.0029454771,0.0024635557,0.0003099883],"domain_scores_gemma":[0.97377354,0.010403813,0.0029775463,0.0061178072,0.0064192964,0.00030812254],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.018154446,0.00065339415,0.0007826732,0.0008875731,0.00067317806,0.0012545872,0.0009246326,0.0007954441,0.0009635662],"category_scores_gemma":[0.031266507,0.0006271076,0.00066433806,0.00077640876,0.00086869585,0.0007152478,0.0011412873,0.0004419477,0.0006124154],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006807328,0.0005250239,0.3158594,0.0013883446,0.0035474976,0.0010045612,0.0073512346,0.011585505,0.489941,0.0015635815,0.0021482257,0.15827832],"study_design_scores_gemma":[0.00025414844,0.0025715886,0.77786833,0.00015001066,0.0015505264,0.003952208,0.0011106319,0.031200014,0.1705471,0.0023766144,0.0080869915,0.00033192476],"about_ca_topic_score_codex":0.0016071361,"about_ca_topic_score_gemma":0.0031121608,"teacher_disagreement_score":0.98184556,"about_ca_system_score_codex":0.00030846422,"about_ca_system_score_gemma":0.0005236953,"threshold_uncertainty_score":0.09601104},"labels":[],"label_agreement":null},{"id":"W2901083077","doi":"10.1002/jmri.26543","title":"White matter myelin profiles linked to clinical subtypes of Parkinson's disease","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Myelin; Psychology; Medicine; Apathy; Population; Cingulum (brain); Internal medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.043332027507938325,"score_gpt":0.37115914392323757,"score_spread":0.32782711641529927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901083077","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99969494,0.00007170462,0.000053007432,0.0000063810176,6.769041e-7,0.0000063002194,0.00007083112,0.0000019086522,0.00009430105],"genre_scores_gemma":[0.99965274,0.000023355304,0.00007585225,0.000005657835,0.0000027328574,0.0000064282053,0.00018197639,0.0000012890663,0.00004988246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978524,0.000049079226,0.000038583727,0.00006677761,0.0000387663,0.000021538148],"domain_scores_gemma":[0.9982634,0.0002803634,0.0009794781,0.000102859485,0.00020481662,0.00016908794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057098496,0.0004457786,0.00029918703,0.00093532255,0.00034703515,0.00032787485,0.00023777557,0.00047639527,0.0014101093],"category_scores_gemma":[0.0019237825,0.00020214409,0.00017031046,0.0004971974,0.0004157531,0.00027505847,0.0004744145,0.00027792176,0.00020930036],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060798135,0.00004604204,0.9953537,0.00001634905,0.00006636633,0.00022997674,0.000106604006,0.00007523324,0.0020139087,0.000018257946,0.000037831418,0.0014278396],"study_design_scores_gemma":[0.000011127826,0.00017940963,0.9982091,0.0000032930511,0.000018760084,0.0011640489,0.0000721415,0.00009492927,0.00017103819,0.00004056377,0.00003357987,0.0000019538334],"about_ca_topic_score_codex":0.0011495277,"about_ca_topic_score_gemma":0.0014010266,"teacher_disagreement_score":0.0014101093,"about_ca_system_score_codex":0.00018139735,"about_ca_system_score_gemma":0.00016395187,"threshold_uncertainty_score":0.004717231},"labels":[],"label_agreement":null},{"id":"W2901161095","doi":"10.1089/brain.2018.0611","title":"Microstructural Findings in White Matter Associated with Cannabis and Alcohol Use in Early-Phase Psychosis: A Diffusion Tensor Imaging and Relaxometry Study","year":2018,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"International Business Machines Corporation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Cannabis; Psychosis; Psychology; Relaxometry; Inferior longitudinal fasciculus; Schizophrenia (object-oriented programming); Psychiatry; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.03454579141614181,"score_gpt":0.3432349715257514,"score_spread":0.30868918010960955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901161095","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995623,0.00012525677,0.000118055854,0.000013554126,8.868264e-7,0.000008303308,0.000036984755,0.0000017880914,0.00013291402],"genre_scores_gemma":[0.9995684,0.0001025621,0.00016676231,0.000007104238,0.0000025209383,0.000004465511,0.000046086614,0.0000015604184,0.00010061971],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989486,0.00001629701,0.000015782805,0.000026940612,0.000021823935,0.000024298228],"domain_scores_gemma":[0.99953973,0.000072396215,0.00020449865,0.000030750292,0.0000644597,0.00008825264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003305609,0.00030750845,0.00020153921,0.0012182838,0.0003388234,0.0003460104,0.00017347449,0.00029556177,0.0010241122],"category_scores_gemma":[0.0011193458,0.00030410028,0.00027119418,0.00054302125,0.0003855077,0.00032266037,0.0004641878,0.00024758742,0.00013946068],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012845807,0.00018360549,0.9181769,0.0001274373,0.00018203926,0.00811014,0.0016008216,0.00024301284,0.062601514,0.00010852826,0.00007032268,0.0073112245],"study_design_scores_gemma":[0.0000077840305,0.00017447244,0.99450016,0.000007417331,0.000034864282,0.0037716413,0.0002791124,0.00021148466,0.00087218836,0.000047129462,0.00008742507,0.0000063257535],"about_ca_topic_score_codex":0.0057975114,"about_ca_topic_score_gemma":0.0063645174,"teacher_disagreement_score":0.0057975114,"about_ca_system_score_codex":0.0002713809,"about_ca_system_score_gemma":0.00039117754,"threshold_uncertainty_score":0.011527538},"labels":[],"label_agreement":null},{"id":"W2901273401","doi":"10.1371/journal.pone.0203271","title":"Diffusion spectrum imaging in white matter microstructure in subjects with type 2 diabetes","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Fractional anisotropy; Cingulum (brain); Uncinate fasciculus; White matter; Medicine; Diffusion MRI; Internal medicine; Tractography; Cardiology; Glycated hemoglobin; Type 2 diabetes; Fasciculus; Diabetes mellitus; Nuclear medicine; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.02455098010149183,"score_gpt":0.26337317626290463,"score_spread":0.23882219616141281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901273401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999116,0.000552243,0.00008372498,0.000014924757,0.0000044815706,0.0000036352553,0.000037223734,0.0000023394232,0.00018549424],"genre_scores_gemma":[0.99937975,0.00022152084,0.00017372817,0.000017897328,0.000011468979,0.0000037282077,0.00006778198,0.0000013574848,0.00012285219],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998963,0.000022050832,0.00001254796,0.00003684591,0.000018523897,0.000013836114],"domain_scores_gemma":[0.99977833,0.00003820424,0.00010597877,0.000013939915,0.000028783452,0.000034694247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036383385,0.00032491036,0.00023310697,0.00052748446,0.00029262056,0.00041104577,0.00011214744,0.00030950317,0.00065281184],"category_scores_gemma":[0.00072713377,0.00014522737,0.00015309484,0.00039885537,0.00019272412,0.0002730721,0.00018407499,0.0002121441,0.00008503788],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059911126,0.000074813666,0.9853431,0.00003524019,0.00009534727,0.0004545297,0.0002717821,0.00006770142,0.0064384984,0.00003291778,0.00005973888,0.006527101],"study_design_scores_gemma":[0.000009983046,0.00013454897,0.99877673,0.0000041729863,0.000032027594,0.0004986744,0.000099071854,0.000112906906,0.00020756898,0.000029071376,0.000092565555,0.0000027253454],"about_ca_topic_score_codex":0.00253781,"about_ca_topic_score_gemma":0.0032451442,"teacher_disagreement_score":0.00253781,"about_ca_system_score_codex":0.00012713161,"about_ca_system_score_gemma":0.00011563737,"threshold_uncertainty_score":0.00504601},"labels":[],"label_agreement":null},{"id":"W2901408666","doi":"10.1159/000494134","title":"Repeated Pediatric Concussions Evoke Long-Term Oligodendrocyte and White Matter Microstructural Dysregulation Distant from the Injury","year":2018,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"","keywords":"White matter; Concussion; Diffusion MRI; OLIG2; Traumatic brain injury; Medicine; Neuroscience; Anterior commissure; Neuropsychology; Psychology; Oligodendrocyte; Poison control; Myelin; Cognition; Injury prevention; Magnetic resonance imaging; Psychiatry; Central nervous system; Radiology","score_opus":0.031064054534084288,"score_gpt":0.31557673334302994,"score_spread":0.28451267880894565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901408666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98840106,0.0031023903,0.0044492823,0.00020976314,0.00009851391,0.00010060591,0.0012259017,0.0001873903,0.0022250244],"genre_scores_gemma":[0.98540944,0.003916974,0.0045858794,0.0002926568,0.000045304252,0.0002779224,0.0016479309,0.000055986944,0.0037679828],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99958855,0.000022454336,0.000038367263,0.00010167161,0.00012024266,0.00012871766],"domain_scores_gemma":[0.99961215,0.000016785374,0.00017074008,0.000023123912,0.00007931848,0.000097807475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021318858,0.00075771735,0.0005393706,0.0007505539,0.00047292607,0.0004588897,0.00028783455,0.0006270028,0.0015227768],"category_scores_gemma":[0.00025729035,0.00026470155,0.00055907137,0.0003624316,0.0005883345,0.00046992337,0.0005518408,0.0014256713,0.0004477256],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003816996,0.000159039,0.0062528444,0.00032737886,0.00004959032,0.0009745591,0.00021153865,0.00013247122,0.98494697,0.00019078421,0.00031318265,0.006060005],"study_design_scores_gemma":[0.000033709137,0.002651639,0.17938711,0.00016193044,0.00018326545,0.0038476526,0.001150095,0.0007718215,0.80584735,0.00027851472,0.005649926,0.000037048878],"about_ca_topic_score_codex":0.0030110604,"about_ca_topic_score_gemma":0.0074935146,"teacher_disagreement_score":0.0030110604,"about_ca_system_score_codex":0.0004976129,"about_ca_system_score_gemma":0.0006790335,"threshold_uncertainty_score":0.005987048},"labels":[],"label_agreement":null},{"id":"W2901469177","doi":"10.1016/j.arr.2018.11.004","title":"MRI-based evaluation of structural degeneration in the ageing brain: Pathophysiology and assessment","year":2018,"lang":"en","type":"review","venue":"Ageing Research Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Columbian Hospital; Surrey Memorial Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; China Scholarship Council","keywords":"Ageing; White matter; Neuroscience; Atrophy; Brain aging; Medicine; Magnetic resonance imaging; Degeneration (medical); Pathology; Physical medicine and rehabilitation; Psychology; Radiology; Disease; Internal medicine","score_opus":0.5339555385415052,"score_gpt":0.6172250369411001,"score_spread":0.08326949839959485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901469177","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00025140587,0.99876934,0.00030605413,0.00018168887,0.000077616154,0.000005565175,0.000022410977,0.0000062546483,0.0003795983],"genre_scores_gemma":[0.001995332,0.99646616,0.0008129704,0.00015554731,0.0002598397,0.0000093477065,0.00003521112,0.0000023722228,0.00026324933],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99962497,0.000068630514,0.000061919534,0.000074672775,0.00014036291,0.000029414794],"domain_scores_gemma":[0.9988605,0.0005920146,0.00017111977,0.00002673781,0.00031255002,0.00003716144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013271588,0.0010990619,0.0018972242,0.0035665773,0.00019536188,0.0013746297,0.0009922108,0.0013564115,0.001414694],"category_scores_gemma":[0.002516561,0.0003218057,0.0006576201,0.0021354528,0.0008371996,0.0014868149,0.00066218415,0.0011077484,0.0008306955],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012840902,0.000073730735,0.0012979362,0.020458778,0.00027817354,0.00037842497,0.000078015815,0.00030963297,0.004458634,0.0020580213,0.011164672,0.95931554],"study_design_scores_gemma":[0.00008324817,0.00056843564,0.021147551,0.03195296,0.0024184056,0.017915538,0.00054619,0.001216253,0.009853013,0.013422249,0.90063673,0.00023951009],"about_ca_topic_score_codex":0.0023701007,"about_ca_topic_score_gemma":0.0040409495,"teacher_disagreement_score":0.0035665773,"about_ca_system_score_codex":0.00054935744,"about_ca_system_score_gemma":0.0015785227,"threshold_uncertainty_score":0.007018745},"labels":[],"label_agreement":null},{"id":"W2901502594","doi":"10.1016/j.neuroimage.2018.11.018","title":"Bundle-specific tractography with incorporated anatomical and orientational priors","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Computer science; Artificial intelligence; Bundle; Diffusion MRI; Representation (politics); Prior probability; False positive paradox; Pattern recognition (psychology); Computer vision; Bayesian probability; Magnetic resonance imaging","score_opus":0.05679261682419582,"score_gpt":0.3304423075185419,"score_spread":0.2736496906943461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901502594","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036051448,0.000095235424,0.9949883,0.00010277989,0.000021791178,0.000022595861,0.00011776739,0.0006915408,0.00035486804],"genre_scores_gemma":[0.12802121,0.00039088223,0.8656325,0.000120189514,0.000069949776,0.0001858592,0.000771409,0.0010930529,0.0037149661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995024,0.00019825224,0.00003539657,0.0001244792,0.00009888351,0.000040554354],"domain_scores_gemma":[0.9985341,0.0006638406,0.0001926129,0.0003093616,0.00020485028,0.0000952357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023302566,0.0010724426,0.0012758086,0.0008452366,0.0005958317,0.0021669094,0.0014914364,0.0022465342,0.0038157422],"category_scores_gemma":[0.0068821837,0.0014325824,0.0015263675,0.0015610243,0.0007354183,0.0024707373,0.0016206893,0.0025182983,0.002302164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044689968,0.00012946717,0.0017714698,0.00029807098,0.00040080692,0.00031539364,0.00023735748,0.7256013,0.015845316,0.04981859,0.0068653286,0.1982699],"study_design_scores_gemma":[0.000031640182,0.000046531703,0.0004413483,0.000024257819,0.000050325292,0.00019745188,0.000011098266,0.9676783,0.0037323774,0.023617467,0.00413624,0.000032975437],"about_ca_topic_score_codex":0.007507482,"about_ca_topic_score_gemma":0.016806986,"teacher_disagreement_score":0.007507482,"about_ca_system_score_codex":0.00071472785,"about_ca_system_score_gemma":0.0031756142,"threshold_uncertainty_score":0.014927566},"labels":[],"label_agreement":null},{"id":"W2901779940","doi":"10.1007/s00429-018-1798-7","title":"A population-based atlas of the human pyramidal tract in 410 healthy participants","year":2018,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Région Normandie","keywords":"Tractography; Pyramidal tracts; Diffusion MRI; Atlas (anatomy); Population; Corticospinal tract; Human brain; Artificial intelligence; Neuroscience; Psychology; Magnetic resonance imaging; Computer science; Anatomy; Medicine; Radiology","score_opus":0.0587474499733975,"score_gpt":0.3642715730419366,"score_spread":0.3055241230685391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901779940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9478482,0.00026524658,0.018810026,0.00014877977,0.000017037013,0.00013750487,0.023562478,0.00043714215,0.008773571],"genre_scores_gemma":[0.9781697,0.00021846476,0.010136333,0.00003545034,0.000008071961,0.00013156584,0.0070698624,0.00006609379,0.004164537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999329,0.000011865749,0.000005316782,0.000028289684,0.000011437022,0.000010164589],"domain_scores_gemma":[0.9998739,0.00003018915,0.000016890706,0.00002952623,0.000038508955,0.000010994809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020724387,0.00019611888,0.00016949848,0.0007162559,0.00040823166,0.00038126393,0.00026613663,0.00039219053,0.0061437986],"category_scores_gemma":[0.0006135193,0.00020900244,0.00015018084,0.0008703268,0.00025418936,0.00020938378,0.00024205068,0.00014382062,0.0009870538],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024957135,0.0003952057,0.4956232,0.0006850712,0.0004794373,0.007608616,0.009393536,0.014883861,0.112477906,0.008087458,0.06134764,0.2865224],"study_design_scores_gemma":[0.000056992736,0.00024841275,0.9441519,0.00003833441,0.00010695039,0.012372022,0.0014940302,0.0059441226,0.0034165573,0.0046795676,0.027423685,0.00006751223],"about_ca_topic_score_codex":0.020581774,"about_ca_topic_score_gemma":0.05104241,"teacher_disagreement_score":0.020581774,"about_ca_system_score_codex":0.00025838453,"about_ca_system_score_gemma":0.0005807182,"threshold_uncertainty_score":0.040923953},"labels":[],"label_agreement":null},{"id":"W2901968891","doi":"10.3389/fncel.2018.00430","title":"Patterns of Cerebellar Gray Matter Atrophy Across Alzheimer’s Disease Progression","year":2018,"lang":"en","type":"article","venue":"Frontiers in Cellular Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministero della Salute","keywords":"Cerebellum; Voxel-based morphometry; Cerebellar vermis; Neuroscience; Atrophy; Dementia; Grey matter; Voxel; Psychology; Pathology; Cognition; Alzheimer's disease; Medicine; Anatomy; White matter; Disease; Magnetic resonance imaging; Radiology","score_opus":0.04246044604399141,"score_gpt":0.3516118511360751,"score_spread":0.3091514050920837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901968891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985104,0.0003889838,0.00033005324,0.000012394272,0.0000017034268,0.0000073695596,0.00022799154,0.000023679226,0.0004974807],"genre_scores_gemma":[0.99865746,0.00017539755,0.0004398421,0.000006087899,0.0000026546193,0.000008306116,0.0002843792,0.0000065402132,0.00041937598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986565,0.000024275052,0.00001381495,0.00005435832,0.000020752901,0.000021107433],"domain_scores_gemma":[0.99970573,0.000046942292,0.00012170784,0.00003351629,0.0000510699,0.00004099177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003944235,0.0002238857,0.0002238522,0.0014521104,0.00017941452,0.00047367168,0.00017998903,0.00028042452,0.000964339],"category_scores_gemma":[0.0005958916,0.000117228585,0.00021741606,0.0004760882,0.00027833437,0.00021143611,0.0003005192,0.00022027995,0.0002729508],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027001004,0.00014958173,0.8291605,0.00014482978,0.0002879312,0.0014395269,0.0021391283,0.0010787019,0.10813842,0.00030026832,0.00047491112,0.053985998],"study_design_scores_gemma":[0.000003695463,0.0001487362,0.99741334,0.000006633172,0.000024038045,0.0005278678,0.00010410579,0.00027376582,0.0011588598,0.00009018915,0.00024464034,0.000004020077],"about_ca_topic_score_codex":0.0036452697,"about_ca_topic_score_gemma":0.004066411,"teacher_disagreement_score":0.0036452697,"about_ca_system_score_codex":0.00017863253,"about_ca_system_score_gemma":0.00016219143,"threshold_uncertainty_score":0.0072481036},"labels":[],"label_agreement":null},{"id":"W2901971624","doi":"10.1002/hbm.24463","title":"Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research; National Institute of Nursing Research; Alzheimer Society Research Program; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; Canadian Bee Research Fund; National Institutes of Health; Michael Smith Health Research BC","keywords":"Covariate; Database; Harmonization; Computer science; Goodness of fit; Confounding; Statistics; Data mining; Mathematics; Machine learning","score_opus":0.08452248102561821,"score_gpt":0.3890073806962967,"score_spread":0.3044848996706785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901971624","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41793266,0.000920661,0.57323885,0.00060161337,0.000113128335,0.0007198282,0.0018517084,0.0020662234,0.002555282],"genre_scores_gemma":[0.84711415,0.00013792819,0.1495038,0.0001091415,0.000039795814,0.00039574207,0.0016748107,0.0007163537,0.00030833433],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.93845016,0.043131005,0.0053742016,0.005434819,0.006998403,0.0006114131],"domain_scores_gemma":[0.7399969,0.18874854,0.016943494,0.042128637,0.011528026,0.0006543041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.086004145,0.0008787614,0.00083186186,0.0031428463,0.0011442585,0.002492865,0.0012569723,0.00091985246,0.0017106053],"category_scores_gemma":[0.21513082,0.00044550098,0.0014066786,0.0035146282,0.003026236,0.0022559327,0.0027291377,0.0009991394,0.00042845547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003472787,0.00043551944,0.46812713,0.00101772,0.0054765255,0.00046889088,0.0031306709,0.096212804,0.02558671,0.018780174,0.00795715,0.36933404],"study_design_scores_gemma":[0.00027845282,0.0016373745,0.63588625,0.00025273004,0.0009067856,0.001682189,0.001466957,0.28214425,0.04116695,0.022062827,0.012099858,0.0004153373],"about_ca_topic_score_codex":0.0016806866,"about_ca_topic_score_gemma":0.002511129,"teacher_disagreement_score":0.086004145,"about_ca_system_score_codex":0.00073203543,"about_ca_system_score_gemma":0.0015283673,"threshold_uncertainty_score":0.4548388},"labels":[],"label_agreement":null},{"id":"W2902067632","doi":"10.1016/j.mri.2018.11.014","title":"Challenges in diffusion MRI tractography – Lessons learned from international benchmark competitions","year":2018,"lang":"en","type":"review","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Science Foundation","keywords":"Tractography; Diffusion MRI; Benchmark (surveying); Computer science; Neuroimaging; Perspective (graphical); Data science; Field (mathematics); Reliability (semiconductor); Medical physics; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology; Cartography; Geography; Mathematics; Physics","score_opus":0.20952158320229128,"score_gpt":0.4216562884691373,"score_spread":0.212134705266846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902067632","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009978319,0.98533314,0.0010276927,0.008797673,0.0010823391,0.000011347349,0.00007347359,0.0000191489,0.0026572396],"genre_scores_gemma":[0.012030705,0.97851026,0.0023102816,0.0032625915,0.0018920439,0.000035315126,0.00030822135,0.000038284412,0.0016122384],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985545,0.00035978772,0.00025682477,0.0002174781,0.0004659055,0.00014536224],"domain_scores_gemma":[0.9888021,0.006263848,0.0006899366,0.00024629323,0.003350514,0.0006473935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011834637,0.00075607246,0.001443791,0.0025530246,0.00047525662,0.0041098143,0.0015263204,0.0020866443,0.0040852074],"category_scores_gemma":[0.013819934,0.00025804035,0.0007124644,0.0026482807,0.00184254,0.0038965845,0.002091763,0.0028825388,0.0013743954],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013525535,0.00008527951,0.0008608212,0.00701635,0.00010148637,0.00019309265,0.0002051002,0.0010175544,0.0005534044,0.013228293,0.04396107,0.9326424],"study_design_scores_gemma":[0.000032770717,0.00019908913,0.003409392,0.0134704225,0.0001257739,0.00107955,0.00059269887,0.00057755446,0.00067770586,0.01808862,0.9616807,0.00006577859],"about_ca_topic_score_codex":0.0033724764,"about_ca_topic_score_gemma":0.007423708,"teacher_disagreement_score":0.011834637,"about_ca_system_score_codex":0.0015205438,"about_ca_system_score_gemma":0.0051213913,"threshold_uncertainty_score":0.062588274},"labels":[],"label_agreement":null},{"id":"W2902151647","doi":"10.1016/j.nicl.2018.101627","title":"Linked MRI signatures of the brain's acute and persistent response to concussion in female varsity rugby players","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Fowler Kennedy Sport Medicine Clinic; Robarts Clinical Trials; Western University","funders":"Schulich School of Medicine and Dentistry; Schulich School of Medicine and Dentistry, Western University; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Concussion; Diffusion MRI; White matter; Athletes; Medicine; Resting state fMRI; Physical medicine and rehabilitation; Psychology; Brain Structure and Function; Functional connectivity; Neuroscience; Neuroimaging; Physical therapy; Poison control; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.09107329699219512,"score_gpt":0.42450009547508755,"score_spread":0.3334267984828924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902151647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996834,0.00007277331,0.000058401492,0.000009047725,0.0000010327363,0.0000036007489,0.000075543714,0.0000016870996,0.000094532996],"genre_scores_gemma":[0.9993298,0.00008180213,0.00012235322,0.000008137848,0.0000062434037,0.000010918565,0.00020305954,0.000001656576,0.00023600513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999186,0.0000112634125,0.0000064347487,0.000027784796,0.000012255269,0.000023621975],"domain_scores_gemma":[0.99973994,0.00003657508,0.00012677029,0.000015254818,0.000038317634,0.000043070584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013626965,0.0002231877,0.00020109043,0.0009915266,0.00022347197,0.0003314192,0.0001947368,0.0003401351,0.000744842],"category_scores_gemma":[0.0007360108,0.00012387156,0.0001158367,0.0004854382,0.00027575798,0.00015312491,0.00034743108,0.00015811838,0.0001419684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049309514,0.00009200837,0.9553172,0.000052152565,0.000117027914,0.0011663993,0.0011611596,0.00025299517,0.030330194,0.00007613183,0.00018620567,0.010755412],"study_design_scores_gemma":[0.0000010967253,0.000039601204,0.9991841,0.0000023978341,0.00000820662,0.00032786827,0.00016124219,0.00006302711,0.00013564595,0.000010845971,0.00006411398,0.0000018563551],"about_ca_topic_score_codex":0.006643825,"about_ca_topic_score_gemma":0.013878787,"teacher_disagreement_score":0.006643825,"about_ca_system_score_codex":0.00019106259,"about_ca_system_score_gemma":0.00015568057,"threshold_uncertainty_score":0.013210297},"labels":[],"label_agreement":null},{"id":"W2902209191","doi":"10.1038/sdata.2018.270","title":"In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Atlas (anatomy); Segmentation; Computer science; Magnetic resonance imaging; Artificial intelligence; Thalamus; Cluster analysis; Diffusion MRI; Diffusion-Weighted Magnetic Resonance Imaging; Pattern recognition (psychology); Probabilistic logic; Brain atlas; Functional magnetic resonance imaging; Neuroimaging; Neuroscience; Biology; Anatomy; Medicine; Radiology","score_opus":0.05710554135325454,"score_gpt":0.3492608401373721,"score_spread":0.29215529878411756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902209191","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16164559,0.0005542604,0.8263133,0.00021025799,0.00006197836,0.00044379645,0.0052419677,0.0019558794,0.0035729748],"genre_scores_gemma":[0.5592004,0.00085439044,0.42958638,0.00006483818,0.000032805445,0.00051127747,0.0068228804,0.00049422705,0.0024327692],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9995813,0.00011701331,0.00003437581,0.00014315211,0.000096692296,0.000027601094],"domain_scores_gemma":[0.9995548,0.00014042282,0.00006893905,0.00011984204,0.000090823625,0.000025165647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063019834,0.00055521476,0.00046536786,0.0013418333,0.00041976615,0.0013230949,0.0008377954,0.0006902872,0.0029165319],"category_scores_gemma":[0.0017322775,0.00043029388,0.0007548281,0.0013891959,0.000542142,0.0005044677,0.00090004137,0.0004311857,0.0009817017],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010775963,0.00026222004,0.01664814,0.0010641628,0.00046856265,0.0011566452,0.0013386331,0.50336844,0.15598002,0.018712651,0.009465393,0.29045752],"study_design_scores_gemma":[0.00007666042,0.00030793334,0.03474864,0.00012218286,0.00019417731,0.0036456701,0.00036601396,0.85975164,0.0633345,0.01612948,0.021155871,0.00016730114],"about_ca_topic_score_codex":0.0071334075,"about_ca_topic_score_gemma":0.012632737,"teacher_disagreement_score":0.0071334075,"about_ca_system_score_codex":0.00079986145,"about_ca_system_score_gemma":0.0013196077,"threshold_uncertainty_score":0.01418376},"labels":[],"label_agreement":null},{"id":"W2903146653","doi":"10.1101/480905","title":"A macaque connectome for large-scale network simulations in TheVirtualBrain","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; McGill University; Montreal Neurological Institute and Hospital; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Horizon 2020 Framework Programme; Canada First Research Excellence Fund; Berlin Institute of Health; Deutsche Forschungsgemeinschaft","keywords":"Connectome; Macaque; Human Connectome Project; Tractography; Computer science; Connectomics; Tracing; Resting state fMRI; Diffusion MRI; Neuroscience; Scale (ratio); Functional connectivity; Cartography; Psychology; Geography; Magnetic resonance imaging","score_opus":0.03937587564426802,"score_gpt":0.31196897709648386,"score_spread":0.2725931014522158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903146653","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7478308,0.00028849224,0.2345095,0.0016993323,0.0001074031,0.00014286864,0.0024544792,0.002912593,0.0100545],"genre_scores_gemma":[0.9106504,0.00017408404,0.08501141,0.00018288726,0.000029252918,0.00034841272,0.0014135237,0.0004610281,0.0017290221],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998971,0.00004487584,0.000003698287,0.000017828872,0.000023447592,0.000012980953],"domain_scores_gemma":[0.99945563,0.00031421156,0.000040627943,0.00006747779,0.00006909234,0.000052942763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005173136,0.00041214484,0.00035962724,0.0007665681,0.0005709798,0.00056932267,0.0011085928,0.00096709654,0.004072835],"category_scores_gemma":[0.0022812972,0.00033111032,0.0006787999,0.0004773169,0.0005607084,0.00045378742,0.0009751558,0.00064330414,0.00023138375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000625948,0.00005981274,0.0020430435,0.000069836206,0.000054890294,0.00022388714,0.00017427637,0.97235787,0.0036856327,0.01522996,0.0020772435,0.003960991],"study_design_scores_gemma":[0.0000120777295,0.000010032565,0.0004645918,0.0000058531327,0.000003951837,0.000021413465,0.000013850421,0.99382025,0.0003931255,0.0042753187,0.00097372266,0.00000585851],"about_ca_topic_score_codex":0.017216656,"about_ca_topic_score_gemma":0.016069878,"teacher_disagreement_score":0.017216656,"about_ca_system_score_codex":0.0008666835,"about_ca_system_score_gemma":0.00095345813,"threshold_uncertainty_score":0.034232855},"labels":[],"label_agreement":null},{"id":"W2903516807","doi":"10.1101/484543","title":"Tractography Reproducibility Challenge with Empirical Data (TraCED): The 2017 ISMRM Diffusion Study Group Challenge","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; China Scholarship Council; National Center for Research Resources; National Natural Science Foundation of China; National Institutes of Health; Vanderbilt University","keywords":"Reproducibility; Tractography; Diffusion MRI; Computer science; Outlier; Imaging phantom; Tracking (education); Ground truth; Diffusion; Artificial intelligence; Magnetic resonance imaging; Pattern recognition (psychology); Data mining; Nuclear medicine; Statistics; Mathematics; Psychology; Medicine; Physics; Radiology","score_opus":0.14012493138709564,"score_gpt":0.3588019647956082,"score_spread":0.21867703340851258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903516807","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29993886,0.025288854,0.46848327,0.1215053,0.015834525,0.004868371,0.03570223,0.008803592,0.019574968],"genre_scores_gemma":[0.5665223,0.0041312254,0.32660908,0.016500901,0.006827654,0.007960496,0.05362502,0.0076649794,0.01015839],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.88008237,0.05972382,0.014077843,0.015401996,0.028954122,0.0017597919],"domain_scores_gemma":[0.44857886,0.34863168,0.029975174,0.06141591,0.1002149,0.011183396],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.16560327,0.0014645186,0.0023798428,0.0030341202,0.0031102914,0.0067237946,0.004207982,0.004561032,0.0029503033],"category_scores_gemma":[0.3997363,0.0008412789,0.0022703132,0.002986118,0.004179534,0.004388791,0.0073843123,0.0034600776,0.002323628],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032565685,0.000895649,0.08002865,0.009147608,0.002589203,0.0016431432,0.0075370306,0.024134118,0.008565714,0.029069275,0.3603778,0.4727553],"study_design_scores_gemma":[0.0015359698,0.003271463,0.11912609,0.007762089,0.0013769415,0.009062084,0.0060340245,0.10706125,0.024768632,0.13016161,0.5887933,0.0010465821],"about_ca_topic_score_codex":0.0073444075,"about_ca_topic_score_gemma":0.0075609544,"teacher_disagreement_score":0.8343967,"about_ca_system_score_codex":0.0028230532,"about_ca_system_score_gemma":0.011438289,"threshold_uncertainty_score":0.87580425},"labels":[],"label_agreement":null},{"id":"W2903623499","doi":"10.1007/s13253-018-00344-0","title":"Modeling and Prediction of Multiple Correlated Functional Outcomes","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Cancer Institute; King Abdullah University of Science and Technology","keywords":"Copula (linguistics); Marginal distribution; Diffusion MRI; Skew; Multivariate statistics; Computer science; Mathematics; Algorithm; Statistics; Econometrics; Random variable","score_opus":0.060400101196526314,"score_gpt":0.2668792346862158,"score_spread":0.20647913348968952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903623499","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58661216,0.00082227663,0.40748918,0.002122298,0.0001372222,0.00007625179,0.0013168602,0.00040915018,0.0010145901],"genre_scores_gemma":[0.97975016,0.00030445063,0.016586995,0.00008094142,0.000091446665,0.00012147814,0.0006651977,0.0000322956,0.0023671384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986928,0.00055208016,0.000065566855,0.0004090588,0.00010869858,0.00017182654],"domain_scores_gemma":[0.98637646,0.0113504855,0.0011021377,0.00043999805,0.00040776492,0.00032310924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005556139,0.0013873568,0.0018400721,0.0013187195,0.00046733892,0.001965143,0.0026892372,0.0020584038,0.001833072],"category_scores_gemma":[0.013641173,0.0010484912,0.001579227,0.0012748652,0.0014064508,0.0013817193,0.0014572089,0.0024292935,0.00033831195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027571883,0.00021334711,0.034774877,0.00004513835,0.00031877487,0.00033771826,0.00010692295,0.93417066,0.0003079253,0.010785738,0.0007491882,0.017913956],"study_design_scores_gemma":[0.000011256417,0.000020779378,0.0016885167,0.0000046551454,0.000021592983,0.000024799887,0.000008878289,0.99219817,0.00006213572,0.0058955676,0.00005679198,0.000006873367],"about_ca_topic_score_codex":0.021705598,"about_ca_topic_score_gemma":0.021502612,"teacher_disagreement_score":0.021705598,"about_ca_system_score_codex":0.0011392887,"about_ca_system_score_gemma":0.001661935,"threshold_uncertainty_score":0.04315853},"labels":[],"label_agreement":null},{"id":"W2904087114","doi":"10.1016/j.nicl.2018.101642","title":"Spatial correlations exploitation based on nonlocal voxel-wise GWAS for biomarker detection of AD","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Science and Technology Planning Project of Guangdong Province; Canadian Institutes of Health Research; University of California, San Diego; GE Healthcare; National Institutes of Health; Genentech; National Natural Science Foundation of China; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Takeda Pharmaceutical Company; Eli Lilly and Company; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Johnson and Johnson Pharmaceutical Research and Development; Merck; Alzheimer's Drug Discovery Foundation; Eisai; National Institute on Aging; Fujirebio Europe; Alzheimer's Association","keywords":"Voxel; Computer science; Weighting; Artificial intelligence; Pattern recognition (psychology); Data set; Genome-wide association study; Biology; Medicine; Single-nucleotide polymorphism; Genetics","score_opus":0.1840363593501134,"score_gpt":0.451933414664985,"score_spread":0.2678970553148716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904087114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05710094,0.0007251197,0.9406987,0.0001467333,0.000040403258,0.00004763374,0.00011470216,0.00052229164,0.00060352124],"genre_scores_gemma":[0.54794246,0.0006983936,0.44788128,0.00020208056,0.00008346276,0.00016080949,0.0005429717,0.00014585775,0.0023427173],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99932563,0.00024677656,0.000037841666,0.00017014603,0.00015315576,0.00006634292],"domain_scores_gemma":[0.9983909,0.0008436058,0.00018821361,0.00019132874,0.0003116535,0.00007430498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019401938,0.00066037953,0.0007729671,0.0012644664,0.0003762085,0.000590765,0.0009506471,0.0006550527,0.0009534232],"category_scores_gemma":[0.005262315,0.0003451451,0.0011143734,0.0013856633,0.00053669186,0.00095165847,0.0010282559,0.0005694184,0.00025825057],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007419964,0.00020606244,0.047262855,0.00043898565,0.00076345884,0.0011636822,0.00044287866,0.42729345,0.05565536,0.023731228,0.003208221,0.4390919],"study_design_scores_gemma":[0.000041732008,0.00008957034,0.008430029,0.000017686427,0.00013456967,0.00034675552,0.000049147708,0.97302747,0.0066385176,0.009465586,0.0017219292,0.000036990466],"about_ca_topic_score_codex":0.0044041756,"about_ca_topic_score_gemma":0.008784484,"teacher_disagreement_score":0.0044041756,"about_ca_system_score_codex":0.00031008472,"about_ca_system_score_gemma":0.0011126031,"threshold_uncertainty_score":0.01026082},"labels":[],"label_agreement":null},{"id":"W2904338322","doi":"10.1038/s41386-018-0298-z","title":"Brain structure, cognition, and brain age in schizophrenia, bipolar disorder, and healthy controls","year":2018,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":176,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health; Western University","funders":"","keywords":"Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Bipolar disorder; Cognition; Psychosis; Age of onset; Psychiatry; Brain aging; Clinical psychology; Neuroscience; Audiology; Magnetic resonance imaging; Diffusion MRI; Medicine; Internal medicine","score_opus":0.028203336023498834,"score_gpt":0.37257286489913416,"score_spread":0.3443695288756353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904338322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99971706,0.00007856864,0.00001932134,0.0000095623855,0.000002873058,0.000002077325,0.00006168335,0.0000013494086,0.000107449916],"genre_scores_gemma":[0.999652,0.00004964736,0.000028429171,0.000008724179,0.0000045173683,0.0000030283811,0.000110898465,0.0000010313929,0.00014170527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988806,0.000018711664,0.000011262145,0.000033594286,0.000017777233,0.00003067874],"domain_scores_gemma":[0.99979013,0.000038065256,0.00006822944,0.000019069863,0.000017438782,0.00006722118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026080984,0.00047348655,0.00038377315,0.0010786519,0.000521824,0.00046865767,0.00020729286,0.0004383921,0.0016239393],"category_scores_gemma":[0.0008973693,0.0002483563,0.0002240995,0.00038177366,0.00049937743,0.00032595996,0.00044151087,0.00029042433,0.00013495544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0069241915,0.00044695902,0.9718328,0.000035067977,0.00025296715,0.0009973284,0.0009397642,0.00015632786,0.011474458,0.00022873541,0.00025061105,0.0064607966],"study_design_scores_gemma":[0.000032532396,0.00021214718,0.9988494,0.0000021941876,0.000033102773,0.0002745928,0.00026791406,0.00008817436,0.00008987812,0.00009702733,0.000049969494,0.00000306255],"about_ca_topic_score_codex":0.01670779,"about_ca_topic_score_gemma":0.014620044,"teacher_disagreement_score":0.01670779,"about_ca_system_score_codex":0.00049976056,"about_ca_system_score_gemma":0.00019077952,"threshold_uncertainty_score":0.033221066},"labels":[],"label_agreement":null},{"id":"W2904572182","doi":"10.1101/497669","title":"White matter microstructure in women with acute and remitted anorexia nervosa: an exploratory neuroimaging study","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Psychology; External capsule; Anorexia nervosa; Neuroimaging; Grey matter; Corona radiata (embryology); Psychiatry; Neuroscience; Internal medicine; Medicine; Eating disorders; Magnetic resonance imaging; Radiology","score_opus":0.020924928740851025,"score_gpt":0.2718497284903547,"score_spread":0.2509247997495037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904572182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99964917,0.0000833307,0.000027684406,0.000013121873,0.0000010770801,0.000015927546,0.00006062871,7.527949e-7,0.00014840194],"genre_scores_gemma":[0.9994991,0.000075002354,0.00012579556,0.00002542147,0.000005464487,0.00002036124,0.00009531892,0.0000011613766,0.00015245102],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989116,0.000025201836,0.000008968373,0.00003674652,0.000016235024,0.000021681233],"domain_scores_gemma":[0.9997929,0.000032800937,0.00008120788,0.000022730168,0.000022840315,0.000047517624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027842913,0.00035634043,0.00031374744,0.00049393164,0.00052115944,0.0003193707,0.00021950358,0.0003711389,0.0007957511],"category_scores_gemma":[0.00091505167,0.00022843761,0.00020464539,0.00037207434,0.000327818,0.0002490292,0.0004168011,0.00024326719,0.00016791336],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015562369,0.0003723089,0.97640955,0.000054678494,0.00007810842,0.0032861459,0.0030179808,0.000048638645,0.009555252,0.00006876689,0.0001222119,0.005430095],"study_design_scores_gemma":[0.0000138069545,0.0005553376,0.9965215,0.000005157846,0.000019220992,0.0015664053,0.00093860435,0.000041123752,0.00012110679,0.000027829388,0.00018610439,0.000003830325],"about_ca_topic_score_codex":0.0031087645,"about_ca_topic_score_gemma":0.0045521837,"teacher_disagreement_score":0.0031087645,"about_ca_system_score_codex":0.00025475395,"about_ca_system_score_gemma":0.0002061019,"threshold_uncertainty_score":0.0061813593},"labels":[],"label_agreement":null},{"id":"W2905156767","doi":"10.1503/jpn.170221","title":"Psychoradiologic abnormalities of white matter in patients with bipolar disorder: diffusion tensor imaging studies using tract-based spatial statistics","year":2018,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Diffusion MRI; White matter; Bipolar disorder; Fractional anisotropy; Cardiology; Medicine; Magnetic resonance imaging; Audiology; Psychology; Internal medicine; Pathology; Radiology; Lithium (medication)","score_opus":0.061533307337877895,"score_gpt":0.378008227620823,"score_spread":0.3164749202829451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905156767","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16584669,0.8261291,0.0036993965,0.000987893,0.00016630019,0.00013908066,0.0018929262,0.000036378126,0.0011022713],"genre_scores_gemma":[0.9003652,0.09364687,0.0039153737,0.00046905375,0.00021946065,0.00016340519,0.001046055,0.000030947213,0.00014358513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99520594,0.002097428,0.0011469171,0.0009153854,0.00050182454,0.00013253493],"domain_scores_gemma":[0.981931,0.01049469,0.005376572,0.0011870519,0.0008640241,0.0001466951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010542388,0.00095020747,0.0023144048,0.004719861,0.0004621582,0.0018422331,0.00073015224,0.0006140355,0.0013673524],"category_scores_gemma":[0.017905626,0.00061661,0.0083849,0.0051317005,0.00076184474,0.00082822784,0.0007510773,0.0007347157,0.00010247794],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026271848,0.000057335565,0.444921,0.05666133,0.43207404,0.0004144689,0.0004890824,0.0020702349,0.0024490075,0.00095664314,0.0016763164,0.055603318],"study_design_scores_gemma":[0.0006214723,0.0005028365,0.4680377,0.015169664,0.5021238,0.0011646408,0.00039630194,0.0017937183,0.0011642887,0.0038045715,0.0051229093,0.00009819569],"about_ca_topic_score_codex":0.0052777077,"about_ca_topic_score_gemma":0.011491535,"teacher_disagreement_score":0.010542388,"about_ca_system_score_codex":0.0008452732,"about_ca_system_score_gemma":0.0010946962,"threshold_uncertainty_score":0.055754185},"labels":[],"label_agreement":null},{"id":"W2905311230","doi":"10.1007/s11682-018-0012-0","title":"Dopamine receptor density and white mater integrity: 18F-fallypride positron emission tomography and diffusion tensor imaging study in healthy and schizophrenia subjects","year":2018,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Neuroscience; Corpus callosum; Internal capsule; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.024148494034705165,"score_gpt":0.32844904230493227,"score_spread":0.3043005482702271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905311230","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997576,0.00004657105,0.000019192357,0.000009459417,0.0000010233185,0.0000028684135,0.00005314479,9.2760695e-7,0.0001091811],"genre_scores_gemma":[0.999658,0.000026130607,0.00002886605,0.000009459998,0.000001910277,0.0000030246124,0.00007437971,0.0000010821027,0.0001972232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990296,0.000015210729,0.00001272648,0.000027387956,0.000015335527,0.000026282585],"domain_scores_gemma":[0.9997553,0.00003587183,0.00006688976,0.000020868534,0.000030559742,0.000090579895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027838294,0.0003713532,0.00033681808,0.00075439597,0.00055877835,0.00047441633,0.0002632082,0.00048740464,0.0017591404],"category_scores_gemma":[0.0006657508,0.0003242216,0.00022862632,0.00026887655,0.0005182775,0.00039152673,0.00034681853,0.0003505893,0.0002547962],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003568154,0.0005400002,0.9704607,0.000029608778,0.0002356433,0.0013875292,0.0014273303,0.000114593815,0.018943232,0.0001264573,0.00013325202,0.0030334846],"study_design_scores_gemma":[0.000023920027,0.00025463334,0.99809486,0.0000017432728,0.00003294306,0.0005935514,0.00048328546,0.00011632387,0.00030545305,0.000039122904,0.000049567658,0.0000045287097],"about_ca_topic_score_codex":0.014063753,"about_ca_topic_score_gemma":0.012627285,"teacher_disagreement_score":0.014063753,"about_ca_system_score_codex":0.00045617323,"about_ca_system_score_gemma":0.00025848852,"threshold_uncertainty_score":0.027963758},"labels":[],"label_agreement":null},{"id":"W2907533374","doi":"10.1016/j.neubiorev.2018.12.030","title":"Variation in fourteen brain structure volumes in schizophrenia: A comprehensive meta-analysis of 246 studies","year":2019,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":153,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fogarty International Center; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Planum temporale; Caudate nucleus; Psychology; Brain size; Neuroscience; Brain morphometry; Lateral ventricles; Gray (unit); Magnetic resonance imaging; Medicine; Nuclear medicine; Radiology","score_opus":0.6347428318919834,"score_gpt":0.5433849932673688,"score_spread":0.09135783862461466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907533374","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027848637,0.9692495,0.0012349293,0.00020123708,0.00011660956,0.00004855478,0.0010458448,0.00004843629,0.00020631796],"genre_scores_gemma":[0.55937856,0.4319555,0.0046726544,0.0007407317,0.00021678518,0.00015242316,0.0023143077,0.00010395089,0.0004650606],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99641824,0.0012920045,0.0009185445,0.0008265359,0.00037231488,0.0001724285],"domain_scores_gemma":[0.99496377,0.0034199283,0.00082458125,0.00036016657,0.0003242249,0.000107300664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005630425,0.0021643704,0.0072139674,0.0030334438,0.00048719838,0.0019917616,0.0013699307,0.0013482331,0.0023200677],"category_scores_gemma":[0.009272834,0.0010775124,0.017538974,0.004773484,0.0005607014,0.0010431132,0.0015061802,0.0012074232,0.0002532701],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026710185,0.00003852006,0.036547653,0.054179985,0.87270474,0.00033608158,0.00017750566,0.00087355514,0.001445125,0.000244721,0.0012223409,0.029558796],"study_design_scores_gemma":[0.00034414016,0.0001753699,0.042264365,0.00343319,0.9493696,0.00027015322,0.000110619396,0.00020443367,0.0002455107,0.00053770596,0.0029940691,0.000050885963],"about_ca_topic_score_codex":0.004813504,"about_ca_topic_score_gemma":0.011983864,"teacher_disagreement_score":0.0072139674,"about_ca_system_score_codex":0.00078806916,"about_ca_system_score_gemma":0.001342812,"threshold_uncertainty_score":0.029776871},"labels":[],"label_agreement":null},{"id":"W2907839286","doi":"","title":"In Vivo Assessment of Spinal Cord Integrity Using Magnetic Resonance Diffusion Tensor Imaging","year":2008,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Nuclear magnetic resonance; Spinal cord; Medicine; Neuroscience; Physics; Psychology; Radiology","score_opus":0.08826950733957728,"score_gpt":0.3983357910574297,"score_spread":0.31006628371785244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907839286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8994168,0.0023017281,0.09278938,0.00046699384,0.000085663974,0.00014380876,0.0006351279,0.00028257293,0.003877854],"genre_scores_gemma":[0.96407163,0.0021785584,0.030448016,0.00012535548,0.000073761876,0.00007759648,0.00037673322,0.00006910366,0.002579256],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998172,0.000065485794,0.00001783542,0.000038160717,0.000045043154,0.000016202705],"domain_scores_gemma":[0.9996075,0.00010601423,0.00008552566,0.0000631977,0.00009744541,0.000040270173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006440025,0.00041707576,0.00028374264,0.00048699754,0.00034116377,0.0008158685,0.00023676976,0.00068116985,0.0016196489],"category_scores_gemma":[0.001388329,0.00028242046,0.00014547005,0.00024541534,0.0004166627,0.0009365214,0.00030134147,0.00053304667,0.00035922704],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086430775,0.000307412,0.008931443,0.00021213015,0.000107006854,0.00025818785,0.00018267623,0.0016127765,0.9532959,0.00052679516,0.0005310061,0.033170354],"study_design_scores_gemma":[0.00014448537,0.004538611,0.11193597,0.00009116664,0.0004959595,0.007768318,0.00051511,0.040542495,0.8243294,0.002499589,0.0070239557,0.000115024406],"about_ca_topic_score_codex":0.001068203,"about_ca_topic_score_gemma":0.0015520193,"teacher_disagreement_score":0.0016196489,"about_ca_system_score_codex":0.00012888797,"about_ca_system_score_gemma":0.00036719342,"threshold_uncertainty_score":0.005418241},"labels":[],"label_agreement":null},{"id":"W2909504075","doi":"10.1017/9781316257951.008","title":"Imaging White Matter Pathology in Epilepsy","year":2019,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Epilepsy; Pathology; Medicine; Neuroscience; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.03311763258857997,"score_gpt":0.25720206037748483,"score_spread":0.22408442778890486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909504075","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00070030947,0.6405614,0.010209389,0.008322685,0.006903296,0.000054224187,0.00030192698,0.00035328642,0.3325935],"genre_scores_gemma":[0.00573535,0.41233853,0.010918848,0.003707768,0.0067870906,0.00008348367,0.0004056179,0.00024391177,0.55977947],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998442,0.000025096251,0.00001555469,0.00002144587,0.000081346065,0.0000123683385],"domain_scores_gemma":[0.99977523,0.000119398646,0.000011711132,0.000020174804,0.00005205908,0.000021470254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049830734,0.00095573417,0.0007671344,0.0025500536,0.0002880613,0.0016438335,0.0007035841,0.0015868442,0.03201122],"category_scores_gemma":[0.0008142886,0.00048743503,0.0003131772,0.0016162104,0.00086771103,0.00230386,0.0010363533,0.0019027783,0.018200783],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025081748,0.000021644988,0.00007832537,0.0006656348,0.000011150421,0.00030358197,0.00009142189,0.00025420185,0.0018677965,0.019900657,0.35427827,0.6225022],"study_design_scores_gemma":[0.000007895994,0.000022011165,0.00063535536,0.000722705,0.000010643996,0.0021707,0.000049474893,0.00018043397,0.0005961114,0.023195436,0.9723943,0.00001496874],"about_ca_topic_score_codex":0.0020182896,"about_ca_topic_score_gemma":0.007637752,"teacher_disagreement_score":0.03201122,"about_ca_system_score_codex":0.00067224936,"about_ca_system_score_gemma":0.00074462587,"threshold_uncertainty_score":0.10708815},"labels":[],"label_agreement":null},{"id":"W2909531344","doi":"10.1101/524785","title":"Global and regional white matter development in early childhood","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Foundation; Children's Hospital Foundation","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Brain development; Early childhood; Developmental psychology; Tractography; Psychology; Pediatrics; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.023823727102381568,"score_gpt":0.2624490381423651,"score_spread":0.23862531103998352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909531344","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971969,0.0005951985,0.0003405367,0.000015011489,0.0000019167815,0.0000023155972,0.0014881387,0.00001334476,0.00034658815],"genre_scores_gemma":[0.99673766,0.0005609603,0.0010051276,0.000007134494,0.0000022726315,0.0000064936335,0.0014035482,0.000013084816,0.00026369325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997863,0.00002996542,0.000018083692,0.000071833005,0.000043591528,0.00005021826],"domain_scores_gemma":[0.9994148,0.000106087835,0.00028729896,0.000048623293,0.000087763816,0.00005542014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038889662,0.0002606142,0.0002270871,0.0011224562,0.000206938,0.0004965573,0.00012922467,0.00018661575,0.0012739877],"category_scores_gemma":[0.0010805092,0.0001652642,0.00021341332,0.0011169816,0.0002371708,0.00034421694,0.00031794465,0.00015939176,0.0002411153],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019680677,0.000012019805,0.9730971,0.00009903599,0.000142252,0.00022642837,0.00038432959,0.00048180914,0.010130676,0.00012646908,0.0003432873,0.01475972],"study_design_scores_gemma":[4.6526134e-7,0.000010918731,0.9990421,0.0000060187967,0.000007725046,0.00013705957,0.00007752675,0.000046436286,0.0004791015,0.000023739532,0.00016765494,0.000001197737],"about_ca_topic_score_codex":0.011218258,"about_ca_topic_score_gemma":0.019813037,"teacher_disagreement_score":0.011218258,"about_ca_system_score_codex":0.00024442686,"about_ca_system_score_gemma":0.00027492136,"threshold_uncertainty_score":0.022305906},"labels":[],"label_agreement":null},{"id":"W2909661867","doi":"10.1016/j.dadm.2018.10.008","title":"White matter and its relationship with cognition in subjective cognitive decline","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Merck; Alzheimer's Drug Discovery Foundation; AbbVie; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"White matter; Corpus callosum; Diffusion MRI; Cognition; Psychology; Neuroimaging; Neuropsychology; Cognitive decline; Neuroscience; Disease; Medicine; Dementia; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.07467865023449355,"score_gpt":0.3896330849859277,"score_spread":0.31495443475143414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909661867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984377,0.0007765645,0.00011515302,0.000046744084,0.000004117351,0.0000048899324,0.00013858429,0.0000033729257,0.000472704],"genre_scores_gemma":[0.9995241,0.00013547296,0.000112661604,0.00001150406,0.000008361946,0.0000021777937,0.00012348713,9.288313e-7,0.000081303355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998621,0.000030887197,0.000023517177,0.000028210576,0.000037637623,0.00001766213],"domain_scores_gemma":[0.9980428,0.0002496662,0.0012448763,0.00009060023,0.00021714682,0.00015490304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006556698,0.00031402335,0.0001944038,0.001404088,0.00022044108,0.0005788344,0.00020699207,0.0002516571,0.0011552403],"category_scores_gemma":[0.0032936886,0.00009694108,0.00014677965,0.000676164,0.00037939433,0.0003903437,0.00040714885,0.00024427284,0.00013065252],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019807417,0.000051763163,0.9918583,0.000034431618,0.00009562615,0.00016326904,0.00017006414,0.00011435526,0.0008228951,0.000060537583,0.00008902947,0.0063415896],"study_design_scores_gemma":[0.000002065876,0.000049894326,0.99915373,0.000009708831,0.000017116812,0.00029147006,0.000052512583,0.000111813475,0.00013984606,0.00009028355,0.000079668505,0.0000018372006],"about_ca_topic_score_codex":0.0026888356,"about_ca_topic_score_gemma":0.0038789692,"teacher_disagreement_score":0.0026888356,"about_ca_system_score_codex":0.00018143644,"about_ca_system_score_gemma":0.00014365492,"threshold_uncertainty_score":0.005346358},"labels":[],"label_agreement":null},{"id":"W2910571127","doi":"10.3389/fnagi.2018.00436","title":"Relationship Between DTI Metrics and Cognitive Function in Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":151,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; University of Manitoba; University of Calgary; University of Victoria","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Alberta Innovates; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; University of California, San Diego; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Psychology; Executive dysfunction; Episodic memory; Neuropsychology; Neuroimaging; Cognition; Memory impairment; Neuroscience; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.10609777979272579,"score_gpt":0.3567329223139554,"score_spread":0.25063514252122965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910571127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98834383,0.0045211087,0.0020647324,0.00016496422,0.000025161993,0.00003232519,0.0025167875,0.00006052027,0.0022704701],"genre_scores_gemma":[0.99652785,0.00046481713,0.0016758058,0.00001981878,0.000018742583,0.000017327726,0.0010220205,0.000008807801,0.00024471935],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99965525,0.000087487155,0.00006852527,0.000078657424,0.00008617564,0.000023968736],"domain_scores_gemma":[0.997661,0.00048350097,0.0012152501,0.00017205512,0.0003170402,0.00015114984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012374846,0.00044305902,0.00025923783,0.0016634405,0.00026457311,0.0005312686,0.0002599199,0.00027999014,0.0011206741],"category_scores_gemma":[0.004527462,0.0001356665,0.00021203894,0.0014644852,0.00024765232,0.00037218202,0.00038669197,0.00030566932,0.00022619571],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031697974,0.000025536718,0.9850699,0.00007018142,0.0003226785,0.000090274036,0.000076670345,0.00057784695,0.0013376859,0.00015075498,0.0004715676,0.011489798],"study_design_scores_gemma":[0.00000492806,0.000078175464,0.99644417,0.000015899843,0.00005559051,0.00061705644,0.000030570307,0.0012785464,0.00039823772,0.00045274463,0.00061619,0.000008045899],"about_ca_topic_score_codex":0.0033731034,"about_ca_topic_score_gemma":0.0040249834,"teacher_disagreement_score":0.0033731034,"about_ca_system_score_codex":0.00047631402,"about_ca_system_score_gemma":0.00035303802,"threshold_uncertainty_score":0.006706953},"labels":[],"label_agreement":null},{"id":"W2910624401","doi":"10.3389/fnins.2018.01055","title":"Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Réseau québécois de recherche sur le vieillissement; Canadian Institutes of Health Research; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Tractography; Diffusion MRI; Arcuate fasciculus; Fractional anisotropy; White matter; Inferior longitudinal fasciculus; Reliability (semiconductor); Computer science; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.02681081110324444,"score_gpt":0.30219033126579137,"score_spread":0.2753795201625469,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910624401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95863307,0.00034735777,0.038771313,0.000045511286,0.00007106489,0.00021896708,0.0004018903,0.00023566977,0.001275123],"genre_scores_gemma":[0.98142576,0.000105067105,0.016703928,0.000028989809,0.000025312722,0.00023333909,0.0006008598,0.00013019743,0.000746626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9956672,0.0015254407,0.0004601056,0.0014367143,0.00076088187,0.00014958711],"domain_scores_gemma":[0.97872365,0.009320351,0.0024023568,0.004268861,0.004925261,0.0003594736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0083062835,0.00063475466,0.0005015394,0.00089320645,0.00047722954,0.00078019797,0.00052702083,0.0006512565,0.0009523823],"category_scores_gemma":[0.029747862,0.00036399654,0.00063570845,0.00042437844,0.0010806317,0.0007994408,0.00090583914,0.0006819961,0.0006247379],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051203226,0.0008088376,0.555122,0.00067151146,0.0031683268,0.00040231063,0.008270753,0.010053819,0.25354752,0.0010900529,0.0018744865,0.15986997],"study_design_scores_gemma":[0.000121864585,0.0016050675,0.9478181,0.000045022312,0.00039548686,0.0006173438,0.00054506393,0.016563559,0.028792806,0.001419128,0.0019543797,0.00012219604],"about_ca_topic_score_codex":0.001402143,"about_ca_topic_score_gemma":0.0032808306,"teacher_disagreement_score":0.0083062835,"about_ca_system_score_codex":0.00024158633,"about_ca_system_score_gemma":0.00033911667,"threshold_uncertainty_score":0.043928325},"labels":[],"label_agreement":null},{"id":"W2911682836","doi":"10.1093/brain/awz021","title":"A probabilistic map of negative motor areas of the upper limb and face: a brain stimulation study","year":2019,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; National Institutes of Health","keywords":"Physical medicine and rehabilitation; Stimulation; Neuroscience; Upper limb; Psychology; Face (sociological concept); Medicine","score_opus":0.03587705274377593,"score_gpt":0.3381441764944299,"score_spread":0.30226712375065395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911682836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98404896,0.0002280351,0.013777251,0.000042421038,0.0000026384232,0.000044635803,0.00032263252,0.00006820982,0.0014653162],"genre_scores_gemma":[0.99684554,0.00006542124,0.0026180118,0.000005708752,0.000004938242,0.000019498671,0.00020068866,0.0000075330377,0.00023258256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998796,0.000026346492,0.0000056079666,0.000031139938,0.000034575478,0.000022726113],"domain_scores_gemma":[0.99976593,0.00010639031,0.000049872455,0.000024349976,0.000032036663,0.000021481525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020173281,0.00014100499,0.00016931322,0.0009209662,0.00017177354,0.0003005725,0.00014159513,0.00016280315,0.0014359129],"category_scores_gemma":[0.0007269702,0.00009312213,0.00030169074,0.00058319763,0.00029823044,0.000205612,0.00029351158,0.00014158257,0.00022925912],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00353638,0.0001869279,0.4289239,0.0006430346,0.00054822274,0.004089761,0.0021346442,0.038374297,0.2767925,0.004550699,0.0017914316,0.23842816],"study_design_scores_gemma":[0.000036056972,0.00029012252,0.93853396,0.000016367547,0.000088879104,0.0052350904,0.00037212807,0.039551754,0.011187786,0.0028098973,0.0018277864,0.00005020075],"about_ca_topic_score_codex":0.0032987392,"about_ca_topic_score_gemma":0.0027975899,"teacher_disagreement_score":0.0032987392,"about_ca_system_score_codex":0.00024150066,"about_ca_system_score_gemma":0.00025740493,"threshold_uncertainty_score":0.006559074},"labels":[],"label_agreement":null},{"id":"W2911755615","doi":"10.1016/j.psychres.2019.02.028","title":"Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI","year":2019,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Research Council; National Institute for Health and Care Research; Maudsley Charity; Guy's and St Thomas' Charity; Wellcome Trust; South London and Maudsley NHS Foundation Trust; King's College London; King's University College; Health Research","keywords":"Schizophrenia (object-oriented programming); Cortex (anatomy); Neuroscience; Psychology; Temporal cortex; Temporal lobe; Neuroimaging; Posterior cingulate; Cingulate cortex; Anterior cingulate cortex; Psychosis; Gyrus; Occipital lobe; Cerebral cortex; Precentral gyrus; Medicine; Magnetic resonance imaging; Psychiatry; Cognition; Central nervous system; Epilepsy; Radiology","score_opus":0.06503372729228592,"score_gpt":0.4089443704777311,"score_spread":0.3439106431854452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911755615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942589,0.00026603477,0.0044399495,0.00010982636,0.0000080845175,0.00002014457,0.00017692203,0.000041295913,0.0006788307],"genre_scores_gemma":[0.99834037,0.00016868139,0.0011126614,0.00001543065,0.0000047846297,0.0000066772072,0.000084743544,0.000013251354,0.00025346165],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999269,0.00002986726,0.000006017811,0.000008429029,0.000014969998,0.000013742353],"domain_scores_gemma":[0.999793,0.000079054524,0.000055326494,0.000031410407,0.000024391076,0.000016778504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035706203,0.0003117866,0.00019461356,0.0005853767,0.00017921344,0.0003864419,0.00019371917,0.00033473238,0.0010730405],"category_scores_gemma":[0.0010399608,0.00023512596,0.0001646737,0.00022671327,0.00034011548,0.00026419703,0.00017049098,0.00030354934,0.00014433857],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048083887,0.0002950785,0.061310377,0.00021323221,0.00029025562,0.00237536,0.00071045454,0.0075448733,0.8558473,0.00077151443,0.00093161064,0.06490146],"study_design_scores_gemma":[0.00021664107,0.0018784779,0.83382684,0.00006156097,0.0003534864,0.010225304,0.0012121415,0.049856517,0.09701531,0.0036177645,0.001664844,0.00007104407],"about_ca_topic_score_codex":0.0034633446,"about_ca_topic_score_gemma":0.006028794,"teacher_disagreement_score":0.0034633446,"about_ca_system_score_codex":0.00019942998,"about_ca_system_score_gemma":0.00020407213,"threshold_uncertainty_score":0.0068864226},"labels":[],"label_agreement":null},{"id":"W2911790418","doi":"10.1161/str.50.suppl_1.wp454","title":"Abstract WP454: Multi-modal Neuroimaging Biomarkers of Aneurysmal Subarachnoid Hemorrhage","year":2019,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital","funders":"","keywords":"Medicine; Neuroimaging; Diffusion MRI; Corona radiata (embryology); White matter; Fractional anisotropy; Subarachnoid hemorrhage; Stroke (engine); Magnetic resonance imaging; Neuroscience; Cerebral amyloid angiopathy; Cardiology; Radiology; Pathology; Internal medicine; Psychology; Dementia; Psychiatry; Disease","score_opus":0.039012557082769676,"score_gpt":0.323920451514626,"score_spread":0.2849078944318563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911790418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99870133,0.00031003993,0.00024693468,0.000036265264,0.000004915146,0.000012446656,0.0002236674,0.000009814503,0.00045460838],"genre_scores_gemma":[0.9989305,0.00010964085,0.00044330794,0.00001997914,0.000010134547,0.000010610355,0.00026117332,0.0000017178663,0.00021289852],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991643,0.000022136275,0.000012562822,0.000018279181,0.000019368515,0.000011326478],"domain_scores_gemma":[0.9997371,0.000037991103,0.00012399803,0.000023557579,0.000037802445,0.000039594564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027342432,0.00030259753,0.0002534498,0.0007298197,0.00028339983,0.0004008265,0.00019030225,0.0003720857,0.0012122673],"category_scores_gemma":[0.00074424484,0.00009889834,0.000112564536,0.00032412919,0.00017121038,0.0002476828,0.0003404652,0.0001875367,0.00018945077],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011922814,0.0002610254,0.91787195,0.000110092,0.0003322218,0.00086218223,0.00017609891,0.00028578658,0.049827013,0.00009994295,0.00061048724,0.028371088],"study_design_scores_gemma":[0.000007007131,0.00017442428,0.9962568,0.0000060855787,0.00003829986,0.00074240373,0.000055391363,0.00028635454,0.0021674656,0.0001006542,0.00016116095,0.000003973679],"about_ca_topic_score_codex":0.00069229887,"about_ca_topic_score_gemma":0.00081657193,"teacher_disagreement_score":0.0012122673,"about_ca_system_score_codex":0.00010272038,"about_ca_system_score_gemma":0.00010085393,"threshold_uncertainty_score":0.0040554404},"labels":[],"label_agreement":null},{"id":"W2911926566","doi":"10.1016/j.mri.2019.04.013","title":"Tractography and machine learning: Current state and open challenges","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Robustness (evolution); Tractography; Machine learning; False positive paradox; Prior probability; Bayesian probability; Diffusion MRI","score_opus":0.06153289244575866,"score_gpt":0.34137806627959294,"score_spread":0.2798451738338343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911926566","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035605049,0.8737672,0.04303421,0.07346676,0.0015958551,0.00005846535,0.00022724042,0.0002126343,0.0040770806],"genre_scores_gemma":[0.054465584,0.85910034,0.0601847,0.008043882,0.015376137,0.0002122861,0.00048585175,0.00015852891,0.00197269],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9932059,0.0032568495,0.00070210773,0.0012033754,0.0012947626,0.00033698906],"domain_scores_gemma":[0.8242076,0.15038562,0.0044343877,0.004799174,0.013366171,0.002807077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03898402,0.0013283209,0.0050502997,0.0037350047,0.0013245342,0.013292556,0.0052323597,0.007528246,0.009291951],"category_scores_gemma":[0.05107504,0.0010974209,0.0013017718,0.0046872874,0.013129999,0.022643939,0.0051389867,0.007389305,0.003230775],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005697773,0.00035121478,0.006950221,0.0062495726,0.00038280716,0.00013156005,0.0005244971,0.0039667976,0.0008548012,0.0893177,0.027061064,0.86363995],"study_design_scores_gemma":[0.00015752592,0.0005429948,0.0057847295,0.01177913,0.00031062044,0.0008082054,0.0022892405,0.031031994,0.0013607345,0.65279585,0.29274118,0.00039776863],"about_ca_topic_score_codex":0.004712855,"about_ca_topic_score_gemma":0.006064339,"teacher_disagreement_score":0.03898402,"about_ca_system_score_codex":0.0027119943,"about_ca_system_score_gemma":0.008352799,"threshold_uncertainty_score":0.20616966},"labels":[],"label_agreement":null},{"id":"W2912265831","doi":"10.3389/fneur.2019.00081","title":"A Neuroimaging Marker Based on Diffusion Tensor Imaging and Cognitive Impairment Due to Cerebral White Matter Lesions","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; Ministry of Science and Technology of the People's Republic of China; Beijing Institute For Brain Disorders; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support; National Natural Science Foundation of China","keywords":"Hyperintensity; Montreal Cognitive Assessment; Diffusion MRI; Cognition; Magnetic resonance imaging; Neuropsychology; Neuroimaging; Medicine; Cardiology; White matter; Internal medicine; Psychology; Audiology; Cognitive impairment; Psychiatry; Radiology","score_opus":0.01172256914487974,"score_gpt":0.2741991326381511,"score_spread":0.26247656349327136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912265831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997607,0.00076740986,0.00025984534,0.000054063254,0.000009581268,0.000016482732,0.00019574224,0.000008604383,0.0010812435],"genre_scores_gemma":[0.9990552,0.00020133541,0.0002998693,0.000011112082,0.000020828598,0.000008428606,0.0002219904,0.0000016992941,0.00017948398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997646,0.00004496598,0.000042950804,0.00005790443,0.000059393653,0.00003020091],"domain_scores_gemma":[0.99857223,0.00015308963,0.00097093097,0.000052457504,0.00012436986,0.00012690293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004478622,0.0005266171,0.00032345435,0.0016416073,0.00030472165,0.0005808383,0.00027443373,0.0003509352,0.0016140307],"category_scores_gemma":[0.001686408,0.00014859358,0.00031335105,0.001086457,0.0003498636,0.00040789496,0.00036033904,0.00035990318,0.00020840584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004598518,0.00006734531,0.9911374,0.00005352166,0.000141835,0.0006506157,0.00009441213,0.00011981512,0.0023067244,0.000092042224,0.00014719757,0.004729191],"study_design_scores_gemma":[0.000006776739,0.00015320217,0.9963649,0.00001511594,0.00007049164,0.00212334,0.000057817477,0.00046172645,0.00039392596,0.00015275268,0.00019387912,0.0000061803444],"about_ca_topic_score_codex":0.0018412314,"about_ca_topic_score_gemma":0.0019513543,"teacher_disagreement_score":0.0018412314,"about_ca_system_score_codex":0.0003426833,"about_ca_system_score_gemma":0.00037992166,"threshold_uncertainty_score":0.0053994656},"labels":[],"label_agreement":null},{"id":"W2912348536","doi":"10.1101/541631","title":"Formalin Tissue Fixation Biases Myelin-Sensitive MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Vanderbilt University; University of British Columbia; Multiple Sclerosis Society; Icahn School of Medicine at Mount Sinai; National Institutes of Health","keywords":"Fixation (population genetics); Myelin; Chemistry; Nuclear magnetic resonance; Nuclear medicine; Medicine; Biochemistry; Internal medicine; Central nervous system; Physics","score_opus":0.046579405526018136,"score_gpt":0.30794883079322455,"score_spread":0.2613694252672064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912348536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96112865,0.00925034,0.025346428,0.00029990886,0.00019449725,0.00014108406,0.00028751494,0.00026869148,0.0030827762],"genre_scores_gemma":[0.9785196,0.0033435342,0.014370457,0.0003613063,0.00005515017,0.00014474163,0.00040596852,0.00017922501,0.0026199014],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99936956,0.00017234469,0.00006554449,0.0001492132,0.00013864329,0.00010470524],"domain_scores_gemma":[0.99892694,0.00034002902,0.00035105026,0.00012879842,0.00021013066,0.000042997075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013447604,0.0012347125,0.0003054884,0.00069662154,0.00034114215,0.0005897218,0.0004987224,0.00053342304,0.0018104214],"category_scores_gemma":[0.002305599,0.00063062046,0.00027461487,0.0002940076,0.0009518766,0.0007676624,0.0005937684,0.00046758156,0.0004486249],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020357073,0.000011183392,0.0013809126,0.00012992321,0.00001948416,0.00009766098,0.00004477484,0.00013381698,0.9952415,0.000093477414,0.000058794663,0.0025849198],"study_design_scores_gemma":[0.000021447193,0.0007234239,0.02173328,0.00006532069,0.000095164396,0.0008123794,0.000103456936,0.0012515873,0.9727821,0.00024251835,0.002142395,0.0000269313],"about_ca_topic_score_codex":0.0020365345,"about_ca_topic_score_gemma":0.0024224021,"teacher_disagreement_score":0.0020365345,"about_ca_system_score_codex":0.00067836983,"about_ca_system_score_gemma":0.00041034186,"threshold_uncertainty_score":0.0071118474},"labels":[],"label_agreement":null},{"id":"W2912379919","doi":"10.1109/bibm.2018.8621466","title":"Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Gait; Computer science; Artificial neural network; Artificial intelligence; Parkinsonism; Pattern recognition (psychology); Physical medicine and rehabilitation; Medicine","score_opus":0.05928719116410922,"score_gpt":0.3236009863481946,"score_spread":0.2643137951840854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912379919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98829705,0.0004011296,0.009926467,0.00011849817,0.000052972166,0.000030210012,0.0002885494,0.00008472067,0.00080038805],"genre_scores_gemma":[0.995824,0.00009411336,0.003493191,0.000021535767,0.000011283876,0.000013001195,0.00027936322,0.0000028993877,0.00026069506],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997309,0.00007475329,0.000044271655,0.000063837695,0.00004892842,0.000037283175],"domain_scores_gemma":[0.9994978,0.00024430858,0.000080638216,0.00002583243,0.00011118886,0.000040255465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006314676,0.00042318404,0.00038115706,0.0009876714,0.00012586042,0.00048584843,0.00021080386,0.00048101682,0.00071718247],"category_scores_gemma":[0.0020961552,0.000104714985,0.00029918732,0.0003737142,0.0001540775,0.00022467715,0.00026789654,0.00028681906,0.00019239912],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032402833,0.001048972,0.4132196,0.00021431492,0.0005047785,0.00076224876,0.00022773424,0.07234428,0.024815297,0.00041393607,0.001981867,0.48122668],"study_design_scores_gemma":[0.000043246848,0.00071877474,0.1836476,0.000052660904,0.00011939174,0.00038090543,0.00018732602,0.80853575,0.00537634,0.000601693,0.0003123713,0.000023835577],"about_ca_topic_score_codex":0.002462953,"about_ca_topic_score_gemma":0.0024527877,"teacher_disagreement_score":0.002462953,"about_ca_system_score_codex":0.00027114453,"about_ca_system_score_gemma":0.00019258121,"threshold_uncertainty_score":0.004897177},"labels":[],"label_agreement":null},{"id":"W2912545990","doi":"10.1016/j.bpj.2018.11.1270","title":"High Resolution Imaging and Histopathological Characterization of Myocardial Infarction","year":2019,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Centre for Phenogenomics; University of Toronto","funders":"","keywords":"Histopathology; Sirius Red; Infarction; Medicine; Fractional anisotropy; Myocardial infarction; Fibrosis; Diffusion MRI; Pathology; Magnetic resonance imaging; CD31; Ex vivo; Artery; Cardiology; Immunohistochemistry; In vivo; Radiology; Biology","score_opus":0.022545619925701647,"score_gpt":0.28875458375245733,"score_spread":0.2662089638267557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912545990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9796861,0.0060920417,0.0095818285,0.00021944854,0.000021244168,0.000067792294,0.00020450114,0.00006178636,0.0040652305],"genre_scores_gemma":[0.98995167,0.0020567344,0.005986432,0.000093318944,0.000056901772,0.000031071817,0.00020189481,0.000014403042,0.0016076292],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985623,0.000034435936,0.00001610302,0.00002209308,0.00003195177,0.000039134313],"domain_scores_gemma":[0.9997557,0.0000547686,0.000058899623,0.000039111208,0.000060238457,0.00003132948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069858215,0.0002193908,0.00017048854,0.0015042316,0.00019651327,0.000535403,0.00028944938,0.00056019664,0.0014634375],"category_scores_gemma":[0.0006827898,0.00029918703,0.00015245401,0.00045805852,0.00030980076,0.0005010737,0.0002671273,0.00040768523,0.00037494928],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025438294,0.0002756106,0.039300174,0.00027143804,0.000110579116,0.0038538163,0.00023207677,0.00042323166,0.9177419,0.0007943544,0.00029376024,0.03415922],"study_design_scores_gemma":[0.000113462855,0.0011561728,0.56028193,0.00012321329,0.00029262665,0.025717014,0.00070951023,0.0076982426,0.39766526,0.0014729728,0.0047228634,0.00004678103],"about_ca_topic_score_codex":0.0004554539,"about_ca_topic_score_gemma":0.0004076005,"teacher_disagreement_score":0.0015042316,"about_ca_system_score_codex":0.00013581107,"about_ca_system_score_gemma":0.000142515,"threshold_uncertainty_score":0.004895687},"labels":[],"label_agreement":null},{"id":"W2912735102","doi":"10.1002/brb3.1233","title":"Diffusion tensor imaging of neurocognitive profiles in a community cohort living in marginal housing","year":2019,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Neurocognitive; White matter; Diffusion MRI; Psychology; Cohort; Neuropsychology; Cognition; Neuroscience; Medicine; Magnetic resonance imaging; Internal medicine","score_opus":0.036527671610566026,"score_gpt":0.3407798012256903,"score_spread":0.30425212961512427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912735102","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99988794,0.000011687848,0.000018687124,0.000004945856,3.0978885e-7,0.0000024944384,0.000035905243,4.775051e-7,0.000037592716],"genre_scores_gemma":[0.9998266,0.000010560366,0.000045271136,0.0000043917453,6.507514e-7,0.000002681107,0.0000590755,4.964376e-7,0.00005041472],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999882,0.0000151648865,0.000008164202,0.000026951262,0.000028124397,0.00003968582],"domain_scores_gemma":[0.9997334,0.000016647606,0.0000879355,0.000018238,0.00007926647,0.00006445475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024147765,0.0002850531,0.00020206509,0.0008253897,0.0009934453,0.00054741174,0.0002739248,0.00022373804,0.0006492467],"category_scores_gemma":[0.0008509479,0.00015385011,0.00015022638,0.0005151859,0.00044031633,0.00022518929,0.0004955338,0.00021998315,0.00009197099],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008829103,0.000029728808,0.9963192,0.0000061649266,0.000021627775,0.00016981219,0.0006843572,0.000028510682,0.0013997008,0.000016840388,0.000047201847,0.0011886745],"study_design_scores_gemma":[0.00000184926,0.00003525617,0.99876827,0.0000025533127,0.000006098407,0.00019365484,0.00075854734,0.00008971566,0.00008425258,0.000016024469,0.00004198165,0.0000017197968],"about_ca_topic_score_codex":0.124370545,"about_ca_topic_score_gemma":0.2219495,"teacher_disagreement_score":0.124370545,"about_ca_system_score_codex":0.0006799417,"about_ca_system_score_gemma":0.0007918103,"threshold_uncertainty_score":0.24729323},"labels":[],"label_agreement":null},{"id":"W2912783379","doi":"10.1101/541920","title":"Reducing variability in along-tract analysis with diffusion profile realignment","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; Fonds de recherche du Québec – Nature et technologies; McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Resampling; Fractional anisotropy; Diffusion MRI; Human Connectome Project; White matter; Anisotropy; Artificial intelligence; Computer science; Fiber tract; Pairwise comparison; Thermal diffusivity; Magnetic resonance imaging; Pattern recognition (psychology); Mathematics; Physics; Neuroscience; Biology; Functional connectivity; Medicine; Radiology; Optics","score_opus":0.024060956204398954,"score_gpt":0.28199231162539695,"score_spread":0.257931355420998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912783379","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055991225,0.00018244972,0.94180954,0.0001286167,0.00006436255,0.00007251059,0.00011477301,0.0013722928,0.00026429974],"genre_scores_gemma":[0.31007186,0.0001507072,0.68757796,0.00006433818,0.000046058278,0.00015087647,0.00053802284,0.00068926875,0.0007108647],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981565,0.0006641749,0.00015405909,0.00046851896,0.00045712,0.00009952818],"domain_scores_gemma":[0.9937069,0.0025279792,0.0009897735,0.0017319276,0.00091784995,0.00012565871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004023468,0.0012630167,0.00088451745,0.001404255,0.00039076456,0.0011344721,0.0009541188,0.0009504755,0.0012299493],"category_scores_gemma":[0.017952997,0.0004443444,0.0012816602,0.0012681658,0.0006528989,0.0011676396,0.0014876213,0.0014023267,0.0006862002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008252771,0.00029437587,0.007993907,0.00047268227,0.00056787475,0.00045073812,0.00061139127,0.34496766,0.13301083,0.008415113,0.0031279614,0.4992623],"study_design_scores_gemma":[0.000043494892,0.00031985843,0.0073649855,0.00003689252,0.000104570536,0.0004178075,0.00006596055,0.92907333,0.052406766,0.0055254195,0.0045568743,0.00008402502],"about_ca_topic_score_codex":0.0021957408,"about_ca_topic_score_gemma":0.0019548342,"teacher_disagreement_score":0.004023468,"about_ca_system_score_codex":0.0004286855,"about_ca_system_score_gemma":0.0009994197,"threshold_uncertainty_score":0.021278381},"labels":[],"label_agreement":null},{"id":"W2913104887","doi":"10.1016/j.schres.2019.01.041","title":"Progressive post-onset reorganisation of MRI-derived cortical thickness in adolescents with schizophrenia","year":2019,"lang":"en","type":"letter","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Schulich School of Medicine and Dentistry; Canadian Institutes of Health Research; Western University; Academic Medical Organization of Southwestern Ontario; Chrysalis","keywords":"Default mode network; Thalamus; Basal ganglia; Salience (neuroscience); Neuroscience; Grey matter; Psychology; Voxel; Schizophrenia (object-oriented programming); Functional connectivity; Medicine; Psychiatry; Magnetic resonance imaging; Central nervous system; White matter","score_opus":0.07153619351847491,"score_gpt":0.382296318182013,"score_spread":0.3107601246635381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913104887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822712,0.00084745354,0.0005096509,0.012392285,0.00026830772,0.000016929873,0.00020726609,0.000046010333,0.003440941],"genre_scores_gemma":[0.9971649,0.00036515927,0.00023293946,0.0014224069,0.00020440287,0.0000049167006,0.000035607904,0.00001043784,0.0005592099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998673,0.000028913839,0.00001979077,0.000025476884,0.00003036132,0.000028045402],"domain_scores_gemma":[0.9987263,0.0005031637,0.0003065995,0.00006907505,0.00022296995,0.00017192509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034862038,0.00029228374,0.00030422787,0.00036888124,0.0004053952,0.00044498313,0.00037903336,0.001264678,0.00084531464],"category_scores_gemma":[0.0031339342,0.00019323123,0.00019921447,0.000302081,0.0004966212,0.00042736024,0.00022877155,0.0012087442,0.00018888371],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022409318,0.0002601107,0.5109449,0.0002273929,0.00015656784,0.38261387,0.0026732788,0.0006180054,0.0302716,0.0016289969,0.010757939,0.057606377],"study_design_scores_gemma":[0.00009187242,0.00044088796,0.79115504,0.00011417853,0.00010759901,0.19755682,0.0012941998,0.001621964,0.003214676,0.0014919571,0.0028748615,0.000036029945],"about_ca_topic_score_codex":0.007208,"about_ca_topic_score_gemma":0.009225147,"teacher_disagreement_score":0.007208,"about_ca_system_score_codex":0.00061866804,"about_ca_system_score_gemma":0.00045904415,"threshold_uncertainty_score":0.014332056},"labels":[],"label_agreement":null},{"id":"W2913496827","doi":"10.1017/s0033291718003951","title":"White matter microstructure of the extended limbic system in male and female youth with conduct disorder","year":2019,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"Consejo Nacional de Ciencia y Tecnología; European Commission","keywords":"Cingulum (brain); Fornix; Uncinate fasciculus; Fractional anisotropy; Limbic system; White matter; Psychology; Tractography; Retrosplenial cortex; Neuroscience; Diffusion MRI; Magnetic resonance imaging; Medicine; Hippocampus; Central nervous system","score_opus":0.0557079454839565,"score_gpt":0.35129266129423364,"score_spread":0.2955847158102771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913496827","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99962914,0.00007567055,0.000035171353,0.000007965265,6.6443926e-7,0.0000021980609,0.00008126569,0.0000023895955,0.00016555811],"genre_scores_gemma":[0.99964154,0.000046203313,0.00007185069,0.000007075507,0.0000015960228,0.000003200985,0.00009610982,0.0000022537772,0.00013030521],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990094,0.00001457671,0.000007922515,0.00003788729,0.000020441039,0.000018286011],"domain_scores_gemma":[0.9997085,0.00003510136,0.00015187575,0.000018341938,0.000035083256,0.000051231204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024448792,0.000279343,0.0002132335,0.0009359742,0.0002624777,0.00039104687,0.0001546607,0.00024663814,0.0015224477],"category_scores_gemma":[0.0006162854,0.00017916014,0.00010026573,0.0002935253,0.00035400782,0.00021029935,0.00023458296,0.00014416581,0.00018517347],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002544788,0.000044684548,0.98799706,0.000015560807,0.00004267202,0.0006747192,0.00043334978,0.00007180136,0.006148294,0.000044463843,0.000104892555,0.0041679633],"study_design_scores_gemma":[0.0000019682493,0.000031047217,0.99880743,0.0000022900065,0.000006578631,0.0008482015,0.00008577506,0.000042592692,0.00011574869,0.000010074279,0.000047486956,8.331231e-7],"about_ca_topic_score_codex":0.004720795,"about_ca_topic_score_gemma":0.008487065,"teacher_disagreement_score":0.004720795,"about_ca_system_score_codex":0.0003058664,"about_ca_system_score_gemma":0.00012948518,"threshold_uncertainty_score":0.009386659},"labels":[],"label_agreement":null},{"id":"W2913682618","doi":"10.1101/537092","title":"Free water in white matter differentiates MCI and AD from control subjects","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Q & T Research","funders":"","keywords":"White matter; Diffusion MRI; Hyperintensity; Fluid-attenuated inversion recovery; Partial volume; Neuroinflammation; Psychology; Cardiology; Neuroscience; Internal medicine; Pathology; Medicine; Nuclear medicine; Magnetic resonance imaging; Disease; Radiology","score_opus":0.018025699262401617,"score_gpt":0.24500930733610846,"score_spread":0.22698360807370685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913682618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99659234,0.00059768104,0.0020041787,0.00002033233,0.000013785043,0.000037830447,0.00027245612,0.000066896995,0.00039444145],"genre_scores_gemma":[0.9966112,0.00012794418,0.0022441312,0.000023335015,0.000016781874,0.00002950053,0.0006492708,0.000018466064,0.00027944514],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971396,0.000052990898,0.000043602096,0.000099306504,0.000053546915,0.000036570014],"domain_scores_gemma":[0.99948907,0.00016357221,0.00012244604,0.0000743107,0.000073744646,0.000076801596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010700959,0.00076538307,0.0005873932,0.0021825605,0.0003222472,0.00087797217,0.00028426523,0.0006081055,0.0015506815],"category_scores_gemma":[0.0021327955,0.0002115091,0.00036535677,0.00052347,0.00047105917,0.00041586708,0.0004456507,0.00021276945,0.00030426035],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011116412,0.00058661745,0.76401114,0.00050898595,0.0010258126,0.0014892073,0.0013213326,0.0018887924,0.13625559,0.00053862674,0.0012119992,0.08004555],"study_design_scores_gemma":[0.0000819563,0.0006894752,0.9803388,0.000030346226,0.00020353965,0.0008116747,0.00045467884,0.0056317514,0.010236213,0.0006514785,0.00084176625,0.00002823927],"about_ca_topic_score_codex":0.0026752467,"about_ca_topic_score_gemma":0.003039154,"teacher_disagreement_score":0.0026752467,"about_ca_system_score_codex":0.00015330636,"about_ca_system_score_gemma":0.00017531276,"threshold_uncertainty_score":0.005659282},"labels":[],"label_agreement":null},{"id":"W2913858605","doi":"10.1155/2019/7092496","title":"White Matter Biomarkers Associated with Motor Change in Individuals with Stroke: A Continuous Theta Burst Stimulation Study","year":2019,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Regina; BC Mental Health & Substance Use Services; University of British Columbia; Memorial University of Newfoundland","funders":"Medical Research Council; National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"CTBS; Fractional anisotropy; White matter; Medicine; Stimulation; Motor cortex; Stroke (engine); Primary motor cortex; Neuroscience; Psychology; Diffusion MRI; Brain stimulation; Physical medicine and rehabilitation; Magnetic resonance imaging; Physics","score_opus":0.04277785402908888,"score_gpt":0.3107162946795218,"score_spread":0.2679384406504329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913858605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995117,0.00011404302,0.000064581705,0.000017246333,0.0000028588554,0.00003701693,0.00009057087,0.000001861851,0.00016019179],"genre_scores_gemma":[0.99931896,0.000056985806,0.00013614616,0.00003182451,0.00001139603,0.00004290665,0.00017817247,0.0000012123544,0.00022236179],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977833,0.000042565644,0.000035138513,0.00007106079,0.000040837964,0.000032062613],"domain_scores_gemma":[0.9994698,0.00006693427,0.00017165283,0.000051931722,0.00011032608,0.00012930408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045790893,0.0005074701,0.0006074358,0.0005140383,0.00042647182,0.00036061203,0.00023958199,0.0009341127,0.0008005393],"category_scores_gemma":[0.0010005287,0.00020361676,0.00037004284,0.00046063354,0.00021390711,0.0003400949,0.00035027525,0.0004489849,0.00022308475],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051310915,0.0013192728,0.9713183,0.000100726276,0.00043537724,0.00052700023,0.0004509282,0.00015592507,0.013903329,0.000030499734,0.00015714859,0.006470519],"study_design_scores_gemma":[0.000030993462,0.0014107532,0.99773335,0.0000044168264,0.00007751732,0.00018699256,0.000092263086,0.00009584488,0.00026022026,0.000017040527,0.00008645216,0.000004068548],"about_ca_topic_score_codex":0.0013955947,"about_ca_topic_score_gemma":0.0022544833,"teacher_disagreement_score":0.0013955947,"about_ca_system_score_codex":0.00019134169,"about_ca_system_score_gemma":0.00020358997,"threshold_uncertainty_score":0.0027748942},"labels":[],"label_agreement":null},{"id":"W291418382","doi":"10.1016/j.neuroimage.2015.05.023","title":"In vivo histology of the myelin g-ratio with magnetic resonance imaging","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":316,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Polytechnique Montréal; Université Laval; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Research Council for Economics, Humanities and Social Science","keywords":"Myelin; White matter; Magnetic resonance imaging; Corpus callosum; Axon; Multiple sclerosis; Histology; Human brain; Nuclear magnetic resonance; Chemistry; Pathology; Anatomy; Medicine; Biology; Central nervous system; Neuroscience; Physics; Radiology","score_opus":0.044427088814174766,"score_gpt":0.3155453774144212,"score_spread":0.2711182886002464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W291418382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7834254,0.006141938,0.19120528,0.0007965969,0.00020884327,0.000190521,0.0009193058,0.0012160173,0.015896115],"genre_scores_gemma":[0.9145066,0.004075504,0.069442295,0.0002058244,0.00008099667,0.000107544525,0.00038562424,0.0005674822,0.010628116],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997938,0.00006640172,0.000016586333,0.000054052016,0.000037619695,0.00003150842],"domain_scores_gemma":[0.99970955,0.000053495787,0.000064494096,0.000056024357,0.000086527034,0.000029925453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009306796,0.0005937537,0.00022950057,0.0013370501,0.0006233262,0.0008665328,0.00044074134,0.00086463173,0.0034947612],"category_scores_gemma":[0.00086800614,0.00051453465,0.00021306278,0.0006791445,0.0007285949,0.001671401,0.00039555202,0.0009042511,0.0008857749],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063284324,0.00007526219,0.0020037647,0.0002044873,0.00006211847,0.00040182294,0.00019474947,0.00038558134,0.97628003,0.0019625998,0.0002944328,0.01750234],"study_design_scores_gemma":[0.000060391143,0.00060961145,0.022614814,0.00006345775,0.00015311773,0.004403636,0.00047824063,0.0051440503,0.9562092,0.0033209953,0.006905563,0.000036951486],"about_ca_topic_score_codex":0.00160251,"about_ca_topic_score_gemma":0.0015100173,"teacher_disagreement_score":0.0034947612,"about_ca_system_score_codex":0.00030514813,"about_ca_system_score_gemma":0.00044504934,"threshold_uncertainty_score":0.011691153},"labels":[],"label_agreement":null},{"id":"W2914916753","doi":"10.3389/fnins.2019.00011","title":"Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Medical Research Council; Alzheimer Society Research Program; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Engineering and Physical Sciences Research Council; Alzheimer Society; National Institute for Health and Care Research; University College London; National Institute on Aging; Eli Lilly and Company","keywords":"Ex vivo; In vivo; Neuroimaging; Magnetic resonance imaging; Statistical power; Brain size; Biomedical engineering; Pathology; Neuroscience; Medicine; Biology; Mathematics; Radiology; Statistics","score_opus":0.0587991854399033,"score_gpt":0.38115759191798915,"score_spread":0.32235840647808583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914916753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90136117,0.0017630574,0.091474734,0.0002894333,0.00019037243,0.00014397087,0.0028143325,0.00090910867,0.0010537932],"genre_scores_gemma":[0.93827623,0.0012737021,0.052848525,0.0002054048,0.00007394917,0.00077061815,0.003191156,0.000427381,0.0029329741],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993574,0.00008171231,0.00006388851,0.00023356476,0.00018268813,0.00008080308],"domain_scores_gemma":[0.99876213,0.00017419398,0.0005072804,0.0001986406,0.00024372074,0.00011405273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010723838,0.00094886264,0.0007726431,0.0014821289,0.0003047408,0.00059922563,0.00042882198,0.0007821907,0.0017399067],"category_scores_gemma":[0.00087311765,0.0003793994,0.0006924747,0.0005398155,0.0006078502,0.0008022499,0.00039684976,0.0018397087,0.00040383075],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032903085,0.00024643505,0.0016919049,0.00010357592,0.00008465948,0.000047054396,0.0000735103,0.0006394176,0.99040717,0.00017938264,0.00014747061,0.006050367],"study_design_scores_gemma":[0.000034350647,0.0014124966,0.040706355,0.000020991763,0.00020387046,0.0003435126,0.000086619155,0.012212733,0.9428211,0.0005360581,0.0015735921,0.000048335303],"about_ca_topic_score_codex":0.00064010464,"about_ca_topic_score_gemma":0.0011047602,"teacher_disagreement_score":0.0017399067,"about_ca_system_score_codex":0.00032885815,"about_ca_system_score_gemma":0.00025693807,"threshold_uncertainty_score":0.005820632},"labels":[],"label_agreement":null},{"id":"W2915476106","doi":"10.1073/pnas.1807983116","title":"Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":241,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Royal Ottawa Mental Health Centre; University of Ottawa","funders":"National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Alliance for Research on Schizophrenia and Depression; New York State Psychiatric Institute; Parkinson's Foundation; Parkinson's Disease Foundation; Ministero dell’Istruzione, dell’Università e della Ricerca; Dana Foundation","keywords":"Neuromelanin; Dopamine; Substantia nigra; Neurodegeneration; Neuroscience; Parkinson's disease; Human brain; Striatum; Medicine; Pathology; Dopaminergic; Psychology; Disease","score_opus":0.06439228242440746,"score_gpt":0.35239454207170023,"score_spread":0.28800225964729276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915476106","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7878356,0.016749177,0.18880878,0.0005781051,0.00011389189,0.00016213242,0.0010212952,0.0004487986,0.0042821392],"genre_scores_gemma":[0.89052856,0.00535048,0.10100293,0.00042944145,0.00010480817,0.0001961519,0.0005192304,0.00008829167,0.0017802044],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99984705,0.00006874606,0.000007704669,0.000041211995,0.0000213096,0.00001388941],"domain_scores_gemma":[0.999835,0.000061554994,0.000048350787,0.000017772425,0.000019770512,0.000017395449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047335977,0.00038386916,0.00023747356,0.0005872127,0.00013304662,0.00033505677,0.00022658143,0.00052662566,0.0006617375],"category_scores_gemma":[0.0007477953,0.0002693751,0.00013392285,0.00029732083,0.0002906401,0.00036124053,0.00028309601,0.00039627022,0.0001563779],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022402203,0.000046375368,0.005082607,0.0002799608,0.00011497844,0.00027955926,0.000084022366,0.0006721071,0.9760366,0.0006231237,0.00037002418,0.016186664],"study_design_scores_gemma":[0.00008717852,0.001284513,0.17289795,0.00019587576,0.0005956659,0.008335425,0.0003529589,0.044751093,0.75381434,0.0047265794,0.012836045,0.00012232672],"about_ca_topic_score_codex":0.0005641809,"about_ca_topic_score_gemma":0.0018276133,"teacher_disagreement_score":0.0006617375,"about_ca_system_score_codex":0.00011155475,"about_ca_system_score_gemma":0.0001809318,"threshold_uncertainty_score":0.002503395},"labels":[],"label_agreement":null},{"id":"W2916685372","doi":"10.1101/559351","title":"Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Diffusion imaging; White matter; Dimensionality reduction; Diffusion; Covariance; Computer science; Tractography; Neuroscience; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Psychology; Medicine; Mathematics; Physics; Statistics; Radiology","score_opus":0.042554195835598475,"score_gpt":0.3120515487837536,"score_spread":0.2694973529481551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916685372","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16139765,0.00055761833,0.83462083,0.00042613194,0.00006206468,0.00014654588,0.0012655582,0.00085937546,0.0006642044],"genre_scores_gemma":[0.38084066,0.00038899522,0.6154207,0.00004947076,0.0000595605,0.00026036004,0.0019939125,0.0002676169,0.0007187537],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992887,0.00029467067,0.00006650744,0.0001471492,0.00016121632,0.00004180092],"domain_scores_gemma":[0.99808276,0.00085259957,0.00027080055,0.00044473697,0.00029490874,0.000054198812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017395051,0.00097239244,0.0006843536,0.002868023,0.0004037776,0.0013098702,0.00035147177,0.00042958016,0.0012778601],"category_scores_gemma":[0.007118493,0.0002846707,0.0011159021,0.0017368724,0.00055263407,0.0006464038,0.0008023572,0.0009370333,0.00051715196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034048303,0.00027240175,0.02378747,0.0007044031,0.00078855705,0.00032923764,0.00094444375,0.12598139,0.19164039,0.029885843,0.0090704,0.61625487],"study_design_scores_gemma":[0.000035559995,0.0001998916,0.063407965,0.000087422166,0.00017411775,0.00040900568,0.0002553054,0.86318606,0.03239118,0.030750176,0.0089843115,0.00011899168],"about_ca_topic_score_codex":0.0029226786,"about_ca_topic_score_gemma":0.0035634553,"teacher_disagreement_score":0.0029226786,"about_ca_system_score_codex":0.0006026154,"about_ca_system_score_gemma":0.0011213046,"threshold_uncertainty_score":0.0091995},"labels":[],"label_agreement":null},{"id":"W2916731520","doi":"10.3171/2018.9.jns182022","title":"Quantitative assessment of secondary white matter injury in the visual pathway by pituitary adenomas: a multimodal study at 7-Tesla MRI","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Francophone University Association","funders":"National Cancer Institute","keywords":"Optic chiasm; Medicine; White matter; Diffusion MRI; Visual field; Tractography; Fractional anisotropy; Optic tract; Optic radiation; Visual system; Optic nerve; Visual cortex; Ophthalmology; Radiology; Magnetic resonance imaging; Pathology; Nuclear medicine; Neuroscience; Psychology","score_opus":0.03209522537419985,"score_gpt":0.374945952573815,"score_spread":0.3428507271996152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916731520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991351,0.00016471017,0.0005370367,0.0000062483814,5.5889035e-7,0.0000029249877,0.000018451334,0.0000051423035,0.00012987528],"genre_scores_gemma":[0.9995059,0.00006218418,0.00034123406,0.0000029246642,0.000002781668,0.000002772605,0.000024765277,0.000002565835,0.000054940556],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990726,0.00002196672,0.000007992367,0.000026496466,0.000023249586,0.000013064818],"domain_scores_gemma":[0.99967325,0.00006324057,0.00012468308,0.000024826277,0.00007067689,0.000043406984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032023384,0.00021972953,0.00014110761,0.00062278024,0.00014148904,0.00023990704,0.00009835643,0.00020374086,0.0006494766],"category_scores_gemma":[0.00091299164,0.00013418592,0.00014558702,0.00019054064,0.0002418032,0.00032331256,0.0002132199,0.00013281948,0.0001691175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018139607,0.00011095903,0.5509476,0.0002195284,0.0003029801,0.0033151864,0.0009769392,0.0008288745,0.41851294,0.000096856355,0.00013061793,0.022743434],"study_design_scores_gemma":[0.000017047394,0.0007516475,0.97225404,0.0000129645205,0.000099703444,0.008137333,0.00024573813,0.001414368,0.016689043,0.00006668038,0.00029302796,0.000018484892],"about_ca_topic_score_codex":0.00075599796,"about_ca_topic_score_gemma":0.0007286987,"teacher_disagreement_score":0.00075599796,"about_ca_system_score_codex":0.0001300338,"about_ca_system_score_gemma":0.00009450261,"threshold_uncertainty_score":0.0021727085},"labels":[],"label_agreement":null},{"id":"W2916984470","doi":"10.1016/j.cortex.2019.02.010","title":"Organization of extrastriate and temporal cortex in chimpanzees compared to humans and macaques","year":2019,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Deafness and Other Communication Disorders; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; James S. McDonnell Foundation; National Institutes of Health; Yerkes National Primate Research Center, Emory University; John Templeton Foundation","keywords":"Extrastriate cortex; Neuroscience; Visual cortex; Primate; Cortex (anatomy); Macaque; Temporal cortex; Psychology; White matter; Association (psychology); Posterior parietal cortex; Medicine; Magnetic resonance imaging","score_opus":0.03511358491176709,"score_gpt":0.3282728182939709,"score_spread":0.29315923338220384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916984470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968119,0.00078713987,0.00047521904,0.000049201215,0.0000043907257,0.0000040092477,0.00018230852,0.000013119191,0.0016727392],"genre_scores_gemma":[0.99808997,0.00025266278,0.00059935264,0.000027302418,0.0000034116194,0.000008500203,0.00009613266,0.000011119591,0.0009115295],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999324,0.0000106004145,0.0000035399153,0.000027326849,0.0000098254395,0.00001626224],"domain_scores_gemma":[0.9997844,0.000055208853,0.00006335681,0.000025848614,0.00003321903,0.000037850517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014951157,0.00017945506,0.00017897507,0.001078472,0.0002515319,0.0005008872,0.0002121698,0.00019109355,0.0045137503],"category_scores_gemma":[0.00038152133,0.00021670309,0.0001422706,0.00040554497,0.00048107156,0.00040059316,0.0003545276,0.0003242287,0.00021648419],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016254499,0.000068013156,0.05525752,0.00032651334,0.0002992177,0.0017380643,0.0015870492,0.0006992663,0.90243423,0.0034724262,0.00041514914,0.032077163],"study_design_scores_gemma":[0.00001778342,0.000080126774,0.9867219,0.00001285666,0.000042221345,0.0021579778,0.00048032004,0.00038773185,0.008573171,0.00067586504,0.0008418379,0.000008222911],"about_ca_topic_score_codex":0.004879871,"about_ca_topic_score_gemma":0.011121719,"teacher_disagreement_score":0.004879871,"about_ca_system_score_codex":0.00026183535,"about_ca_system_score_gemma":0.00018008637,"threshold_uncertainty_score":0.015099943},"labels":[],"label_agreement":null},{"id":"W2917580875","doi":"10.1192/bjp.2018.299","title":"Evaluation of functional connectivity in subdivisions of the thalamus in schizophrenia","year":2019,"lang":"en","type":"article","venue":"The British Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"University of Electronic Science and Technology of China; National Natural Science Foundation of China","keywords":"Thalamus; Neuroscience; Schizophrenia (object-oriented programming); Functional magnetic resonance imaging; Functional connectivity; Psychology; Psychiatry","score_opus":0.0527393387733216,"score_gpt":0.33633084107450534,"score_spread":0.28359150230118374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917580875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99087816,0.00012668446,0.008567136,0.0000149067555,0.0000011135227,0.00003108619,0.00016361981,0.000025065938,0.00019235232],"genre_scores_gemma":[0.99406284,0.000042713997,0.0055329953,0.0000032718974,0.0000012658878,0.000036553793,0.0002627229,0.0000047286644,0.000052928866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998472,0.000054856315,0.000012415127,0.000032328117,0.000035436547,0.000017804177],"domain_scores_gemma":[0.9996598,0.00011490955,0.000093959934,0.00003614207,0.00006314077,0.000032061747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035875442,0.0002340316,0.0002169185,0.00094516505,0.00020677902,0.00031212386,0.00017885854,0.00014546158,0.00054967246],"category_scores_gemma":[0.0010672498,0.000108983244,0.00026698472,0.00039699505,0.0002826451,0.00017162146,0.0003792399,0.00013081457,0.00005204534],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015822331,0.00013465017,0.6107312,0.00032868687,0.00053515204,0.00086226535,0.0017008646,0.01566061,0.26296607,0.0012442176,0.00032605344,0.103928074],"study_design_scores_gemma":[0.000044432185,0.0003917897,0.9366301,0.000025984455,0.0001172601,0.0010559983,0.00046607695,0.04394684,0.015518699,0.0012570409,0.0005172668,0.000028509914],"about_ca_topic_score_codex":0.0037929416,"about_ca_topic_score_gemma":0.0069340034,"teacher_disagreement_score":0.0037929416,"about_ca_system_score_codex":0.000466335,"about_ca_system_score_gemma":0.00035779295,"threshold_uncertainty_score":0.007541716},"labels":[],"label_agreement":null},{"id":"W2917789037","doi":"10.1002/nbm.4073","title":"VERDICT MRI validation in fresh and fixed prostate specimens using patient‐specific moulds for histological and MR alignment","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"Programme Grants for Applied Research; National Health and Medical Research Council; Cancer Research UK; Prostate Cancer UK; Medical Research Council; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; University College London","keywords":"Histology; Ex vivo; Diffusion MRI; Prostatectomy; Verdict; Fixation (population genetics); Prostate; Pathology; Anatomy; Medicine; Biomedical engineering; Chemistry; Materials science; Biology; Magnetic resonance imaging; In vivo; Radiology; Internal medicine","score_opus":0.06177218552594573,"score_gpt":0.34663223746614713,"score_spread":0.2848600519402014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917789037","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6393651,0.0005789243,0.35701317,0.00011483955,0.000059955873,0.0001409707,0.0005811131,0.0009881768,0.0011577415],"genre_scores_gemma":[0.89216727,0.00032113132,0.1057108,0.000036815865,0.000006969298,0.0001145893,0.00049755484,0.0002785233,0.0008662776],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99965894,0.00006257924,0.000033748413,0.00007774962,0.00014134764,0.000025652946],"domain_scores_gemma":[0.9985771,0.00051942153,0.00021949939,0.00031608334,0.00032482194,0.000043012777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016056088,0.000563148,0.00030919822,0.0006766398,0.00025801995,0.000537262,0.0003920562,0.0006110674,0.00096912903],"category_scores_gemma":[0.0036751411,0.00043625286,0.0004351796,0.00032391542,0.0006148946,0.00042424983,0.0005085781,0.00052469736,0.00028452094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024972472,0.000042243933,0.003105251,0.00022739322,0.000044043903,0.0002193323,0.00035256296,0.04970852,0.9294417,0.0009873583,0.0001722393,0.015449611],"study_design_scores_gemma":[0.000020177555,0.0005255138,0.021592662,0.000042300926,0.00008017872,0.0012189908,0.00017103896,0.14560573,0.8267167,0.0008108537,0.0031079417,0.000107802465],"about_ca_topic_score_codex":0.0017427696,"about_ca_topic_score_gemma":0.0022404278,"teacher_disagreement_score":0.0017427696,"about_ca_system_score_codex":0.0005406461,"about_ca_system_score_gemma":0.00047853694,"threshold_uncertainty_score":0.008491397},"labels":[],"label_agreement":null},{"id":"W2919694754","doi":"10.3389/fnana.2019.00024","title":"The Superoanterior Fasciculus (SAF): A Novel White Matter Pathway in the Human Brain?","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institutes of Health; National Institute of Mental Health; Medical Research Council; University of Bristol; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Human Connectome Project; Tractography; White matter; Cingulum (brain); Human brain; Neuroscience; Uncinate fasciculus; Diffusion MRI; Computer science; Fiber tract; Fasciculus; Arcuate fasciculus; Brain mapping; Fractional anisotropy; Artificial intelligence; Psychology; Magnetic resonance imaging; Medicine; Functional connectivity; Radiology","score_opus":0.01904501160294042,"score_gpt":0.2936389971660267,"score_spread":0.2745939855630863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919694754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8658318,0.015776908,0.10697854,0.0035515127,0.00022807035,0.00010809331,0.0006757321,0.00037696012,0.006472302],"genre_scores_gemma":[0.95348525,0.0050842497,0.039240744,0.00032762066,0.00017104478,0.000050617964,0.00023065462,0.000048972124,0.0013608293],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9999049,0.000018126173,0.0000063172956,0.000035231722,0.000019316274,0.000016113529],"domain_scores_gemma":[0.99977833,0.00004751947,0.00008987322,0.000028421782,0.000029459174,0.000026494059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030061576,0.0004554181,0.00015675544,0.0006417989,0.00029429758,0.0005490488,0.0002226784,0.0005330706,0.0015603029],"category_scores_gemma":[0.00089906296,0.00013357823,0.00016675166,0.0004884327,0.0013256025,0.0012688542,0.00037537472,0.0002640915,0.00037759202],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019321841,0.00009306925,0.08148192,0.0014398986,0.00019056055,0.010875522,0.0022496292,0.002475384,0.37050045,0.026963577,0.0057269474,0.4960708],"study_design_scores_gemma":[0.00023857351,0.001967481,0.438193,0.0015012888,0.0005098821,0.113074355,0.002473522,0.028948605,0.1664154,0.15037824,0.09598766,0.0003120053],"about_ca_topic_score_codex":0.0020029072,"about_ca_topic_score_gemma":0.0037845427,"teacher_disagreement_score":0.0020029072,"about_ca_system_score_codex":0.00023671536,"about_ca_system_score_gemma":0.0005356526,"threshold_uncertainty_score":0.005219698},"labels":[],"label_agreement":null},{"id":"W2920455229","doi":"10.1038/s41598-019-39199-x","title":"Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre; Canadian Institute for Advanced Research","funders":"National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Nuclear medicine; Region of interest; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Psychology; Physics; Radiology","score_opus":0.0669565510197751,"score_gpt":0.3679131003551871,"score_spread":0.300956549335412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920455229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99585503,0.0012865099,0.001887702,0.000020345246,0.000007090473,0.000023421746,0.0002875463,0.000022724096,0.0006095529],"genre_scores_gemma":[0.9975036,0.000284262,0.0016577536,0.000013447135,0.000007696843,0.000025569676,0.00027039496,0.000010677819,0.00022660424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99953544,0.00009543081,0.000066162844,0.00020767616,0.000063437576,0.000031982545],"domain_scores_gemma":[0.998725,0.0005066244,0.00035408695,0.00017207181,0.00015968499,0.00008259915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015411635,0.00043453134,0.0002882157,0.0015050469,0.00022441146,0.0005026013,0.00021160996,0.00045720828,0.0009614098],"category_scores_gemma":[0.0047564995,0.00019225023,0.00025591176,0.0006972459,0.00062104943,0.000754383,0.00038416774,0.0001534352,0.00023221584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004596253,0.00026188823,0.72796744,0.00078577513,0.0023450279,0.0010398092,0.003289126,0.0019749403,0.17950745,0.0010775268,0.00075385044,0.07640092],"study_design_scores_gemma":[0.000027901106,0.00051262666,0.98802257,0.000017203609,0.0001435791,0.0011057383,0.0003446799,0.0013504993,0.0069873943,0.0009845544,0.00048134848,0.000021949383],"about_ca_topic_score_codex":0.0018477961,"about_ca_topic_score_gemma":0.0023336678,"teacher_disagreement_score":0.0018477961,"about_ca_system_score_codex":0.0001635489,"about_ca_system_score_gemma":0.0002186505,"threshold_uncertainty_score":0.008150578},"labels":[],"label_agreement":null},{"id":"W2921139541","doi":"10.1038/s41598-019-40070-2","title":"Subtle white matter alterations in schizophrenia identified with a new measure of fiber density","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"McGill University; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Schizophrenia (object-oriented programming); Fasciculus; Neuroscience; Uncinate fasciculus; Superior longitudinal fasciculus; Arcuate fasciculus; Psychology; Medicine; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.029030859436621186,"score_gpt":0.29265932818484636,"score_spread":0.26362846874822515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921139541","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932662,0.00028157045,0.005906207,0.000027623593,0.0000035726846,0.000011317698,0.00023336845,0.000039081802,0.00023101857],"genre_scores_gemma":[0.99321234,0.00022275014,0.006231129,0.000008199706,0.000005466539,0.000014221539,0.0001878496,0.0000071791706,0.000110919966],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999038,0.000016604903,0.000016498449,0.000023015531,0.000028783714,0.000011354433],"domain_scores_gemma":[0.9997427,0.00003993179,0.00012951801,0.000033369888,0.0000241791,0.00003030784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004001868,0.00030511728,0.00022998184,0.0012918544,0.00014976056,0.0002649553,0.000099886965,0.00016084415,0.00054482516],"category_scores_gemma":[0.0006756104,0.00013680905,0.00018582969,0.00050762785,0.00033480898,0.00027505297,0.00037020072,0.00017487234,0.000058916623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015131644,0.00007334952,0.26350477,0.00025425677,0.00032875733,0.00071922434,0.0006083656,0.0021775109,0.6604899,0.00086203817,0.00025660318,0.06921217],"study_design_scores_gemma":[0.000022931607,0.0003042994,0.9666417,0.000023636461,0.00010856889,0.001629387,0.00019752687,0.008251251,0.021264909,0.0010067186,0.0005199452,0.000029054667],"about_ca_topic_score_codex":0.0025147984,"about_ca_topic_score_gemma":0.0034055924,"teacher_disagreement_score":0.0025147984,"about_ca_system_score_codex":0.00021976765,"about_ca_system_score_gemma":0.00024892332,"threshold_uncertainty_score":0.0050002933},"labels":[],"label_agreement":null},{"id":"W2922001838","doi":"10.1117/12.2512870","title":"Constructing an average geometry and diffusion tensor magnetic resonance field from freshly explanted porcine hearts","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Tech University","funders":"","keywords":"Diffusion MRI; Atlas (anatomy); Tensor (intrinsic definition); Tensor field; Cardiac cycle; Diffusion; Magnetic resonance imaging; Structure tensor; Transformation (genetics); Physics; Computer science; Geometry; Nuclear magnetic resonance; Mathematics; Mathematical analysis; Artificial intelligence; Chemistry; Anatomy; Exact solutions in general relativity","score_opus":0.026086190324028775,"score_gpt":0.29552196630262056,"score_spread":0.2694357759785918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922001838","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057783134,0.000092118185,0.93942606,0.00009802088,0.00003757762,0.00006177249,0.0004209789,0.0012239057,0.00085646426],"genre_scores_gemma":[0.22040881,0.0005220569,0.77561146,0.000051523075,0.000034842447,0.00015327914,0.0014440526,0.0004977959,0.0012762188],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998568,0.000016928621,0.00001196936,0.000054496584,0.000047371705,0.000012544354],"domain_scores_gemma":[0.9997111,0.000068151996,0.000060572762,0.00007516156,0.000061003146,0.000023953187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038504953,0.00056254497,0.00043320225,0.0006839386,0.00029654658,0.0007660303,0.0006613567,0.0005192526,0.0012015422],"category_scores_gemma":[0.0011303643,0.00060246926,0.00070469367,0.0004748561,0.00045626826,0.0005235463,0.0006565952,0.00075102143,0.0006880981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013646453,0.00005723608,0.0028162608,0.00023876087,0.00007482862,0.00066503225,0.00027942844,0.3179616,0.43774837,0.013551344,0.002695701,0.22377497],"study_design_scores_gemma":[0.000015180819,0.00027256124,0.0058641476,0.000026509168,0.00004744972,0.0011137837,0.000106579275,0.84546274,0.118875936,0.016161395,0.011953309,0.00010042003],"about_ca_topic_score_codex":0.0019849855,"about_ca_topic_score_gemma":0.0038562443,"teacher_disagreement_score":0.0019849855,"about_ca_system_score_codex":0.00033190678,"about_ca_system_score_gemma":0.001129706,"threshold_uncertainty_score":0.0040195584},"labels":[],"label_agreement":null},{"id":"W2922076169","doi":"10.1007/s00429-019-01856-2","title":"Uncovering the inferior fronto-occipital fascicle and its topological organization in non-human primates: the missing connection for language evolution","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fascicle; Tractography; Fiber tract; Non-human; Human brain; Diffusion MRI; Neuroscience; Psychology; Computer science; Cognitive science; Biology; Philosophy; Anatomy; Medicine","score_opus":0.01409800587079065,"score_gpt":0.3024756631009879,"score_spread":0.28837765723019726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922076169","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95854795,0.0026085493,0.033909947,0.00073978916,0.000042877084,0.0000119994165,0.00031721723,0.00016633878,0.0036553673],"genre_scores_gemma":[0.9909691,0.00054661016,0.00787262,0.000046952635,0.000030830048,0.00000834261,0.000110180714,0.000026600592,0.00038872779],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995065,0.000008837446,0.0000026207183,0.000016056863,0.0000090559115,0.000012786602],"domain_scores_gemma":[0.9996877,0.00008596158,0.00009256652,0.00005341901,0.00003736186,0.00004295516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021680974,0.00017552484,0.00016499212,0.0014032859,0.00031231644,0.00060341397,0.0002701995,0.00034085818,0.0015381243],"category_scores_gemma":[0.00091746467,0.00016494714,0.00013814695,0.000606219,0.0012987439,0.0012599414,0.00044208323,0.00043210722,0.00025745036],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005018448,0.000055267297,0.11576065,0.0005274772,0.00020752798,0.00268896,0.0022948931,0.0037733766,0.65785456,0.026907118,0.0014760965,0.18795231],"study_design_scores_gemma":[0.00003396866,0.0002629185,0.79761124,0.00021511586,0.00017792502,0.00821881,0.0029755249,0.025884384,0.03663382,0.112637796,0.015237992,0.00011058146],"about_ca_topic_score_codex":0.0015092245,"about_ca_topic_score_gemma":0.0034732642,"teacher_disagreement_score":0.0015381243,"about_ca_system_score_codex":0.0001805616,"about_ca_system_score_gemma":0.0003254774,"threshold_uncertainty_score":0.00514555},"labels":[],"label_agreement":null},{"id":"W2922110169","doi":"10.1002/cjs.11601","title":"A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Centre for Advancing Health Outcomes","funders":"National Institute of Dental and Craniofacial Research; National Institute on Drug Abuse","keywords":"Diffusion MRI; Bayesian probability; Tensor (intrinsic definition); Semiparametric model; Mathematics; Positive-definite matrix; Semiparametric regression; Diffusion; Statistical physics; Computer science; Econometrics; Statistics; Physics; Medicine; Geometry; Eigenvalues and eigenvectors; Radiology; Nonparametric statistics; Thermodynamics","score_opus":0.02534461656232357,"score_gpt":0.291729914995808,"score_spread":0.26638529843348446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922110169","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003134968,0.00028125773,0.99569964,0.00027037848,0.00002329398,0.00003773652,0.000082220016,0.00008807807,0.0003824503],"genre_scores_gemma":[0.26145765,0.0018646069,0.72598153,0.00040115922,0.00033472193,0.0007903073,0.0008213853,0.00027948682,0.0080690915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9958882,0.0027326497,0.00013723686,0.000532155,0.0005355851,0.00017428942],"domain_scores_gemma":[0.98249453,0.014490162,0.00096400914,0.00063784653,0.0011520141,0.0002614586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010678997,0.001323066,0.0022323446,0.0020334502,0.0008827885,0.0022178297,0.003131522,0.002108992,0.0041645095],"category_scores_gemma":[0.024907991,0.0013752719,0.0023145722,0.0023949197,0.0026727607,0.0028838548,0.0028579824,0.0033118497,0.0010479465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001232342,0.00008105246,0.0016528687,0.0001721711,0.0002099902,0.00020540885,0.00025521114,0.63660085,0.001110899,0.32053754,0.0021546267,0.036896106],"study_design_scores_gemma":[0.000011605015,0.000017699163,0.00018905252,0.00001671822,0.00002157729,0.000027267797,0.000010967496,0.9550567,0.00011827919,0.0436401,0.00087068713,0.000019257148],"about_ca_topic_score_codex":0.01145102,"about_ca_topic_score_gemma":0.011410666,"teacher_disagreement_score":0.01145102,"about_ca_system_score_codex":0.0015183513,"about_ca_system_score_gemma":0.0021501714,"threshold_uncertainty_score":0.056476593},"labels":[],"label_agreement":null},{"id":"W2922746028","doi":"10.1111/acer.14024","title":"Myelin Water Fraction Imaging of the Brain in Children with Prenatal Alcohol Exposure","year":2019,"lang":"en","type":"article","venue":"Alcoholism Clinical and Experimental Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of British Columbia; University of Alberta; University of Guelph","funders":"Kids Brain Health Network; Canada Research Chairs; Australian Government; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute","keywords":"Splenium; Corpus callosum; White matter; Internal capsule; Putamen; Caudate nucleus; Myelin; Magnetic resonance imaging; Anatomy; Medicine; Brain size; Pathology; Internal medicine; Central nervous system; Radiology","score_opus":0.11943737111477723,"score_gpt":0.4770539394554527,"score_spread":0.35761656834067546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922746028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99917173,0.00015298897,0.0003790612,0.000025252535,0.000001647855,0.0000058372575,0.000085221945,0.000012665468,0.00016556082],"genre_scores_gemma":[0.9982925,0.00022091041,0.001240241,0.000020298508,0.000003305141,0.000013907575,0.00007581777,0.0000069835305,0.00012597712],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998709,0.00002067159,0.000010604009,0.000041269694,0.000027735843,0.00002877467],"domain_scores_gemma":[0.99975413,0.000050681636,0.00010412545,0.000011031637,0.000044497752,0.000035566845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027307184,0.00032352284,0.00026416077,0.0009953049,0.0002662762,0.0001954394,0.00015252105,0.00031897755,0.0007354862],"category_scores_gemma":[0.0008333975,0.00020311493,0.00016745033,0.00033409856,0.0003564573,0.00027489543,0.0003227419,0.00025131134,0.00008165322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011143315,0.00011789126,0.8125028,0.0001877562,0.00008926923,0.0077789766,0.0019237733,0.0004009375,0.15240851,0.00013974535,0.0003719337,0.022963995],"study_design_scores_gemma":[0.000008680307,0.00040238418,0.9725514,0.000020178968,0.000047169193,0.010596828,0.0006045312,0.00046265576,0.014807815,0.00010709843,0.000381227,0.00001014732],"about_ca_topic_score_codex":0.004828583,"about_ca_topic_score_gemma":0.0043509956,"teacher_disagreement_score":0.004828583,"about_ca_system_score_codex":0.00026720573,"about_ca_system_score_gemma":0.00021760605,"threshold_uncertainty_score":0.009600937},"labels":[],"label_agreement":null},{"id":"W2922947702","doi":"10.1002/hbm.24574","title":"Proprioception and motor performance after stroke: An examination of diffusion properties in sensory and motor pathways","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Proprioception; Postcentral gyrus; Corticospinal tract; Psychology; Supramarginal gyrus; Sensory system; Physical medicine and rehabilitation; Gyrus; Neuroscience; Diffusion MRI; Pyramidal tracts; Medicine; Somatosensory system; Magnetic resonance imaging","score_opus":0.06381975238675555,"score_gpt":0.2805149586489354,"score_spread":0.21669520626217983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922947702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992119,0.0002386196,0.00029444435,0.000013394203,8.869848e-7,0.0000051714756,0.00006726314,0.0000053350245,0.00016290549],"genre_scores_gemma":[0.9989786,0.00020068011,0.00032766143,0.0000046920923,0.0000026602686,0.000009788921,0.0001276434,0.0000022599465,0.00034605866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991274,0.00001628655,0.000009144871,0.000022270717,0.000022165683,0.000017331487],"domain_scores_gemma":[0.99959296,0.0000911399,0.00017243254,0.000029261955,0.000047404483,0.00006678413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042523514,0.00018820452,0.00019619873,0.00050765957,0.00015971337,0.00026442384,0.00013365265,0.0003123462,0.001134296],"category_scores_gemma":[0.001158851,0.000097457356,0.00015986498,0.00031330445,0.000285793,0.00051917,0.0003332273,0.0002679241,0.00021963274],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026809634,0.00049601606,0.7420462,0.00024387389,0.00025517566,0.00067134463,0.000858857,0.001671148,0.19754064,0.00014605546,0.000202689,0.053187057],"study_design_scores_gemma":[0.0000043432833,0.0004359518,0.9957064,0.000004659183,0.000016953376,0.00042837553,0.000065354885,0.00060054293,0.0025434906,0.000046458434,0.00014093937,0.0000065528675],"about_ca_topic_score_codex":0.0018046603,"about_ca_topic_score_gemma":0.0029309555,"teacher_disagreement_score":0.0018046603,"about_ca_system_score_codex":0.00019040407,"about_ca_system_score_gemma":0.00024461615,"threshold_uncertainty_score":0.0037946105},"labels":[],"label_agreement":null},{"id":"W2924890706","doi":"10.1101/590521","title":"Improving spatial normalization of brain diffusion MRI to measure longitudinal changes of tissue microstructure in the cortex and white matter","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Universidad de Buenos Aires","keywords":"Reproducibility; White matter; Spatial normalization; Diffusion MRI; Fractional anisotropy; Normalization (sociology); Magnetic resonance imaging; Computer science; Artificial intelligence; Medicine; Nuclear medicine; Mathematics; Statistics; Radiology","score_opus":0.018899622846885046,"score_gpt":0.26397221897469425,"score_spread":0.2450725961278092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2924890706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59153163,0.00070875755,0.40347108,0.0001517669,0.00007687703,0.00025668618,0.0004514257,0.002076794,0.0012750332],"genre_scores_gemma":[0.6974446,0.00027993481,0.29951853,0.000040246367,0.000019859961,0.00031321688,0.0006442195,0.00048759917,0.0012517263],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99896,0.00035917223,0.000094748975,0.00031823205,0.00020902875,0.000058727834],"domain_scores_gemma":[0.99818987,0.0006022191,0.00026046974,0.0004115358,0.00050105114,0.000034842484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003932847,0.00062739494,0.00042647123,0.0006759069,0.00031173573,0.0006982493,0.0004934095,0.00036238966,0.0013649792],"category_scores_gemma":[0.008145486,0.00031338094,0.0005517814,0.0005867844,0.00039395902,0.0007184579,0.00054732565,0.00040698703,0.00048588426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014177198,0.0003326927,0.027379446,0.00041543538,0.00040786198,0.0000888572,0.0004538311,0.016583502,0.6806186,0.0013889085,0.0015315748,0.26938155],"study_design_scores_gemma":[0.00018069024,0.0018262371,0.2052843,0.00006452135,0.00044173826,0.0010025308,0.00014949408,0.1840802,0.59605455,0.002433576,0.00833311,0.00014899323],"about_ca_topic_score_codex":0.0019497548,"about_ca_topic_score_gemma":0.0035966753,"teacher_disagreement_score":0.003932847,"about_ca_system_score_codex":0.0004015034,"about_ca_system_score_gemma":0.0009770287,"threshold_uncertainty_score":0.02079916},"labels":[],"label_agreement":null},{"id":"W2929956211","doi":"10.1186/s13229-019-0261-9","title":"The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in Nrxn2 deletion mice","year":2019,"lang":"en","type":"article","venue":"Molecular Autism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Biotechnology and Biological Sciences Research Council; National Institute of General Medical Sciences; Royal Society; Medical Research Council; Alzheimer's Society; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Orbitofrontal cortex; Neuroscience; Anterior cingulate cortex; Diffusion MRI; Amygdala; Fractional anisotropy; Cortex (anatomy); Posterior cingulate; Psychology; Connectome; Thalamus; Biology; Prefrontal cortex; Medicine; Magnetic resonance imaging; Functional connectivity; Cognition","score_opus":0.013275047935143737,"score_gpt":0.29864701728910575,"score_spread":0.28537196935396203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2929956211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9688737,0.00037851295,0.027314603,0.00021309496,0.000047177527,0.00008483561,0.0014651063,0.00049011165,0.0011329704],"genre_scores_gemma":[0.9138178,0.0010476107,0.073236935,0.00021601007,0.000044745626,0.000555265,0.0020990144,0.0008154592,0.008167114],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995053,0.000054848333,0.00004809849,0.00021482265,0.000113746726,0.00006310283],"domain_scores_gemma":[0.99904126,0.00011320186,0.00047336725,0.00010519101,0.00009285023,0.00017397269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082947535,0.0012382452,0.0006405996,0.0012908556,0.00039658108,0.00053587323,0.0004949063,0.00069038983,0.001848999],"category_scores_gemma":[0.00071343593,0.00065663405,0.000534608,0.0003574043,0.0010557013,0.00047021935,0.0006431488,0.0010934591,0.0003020528],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029378067,0.000061326886,0.0006016226,0.00004094636,0.00003323751,0.0001883035,0.00010622157,0.00031591495,0.9962012,0.00023822483,0.00008949547,0.0018296303],"study_design_scores_gemma":[0.00016380986,0.002385159,0.093967855,0.00010665656,0.00031331103,0.0040955804,0.00028238396,0.010252348,0.88217247,0.001180517,0.0049714795,0.00010835],"about_ca_topic_score_codex":0.002157579,"about_ca_topic_score_gemma":0.0052056573,"teacher_disagreement_score":0.002157579,"about_ca_system_score_codex":0.00034802215,"about_ca_system_score_gemma":0.00036157333,"threshold_uncertainty_score":0.0061855316},"labels":[],"label_agreement":null},{"id":"W2936247364","doi":"10.1093/schbul/sbz019.297","title":"T17. ACUTE CONCEPTUAL DISORGANIZATION IN UNTREATED FIRST-EPISODE PSYCHOSIS: A 7T DTI STUDY OF CINGULUM TRAC","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Precuneus; Psychosis; Psychology; Diffusion MRI; Default mode network; Uncinate fasciculus; Medicine; Cardiology; Neuroscience; Audiology; Radiology; Psychiatry; Magnetic resonance imaging; Functional connectivity; Cognition","score_opus":0.023117003794150978,"score_gpt":0.29998956188496223,"score_spread":0.27687255809081124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936247364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992011,0.0000798368,0.000077198274,0.00003987162,0.0000042211277,0.000013832521,0.00005417371,0.0000022111103,0.0005276131],"genre_scores_gemma":[0.9994443,0.000052663083,0.00008688025,0.000025188892,0.000007946934,0.000008541116,0.00011190916,0.000002770621,0.00025991042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999895,0.000021294712,0.000009290959,0.000026998381,0.000020595031,0.000026803405],"domain_scores_gemma":[0.9997855,0.000033638058,0.00006394001,0.000021820153,0.000026800166,0.00006837399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032765084,0.0003131892,0.00026532362,0.00054288696,0.00086082314,0.00038881393,0.00021528086,0.0003894453,0.0017412921],"category_scores_gemma":[0.00094224914,0.00022490947,0.000179064,0.00047018126,0.0004713172,0.00022851779,0.00039566928,0.00041790536,0.00020031119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009014087,0.0019879134,0.78122026,0.00020762798,0.00021971836,0.06439592,0.005269762,0.00054927316,0.10075767,0.00094159064,0.000815974,0.034620147],"study_design_scores_gemma":[0.00006298728,0.00080721313,0.98945236,0.000008937979,0.000028986682,0.007789197,0.0003192471,0.0003243902,0.00067698275,0.00014441149,0.00037618633,0.000009090965],"about_ca_topic_score_codex":0.009613864,"about_ca_topic_score_gemma":0.008947662,"teacher_disagreement_score":0.009613864,"about_ca_system_score_codex":0.0003842666,"about_ca_system_score_gemma":0.00035775846,"threshold_uncertainty_score":0.019115806},"labels":[],"label_agreement":null},{"id":"W2936261028","doi":"10.1093/schbul/sbz021.225","title":"O7.1. ABNORMAL DEVELOPMENT, FAULTY MATURATION OR ACCELERATED AGING? “WHITE MATTER AT THE CENTER STAGE OF SCHIZOPHRENIA” REVISITED","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Psychology; Neuroimaging; Human Connectome Project; Schizophrenia (object-oriented programming); Nuclear medicine; Medicine; Statistics; Neuroscience; Magnetic resonance imaging; Mathematics; Psychiatry; Radiology; Functional connectivity","score_opus":0.036109064608451945,"score_gpt":0.30834092205080255,"score_spread":0.2722318574423506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936261028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87793815,0.047015734,0.026264135,0.033768598,0.0007941564,0.00011769358,0.0013768326,0.00016389672,0.012560798],"genre_scores_gemma":[0.9688922,0.01612561,0.008812621,0.0030139983,0.0008350034,0.00004512109,0.0006181828,0.00005886454,0.0015983883],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993838,0.00018041719,0.000064552136,0.00016363691,0.00012764464,0.00007989459],"domain_scores_gemma":[0.9985676,0.0004923955,0.00046598047,0.00009301035,0.0002569629,0.00012397375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027308746,0.0004605341,0.0006032027,0.0009608425,0.00048305624,0.0020276322,0.0011142052,0.0012584728,0.0023396125],"category_scores_gemma":[0.0036229384,0.00018824919,0.00055016496,0.0012643732,0.0028046465,0.0027391033,0.0012071817,0.00085174287,0.00035275912],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014680356,0.000107090134,0.55536294,0.0024994796,0.000578195,0.004231958,0.007684804,0.003837169,0.019642577,0.099023424,0.012809191,0.2927552],"study_design_scores_gemma":[0.00009014341,0.0011330502,0.74113625,0.0021497116,0.0005938474,0.0045415917,0.012025984,0.016499422,0.008213164,0.1682942,0.045199562,0.00012304069],"about_ca_topic_score_codex":0.0072707576,"about_ca_topic_score_gemma":0.007773486,"teacher_disagreement_score":0.0072707576,"about_ca_system_score_codex":0.00084005686,"about_ca_system_score_gemma":0.0018045839,"threshold_uncertainty_score":0.014456868},"labels":[],"label_agreement":null},{"id":"W2937654715","doi":"10.1101/614008","title":"The role of diffusion and perivascular spaces in dynamic susceptibility contrast MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"White matter; Diffusion MRI; Contrast (vision); Voxel; Isotropy; Nuclear magnetic resonance; Orientation (vector space); Anisotropy; Physics; Diffusion; Magnetic resonance imaging; Mathematics; Geometry; Medicine; Optics; Radiology","score_opus":0.011591502086148706,"score_gpt":0.25793157756593144,"score_spread":0.24634007547978273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937654715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93968654,0.0012781366,0.05784792,0.00009770046,0.000013001109,0.000024653615,0.00004651953,0.00010642792,0.0008991623],"genre_scores_gemma":[0.9897989,0.00024275694,0.009723763,0.000009645837,0.0000066413954,0.000010650932,0.000014405215,0.000028368377,0.00016487781],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995896,0.00022962411,0.000020646981,0.000043021333,0.00008390898,0.00003322675],"domain_scores_gemma":[0.996552,0.002479767,0.00041324995,0.00023977911,0.00020212658,0.000113026465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011100682,0.00047423615,0.00024687438,0.00032438204,0.0002137846,0.00064647157,0.00021086638,0.00030264573,0.0005019947],"category_scores_gemma":[0.0072176456,0.0002477735,0.00016666215,0.00019664221,0.0005431522,0.0007532075,0.00040090238,0.00023984551,0.00011398622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009002842,0.00008504958,0.013758252,0.00020473923,0.000068786954,0.0004318338,0.00028411899,0.05673445,0.8922008,0.0031080649,0.00009249485,0.032131083],"study_design_scores_gemma":[0.000086421365,0.0009688157,0.06418744,0.00007343367,0.00022333673,0.0016835935,0.000226412,0.266438,0.6566928,0.006729807,0.0025773637,0.00011261445],"about_ca_topic_score_codex":0.0010306824,"about_ca_topic_score_gemma":0.0009776964,"teacher_disagreement_score":0.0011100682,"about_ca_system_score_codex":0.00023061004,"about_ca_system_score_gemma":0.0002876653,"threshold_uncertainty_score":0.0058706403},"labels":[],"label_agreement":null},{"id":"W2939399262","doi":"10.1101/608349","title":"Reducing false positives in tractography with microstructural and anatomical priors","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"False positive paradox; Tractography; Prior probability; Regularization (linguistics); Synthetic data; Pattern recognition (psychology); Convex optimization; Magnetic resonance imaging; False positives and false negatives","score_opus":0.017685054265505165,"score_gpt":0.271381288056013,"score_spread":0.2536962337905079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939399262","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032288805,0.0002490364,0.9662534,0.00032180102,0.00003080324,0.000042581953,0.000052681375,0.0004842124,0.0002767434],"genre_scores_gemma":[0.39174983,0.000257983,0.60586774,0.00022804271,0.00007600877,0.00011639888,0.00032977623,0.0003094488,0.0010646987],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957581,0.0022332028,0.00018184747,0.0004949728,0.0011086855,0.00022310056],"domain_scores_gemma":[0.9660474,0.025529249,0.0022747254,0.0034531238,0.0021560239,0.0005394328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009716742,0.0014904715,0.0015461111,0.0016393126,0.00061107293,0.00178781,0.0019056875,0.0030267024,0.0009932938],"category_scores_gemma":[0.04198691,0.0012140457,0.00090806175,0.0012915578,0.0021790212,0.0024610162,0.0033799536,0.0029463714,0.00038885878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011725009,0.00019189315,0.009128264,0.00042402642,0.0003999576,0.0009510282,0.00049781986,0.74981517,0.03390491,0.03713525,0.0030106201,0.16336861],"study_design_scores_gemma":[0.000025035932,0.000058561294,0.0010429968,0.000016435726,0.000026794036,0.00023332193,0.000021512187,0.9779137,0.007547558,0.012566452,0.0005273589,0.000020340134],"about_ca_topic_score_codex":0.0024066702,"about_ca_topic_score_gemma":0.0027500128,"teacher_disagreement_score":0.009716742,"about_ca_system_score_codex":0.00079481263,"about_ca_system_score_gemma":0.0016501609,"threshold_uncertainty_score":0.051387608},"labels":[],"label_agreement":null},{"id":"W2942142200","doi":"10.1016/j.neuroimage.2019.04.067","title":"Test-retest reliability of Diffusion Tensor Imaging metrics in neonates","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Turun Yliopistosäätiö; Emil Aaltosen Säätiö; Sigrid Juséliuksen Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Alfred Kordelinin Säätiö","keywords":"Diffusion MRI; Reliability (semiconductor); Fractional anisotropy; White matter; Repeatability; Intraclass correlation; Computer science; Pattern recognition (psychology); Artificial intelligence; Mathematics; Psychology; Statistics; Medicine; Reproducibility; Magnetic resonance imaging; Physics; Radiology","score_opus":0.0285276830363727,"score_gpt":0.3201254471056927,"score_spread":0.29159776406932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942142200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953216,0.0009718166,0.0022118085,0.00007142913,0.000102690254,0.000033564764,0.0002758408,0.000055150642,0.00095624325],"genre_scores_gemma":[0.99688053,0.00029833047,0.0017177443,0.00004428864,0.000020020525,0.000077066004,0.0003288405,0.0000431057,0.0005901414],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953236,0.0012649556,0.00073153415,0.0011906289,0.0012233717,0.0002659243],"domain_scores_gemma":[0.9765613,0.012027456,0.0025068722,0.0028774836,0.0054681185,0.0005587044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008715928,0.0005582846,0.0006182695,0.0010674217,0.00047669624,0.001082789,0.0006422312,0.00089430285,0.00052957964],"category_scores_gemma":[0.04972809,0.0004067142,0.0006803572,0.00048774714,0.0009455172,0.0011932355,0.0013297437,0.0009910109,0.00044989533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013027363,0.00018363005,0.9132222,0.00020786928,0.000801802,0.0007194514,0.006009628,0.0013647535,0.015833614,0.0005915171,0.0011154287,0.058647297],"study_design_scores_gemma":[0.000024705481,0.0009340688,0.9809753,0.00010523684,0.00024383925,0.0011925169,0.0012598907,0.0023444537,0.010303473,0.00042408225,0.0021395641,0.00005287302],"about_ca_topic_score_codex":0.0037746064,"about_ca_topic_score_gemma":0.0062587624,"teacher_disagreement_score":0.008715928,"about_ca_system_score_codex":0.0009006724,"about_ca_system_score_gemma":0.00065812893,"threshold_uncertainty_score":0.046094775},"labels":[],"label_agreement":null},{"id":"W2942578351","doi":"10.1002/nbm.4092","title":"The role of iron and myelin in orientation dependent R<sub>2</sub><sup>*</sup> of white matter","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Myelin; White matter; Multiple sclerosis; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Pathology; Internal medicine; Biology; Medicine; Immunology; Central nervous system; Physics","score_opus":0.011263521046215098,"score_gpt":0.2897892733660687,"score_spread":0.2785257523198536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942578351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9440995,0.00062557176,0.05387604,0.000101554986,0.000007800669,0.000013481664,0.00006294841,0.00019213064,0.0010210557],"genre_scores_gemma":[0.9933454,0.00021211077,0.005956364,0.00001565192,0.0000025468075,0.0000079174215,0.00003596121,0.000033505275,0.00039051368],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99993277,0.000020862028,0.0000030587894,0.000014846039,0.000015588546,0.000012826263],"domain_scores_gemma":[0.99977976,0.00009013531,0.00007014037,0.00002333467,0.000022473092,0.000014109904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028715178,0.00045631177,0.00012724817,0.00022925934,0.00014307351,0.00025265216,0.00033105825,0.00041751593,0.000332872],"category_scores_gemma":[0.00084140594,0.00027158437,0.00020747873,0.00012602807,0.0003640519,0.00044983978,0.00020295405,0.0001642816,0.00014352828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005719123,0.000092835704,0.023717893,0.00013894512,0.00006160527,0.0010049576,0.000262301,0.21041901,0.7402921,0.0032848017,0.00030619703,0.019847449],"study_design_scores_gemma":[0.0000139986,0.0001810304,0.023697661,0.000015600504,0.00004836931,0.0009623492,0.00012477007,0.8030726,0.16840014,0.0028179449,0.0006256789,0.000039814877],"about_ca_topic_score_codex":0.003334472,"about_ca_topic_score_gemma":0.0026640655,"teacher_disagreement_score":0.003334472,"about_ca_system_score_codex":0.0003222598,"about_ca_system_score_gemma":0.000281987,"threshold_uncertainty_score":0.0066301227},"labels":[],"label_agreement":null},{"id":"W2942629314","doi":"10.1101/624445","title":"Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; Université de Sherbrooke; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Working memory; Concussion; Tractography; Neuroscience; Neuropathology; Prefrontal cortex; Fractional anisotropy; Diffusion MRI; Psychology; Dorsolateral prefrontal cortex; Anterior cingulate cortex; Medicine; Poison control; Pathology; Cognition; Magnetic resonance imaging; Radiology; Injury prevention","score_opus":0.016228301816442928,"score_gpt":0.24782085475783042,"score_spread":0.23159255294138748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942629314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996153,0.00005711703,0.00013946346,0.000007583013,6.754574e-7,0.0000037084494,0.0000884365,0.000004327574,0.00008341534],"genre_scores_gemma":[0.99941695,0.000050460527,0.0003113698,0.000004693166,0.000001146085,0.000005453303,0.000110013454,0.0000030760314,0.0000967191],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998522,0.000013905386,0.000022995959,0.000044291977,0.000028329514,0.00003821606],"domain_scores_gemma":[0.9989753,0.0001459871,0.00055315153,0.00006492419,0.0001547504,0.00010603471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035448314,0.0004612214,0.000257522,0.001308572,0.00030766183,0.000503154,0.00029106383,0.00044905895,0.0013251626],"category_scores_gemma":[0.0017827885,0.00028387498,0.00026871843,0.0005393673,0.00047327782,0.00040619518,0.0004832259,0.0002830615,0.00024238438],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000792795,0.000019301884,0.9924648,0.000015304691,0.000028032433,0.00028755816,0.00033709584,0.00014069653,0.0042894552,0.000021818567,0.000050924886,0.0022658368],"study_design_scores_gemma":[0.0000017498583,0.000042995962,0.9980907,0.0000069322646,0.000012101494,0.0005431158,0.00026289688,0.0002777372,0.00069740904,0.000017642427,0.00004413837,0.0000025507145],"about_ca_topic_score_codex":0.013480807,"about_ca_topic_score_gemma":0.016671097,"teacher_disagreement_score":0.013480807,"about_ca_system_score_codex":0.00029889165,"about_ca_system_score_gemma":0.00027129037,"threshold_uncertainty_score":0.026804686},"labels":[],"label_agreement":null},{"id":"W2942766429","doi":"10.3390/e21050475","title":"Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Entropy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; F. Hoffmann-La Roche; University of Southern California; Pfizer; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Connectome; Connectomics; Neuroscience; Diffusion MRI; Tractography; Human Connectome Project; Neuroimaging; Receiver operating characteristic; Cortex (anatomy); Functional connectivity; Computer science; Psychology; Medicine; Magnetic resonance imaging; Machine learning","score_opus":0.042057004459428775,"score_gpt":0.3420695597698176,"score_spread":0.30001255531038884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942766429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94354385,0.00041210838,0.054702844,0.00008228478,0.00000587479,0.000018753379,0.00019757437,0.00008279897,0.000953947],"genre_scores_gemma":[0.99338925,0.00015490517,0.006065639,0.0000072033226,0.000015716048,0.000010005078,0.00018952628,0.000009941893,0.00015790256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982363,0.00005668684,0.000016587299,0.000042017513,0.000038095546,0.000022979124],"domain_scores_gemma":[0.9986908,0.0006899994,0.00035102436,0.00010192196,0.00010098905,0.000065415574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007323812,0.00041002923,0.00025528157,0.002825262,0.00022686721,0.0005608067,0.00020692596,0.00028927941,0.00064233673],"category_scores_gemma":[0.0031256373,0.00012332306,0.00027415942,0.00094322604,0.0004680558,0.00078781083,0.00048686273,0.00020183671,0.000089864334],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012601393,0.00024342854,0.51859593,0.00047593363,0.00066433713,0.001476963,0.0017233911,0.09134426,0.123550184,0.01340241,0.0011216224,0.24614134],"study_design_scores_gemma":[0.000021623313,0.0003079499,0.5751345,0.00005813304,0.00020533479,0.0020636315,0.0005775765,0.37999016,0.020315968,0.020081349,0.0011915409,0.000052216277],"about_ca_topic_score_codex":0.0010544665,"about_ca_topic_score_gemma":0.0013483076,"teacher_disagreement_score":0.002825262,"about_ca_system_score_codex":0.00021694269,"about_ca_system_score_gemma":0.00013176892,"threshold_uncertainty_score":0.003873229},"labels":[],"label_agreement":null},{"id":"W2942862165","doi":"10.1371/journal.pone.0215974","title":"Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) in rats at 9.4 Tesla","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Reproducibility; Neurite; Biomedical engineering; Voxel; Nuclear medicine; Region of interest; Orientation (vector space); Coefficient of variation; Nuclear magnetic resonance; Materials science; Chemistry; Medicine; Physics; Chromatography; Mathematics; Radiology","score_opus":0.06374813235442438,"score_gpt":0.31174422065228036,"score_spread":0.24799608829785597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942862165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9624601,0.00073245686,0.035075203,0.00005940371,0.000044371704,0.00007931996,0.0005137753,0.00035460398,0.00068068056],"genre_scores_gemma":[0.9706048,0.00040053003,0.02576865,0.00006407552,0.000021342408,0.0002636797,0.00082633283,0.00022857169,0.0018221778],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988912,0.0001961698,0.000102926235,0.00043492217,0.00026571174,0.00010920879],"domain_scores_gemma":[0.9960155,0.00065553735,0.00092498894,0.0009985971,0.0012206042,0.00018485829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024802373,0.0004791401,0.0004272197,0.0007629174,0.00033477385,0.00042873126,0.0003687592,0.0003874087,0.00064121716],"category_scores_gemma":[0.00403667,0.00038920404,0.00028646353,0.00023758408,0.00060711894,0.0004555139,0.00045414036,0.0005431618,0.0003087187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017161095,0.00013534493,0.016258564,0.00008940465,0.0001337949,0.00011777488,0.0002786016,0.00062244834,0.95746493,0.00012570295,0.00014566354,0.022911647],"study_design_scores_gemma":[0.00007085673,0.00402569,0.19540176,0.000032090258,0.00033676322,0.0007883346,0.00017741244,0.006498526,0.7904129,0.00031473284,0.0018465584,0.000094422816],"about_ca_topic_score_codex":0.0013704292,"about_ca_topic_score_gemma":0.0025302821,"teacher_disagreement_score":0.0024802373,"about_ca_system_score_codex":0.00028976332,"about_ca_system_score_gemma":0.00033763787,"threshold_uncertainty_score":0.013116896},"labels":[],"label_agreement":null},{"id":"W2942962900","doi":"10.1038/s41537-019-0076-x","title":"Impaired illness awareness in schizophrenia and posterior corpus callosal white matter tract integrity","year":2019,"lang":"en","type":"article","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Krembil Foundation; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institutes of Health; Ontario Ministry of Health and Long-Term Care; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; Weston Brain Institute; Consejo Nacional de Ciencia y Tecnología; Government of Canada; Vancouver Coastal Health Research Institute; Centre for Addiction and Mental Health; National Institute of Mental Health; Pfizer; Fondation Brain Canada; National Alliance for Research on Schizophrenia and Depression; Eli Lilly and Company; Ontario Ministry of Research and Innovation; Patient-Centered Outcomes Research Institute","keywords":"Splenium; Corpus callosum; White matter; Psychology; Diffusion MRI; Fractional anisotropy; Disconnection; Schizophrenia (object-oriented programming); Cingulum (brain); Neuroscience; Audiology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.029134793893927573,"score_gpt":0.31299480591915074,"score_spread":0.28386001202522315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942962900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997993,0.000053813143,0.0000315119,0.000006845959,4.414731e-7,0.0000014922741,0.000020165155,0.0000014371959,0.000084880085],"genre_scores_gemma":[0.99980885,0.000034371344,0.000063400366,0.0000030143644,7.322608e-7,0.0000012206459,0.000045883226,8.0609095e-7,0.00004173144],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999912,0.0000138320165,0.000013931492,0.00002121942,0.000020243542,0.000018704153],"domain_scores_gemma":[0.9994173,0.00006360647,0.0003604332,0.000030696483,0.000031310035,0.00009667449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025231324,0.00035244465,0.00018773745,0.0008300305,0.0002894455,0.00034694356,0.000109251894,0.00022849905,0.0010692057],"category_scores_gemma":[0.0010759665,0.00020379253,0.00015517209,0.00027257996,0.00037450434,0.00030588388,0.00036158488,0.00024468265,0.000085137275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009478599,0.00007985868,0.9473837,0.00004965902,0.0001092051,0.0007655737,0.00074881694,0.00020076394,0.0410927,0.00007729901,0.00005982628,0.008484759],"study_design_scores_gemma":[0.0000043505047,0.0000764552,0.9985905,0.0000038411267,0.000011771718,0.00059764396,0.000107548,0.000095980206,0.00044539353,0.000036943937,0.000027065775,0.0000025126471],"about_ca_topic_score_codex":0.005587042,"about_ca_topic_score_gemma":0.011842938,"teacher_disagreement_score":0.005587042,"about_ca_system_score_codex":0.00030812,"about_ca_system_score_gemma":0.00023183227,"threshold_uncertainty_score":0.011109054},"labels":[],"label_agreement":null},{"id":"W2943048304","doi":"10.1109/ichi.2019.8904574","title":"CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Computer science; Artificial intelligence; Discriminator; Stroke (engine); Ground truth; Convolutional neural network; Magnetic resonance imaging; Pattern recognition (psychology); Medicine; Radiology; Physics","score_opus":0.08452751323886673,"score_gpt":0.3879938338791196,"score_spread":0.3034663206402529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943048304","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12931865,0.0005890957,0.86055416,0.00086597906,0.00011646959,0.00009268019,0.00059520244,0.0040834853,0.0037842502],"genre_scores_gemma":[0.8896763,0.00023146422,0.10403136,0.0002922805,0.000053416643,0.000094042305,0.0011023942,0.0002958344,0.0042230426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996941,0.00012120789,0.000011063972,0.000073590025,0.00006086253,0.000039081915],"domain_scores_gemma":[0.9988029,0.0007905035,0.000098154684,0.00015089483,0.00011333017,0.000044229637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000981291,0.001034417,0.00043551408,0.0003846962,0.00022901423,0.0004759246,0.00085320295,0.00092977204,0.0021783519],"category_scores_gemma":[0.0043060025,0.0004416445,0.0006478291,0.00031488104,0.0007988019,0.000627278,0.000950634,0.0015094767,0.00045337217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079011304,0.000017624881,0.00029634597,0.000020332403,0.000022376995,0.00004291942,0.000015290174,0.9827147,0.0022895662,0.0014875648,0.00063206034,0.0123822605],"study_design_scores_gemma":[0.0000023027446,0.00000706181,0.00009157738,0.0000023028585,0.0000025134939,0.0000092533,0.0000012554658,0.99742484,0.0011611598,0.0012067084,0.00008897256,0.0000020760892],"about_ca_topic_score_codex":0.0064151296,"about_ca_topic_score_gemma":0.0061939494,"teacher_disagreement_score":0.0064151296,"about_ca_system_score_codex":0.0009922987,"about_ca_system_score_gemma":0.00059226755,"threshold_uncertainty_score":0.012755573},"labels":[],"label_agreement":null},{"id":"W2943572673","doi":"10.1101/623892","title":"Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Voxel; Diffusion MRI; Segmentation; Computer science; Bundle; Artificial intelligence; Dissection (medical); Magnetic resonance imaging; Radiology; Medicine","score_opus":0.03789750424890323,"score_gpt":0.3128440670341284,"score_spread":0.2749465627852252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943572673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24204251,0.0010128284,0.7266579,0.00035430366,0.000685756,0.0034009402,0.007666956,0.012078333,0.0061003864],"genre_scores_gemma":[0.6612944,0.00021162062,0.31097737,0.0001231932,0.00019696826,0.008640015,0.007079293,0.008475832,0.0030012685],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.85494095,0.09350789,0.016680222,0.01730738,0.016025295,0.001538239],"domain_scores_gemma":[0.61017954,0.22761796,0.036065347,0.07887661,0.044956136,0.0023044122],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.15495765,0.0022039632,0.002200179,0.0044956817,0.0019702427,0.0044499743,0.0028161015,0.0017030694,0.005691493],"category_scores_gemma":[0.29233268,0.0008283052,0.0026646561,0.005510944,0.0026883178,0.002569301,0.004517594,0.0017232881,0.002699195],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0110301245,0.0006875086,0.38002485,0.004064049,0.013766942,0.0011196507,0.012065267,0.0368974,0.038732,0.013210044,0.045797173,0.44260502],"study_design_scores_gemma":[0.0014564317,0.004336802,0.5535016,0.0007252927,0.0027753734,0.0034692483,0.0025854092,0.28111672,0.07749621,0.026182415,0.04526848,0.0010859463],"about_ca_topic_score_codex":0.0024315536,"about_ca_topic_score_gemma":0.003182075,"teacher_disagreement_score":0.84504235,"about_ca_system_score_codex":0.0014492735,"about_ca_system_score_gemma":0.0023999196,"threshold_uncertainty_score":0.8195042},"labels":[],"label_agreement":null},{"id":"W2944031440","doi":"10.1101/620419","title":"Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institutes of Health","keywords":"Cingulum (brain); White matter; Univariate; Grey matter; Corpus callosum; Fornix; Fractional anisotropy; Psychology; Neuroscience; Brain size; Anatomy; Multivariate statistics; Biology; Medicine; Mathematics; Magnetic resonance imaging; Hippocampus","score_opus":0.02039391204576375,"score_gpt":0.2898791029104136,"score_spread":0.26948519086464984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944031440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92569304,0.0004508759,0.07163767,0.00012873525,0.000015751964,0.000078303725,0.0011199896,0.0003618877,0.00051383727],"genre_scores_gemma":[0.9878726,0.000089359084,0.010997132,0.000014634832,0.000013061428,0.00006476006,0.00046062577,0.00003743938,0.0004503349],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992236,0.00032912655,0.00004805926,0.00022762822,0.00013323188,0.000038439783],"domain_scores_gemma":[0.9985091,0.00064181944,0.00027240152,0.00031183966,0.00021220965,0.00005269008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026305842,0.0006118454,0.00056134147,0.0008315932,0.00020117003,0.00039921977,0.0003891924,0.00025901743,0.0012691577],"category_scores_gemma":[0.0044409316,0.0002786206,0.0007290342,0.00090599107,0.0004322279,0.00032394196,0.00039783173,0.00028603125,0.00029445952],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013336812,0.00018172224,0.7997675,0.0002622091,0.0030207755,0.00050566084,0.00053861825,0.03104077,0.029795665,0.0017040727,0.002881496,0.12896793],"study_design_scores_gemma":[0.00002310721,0.0004382004,0.86976314,0.000011930836,0.00031916043,0.0003936643,0.000101915,0.122521386,0.003552957,0.001874855,0.00096647243,0.000033262895],"about_ca_topic_score_codex":0.0048135133,"about_ca_topic_score_gemma":0.004296039,"teacher_disagreement_score":0.0048135133,"about_ca_system_score_codex":0.00019288185,"about_ca_system_score_gemma":0.00067659974,"threshold_uncertainty_score":0.013912082},"labels":[],"label_agreement":null},{"id":"W2944052887","doi":"10.1007/s00429-019-01864-2","title":"Diffusion weighted imaging evidence of extra-callosal pathways for interhemispheric communication after complete commissurotomy","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institute for Advanced Research; University of Miami","keywords":"Corpus callosum; Commissurotomy; White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Psychology; Tractography; Commissure; Cognition; Magnetic resonance imaging; Medicine; Cardiology; Radiology","score_opus":0.040573470213786086,"score_gpt":0.3049478365474945,"score_spread":0.2643743663337084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944052887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803908,0.0016632027,0.0043046223,0.0007193433,0.0001360442,0.00012285657,0.00027601558,0.00016553221,0.012221526],"genre_scores_gemma":[0.99739707,0.00030831172,0.00053026417,0.00011666223,0.00006663767,0.00003548109,0.00018636652,0.000016032729,0.0013432275],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.9997873,0.000021126198,0.00001949242,0.00003696303,0.00005280147,0.00008225295],"domain_scores_gemma":[0.99818146,0.0006905577,0.00038055092,0.00036419203,0.0001946632,0.00018861178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030118984,0.0005155494,0.000502775,0.0014584409,0.0007941797,0.00044200016,0.00091501896,0.0015343013,0.0061184624],"category_scores_gemma":[0.0020109105,0.00030557084,0.0005109729,0.00085261423,0.0021516657,0.001209471,0.0004884262,0.002779492,0.0007741023],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016434072,0.001895553,0.04653214,0.00055899273,0.0006482104,0.65244746,0.0008527467,0.0022009697,0.19824825,0.0028142964,0.0016857372,0.07568161],"study_design_scores_gemma":[0.0009464006,0.0070008803,0.37109917,0.00017003584,0.00072803337,0.4104052,0.0009846773,0.004132987,0.1915788,0.0038884382,0.008897953,0.0001673818],"about_ca_topic_score_codex":0.003311722,"about_ca_topic_score_gemma":0.00473799,"teacher_disagreement_score":0.0061184624,"about_ca_system_score_codex":0.00060075964,"about_ca_system_score_gemma":0.0010966924,"threshold_uncertainty_score":0.020468354},"labels":[],"label_agreement":null},{"id":"W2944068640","doi":"10.1007/s12264-019-00381-w","title":"White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging","year":2019,"lang":"en","type":"article","venue":"Neuroscience Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Neurocognitive; Major depressive disorder; Psychology; Subgroup analysis; Depression (economics); Medicine; Internal medicine; Oncology; Psychiatry; Magnetic resonance imaging; Neuroscience; Cognition; Radiology; Meta-analysis","score_opus":0.016822475210303944,"score_gpt":0.2899825822187401,"score_spread":0.2731601070084362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944068640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984781,0.00029805602,0.00014718206,0.00009043788,0.000008175186,0.000009099151,0.00012896556,0.00000384131,0.0008359958],"genre_scores_gemma":[0.9990957,0.00021492434,0.00018641687,0.000033628443,0.000014773469,0.0000041427347,0.00014612533,0.00000320614,0.0003010735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999224,0.000010820169,0.000015456193,0.000018290208,0.000014144092,0.000018762841],"domain_scores_gemma":[0.9997435,0.0000407938,0.00012664603,0.000016122594,0.00003439552,0.000038455823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022830653,0.00034669257,0.00018303904,0.0008839466,0.00029831604,0.00043623958,0.00026094937,0.00032522774,0.0015575353],"category_scores_gemma":[0.0009795186,0.00019955095,0.00019402233,0.00043642137,0.0003950954,0.0003817076,0.00034718608,0.0003277586,0.00027137212],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030994571,0.00018470483,0.8762497,0.00008971943,0.0002274887,0.016731253,0.00062679936,0.00035669925,0.07659649,0.0005899418,0.0007991375,0.024448618],"study_design_scores_gemma":[0.000019185325,0.00009950325,0.99143046,0.000012870288,0.00003652813,0.0061346535,0.00021789315,0.0004083397,0.001098943,0.00035941435,0.00017654749,0.0000055910905],"about_ca_topic_score_codex":0.0037246908,"about_ca_topic_score_gemma":0.0053198324,"teacher_disagreement_score":0.0037246908,"about_ca_system_score_codex":0.00028268527,"about_ca_system_score_gemma":0.0001737478,"threshold_uncertainty_score":0.007406056},"labels":[],"label_agreement":null},{"id":"W2944274429","doi":"10.1101/631952","title":"TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow &amp; Singularity","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Pipeline (software); Diffusion MRI; Tractography; Fractional anisotropy; Orientation (vector space); Artificial intelligence; Image processing; Computation; Data mining; Pattern recognition (psychology); Image (mathematics); Algorithm; Mathematics","score_opus":0.05343977480373192,"score_gpt":0.28627855693465654,"score_spread":0.23283878213092463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944274429","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005666355,0.00032716265,0.7987159,0.00023555846,0.0001206095,0.00033195934,0.002411408,0.19021499,0.0019760649],"genre_scores_gemma":[0.069065206,0.00037376647,0.8810378,0.00032972888,0.0000949438,0.0009065966,0.016096644,0.025470607,0.0066246833],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990845,0.00010467817,0.00009205119,0.00024647661,0.000353174,0.00011920401],"domain_scores_gemma":[0.99888736,0.0002555408,0.000111173635,0.00031673355,0.0002885531,0.00014066926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017736196,0.00179399,0.0010596107,0.0014365681,0.0007531479,0.002292907,0.0032895117,0.001047657,0.02589379],"category_scores_gemma":[0.005620575,0.0012735558,0.0012665072,0.0009838851,0.0006873574,0.0026586398,0.003366443,0.0016853678,0.013540121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016486684,0.00019994963,0.0024711958,0.00083482714,0.0002870801,0.0007780688,0.0005695313,0.024439344,0.08522999,0.016309833,0.19717865,0.6700529],"study_design_scores_gemma":[0.0004939098,0.0003353002,0.0023311656,0.0001603222,0.00008175801,0.0006753954,0.00008557777,0.6862278,0.13017967,0.03285788,0.14621875,0.00035239436],"about_ca_topic_score_codex":0.003930102,"about_ca_topic_score_gemma":0.003238122,"teacher_disagreement_score":0.02589379,"about_ca_system_score_codex":0.00086086825,"about_ca_system_score_gemma":0.0020155455,"threshold_uncertainty_score":0.08662331},"labels":[],"label_agreement":null},{"id":"W2944454351","doi":"10.1016/j.nicl.2019.101855","title":"White matter microstructural differences identified using multi-shell diffusion imaging in six-year-old children born very preterm","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; University of Toronto; Mental Health Research Canada; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Shell (structure); Diffusion imaging; Diffusion; Medicine; Psychology; Magnetic resonance imaging; Physics; Materials science; Radiology","score_opus":0.07307813547691652,"score_gpt":0.3862503993791584,"score_spread":0.31317226390224184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944454351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996984,0.00008227819,0.00006153549,0.000008846919,0.00000173313,0.0000035155797,0.000083665436,0.0000027587155,0.000057360332],"genre_scores_gemma":[0.99929726,0.00014283042,0.00029723253,0.000007439986,0.000002112812,0.0000106276,0.00014571585,0.0000021800586,0.00009452676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997764,0.000023608214,0.000034146855,0.00006361987,0.00005934379,0.0000428037],"domain_scores_gemma":[0.9990115,0.00013069736,0.0004891549,0.00005336298,0.00014691197,0.0001683153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005962143,0.00044742657,0.00049423025,0.0013832636,0.00041290122,0.0006426916,0.0003418167,0.000499298,0.0007785785],"category_scores_gemma":[0.0019232358,0.00030467805,0.00048395744,0.0005262874,0.0005874044,0.00046031224,0.00070915115,0.000482855,0.00016577364],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005462939,0.00009989123,0.9728607,0.00009627595,0.00011235186,0.0035155916,0.001974683,0.00016165005,0.013533205,0.000061661405,0.00010345119,0.0069342456],"study_design_scores_gemma":[0.0000025067288,0.00013214436,0.99673826,0.000008037589,0.000021033487,0.0018666539,0.0004214739,0.000057706362,0.00066893554,0.000019695486,0.0000589631,0.000004651676],"about_ca_topic_score_codex":0.006571268,"about_ca_topic_score_gemma":0.005666377,"teacher_disagreement_score":0.006571268,"about_ca_system_score_codex":0.0003794766,"about_ca_system_score_gemma":0.0003175324,"threshold_uncertainty_score":0.013066053},"labels":[],"label_agreement":null},{"id":"W2944551460","doi":"10.1101/624171","title":"Early childhood development of white matter fiber density and morphology","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates; National Imaging Facility; Australian Government","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Corticospinal tract; Brain development; Tractography; Fiber bundle; Anatomy; Fiber; Biology; Neuroscience; Psychology; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.02070771686353873,"score_gpt":0.2536076822523065,"score_spread":0.23289996538876778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944551460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962894,0.00026727255,0.0018963635,0.000028103263,0.0000030857755,0.0000062666377,0.0009408756,0.000045396155,0.00052330014],"genre_scores_gemma":[0.9963258,0.00023941626,0.0026218635,0.000008454412,0.000002334341,0.0000111836025,0.00040902148,0.000019966916,0.00036183817],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997557,0.00003807287,0.000016698861,0.00008704327,0.00006517468,0.000037372603],"domain_scores_gemma":[0.9991117,0.00013843748,0.0004640603,0.00007235065,0.00015108797,0.00006229567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061544636,0.0002649505,0.00021251176,0.0008946586,0.00025333915,0.00061698275,0.00020066694,0.00021582695,0.0015578453],"category_scores_gemma":[0.0015443565,0.00020188982,0.00023588087,0.00048538548,0.00032524476,0.00035166045,0.00034247135,0.00025527863,0.00023273674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014786166,0.000021484924,0.961119,0.000055678152,0.00009288833,0.00021015039,0.00038329762,0.00046263586,0.022310806,0.00023409854,0.00023938074,0.014722847],"study_design_scores_gemma":[5.957793e-7,0.000022795655,0.9973091,0.000007987396,0.0000084161375,0.0002094557,0.00007392572,0.00019950487,0.0019412644,0.00005048383,0.00017434229,0.0000022615466],"about_ca_topic_score_codex":0.012022996,"about_ca_topic_score_gemma":0.0140279345,"teacher_disagreement_score":0.012022996,"about_ca_system_score_codex":0.000463415,"about_ca_system_score_gemma":0.00042811292,"threshold_uncertainty_score":0.023906052},"labels":[],"label_agreement":null},{"id":"W2944724695","doi":"10.1136/bcr-2018-228971","title":"Spatial reorganisation of the somatosensory cortex in a patient with a low-grade glioma","year":2019,"lang":"en","type":"article","venue":"BMJ Case Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; St. Michael's Hospital","funders":"Canadian Cancer Society Research Institute","keywords":"Somatosensory system; Glioma; Neuroplasticity; Psychology; Neuroscience; Dissociation (chemistry); Medicine; Sensation","score_opus":0.022743683206585312,"score_gpt":0.3112501977776423,"score_spread":0.28850651457105697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944724695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877401,0.0011335218,0.0011401211,0.0026793152,0.00014959899,0.000068058085,0.00016732639,0.000098876146,0.0068229944],"genre_scores_gemma":[0.99826694,0.0003179445,0.00038572264,0.00035160276,0.00012437251,0.000006065517,0.000041174186,0.000010070499,0.0004961189],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.999778,0.0000192306,0.000022150292,0.00004519478,0.000043986467,0.00009147821],"domain_scores_gemma":[0.99912065,0.00028000295,0.00015890994,0.000056901677,0.00006444546,0.00031908587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001997899,0.0009280236,0.0007538487,0.0018725198,0.0012743524,0.0008109493,0.0008364051,0.0027755045,0.0014875812],"category_scores_gemma":[0.0023195238,0.0004725827,0.0005802507,0.0010898696,0.0012268026,0.0009917355,0.0007407463,0.0022043756,0.00050023955],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035056244,0.000017928147,0.0041556344,0.000017595392,0.0000036369825,0.99365604,0.00016310826,0.00005009345,0.0010084334,0.00007236525,0.00009476305,0.0007253882],"study_design_scores_gemma":[0.0000057292527,0.00009952389,0.0070771226,0.000008688905,0.000008499462,0.99158406,0.00012352588,0.00023750524,0.0005233358,0.00012663455,0.00019511605,0.0000102719005],"about_ca_topic_score_codex":0.0037741994,"about_ca_topic_score_gemma":0.0054853866,"teacher_disagreement_score":0.0037741994,"about_ca_system_score_codex":0.0012009975,"about_ca_system_score_gemma":0.0007377076,"threshold_uncertainty_score":0.008713961},"labels":[],"label_agreement":null},{"id":"W2944868864","doi":"10.1016/j.neuroimage.2019.05.042","title":"The influence of brain iron on myelin water imaging","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Austrian Science Fund; National Multiple Sclerosis Society","keywords":"Myelin; Neuroscience; Chemistry; Psychology","score_opus":0.020942089022172292,"score_gpt":0.3187720889944748,"score_spread":0.2978299999723025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944868864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9391625,0.019176245,0.026882866,0.00088071584,0.00017070117,0.000052328218,0.00016631094,0.00018700946,0.01332121],"genre_scores_gemma":[0.9892281,0.0031323906,0.0047935266,0.00016635763,0.00013422138,0.000013885093,0.000070531125,0.00020629317,0.0022547406],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996325,0.00017978149,0.000012057171,0.00005142134,0.00008028709,0.00004392256],"domain_scores_gemma":[0.99725753,0.002081056,0.00026110047,0.00010889675,0.00018955307,0.000102010854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001188618,0.0003831566,0.00025467988,0.0006001633,0.00035656488,0.00071887084,0.00038261293,0.0005883236,0.0018212021],"category_scores_gemma":[0.0067611476,0.000261912,0.00018792067,0.0002469928,0.00071080757,0.0006916002,0.00030905116,0.0004547696,0.0003037679],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006206002,0.00015600049,0.017157601,0.0005600515,0.00033020234,0.0028123304,0.0005655702,0.0028986994,0.8495558,0.0025871035,0.0013818664,0.115788884],"study_design_scores_gemma":[0.00012876875,0.0016733818,0.11644043,0.00015295969,0.000724078,0.0057696556,0.00032232923,0.01846888,0.84530807,0.003669055,0.0072860923,0.00005631357],"about_ca_topic_score_codex":0.0022508565,"about_ca_topic_score_gemma":0.00279092,"teacher_disagreement_score":0.0022508565,"about_ca_system_score_codex":0.00029160545,"about_ca_system_score_gemma":0.00036283024,"threshold_uncertainty_score":0.0062860847},"labels":[],"label_agreement":null},{"id":"W2944934343","doi":"10.1007/978-3-030-20351-1_14","title":"Minimizing Non-holonomicity: Finding Sheets in Fibrous Structures","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Computer science; Algorithm; Contraction (grammar); Field (mathematics); Exploit; Measure (data warehouse); Human heart; Theoretical computer science; Mathematics; Data mining; Pure mathematics","score_opus":0.049636773734566174,"score_gpt":0.32846047506756243,"score_spread":0.2788237013329963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944934343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05040692,0.00061991514,0.94479424,0.00019298922,0.00006506281,0.000031006934,0.000086527696,0.00031332774,0.003489984],"genre_scores_gemma":[0.22947606,0.0010939066,0.75772244,0.000071426904,0.00013952285,0.00006938664,0.00034359543,0.00039045533,0.010693188],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998325,0.000042184187,0.0000094731895,0.000041712214,0.000060056314,0.000014067265],"domain_scores_gemma":[0.99921083,0.00045361416,0.00009969205,0.000081803075,0.00008349274,0.00007046622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005038069,0.0010233778,0.00086272944,0.00094098784,0.00041943093,0.0012237437,0.0011277571,0.0010699879,0.0021066281],"category_scores_gemma":[0.0021046004,0.0006633261,0.00055452564,0.0006539174,0.00082362466,0.0017215892,0.0012593481,0.0010284631,0.00057859556],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039714458,0.00014987608,0.0019156147,0.0011549667,0.00011784838,0.0007036613,0.0009607014,0.24160796,0.070718005,0.1368973,0.013749139,0.53162783],"study_design_scores_gemma":[0.000023273353,0.00020116154,0.0010040789,0.000078557976,0.000039384675,0.0005845073,0.00028367553,0.73040676,0.013098649,0.24663882,0.0075984974,0.000042569718],"about_ca_topic_score_codex":0.00041678624,"about_ca_topic_score_gemma":0.0006441487,"teacher_disagreement_score":0.0021066281,"about_ca_system_score_codex":0.0002114073,"about_ca_system_score_gemma":0.0003348639,"threshold_uncertainty_score":0.007047415},"labels":[],"label_agreement":null},{"id":"W2946033723","doi":"10.1002/hbm.24622","title":"The efficiency of the brain connectome is associated with cerebrovascular reactivity in persons with white matter hyperintensities","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"White matter; Hyperintensity; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Connectomics; Psychology; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.031500696721701804,"score_gpt":0.27386803603567733,"score_spread":0.24236733931397553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946033723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99931514,0.000094543786,0.00024090873,0.00002410794,0.0000018433561,0.0000051234865,0.000045495133,0.000003789954,0.0002691556],"genre_scores_gemma":[0.999561,0.00005014755,0.00021438743,0.000008182843,0.00000707348,0.0000040882214,0.000075867356,0.0000020738853,0.000077158715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973255,0.000075338845,0.000035787227,0.000077938574,0.00004401762,0.000034395212],"domain_scores_gemma":[0.99739,0.00066328427,0.0014331749,0.0001804922,0.00018524831,0.0001478415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071107683,0.00040951438,0.0002822272,0.00096019683,0.00032539424,0.00050758116,0.00021851296,0.0005128268,0.0011587584],"category_scores_gemma":[0.0043474813,0.00023536461,0.0003207802,0.0005241043,0.000309952,0.00043753206,0.00040805945,0.00044358135,0.00014206712],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024184237,0.00007192497,0.9916338,0.000025030948,0.00018952705,0.00023897264,0.00022760409,0.00036833415,0.0028201258,0.00007852011,0.00005914243,0.004045207],"study_design_scores_gemma":[0.0000016928245,0.000046083744,0.99917835,0.0000029704586,0.000019498355,0.00021138445,0.00006657751,0.00025115648,0.00013543475,0.0000553879,0.000028600927,0.00000285046],"about_ca_topic_score_codex":0.0015008978,"about_ca_topic_score_gemma":0.0022845904,"teacher_disagreement_score":0.0015008978,"about_ca_system_score_codex":0.00013074225,"about_ca_system_score_gemma":0.000093649316,"threshold_uncertainty_score":0.003876388},"labels":[],"label_agreement":null},{"id":"W2946440603","doi":"10.1016/j.neuroimage.2019.05.003","title":"Combining white matter diffusion and geometry for tract-specific alignment and variability analysis","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministry of Defense; Israel Science Foundation","keywords":"Diffusion MRI; Human Connectome Project; Tractography; Voxel; White matter; Fiber tract; Artificial intelligence; Computer science; Fractional anisotropy; Fiber bundle; Diffusion; Pattern recognition (psychology); Fiber; Mathematics; Physics; Magnetic resonance imaging; Neuroscience; Psychology; Chemistry; Medicine; Functional connectivity","score_opus":0.031622683434222795,"score_gpt":0.310384717275131,"score_spread":0.2787620338409082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946440603","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008657644,0.00017156919,0.98829484,0.000078645,0.000030401563,0.000042476764,0.00034904134,0.002096645,0.00027864505],"genre_scores_gemma":[0.17937866,0.00062445697,0.81442,0.000084795036,0.00012362232,0.0001934842,0.0017881765,0.0020697643,0.0013170728],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907935,0.00021658106,0.00007608215,0.0003239011,0.00022942263,0.000074717325],"domain_scores_gemma":[0.99810094,0.00059454475,0.00038687207,0.0004142172,0.00040360406,0.00009988396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002073061,0.0016257656,0.0014824147,0.0034528933,0.00071830285,0.0023393943,0.0010882393,0.0014770594,0.0020720134],"category_scores_gemma":[0.007606608,0.0009306649,0.0021541284,0.0042406265,0.0005540332,0.001733868,0.0017679823,0.0019322276,0.002191887],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041797632,0.00019650134,0.0110234935,0.00041591437,0.0010784686,0.00043168684,0.00036129533,0.13384844,0.1308627,0.011566138,0.008074865,0.7017225],"study_design_scores_gemma":[0.000035396868,0.00011426598,0.011568996,0.000040312156,0.00028472135,0.0009626434,0.00012012329,0.9156925,0.0393577,0.024244929,0.0074371104,0.00014120762],"about_ca_topic_score_codex":0.005572675,"about_ca_topic_score_gemma":0.011258879,"teacher_disagreement_score":0.005572675,"about_ca_system_score_codex":0.00050263316,"about_ca_system_score_gemma":0.002595001,"threshold_uncertainty_score":0.011080503},"labels":[],"label_agreement":null},{"id":"W2946716788","doi":"10.1016/j.neurobiolaging.2019.05.005","title":"Synergism between fornix microstructure and beta amyloid accelerates memory decline in clinically normal older adults","year":2019,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council; National Institute on Aging; National Institutes of Health; Canadian Institutes of Health Research; Biogen","keywords":"Fornix; Episodic memory; Cognitive decline; Medicine; Hippocampus; Psychology; Cognition; Neuroscience; Internal medicine; Dementia; Disease","score_opus":0.023823285753759707,"score_gpt":0.3256395321655264,"score_spread":0.3018162464117667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946716788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99871397,0.00069356844,0.000090732254,0.000058209585,0.000009668826,0.000006276284,0.00008322876,0.000007961327,0.00033643868],"genre_scores_gemma":[0.99923086,0.00023323784,0.0001397743,0.00003200569,0.000030689294,0.000004695856,0.00007632983,0.000002662245,0.00024965464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999051,0.000017776842,0.000012677109,0.000031626092,0.000019842018,0.000013063667],"domain_scores_gemma":[0.99939847,0.00006201157,0.00036645756,0.00004863706,0.00006876662,0.000055629025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037029712,0.000687457,0.0006035046,0.0006580602,0.00027773503,0.00060329726,0.0002967952,0.0006758348,0.0011266619],"category_scores_gemma":[0.0012240246,0.00034964105,0.00021277169,0.00044903497,0.00032665554,0.0006005132,0.00031282572,0.00039027855,0.00016981928],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003857204,0.00028949327,0.9619644,0.00010517359,0.000423101,0.0020228631,0.0003456909,0.00015135063,0.017282724,0.00010004582,0.00033761875,0.013120172],"study_design_scores_gemma":[0.000010768069,0.00024660173,0.99804735,0.0000063745724,0.00006739948,0.00083327276,0.00008420204,0.00013435111,0.0003491727,0.00015563346,0.000061028888,0.0000037732666],"about_ca_topic_score_codex":0.0021492152,"about_ca_topic_score_gemma":0.004096282,"teacher_disagreement_score":0.0021492152,"about_ca_system_score_codex":0.00019092181,"about_ca_system_score_gemma":0.0002063538,"threshold_uncertainty_score":0.0042734146},"labels":[],"label_agreement":null},{"id":"W2947056593","doi":"10.1016/j.dadm.2019.03.002","title":"Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Alzheimer's Disease Research Center, Emory University; Servier; Pfizer; BioClinica; Biogen; Eli Lilly and Company; U.S. Department of Defense; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Roche; Merck; Alzheimer's Drug Discovery Foundation; Takeda Pharmaceutical Company; AbbVie; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Perivascular space; Magnetic resonance imaging; Interstitial fluid; Diffusion MRI; Pathology; Parenchyma; Cognitive decline; Hyperintensity; Cerebrospinal fluid; Thermal diffusivity; Pathological; Pathophysiology; Medicine; Disease; Dementia; Radiology; Physics","score_opus":0.08263600615335222,"score_gpt":0.3967723127486974,"score_spread":0.3141363065953452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947056593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99772316,0.0007249375,0.0010179201,0.00004286801,0.0000039316124,0.000008661463,0.00010093712,0.00002733998,0.00035028614],"genre_scores_gemma":[0.99846953,0.00019919354,0.0010857764,0.000008331381,0.000008610007,0.0000045560164,0.00007643938,0.0000060980365,0.00014157896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990976,0.000018909255,0.000011364922,0.000027032738,0.000022435539,0.000010588757],"domain_scores_gemma":[0.9993839,0.00011370104,0.00034853572,0.0000423786,0.00006253042,0.00004886449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053883775,0.00042834214,0.0003102953,0.0011014978,0.00019770593,0.0005080337,0.00023671266,0.00025348944,0.0010063229],"category_scores_gemma":[0.0013646146,0.00015182108,0.00012893099,0.00041710437,0.00033459425,0.00050065905,0.00038055182,0.00023332107,0.00015207985],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024104563,0.00019574782,0.7944973,0.0003180942,0.00019940901,0.0020474743,0.0005873849,0.0006865765,0.15368623,0.0002997646,0.00041464122,0.044656854],"study_design_scores_gemma":[0.000017582197,0.00024283421,0.96778685,0.000037778904,0.00009747076,0.0048117507,0.00019017678,0.0020137108,0.0233759,0.00068566325,0.0007236483,0.000016815398],"about_ca_topic_score_codex":0.0009538598,"about_ca_topic_score_gemma":0.0013003071,"teacher_disagreement_score":0.0011014978,"about_ca_system_score_codex":0.00017477,"about_ca_system_score_gemma":0.00023208327,"threshold_uncertainty_score":0.00336653},"labels":[],"label_agreement":null},{"id":"W2947357678","doi":"10.1016/j.nicl.2019.101883","title":"Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London Hospitals NHS Foundation Trust; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; University College London; Wellcome Trust","keywords":"Computer science; Segmentation; Tractography; Artificial intelligence; White matter; Diffusion MRI; Surgical planning; Pipeline (software); Task (project management); Perspective (graphical); Machine learning; Natural language processing; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.10703746224582505,"score_gpt":0.4296475374320574,"score_spread":0.32261007518623236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947357678","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2994994,0.0012516447,0.6912322,0.00026049736,0.00012996209,0.0006057946,0.0006362841,0.004293605,0.0020906224],"genre_scores_gemma":[0.66019976,0.00036046002,0.3348525,0.00014078202,0.000058008045,0.00047505344,0.001636001,0.0013505571,0.0009268665],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9897453,0.0054159677,0.0008206602,0.0017797183,0.0018768759,0.00036133267],"domain_scores_gemma":[0.96531725,0.019692674,0.003075072,0.0068006334,0.0046445113,0.00046981836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015296548,0.0020591582,0.0010027407,0.0024671087,0.0010578431,0.0020209278,0.00147828,0.0017034861,0.0030893525],"category_scores_gemma":[0.05063479,0.00073564996,0.0011996232,0.0009777602,0.0014165632,0.0015336047,0.002627171,0.0011297,0.001466029],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020768696,0.0007067099,0.036242526,0.00169405,0.0011310433,0.0009093602,0.003105954,0.15227205,0.13296384,0.002917174,0.004970171,0.66101027],"study_design_scores_gemma":[0.0002638223,0.0012897665,0.05827833,0.0006421927,0.00035897284,0.0024443767,0.0007687122,0.7634517,0.15339933,0.009094655,0.009659008,0.0003491483],"about_ca_topic_score_codex":0.002826978,"about_ca_topic_score_gemma":0.0050632595,"teacher_disagreement_score":0.015296548,"about_ca_system_score_codex":0.0007088147,"about_ca_system_score_gemma":0.0020999839,"threshold_uncertainty_score":0.080896854},"labels":[],"label_agreement":null},{"id":"W2947735528","doi":"10.1002/jmri.26807","title":"Increasing body mass index in an elderly cohort: Effects on the quantitative MR parameters of the brain","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Universität Duisburg-Essen","keywords":"Body mass index; Medicine; White matter; Nuclear medicine; Voxel-based morphometry; Bayesian multivariate linear regression; Magnetic resonance imaging; Internal medicine; Cardiology; Linear regression; Radiology; Statistics; Mathematics","score_opus":0.022895981403102793,"score_gpt":0.3249197381238344,"score_spread":0.3020237567207316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947735528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992544,0.000302668,0.00007702118,0.00003389561,0.000007718018,0.0000029483679,0.00014421393,0.000004264999,0.00017286949],"genre_scores_gemma":[0.9994697,0.000113061666,0.00007856741,0.00002502778,0.000013868976,0.000004456562,0.00012709429,0.000002724265,0.00016557987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988604,0.00002847159,0.0000073833726,0.000038521324,0.00001647509,0.000023089033],"domain_scores_gemma":[0.99948514,0.00009142498,0.00016341735,0.00006415728,0.00005934795,0.0001364332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003931513,0.00034068697,0.00027629643,0.0003794972,0.0002523195,0.00032801495,0.00014350638,0.00044914414,0.0012707931],"category_scores_gemma":[0.0009698749,0.0001687467,0.000347219,0.00031428452,0.00019799305,0.00022067576,0.00022487408,0.00038336797,0.00019995627],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021583447,0.00008258278,0.99078006,0.0000131414745,0.00019455703,0.000222792,0.000077148106,0.00006106347,0.0034814507,0.000015139685,0.00013976685,0.0027738975],"study_design_scores_gemma":[0.0000055028872,0.00011503283,0.99954,0.0000013380793,0.00003508129,0.000106734005,0.000024062596,0.000050810097,0.00006617154,0.0000095697405,0.000044424964,0.000001282332],"about_ca_topic_score_codex":0.0027018853,"about_ca_topic_score_gemma":0.0024602916,"teacher_disagreement_score":0.0027018853,"about_ca_system_score_codex":0.00008789841,"about_ca_system_score_gemma":0.00012419658,"threshold_uncertainty_score":0.005372286},"labels":[],"label_agreement":null},{"id":"W2948371953","doi":"10.3389/fnagi.2019.00134","title":"Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson’s Disease","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Siemens Healthineers; Ministero della Salute; University of Southern California","keywords":"Fractional anisotropy; Putamen; Cerebral blood flow; Basal ganglia; Diffusion MRI; Caudate nucleus; Subthalamic nucleus; Medicine; Parkinson's disease; Nuclear medicine; Cardiology; Internal medicine; Pathology; Psychology; Magnetic resonance imaging; Radiology; Deep brain stimulation; Central nervous system; Disease","score_opus":0.021040234148796445,"score_gpt":0.29554198216451116,"score_spread":0.2745017480157147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948371953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992893,0.0004010899,0.00013893392,0.000007965754,0.0000014143571,0.000004668142,0.00003058736,0.0000032201656,0.00012276307],"genre_scores_gemma":[0.9991899,0.0001718219,0.00043078532,0.0000065885733,0.000004909982,0.0000064590686,0.00007569944,0.0000011644394,0.00011268044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997315,0.000059712394,0.000036488473,0.00006967504,0.0000694903,0.000033168395],"domain_scores_gemma":[0.9993693,0.00011827454,0.0002473479,0.000032156746,0.00010656995,0.00012634354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074732513,0.00056394265,0.00070478034,0.0015876641,0.0003049248,0.00048811786,0.00019970267,0.00042321536,0.0005447595],"category_scores_gemma":[0.0013663085,0.0003011077,0.00019244206,0.0004628667,0.00027240955,0.00040094653,0.0004765522,0.00036060344,0.00011145502],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029955045,0.00020715107,0.9217838,0.00013873195,0.00039017023,0.0011395841,0.0006549232,0.00031750216,0.047414377,0.000028995308,0.00010624528,0.024822999],"study_design_scores_gemma":[0.0000234904,0.00041778616,0.9967349,0.000008068536,0.00008136842,0.00079316023,0.00012207683,0.0003619022,0.0013312661,0.0000324774,0.00008499019,0.0000085305455],"about_ca_topic_score_codex":0.002201973,"about_ca_topic_score_gemma":0.0058160457,"teacher_disagreement_score":0.002201973,"about_ca_system_score_codex":0.00025722486,"about_ca_system_score_gemma":0.00014297942,"threshold_uncertainty_score":0.004378319},"labels":[],"label_agreement":null},{"id":"W2949115936","doi":"10.1016/j.bandl.2017.10.008","title":"Brain white matter structure and language ability in preschool-aged children","year":2017,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; MediWound","keywords":"Fractional anisotropy; Psychology; White matter; Diffusion MRI; Corpus callosum; Lateralization of brain function; Tractography; Developmental psychology; Cognitive psychology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.012146118882947981,"score_gpt":0.32078468978117297,"score_spread":0.308638570898225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949115936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992192,0.00027994884,0.000034419507,0.000024227891,0.000003035297,0.00000204134,0.00013592826,0.000006943267,0.00029428425],"genre_scores_gemma":[0.99860114,0.00032968214,0.00013532604,0.000018120294,0.0000031787295,0.00000734347,0.00019182822,0.0000045313145,0.000708956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987733,0.0000098433175,0.00001444358,0.000034975288,0.000019504942,0.00004383501],"domain_scores_gemma":[0.99967,0.00006990664,0.0001237491,0.000018814399,0.00005096532,0.00006660152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034419217,0.00050618505,0.0004167014,0.0014661553,0.00052549416,0.0007275049,0.00030086955,0.0004920236,0.0019458261],"category_scores_gemma":[0.0011577389,0.0003351686,0.0003561117,0.00062003185,0.00064045185,0.00078973314,0.0005028855,0.0005279578,0.00032524942],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085508433,0.0003185113,0.9507583,0.0001498568,0.00018477601,0.004009401,0.004058957,0.00044901404,0.02228617,0.00052759575,0.000600081,0.015802333],"study_design_scores_gemma":[0.000004977377,0.00009667286,0.9967524,0.000011182076,0.000033033848,0.0006486915,0.0011565556,0.00008027458,0.00093635626,0.000113061375,0.00016099557,0.0000058335563],"about_ca_topic_score_codex":0.03508813,"about_ca_topic_score_gemma":0.043490387,"teacher_disagreement_score":0.03508813,"about_ca_system_score_codex":0.0007479232,"about_ca_system_score_gemma":0.00066976907,"threshold_uncertainty_score":0.06976777},"labels":[],"label_agreement":null},{"id":"W2949343593","doi":"10.1016/j.nicl.2019.101896","title":"Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia Hospital; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multiple sclerosis; Spinal cord; Myelin; Medicine; Neuromyelitis optica; Diffusion MRI; White matter; Magnetic resonance imaging; Cord; Lesion; Nuclear medicine; Transverse myelitis; Radiology; Pathology; Central nervous system; Internal medicine; Surgery; Immunology","score_opus":0.1589229524372321,"score_gpt":0.4829302378793488,"score_spread":0.3240072854421167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949343593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9595696,0.009318462,0.025162313,0.0003567224,0.00005329228,0.00033142214,0.0011488337,0.00031012227,0.0037493464],"genre_scores_gemma":[0.9709099,0.0015899974,0.02485469,0.000047958983,0.00002676684,0.00021387583,0.0005297634,0.000054211356,0.0017729213],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986494,0.000033299864,0.0000105713825,0.000031164323,0.000047880105,0.000012101705],"domain_scores_gemma":[0.999767,0.00004801556,0.000074213225,0.000019385188,0.000065152795,0.000026172165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000590243,0.0005165051,0.00020129723,0.00096174784,0.00023967566,0.00030809682,0.00036780373,0.00030865308,0.002721253],"category_scores_gemma":[0.0011054556,0.00014154126,0.00013640731,0.00039851805,0.0002389715,0.0005673806,0.00039679452,0.00024332355,0.00035874022],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036157004,0.0002525598,0.1009375,0.001989099,0.0003606696,0.0009103944,0.00045826062,0.0024179784,0.42470643,0.0015243854,0.0037071316,0.45911983],"study_design_scores_gemma":[0.00030912462,0.0050807702,0.78005636,0.00034705008,0.0004246987,0.011013677,0.00043573522,0.01974833,0.1614486,0.004418883,0.016571494,0.00014531234],"about_ca_topic_score_codex":0.0021223207,"about_ca_topic_score_gemma":0.0054275896,"teacher_disagreement_score":0.002721253,"about_ca_system_score_codex":0.00043508835,"about_ca_system_score_gemma":0.00048221042,"threshold_uncertainty_score":0.009103477},"labels":[],"label_agreement":null},{"id":"W2949992076","doi":"","title":"Variability of basal ganglia morphology after spatial normalization: Implications for group studies","year":2010,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Normalization (sociology); Morphology (biology); Basal ganglia; Biology; Zoology; Neuroscience; Central nervous system; Anthropology","score_opus":0.05948938173205512,"score_gpt":0.3802843787120086,"score_spread":0.3207949969799535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949992076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6461254,0.0013469714,0.3354861,0.001124809,0.0008308523,0.00059005455,0.0015258027,0.002029553,0.010940415],"genre_scores_gemma":[0.9625506,0.00023194466,0.033948325,0.00019113066,0.0002348104,0.00029748192,0.00083826575,0.0009529177,0.0007547133],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9872255,0.0065356176,0.0011242251,0.002735513,0.0020700267,0.00030910468],"domain_scores_gemma":[0.8842667,0.073004715,0.0052848593,0.031436726,0.005304357,0.00070268195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031680338,0.00065087946,0.0018762622,0.0017045982,0.0011228096,0.0026853597,0.0019188098,0.0009867431,0.0030845643],"category_scores_gemma":[0.16637625,0.00037981122,0.0010084372,0.002908661,0.0020548473,0.0027622986,0.0014275013,0.0017950636,0.00066520704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0064953608,0.0008781708,0.28647026,0.0011253511,0.0054144687,0.0019556473,0.007963654,0.019131228,0.085018076,0.024679558,0.012251991,0.5486162],"study_design_scores_gemma":[0.00022220361,0.00087226933,0.85900956,0.00014653128,0.00097256165,0.0022092094,0.0014699976,0.041599005,0.018529871,0.06930389,0.005497479,0.00016743322],"about_ca_topic_score_codex":0.0021398223,"about_ca_topic_score_gemma":0.0023487133,"teacher_disagreement_score":0.031680338,"about_ca_system_score_codex":0.0005754316,"about_ca_system_score_gemma":0.0008395107,"threshold_uncertainty_score":0.16754359},"labels":[],"label_agreement":null},{"id":"W2950007767","doi":"10.1101/547588","title":"White matter changes in the perforant path in patients with amyotrophic lateral sclerosis","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Nederland; Alzheimer Society","keywords":"Amyotrophic lateral sclerosis; Fractional anisotropy; White matter; Frontotemporal dementia; Neuroscience; Psychology; Perforant path; Pathology; Hippocampal formation; Hippocampus; Diffusion MRI; Chemistry; Dementia; Medicine; Disease; Magnetic resonance imaging; Dentate gyrus; Radiology","score_opus":0.026160296775236836,"score_gpt":0.23843515976293797,"score_spread":0.21227486298770112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950007767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994803,0.000106316205,0.00007797377,0.000021334903,0.0000029907594,0.000006227134,0.000047039604,0.000006345897,0.00025156254],"genre_scores_gemma":[0.9997156,0.000051752588,0.00007587685,0.00001759229,0.0000043262835,0.0000040592204,0.00005082969,0.0000010515234,0.0000789065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988496,0.000019743462,0.000017871742,0.000041042465,0.000021532758,0.000014795409],"domain_scores_gemma":[0.9997373,0.00004118284,0.000120890465,0.000012721922,0.000038079655,0.000049739938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023340431,0.0005718651,0.0003159341,0.0007887829,0.00040866729,0.0002784156,0.00016873334,0.00051148824,0.0012445813],"category_scores_gemma":[0.00064490543,0.0002184946,0.00016585887,0.00040030206,0.00041275955,0.0003659183,0.00025172453,0.00027043791,0.00019355207],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018804936,0.0002754833,0.9099582,0.00011232453,0.00022529687,0.016902102,0.0011512226,0.00026850548,0.06140781,0.00008876048,0.0002650318,0.0074647726],"study_design_scores_gemma":[0.000029869456,0.00066156365,0.9815869,0.000013049871,0.000052023304,0.014983713,0.00030172148,0.00019865467,0.0018290195,0.00010472759,0.000229086,0.000009613703],"about_ca_topic_score_codex":0.0011229411,"about_ca_topic_score_gemma":0.0010501887,"teacher_disagreement_score":0.0012445813,"about_ca_system_score_codex":0.00018137624,"about_ca_system_score_gemma":0.00011161051,"threshold_uncertainty_score":0.0041635036},"labels":[],"label_agreement":null},{"id":"W2950133780","doi":"10.1016/j.bpsc.2019.05.016","title":"White Matter Indices of Medication Response in Major Depression: A Diffusion Tensor Imaging Study","year":2019,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; St. Michael's Hospital; Queen's University; McMaster University; University of Alberta; Baycrest Hospital; University of Calgary; University of British Columbia; St. Joseph’s Healthcare Hamilton","funders":"Janssen Pharmaceuticals; Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; St. Jude Medical; Janssen Biotech; Johnson and Johnson; Sunovion; H. Lundbeck A/S; Servier; Leading Edge Endowment Fund; Otsuka America; Victoria General Hospital Foundation; Allergan; Canadian Psychiatric Association; Ontario Mental Health Foundation; Hamilton Health Sciences Foundation; Alkermes; Bristol-Myers Squibb; Government of Ontario; Canadian Network for Mood and Anxiety Treatments; AllerGen; Pfizer; Ontario Brain Institute; University Health Network; Fondation Brain Canada; Abbott Laboratories; Merck; Hamilton Health Sciences; Akili Interactive Labs; Shire","keywords":"Diffusion MRI; White matter; Depression (economics); Medicine; White (mutation); Psychiatry; Psychology; Magnetic resonance imaging; Radiology; Chemistry; Economics","score_opus":0.04691694577998693,"score_gpt":0.35836275280229446,"score_spread":0.3114458070223075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950133780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957985,0.000116330964,0.000036401092,0.000022461016,0.0000025542959,0.000007831792,0.00006622576,0.0000010438675,0.00016738739],"genre_scores_gemma":[0.99958616,0.000059177044,0.000101328806,0.000018753457,0.0000069355974,0.000005749505,0.00009927136,0.0000011202723,0.00012159978],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982184,0.000060205453,0.00002414,0.000036984406,0.000035457993,0.000021430424],"domain_scores_gemma":[0.9992612,0.00014921282,0.00029649623,0.00007164767,0.00007612417,0.00014533645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065778935,0.00038877095,0.00031814905,0.000521475,0.00040036064,0.000537543,0.00035705947,0.00053271017,0.0007150137],"category_scores_gemma":[0.0016449584,0.00028982272,0.00031790376,0.00060462696,0.00031228873,0.00042101424,0.00026649082,0.0005440665,0.00017068016],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024313799,0.0005110678,0.98305064,0.000029073495,0.00041245687,0.00037741466,0.00034997717,0.00009189939,0.0076731164,0.000040728843,0.000106963416,0.0049252277],"study_design_scores_gemma":[0.000019000227,0.000175406,0.9993001,0.0000016963667,0.00004028867,0.0001310917,0.000068890404,0.000111097455,0.00009839958,0.00001567741,0.000035568868,0.0000027114068],"about_ca_topic_score_codex":0.0049199513,"about_ca_topic_score_gemma":0.007209129,"teacher_disagreement_score":0.0049199513,"about_ca_system_score_codex":0.00031425094,"about_ca_system_score_gemma":0.00021822979,"threshold_uncertainty_score":0.009782612},"labels":[],"label_agreement":null},{"id":"W2950351598","doi":"10.1101/661348","title":"A data-driven approach to optimising the encoding for multi-shell diffusion MRI with application to neonatal imaging","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"Centre For Medical Engineering, King’s College London; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; European Commission; King's College London; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Human Connectome Project; Diffusion MRI; Computer science; Data acquisition; Encoding (memory); Diffusion; Shell (structure); Protocol (science); Data mining; Diffusion imaging; Pattern recognition (psychology); Artificial intelligence; Algorithm; Magnetic resonance imaging; Physics; Radiology; Engineering; Pathology; Medicine","score_opus":0.06284205203733073,"score_gpt":0.3156799636398977,"score_spread":0.25283791160256697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950351598","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01746855,0.00009006925,0.98107374,0.00009255405,0.000014113554,0.000100212026,0.000051728042,0.0004705768,0.00063855783],"genre_scores_gemma":[0.14554307,0.00008532737,0.852863,0.000041176354,0.000008260441,0.00018929622,0.000093357776,0.00018349405,0.0009930755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996462,0.00011976662,0.00002372466,0.000059296806,0.00012626687,0.000024677413],"domain_scores_gemma":[0.9987331,0.0005119868,0.00016436387,0.00009770274,0.0004420561,0.000050747294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015570149,0.0006043988,0.0004040766,0.00055237045,0.00022492748,0.000714828,0.0010906917,0.00071377907,0.0019639602],"category_scores_gemma":[0.0034573067,0.0004991859,0.00037624832,0.00034408033,0.0004017318,0.00059576926,0.0007364907,0.0007520972,0.0004450065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003014859,0.00013459292,0.0015972768,0.00033850342,0.000052070387,0.00024608147,0.0003520659,0.60097957,0.18967259,0.007977269,0.0013105703,0.19703798],"study_design_scores_gemma":[0.00001691686,0.00010069571,0.00025340574,0.000016165995,0.000012028039,0.000056011086,0.00002144958,0.956468,0.038965352,0.0013698156,0.0027015437,0.000018607338],"about_ca_topic_score_codex":0.0015060259,"about_ca_topic_score_gemma":0.0017142304,"teacher_disagreement_score":0.0019639602,"about_ca_system_score_codex":0.0006713425,"about_ca_system_score_gemma":0.0009249755,"threshold_uncertainty_score":0.008234322},"labels":[],"label_agreement":null},{"id":"W2950396589","doi":"10.1016/j.dcn.2017.12.002","title":"Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress","year":2017,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute for Health and Care Research","keywords":"Diffusion MRI; Neuroimaging; Psychology; White matter; Brain development; Popularity; Data science; Neuroscience; Cognitive psychology; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.1406222692049797,"score_gpt":0.4381496966508886,"score_spread":0.2975274274459089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950396589","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010651376,0.998273,0.0004520508,0.0005757799,0.00012411803,0.0000050645394,0.00001754134,0.000006935819,0.00043886297],"genre_scores_gemma":[0.0007207006,0.99799263,0.00070634356,0.00018769443,0.00019870498,0.000011416854,0.000024570005,0.0000031605832,0.00015481169],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991555,0.00021026157,0.00014926025,0.0001868709,0.00025044946,0.000047599366],"domain_scores_gemma":[0.996222,0.0024821537,0.0002807357,0.00010871285,0.000803399,0.00010288554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044029295,0.0010320471,0.0017712724,0.0038519918,0.00035156158,0.0018375727,0.0013185405,0.0018510204,0.0015569022],"category_scores_gemma":[0.005215952,0.00056198175,0.0007578069,0.0032327797,0.0017892903,0.0027784507,0.001208388,0.0025220935,0.0012602445],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004138039,0.000037663474,0.00087873265,0.017050767,0.00011405885,0.00013576922,0.00017478893,0.00037320823,0.0009673021,0.0070542768,0.010772888,0.9623993],"study_design_scores_gemma":[0.000018466268,0.00012941872,0.0061580953,0.019368457,0.00033922977,0.0035438878,0.0004121909,0.00055760937,0.0018023798,0.015775025,0.9517765,0.00011874455],"about_ca_topic_score_codex":0.0038815718,"about_ca_topic_score_gemma":0.0048286975,"teacher_disagreement_score":0.0044029295,"about_ca_system_score_codex":0.0012261841,"about_ca_system_score_gemma":0.0029660603,"threshold_uncertainty_score":0.02328521},"labels":[],"label_agreement":null},{"id":"W2951010418","doi":"10.1101/424150","title":"Structural connectivity analysis using Finsler geometry","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Geodesic; Tractography; Metric (unit); Finsler manifold; Computer science; Diffusion MRI; Connectome; Population; Riemannian geometry; Human Connectome Project; Mathematics; Artificial intelligence; Functional connectivity; Geometry; Psychology; Neuroscience; Magnetic resonance imaging; Engineering; Medicine","score_opus":0.0570971091719142,"score_gpt":0.31910423698519813,"score_spread":0.26200712781328395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951010418","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058292676,0.00025570244,0.9357576,0.00033068887,0.000049183156,0.000037128048,0.00028899158,0.00093980285,0.004048294],"genre_scores_gemma":[0.663152,0.0004129068,0.33210477,0.00012799371,0.00010016972,0.000073475094,0.00064825005,0.00032600597,0.0030544617],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994349,0.00017855906,0.00003955871,0.00014800807,0.00016087205,0.000038150345],"domain_scores_gemma":[0.9988709,0.00048192678,0.00018075417,0.00021121404,0.00017900714,0.000076210265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092979363,0.0006555861,0.0005603851,0.0040048272,0.00051105715,0.0013557709,0.0006667789,0.0006396119,0.003339423],"category_scores_gemma":[0.004414242,0.00022799612,0.00078565127,0.0018148082,0.0013381393,0.0019911088,0.001268803,0.0006924523,0.0005743796],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012983562,0.00006097171,0.0072652213,0.0002003326,0.00026936224,0.00083751953,0.00066336803,0.25539228,0.028878275,0.5265362,0.005457635,0.17430909],"study_design_scores_gemma":[0.000015449139,0.00010362477,0.0052837646,0.00003473581,0.0000351939,0.00043186333,0.00011134598,0.6460951,0.00644063,0.334182,0.007207195,0.000059166323],"about_ca_topic_score_codex":0.0036383383,"about_ca_topic_score_gemma":0.0033152418,"teacher_disagreement_score":0.0040048272,"about_ca_system_score_codex":0.0006998115,"about_ca_system_score_gemma":0.0007104821,"threshold_uncertainty_score":0.01117146},"labels":[],"label_agreement":null},{"id":"W2951189597","doi":"10.1038/tp.2017.92","title":"The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging","year":2017,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Striatum; Thalamus; Nucleus accumbens; Ventral striatum; Kurtosis; Neuroscience; Addiction; Magnetic resonance imaging; Psychology; Cocaine dependence; Brain morphometry; Medicine; Dopamine; Radiology; Mathematics","score_opus":0.022930719908856142,"score_gpt":0.3311533694720586,"score_spread":0.30822264956320244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951189597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99900717,0.0002424948,0.00045404816,0.000011070444,0.0000022456124,0.000008861415,0.000068542395,0.00000546012,0.00020018636],"genre_scores_gemma":[0.9983552,0.00020583357,0.0009775518,0.000012902133,0.0000032054568,0.000009238537,0.00008434489,0.000008397684,0.00034322563],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989057,0.000019607141,0.000010743797,0.000037807094,0.000028392868,0.000012855502],"domain_scores_gemma":[0.9995665,0.00007503331,0.00019276958,0.000038322385,0.00007177545,0.00005565398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020934567,0.00020746331,0.00013869179,0.00053420407,0.0001115738,0.00023821872,0.00009532143,0.00020723081,0.0009317425],"category_scores_gemma":[0.00070085836,0.0001470074,0.00016031269,0.00018635081,0.00024511555,0.00025713022,0.00026927344,0.00016770135,0.000066323926],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033410466,0.00022921477,0.34781972,0.00019841001,0.0003452885,0.0011774844,0.0009825403,0.0005919662,0.6080807,0.00021990058,0.00022871791,0.03678516],"study_design_scores_gemma":[0.0000067859282,0.00034672374,0.9872665,0.000007777034,0.000050060666,0.00081320945,0.00013367295,0.0010816318,0.010024846,0.00005597153,0.00020154123,0.000011364107],"about_ca_topic_score_codex":0.0029603143,"about_ca_topic_score_gemma":0.006765642,"teacher_disagreement_score":0.0029603143,"about_ca_system_score_codex":0.0001684361,"about_ca_system_score_gemma":0.00012189611,"threshold_uncertainty_score":0.005886197},"labels":[],"label_agreement":null},{"id":"W2951290748","doi":"10.1016/j.neuroimage.2017.07.028","title":"Fiber tractography using machine learning","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Deutsche Forschungsgemeinschaft","keywords":"Tractography; Computer science; Artificial intelligence; Random forest; Diffusion MRI; Imaging phantom; Fiber; Pattern recognition (psychology); Machine learning; Chemistry; Medicine; Nuclear medicine; Magnetic resonance imaging","score_opus":0.1365906204835527,"score_gpt":0.3990254124329575,"score_spread":0.26243479194940483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951290748","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004326416,0.00019903836,0.99302906,0.00010758019,0.000029208111,0.0000350055,0.00010619136,0.0016524781,0.00051504717],"genre_scores_gemma":[0.12002038,0.0005177414,0.87439525,0.000078915196,0.000068523885,0.00015155987,0.00030159752,0.00050393236,0.003962095],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973804,0.00007405568,0.000021366674,0.00007765647,0.00006714669,0.000021821616],"domain_scores_gemma":[0.9986444,0.0006347082,0.00017737664,0.0002676742,0.00022583354,0.000050049464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010210279,0.00069781195,0.00094343716,0.0019808523,0.00058715703,0.0016058099,0.00079162885,0.0011187631,0.004972974],"category_scores_gemma":[0.003702124,0.00065786776,0.001078399,0.0015893808,0.0005823056,0.0013588448,0.0008489188,0.0014368875,0.002273916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016791723,0.00010725395,0.0030967186,0.00031952243,0.00036258294,0.0002193107,0.00015156869,0.15981537,0.01991183,0.022362217,0.006513783,0.78697187],"study_design_scores_gemma":[0.000015324926,0.000032731044,0.0012836138,0.000037785103,0.000047505862,0.000303751,0.000019558789,0.9556302,0.008774825,0.028412525,0.00541519,0.000027035543],"about_ca_topic_score_codex":0.00631111,"about_ca_topic_score_gemma":0.009287408,"teacher_disagreement_score":0.00631111,"about_ca_system_score_codex":0.00083617197,"about_ca_system_score_gemma":0.0016547099,"threshold_uncertainty_score":0.016636252},"labels":[],"label_agreement":null},{"id":"W2951488689","doi":"10.3389/fninf.2019.00002","title":"Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; BioClinica; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Clinical Dementia Rating; Fornix; Neuroimaging; Cingulum (brain); Dementia; Psychology; Cognitive impairment; Medicine; Cognition; Neuroscience; Magnetic resonance imaging; Disease; Pathology; Radiology; Hippocampus","score_opus":0.02635451086619333,"score_gpt":0.31591104852532836,"score_spread":0.289556537659135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951488689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59823155,0.037980467,0.2959981,0.0019785687,0.0010365312,0.029275307,0.021879641,0.0020037184,0.011616114],"genre_scores_gemma":[0.52304256,0.007056974,0.3726942,0.00061210804,0.0002430568,0.068477474,0.023869969,0.00079206243,0.0032116089],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98327845,0.008491174,0.0035486238,0.0014112919,0.0030188984,0.0002516062],"domain_scores_gemma":[0.9810477,0.0041079274,0.0048933323,0.0027268205,0.006950369,0.00027398867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.050228357,0.0016292273,0.0015770249,0.0043944344,0.0014565506,0.0024165395,0.0021708638,0.0010735911,0.000656661],"category_scores_gemma":[0.050037593,0.00093060423,0.002234974,0.005900691,0.0008222735,0.00206402,0.0021302325,0.0017781333,0.00028944688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0065514413,0.00086828385,0.545053,0.0062203263,0.02220576,0.00060221285,0.0028755188,0.009961448,0.009455133,0.0042377617,0.026036054,0.365933],"study_design_scores_gemma":[0.0013654621,0.002375923,0.9077313,0.0014439377,0.0063322666,0.002337392,0.00062182936,0.02548955,0.0073483256,0.0068322313,0.037585787,0.00053599343],"about_ca_topic_score_codex":0.006149304,"about_ca_topic_score_gemma":0.015263557,"teacher_disagreement_score":0.050228357,"about_ca_system_score_codex":0.0021458769,"about_ca_system_score_gemma":0.0033607492,"threshold_uncertainty_score":0.26563615},"labels":[],"label_agreement":null},{"id":"W2951503675","doi":"10.1101/232439","title":"Shape-related characteristics of age-related differences in subcortical structures","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Sphericity; Curse of dimensionality; Fractal dimension; Fractal; Brain size; Measure (data warehouse); Curvature; Volume (thermodynamics); Mathematics; Psychology; Statistics; Computer science; Medicine; Geometry; Physics; Mathematical analysis; Magnetic resonance imaging","score_opus":0.044141022166421566,"score_gpt":0.2950998302017782,"score_spread":0.25095880803535664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951503675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968317,0.0002830937,0.0019291951,0.00002166744,0.000005246752,0.000009818334,0.00036854658,0.000019372621,0.00053136976],"genre_scores_gemma":[0.99907315,0.000038658713,0.0005930259,0.000007990925,0.000003719054,0.000004599019,0.00016682441,0.000004866472,0.000107245614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997881,0.000038614795,0.00002659213,0.0000665004,0.00006212485,0.000018129693],"domain_scores_gemma":[0.99817324,0.00050872384,0.00064410246,0.00022335157,0.00034248826,0.000108105414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055779447,0.00025212302,0.00029734918,0.0014996598,0.00015611241,0.00050694554,0.00019186438,0.00033554793,0.0011183034],"category_scores_gemma":[0.00288528,0.0001128246,0.00029347133,0.00063824456,0.00037709362,0.0003804412,0.0003508198,0.0001958735,0.000148668],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005477481,0.000058008136,0.9091061,0.000089032845,0.00040218866,0.00027657356,0.00051908207,0.002276027,0.049893156,0.00069210783,0.00046567863,0.035674293],"study_design_scores_gemma":[0.000003069075,0.00004894045,0.9948914,0.0000043374694,0.000020641013,0.00040061763,0.00007666851,0.0020468552,0.0018173909,0.0005455874,0.00013634533,0.000008129801],"about_ca_topic_score_codex":0.0013495609,"about_ca_topic_score_gemma":0.0013819819,"teacher_disagreement_score":0.0014996598,"about_ca_system_score_codex":0.00020341767,"about_ca_system_score_gemma":0.000091951006,"threshold_uncertainty_score":0.0037410855},"labels":[],"label_agreement":null},{"id":"W2951540119","doi":"10.7554/elife.26653","title":"Anatomical and functional organization of the human substantia nigra and its connections","year":2017,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Neuroscience; Substantia nigra; Salience (neuroscience); Striatum; Psychology; Impulsivity; Human brain; Ventral striatum; Basal ganglia; Human Connectome Project; Putamen; Functional connectivity; Biology; Dopamine; Dopaminergic; Central nervous system; Developmental psychology","score_opus":0.06987130663645406,"score_gpt":0.34711368151375155,"score_spread":0.27724237487729747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951540119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849332,0.0014110674,0.010011984,0.00015119129,0.000003357846,0.000009981404,0.00032790954,0.0000787857,0.00307242],"genre_scores_gemma":[0.9919531,0.00039077047,0.0065144966,0.000028456809,0.0000027053734,0.000011156756,0.00017530302,0.000009189646,0.00091484346],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999026,0.00001803392,0.000004208682,0.00003177236,0.000032026597,0.000011321257],"domain_scores_gemma":[0.9998716,0.000029281253,0.000035182635,0.000022245858,0.00002948261,0.000012296862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018672859,0.00008415158,0.000116042764,0.0006733156,0.00034222298,0.00045560396,0.00016474577,0.00028929737,0.0006674967],"category_scores_gemma":[0.00049409905,0.00017105813,0.00011711864,0.00040953682,0.00039883843,0.00022022113,0.00027042063,0.00013513108,0.00016892426],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003313915,0.000051954878,0.10600362,0.00022703869,0.00029046446,0.0015288377,0.0019494214,0.0047933655,0.7411738,0.006898623,0.000744814,0.13600671],"study_design_scores_gemma":[0.000017006192,0.00018442178,0.9137033,0.000052323547,0.00012633392,0.008115952,0.00075027504,0.014769145,0.044480298,0.007593993,0.01014958,0.000057334084],"about_ca_topic_score_codex":0.0140352985,"about_ca_topic_score_gemma":0.029933749,"teacher_disagreement_score":0.0140352985,"about_ca_system_score_codex":0.0002716196,"about_ca_system_score_gemma":0.00033477676,"threshold_uncertainty_score":0.027907193},"labels":[],"label_agreement":null},{"id":"W2951566176","doi":"10.1016/j.neuroimage.2018.10.033","title":"Axons morphometry in the human spinal cord","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Multiple Sclerosis Society of Canada; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Axon; Spinal cord; Anatomy; Myelin; Neuroscience; Magnetic resonance imaging; Central nervous system; Biology; Medicine; Radiology","score_opus":0.14608111365162862,"score_gpt":0.4319122923201034,"score_spread":0.2858311786684748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951566176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.978634,0.002415986,0.015421795,0.00050602155,0.000019947962,0.000021053738,0.00034422477,0.00019101861,0.0024459583],"genre_scores_gemma":[0.98944306,0.0011934789,0.0072151306,0.000028051276,0.000012271793,0.000010558607,0.000079334,0.000047462127,0.0019707573],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99990666,0.000023540419,0.00000842582,0.000020981935,0.00003118013,0.000009095734],"domain_scores_gemma":[0.9997873,0.000071194714,0.000051711555,0.000028236485,0.0000459587,0.000015531867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003452139,0.00017545909,0.0001143892,0.0010982784,0.00034012247,0.0007504245,0.00018630904,0.00044844678,0.0013296582],"category_scores_gemma":[0.0012141261,0.0001815877,0.00010710825,0.0008210604,0.0005081057,0.00077450415,0.0002612613,0.00021401403,0.00020621927],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015191311,0.000099819306,0.16306882,0.00095658115,0.00028598303,0.0016851764,0.002647298,0.029894881,0.3160281,0.017373495,0.0025735921,0.4638671],"study_design_scores_gemma":[0.000038148057,0.00033496757,0.7805976,0.0002132748,0.00019413207,0.008293662,0.0015799338,0.0921776,0.08925886,0.020102981,0.0071174465,0.00009133475],"about_ca_topic_score_codex":0.0125000775,"about_ca_topic_score_gemma":0.016781807,"teacher_disagreement_score":0.0125000775,"about_ca_system_score_codex":0.0004145,"about_ca_system_score_gemma":0.00078198063,"threshold_uncertainty_score":0.02485466},"labels":[],"label_agreement":null},{"id":"W2951846649","doi":"10.1101/392571","title":"Limits to anatomical accuracy of diffusion tractography using modern approaches","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; Vanderbilt Institute for Clinical and Translational Research; National Institutes of Health; Vanderbilt University","keywords":"Tractography; Diffusion MRI; Computer science; Artificial intelligence; White matter; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.10965666558173885,"score_gpt":0.3205598659333588,"score_spread":0.2109032003516199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951846649","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061725643,0.009103289,0.9157791,0.0037771761,0.0004138103,0.00009113921,0.0008749043,0.0018300877,0.00640479],"genre_scores_gemma":[0.5954312,0.0039657117,0.3953346,0.0007512264,0.00041334203,0.00022141734,0.0013695959,0.0011499678,0.0013630022],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9759664,0.010671281,0.0016690525,0.0036475838,0.0076162005,0.00042941183],"domain_scores_gemma":[0.8535788,0.10191125,0.0056367386,0.02603531,0.011993811,0.0008441605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028915875,0.0012117616,0.0013926645,0.002838412,0.0010295601,0.003613269,0.0024098905,0.0024522953,0.0024890348],"category_scores_gemma":[0.13642307,0.0011195787,0.0010395141,0.0019291651,0.0037012852,0.0047504855,0.004345543,0.0026968971,0.0017912016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012031839,0.0001652451,0.02832288,0.0029926293,0.0012509075,0.0004019489,0.0018972114,0.3176856,0.052944228,0.107849665,0.0144214155,0.4708651],"study_design_scores_gemma":[0.00009089285,0.0002886066,0.017943278,0.0010250211,0.00018713748,0.0014932926,0.00036772905,0.6543403,0.049610138,0.24396905,0.030411625,0.00027287222],"about_ca_topic_score_codex":0.0030790735,"about_ca_topic_score_gemma":0.0022692604,"teacher_disagreement_score":0.028915875,"about_ca_system_score_codex":0.0016174436,"about_ca_system_score_gemma":0.0016693829,"threshold_uncertainty_score":0.15292352},"labels":[],"label_agreement":null},{"id":"W2951906816","doi":"10.1101/402255","title":"Deep Learning for Quality Control of Subcortical Brain 3D Shape Models","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Artificial intelligence; Computer science; Deep learning; Convolutional neural network; Residual neural network; Feature (linguistics); Grey matter; Pattern recognition (psychology); Human Connectome Project; Machine learning; Neuroscience; Functional connectivity; Magnetic resonance imaging; Psychology; White matter; Medicine","score_opus":0.062254647520927985,"score_gpt":0.3322475259131574,"score_spread":0.26999287839222946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951906816","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14218259,0.0018300584,0.8349071,0.0012033747,0.00014550277,0.0002126606,0.0022483093,0.015064967,0.002205359],"genre_scores_gemma":[0.8070036,0.0004921124,0.18489508,0.00037671486,0.0000582583,0.00016058396,0.0036196595,0.0010451527,0.0023487918],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99821544,0.0004933088,0.00011055696,0.0004818161,0.00052912,0.00016977736],"domain_scores_gemma":[0.99345064,0.003020347,0.0008481082,0.0014474822,0.0010274395,0.00020600816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006516637,0.0016535942,0.0010217236,0.0016107822,0.00046898457,0.0020421068,0.0025429502,0.0015306212,0.002593883],"category_scores_gemma":[0.020651234,0.000783755,0.001383016,0.0011375156,0.0013196165,0.0017188363,0.0024514275,0.0024054572,0.0008683247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039606643,0.0000720155,0.004492489,0.00015436827,0.00016498478,0.00008233696,0.00007232964,0.80502015,0.006344805,0.0033463202,0.0052292882,0.1746248],"study_design_scores_gemma":[0.000011512699,0.000026483689,0.0003888205,0.00001311703,0.000007477894,0.000020236075,0.0000055124024,0.9940639,0.003316092,0.0018537475,0.0002862394,0.000006859719],"about_ca_topic_score_codex":0.015389616,"about_ca_topic_score_gemma":0.015430049,"teacher_disagreement_score":0.015389616,"about_ca_system_score_codex":0.0032495433,"about_ca_system_score_gemma":0.0020458107,"threshold_uncertainty_score":0.034463704},"labels":[],"label_agreement":null},{"id":"W2951972782","doi":"10.1002/jmri.26794","title":"Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge","year":2019,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; Vanderbilt University; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Reproducibility; Context (archaeology); Intraclass correlation; Computer science; Diffusion MRI; Tractography; Similarity (geometry); Artificial intelligence; Nuclear medicine; Statistics; Magnetic resonance imaging; Medicine; Mathematics; Radiology","score_opus":0.2806202968680405,"score_gpt":0.45689265641747934,"score_spread":0.17627235954943882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951972782","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09922417,0.34185112,0.3364954,0.1685219,0.010314385,0.015655473,0.013694016,0.0012603012,0.012983194],"genre_scores_gemma":[0.5000369,0.050999362,0.3536059,0.034072064,0.0064067487,0.036259975,0.01319266,0.0020693273,0.00335705],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.64073503,0.21399163,0.07038024,0.020499716,0.05297033,0.0014230211],"domain_scores_gemma":[0.15622863,0.656571,0.055832557,0.04545423,0.08266332,0.0032503079],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.47586536,0.0013552391,0.0042619486,0.005420289,0.002381092,0.0064138197,0.005174163,0.0041194763,0.0025312942],"category_scores_gemma":[0.6948155,0.0015295851,0.0058421316,0.0049542794,0.0067350906,0.0059314095,0.0067390027,0.0046648527,0.0009346259],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002737391,0.00023201093,0.055087782,0.10140896,0.018508175,0.0010153875,0.009520157,0.0078629255,0.0022228584,0.04271172,0.078997865,0.6796948],"study_design_scores_gemma":[0.0020591205,0.005020749,0.12431382,0.16883235,0.017469987,0.007436685,0.007987355,0.028355232,0.007981278,0.19123515,0.43793842,0.0013698566],"about_ca_topic_score_codex":0.009087584,"about_ca_topic_score_gemma":0.012766355,"teacher_disagreement_score":0.52413464,"about_ca_system_score_codex":0.0067621437,"about_ca_system_score_gemma":0.02403958,"threshold_uncertainty_score":0.64635134},"labels":[],"label_agreement":null},{"id":"W2952148882","doi":"10.1016/j.neuroimage.2019.06.016","title":"Reducing variability in along-tract analysis with diffusion profile realignment","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; Fonds de recherche du Québec – Nature et technologies; McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Diffusion; Phase (matter); Computer science; Geology; Chemistry; Physics; Thermodynamics","score_opus":0.02698230986161734,"score_gpt":0.3208204024195131,"score_spread":0.2938380925578958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952148882","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024119811,0.00012862978,0.9743289,0.00009004968,0.000043458473,0.00005135492,0.00008440189,0.0009603595,0.0001931076],"genre_scores_gemma":[0.17323679,0.00019660476,0.8240954,0.00007067856,0.00004940393,0.00018074721,0.00057034794,0.00083619327,0.0007638368],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99738187,0.0008422221,0.0002463978,0.00069927884,0.0007141815,0.000116103394],"domain_scores_gemma":[0.9927941,0.0026747587,0.0010640165,0.0022902368,0.001054613,0.0001223218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048276572,0.0013891337,0.0010336495,0.001574445,0.00052746484,0.0014516506,0.0011985376,0.0011043657,0.0011892805],"category_scores_gemma":[0.021221027,0.0005960694,0.0014310852,0.0017001017,0.00081739755,0.0016018304,0.0018246989,0.0017753113,0.0008628914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062839314,0.00025247608,0.008035551,0.00047458286,0.000610811,0.0004577606,0.0009726963,0.18734208,0.12656224,0.011883421,0.0032518557,0.65952814],"study_design_scores_gemma":[0.00006333972,0.0004458918,0.011815348,0.000051347466,0.00016903467,0.00081387226,0.00013098336,0.88563246,0.078005694,0.013016301,0.009707743,0.00014796836],"about_ca_topic_score_codex":0.0021435674,"about_ca_topic_score_gemma":0.0025101558,"teacher_disagreement_score":0.0048276572,"about_ca_system_score_codex":0.0004709117,"about_ca_system_score_gemma":0.0012837285,"threshold_uncertainty_score":0.025531411},"labels":[],"label_agreement":null},{"id":"W2952326196","doi":"10.1101/677153","title":"Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; Lawson Health Research Institute; Western University","funders":"National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Medical Research Council; Clinical Science Research and Development; National Institutes of Health; Congressionally Directed Medical Research Programs; Bill and Melinda Gates Foundation; ZonMw; National Alliance for Research on Schizophrenia and Depression; Canadian Institute for Military and Veteran Health Research; Chinese Academy of Sciences; Division of Research Capacity Development; Deutsche Forschungsgemeinschaft; National Research Foundation; Yale Center for Clinical Investigation, Yale School of Medicine; Institute for Clinical and Translational Research, University of Wisconsin, Madison; Medical Research and Materiel Command; National Natural Science Foundation of China; Georgia Clinical and Translational Science Alliance; Waisman Center; Yale University; U.S. Department of Veterans Affairs; Office of Research and Development; Michael J. Fox Foundation for Parkinson's Research; Traumatic Brain Injury Center of Excellence; South African Medical Research Council; U.S. Department of Defense; National Center for PTSD, U.S. Department of Veterans Affairs; Canadian Institutes of Health Research; National Science Foundation","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Neuroimaging; Psychology; Depression (economics); Brain Structure and Function; Tractography; Psychiatry; Traumatic stress; Confounding; Clinical psychology; Medicine; Neuroscience; Internal medicine; Magnetic resonance imaging","score_opus":0.01758380025829856,"score_gpt":0.26954051819305536,"score_spread":0.2519567179347568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952326196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99581474,0.0003598193,0.00019340448,0.00011777689,0.0000094894995,0.0000171624,0.0032604379,0.000009882464,0.00021724612],"genre_scores_gemma":[0.99634796,0.00016949157,0.00024376778,0.00006361307,0.000012265079,0.00003469855,0.0029504583,0.0000141966475,0.00016365576],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988977,0.00023845858,0.00011773751,0.00045986983,0.00017600216,0.00011022707],"domain_scores_gemma":[0.99747133,0.00032474456,0.0011116727,0.0004199518,0.00038358857,0.00028878148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019592524,0.0004593773,0.00053968845,0.0010840473,0.0009608833,0.0009093245,0.0008931571,0.00079912884,0.0016033936],"category_scores_gemma":[0.0045252773,0.00040982914,0.0012091732,0.0018656702,0.00048577593,0.0004530717,0.0019829774,0.0007075537,0.00020506202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042876165,0.0000336457,0.9940082,0.00006854532,0.0015954068,0.00014585676,0.00035175605,0.00013971994,0.00073387066,0.000055397784,0.0006100581,0.0018287897],"study_design_scores_gemma":[0.000025636204,0.000056694178,0.9985826,0.000018646557,0.00036233166,0.00020168899,0.00025587928,0.00006780507,0.000097221084,0.00004384418,0.0002791309,0.000008427962],"about_ca_topic_score_codex":0.02333885,"about_ca_topic_score_gemma":0.025008032,"teacher_disagreement_score":0.02333885,"about_ca_system_score_codex":0.00042139748,"about_ca_system_score_gemma":0.00049051875,"threshold_uncertainty_score":0.04640603},"labels":[],"label_agreement":null},{"id":"W2952355381","doi":"10.1016/j.neuroimage.2019.04.004","title":"Global and regional white matter development in early childhood","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":134,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Foundation; University of Calgary","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Brain development; Early childhood; Developmental psychology; Tractography; Psychology; Pediatrics; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.026618182018506444,"score_gpt":0.2961953305486827,"score_spread":0.2695771485301762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952355381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923673,0.0028146715,0.0006771836,0.00012844242,0.000012396801,0.0000074491654,0.0005843211,0.000029690518,0.003378532],"genre_scores_gemma":[0.99306387,0.0034133962,0.0010072895,0.000027442687,0.000009896039,0.000010665764,0.00039554195,0.000026383725,0.0020455695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998043,0.000033408345,0.00001305046,0.000045618963,0.000046347745,0.000057333757],"domain_scores_gemma":[0.9995703,0.0001024529,0.00014057038,0.00002050084,0.00009964369,0.00006647374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049656816,0.00046673638,0.00028041276,0.0016664197,0.00042727022,0.00083578407,0.00025318365,0.0003885016,0.0014741324],"category_scores_gemma":[0.0012621898,0.00039265276,0.00023754647,0.0011197153,0.0005295633,0.0006777776,0.0005588335,0.0005176128,0.00025261147],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008320218,0.00011832335,0.8829314,0.00034836654,0.00024450786,0.0029079576,0.0025749689,0.0020739795,0.02935215,0.0028192122,0.0012509689,0.07454612],"study_design_scores_gemma":[0.0000014985,0.000039500577,0.99445665,0.000033895907,0.00003296018,0.0008082326,0.00048899447,0.00014105704,0.0028946144,0.00035192634,0.000745597,0.000005007979],"about_ca_topic_score_codex":0.02328873,"about_ca_topic_score_gemma":0.048476577,"teacher_disagreement_score":0.02328873,"about_ca_system_score_codex":0.0008649584,"about_ca_system_score_gemma":0.0006698862,"threshold_uncertainty_score":0.04630637},"labels":[],"label_agreement":null},{"id":"W2952547383","doi":"10.1016/j.nicl.2019.101886","title":"Facial emotion recognition in children treated for posterior fossa tumours and typically developing children: A divergence of predictors","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Pediatric Oncology Group","funders":"Canadian Institutes of Health Research; Pediatric Oncology Group of Ontario","keywords":"White matter; Neuroimaging; Cognition; Psychology; Fractional anisotropy; Audiology; Social cognition; Medicine; Developmental psychology; Neuroscience; Magnetic resonance imaging","score_opus":0.07999941178710104,"score_gpt":0.3779813293236043,"score_spread":0.29798191753650327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952547383","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99973065,0.00009209975,0.000017674483,0.000015600594,0.0000016366387,0.0000029514981,0.00004538021,0.0000011532478,0.0000928684],"genre_scores_gemma":[0.99967265,0.00010969426,0.00005080497,0.000010097345,0.0000020738241,0.0000069401804,0.0001064229,0.0000015156023,0.00003994076],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994667,0.00007562832,0.000057517158,0.0001254351,0.00013437383,0.0001403225],"domain_scores_gemma":[0.9986486,0.00029487532,0.00074130984,0.00003864221,0.00008635167,0.00019035187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043097202,0.0005230735,0.00041857696,0.0008998129,0.0004480069,0.0006569583,0.0003481476,0.000534117,0.000734337],"category_scores_gemma":[0.00287245,0.00024864107,0.00044970022,0.00066817674,0.00066388305,0.00045478868,0.0009061529,0.00074570096,0.000104254286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010241704,0.000025553984,0.99698454,0.0000100791085,0.000016315744,0.00032736216,0.00040599777,0.000028849838,0.00042410663,0.000014204065,0.000046607773,0.0016140913],"study_design_scores_gemma":[0.0000028133181,0.00006322898,0.9980337,0.000004991519,0.000011264847,0.0010295275,0.0006416586,0.000055168075,0.00009268707,0.000013267868,0.000048535683,0.0000032198761],"about_ca_topic_score_codex":0.020804564,"about_ca_topic_score_gemma":0.02146435,"teacher_disagreement_score":0.020804564,"about_ca_system_score_codex":0.00084649434,"about_ca_system_score_gemma":0.00057789974,"threshold_uncertainty_score":0.041366935},"labels":[],"label_agreement":null},{"id":"W2952939467","doi":"10.1016/j.neuroimage.2019.06.020","title":"Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Dimensionality reduction; Diffusion MRI; Diffusion; Diffusion map; Reduction (mathematics); Human brain; Multifactor dimensionality reduction; Curse of dimensionality; Computer science; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Chemistry; Psychology; Mathematics; Magnetic resonance imaging; Medicine; Physics; Nonlinear dimensionality reduction; Radiology","score_opus":0.0538105318690795,"score_gpt":0.36017632451497034,"score_spread":0.3063657926458908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952939467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.075190075,0.0009801362,0.91969025,0.00055653194,0.000076742646,0.00021032248,0.0012652574,0.0009692593,0.0010613624],"genre_scores_gemma":[0.2172139,0.0007296097,0.77842265,0.000079481775,0.000058568527,0.0004091549,0.0020204342,0.0003823629,0.00068378705],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990447,0.00039705625,0.00010045102,0.00018069254,0.00022291027,0.00005422937],"domain_scores_gemma":[0.99735665,0.0011635844,0.00036730117,0.00060309574,0.00044865592,0.000060701983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025290428,0.0012910517,0.000713843,0.0035783262,0.00066224346,0.0016689943,0.00044039337,0.00046955375,0.0015822788],"category_scores_gemma":[0.012224796,0.00033305134,0.0015266524,0.00265921,0.0006220574,0.0010159251,0.0011160638,0.0015370533,0.0007964222],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022305394,0.00023577016,0.024062918,0.00096326607,0.00088677823,0.00031744002,0.002210336,0.08052598,0.13337402,0.04854382,0.011199232,0.6974574],"study_design_scores_gemma":[0.000057522073,0.00033717413,0.108005755,0.00031966114,0.00043468399,0.0010229034,0.0008163503,0.6758356,0.051041346,0.12321083,0.0385639,0.00035429146],"about_ca_topic_score_codex":0.0040713577,"about_ca_topic_score_gemma":0.0073228967,"teacher_disagreement_score":0.0040713577,"about_ca_system_score_codex":0.00073680514,"about_ca_system_score_gemma":0.0016503871,"threshold_uncertainty_score":0.013374984},"labels":[],"label_agreement":null},{"id":"W2953031404","doi":"10.1016/j.media.2019.06.010","title":"XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI","year":2019,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Resolution (logic); Computer science; Image resolution; Focus (optics); Artificial intelligence; SIGNAL (programming language); Pattern recognition (psychology); Domain (mathematical analysis); Joint (building); Mathematics; Magnetic resonance imaging; Physics; Optics; Mathematical analysis; Medicine","score_opus":0.014259364138998113,"score_gpt":0.31385705844009204,"score_spread":0.29959769430109395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953031404","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077559347,0.000579227,0.9829972,0.00022698642,0.00006720651,0.00008828166,0.00035722426,0.006424107,0.0015038777],"genre_scores_gemma":[0.04341768,0.00056642113,0.95182794,0.00016126642,0.00007020332,0.00012886459,0.00037139188,0.0010916939,0.0023645542],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971896,0.00007811618,0.000019226862,0.000037759924,0.00012030802,0.000025633406],"domain_scores_gemma":[0.9991254,0.0003442936,0.00008804141,0.00013952424,0.00021987915,0.00008284998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015303319,0.0008338375,0.0005350347,0.0008519397,0.0003190022,0.001134263,0.0009345359,0.0009841102,0.006272785],"category_scores_gemma":[0.0028956737,0.0004448648,0.00040485975,0.0010275054,0.00038623053,0.0011793729,0.0014066992,0.00092866353,0.002039733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008011658,0.00018155022,0.0019206976,0.0007216911,0.00018111218,0.0009049954,0.00032652591,0.026342321,0.12590815,0.02871868,0.034441672,0.77955145],"study_design_scores_gemma":[0.00011160211,0.00026595884,0.0035182904,0.000076849305,0.00008214464,0.002416792,0.00010259925,0.8268556,0.106504805,0.015530414,0.04442381,0.00011116332],"about_ca_topic_score_codex":0.0011563782,"about_ca_topic_score_gemma":0.0022012126,"teacher_disagreement_score":0.006272785,"about_ca_system_score_codex":0.00016987743,"about_ca_system_score_gemma":0.0006663101,"threshold_uncertainty_score":0.02098459},"labels":[],"label_agreement":null},{"id":"W2953109071","doi":"10.1016/j.neuroimage.2019.02.018","title":"Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; James S. McDonnell Foundation","keywords":"Connectome; Tractography; Macaque; Betweenness centrality; Diffusion MRI; Human Connectome Project; Connectomics; Modularity (biology); Computer science; Neuroscience; Network topology; Artificial intelligence; Pattern recognition (psychology); Centrality; Psychology; Biology; Functional connectivity; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.2828809455244366,"score_gpt":0.41036486000167766,"score_spread":0.12748391447724106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953109071","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7975756,0.0072720256,0.18563662,0.004375946,0.00004094837,0.00003231091,0.00014374264,0.00024279357,0.004679944],"genre_scores_gemma":[0.9748395,0.0015753657,0.022989284,0.000078703204,0.00003751701,0.0000236284,0.000055621105,0.000052944615,0.00034746138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99832374,0.0010502477,0.00007052341,0.00023595648,0.0002449122,0.000074585456],"domain_scores_gemma":[0.9618285,0.031630322,0.0022503147,0.0022319956,0.00138631,0.000672659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009571855,0.00069661095,0.00075793476,0.0025905124,0.00079683587,0.003724018,0.0011686567,0.0015927971,0.0007107103],"category_scores_gemma":[0.06571143,0.00064763956,0.00038518902,0.0011832588,0.0032134494,0.007400712,0.0023636185,0.0015784281,0.00013276363],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012513285,0.00023470099,0.11130746,0.0013331545,0.0009988884,0.001399537,0.0052510845,0.30154708,0.0556095,0.2864167,0.0018839906,0.23276652],"study_design_scores_gemma":[0.00003598461,0.00014367621,0.033392806,0.0002811161,0.00014248797,0.00075347966,0.0009058007,0.53902644,0.008613958,0.4133328,0.0032936574,0.00007784515],"about_ca_topic_score_codex":0.010833926,"about_ca_topic_score_gemma":0.008955077,"teacher_disagreement_score":0.010833926,"about_ca_system_score_codex":0.0014348016,"about_ca_system_score_gemma":0.0015727864,"threshold_uncertainty_score":0.05062139},"labels":[],"label_agreement":null},{"id":"W2953163966","doi":"10.1016/j.jagp.2019.06.006","title":"Molecular Senescence Is Associated With White Matter Microstructural Damage in Late-Life Depression","year":2019,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Depression (economics); Senescence; White matter; Psychology; Gerontology; Medicine; Internal medicine; Economics","score_opus":0.007345487743370153,"score_gpt":0.27497534413216923,"score_spread":0.2676298563887991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953163966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983072,0.0010995242,0.00013262147,0.00006445217,0.000009574342,0.000004660229,0.000091219066,0.0000033106285,0.00028738397],"genre_scores_gemma":[0.99916244,0.00036580124,0.00010776631,0.000024168869,0.00001787532,0.0000035468877,0.00010055189,0.0000015372963,0.00021631956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999182,0.000018761457,0.000011981652,0.00002184958,0.000015164842,0.000014041274],"domain_scores_gemma":[0.99911636,0.00006313064,0.00061799475,0.00003760059,0.000087001295,0.000077942255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002840144,0.00024169992,0.00026854762,0.00059906946,0.00024765942,0.00045936613,0.00024420672,0.00039135883,0.00088073756],"category_scores_gemma":[0.0011649177,0.00018559895,0.00020178802,0.0005168306,0.0001949843,0.00028443767,0.00025007874,0.0003937193,0.00013482476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017459883,0.00013533312,0.9620299,0.000106365886,0.00030353374,0.0009832182,0.00032292423,0.00011511967,0.021266673,0.00013708766,0.000262166,0.012591718],"study_design_scores_gemma":[0.000003936146,0.00006613329,0.99885845,0.0000069056614,0.000028427847,0.00042541875,0.00006928291,0.00010101208,0.00023481243,0.00010694265,0.000096283955,0.0000023634418],"about_ca_topic_score_codex":0.001623773,"about_ca_topic_score_gemma":0.002073938,"teacher_disagreement_score":0.001623773,"about_ca_system_score_codex":0.00018157055,"about_ca_system_score_gemma":0.000115856354,"threshold_uncertainty_score":0.0032286048},"labels":[],"label_agreement":null},{"id":"W2953687313","doi":"10.1016/j.bbr.2019.112042","title":"Effect of aerobic exercise on white matter microstructure in the aging brain","year":2019,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Libin Cardiovascular Institute of Alberta; Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Fasciculus; White matter; Diffusion MRI; Aerobic exercise; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Uncinate fasciculus; Medicine; Psychology; Cardiology; Internal medicine; Magnetic resonance imaging","score_opus":0.07756362520729278,"score_gpt":0.4381327679662803,"score_spread":0.36056914275898755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953687313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99889994,0.0005005134,0.00011168182,0.000041463045,0.000019223151,0.0000073890387,0.00010176429,0.0000056654103,0.00031244013],"genre_scores_gemma":[0.99830085,0.00034018455,0.00014280331,0.000041579737,0.000020751964,0.000013176833,0.00008500714,0.000006286288,0.0010495764],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999224,0.000013617856,0.000005073933,0.000022882914,0.000007065032,0.000028995291],"domain_scores_gemma":[0.99983907,0.00003858945,0.000027378946,0.000022084401,0.00001669898,0.000056136498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018027535,0.00034738256,0.0003818421,0.00014277002,0.0001894954,0.00026149355,0.0001239869,0.00027922104,0.002011909],"category_scores_gemma":[0.00044766412,0.00016435227,0.00022064673,0.0001441775,0.00031876203,0.00026194646,0.00027114686,0.00037594952,0.00010040044],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.14925283,0.0051955655,0.07133344,0.00054213585,0.0015319838,0.0006917224,0.00089308067,0.000969246,0.6796346,0.00036424465,0.0007496513,0.08884149],"study_design_scores_gemma":[0.00019805197,0.007130535,0.9750289,0.00001938415,0.00046027522,0.00010950922,0.00018132945,0.0005307305,0.015448006,0.0003598861,0.00051929295,0.000014094389],"about_ca_topic_score_codex":0.002885077,"about_ca_topic_score_gemma":0.0040509757,"teacher_disagreement_score":0.002885077,"about_ca_system_score_codex":0.00012266067,"about_ca_system_score_gemma":0.00018358299,"threshold_uncertainty_score":0.0067304373},"labels":[],"label_agreement":null},{"id":"W2953691333","doi":"10.1002/glia.23661","title":"White matter plasticity and maturation in human cognition","year":2019,"lang":"en","type":"review","venue":"Glia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; University of Toronto; University Health Network; SickKids Foundation; McGill University; Mental Health Research Canada; Hospital for Sick Children","funders":"Ontario Institute for Regenerative Medicine","keywords":"White matter; Cognition; Neuroscience; Psychology; Biology; Neuroplasticity; Cognitive psychology; Developmental psychology; Medicine; Magnetic resonance imaging","score_opus":0.13386162556062928,"score_gpt":0.42031177553835386,"score_spread":0.28645014997772456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953691333","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009816558,0.99895287,0.00008485217,0.00022172183,0.00008844408,0.000002250258,0.000008091227,0.000004219129,0.00053942215],"genre_scores_gemma":[0.0009719414,0.99839056,0.00011931939,0.0000902857,0.0001323249,0.000005460727,0.000011851832,0.000001021814,0.00027728727],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998765,0.000027121441,0.000021636302,0.000029184823,0.000033686163,0.000011711737],"domain_scores_gemma":[0.9997335,0.00013798015,0.000041440617,0.000009967797,0.00005391084,0.000023230921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005180232,0.0007956976,0.0008743819,0.001962516,0.00024792165,0.0008749765,0.000671234,0.001279218,0.0023904229],"category_scores_gemma":[0.0007838103,0.0001989138,0.00036449052,0.0018475695,0.0008899184,0.0010247461,0.00068232237,0.0011972887,0.0014274884],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055062763,0.000036666977,0.00032887334,0.014562072,0.000081655795,0.00016819825,0.00008386578,0.000452145,0.0011911072,0.007026042,0.015694123,0.96032006],"study_design_scores_gemma":[0.000018591549,0.00014816238,0.0063282144,0.008965077,0.00014584363,0.0024298418,0.00016171463,0.00019807379,0.0007642753,0.017103901,0.96369565,0.00004065402],"about_ca_topic_score_codex":0.0017974286,"about_ca_topic_score_gemma":0.002082183,"teacher_disagreement_score":0.0023904229,"about_ca_system_score_codex":0.0007124786,"about_ca_system_score_gemma":0.0013384981,"threshold_uncertainty_score":0.007996738},"labels":[],"label_agreement":null},{"id":"W2953747591","doi":"10.1101/690701","title":"Early life maturation of human visual system white matter is altered by monocular enucleation","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; University of Waterloo","funders":"","keywords":"Enucleation; White matter; Monocular; Diffusion MRI; Eye Enucleation; Optic radiation; Visual system; Anatomy; Psychology; Optic tract; Ophthalmology; Neuroscience; Medicine; Optic nerve; Visual cortex; Magnetic resonance imaging; Surgery; Optics; Radiology; Physics","score_opus":0.023548082950263057,"score_gpt":0.280683093048121,"score_spread":0.25713501009785794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953747591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989453,0.00029430544,0.00021277096,0.000019312078,0.0000026035625,0.0000033996002,0.00016096862,0.000006531899,0.00035490873],"genre_scores_gemma":[0.9988279,0.00015901691,0.000246036,0.000016193404,0.0000020568546,0.000006114915,0.00016590714,0.000004304744,0.0005725423],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99991584,0.000009984153,0.000004747878,0.00002564809,0.000020589096,0.000023095601],"domain_scores_gemma":[0.9997707,0.000022920849,0.0001265133,0.000013897174,0.000031203224,0.000034695604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016036589,0.00013055313,0.00014611635,0.00037105207,0.00017145248,0.00018166372,0.0000838292,0.00017849344,0.0013000711],"category_scores_gemma":[0.00032817008,0.00007973336,0.00009186021,0.00011525901,0.00018943525,0.00014662382,0.00024330337,0.00018059208,0.00013461152],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088850723,0.000079782534,0.21536887,0.000080766884,0.00005671344,0.0023407678,0.0006191445,0.00014631185,0.76150244,0.00024569925,0.0004985562,0.018172385],"study_design_scores_gemma":[0.0000025076288,0.00015266171,0.9776129,0.000007379672,0.0000062352024,0.0013226734,0.0001596077,0.00008508077,0.020090394,0.000047854555,0.0005081018,0.0000044388444],"about_ca_topic_score_codex":0.0032479698,"about_ca_topic_score_gemma":0.0038578182,"teacher_disagreement_score":0.0032479698,"about_ca_system_score_codex":0.00020500182,"about_ca_system_score_gemma":0.00013494799,"threshold_uncertainty_score":0.0064581633},"labels":[],"label_agreement":null},{"id":"W2953829863","doi":"10.1080/02699052.2019.1605620","title":"Impact of non-invasive brain stimulation on transcallosal modulation in mild traumatic brain injury: a multimodal pilot investigation","year":2019,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; CHU Sainte-Justine Foundation","keywords":"Corpus callosum; Transcranial magnetic stimulation; Fractional anisotropy; Psychology; Traumatic brain injury; Concussion; Functional magnetic resonance imaging; White matter; Diffusion MRI; Physical medicine and rehabilitation; Neuroscience; Magnetic resonance imaging; Stimulation; Medicine; Poison control; Psychiatry; Injury prevention; Radiology","score_opus":0.07497996076537589,"score_gpt":0.3880042181379802,"score_spread":0.3130242573726043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953829863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99908566,0.00014673636,0.00040197943,0.000015568003,0.0000042626284,0.000100477744,0.000023184602,0.000007476723,0.00021458385],"genre_scores_gemma":[0.9989329,0.0001811181,0.0005087162,0.000023787838,0.000019932939,0.00013114854,0.00003506259,0.00000219197,0.00016527959],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998661,0.000040692175,0.00001083786,0.00002128206,0.000019795674,0.000041224885],"domain_scores_gemma":[0.99983275,0.000062749335,0.00002461512,0.000022399543,0.000015664818,0.000041783693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036741054,0.0004398769,0.000328253,0.00017941605,0.0002289688,0.00015765439,0.00029067448,0.00029172,0.0021154678],"category_scores_gemma":[0.00074062776,0.00009139503,0.0002512785,0.00010057647,0.0005982723,0.00018707592,0.00033115578,0.00025588978,0.00018664227],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.043580957,0.017573617,0.01730524,0.0010495045,0.0002049105,0.0032209456,0.0015817995,0.00106903,0.76991683,0.0001795463,0.00027477252,0.14404279],"study_design_scores_gemma":[0.0038345833,0.6078449,0.25779644,0.00008356494,0.00052087405,0.0052567245,0.0014186418,0.0026514523,0.11842578,0.0004005844,0.0017128699,0.000053612195],"about_ca_topic_score_codex":0.0007502221,"about_ca_topic_score_gemma":0.0010960558,"teacher_disagreement_score":0.0021154678,"about_ca_system_score_codex":0.00014106954,"about_ca_system_score_gemma":0.00033884228,"threshold_uncertainty_score":0.007076919},"labels":[],"label_agreement":null},{"id":"W2954554842","doi":"10.1111/jon.12646","title":"Brain Amyloid PET Tracer Delivery is Related to White Matter Integrity in Patients with Mild Cognitive Impairment","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Sunnybrook Health Science Centre; Baycrest Hospital; Health Sciences Centre; University of Toronto; University Health Network; St. Michael's Hospital; Centre for Addiction and Mental Health","funders":"Health Canada; Fondation Brain Canada","keywords":"White matter; Fractional anisotropy; Medicine; Hyperintensity; Pittsburgh compound B; Cerebral blood flow; Positron emission tomography; Pathology; Magnetic resonance imaging; Neuroimaging; Alzheimer's disease; Nuclear medicine; Internal medicine; Disease; Radiology; Psychiatry","score_opus":0.021372388126418503,"score_gpt":0.3094134326514754,"score_spread":0.2880410445250569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954554842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993222,0.00018556631,0.000049940823,0.000033155036,0.0000046284517,0.0000043409927,0.000062678075,0.000005160399,0.0003323242],"genre_scores_gemma":[0.9997603,0.000037074933,0.000031945998,0.00001483636,0.00000571943,0.000002929253,0.000048285154,8.768337e-7,0.00009802388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998536,0.00002403436,0.0000233226,0.000038087026,0.000032007134,0.000028808769],"domain_scores_gemma":[0.99886703,0.00017279062,0.0005802127,0.000045565244,0.00013130544,0.00020303983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003110242,0.00044761892,0.00045824607,0.00089724525,0.0004977175,0.0006108496,0.00026656836,0.00055705255,0.0014405019],"category_scores_gemma":[0.0021654663,0.00020335482,0.00026440492,0.00049000164,0.0003225238,0.00030024885,0.00028486972,0.0004697145,0.0002326245],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007189001,0.00011615878,0.9944405,0.000016789743,0.00009163817,0.0004653278,0.00012415161,0.000095962554,0.0012406101,0.000018128143,0.00009911247,0.002572745],"study_design_scores_gemma":[0.00000935481,0.00016095479,0.9987834,0.0000041606477,0.000035359237,0.0005171316,0.000056073754,0.00018940131,0.0001566925,0.000034246354,0.000050045408,0.0000031258726],"about_ca_topic_score_codex":0.005124424,"about_ca_topic_score_gemma":0.0056044534,"teacher_disagreement_score":0.005124424,"about_ca_system_score_codex":0.0003742101,"about_ca_system_score_gemma":0.00021188133,"threshold_uncertainty_score":0.010189176},"labels":[],"label_agreement":null},{"id":"W2955848820","doi":"10.7554/elife.44056","title":"Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age","year":2019,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"H2020 European Research Council; National Institute of Biomedical Imaging and Bioengineering; Seventh Framework Programme; Max-Planck-Gesellschaft; Horizon 2020 Framework Programme; Jacobs Foundation; National Institute of Mental Health; Medical Research Council; Bundesministerium für Bildung und Forschung","keywords":"Structural equation modeling; Voxel; Alcohol Use Disorders Identification Test; Voxel-based morphometry; Psychology; Neuroimaging; Grey matter; Alcohol use disorder; Developmental psychology; Clinical psychology; Alcohol; Neuroscience; Medicine; Artificial intelligence; Magnetic resonance imaging; Machine learning; Computer science; Poison control; Biology; Injury prevention; White matter; Environmental health; Radiology","score_opus":0.03187171842279533,"score_gpt":0.3125187406850376,"score_spread":0.28064702226224225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955848820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977742,0.00008754909,0.0016081955,0.000055710705,0.0000028075724,0.000006325164,0.0003198652,0.00001546865,0.00012979786],"genre_scores_gemma":[0.99617296,0.00012990448,0.0025821747,0.000008777759,0.0000025115507,0.000013706294,0.00081929925,0.00000971288,0.00026098295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997534,0.0000962232,0.000012788325,0.00006995169,0.000033440687,0.000034220524],"domain_scores_gemma":[0.9990609,0.00036516966,0.00024218245,0.00012522248,0.00011476528,0.00009177694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011100179,0.00038308906,0.00025990876,0.0006178946,0.00021277694,0.00046101134,0.00036167796,0.00033742358,0.00077871914],"category_scores_gemma":[0.003439831,0.00031942796,0.0006067427,0.00040009108,0.00019386884,0.0003944596,0.0005061344,0.0006554458,0.00018395796],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055751796,0.000041102285,0.99094373,0.000006990244,0.00009541624,0.000029890518,0.0001191098,0.00081173365,0.0007235714,0.000084516774,0.000121746874,0.0069664465],"study_design_scores_gemma":[0.0000025120773,0.000059105092,0.99227023,0.000008589351,0.000039986175,0.00008251665,0.00014763956,0.006618106,0.00038534487,0.0002154281,0.00016705871,0.0000035197647],"about_ca_topic_score_codex":0.017571596,"about_ca_topic_score_gemma":0.04780208,"teacher_disagreement_score":0.017571596,"about_ca_system_score_codex":0.00035822176,"about_ca_system_score_gemma":0.0007083872,"threshold_uncertainty_score":0.034938633},"labels":[],"label_agreement":null},{"id":"W2955883382","doi":"10.1136/gutjnl-2019-318308","title":"Role of brain imaging in disorders of brain–gut interaction: a Rome Working Team Report","year":2019,"lang":"en","type":"review","venue":"Gut","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Neuroimaging; Neuroscience; Vulvodynia; Medicine; Brain activity and meditation; Cognition; Identification (biology); Psychology; Bioinformatics; Pelvic pain; Electroencephalography; Biology","score_opus":0.0846703725919825,"score_gpt":0.4276850734605936,"score_spread":0.3430147008686111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955883382","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000050003408,0.99763024,0.00006758374,0.0011044458,0.00039085213,0.000006193247,0.000015614683,0.0000042588463,0.0007307906],"genre_scores_gemma":[0.000677661,0.99733585,0.00022524722,0.0007657584,0.000405591,0.000014082772,0.00003409385,0.0000033416547,0.00053842366],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994979,0.0001600355,0.00009152229,0.00007758468,0.00012808995,0.000044892204],"domain_scores_gemma":[0.9980457,0.0011694669,0.00014738739,0.000053356966,0.00048257242,0.000101471414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002713105,0.0008074147,0.0013078892,0.0034667791,0.00024854837,0.001718051,0.00086727826,0.0018683155,0.0027966723],"category_scores_gemma":[0.0028237752,0.00032280252,0.0010319296,0.0020727245,0.0009837783,0.0017067597,0.0011643553,0.0027921638,0.001775782],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012917629,0.000045785247,0.0002234686,0.015965298,0.00013388853,0.00016937368,0.000079892256,0.00015938081,0.0006117399,0.0059292177,0.061081246,0.91547155],"study_design_scores_gemma":[0.00004821451,0.00012340066,0.0020297745,0.024540955,0.00025432245,0.0017433628,0.000095186006,0.00009876365,0.0005054761,0.0033967597,0.96712565,0.00003803468],"about_ca_topic_score_codex":0.002257364,"about_ca_topic_score_gemma":0.0028464631,"teacher_disagreement_score":0.0034667791,"about_ca_system_score_codex":0.0013277562,"about_ca_system_score_gemma":0.0027318955,"threshold_uncertainty_score":0.014348388},"labels":[],"label_agreement":null},{"id":"W2955905284","doi":"10.1101/689778","title":"Effects of unilateral cortical resection of the visual cortex on bilateral human white matter","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institutes of Health","keywords":"White matter; Psychology; Cortex (anatomy); Resection; Visual cortex; Neuroscience; Inferior longitudinal fasciculus; Lateralization of brain function; Tractography; Anatomy; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.01951688567825972,"score_gpt":0.2928760603138892,"score_spread":0.2733591746356295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955905284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995956,0.000032970544,0.00019129453,0.000007320673,0.0000011460056,0.000003855789,0.00003340956,0.000007745058,0.0001266796],"genre_scores_gemma":[0.9997105,0.000025051531,0.00013954539,0.0000052799155,7.738176e-7,0.0000054390816,0.00004107305,0.0000032528458,0.00006910949],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999038,0.000016259184,0.0000076479155,0.000030088993,0.000018647168,0.000023676725],"domain_scores_gemma":[0.9997532,0.000076494005,0.000092643146,0.000027855434,0.000013216657,0.000036610043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104970226,0.00024032989,0.00014225242,0.00024284727,0.00013121372,0.000106664374,0.00007353157,0.000080249236,0.0013205198],"category_scores_gemma":[0.00045011088,0.000088278764,0.00013615703,0.00010582259,0.00044493098,0.00010438678,0.00024516368,0.00014844687,0.000060935763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045752,0.00043442432,0.14529917,0.00015634137,0.00027584672,0.0063226693,0.00056290865,0.0034836521,0.8001489,0.0006182808,0.00041921178,0.0377034],"study_design_scores_gemma":[0.00006831516,0.0026473638,0.9264452,0.0000124891885,0.000079788115,0.0056721335,0.00037605406,0.0024002097,0.061414994,0.00033395767,0.0005370847,0.0000125550005],"about_ca_topic_score_codex":0.0029708715,"about_ca_topic_score_gemma":0.005083873,"teacher_disagreement_score":0.0029708715,"about_ca_system_score_codex":0.0002357136,"about_ca_system_score_gemma":0.00022546557,"threshold_uncertainty_score":0.005907178},"labels":[],"label_agreement":null},{"id":"W2955932350","doi":"10.1016/j.media.2020.101758","title":"Automated characterization of noise distributions in diffusion MRI data","year":2020,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Noise (video); Scanner; Computer science; Imaging phantom; Artificial intelligence; Noise reduction; Algorithm; Sensitivity (control systems); Pattern recognition (psychology); Physics; Optics","score_opus":0.05534162756861639,"score_gpt":0.3762756233350233,"score_spread":0.3209339957664069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955932350","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020564826,0.00021327334,0.9778765,0.00006911456,0.000013452322,0.00004188697,0.00009342866,0.00085495034,0.00027264058],"genre_scores_gemma":[0.1547961,0.00038719963,0.8420998,0.00008809479,0.000034670815,0.00014191112,0.00085877813,0.00064736995,0.0009460958],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986953,0.00036784273,0.0001204052,0.0003232774,0.00039735655,0.000095787815],"domain_scores_gemma":[0.9961302,0.0018930214,0.00045401652,0.00069780514,0.00074232067,0.00008267522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024778873,0.0011270005,0.0012071524,0.0018011231,0.0005638043,0.0016827438,0.0013062349,0.0012134735,0.0008208421],"category_scores_gemma":[0.009013872,0.00049578375,0.0009151109,0.0011301392,0.00090859353,0.0014205289,0.0012989554,0.0012832541,0.0006000503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056345284,0.00016151887,0.0040375716,0.0006131995,0.00018539718,0.00043288348,0.0005671795,0.24200082,0.16172439,0.014020312,0.0023478332,0.5733454],"study_design_scores_gemma":[0.00003415045,0.0001034496,0.0041345307,0.00003968888,0.000042880612,0.00058461877,0.000075084616,0.89450186,0.08454388,0.011627714,0.0042247106,0.00008746827],"about_ca_topic_score_codex":0.0020298122,"about_ca_topic_score_gemma":0.0034009072,"teacher_disagreement_score":0.0024778873,"about_ca_system_score_codex":0.000594765,"about_ca_system_score_gemma":0.0014427877,"threshold_uncertainty_score":0.013104439},"labels":[],"label_agreement":null},{"id":"W2956022343","doi":"10.1503/jpn.170241","title":"Altered white matter connectivity in young people exposed to childhood abuse: a tract-based spatial statistics (TBSS) and tractography study","year":2019,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Institute of Psychiatry, Psychology and Neuroscience, King’s College London; Lee Kong Chian School of Medicine, Nanyang Technological University; King's College London; Imperial College London; Nanyang Technological University; National Institute for Health and Care Research; Wellcome Trust","keywords":"Fractional anisotropy; Uncinate fasciculus; Fasciculus; Inferior longitudinal fasciculus; White matter; Psychiatry; Psychology; Corpus callosum; Superior longitudinal fasciculus; Splenium; Tractography; Child abuse; Medicine; Clinical psychology; Poison control; Neuroscience; Magnetic resonance imaging; Injury prevention","score_opus":0.019118047283042033,"score_gpt":0.3101815627143095,"score_spread":0.2910635154312675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956022343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990765,0.00013454969,0.00042214384,0.00001682642,0.0000011545767,0.000013716491,0.00020293875,0.0000055547844,0.00012658277],"genre_scores_gemma":[0.9988827,0.00012092404,0.00067447213,0.000006673365,0.0000028532932,0.000013086253,0.00022389732,0.000004850524,0.00007062309],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981314,0.000040069233,0.000026032674,0.00004700481,0.00003474108,0.00003917796],"domain_scores_gemma":[0.9993284,0.00009310233,0.00034243558,0.00007771635,0.00007463353,0.00008389641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053384673,0.00025319232,0.00034079712,0.0012932122,0.00042563924,0.0004600473,0.00018388624,0.000231128,0.0011512954],"category_scores_gemma":[0.0013322466,0.00022873425,0.00041249485,0.001362053,0.00047345273,0.0003211431,0.0004901967,0.00020349021,0.00015722474],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015206393,0.000027435288,0.9908948,0.0000359197,0.00013738395,0.0005044608,0.0007703774,0.00014561805,0.0031353065,0.00007264308,0.00008907175,0.00403495],"study_design_scores_gemma":[0.0000030209856,0.00005264757,0.9974305,0.0000086542905,0.000034945046,0.0011953672,0.00030931956,0.0004118047,0.00034611896,0.00005721531,0.00014740838,0.000003093219],"about_ca_topic_score_codex":0.008733228,"about_ca_topic_score_gemma":0.014276571,"teacher_disagreement_score":0.008733228,"about_ca_system_score_codex":0.0004884057,"about_ca_system_score_gemma":0.00048755217,"threshold_uncertainty_score":0.01736474},"labels":[],"label_agreement":null},{"id":"W2956846297","doi":"10.1007/s00062-019-00805-0","title":"Microstructural White Matter Alterations in Mild Cognitive Impairment and Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Clinical Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Corpus callosum; Receiver operating characteristic; Area under the curve; Montreal Cognitive Assessment; White matter; Audiology; Splenium; Alzheimer's disease; Psychology; Medicine; Internal medicine; Dementia; Cardiology; Magnetic resonance imaging; Pathology; Disease; Radiology","score_opus":0.09006671855847243,"score_gpt":0.419373250352193,"score_spread":0.3293065317937206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956846297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99567455,0.0029095593,0.000105383835,0.0001080209,0.000017158003,0.000013277848,0.0000886323,0.000008502346,0.0010747439],"genre_scores_gemma":[0.99872774,0.00068391376,0.00015135936,0.00004099223,0.000039491457,0.0000061803253,0.00007302722,0.0000015062211,0.00027571572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998504,0.00003261423,0.000029101739,0.000024142622,0.00003777887,0.000025910642],"domain_scores_gemma":[0.9995741,0.0000718353,0.00018947931,0.000021514921,0.000055990862,0.00008710368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005903927,0.00051012443,0.00031422818,0.0025175128,0.00045506767,0.00055860024,0.00040143263,0.00042040125,0.0008252985],"category_scores_gemma":[0.0014224369,0.00028013164,0.00020712573,0.0009292804,0.00057886366,0.00047358876,0.0004676493,0.00030384207,0.0001430757],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006550689,0.00060278754,0.8939603,0.0004614437,0.00077267695,0.009764503,0.000881666,0.0006057629,0.025478933,0.00047914003,0.0008191587,0.05962295],"study_design_scores_gemma":[0.0000101246715,0.00014148864,0.99660754,0.000012076851,0.000046652436,0.0018750342,0.00014482929,0.00015285955,0.00048913556,0.0003484004,0.00016642571,0.000005463736],"about_ca_topic_score_codex":0.0076194,"about_ca_topic_score_gemma":0.009206095,"teacher_disagreement_score":0.0076194,"about_ca_system_score_codex":0.0004508531,"about_ca_system_score_gemma":0.00036830653,"threshold_uncertainty_score":0.01515013},"labels":[],"label_agreement":null},{"id":"W2957612371","doi":"10.1016/j.neuroimage.2019.116017","title":"White matter information flow mapping from diffusion MRI and EEG","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Université de Sherbrooke; École de Technologie Supérieure","funders":"H2020 European Research Council; European Research Council","keywords":"Diffusion MRI; Electroencephalography; White matter; Computer science; Tractography; Information flow; Artificial intelligence; Diffusion; Pattern recognition (psychology); Neuroscience; Computer vision; Magnetic resonance imaging; Psychology; Physics","score_opus":0.019871119711756677,"score_gpt":0.27120904374643257,"score_spread":0.25133792403467586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2957612371","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20597719,0.012116556,0.7660226,0.0012210625,0.00041303932,0.00025590954,0.0020864045,0.0012789709,0.010628239],"genre_scores_gemma":[0.7117297,0.010014508,0.27039036,0.00024134791,0.0005817325,0.00015357255,0.0010210385,0.00029368102,0.005574086],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991524,0.000023943689,0.000006064881,0.00001904782,0.000024360768,0.000011387051],"domain_scores_gemma":[0.9997693,0.00011861268,0.000031607084,0.000017263319,0.00004576194,0.000017539658],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046495858,0.00048638773,0.00025535605,0.001690887,0.00021616324,0.0011690842,0.00029283966,0.00060167303,0.0025871585],"category_scores_gemma":[0.0025620367,0.000243196,0.00033736954,0.001191718,0.00035164587,0.0015881851,0.00029970545,0.0005403653,0.00061881955],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089351175,0.0001238981,0.008697135,0.001122461,0.00022345688,0.0015387207,0.00037389665,0.011490318,0.26581377,0.012971005,0.0053497734,0.691402],"study_design_scores_gemma":[0.0003673815,0.0009362904,0.12120138,0.00067072327,0.0006326217,0.01941771,0.0008760107,0.28956345,0.36717963,0.15856707,0.04022902,0.00035867593],"about_ca_topic_score_codex":0.0014785138,"about_ca_topic_score_gemma":0.0018703564,"teacher_disagreement_score":0.0025871585,"about_ca_system_score_codex":0.00016164903,"about_ca_system_score_gemma":0.0003606999,"threshold_uncertainty_score":0.008654952},"labels":[],"label_agreement":null},{"id":"W2957869398","doi":"10.1038/s41597-019-0129-z","title":"A macaque connectome for large-scale network simulations in TheVirtualBrain","year":2019,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; McGill University; Montreal Neurological Institute and Hospital; Baycrest Hospital","funders":"Deutsche Forschungsgemeinschaft; European Commission","keywords":"Connectome; Macaque; Connectomics; Tractography; Computer science; Human Connectome Project; Diffusion MRI; Resting state fMRI; Neuroscience; Scale (ratio); Tracing; Functional connectivity; Biology; Cartography; Magnetic resonance imaging; Geography; Medicine","score_opus":0.11977953947096279,"score_gpt":0.40320857664028026,"score_spread":0.28342903716931744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2957869398","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5409583,0.00043309433,0.43246716,0.0019188933,0.00017213811,0.00022394002,0.004813553,0.0043366593,0.014676235],"genre_scores_gemma":[0.7854897,0.00035619264,0.20571832,0.00028789227,0.000045373887,0.00084631424,0.0033333898,0.0009175236,0.0030052683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99990785,0.000036900667,0.0000041585727,0.00001834717,0.000020844069,0.000011883049],"domain_scores_gemma":[0.9995023,0.00028004794,0.000037617225,0.0000616811,0.000068991794,0.00004930198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004496218,0.00048229264,0.00034910394,0.00075527566,0.000650314,0.00055229384,0.0011115294,0.0010950346,0.0046307333],"category_scores_gemma":[0.0022555206,0.00034924046,0.00076166,0.00057567627,0.0005185508,0.00059399876,0.0010084411,0.000762691,0.00030822755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059624006,0.000061744024,0.0021203083,0.00011120019,0.000065519074,0.0002628643,0.00024062391,0.9607181,0.005224232,0.021563176,0.0037309742,0.005841607],"study_design_scores_gemma":[0.000017144504,0.000013413338,0.000571825,0.000010177757,0.000006212574,0.000038339127,0.000019936622,0.9881991,0.0005594629,0.00788427,0.002669943,0.00001018266],"about_ca_topic_score_codex":0.0163245,"about_ca_topic_score_gemma":0.019112041,"teacher_disagreement_score":0.0163245,"about_ca_system_score_codex":0.00076278835,"about_ca_system_score_gemma":0.0010499811,"threshold_uncertainty_score":0.03245896},"labels":[],"label_agreement":null},{"id":"W2961056674","doi":"10.3389/fcell.2019.00124","title":"Structural and Diffusion MRI Analyses With Histological Observations in Patients With Lissencephaly","year":2019,"lang":"en","type":"article","venue":"Frontiers in Cell and Developmental Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; St. Francis Xavier University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"Lissencephaly; White matter; Magnetic resonance imaging; Diffusion MRI; Doublecortin; Biology; Anatomy; Medicine; Pathology; Neuroscience; Radiology; Central nervous system; Genetics","score_opus":0.03643628097830259,"score_gpt":0.28764108186933757,"score_spread":0.251204800891035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961056674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994205,0.00011036061,0.000094042145,0.000016669257,0.000001922584,0.0000037305579,0.00006162796,0.000008363368,0.00028276173],"genre_scores_gemma":[0.9994381,0.00013131314,0.00020411138,0.000010786058,0.0000040075997,0.0000045736374,0.00007903438,0.0000035230944,0.00012441931],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998312,0.000018232393,0.00003479247,0.000060887593,0.000029043455,0.000025823976],"domain_scores_gemma":[0.9994461,0.00007011957,0.00030339663,0.00003974535,0.00007007511,0.000070654154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032286224,0.00045449633,0.0003050097,0.0020331154,0.00039977065,0.00033369783,0.00021250304,0.0003736985,0.0011611776],"category_scores_gemma":[0.0011294064,0.00035418622,0.00015636538,0.0006614673,0.00052105787,0.0002721131,0.00021972512,0.00019277356,0.00018805437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006067919,0.00007927508,0.89701355,0.00006446635,0.000100957375,0.018974008,0.0011979333,0.00027140905,0.07472267,0.00012376718,0.00014175207,0.006703341],"study_design_scores_gemma":[0.000013201901,0.00016202149,0.975873,0.000009002322,0.0000490797,0.019599205,0.00048815884,0.00024124216,0.0032247445,0.00011873738,0.00021280533,0.000008930426],"about_ca_topic_score_codex":0.0020534943,"about_ca_topic_score_gemma":0.0026099577,"teacher_disagreement_score":0.0020534943,"about_ca_system_score_codex":0.0002667392,"about_ca_system_score_gemma":0.00021583168,"threshold_uncertainty_score":0.004083097},"labels":[],"label_agreement":null},{"id":"W2961338082","doi":"10.1002/hbm.24706","title":"A multiparametric analysis of white matter maturation during late childhood and adolescence","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"White matter; Psychology; Developmental psychology; White (mutation); Medicine; Biology; Magnetic resonance imaging; Genetics","score_opus":0.02860885313794186,"score_gpt":0.3029596770906897,"score_spread":0.27435082395274785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961338082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989611,0.00013698378,0.0005657227,0.0000072826124,0.0000010576325,0.0000024523736,0.00017315712,0.000009230647,0.00014293648],"genre_scores_gemma":[0.9991386,0.000063530664,0.00050706137,0.0000022846612,0.0000015240024,0.0000057131047,0.00013693,0.000004727431,0.00013956307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998863,0.000024573372,0.0000110855135,0.000034062392,0.000019444218,0.00002454653],"domain_scores_gemma":[0.9995832,0.00008880815,0.00017850228,0.000037267928,0.00006751839,0.0000446569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040425,0.00019501869,0.00015207406,0.000814315,0.00014321288,0.00029459852,0.00011904016,0.00019736314,0.000544542],"category_scores_gemma":[0.00088741677,0.000112827605,0.00019947544,0.00044064177,0.000101075944,0.00021318879,0.0002836807,0.00013128418,0.00010778324],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004167419,0.000044347966,0.92597544,0.000052699932,0.0001214844,0.0003844365,0.00055518054,0.0006664873,0.047075495,0.00016579061,0.00019195987,0.024349986],"study_design_scores_gemma":[7.638832e-7,0.000041177573,0.99742126,0.0000034610025,0.0000111607515,0.00024761763,0.000085715175,0.00050737563,0.0015077537,0.0000309537,0.00014000728,0.0000026607104],"about_ca_topic_score_codex":0.0021977434,"about_ca_topic_score_gemma":0.0024360442,"teacher_disagreement_score":0.0021977434,"about_ca_system_score_codex":0.0001397994,"about_ca_system_score_gemma":0.0001541432,"threshold_uncertainty_score":0.0043699145},"labels":[],"label_agreement":null},{"id":"W2962033364","doi":"10.1101/703835","title":"Comparison of CPU and GPU Bayesian Estimates of Fibre Orientations from Diffusion MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"BC Children's Hospital","keywords":"Markov chain Monte Carlo; Computer science; Diffusion; Voxel; Central processing unit; Bayesian probability; Monte Carlo method; Markov chain; Algorithm; Fraction (chemistry); Diffusion MRI; Artificial intelligence; Mathematics; Statistics; Physics; Machine learning; Computer hardware","score_opus":0.03499608116880228,"score_gpt":0.3237638238203944,"score_spread":0.28876774265159216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962033364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61236197,0.0011720773,0.35627785,0.0006293849,0.0002458115,0.00015427462,0.0018457733,0.016890489,0.010422454],"genre_scores_gemma":[0.73192203,0.00031862047,0.25797766,0.00018200421,0.00004889984,0.00015494625,0.003601107,0.0023774311,0.0034174237],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989668,0.00029804217,0.000075681375,0.00019314366,0.0003902409,0.00007607932],"domain_scores_gemma":[0.9965933,0.0015982789,0.00016116603,0.00056505605,0.00094797276,0.00013424664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019294776,0.0006771997,0.00078402954,0.0010250087,0.0003676472,0.0018852799,0.0010489428,0.0008810834,0.005450438],"category_scores_gemma":[0.012329409,0.0004634676,0.00044019084,0.0009564488,0.0004092847,0.001037993,0.0010611502,0.0010327395,0.0013993751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056657023,0.00045414118,0.019775268,0.00064149493,0.00046277602,0.00024987524,0.0005592818,0.28858525,0.04063128,0.010615622,0.016756954,0.61560243],"study_design_scores_gemma":[0.00014304048,0.00019996798,0.008864159,0.00004872475,0.00004142518,0.00014101501,0.00006856497,0.9632876,0.021130113,0.00329479,0.0027399403,0.00004074399],"about_ca_topic_score_codex":0.006911509,"about_ca_topic_score_gemma":0.00697865,"teacher_disagreement_score":0.006911509,"about_ca_system_score_codex":0.00065310526,"about_ca_system_score_gemma":0.0010752677,"threshold_uncertainty_score":0.018233478},"labels":[],"label_agreement":null},{"id":"W2964269336","doi":"10.1090/tran/7641","title":"From dimers to webs","year":2018,"lang":"en","type":"article","venue":"Transactions of the American Mathematical Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Perimeter Institute","funders":"National Science Foundation","keywords":"Algorithm; Annotation; Computer science; Artificial intelligence; Type (biology); Mathematics; Biology","score_opus":0.041730274093232565,"score_gpt":0.3582147635843501,"score_spread":0.31648448949111757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964269336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054505598,0.0009045478,0.61019474,0.0040723896,0.0013925419,0.00021566494,0.0019930128,0.0026086878,0.32411274],"genre_scores_gemma":[0.60122,0.0011875881,0.20248082,0.002744995,0.0013895744,0.0008527754,0.0034571053,0.0033243878,0.18334277],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99775726,0.0004872435,0.00012590861,0.0007378796,0.00052172696,0.00036995203],"domain_scores_gemma":[0.9981342,0.00036124708,0.00016901866,0.00065965485,0.00036137007,0.00031460306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011297937,0.0012066702,0.0010493551,0.0023208659,0.0032095707,0.0063296054,0.0022875716,0.002830207,0.052624922],"category_scores_gemma":[0.003740854,0.00088425836,0.0018976659,0.0017816696,0.0027601751,0.011855617,0.0052427268,0.0034502132,0.015106006],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008897574,0.000012577255,0.000054225835,0.000030553303,0.0000035140604,0.000048828602,0.00009761451,0.000931773,0.00019366844,0.9904882,0.0039533335,0.0041767033],"study_design_scores_gemma":[0.000006456156,0.000008655471,0.000042872973,0.000016915006,0.000003969697,0.000075910466,0.00007064515,0.006657661,0.0003516123,0.9765232,0.01623075,0.000011401841],"about_ca_topic_score_codex":0.001806871,"about_ca_topic_score_gemma":0.0019441778,"teacher_disagreement_score":0.052624922,"about_ca_system_score_codex":0.0017355027,"about_ca_system_score_gemma":0.0009465917,"threshold_uncertainty_score":0.17604792},"labels":[],"label_agreement":null},{"id":"W2965216242","doi":"10.1101/730366","title":"Mapping the living mouse brain neural architecture: strain specific patterns of brain structural and functional connectivity","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Neuroscience; Corpus callosum; Splenium; Connectome; Diffusion MRI; Biology; Human Connectome Project; Brain mapping; Psychology; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.0428710507140658,"score_gpt":0.2623174863620694,"score_spread":0.21944643564800362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965216242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9767596,0.0009787534,0.019386446,0.00006355198,0.000022949382,0.000027366177,0.0013471537,0.0002590692,0.00115516],"genre_scores_gemma":[0.9709283,0.0008298831,0.024100093,0.000068830064,0.000011007151,0.00011215074,0.0013199567,0.00019647696,0.0024332376],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997652,0.000024952804,0.000020754518,0.00010096108,0.00005445621,0.0000337289],"domain_scores_gemma":[0.9996594,0.00004880125,0.00014274898,0.00006062014,0.000034694884,0.000053665914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030073762,0.0005176917,0.00019934976,0.0015186846,0.00022045875,0.0004487203,0.00034212804,0.00042627062,0.0014831256],"category_scores_gemma":[0.00020967526,0.000292393,0.00027371646,0.00037553112,0.0005289735,0.00024989544,0.00032185632,0.00067974505,0.0001980529],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047434474,0.000019809586,0.0008447183,0.00002203698,0.000014092561,0.00003410106,0.000020947553,0.00017691252,0.99747247,0.00014234014,0.000020810818,0.001184252],"study_design_scores_gemma":[0.000020193549,0.00057141745,0.09579686,0.000048248257,0.0001347942,0.001241017,0.00012527661,0.0057594306,0.8934268,0.0006922653,0.0021434592,0.00004023258],"about_ca_topic_score_codex":0.0009341456,"about_ca_topic_score_gemma":0.0014544353,"teacher_disagreement_score":0.0015186846,"about_ca_system_score_codex":0.00018772134,"about_ca_system_score_gemma":0.00013082418,"threshold_uncertainty_score":0.0049614906},"labels":[],"label_agreement":null},{"id":"W2965361043","doi":"10.1038/s41467-019-11244-3","title":"Brainstem and spinal cord MRI identifies altered sensorimotor pathways post-stroke","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Corticospinal tract; Brainstem; Spinal cord; Pyramidal tracts; Neuroscience; Stroke (engine); Medicine; Magnetic resonance imaging; Anatomy; Psychology; Diffusion MRI; Radiology","score_opus":0.058971944821037674,"score_gpt":0.36943882185410293,"score_spread":0.31046687703306525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965361043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951975,0.001381856,0.0013856249,0.00011789397,0.0000115589155,0.000025932814,0.00023079525,0.000057996385,0.0015909738],"genre_scores_gemma":[0.9976539,0.0006411297,0.0006546515,0.0000433862,0.000008402789,0.000011239532,0.00013224203,0.0000058179166,0.0008492973],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988866,0.000016720875,0.0000116687115,0.000031807416,0.000023951434,0.000027156946],"domain_scores_gemma":[0.9998436,0.000019709123,0.00006878806,0.000012366067,0.000026222617,0.000029256038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019366431,0.00031971524,0.00028113634,0.00090919674,0.00019467759,0.00031796165,0.00014174319,0.0004440226,0.0026972766],"category_scores_gemma":[0.00053881697,0.00013566481,0.00013183389,0.00030051664,0.00028837073,0.00033599883,0.00024735383,0.0002727024,0.00034142018],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015648592,0.00017609948,0.07737094,0.0004533895,0.00027853166,0.0024171574,0.0003580926,0.0004305364,0.87397337,0.00021171736,0.000574005,0.042191304],"study_design_scores_gemma":[0.000014910812,0.00076211727,0.9468627,0.00003743648,0.00011821016,0.003550081,0.00017759025,0.0006313738,0.047050808,0.0002584228,0.00052238005,0.000014011607],"about_ca_topic_score_codex":0.0023025386,"about_ca_topic_score_gemma":0.0048625437,"teacher_disagreement_score":0.0026972766,"about_ca_system_score_codex":0.00019809787,"about_ca_system_score_gemma":0.00021780822,"threshold_uncertainty_score":0.009023309},"labels":[],"label_agreement":null},{"id":"W2965413344","doi":"10.3389/fnagi.2019.00211","title":"Topographical Heterogeneity of Alzheimer’s Disease Based on MR Imaging, Tau PET, and Amyloid PET","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Fondation Brain Canada; Ministry of Science and ICT, South Korea; Korea Health Industry Development Institute; College of Medicine, Seoul National University; National Research Foundation; Fonds de Recherche du Québec - Santé; Seoul National University","keywords":"Atrophy; Dementia; Magnetic resonance imaging; Pittsburgh compound B; Positron emission tomography; Pathology; Medicine; Clinical Dementia Rating; Alzheimer's disease; Nuclear medicine; Disease; Radiology","score_opus":0.029856257097428607,"score_gpt":0.31957953744253653,"score_spread":0.2897232803451079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965413344","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944471,0.00072771666,0.00088349934,0.000046804777,0.000010848795,0.000048215694,0.000500133,0.000034032662,0.003301492],"genre_scores_gemma":[0.9988869,0.0001185653,0.00031070586,0.000016101714,0.000010696757,0.000010794686,0.0003215853,0.000007906453,0.00031668955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996767,0.000052808475,0.00006158628,0.00009318996,0.000060697086,0.0000549868],"domain_scores_gemma":[0.9992704,0.00012527585,0.00026997746,0.000103328,0.00013189661,0.0000991872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070205535,0.0003958534,0.0003982668,0.0016139762,0.00038442286,0.0009630095,0.0004117841,0.0003510761,0.0028806508],"category_scores_gemma":[0.0014856028,0.00019461058,0.0005268124,0.00065160316,0.0003500177,0.0005959509,0.00045246034,0.00023820238,0.0009653636],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013273695,0.00009860772,0.9471581,0.0000755192,0.00031981216,0.0023021963,0.00043904365,0.00012912625,0.022985332,0.0003577676,0.0007464005,0.024060681],"study_design_scores_gemma":[0.0000117889185,0.0000824401,0.9926912,0.000011584077,0.000053576696,0.004931181,0.00017572482,0.00020766394,0.0009563151,0.00047658893,0.00039344377,0.000008377439],"about_ca_topic_score_codex":0.002647252,"about_ca_topic_score_gemma":0.003407122,"teacher_disagreement_score":0.0028806508,"about_ca_system_score_codex":0.00028603588,"about_ca_system_score_gemma":0.00022451204,"threshold_uncertainty_score":0.00963676},"labels":[],"label_agreement":null},{"id":"W2965430693","doi":"10.1016/j.nicl.2019.101975","title":"White matter integrity is associated with gait impairment and falls in mild cognitive impairment. Results from the gait and brain study","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkwood Institute; Lawson Health Research Institute; Western University","funders":"Ontario Ministry of Research and Innovation; Canadian Institutes of Health Research; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Gait; Cognitive impairment; Physical medicine and rehabilitation; White matter; Cognition; Psychology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.07902827855567719,"score_gpt":0.3935651748319158,"score_spread":0.3145368962762386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965430693","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991328,0.00017746186,0.000043662567,0.000026075915,0.0000035561675,0.000008806687,0.00036864157,0.000004091297,0.00023486505],"genre_scores_gemma":[0.99913424,0.000059602273,0.00007561981,0.000012370853,0.0000066143766,0.000008501042,0.000573236,0.000001607807,0.00012810626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997985,0.00003056322,0.00003481546,0.000046309786,0.00005808338,0.000031783296],"domain_scores_gemma":[0.9990772,0.00006076108,0.0004502976,0.000042937976,0.00014076283,0.00022797807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004988912,0.00039928523,0.0003799061,0.0010608454,0.00044648346,0.0005018478,0.0003249017,0.0004545474,0.001144686],"category_scores_gemma":[0.0017818926,0.0002074908,0.00037897917,0.00084232487,0.00022197378,0.00025288932,0.00049523776,0.0003937895,0.0002138335],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001516223,0.000033333275,0.9981382,0.0000117318405,0.00008926149,0.00008171698,0.000046865825,0.000023598452,0.00029643148,0.0000061019227,0.00008698794,0.0010340591],"study_design_scores_gemma":[0.0000023771868,0.00003188224,0.9997482,0.0000017785452,0.00001278905,0.00010257536,0.000018585275,0.000027490683,0.000021805921,0.000007994678,0.000023676741,8.964648e-7],"about_ca_topic_score_codex":0.0070240134,"about_ca_topic_score_gemma":0.010009936,"teacher_disagreement_score":0.0070240134,"about_ca_system_score_codex":0.00021963338,"about_ca_system_score_gemma":0.0002635457,"threshold_uncertainty_score":0.013966262},"labels":[],"label_agreement":null},{"id":"W2965493050","doi":"10.1093/cercor/bhz143","title":"Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory","year":2019,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Neurological Institute and Hospital","funders":"Medical Research Council; Wellcome Trust","keywords":"Diffusion MRI; White matter; Neuroscience; Anterior commissure; Tractography; Corpus callosum; Psychology; Commissure; Temporal lobe; Hippocampal formation; Cingulum (brain); Anatomy; Fractional anisotropy; Hippocampus; Magnetic resonance imaging; Biology; Medicine","score_opus":0.044399753488846117,"score_gpt":0.3165180994592483,"score_spread":0.2721183459704022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965493050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9729716,0.0016852429,0.022640357,0.0003943489,0.000022087524,0.000019139274,0.00012649714,0.000100370366,0.0020403597],"genre_scores_gemma":[0.9916421,0.0003852681,0.0072519775,0.000042714422,0.000013285114,0.000006107764,0.000063156964,0.000016282402,0.0005791043],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999144,0.000012142326,0.0000042245115,0.000037369016,0.000019472787,0.000012495787],"domain_scores_gemma":[0.99960643,0.00009441832,0.000117291995,0.00009640432,0.000041797583,0.0000436482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003799014,0.0002751878,0.00018311638,0.0005353783,0.00027896347,0.00071404944,0.00028184403,0.00043953402,0.0011574588],"category_scores_gemma":[0.0010780859,0.00016487385,0.00015726927,0.00025864778,0.001099849,0.00074211665,0.00037464182,0.00046091178,0.00022433551],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075089344,0.00017368776,0.1024784,0.00033567604,0.00024375269,0.0015556485,0.0015381128,0.0037584614,0.7131165,0.007958849,0.0007405852,0.16734941],"study_design_scores_gemma":[0.00007017907,0.0010135055,0.6924397,0.00018722417,0.00031114332,0.0063915052,0.0015244584,0.044421516,0.21473004,0.028187972,0.010616126,0.000106652406],"about_ca_topic_score_codex":0.0052582803,"about_ca_topic_score_gemma":0.010896652,"teacher_disagreement_score":0.0052582803,"about_ca_system_score_codex":0.0002621511,"about_ca_system_score_gemma":0.0006035903,"threshold_uncertainty_score":0.01045537},"labels":[],"label_agreement":null},{"id":"W2965530185","doi":"","title":"Non-negative least squares fitting of multi-exponential T2 decay data: Are we able to accurately measure the fraction of myelin water?","year":2019,"lang":"en","type":"article","venue":"Lund University Publications (Lund University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Exponential function; Fraction (chemistry); Myelin; Measure (data warehouse); Exponential decay; Least-squares function approximation; Mathematics; Chemistry; Biological system; Statistics; Internal medicine; Biology; Mathematical analysis; Physics; Chromatography; Medicine; Computer science; Data mining; Central nervous system","score_opus":0.14249787062635028,"score_gpt":0.328629429196639,"score_spread":0.18613155857028874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965530185","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20458208,0.002123488,0.7869517,0.0015045957,0.000145072,0.00010199743,0.0003966893,0.0019418407,0.0022524404],"genre_scores_gemma":[0.66212285,0.0021354828,0.3307447,0.00060263305,0.00004555162,0.00032437054,0.00091850443,0.0014546154,0.001651335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99913967,0.0003500237,0.000054042415,0.00018175658,0.00019316786,0.00008125843],"domain_scores_gemma":[0.99564713,0.0027081533,0.0004831561,0.0005379271,0.00050542486,0.00011818481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054419353,0.0012537839,0.000991691,0.0004164792,0.00046668164,0.0010091725,0.0012149521,0.0017664572,0.0013744798],"category_scores_gemma":[0.02501422,0.0006582274,0.0005968858,0.00075424643,0.001210939,0.003889358,0.00083842827,0.0017080837,0.001004929],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024805737,0.0003711021,0.011734852,0.0028245344,0.0007033659,0.0010295316,0.0017400463,0.43954656,0.3333624,0.020145018,0.006641208,0.17942087],"study_design_scores_gemma":[0.00010782187,0.00027588475,0.0041229343,0.00019324495,0.00009270039,0.00048644177,0.00023648997,0.8484793,0.11642324,0.021894526,0.0074726176,0.00021488899],"about_ca_topic_score_codex":0.0032832357,"about_ca_topic_score_gemma":0.003072592,"teacher_disagreement_score":0.0054419353,"about_ca_system_score_codex":0.00052831316,"about_ca_system_score_gemma":0.0013059705,"threshold_uncertainty_score":0.028780043},"labels":[],"label_agreement":null},{"id":"W2965761097","doi":"10.2967/jnumed.118.225508","title":"Multimodal <sup>18</sup>F-AV-1451 and MRI Findings in Nonfluent Variant of Primary Progressive Aphasia: Possible Insights on Nodal Propagation of Tau Protein Across the Syntactic Network","year":2019,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Fractional anisotropy; White matter; Primary progressive aphasia; Aphasia; Node (physics); Fasciculus; Neuroscience; Neuroimaging; Psychology; Medicine; Magnetic resonance imaging; Physics; Disease; Pathology; Dementia; Frontotemporal dementia; Radiology","score_opus":0.023955157340165182,"score_gpt":0.31416947141654633,"score_spread":0.29021431407638115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965761097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999574,0.000055123845,0.00007962292,0.00002179337,0.0000010734225,0.0000044749577,0.000017552564,0.0000035759026,0.00024278123],"genre_scores_gemma":[0.9997156,0.00003424907,0.000103980725,0.000017233146,0.0000070516444,0.0000032363173,0.00002569669,0.0000026645805,0.00009021441],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.000016493324,0.000014146964,0.000034797762,0.00001869163,0.000023240182],"domain_scores_gemma":[0.9995956,0.000111122674,0.00017767634,0.000026489974,0.000027708382,0.000061383806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028361013,0.00060942315,0.0003547477,0.0009605487,0.00038993065,0.00032508976,0.0003282148,0.0006470399,0.002417012],"category_scores_gemma":[0.0010317694,0.00036262342,0.00019876669,0.00026477274,0.00076904957,0.0004956744,0.00019204119,0.00034628957,0.00025821116],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024456754,0.00025002228,0.710477,0.000106417974,0.00019464774,0.16215728,0.0020925056,0.00032480914,0.113238305,0.00018842709,0.0002411578,0.008283798],"study_design_scores_gemma":[0.00005107523,0.0005152771,0.9053057,0.00001166299,0.00007130337,0.08869785,0.00039917085,0.0006270375,0.0040150667,0.00015926214,0.00013350781,0.00001307479],"about_ca_topic_score_codex":0.0038746546,"about_ca_topic_score_gemma":0.004487997,"teacher_disagreement_score":0.0038746546,"about_ca_system_score_codex":0.00034722115,"about_ca_system_score_gemma":0.00021370857,"threshold_uncertainty_score":0.008085668},"labels":[],"label_agreement":null},{"id":"W2966311196","doi":"10.3389/fneur.2019.00884","title":"Microstructural White Matter Characteristics in Parkinson's Disease With Depression: A Diffusion Tensor Imaging Replication Study","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Sanofi Genzyme; Genentech; H. Lundbeck A/S; Teva Pharmaceutical Industries; Union Chimique Belge; Sanofi; Biogen; GlaxoSmithKline; Servier; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; Michael J. Fox Foundation for Parkinson's Research","keywords":"Diffusion MRI; White matter; Neuroimaging; Neuropathology; Depression (economics); Psychology; Clinical psychology; Fractional anisotropy; Replication (statistics); Parkinson's disease; Neuroscience; Medicine; Disease; Psychiatry; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.010471842581975623,"score_gpt":0.2728891978692175,"score_spread":0.26241735528724186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966311196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999263,0.00010438602,0.00023778013,0.000020869957,0.0000050355047,0.00004683004,0.00017137887,0.0000027308074,0.00014791205],"genre_scores_gemma":[0.9993432,0.000029866911,0.00030395584,0.000017458737,0.000004650358,0.000025873627,0.00020715104,0.0000022945082,0.00006552989],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990903,0.000323854,0.00012177928,0.0002656806,0.00013075118,0.000067612455],"domain_scores_gemma":[0.99653625,0.0005173993,0.00079114205,0.0013612689,0.00056231016,0.00023160304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029422587,0.00047877556,0.00040110233,0.00042278145,0.0006826779,0.00060881564,0.0005977306,0.0005562217,0.0006768732],"category_scores_gemma":[0.0069997413,0.00035356937,0.0005848213,0.0003881048,0.0004425415,0.00042952443,0.0007641445,0.0005516102,0.0003063567],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066633587,0.00031093412,0.9863565,0.000055171815,0.00039600022,0.0006618169,0.0015875595,0.00009137507,0.0035953117,0.00006935384,0.00024652688,0.0059630275],"study_design_scores_gemma":[0.00009692869,0.0007973429,0.99554515,0.000018105891,0.00018618128,0.0015545966,0.0005971142,0.0002476072,0.00039859983,0.00011857459,0.00042798076,0.000011868756],"about_ca_topic_score_codex":0.0046638628,"about_ca_topic_score_gemma":0.0061707487,"teacher_disagreement_score":0.0046638628,"about_ca_system_score_codex":0.0003466812,"about_ca_system_score_gemma":0.00033139423,"threshold_uncertainty_score":0.015560389},"labels":[],"label_agreement":null},{"id":"W2967310397","doi":"10.3171/2019.5.jns19890","title":"Intraoperative acquisition of DTI in cranial neurosurgery: readout-segmented DTI versus standard single-shot DTI","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Diffusion MRI; Artifact (error); Multislice; Nuclear medicine; Magnetic resonance imaging; Tractography; Intraoperative MRI; Radiology; Interventional magnetic resonance imaging; Neuroscience","score_opus":0.10298990287274894,"score_gpt":0.3542022665953433,"score_spread":0.25121236372259437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967310397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754125,0.0016153897,0.021988798,0.00009600189,0.000032391537,0.000039711587,0.000070912414,0.000103906685,0.00064040185],"genre_scores_gemma":[0.9589882,0.0010499842,0.0394186,0.000035487803,0.000041811025,0.000032436714,0.0001937416,0.000054519012,0.00018518344],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99972194,0.00010174843,0.000030145151,0.0000592918,0.00006824893,0.000018558007],"domain_scores_gemma":[0.9990305,0.00036342425,0.000213365,0.00012853739,0.00017647316,0.000087713925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012686793,0.0005579415,0.00028421482,0.0004352603,0.00015456325,0.00052110874,0.00036251402,0.00034803478,0.0005747421],"category_scores_gemma":[0.003777647,0.00024534116,0.00015999474,0.00032004158,0.000433467,0.0006139293,0.0004181588,0.00037350014,0.0001702069],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012123596,0.000401441,0.11052605,0.0010213146,0.00039783787,0.0013194289,0.0010967948,0.008919474,0.44789946,0.00060277915,0.0009490773,0.41474277],"study_design_scores_gemma":[0.0006299881,0.021254448,0.5303204,0.00022072185,0.001312953,0.02069757,0.00096485805,0.086654104,0.33002034,0.0014164895,0.0062657734,0.00024238131],"about_ca_topic_score_codex":0.0007944552,"about_ca_topic_score_gemma":0.002288021,"teacher_disagreement_score":0.0012686793,"about_ca_system_score_codex":0.00020745659,"about_ca_system_score_gemma":0.00038630748,"threshold_uncertainty_score":0.006709516},"labels":[],"label_agreement":null},{"id":"W2967480225","doi":"10.1016/j.neurobiolaging.2019.08.011","title":"Tracking white matter degeneration in asymptomatic and symptomatic MAPT mutation carriers","year":2019,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health","keywords":"Asymptomatic; Asymptomatic carrier; White matter; Fractional anisotropy; Medicine; Mutation; Internal medicine; Psychology; Pathology; Genetics; Magnetic resonance imaging; Biology; Radiology","score_opus":0.021201181684875284,"score_gpt":0.29957009963799514,"score_spread":0.27836891795311985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967480225","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975358,0.00027205786,0.0015706375,0.000055450313,0.000012309094,0.000008976039,0.00013988563,0.000069683985,0.00033505762],"genre_scores_gemma":[0.9964993,0.00017639271,0.0027188123,0.000028551838,0.000011405839,0.000010013188,0.00013491932,0.000023543982,0.00039700136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999188,0.000016445287,0.000008287904,0.000029477309,0.00001488726,0.000012001512],"domain_scores_gemma":[0.99960095,0.0001480229,0.0000752285,0.000021176334,0.00007591453,0.000078726385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004962074,0.00036357951,0.00030929374,0.0010384965,0.0003408715,0.0007807729,0.00023830119,0.00088209147,0.00085255527],"category_scores_gemma":[0.002519124,0.00019154469,0.00013028116,0.00028881346,0.00019654512,0.0004925489,0.00036578716,0.00025933076,0.00019633929],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004641396,0.00023008502,0.7802998,0.00014127906,0.00015921314,0.007146536,0.0011508818,0.0028546257,0.111198574,0.00050094555,0.0014217455,0.0902549],"study_design_scores_gemma":[0.00012011999,0.0014343798,0.9127815,0.00011303057,0.0002480605,0.014752309,0.0011859868,0.040410824,0.02461476,0.0028412805,0.0014357662,0.00006203376],"about_ca_topic_score_codex":0.0031870068,"about_ca_topic_score_gemma":0.00522657,"teacher_disagreement_score":0.0031870068,"about_ca_system_score_codex":0.00021999849,"about_ca_system_score_gemma":0.00019849662,"threshold_uncertainty_score":0.0063369274},"labels":[],"label_agreement":null},{"id":"W2967676857","doi":"10.1111/jon.12659","title":"Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T<sub>2</sub>Normative Atlases for the Cervical Spinal Cord from 3T MRI","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Simon Fraser University; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; International Collaboration on Repair Discoveries; National Institute for Health and Care Research; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Medicine; Spinal cord; Multiple sclerosis; Myelin; Population; Anatomy; Nuclear medicine; Central nervous system; Internal medicine","score_opus":0.04186393742645254,"score_gpt":0.31857417548462164,"score_spread":0.2767102380581691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967676857","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41980624,0.0012918976,0.54749393,0.0005059009,0.00016204883,0.0006586412,0.010754833,0.007418556,0.011908029],"genre_scores_gemma":[0.6867239,0.00056610315,0.29837248,0.00017051972,0.000052434156,0.0015534773,0.008844945,0.0020167031,0.0016993165],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989868,0.00022105266,0.00016264543,0.00022285354,0.0003596151,0.000046930367],"domain_scores_gemma":[0.99828583,0.00037551366,0.0004254754,0.00036288972,0.00049875694,0.000051539977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025747383,0.0006842297,0.00039246355,0.0036287403,0.0007114351,0.0019524002,0.0009927531,0.00063078065,0.0031767918],"category_scores_gemma":[0.005773107,0.00031281318,0.0005564221,0.0015927501,0.0008705835,0.00088627095,0.0008525898,0.00048600725,0.000747433],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019642129,0.0003029398,0.113490775,0.0019528464,0.00079589855,0.0030580084,0.0051739602,0.052594937,0.32689512,0.044805348,0.03831111,0.41065484],"study_design_scores_gemma":[0.00019054305,0.00088505563,0.5104547,0.0006022221,0.00048739352,0.013621765,0.0022918098,0.15417406,0.17827469,0.053751394,0.08467655,0.0005898182],"about_ca_topic_score_codex":0.006415476,"about_ca_topic_score_gemma":0.0112066865,"teacher_disagreement_score":0.006415476,"about_ca_system_score_codex":0.0009865961,"about_ca_system_score_gemma":0.0012760845,"threshold_uncertainty_score":0.013616681},"labels":[],"label_agreement":null},{"id":"W2967827238","doi":"10.1097/pr9.0000000000000755","title":"Trigeminal nerve and white matter brain abnormalities in chronic orofacial pain disorders","year":2019,"lang":"en","type":"review","venue":"PAIN Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Connaught Fund; University of Toronto","keywords":"Orofacial pain; Trigeminal neuralgia; Diffusion MRI; Trigeminal nerve; Medicine; Temporomandibular joint; Chronic pain; White matter; Neuroscience; TMJ disorders; Magnetic resonance imaging; Pathology; Psychology; Anatomy; Radiology; Anesthesia; Physical therapy","score_opus":0.06113211186667545,"score_gpt":0.37753809467731836,"score_spread":0.3164059828106429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967827238","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000092225324,0.9987299,0.00006242319,0.00019167482,0.00011366087,0.000003315772,0.000013541741,0.000005530259,0.00078776816],"genre_scores_gemma":[0.00072969275,0.99845684,0.00011343253,0.000123035,0.0001547942,0.000004224666,0.000021237782,0.0000010411208,0.00039583514],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99980897,0.00002667157,0.00003783373,0.00003672777,0.00007300164,0.00001697139],"domain_scores_gemma":[0.9996276,0.0001806425,0.000073620926,0.00000913374,0.00008548945,0.000023514242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045766003,0.00082184427,0.0009710135,0.0044513773,0.00027071757,0.00089353294,0.0007028975,0.000881146,0.004267904],"category_scores_gemma":[0.00093650987,0.00022047704,0.0005433109,0.0034097282,0.00055076147,0.0011988945,0.00058945315,0.0011844086,0.0014099737],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048920345,0.000032090888,0.00033002612,0.02786389,0.00009905751,0.00032307356,0.000115142604,0.00024266282,0.0010766202,0.0028748945,0.029718647,0.93727493],"study_design_scores_gemma":[0.000017735782,0.000073362324,0.004171649,0.013944812,0.0002627469,0.005904864,0.00016754508,0.000120808996,0.00048243298,0.0041206595,0.97070193,0.000031368287],"about_ca_topic_score_codex":0.0019527039,"about_ca_topic_score_gemma":0.0028991948,"teacher_disagreement_score":0.0044513773,"about_ca_system_score_codex":0.0006510727,"about_ca_system_score_gemma":0.0013490249,"threshold_uncertainty_score":0.014277577},"labels":[],"label_agreement":null},{"id":"W2968037752","doi":"10.1016/s1474-4422(19)30138-3","title":"MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers","year":2019,"lang":"en","type":"review","venue":"The Lancet Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":208,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"Horizon 2020; Canadian Institutes of Health Research; European Research Council; International Foundation for CDKL5 Research; H2020 European Research Council; Eisai; International Foundation for Research in Paraplegia; Siemens; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; F. Hoffmann-La Roche; Singapore Eye Research Institute; University College London Hospitals NHS Foundation Trust; European Commission; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Wings for Life; International Spinal Research Trust; University College London; Staatssekretariat für Bildung, Forschung und Innovation; Craig H. Neilsen Foundation; Wellcome Trust","keywords":"Medicine; Neuroimaging; Magnetic resonance imaging; Spinal cord; Spinal cord injury; Traumatic brain injury; Spinal cord compression; Radiology; Physical medicine and rehabilitation","score_opus":0.3661599137340523,"score_gpt":0.5518174254858047,"score_spread":0.18565751175175238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968037752","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000019753425,0.99953115,0.000036659345,0.00016335664,0.00010047913,0.0000013982657,0.0000059719473,0.0000018773171,0.00013924997],"genre_scores_gemma":[0.00032948426,0.9988292,0.00009212039,0.00035325653,0.00027746998,0.0000031467291,0.000012036135,9.083103e-7,0.00010244559],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994154,0.00012676927,0.00012234702,0.00011134364,0.00017940046,0.00004475146],"domain_scores_gemma":[0.9978387,0.0014342383,0.00024465364,0.0000432559,0.00036255666,0.00007656883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017313551,0.0013618312,0.0032196792,0.003882003,0.00024742246,0.0019658464,0.00146283,0.002223864,0.0024871766],"category_scores_gemma":[0.003289785,0.00052976975,0.000920204,0.0031559258,0.0012948348,0.002183034,0.0012166307,0.00278882,0.001360216],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014211347,0.00005137642,0.00034513016,0.034834072,0.00028139568,0.00018091642,0.000053897358,0.00037863656,0.00062471343,0.0032690868,0.0308314,0.9290073],"study_design_scores_gemma":[0.00013242857,0.00025538987,0.0034676222,0.042476207,0.001053005,0.0025871457,0.00022560376,0.00036239933,0.00043702198,0.007007365,0.9419016,0.00009408188],"about_ca_topic_score_codex":0.0025169763,"about_ca_topic_score_gemma":0.0040529617,"teacher_disagreement_score":0.003882003,"about_ca_system_score_codex":0.0011047386,"about_ca_system_score_gemma":0.0022005653,"threshold_uncertainty_score":0.009156346},"labels":[],"label_agreement":null},{"id":"W2968327236","doi":"10.1002/hbm.24760","title":"Neurite orientation dispersion and density imaging (NODDI) and free‐water imaging in Parkinsonism","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"High Magnetic Field Laboratory, Chinese Academy of Sciences; Division of Materials Research; McKnight Foundation; National Institute of Neurological Disorders and Stroke; National High Magnetic Field Laboratory; National Institutes of Health; National Science Foundation","keywords":"Parkinsonism; Corpus callosum; Globus pallidus; Basal ganglia; Neuroscience; Cerebellum; Fractional anisotropy; Thalamus; Midbrain; Striatum; Substantia nigra; Diffusion MRI; Psychology; Chemistry; Pathology; Anatomy; Magnetic resonance imaging; Biology; Medicine; Dopaminergic; Central nervous system; Radiology; Dopamine","score_opus":0.027206375517248926,"score_gpt":0.3040667323848043,"score_spread":0.2768603568675554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968327236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94816864,0.004294844,0.045816932,0.00015522187,0.00003698753,0.00006861468,0.00011332495,0.000098741366,0.001246726],"genre_scores_gemma":[0.96336913,0.0010707893,0.03484655,0.00004493115,0.000015228964,0.00008208554,0.00010189994,0.000021310452,0.0004479571],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99963963,0.00014768091,0.000028572491,0.00008688464,0.00006030112,0.00003684826],"domain_scores_gemma":[0.99937075,0.00034545345,0.00012088095,0.00006478244,0.000050151397,0.00004793619],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017705155,0.00046813482,0.0005247431,0.0005420824,0.00019870284,0.00037778463,0.00032360674,0.0005065307,0.00031705384],"category_scores_gemma":[0.0022319697,0.00034736897,0.00021455219,0.0003061891,0.000631877,0.00053858355,0.0006005063,0.00046847787,0.000030062989],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038150586,0.00022560907,0.1010655,0.001171715,0.00070357654,0.00074400817,0.00068573904,0.006916564,0.7268011,0.002569743,0.00048744108,0.15481395],"study_design_scores_gemma":[0.00021705215,0.0025403134,0.72489583,0.0001498562,0.0005172199,0.005807212,0.00048991165,0.04773916,0.2071676,0.0064267726,0.003919491,0.00012957315],"about_ca_topic_score_codex":0.0013331427,"about_ca_topic_score_gemma":0.00468874,"teacher_disagreement_score":0.0017705155,"about_ca_system_score_codex":0.0003211477,"about_ca_system_score_gemma":0.0002566859,"threshold_uncertainty_score":0.009363472},"labels":[],"label_agreement":null},{"id":"W2969721658","doi":"10.1038/s41386-019-0485-6","title":"Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals","year":2019,"lang":"en","type":"review","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":235,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Institute on Aging; National Center for Mental Health; European Regional Development Fund; Instituto de Salud Carlos III; Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Dalhousie University; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Norges Forskningsråd; Dainippon Sumitomo Pharma; National Institute of Mental Health; Fondation pour la Recherche Médicale; South African Medical Research Council; Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya; Generalitat de Catalunya; University of Edinburgh; Sanofi; European Commission; Nova Scotia Health Research Foundation; Deutsche Forschungsgemeinschaft; H. Lundbeck A/S; Centres de Recerca de Catalunya; Ministerio de Ciencia, Innovación y Universidades; Universitetet i Oslo; Allergan; Fundação de Amparo à Pesquisa do Estado de São Paulo; Royal College of Physicians of Edinburgh; NIH Clinical Center; Agence Nationale de la Recherche; Fondation de l'Avenir pour la Recherche Médicale Appliquée; Wellcome Trust; Biogen; Centro de Investigación Biomédica en Red de Salud Mental; National Alliance for Research on Schizophrenia and Depression","keywords":"Corpus callosum; Fractional anisotropy; White matter; Diffusion MRI; Cingulum (brain); Bipolar disorder; Medicine; Internal medicine; Psychology; Biomarker; Cardiology; Neuroscience; Magnetic resonance imaging; Lithium (medication); Biology; Radiology; Genetics","score_opus":0.2973544460892999,"score_gpt":0.513220610675638,"score_spread":0.21586616458633806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969721658","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37175035,0.61599374,0.0033779202,0.00086374657,0.00039632866,0.00012823848,0.006150779,0.00011825075,0.0012206071],"genre_scores_gemma":[0.952817,0.041883573,0.0018019307,0.00040522584,0.00012282131,0.000126916,0.002548679,0.000057244706,0.00023657318],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9955329,0.0021924162,0.0007986428,0.0009510829,0.00035130972,0.00017367068],"domain_scores_gemma":[0.9938065,0.0037477002,0.0011403637,0.0007236658,0.0004170651,0.0001648132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067878487,0.0014157486,0.0038121408,0.0020865956,0.00075720594,0.001718537,0.0010200999,0.0011089526,0.001705837],"category_scores_gemma":[0.010477181,0.000987806,0.012914873,0.0038016886,0.00054573914,0.00058707333,0.0010965499,0.001171838,0.00023315208],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0065716873,0.000041139392,0.1799032,0.015244037,0.7793705,0.00044765393,0.00023183753,0.0010505882,0.0016449168,0.000251171,0.0015561131,0.01368721],"study_design_scores_gemma":[0.00070341286,0.00023130122,0.17643729,0.0018324781,0.8169132,0.00026463464,0.000106685766,0.0005920758,0.00035391146,0.0005068723,0.0020267172,0.000031443393],"about_ca_topic_score_codex":0.009953889,"about_ca_topic_score_gemma":0.021183036,"teacher_disagreement_score":0.009953889,"about_ca_system_score_codex":0.0007207192,"about_ca_system_score_gemma":0.00074755447,"threshold_uncertainty_score":0.03589803},"labels":[],"label_agreement":null},{"id":"W2970275262","doi":"10.1038/s41380-019-0477-2","title":"White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group","year":2019,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":373,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Instituto de Salud Carlos III; National Health and Medical Research Council; Rivierduinen; University of California, San Francisco; GGZ inGeest; National Institutes of Health; Vrije Universiteit Amsterdam; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Centro de Investigación Biomédica en Red de Salud Mental; National Alliance for Research on Schizophrenia and Depression; ZonMw; Medical Research Council; Leids Universitair Medisch Centrum; Universiteit Leiden; Universitair Medisch Centrum Groningen; University of Minnesota; Science Foundation Ireland; American Foundation for Suicide Prevention; European Commission; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Deutsche Forschungsgemeinschaft; GlaxoSmithKline; European Regional Development Fund; National Healthcare Group; Rappaport Foundation; Brain and Behavior Research Foundation","keywords":"Fractional anisotropy; Major depressive disorder; Corpus callosum; White matter; Psychology; Diffusion MRI; Depression (economics); Neuroimaging; Psychiatry; Clinical psychology; Internal medicine; Medicine; Neuroscience; Magnetic resonance imaging; Cognition","score_opus":0.009484764895849637,"score_gpt":0.3067051679151785,"score_spread":0.29722040301932884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970275262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862017,0.007406351,0.0013812851,0.00021905977,0.000031204036,0.00009857803,0.004222089,0.000037213016,0.00040257882],"genre_scores_gemma":[0.99048656,0.0019082532,0.0018355683,0.00014268608,0.000035145993,0.00019207342,0.0051784413,0.000043399177,0.00017777039],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968971,0.0010809707,0.00045437602,0.0011495561,0.00026816982,0.00014987518],"domain_scores_gemma":[0.9959539,0.000628794,0.0014945113,0.0009565789,0.0006882936,0.00027794938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052614636,0.00077862485,0.0018032334,0.0022415495,0.0007256544,0.0015146255,0.0009251147,0.0006973283,0.0006430853],"category_scores_gemma":[0.006064396,0.0007321247,0.0026405915,0.003680262,0.00036386715,0.0004373515,0.0024425304,0.00048843457,0.0001702543],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000648224,0.000035435958,0.977702,0.0002718943,0.011992193,0.00017095287,0.00047931023,0.00024740846,0.00083525927,0.00009441176,0.0010937457,0.0064292843],"study_design_scores_gemma":[0.00004613065,0.000050252078,0.9956197,0.00004879371,0.0030783731,0.00015770673,0.00014840261,0.00013990936,0.0000757712,0.00006660671,0.0005568196,0.000011585013],"about_ca_topic_score_codex":0.010231687,"about_ca_topic_score_gemma":0.013758157,"teacher_disagreement_score":0.010231687,"about_ca_system_score_codex":0.00050282583,"about_ca_system_score_gemma":0.00055169826,"threshold_uncertainty_score":0.027825654},"labels":[],"label_agreement":null},{"id":"W2970385260","doi":"10.1016/j.jhevol.2019.102654","title":"Trabecular bone structure scales allometrically in the foot of four human groups","year":2019,"lang":"en","type":"article","venue":"Journal of Human Evolution","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"H2020 European Research Council; Biotechnology and Biological Sciences Research Council; Arts and Humanities Research Council; European Commission; Pennsylvania State University","keywords":"Allometry; Calcaneus; Biology; Anatomy; Scaling; Mathematics; Geometry; Ecology","score_opus":0.044660875609583095,"score_gpt":0.3403876264091231,"score_spread":0.29572675079954003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970385260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991404,0.000029264304,0.00030501606,0.000009301068,0.000001309152,0.0000034652355,0.00008842155,0.0000058372525,0.00041703004],"genre_scores_gemma":[0.9994159,0.00001758777,0.00019240848,0.0000044257604,0.0000012709992,0.0000022377876,0.00006980487,0.00000481049,0.00029151983],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976915,0.00004293679,0.000011222939,0.00006402629,0.000055089724,0.000057586058],"domain_scores_gemma":[0.9991947,0.00025803954,0.00014918852,0.00007597521,0.00019763874,0.00012454283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023461114,0.0002664992,0.00041357602,0.0017879282,0.00062406453,0.0007367209,0.00035209506,0.00052852853,0.0025214003],"category_scores_gemma":[0.0016159196,0.00032552675,0.00025626188,0.0009097028,0.0012772512,0.0003303618,0.00047047736,0.00032640435,0.00040523813],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048677023,0.00027577672,0.8269557,0.00015860572,0.00047960554,0.0016817243,0.0052143103,0.0046589104,0.09625993,0.0016548774,0.0007859745,0.057006903],"study_design_scores_gemma":[0.000021739335,0.00029677092,0.9914471,0.000010818399,0.00005417294,0.0010026885,0.0015915756,0.0034596005,0.0010435951,0.00070104026,0.00034648686,0.000024392893],"about_ca_topic_score_codex":0.018057756,"about_ca_topic_score_gemma":0.02886149,"teacher_disagreement_score":0.018057756,"about_ca_system_score_codex":0.0003102116,"about_ca_system_score_gemma":0.00022669144,"threshold_uncertainty_score":0.0359053},"labels":[],"label_agreement":null},{"id":"W2970513362","doi":"10.1002/epi4.12357","title":"Regional hippocampal diffusion abnormalities associated with subfield‐specific pathology in temporal lobe epilepsy","year":2019,"lang":"en","type":"article","venue":"Epilepsia Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Temporal lobe; Hippocampal sclerosis; Fractional anisotropy; Hippocampus; Hippocampal formation; Pathology; Medicine; Epilepsy; Epilepsy surgery; Psychology; Radiology; Neuroscience; Magnetic resonance imaging; Internal medicine","score_opus":0.06874866591562907,"score_gpt":0.33065790928720207,"score_spread":0.261909243371573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970513362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997135,0.00008901824,0.000057756315,0.000010563543,6.7815216e-7,0.000002505776,0.000022426835,0.0000027524238,0.00010071573],"genre_scores_gemma":[0.99979717,0.00004339523,0.00007264818,0.000005131857,0.0000019405206,0.0000014219644,0.00003399429,8.441106e-7,0.000043513002],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995196,0.0000075146727,0.000008801845,0.000014086035,0.000008923113,0.000008686036],"domain_scores_gemma":[0.99972886,0.000043719836,0.00015375136,0.000015544101,0.000026171267,0.000031888863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018722635,0.00028206312,0.00013895641,0.0005280292,0.00015111915,0.00018680553,0.00009133439,0.00018886372,0.0011993821],"category_scores_gemma":[0.0006419671,0.00010682623,0.00009199889,0.00020604413,0.00034952688,0.00024192494,0.00019107532,0.00010595021,0.00012534684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014500503,0.000082669016,0.9215979,0.00010847524,0.000163836,0.002989778,0.00050428236,0.00036371214,0.05932263,0.00006908315,0.00015983084,0.013187739],"study_design_scores_gemma":[0.000030822543,0.00023367575,0.99017805,0.000007605301,0.00003805328,0.006202101,0.00016539304,0.00031747998,0.002657225,0.00006488322,0.00010025188,0.0000045766365],"about_ca_topic_score_codex":0.0015978545,"about_ca_topic_score_gemma":0.0027856063,"teacher_disagreement_score":0.0015978545,"about_ca_system_score_codex":0.00016890284,"about_ca_system_score_gemma":0.00013420985,"threshold_uncertainty_score":0.0040123463},"labels":[],"label_agreement":null},{"id":"W2971074351","doi":"10.1002/hbm.24774","title":"Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute on Aging; National Institutes of Health","keywords":"Cingulum (brain); White matter; Corpus callosum; Fornix; Univariate; Neuroscience; Fractional anisotropy; Psychology; Anatomy; Multivariate statistics; Biology; Medicine; Magnetic resonance imaging; Hippocampus","score_opus":0.03456366577798601,"score_gpt":0.3363201265224972,"score_spread":0.3017564607445112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971074351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9129129,0.00054044905,0.08489171,0.00013262423,0.000013892637,0.00006198202,0.0005475941,0.0003496033,0.0005491101],"genre_scores_gemma":[0.9846623,0.00012704908,0.014288435,0.000012686182,0.000013151271,0.00006147348,0.00032830113,0.0000366859,0.00046986577],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991806,0.00036022297,0.000041229167,0.00023646257,0.00014480496,0.00003657962],"domain_scores_gemma":[0.99848396,0.00073341053,0.00026998168,0.00025929615,0.00019792184,0.000055424363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022711852,0.00064380246,0.00053663587,0.00078319054,0.00018090266,0.00038118742,0.00041142388,0.00024667085,0.001097009],"category_scores_gemma":[0.0048373733,0.00027508,0.00060396,0.0009100773,0.00047896724,0.0003420987,0.00043075642,0.00026748076,0.0003042418],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013911586,0.00019279879,0.67261297,0.00029745683,0.003270272,0.0008368264,0.0009627694,0.044283815,0.033979636,0.0031417704,0.0033582456,0.23567235],"study_design_scores_gemma":[0.000027940461,0.00048245327,0.7900811,0.000016234422,0.00038658222,0.00063874584,0.00013946975,0.19827403,0.004756029,0.003416258,0.0017343134,0.00004681012],"about_ca_topic_score_codex":0.004620316,"about_ca_topic_score_gemma":0.0046500554,"teacher_disagreement_score":0.004620316,"about_ca_system_score_codex":0.00018709485,"about_ca_system_score_gemma":0.00083771755,"threshold_uncertainty_score":0.012011349},"labels":[],"label_agreement":null},{"id":"W2971116709","doi":"10.1002/hbm.24771","title":"MR‐based age‐related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Weston Brain Institute; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Alzheimer's Society; Fonds de Recherche du Québec - Santé; Michael J. Fox Foundation for Parkinson's Research","keywords":"Globus pallidus; Striatum; Psychology; Putamen; Magnetic resonance imaging; Basal ganglia; Thalamus; Neuroscience; Central nervous system; Medicine; Radiology; Dopamine","score_opus":0.05756960529907895,"score_gpt":0.3559492060056729,"score_spread":0.298379600706594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971116709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980268,0.00049035397,0.00035820142,0.000023964221,0.000004032521,0.0000068322256,0.0007837609,0.000009607245,0.0002964419],"genre_scores_gemma":[0.9985446,0.00014964132,0.00034913435,0.000018607085,0.0000052526907,0.0000085382135,0.0007450188,0.0000074349136,0.00017178808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99965906,0.000062013016,0.00003562293,0.0001741613,0.000043656328,0.000025517094],"domain_scores_gemma":[0.99938345,0.00009055977,0.00022962074,0.000115019524,0.00013525794,0.000046148714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066224474,0.00027003005,0.00027684332,0.0007452005,0.00020453421,0.0003560944,0.00019055208,0.00025210067,0.0007609965],"category_scores_gemma":[0.0021756948,0.00018807536,0.00023765521,0.00038070406,0.00033414987,0.00031129026,0.00040483812,0.00016891187,0.000117542884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078174035,0.000043534536,0.9719509,0.00006793843,0.00052636396,0.00044543238,0.0011577881,0.0003483957,0.010943517,0.00020162866,0.0004964849,0.0130361775],"study_design_scores_gemma":[0.0000019056205,0.000052042345,0.99926704,0.000003926012,0.000030772877,0.00016491034,0.000066823246,0.0000849831,0.00014199276,0.00007573236,0.00010767722,0.0000022352083],"about_ca_topic_score_codex":0.0076279105,"about_ca_topic_score_gemma":0.012480799,"teacher_disagreement_score":0.0076279105,"about_ca_system_score_codex":0.00019483859,"about_ca_system_score_gemma":0.00010304825,"threshold_uncertainty_score":0.015166998},"labels":[],"label_agreement":null},{"id":"W2971514011","doi":"10.1016/j.neuroimage.2019.116156","title":"Construction of a rat spinal cord atlas of axon morphometry","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Fondation Institut de Cardiologie de Montréal; Canada First Research Excellence Fund; Canada Foundation for Innovation","keywords":"White matter; Spinal cord; Axon; Atlas (anatomy); Brain atlas; Neuroscience; Anatomy; Segmentation; Biology; Myelin; Central nervous system; Medicine; Magnetic resonance imaging; Computer science; Artificial intelligence; Radiology","score_opus":0.05231506742740956,"score_gpt":0.3515690291370087,"score_spread":0.29925396170959917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971514011","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07997364,0.00045370197,0.8987907,0.00035967497,0.00015035454,0.00056822324,0.004938641,0.0055546835,0.009210402],"genre_scores_gemma":[0.2299027,0.0009260919,0.75305945,0.00009147385,0.000022425867,0.0009426003,0.0032129579,0.0015066287,0.010335723],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970263,0.000037895607,0.000022497456,0.00007173007,0.00012200543,0.000043211574],"domain_scores_gemma":[0.99935275,0.00010660822,0.00009189327,0.0001751523,0.00022111721,0.000052505417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009245049,0.0007176679,0.0005585686,0.0025379874,0.0010790228,0.0015605169,0.0010638944,0.0006986374,0.005868659],"category_scores_gemma":[0.0011242925,0.00075384474,0.0007670215,0.0019222595,0.0006519979,0.0007710687,0.0012723537,0.001700555,0.0018302143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058268587,0.00028555025,0.008045805,0.0008127172,0.00022612463,0.00090445584,0.0009771249,0.07618038,0.5476478,0.09840924,0.013922738,0.2520054],"study_design_scores_gemma":[0.00014452242,0.00085757906,0.03567419,0.00035710027,0.00036039908,0.0033341846,0.0006018254,0.31765893,0.4560904,0.044155356,0.14048293,0.0002824917],"about_ca_topic_score_codex":0.016479323,"about_ca_topic_score_gemma":0.034974325,"teacher_disagreement_score":0.016479323,"about_ca_system_score_codex":0.001192681,"about_ca_system_score_gemma":0.0039109075,"threshold_uncertainty_score":0.03276676},"labels":[],"label_agreement":null},{"id":"W2971691110","doi":"10.1007/s11682-019-00183-8","title":"Verbal memory and hippocampal volume predict subsequent fornix microstructure in those at risk for Alzheimer’s disease","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Science and Technology Planning Project of Guangdong Province; Canadian Institutes of Health Research; National Institutes of Health; Genentech; University of Hong Kong; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fornix; Fractional anisotropy; Memory impairment; Psychology; Hippocampus; Hippocampal formation; Neuroscience; Diffusion MRI; Medicine; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.031838480286548794,"score_gpt":0.32795009339339315,"score_spread":0.29611161310684436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971691110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99973947,0.00005425627,0.000019840887,0.000016019932,0.0000017876358,0.0000026695354,0.000042959065,0.0000010435045,0.00012194897],"genre_scores_gemma":[0.9996917,0.000021095791,0.000041943513,0.0000076187653,0.0000034394773,0.0000028290183,0.000084922205,5.529145e-7,0.0001458564],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987245,0.000029921199,0.000014451087,0.000033135417,0.000016043778,0.000033996104],"domain_scores_gemma":[0.99928623,0.00014981643,0.00028361325,0.000086542546,0.00006635435,0.00012744767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053620077,0.0003123507,0.00022533597,0.00045248945,0.00030006343,0.00057666696,0.00033368572,0.0006514765,0.0015945763],"category_scores_gemma":[0.0023883474,0.00021057745,0.00033465453,0.00032627242,0.00020387629,0.00043096402,0.00035522843,0.0005039025,0.00023205715],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022642477,0.00005664594,0.99842787,0.0000038688518,0.00002985279,0.000064622756,0.000101338876,0.00003757396,0.00018077708,0.000011086416,0.000038068458,0.0008219597],"study_design_scores_gemma":[0.0000060441557,0.000115339,0.999443,0.0000024877822,0.000014712372,0.0000987248,0.000082383645,0.00012567303,0.00003713343,0.000026544698,0.000046476278,0.0000015787344],"about_ca_topic_score_codex":0.0054869712,"about_ca_topic_score_gemma":0.007020526,"teacher_disagreement_score":0.0054869712,"about_ca_system_score_codex":0.00017141899,"about_ca_system_score_gemma":0.00022329988,"threshold_uncertainty_score":0.010910034},"labels":[],"label_agreement":null},{"id":"W2972389188","doi":"10.1038/s41380-019-0509-y","title":"White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study","year":2019,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":187,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Medical Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Psychiatry; Gerontology; Radiology","score_opus":0.02070048841522074,"score_gpt":0.32664578529911775,"score_spread":0.305945296883897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972389188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99864954,0.00016857777,0.0005787966,0.000031935433,0.0000023552889,0.00002058965,0.00026221032,0.000009016639,0.0002770631],"genre_scores_gemma":[0.99772793,0.00013670968,0.001458501,0.000029646266,0.0000064659625,0.000016908161,0.0004779584,0.000013053934,0.00013289702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996282,0.00010394546,0.000045969096,0.00011025246,0.00005531126,0.000056295718],"domain_scores_gemma":[0.999295,0.00005549007,0.00020305904,0.00017489899,0.00017840895,0.000092979084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015243196,0.00031605942,0.00039163444,0.0012167391,0.00062747445,0.0004942401,0.00038294683,0.0004937991,0.00042468155],"category_scores_gemma":[0.0012133827,0.00026312942,0.00038325746,0.0007292861,0.0004556561,0.00062178884,0.0011829569,0.00026921902,0.00015844272],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030134767,0.00065761217,0.8283831,0.00016556578,0.0011652402,0.0035543262,0.0027948716,0.0020208224,0.09895426,0.0006176669,0.0012041085,0.057469103],"study_design_scores_gemma":[0.000031930518,0.00036302488,0.9931973,0.00001909557,0.00016220867,0.0030417147,0.00047587155,0.00058724446,0.0011806217,0.00022290829,0.00069712306,0.00002101741],"about_ca_topic_score_codex":0.0054165553,"about_ca_topic_score_gemma":0.0073399837,"teacher_disagreement_score":0.0054165553,"about_ca_system_score_codex":0.0005048126,"about_ca_system_score_gemma":0.0006877879,"threshold_uncertainty_score":0.010770023},"labels":[],"label_agreement":null},{"id":"W2972624218","doi":"10.1177/0891988719874132","title":"Clinical and Diffusion Tensor Imaging to Evaluate Falls, Balance and Gait Dysfunction in Leukoaraiosis: an Observational, Prospective Cohort Study","year":2019,"lang":"en","type":"article","venue":"Journal of Geriatric Psychiatry and Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Impact","funders":"Beijing Municipal Science and Technology Commission","keywords":"Fractional anisotropy; Medicine; Corpus callosum; Berg Balance Scale; Diffusion MRI; White matter; Leukoaraiosis; Physical therapy; Physical medicine and rehabilitation; Balance (ability); Poison control; Gait; Internal capsule; Magnetic resonance imaging; Internal medicine; Radiology; Pathology","score_opus":0.049511954185200914,"score_gpt":0.3782518935606128,"score_spread":0.32873993937541185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972624218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994822,0.0001118176,0.00006266384,0.000012176206,0.0000039343845,0.000016441194,0.00020637155,0.0000013986507,0.00010311017],"genre_scores_gemma":[0.9993687,0.00007839436,0.000072239214,0.000024012856,0.000009448949,0.000017619186,0.00033554877,0.000001312582,0.00009263606],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994892,0.00010853159,0.00006622077,0.0001441154,0.00009446525,0.00009743341],"domain_scores_gemma":[0.99906296,0.00006887937,0.00038265277,0.00010560633,0.00013590312,0.00024399304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008478351,0.0005634884,0.0006357112,0.00084091374,0.0009822531,0.000784682,0.00036505732,0.00061104936,0.000957548],"category_scores_gemma":[0.0015486534,0.00053015974,0.0007136525,0.0011009969,0.0003083651,0.00066748116,0.0005262247,0.0007504613,0.00027398014],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013944696,0.0000863527,0.99919504,0.000004466496,0.00006106255,0.00009645447,0.000037110836,0.000010298764,0.000108962944,0.0000043699843,0.000032497974,0.00022392506],"study_design_scores_gemma":[0.00002787156,0.00032260048,0.9987,0.000005128308,0.000056862053,0.0004908362,0.00016510843,0.000100257035,0.000029473236,0.0000124856,0.0000846499,0.0000046865],"about_ca_topic_score_codex":0.004246266,"about_ca_topic_score_gemma":0.0055411733,"teacher_disagreement_score":0.004246266,"about_ca_system_score_codex":0.00026725009,"about_ca_system_score_gemma":0.0004614543,"threshold_uncertainty_score":0.008443117},"labels":[],"label_agreement":null},{"id":"W2972685576","doi":"10.1016/b978-2-294-76430-1.00001-9","title":"Définition et interinfluence de ces trois cerveaux","year":2019,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Collège d'Études Ostéopathiques de Montréal","funders":"","keywords":"Humanities; Geography; Art","score_opus":0.0673091011149228,"score_gpt":0.35029645579318697,"score_spread":0.2829873546782642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972685576","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029791314,0.08210018,0.18154415,0.007524494,0.004529823,0.00023689767,0.0010064195,0.00049149804,0.69277525],"genre_scores_gemma":[0.3432875,0.06843017,0.19930774,0.0030955495,0.009015811,0.0009782942,0.0019960436,0.0006944247,0.37319437],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979284,0.0005346119,0.00018494892,0.00047597504,0.00071775424,0.00015839384],"domain_scores_gemma":[0.99808574,0.00096382404,0.000217239,0.00016973246,0.0004689408,0.00009459584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021057352,0.0015240336,0.0004828978,0.0036188713,0.0016725424,0.004678777,0.0013038247,0.0019984096,0.016353715],"category_scores_gemma":[0.0051953807,0.0005310159,0.0008675216,0.0018461408,0.006173396,0.004399451,0.002144341,0.0038907586,0.004708976],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009661252,0.000026618787,0.0019864507,0.00077612465,0.000039042283,0.0016116912,0.002824043,0.0006336128,0.008928771,0.6910489,0.0106267,0.28140152],"study_design_scores_gemma":[0.00001633064,0.00013532967,0.006219652,0.0015214712,0.00008285319,0.012097624,0.0014500518,0.0011370786,0.008395826,0.12816139,0.8407309,0.000051484327],"about_ca_topic_score_codex":0.005507973,"about_ca_topic_score_gemma":0.0051168185,"teacher_disagreement_score":0.016353715,"about_ca_system_score_codex":0.0017554933,"about_ca_system_score_gemma":0.0018249812,"threshold_uncertainty_score":0.05470866},"labels":[],"label_agreement":null},{"id":"W2973102543","doi":"10.1101/766139","title":"Evaluation of six phase encoding based susceptibility distortion correction methods for diffusion MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"ITEA3; Vetenskapsrådet; Linköpings Universitet; VINNOVA; ITEA","keywords":"Diffusion MRI; Encoding (memory); Ground truth; Preprocessor; Computer science; Diffusion; Phase (matter); Distortion (music); Standard deviation; Algorithm; Data mining; Artificial intelligence; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.0916819829983843,"score_gpt":0.40826539191435013,"score_spread":0.3165834089159658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973102543","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26673317,0.011243502,0.71057034,0.0006872914,0.000518451,0.00089273014,0.0011594697,0.004936062,0.0032590174],"genre_scores_gemma":[0.3636389,0.0026963556,0.62889826,0.00020915804,0.00011697799,0.00034478857,0.0014676716,0.00071281334,0.0019150509],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976611,0.00064922037,0.00026272985,0.00033201586,0.0009881546,0.000106713356],"domain_scores_gemma":[0.98860544,0.0054694414,0.001305887,0.0009781929,0.0033209655,0.00032007875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004725832,0.0016808289,0.00078364264,0.0025002358,0.0004566823,0.0013609753,0.00132141,0.0013238966,0.0011837475],"category_scores_gemma":[0.018745964,0.00043031317,0.00087905204,0.0012175605,0.00053696765,0.0013115786,0.0010626054,0.0010603514,0.00043868998],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021065976,0.0005286088,0.012449433,0.0020205139,0.0009562034,0.00020951145,0.00032074898,0.10499838,0.083830826,0.002583562,0.0035390041,0.7864567],"study_design_scores_gemma":[0.00036601874,0.0032170326,0.0154933585,0.00031833848,0.0006527834,0.0017203578,0.00019098351,0.7704638,0.19594456,0.0023412167,0.008993059,0.00029840606],"about_ca_topic_score_codex":0.0027221423,"about_ca_topic_score_gemma":0.003382084,"teacher_disagreement_score":0.004725832,"about_ca_system_score_codex":0.00071212766,"about_ca_system_score_gemma":0.0011949433,"threshold_uncertainty_score":0.024992883},"labels":[],"label_agreement":null},{"id":"W2973683106","doi":"10.1002/mrm.28232","title":"High‐fidelity, accelerated whole‐brain submillimeter in vivo diffusion MRI using gSlider‐spherical ridgelets (gSlider‐SR)","year":2020,"lang":"en","type":"preprint","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Scanner; Computer science; Diffusion MRI; Redundancy (engineering); Human Connectome Project; Noise (video); Data acquisition; Angular resolution (graph drawing); Image resolution; Signal-to-noise ratio (imaging); Monte Carlo method; SIGNAL (programming language); Artificial intelligence; Computer vision; Physics; Magnetic resonance imaging; Mathematics","score_opus":0.10801500256919347,"score_gpt":0.3738312845897153,"score_spread":0.2658162820205219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973683106","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040969886,0.00020622174,0.9573436,0.00014284931,0.00002111199,0.000036291323,0.00009652053,0.0006602117,0.0005233355],"genre_scores_gemma":[0.16210495,0.00033144787,0.8360193,0.000088558765,0.000023738223,0.000067989524,0.00022197906,0.00019665917,0.0009454091],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99984527,0.000036714046,0.000009698906,0.00002369682,0.00007186355,0.000012791938],"domain_scores_gemma":[0.9996344,0.00010396058,0.00009884612,0.000071432594,0.00006386552,0.000027561053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071873865,0.00049740024,0.0003715901,0.00027335057,0.00011644813,0.0003624178,0.00047008466,0.0005004544,0.0008396451],"category_scores_gemma":[0.0012475206,0.00038109533,0.00046373514,0.00033031328,0.00026522373,0.0005933882,0.00046664252,0.0007036596,0.00044897335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026755047,0.000088772314,0.0022569243,0.00047480158,0.00012809219,0.0005377219,0.00019761866,0.1531967,0.6610969,0.006987826,0.0031382318,0.17162889],"study_design_scores_gemma":[0.00003667023,0.00020140912,0.002848963,0.00003004591,0.000044759694,0.0012560658,0.000029137607,0.7994811,0.18772681,0.002386339,0.005889215,0.00006952293],"about_ca_topic_score_codex":0.0006509589,"about_ca_topic_score_gemma":0.0012272963,"teacher_disagreement_score":0.0008396451,"about_ca_system_score_codex":0.00022667652,"about_ca_system_score_gemma":0.00055232283,"threshold_uncertainty_score":0.0038011074},"labels":[],"label_agreement":null},{"id":"W2974984553","doi":"10.3171/2019.6.jns19612","title":"Tractography-based targeting of the ventral intermediate nucleus: accuracy and clinical utility in MRgFUS thalamotomy","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Western Hospital; University Health Network; University of Toronto; Ontario Brain Institute; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Thalamotomy; Medicine; Tractography; Magnetic resonance imaging; Essential tremor; Radiology; Diffusion MRI; Physical medicine and rehabilitation; Pathology; Parkinson's disease; Deep brain stimulation","score_opus":0.05985985853866739,"score_gpt":0.3699382358241312,"score_spread":0.31007837728546384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2974984553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99019873,0.0006303441,0.008524009,0.000037984966,0.0000032285895,0.000024954234,0.000070643044,0.00003231043,0.0004778655],"genre_scores_gemma":[0.9967379,0.00016920544,0.002922444,0.0000070045603,0.000004495758,0.000011865888,0.000055062195,0.000008971084,0.00008302742],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996698,0.00011132631,0.00003780297,0.00007463589,0.00008710737,0.000019400504],"domain_scores_gemma":[0.9988978,0.00036771456,0.00043039618,0.00012691888,0.00013042575,0.000046776862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008566542,0.00024651331,0.00024338876,0.00035493358,0.000098866374,0.00036518162,0.00018498093,0.00024330568,0.0005973994],"category_scores_gemma":[0.004913074,0.0001197096,0.000135744,0.00020739606,0.0004040878,0.00029727435,0.00030766503,0.00014373111,0.00018416347],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013337285,0.00004240743,0.8579833,0.00013864489,0.00014339178,0.00080204516,0.00033458715,0.0037096525,0.03710083,0.00013693584,0.00012970723,0.09814489],"study_design_scores_gemma":[0.000060188944,0.00088548416,0.9722973,0.000052966072,0.000113793336,0.0055181338,0.00014048479,0.010224903,0.009974555,0.0001501283,0.0005525411,0.000029476827],"about_ca_topic_score_codex":0.001027153,"about_ca_topic_score_gemma":0.0025036025,"teacher_disagreement_score":0.001027153,"about_ca_system_score_codex":0.00023172176,"about_ca_system_score_gemma":0.0002293864,"threshold_uncertainty_score":0.0045304894},"labels":[],"label_agreement":null},{"id":"W2975235655","doi":"10.1038/s41598-019-49970-9","title":"Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Care; Sunnybrook Health Science Centre; St Joseph's Health Centre; McGill University; Jewish General Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Genentech; IXICO; Eisai; University of Southern California; Agence Nationale de la Recherche; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Servier; Alzheimer's Disease Neuroimaging Initiative; Eli Lilly and Company; Foundation for the National Institutes of Health","keywords":"Subiculum; Computer science; Hippocampal formation; Diffusion MRI; Magnetic resonance imaging; Hippocampus; Artificial intelligence; Neuroimaging; Grading (engineering); Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Pattern recognition (psychology); Machine learning; Alzheimer's disease; Pathology; Medicine; Disease; Radiology; Biology; Dentate gyrus","score_opus":0.11005114133744558,"score_gpt":0.37743080638013005,"score_spread":0.26737966504268446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975235655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5873887,0.0058466187,0.39728075,0.00052158046,0.0001495296,0.0004775529,0.0018913702,0.0018365963,0.0046074702],"genre_scores_gemma":[0.8581861,0.0013032078,0.13761264,0.000070353926,0.00013541908,0.00013996808,0.0011093017,0.00006632243,0.0013766417],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996879,0.00005898568,0.000031949497,0.000076109405,0.00009994742,0.000045116212],"domain_scores_gemma":[0.9993861,0.0001433598,0.00011620741,0.00007862971,0.00020203018,0.00007373094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008297968,0.00080180273,0.00074396795,0.0030196214,0.00024110587,0.0007750516,0.00048194916,0.00065096107,0.0015041147],"category_scores_gemma":[0.0018928852,0.00011726101,0.0005697365,0.00091264246,0.00027378587,0.0007921631,0.0007089623,0.00040781175,0.00057710137],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012376701,0.00020573984,0.071096286,0.00044227307,0.0003681736,0.000307783,0.00027065538,0.021435702,0.061621048,0.0014670446,0.00484951,0.8366981],"study_design_scores_gemma":[0.00011550168,0.0011541095,0.1628978,0.00020094289,0.00090751867,0.0024258946,0.0007646927,0.7460615,0.06606374,0.011078727,0.008170496,0.00015909056],"about_ca_topic_score_codex":0.0029246744,"about_ca_topic_score_gemma":0.004602895,"teacher_disagreement_score":0.0030196214,"about_ca_system_score_codex":0.00029339158,"about_ca_system_score_gemma":0.00041745405,"threshold_uncertainty_score":0.005815327},"labels":[],"label_agreement":null},{"id":"W2976721110","doi":"10.1371/journal.pone.0223211","title":"Acute ex vivo changes in brain white matter diffusion tensor metrics","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Toronto Western Hospital; Hospital for Sick Children; University of Toronto; University Health Network","funders":"Mitacs; Fondation Brain Canada","keywords":"Ex vivo; Diffusion MRI; Fractional anisotropy; White matter; Tractography; In vivo; Magnetic resonance imaging; Biomedical engineering; Materials science; Pathology; Anatomy; Biology; Medicine; Radiology","score_opus":0.07238416628773542,"score_gpt":0.3080497953706954,"score_spread":0.23566562908295996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976721110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984248,0.0011412929,0.013419431,0.000057383077,0.000053671978,0.000052780695,0.0003296272,0.00008113175,0.00061682856],"genre_scores_gemma":[0.9933466,0.00079715153,0.0040877946,0.000037749083,0.000019689736,0.00008495853,0.00058807567,0.000025593245,0.0010124256],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997452,0.00004514066,0.000035187648,0.00007222048,0.00006748523,0.00003478666],"domain_scores_gemma":[0.99922633,0.00020110774,0.0002537831,0.00012750873,0.000113296286,0.00007789465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005724339,0.0005031895,0.00035482668,0.00042814354,0.00019323638,0.0005416142,0.00028687404,0.00038337856,0.0024812284],"category_scores_gemma":[0.0009708113,0.00020500591,0.00021986134,0.00023027694,0.0008200395,0.00064169435,0.0004518388,0.0008282721,0.00031007497],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010814789,0.0002432541,0.004043281,0.00017988353,0.000059122358,0.00027143065,0.000098129,0.00055646116,0.9880326,0.00016779802,0.00009537011,0.0051711863],"study_design_scores_gemma":[0.00006990371,0.0062841536,0.09513237,0.000049997485,0.00014299277,0.0019205967,0.00025053136,0.003357278,0.89039445,0.00047378783,0.0018986466,0.00002527465],"about_ca_topic_score_codex":0.0004000577,"about_ca_topic_score_gemma":0.00039778132,"teacher_disagreement_score":0.0024812284,"about_ca_system_score_codex":0.0002982964,"about_ca_system_score_gemma":0.00021933601,"threshold_uncertainty_score":0.008300543},"labels":[],"label_agreement":null},{"id":"W2977486527","doi":"10.3389/fnins.2019.01024","title":"White Matter fMRI Activation Cannot Be Treated as a Nuisance Regressor: Overcoming a Historical Blind Spot","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Fraser Health; Surrey Memorial Hospital; Simon Fraser University; University of Calgary","funders":"","keywords":"White matter; Neuroimaging; Blind spot; Functional magnetic resonance imaging; Psychology; White noise; Cognitive psychology; Magnetic resonance imaging; Neuroscience; Computer science; Medicine","score_opus":0.04601412287914873,"score_gpt":0.32175123125396277,"score_spread":0.275737108374814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977486527","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026925841,0.075809814,0.79996294,0.08139666,0.007273617,0.00014417978,0.00042384813,0.0006163259,0.0074467584],"genre_scores_gemma":[0.39223546,0.055247866,0.46145853,0.058028042,0.022230238,0.00071123434,0.00037112465,0.0015937772,0.008123733],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9560883,0.025351427,0.003013253,0.007622556,0.007389254,0.0005352655],"domain_scores_gemma":[0.7086601,0.24086979,0.012245137,0.02091285,0.015864598,0.001447493],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1519149,0.0013185103,0.0037253224,0.003223975,0.0024166312,0.0068416586,0.0029060426,0.005097796,0.0019399832],"category_scores_gemma":[0.2794673,0.0011323554,0.0013422609,0.0022941555,0.031135466,0.008924044,0.004939274,0.0140106995,0.0011157023],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015535206,0.00013305522,0.021451006,0.0040854244,0.0016804669,0.00086764473,0.0071658976,0.0038023002,0.0062965946,0.43565476,0.028228212,0.48908117],"study_design_scores_gemma":[0.00014290787,0.0002961563,0.0083329445,0.002071167,0.0005632827,0.0017979901,0.000974665,0.009034799,0.008552492,0.8865977,0.08130056,0.00033539295],"about_ca_topic_score_codex":0.002383034,"about_ca_topic_score_gemma":0.002657147,"teacher_disagreement_score":0.8480851,"about_ca_system_score_codex":0.0017783154,"about_ca_system_score_gemma":0.0038814133,"threshold_uncertainty_score":0.8034123},"labels":[],"label_agreement":null},{"id":"W2977674931","doi":"10.1002/hbm.25117","title":"Harmonization of diffusion <scp>MRI</scp> data sets with adaptive dictionary learning","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Harmonization; Diffusion MRI; Diffusion; Computer science; Neuroscience; Artificial intelligence; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.1568266212760925,"score_gpt":0.3388444901377222,"score_spread":0.1820178688616297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977674931","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047563512,0.00018208877,0.9504839,0.0001412324,0.000045315883,0.00011650813,0.00020684012,0.00058791245,0.00067283504],"genre_scores_gemma":[0.37272197,0.00028236327,0.6218857,0.00024311006,0.0000740665,0.00038575346,0.0021206934,0.00039335448,0.0018929668],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987702,0.00045458245,0.000107137355,0.00033460426,0.0002522394,0.00008110439],"domain_scores_gemma":[0.99761486,0.0009870509,0.0002734837,0.00069164956,0.00037418952,0.000058850794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023391352,0.00066966884,0.0008828789,0.001069762,0.00037697642,0.0007859033,0.0009920199,0.00066328095,0.0010723507],"category_scores_gemma":[0.0058773397,0.00030096737,0.0010320683,0.0011747899,0.00077240093,0.0009756521,0.0015790579,0.0010903603,0.00058002176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005469515,0.00032606698,0.0043232427,0.00030324372,0.00046050223,0.0002174769,0.0003306164,0.20580217,0.05209343,0.0076482366,0.005467142,0.72248095],"study_design_scores_gemma":[0.000054986194,0.00033681764,0.004470122,0.000026308746,0.00008200384,0.00035202288,0.00012105046,0.9526622,0.025889453,0.01050306,0.005447113,0.00005478969],"about_ca_topic_score_codex":0.0016288473,"about_ca_topic_score_gemma":0.0020836717,"teacher_disagreement_score":0.0023391352,"about_ca_system_score_codex":0.00030065246,"about_ca_system_score_gemma":0.00083598756,"threshold_uncertainty_score":0.012370706},"labels":[],"label_agreement":null},{"id":"W2977742585","doi":"10.1016/j.neuroimage.2019.116226","title":"Brain status modeling with non-negative projective dictionary learning","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; École de Technologie Supérieure; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Aerospace Science Foundation of China; National Institutes of Health; Fonds de Recherche du Québec - Santé; National Natural Science Foundation of China; Fondation Brain Canada","keywords":"Discriminative model; Neuroimaging; Artificial intelligence; Computer science; Pattern recognition (psychology); Feature selection; Feature (linguistics); Psychology; Neuroscience","score_opus":0.03745440563170813,"score_gpt":0.32865332863927393,"score_spread":0.2911989230075658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977742585","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08182756,0.00024182524,0.91643953,0.00018252012,0.000027761525,0.000034469278,0.00023796891,0.00024301239,0.0007653754],"genre_scores_gemma":[0.8547413,0.00030646843,0.14122726,0.00012613763,0.00004388097,0.00011063112,0.0007122839,0.000049318824,0.0026827184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998012,0.00007166521,0.000010507279,0.00006471499,0.000029869714,0.000022053615],"domain_scores_gemma":[0.9995357,0.00022740092,0.0000710676,0.000059273512,0.00008041281,0.000026213016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005138367,0.00045783148,0.00039689554,0.00043288333,0.00013350502,0.00042905935,0.000644675,0.0004406363,0.0007193554],"category_scores_gemma":[0.0017982724,0.00023576888,0.0004602616,0.0003597975,0.0003810873,0.00058958604,0.000500903,0.0006005212,0.00025782172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018386621,0.00010299265,0.0115136495,0.00009104772,0.00012874485,0.00022198643,0.000160688,0.7458235,0.011898259,0.014039497,0.0027051477,0.21313061],"study_design_scores_gemma":[0.0000032421856,0.000019350071,0.0004971721,0.0000021185574,0.0000043311074,0.000030416893,0.000006289356,0.9965217,0.00050774904,0.0022072783,0.00019696064,0.0000033082829],"about_ca_topic_score_codex":0.0031248722,"about_ca_topic_score_gemma":0.0037105987,"teacher_disagreement_score":0.0031248722,"about_ca_system_score_codex":0.000276809,"about_ca_system_score_gemma":0.00037953592,"threshold_uncertainty_score":0.006213367},"labels":[],"label_agreement":null},{"id":"W2977932297","doi":"10.1093/schbul/sbz019.333","title":"T53. AN EFFECT-SIZE META-ANALYSIS OF WHITE MATTER DAMAGE RELATED TO CANNABIS USE: RELEVANCE TO THE ANATOMY OF PSYCHOSIS","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Cannabis; White matter; Fractional anisotropy; Psychosis; Meta-analysis; Schizophrenia (object-oriented programming); Psychology; Diffusion MRI; Effects of cannabis; Psychiatry; Clinical psychology; Medicine; Audiology; Internal medicine; Magnetic resonance imaging; Radiology; Cannabidiol","score_opus":0.029051361499693812,"score_gpt":0.3427579512224502,"score_spread":0.31370658972275633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977932297","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13068752,0.78641325,0.03642228,0.0060184533,0.0067016785,0.006644093,0.019140797,0.0017493315,0.0062226597],"genre_scores_gemma":[0.910048,0.052147437,0.020567022,0.0029100277,0.0013404434,0.0060329502,0.003108193,0.00036689235,0.00347891],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.98535836,0.009564223,0.0020551018,0.0017072769,0.00087766914,0.00043732094],"domain_scores_gemma":[0.982001,0.014413624,0.0016704524,0.0008934285,0.0007190651,0.00030231432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015552383,0.0028174422,0.008411247,0.0044455086,0.00088222546,0.0028772738,0.0020793343,0.003833771,0.011504581],"category_scores_gemma":[0.039725587,0.0011443807,0.044865333,0.0047194576,0.0008382589,0.0017512002,0.0015340522,0.0027843958,0.00090510026],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0141530465,0.000045633184,0.007194015,0.07650126,0.8870801,0.00042277778,0.00013850092,0.0009742792,0.0017837996,0.00065195025,0.0024149108,0.008639677],"study_design_scores_gemma":[0.0049028415,0.00057564763,0.0057963077,0.0022846696,0.9817939,0.00011888748,0.000030597337,0.00066427654,0.0003728354,0.00090218824,0.0025304933,0.000027362774],"about_ca_topic_score_codex":0.006320992,"about_ca_topic_score_gemma":0.008321479,"teacher_disagreement_score":0.015552383,"about_ca_system_score_codex":0.0010741901,"about_ca_system_score_gemma":0.0019928757,"threshold_uncertainty_score":0.08224988},"labels":[],"label_agreement":null},{"id":"W2978374216","doi":"10.3233/jad-190446","title":"Multicenter Tract-Based Analysis of Microstructural Lesions within the Alzheimer’s Disease Spectrum: Association with Amyloid Pathology and Diagnostic Usefulness","year":2019,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Dementia; Fractional anisotropy; Biomarker; Medicine; Cognitive decline; Prospective cohort study; Internal medicine; Alzheimer's disease; White matter; Disease; Pathology; Oncology; Psychology; Radiology; Magnetic resonance imaging","score_opus":0.03281436635443027,"score_gpt":0.31216672371294624,"score_spread":0.279352357358516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978374216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977684,0.00022878993,0.0017236971,0.000010637644,0.0000015167079,0.000006022117,0.000112945556,0.000015154378,0.00013290951],"genre_scores_gemma":[0.9984497,0.000043798893,0.0012888418,0.000003364398,0.000002700587,0.0000055673795,0.00015912007,0.00000518923,0.00004165667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949443,0.0001928057,0.00006953885,0.00014576073,0.000065495566,0.000031846528],"domain_scores_gemma":[0.9975707,0.0005248434,0.001074662,0.0004602573,0.00025150197,0.00011797197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016823708,0.00025801305,0.00030421626,0.0010523755,0.0002674104,0.0003985469,0.00023026684,0.0002592895,0.00063655875],"category_scores_gemma":[0.0035931007,0.00014424308,0.00033370833,0.0004869537,0.0003068419,0.00035311174,0.00041317943,0.00015560383,0.00012083259],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007598071,0.000045390883,0.95610696,0.00003740078,0.00045188857,0.00015628412,0.00030656927,0.0007809263,0.02588723,0.00011762299,0.00008918067,0.015260741],"study_design_scores_gemma":[0.000008633721,0.0001560979,0.9947391,0.000008928597,0.00006152641,0.00067083305,0.000058298498,0.0017819174,0.0021956726,0.00015158528,0.000159642,0.000007661179],"about_ca_topic_score_codex":0.0023337998,"about_ca_topic_score_gemma":0.0039924886,"teacher_disagreement_score":0.0023337998,"about_ca_system_score_codex":0.00020927422,"about_ca_system_score_gemma":0.00020918464,"threshold_uncertainty_score":0.008897305},"labels":[],"label_agreement":null},{"id":"W2978497465","doi":"10.1017/s1041610219001418","title":"Glutamine + glutamate level predicts the magnitude of microstructural organization in the gray matter in the healthy elderly","year":2019,"lang":"en","type":"article","venue":"International Psychogeriatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"Japan Society for the Promotion of Science","keywords":"Glutamine; White matter; Diffusion MRI; Glutamate receptor; Neuroscience; Anterior cingulate cortex; Posterior cingulate; Prefrontal cortex; Magnetic resonance imaging; Cortex (anatomy); Internal medicine; Psychology; Chemistry; Medicine; Amino acid; Biochemistry","score_opus":0.03147723437835876,"score_gpt":0.3426619046844492,"score_spread":0.3111846703060904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978497465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995413,0.000114361916,0.000055848504,0.000011964212,0.0000018027945,0.000002903272,0.0001416777,0.0000021207575,0.00012804849],"genre_scores_gemma":[0.99963725,0.000050460963,0.000088773064,0.000007205669,0.0000026311695,0.0000026369346,0.00012667158,5.1393783e-7,0.00008383451],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999944,0.000008901028,0.000011100562,0.000018786703,0.000008068818,0.000009124876],"domain_scores_gemma":[0.9995598,0.00009255495,0.00019661793,0.000027564622,0.000050892577,0.000072501934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002882814,0.00033787376,0.00017132191,0.0004126844,0.00018763938,0.00033758607,0.0001316181,0.00034992097,0.0014629659],"category_scores_gemma":[0.0010855586,0.00015537227,0.00020754244,0.00023989582,0.00016675181,0.00020784425,0.0002208383,0.0002067398,0.00024635778],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019442366,0.000018793458,0.9978102,0.000007899354,0.00004448032,0.000041397238,0.00003098367,0.000070793925,0.0008477523,0.000006596552,0.00003763604,0.00088916323],"study_design_scores_gemma":[0.000002958321,0.00005177856,0.9995421,0.0000014575976,0.000017233755,0.00008285016,0.00003381379,0.00014978509,0.00007634705,0.000015281386,0.000025376517,0.0000010484383],"about_ca_topic_score_codex":0.0030830076,"about_ca_topic_score_gemma":0.0036936176,"teacher_disagreement_score":0.0030830076,"about_ca_system_score_codex":0.00012620003,"about_ca_system_score_gemma":0.00010059134,"threshold_uncertainty_score":0.006130159},"labels":[],"label_agreement":null},{"id":"W2978584402","doi":"10.3389/fnagi.2019.00270","title":"Free Water in White Matter Differentiates MCI and AD From Control Subjects","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Hyperintensity; Partial volume; Fluid-attenuated inversion recovery; Cardiology; Psychology; Neuroscience; Internal medicine; Magnetic resonance imaging; Pathology; Medicine; Nuclear medicine; Radiology","score_opus":0.015912025209341336,"score_gpt":0.2660259573467302,"score_spread":0.25011393213738886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978584402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979724,0.0006381679,0.0005904062,0.000020561196,0.000013080501,0.000028100498,0.00016984371,0.000024951136,0.0005424569],"genre_scores_gemma":[0.9982919,0.00015563596,0.0007072696,0.00003301354,0.000020643984,0.00002562014,0.0005013258,0.000008394662,0.00025618175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996644,0.00006273077,0.000056037912,0.00012463752,0.000052836083,0.000039459188],"domain_scores_gemma":[0.9995384,0.00013580942,0.00012427062,0.00006280468,0.000056050834,0.00008274018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010700556,0.00073065376,0.00058242824,0.0023343628,0.00037370957,0.00081582065,0.00028177764,0.00076478085,0.0011961785],"category_scores_gemma":[0.0017895305,0.00018746914,0.00030861393,0.0005315107,0.0005955248,0.0004394576,0.0004877648,0.00020648389,0.0002734749],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010226298,0.0005622788,0.88056433,0.00032367726,0.0007592512,0.0011686899,0.0013669481,0.0006179926,0.054882716,0.0005014546,0.0007255204,0.048300833],"study_design_scores_gemma":[0.00005812392,0.0005826405,0.99332786,0.000017180137,0.000117511896,0.0006016273,0.0004034565,0.0012152401,0.0026716294,0.00038253504,0.00060391694,0.000018279441],"about_ca_topic_score_codex":0.003390199,"about_ca_topic_score_gemma":0.0037312824,"teacher_disagreement_score":0.003390199,"about_ca_system_score_codex":0.00019075678,"about_ca_system_score_gemma":0.00018969427,"threshold_uncertainty_score":0.0067409277},"labels":[],"label_agreement":null},{"id":"W2978944956","doi":"10.3389/fnins.2019.01053","title":"Quantifying Neurodegenerative Progression With DeepSymNet, an End-to-End Data-Driven Approach","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; Nvidia; F. Hoffmann-La Roche; National Center for Advancing Translational Sciences; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Neuroimaging; Computer science; Artificial intelligence; Voxel; Population; Deep learning; Preprocessor; Machine learning; Medicine; Neuroscience; Psychology","score_opus":0.12866102627308487,"score_gpt":0.38915079730854735,"score_spread":0.26048977103546245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978944956","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08531211,0.0014891628,0.8942237,0.0013436539,0.00026947077,0.00032184634,0.0038333177,0.011464463,0.0017423282],"genre_scores_gemma":[0.5564587,0.00065044564,0.42482933,0.0009038949,0.0001765237,0.00046943518,0.009725147,0.00060721394,0.0061793723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960095,0.000057306082,0.000027527034,0.00016569482,0.000099763696,0.00004879365],"domain_scores_gemma":[0.99931157,0.00021175263,0.00007330666,0.00009052062,0.00025053468,0.00006238686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015862498,0.001816549,0.0012175512,0.0010504308,0.00046865252,0.0010213227,0.00206126,0.0019150722,0.0017294843],"category_scores_gemma":[0.0024922737,0.00073573616,0.0010957902,0.0007878949,0.0005721432,0.0012948342,0.0014520115,0.0022459754,0.00079752144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053894427,0.00041788892,0.0075012087,0.00022203273,0.0003466083,0.00028841334,0.00008568764,0.6499208,0.0077588693,0.0030245343,0.012183603,0.31771144],"study_design_scores_gemma":[0.00001245476,0.000046301935,0.00040376716,0.00000921152,0.000016087113,0.00003948595,0.0000068669706,0.9932621,0.002109965,0.0033560882,0.0007270093,0.000010736992],"about_ca_topic_score_codex":0.010943747,"about_ca_topic_score_gemma":0.023095367,"teacher_disagreement_score":0.010943747,"about_ca_system_score_codex":0.0013359084,"about_ca_system_score_gemma":0.0019392829,"threshold_uncertainty_score":0.021760106},"labels":[],"label_agreement":null},{"id":"W2979488433","doi":"10.1007/s11682-019-00193-6","title":"White matter microstructure in women with acute and remitted anorexia nervosa: an exploratory neuroimaging study","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Psychology; Neuroimaging; External capsule; Anorexia nervosa; Corona radiata (embryology); Internal capsule; Grey matter; Psychiatry; Internal medicine; Neuroscience; Medicine; Eating disorders; Magnetic resonance imaging; Radiology","score_opus":0.018105067132589463,"score_gpt":0.30612855027810437,"score_spread":0.2880234831455149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979488433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99966395,0.00007345767,0.0000123190375,0.000011487052,0.0000010630553,0.000010106033,0.000047243833,4.8373045e-7,0.00017982934],"genre_scores_gemma":[0.99945265,0.00010558154,0.00005870118,0.000026901977,0.000005243193,0.000010803603,0.00009876106,9.2196524e-7,0.00024039038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999062,0.000022448365,0.000008313035,0.000025286454,0.0000117974505,0.00002595834],"domain_scores_gemma":[0.9997619,0.00004661764,0.00008333723,0.000020600695,0.000024820689,0.000062828476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026999685,0.0004424734,0.00038281013,0.00064800907,0.00076932553,0.00041251176,0.0003143034,0.0005541605,0.0012424327],"category_scores_gemma":[0.00090844644,0.00037714414,0.00029371903,0.0005850072,0.0006457111,0.0004771163,0.00051626906,0.00040199136,0.00022792962],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001322606,0.0006463423,0.98641485,0.000031728163,0.0000677118,0.003142118,0.0019740085,0.000042224154,0.0039820066,0.00005132119,0.000055022643,0.0022700327],"study_design_scores_gemma":[0.000012409332,0.00051097,0.9966774,0.0000028265738,0.000019212692,0.0013141042,0.0012908556,0.000026444677,0.000057938123,0.00001989774,0.00006458505,0.0000032510868],"about_ca_topic_score_codex":0.009477975,"about_ca_topic_score_gemma":0.012768182,"teacher_disagreement_score":0.009477975,"about_ca_system_score_codex":0.00045375866,"about_ca_system_score_gemma":0.0003997495,"threshold_uncertainty_score":0.018845618},"labels":[],"label_agreement":null},{"id":"W2979668791","doi":"10.1101/796615","title":"Freewater EstimatoR using iNtErpolated iniTialization (FERNET): Toward Accurate Estimation of Free Water in Peritumoral Region Using Single-Shell Diffusion MRI Data","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Initialization; Diffusion MRI; Tractography; Estimator; Computer science; Free water; Shell (structure); Magnetic resonance imaging; Diffusion; Biomedical engineering; Algorithm; Artificial intelligence; Medicine; Radiology; Materials science; Mathematics; Statistics; Physics; Geology","score_opus":0.127315405091424,"score_gpt":0.32864350684893223,"score_spread":0.20132810175750823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979668791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010112974,0.00015268117,0.98865926,0.00008210181,0.000025241368,0.000029911587,0.00005505624,0.00067154097,0.00021117074],"genre_scores_gemma":[0.099884905,0.00022271564,0.8978862,0.00008756206,0.000031079806,0.000096539436,0.00040323593,0.00036151247,0.0010262971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996201,0.00013795543,0.000023194772,0.00009180992,0.0000900636,0.000036846133],"domain_scores_gemma":[0.9985448,0.00079129625,0.00018870852,0.00015993595,0.00023901925,0.00007634394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023184624,0.0011379557,0.0008113551,0.0013541456,0.00048950565,0.0010107986,0.0012548132,0.001845591,0.0011197659],"category_scores_gemma":[0.008563746,0.00059591886,0.0006804733,0.0009751046,0.00074829534,0.0016384637,0.0015376521,0.0015206966,0.00061264215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008020631,0.00020257896,0.0034916755,0.00041059832,0.00014799285,0.00033850982,0.00033294456,0.50212306,0.08030444,0.013739996,0.005609453,0.39249673],"study_design_scores_gemma":[0.000024391396,0.000041365758,0.00033205232,0.000021314763,0.000011222691,0.00007450845,0.000014959742,0.97955036,0.015027534,0.003154002,0.0017274522,0.00002083845],"about_ca_topic_score_codex":0.0039262907,"about_ca_topic_score_gemma":0.0054027936,"teacher_disagreement_score":0.0039262907,"about_ca_system_score_codex":0.0005867355,"about_ca_system_score_gemma":0.001526923,"threshold_uncertainty_score":0.012261331},"labels":[],"label_agreement":null},{"id":"W2979919254","doi":"10.1016/j.neuroimage.2019.116255","title":"Quantification of apparent axon density and orientation dispersion in the white matter of youth born with congenital heart disease","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Montreal Children's Hospital; Université de Sherbrooke; McGill University Health Centre; McGill University","funders":"Canada First Research Excellence Fund; Canadian Institutes of Health Research; McGill University Health Centre; Faculty of Medicine, McGill University; McGill University; Institut de recherche, Centre universitaire de santé McGill","keywords":"White matter; Corpus callosum; Diffusion MRI; Fractional anisotropy; Axon; Magnetic resonance imaging; Psychology; Neuroscience; Anatomy; Cardiology; Medicine; Radiology","score_opus":0.03581453844897592,"score_gpt":0.301980156900281,"score_spread":0.2661656184513051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979919254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99962425,0.000049821894,0.00019104604,0.0000023787584,4.7105507e-7,0.000003031863,0.00007737922,0.000003857172,0.00004763355],"genre_scores_gemma":[0.9985877,0.000087352986,0.0010643938,0.0000027847636,0.0000011471168,0.0000069745724,0.00017826838,0.0000030554793,0.00006834472],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998909,0.000015268359,0.0000134495285,0.000030766965,0.000032075463,0.000017453984],"domain_scores_gemma":[0.99929726,0.000097652635,0.00038428928,0.000035567005,0.00010011428,0.00008508703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042533202,0.00024879852,0.0001965873,0.0011712572,0.00016457433,0.00033474131,0.00014553637,0.00020992993,0.0005114556],"category_scores_gemma":[0.0011283439,0.0001252085,0.000114005576,0.0004151828,0.00026050242,0.00023519457,0.00032462736,0.00018088333,0.0000690993],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015935654,0.000034113316,0.9822375,0.000026886595,0.000027125834,0.00025372716,0.00030845532,0.00016183054,0.010246712,0.00004095765,0.000041015424,0.0064623444],"study_design_scores_gemma":[0.0000013697928,0.00007025008,0.99788576,0.000006543416,0.0000098941055,0.00046273036,0.00015855348,0.00025708418,0.0010805996,0.000018697378,0.00004607143,0.0000023999128],"about_ca_topic_score_codex":0.0039201714,"about_ca_topic_score_gemma":0.005772891,"teacher_disagreement_score":0.0039201714,"about_ca_system_score_codex":0.00029363896,"about_ca_system_score_gemma":0.00023588334,"threshold_uncertainty_score":0.007794678},"labels":[],"label_agreement":null},{"id":"W2980279673","doi":"10.3389/conf.fnhum.2019.01.00114","title":"A DTI study of cognitive function post stroke","year":2019,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; Neurocognitive; Diffusion MRI; Stroke (engine); Superior longitudinal fasciculus; Medicine; Montreal Cognitive Assessment; Corpus callosum; Rehabilitation; Arcuate fasciculus; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Physical therapy; Pathology; Psychiatry; Cognitive impairment; Radiology","score_opus":0.04839063865320071,"score_gpt":0.34380756651479344,"score_spread":0.29541692786159274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980279673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928116,0.000575707,0.00016051557,0.0002564623,0.00003713809,0.00014021865,0.0013912048,0.0000088336965,0.0046182508],"genre_scores_gemma":[0.9945251,0.00047651955,0.0002880724,0.00010649099,0.000083479616,0.0001113627,0.0012859122,0.0000067396413,0.003116355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998085,0.000050572184,0.000023289807,0.00003665892,0.000032481505,0.000048497008],"domain_scores_gemma":[0.99927276,0.00013925752,0.00012140375,0.00006919865,0.00014612544,0.0002512612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007251263,0.00041664916,0.0005133163,0.0015557862,0.0012868734,0.0006536763,0.0003217784,0.00053943286,0.003591718],"category_scores_gemma":[0.0021749642,0.00017953242,0.00028151664,0.0017428701,0.00044969766,0.00079569843,0.0005920821,0.00072345935,0.0010039624],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012495793,0.003498621,0.92314696,0.00030386474,0.00053752965,0.007683204,0.003297957,0.00025857252,0.005434151,0.0007768009,0.0044820826,0.038084522],"study_design_scores_gemma":[0.00013331555,0.0021842876,0.9926778,0.000020740254,0.00009015043,0.0017602706,0.000737376,0.000117390766,0.0002800976,0.00034131823,0.0016323379,0.000024923647],"about_ca_topic_score_codex":0.015273014,"about_ca_topic_score_gemma":0.016163865,"teacher_disagreement_score":0.015273014,"about_ca_system_score_codex":0.00065112894,"about_ca_system_score_gemma":0.0009889742,"threshold_uncertainty_score":0.030368209},"labels":[],"label_agreement":null},{"id":"W2980535964","doi":"10.1007/s00429-019-01963-0","title":"The descending motor tracts are different in dancers and musicians","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep Marie-Victorin; Concordia University; McGill University; International Laboratory for Brain, Music and Sound Research","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Diffusion MRI; Tractography; Psychology; Dance; Corticospinal tract; White matter; Neuroscience; Pyramidal tracts; Motor cortex; Corpus callosum; Motor learning; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.023335629380980775,"score_gpt":0.27973532344128127,"score_spread":0.2563996940603005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980535964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956802,0.0010478394,0.0012446032,0.00015335817,0.000016646465,0.000011442639,0.00011863287,0.000022464365,0.0017048452],"genre_scores_gemma":[0.995805,0.0005709585,0.0011935853,0.00009539353,0.000027078191,0.00001648088,0.00014852156,0.00002065026,0.0021222422],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99990356,0.00001501009,0.000008680516,0.00003612314,0.000015535019,0.000021041064],"domain_scores_gemma":[0.9996966,0.00007956051,0.00011603739,0.000025577063,0.00003789458,0.000044304266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020225649,0.00040052534,0.00030390028,0.0008842978,0.00036090266,0.00060395396,0.00021000499,0.0004605442,0.003653882],"category_scores_gemma":[0.0011409677,0.00021391653,0.00018347746,0.0004110746,0.00065258326,0.0005788863,0.000274265,0.0004275489,0.0004476667],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033304999,0.00019313407,0.35551396,0.00049057766,0.00040730342,0.0042955205,0.0036667534,0.00042889258,0.50405926,0.0026618703,0.00077823305,0.124173924],"study_design_scores_gemma":[0.00002383475,0.00018274048,0.9899923,0.0000361378,0.000046326422,0.0021598244,0.00080179307,0.0003181384,0.005043858,0.0008206998,0.00056567293,0.00000869802],"about_ca_topic_score_codex":0.0032455686,"about_ca_topic_score_gemma":0.0062020887,"teacher_disagreement_score":0.003653882,"about_ca_system_score_codex":0.00024987446,"about_ca_system_score_gemma":0.00020679126,"threshold_uncertainty_score":0.012223482},"labels":[],"label_agreement":null},{"id":"W2980627049","doi":"10.3389/fnhum.2019.00352","title":"White Matter Integrity Is Associated With Intraindividual Variability in Neuropsychological Test Performance in Healthy Older Adults","year":2019,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Neuropsychology; White matter; Psychology; Neuropsychological test; Test (biology); Clinical psychology; Audiology; Medicine; Cognition; Psychiatry; Magnetic resonance imaging; Biology","score_opus":0.03180931399941534,"score_gpt":0.32035138698081667,"score_spread":0.28854207298140133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980627049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965703,0.00007005422,0.00007152979,0.000011362906,0.0000012539473,0.0000022171123,0.00004991227,0.0000028440877,0.00013371352],"genre_scores_gemma":[0.99974316,0.000021848005,0.00007848794,0.000005987952,0.00000383036,0.0000019346062,0.000074528485,0.0000012459585,0.00006894645],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99969494,0.000055866516,0.00006225849,0.00008929062,0.000064112755,0.000033661167],"domain_scores_gemma":[0.99771935,0.000356337,0.0013577593,0.00023332651,0.00018799663,0.00014518612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007052409,0.00029636992,0.0002449513,0.0008553308,0.00023614414,0.00042495996,0.00023227476,0.00046684404,0.00066084036],"category_scores_gemma":[0.0034843183,0.00019099975,0.00021026768,0.0004454449,0.00031696016,0.00043549208,0.0004562069,0.00030694285,0.00017201202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014978451,0.000030391646,0.99602985,0.000006448264,0.00006122758,0.00005520737,0.00022233996,0.00004967225,0.0012050103,0.000014280881,0.00003240964,0.002143336],"study_design_scores_gemma":[7.8255687e-7,0.000036286678,0.9996799,8.837223e-7,0.0000053348367,0.000076080134,0.000032556745,0.00005403632,0.00008284996,0.000016728995,0.000013448152,0.0000010652734],"about_ca_topic_score_codex":0.002735161,"about_ca_topic_score_gemma":0.004217194,"teacher_disagreement_score":0.002735161,"about_ca_system_score_codex":0.00016864135,"about_ca_system_score_gemma":0.00010701505,"threshold_uncertainty_score":0.005438447},"labels":[],"label_agreement":null},{"id":"W2980921467","doi":"10.1016/j.neuroimage.2019.116274","title":"Adaptive phase correction of diffusion-weighted images","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; CARE Canada; Philips (Canada)","funders":"European Research Council; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Diffusion MRI; Regularization (linguistics); Preprocessor; Mathematics; Gaussian; Image quality; Algorithm; Gaussian noise; Artificial intelligence; Rician fading; Noise (video); Computer science; Pattern recognition (psychology); Magnetic resonance imaging; Image (mathematics); Physics","score_opus":0.04029410667227545,"score_gpt":0.3471191143887975,"score_spread":0.30682500771652205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980921467","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010967944,0.00036960194,0.9866648,0.00011078102,0.00007822783,0.000057096142,0.0000789962,0.000723751,0.00094883307],"genre_scores_gemma":[0.11835176,0.0010220899,0.87703407,0.000108589324,0.00006193521,0.00009887029,0.00028211332,0.00051208405,0.0025285569],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956447,0.000089072135,0.000028033219,0.00012649011,0.00015762258,0.000034284738],"domain_scores_gemma":[0.9991424,0.00029830754,0.00015250305,0.00016268487,0.00022003162,0.000024083713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136179,0.00095538184,0.0005208994,0.0007743772,0.0003374535,0.00095458294,0.00078743586,0.0007627953,0.002743392],"category_scores_gemma":[0.004407968,0.00041618533,0.00048653703,0.0010343362,0.000557474,0.00092075265,0.0007601637,0.0010518143,0.0013151021],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032948743,0.000080338854,0.0014880261,0.0005805669,0.00010272653,0.0003632925,0.00017844499,0.045796636,0.4310576,0.01683329,0.0034777618,0.49971193],"study_design_scores_gemma":[0.000060942562,0.00028409986,0.0033288654,0.000086666674,0.000106447005,0.0018076396,0.000061267434,0.46554524,0.47239006,0.016363153,0.039855685,0.00011009088],"about_ca_topic_score_codex":0.0008075236,"about_ca_topic_score_gemma":0.0010541747,"teacher_disagreement_score":0.002743392,"about_ca_system_score_codex":0.00030695484,"about_ca_system_score_gemma":0.0008192421,"threshold_uncertainty_score":0.009177566},"labels":[],"label_agreement":null},{"id":"W2980937299","doi":"10.1016/j.jalz.2019.08.120","title":"P4‐572: NEURAL CORRELATES OF COGNITIVE PERFORMANCE IN ALZHEIMER'S DISEASE AND LEWY BODY DISEASE SPECTRA","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Psychology; Executive dysfunction; Diffusion MRI; Audiology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Neuropsychology; Radiology","score_opus":0.032088284934262946,"score_gpt":0.3095251436414882,"score_spread":0.27743685870722523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980937299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99951565,0.0000735165,0.000017323366,0.000007457497,0.0000018002331,0.0000044424746,0.00010357221,0.000001008838,0.00027521656],"genre_scores_gemma":[0.9994294,0.000041578933,0.0000393437,0.000010795956,0.0000054830434,0.000006163582,0.00026725943,0.0000010511502,0.00019895575],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998896,0.000012037807,0.00001721351,0.000026673622,0.000026710686,0.000027767886],"domain_scores_gemma":[0.9994863,0.00007247345,0.00022463017,0.000028597222,0.00007676243,0.00011130111],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025927243,0.0005316969,0.00042238142,0.0010996279,0.00041514816,0.00052517996,0.00029897116,0.00035901458,0.0016913136],"category_scores_gemma":[0.0012384835,0.00019419797,0.00020402916,0.00068388844,0.00035582954,0.00040029996,0.00048313037,0.00037839037,0.0003687756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065205625,0.00009103308,0.9946484,0.000014275075,0.000050705727,0.00064953545,0.00010711823,0.00005036605,0.0013080915,0.000022083854,0.00006370655,0.0023426632],"study_design_scores_gemma":[0.000010962066,0.00013649532,0.99866605,0.0000031143773,0.000015933032,0.0006801956,0.00010676778,0.0000986872,0.00016725718,0.000039730057,0.000071843446,0.0000030257463],"about_ca_topic_score_codex":0.004010684,"about_ca_topic_score_gemma":0.0037456,"teacher_disagreement_score":0.004010684,"about_ca_system_score_codex":0.00030974348,"about_ca_system_score_gemma":0.00019711003,"threshold_uncertainty_score":0.007974684},"labels":[],"label_agreement":null},{"id":"W2980965008","doi":"10.1016/j.jalz.2019.06.1200","title":"P1‐595: HIGHER LITERACY ASSOCIATES WITH BETTER BRAIN STRUCTURE AND COGNITION IN MIDDLE‐AGED INDIVIDUALS","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; White matter; Psychology; Logistic regression; Literacy; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Clinical psychology; Medicine; Internal medicine; Gerontology; Magnetic resonance imaging; Neuroscience","score_opus":0.03496237975333192,"score_gpt":0.3097574231830202,"score_spread":0.27479504342968825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980965008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970901,0.00013629343,0.000109421,0.00018432291,0.000014215882,0.000008329802,0.00051316415,0.000007126461,0.0019370344],"genre_scores_gemma":[0.9988207,0.000040943338,0.00010453533,0.000054055003,0.000018435452,0.000008883129,0.00030803386,0.0000021412773,0.000642239],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998678,0.00002879904,0.000016352802,0.000040843996,0.000022423304,0.000023793755],"domain_scores_gemma":[0.99906033,0.00019764816,0.0004012088,0.00004615712,0.00008772441,0.00020684648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027198368,0.00034468083,0.00028741418,0.00045763186,0.00043306657,0.00056900014,0.00030314445,0.00074404385,0.015059268],"category_scores_gemma":[0.0024003214,0.00017914118,0.00040362732,0.00047706196,0.000357274,0.00051197724,0.00058161916,0.0006168384,0.0013430978],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056355435,0.0001935822,0.9918379,0.000040259227,0.0000841074,0.0002474014,0.0001637947,0.000038433616,0.0006070559,0.00006374964,0.0006579146,0.005502283],"study_design_scores_gemma":[0.00001536413,0.00014250337,0.99901354,0.000008923447,0.000028899125,0.00020967945,0.00007892814,0.00016426771,0.00006262986,0.00012379645,0.00014902074,0.0000023939954],"about_ca_topic_score_codex":0.0033523412,"about_ca_topic_score_gemma":0.002475689,"teacher_disagreement_score":0.015059268,"about_ca_system_score_codex":0.00012249865,"about_ca_system_score_gemma":0.000239878,"threshold_uncertainty_score":0.050378263},"labels":[],"label_agreement":null},{"id":"W2980976190","doi":"10.1016/j.jalz.2019.06.4200","title":"IC‐P‐038: DIFFERENTIAL GREY AND WHITE MATTER MICROSTRUCTURAL ABNORMALITIES IN EARLY AND LATE‐ONSET ALZHEIMER'S DISEASE AND MILD COGNITIVE IMPAIRMENT","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Precuneus; Diffusion MRI; Grey matter; Fractional anisotropy; Dementia; Cardiology; Cognitive decline; Medicine; Internal medicine; Age of onset; Psychology; Audiology; Disease; Neuroscience; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.024555491158394695,"score_gpt":0.29118170939955274,"score_spread":0.26662621824115806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980976190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991198,0.000109805624,0.000042686133,0.000016894926,0.0000045400366,0.000009454023,0.00012933169,0.0000068072304,0.0005606994],"genre_scores_gemma":[0.99885106,0.000044842232,0.00009491498,0.000029482811,0.000009878407,0.000011268053,0.00038225434,0.00000532421,0.0005709895],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992216,0.000011649511,0.00000850004,0.000025359357,0.0000134294405,0.000018890007],"domain_scores_gemma":[0.99979955,0.000024880614,0.000046727204,0.000020837379,0.000034856163,0.00007323406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025735953,0.00039760294,0.00032981863,0.00035890818,0.00025890264,0.00027366084,0.00022835704,0.00037420387,0.0025621452],"category_scores_gemma":[0.00051628036,0.0001189605,0.00012803198,0.00025782027,0.00021749134,0.00014885949,0.000285254,0.00025387545,0.00056806],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018033946,0.0015260538,0.8133411,0.00021032074,0.00025140238,0.0061082975,0.0006360962,0.00021232902,0.10484165,0.00015235838,0.0019342239,0.052752163],"study_design_scores_gemma":[0.00006789023,0.00083355355,0.9950539,0.0000054808547,0.000026619813,0.0021561678,0.000054577402,0.00015937744,0.0011172289,0.000046309786,0.00047461668,0.0000043431537],"about_ca_topic_score_codex":0.0041924957,"about_ca_topic_score_gemma":0.0028126582,"teacher_disagreement_score":0.0041924957,"about_ca_system_score_codex":0.00017350311,"about_ca_system_score_gemma":0.0002110655,"threshold_uncertainty_score":0.0085712075},"labels":[],"label_agreement":null},{"id":"W2981131390","doi":"10.1016/j.jalz.2019.06.2813","title":"P2‐406: INVESTIGATING THE SENSITIVITY OF FREE‐WATER IMAGING IN DETECTING WHITE‐MATTER ABNORMALITIES WITHIN PATIENTS WITH ALZHEIMER'S DISEASE","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Corpus callosum; Splenium; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Nuclear magnetic resonance; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Audiology; Nuclear medicine; Physics; Radiology","score_opus":0.025644432178095398,"score_gpt":0.2713589953143164,"score_spread":0.245714563136221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981131390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992424,0.000054725348,0.00013329933,0.000021146041,0.0000045662487,0.000011354456,0.00011075233,0.000007309214,0.00041441774],"genre_scores_gemma":[0.9993333,0.000026701631,0.0002366027,0.00001355539,0.000008687264,0.000013420765,0.00015581156,0.0000042779157,0.00020768544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99960047,0.000089804715,0.00005147057,0.00014131243,0.00007283887,0.000044127337],"domain_scores_gemma":[0.9987054,0.00050268916,0.0002729513,0.00010936772,0.00016764192,0.00024188185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013428075,0.00053384475,0.00035265423,0.0006625582,0.00045937355,0.00072054483,0.0003615997,0.0010407126,0.0018944696],"category_scores_gemma":[0.004387449,0.00025958286,0.00029729703,0.00042919233,0.00040484546,0.0007185113,0.00063280656,0.0004276437,0.00073007605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054386514,0.00030565148,0.96932775,0.000063536594,0.000235982,0.00055420486,0.00073547265,0.00042762785,0.010518054,0.00006566634,0.0002555368,0.01207197],"study_design_scores_gemma":[0.00006631275,0.0015515217,0.9929617,0.0000074032087,0.0000701548,0.0011640225,0.00029642318,0.0015364189,0.0016407719,0.00019001466,0.00049949985,0.000015824131],"about_ca_topic_score_codex":0.0012406411,"about_ca_topic_score_gemma":0.0011432889,"teacher_disagreement_score":0.0018944696,"about_ca_system_score_codex":0.00015217182,"about_ca_system_score_gemma":0.00015338343,"threshold_uncertainty_score":0.007101536},"labels":[],"label_agreement":null},{"id":"W2981254264","doi":"10.1016/j.jalz.2019.06.2736","title":"P2‐329: TRACKING WHITE MATTER DEGENERATION IN ASYMPTOMATIC AND SYMPTOMATIC <i>MAPT</i> MUTATION CARRIERS WITH DTI","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Asymptomatic; Asymptomatic carrier; White matter; Fractional anisotropy; Diffusion MRI; Frontotemporal lobar degeneration; Medicine; Frontotemporal dementia; Pathology; Internal medicine; Dementia; Magnetic resonance imaging; Radiology; Disease","score_opus":0.02619467090158327,"score_gpt":0.2912314390830439,"score_spread":0.2650367681814606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981254264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991881,0.00002243584,0.0004703366,0.000010264707,9.666697e-7,0.0000072284765,0.00015127499,0.000022984235,0.00012636208],"genre_scores_gemma":[0.99820423,0.000023890958,0.001342245,0.0000043568293,0.0000018335616,0.000012320879,0.00024767828,0.000008188883,0.00015531095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999435,0.000013661394,0.0000044450676,0.000022513288,0.000008805717,0.000007146623],"domain_scores_gemma":[0.99975544,0.00005146603,0.000090610156,0.000013825421,0.000039588005,0.000049137947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003002649,0.00031323874,0.00019387217,0.000471257,0.000208211,0.00032259978,0.00014551556,0.00029776705,0.0008437869],"category_scores_gemma":[0.0011647741,0.00011538899,0.00013207963,0.00020821953,0.00009945983,0.00022320921,0.00018065858,0.00013745422,0.00023929366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010916148,0.00011918995,0.937512,0.000045483823,0.00007872386,0.00085856667,0.0003745715,0.0010928262,0.03658912,0.00006260488,0.00059742527,0.021577748],"study_design_scores_gemma":[0.00001470082,0.00048235472,0.9868015,0.000009307021,0.00003253542,0.0015070634,0.00012980812,0.0068676416,0.003714574,0.0000819391,0.0003481145,0.000010593008],"about_ca_topic_score_codex":0.00514327,"about_ca_topic_score_gemma":0.006253334,"teacher_disagreement_score":0.00514327,"about_ca_system_score_codex":0.00014495524,"about_ca_system_score_gemma":0.00014571202,"threshold_uncertainty_score":0.010226667},"labels":[],"label_agreement":null},{"id":"W2981767205","doi":"10.1016/j.nicl.2019.102033","title":"Premature white matter aging in patients with right mesial temporal lobe epilepsy: A machine learning approach based on diffusion MRI data","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ministry of Science and Technology, Taiwan","keywords":"White matter; Epilepsy; Mesial temporal lobe epilepsy; Diffusion MRI; Temporal lobe; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Radiology","score_opus":0.048352604006440265,"score_gpt":0.35092793752135176,"score_spread":0.3025753335149115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981767205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.926944,0.0008217638,0.07065529,0.00034921998,0.000023002272,0.00006731111,0.00048776614,0.00019889833,0.00045284527],"genre_scores_gemma":[0.9836023,0.00024035585,0.01546496,0.000022474318,0.000018667453,0.000032807704,0.00039389305,0.0000066429143,0.00021786171],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998,0.000058339505,0.00002524488,0.00007590423,0.00002111402,0.000019387864],"domain_scores_gemma":[0.9994006,0.00034048414,0.00009816923,0.000046536574,0.00007414571,0.000040095772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010232872,0.0004518539,0.0005418367,0.0013282577,0.00019690396,0.0005360372,0.00029214472,0.00048420753,0.00028727556],"category_scores_gemma":[0.0020452372,0.0001527746,0.00061022234,0.0005287885,0.00017013079,0.00044262377,0.0003104462,0.0005217305,0.00012353361],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013922362,0.00047755952,0.4872162,0.00019768736,0.0006142263,0.0012895976,0.0005519842,0.25888136,0.015484711,0.001409084,0.0013023623,0.23118307],"study_design_scores_gemma":[0.000015537862,0.000119206285,0.04376444,0.000016674065,0.00005835727,0.0002485624,0.00007155737,0.95248795,0.0016300258,0.001217315,0.00034724388,0.000023168774],"about_ca_topic_score_codex":0.005376808,"about_ca_topic_score_gemma":0.0047535147,"teacher_disagreement_score":0.005376808,"about_ca_system_score_codex":0.00033182136,"about_ca_system_score_gemma":0.00033494944,"threshold_uncertainty_score":0.010691047},"labels":[],"label_agreement":null},{"id":"W2982063848","doi":"10.1503/jpn.180243","title":"Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder","year":2019,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Superior longitudinal fasciculus; Major depressive disorder; Fractional anisotropy; White matter; Corpus callosum; Psychology; Cardiology; Internal medicine; Medicine; Psychiatry; Magnetic resonance imaging; Neuroscience; Radiology; Cognition","score_opus":0.027936833045804157,"score_gpt":0.3461763405610605,"score_spread":0.31823950751525637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982063848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99952173,0.00018527442,0.000021306181,0.00009679512,0.0000050475946,0.000008470182,0.000078610174,0.000001075902,0.00008167906],"genre_scores_gemma":[0.9993818,0.00013995149,0.00006104543,0.00006379381,0.000008596499,0.000011073856,0.00019502481,8.6734e-7,0.00013792176],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981195,0.000053256157,0.000017428689,0.000041305608,0.000028363896,0.000047786198],"domain_scores_gemma":[0.9990759,0.000053724638,0.00045084016,0.00005721211,0.00011455814,0.00024773955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089240127,0.0001980735,0.00032881147,0.00037273983,0.0007650137,0.000739826,0.00031668105,0.0007964779,0.00060177024],"category_scores_gemma":[0.0016867002,0.00032526586,0.00043162736,0.0004199787,0.00027165067,0.0006940554,0.00036844998,0.0007679841,0.00020127228],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007538965,0.0004870012,0.9937669,0.000019455514,0.00008512905,0.00028520226,0.0006391868,0.000029002842,0.0008356771,0.00002352867,0.00027810523,0.002796774],"study_design_scores_gemma":[0.000014961391,0.00029657205,0.99902034,0.000007047735,0.000019109466,0.00013041314,0.00030580247,0.00005140686,0.000026348538,0.000014377009,0.00010977323,0.000003827174],"about_ca_topic_score_codex":0.009580171,"about_ca_topic_score_gemma":0.013288216,"teacher_disagreement_score":0.009580171,"about_ca_system_score_codex":0.00048692472,"about_ca_system_score_gemma":0.00053786434,"threshold_uncertainty_score":0.01904881},"labels":[],"label_agreement":null},{"id":"W2982389559","doi":"10.1101/824706","title":"Harmonization of diffusion MRI datasets with adaptive dictionary learning","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Engineering and Physical Sciences Research Council; Wolfson Foundation; Cardiff University; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Scanner; Pooling; Computer science; Artificial intelligence; Pattern recognition (psychology); Harmonization; Matching (statistics); Image registration; Diffusion MRI; Population; Data mining; Computer vision; Magnetic resonance imaging; Statistics; Mathematics; Image (mathematics); Radiology","score_opus":0.02812963206835971,"score_gpt":0.26737774111580564,"score_spread":0.23924810904744592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982389559","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1005595,0.00024809997,0.89648217,0.00018752104,0.00007717405,0.00018115946,0.0003185229,0.0012467608,0.0006991007],"genre_scores_gemma":[0.50587523,0.00018531305,0.4893385,0.00016046503,0.00006700907,0.0003071728,0.002196972,0.0003128024,0.001556607],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847084,0.00066911936,0.00012405682,0.00038656875,0.0002506495,0.000098711665],"domain_scores_gemma":[0.9971323,0.0010980521,0.00028314235,0.00089142326,0.0005221505,0.0000728542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033619697,0.0006847493,0.0009673117,0.0012389614,0.0003292208,0.0008783751,0.0010282457,0.0007463813,0.0010315867],"category_scores_gemma":[0.007674349,0.00031560325,0.0008927814,0.0011642843,0.00066310586,0.0009015876,0.0016744982,0.0009066499,0.0004844714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011126737,0.000461102,0.005285091,0.00030822842,0.0005273423,0.00021106028,0.00031003516,0.39002934,0.047659386,0.006838856,0.0062938263,0.540963],"study_design_scores_gemma":[0.00005994965,0.00020121824,0.0022106876,0.000014930306,0.00004766434,0.00011854544,0.0000627835,0.972361,0.01818143,0.004564719,0.0021477109,0.000029395464],"about_ca_topic_score_codex":0.0017953705,"about_ca_topic_score_gemma":0.001579085,"teacher_disagreement_score":0.0033619697,"about_ca_system_score_codex":0.0003396651,"about_ca_system_score_gemma":0.00073406834,"threshold_uncertainty_score":0.017780006},"labels":[],"label_agreement":null},{"id":"W2982576266","doi":"10.1016/j.mri.2019.09.012","title":"Inherent spatial structure in myelin water fraction maps","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Purdue Policy Research Institute, Purdue University; Vancouver Coastal Health Research Institute; Genzyme; Roche; University of British Columbia; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Voxel; Spatial distribution; Fiber bundle; Mathematics; Anisotropy; Anatomy; Bundle; Physics; Biology; Optics; Medicine; Materials science; Statistics; Magnetic resonance imaging; Radiology","score_opus":0.017132514992752538,"score_gpt":0.29561739947951193,"score_spread":0.2784848844867594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982576266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53594214,0.00093143515,0.4562496,0.00035396643,0.00003246532,0.0000376353,0.00037108417,0.00036312256,0.005718626],"genre_scores_gemma":[0.9431896,0.0006275819,0.053832468,0.000040902407,0.000046572615,0.000020629805,0.00023435641,0.00011522611,0.0018926644],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998847,0.000026477202,0.0000059542494,0.00002551346,0.000043673055,0.000013683395],"domain_scores_gemma":[0.9989538,0.0005495419,0.00016113326,0.00013195208,0.00014996929,0.000053580192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055863836,0.00025757874,0.00013822614,0.0009171518,0.00025419978,0.00086096924,0.00031955345,0.00038148224,0.0009472521],"category_scores_gemma":[0.0042007375,0.00027911246,0.00013276882,0.0006832285,0.000518938,0.0013125495,0.0007029551,0.00039270855,0.00020689123],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086674007,0.00011614972,0.03251708,0.00068817387,0.00020569091,0.00341518,0.0013529841,0.080980174,0.4904937,0.14513156,0.0027985398,0.24143404],"study_design_scores_gemma":[0.00005315799,0.00025446067,0.061401367,0.00009211922,0.00020012715,0.010202602,0.00055520044,0.4850918,0.21188371,0.22089761,0.009267923,0.000100010875],"about_ca_topic_score_codex":0.000616571,"about_ca_topic_score_gemma":0.0009489486,"teacher_disagreement_score":0.0009472521,"about_ca_system_score_codex":0.00017677378,"about_ca_system_score_gemma":0.0003383808,"threshold_uncertainty_score":0.0031689405},"labels":[],"label_agreement":null},{"id":"W2982698399","doi":"10.1038/s41582-019-0270-5","title":"Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging","year":2019,"lang":"en","type":"review","venue":"Nature Reviews Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":229,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; University of Toronto","funders":"","keywords":"Medicine; Spinal cord; Myelopathy; Spinal cord injury; Neuroimaging; Pathological; White matter; Neuroscience; Grey matter; Pathophysiology; Central nervous system disease; Pathology; Magnetic resonance imaging; Radiology; Surgery; Psychology","score_opus":0.18370922188088395,"score_gpt":0.46205088929619076,"score_spread":0.2783416674153068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982698399","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003920104,0.9991035,0.000066500885,0.00018069334,0.00013545483,0.0000018055313,0.000009940333,0.000004288605,0.0004586643],"genre_scores_gemma":[0.00025688214,0.99904805,0.000104950035,0.00015614991,0.0002474087,0.0000019958625,0.000014484561,8.8399634e-7,0.00016906824],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997341,0.000037870785,0.000051585517,0.000046117468,0.00010354249,0.00002668764],"domain_scores_gemma":[0.999201,0.00044082012,0.00010576676,0.000026377038,0.00017786877,0.000048236336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007966855,0.0012275857,0.0018997832,0.0036392754,0.00028674444,0.0017130752,0.0011655982,0.0015383177,0.0027840436],"category_scores_gemma":[0.0016635853,0.00033649246,0.00058178185,0.0034618618,0.0010268497,0.0024495241,0.0010056865,0.0018422041,0.0018010408],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006612509,0.00004016328,0.00026126433,0.019108342,0.00009497301,0.0003840615,0.00005452795,0.00031013245,0.0011267503,0.0036195954,0.034019843,0.9409142],"study_design_scores_gemma":[0.000021547838,0.00007601559,0.001660699,0.011371916,0.00024494343,0.0042195297,0.00014933616,0.00015736053,0.0003434866,0.006526594,0.97518605,0.00004247926],"about_ca_topic_score_codex":0.001648855,"about_ca_topic_score_gemma":0.003279292,"teacher_disagreement_score":0.0036392754,"about_ca_system_score_codex":0.0007354239,"about_ca_system_score_gemma":0.0019588629,"threshold_uncertainty_score":0.009313524},"labels":[],"label_agreement":null},{"id":"W2983379126","doi":"10.1101/833095","title":"Assessing white matter pathway reproducibility from human whole-brain tractography clustering","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Compute Canada","keywords":"Human Connectome Project; Tractography; Connectome; Diffusion MRI; Cluster analysis; White matter; Human brain; Intraclass correlation; Computer science; Identification (biology); Artificial intelligence; Pattern recognition (psychology); Fractional anisotropy; Reproducibility; Cartography; Neuroscience; Biology; Magnetic resonance imaging; Mathematics; Statistics; Medicine; Geography; Functional connectivity; Radiology","score_opus":0.054635329108588065,"score_gpt":0.31618647453421356,"score_spread":0.2615511454256255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983379126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82784694,0.00066661637,0.16480076,0.00009790953,0.00005281692,0.00014466654,0.00333733,0.0018446004,0.0012084455],"genre_scores_gemma":[0.9507549,0.00011062656,0.043585178,0.000025461537,0.000020279756,0.00015370846,0.004439244,0.00052135356,0.00038934982],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9951297,0.0017939829,0.00050919375,0.0014946358,0.0009390485,0.00013342618],"domain_scores_gemma":[0.97281194,0.011463229,0.0037137887,0.0068165427,0.0047964114,0.0003980415],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.010599349,0.00066365715,0.00071043306,0.0030591788,0.00081138645,0.0012878291,0.00071102707,0.0009395347,0.001143845],"category_scores_gemma":[0.033819627,0.00039431392,0.0007338784,0.0023092139,0.0010377686,0.0007077907,0.0012730969,0.00048640883,0.00056775595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004932462,0.00047906145,0.41446233,0.0017122603,0.005793908,0.0007875533,0.0031049368,0.17960462,0.16143216,0.0042114127,0.008865385,0.21461394],"study_design_scores_gemma":[0.00013275957,0.0008955552,0.5761655,0.00016683573,0.00070173544,0.002073705,0.00046993955,0.33745995,0.06966676,0.0073016207,0.0047274227,0.00023831338],"about_ca_topic_score_codex":0.0039522336,"about_ca_topic_score_gemma":0.003935482,"teacher_disagreement_score":0.9894006,"about_ca_system_score_codex":0.00043874828,"about_ca_system_score_gemma":0.0007583112,"threshold_uncertainty_score":0.056055367},"labels":[],"label_agreement":null},{"id":"W2983420661","doi":"10.1016/j.compbiomed.2019.103528","title":"Synthesizing diffusion tensor imaging from functional MRI using fully convolutional networks","year":2019,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Institute for Information and Communications Technology Promotion; Institute for Basic Science; National Research Foundation of Korea; Korea Institute for Advancement of Technology; Ministry of Science, ICT and Future Planning; Ministry of Trade, Industry and Energy","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Diffusion; Convolutional neural network; Artificial intelligence; Magnetic resonance imaging; Nuclear magnetic resonance; Pattern recognition (psychology); Physics; Mathematics; Radiology; Medicine; Geometry","score_opus":0.04606733961215789,"score_gpt":0.3430287233218202,"score_spread":0.2969613837096623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983420661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008120486,0.00043868754,0.9883485,0.0002621932,0.000102714934,0.000027082058,0.00034430355,0.0016903407,0.00066570734],"genre_scores_gemma":[0.2277515,0.0015594963,0.7615612,0.00025215096,0.0002001565,0.00011835526,0.0020806822,0.0006678574,0.0058086165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985373,0.000021784776,0.000010129442,0.00004440616,0.00004998779,0.000019988316],"domain_scores_gemma":[0.99932456,0.0003419603,0.00007753927,0.00009517113,0.00012627477,0.000034482575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005005341,0.0013369541,0.00072789605,0.00092014135,0.00024423303,0.0008571922,0.0010517195,0.0012521095,0.0020864299],"category_scores_gemma":[0.0025673467,0.0009813551,0.0012491412,0.0008836754,0.00039689592,0.001001625,0.00076484063,0.0019249328,0.0015029967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020299923,0.00008660102,0.0008925589,0.00034399956,0.00020158186,0.00033129627,0.000072831055,0.5089823,0.060147204,0.0111751575,0.008601687,0.40896168],"study_design_scores_gemma":[0.000004741977,0.00001967295,0.00016107092,0.000010998731,0.000021060516,0.0000699471,0.0000057916527,0.9841076,0.008230669,0.0055957926,0.0017599791,0.000012680644],"about_ca_topic_score_codex":0.011494747,"about_ca_topic_score_gemma":0.02060803,"teacher_disagreement_score":0.011494747,"about_ca_system_score_codex":0.0005684502,"about_ca_system_score_gemma":0.0013428951,"threshold_uncertainty_score":0.022855699},"labels":[],"label_agreement":null},{"id":"W2983699868","doi":"10.1007/s00429-019-01973-y","title":"Brain structure and internalizing and externalizing behavior in typically developing children and adolescents","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute","keywords":"White matter; Cingulum (brain); Fractional anisotropy; Uncinate fasciculus; Psychology; Diffusion MRI; Limbic system; Prefrontal cortex; Clinical psychology; Neuroscience; Developmental psychology; Medicine; Cognition; Central nervous system; Magnetic resonance imaging","score_opus":0.016695107895879746,"score_gpt":0.29450722829315745,"score_spread":0.2778121203972777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983699868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993137,0.00027541193,0.000043521006,0.000015449732,0.0000014211115,0.0000027034087,0.000048842467,0.000002204155,0.00029678707],"genre_scores_gemma":[0.99927396,0.00033665958,0.00013467102,0.0000104163955,0.0000023697187,0.000005856407,0.00008407012,0.0000018156027,0.0001501851],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999905,0.00001879995,0.000008807889,0.00002223911,0.000020443345,0.000024685121],"domain_scores_gemma":[0.9997578,0.00006208216,0.00009670227,0.000009157127,0.000032249172,0.000041942683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022389553,0.00030290958,0.00023047948,0.0010691329,0.00028667858,0.0004521426,0.00022543785,0.00025204275,0.00074548606],"category_scores_gemma":[0.000959933,0.00021435814,0.0001928105,0.00054699235,0.00055414834,0.00034618677,0.0003384255,0.0003783855,0.000065875574],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011712605,0.00009978675,0.9826614,0.00003899307,0.00007874525,0.0011800862,0.0010038785,0.00017631888,0.004825386,0.00024368207,0.00013594079,0.009438606],"study_design_scores_gemma":[0.0000013629067,0.000031179294,0.9986438,0.0000048476254,0.000013162354,0.0005304604,0.00039420676,0.000058297825,0.00021993565,0.000046532525,0.000055168483,0.0000011879006],"about_ca_topic_score_codex":0.016960217,"about_ca_topic_score_gemma":0.028169118,"teacher_disagreement_score":0.016960217,"about_ca_system_score_codex":0.00050967897,"about_ca_system_score_gemma":0.00038825406,"threshold_uncertainty_score":0.033722997},"labels":[],"label_agreement":null},{"id":"W2983754438","doi":"10.1093/geroni/igz038.1343","title":"POOR SLEEP QUALITY IS RELATED TO DECREASED WHITE MATTER INTEGRITY IN BRAIN NOCICEPTIVE PATHWAYS IN OLDER ADULTS","year":2019,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fractional anisotropy; White matter; Insula; Precuneus; Medicine; Bonferroni correction; Diffusion MRI; Audiology; Psychology; Neuroscience; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.04339950372748718,"score_gpt":0.36636418589470415,"score_spread":0.32296468216721697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983754438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989374,0.00041495002,0.00013408152,0.000025913017,0.0000030410636,0.000008026727,0.0002512835,0.0000029772002,0.00022217137],"genre_scores_gemma":[0.99941194,0.000099642246,0.00010862798,0.000021234046,0.000005324873,0.000006273935,0.00019502848,0.0000012467176,0.00015057572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999068,0.000016110193,0.00001812199,0.000024602274,0.000017693941,0.000016791762],"domain_scores_gemma":[0.99924016,0.00007291309,0.00046635655,0.000042424504,0.000109195586,0.00006892004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028301263,0.00023170828,0.00021751788,0.0005378748,0.0002656375,0.00036223352,0.00015733782,0.0002787638,0.0018226772],"category_scores_gemma":[0.0011202012,0.00015640055,0.00020970487,0.00039366056,0.00018867635,0.0002367095,0.00027029277,0.00022258946,0.0001289872],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004974515,0.000047783244,0.98824966,0.000062008665,0.00020496816,0.000120896286,0.00019661504,0.00007421261,0.006899376,0.000016240385,0.000098250304,0.0035325023],"study_design_scores_gemma":[0.0000017917761,0.000035404722,0.99974686,0.0000027938145,0.000010180964,0.000046055913,0.000035923254,0.00003413298,0.0000569362,0.000009458242,0.000019856745,5.9110175e-7],"about_ca_topic_score_codex":0.008249253,"about_ca_topic_score_gemma":0.016171139,"teacher_disagreement_score":0.008249253,"about_ca_system_score_codex":0.00014126001,"about_ca_system_score_gemma":0.0001241864,"threshold_uncertainty_score":0.016402483},"labels":[],"label_agreement":null},{"id":"W2984354293","doi":"10.1016/j.schres.2019.10.034","title":"Topographic diversity of structural connectivity in schizophrenia","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Higher Education Discipline Innovation Project; Taipei Veterans General Hospital; Janssen Canada; National Key Research and Development Program of China; Canadian Institutes of Health Research; Academia Sinica; Natural Science Foundation of Shanghai; National Natural Science Foundation of China; Health Research Foundation; National Health Research Institutes; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Diversity (politics); Geography; Economic geography; Psychology; Psychiatry; Sociology; Anthropology","score_opus":0.11330511247548293,"score_gpt":0.4080466097785989,"score_spread":0.294741497303116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984354293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958118,0.00047648198,0.0020838797,0.000120604265,0.0000032145283,0.0000038914973,0.00018875228,0.000013981423,0.0012975384],"genre_scores_gemma":[0.999134,0.00018801629,0.0004598181,0.00000726607,0.000009459369,0.0000023194625,0.000071027665,0.0000033763886,0.0001247809],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999006,0.0000294777,0.0000075781923,0.00001949199,0.000025441215,0.000017410728],"domain_scores_gemma":[0.99948126,0.00022061964,0.00013466622,0.000056516637,0.00006825586,0.000038706974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029604937,0.000120139004,0.0001750789,0.0018477292,0.00023386473,0.00046606615,0.00015748176,0.0001309666,0.0011582176],"category_scores_gemma":[0.0014669305,0.00016732328,0.00012447436,0.0012604089,0.00042597635,0.0006404171,0.00043707874,0.00017091629,0.000078601275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001620127,0.00009205052,0.48748094,0.00026357014,0.0005055315,0.0020176165,0.0028057657,0.010696272,0.29227293,0.02208312,0.0014231625,0.17873895],"study_design_scores_gemma":[0.000014752454,0.000076599455,0.97480226,0.000012836617,0.000052229865,0.0019067532,0.0005260448,0.005147026,0.0031557349,0.013845248,0.0004445773,0.000015925685],"about_ca_topic_score_codex":0.0024914795,"about_ca_topic_score_gemma":0.0052184844,"teacher_disagreement_score":0.0024914795,"about_ca_system_score_codex":0.00019365342,"about_ca_system_score_gemma":0.0002414088,"threshold_uncertainty_score":0.004953921},"labels":[],"label_agreement":null},{"id":"W2984423921","doi":"10.1016/j.brs.2019.11.003","title":"Interhemispheric pathways in agenesis of the corpus callosum and Parkinson’s disease","year":2019,"lang":"en","type":"letter","venue":"Brain stimulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Toronto Western Hospital; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Transcranial magnetic stimulation; Neuroscience; Motor cortex; Inhibitory postsynaptic potential; Agenesis of the corpus callosum; Excitatory postsynaptic potential; Pyramidal tracts; Psychology; Cortex (anatomy); Primary motor cortex; Medicine; Stimulation","score_opus":0.058007788290823446,"score_gpt":0.30852700349884815,"score_spread":0.2505192152080247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984423921","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27572367,0.02007671,0.0039401366,0.62230086,0.017980967,0.00018041486,0.0002203367,0.00024110025,0.059335846],"genre_scores_gemma":[0.8529069,0.006296442,0.0023105321,0.07677644,0.049983956,0.000118780714,0.00007312914,0.000049508082,0.011484291],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.9996087,0.000114611365,0.000056423345,0.000055017834,0.0000778006,0.00008750227],"domain_scores_gemma":[0.99789256,0.0014945698,0.00014436818,0.00007595403,0.00013235265,0.00026009727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006707365,0.00064380496,0.00085175544,0.00091282633,0.0017357309,0.0010435937,0.00077569543,0.017797636,0.0018302813],"category_scores_gemma":[0.0051057297,0.0003895591,0.0006295794,0.0006110429,0.0025710282,0.0015166266,0.00063938793,0.007922696,0.00055593177],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057760364,0.00010091509,0.0061591286,0.00019239559,0.000049621034,0.9409795,0.00032415584,0.00042376915,0.0020813274,0.0041988348,0.03037048,0.0145422965],"study_design_scores_gemma":[0.00056405197,0.0003799355,0.014052843,0.00026855472,0.00009988306,0.89598763,0.0007818076,0.004312108,0.0023759843,0.026566189,0.054520093,0.000090911344],"about_ca_topic_score_codex":0.003343231,"about_ca_topic_score_gemma":0.007787471,"teacher_disagreement_score":0.017797636,"about_ca_system_score_codex":0.0022067986,"about_ca_system_score_gemma":0.0010694722,"threshold_uncertainty_score":0.016011536},"labels":[],"label_agreement":null},{"id":"W2984928487","doi":"10.1016/j.nic.2019.09.007","title":"Neuroimaging in Schizophrenia","year":2019,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"H2020 Marie Skłodowska-Curie Actions; National Institute of Mental Health; Harvard Catalyst","keywords":"Neuroimaging; Schizophrenia (object-oriented programming); Neurochemical; Medicine; Neuroscience; Functional neuroimaging; Cognition; Psychiatry; Psychology; Internal medicine","score_opus":0.14971513642966588,"score_gpt":0.4372400620032872,"score_spread":0.2875249255736213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984928487","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003511788,0.99920744,0.000030317276,0.00016280691,0.00009992454,0.0000018727203,0.00000689261,0.000002564712,0.00045307633],"genre_scores_gemma":[0.00042488315,0.9988356,0.000084279476,0.00017910669,0.00023805909,0.000002999212,0.00001187743,6.246482e-7,0.00022258791],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999764,0.000063719446,0.000053297957,0.000035801055,0.00005790163,0.000025242745],"domain_scores_gemma":[0.9994186,0.00028204668,0.000119771335,0.000019500254,0.00010819891,0.000051918913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009204996,0.0013974314,0.001453734,0.0056688194,0.0003327394,0.0013834988,0.00065581256,0.0015808097,0.0037033306],"category_scores_gemma":[0.0016464344,0.00047617604,0.0005433705,0.003824251,0.00092340144,0.0017241266,0.0012826242,0.0016359166,0.0013408995],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090117945,0.00003870831,0.00029526174,0.019937508,0.0001064546,0.00039177833,0.00009563483,0.00030901993,0.0005189002,0.0037764928,0.03918271,0.9352573],"study_design_scores_gemma":[0.00006243671,0.00011627694,0.0025150708,0.022614418,0.00047095172,0.003966051,0.0001894392,0.00019071171,0.00029900364,0.0058548492,0.96366936,0.000051445462],"about_ca_topic_score_codex":0.005945723,"about_ca_topic_score_gemma":0.014258224,"teacher_disagreement_score":0.005945723,"about_ca_system_score_codex":0.0013691793,"about_ca_system_score_gemma":0.0035278746,"threshold_uncertainty_score":0.012388885},"labels":[],"label_agreement":null},{"id":"W2985279176","doi":"10.1016/j.cmpb.2019.105200","title":"Novel atlas of fiber directions built from ex-vivo diffusion tensor images of porcine hearts","year":2019,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Diffusion MRI; Atlas (anatomy); Ex vivo; Fractional anisotropy; Computer science; Artificial intelligence; Computer vision; Pattern recognition (psychology); Biomedical engineering; Anatomy; Medicine; In vivo; Biology; Magnetic resonance imaging; Radiology","score_opus":0.09102182885112914,"score_gpt":0.4095629576410048,"score_spread":0.31854112878987567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985279176","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056883696,0.00052628963,0.9359354,0.00023595584,0.000098375014,0.00010659337,0.0015771819,0.0018729463,0.002763592],"genre_scores_gemma":[0.2787375,0.0017845196,0.7107681,0.0001248309,0.000078011384,0.0002142646,0.0028682807,0.000615937,0.0048085125],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991786,0.000012069726,0.000006745265,0.000026218537,0.000024938246,0.000012179991],"domain_scores_gemma":[0.9997992,0.00003982991,0.00003580976,0.000053345397,0.000048070207,0.000023871717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037119235,0.0006163298,0.00026607548,0.001018778,0.00032946383,0.0012267727,0.0005216226,0.0009416411,0.002008403],"category_scores_gemma":[0.00049930345,0.00041680134,0.0004350987,0.00089912344,0.0003051775,0.0005302262,0.00056056783,0.00086173124,0.00077477243],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006466588,0.00019618917,0.010042911,0.00094089063,0.00020586877,0.002074205,0.0006503287,0.1412274,0.41555205,0.021234067,0.017482191,0.38974726],"study_design_scores_gemma":[0.00008155782,0.000278828,0.023832545,0.00023043161,0.00016878363,0.00648583,0.00021688231,0.71696603,0.18444137,0.018936874,0.04816306,0.00019773383],"about_ca_topic_score_codex":0.0030970338,"about_ca_topic_score_gemma":0.0062376815,"teacher_disagreement_score":0.0030970338,"about_ca_system_score_codex":0.0002968733,"about_ca_system_score_gemma":0.0014019168,"threshold_uncertainty_score":0.0067188144},"labels":[],"label_agreement":null},{"id":"W2985804183","doi":"10.1038/s41467-019-12867-2","title":"Author Correction: The challenge of mapping the human connectome based on diffusion tractography","year":2019,"lang":"en","type":"erratum","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MaRS; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Wellcome Trust","keywords":"Connectome; Tractography; Diffusion MRI; Computer science; Human Connectome Project; Diffusion; Connectomics; Neuroscience; Data science; Functional connectivity; Biology; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.10895082961789886,"score_gpt":0.3856030417001582,"score_spread":0.2766522120822593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985804183","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001100812,0.00065796304,0.0010819327,0.053859517,0.9414417,0.000015904336,0.000592443,0.00034995514,0.0018904598],"genre_scores_gemma":[0.01821748,0.008413592,0.012244017,0.14540453,0.5584265,0.0003063745,0.0023451736,0.002723095,0.25191927],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99293715,0.0011580496,0.0012625258,0.0011397629,0.0030855797,0.00041690798],"domain_scores_gemma":[0.93539673,0.019252589,0.0029223925,0.0044450257,0.035758752,0.0022245604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063466686,0.002087993,0.0016885558,0.004476397,0.0040982277,0.0045648003,0.003799762,0.008276437,0.04042923],"category_scores_gemma":[0.11352437,0.0010287714,0.0016315302,0.0027551334,0.0034270186,0.0028182515,0.0024304537,0.015196082,0.031146528],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017142986,0.0000025366674,0.000037157934,0.00006749255,0.000007304066,0.00018317321,0.000034937388,0.000028034106,0.000037612328,0.00090141885,0.9947225,0.003960783],"study_design_scores_gemma":[0.00003450823,0.000015306949,0.000368675,0.00041126474,0.000037760004,0.00088171475,0.0001126666,0.00029341062,0.00040142413,0.0041536265,0.9932446,0.000044948705],"about_ca_topic_score_codex":0.014965407,"about_ca_topic_score_gemma":0.020643156,"teacher_disagreement_score":0.04042923,"about_ca_system_score_codex":0.0036401197,"about_ca_system_score_gemma":0.0070899096,"threshold_uncertainty_score":0.13524926},"labels":[],"label_agreement":null},{"id":"W2986314683","doi":"10.1016/j.neuroimage.2019.116345","title":"Effects of unilateral cortical resection of the visual cortex on bilateral human white matter","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Eye Institute; National Institutes of Health","keywords":"White matter; Resection; Psychology; Visual cortex; Inferior longitudinal fasciculus; Cortex (anatomy); Neuroscience; Tractography; Anatomy; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.02010873190519451,"score_gpt":0.3333295160145337,"score_spread":0.3132207841093392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986314683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976283,0.000025779618,0.00009624274,0.000004530973,8.135511e-7,0.0000028593008,0.000014951834,0.0000051529496,0.000086795466],"genre_scores_gemma":[0.9997458,0.000032721502,0.00013263879,0.000003824683,0.0000010867142,0.000004085352,0.000032569482,0.0000035305773,0.00004376279],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998652,0.00002492098,0.00001199445,0.000043369466,0.000021469381,0.000032992302],"domain_scores_gemma":[0.99961203,0.00016182497,0.00012621476,0.000039296174,0.000013319732,0.000047389112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013436055,0.00032222632,0.0001814887,0.00029034377,0.0001441096,0.0000995589,0.00008598704,0.00011257849,0.0010019118],"category_scores_gemma":[0.00066870585,0.00012568675,0.00016545024,0.00013733552,0.00068174227,0.00014320413,0.00026897682,0.00016073191,0.000059017948],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006189018,0.0006746223,0.17684586,0.00021191644,0.00038141033,0.0074726143,0.0007672643,0.0026679845,0.7622056,0.0004256484,0.00026260098,0.041895434],"study_design_scores_gemma":[0.000096240154,0.004369291,0.9251744,0.000010368334,0.00012509324,0.0067534447,0.00036720154,0.0014867386,0.061051212,0.000223665,0.00032694466,0.000015473515],"about_ca_topic_score_codex":0.002201266,"about_ca_topic_score_gemma":0.0050886455,"teacher_disagreement_score":0.002201266,"about_ca_system_score_codex":0.00022896947,"about_ca_system_score_gemma":0.00017660094,"threshold_uncertainty_score":0.0043768883},"labels":[],"label_agreement":null},{"id":"W2986892424","doi":"10.7554/elife.44056.011","title":"Author response: Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age","year":2019,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"","keywords":"Psychology; Alcohol Use Disorders Identification Test; Voxel; Structural equation modeling; Novelty; Alcohol consumption; Artificial intelligence; Developmental psychology; Computer science; Machine learning; Social psychology; Alcohol","score_opus":0.08138228622988378,"score_gpt":0.3876331510564533,"score_spread":0.3062508648265695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986892424","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023069058,0.0042057997,0.0011906686,0.85686624,0.07553341,0.00034204926,0.022257514,0.00074719015,0.01578812],"genre_scores_gemma":[0.14114359,0.006170001,0.0029281646,0.74149054,0.038971685,0.0026356636,0.0076797674,0.00043608082,0.058544535],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99875116,0.00055670645,0.00016618813,0.000192293,0.00023622395,0.00009735906],"domain_scores_gemma":[0.9794743,0.010932859,0.0009385146,0.0004819003,0.0067799916,0.0013923644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027753199,0.0005821022,0.00081287575,0.0006907765,0.00085078453,0.0009567031,0.0010286665,0.0061321342,0.053890456],"category_scores_gemma":[0.06554722,0.0003525818,0.0010233686,0.00052988034,0.00061347627,0.0011630063,0.0011671559,0.0034813394,0.01473881],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027911575,0.00003277989,0.011918477,0.00041848564,0.0000652714,0.00011867047,0.00016338663,0.000065880646,0.00005500105,0.00015910712,0.9731082,0.013615684],"study_design_scores_gemma":[0.0021656356,0.001307781,0.18692125,0.0075292373,0.00074488396,0.002868536,0.009549029,0.0019320536,0.0014896664,0.007352379,0.7775829,0.0005567162],"about_ca_topic_score_codex":0.005045232,"about_ca_topic_score_gemma":0.0068000983,"teacher_disagreement_score":0.053890456,"about_ca_system_score_codex":0.000860817,"about_ca_system_score_gemma":0.0015431341,"threshold_uncertainty_score":0.18028152},"labels":[],"label_agreement":null},{"id":"W2988205449","doi":"10.7554/elife.50482.024","title":"Author response: Shifts in myeloarchitecture characterise adolescent development of cortical gradients","year":2019,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroscience; Biology; Evolutionary biology; Computational biology; Cognitive science; Psychology","score_opus":0.11240874232942236,"score_gpt":0.4142457435658354,"score_spread":0.301837001236413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988205449","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009056088,0.003639433,0.0018330053,0.8665713,0.08719517,0.00011009155,0.0015403967,0.00023249238,0.029822027],"genre_scores_gemma":[0.22900438,0.012433125,0.004039367,0.39523304,0.07619723,0.00044505668,0.0016784631,0.00060563185,0.28036377],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99850535,0.00047543293,0.00015051506,0.00017682282,0.00051227707,0.00017956234],"domain_scores_gemma":[0.98159033,0.0065498063,0.0013367748,0.0006596029,0.00862067,0.0012427381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002186164,0.00026849515,0.00035883597,0.00060781115,0.0006297772,0.0010373786,0.000635524,0.0042545586,0.044784423],"category_scores_gemma":[0.04361337,0.00017731737,0.00028478474,0.00035357845,0.0010276673,0.0007761314,0.0009031145,0.0035673433,0.0108430665],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019146006,0.00001640564,0.0033124534,0.0003437604,0.00002252901,0.0023049354,0.0005535341,0.00009719607,0.00066874904,0.0023813155,0.9614685,0.028639236],"study_design_scores_gemma":[0.00006765951,0.000098823744,0.01015338,0.00078018673,0.00002875976,0.0064846547,0.0024106181,0.00014073844,0.0015674123,0.0037552018,0.9744597,0.000052909654],"about_ca_topic_score_codex":0.0028342218,"about_ca_topic_score_gemma":0.0050721695,"teacher_disagreement_score":0.044784423,"about_ca_system_score_codex":0.0010278774,"about_ca_system_score_gemma":0.002120764,"threshold_uncertainty_score":0.14981884},"labels":[],"label_agreement":null},{"id":"W2988570450","doi":"10.1016/j.schres.2019.10.014","title":"Amygdala subnucleus volumes in psychosis high-risk state and first-episode psychosis","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Suomalainen Lääkäriseura Duodecim; Seventh Framework Programme; Orionin Tutkimussäätiö; Turun Yliopisto; Academy of Finland; Turun Yliopistollinen Keskussairaala; National Alliance for Research on Schizophrenia and Depression","keywords":"Psychosis; Amygdala; Schizophrenia (object-oriented programming); Psychology; Population; Basal ganglia; Nucleus; Psychiatry; Neuroscience; Medicine; Internal medicine; Central nervous system","score_opus":0.05799041123087315,"score_gpt":0.3859631769696918,"score_spread":0.3279727657388186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988570450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99921227,0.000117623495,0.000041959433,0.000021009479,0.0000018121452,0.0000018637622,0.00009075598,0.000002330256,0.0005104101],"genre_scores_gemma":[0.99975985,0.00003112377,0.00002222418,0.000004217442,0.0000017775639,0.0000014552313,0.00005063613,9.910177e-7,0.00012773907],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993765,0.000014805745,0.000004703818,0.000014505577,0.000012105631,0.00001624312],"domain_scores_gemma":[0.99964786,0.00008863705,0.00014873089,0.000021726539,0.00001868916,0.000074292395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000189841,0.00017633273,0.00024052474,0.00038753523,0.00030857595,0.00052191154,0.00018381735,0.00029779432,0.002436553],"category_scores_gemma":[0.00090208254,0.00019684988,0.00021787238,0.0002316142,0.00027760028,0.0004380241,0.00048188138,0.0003645103,0.00011879953],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020790282,0.00006251432,0.9813936,0.000044697168,0.00020208662,0.0006063735,0.0006809077,0.00040658854,0.008856998,0.0003034452,0.00018219871,0.0051816013],"study_design_scores_gemma":[0.0000035750218,0.00003863805,0.99892765,0.0000036379336,0.000013568276,0.00032652894,0.00017273717,0.00013935396,0.00018031057,0.00015242113,0.000038869737,0.0000027616538],"about_ca_topic_score_codex":0.005220079,"about_ca_topic_score_gemma":0.011985253,"teacher_disagreement_score":0.005220079,"about_ca_system_score_codex":0.00038906976,"about_ca_system_score_gemma":0.00026154864,"threshold_uncertainty_score":0.010379374},"labels":[],"label_agreement":null},{"id":"W2989104806","doi":"10.1016/j.neuron.2019.09.030","title":"Holographic Reconstruction of Axonal Pathways in the Human Brain","year":2019,"lang":"en","type":"article","venue":"Neuron","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":145,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Center for Complementary and Integrative Health; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Neuroscience; Holography; Human brain; Psychology; Biology; Physics; Optics","score_opus":0.06744416312274708,"score_gpt":0.3318688984028369,"score_spread":0.2644247352800898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989104806","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45013696,0.0039001047,0.5187566,0.0013992029,0.00011900734,0.00012152282,0.0011412569,0.000668273,0.023756988],"genre_scores_gemma":[0.8421033,0.00417365,0.14024566,0.00017104294,0.000054753706,0.000042584317,0.00028151117,0.00012782407,0.012799729],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999715,0.000007658353,0.0000018233585,0.000004056625,0.000011105283,0.0000039599713],"domain_scores_gemma":[0.99993956,0.000028107945,0.0000071485033,0.000011396661,0.000009161693,0.0000045502484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011100477,0.00017544904,0.00010376472,0.00046345562,0.00013509154,0.0005071469,0.0001732976,0.00033039958,0.0033943178],"category_scores_gemma":[0.0004276861,0.00018629254,0.000098260716,0.00054433465,0.00034514116,0.0004837257,0.00023472322,0.00042082646,0.0004131922],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011960914,0.00013067765,0.0067279027,0.0011188549,0.00009905611,0.003007359,0.0012621875,0.06776285,0.51409495,0.07375255,0.006772111,0.32407546],"study_design_scores_gemma":[0.00028315943,0.00047999897,0.045793008,0.00035216508,0.00014063188,0.026504269,0.0015966248,0.4318113,0.37669545,0.07411535,0.042083208,0.00014483997],"about_ca_topic_score_codex":0.0022098077,"about_ca_topic_score_gemma":0.0030433193,"teacher_disagreement_score":0.0033943178,"about_ca_system_score_codex":0.00016801746,"about_ca_system_score_gemma":0.0006118903,"threshold_uncertainty_score":0.011355102},"labels":[],"label_agreement":null},{"id":"W2989717595","doi":"10.1002/mrm.28083","title":"Diffusion dispersion imaging: Mapping oscillating gradient spin‐echo frequency dependence in the human brain","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dispersion (optics); Nuclear magnetic resonance; Diffusion; White matter; Spin echo; Diffusion MRI; Isotropy; Effective diffusion coefficient; Human brain; Materials science; Physics; Magnetic resonance imaging; Optics; Medicine; Radiology","score_opus":0.0410082662047876,"score_gpt":0.340301888024965,"score_spread":0.29929362182017744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989717595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68289685,0.009191698,0.3037571,0.0005873835,0.00008033884,0.00020459305,0.00026983808,0.00044446942,0.0025676992],"genre_scores_gemma":[0.8673364,0.0044432436,0.12601908,0.00013577146,0.00006824701,0.000116579125,0.00024687994,0.0000809531,0.0015528386],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999018,0.000026395259,0.0000064498277,0.000028029843,0.000029176934,0.000008131394],"domain_scores_gemma":[0.9998435,0.00006419381,0.000031184674,0.000012869937,0.000035306108,0.000012935743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000510059,0.0003916475,0.00020326469,0.0005676208,0.00015281918,0.00030923478,0.0002996309,0.0005499211,0.00065231055],"category_scores_gemma":[0.001289569,0.00018910464,0.00012621592,0.0002985132,0.000492544,0.0005338775,0.00029957094,0.00030547412,0.00014494653],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005161977,0.000068931266,0.0036594863,0.00049861957,0.00005651377,0.00031351435,0.00013165057,0.0029559988,0.89849854,0.0010333721,0.00046150008,0.09180567],"study_design_scores_gemma":[0.00017066044,0.0016506279,0.041708328,0.0001809076,0.00024370702,0.0061887596,0.00017053646,0.06842612,0.86812603,0.005306239,0.0077342354,0.00009388755],"about_ca_topic_score_codex":0.000989411,"about_ca_topic_score_gemma":0.0016542178,"teacher_disagreement_score":0.000989411,"about_ca_system_score_codex":0.00020656403,"about_ca_system_score_gemma":0.00036059693,"threshold_uncertainty_score":0.0026974678},"labels":[],"label_agreement":null},{"id":"W2990004766","doi":"10.1101/861880","title":"Use of multi-flip angle measurements to account for transmit inhomogeneity and non-Gaussian diffusion in DW-SSFP","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Steady-state free precession imaging; Flip angle; Diffusion; Gaussian; Diffusion MRI; Nuclear magnetic resonance; Computational physics; Physics; Statistical physics","score_opus":0.10267477529616657,"score_gpt":0.3162942403898048,"score_spread":0.21361946509363822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990004766","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3199459,0.0007627882,0.6772304,0.00028273553,0.00008677352,0.00013374396,0.00021432334,0.0007283002,0.00061499845],"genre_scores_gemma":[0.7034387,0.0003836542,0.29506502,0.000063838845,0.000021787977,0.00014736474,0.0002605866,0.00019082986,0.00042823382],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995963,0.00014394471,0.000045394845,0.00008968049,0.000095632604,0.00002896881],"domain_scores_gemma":[0.99877256,0.00034541826,0.000244694,0.0002602455,0.000308071,0.000069062036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028132629,0.000880602,0.00043095887,0.0005809621,0.00036955142,0.00085468596,0.00065020646,0.00073289644,0.000716571],"category_scores_gemma":[0.0041277576,0.00035502476,0.0004506589,0.00044242907,0.0004295953,0.00072111486,0.00069181377,0.000738081,0.00016374301],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042511887,0.000103194296,0.009651238,0.00039716842,0.00022276155,0.00037718675,0.00021340775,0.064126424,0.83333254,0.0022855573,0.0007792319,0.0880862],"study_design_scores_gemma":[0.00004630235,0.0004078088,0.031630516,0.00007452932,0.0002506361,0.00093043956,0.00010928366,0.53805804,0.41935644,0.003940479,0.0050621387,0.00013338211],"about_ca_topic_score_codex":0.0017149298,"about_ca_topic_score_gemma":0.0038623158,"teacher_disagreement_score":0.0028132629,"about_ca_system_score_codex":0.00034628267,"about_ca_system_score_gemma":0.000840516,"threshold_uncertainty_score":0.014878154},"labels":[],"label_agreement":null},{"id":"W2990322742","doi":"10.1101/859538","title":"Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute for Health and Care Research; National Institute of Neurological Disorders and Stroke; Canada First Research Excellence Fund; National Institutes of Health; Craig H. Neilsen Foundation; Natural Sciences and Engineering Research Council of Canada; Engineering and Physical Sciences Research Council; Institut de Valorisation des Données; European Commission; Multiple Sclerosis Society; Canadian Institutes of Health Research","keywords":"Noise reduction; Computer science; Parametric statistics; SIGNAL (programming language); Artificial intelligence; Noise (video); Principal component analysis; Diffusion MRI; Pattern recognition (psychology); Image quality; Algorithm; Mathematics; Magnetic resonance imaging; Image (mathematics); Medicine; Radiology","score_opus":0.06322021613638709,"score_gpt":0.33134311904228686,"score_spread":0.2681229029058998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990322742","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076135196,0.00032095684,0.9220623,0.0001152448,0.000024534202,0.00004498102,0.00014121864,0.00069145096,0.00046414076],"genre_scores_gemma":[0.40479085,0.00026628474,0.59343684,0.0000799175,0.00003363714,0.00018074934,0.0003546556,0.00025994872,0.000597192],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993548,0.00019354213,0.000048514863,0.00015340828,0.00019534605,0.000054386015],"domain_scores_gemma":[0.9989152,0.0003476751,0.00019476262,0.0002396252,0.00023842366,0.00006435459],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020064092,0.0010298368,0.0007898735,0.00079488603,0.00022385496,0.00090542575,0.00075392704,0.001087793,0.00079164584],"category_scores_gemma":[0.004123965,0.00048072985,0.00074519234,0.0010235562,0.00086463336,0.0010507876,0.0013546222,0.0010608212,0.000312894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052767736,0.00017129337,0.0020455385,0.00048232076,0.00027512896,0.00039487772,0.00026739706,0.15322627,0.7323289,0.0071884063,0.0009557714,0.102136455],"study_design_scores_gemma":[0.00002524879,0.0002651521,0.0037029376,0.00003565979,0.00009747621,0.00056623097,0.00003812985,0.79938966,0.18887354,0.004950232,0.0019667756,0.00008896318],"about_ca_topic_score_codex":0.0006391137,"about_ca_topic_score_gemma":0.00078005076,"teacher_disagreement_score":0.0020064092,"about_ca_system_score_codex":0.00031047195,"about_ca_system_score_gemma":0.0005129559,"threshold_uncertainty_score":0.010611057},"labels":[],"label_agreement":null},{"id":"W2990532819","doi":"10.1002/hipo.23177","title":"Curved multiplanar reformatting provides improved visualization of hippocampal anatomy","year":2019,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Hippocampal formation; Visualization; Anatomy; Coronal plane; Computer science; Neuroscience; Dentate gyrus; Biology; Artificial intelligence","score_opus":0.031107763402867576,"score_gpt":0.34284111682084806,"score_spread":0.3117333534179805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990532819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63442415,0.0044218698,0.3403957,0.0017769468,0.00015869734,0.00023583269,0.0011286719,0.003506497,0.0139516],"genre_scores_gemma":[0.7366076,0.0021576358,0.25409585,0.00040487727,0.00007176491,0.00006606919,0.00067899795,0.00078439317,0.005132873],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998054,0.00005850155,0.000025155325,0.00003611081,0.00005470028,0.000020207322],"domain_scores_gemma":[0.9991755,0.00029299053,0.00011817179,0.00014902341,0.00021927535,0.000044985532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008501626,0.0005612543,0.00019099702,0.001169615,0.00022362414,0.0007708009,0.00034233832,0.0007386858,0.008852767],"category_scores_gemma":[0.0020468798,0.0004779083,0.00022950867,0.0005391758,0.000543488,0.000932286,0.0004934274,0.00075879006,0.0016188826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042730125,0.000056020923,0.00305385,0.0005192525,0.000095397365,0.0015474461,0.00034090856,0.004330161,0.92403257,0.0012993686,0.0031750866,0.061122566],"study_design_scores_gemma":[0.0001945559,0.0012688192,0.092586294,0.00026756158,0.00036335696,0.025098825,0.00054695626,0.05072629,0.7753424,0.0040597534,0.04928779,0.00025734166],"about_ca_topic_score_codex":0.0013461655,"about_ca_topic_score_gemma":0.002421401,"teacher_disagreement_score":0.008852767,"about_ca_system_score_codex":0.00016350462,"about_ca_system_score_gemma":0.0004053724,"threshold_uncertainty_score":0.029615521},"labels":[],"label_agreement":null},{"id":"W2990740276","doi":"10.3389/fnana.2019.00096","title":"Internal Subdivisions of the Marmoset Claustrum Complex: Identification by Myeloarchitectural Features and High Field Strength Imaging","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"Claustrum; Marmoset; Identification (biology); Field (mathematics); Psychology; Neuroscience; Artificial intelligence; Computer science; Biology; Mathematics; Paleontology","score_opus":0.010110163181727572,"score_gpt":0.28268659783731115,"score_spread":0.27257643465558357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990740276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977984,0.00021999124,0.0013379313,0.0000067686883,9.125703e-7,0.0000080607315,0.00002718212,0.000010860884,0.0005898901],"genre_scores_gemma":[0.9972613,0.000120259836,0.002261489,0.0000066592734,0.0000016027772,0.0000102422555,0.000081801845,0.000004074795,0.00025264715],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994385,0.0000050954654,0.0000051068687,0.000017304941,0.000012827554,0.00001570234],"domain_scores_gemma":[0.99988294,0.000007862669,0.000047566293,0.000017225184,0.000018537256,0.000025808497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010767506,0.00020907397,0.00014753907,0.0008592379,0.00026144172,0.00037637335,0.00017918543,0.00022722507,0.0005545016],"category_scores_gemma":[0.00021815218,0.00017914067,0.00016665325,0.00023971473,0.0005502373,0.0003191817,0.0005003328,0.00020103944,0.000102475205],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017386359,0.0000154782,0.040027134,0.00007313395,0.000039131977,0.00047462422,0.00073307834,0.00022013659,0.9461243,0.0005260907,0.000026793252,0.011566133],"study_design_scores_gemma":[0.000012644989,0.00022451174,0.9350711,0.00002871775,0.00005712366,0.0027370488,0.00056653185,0.002068235,0.057713732,0.00056928996,0.0009336676,0.000017483464],"about_ca_topic_score_codex":0.0023595057,"about_ca_topic_score_gemma":0.0039698295,"teacher_disagreement_score":0.0023595057,"about_ca_system_score_codex":0.00017072036,"about_ca_system_score_gemma":0.00016196132,"threshold_uncertainty_score":0.004691541},"labels":[],"label_agreement":null},{"id":"W2990802750","doi":"10.1016/j.exger.2019.110792","title":"Tractography of the external capsule and cognition: A diffusion MRI study of cholinergic fibers","year":2019,"lang":"en","type":"article","venue":"Experimental Gerontology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; Cégep de l'Abitibi Témiscamingue; Centre intégré de santé et de services sociaux de Chaudière-Appalaches","funders":"","keywords":"Tractography; Cholinergic; Diffusion MRI; Cognition; Capsule; Internal capsule; Medicine; Neuroscience; External capsule; Magnetic resonance imaging; Anatomy; Psychology; Pathology; Biology; Radiology; Fractional anisotropy","score_opus":0.05096605843489169,"score_gpt":0.36334770724545473,"score_spread":0.3123816488105631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990802750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99677664,0.0008102085,0.001630797,0.00008492828,0.0000052821574,0.000023346323,0.00007883233,0.000007963112,0.00058194844],"genre_scores_gemma":[0.9959125,0.0009659707,0.0017943346,0.000023456225,0.000015796108,0.000030915246,0.00007376048,0.000008195835,0.0011750623],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999194,0.00001853942,0.0000054230727,0.000027840704,0.000012284674,0.000016521033],"domain_scores_gemma":[0.999762,0.00007137212,0.00006252645,0.000045136512,0.000020296871,0.000038611575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057974015,0.00043680385,0.00023477605,0.0006975257,0.0004665811,0.0004154785,0.00032784455,0.0005201825,0.0014377513],"category_scores_gemma":[0.0008152949,0.00020649847,0.00020489687,0.00052503234,0.0014361959,0.0006989986,0.0004042288,0.0004462284,0.0001497056],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012641711,0.0018386189,0.07962961,0.0006255541,0.0005307798,0.003908679,0.002620284,0.0014703397,0.82268023,0.004790715,0.0004187753,0.06884469],"study_design_scores_gemma":[0.0006619993,0.0045930506,0.8553533,0.00008317585,0.00045751393,0.008243835,0.0015749705,0.0056678886,0.11236695,0.00774156,0.0031634762,0.000092239796],"about_ca_topic_score_codex":0.0039050407,"about_ca_topic_score_gemma":0.004183473,"teacher_disagreement_score":0.0039050407,"about_ca_system_score_codex":0.00037068067,"about_ca_system_score_gemma":0.000646462,"threshold_uncertainty_score":0.007764578},"labels":[],"label_agreement":null},{"id":"W2991015307","doi":"10.1016/j.nicl.2019.102102","title":"Microstructural abnormalities in deep and superficial white matter in youths with mild traumatic brain injury","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Centre for Addiction and Mental Health; Hospital for Sick Children; Toronto Rehabilitation Institute; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Hospital for Sick Children","keywords":"White matter; Fractional anisotropy; Voxel; Diffusion MRI; Traumatic brain injury; Psychology; Audiology; Neuroscience; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.07875665709767951,"score_gpt":0.3932316182364547,"score_spread":0.31447496113877516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991015307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965656,0.000106296226,0.000051980274,0.00001193465,0.0000011680257,0.00000475937,0.00007141967,0.000004569971,0.0000913164],"genre_scores_gemma":[0.99962115,0.000077711324,0.00013353374,0.0000057874895,0.0000024188969,0.000005094258,0.0001028449,0.0000015953177,0.00004979984],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981266,0.000018547235,0.000030776708,0.000049123846,0.00005070994,0.000038278526],"domain_scores_gemma":[0.9992243,0.000053306845,0.00049248565,0.00003319377,0.00008188146,0.00011490968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004172973,0.00034562056,0.0002923863,0.0018007322,0.00045819295,0.00038321668,0.00018548217,0.00024258901,0.001057141],"category_scores_gemma":[0.0012570884,0.00021406669,0.00026132658,0.00066225074,0.00051974464,0.00030048942,0.0005752638,0.00023488577,0.000136629],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017658203,0.000028064607,0.9882796,0.00003620684,0.000039178063,0.0006601133,0.00078859297,0.000057968333,0.003910076,0.000039374034,0.000098964505,0.0058853747],"study_design_scores_gemma":[0.0000015771484,0.00005920802,0.9983779,0.0000062716235,0.00001158772,0.000944844,0.00025910992,0.000046305107,0.00022442428,0.000023011375,0.00004441218,0.0000013738563],"about_ca_topic_score_codex":0.0078771245,"about_ca_topic_score_gemma":0.013895033,"teacher_disagreement_score":0.0078771245,"about_ca_system_score_codex":0.00041631347,"about_ca_system_score_gemma":0.0003723932,"threshold_uncertainty_score":0.01566255},"labels":[],"label_agreement":null},{"id":"W2991457998","doi":"10.1101/852764","title":"Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Australian Government; National Imaging Facility; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Diffusion MRI; White matter; Neurite; Tractography; Neuroscience; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.01361255381374003,"score_gpt":0.25412181501823183,"score_spread":0.24050926120449181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991457998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99898857,0.00015651005,0.00019933909,0.000013258998,0.0000011535717,0.0000020533616,0.00027571278,0.0000067830147,0.00035658723],"genre_scores_gemma":[0.9988562,0.00017457544,0.0004257112,0.0000039223623,0.0000014260122,0.000005817944,0.000269597,0.000005439023,0.00025736023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981815,0.00002062989,0.000016241798,0.000053762655,0.00005025023,0.000040922987],"domain_scores_gemma":[0.9991429,0.00013850901,0.00041923544,0.000056943874,0.0001573594,0.00008507624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041144763,0.000207915,0.0001907275,0.0008222668,0.0002601651,0.00049966126,0.00014713712,0.00021564716,0.0013051169],"category_scores_gemma":[0.0013568824,0.00017818344,0.00014927995,0.00047713882,0.00029056004,0.00033392152,0.00029060576,0.00023924437,0.00017106856],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002895444,0.00004434607,0.9575666,0.00004286044,0.000053365566,0.0005105175,0.000772962,0.000316978,0.022648904,0.00016418104,0.00025472377,0.01733514],"study_design_scores_gemma":[5.4051105e-7,0.000014338559,0.9986268,0.0000039094457,0.0000038139917,0.00021701586,0.000107163265,0.00007048571,0.0008470067,0.000025704494,0.000081597536,0.000001647704],"about_ca_topic_score_codex":0.015306685,"about_ca_topic_score_gemma":0.0203248,"teacher_disagreement_score":0.015306685,"about_ca_system_score_codex":0.00041222948,"about_ca_system_score_gemma":0.00036785982,"threshold_uncertainty_score":0.030435145},"labels":[],"label_agreement":null},{"id":"W2991597154","doi":"10.1523/jneurosci.1650-18.2019","title":"Differences in Frontal Network Anatomy Across Primate Species","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; King's College London; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Primate; Anatomy; Biology; Evolutionary biology; Neuroscience","score_opus":0.11234750293543096,"score_gpt":0.3886606071373994,"score_spread":0.2763131042019685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991597154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881323,0.0011012959,0.005829946,0.00011184325,0.000010156341,0.000010280981,0.00038101774,0.00009132516,0.0043319324],"genre_scores_gemma":[0.9971867,0.00029549972,0.001881361,0.000020694377,0.0000059568947,0.000009341111,0.00023114853,0.000022379754,0.0003468321],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998636,0.000022243046,0.000007249185,0.00007067357,0.00002054779,0.000015697593],"domain_scores_gemma":[0.9997644,0.000051846804,0.000093052746,0.000043060998,0.00002754288,0.000020056588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001999511,0.00020503583,0.00016053357,0.0011273576,0.00042700573,0.00047375384,0.0001487576,0.0001887161,0.0027262205],"category_scores_gemma":[0.0007521191,0.00013110129,0.00019950834,0.00041483025,0.000573962,0.00043401401,0.00042924017,0.00015612386,0.00027661535],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047902376,0.000034812336,0.27992442,0.00032340642,0.00053732016,0.0007608454,0.0046447515,0.001813242,0.5935167,0.0051483996,0.00069184415,0.11212524],"study_design_scores_gemma":[0.000005067879,0.000054920438,0.98543465,0.000036312937,0.00004874301,0.0013944233,0.0005121558,0.0016759232,0.0060684117,0.0023860028,0.0023699184,0.000013435185],"about_ca_topic_score_codex":0.0041760486,"about_ca_topic_score_gemma":0.007697923,"teacher_disagreement_score":0.0041760486,"about_ca_system_score_codex":0.0002771322,"about_ca_system_score_gemma":0.00017685877,"threshold_uncertainty_score":0.009120166},"labels":[],"label_agreement":null},{"id":"W2994619082","doi":"10.1002/brb3.1514","title":"Diffusion tensor imaging tractography reveals altered fornix in all diagnostic subtypes of multiple sclerosis","year":2019,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Canada Research Chairs; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Uncinate fasciculus; White matter; Inferior longitudinal fasciculus; Cingulum (brain); Medicine; Tractography; Multiple sclerosis; Psychology; Neuroscience; Magnetic resonance imaging; Pathology; Radiology; Internal medicine; Hippocampus; Psychiatry","score_opus":0.07964463984501635,"score_gpt":0.33372659288023976,"score_spread":0.2540819530352234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994619082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990576,0.00016620423,0.00015719522,0.000027376416,0.0000010954567,0.000007764999,0.00014421811,0.000009742947,0.00042885574],"genre_scores_gemma":[0.9992631,0.00005298984,0.00026861255,0.000012734989,0.000002629114,0.0000045801867,0.00023730738,0.0000035601336,0.00015452846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986374,0.000020887663,0.000017801618,0.000040764404,0.000032907912,0.000023881204],"domain_scores_gemma":[0.9996276,0.000040584044,0.00020323513,0.00003565811,0.000043290947,0.00004975212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035372612,0.00044900543,0.00032626712,0.0007761399,0.00029921756,0.00028369477,0.00017852357,0.00028918788,0.0013652289],"category_scores_gemma":[0.00095787144,0.00012225092,0.00014439419,0.00039174853,0.0002973543,0.00022725409,0.0002483397,0.00015559331,0.00025697163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001175249,0.000064745924,0.91791224,0.00006807163,0.00021322604,0.0013799014,0.00057153695,0.00016902044,0.061987557,0.00009877218,0.00040676515,0.015953014],"study_design_scores_gemma":[0.000012242102,0.00010028528,0.9947366,0.000008847449,0.000026152222,0.0032065993,0.00011817136,0.00013836134,0.0013552872,0.00009326174,0.000201523,0.000002602835],"about_ca_topic_score_codex":0.0046939924,"about_ca_topic_score_gemma":0.007034884,"teacher_disagreement_score":0.0046939924,"about_ca_system_score_codex":0.0003069057,"about_ca_system_score_gemma":0.00025949228,"threshold_uncertainty_score":0.0093333125},"labels":[],"label_agreement":null},{"id":"W2995065313","doi":"10.1038/s41380-019-0631-x","title":"Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium","year":2019,"lang":"en","type":"review","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":117,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Lawson Health Research Institute; Western University","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; National Institute of Allergy and Infectious Diseases; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute on Alcohol Abuse and Alcoholism; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Clinical Science Research and Development; National Institutes of Health; Congressionally Directed Medical Research Programs; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Bill and Melinda Gates Foundation; ZonMw; National Alliance for Research on Schizophrenia and Depression; Canadian Institute for Military and Veteran Health Research; Chinese Academy of Sciences; Division of Research Capacity Development; Deutsche Forschungsgemeinschaft; National Research Foundation; Yale Center for Clinical Investigation, Yale School of Medicine; Institute for Clinical and Translational Research, University of Wisconsin, Madison; Medical Research and Materiel Command; National Natural Science Foundation of China; Georgia Clinical and Translational Science Alliance; Waisman Center; U.S. Department of Veterans Affairs; Yale University; Office of Research and Development; National Center for PTSD, U.S. Department of Veterans Affairs; Michael J. Fox Foundation for Parkinson's Research; Traumatic Brain Injury Center of Excellence; South African Medical Research Council; U.S. Department of Defense","keywords":"Fractional anisotropy; White matter; Corpus callosum; Psychology; Neuroimaging; Psychiatry; Diffusion MRI; Brain Structure and Function; Depression (economics); Clinical psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.033739197866423314,"score_gpt":0.3567746116945881,"score_spread":0.32303541382816475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995065313","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011375207,0.99779546,0.000064191976,0.00022737225,0.000070687376,0.0000068131217,0.00035827144,0.000005134268,0.00033460403],"genre_scores_gemma":[0.0036367932,0.99518186,0.0002299208,0.00023330044,0.00008208631,0.00001068739,0.0005057233,0.000002718718,0.000116982264],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99981123,0.000026598529,0.000036222948,0.000058120193,0.00005022803,0.00001770091],"domain_scores_gemma":[0.99956745,0.00017876351,0.00010591681,0.00001287888,0.00010785452,0.000027114505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008843249,0.0006161054,0.0013200514,0.001510881,0.00016479417,0.0007488471,0.00071858324,0.0005107134,0.0013636618],"category_scores_gemma":[0.0013612048,0.0001937648,0.0007261086,0.0021589654,0.0002565518,0.0005740306,0.0007213421,0.00058627874,0.0004319991],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004174204,0.00003743481,0.0090009365,0.0320187,0.0024235547,0.00018221012,0.000120941455,0.000245115,0.0006926633,0.00058388873,0.020439908,0.9338373],"study_design_scores_gemma":[0.0003084367,0.0005437244,0.26793322,0.06521381,0.017868496,0.004459673,0.00082445244,0.00022670561,0.0011174949,0.0039320686,0.63733643,0.00023555788],"about_ca_topic_score_codex":0.007038099,"about_ca_topic_score_gemma":0.014086184,"teacher_disagreement_score":0.007038099,"about_ca_system_score_codex":0.00047420454,"about_ca_system_score_gemma":0.001818575,"threshold_uncertainty_score":0.013994217},"labels":[],"label_agreement":null},{"id":"W2995216162","doi":"10.3233/jad-191005","title":"Associations of White Matter Hyperintensities with Cognitive Decline: A Longitudinal Study","year":2019,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Hyperintensity; Cognition; Cognitive decline; Psychology; White matter; Longitudinal study; Medicine; Neuroscience; Dementia; Magnetic resonance imaging; Disease; Internal medicine; Pathology","score_opus":0.07958373307148219,"score_gpt":0.37107292871685926,"score_spread":0.29148919564537706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995216162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99802244,0.00040969436,0.00016522991,0.00005843617,0.000009310947,0.000015808393,0.0010966673,0.000006571731,0.00021579309],"genre_scores_gemma":[0.99685776,0.00024352205,0.00031125892,0.000063339656,0.000027815082,0.00004210467,0.002131824,0.0000070483984,0.00031529367],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930274,0.00015772639,0.000065761495,0.00027029432,0.00007686898,0.00012660181],"domain_scores_gemma":[0.9980938,0.00016127097,0.0005291049,0.00038910977,0.0004356896,0.00039096735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002422598,0.00048576758,0.0005959163,0.00073092774,0.0010367122,0.0009921385,0.00052334997,0.0006301521,0.0008895696],"category_scores_gemma":[0.0032984035,0.00060469494,0.0007703401,0.0012125422,0.00030453605,0.0008002456,0.0010445764,0.0013557818,0.00028862213],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006615495,0.00013279874,0.99594563,0.000019976416,0.0005747765,0.0000906108,0.00020250317,0.000054896213,0.00032338873,0.000029722849,0.00031236096,0.0016517167],"study_design_scores_gemma":[0.000038963237,0.00023677372,0.9984889,0.000012701406,0.00025674718,0.00015559292,0.00014015153,0.00021310843,0.000057739064,0.00006003283,0.00033146527,0.000007841067],"about_ca_topic_score_codex":0.010496444,"about_ca_topic_score_gemma":0.014845072,"teacher_disagreement_score":0.010496444,"about_ca_system_score_codex":0.00047820312,"about_ca_system_score_gemma":0.000594949,"threshold_uncertainty_score":0.020870686},"labels":[],"label_agreement":null},{"id":"W2995316596","doi":"10.1016/j.jmr.2019.106667","title":"Constant gradient FEXSY: A time-efficient method for measuring exchange","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Raymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, Yale University; Azrieli Foundation; Israel Science Foundation","keywords":"Mixing (physics); Chemistry; Diffusion; SIGNAL (programming language); Filter (signal processing); Constant (computer programming); Time constant; Weighting; Fick's laws of diffusion; Analytical Chemistry (journal); Residence time (fluid dynamics); Pulsed field gradient; Biological system; Chromatography; Thermodynamics; Physics; Computer science; Acoustics","score_opus":0.0584617030778875,"score_gpt":0.34395649548648843,"score_spread":0.28549479240860093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995316596","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0740334,0.0029100107,0.91091883,0.0007403082,0.00042154812,0.00033342082,0.0007459349,0.0033914105,0.006505183],"genre_scores_gemma":[0.19656707,0.002691811,0.78768766,0.00048606828,0.00014484032,0.000501046,0.0006395892,0.001201068,0.010080891],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99953794,0.000102937396,0.000026659258,0.00009326086,0.00019234118,0.000046862046],"domain_scores_gemma":[0.9991788,0.00032737164,0.0001338378,0.00012774851,0.00016768796,0.00006441027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014676081,0.0012317196,0.0007325477,0.0013555172,0.0009200247,0.0013460713,0.0016431333,0.0015613774,0.003960908],"category_scores_gemma":[0.0021019303,0.00063524814,0.00028128404,0.0009790005,0.00084573607,0.0016736424,0.0014311179,0.001902169,0.00089108257],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007121226,0.000108170534,0.0015649764,0.00084553024,0.00013966931,0.0004831941,0.00028915986,0.0016803794,0.8727207,0.008083393,0.0076405653,0.105732135],"study_design_scores_gemma":[0.00020347508,0.0003394623,0.0034952129,0.00013785747,0.00017655696,0.0019825841,0.00014355457,0.057908077,0.88753116,0.0053548585,0.042561974,0.00016518508],"about_ca_topic_score_codex":0.0010626409,"about_ca_topic_score_gemma":0.0033142003,"teacher_disagreement_score":0.003960908,"about_ca_system_score_codex":0.00038392225,"about_ca_system_score_gemma":0.00089566555,"threshold_uncertainty_score":0.01325053},"labels":[],"label_agreement":null},{"id":"W2995329121","doi":"10.1101/661702","title":"Hippocampal subfields and limbic white matter jointly predict learning rate in older adults","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"College of Engineering, Michigan State University; National Institutes of Health; Deutsche Forschungsgemeinschaft; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Strategic Innovation Fund; Michigan State University","keywords":"Fractional anisotropy; White matter; Psychology; Limbic system; Magnetic resonance imaging; Diffusion MRI; Verbal learning; Hippocampal formation; Tractography; Hippocampus; Brain size; Limbic lobe; Audiology; Neuroscience; Cognition; Medicine; Radiology; Central nervous system","score_opus":0.016038070354299192,"score_gpt":0.2524127172686653,"score_spread":0.23637464691436613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995329121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995627,0.000029580335,0.00021207891,0.000014855612,8.2023695e-7,0.0000022205127,0.000098074815,0.0000035277365,0.00007611155],"genre_scores_gemma":[0.9995097,0.00001680805,0.00019151739,0.0000047480953,0.0000021325022,0.0000025232434,0.00012548271,0.0000015356014,0.00014560485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985135,0.00003735925,0.000018377918,0.00005568864,0.000019334444,0.00001797671],"domain_scores_gemma":[0.99792993,0.0008345756,0.00070450804,0.0002629656,0.00012569764,0.00014228474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010664221,0.00045816108,0.00033512161,0.0004693459,0.00016814424,0.0006304053,0.00023585318,0.0005222151,0.0015238153],"category_scores_gemma":[0.0049596415,0.00021809187,0.00033719878,0.000272395,0.00024926246,0.00044536867,0.00038651013,0.00043665123,0.00024795404],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022436623,0.0000853294,0.9944351,0.000007439862,0.00007820452,0.000035797028,0.00013227173,0.0008328139,0.00070179877,0.00004359446,0.000059512,0.003363751],"study_design_scores_gemma":[0.000005739781,0.00011686579,0.9939275,0.0000051859893,0.000032358876,0.00008414782,0.00008553102,0.0050749136,0.00029477305,0.0003155837,0.000052922922,0.0000045206993],"about_ca_topic_score_codex":0.0039977804,"about_ca_topic_score_gemma":0.0049428004,"teacher_disagreement_score":0.0039977804,"about_ca_system_score_codex":0.00015005487,"about_ca_system_score_gemma":0.00016183581,"threshold_uncertainty_score":0.007948995},"labels":[],"label_agreement":null},{"id":"W2995345211","doi":"10.1007/s11682-019-00211-7","title":"Differences in attentional control and white matter microstructure in adolescents with attentional, affective, and behavioral disorders","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; Lotte and John Hecht Memorial Foundation","keywords":"Psychology; Fractional anisotropy; Psychopathology; Neuropsychology; White matter; Cognition; Association (psychology); Attentional control; Developmental psychology; Clinical psychology; Neuroscience; Medicine","score_opus":0.013776475550799572,"score_gpt":0.2962825678662885,"score_spread":0.2825060923154889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995345211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99958974,0.00007928193,0.000032926895,0.00001694566,0.0000018726562,0.0000025956597,0.000028342803,0.0000012048166,0.0002471355],"genre_scores_gemma":[0.99964845,0.000051156952,0.000048620517,0.000013758285,0.0000023327054,0.000003526337,0.000047705085,0.0000017619708,0.00018268106],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988174,0.000014913394,0.000013790584,0.000035035868,0.000025109213,0.000029263347],"domain_scores_gemma":[0.9995838,0.000067752444,0.00018788561,0.0000148457275,0.000058996637,0.00008673582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020075937,0.00021429746,0.0002114698,0.00071436324,0.000292439,0.00046253836,0.0001660209,0.00033287104,0.0014840525],"category_scores_gemma":[0.0010890611,0.000171351,0.00014357344,0.00033846486,0.0003005516,0.00028359875,0.0002740703,0.00044023598,0.00013158246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001991135,0.00020365407,0.98804015,0.000015582276,0.00004361576,0.0006140853,0.0006864118,0.000060102273,0.0050692465,0.00015798623,0.00009545282,0.004814661],"study_design_scores_gemma":[0.0000026785494,0.000049593145,0.9989491,0.0000030716283,0.000010043244,0.00037537294,0.0002811474,0.00006464817,0.0001637727,0.000050718256,0.00004867077,0.0000012183884],"about_ca_topic_score_codex":0.0060452926,"about_ca_topic_score_gemma":0.007656047,"teacher_disagreement_score":0.0060452926,"about_ca_system_score_codex":0.00031520572,"about_ca_system_score_gemma":0.00020905086,"threshold_uncertainty_score":0.012020171},"labels":[],"label_agreement":null},{"id":"W2995639855","doi":"10.1371/journal.pone.0226715","title":"Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Parkwood Institute; Ottawa Hospital; Health Sciences Centre; Baycrest Hospital; University of Toronto; Sunnybrook Health Science Centre; Western University","funders":"Faculty of Health Sciences, Queen's University; London Health Sciences Foundation; Queen's University; Centre for Addiction and Mental Health Foundation; McMaster University; Fondation Brain Canada; Temerty Family Foundation; University of Ottawa; Ontario Brain Institute; Canada First Research Excellence Fund; Government of Ontario","keywords":"Diffusion MRI; Artifact (error); Fractional anisotropy; Computer science; Artificial intelligence; Ground truth; Standard deviation; White matter; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Medicine","score_opus":0.1955343761508801,"score_gpt":0.5016304248407035,"score_spread":0.30609604868982343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995639855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1801182,0.0027594473,0.8028904,0.00036544955,0.00032155972,0.001421776,0.00083168043,0.00986061,0.0014309245],"genre_scores_gemma":[0.36300728,0.0008000298,0.6283239,0.00018392483,0.00011978814,0.0017727031,0.003131742,0.001818501,0.00084219413],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9839685,0.005888759,0.0021184671,0.0021776643,0.0053091287,0.00053742377],"domain_scores_gemma":[0.9206244,0.0381469,0.0065473136,0.008120646,0.025768828,0.00079200545],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03296457,0.0017321447,0.0009774133,0.003741766,0.0010600424,0.0029571478,0.0024079941,0.0014011447,0.0014438385],"category_scores_gemma":[0.10000668,0.0009327795,0.0017621615,0.0023370564,0.0015110155,0.0019737235,0.0021991816,0.0013069453,0.00059869385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00850244,0.0010067925,0.036147412,0.00204555,0.0016907579,0.0003665913,0.0013934149,0.11527071,0.06420753,0.0077116173,0.0068985154,0.7547587],"study_design_scores_gemma":[0.0013020795,0.003285904,0.05772656,0.0003479095,0.00094773114,0.00100204,0.00039970418,0.8043296,0.11332456,0.006183851,0.010672888,0.0004771959],"about_ca_topic_score_codex":0.0063859057,"about_ca_topic_score_gemma":0.003894469,"teacher_disagreement_score":0.9670354,"about_ca_system_score_codex":0.0015962936,"about_ca_system_score_gemma":0.002597584,"threshold_uncertainty_score":0.17433542},"labels":[],"label_agreement":null},{"id":"W2995803042","doi":"10.1002/nbm.4222","title":"Myelin water imaging and R<sub>2</sub><sup>*</sup> mapping in neonates: Investigating R<sub>2</sub><sup>*</sup> dependence on myelin and fibre orientation in whole brain white matter","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"White matter; Myelin; Nuclear medicine; Nuclear magnetic resonance; Orientation (vector space); Magnetic resonance imaging; Medicine; Multiple sclerosis; T2 relaxation; Physics; Internal medicine; Radiology; Central nervous system; Mathematics","score_opus":0.01954663813922236,"score_gpt":0.2835762526544734,"score_spread":0.26402961451525103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995803042","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992893,0.00016101789,0.00041984828,0.000011336259,0.00000159508,0.0000053347608,0.00003292924,0.0000037082232,0.00007490506],"genre_scores_gemma":[0.998406,0.0002054951,0.001135432,0.000022407974,0.0000023447694,0.000016350743,0.00004556337,0.0000055713,0.00016074583],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985385,0.000035233177,0.000016719081,0.00004448785,0.000025979121,0.000023755196],"domain_scores_gemma":[0.99963427,0.000066171786,0.00011810907,0.000028273873,0.000063237494,0.00008993331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006809533,0.00037147978,0.00029290305,0.00046519667,0.00021602027,0.00024045665,0.00026398705,0.00048834656,0.0005012629],"category_scores_gemma":[0.0011226614,0.00023378382,0.00012600234,0.0002355608,0.00045707604,0.00030514144,0.0003588064,0.00024631643,0.00009573235],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024589167,0.000120127,0.50395995,0.00023214973,0.00008330363,0.01016025,0.0022107048,0.00035450043,0.4635736,0.0002495477,0.00017517759,0.016421787],"study_design_scores_gemma":[0.000020424719,0.0014155995,0.94162726,0.00003794462,0.000065668624,0.008426994,0.0018990469,0.0010651773,0.044790827,0.00014422572,0.00047968392,0.000027200604],"about_ca_topic_score_codex":0.0030083964,"about_ca_topic_score_gemma":0.0030395368,"teacher_disagreement_score":0.0030083964,"about_ca_system_score_codex":0.00020592062,"about_ca_system_score_gemma":0.00023631057,"threshold_uncertainty_score":0.0059817433},"labels":[],"label_agreement":null},{"id":"W2995804543","doi":"10.1016/j.nicl.2019.102133","title":"Organization of the commissural fiber system in congenital and late-onset blindness","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Western University","funders":"H. Lundbeck A/S; Natural Sciences and Engineering Research Council of Canada; Lundbeckfonden","keywords":"Corpus callosum; Tractography; Commissure; Anterior commissure; Posterior commissure; Diffusion MRI; Anatomy; Magnetic resonance imaging; Neuroscience; Optic chiasm; Psychology; Medicine; Radiology","score_opus":0.0692362285574352,"score_gpt":0.3780526058192199,"score_spread":0.3088163772617847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995804543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997805,0.00006027167,0.00008366496,0.000004481379,4.7382903e-7,0.0000016741874,0.00002047787,0.0000028602105,0.000045699737],"genre_scores_gemma":[0.99975365,0.000024495292,0.00012696476,0.0000035218613,0.0000010698286,0.0000025526067,0.000035667163,0.0000019453387,0.000050036488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970144,0.00006180728,0.000025142974,0.00009007498,0.00006129623,0.00006026087],"domain_scores_gemma":[0.998811,0.00021170995,0.00055394287,0.000091903996,0.00012981262,0.00020168183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003984487,0.0004078899,0.000247243,0.0014532212,0.00027982172,0.00025865147,0.0001910411,0.00030335638,0.00079879427],"category_scores_gemma":[0.0017989795,0.00019804499,0.00014181876,0.00029970176,0.0009123677,0.00026747008,0.00039637563,0.00023113965,0.00006224643],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0046134456,0.00032432904,0.5787405,0.00013426326,0.00020954762,0.0036687828,0.0019874878,0.0006105286,0.38312006,0.00030837744,0.0001371254,0.02614548],"study_design_scores_gemma":[0.0000082726265,0.00021566405,0.9959571,0.000003368986,0.00001368756,0.00086468406,0.00009420712,0.00026292898,0.0024805968,0.00005272434,0.000042021962,0.0000047982644],"about_ca_topic_score_codex":0.007845326,"about_ca_topic_score_gemma":0.009400553,"teacher_disagreement_score":0.007845326,"about_ca_system_score_codex":0.00035272012,"about_ca_system_score_gemma":0.00025030176,"threshold_uncertainty_score":0.01559931},"labels":[],"label_agreement":null},{"id":"W2995848445","doi":"10.1101/864108","title":"Diffusion Weighted Image Co-registration: Investigation of Best Practices","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Image registration; Diffusion MRI; Fractional anisotropy; Artificial intelligence; Scalar (mathematics); Computer science; Computer vision; Mathematics; Nuclear medicine; Image (mathematics); Pattern recognition (psychology); Medicine; Radiology; Magnetic resonance imaging; Geometry","score_opus":0.06417132458827192,"score_gpt":0.33094702908479406,"score_spread":0.26677570449652216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995848445","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29142535,0.094973475,0.54827815,0.01248926,0.0006381648,0.0017150153,0.001455627,0.0047970964,0.044227883],"genre_scores_gemma":[0.488362,0.010598606,0.49715126,0.00032343593,0.00010144108,0.00034243322,0.00055641454,0.00075768336,0.0018067184],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9537086,0.0244262,0.004390095,0.0045071226,0.012382454,0.0005855892],"domain_scores_gemma":[0.8227516,0.10420218,0.018420672,0.020306874,0.033089332,0.0012294266],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.061985992,0.0009065541,0.0011866122,0.0073486087,0.0012460201,0.0067686704,0.0035931775,0.0018018048,0.0031278206],"category_scores_gemma":[0.19328225,0.0008174096,0.001207548,0.010471077,0.002427549,0.0067496295,0.002613888,0.0012001799,0.0011758097],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053016917,0.0003779718,0.028897965,0.0026503392,0.00067303405,0.00020779115,0.0015672749,0.007816644,0.0027746812,0.021124845,0.0057628155,0.9276164],"study_design_scores_gemma":[0.00031616414,0.0057679196,0.10154039,0.013050969,0.0027992204,0.010407956,0.011892659,0.49653822,0.061776128,0.17110418,0.12397767,0.00082852936],"about_ca_topic_score_codex":0.00346477,"about_ca_topic_score_gemma":0.003909667,"teacher_disagreement_score":0.93801403,"about_ca_system_score_codex":0.0031461169,"about_ca_system_score_gemma":0.0036461118,"threshold_uncertainty_score":0.32781714},"labels":[],"label_agreement":null},{"id":"W2995940953","doi":"10.3174/ajnr.a6357","title":"Diffusion Properties of Normal-Appearing White Matter Microstructure and Severity of Motor Impairment in Acute Ischemic Stroke","year":2019,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"Agency for Healthcare Research and Quality; National Institutes of Health; Davee Foundation; Northwestern University","keywords":"Fractional anisotropy; Internal capsule; Medicine; Diffusion MRI; Splenium; White matter; Cingulum (brain); Corpus callosum; Stroke (engine); Cardiology; Fluid-attenuated inversion recovery; Internal medicine; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.011559684935330834,"score_gpt":0.2639780858234442,"score_spread":0.25241840088811335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995940953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994728,0.00023933584,0.000094762814,0.00001054186,8.5684e-7,0.000005349707,0.000043550193,0.0000030178405,0.00012981193],"genre_scores_gemma":[0.9997217,0.00006154519,0.000116162104,0.0000037486964,0.0000028140855,0.0000027820086,0.000058307673,8.596311e-7,0.000032016094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999099,0.000022359352,0.00001868151,0.000018955338,0.000016502672,0.000013677725],"domain_scores_gemma":[0.9990477,0.00012876243,0.00058051356,0.00005225519,0.000084542844,0.00010620252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000367379,0.00025642756,0.00015532752,0.0007026185,0.00014522584,0.0002515242,0.00013396218,0.00022008638,0.0007822511],"category_scores_gemma":[0.0017470954,0.00009238395,0.00009084284,0.00025624866,0.00028205503,0.0002521514,0.00015252817,0.00015303907,0.00012993712],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012269617,0.00009858139,0.9777489,0.00006192389,0.00012772768,0.00022555586,0.00015432102,0.00033949284,0.009829169,0.00003520577,0.00010689954,0.010045319],"study_design_scores_gemma":[0.0000048510933,0.0001173178,0.9987771,0.0000026447683,0.0000123958325,0.0003671948,0.000029543813,0.00016967453,0.00045658663,0.000028936516,0.000031743377,0.0000018958624],"about_ca_topic_score_codex":0.0013389495,"about_ca_topic_score_gemma":0.0015239626,"teacher_disagreement_score":0.0013389495,"about_ca_system_score_codex":0.000194644,"about_ca_system_score_gemma":0.00012072421,"threshold_uncertainty_score":0.002662301},"labels":[],"label_agreement":null},{"id":"W2996631414","doi":"10.1159/000505077","title":"An Analysis of Clinical Outcome and Tractography following Bilateral Anterior Capsulotomy for Depression","year":2019,"lang":"en","type":"article","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Internal capsule; Medicine; Neuropsychology; Beck Depression Inventory; Sham surgery; Depression (economics); Psychology; Internal medicine; Neuroscience; Psychiatry; Pathology; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.09817051744641327,"score_gpt":0.40837371373684556,"score_spread":0.3102031962904323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996631414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997764,0.000024744852,0.00006970025,0.0000038179996,3.8998826e-7,0.0000037929008,0.000034911613,0.0000010982195,0.00008507532],"genre_scores_gemma":[0.9998202,0.000012702511,0.000052316595,0.0000018826585,0.0000011385886,0.000003141802,0.00007909265,5.3488293e-7,0.00002891562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988127,0.000029104109,0.000011356938,0.000026384478,0.00002709696,0.00002488872],"domain_scores_gemma":[0.9993499,0.00010794114,0.0003287004,0.00003708128,0.00006307522,0.00011339461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021767826,0.00016487323,0.00015282225,0.0005152618,0.00017080062,0.00016970403,0.00010926232,0.00018520842,0.0009072082],"category_scores_gemma":[0.0009287303,0.00006325266,0.0001649572,0.00027042296,0.0001895339,0.00014515968,0.00020923471,0.0001355761,0.00013084426],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060974946,0.000051092877,0.9864674,0.000013943886,0.00006365316,0.00080010976,0.00009250738,0.0001277408,0.0059429896,0.000016463495,0.000048560134,0.005765721],"study_design_scores_gemma":[0.0000052583746,0.00025184648,0.99805814,0.0000019488969,0.00001402918,0.0011152265,0.00004462757,0.00019133868,0.00026903374,0.000011245769,0.000035170404,0.0000020942998],"about_ca_topic_score_codex":0.0009586867,"about_ca_topic_score_gemma":0.0019746528,"teacher_disagreement_score":0.0009586867,"about_ca_system_score_codex":0.00020711348,"about_ca_system_score_gemma":0.0001545737,"threshold_uncertainty_score":0.0030349493},"labels":[],"label_agreement":null},{"id":"W2998287850","doi":"10.1007/s00429-019-02002-8","title":"Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children","year":2020,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; McGill University; Université de Sherbrooke; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Working memory; White matter; Concussion; Neuropathology; Tractography; Neuroscience; Prefrontal cortex; Fractional anisotropy; Diffusion MRI; Psychology; Dorsolateral prefrontal cortex; Medicine; Poison control; Pathology; Cognition; Magnetic resonance imaging; Radiology; Injury prevention","score_opus":0.01671676476347245,"score_gpt":0.24953331171933826,"score_spread":0.23281654695586582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998287850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999554,0.000054367916,0.00005654188,0.000029383884,0.0000016212465,0.0000024762112,0.00006056261,0.0000032563587,0.00023776774],"genre_scores_gemma":[0.9995377,0.00005450429,0.00011154518,0.000008438325,0.0000030027918,0.0000031923485,0.00009847893,0.0000019271163,0.00018118972],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998772,0.000012769275,0.00001528161,0.00002923677,0.00002972909,0.0000358131],"domain_scores_gemma":[0.99914634,0.00015578642,0.00043907374,0.00003474752,0.00011212531,0.00011198286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020568847,0.00053390756,0.00019173144,0.0010955011,0.00034827107,0.00044110994,0.000548034,0.00057891995,0.0015912381],"category_scores_gemma":[0.001579609,0.0002824751,0.0002108334,0.00052507233,0.00063198357,0.00034130903,0.00033883,0.00045465276,0.00022998688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059750375,0.000044924232,0.9933381,0.000011185532,0.000023909051,0.0011040799,0.00019921351,0.00015667929,0.0032460014,0.000035530804,0.00007499545,0.0017056771],"study_design_scores_gemma":[0.0000014939827,0.00003892124,0.9980958,0.000004501797,0.000010147414,0.00094210124,0.00024985525,0.00016487027,0.00044220084,0.000020098989,0.000028186887,0.0000018506532],"about_ca_topic_score_codex":0.022070872,"about_ca_topic_score_gemma":0.027783213,"teacher_disagreement_score":0.022070872,"about_ca_system_score_codex":0.0004499532,"about_ca_system_score_gemma":0.00045751434,"threshold_uncertainty_score":0.043884814},"labels":[],"label_agreement":null},{"id":"W2999007024","doi":"10.1088/1741-2552/ab6aad","title":"Common misconceptions, hidden biases and modern challenges of dMRI tractography","year":2020,"lang":"en","type":"review","venue":"Journal of Neural Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Computer science; Connectomics; Focus (optics); Connectome; Diffusion MRI; Data science; Field (mathematics); Artificial intelligence; Functional connectivity; Neuroscience; Psychology; Medicine; Mathematics; Magnetic resonance imaging; Physics","score_opus":0.20854267233809906,"score_gpt":0.3999560560535329,"score_spread":0.19141338371543384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999007024","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00092362525,0.95479107,0.008598217,0.032009516,0.0013771461,0.000019977044,0.000093877876,0.0000642289,0.002122222],"genre_scores_gemma":[0.011737581,0.9630694,0.008853539,0.012135376,0.0032077061,0.00007822137,0.00010191438,0.00006437371,0.00075193663],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9875108,0.005629935,0.0020237153,0.0014463068,0.0031585319,0.00023066555],"domain_scores_gemma":[0.9159928,0.07196115,0.0032887293,0.0019418037,0.006312329,0.0005031413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03468715,0.00090199144,0.0018922717,0.0049266606,0.0009358012,0.0040692664,0.0029336335,0.0030452034,0.001874453],"category_scores_gemma":[0.05725332,0.00077264017,0.0012016995,0.0045762854,0.011130685,0.008378337,0.0020526473,0.006662525,0.0014933576],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001257477,0.000040980176,0.0020867595,0.023956457,0.0005308287,0.00071848655,0.0031734325,0.0012530824,0.00087283045,0.0832828,0.045891445,0.83806723],"study_design_scores_gemma":[0.00003113001,0.000139411,0.0040007536,0.04297178,0.000524673,0.007437928,0.0025244108,0.0009581624,0.0022401137,0.16542165,0.77350485,0.00024510178],"about_ca_topic_score_codex":0.0030508603,"about_ca_topic_score_gemma":0.004376837,"teacher_disagreement_score":0.03468715,"about_ca_system_score_codex":0.0023440898,"about_ca_system_score_gemma":0.0041904994,"threshold_uncertainty_score":0.18344533},"labels":[],"label_agreement":null},{"id":"W2999285008","doi":"10.1016/j.neuroimage.2020.116533","title":"Diffusion time dependency along the human corpus callosum and exploration of age and sex differences as assessed by oscillating gradient spin-echo diffusion tensor imaging","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Corpus callosum; Diffusion MRI; Diffusion; Dependency (UML); Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Spin echo; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Computer science; Artificial intelligence; Mathematics; Quantum mechanics; Radiology; Geometry","score_opus":0.06032784273529428,"score_gpt":0.3258782284872872,"score_spread":0.2655503857519929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999285008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971867,0.00048665106,0.0019241044,0.000030374556,0.0000033262,0.0000042940455,0.000092742936,0.000019139206,0.00025275553],"genre_scores_gemma":[0.99706584,0.0003565607,0.002229914,0.000010357737,0.000005296676,0.0000074641835,0.00010785539,0.000008978641,0.00020776986],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994886,0.000013640495,0.0000037760165,0.00001678781,0.0000109888815,0.0000058908054],"domain_scores_gemma":[0.9997304,0.00012609964,0.00007159735,0.000021540849,0.00003663778,0.000013689389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028030423,0.00019751526,0.00012080919,0.00037653215,0.000106629705,0.00019769483,0.000116451236,0.00027058416,0.00049268367],"category_scores_gemma":[0.0012054312,0.00014846768,0.00014628559,0.0002324429,0.0001922088,0.0002238441,0.00014397307,0.000106237734,0.0000868289],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001926873,0.000088899775,0.28107774,0.00042631497,0.00037524846,0.0025118391,0.001620227,0.019448947,0.5981567,0.0015167358,0.00070632045,0.09214405],"study_design_scores_gemma":[0.000040277704,0.0005476213,0.8827708,0.000040613388,0.00019831638,0.0042369594,0.00034062105,0.051557574,0.05640254,0.0016402566,0.0021441807,0.00008034108],"about_ca_topic_score_codex":0.0027754083,"about_ca_topic_score_gemma":0.0031025284,"teacher_disagreement_score":0.0027754083,"about_ca_system_score_codex":0.00010429405,"about_ca_system_score_gemma":0.00017454317,"threshold_uncertainty_score":0.0055185556},"labels":[],"label_agreement":null},{"id":"W2999340690","doi":"10.1101/2020.01.07.896951","title":"Age-related changes of Peak width Skeletonized Mean Diffusivity (PSMD) across the adult life span: a multi-cohort study","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; Fondation pour la Recherche Médicale; Bundesministerium für Bildung und Forschung; National Health and Medical Research Council; European Commission; Fondation Leducq; Agence Nationale de la Recherche; Canadian Institutes of Health Research; EU Joint Programme – Neurodegenerative Disease Research","keywords":"Life span; Cohort; Span (engineering); Thermal diffusivity; Cohort study; Longevity; Demography; Gerontology; Medicine; Statistics; Mathematics; Physics; Engineering; Structural engineering; Thermodynamics; Sociology","score_opus":0.04884314225868297,"score_gpt":0.31313215610129996,"score_spread":0.264289013842617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999340690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99491066,0.0019031565,0.0008979117,0.00004899842,0.000022367421,0.0000292192,0.0018963018,0.00001230183,0.00027903458],"genre_scores_gemma":[0.9975674,0.00044666647,0.0005284128,0.00003572233,0.000019578963,0.000036414036,0.0010960413,0.000012581163,0.00025725155],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99901223,0.00017103823,0.00013403274,0.0005114024,0.00009267572,0.00007866217],"domain_scores_gemma":[0.9981369,0.00027404306,0.0005021156,0.0005462444,0.00039705727,0.00014366754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026601686,0.00050514087,0.00067220355,0.0008732953,0.0006703007,0.00091028545,0.0004527345,0.0005566608,0.0011314239],"category_scores_gemma":[0.0028450205,0.0004473133,0.0012943211,0.0011184195,0.00026840632,0.0005966227,0.0008205934,0.0006725813,0.00021504496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078696426,0.00004214556,0.98896796,0.00011526335,0.003077303,0.0002288271,0.00039495606,0.0001560367,0.0014887209,0.00010965767,0.0004961121,0.004136143],"study_design_scores_gemma":[0.00001916028,0.00012106424,0.99734724,0.000030262365,0.0011857583,0.00021699279,0.00014820007,0.00023180433,0.0001538495,0.000069818074,0.0004655262,0.000010320523],"about_ca_topic_score_codex":0.0075681964,"about_ca_topic_score_gemma":0.009347329,"teacher_disagreement_score":0.0075681964,"about_ca_system_score_codex":0.00025209706,"about_ca_system_score_gemma":0.00027409667,"threshold_uncertainty_score":0.015048325},"labels":[],"label_agreement":null},{"id":"W2999483695","doi":"10.1101/2020.01.17.911032","title":"Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Health and Medical Research Council; Medical Research Council; National Institutes of Health; Ramsay Health Care; NSW Ministry of Health; Pratt Foundation; Australian Schizophrenia Research Bank; Sylvia and Charles Viertel Charitable Foundation","keywords":"White matter; Normative; Percentile; Schizophrenia (object-oriented programming); Cohort; Fractional anisotropy; Psychology; Magnetic resonance imaging; Medicine; Internal medicine; Psychiatry; Radiology; Statistics; Mathematics","score_opus":0.0449064795165414,"score_gpt":0.3063060764977635,"score_spread":0.26139959698122206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999483695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965966,0.00001538706,0.00016618676,0.0000066556977,8.398739e-7,0.0000022215077,0.00008964735,0.0000032392363,0.000056127334],"genre_scores_gemma":[0.99962187,0.000013890018,0.000089407215,0.000003383247,0.0000010750354,0.0000041825247,0.00021911591,0.0000025270188,0.00004461419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995264,0.00017463129,0.0000344947,0.00016352779,0.00006550697,0.00003552305],"domain_scores_gemma":[0.99873215,0.000323951,0.00035814106,0.00033546187,0.00012191036,0.00012843752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013871177,0.00030087872,0.0002265296,0.0007282919,0.0003821675,0.00055135234,0.00036261635,0.0003459977,0.0010020459],"category_scores_gemma":[0.0030587749,0.00029263925,0.00026085982,0.00037768544,0.0004091747,0.00034848164,0.0005077825,0.0004634574,0.00019808295],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014184395,0.000029056717,0.9968946,0.0000026536684,0.00011099079,0.00008688287,0.00027363203,0.00023551223,0.000982224,0.00006457744,0.00007664133,0.0011012307],"study_design_scores_gemma":[0.0000045916645,0.000079948,0.99802727,0.0000022817044,0.000022051823,0.0003679302,0.00021454672,0.0009582056,0.00010801006,0.00011724773,0.00009225181,0.0000057482903],"about_ca_topic_score_codex":0.004242669,"about_ca_topic_score_gemma":0.0035132626,"teacher_disagreement_score":0.004242669,"about_ca_system_score_codex":0.0002088138,"about_ca_system_score_gemma":0.00014647206,"threshold_uncertainty_score":0.008435905},"labels":[],"label_agreement":null},{"id":"W3000068606","doi":"10.1101/2020.01.17.910851","title":"Elucidating the complex organization of neural micro-domains in the locust <i>Schistocerca gregaria</i> using dMRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Desert locust; Schistocerca; Kurtosis; Diffusion MRI; Fractional anisotropy; Locust; Neuroscience; Computer science; Magnetic resonance imaging; Diffusion imaging; Artificial intelligence; Biological system; Biology; Medicine; Mathematics; Ecology; Radiology","score_opus":0.06645331878895105,"score_gpt":0.29559273025199106,"score_spread":0.22913941146304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000068606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9823278,0.0006808909,0.014624633,0.000072299925,0.0000058768296,0.000015193396,0.00043941793,0.00014483482,0.0016890706],"genre_scores_gemma":[0.98621756,0.00032613854,0.012059138,0.000038197682,0.0000035659389,0.000012348255,0.00036051287,0.000030598767,0.0009519306],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99997866,0.0000024782507,0.0000015458057,0.000008430204,0.000004611976,0.000004239146],"domain_scores_gemma":[0.9999174,0.000010499542,0.0000382296,0.000007767599,0.000013694901,0.000012347428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007203289,0.00016160867,0.00009977816,0.00044854236,0.00012605161,0.00023474025,0.000097328266,0.00020432952,0.0008375188],"category_scores_gemma":[0.000098767996,0.00011377511,0.00010101448,0.00015020948,0.00022002889,0.000188425,0.0001786845,0.00017438381,0.00021921015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018287259,0.0000026746957,0.0017270336,0.000030029867,0.00000651775,0.00006320369,0.00002803978,0.0003220793,0.9955065,0.000093543604,0.000042523934,0.0021595487],"study_design_scores_gemma":[0.000014816248,0.00017582242,0.5750344,0.000045643785,0.00005018945,0.0018198071,0.00035048995,0.02106818,0.3950435,0.000724972,0.005637368,0.000034864286],"about_ca_topic_score_codex":0.002378944,"about_ca_topic_score_gemma":0.005261179,"teacher_disagreement_score":0.002378944,"about_ca_system_score_codex":0.00017346175,"about_ca_system_score_gemma":0.00010307568,"threshold_uncertainty_score":0.004730165},"labels":[],"label_agreement":null},{"id":"W3000134386","doi":"10.1002/hbm.24917","title":"Tractostorm: The what, why, and how of tractography dissection reproducibility","year":2020,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Protocol (science); Diffusion MRI; Reproducibility; Standardization; Bundle; Computer science; Fractional anisotropy; Checklist; Segmentation; Medical physics; Data mining; Psychology; Artificial intelligence; Medicine; Radiology; Magnetic resonance imaging; Pathology; Cognitive psychology; Statistics; Mathematics","score_opus":0.22686246618368003,"score_gpt":0.4114473892578078,"score_spread":0.1845849230741278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000134386","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06128701,0.09320015,0.42099178,0.37053078,0.014971898,0.0012544272,0.0019699184,0.0054096268,0.030384436],"genre_scores_gemma":[0.49000648,0.028094076,0.3993564,0.049137916,0.01280134,0.0032267103,0.0013388896,0.009473863,0.0065643494],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.7221488,0.19041245,0.024689559,0.019579574,0.04092444,0.0022451933],"domain_scores_gemma":[0.22785416,0.5920829,0.026974589,0.06947097,0.07896007,0.004657372],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.36855847,0.0013960493,0.0026857862,0.0044930363,0.0032471626,0.013048917,0.004750736,0.0053469036,0.00346451],"category_scores_gemma":[0.6535477,0.001588046,0.002266303,0.0041678413,0.026573878,0.021143546,0.0068030288,0.008591576,0.003407865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010551558,0.00013507808,0.09276491,0.004268464,0.001314616,0.00041835842,0.017223934,0.0032127395,0.0020653587,0.08887748,0.093720555,0.6949433],"study_design_scores_gemma":[0.0004698204,0.0009676195,0.09980939,0.021824522,0.000925648,0.0036756177,0.01054288,0.026293553,0.009267101,0.49911904,0.32565236,0.0014524623],"about_ca_topic_score_codex":0.007388284,"about_ca_topic_score_gemma":0.0064204144,"teacher_disagreement_score":0.63144153,"about_ca_system_score_codex":0.005792525,"about_ca_system_score_gemma":0.008422669,"threshold_uncertainty_score":0.77867985},"labels":[],"label_agreement":null},{"id":"W3000146139","doi":"10.1016/j.pnpbp.2020.109871","title":"White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"Progress in Neuro-Psychopharmacology and Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Douglas Mental Health University Institute; McGill University","funders":"Daiichi Sankyo Europe; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Novartis Pharma; National Institutes of Health; Japan Health Foundation; SENSHIN Medical Research Foundation; Mochida Memorial Foundation for Medical and Pharmaceutical Research; Ministero dello Sviluppo Economico; Meiji Seika Pharma; Shionogi; Eisai; Daiichi-Sankyo; Novartis; Ontario Mental Health Foundation; W. Garfield Weston Foundation; Otsuka Pharmaceutical; National Alliance for Research on Schizophrenia and Depression; Weston Brain Institute; Fujifilm Corporation; Michael J. Fox Foundation for Parkinson's Research; Takeda Science Foundation; Dainippon Sumitomo Pharma; Janssen Japan; Natural Sciences and Engineering Research Council of Canada; Pfizer; Japan Research Foundation for Clinical Pharmacology; Japan Agency for Medical Research and Development; Naito Foundation; McGill University; Consejo Nacional de Ciencia y Tecnología; Instituto de Ciencia y Tecnología del Distrito Federal; Uehara Memorial Foundation; Innovationsfonden; Tsumura and Company; Alzheimer's Association","keywords":"White matter; Uncinate fasciculus; Corpus callosum; Internal capsule; Fractional anisotropy; Fasciculus; Diffusion MRI; Superior longitudinal fasciculus; Medicine; Psychology; Positive and Negative Syndrome Scale; Cerebral peduncle; Corona radiata (embryology); Population; Internal medicine; Magnetic resonance imaging; Neuroscience; Psychiatry; Radiology; Psychosis","score_opus":0.01835313595439185,"score_gpt":0.31278221084865754,"score_spread":0.2944290748942657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000146139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997185,0.000036880137,0.000023164204,0.000021562273,0.0000011889645,0.000004928478,0.000042014537,9.925998e-7,0.00015077282],"genre_scores_gemma":[0.9997274,0.000039496917,0.000044471788,0.0000147429255,0.0000046520927,0.0000027899741,0.00009475478,0.0000011298085,0.00007056818],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999866,0.00002972252,0.000025443078,0.000028650076,0.000026175609,0.000024012115],"domain_scores_gemma":[0.99948955,0.000081934595,0.000212304,0.000040554147,0.000051800038,0.00012380713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004375815,0.00063051167,0.0003746763,0.0009383055,0.00084011286,0.00054339354,0.00027712298,0.00061732833,0.0011427755],"category_scores_gemma":[0.0012441138,0.00042145033,0.0003342563,0.00055950636,0.00065966806,0.00061062054,0.00044538587,0.00051053765,0.0002431867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002643572,0.00062855886,0.96505964,0.000067284105,0.00026745972,0.0050678975,0.002092687,0.0002392546,0.019173754,0.00012592679,0.00019056113,0.0044435496],"study_design_scores_gemma":[0.00004037711,0.00034340363,0.99628484,0.000003888518,0.00004489917,0.0022276489,0.0005742867,0.00016147547,0.00018494461,0.000056775843,0.00006862963,0.000008912484],"about_ca_topic_score_codex":0.007098283,"about_ca_topic_score_gemma":0.010070483,"teacher_disagreement_score":0.007098283,"about_ca_system_score_codex":0.00036418397,"about_ca_system_score_gemma":0.0004361714,"threshold_uncertainty_score":0.014113963},"labels":[],"label_agreement":null},{"id":"W3000797342","doi":"10.1016/j.jneumeth.2020.108593","title":"A framework for quality control of corpus callosum segmentation in large-scale studies","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; NYU Langone Medical Center","keywords":"Segmentation; Pattern recognition (psychology); Artificial intelligence; Computer science; Support vector machine; Ground truth; Classifier (UML); Metric (unit); Machine learning","score_opus":0.36441515726137436,"score_gpt":0.5804615676928803,"score_spread":0.2160464104315059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000797342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00060846895,0.00019556322,0.9985746,0.00018291848,0.00001985996,0.000051204443,0.000043090182,0.00015182896,0.00017243488],"genre_scores_gemma":[0.05208889,0.00039497076,0.94559056,0.00018035492,0.00018687369,0.000485779,0.0003239319,0.00031164798,0.0004369835],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97281915,0.01571558,0.0022895765,0.00403384,0.00438901,0.0007528788],"domain_scores_gemma":[0.8851326,0.06986713,0.009568351,0.015211359,0.018338675,0.0018819128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.075340405,0.0019382004,0.0033920764,0.005160348,0.0022941388,0.008720073,0.00688468,0.0037428983,0.0020871647],"category_scores_gemma":[0.16053003,0.0015620228,0.0025512727,0.0049239304,0.005463175,0.0064148596,0.009049032,0.005175346,0.00076358585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048497962,0.00018159708,0.0070304233,0.0011134114,0.00097571977,0.0005144718,0.0015034245,0.17728965,0.008912683,0.51987773,0.008816226,0.2732998],"study_design_scores_gemma":[0.00012313451,0.00013855429,0.0027668513,0.0003074669,0.00024113625,0.00028273158,0.0001941576,0.61753297,0.004248115,0.36342004,0.010610295,0.00013458835],"about_ca_topic_score_codex":0.00969195,"about_ca_topic_score_gemma":0.007408661,"teacher_disagreement_score":0.075340405,"about_ca_system_score_codex":0.0029514523,"about_ca_system_score_gemma":0.008254913,"threshold_uncertainty_score":0.39844292},"labels":[],"label_agreement":null},{"id":"W3002121850","doi":"10.1016/j.neuroimage.2020.116552","title":"Early childhood development of white matter fiber density and morphology","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Hotchkiss Brain Institute","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Corticospinal tract; Brain development; Tractography; Fiber bundle; Anatomy; Fiber; Biology; Neuroscience; Psychology; Chemistry; Medicine; Magnetic resonance imaging","score_opus":0.0390138754629844,"score_gpt":0.2901391307683762,"score_spread":0.2511252553053918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002121850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99148846,0.0005609559,0.0056863753,0.000042416083,0.0000050504136,0.000012829422,0.0012123231,0.00008826851,0.0009033253],"genre_scores_gemma":[0.9901231,0.00061694294,0.0079710735,0.0000147718565,0.0000031916416,0.00002397965,0.0006253876,0.000038682985,0.0005828345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996917,0.000041731328,0.000020993035,0.00012521207,0.00008260424,0.000037782454],"domain_scores_gemma":[0.9991948,0.00013688118,0.00041943,0.0000754387,0.00012380509,0.000049693506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066961686,0.00033034477,0.00027417927,0.0009288003,0.00032554258,0.0006583535,0.00021230537,0.00021049455,0.0012330802],"category_scores_gemma":[0.0018101541,0.00023791277,0.00031194388,0.00057136774,0.00040660737,0.00044368178,0.00039779817,0.0002615988,0.00023824871],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018399608,0.000025609026,0.92756885,0.00011725778,0.00016281169,0.0003618041,0.00090914866,0.00087603246,0.03247521,0.00054063625,0.00032110914,0.036457505],"study_design_scores_gemma":[7.9557475e-7,0.000030938067,0.99631786,0.000011601831,0.00001534904,0.00031074608,0.000108401524,0.0002866125,0.0024843477,0.00009621251,0.00033343813,0.0000037043503],"about_ca_topic_score_codex":0.014254015,"about_ca_topic_score_gemma":0.022678921,"teacher_disagreement_score":0.014254015,"about_ca_system_score_codex":0.00050036114,"about_ca_system_score_gemma":0.000559648,"threshold_uncertainty_score":0.028342068},"labels":[],"label_agreement":null},{"id":"W3002904902","doi":"10.1038/s41598-020-58128-x","title":"Predicting change trajectories of neuroticism from baseline brain structure using whole brain analyses and latent growth curve models in adolescents","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Jacobs Foundation; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Neuroticism; Psychopathology; Structural equation modeling; Psychology; Personality; Growth curve (statistics); Latent growth modeling; Voxel; Neuroimaging; Developmental psychology; Clinical psychology; Neuroscience; Statistics; Social psychology; Artificial intelligence; Computer science; Mathematics","score_opus":0.1774518183243011,"score_gpt":0.36909903682310813,"score_spread":0.19164721849880703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002904902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998684,0.000041686395,0.0010769786,0.000023060573,0.0000011942071,0.0000036846595,0.00008970646,0.0000070543038,0.00007262877],"genre_scores_gemma":[0.99891186,0.00004155891,0.0006976122,0.000002247369,8.3642345e-7,0.0000068847444,0.0002525359,0.000004773378,0.00008169418],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996258,0.00019052434,0.000019664994,0.00007570516,0.000035965044,0.000052313062],"domain_scores_gemma":[0.9984634,0.00077773706,0.00029570088,0.00022050049,0.000107738066,0.00013501891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017988726,0.00038040878,0.00023763707,0.0007189863,0.00019071586,0.00068990403,0.00029491354,0.00027082054,0.00070933875],"category_scores_gemma":[0.0042159525,0.0002582902,0.0007104612,0.0004482656,0.00027353383,0.00041326703,0.00053833186,0.0006741455,0.00016415102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098278215,0.00004273355,0.99032414,0.000007507016,0.00010074775,0.00006491867,0.00028883587,0.0019854854,0.0006258712,0.00017688476,0.000074923795,0.0062095947],"study_design_scores_gemma":[0.0000029268122,0.00010020995,0.9783094,0.000012333084,0.00003307392,0.00011000066,0.0003520041,0.020258283,0.0003512397,0.00032781457,0.0001373826,0.0000053536846],"about_ca_topic_score_codex":0.011127505,"about_ca_topic_score_gemma":0.01596928,"teacher_disagreement_score":0.011127505,"about_ca_system_score_codex":0.0003880058,"about_ca_system_score_gemma":0.00051221787,"threshold_uncertainty_score":0.022125483},"labels":[],"label_agreement":null},{"id":"W3003448798","doi":"10.1016/j.bpsc.2020.01.004","title":"Fully Automated Habenula Segmentation Provides Robust and Reliable Volume Estimation Across Large Magnetic Resonance Imaging Datasets, Suggesting Intriguing Developmental Trajectories in Psychiatric Disease","year":2020,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; McGill University; Douglas Mental Health University Institute; University Health Network","funders":"General Armaments Department, People's Liberation Army; Fundação de Amparo à Pesquisa do Estado de São Paulo; National Alliance for Research on Schizophrenia and Depression; Wellcome Trust; Fondation Brain Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Compute Canada; Health Canada; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); Segmentation; Bipolar disorder; Magnetic resonance imaging; Habenula; Reliability (semiconductor); Neuroimaging; Computer science; Artificial intelligence; Neuroscience; Psychology; Medicine; Psychiatry; Radiology; Cognition; Physics","score_opus":0.055396165592117824,"score_gpt":0.34116374613976697,"score_spread":0.28576758054764917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003448798","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26368552,0.0028410987,0.70843977,0.00072704273,0.00023231721,0.00046190646,0.006699068,0.012780683,0.004132538],"genre_scores_gemma":[0.35247207,0.0010749476,0.6269921,0.00030442447,0.00014880858,0.00061637163,0.011408744,0.0047069113,0.0022755384],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987534,0.0003550745,0.00012775174,0.0004186588,0.00025362262,0.000091526366],"domain_scores_gemma":[0.9978033,0.0008062136,0.00031835653,0.0006275296,0.00035968746,0.00008494289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029628247,0.0010292826,0.000715998,0.0020012485,0.00082603085,0.001957561,0.00100675,0.0010159502,0.0025771188],"category_scores_gemma":[0.007935779,0.00081700465,0.0009754281,0.0009610664,0.0007158001,0.0012158481,0.0019150431,0.0010150133,0.0012739331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010016124,0.00028386488,0.04624518,0.0012789425,0.0015569018,0.0008696933,0.0015102406,0.0474133,0.35999045,0.0076487698,0.017598363,0.5146028],"study_design_scores_gemma":[0.00029607653,0.0007242433,0.20832592,0.0005585316,0.00076164445,0.0047845254,0.00085228385,0.41812646,0.26858488,0.03945309,0.05700757,0.00052477693],"about_ca_topic_score_codex":0.003835399,"about_ca_topic_score_gemma":0.012761182,"teacher_disagreement_score":0.003835399,"about_ca_system_score_codex":0.0005264437,"about_ca_system_score_gemma":0.001418133,"threshold_uncertainty_score":0.015669107},"labels":[],"label_agreement":null},{"id":"W3003557145","doi":"10.1016/j.ymgme.2019.11.297","title":"Intraspinal space restriction at the occipito-cervical junction alters cervical spinal cord diffusion MRI metrics in mucopolysacharidoses patients","year":2020,"lang":"en","type":"article","venue":"Molecular Genetics and Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Normalization (sociology); Generalization; Artificial neural network; Computer science; Context (archaeology); Artificial intelligence; Diffusion MRI; Inductive bias; Space (punctuation); Machine learning; Neuroscience; Task (project management); Psychology; Biology; Mathematics; Magnetic resonance imaging; Medicine","score_opus":0.033533848730522314,"score_gpt":0.30845885781807564,"score_spread":0.27492500908755335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003557145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99873155,0.00012333662,0.000058374048,0.00007064553,0.0000058395794,0.0000037552334,0.00023736172,0.000005479487,0.00076367793],"genre_scores_gemma":[0.9994041,0.000055359007,0.00005383909,0.000026137426,0.000006291099,0.0000034995278,0.0001701779,0.0000055042383,0.00027505148],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983954,0.000019857334,0.000024127123,0.00005402027,0.000027410624,0.00003510108],"domain_scores_gemma":[0.99946946,0.000108722124,0.00025389378,0.000026836597,0.00005671385,0.00008435154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014163887,0.00045002226,0.00023610903,0.000610245,0.00053203094,0.0006748401,0.000392963,0.00064825,0.004433178],"category_scores_gemma":[0.0019469934,0.00015511423,0.00028635567,0.0006023369,0.00041078214,0.00035713165,0.00032135934,0.0003688009,0.00044818397],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093842804,0.000106813284,0.96359843,0.000046060726,0.00014861808,0.006260693,0.0006540861,0.00030714605,0.014751541,0.00022145509,0.0006139492,0.012352745],"study_design_scores_gemma":[0.000008535849,0.00010979712,0.99444264,0.00001940831,0.000059140115,0.0036865713,0.00040392778,0.00017416645,0.00061156397,0.00017820642,0.00029700913,0.000009071792],"about_ca_topic_score_codex":0.008934264,"about_ca_topic_score_gemma":0.008965777,"teacher_disagreement_score":0.008934264,"about_ca_system_score_codex":0.00037762118,"about_ca_system_score_gemma":0.0003788253,"threshold_uncertainty_score":0.017764509},"labels":[],"label_agreement":null},{"id":"W3003644065","doi":"10.3390/app10030934","title":"Machine Learning and DWI Brain Communicability Networks for Alzheimer’s Disease Detection","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Servier; University of Southern California; Eli Lilly and Company; Genentech; IXICO","keywords":"Computer science; Artificial intelligence; Machine learning; Brain disease; Feature (linguistics); Pattern recognition (psychology); Disease; Medicine; Pathology","score_opus":0.11891175296995896,"score_gpt":0.3755350759972443,"score_spread":0.2566233230272853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003644065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24257335,0.004269362,0.7479529,0.0010255033,0.00010734721,0.000111741014,0.000689141,0.0007018681,0.0025687986],"genre_scores_gemma":[0.885792,0.0015481396,0.11014863,0.00009412692,0.0001415633,0.00011074458,0.0007316765,0.000036511916,0.0013966121],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994809,0.00021212143,0.000032126856,0.000110170324,0.0001164824,0.000048180227],"domain_scores_gemma":[0.99873394,0.00075150485,0.00022154812,0.00008812013,0.00016443658,0.00004044935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013356031,0.0007875668,0.0005365878,0.0019348171,0.00031226224,0.00066971994,0.00055013056,0.00074378087,0.00097005226],"category_scores_gemma":[0.0046661836,0.00020016152,0.00051902304,0.0014536697,0.00040053873,0.0010451942,0.00052054506,0.0007119835,0.00030158032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004502552,0.000276622,0.020914167,0.00026838778,0.0002544937,0.00027450858,0.00013975632,0.42102692,0.012708231,0.013115225,0.0029305806,0.52764094],"study_design_scores_gemma":[0.000007589169,0.0000668471,0.00489846,0.000016046808,0.000024360797,0.00009211116,0.000020699837,0.98414767,0.002277425,0.007778791,0.00065904105,0.000010967713],"about_ca_topic_score_codex":0.0030428388,"about_ca_topic_score_gemma":0.0025713951,"teacher_disagreement_score":0.0030428388,"about_ca_system_score_codex":0.0005561909,"about_ca_system_score_gemma":0.0003706499,"threshold_uncertainty_score":0.0070634484},"labels":[],"label_agreement":null},{"id":"W3003733514","doi":"10.1038/s41598-020-58291-1","title":"Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Alzheimer's Disease Neuroimaging Initiative; Organization for Women in Science for the Developing World; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; F. Hoffmann-La Roche; Styrelsen för Internationellt Utvecklingssamarbete; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; University of Cape Town; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Genome-wide association study; Neuroimaging; Disease; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Genetic association; Single-nucleotide polymorphism; Imaging genetics; Neuroscience; Computational biology; Biology; Bioinformatics; Medicine; Genetics; Gene; Genotype; Pathology","score_opus":0.11546791995508524,"score_gpt":0.3674257070247437,"score_spread":0.25195778706965843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003733514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99657756,0.00044286982,0.001483893,0.00021749738,0.00001916491,0.000008893484,0.00079653494,0.000032818345,0.00042082582],"genre_scores_gemma":[0.99792117,0.00015302177,0.0011320264,0.0000348555,0.000016700824,0.0000133575995,0.0006007774,0.000010856586,0.000117241856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998811,0.0004892862,0.00008474162,0.00040313313,0.00012168627,0.00009012203],"domain_scores_gemma":[0.9967713,0.0014369247,0.0008759084,0.00044753795,0.00018399354,0.000284397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018769534,0.0003355289,0.0004173072,0.0011272266,0.00056034856,0.00051368296,0.0003383181,0.00047763027,0.0018517844],"category_scores_gemma":[0.005154009,0.00020792194,0.00073278684,0.0018274958,0.0004484624,0.00029334152,0.0005334017,0.00088416605,0.00012686533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007077906,0.00014000927,0.9766594,0.000046834353,0.0030588075,0.00043638286,0.00018511937,0.0008048281,0.0102765085,0.0006010281,0.00058024155,0.0065030004],"study_design_scores_gemma":[0.000020209904,0.000077117686,0.9971553,0.0000052076807,0.00030189284,0.00028715917,0.000034592136,0.001062564,0.00035710706,0.00037760366,0.000313856,0.0000073770416],"about_ca_topic_score_codex":0.004362778,"about_ca_topic_score_gemma":0.007970825,"teacher_disagreement_score":0.004362778,"about_ca_system_score_codex":0.00021686121,"about_ca_system_score_gemma":0.00041179822,"threshold_uncertainty_score":0.009926379},"labels":[],"label_agreement":null},{"id":"W3005461968","doi":"10.1101/2020.02.05.934430","title":"Myelin water fraction decrease in mild traumatic brain injury","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Mitacs","keywords":"Splenium; Corpus callosum; White matter; Traumatic brain injury; Myelin; Corticospinal tract; Medicine; Superior longitudinal fasciculus; Cognition; Psychology; Fasciculus; Neuroscience; Internal medicine; Diffusion MRI; Audiology; Anesthesia; Cardiology; Magnetic resonance imaging; Pathology; Central nervous system; Psychiatry; Radiology","score_opus":0.06387169348619276,"score_gpt":0.3208510489758709,"score_spread":0.25697935548967815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005461968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991441,0.0003641958,0.00020910114,0.000015157612,0.000002534652,0.00000424804,0.00009274923,0.00001199577,0.0001559872],"genre_scores_gemma":[0.99943656,0.00010674301,0.00014368624,0.000009748884,0.0000027295473,0.000004528009,0.00009831977,0.0000022069225,0.00019549808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999473,0.0000061574674,0.000005490617,0.000014173531,0.000012815298,0.000014037049],"domain_scores_gemma":[0.9997894,0.000015722824,0.00011593677,0.000011383024,0.000032123447,0.000035330973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015615246,0.00024740407,0.00022000121,0.00084494305,0.0002353792,0.00020900523,0.00012840306,0.0002646203,0.0015164547],"category_scores_gemma":[0.0005863022,0.00012393229,0.000099414225,0.000315792,0.00030649485,0.000217,0.0003433676,0.00020949163,0.00017514001],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004362647,0.00025628548,0.58442515,0.00033459673,0.00021615409,0.001131407,0.0009864469,0.00035100934,0.36540034,0.00013721964,0.0007030635,0.041695718],"study_design_scores_gemma":[0.000009941424,0.0006954597,0.9776044,0.000009956063,0.000033591365,0.0010468216,0.00025153125,0.00020806168,0.019734945,0.00012571471,0.00027310225,0.000006556664],"about_ca_topic_score_codex":0.0028266849,"about_ca_topic_score_gemma":0.0018927869,"teacher_disagreement_score":0.0028266849,"about_ca_system_score_codex":0.0001446232,"about_ca_system_score_gemma":0.00012198251,"threshold_uncertainty_score":0.0056204796},"labels":[],"label_agreement":null},{"id":"W3005837005","doi":"10.1002/jmri.27092","title":"Improving Spatial Normalization of Brain Diffusion MRI to Measure Longitudinal Changes of Tissue Microstructure in the Cortex and White Matter","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Agencia Nacional de Promoción Científica y Tecnológica; Ministry of Defense; Fondo para la Investigación Científica y Tecnológica; Universidad de Buenos Aires; Réseau en Bio-Imagerie du Quebec","keywords":"Reproducibility; White matter; Diffusion MRI; Fractional anisotropy; Spatial normalization; Normalization (sociology); Diffusion imaging; Medicine; Nuclear medicine; Computer science; Artificial intelligence; Mathematics; Magnetic resonance imaging; Radiology; Statistics","score_opus":0.02012599535054777,"score_gpt":0.2876542271717417,"score_spread":0.26752823182119395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005837005","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69946957,0.0006657547,0.29646537,0.00017468043,0.000068656744,0.0002895392,0.00033669267,0.0011246268,0.0014050935],"genre_scores_gemma":[0.6715391,0.00031642563,0.325604,0.000049390634,0.000022128073,0.00033614054,0.00057519064,0.00041736773,0.0011402632],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992065,0.00024514232,0.00007560033,0.00023961462,0.0001839612,0.0000492052],"domain_scores_gemma":[0.99801755,0.00068340654,0.0003246885,0.00041555156,0.0005176004,0.000041172538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003597101,0.00051256147,0.0003437318,0.0005374221,0.000306973,0.00052506535,0.0004583061,0.00034600747,0.0013821484],"category_scores_gemma":[0.009002029,0.00028142807,0.00045005896,0.00045913408,0.000407099,0.000725521,0.0005279927,0.00042962274,0.00043977436],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014551604,0.00044018123,0.03591584,0.0003529275,0.0003746605,0.00009922622,0.00049772154,0.015785228,0.6410745,0.001359492,0.0016711722,0.30097386],"study_design_scores_gemma":[0.00024790422,0.0026111975,0.3195322,0.00007382706,0.000414302,0.0016195035,0.00016571314,0.15736768,0.5040935,0.0030770332,0.010624913,0.00017228513],"about_ca_topic_score_codex":0.0020488931,"about_ca_topic_score_gemma":0.0047112512,"teacher_disagreement_score":0.003597101,"about_ca_system_score_codex":0.0003893564,"about_ca_system_score_gemma":0.00086251245,"threshold_uncertainty_score":0.019023478},"labels":[],"label_agreement":null},{"id":"W3006287032","doi":"10.1002/nbm.4270","title":"Rapid acquisition diffusion MR spectroscopy of metabolites in human brain","year":2020,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Diffusion; Data acquisition; White matter; Nuclear magnetic resonance; Diffusion imaging; Spectroscopy; Computer science; Physics; Biological system; Magnetic resonance imaging; Medicine; Biology","score_opus":0.0527022688788116,"score_gpt":0.3695152712650518,"score_spread":0.3168130023862402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006287032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5662398,0.046807054,0.37457415,0.0017449895,0.0003227221,0.00054179545,0.0010939622,0.0011588744,0.007516739],"genre_scores_gemma":[0.714674,0.021301942,0.25717172,0.0004846365,0.00027063675,0.00043093073,0.00097485405,0.0002358209,0.0044554546],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998342,0.000055559205,0.000009630171,0.000051436033,0.00003699319,0.000012163209],"domain_scores_gemma":[0.9998105,0.0000677067,0.00003643235,0.000023457616,0.000043773638,0.000018126277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008320787,0.00040935574,0.0002934671,0.00053198787,0.00018367334,0.0003619201,0.00027294277,0.00053655275,0.0014414452],"category_scores_gemma":[0.0011951113,0.00025181478,0.00014038758,0.00033605628,0.00028903934,0.0008614316,0.00038937922,0.00035936318,0.00056497805],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043209488,0.000059919817,0.0006920359,0.00053046166,0.00004124907,0.00020381335,0.00009048598,0.0006761161,0.93327886,0.0011564125,0.0010995939,0.061738893],"study_design_scores_gemma":[0.00030146347,0.0026381519,0.0207629,0.00014112607,0.00020013063,0.007534797,0.00018254435,0.012150605,0.91045773,0.007006896,0.038463183,0.00016047044],"about_ca_topic_score_codex":0.00029853854,"about_ca_topic_score_gemma":0.0005612634,"teacher_disagreement_score":0.0014414452,"about_ca_system_score_codex":0.000114306014,"about_ca_system_score_gemma":0.00031021985,"threshold_uncertainty_score":0.004822135},"labels":[],"label_agreement":null},{"id":"W3006318419","doi":"10.1101/2020.02.14.949826","title":"Network efficiency predicts resilience to cognitive decline in elderly at risk for Alzheimer’s","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Eisai; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cognitive decline; White matter; Hyperintensity; Dementia; Cognition; Effects of sleep deprivation on cognitive performance; Neuropsychology; Psychology; Psychological resilience; Internal medicine; Cognitive reserve; Medicine; Gerontology; Cardiology; Neuroscience; Cognitive impairment; Magnetic resonance imaging; Disease; Radiology","score_opus":0.05382894729616882,"score_gpt":0.3177781001630959,"score_spread":0.26394915286692705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006318419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992337,0.00008269389,0.00021575933,0.000030595493,0.000002452348,0.0000046437995,0.000094102434,0.0000044162775,0.00033161638],"genre_scores_gemma":[0.9996786,0.000028357355,0.00008154206,0.0000052332416,0.0000031409018,0.0000031688646,0.00008216342,6.6471557e-7,0.00011714642],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999043,0.000022497188,0.000010679567,0.000027134562,0.000014285456,0.000021055932],"domain_scores_gemma":[0.9987276,0.00027881918,0.0005227451,0.00012815918,0.00012782252,0.00021473679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064589054,0.0003483905,0.00026158208,0.0006278175,0.00019681799,0.00039570002,0.00023056894,0.00030698263,0.0020008544],"category_scores_gemma":[0.0040204385,0.00012875433,0.00021011816,0.00027516077,0.0002467513,0.0004883845,0.00052100397,0.0003014452,0.00017533851],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005381867,0.00013655091,0.98857516,0.000025671865,0.00027691867,0.00016433823,0.00024049339,0.0014464041,0.0021864725,0.00017410015,0.0001774341,0.006058202],"study_design_scores_gemma":[0.0000032433259,0.00009013351,0.9980136,0.0000053390595,0.00002133985,0.000077308636,0.00009384593,0.0012141971,0.000116375755,0.00029459427,0.00006632491,0.0000037029772],"about_ca_topic_score_codex":0.00182275,"about_ca_topic_score_gemma":0.0025651155,"teacher_disagreement_score":0.0020008544,"about_ca_system_score_codex":0.00019452283,"about_ca_system_score_gemma":0.00008758097,"threshold_uncertainty_score":0.006693542},"labels":[],"label_agreement":null},{"id":"W3006482384","doi":"10.1111/jon.12689","title":"Brain Myelin Water Fraction and Diffusion Tensor Imaging Atlases for 9‐10 Year‐Old Children","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Canadian Language and Literacy Research Network","keywords":"Medicine; Diffusion MRI; White matter; Fractional anisotropy; Corpus callosum; Neuroimaging; Magnetic resonance imaging; Nuclear medicine; Radiology; Pathology; Psychiatry","score_opus":0.045986652713089805,"score_gpt":0.33084603988391603,"score_spread":0.2848593871708262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006482384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7964174,0.0010333908,0.11597901,0.0003197143,0.000106512656,0.00063913077,0.06595758,0.0038603544,0.015686868],"genre_scores_gemma":[0.71438545,0.00096903264,0.23764008,0.000067456014,0.000028584118,0.0017125622,0.039871898,0.0011201625,0.0042047505],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995664,0.000070349866,0.00007593494,0.00014272316,0.00010272506,0.000041974185],"domain_scores_gemma":[0.99877614,0.00024029525,0.0004256304,0.00022153086,0.0002739546,0.00006235986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011490784,0.0006195135,0.00028042906,0.0035326416,0.00049627904,0.0010043953,0.00047783292,0.00033209764,0.005146218],"category_scores_gemma":[0.0020611668,0.00031900645,0.00049277995,0.0014488278,0.0004490611,0.0006614638,0.0006955601,0.0004189624,0.0013759598],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018737866,0.00023074796,0.45776078,0.0011718305,0.0004226031,0.0036881808,0.0070618307,0.022534221,0.056363635,0.021064693,0.059956033,0.36787173],"study_design_scores_gemma":[0.00008216816,0.00038117095,0.8158163,0.00028465956,0.00017709164,0.01514938,0.001866188,0.018770196,0.024516294,0.004994795,0.11778193,0.00017986243],"about_ca_topic_score_codex":0.007855358,"about_ca_topic_score_gemma":0.012539776,"teacher_disagreement_score":0.007855358,"about_ca_system_score_codex":0.00091286376,"about_ca_system_score_gemma":0.0011391492,"threshold_uncertainty_score":0.017215788},"labels":[],"label_agreement":null},{"id":"W3006508673","doi":"","title":"PAM50 : multimodal template of the brainstem and spinal cord compatible with the ICBM152 space","year":2017,"lang":"en","type":"preprint","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"","keywords":"Spinal cord; Brainstem; Computer science; Template; Artificial intelligence; Medicine; Pattern recognition (psychology)","score_opus":0.041770262395684946,"score_gpt":0.31750391863496125,"score_spread":0.2757336562392763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006508673","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05953659,0.0018617209,0.7921126,0.0026197538,0.0009516787,0.0007767839,0.027758233,0.033568233,0.08081443],"genre_scores_gemma":[0.33243227,0.0010848135,0.6001344,0.0020937289,0.00043474263,0.0011531923,0.025475502,0.008685451,0.028505895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998412,0.000031714862,0.000011147391,0.000032529995,0.000046994835,0.000036298243],"domain_scores_gemma":[0.99978036,0.00004561,0.000012048849,0.00005252788,0.000051051746,0.00005841039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051282585,0.0006659209,0.00027842674,0.0006694401,0.00032021216,0.0012425972,0.0005733291,0.0014662644,0.041816954],"category_scores_gemma":[0.001821393,0.00034012555,0.00034389962,0.00052884495,0.00023910345,0.0008177598,0.0013372061,0.00061657216,0.009290909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002191524,0.00012968462,0.0034142786,0.0008804116,0.00013915476,0.0020910024,0.00048626654,0.009247746,0.17541438,0.01356051,0.27853465,0.5139103],"study_design_scores_gemma":[0.00027112005,0.0005294263,0.031509027,0.0004980515,0.00018906158,0.010953744,0.00036712846,0.11091801,0.22679786,0.027296193,0.59040076,0.0002696649],"about_ca_topic_score_codex":0.0018323333,"about_ca_topic_score_gemma":0.004104675,"teacher_disagreement_score":0.041816954,"about_ca_system_score_codex":0.00029452212,"about_ca_system_score_gemma":0.0010946707,"threshold_uncertainty_score":0.13989162},"labels":[],"label_agreement":null},{"id":"W3007025644","doi":"10.1109/embc44109.2020.9176229","title":"Rapid Quantification of White Matter Disconnection in the Human Brain","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften","keywords":"Disconnection; White matter; Diffusion MRI; Hyperintensity; Tractography; Neuroscience; Population; Cognition; Psychology; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.14886587824039635,"score_gpt":0.3980968119004431,"score_spread":0.24923093366004676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007025644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5329608,0.00061755656,0.4591286,0.00028139036,0.000037329766,0.00009292544,0.0015442413,0.0037776178,0.0015595533],"genre_scores_gemma":[0.85055643,0.00041815732,0.14616902,0.000042572025,0.000018150276,0.000079995836,0.0013721446,0.00031766057,0.0010257616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998814,0.000027917866,0.0000066216776,0.000033469794,0.000041506122,0.000009109297],"domain_scores_gemma":[0.9996717,0.00016642794,0.00005539464,0.00005221632,0.000030157524,0.000024069712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003010968,0.0006079762,0.00027253033,0.0007785725,0.00016627803,0.00039719947,0.00029041574,0.0004420187,0.001444837],"category_scores_gemma":[0.0017212459,0.00026540458,0.0002589446,0.00037868755,0.00025965337,0.00043226665,0.0005480183,0.00030398025,0.00028770807],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000612559,0.00018438685,0.020931873,0.0004987363,0.00036158823,0.0009013369,0.00066797534,0.61742914,0.17560895,0.008120233,0.004842447,0.1698408],"study_design_scores_gemma":[0.00003489623,0.00017888103,0.020737201,0.000023932145,0.000034414305,0.0010249318,0.000076432625,0.9399986,0.027296463,0.008555772,0.0020047324,0.000033792956],"about_ca_topic_score_codex":0.002600244,"about_ca_topic_score_gemma":0.003752291,"teacher_disagreement_score":0.002600244,"about_ca_system_score_codex":0.00024266464,"about_ca_system_score_gemma":0.00032404513,"threshold_uncertainty_score":0.005170226},"labels":[],"label_agreement":null},{"id":"W3007327257","doi":"10.3389/fninf.2020.00007","title":"A Standardized Protocol for Efficient and Reliable Quality Control of Brain Registration in Functional MRI Studies","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Jewish General Hospital; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Protocol (science); Reliability (semiconductor); Computer science; Consistency (knowledge bases); Kappa; Quality (philosophy); Medical physics; Inter-rater reliability; Artificial intelligence; Data mining; Medicine; Statistics; Rating scale; Pathology; Mathematics","score_opus":0.11857537595006894,"score_gpt":0.4060679210469642,"score_spread":0.28749254509689526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007327257","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017970847,0.0015732336,0.88692456,0.0012758691,0.0014131544,0.06826826,0.0036704927,0.009052683,0.009850897],"genre_scores_gemma":[0.03211415,0.0011090412,0.796571,0.001228625,0.0005141991,0.1552884,0.004323259,0.003537831,0.0053134765],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9680343,0.01726077,0.0057079876,0.003175023,0.004832888,0.0009889724],"domain_scores_gemma":[0.91014016,0.027911872,0.0046288962,0.02207567,0.033792496,0.0014508752],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0708971,0.0021176322,0.0021884711,0.0038803013,0.0028341543,0.0029535987,0.0028329394,0.003268835,0.032208946],"category_scores_gemma":[0.09285445,0.0017708644,0.0018960887,0.0025391357,0.0029499878,0.0023733974,0.003098978,0.0048055067,0.017805016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006658427,0.0024355873,0.008732536,0.010839041,0.00054523384,0.003894183,0.010850559,0.0062704794,0.20187546,0.027218992,0.25593162,0.46474788],"study_design_scores_gemma":[0.0023369892,0.004573862,0.053934015,0.0067282217,0.0008457898,0.0067606424,0.0022648738,0.030693084,0.11420872,0.03405313,0.7423135,0.0012872333],"about_ca_topic_score_codex":0.0011244622,"about_ca_topic_score_gemma":0.002463404,"teacher_disagreement_score":0.9291029,"about_ca_system_score_codex":0.0014150322,"about_ca_system_score_gemma":0.007733635,"threshold_uncertainty_score":0.3749442},"labels":[],"label_agreement":null},{"id":"W3007568584","doi":"10.3233/adr-190149","title":"Identification of Superficial White Matter Abnormalities in Alzheimer’s Disease and Mild Cognitive Impairment Using Diffusion Tensor Imaging","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; University of Toronto; National Institute on Aging; National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Diffusion MRI; White matter; Cognitive impairment; Medicine; Identification (biology); Cognition; Disease; Psychology; Neuroscience; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.062459267255215146,"score_gpt":0.34403485168776377,"score_spread":0.2815755844325486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007568584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99839145,0.00034976777,0.0007167805,0.000028326165,0.0000035295893,0.00002910515,0.000118709206,0.000010410452,0.00035179753],"genre_scores_gemma":[0.99769694,0.00017978196,0.001725465,0.000014583665,0.000009923405,0.00002249085,0.0002310415,0.0000026580262,0.00011709317],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981385,0.000040967047,0.0000360619,0.00004015284,0.000046453195,0.000022499507],"domain_scores_gemma":[0.9993467,0.00010207161,0.00030345813,0.000047503574,0.00008866182,0.00011170897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009841227,0.00049204234,0.0003331838,0.0022449284,0.00025948387,0.0005683819,0.00021482342,0.00027791728,0.0009748552],"category_scores_gemma":[0.0018431197,0.0001672649,0.00031884195,0.0005922263,0.0004084105,0.00046436707,0.0005222164,0.00024182763,0.00017068081],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012563248,0.00016455883,0.9424954,0.00014755885,0.00032053192,0.0007393917,0.0004924784,0.000313431,0.016451547,0.00016151271,0.00028496387,0.03717234],"study_design_scores_gemma":[0.000018557274,0.0001654659,0.99682814,0.000013873156,0.00004690333,0.0010539467,0.00012493666,0.0006101072,0.00072744826,0.00024953127,0.00015434934,0.0000067563824],"about_ca_topic_score_codex":0.0025735619,"about_ca_topic_score_gemma":0.0046350583,"teacher_disagreement_score":0.0025735619,"about_ca_system_score_codex":0.00025973708,"about_ca_system_score_gemma":0.00032218514,"threshold_uncertainty_score":0.0052045584},"labels":[],"label_agreement":null},{"id":"W3008115946","doi":"10.1016/j.neuroimage.2020.116675","title":"Diffusion tensor imaging of the corpus callosum in healthy aging: Investigating higher order polynomial regression modelling","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Women and Children’s Health Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Corpus callosum; White matter; Fractional anisotropy; Linear regression; Mathematics; Polynomial; Regression; Voxel; Statistics; Psychology; Medicine; Neuroscience; Magnetic resonance imaging; Artificial intelligence; Computer science; Mathematical analysis; Radiology","score_opus":0.10637217483648236,"score_gpt":0.3423117426563857,"score_spread":0.23593956781990333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008115946","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91806,0.0014712833,0.07878358,0.00028874577,0.000019989728,0.000056299883,0.00036567159,0.00017261459,0.0007816923],"genre_scores_gemma":[0.9831548,0.0005432678,0.015595403,0.000021743728,0.000011929612,0.000027915508,0.00018542515,0.000041704603,0.00041780024],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994759,0.00023717644,0.000032214262,0.00014737902,0.000059509777,0.000047963873],"domain_scores_gemma":[0.99630594,0.0022839676,0.0006665501,0.00038114112,0.00027305953,0.000089369096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041526794,0.00091177324,0.00056112214,0.00094757794,0.0002689922,0.0008858433,0.00050164433,0.00062246155,0.00089863135],"category_scores_gemma":[0.015211233,0.0002353101,0.00082477916,0.0008115437,0.00056538294,0.0012105134,0.00045766984,0.0006019977,0.00023049506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021345834,0.00031543864,0.39029512,0.0012958514,0.0012201775,0.0014956053,0.0050408035,0.2949911,0.066545025,0.015113508,0.0014832123,0.22006966],"study_design_scores_gemma":[0.000033454846,0.00058965303,0.2999164,0.000109028406,0.00034766662,0.0013752927,0.0005146752,0.66640115,0.008902582,0.019042557,0.0026444048,0.00012310572],"about_ca_topic_score_codex":0.015860656,"about_ca_topic_score_gemma":0.018056847,"teacher_disagreement_score":0.015860656,"about_ca_system_score_codex":0.0006295285,"about_ca_system_score_gemma":0.0011138215,"threshold_uncertainty_score":0.03153664},"labels":[],"label_agreement":null},{"id":"W3009055550","doi":"10.1101/2020.03.04.962191","title":"Increased Sensitivity and Signal-to-Noise Ratio in Diffusion-Weighted MRI using Multi-Echo Acquisitions","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère de l'Enseignement Supérieur et de la Recherche; Max-Planck-Gesellschaft; Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur et de la Recherche Scientifique; Deutsche Forschungsgemeinschaft","keywords":"Computer science; SIGNAL (programming language); Signal-to-noise ratio (imaging); Noise (video); Diffusion MRI; Monte Carlo method; Image quality; Echo (communications protocol); Sensitivity (control systems); Algorithm; Artificial intelligence; Encoding (memory); Contrast (vision); Pattern recognition (psychology); Computer vision; Mathematics; Image (mathematics); Magnetic resonance imaging; Statistics; Radiology; Telecommunications; Medicine","score_opus":0.044631809135098,"score_gpt":0.2969208412061476,"score_spread":0.2522890320710496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009055550","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10015673,0.001782472,0.89455545,0.0002739875,0.00007552764,0.00005751245,0.00007640016,0.00097001845,0.002051912],"genre_scores_gemma":[0.39852023,0.0013416354,0.59760463,0.00013706491,0.00007335584,0.00012338955,0.00012927143,0.00034795605,0.0017224556],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990728,0.00041998472,0.000043737415,0.00021068091,0.00021460051,0.00003822435],"domain_scores_gemma":[0.99822015,0.0012264687,0.00016480936,0.00018359374,0.0001614499,0.00004342805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017428319,0.0007696251,0.0006558629,0.0005287958,0.0002017505,0.0009440307,0.0006078989,0.0011940411,0.001478682],"category_scores_gemma":[0.005808422,0.0004959539,0.00038560602,0.00045444566,0.0005691468,0.001037741,0.0010410949,0.0008421827,0.0007381204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005491336,0.00010572937,0.0027378695,0.000673547,0.00018852434,0.0007988193,0.00027470008,0.057999436,0.7852302,0.0100453915,0.000840438,0.14055619],"study_design_scores_gemma":[0.0000659315,0.0006880758,0.008244174,0.000105707884,0.0001783721,0.003248489,0.000068671514,0.37246317,0.592312,0.01186204,0.010631955,0.00013137354],"about_ca_topic_score_codex":0.00027423704,"about_ca_topic_score_gemma":0.00052281254,"teacher_disagreement_score":0.0017428319,"about_ca_system_score_codex":0.00024532856,"about_ca_system_score_gemma":0.00026341382,"threshold_uncertainty_score":0.009217024},"labels":[],"label_agreement":null},{"id":"W3009380668","doi":"10.1007/s11682-019-00252-y","title":"Default mode network integrity changes contribute to cognitive deficits in subcortical vascular cognitive impairment, no dementia","year":2020,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Beijing Municipal Science and Technology Commission; National Natural Science Foundation of China","keywords":"Fractional anisotropy; White matter; Default mode network; Diffusion MRI; Psychology; Dementia; Executive dysfunction; Cognition; Montreal Cognitive Assessment; Neuropsychology; Neuroimaging; Vascular dementia; Neuroscience; Audiology; Medicine; Internal medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.05279933910206276,"score_gpt":0.36083473142062916,"score_spread":0.3080353923185664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009380668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996539,0.0005446241,0.0004674761,0.00010763219,0.000011145617,0.000017410775,0.00021136277,0.000016874104,0.0020845477],"genre_scores_gemma":[0.9987614,0.00016391111,0.00036600887,0.000026653895,0.000018246508,0.000007710953,0.000115304545,0.000003024039,0.00053767406],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987626,0.000022195842,0.00001884432,0.000034221855,0.000026555572,0.000021861963],"domain_scores_gemma":[0.9992945,0.00012856573,0.0003459922,0.00006212042,0.00007797712,0.00009081063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005291475,0.0006333306,0.00038758214,0.0014114442,0.00052876153,0.0009315405,0.0005541537,0.00050841016,0.002626535],"category_scores_gemma":[0.0020250846,0.00028266775,0.00023039774,0.00059584563,0.000619533,0.00083907286,0.0005907571,0.00050886057,0.000181402],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005338582,0.0007373762,0.9043623,0.0002980679,0.00062039885,0.0059776227,0.00091608556,0.001004386,0.024910333,0.0019286112,0.0011154284,0.05279084],"study_design_scores_gemma":[0.00002520164,0.0001930598,0.9898407,0.000021101909,0.000117864256,0.003472335,0.00024300534,0.0010277525,0.0009854574,0.0038099515,0.00025225745,0.000011307885],"about_ca_topic_score_codex":0.0050756983,"about_ca_topic_score_gemma":0.009694971,"teacher_disagreement_score":0.0050756983,"about_ca_system_score_codex":0.00048809435,"about_ca_system_score_gemma":0.00032736734,"threshold_uncertainty_score":0.010092318},"labels":[],"label_agreement":null},{"id":"W3009440750","doi":"10.1016/j.pscychresns.2020.111060","title":"Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Schizophrenia (object-oriented programming); Psychology; Voxel; Psychosis; Medicine; Neuroscience; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.1562425113989862,"score_gpt":0.4235886478819125,"score_spread":0.26734613648292627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009440750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999678,0.000045361983,0.000015334563,0.000014701425,0.0000021055373,0.0000014271038,0.0000771392,0.0000012445759,0.00016472112],"genre_scores_gemma":[0.9995907,0.000029082417,0.000023347127,0.000011169091,0.000003935964,0.0000019556346,0.000135152,0.0000013249205,0.00020344733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988675,0.000018505181,0.000017284094,0.000027720549,0.000013979984,0.000035722573],"domain_scores_gemma":[0.9993511,0.00019654614,0.00020152722,0.00004314952,0.00005400397,0.00015370881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029232973,0.00035386052,0.0002869274,0.0009138558,0.00049022917,0.0005078546,0.00016646537,0.0004177964,0.0026318168],"category_scores_gemma":[0.001392837,0.00022103946,0.00023194832,0.00040218665,0.00040735502,0.0003481081,0.00042396437,0.00038868142,0.00026613942],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002248175,0.00015815072,0.98979735,0.000014157212,0.00012617945,0.00045132896,0.00060447387,0.00007411937,0.004227434,0.00011252169,0.00008884592,0.0020972467],"study_design_scores_gemma":[0.000013801717,0.00011025932,0.99899083,0.0000015690495,0.000018599023,0.00021442519,0.000335274,0.00010293406,0.00008281196,0.00008627037,0.00004028342,0.0000030917004],"about_ca_topic_score_codex":0.01252145,"about_ca_topic_score_gemma":0.010194572,"teacher_disagreement_score":0.01252145,"about_ca_system_score_codex":0.00038378098,"about_ca_system_score_gemma":0.00027477907,"threshold_uncertainty_score":0.024897099},"labels":[],"label_agreement":null},{"id":"W3010843466","doi":"10.1101/2020.03.17.994574","title":"Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Shanghai Jiao Tong University; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Precuneus; Mnemonic; Superior longitudinal fasciculus; Psychology; Arcuate fasciculus; Neuroscience; Inferior longitudinal fasciculus; Diffusion MRI; Cognitive psychology; Functional magnetic resonance imaging; Metacognition; Fractional anisotropy; Cognition; Human Connectome Project; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.08139070351100748,"score_gpt":0.2942308151786235,"score_spread":0.21284011166761602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010843466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994968,0.00022513996,0.0041867224,0.000046664743,0.0000021061599,0.0000059535287,0.0000733141,0.000016573784,0.00047538202],"genre_scores_gemma":[0.99877137,0.000047061505,0.0010467726,0.000004006653,0.0000019512868,0.000003847113,0.00002779127,0.0000017215842,0.00009544039],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999498,0.000012851434,0.000003409925,0.000018564311,0.0000067660326,0.000008524867],"domain_scores_gemma":[0.99962735,0.00008573453,0.0001892373,0.000044979144,0.00002127779,0.000031291605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018332586,0.00014652514,0.00009916824,0.00037739426,0.000108331726,0.00023319433,0.00008983443,0.00014522597,0.00072363246],"category_scores_gemma":[0.000874002,0.00010783474,0.00006427625,0.00018597025,0.00040823902,0.00029238575,0.00020912502,0.00017427043,0.00004289718],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009937829,0.00009961651,0.2012296,0.00017076418,0.00017026658,0.00050360546,0.00093262404,0.0036867321,0.7349971,0.002633554,0.0003092178,0.05427316],"study_design_scores_gemma":[0.000023244966,0.000120730976,0.9551501,0.00001842307,0.000037779268,0.0005991132,0.00014888422,0.008842274,0.030939335,0.0034976872,0.0006036705,0.00001859452],"about_ca_topic_score_codex":0.0023381694,"about_ca_topic_score_gemma":0.0034962394,"teacher_disagreement_score":0.0023381694,"about_ca_system_score_codex":0.00016566114,"about_ca_system_score_gemma":0.00012982974,"threshold_uncertainty_score":0.0046491027},"labels":[],"label_agreement":null},{"id":"W3010895829","doi":"10.1017/s1355617720000223","title":"Microstructure of the Corpus Callosum Long after Pediatric Concussion","year":2020,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Université de Moncton; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Splenium; Corpus callosum; Fractional anisotropy; Diffusion MRI; Concussion; White matter; Psychology; Medicine; Physical therapy; Magnetic resonance imaging; Poison control; Neuroscience; Radiology; Injury prevention","score_opus":0.04375649190366941,"score_gpt":0.3331737599436393,"score_spread":0.28941726803996987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010895829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887854,0.00067075464,0.00009239189,0.00003046282,0.0000044277617,0.000007759781,0.00012560097,0.0000051016323,0.00018491238],"genre_scores_gemma":[0.99901295,0.00033242392,0.00020013256,0.0000123263935,0.0000063609214,0.000010814019,0.00021693957,0.0000026895177,0.00020539424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997675,0.00003211089,0.000014282944,0.000062666004,0.00006639802,0.00005707236],"domain_scores_gemma":[0.99860424,0.00010840116,0.0007629342,0.000049192942,0.00028630262,0.00018897423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052085874,0.00023619458,0.00027867028,0.0005704399,0.00041184868,0.000507565,0.0002869167,0.00038110494,0.0007173028],"category_scores_gemma":[0.0019243667,0.00011554049,0.00019694169,0.00039853647,0.00038983327,0.00051591836,0.0004140705,0.00044626452,0.00016429224],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062707794,0.000119660304,0.95603263,0.00013080267,0.00012056154,0.0011590892,0.0010399697,0.000220308,0.020104643,0.00008866071,0.00029145737,0.020065237],"study_design_scores_gemma":[0.0000014241729,0.00017657764,0.99802834,0.00001592298,0.000013982481,0.0003958719,0.00022408825,0.0000337734,0.00091389904,0.000012617045,0.00018102003,0.0000023365556],"about_ca_topic_score_codex":0.0084705725,"about_ca_topic_score_gemma":0.013186822,"teacher_disagreement_score":0.0084705725,"about_ca_system_score_codex":0.0005826128,"about_ca_system_score_gemma":0.00054763583,"threshold_uncertainty_score":0.016842544},"labels":[],"label_agreement":null},{"id":"W3010953972","doi":"10.1523/eneuro.0290-19.2020","title":"Resting State BOLD Variability of the Posterior Medial Temporal Lobe Correlates with Cognitive Performance in Older Adults with and without Risk for Cognitive Decline","year":2020,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Montreal Cognitive Assessment; Cognition; Temporal lobe; Psychology; Cognitive decline; Effects of sleep deprivation on cognitive performance; Parahippocampal gyrus; Audiology; Entorhinal cortex; Frontal lobe; Neuroscience; Dementia; Hippocampus; Internal medicine; Medicine; Disease; Cognitive impairment","score_opus":0.02380971415525295,"score_gpt":0.298112807450058,"score_spread":0.27430309329480507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010953972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996991,0.00003959144,0.000056667835,0.000008024579,9.856569e-7,0.0000015205619,0.00007350944,0.0000025389375,0.00011811537],"genre_scores_gemma":[0.9997708,0.000016303848,0.000044483982,0.000005177665,0.00000361061,0.0000020010625,0.00008191874,6.880568e-7,0.00007501688],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994576,0.000009938207,0.000007327876,0.000017640867,0.000009844967,0.000009527466],"domain_scores_gemma":[0.9996408,0.00008003815,0.00015323298,0.000028146456,0.00003750322,0.000060191913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021371673,0.00020025753,0.00018397569,0.00035987847,0.00013311363,0.00025915404,0.000099838784,0.00025919086,0.0008638416],"category_scores_gemma":[0.0009872735,0.00011006952,0.00012713466,0.0001974102,0.00014488449,0.00018078125,0.00015469565,0.00019880384,0.000104523446],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010437301,0.000087849694,0.98296976,0.000017104678,0.00012451108,0.00018773199,0.00023431501,0.00013686778,0.011444328,0.00003633635,0.00010506373,0.0036122499],"study_design_scores_gemma":[0.0000035156088,0.000083812825,0.99942446,6.4261945e-7,0.00000983385,0.00012351414,0.000027191934,0.0001350024,0.00015029986,0.00002405307,0.00001661753,0.0000011040631],"about_ca_topic_score_codex":0.0014085056,"about_ca_topic_score_gemma":0.0022046817,"teacher_disagreement_score":0.0014085056,"about_ca_system_score_codex":0.00007514731,"about_ca_system_score_gemma":0.000056245597,"threshold_uncertainty_score":0.0028898716},"labels":[],"label_agreement":null},{"id":"W3011265095","doi":"10.1007/s00429-020-02056-z","title":"The role of diffusion tractography in refining glial tumor resection","year":2020,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; White matter; Diffusion MRI; Magnetic resonance imaging; Computer science; Neuronavigation; Surgical planning; Diffusion imaging; Imaging phantom; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.03682589367444844,"score_gpt":0.33722179382944417,"score_spread":0.30039590015499573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011265095","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006492999,0.9991646,0.00022023363,0.00017270171,0.00006871899,0.0000020452874,0.000010922122,0.0000042691245,0.00029166814],"genre_scores_gemma":[0.00068016385,0.9983724,0.00045674277,0.00014252469,0.00016459636,0.0000036547679,0.00002389113,0.0000025673141,0.00015351392],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974173,0.000053027255,0.000046330744,0.00006213755,0.00007502614,0.000021624803],"domain_scores_gemma":[0.9984034,0.0010213152,0.00016831295,0.000034032673,0.00031862757,0.00005436549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001620339,0.0013303832,0.0018274705,0.0032892053,0.0002334635,0.0014092415,0.0010345574,0.0013590299,0.0025730943],"category_scores_gemma":[0.0026758169,0.00039003286,0.00081117655,0.003017688,0.0010754982,0.0016595458,0.00076655607,0.002005215,0.0013789212],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007440404,0.000033511362,0.0003394151,0.013035864,0.000185751,0.00015888551,0.000033342603,0.00052346085,0.0009945215,0.0021975145,0.010206005,0.9722172],"study_design_scores_gemma":[0.0000895785,0.00025032938,0.0047291946,0.015644178,0.0011989026,0.0037324217,0.00015132563,0.0008734513,0.002081034,0.0077353725,0.96340287,0.00011132118],"about_ca_topic_score_codex":0.003708546,"about_ca_topic_score_gemma":0.006394032,"teacher_disagreement_score":0.003708546,"about_ca_system_score_codex":0.0009048057,"about_ca_system_score_gemma":0.0022845664,"threshold_uncertainty_score":0.008607864},"labels":[],"label_agreement":null},{"id":"W3011339117","doi":"10.1101/2020.03.11.987925","title":"Myelin water imaging depends on white matter fiber orientation in the human brain","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Canadian Institutes of Health Research; Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Multiple Sclerosis Society","keywords":"White matter; Diffusion MRI; Voxel; Nuclear magnetic resonance; Orientation (vector space); Magnetic resonance imaging; Myelin; Chemistry; Physics; Neuroscience; Psychology; Mathematics; Medicine; Artificial intelligence; Central nervous system; Computer science; Radiology; Geometry","score_opus":0.0336502951825454,"score_gpt":0.3011239643473336,"score_spread":0.26747366916478815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011339117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97791994,0.0017958571,0.018978272,0.0000760331,0.000013131311,0.000011726237,0.000099567,0.000085401574,0.0010200565],"genre_scores_gemma":[0.9931298,0.0010562356,0.00517852,0.000022379825,0.000013543392,0.0000058798937,0.00009704495,0.00004581334,0.0004507925],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985516,0.000040075618,0.000008240515,0.000046342677,0.000035886023,0.000014281254],"domain_scores_gemma":[0.9995128,0.0002008378,0.00016108893,0.00005059403,0.000055490837,0.000019139865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005256948,0.00029696332,0.0001741457,0.0004295304,0.00010942758,0.00037967617,0.000089223664,0.00029273133,0.0006829131],"category_scores_gemma":[0.0025876039,0.000175561,0.0001079717,0.00031959458,0.00041450496,0.0005704299,0.00017188069,0.00015238949,0.00030135355],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071910274,0.0000384388,0.04024375,0.00015171673,0.00008192202,0.00027878163,0.0003952718,0.0023951354,0.88624644,0.0006689001,0.00023032287,0.06855025],"study_design_scores_gemma":[0.00002543634,0.00048447042,0.5743332,0.000046948935,0.00015766913,0.0022915795,0.0003227524,0.01452438,0.40108553,0.0045288354,0.0021361797,0.00006297416],"about_ca_topic_score_codex":0.0012736443,"about_ca_topic_score_gemma":0.0013882224,"teacher_disagreement_score":0.0012736443,"about_ca_system_score_codex":0.00011420043,"about_ca_system_score_gemma":0.00018188955,"threshold_uncertainty_score":0.002780199},"labels":[],"label_agreement":null},{"id":"W3013188727","doi":"10.1176/appi.ajp.2019.19030225","title":"The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium","year":2020,"lang":"en","type":"review","venue":"American Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Department of Psychiatry, University of Toronto; University of California, Irvine; National Institutes of Health; Centre for Cognitive Ageing and Cognitive Epidemiology; H. Lundbeck A/S; Servier; Cilag; University of Cape Town; Science Foundation Ireland; Regeneron Pharmaceuticals; Medical Research Council; Gedeon Richter; Biogen; Otsuka America; Campbell Family Mental Health Research Institute; Georgia State University; School of Medicine, University of California, Irvine; University of Toronto; Sunovion; Sanofi; Pfizer","keywords":"Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Cognition; Effects of sleep deprivation on cognitive performance; Psychology; Sample size determination; Psychosis; Medicine; Clinical psychology; Internal medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.05319407554041516,"score_gpt":0.37948415936031904,"score_spread":0.3262900838199039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013188727","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8508611,0.13965824,0.0028720188,0.00075980753,0.0001712603,0.00015299804,0.004362319,0.00007392683,0.0010883253],"genre_scores_gemma":[0.9871011,0.008612321,0.0015653463,0.00018361308,0.000059549984,0.00017064327,0.0020771266,0.000030369185,0.00019993914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99330056,0.0035900942,0.0009059054,0.0013824102,0.00060349074,0.00021737821],"domain_scores_gemma":[0.98883283,0.004725767,0.003310567,0.0014789854,0.0013392507,0.00031258818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013425028,0.001228958,0.002679789,0.0028634504,0.0007133734,0.0019963908,0.00123929,0.0012987142,0.00097600574],"category_scores_gemma":[0.023952344,0.0007830521,0.008220855,0.0040995847,0.000597709,0.00060021307,0.0016911952,0.0008495711,0.00010955767],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011880729,0.00007918004,0.6020279,0.0059453323,0.35501814,0.00037618377,0.0006057069,0.0017960499,0.0020322306,0.00041333318,0.0013983801,0.01842683],"study_design_scores_gemma":[0.0016043766,0.0006280041,0.7280222,0.0013799749,0.26222092,0.00063020474,0.00031179402,0.0010422673,0.0008507825,0.00077130256,0.0024328334,0.00010530291],"about_ca_topic_score_codex":0.012119804,"about_ca_topic_score_gemma":0.01416797,"teacher_disagreement_score":0.013425028,"about_ca_system_score_codex":0.0009361249,"about_ca_system_score_gemma":0.0009831777,"threshold_uncertainty_score":0.070999146},"labels":[],"label_agreement":null},{"id":"W3013503384","doi":"10.1016/j.bpsc.2020.03.003","title":"In Vivo Imaging of Gray Matter Microstructure in Major Psychiatric Disorders: Opportunities for Clinical Translation","year":2020,"lang":"en","type":"review","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Canon Medical Systems USA; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression; Radiological Society of North America","keywords":"Gray (unit); Translation (biology); Psychiatry; Medicine; Psychology; Radiology; Chemistry","score_opus":0.26774318085976523,"score_gpt":0.45915613417016954,"score_spread":0.1914129533104043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013503384","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008488026,0.9988397,0.00017432701,0.00038530972,0.000093616065,0.0000033036301,0.000015934267,0.000004299666,0.00039864707],"genre_scores_gemma":[0.0007474238,0.998027,0.00044952365,0.0003295702,0.00025062577,0.0000071392687,0.000025586096,0.0000016206295,0.00016146239],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998173,0.00004577007,0.000023250199,0.000040790354,0.000053517117,0.000019358027],"domain_scores_gemma":[0.9986957,0.0008201753,0.000104342274,0.000038451108,0.00027968854,0.00006173945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017399456,0.00091533334,0.001862915,0.0017213861,0.00017284014,0.001555385,0.0010580719,0.0015197557,0.0028366796],"category_scores_gemma":[0.0021215817,0.00028087912,0.00059403334,0.0017285034,0.0009902791,0.0016347411,0.00081116107,0.0021348097,0.0013103792],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015862258,0.000085464366,0.00043839807,0.011260611,0.00015090889,0.00015634949,0.000040783754,0.00031569914,0.0017658229,0.004400262,0.015094942,0.9661321],"study_design_scores_gemma":[0.00013893475,0.00039122833,0.0062295785,0.017397158,0.00064455724,0.0024648672,0.00021806246,0.0005252146,0.0013830754,0.019821705,0.95068955,0.0000961087],"about_ca_topic_score_codex":0.0018557354,"about_ca_topic_score_gemma":0.0037921476,"teacher_disagreement_score":0.0028366796,"about_ca_system_score_codex":0.0007276249,"about_ca_system_score_gemma":0.002095504,"threshold_uncertainty_score":0.009489596},"labels":[],"label_agreement":null},{"id":"W3013886781","doi":"10.1002/hbm.24964","title":"Impact of <i>b</i> ‐value on estimates of apparent fibre density","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Wolfson Foundation; Engineering and Physical Sciences Research Council; International Society for Magnetic Resonance in Medicine; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Deconvolution; Robustness (evolution); Population; White matter; Magnetic resonance imaging; Statistics; Sampling (signal processing); Mathematics; Nuclear magnetic resonance; Nuclear medicine; Physics; Chemistry; Optics; Medicine; Radiology","score_opus":0.13521282274823745,"score_gpt":0.3948600916401611,"score_spread":0.2596472688919237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013886781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92160296,0.0004243126,0.07587097,0.00022578226,0.000034421497,0.00005407623,0.00018811188,0.00044293818,0.0011565372],"genre_scores_gemma":[0.9826376,0.000049840684,0.016991444,0.000040987663,0.0000028918992,0.000022133549,0.000081650636,0.000087209664,0.00008618879],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99728775,0.001755011,0.0001679177,0.00034206535,0.00034310692,0.00010420133],"domain_scores_gemma":[0.97125566,0.022866048,0.001710915,0.0022207901,0.0015832961,0.00036328763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009036085,0.00055634923,0.00041938375,0.0005223321,0.00046844842,0.00072036247,0.000855904,0.0007457415,0.0006675727],"category_scores_gemma":[0.047595654,0.0003708231,0.00037710206,0.0003632258,0.0007042439,0.00085991074,0.0008878443,0.0005616805,0.00018798608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037393763,0.00035735505,0.21863915,0.0008402251,0.0011344369,0.00061101036,0.0014509378,0.4865743,0.15345968,0.0049334946,0.0015290264,0.126731],"study_design_scores_gemma":[0.00012131382,0.00090618536,0.11046067,0.00021433971,0.0002844037,0.0007100972,0.0002834906,0.79849315,0.082757145,0.0042707818,0.0013284987,0.00016991732],"about_ca_topic_score_codex":0.0064550103,"about_ca_topic_score_gemma":0.004938461,"teacher_disagreement_score":0.009036085,"about_ca_system_score_codex":0.0006087581,"about_ca_system_score_gemma":0.0006134897,"threshold_uncertainty_score":0.047787905},"labels":[],"label_agreement":null},{"id":"W3014870269","doi":"10.1089/neu.2019.6886","title":"White Matter Abnormalities in Retired Professional Rugby League Players with a History of Concussion","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Concussion; Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Psychology; Corticospinal tract; Medicine; Physical therapy; Poison control; Physical medicine and rehabilitation; Magnetic resonance imaging; Injury prevention; Neuroscience; Radiology","score_opus":0.12353809413654963,"score_gpt":0.34481904821830844,"score_spread":0.2212809540817588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014870269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998305,0.00006403767,0.000010179591,0.000006706141,9.977337e-7,0.000002147399,0.000017605338,5.453507e-7,0.00006739548],"genre_scores_gemma":[0.9996871,0.000053916567,0.000026444894,0.000012661902,0.0000037572206,0.0000029880646,0.000058733985,4.224254e-7,0.00015397194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986196,0.00002427473,0.000014702279,0.000038915703,0.00002759421,0.000032476983],"domain_scores_gemma":[0.99958116,0.00005582714,0.0001798678,0.000026264355,0.000060789873,0.00009614902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024577478,0.0002824792,0.00026478787,0.00095848535,0.00046173044,0.00045770145,0.00030996176,0.0004968482,0.0011690937],"category_scores_gemma":[0.0012333725,0.00018892334,0.00013514707,0.00044496512,0.00043359966,0.00024238531,0.00035499857,0.00020164992,0.00022458054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028660704,0.000108120585,0.9917504,0.000020962409,0.000035590718,0.0015000824,0.00075248,0.000031301322,0.0022884423,0.000014248546,0.00008433161,0.0031273945],"study_design_scores_gemma":[0.0000023664002,0.00010037155,0.99872965,0.00000209695,0.0000051089437,0.00083171634,0.00021127924,0.000027502045,0.000038885537,0.000003734263,0.00004613621,0.0000011202393],"about_ca_topic_score_codex":0.018030353,"about_ca_topic_score_gemma":0.024095189,"teacher_disagreement_score":0.018030353,"about_ca_system_score_codex":0.0003475487,"about_ca_system_score_gemma":0.00020997759,"threshold_uncertainty_score":0.035850823},"labels":[],"label_agreement":null},{"id":"W3014906913","doi":"10.1089/neu.2020.6992","title":"White Matter Changes Caused by Mild Traumatic Brain Injury in Mice Evaluated Using Neurite Orientation Dispersion and Density Imaging","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto; Hospital for Sick Children","funders":"","keywords":"White matter; Traumatic brain injury; Fractional anisotropy; Diffusion MRI; Glial fibrillary acidic protein; Neuroscience; Pathology; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.14982499954835007,"score_gpt":0.399856576614741,"score_spread":0.2500315770663909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014906913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9815435,0.0020539642,0.009359567,0.00033955945,0.00011909113,0.00016239466,0.003356452,0.000497223,0.002568325],"genre_scores_gemma":[0.9481161,0.0047752853,0.022654044,0.00045369033,0.000062526466,0.0010558186,0.0044263382,0.00027218758,0.018183999],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99963427,0.000028314646,0.000056616787,0.00011270293,0.000086678265,0.00008151916],"domain_scores_gemma":[0.9995803,0.000017943545,0.0001899904,0.000033387485,0.000063933294,0.00011437095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039088566,0.0013497646,0.0005027839,0.002173156,0.0005513363,0.0005287557,0.00045171048,0.0011044414,0.0021808892],"category_scores_gemma":[0.00016497403,0.0005153946,0.0007612326,0.0005991066,0.0007444889,0.0006202517,0.00048982725,0.0019226759,0.00067314913],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043039804,0.00024238629,0.0010036429,0.000125925,0.000028506249,0.00013047757,0.00010532431,0.000114411465,0.99520326,0.00016603914,0.00011558956,0.0023340927],"study_design_scores_gemma":[0.00010125328,0.002717521,0.031404626,0.000076702425,0.00018183213,0.0007571666,0.00024782168,0.0028745339,0.9565384,0.00043630743,0.004620107,0.000043768036],"about_ca_topic_score_codex":0.0020420377,"about_ca_topic_score_gemma":0.0032025352,"teacher_disagreement_score":0.0021808892,"about_ca_system_score_codex":0.0004779306,"about_ca_system_score_gemma":0.0003789273,"threshold_uncertainty_score":0.007295847},"labels":[],"label_agreement":null},{"id":"W3015297905","doi":"10.1002/mrm.28268","title":"MAPL1:<i>q</i>‐space reconstruction using ‐regularized mean apparent propagator","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; National Institute of Mental Health","keywords":"Undersampling; Mathematics; Basis (linear algebra); Basis function; Diffusion MRI; Algorithm; Mathematical analysis; Artificial intelligence; Computer science; Geometry","score_opus":0.09644794645795542,"score_gpt":0.34335743818512676,"score_spread":0.24690949172717136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015297905","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05185814,0.00020726153,0.9418434,0.00048186118,0.000060083865,0.00007145526,0.0003681411,0.0031623722,0.0019472882],"genre_scores_gemma":[0.2942008,0.00023535069,0.70074475,0.00020511897,0.00004840113,0.000202697,0.0007641713,0.001107153,0.0024915482],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99972814,0.00009395427,0.000010418437,0.000047065274,0.000097047414,0.000023398197],"domain_scores_gemma":[0.9988883,0.00047831857,0.00016092764,0.00018570645,0.00021410588,0.000072716895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001376338,0.0008918012,0.00047026217,0.0006141906,0.0003273049,0.00097043446,0.0010428369,0.0012283582,0.0035140908],"category_scores_gemma":[0.004324661,0.00039948281,0.0004883803,0.0005033435,0.0005019727,0.0009717145,0.0010933388,0.00095063983,0.0009729549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010295864,0.00030226848,0.004892707,0.0010280818,0.0002676709,0.0006525491,0.00034321315,0.58948356,0.13030347,0.01709604,0.016041264,0.23855959],"study_design_scores_gemma":[0.000034341494,0.00008150059,0.00060132885,0.000017400735,0.000015664313,0.00019135067,0.000015233656,0.9689334,0.025311545,0.002124003,0.0026468025,0.000027402126],"about_ca_topic_score_codex":0.0017172048,"about_ca_topic_score_gemma":0.0015051134,"teacher_disagreement_score":0.0035140908,"about_ca_system_score_codex":0.00055858295,"about_ca_system_score_gemma":0.0012381993,"threshold_uncertainty_score":0.0117557645},"labels":[],"label_agreement":null},{"id":"W3015883524","doi":"10.3389/fnins.2020.00269","title":"Microstructural Investigations of the Visual Pathways in Pediatric Epilepsy Neurosurgery: Insights From Multi-Shell Diffusion Magnetic Resonance Imaging","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"NIHR Great Ormond Street Hospital Biomedical Research Centre; Medical Research Council Canada; Fight for Sight UK; National Institute for Health and Care Research; Great Ormond Street Institute of Child Health; Medical Research Council","keywords":"Tractography; Optic radiation; Diffusion MRI; Epilepsy surgery; Magnetic resonance imaging; Fractional anisotropy; Medicine; Visual field; White matter; Neurosurgery; Epilepsy; Radiology; Ophthalmology; Psychiatry","score_opus":0.03560498313517041,"score_gpt":0.2768057979748006,"score_spread":0.24120081483963018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015883524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843932,0.0062870244,0.006737133,0.0002851398,0.000011021624,0.000029778428,0.0002857136,0.000044651075,0.0019262601],"genre_scores_gemma":[0.98054343,0.0063026343,0.012566932,0.0000448791,0.000023544082,0.000020091686,0.00013837927,0.000024668221,0.0003354395],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986863,0.00002867984,0.000015502303,0.000028783634,0.00003560024,0.000022775635],"domain_scores_gemma":[0.99928266,0.00015272968,0.00036736365,0.00003572776,0.00010560729,0.000055836128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042963604,0.0003294855,0.00017489669,0.0014126538,0.000152174,0.00043753124,0.00015913192,0.00027523635,0.0007794336],"category_scores_gemma":[0.0011036883,0.00018921646,0.00018503968,0.0005054173,0.0004459943,0.0006845222,0.0003136081,0.0003181927,0.00016662816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037408734,0.00007550047,0.7091898,0.0010118271,0.00016420998,0.012854698,0.0016108181,0.002461628,0.14340524,0.0011856429,0.000909959,0.12675662],"study_design_scores_gemma":[0.000009170505,0.00038789204,0.91127974,0.00021693361,0.00010223693,0.05266156,0.0013108229,0.0027211427,0.025804892,0.0009222101,0.004548709,0.00003471739],"about_ca_topic_score_codex":0.0018727455,"about_ca_topic_score_gemma":0.00438186,"teacher_disagreement_score":0.0018727455,"about_ca_system_score_codex":0.00027482572,"about_ca_system_score_gemma":0.00039401872,"threshold_uncertainty_score":0.0037236214},"labels":[],"label_agreement":null},{"id":"W3015921769","doi":"10.1101/2020.04.07.20057166","title":"Orbitofrontal-striatal structural alterations linked to negative symptoms at different stages of the schizophrenia spectrum","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"McGill University","keywords":"Apathy; Schizotypy; Anhedonia; Orbitofrontal cortex; Schizophrenia (object-oriented programming); Psychosis; Psychology; Ventral striatum; Striatum; Antipsychotic; Pathological; Cohort; Psychiatry; Medicine; Internal medicine; Neuroscience; Prefrontal cortex; Dopamine; Cognition","score_opus":0.0464635915880752,"score_gpt":0.3273896492387321,"score_spread":0.2809260576506569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015921769","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998099,0.000029501181,0.00002966504,0.0000046488,3.7743953e-7,0.0000013874206,0.00004336256,0.0000013336244,0.00007983502],"genre_scores_gemma":[0.99973553,0.000024001862,0.000065367516,0.000004423926,5.710614e-7,0.000001869824,0.00008856421,0.0000012112324,0.00007838306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995625,0.0000059019153,0.0000042412066,0.000011491693,0.000008905876,0.000013160335],"domain_scores_gemma":[0.99980074,0.00002083953,0.00010459759,0.000014362919,0.000017993878,0.000041430914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013636492,0.00026799107,0.00015042275,0.00079903024,0.00025431154,0.00025911425,0.0001182215,0.00022374168,0.0012753208],"category_scores_gemma":[0.0002635811,0.00015938385,0.00014366876,0.00023865113,0.00030573868,0.00011305625,0.0003510358,0.00019992901,0.0000797834],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018112367,0.00006977743,0.78015983,0.000041806914,0.00011842067,0.001290591,0.0008000282,0.00022819283,0.20972574,0.00013409456,0.00011861259,0.0055016424],"study_design_scores_gemma":[0.0000047603953,0.0000473628,0.9985702,0.000002209904,0.0000074001728,0.00043900055,0.00008286745,0.00005419943,0.00073994393,0.000022294797,0.000028264389,0.0000015403168],"about_ca_topic_score_codex":0.005234035,"about_ca_topic_score_gemma":0.008199198,"teacher_disagreement_score":0.005234035,"about_ca_system_score_codex":0.00022467929,"about_ca_system_score_gemma":0.00013056869,"threshold_uncertainty_score":0.01040715},"labels":[],"label_agreement":null},{"id":"W3016018540","doi":"10.1101/2020.04.07.029850","title":"Diffusion MRI of the Unfolded Hippocampus","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Hippocampus; Diffusion MRI; Neuroscience; Hippocampal formation; Tractography; Computer science; Artificial intelligence; Magnetic resonance imaging; Biology; Medicine; Radiology","score_opus":0.03553262599891273,"score_gpt":0.2779900029114306,"score_spread":0.2424573769125179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016018540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52126265,0.0010113678,0.47242948,0.0005990008,0.00008183681,0.00004890298,0.00055069325,0.00053330447,0.0034828258],"genre_scores_gemma":[0.7983622,0.0008912848,0.19735588,0.00009623309,0.000039021765,0.000024662902,0.000351215,0.000114590875,0.0027649314],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999604,0.000009607938,0.0000027958026,0.000012288622,0.0000108515,0.0000040391656],"domain_scores_gemma":[0.99986005,0.000048008584,0.000025139027,0.000022595397,0.000023103521,0.000021058617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019653182,0.00024674283,0.00014513794,0.00037587012,0.00013182359,0.0003742078,0.00016870198,0.00035671535,0.0010662813],"category_scores_gemma":[0.0006574146,0.00021737732,0.0001368534,0.00025241886,0.00034605907,0.00042643523,0.00045405916,0.0002988492,0.00024982446],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024576037,0.00003228043,0.0023647733,0.0002179165,0.00007501532,0.0015760697,0.0002730167,0.100704975,0.83711517,0.015044773,0.0011394045,0.04121077],"study_design_scores_gemma":[0.000090947826,0.0005432243,0.018496662,0.00009314633,0.00009061667,0.006642882,0.0002773145,0.56952965,0.33307362,0.053453404,0.017592398,0.00011612885],"about_ca_topic_score_codex":0.0007046923,"about_ca_topic_score_gemma":0.0008299446,"teacher_disagreement_score":0.0010662813,"about_ca_system_score_codex":0.00015045016,"about_ca_system_score_gemma":0.00020520871,"threshold_uncertainty_score":0.00356704},"labels":[],"label_agreement":null},{"id":"W3016428943","doi":"10.1016/j.media.2021.101988","title":"Magic DIAMOND: Multi-fascicle diffusion compartment imaging with tensor distribution modeling and tensor-valued diffusion encoding","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Diffusion MRI; Voxel; Tractography; Tensor (intrinsic definition); Computer science; Fascicle; Algorithm; Artificial intelligence; Mathematics; Statistical physics; Physics; Geometry; Geology; Magnetic resonance imaging","score_opus":0.03966792182640934,"score_gpt":0.34059918555620194,"score_spread":0.3009312637297926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016428943","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003473894,0.00027555268,0.99204844,0.00024723902,0.000047781374,0.000039158494,0.00031288416,0.0028868902,0.00066808285],"genre_scores_gemma":[0.04273577,0.0005361879,0.95227224,0.00014540646,0.00004024183,0.00014907558,0.00056716317,0.0014523136,0.0021016505],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977535,0.00007136354,0.000016871705,0.000035141762,0.000084754545,0.000016446047],"domain_scores_gemma":[0.9991159,0.00043052647,0.00008875833,0.0001526266,0.00012523176,0.00008710271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012444764,0.0010979647,0.0007558791,0.0006277469,0.00036839803,0.0019800938,0.0016996654,0.0018262845,0.005177443],"category_scores_gemma":[0.0036171938,0.000766849,0.0005646777,0.000879947,0.0003872278,0.0018743086,0.0015616042,0.0017455053,0.0019703873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017456037,0.00024101291,0.0012322139,0.0013604685,0.0004704829,0.0014265531,0.00036421692,0.14188074,0.13306202,0.06794391,0.049397614,0.6008752],"study_design_scores_gemma":[0.000139949,0.00014056911,0.0003214399,0.000068930494,0.000065163316,0.0013269017,0.000041077612,0.89269763,0.051686622,0.02821965,0.025201624,0.000090460475],"about_ca_topic_score_codex":0.0012985243,"about_ca_topic_score_gemma":0.001981437,"teacher_disagreement_score":0.005177443,"about_ca_system_score_codex":0.00030242885,"about_ca_system_score_gemma":0.0011646065,"threshold_uncertainty_score":0.017320275},"labels":[],"label_agreement":null},{"id":"W3016720595","doi":"10.1371/journal.pone.0231669","title":"Neurological soft signs (NSS) and brain morphology in patients with chronic schizophrenia and healthy controls","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Parahippocampal gyrus; Schizophrenia (object-oriented programming); Motor coordination; Medicine; Cerebellum; Thalamus; Magnetic resonance imaging; Neuroscience; Neurological examination; Sensory system; Neuroimaging; Psychology; Audiology; Temporal lobe; Psychiatry; Radiology","score_opus":0.06185096783244322,"score_gpt":0.2826069056056145,"score_spread":0.22075593777317132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016720595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997378,0.000055853514,0.0000098946275,0.000005637074,0.0000010665387,0.0000038057506,0.00008032902,0.0000014846252,0.000104102895],"genre_scores_gemma":[0.9995472,0.000060649818,0.00002933989,0.000008228744,0.0000029125683,0.000008920717,0.00026185246,9.893283e-7,0.00007991168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997938,0.00002702017,0.000035996003,0.0000624496,0.000036055888,0.000044586304],"domain_scores_gemma":[0.9995216,0.000067281806,0.00019258914,0.000024620935,0.000038632712,0.00015531006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027345587,0.00053612434,0.00039001857,0.0015119826,0.0005625257,0.00053936086,0.00016618498,0.0004688538,0.0015531043],"category_scores_gemma":[0.0009824468,0.0002748514,0.00023967201,0.00061491865,0.0005322975,0.00031863502,0.00064558984,0.00023038014,0.00019405913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014682253,0.00011572802,0.991126,0.00003248002,0.00009122018,0.00074989896,0.00049276854,0.000050587678,0.0032739406,0.0000406309,0.00007438872,0.0024840527],"study_design_scores_gemma":[0.000017837032,0.0001563054,0.9990715,0.0000034876232,0.000012952829,0.00040407784,0.00020377748,0.00004035466,0.000036260655,0.000015356332,0.000035100413,0.0000029833557],"about_ca_topic_score_codex":0.010456009,"about_ca_topic_score_gemma":0.009044996,"teacher_disagreement_score":0.010456009,"about_ca_system_score_codex":0.00054251554,"about_ca_system_score_gemma":0.00032360273,"threshold_uncertainty_score":0.020790279},"labels":[],"label_agreement":null},{"id":"W3016882932","doi":"10.3233/jad-200022","title":"Plasma Neurofilament Light and Longitudinal Progression of White Matter Hyperintensity in Elderly Persons Without Dementia","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Hyperintensity; Dementia; Neurofilament; White matter; Medicine; Longitudinal study; Psychology; Gerontology; Neuroscience; Internal medicine; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.06558397709974662,"score_gpt":0.3395510494010985,"score_spread":0.27396707230135187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016882932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99967873,0.00010425978,0.00003963419,0.000009497864,0.0000021673268,0.0000028119498,0.000060262206,0.0000018593388,0.00010078036],"genre_scores_gemma":[0.9995813,0.0000453804,0.000073541734,0.0000117339,0.0000036389363,0.000003241983,0.00009906839,6.3897386e-7,0.00018131502],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.000027149517,0.00001417281,0.000027154643,0.000019147521,0.000019722575],"domain_scores_gemma":[0.9993881,0.00010651809,0.0002788974,0.000042699758,0.00008713873,0.00009666366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004893454,0.0002455066,0.00024241167,0.00048372248,0.00030178338,0.00033850715,0.0001725375,0.00037274926,0.0006868044],"category_scores_gemma":[0.0016434721,0.00023290544,0.00019181042,0.00028772617,0.0001257877,0.00033741456,0.00023117186,0.00043625353,0.0001686193],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044333164,0.00010570733,0.99712735,0.0000072924217,0.000043334938,0.000052754436,0.00007600211,0.000036386868,0.00055430515,0.000007988722,0.000032212392,0.0015134428],"study_design_scores_gemma":[0.000010389282,0.00028011535,0.9991053,0.0000037192053,0.000023734085,0.00011562553,0.00007355335,0.00018717148,0.00011950119,0.000022899849,0.000055966517,0.0000019854742],"about_ca_topic_score_codex":0.002732257,"about_ca_topic_score_gemma":0.003843177,"teacher_disagreement_score":0.002732257,"about_ca_system_score_codex":0.0001297425,"about_ca_system_score_gemma":0.000121395366,"threshold_uncertainty_score":0.005432725},"labels":[],"label_agreement":null},{"id":"W3017144256","doi":"10.1002/brb3.1609","title":"Reliability of multimodal MRI brain measures in youth at risk for mental illness","year":2020,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Canadian Institutes of Health Research; Dalhousie University; Nova Scotia Health Research Foundation; Brain and Behavior Research Foundation; Canada Research Chairs; Fondation Brain Canada; Dalhousie Medical Research Foundation","keywords":"Mental illness; Reliability (semiconductor); Psychology; Neuroimaging; Mental health; Psychiatry; Medicine; Reliability engineering; Physical medicine and rehabilitation; Engineering","score_opus":0.07004747563812988,"score_gpt":0.3552865085876501,"score_spread":0.28523903294952024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017144256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992113,0.0001397104,0.0003636058,0.000019762854,0.00000388769,0.000009204053,0.0000728683,0.00000857019,0.0001710552],"genre_scores_gemma":[0.9992348,0.000052450374,0.00048061225,0.0000073948086,0.0000049347595,0.000013847876,0.00014953325,0.0000040796676,0.000052360912],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861777,0.0005553945,0.00016551433,0.0002738973,0.00027226208,0.000115229814],"domain_scores_gemma":[0.9941287,0.0018347049,0.0020859032,0.000496878,0.0012501224,0.00020364237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043901536,0.00044657712,0.0003785751,0.0010943073,0.0003770325,0.00057770615,0.00044521972,0.000451681,0.00059191085],"category_scores_gemma":[0.012981366,0.0003046592,0.00038463954,0.00043748703,0.00053112855,0.00034622606,0.0008649213,0.00047758973,0.00016268986],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015476142,0.00002802067,0.99047333,0.000027840682,0.00010818679,0.00007095773,0.0007370648,0.00015408137,0.0013458825,0.000024042412,0.00011126762,0.0067646066],"study_design_scores_gemma":[0.0000033384545,0.00012126037,0.99844295,0.00001116146,0.000032055505,0.00016878337,0.000244244,0.0004134576,0.00043895174,0.00002562206,0.00009370766,0.0000045757724],"about_ca_topic_score_codex":0.003151529,"about_ca_topic_score_gemma":0.0057134195,"teacher_disagreement_score":0.0043901536,"about_ca_system_score_codex":0.00030648988,"about_ca_system_score_gemma":0.00024470294,"threshold_uncertainty_score":0.023217618},"labels":[],"label_agreement":null},{"id":"W3017967689","doi":"10.1038/s41598-020-63965-x","title":"An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"CIHR Skin Research Training Centre; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Health Canada; Canadian Open Neuroscience Platform; Government of Canada; Fondation Brain Canada","keywords":"Atlas (anatomy); Brain atlas; Coefficient of variation; Standard deviation; Nuclear medicine; Medicine; Computer science; Anatomy; Artificial intelligence; Statistics; Mathematics","score_opus":0.05158695924931106,"score_gpt":0.3329099153176824,"score_spread":0.2813229560683713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017967689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.091288686,0.0017136662,0.84676516,0.0005242695,0.0004517775,0.0013540515,0.023085449,0.006077296,0.028739573],"genre_scores_gemma":[0.1118423,0.0036084992,0.820351,0.00031448912,0.0000976477,0.0025904584,0.017855745,0.0016917696,0.041648086],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963903,0.000041828254,0.000026124431,0.00007146113,0.0001818372,0.00003971661],"domain_scores_gemma":[0.99964166,0.00004022679,0.000058981714,0.00007975334,0.00013715228,0.000042176816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007000734,0.0008281932,0.0004735315,0.003199238,0.00088719017,0.00078901596,0.0010422042,0.0006989724,0.010661918],"category_scores_gemma":[0.0004237971,0.00047469293,0.00056020514,0.0014975058,0.0005751065,0.0006176561,0.0008278555,0.0011520765,0.00451527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042639708,0.00020647353,0.0025201372,0.00080965506,0.00009869742,0.0010576956,0.0008021603,0.0046275235,0.74925685,0.018702257,0.032404784,0.18908733],"study_design_scores_gemma":[0.00013138034,0.0013655421,0.058854967,0.00037422168,0.00038174776,0.011250063,0.00046026363,0.017838879,0.27989548,0.0144147035,0.61462504,0.00040774574],"about_ca_topic_score_codex":0.0038128223,"about_ca_topic_score_gemma":0.017031405,"teacher_disagreement_score":0.010661918,"about_ca_system_score_codex":0.0008031371,"about_ca_system_score_gemma":0.0020827972,"threshold_uncertainty_score":0.035667717},"labels":[],"label_agreement":null},{"id":"W3018190643","doi":"10.1016/j.nicl.2020.102266","title":"Cingulum-Callosal white-matter microstructure associated with emotional dysregulation in children: A diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Massachusetts Institute of Technology; Canadian Institutes of Health Research; DuPont; Massachusetts General Hospital; Brain and Behavior Research Foundation","keywords":"Fractional anisotropy; Emotional dysregulation; Cingulum (brain); White matter; Diffusion MRI; Psychology; Anxiety; Mood disorders; Mood; Corpus callosum; Neuroimaging; Clinical psychology; Psychiatry; Magnetic resonance imaging; Medicine; Neuroscience","score_opus":0.053075270726928955,"score_gpt":0.3621189217190611,"score_spread":0.30904365099213216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018190643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965096,0.000055557077,0.00009085134,0.000015949447,0.0000015601618,0.0000046459513,0.00008390868,0.0000024890428,0.000094040864],"genre_scores_gemma":[0.9991635,0.00009715999,0.00046240998,0.000015015583,0.000004396172,0.000014021151,0.00015609546,0.0000053127515,0.00008202449],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997155,0.000042546853,0.000034169723,0.00008488552,0.00006557744,0.00005731473],"domain_scores_gemma":[0.99925953,0.00007882674,0.00042369103,0.000052216797,0.00008872691,0.00009690152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047092448,0.00052579254,0.00028108753,0.0011510453,0.0003893304,0.0005555951,0.00023716921,0.00035525553,0.0007744701],"category_scores_gemma":[0.0018318178,0.00035338858,0.00034754703,0.00081735436,0.0004994044,0.00033721566,0.0004542421,0.0003839312,0.00011978313],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010726925,0.00005746617,0.98871887,0.000026532522,0.00006410986,0.0009726054,0.0008302341,0.00010664377,0.005847343,0.000094864416,0.0001324645,0.00304159],"study_design_scores_gemma":[0.0000027866595,0.00004066452,0.9984378,0.000005237759,0.000018498255,0.0008641726,0.00017697772,0.00008800591,0.0002693381,0.000015123096,0.00007872362,0.0000027166266],"about_ca_topic_score_codex":0.009241029,"about_ca_topic_score_gemma":0.012420755,"teacher_disagreement_score":0.009241029,"about_ca_system_score_codex":0.00045454464,"about_ca_system_score_gemma":0.00056165055,"threshold_uncertainty_score":0.018374443},"labels":[],"label_agreement":null},{"id":"W3018777018","doi":"10.1016/j.maturitas.2020.04.012","title":"Prospective associations between physical activity levels and white matter integrity in older adults: results from the MAPT study","year":2020,"lang":"en","type":"article","venue":"Maturitas","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre Hospitalier Universitaire de Toulouse; Agence Nationale de la Recherche; Les Laboratories Pierre Fabre","keywords":"Medicine; Gerontology; Physical activity; Prospective cohort study; White matter; Internal medicine; Physical therapy; Magnetic resonance imaging","score_opus":0.07486253772604844,"score_gpt":0.35638171580147754,"score_spread":0.2815191780754291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018777018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998887,0.00015264445,0.000063676365,0.000042202777,0.0000066735015,0.000006925942,0.0006068562,0.0000026395483,0.00023137027],"genre_scores_gemma":[0.9985378,0.0001423573,0.00013019313,0.000033571385,0.000017411758,0.00001778958,0.00070696295,0.0000040599743,0.00040982108],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996872,0.000081595965,0.0000377606,0.00009604659,0.00005400642,0.000043384494],"domain_scores_gemma":[0.9992143,0.000085773674,0.00030556737,0.00011074435,0.0001131934,0.00017043205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007012011,0.0004974133,0.0005062435,0.0005854456,0.00060259475,0.00097003375,0.00047238928,0.00071771676,0.0010850002],"category_scores_gemma":[0.0018458747,0.00061452907,0.000683209,0.0011813206,0.00027820756,0.0007603847,0.00088367803,0.0008003402,0.00032255548],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038560273,0.00012242509,0.99721694,0.000014381101,0.00035204948,0.00008566069,0.00023780277,0.00003446769,0.00039655404,0.000022720651,0.00015573668,0.00097566243],"study_design_scores_gemma":[0.000006695506,0.000053393167,0.99959284,0.0000018803931,0.00006362201,0.000043576696,0.00009270297,0.00003704349,0.000020994243,0.000013297215,0.0000718781,0.0000021550939],"about_ca_topic_score_codex":0.009957146,"about_ca_topic_score_gemma":0.014689092,"teacher_disagreement_score":0.009957146,"about_ca_system_score_codex":0.00022062045,"about_ca_system_score_gemma":0.000179085,"threshold_uncertainty_score":0.019798338},"labels":[],"label_agreement":null},{"id":"W3019621902","doi":"10.3171/2020.2.jns193177","title":"Dissecting the default mode network: direct structural evidence on the morphology and axonal connectivity of the fifth component of the cingulum bundle","year":2020,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Cingulum (brain); Default mode network; Precuneus; Neuroscience; Medicine; Anatomy; Functional connectivity; White matter; Magnetic resonance imaging; Biology; Functional magnetic resonance imaging; Fractional anisotropy; Radiology","score_opus":0.12761878272212182,"score_gpt":0.34515009010465486,"score_spread":0.21753130738253304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019621902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965591,0.00048356564,0.0023917528,0.000016219316,0.0000032147382,0.0000066329912,0.00004086898,0.000012885716,0.00048572687],"genre_scores_gemma":[0.9971328,0.00018958052,0.002392956,0.0000076155216,0.0000033463443,0.000008796589,0.000055540615,0.0000029238818,0.00020636864],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995565,0.000004464533,0.0000035363869,0.000017119624,0.000008984728,0.000010285708],"domain_scores_gemma":[0.9999018,0.000020684376,0.00003282676,0.000014579572,0.000016570635,0.000013664967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001440008,0.0001566371,0.00006477343,0.00048889755,0.00020127918,0.00012875076,0.00012238203,0.00015033271,0.000862353],"category_scores_gemma":[0.00023921087,0.00009420481,0.000080281156,0.00014115538,0.00036733612,0.00019857234,0.00018249759,0.00010378571,0.000121066136],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031027241,0.00003400198,0.07876647,0.000110684334,0.000046365363,0.0012242261,0.00053836184,0.00017498505,0.88309747,0.0005875318,0.000095964126,0.035013728],"study_design_scores_gemma":[0.000036057718,0.0007659602,0.8767766,0.000039245082,0.00008947209,0.0076569403,0.0005041161,0.0015860607,0.109500244,0.00081899983,0.0022097921,0.000016582871],"about_ca_topic_score_codex":0.0011005726,"about_ca_topic_score_gemma":0.002169512,"teacher_disagreement_score":0.0011005726,"about_ca_system_score_codex":0.000109237844,"about_ca_system_score_gemma":0.00014492829,"threshold_uncertainty_score":0.0028848648},"labels":[],"label_agreement":null},{"id":"W3020957360","doi":"10.1101/2020.05.01.064576","title":"Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"National Institutes of Health","keywords":"Semantic dementia; Frontotemporal lobar degeneration; Frontotemporal dementia; Primary progressive aphasia; White matter; Atrophy; Psychology; Neuroscience; Neuroimaging; Dementia; Diffusion MRI; Voxel-based morphometry; Cognitive decline; Cognition; Voxel; Pathology; Executive dysfunction; Disease; Medicine; Neuropsychology; Magnetic resonance imaging; Radiology","score_opus":0.05855679745492247,"score_gpt":0.3123917869707199,"score_spread":0.2538349895157974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3020957360","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99949133,0.00014813562,0.00004174545,0.000010452967,0.0000020787897,0.0000020520217,0.000063893895,0.000002099999,0.00023817403],"genre_scores_gemma":[0.99981314,0.00002085084,0.000042104435,0.0000044104595,0.0000013026581,0.0000011102555,0.000047505353,8.436621e-7,0.00006874255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998155,0.00005013072,0.000022114102,0.000045674195,0.000033889617,0.00003272319],"domain_scores_gemma":[0.9992663,0.00020599451,0.00024160308,0.000070114176,0.00008366588,0.00013234603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006503267,0.00037115096,0.00022116172,0.0007236276,0.00039987735,0.00046071105,0.0001748135,0.00032473294,0.0013465988],"category_scores_gemma":[0.0020179756,0.00011563661,0.00032276928,0.0002409195,0.00037398134,0.00031245314,0.0003898539,0.00023855876,0.00012023388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054242145,0.00023229972,0.95557916,0.00009477367,0.00043883247,0.0014578324,0.0005427774,0.00039374933,0.018268747,0.00009270732,0.0001484828,0.017326478],"study_design_scores_gemma":[0.0000054573775,0.00021085823,0.998292,0.000007684402,0.000059253256,0.0004292918,0.00011200294,0.00019653399,0.00055017567,0.0000775443,0.0000558756,0.000003248026],"about_ca_topic_score_codex":0.007001345,"about_ca_topic_score_gemma":0.00936376,"teacher_disagreement_score":0.007001345,"about_ca_system_score_codex":0.00037305977,"about_ca_system_score_gemma":0.0002200163,"threshold_uncertainty_score":0.013921201},"labels":[],"label_agreement":null},{"id":"W3020977526","doi":"10.1101/2020.01.08.899583","title":"A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Human brain; Tractography; Cortex (anatomy); Human Connectome Project; Cerebral cortex; Neuroimaging; Dynamics (music); Computational model; Nerve net","score_opus":0.03424715446565342,"score_gpt":0.26647884742329186,"score_spread":0.23223169295763846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3020977526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6297755,0.0012415508,0.35634604,0.0013148318,0.000042889318,0.000038956096,0.0012988047,0.00088550185,0.009055958],"genre_scores_gemma":[0.97666454,0.00031240412,0.02164852,0.00004902727,0.000013221522,0.000027140757,0.00021380397,0.00004568994,0.0010256058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985635,0.000049922415,0.000004126785,0.000059893187,0.000020394076,0.00000920327],"domain_scores_gemma":[0.99981445,0.00005760432,0.000046654426,0.000044529217,0.000020058644,0.000016824337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024175983,0.000257347,0.00016526892,0.00043343724,0.00020483066,0.0010224374,0.0002177476,0.00036967456,0.0021730256],"category_scores_gemma":[0.0014112049,0.00018544133,0.00022516181,0.00033629953,0.0010680987,0.0006607059,0.0005096411,0.00025060883,0.0003026189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047483496,0.00008110498,0.062819704,0.00031207773,0.00035740618,0.0007725833,0.00226715,0.35797268,0.09040147,0.2309812,0.0129779205,0.24058184],"study_design_scores_gemma":[0.000042797135,0.00019097519,0.12825826,0.00008424191,0.00009358226,0.0013272928,0.00053369213,0.44240904,0.011512973,0.40057123,0.014888414,0.0000875563],"about_ca_topic_score_codex":0.0043186108,"about_ca_topic_score_gemma":0.003249129,"teacher_disagreement_score":0.0043186108,"about_ca_system_score_codex":0.00036714584,"about_ca_system_score_gemma":0.000347061,"threshold_uncertainty_score":0.008587003},"labels":[],"label_agreement":null},{"id":"W3021621901","doi":"10.3389/fpsyt.2020.00342","title":"Age-Related Changes of Peak Width Skeletonized Mean Diffusivity (PSMD) Across the Adult Lifespan: A Multi-Cohort Study","year":2020,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Hospital for Sick Children; University of Toronto","funders":"Medical Research Council; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; Bundesministerium für Bildung und Forschung; National Health and Medical Research Council; European Commission; Fondation Leducq; Agence Nationale de la Recherche; Canadian Institutes of Health Research; EU Joint Programme – Neurodegenerative Disease Research","keywords":"Cohort; Demography; Gerontology; Medicine; Psychology; Internal medicine; Sociology","score_opus":0.0323848196296587,"score_gpt":0.3353835566800775,"score_spread":0.3029987370504188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021621901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99754107,0.0004721174,0.00052296696,0.000021978363,0.000008664384,0.000016225562,0.0012191555,0.000009851151,0.00018800121],"genre_scores_gemma":[0.99720484,0.00031235558,0.0006863986,0.000027892673,0.0000149469115,0.000035643337,0.0012917432,0.00001667482,0.00040957468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994153,0.00006958237,0.00006725168,0.0003307549,0.000059146332,0.00005809928],"domain_scores_gemma":[0.9986528,0.00012009653,0.00034719333,0.000400862,0.00032969037,0.00014944488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017068384,0.0004619272,0.0005379135,0.00083892496,0.00065187615,0.00078984455,0.0003883298,0.00046244706,0.00080332806],"category_scores_gemma":[0.002073948,0.00036610742,0.00067958346,0.00077749864,0.00022291207,0.00054474885,0.0008691227,0.00058251846,0.00023613423],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007260031,0.00006256444,0.98793703,0.00004167467,0.0008520082,0.00032263465,0.0007154885,0.00017148566,0.002805765,0.000091700764,0.00050143444,0.005772128],"study_design_scores_gemma":[0.000008351255,0.0001083031,0.9985128,0.000011567467,0.00022041156,0.00026235246,0.00013661265,0.0001546289,0.00014966565,0.000043891567,0.00038300324,0.000008355095],"about_ca_topic_score_codex":0.00988063,"about_ca_topic_score_gemma":0.010691815,"teacher_disagreement_score":0.00988063,"about_ca_system_score_codex":0.00026341682,"about_ca_system_score_gemma":0.00028012338,"threshold_uncertainty_score":0.019646227},"labels":[],"label_agreement":null},{"id":"W3021820897","doi":"10.1016/j.neuroimage.2020.116884","title":"Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Horizon 2020; Horizon 2020 Framework Programme; Engineering and Physical Sciences Research Council; Institut de Valorisation des Données; Spinal Research; Department of Health and Aged Care, Australian Government; Multiple Sclerosis Society; Fonds Wetenschappelijk Onderzoek; Department of Health and Social Care; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; National Multiple Sclerosis Society; Craig H. Neilsen Foundation; Natural Sciences and Engineering Research Council of Canada; Wings for Life; ASCRS Research Foundation","keywords":"Noise reduction; Singular value decomposition; Computer science; Parametric statistics; SIGNAL (programming language); Noise (video); Artificial intelligence; Pattern recognition (psychology); Image quality; Computer vision; Mathematics; Image (mathematics)","score_opus":0.1312747457715866,"score_gpt":0.3881293509769566,"score_spread":0.25685460520537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021820897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054625116,0.0002888457,0.94338346,0.00012594294,0.000023593557,0.00006343307,0.00015054332,0.0007299324,0.0006090635],"genre_scores_gemma":[0.25679472,0.00046557098,0.74074256,0.00012307872,0.000032014574,0.0003597038,0.0004315999,0.0003275623,0.0007231161],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99942136,0.00014071346,0.000044222597,0.00013434107,0.00021406513,0.000045264653],"domain_scores_gemma":[0.9990876,0.00030160273,0.0001591487,0.00021158971,0.00018704684,0.000053123607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018200513,0.00089122524,0.00077059126,0.00052623724,0.00024194176,0.0007903456,0.00085361814,0.001127283,0.00095691736],"category_scores_gemma":[0.0036285128,0.00047767215,0.0005885844,0.0006840377,0.00085024437,0.0009674988,0.001134799,0.0012534561,0.0004344733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035431763,0.00014661532,0.0012124708,0.00047537766,0.00014624889,0.0003121619,0.00023769891,0.049621165,0.87717015,0.005432645,0.00086670596,0.06402441],"study_design_scores_gemma":[0.00003618213,0.0005075599,0.004968003,0.00005663533,0.00010630352,0.0012913704,0.000054511707,0.48086056,0.502773,0.005303902,0.003928071,0.00011381951],"about_ca_topic_score_codex":0.0005162105,"about_ca_topic_score_gemma":0.0007589886,"teacher_disagreement_score":0.0018200513,"about_ca_system_score_codex":0.00028349983,"about_ca_system_score_gemma":0.00055606157,"threshold_uncertainty_score":0.0096254945},"labels":[],"label_agreement":null},{"id":"W3022230549","doi":"10.1111/gbb.12656","title":"Genetic risk for Alzheimer disease in children: Evidence from early‐life IQ and brain white‐matter microstructure","year":2020,"lang":"en","type":"article","venue":"Genes Brain & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Health, British Columbia; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Erasmus Medisch Centrum; Erasmus Universiteit Rotterdam; ZonMw; Agence Nationale de la Recherche; Health Research","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Intelligence quotient; Medicine; Internal medicine; Physiology; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.051463965432771715,"score_gpt":0.3338814669371,"score_spread":0.2824175015043283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022230549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963953,0.0020729476,0.00027513868,0.00021024956,0.000012982156,0.0000052703667,0.00032976648,0.000010704566,0.00068764837],"genre_scores_gemma":[0.998206,0.0009517442,0.00030035342,0.000058253267,0.000022207189,0.000007962091,0.00029558744,0.000006298052,0.00015153385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989311,0.00033821317,0.000098824814,0.0003156633,0.00023373582,0.00008240131],"domain_scores_gemma":[0.99541867,0.0013660827,0.0021889447,0.00039275002,0.0002956162,0.00033793767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016837552,0.0007849909,0.00044103907,0.0011521818,0.00037301655,0.0007239301,0.00069033186,0.0008546322,0.0012978801],"category_scores_gemma":[0.0062428913,0.00041749462,0.0009251636,0.0010741118,0.00094477297,0.00037820736,0.00070265774,0.00072098605,0.00016301704],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014502306,0.000027616203,0.9959842,0.000024161822,0.00035154255,0.00026570415,0.00016109194,0.00013035836,0.0003074683,0.00009505758,0.0001090456,0.002398762],"study_design_scores_gemma":[0.0000054975585,0.000051140825,0.9990951,0.000017598513,0.00010526974,0.00029931185,0.000049735154,0.00012032023,0.00007312421,0.000063621694,0.000115357805,0.0000038798044],"about_ca_topic_score_codex":0.013217168,"about_ca_topic_score_gemma":0.0071330126,"teacher_disagreement_score":0.013217168,"about_ca_system_score_codex":0.00029760614,"about_ca_system_score_gemma":0.0003486729,"threshold_uncertainty_score":0.026280522},"labels":[],"label_agreement":null},{"id":"W3022546824","doi":"10.1038/s41386-020-0691-2","title":"Multiparametric mapping of white matter microstructure in catatonia","year":2020,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"Catatonia; Fractional anisotropy; White matter; Psychology; Diffusion MRI; Orbitofrontal cortex; Corticospinal tract; Neuroscience; Corpus callosum; Putamen; Schizophrenia (object-oriented programming); Psychiatry; Magnetic resonance imaging; Medicine; Prefrontal cortex; Cognition; Radiology","score_opus":0.05974089286520401,"score_gpt":0.36466737453720777,"score_spread":0.30492648167200376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022546824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99746454,0.0002532388,0.0017613758,0.00008813882,0.0000040020973,0.000008301836,0.000051598403,0.000009654502,0.00035913358],"genre_scores_gemma":[0.99859935,0.00017762677,0.0009669525,0.00001757189,0.0000028989407,0.0000055298055,0.000023449096,0.0000045905513,0.00020197975],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999516,0.000010353416,0.0000055700675,0.000014938778,0.000008987795,0.000008586271],"domain_scores_gemma":[0.99986815,0.000028190496,0.000050088627,0.000019587435,0.00001641005,0.0000175513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023188643,0.0001827912,0.00014867324,0.00051509356,0.00015438414,0.00037036557,0.00017026273,0.0002450536,0.00067826064],"category_scores_gemma":[0.0005829211,0.0001634382,0.00011845768,0.0003335598,0.00027940053,0.0003456705,0.00033345202,0.00033194126,0.000054671695],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002437155,0.0001790853,0.19477941,0.00033096882,0.00042694682,0.0037004745,0.00068591774,0.0029606703,0.68405706,0.002100382,0.00048051472,0.107861355],"study_design_scores_gemma":[0.000042473697,0.0003307289,0.96536446,0.000025021965,0.000094527786,0.0043258234,0.0002898161,0.007173007,0.01894144,0.0027735662,0.00061554735,0.000023549446],"about_ca_topic_score_codex":0.0023871437,"about_ca_topic_score_gemma":0.0038369098,"teacher_disagreement_score":0.0023871437,"about_ca_system_score_codex":0.00030230256,"about_ca_system_score_gemma":0.00023899792,"threshold_uncertainty_score":0.0047465563},"labels":[],"label_agreement":null},{"id":"W3023084566","doi":"10.1016/j.biopsych.2020.02.379","title":"Assessing Intracortical Myelin and Neurocognitive Performance in Substance Use Disorder","year":2020,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Neurocognitive; Myelin; Schizophrenia (object-oriented programming); Neuroscience; Bipolar disorder; Psychology; Biomarker; Magnetic resonance imaging; Medicine; Cognition; Psychiatry; Central nervous system; Biology","score_opus":0.1649639880212219,"score_gpt":0.37374512140220173,"score_spread":0.20878113338097984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023084566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987723,0.00039499378,0.00013448052,0.000031103944,0.000003195915,0.000006051199,0.00003282222,0.0000036769218,0.00062136917],"genre_scores_gemma":[0.99914706,0.00023730789,0.0003235958,0.000020633981,0.0000057676957,0.0000053925864,0.000031388383,0.0000017140375,0.00022724662],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986017,0.00005885289,0.0000151264085,0.000019217532,0.000026519283,0.000020141875],"domain_scores_gemma":[0.99933463,0.0002356397,0.00022447486,0.00002465994,0.00008158072,0.00009896039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051502825,0.0003416336,0.00017443868,0.0006327882,0.000277082,0.00057502865,0.00021936798,0.0003847646,0.00081157126],"category_scores_gemma":[0.0018348667,0.00012107746,0.0001183547,0.00042450262,0.0002953964,0.0003445576,0.00040157596,0.0003959168,0.000116017756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011293298,0.00036058496,0.96216315,0.00005605165,0.00017021135,0.00041498698,0.00030845258,0.00046152782,0.005610695,0.000070490685,0.00010222187,0.029152354],"study_design_scores_gemma":[0.000011852744,0.00043971394,0.996637,0.00001725989,0.0000413561,0.00035674975,0.00032386667,0.0006669697,0.0012225411,0.00016941823,0.000108243024,0.000005037555],"about_ca_topic_score_codex":0.0054321396,"about_ca_topic_score_gemma":0.012638884,"teacher_disagreement_score":0.0054321396,"about_ca_system_score_codex":0.00031947912,"about_ca_system_score_gemma":0.00028716054,"threshold_uncertainty_score":0.010801017},"labels":[],"label_agreement":null},{"id":"W3023831429","doi":"10.1101/2020.05.02.064840","title":"Structural alterations in the macaque frontoparietal white matter network after recovery from prefrontal cortex lesions","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Neuroscience; Lesion; Superior longitudinal fasciculus; Macaque; Prefrontal cortex; Fractional anisotropy; Psychology; Diffusion MRI; Tractography; Uncinate fasciculus; Saccade; Inferior longitudinal fasciculus; Cortex (anatomy); Posterior parietal cortex; Medicine; Magnetic resonance imaging; Cognition; Eye movement; Radiology","score_opus":0.029669665462461164,"score_gpt":0.26724888598683194,"score_spread":0.23757922052437078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023831429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986656,0.00016306814,0.00078765355,0.000038275874,0.000003768122,0.0000049174178,0.00008028757,0.000038733928,0.00021758402],"genre_scores_gemma":[0.99768984,0.00014008253,0.0008639367,0.000021690186,0.0000026073303,0.000013563693,0.0002050528,0.000013465561,0.0010498383],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999504,0.0000032795797,0.0000032351052,0.000015561816,0.000012003104,0.00001545309],"domain_scores_gemma":[0.9998448,0.000015411104,0.00006448996,0.000023524957,0.000025444164,0.00002638301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010023161,0.0002309643,0.00020256007,0.0004139926,0.0001713005,0.00022290974,0.00016066236,0.0002693515,0.001228137],"category_scores_gemma":[0.00025686607,0.00012227971,0.00014183295,0.000115196926,0.0003543041,0.00019034652,0.00016701387,0.00034617292,0.00017171474],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020442721,0.000048479924,0.0033269806,0.000036023477,0.000025304696,0.0004128096,0.00012899408,0.0002510295,0.9896549,0.00007436542,0.000072664436,0.005764067],"study_design_scores_gemma":[0.00004048482,0.0010416318,0.48259908,0.00003562263,0.000092456954,0.0055540316,0.00052763626,0.0053975745,0.50104684,0.00091346086,0.0027222508,0.000028987688],"about_ca_topic_score_codex":0.003822061,"about_ca_topic_score_gemma":0.004709655,"teacher_disagreement_score":0.003822061,"about_ca_system_score_codex":0.00030559706,"about_ca_system_score_gemma":0.00022655813,"threshold_uncertainty_score":0.007599652},"labels":[],"label_agreement":null},{"id":"W3025004389","doi":"10.1038/s41598-020-64124-y","title":"Dissociating the white matter tracts connecting the temporo-parietal cortical region with frontal cortex using diffusion tractography","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Neuroscience; Inferior parietal lobule; White matter; Tractography; Superior longitudinal fasciculus; Macaque; Superior parietal lobule; Anatomy; Premotor cortex; Posterior parietal cortex; Biology; Supramarginal gyrus; Diffusion MRI; Cortex (anatomy); Temporal cortex; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Dorsum; Fractional anisotropy","score_opus":0.05775910657762829,"score_gpt":0.31057148671502416,"score_spread":0.2528123801373959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025004389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70656765,0.0015657053,0.28813574,0.0002113553,0.000030995492,0.00021422042,0.0004390312,0.00019593681,0.0026393072],"genre_scores_gemma":[0.72601503,0.0023672266,0.26844066,0.000069179245,0.00001402619,0.00023456529,0.00065235933,0.00013687841,0.0020700572],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998536,0.00002086708,0.000012929141,0.000053044467,0.000025458077,0.000034048808],"domain_scores_gemma":[0.9997551,0.0000958783,0.000057619854,0.000035523182,0.00002776007,0.000028232209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006034971,0.0006781116,0.0003046586,0.0013234951,0.0005571728,0.0008622552,0.00024368806,0.0005255247,0.0016345808],"category_scores_gemma":[0.0009692961,0.00033436847,0.0003447672,0.0003995327,0.0009369142,0.0006702697,0.00049403595,0.00065698056,0.0004131097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017670686,0.00004547739,0.0034785396,0.00012577277,0.00004956814,0.00023092462,0.00022595462,0.0012692531,0.9688392,0.0020974677,0.00007198304,0.023389256],"study_design_scores_gemma":[0.0001676421,0.0006416311,0.1270828,0.00012307832,0.00021079033,0.004015142,0.0004981759,0.03921813,0.80564934,0.010858263,0.011441748,0.000093203],"about_ca_topic_score_codex":0.0063875094,"about_ca_topic_score_gemma":0.020232253,"teacher_disagreement_score":0.0063875094,"about_ca_system_score_codex":0.0004940828,"about_ca_system_score_gemma":0.0014987905,"threshold_uncertainty_score":0.012700617},"labels":[],"label_agreement":null},{"id":"W3026205139","doi":"10.1016/j.pscychresns.2020.111106","title":"White Matter Connectivity in Youth at Risk for Serious Mental Illness: A Longitudinal Analysis","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Ottawa; University Health Network; University of Toronto; Heart and Stroke Foundation; Sunnybrook Health Science Centre; Alberta Children's Hospital; Health Sciences Centre; Hotchkiss Brain Institute; Mental Health Research Canada; University of Calgary","funders":"National Institute of Mental Health; Fondation Brain Canada","keywords":"Fractional anisotropy; White matter; Fasciculus; Uncinate fasciculus; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Diffusion MRI; Psychology; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.13071774812324316,"score_gpt":0.4199659554645772,"score_spread":0.28924820734133405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026205139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99952865,0.00009617918,0.000045981396,0.000042424006,0.0000034138764,0.000003238061,0.00017143128,0.0000018847768,0.00010674999],"genre_scores_gemma":[0.99912375,0.00011183476,0.00009994037,0.000017996827,0.0000072983657,0.000011433414,0.0003653586,0.0000022881486,0.00026017366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996728,0.00006929087,0.000021192182,0.00008959999,0.00003842158,0.00010875337],"domain_scores_gemma":[0.99886227,0.00010283937,0.00046928975,0.00010292453,0.00017931827,0.00028336592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007948069,0.00036594275,0.00034383536,0.00096251466,0.0011554781,0.00091252505,0.0005616816,0.0008210013,0.0013416781],"category_scores_gemma":[0.0020179593,0.0004955657,0.00073747284,0.001264449,0.00042961782,0.0009784106,0.0010280669,0.0012798638,0.00021087684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013800961,0.00011691529,0.9979109,0.0000048897673,0.00010348208,0.00012408107,0.00024189765,0.00003463704,0.00019619946,0.000040332543,0.00009981867,0.0009888648],"study_design_scores_gemma":[0.0000051280485,0.00009134219,0.99901617,0.0000052888677,0.000051241845,0.00015979171,0.00038703097,0.000115653595,0.000035771413,0.0000399116,0.0000891094,0.0000035527694],"about_ca_topic_score_codex":0.027449988,"about_ca_topic_score_gemma":0.047074657,"teacher_disagreement_score":0.027449988,"about_ca_system_score_codex":0.00063769304,"about_ca_system_score_gemma":0.0010002209,"threshold_uncertainty_score":0.05458045},"labels":[],"label_agreement":null},{"id":"W3026323094","doi":"10.3389/fnagi.2020.00129","title":"Fitness Level Influences White Matter Microstructure in Postmenopausal Women","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"Canada Research Chairs; McMaster University","keywords":"Cingulum (brain); Cardiorespiratory fitness; White matter; Aerobic exercise; Diffusion MRI; Brain Structure and Function; Psychology; Neuroimaging; Transcranial magnetic stimulation; Neuroscience; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Fractional anisotropy; Physical medicine and rehabilitation; Internal medicine; Stimulation","score_opus":0.04494927487757623,"score_gpt":0.31467662526375023,"score_spread":0.269727350386174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026323094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979494,0.0011435702,0.000088073495,0.000064199245,0.0000056936065,0.000007326594,0.00009931972,0.0000033926046,0.0006390603],"genre_scores_gemma":[0.9993456,0.00022451566,0.00005145018,0.000035547633,0.000007301573,0.0000046482633,0.00005047945,0.0000012183397,0.00027921848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999541,0.000009331121,0.0000041144594,0.00001770023,0.000006132626,0.0000086203345],"domain_scores_gemma":[0.9998944,0.000019988425,0.000047388625,0.000008088911,0.000011470902,0.000018622539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013072492,0.00015672376,0.00016079246,0.00023043333,0.00016732408,0.00023879383,0.00007353424,0.00025591126,0.0011631952],"category_scores_gemma":[0.000661946,0.00011033308,0.00011494148,0.00020924529,0.00012981032,0.00012048753,0.0001349987,0.00011059662,0.00016228115],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016266622,0.000102511025,0.96170264,0.00008404822,0.00022996674,0.000562512,0.00066912465,0.00008730368,0.014520693,0.00008002662,0.00029707619,0.020037375],"study_design_scores_gemma":[0.0000037193158,0.00009937855,0.9993818,0.0000045264787,0.000028934712,0.00012972363,0.000064870386,0.000037510526,0.000091919865,0.000035077708,0.00012109689,0.0000013684961],"about_ca_topic_score_codex":0.0029523952,"about_ca_topic_score_gemma":0.005280174,"teacher_disagreement_score":0.0029523952,"about_ca_system_score_codex":0.00008077107,"about_ca_system_score_gemma":0.000081916274,"threshold_uncertainty_score":0.005870402},"labels":[],"label_agreement":null},{"id":"W3026522746","doi":"10.1016/j.neuroimage.2020.116889","title":"TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow &amp; Singularity","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":199,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs","keywords":"Tractography; Pipeline (software); Computer science; Diffusion MRI; Tensor (intrinsic definition); Diffusion; Singularity; Orientation (vector space); Data mining; Artificial intelligence; Algorithm; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.13229725443034684,"score_gpt":0.3335525059408864,"score_spread":0.20125525151053958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026522746","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073080524,0.0003752001,0.7634476,0.0002599473,0.00010225929,0.0002729903,0.004353678,0.22207731,0.0018030166],"genre_scores_gemma":[0.0708574,0.00040345968,0.8677267,0.00029960097,0.000060652106,0.00073419715,0.018129176,0.03738324,0.0044056033],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993175,0.00009128003,0.00009549057,0.00022545083,0.0001994635,0.00007074574],"domain_scores_gemma":[0.9982693,0.0005661486,0.0001668567,0.00047899786,0.00038575317,0.00013289826],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0020172268,0.002158614,0.0012625301,0.0019119814,0.00095135975,0.0026301076,0.0027015603,0.0012703036,0.02069415],"category_scores_gemma":[0.008981277,0.0015037454,0.0016396998,0.0013318628,0.0006970851,0.0025614896,0.003063421,0.001755494,0.011116387],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002045252,0.0001882975,0.005103321,0.0018316935,0.00063769217,0.0011674778,0.0008718559,0.0314057,0.0869673,0.01680606,0.24219595,0.61077946],"study_design_scores_gemma":[0.0005777079,0.0003035272,0.0044287476,0.00019728941,0.00016446713,0.002100163,0.00014320269,0.6446692,0.15397844,0.047084283,0.14592946,0.0004234935],"about_ca_topic_score_codex":0.0046182573,"about_ca_topic_score_gemma":0.006401297,"teacher_disagreement_score":0.9979828,"about_ca_system_score_codex":0.00089682994,"about_ca_system_score_gemma":0.0022578205,"threshold_uncertainty_score":0.06922877},"labels":[],"label_agreement":null},{"id":"W3026648707","doi":"10.1016/j.pscychresns.2020.111105","title":"White Matter Microstructural Properties Associated with Impaired Attention in Chronic Schizophrenia: A Multi-Center Study","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Splenium; Cingulum (brain); Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Medicine; Psychology; Neurocognitive; Audiology; Cardiology; Internal medicine; Neuroscience; Cognition; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.1547307103881278,"score_gpt":0.3952001869922741,"score_spread":0.2404694766041463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026648707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998536,0.000030233974,0.000025221376,0.000008291379,8.904905e-7,0.0000052954974,0.000041522388,7.282521e-7,0.000034163135],"genre_scores_gemma":[0.99966085,0.000043413816,0.00007770841,0.000014178446,0.0000062395548,0.000006951538,0.00012544006,0.0000014175248,0.000063730186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99969447,0.0000713677,0.000033167802,0.00007908081,0.000040876228,0.00008107113],"domain_scores_gemma":[0.99891067,0.00011856564,0.0004534729,0.00010334657,0.000129593,0.00028446162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008372982,0.00079710357,0.00057356985,0.0014399292,0.0016319777,0.0007558611,0.00047868406,0.00060954195,0.0012632759],"category_scores_gemma":[0.0009738007,0.0005508397,0.0005942253,0.0012236737,0.0011570327,0.00087788806,0.0010728785,0.0006093131,0.00022271388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018939117,0.00069290854,0.98455644,0.000035068093,0.0003336562,0.0007885096,0.0011850361,0.00008098615,0.007805751,0.00005722768,0.00012333578,0.0024470305],"study_design_scores_gemma":[0.000035526667,0.00026390087,0.9982324,0.0000040123427,0.00006130173,0.00044801962,0.0006594433,0.000091947244,0.0001291461,0.000026375381,0.00003890419,0.000009022023],"about_ca_topic_score_codex":0.02102718,"about_ca_topic_score_gemma":0.02525916,"teacher_disagreement_score":0.02102718,"about_ca_system_score_codex":0.0011892952,"about_ca_system_score_gemma":0.0009940545,"threshold_uncertainty_score":0.04180956},"labels":[],"label_agreement":null},{"id":"W3026862239","doi":"10.1016/j.compbiomed.2020.103815","title":"Multi-scale segmentation in GBM treatment using diffusion tensor imaging","year":2020,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institute for Health and Care Research; NIHR Imperial Biomedical Research Centre; University of Cambridge; Cancer Research UK; Nvidia","keywords":"Fluid-attenuated inversion recovery; Diffusion MRI; Segmentation; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine; Fractional anisotropy; Convolutional neural network; White matter; Radiation treatment planning; Image segmentation; Radiology; Pattern recognition (psychology); Radiation therapy","score_opus":0.11511095803964475,"score_gpt":0.42537756107860614,"score_spread":0.31026660303896136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026862239","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1659996,0.002463838,0.8255265,0.00076604815,0.00013217058,0.00025873003,0.0002784032,0.0022673253,0.002307424],"genre_scores_gemma":[0.6222281,0.0014578233,0.37380773,0.00015235074,0.000050338404,0.00016055239,0.0003456405,0.00042722726,0.001370215],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998061,0.00004722613,0.0000168856,0.000042642154,0.000061836094,0.000025223711],"domain_scores_gemma":[0.9998062,0.00004297468,0.000053972846,0.000022781947,0.000052893138,0.000021085938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005868814,0.00068322395,0.0004504804,0.0010482236,0.0003340543,0.0007403193,0.0005235224,0.00056260906,0.0005884492],"category_scores_gemma":[0.0010884533,0.00036707267,0.00080882775,0.0006700235,0.0003056845,0.0006185554,0.00070478563,0.00048273907,0.00022931267],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036571472,0.00014535159,0.005707251,0.00041701927,0.00021540634,0.00045660595,0.00033633705,0.37578762,0.1837802,0.0035929075,0.0024571253,0.42673838],"study_design_scores_gemma":[0.0000112227135,0.00008555082,0.0025117642,0.00002017324,0.000057700123,0.00020012405,0.000032956148,0.95260173,0.03996934,0.0017500316,0.002719938,0.00003955334],"about_ca_topic_score_codex":0.0076078316,"about_ca_topic_score_gemma":0.008320451,"teacher_disagreement_score":0.0076078316,"about_ca_system_score_codex":0.0008054202,"about_ca_system_score_gemma":0.0008942697,"threshold_uncertainty_score":0.015127063},"labels":[],"label_agreement":null},{"id":"W3027797983","doi":"10.1093/schbul/sbaa030.335","title":"M23. ALTERATION OF REGIONAL CEREBRAL BLOOD FLOW MEASURED BY ARTERIAL SPIN LABELING IN PATIENTS WITH TREATMENT-RESISTANT SCHIZOPHRENIA","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Centre for Addiction and Mental Health","funders":"","keywords":"Cerebral blood flow; Antipsychotic; Positive and Negative Syndrome Scale; Schizophrenia (object-oriented programming); Putamen; Psychology; Internal medicine; Medicine; Magnetic resonance imaging; Cardiology; Nuclear medicine; Psychosis; Psychiatry; Radiology","score_opus":0.028374071167982698,"score_gpt":0.2605660444093958,"score_spread":0.2321919732414131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027797983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97810215,0.017299986,0.000429696,0.00035263522,0.000044382476,0.000054616798,0.0016743186,0.00003484398,0.002007399],"genre_scores_gemma":[0.9976649,0.0012499422,0.0003551221,0.00009665069,0.000023478819,0.000027486927,0.00044068068,0.000005455166,0.00013643992],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996573,0.00010683157,0.00006658059,0.000085933396,0.00006011586,0.00002330748],"domain_scores_gemma":[0.99904305,0.0001295479,0.00065090257,0.000031637064,0.0000968361,0.000048010912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072192185,0.00031155988,0.0004888922,0.00058201177,0.00022329667,0.000362338,0.00023557476,0.0003456558,0.0021075227],"category_scores_gemma":[0.0016549376,0.00012259284,0.0004921645,0.00062035606,0.00017830565,0.00021551622,0.00013859462,0.00022379564,0.00023263934],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009744896,0.0003224837,0.85204715,0.0042265193,0.0039141434,0.0021869745,0.00038931228,0.00055037375,0.024061322,0.00033276313,0.0027742665,0.09944975],"study_design_scores_gemma":[0.00022076821,0.00086719764,0.99199355,0.00022490209,0.00087847613,0.001862065,0.00011606074,0.000484188,0.0012851238,0.00032325453,0.0017199727,0.000024442581],"about_ca_topic_score_codex":0.002509337,"about_ca_topic_score_gemma":0.0034057673,"teacher_disagreement_score":0.002509337,"about_ca_system_score_codex":0.00040640277,"about_ca_system_score_gemma":0.0002408258,"threshold_uncertainty_score":0.007050395},"labels":[],"label_agreement":null},{"id":"W3027998805","doi":"10.1093/schbul/sbaa031.223","title":"S157. A MULTICENTER HARMONIZED DIFFUSION TENSOR IMAGING STUDY ON THE ASSOCIATION OF WHITE MATTER STRUCTURE AND CLINICAL FUNCTIONING","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Fasciculus; Fractional anisotropy; Uncinate fasciculus; Cingulum (brain); White matter; Diffusion MRI; Inferior longitudinal fasciculus; Psychology; Superior longitudinal fasciculus; Internal medicine; Neuroscience; Medicine; Audiology; Magnetic resonance imaging; Radiology","score_opus":0.03780438445684866,"score_gpt":0.3140589004211563,"score_spread":0.27625451596430767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027998805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927872,0.00024103992,0.0005179773,0.00012784648,0.00002172071,0.00012124919,0.005391953,0.000012961015,0.0007780133],"genre_scores_gemma":[0.9947684,0.000043592612,0.00045048335,0.000043447388,0.00002632123,0.00010565446,0.0041567115,0.000010140298,0.00039539437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99927205,0.0003608121,0.00009734632,0.00012875485,0.000083286475,0.00005784175],"domain_scores_gemma":[0.9988669,0.00015366642,0.00046291683,0.00017227378,0.00018398307,0.00016026212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002287589,0.0004107019,0.00044079425,0.00072821695,0.0005176431,0.00034120656,0.00032748,0.0004217745,0.0038473762],"category_scores_gemma":[0.002299956,0.00015733571,0.0005014311,0.0009678607,0.00023412511,0.00035672128,0.00048389632,0.00017698293,0.00056103687],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043014796,0.00018044557,0.9799922,0.00008479894,0.00050106464,0.00038074085,0.00025232456,0.00031753498,0.0032967003,0.0002344766,0.0020951075,0.008363177],"study_design_scores_gemma":[0.00016986277,0.0006550789,0.99672997,0.000015561276,0.000107362874,0.00026286414,0.00010704624,0.00042011062,0.00033857216,0.00008763897,0.0010971915,0.000008649648],"about_ca_topic_score_codex":0.004384447,"about_ca_topic_score_gemma":0.003702724,"teacher_disagreement_score":0.004384447,"about_ca_system_score_codex":0.00027382924,"about_ca_system_score_gemma":0.0005915079,"threshold_uncertainty_score":0.012870789},"labels":[],"label_agreement":null},{"id":"W3028002316","doi":"10.1093/schbul/sbaa028.029","title":"O5.6. ADVANCED DIFFUSION IMAGING IN PSYCHOSIS RISK: A CROSS-SECTIONAL AND LONGITUDINAL STUDY OF WHITE MATTER DEVELOPMENT","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Psychosis; Prodrome; Magnetic resonance imaging; Fractional anisotropy; Population; Diffusion MRI; Psychology; Neuroimaging; Brain size; Human Connectome Project; Medicine; Neuroscience; Physiology; Internal medicine; Psychiatry; Radiology","score_opus":0.04204082862059,"score_gpt":0.33206056112335847,"score_spread":0.29001973250276847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028002316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99789596,0.00021927018,0.00050405145,0.00007925128,0.0000054591674,0.000016507362,0.0008486086,0.000012156452,0.00041869306],"genre_scores_gemma":[0.99822074,0.00007428388,0.0005364493,0.000024215316,0.0000049402893,0.000027225624,0.00071428274,0.000008778247,0.00038904772],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938464,0.00018544133,0.00005176665,0.00022519627,0.00007285836,0.00008000247],"domain_scores_gemma":[0.9981664,0.00024786382,0.00085633,0.00021630185,0.00025496434,0.00025804996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017099694,0.00029591535,0.00020308452,0.0005338572,0.0008136286,0.0006496818,0.00044399337,0.00052248425,0.0022636133],"category_scores_gemma":[0.0028848357,0.00032303494,0.00048677108,0.0006842281,0.0003441994,0.0006351749,0.00080975087,0.0006654613,0.00036540136],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017318578,0.000048140595,0.99527293,0.00002343218,0.00011322738,0.00010958885,0.0002937763,0.00007181915,0.0012390156,0.00007650279,0.00018867893,0.0023897837],"study_design_scores_gemma":[0.0000029728526,0.00005308948,0.99926776,0.000007408959,0.000028180368,0.00012411346,0.000080049576,0.00011809098,0.00010598547,0.000045175508,0.0001652475,0.0000020368093],"about_ca_topic_score_codex":0.013510727,"about_ca_topic_score_gemma":0.013421056,"teacher_disagreement_score":0.013510727,"about_ca_system_score_codex":0.0003128472,"about_ca_system_score_gemma":0.00063815207,"threshold_uncertainty_score":0.026864171},"labels":[],"label_agreement":null},{"id":"W3028068931","doi":"10.1038/s41366-020-0582-y","title":"Inflammatory agents partially explain associations between cortical thickness, surface area, and body mass in adolescents and young adulthood","year":2020,"lang":"en","type":"article","venue":"International Journal of Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Internal medicine; Body mass index; Medicine; Endocrinology; Cerebral cortex; Body surface area; Precentral gyrus; Magnetic resonance imaging","score_opus":0.050980610371409024,"score_gpt":0.33661345225046235,"score_spread":0.28563284187905336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028068931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958276,0.0024241013,0.0002888425,0.00019242273,0.000016973092,0.00000979037,0.0002843392,0.000014010663,0.00094195467],"genre_scores_gemma":[0.99892634,0.00050043187,0.00018856829,0.000026566067,0.000017814145,0.0000066057955,0.000116702795,0.000004334141,0.00021259696],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99965155,0.00010411615,0.000034283603,0.000090856585,0.000055497854,0.0000635788],"domain_scores_gemma":[0.99796766,0.00073653786,0.00080556126,0.00018908823,0.00014258978,0.00015847548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008168626,0.00074263953,0.0004809384,0.0007980851,0.00028088904,0.00090774166,0.0005030641,0.00076249585,0.0024581954],"category_scores_gemma":[0.003941773,0.0006579709,0.00080830423,0.00074129394,0.0004782562,0.0005449763,0.00058095815,0.0008377259,0.00025683522],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022079593,0.00005336865,0.9953146,0.00003397852,0.00026364016,0.00016092701,0.00012789722,0.00010521622,0.0006175853,0.00012747286,0.00008106454,0.0028934919],"study_design_scores_gemma":[0.0000050140548,0.000044722998,0.9987311,0.00001633147,0.00014097976,0.00021687629,0.00010032692,0.00028139845,0.00015181758,0.00021261055,0.00009671229,0.000002158559],"about_ca_topic_score_codex":0.0049934327,"about_ca_topic_score_gemma":0.006200716,"teacher_disagreement_score":0.0049934327,"about_ca_system_score_codex":0.0002273347,"about_ca_system_score_gemma":0.0005026701,"threshold_uncertainty_score":0.009928763},"labels":[],"label_agreement":null},{"id":"W3028115645","doi":"10.1093/schbul/sbaa030.367","title":"M55. STRUCTURAL CHANGES RELEVANT TO MUSICAL DEFICITS IN SCHIZOPHRENIA","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Gyrification; Audiology; Diffusion MRI; Cognition; Neuroscience; Positive and Negative Syndrome Scale; Tractography; Psychiatry; Psychosis; Medicine; Magnetic resonance imaging; Cerebral cortex","score_opus":0.0482970804247953,"score_gpt":0.3096000113988383,"score_spread":0.261302930974043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028115645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978041,0.00041699607,0.00033317908,0.00007594135,0.000009019614,0.000011364797,0.00037900204,0.000024906969,0.0009455035],"genre_scores_gemma":[0.9991394,0.00012918386,0.00028192677,0.000022444032,0.0000060006064,0.000007360614,0.00014862674,0.0000062128047,0.00025879417],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994504,0.0000065606782,0.000010234934,0.000013732187,0.00001089101,0.0000135981645],"domain_scores_gemma":[0.99973565,0.000020999725,0.00015852958,0.000017121049,0.000020257756,0.000047487272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019128133,0.00034683774,0.00020765825,0.0009170552,0.00039469468,0.00026542204,0.00014614435,0.000307233,0.005615788],"category_scores_gemma":[0.00047809622,0.00017637931,0.00023958406,0.00034580316,0.00033742792,0.00021072246,0.000325795,0.00021061099,0.00039186468],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004239293,0.00019359168,0.25462723,0.00047537542,0.0002920837,0.015724817,0.0007907634,0.00097193924,0.6828803,0.0013310274,0.001111491,0.037362132],"study_design_scores_gemma":[0.00008306989,0.00043330318,0.96729046,0.000053593765,0.00014132443,0.009854963,0.0003334131,0.0011765778,0.018629484,0.0009117411,0.0010746338,0.000017455455],"about_ca_topic_score_codex":0.004398937,"about_ca_topic_score_gemma":0.0034278543,"teacher_disagreement_score":0.005615788,"about_ca_system_score_codex":0.00035513903,"about_ca_system_score_gemma":0.0002924432,"threshold_uncertainty_score":0.018786728},"labels":[],"label_agreement":null},{"id":"W3028304957","doi":"10.1093/schbul/sbaa030.472","title":"M160. INVESTIGATING STRUCTURAL CONNECTIVITY CORRELATES OF VERBAL MEMORY DEFICITS AMONG FIRST-EPISODE PSYCHOSIS PATIENTS","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"","keywords":"Tractography; Fractional anisotropy; Psychology; White matter; Verbal memory; Psychosis; Cognition; Schizophrenia (object-oriented programming); Wechsler Adult Intelligence Scale; Audiology; Cognitive psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.0334144047036408,"score_gpt":0.27990410711341634,"score_spread":0.24648970240977555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028304957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995442,0.000047719306,0.00003182874,0.000021392929,0.0000013239116,0.000006567543,0.00012161451,0.0000026370337,0.00022271503],"genre_scores_gemma":[0.9995902,0.000025415304,0.00007480523,0.0000077339,0.000002108487,0.00000949332,0.00013414944,0.0000012911781,0.00015471326],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993503,0.000010680303,0.00000788548,0.000021712354,0.000008238659,0.000016532955],"domain_scores_gemma":[0.9997141,0.000044650656,0.00015151144,0.0000126709765,0.00002060525,0.000056460834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013885813,0.00022270305,0.00019411986,0.0005556311,0.00043259026,0.00037218502,0.00018918292,0.0003641614,0.004886936],"category_scores_gemma":[0.00086539943,0.000112482565,0.00018666897,0.00039467006,0.00014388688,0.00026791953,0.000395284,0.00020086853,0.00034912908],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006288896,0.00012159511,0.9839489,0.000064635846,0.00006670172,0.00051763863,0.00050565554,0.0001078885,0.0045968993,0.000068691996,0.00024333161,0.009129061],"study_design_scores_gemma":[0.000010252126,0.00015790231,0.9984756,0.000009191173,0.000019698758,0.000506323,0.00025858302,0.0001581573,0.00023392017,0.000064453205,0.00010329969,0.0000026852426],"about_ca_topic_score_codex":0.0030975065,"about_ca_topic_score_gemma":0.005079061,"teacher_disagreement_score":0.004886936,"about_ca_system_score_codex":0.00027412284,"about_ca_system_score_gemma":0.00020358957,"threshold_uncertainty_score":0.016348422},"labels":[],"label_agreement":null},{"id":"W3028433604","doi":"10.1016/j.neuroimage.2020.116968","title":"Virtual histology of multi-modal magnetic resonance imaging of cerebral cortex in young men","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institutes of Health; National Institute of Mental Health; Medical Research Council; University of Bristol; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Fractional anisotropy; Magnetization transfer; Myelin; Magnetic resonance imaging; White matter; Neuroscience; Nuclear magnetic resonance; Psychology; Medicine; Central nervous system; Radiology; Physics","score_opus":0.04138358293079613,"score_gpt":0.3167914785572872,"score_spread":0.27540789562649104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028433604","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980312,0.00022551973,0.0013554989,0.00001067192,0.0000035881603,0.0000051153766,0.000060006343,0.000015096436,0.00029323946],"genre_scores_gemma":[0.9990036,0.00009920651,0.000586482,0.000005836264,0.0000022964687,0.0000028519623,0.000034162782,0.000006156768,0.00025943827],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998834,0.000028230124,0.00000564659,0.000045848068,0.000021302632,0.000015602116],"domain_scores_gemma":[0.99968016,0.00009602448,0.00010596301,0.000055337343,0.000031609572,0.000031001204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035597626,0.00020579911,0.00015110243,0.00081735704,0.00024172642,0.00031940054,0.00017603017,0.00020068281,0.0011459417],"category_scores_gemma":[0.0010359569,0.00033347995,0.00012123687,0.00020196453,0.00045804447,0.00027344518,0.00026612953,0.00013354246,0.00019133023],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019749051,0.00023978727,0.6391003,0.00022720106,0.00031922935,0.0043796967,0.003160517,0.0035162917,0.28437915,0.0011282823,0.00029215706,0.061282437],"study_design_scores_gemma":[0.0000056741633,0.000308179,0.9822397,0.000009108602,0.000047386882,0.0033603085,0.00051499694,0.0018008396,0.011016624,0.00030201228,0.00038335723,0.000011901062],"about_ca_topic_score_codex":0.0021791821,"about_ca_topic_score_gemma":0.003168118,"teacher_disagreement_score":0.0021791821,"about_ca_system_score_codex":0.00018815714,"about_ca_system_score_gemma":0.00019851573,"threshold_uncertainty_score":0.0043330193},"labels":[],"label_agreement":null},{"id":"W3028537570","doi":"10.1016/j.schres.2020.04.016","title":"Thalamic and striato-pallidal volumes in schizophrenia patients and individuals at risk for psychosis: A multi-atlas segmentation study","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Japan Society for the Promotion of Science; Japan Agency for Medical Research and Development","keywords":"Globus pallidus; Putamen; Psychosis; Psychology; Thalamus; Neuroscience; Striatum; Schizophrenia (object-oriented programming); Basal ganglia; Caudate nucleus; Neuroimaging; Medicine; Psychiatry; Central nervous system; Dopamine","score_opus":0.13793972385796965,"score_gpt":0.4255632434515125,"score_spread":0.2876235195935428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028537570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977385,0.00018694394,0.0008697936,0.000041502768,0.0000025239901,0.00001089086,0.0006542061,0.000028777122,0.00046695292],"genre_scores_gemma":[0.9980393,0.000097915065,0.0009203917,0.000013234126,0.0000029741775,0.00001090797,0.00056258467,0.000029024657,0.00032365962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982506,0.00003778703,0.000012373364,0.000059125232,0.000028955,0.00003665687],"domain_scores_gemma":[0.99967325,0.000096963915,0.000095455536,0.000063279775,0.000032191998,0.000038893002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005196775,0.0003377034,0.00043902048,0.0015838614,0.00054284453,0.0012039508,0.0005472223,0.0005790143,0.001560404],"category_scores_gemma":[0.0013467984,0.0004199831,0.0006356927,0.0010439497,0.0005954391,0.0006249004,0.0008435393,0.00031107105,0.00021030394],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005515937,0.00022948041,0.86523247,0.00033002565,0.0014303739,0.002331441,0.008541446,0.0076015186,0.052138563,0.0031849416,0.0020012965,0.05146255],"study_design_scores_gemma":[0.000047403126,0.000109857196,0.98719007,0.000027418502,0.00018986456,0.0023604208,0.0016244903,0.0053898403,0.0012151331,0.0010881901,0.0007237353,0.00003349711],"about_ca_topic_score_codex":0.022206152,"about_ca_topic_score_gemma":0.041060574,"teacher_disagreement_score":0.022206152,"about_ca_system_score_codex":0.00086381694,"about_ca_system_score_gemma":0.00069023983,"threshold_uncertainty_score":0.04415381},"labels":[],"label_agreement":null},{"id":"W3029385835","doi":"10.1371/journal.pone.0233645","title":"Freewater estimatoR using iNtErpolated iniTialization (FERNET): Characterizing peritumoral edema using clinically feasible diffusion MRI data","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Initialization; Diffusion MRI; Estimator; Tractography; Computer science; Magnetic resonance imaging; Edema; Compartment (ship); Medicine; Radiology; Biomedical engineering; Algorithm; Mathematics; Surgery; Statistics","score_opus":0.47849369363589145,"score_gpt":0.4139731804885342,"score_spread":0.06452051314735724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029385835","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0140962405,0.0002846647,0.9840867,0.00010668057,0.000037194808,0.000048976308,0.00009851607,0.00088471215,0.00035624174],"genre_scores_gemma":[0.18689457,0.00042047614,0.8092877,0.00016188198,0.000046434223,0.00016477346,0.00084646355,0.0004678647,0.0017098048],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996561,0.000117452735,0.000023398987,0.0000885608,0.00007461437,0.00003989369],"domain_scores_gemma":[0.99866724,0.00074337213,0.00016927916,0.00014404097,0.00020760682,0.00006845493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019708907,0.0010465542,0.00077348034,0.0011208,0.00052907516,0.00088918064,0.0010450906,0.0015952863,0.0011310709],"category_scores_gemma":[0.008281704,0.00043125477,0.00071925466,0.000811717,0.00065063423,0.0015363758,0.0013197836,0.0013247429,0.00055392634],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089468877,0.00022669382,0.0055954834,0.00049565523,0.00017519269,0.00048705726,0.000386171,0.41573247,0.069044195,0.012979552,0.007423798,0.486559],"study_design_scores_gemma":[0.00004803768,0.000091255875,0.0009288511,0.000041393854,0.000030310048,0.00023108123,0.000034243967,0.963654,0.02520078,0.0058290716,0.0038680912,0.000042977495],"about_ca_topic_score_codex":0.0041044857,"about_ca_topic_score_gemma":0.006658042,"teacher_disagreement_score":0.0041044857,"about_ca_system_score_codex":0.00050645805,"about_ca_system_score_gemma":0.0015615352,"threshold_uncertainty_score":0.010423183},"labels":[],"label_agreement":null},{"id":"W3029732117","doi":"10.1002/jmri.27203","title":"Longitudinal Structural <scp>MRI</scp> in Neurologically Healthy Adults","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University College London Hospitals NHS Foundation Trust; Canadian Institutes of Health Research; UK Dementia Research Institute; National Institute for Health and Care Research; Alzheimer's Society; Wellcome Trust; Medical Research Council; Canadian Institute for Advanced Research; CHDI Foundation; Auburn University; Cure Huntington's Disease Initiative","keywords":"Fractional anisotropy; Intraclass correlation; Diffusion MRI; Magnetic resonance imaging; Nuclear medicine; Medicine; Psychology; Mathematics; Radiology; Statistics; Reproducibility","score_opus":0.041494978350020285,"score_gpt":0.3272383641464254,"score_spread":0.28574338579640507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029732117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99879587,0.00014464447,0.00009530829,0.000058536138,0.0000033546692,0.00001998729,0.0005559085,0.0000073401197,0.00031908043],"genre_scores_gemma":[0.9982804,0.00009845979,0.00022248455,0.00004925063,0.0000102417,0.00003080789,0.0011257058,0.0000028503873,0.0001798526],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997253,0.00005678027,0.000038466012,0.00007695511,0.00006239008,0.000040083367],"domain_scores_gemma":[0.9983664,0.00019417616,0.00058567605,0.00013385963,0.00051236904,0.00020749914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009671697,0.00024801126,0.00020376242,0.00080793886,0.0006300867,0.00040791402,0.0003003926,0.0006429802,0.001083389],"category_scores_gemma":[0.003206393,0.0002462453,0.00021034268,0.00061294704,0.0003226776,0.0006902174,0.00040841906,0.0005548278,0.0005642548],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115435105,0.00004179722,0.9970414,0.000011985388,0.000028021801,0.00016165219,0.00018121599,0.000024932995,0.00035257597,0.000007324257,0.00017044316,0.0018632183],"study_design_scores_gemma":[0.0000046602636,0.00016033198,0.99914706,0.0000039360143,0.0000111097015,0.00033550925,0.000082134924,0.000039281225,0.00007954498,0.000010472601,0.00012404202,0.0000018937903],"about_ca_topic_score_codex":0.0123170065,"about_ca_topic_score_gemma":0.017617078,"teacher_disagreement_score":0.0123170065,"about_ca_system_score_codex":0.0002454591,"about_ca_system_score_gemma":0.00037367342,"threshold_uncertainty_score":0.024490595},"labels":[],"label_agreement":null},{"id":"W3030622902","doi":"10.3760/cma.j.issn.0254-1424.2014.04.006","title":"Diffusion tensor imaging and the Montreal cognitive assessment for assessing severe traumatic brain injury","year":2014,"lang":"en","type":"article","venue":"Zhonghua wuli yixue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Superior longitudinal fasciculus; White matter; Fasciculus; Psychology; Traumatic brain injury; Medicine; Internal capsule; Audiology; Neuroscience; Cognition; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.03697124716353998,"score_gpt":0.37579117782277427,"score_spread":0.33881993065923427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3030622902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94521207,0.012738609,0.011923834,0.0010205008,0.00019750961,0.0016334008,0.005611034,0.000255123,0.021407941],"genre_scores_gemma":[0.97713643,0.0025270442,0.013949531,0.00013764805,0.000075503995,0.0008630252,0.0018725176,0.000014666335,0.0034236312],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993073,0.0001640295,0.00011023978,0.00008949166,0.00024830337,0.00008073363],"domain_scores_gemma":[0.9989015,0.00008689006,0.00055529247,0.000038194692,0.0002645645,0.0001535856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013557359,0.0011164348,0.0005154447,0.002691873,0.00046041602,0.0004891292,0.00043058174,0.00042930726,0.0017326345],"category_scores_gemma":[0.00280191,0.00013626704,0.0005821524,0.0011573039,0.00044076508,0.00058374426,0.0006657528,0.0005741817,0.0003572752],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011754349,0.00045638124,0.82877034,0.0006142698,0.0007534378,0.00078640226,0.00038920826,0.0011460213,0.0062435837,0.0020261253,0.0048287506,0.1528101],"study_design_scores_gemma":[0.000078069104,0.00096447126,0.9912156,0.000056818746,0.000086176864,0.0015437759,0.00014278389,0.0012134663,0.0009146046,0.0007169519,0.0030332839,0.000033998633],"about_ca_topic_score_codex":0.01197014,"about_ca_topic_score_gemma":0.023109067,"teacher_disagreement_score":0.01197014,"about_ca_system_score_codex":0.0009112708,"about_ca_system_score_gemma":0.0013901574,"threshold_uncertainty_score":0.02380091},"labels":[],"label_agreement":null},{"id":"W3031362040","doi":"10.3760/cma.j.issn.1674-6554.2019.03.001","title":"Brain structural network changes in Parkinson's disease with mild cognitive impairment: a diffusion tensor imaging study","year":2019,"lang":"en","type":"article","venue":"Zhonghua xingwei yixue yu naokexue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Cognition; Parkinson's disease; Cognitive impairment; Montreal Cognitive Assessment; Neurology; Psychology; Medicine; Internal medicine; Audiology; Neuroscience; Disease; Magnetic resonance imaging; Radiology","score_opus":0.021327565241089454,"score_gpt":0.30913904425309796,"score_spread":0.2878114790120085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031362040","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99919385,0.0002611353,0.00019557553,0.000036293255,0.0000030991782,0.000015266813,0.00008920383,0.0000030239462,0.00020254552],"genre_scores_gemma":[0.9994324,0.00010002265,0.00022256187,0.00001279544,0.0000089392015,0.000009898342,0.00011365386,8.3158307e-7,0.000098897886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986076,0.000023248684,0.000018413299,0.00004952865,0.00002243149,0.000025726438],"domain_scores_gemma":[0.9996687,0.000030704967,0.00017593536,0.000020471714,0.00004080546,0.000063428306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033234878,0.0004424601,0.0003230565,0.0009548977,0.0004602978,0.00037003384,0.00024343748,0.00034167955,0.0008265561],"category_scores_gemma":[0.00091610156,0.00022913021,0.00035178536,0.00056118926,0.00034175918,0.0005993202,0.00045821874,0.00024608593,0.00010938992],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093284505,0.00018275136,0.97858584,0.000099396486,0.00033659936,0.002377945,0.0007561801,0.00042370457,0.007646214,0.0001550105,0.00025812606,0.008245359],"study_design_scores_gemma":[0.000022572287,0.0002319181,0.9964502,0.0000099688095,0.00007097522,0.0014087461,0.00027760986,0.0009883203,0.00020713743,0.00015599791,0.00016940376,0.0000071874992],"about_ca_topic_score_codex":0.0048033474,"about_ca_topic_score_gemma":0.0069658207,"teacher_disagreement_score":0.0048033474,"about_ca_system_score_codex":0.00035333482,"about_ca_system_score_gemma":0.00025268734,"threshold_uncertainty_score":0.00955081},"labels":[],"label_agreement":null},{"id":"W3031445639","doi":"10.1093/brain/awaa140","title":"Slow blood-to-brain transport underlies enduring barrier dysfunction in American football players","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Izaak Walton Killam Health Centre; Dalhousie University; McGill University","funders":"Canadian Institutes of Health Research; European Commission; National Institutes of Health; National Institute on Aging; Nova Scotia Health Research Foundation; Israel Science Foundation; School of Medicine, Boston University","keywords":"Blood–brain barrier; Football; Neuroscience; American football; Psychology; Football players; Medicine; History; Central nervous system","score_opus":0.053116205411711165,"score_gpt":0.3158144215079702,"score_spread":0.262698216096259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031445639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997633,0.000042490214,0.000104628794,0.0000052102487,4.308675e-7,0.0000023538423,0.000009269927,0.0000021141502,0.000070023256],"genre_scores_gemma":[0.9998079,0.000036539983,0.000070731316,0.000004064228,0.000001713247,0.0000024097192,0.000017942924,8.6369585e-7,0.000057872596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999131,0.000021299182,0.0000076172983,0.000023303666,0.000013942593,0.000020770281],"domain_scores_gemma":[0.9997373,0.00004886518,0.00014002492,0.00001540125,0.000024929035,0.000033406966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023593282,0.00036661891,0.0002317158,0.0009861647,0.00022062002,0.0003760911,0.00015731125,0.00028914513,0.00065883336],"category_scores_gemma":[0.00063508196,0.00023682688,0.00011189846,0.00036733696,0.00040603915,0.00022613103,0.00026403237,0.00020644354,0.00009831516],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012361315,0.00015842714,0.8897025,0.000042307252,0.0000977199,0.0018826944,0.00050544034,0.00025960614,0.097693965,0.00007899536,0.00006999222,0.008272227],"study_design_scores_gemma":[0.0000039988904,0.00022007486,0.9959906,0.0000025481502,0.000018132469,0.0017080972,0.00013910305,0.0004395329,0.0013907283,0.000029558933,0.000053658576,0.000003883183],"about_ca_topic_score_codex":0.0028847177,"about_ca_topic_score_gemma":0.002619229,"teacher_disagreement_score":0.0028847177,"about_ca_system_score_codex":0.00016140477,"about_ca_system_score_gemma":0.00011697276,"threshold_uncertainty_score":0.005735934},"labels":[],"label_agreement":null},{"id":"W3031563897","doi":"10.3390/molecules25112472","title":"White Matter Brain Network Research in Alzheimer’s Disease Using Persistent Features","year":2020,"lang":"en","type":"article","venue":"Molecules","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Shanxi Provincial Key Research and Development Project; National Key Research and Development Program of China; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; H. Lundbeck A/S; Servier; Genentech; IXICO; North University of China; National Institutes of Health; Natural Science Foundation of Shanxi Province; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Persistent homology; Neuroscience; Connectome; Disease; Psychology; Cognition; Connectomics; Alzheimer's disease; Computer science; Medicine; Functional connectivity; Pathology; Magnetic resonance imaging","score_opus":0.2368974460481099,"score_gpt":0.4271473711546619,"score_spread":0.190249925106552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031563897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95636433,0.0024943731,0.038949344,0.00015235157,0.000017788167,0.000039651895,0.0003719195,0.0000627598,0.0015473955],"genre_scores_gemma":[0.9918391,0.0006378675,0.0070952657,0.0000119381875,0.000018731982,0.00002662288,0.0001898326,0.000007546372,0.00017309975],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999767,0.00007965425,0.00001712936,0.000068275906,0.000042618816,0.00002526635],"domain_scores_gemma":[0.9991435,0.0002902081,0.0002991115,0.00011375306,0.00008096442,0.00007249807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008752204,0.00030250582,0.0002852649,0.0034605248,0.00034434072,0.00074693136,0.00029811473,0.0002939723,0.00083907525],"category_scores_gemma":[0.0023631025,0.00013108503,0.00031520723,0.0020281968,0.00065186346,0.0016803362,0.00059560343,0.00032245065,0.00007893394],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010637623,0.00023644954,0.52881294,0.0011012974,0.001568718,0.000648348,0.0024311026,0.036186807,0.094828285,0.03249616,0.0017846251,0.29884154],"study_design_scores_gemma":[0.000041006875,0.00066878716,0.7773417,0.00015757381,0.00044638696,0.0015800154,0.0011459121,0.1361068,0.013059909,0.06569623,0.0036843386,0.00007133844],"about_ca_topic_score_codex":0.001980958,"about_ca_topic_score_gemma":0.0030619232,"teacher_disagreement_score":0.0034605248,"about_ca_system_score_codex":0.00046351773,"about_ca_system_score_gemma":0.00025263362,"threshold_uncertainty_score":0.0046286583},"labels":[],"label_agreement":null},{"id":"W3032589417","doi":"10.1101/2020.05.26.116152","title":"Plis de passage in the Superior Temporal Sulcus: Morphology and local connectivity","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Agence Nationale de la Recherche; Aix-Marseille Université","keywords":"Human Connectome Project; Sulcus; Central sulcus; Morphology (biology); Anatomy; Biology; Functional connectivity; Neuroscience; Cartography; Geology; Geography; Paleontology","score_opus":0.04102571676518483,"score_gpt":0.2898513356119279,"score_spread":0.24882561884674306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032589417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99447167,0.0002193753,0.003636077,0.00006300914,0.000004711551,0.000013688747,0.0005908781,0.000049489987,0.00095107267],"genre_scores_gemma":[0.99820685,0.00008028423,0.001119905,0.000006671267,0.000006696777,0.000008002063,0.00031696662,0.000013218447,0.00024149702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998809,0.000027209957,0.000010124173,0.00004292689,0.000025418403,0.000013414883],"domain_scores_gemma":[0.9994649,0.00019249282,0.00016921172,0.000077677185,0.000050919884,0.000044868637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026929704,0.00023897013,0.00018768912,0.0011421199,0.00021878729,0.00056016323,0.00012926102,0.00022553976,0.0031573663],"category_scores_gemma":[0.001586033,0.00014681647,0.00019007792,0.000941298,0.000692812,0.00058928266,0.0003879694,0.00016020205,0.00030819525],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002087275,0.00010890286,0.52355176,0.00055365957,0.00059379695,0.003967496,0.0022003166,0.0058141155,0.32145548,0.0041233636,0.0032554164,0.13228832],"study_design_scores_gemma":[0.000017420563,0.00009743051,0.9831472,0.000016106811,0.000056215933,0.002510665,0.00026918697,0.0053023375,0.005562905,0.002457243,0.0005515557,0.000011810647],"about_ca_topic_score_codex":0.0018595267,"about_ca_topic_score_gemma":0.0036274958,"teacher_disagreement_score":0.0031573663,"about_ca_system_score_codex":0.00013199137,"about_ca_system_score_gemma":0.00017441923,"threshold_uncertainty_score":0.0105624795},"labels":[],"label_agreement":null},{"id":"W3032824173","doi":"10.1101/2020.05.29.118737","title":"Axon morphology is modulated by the local environment and impacts the non-invasive investigation of its structure-function relationship","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Vetenskapsrådet","keywords":"Axon; White matter; Soma; Corpus callosum; Magnetic resonance imaging; Diffusion MRI; Biophysics; Nuclear magnetic resonance; Neuroscience; Anatomy; Biology; Physics; Medicine","score_opus":0.035226373212578016,"score_gpt":0.25234472874585734,"score_spread":0.21711835553327932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032824173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9857384,0.00040773948,0.012326442,0.00008556552,0.000008183923,0.0000049444243,0.00017457294,0.00013025414,0.0011238899],"genre_scores_gemma":[0.99428326,0.00028528896,0.004649677,0.000031891836,0.0000050258404,0.000008147325,0.000096627075,0.00003922246,0.00060076395],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989617,0.000017458618,0.0000050869735,0.00003319639,0.0000321092,0.000015982765],"domain_scores_gemma":[0.9997187,0.00009121293,0.00008115958,0.000038774702,0.00004750667,0.000022541028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020949422,0.00019942275,0.0002358669,0.00029711143,0.00026427765,0.0007211912,0.00016301005,0.00033932977,0.0008432954],"category_scores_gemma":[0.00051886874,0.00017939929,0.00008117444,0.00027496408,0.000493653,0.0004695806,0.00024795547,0.00024587766,0.00019738497],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052856452,0.000011614666,0.0052936645,0.000045328034,0.000011222835,0.000103495804,0.00007288989,0.001639322,0.9881925,0.0006137461,0.00012147557,0.0038418516],"study_design_scores_gemma":[0.000013679015,0.0001463581,0.29271615,0.00004040843,0.000051295643,0.00094866054,0.00040468038,0.06182989,0.6382131,0.00310876,0.0024689147,0.000058034246],"about_ca_topic_score_codex":0.0012131787,"about_ca_topic_score_gemma":0.0020722768,"teacher_disagreement_score":0.0012131787,"about_ca_system_score_codex":0.0002641512,"about_ca_system_score_gemma":0.00021200135,"threshold_uncertainty_score":0.0028210878},"labels":[],"label_agreement":null},{"id":"W3033410889","doi":"10.1007/s12021-020-09469-5","title":"Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer’s Disease","year":2020,"lang":"en","type":"review","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Chinese Government Scholarship; Canadian Institutes of Health Research; National Institute on Aging; Agence Nationale de la Recherche","keywords":"Computer science; Pattern recognition (psychology); Artificial intelligence; Preprocessor; Feature selection; Diffusion MRI; Voxel; Feature extraction; Smoothing; Feature (linguistics); Data mining; Magnetic resonance imaging; Computer vision; Medicine; Radiology","score_opus":0.19711400074071547,"score_gpt":0.42456733330900737,"score_spread":0.2274533325682919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033410889","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017291808,0.99477285,0.001805287,0.00031512097,0.00014166483,0.000031232314,0.00016471816,0.00004214953,0.0009978126],"genre_scores_gemma":[0.020480663,0.9701836,0.006913569,0.00048581118,0.0003558914,0.00005656073,0.0007739603,0.000015205963,0.0007347607],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994979,0.000093065035,0.00007580174,0.00013418759,0.0001692851,0.000029800285],"domain_scores_gemma":[0.9983588,0.0008828454,0.0002314862,0.00005473622,0.00043116813,0.000040905285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00209968,0.0011226727,0.0020000706,0.0026734166,0.0001456966,0.0012003925,0.0011792628,0.0007787814,0.0011933998],"category_scores_gemma":[0.0029348598,0.00027517494,0.00091371435,0.0015399284,0.0004651767,0.0008858623,0.0005077009,0.0010058829,0.0008063437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001324792,0.000055901364,0.0015238182,0.007983075,0.00038982948,0.000063502535,0.000030125828,0.0002882754,0.0017063399,0.0008942236,0.0067172647,0.9802151],"study_design_scores_gemma":[0.00057845074,0.0016305143,0.08062125,0.035165586,0.008549303,0.0070320223,0.00046260923,0.00912844,0.022485143,0.016232276,0.81764495,0.00046940745],"about_ca_topic_score_codex":0.0019471667,"about_ca_topic_score_gemma":0.0029901979,"teacher_disagreement_score":0.0026734166,"about_ca_system_score_codex":0.00053489726,"about_ca_system_score_gemma":0.001197108,"threshold_uncertainty_score":0.011104286},"labels":[],"label_agreement":null},{"id":"W3033502402","doi":"10.3389/fnins.2020.00806","title":"Corrigendum: Histological Correlates of Diffusion-Weighted Magnetic Resonance Microscopy in a Mouse Model of Mesial Temporal Lobe Epilepsy","year":2020,"lang":"en","type":"erratum","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"","keywords":"Temporal lobe; Epilepsy; Diffusion-Weighted Magnetic Resonance Imaging; Mesial temporal lobe epilepsy; Magnetic resonance imaging; Diffusion MRI; Nuclear magnetic resonance; Neuroscience; Diffusion; Psychology; Medicine; Physics; Radiology","score_opus":0.0432563520567713,"score_gpt":0.2994360851847402,"score_spread":0.2561797331279689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033502402","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002757812,0.0020609791,0.0012590399,0.038197506,0.95019484,0.000056374967,0.0012433166,0.0008470584,0.0058650104],"genre_scores_gemma":[0.014792692,0.016673818,0.0059162835,0.057185296,0.36023977,0.0005057945,0.0068090516,0.0024758985,0.5354014],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99634355,0.00044634278,0.0004787472,0.0005921585,0.0018189704,0.0003200939],"domain_scores_gemma":[0.9762565,0.002727572,0.0009301667,0.0011329082,0.017662948,0.001289859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029228632,0.002114537,0.002144405,0.0039035976,0.0024492387,0.0025578898,0.003499218,0.0054721595,0.09770201],"category_scores_gemma":[0.023767853,0.00096736057,0.0020003887,0.0018372139,0.001763411,0.0019759529,0.0023194312,0.004065343,0.05454948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023956634,0.000008432618,0.000040263858,0.0000853676,0.0000055831856,0.00012391913,0.000012450532,0.00002751085,0.00018639973,0.00029130265,0.9939453,0.0052495496],"study_design_scores_gemma":[0.000027525848,0.000039711795,0.0009712111,0.00015919143,0.000045216475,0.00061165576,0.000050049308,0.00025792912,0.0019017758,0.0007418949,0.99514836,0.00004549963],"about_ca_topic_score_codex":0.013896294,"about_ca_topic_score_gemma":0.018860562,"teacher_disagreement_score":0.09770201,"about_ca_system_score_codex":0.00529163,"about_ca_system_score_gemma":0.0030018687,"threshold_uncertainty_score":0.32684577},"labels":[],"label_agreement":null},{"id":"W3035270228","doi":"10.1111/jon.12741","title":"Learning‐Challenged Youth Show an Abnormal Relationship Between Fronto‐Parietal Myelination and Mathematical Ability","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"White matter; Myelin; Typically developing; Developmental psychology; Psychology; Audiology; Medicine; Cognitive psychology; Magnetic resonance imaging; Neuroscience; Central nervous system","score_opus":0.20074021644277756,"score_gpt":0.37663562283373336,"score_spread":0.1758954063909558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035270228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996126,0.000054475066,0.000092306225,0.000012892058,0.0000012297893,0.0000018570627,0.00006776286,0.000011548753,0.00014535442],"genre_scores_gemma":[0.9995571,0.00004114809,0.00017133761,0.0000075017115,0.000001553086,0.0000031780123,0.00008225659,0.0000037537523,0.0001322885],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983597,0.000014653647,0.000018527478,0.000056343033,0.00003882965,0.00003572607],"domain_scores_gemma":[0.9989675,0.00011814392,0.0006389316,0.00003857615,0.00009446873,0.0001423751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026678902,0.000391537,0.00029983494,0.00071388343,0.0002138217,0.0005864931,0.00024183937,0.00036036718,0.0017882602],"category_scores_gemma":[0.0011852978,0.0001706014,0.00016127461,0.00038502106,0.0005263301,0.00036208334,0.00050377497,0.0003708337,0.0002459738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022233537,0.00010987572,0.97273064,0.000042342286,0.00003412476,0.0018342099,0.00057721947,0.000112013346,0.017345445,0.00009428674,0.00015071951,0.006746729],"study_design_scores_gemma":[0.0000018364394,0.00010059653,0.99624455,0.0000053646745,0.000010499516,0.0016443912,0.00020812145,0.00012101426,0.0015422646,0.00004651423,0.00007246325,0.0000024491544],"about_ca_topic_score_codex":0.004190605,"about_ca_topic_score_gemma":0.0043119746,"teacher_disagreement_score":0.004190605,"about_ca_system_score_codex":0.00024303695,"about_ca_system_score_gemma":0.00033818424,"threshold_uncertainty_score":0.008332431},"labels":[],"label_agreement":null},{"id":"W3035680799","doi":"10.3389/fneur.2020.00561","title":"Altered White Matter Structural Network in Frontal and Temporal Lobe Epilepsy: A Graph-Theoretical Study","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Diffusion MRI; Temporal lobe; Epilepsy; Neuroscience; Psychology; Frontal lobe; Cognition; Connectome; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.020287890543845912,"score_gpt":0.2900120420111246,"score_spread":0.26972415146727874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035680799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9460922,0.00039476293,0.05096641,0.00030082057,0.00000852966,0.000044189535,0.0003309279,0.000042962143,0.0018191767],"genre_scores_gemma":[0.9894085,0.00023635308,0.009665841,0.000020758871,0.000012499798,0.000027043863,0.0003345108,0.000010253401,0.0002842435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998872,0.000047569174,0.0000039696038,0.000034617773,0.000014159143,0.000012506105],"domain_scores_gemma":[0.9992514,0.00040212183,0.0001568157,0.00005501469,0.000068883164,0.00006585338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049192365,0.00025885328,0.00018013429,0.0015137136,0.00020186481,0.00040636968,0.00033784367,0.00025224974,0.0015379259],"category_scores_gemma":[0.0019893926,0.00011528593,0.0005332253,0.00059768726,0.00052079273,0.0007440729,0.00031929766,0.00021640948,0.00010692947],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001025834,0.00065807364,0.40221792,0.00072848465,0.0012809132,0.003078753,0.0026104413,0.3133537,0.024402361,0.13904269,0.003636568,0.10796424],"study_design_scores_gemma":[0.000035953166,0.00018981734,0.12922104,0.000037319976,0.00017947823,0.0008570703,0.0004899683,0.7975754,0.0009582105,0.06887974,0.001547999,0.000027992719],"about_ca_topic_score_codex":0.003364628,"about_ca_topic_score_gemma":0.0031993964,"teacher_disagreement_score":0.003364628,"about_ca_system_score_codex":0.00044906346,"about_ca_system_score_gemma":0.00024701917,"threshold_uncertainty_score":0.006690085},"labels":[],"label_agreement":null},{"id":"W3035690190","doi":"10.1101/2020.06.12.148999","title":"Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; Compute Canada; Vanderbilt Institute for Clinical and Translational Research; National Institutes of Health; Vanderbilt University; U.S. Department of Defense","keywords":"White matter; Tractography; Diffusion MRI; Human Connectome Project; Fiber tract; Population; Artificial intelligence; Computer science; Neuroscience; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine","score_opus":0.02904121661004588,"score_gpt":0.2664746249582702,"score_spread":0.2374334083482243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035690190","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14648077,0.00044244225,0.7831409,0.00023831055,0.0001566424,0.00049413816,0.04019155,0.019033812,0.009821423],"genre_scores_gemma":[0.38382405,0.0004255737,0.5537543,0.00007145271,0.00008529037,0.00167125,0.051019315,0.002878571,0.006270084],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951446,0.00013882943,0.00004132176,0.00018601505,0.00008797948,0.000031473253],"domain_scores_gemma":[0.99907255,0.00028511314,0.00012894307,0.0002724583,0.00019222393,0.000048626767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012439301,0.0006585556,0.000645477,0.0026678487,0.0005905525,0.0016784613,0.00094164786,0.0005155096,0.014229561],"category_scores_gemma":[0.0030137643,0.00059688516,0.00069855945,0.0022982846,0.00046427434,0.0008311527,0.0013624046,0.0008978166,0.0028889203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017101399,0.00041316377,0.04703753,0.0009565764,0.001114245,0.000911771,0.0017887586,0.12734684,0.046888847,0.04193231,0.1374756,0.5924242],"study_design_scores_gemma":[0.00040998336,0.00055139465,0.12702274,0.00022405281,0.00042513982,0.0031988116,0.00051311543,0.5794336,0.023821812,0.06402663,0.20006487,0.0003078057],"about_ca_topic_score_codex":0.00704832,"about_ca_topic_score_gemma":0.010852809,"teacher_disagreement_score":0.014229561,"about_ca_system_score_codex":0.0005558268,"about_ca_system_score_gemma":0.0013108697,"threshold_uncertainty_score":0.047602654},"labels":[],"label_agreement":null},{"id":"W3035781430","doi":"10.1007/s10237-020-01346-z","title":"Fluorescence recovery after photobleaching: direct measurement of diffusion anisotropy","year":2020,"lang":"en","type":"article","venue":"Biomechanics and Modeling in Mechanobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fluorescence recovery after photobleaching; Anisotropy; Thermal diffusivity; Isotropy; Materials science; Diffusion; Anisotropic diffusion; Tensor (intrinsic definition); Photobleaching; Work (physics); Optics; Thermodynamics; Fluorescence; Physics; Geometry; Mathematics","score_opus":0.11660971423851212,"score_gpt":0.30834446034793317,"score_spread":0.19173474610942104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035781430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7799116,0.0028597724,0.20257895,0.0011047865,0.00015152495,0.00022732577,0.0010185053,0.0012076768,0.010939954],"genre_scores_gemma":[0.9121447,0.002499516,0.07258771,0.00027508993,0.00006138742,0.0002151916,0.00058295217,0.00028048723,0.011352878],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966633,0.00003215434,0.000009149403,0.000115752926,0.0000995502,0.00007705691],"domain_scores_gemma":[0.999483,0.00021668323,0.00008082495,0.000081577426,0.00008044147,0.00005747664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005635749,0.00051022193,0.00047392774,0.0004724048,0.00056476326,0.00070302584,0.0010926594,0.0010005111,0.0023242647],"category_scores_gemma":[0.001307462,0.00039481322,0.00020517017,0.00047650357,0.0008525906,0.0012856789,0.00054313254,0.0019477783,0.000695368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009263412,0.00003133851,0.00015374995,0.00006974509,0.0000052355776,0.000046382902,0.000058867565,0.0001268393,0.9949307,0.00055942853,0.00020348094,0.0037216041],"study_design_scores_gemma":[0.000022638857,0.000063203464,0.0025064116,0.000010595268,0.000012843403,0.00021660578,0.00004594586,0.0041920207,0.99121535,0.00034103272,0.001355173,0.000018080555],"about_ca_topic_score_codex":0.0037564167,"about_ca_topic_score_gemma":0.0042498726,"teacher_disagreement_score":0.0037564167,"about_ca_system_score_codex":0.0006724211,"about_ca_system_score_gemma":0.0007863112,"threshold_uncertainty_score":0.007775426},"labels":[],"label_agreement":null},{"id":"W3035809474","doi":"10.1002/jmri.27188","title":"Mapping Structural Connectivity Using Diffusion <scp>MRI</scp>: Challenges and Opportunities","year":2020,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":199,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Australian Research Council; Medical Research Council; State Government of Victoria; National Health and Medical Research Council; Wellcome Trust","keywords":"Connectome; Tractography; Diffusion MRI; Computer science; Connectomics; Human Connectome Project; Graph theory; Graph; Artificial intelligence; Data science; Complex network; Machine learning; Neuroscience; Functional connectivity; Theoretical computer science; Psychology; Magnetic resonance imaging; Mathematics; Medicine; World Wide Web","score_opus":0.18716514936947706,"score_gpt":0.37723593507207087,"score_spread":0.1900707857025938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035809474","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000052431362,0.9977301,0.0002777261,0.0010648243,0.000141406,0.0000049042587,0.000017073216,0.0000057181837,0.0007059052],"genre_scores_gemma":[0.0005955998,0.9981192,0.0005789471,0.00026842608,0.00019052987,0.00000967308,0.000023109422,0.0000024249514,0.00021214256],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994235,0.00015600523,0.000095026546,0.00008564285,0.00020346881,0.000036331523],"domain_scores_gemma":[0.99645835,0.0023499914,0.00036229796,0.00009115047,0.0006400989,0.0000980367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028809933,0.00081844424,0.0018915578,0.0039369627,0.00028364745,0.0021271796,0.0013838921,0.0022319772,0.005039675],"category_scores_gemma":[0.0050554103,0.0004029503,0.0009829318,0.0038670006,0.0010351036,0.003114687,0.0009044687,0.0024067757,0.0030879548],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037460806,0.000025631902,0.00016567654,0.031855796,0.00012561803,0.00011584731,0.00006911947,0.00032482916,0.0005634837,0.011569192,0.016563782,0.9385836],"study_design_scores_gemma":[0.000028158416,0.00013333182,0.0021141768,0.05005651,0.00033467068,0.001680136,0.00021096751,0.00036886698,0.00070032914,0.018418755,0.92589617,0.000058026028],"about_ca_topic_score_codex":0.0023439284,"about_ca_topic_score_gemma":0.0036773486,"teacher_disagreement_score":0.005039675,"about_ca_system_score_codex":0.0010373915,"about_ca_system_score_gemma":0.0032385653,"threshold_uncertainty_score":0.016859353},"labels":[],"label_agreement":null},{"id":"W3035841897","doi":"10.1001/jamapsychiatry.2020.1495","title":"Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders","year":2020,"lang":"en","type":"article","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Medical Research Council","keywords":"Cohort; Psychology; Neuroimaging; Psychiatry; Neuroscience; Medicine; Pathology","score_opus":0.02741887362394515,"score_gpt":0.3249181216440192,"score_spread":0.29749924802007405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035841897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99645424,0.001643523,0.0006599007,0.00005994102,0.0000022855984,0.000024517116,0.00061890093,0.0000073673423,0.0005293533],"genre_scores_gemma":[0.99777406,0.0008593178,0.0008124731,0.000016763828,0.0000055789674,0.000030820935,0.00036205447,0.0000024623223,0.00013648049],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975604,0.00008651505,0.000025005793,0.000054038323,0.000045239154,0.00003305591],"domain_scores_gemma":[0.99876994,0.00025520418,0.00066913787,0.000085705775,0.00015142006,0.00006860288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096248346,0.00024799284,0.00017991904,0.0014197769,0.00025099432,0.00042135574,0.0002727601,0.00021522914,0.0009861342],"category_scores_gemma":[0.0018934996,0.00014750348,0.00032830556,0.0008954454,0.0003824895,0.00041834,0.0003393676,0.00027841667,0.00007808087],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008205969,0.00001608232,0.9929321,0.00003258278,0.0000579524,0.000062468695,0.000109388784,0.00014613023,0.0012918367,0.000053026004,0.000050557777,0.00516583],"study_design_scores_gemma":[8.4160826e-7,0.000016877686,0.99944335,0.000008754334,0.000009249091,0.00009709503,0.00006388816,0.00008998012,0.00017864878,0.000039553383,0.00005081119,0.0000010927988],"about_ca_topic_score_codex":0.004003884,"about_ca_topic_score_gemma":0.006662973,"teacher_disagreement_score":0.004003884,"about_ca_system_score_codex":0.0002946443,"about_ca_system_score_gemma":0.00038718793,"threshold_uncertainty_score":0.007961154},"labels":[],"label_agreement":null},{"id":"W3036457878","doi":"10.3233/jad-200213","title":"Fascicle- and Glucose-Specific Deterioration in White Matter Energy Supply in Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"White matter; Disease; Fascicle; Alzheimer's disease; Medicine; Neuroscience; Internal medicine; Psychology; Anatomy","score_opus":0.06738659874914049,"score_gpt":0.3170203315413269,"score_spread":0.24963373279218642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036457878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99702555,0.0012371611,0.0013552408,0.000009920907,0.0000035204469,0.000009419373,0.000096463926,0.000013849582,0.00024888045],"genre_scores_gemma":[0.9969272,0.000583581,0.0020003314,0.0000084583035,0.000004314632,0.000014246673,0.00017972157,0.0000061723135,0.00027599162],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999143,0.00001038493,0.000009106497,0.000029306977,0.000021098636,0.00001583679],"domain_scores_gemma":[0.9997638,0.000020065185,0.00012992552,0.000016300564,0.000037324677,0.000032697477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032989285,0.0004237468,0.00020395096,0.001250899,0.00021577346,0.0003286933,0.00013266949,0.00024716737,0.00069895905],"category_scores_gemma":[0.00030065217,0.00016456992,0.00018376372,0.00043539432,0.00029171444,0.0003124948,0.0003467549,0.00017896498,0.0001277247],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032009075,0.0001126843,0.28001252,0.00037301023,0.00039199245,0.0010827157,0.0006216446,0.0008510324,0.66898495,0.00020175945,0.00022364898,0.043943226],"study_design_scores_gemma":[0.000009179799,0.00018876267,0.9799906,0.000014075336,0.00006428165,0.001461162,0.000140665,0.0008392441,0.016677545,0.00021695723,0.00038957765,0.000007813936],"about_ca_topic_score_codex":0.0011046323,"about_ca_topic_score_gemma":0.001673291,"teacher_disagreement_score":0.001250899,"about_ca_system_score_codex":0.00018062326,"about_ca_system_score_gemma":0.000103071456,"threshold_uncertainty_score":0.0023382306},"labels":[],"label_agreement":null},{"id":"W3036999708","doi":"10.1002/hbm.24977","title":"Depth‐dependent abnormal cortical myelination in first‐episode treatment‐naïve schizophrenia","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"West China Hospital, Sichuan University; National Key Research and Development Program of China; Sichuan University; National Natural Science Foundation of China","keywords":"Supramarginal gyrus; Neuroscience; Psychology; Superior temporal gyrus; Myelin; Schizophrenia (object-oriented programming); Posterior cingulate; Parietal lobe; Middle frontal gyrus; Superior frontal gyrus; Cortex (anatomy); Temporal lobe; Cognition; Central nervous system; Functional magnetic resonance imaging; Epilepsy; Psychiatry","score_opus":0.11093449547315763,"score_gpt":0.35089601582930047,"score_spread":0.23996152035614282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036999708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99968493,0.00008068701,0.000055712728,0.000012837448,8.1671215e-7,0.0000027675771,0.000033429664,0.0000029984262,0.00012590176],"genre_scores_gemma":[0.9997811,0.000054913875,0.000050440223,0.0000059168965,5.8524455e-7,0.0000015270432,0.000036454563,0.0000010223866,0.00006803442],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999946,0.000010787082,0.000006671829,0.000010461184,0.00001161037,0.000014526961],"domain_scores_gemma":[0.99982774,0.000019351328,0.000092809685,0.000009042829,0.000013808432,0.000037153044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016675387,0.00024955496,0.00016732806,0.00045543007,0.00020413676,0.00021666796,0.00009229158,0.00024936112,0.0011399324],"category_scores_gemma":[0.00055251684,0.00014923952,0.00013609978,0.00013913063,0.00020472094,0.00017491703,0.00018375127,0.000237522,0.00007927204],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048612407,0.00031291446,0.5075951,0.0002327648,0.00021873247,0.0040462636,0.001743076,0.0007929483,0.44537523,0.00026324217,0.0002654409,0.034293085],"study_design_scores_gemma":[0.00001647673,0.00031382337,0.9935766,0.000010303294,0.000025023892,0.0015752846,0.00023752131,0.00034129218,0.0036814832,0.00010636153,0.000109072455,0.000006748192],"about_ca_topic_score_codex":0.006718215,"about_ca_topic_score_gemma":0.01251129,"teacher_disagreement_score":0.006718215,"about_ca_system_score_codex":0.00048712548,"about_ca_system_score_gemma":0.00026134326,"threshold_uncertainty_score":0.013358235},"labels":[],"label_agreement":null},{"id":"W3037018865","doi":"10.1186/s41824-020-00079-7","title":"18F-FDG PET-guided diffusion tractography reveals white matter abnormalities around the epileptic focus in medically refractory epilepsy: implications for epilepsy surgical evaluation","year":2020,"lang":"en","type":"article","venue":"European Journal of Hybrid Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; St. Michael's Hospital; Queen's University; Lawson Health Research Institute; Western University","funders":"Mitacs; Physicians' Services Incorporated Foundation; London Health Sciences Centre; Lawson Health Research Institute","keywords":"Diffusion MRI; White matter; Medicine; Fractional anisotropy; Epilepsy; Tractography; Nuclear medicine; Lateralization of brain function; Positron emission tomography; Radiology; Magnetic resonance imaging; Audiology","score_opus":0.06948927614457129,"score_gpt":0.3434076416982299,"score_spread":0.2739183655536586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037018865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99939907,0.00014579757,0.00017912025,0.000028552162,0.0000011266856,0.0000057689354,0.000014175449,0.0000040721666,0.00022244813],"genre_scores_gemma":[0.99962723,0.00007291414,0.00022632652,0.0000134886595,0.000004511294,0.0000029167127,0.000020009746,0.0000014527006,0.000031139654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989164,0.000025517822,0.00001943798,0.000020991669,0.000023718087,0.000018704613],"domain_scores_gemma":[0.9994822,0.00022215203,0.00015055429,0.00003532133,0.000051564162,0.000058160218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047076066,0.00025886585,0.0002093746,0.00067620043,0.0001939711,0.0002450618,0.00016285594,0.00028893794,0.0006241674],"category_scores_gemma":[0.0021845596,0.00010302704,0.00010397045,0.00019389305,0.0004488805,0.0002563765,0.00014093965,0.00012249562,0.00014731415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047030702,0.00008420953,0.94700295,0.00004634633,0.000027134387,0.007162963,0.00016042523,0.0002773634,0.02396165,0.000043064854,0.00013392669,0.020629711],"study_design_scores_gemma":[0.00004760477,0.00047468976,0.94512296,0.000020319312,0.000041845044,0.04504249,0.00022573504,0.001578516,0.0070188926,0.00012966644,0.0002868461,0.000010376258],"about_ca_topic_score_codex":0.0007416314,"about_ca_topic_score_gemma":0.0016769998,"teacher_disagreement_score":0.0007416314,"about_ca_system_score_codex":0.00021532645,"about_ca_system_score_gemma":0.00022481041,"threshold_uncertainty_score":0.0024896264},"labels":[],"label_agreement":null},{"id":"W3037092022","doi":"10.1016/j.nicl.2020.102320","title":"Network reorganisation following anterior temporal lobe resection and relation with post-surgery seizure relapse: A longitudinal study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Temporal lobe; Anterior temporal lobectomy; Tractography; Epilepsy; Fractional anisotropy; White matter; Uncinate fasciculus; Epilepsy surgery; Medicine; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Neuroscience; Surgery; Magnetic resonance imaging; Radiology","score_opus":0.1658678099377777,"score_gpt":0.406680260432219,"score_spread":0.2408124504944413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037092022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99968755,0.00008176706,0.000042845182,0.000014577047,0.0000013307907,0.000004602326,0.00008246402,0.0000017350974,0.00008321184],"genre_scores_gemma":[0.9995851,0.000042693755,0.000039011746,0.000004805609,0.000002439539,0.000006475602,0.00017652012,0.0000010442443,0.00014196605],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983,0.000032642438,0.000017013737,0.000052766172,0.000027676897,0.000039820654],"domain_scores_gemma":[0.99887913,0.00009725497,0.0006544355,0.00008773669,0.00011536235,0.00016598402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005197736,0.0002034163,0.000246397,0.000512699,0.00037138312,0.00043428884,0.00023323634,0.0003686596,0.00091299857],"category_scores_gemma":[0.001560476,0.00014560076,0.0002957763,0.0004983779,0.00022934811,0.0004895094,0.0003523479,0.00044460132,0.00018563063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004487962,0.00015927815,0.9942918,0.000009619572,0.00010199966,0.00020397142,0.00030421867,0.00007188046,0.0012865936,0.00001799632,0.00006780855,0.0030359847],"study_design_scores_gemma":[0.0000048435495,0.00023609314,0.99910575,0.0000022556756,0.000020171547,0.00019950132,0.00011269686,0.00010795677,0.00011252481,0.000019192192,0.00007570043,0.0000032222376],"about_ca_topic_score_codex":0.0040489463,"about_ca_topic_score_gemma":0.0061686,"teacher_disagreement_score":0.0040489463,"about_ca_system_score_codex":0.00026360826,"about_ca_system_score_gemma":0.00024156792,"threshold_uncertainty_score":0.00805074},"labels":[],"label_agreement":null},{"id":"W3037939475","doi":"10.3389/fnagi.2020.00202","title":"Volumetric and Diffusion Abnormalities in Subcortical Nuclei of Older Adults With Cognitive Frailty","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Fujian University of Traditional Chinese Medicine; National Natural Science Foundation of China","keywords":"Montreal Cognitive Assessment; Cognition; Caudate nucleus; Diffusion MRI; Thalamus; Psychology; Effects of sleep deprivation on cognitive performance; Medicine; Putamen; Nucleus accumbens; Cognitive decline; Neuroscience; Audiology; Internal medicine; Cognitive impairment; Magnetic resonance imaging; Dementia; Central nervous system; Radiology; Disease","score_opus":0.03367734249124475,"score_gpt":0.2976633712077241,"score_spread":0.26398602871647936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037939475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990771,0.00049357716,0.00009037742,0.000012836667,0.0000017200431,0.000005342644,0.000082810584,0.000002695805,0.0002335614],"genre_scores_gemma":[0.99962914,0.000104507555,0.000091153284,0.000008921201,0.0000028203128,0.0000042938536,0.00007030156,4.782236e-7,0.00008831038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999403,0.0000071288882,0.000007794283,0.000018938836,0.000013926253,0.000011935066],"domain_scores_gemma":[0.999796,0.000021828457,0.000105349114,0.000012498812,0.0000343571,0.000029982317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016660543,0.00026849515,0.0002069007,0.00077309937,0.00018848808,0.00026971177,0.00015438972,0.00019133258,0.00092592905],"category_scores_gemma":[0.0006604336,0.000099116616,0.00016022802,0.00026712855,0.00024167502,0.00020339285,0.00024627018,0.00011863832,0.00007020157],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004994375,0.000041495547,0.97545856,0.000078239435,0.00011895812,0.0011659593,0.00052524963,0.00015205648,0.009179704,0.00006104693,0.00012495984,0.012594342],"study_design_scores_gemma":[0.0000059891386,0.00009044102,0.99835855,0.000008496791,0.00002103311,0.0009118335,0.00014283281,0.00011033823,0.00020853025,0.00007072707,0.00006899629,0.0000021681462],"about_ca_topic_score_codex":0.0053338064,"about_ca_topic_score_gemma":0.008634327,"teacher_disagreement_score":0.0053338064,"about_ca_system_score_codex":0.00022021233,"about_ca_system_score_gemma":0.00013301961,"threshold_uncertainty_score":0.010605514},"labels":[],"label_agreement":null},{"id":"W3038146172","doi":"10.1101/2020.07.07.191809","title":"Beware of White Matter Hyperintensities Causing Systematic Errors in Grey Matter Segmentations!","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; University of Alberta; Centres Intégré Universitaires de Santé et de Services Sociaux","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; Alzheimer Society; U.S. Department of Defense; Eli Lilly and Company; Consortium canadien en neurodégénérescence associée au vieillissement; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Sanofi; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Hyperintensity; Putamen; Grey matter; White matter; Fluid-attenuated inversion recovery; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Cardiology; Internal medicine; Effects of sleep deprivation on cognitive performance; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Cognition; Disease; Cognitive impairment; Radiology","score_opus":0.04253700151309517,"score_gpt":0.28508521451069563,"score_spread":0.24254821299760046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038146172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27330342,0.0102454815,0.58113766,0.046735793,0.015109997,0.0008868523,0.008118431,0.038075875,0.026386429],"genre_scores_gemma":[0.6328483,0.0021947646,0.32029295,0.013302195,0.0023210822,0.0010261649,0.0023680478,0.008133883,0.017512612],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9879957,0.005444114,0.001482862,0.0021602137,0.002663692,0.0002535226],"domain_scores_gemma":[0.8977763,0.05011961,0.01816509,0.021119796,0.011614342,0.0012048406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025940971,0.0008139571,0.0010051128,0.0015955255,0.0009798118,0.0021711932,0.0019105123,0.0017232398,0.019648004],"category_scores_gemma":[0.12841868,0.0010326289,0.0008339361,0.001358614,0.0019665267,0.0021378503,0.0015566864,0.0016987781,0.006945617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019815825,0.00022908358,0.15245818,0.0037378683,0.0018018098,0.003404038,0.005625718,0.0045785354,0.025626209,0.0130995475,0.29526797,0.4921895],"study_design_scores_gemma":[0.00050755066,0.00081843184,0.2757659,0.0060100565,0.0010962216,0.01461163,0.002822598,0.05154884,0.110618055,0.12118699,0.4143423,0.00067141565],"about_ca_topic_score_codex":0.002514027,"about_ca_topic_score_gemma":0.0050207325,"teacher_disagreement_score":0.025940971,"about_ca_system_score_codex":0.0006372401,"about_ca_system_score_gemma":0.0013408241,"threshold_uncertainty_score":0.13719058},"labels":[],"label_agreement":null},{"id":"W3038220767","doi":"10.1016/j.neuroimage.2020.117129","title":"Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":313,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research; Johnson and Johnson; Janssen Research and Development; National Institutes of Health; H. Lundbeck A/S; IXICO; Genentech; GE Healthcare; Fujirebio US; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Southern California; Merck","keywords":"Scanner; Longitudinal data; Computer science; Artificial intelligence; Data science; Data mining","score_opus":0.46129922390750755,"score_gpt":0.4545831753150153,"score_spread":0.006716048592492252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038220767","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011066263,0.00016006966,0.98497933,0.00019416978,0.00011253289,0.00029771493,0.0010910294,0.0016828001,0.00041602898],"genre_scores_gemma":[0.112674154,0.00021280261,0.8766105,0.00036365792,0.00025036783,0.001572142,0.0060287057,0.00096325995,0.0013243146],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.989007,0.006315648,0.0008224336,0.0019401589,0.0015934354,0.0003213514],"domain_scores_gemma":[0.977829,0.009343111,0.0021964395,0.0073774396,0.002886933,0.000367102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023739316,0.0012257274,0.0015951085,0.0032846718,0.00093067874,0.0016387088,0.0025355914,0.0012163381,0.003702731],"category_scores_gemma":[0.047705967,0.0011721262,0.0029115886,0.003689155,0.0013184136,0.0018290961,0.0036556444,0.0022254062,0.0011591939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020039845,0.00041087752,0.05001253,0.0007021835,0.0033202886,0.00058769895,0.0014825407,0.1339106,0.012839165,0.03780942,0.035119075,0.7218017],"study_design_scores_gemma":[0.00063275144,0.001079955,0.03322767,0.00015308236,0.0006739248,0.0014524133,0.000659191,0.8080866,0.010880267,0.081238866,0.061579365,0.00033590666],"about_ca_topic_score_codex":0.0027661803,"about_ca_topic_score_gemma":0.0027105259,"teacher_disagreement_score":0.023739316,"about_ca_system_score_codex":0.00061044685,"about_ca_system_score_gemma":0.0020406137,"threshold_uncertainty_score":0.12554705},"labels":[],"label_agreement":null},{"id":"W3038476824","doi":"10.1016/j.nicl.2020.102340","title":"Post-mortem 7 Tesla MRI detection of white matter hyperintensities: A multidisciplinary voxel-wise comparison of imaging and histological correlates","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Health Research","keywords":"Hyperintensity; White matter; Magnetic resonance imaging; Voxel; Medicine; Neuroimaging; Pathology; Neuroscience; Radiology; Psychology","score_opus":0.10254094753991623,"score_gpt":0.4015952357323905,"score_spread":0.29905428819247426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038476824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9872416,0.0017068035,0.009485286,0.000057749276,0.000020123069,0.000076133874,0.00018484685,0.000118381446,0.0011090764],"genre_scores_gemma":[0.9853666,0.0006812807,0.012739895,0.000043213397,0.000028482827,0.000048403173,0.00039347558,0.000038548955,0.0006601317],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996737,0.00009308522,0.000042928845,0.00010270446,0.000054115666,0.000033483204],"domain_scores_gemma":[0.9986413,0.00027542512,0.0004046981,0.00016308471,0.0003810853,0.00013448056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015625836,0.00038775973,0.00043254058,0.0013615459,0.00029915367,0.0005976569,0.0003197817,0.00054388866,0.0005820844],"category_scores_gemma":[0.0022507815,0.00023801895,0.00021102968,0.0003113039,0.0004242953,0.0004962684,0.00040431204,0.00030658927,0.0003040904],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017694684,0.00036937144,0.34212488,0.00047289187,0.00066863414,0.0016006234,0.0011413565,0.0007969373,0.56451297,0.00038651028,0.0009479574,0.08520834],"study_design_scores_gemma":[0.00001768626,0.0014529749,0.95301884,0.000039753686,0.00018886081,0.0045281234,0.0004268246,0.001564738,0.037244663,0.00042788466,0.0010567195,0.00003292024],"about_ca_topic_score_codex":0.0005402551,"about_ca_topic_score_gemma":0.0019739894,"teacher_disagreement_score":0.0015625836,"about_ca_system_score_codex":0.00017041978,"about_ca_system_score_gemma":0.00018552288,"threshold_uncertainty_score":0.008263826},"labels":[],"label_agreement":null},{"id":"W3038661352","doi":"10.1101/2020.07.01.183038","title":"Surface-Based Connectivity Integration","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"White matter; Human Connectome Project; Diffusion MRI; Diffusion imaging; Computer science; Connectome; Functional connectivity; High resolution; Neuroscience; Pattern recognition (psychology); Artificial intelligence; Psychology; Magnetic resonance imaging; Geology; Medicine","score_opus":0.062445125858220006,"score_gpt":0.30318049289518945,"score_spread":0.24073536703696943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038661352","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027414916,0.000288094,0.9671242,0.0001817811,0.000041420913,0.00007455075,0.0003350228,0.000846664,0.0036933874],"genre_scores_gemma":[0.61661,0.0004319997,0.3779911,0.00013232163,0.00012745384,0.00022934788,0.001500437,0.00044334686,0.0025340526],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990163,0.0002636928,0.00003585205,0.00023772939,0.00036942156,0.0000770137],"domain_scores_gemma":[0.99859005,0.0004911405,0.00017618151,0.00019716269,0.00047653235,0.00006892482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010083806,0.00081251253,0.00094645284,0.0038906164,0.0004124832,0.0015463423,0.0011886419,0.0009184954,0.0037231375],"category_scores_gemma":[0.004342782,0.00034415512,0.001065675,0.003178926,0.0011660985,0.0017750409,0.0014667448,0.0010685266,0.00069972884],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015353141,0.00008069039,0.004161416,0.00021454284,0.00024848545,0.00024265698,0.00039668332,0.5377498,0.020991381,0.14293705,0.0053051957,0.28751853],"study_design_scores_gemma":[0.0000057249845,0.000028269345,0.001199744,0.000011000837,0.000018622099,0.000045410987,0.000024665474,0.96010476,0.0012211216,0.035833765,0.0014905424,0.000016298063],"about_ca_topic_score_codex":0.004802803,"about_ca_topic_score_gemma":0.0037235797,"teacher_disagreement_score":0.004802803,"about_ca_system_score_codex":0.001093756,"about_ca_system_score_gemma":0.0007127849,"threshold_uncertainty_score":0.012455165},"labels":[],"label_agreement":null},{"id":"W3039504579","doi":"10.1016/j.cmpb.2020.105636","title":"VBM sensitivity to localization and extent of mouse brain lesions: A simulation approach","year":2020,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Agencia Nacional de Promoción Científica y Tecnológica","keywords":"Voxel; Computer science; Neuroimaging; Artificial intelligence; Workflow; Preprocessor; Voxel-based morphometry; Pattern recognition (psychology); Pipeline (software); Magnetic resonance imaging; Computer vision; Psychology; Neuroscience; Medicine; Radiology; White matter","score_opus":0.2049777215591546,"score_gpt":0.45221734157210725,"score_spread":0.24723962001295263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039504579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4826962,0.0009978585,0.5047306,0.00093147863,0.00006872548,0.00014237208,0.00061080366,0.0013695649,0.008452469],"genre_scores_gemma":[0.9658372,0.00021585467,0.03234586,0.00015173142,0.000011648312,0.00008242276,0.00014727816,0.00018709994,0.0010210708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957126,0.00023985025,0.000015697895,0.00005784527,0.0000800726,0.000035215468],"domain_scores_gemma":[0.99340546,0.0057098996,0.000350238,0.00022694253,0.00024404544,0.00006335954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021118592,0.0005310291,0.0006780386,0.0010767545,0.0003117536,0.00095534633,0.0009682989,0.0016305076,0.0013653024],"category_scores_gemma":[0.014652876,0.0006527431,0.00066008465,0.00070657185,0.00061089644,0.00045181537,0.00060346344,0.00068469543,0.00017347862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015085677,0.000031558633,0.0014534274,0.000037813737,0.00005496119,0.000071788396,0.000043742384,0.98897994,0.003374718,0.0018248667,0.00019701025,0.0037792705],"study_design_scores_gemma":[0.000011855314,0.000026646896,0.00055941875,0.000008756061,0.000019757697,0.00007048087,0.000008725119,0.9962392,0.0014730952,0.0014159046,0.00015787772,0.000008311794],"about_ca_topic_score_codex":0.011500389,"about_ca_topic_score_gemma":0.005077801,"teacher_disagreement_score":0.011500389,"about_ca_system_score_codex":0.0009546498,"about_ca_system_score_gemma":0.0009411595,"threshold_uncertainty_score":0.022866905},"labels":[],"label_agreement":null},{"id":"W3040060243","doi":"10.1101/2020.07.02.185397","title":"Microstructural characterization and validation of a 3D printed axon-mimetic phantom for diffusion MRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Research Council Canada; Western Economic Diversification Canada; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Canada First Research Excellence Fund; University of Saskatchewan; Canadian Light Source","keywords":"Imaging phantom; Reproducibility; Characterization (materials science); Microscopy; Confocal microscopy; Anisotropy; Tortuosity; Kurtosis; Diffusion","score_opus":0.031108065820987178,"score_gpt":0.283938934636493,"score_spread":0.2528308688155058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040060243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8374462,0.00083568174,0.15779917,0.00016790142,0.000051783434,0.0001899561,0.00057772093,0.0008560571,0.002075473],"genre_scores_gemma":[0.8518628,0.00043483806,0.14511465,0.000082554805,0.000010928565,0.00022140563,0.00044726703,0.00016163955,0.0016638618],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996063,0.00008012047,0.000028531675,0.00007073257,0.00018821769,0.000026075064],"domain_scores_gemma":[0.9987123,0.00049991807,0.00030667067,0.0002092124,0.00020635875,0.00006555745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011174649,0.00047001056,0.00021632346,0.0004404553,0.00018191975,0.0005055139,0.00037097532,0.00056265225,0.0005407087],"category_scores_gemma":[0.00168249,0.0002666423,0.0002339455,0.00022044823,0.0004251611,0.00031564117,0.0002473739,0.00029587388,0.0003065799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025421474,0.000014221462,0.0002064107,0.000026763892,0.0000030258427,0.000064438784,0.000033520653,0.0010950629,0.9968491,0.000089171204,0.00002784491,0.0015650489],"study_design_scores_gemma":[0.0000041639664,0.00013137273,0.0020643957,0.0000054081675,0.000008511049,0.00025062755,0.00001650848,0.006705226,0.989513,0.000059373346,0.001229367,0.000012160697],"about_ca_topic_score_codex":0.0004314281,"about_ca_topic_score_gemma":0.0006055797,"teacher_disagreement_score":0.0011174649,"about_ca_system_score_codex":0.0003803288,"about_ca_system_score_gemma":0.00029564518,"threshold_uncertainty_score":0.0059098005},"labels":[],"label_agreement":null},{"id":"W3040109440","doi":"10.1038/s42003-020-1050-x","title":"A time-dependent diffusion MRI signature of axon caliber variations and beading","year":2020,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; U.S. Department of Health and Human Services; National Institutes of Health; Center for Advanced Imaging Innovation and Research; National Institute of Biomedical Imaging and Bioengineering; York University","keywords":"Caliber; Signature (topology); Diffusion MRI; Diffusion; Neuroscience; Medicine; Biology; Physics; Magnetic resonance imaging; Mathematics; Radiology; Materials science; Geometry","score_opus":0.07668858133215542,"score_gpt":0.36070362206639867,"score_spread":0.2840150407342432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040109440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7944059,0.0013978989,0.19783556,0.00035723636,0.000048402966,0.00004626596,0.0004620044,0.0007518489,0.004694959],"genre_scores_gemma":[0.9761421,0.00042426022,0.021797422,0.000058540118,0.000014971905,0.000018883387,0.00015281308,0.00007562192,0.0013153896],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994445,0.0000059610993,0.0000026385878,0.000017712724,0.000020389281,0.000008824969],"domain_scores_gemma":[0.99964404,0.00010532345,0.00013299692,0.000037066024,0.000039541486,0.00004095025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012582573,0.00019676676,0.00013203002,0.00036058165,0.00017892609,0.00028640236,0.00019120218,0.00029507861,0.0011922432],"category_scores_gemma":[0.00084594643,0.00013841157,0.000102833095,0.00024321082,0.00035630612,0.00046037172,0.00023997338,0.00039522178,0.00018777719],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054638553,0.000014044738,0.001833465,0.00007781733,0.000013070029,0.00011767951,0.000067277426,0.0019530129,0.9887446,0.0010470103,0.00015533667,0.0059219333],"study_design_scores_gemma":[0.000018156108,0.00024243977,0.05204671,0.000029496785,0.000051126914,0.0021781118,0.00012386568,0.06332514,0.8736653,0.0037861913,0.004481113,0.000052453186],"about_ca_topic_score_codex":0.0005479113,"about_ca_topic_score_gemma":0.000957392,"teacher_disagreement_score":0.0011922432,"about_ca_system_score_codex":0.00016981766,"about_ca_system_score_gemma":0.00015691202,"threshold_uncertainty_score":0.003988445},"labels":[],"label_agreement":null},{"id":"W3040260334","doi":"10.1016/j.nicl.2020.102338","title":"Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; H. Lundbeck A/S; Arizona Alzheimer’s Consortium; Genentech; Fujirebio US; GE Healthcare; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Canadian Institutes of Health Research; University of Southern California","keywords":"Magnetic resonance imaging; Cardiology; Medicine; Internal medicine; Biomarker; Cognitive decline; Cohort; Neuroimaging; Disease; Psychology; Radiology; Dementia; Psychiatry; Biology","score_opus":0.18913676788077588,"score_gpt":0.4249174092099615,"score_spread":0.23578064132918564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040260334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944072,0.00009576223,0.00501782,0.000015251558,0.000004801322,0.00001334441,0.00021249226,0.00009056484,0.00014276944],"genre_scores_gemma":[0.99462694,0.00004953989,0.0049007228,0.000008842129,0.0000069010034,0.000015024381,0.00028458174,0.000014459558,0.00009311665],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987614,0.000028269846,0.000010492994,0.000046030953,0.000025262072,0.000013749297],"domain_scores_gemma":[0.99968207,0.00008643756,0.00009546275,0.00006990282,0.000039970477,0.000026219155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048800086,0.0003172401,0.0002578992,0.0013458751,0.00017188003,0.00047310846,0.0002448222,0.00028353685,0.00039944286],"category_scores_gemma":[0.0011390331,0.00014731246,0.00026991835,0.00059039827,0.0002853095,0.00023676276,0.00036032096,0.00015705872,0.0001110647],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017988542,0.000111395006,0.7341335,0.000106264764,0.00037337551,0.0006644586,0.00089865836,0.0070025786,0.12836549,0.00047740978,0.0005986981,0.12546924],"study_design_scores_gemma":[0.000018897712,0.00031626306,0.95935196,0.000008319018,0.0000766317,0.00073542754,0.000355023,0.032015126,0.0060851662,0.0006328067,0.00038549438,0.00001890218],"about_ca_topic_score_codex":0.0022893918,"about_ca_topic_score_gemma":0.0031857134,"teacher_disagreement_score":0.0022893918,"about_ca_system_score_codex":0.00016416448,"about_ca_system_score_gemma":0.00015653798,"threshold_uncertainty_score":0.0045521855},"labels":[],"label_agreement":null},{"id":"W3041096751","doi":"10.1038/s41467-020-17328-9","title":"Synucleinopathy alters nanoscale organization and diffusion in the brain extracellular space through hyaluronan remodeling","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; LabEx BRAIN; Centre National de la Recherche Scientifique; Institut National de la Santé et de la Recherche Médicale; Université de Bordeaux; Eusko Jaurlaritza; Agence Nationale de la Recherche; Association France Parkinson; Ottawa Hospital Research Institute; Fondation pour l'Aide à la Recherche sur la Sclérose en Plaques","keywords":"Extracellular matrix; Microglia; Extracellular; Neurodegeneration; Neuroscience; Biophysics; Cell biology; Chemistry; Biology; Pathology; Inflammation; Medicine; Disease; Immunology","score_opus":0.05432275051677585,"score_gpt":0.3348001035359066,"score_spread":0.2804773530191308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041096751","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99532723,0.0011194061,0.0029139875,0.00006058534,0.0000066513744,0.0000052872333,0.00009910023,0.0000420284,0.00042574582],"genre_scores_gemma":[0.9960372,0.0008417618,0.0019774341,0.000033667664,0.000004351743,0.000009293789,0.00008820444,0.000011875551,0.0009962502],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999944,0.000008864263,0.0000039848387,0.000016722375,0.000016051185,0.00001040841],"domain_scores_gemma":[0.9999075,0.000011341454,0.00004753114,0.0000063848274,0.000009966898,0.00001724303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008537279,0.00020038379,0.000113198315,0.00021878626,0.00011684612,0.00026252776,0.00008437423,0.00022391453,0.00046149892],"category_scores_gemma":[0.00006371256,0.000118370735,0.000108708286,0.00010704413,0.0002395338,0.0002905678,0.00015220462,0.00026866773,0.00009167381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063908774,0.000006359387,0.00067577645,0.000021110744,0.0000065630084,0.00010764944,0.000022815862,0.00007610744,0.9979456,0.00010919368,0.000020118785,0.00094485376],"study_design_scores_gemma":[0.000010477056,0.00017260449,0.04354551,0.000017776681,0.000035671776,0.001190645,0.00015558905,0.0027413892,0.94990045,0.00049608765,0.0017235619,0.0000101582855],"about_ca_topic_score_codex":0.0003794936,"about_ca_topic_score_gemma":0.000619368,"teacher_disagreement_score":0.00046149892,"about_ca_system_score_codex":0.00015778808,"about_ca_system_score_gemma":0.00009006663,"threshold_uncertainty_score":0.0015438199},"labels":[],"label_agreement":null},{"id":"W3041520709","doi":"10.1101/2020.07.10.197921","title":"Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Reproducibility; Kurtosis; Human Connectome Project; Diffusion imaging; Diffusion MRI; Imaging phantom; Effective diffusion coefficient; White matter; Pearson product-moment correlation coefficient; Nuclear medicine; Mathematics; Statistics; Medicine; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.13042504876051228,"score_gpt":0.36884988830109555,"score_spread":0.23842483954058327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041520709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7529362,0.0019165002,0.23764096,0.00027850282,0.0001024326,0.00022822728,0.0030432888,0.0017166286,0.002137256],"genre_scores_gemma":[0.9648243,0.0001936605,0.032128505,0.00005742446,0.0000264609,0.00013794396,0.0017928655,0.0005479906,0.00029082393],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9922827,0.0035899554,0.0010786477,0.0014760537,0.0013910161,0.00018171775],"domain_scores_gemma":[0.95391375,0.023632059,0.0057656025,0.007973794,0.008266763,0.00044804832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022166517,0.0008547104,0.0008667376,0.0019022622,0.00055747264,0.002096227,0.0009673836,0.0010492922,0.00139892],"category_scores_gemma":[0.06549709,0.00048494712,0.0011442766,0.0016132555,0.00077100337,0.0010800461,0.0010854226,0.0005082856,0.00055867585],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008183626,0.0003810655,0.4859515,0.0017635311,0.008321237,0.000853942,0.0022948778,0.1442731,0.10956722,0.0021436103,0.0053840037,0.23088224],"study_design_scores_gemma":[0.00027082374,0.0011830239,0.58610487,0.0002336121,0.0018363365,0.0027876229,0.000568499,0.3154958,0.078496486,0.006175149,0.0062819086,0.0005658799],"about_ca_topic_score_codex":0.0024237633,"about_ca_topic_score_gemma":0.0026840908,"teacher_disagreement_score":0.022166517,"about_ca_system_score_codex":0.0005073889,"about_ca_system_score_gemma":0.00056264445,"threshold_uncertainty_score":0.11722916},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W3041613148","doi":"10.1089/neu.2020.7170","title":"Diffusion Tensor Imaging in Contact and Non-Contact University-Level Sport Athletes","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Carleton University; Université de Sherbrooke; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Corticospinal tract; Athletes; Medicine; Pyramidal tracts; Magnetic resonance imaging; Psychology; Tractography; Physical medicine and rehabilitation; Physical therapy; Audiology; Anatomy; Radiology","score_opus":0.1042042585678643,"score_gpt":0.3281349210044294,"score_spread":0.22393066243656512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041613148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99981123,0.00003521277,0.00002879524,0.000004211429,5.503207e-7,0.0000030769131,0.000013603466,5.394826e-7,0.000102694394],"genre_scores_gemma":[0.9997125,0.00003283213,0.000053834803,0.000004121236,0.0000019982035,0.000004236434,0.00003553861,6.2389097e-7,0.00015425953],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987876,0.000024763815,0.000013078793,0.00003329664,0.000017719705,0.00003224403],"domain_scores_gemma":[0.99965024,0.000044765733,0.0001326002,0.000023829427,0.000045966775,0.00010252335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026659018,0.00022223765,0.00022231224,0.0006278289,0.00030214584,0.00030621156,0.00013704262,0.0003264205,0.0012402743],"category_scores_gemma":[0.0009912348,0.00012208469,0.0001222296,0.0003232469,0.00027751454,0.00022903256,0.0003721948,0.00015397088,0.00015199634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001899162,0.00044259813,0.94645387,0.00009163149,0.0001667172,0.0010274039,0.0019350466,0.00015310435,0.032955628,0.00006834013,0.00010118392,0.014705182],"study_design_scores_gemma":[0.0000048735737,0.0002894558,0.9983342,0.0000025733416,0.000012661697,0.0003685964,0.0003685778,0.000087732165,0.0004788399,0.000017026008,0.000033176668,0.0000021889773],"about_ca_topic_score_codex":0.00412618,"about_ca_topic_score_gemma":0.0075727277,"teacher_disagreement_score":0.00412618,"about_ca_system_score_codex":0.00021202702,"about_ca_system_score_gemma":0.00019494191,"threshold_uncertainty_score":0.008204341},"labels":[],"label_agreement":null},{"id":"W3042104279","doi":"10.1016/j.neuroimage.2020.117147","title":"Groupwise track filtering via iterative message passing and pruning","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Research and Development; NIH Blueprint for Neuroscience Research; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; National Eye Institute; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Alzheimer's Association; Fujirebio US; BioClinica; U.S. Department of Defense; University of Southern California; Bristol-Myers Squibb; Northern California Institute for Research and Education; Merck; Alzheimer's Drug Discovery Foundation; Johnson and Johnson; AbbVie; National Institute on Aging","keywords":"Human Connectome Project; Computer science; Tractography; Artificial intelligence; Pruning; False positive paradox; Consistency (knowledge bases); Diffusion MRI; Prior probability; Pattern recognition (psychology); Computer vision; Neuroscience; Magnetic resonance imaging","score_opus":0.08999241902420518,"score_gpt":0.33917935358025914,"score_spread":0.24918693455605395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042104279","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050882674,0.00006755838,0.99404186,0.000057174868,0.000020214507,0.000048578593,0.000020295987,0.0004491468,0.00020695727],"genre_scores_gemma":[0.09049032,0.00010392343,0.906739,0.000086370586,0.00006508635,0.0003158496,0.00029343728,0.00015661544,0.0017494132],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971499,0.0005934431,0.00026144175,0.00052020565,0.0012420473,0.00023304306],"domain_scores_gemma":[0.9925547,0.004002191,0.0007684814,0.0010536403,0.0014118693,0.00020907995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038514119,0.0015864326,0.002216204,0.002624607,0.0015599278,0.0016834714,0.002521056,0.0022225005,0.001801972],"category_scores_gemma":[0.013906113,0.00075198757,0.0014135069,0.0025269038,0.001378656,0.002002952,0.0025806746,0.0022448215,0.0010434109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036232403,0.00020758793,0.0027031242,0.0001977164,0.00019346167,0.0003033967,0.0007991273,0.37745252,0.020590663,0.023125963,0.003104008,0.57096004],"study_design_scores_gemma":[0.000038637343,0.000075532254,0.00029710052,0.000011346874,0.000026670308,0.0000665485,0.000034597615,0.9825173,0.006414969,0.0087116,0.001790629,0.000014969421],"about_ca_topic_score_codex":0.010601289,"about_ca_topic_score_gemma":0.016163455,"teacher_disagreement_score":0.010601289,"about_ca_system_score_codex":0.0013206098,"about_ca_system_score_gemma":0.0030278163,"threshold_uncertainty_score":0.021079123},"labels":[],"label_agreement":null},{"id":"W3042227298","doi":"10.1101/2020.07.15.205401","title":"PhyloBrain atlas: a cortical brain MRI atlas following a phylogenetic approach","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval; Montreal Neurological Institute and Hospital; Université du Québec à Trois-Rivières","funders":"","keywords":"Precuneus; Cortex (anatomy); Neocortex; Neuroscience; Anatomy; Biology; Posterior cingulate; Temporal cortex; Functional magnetic resonance imaging","score_opus":0.04230195230271715,"score_gpt":0.291712293993612,"score_spread":0.24941034169089482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042227298","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0593562,0.0018846545,0.7678191,0.0008196316,0.00021014728,0.0006698588,0.10245674,0.027623458,0.03916029],"genre_scores_gemma":[0.20487984,0.0016950311,0.6827899,0.00027585268,0.000086879074,0.002279608,0.08378185,0.0057835327,0.018427486],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997464,0.00007422047,0.000021906495,0.0000771333,0.000049482907,0.000030927127],"domain_scores_gemma":[0.9996854,0.00008692973,0.000051358875,0.00006665006,0.00008869704,0.00002099637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060097297,0.00058103155,0.00035947745,0.0027065624,0.0005940531,0.0013924304,0.0009441764,0.00066162867,0.02351533],"category_scores_gemma":[0.0011836529,0.0004195563,0.00047705421,0.0025583107,0.00031077312,0.0005323866,0.0010280273,0.0008218118,0.00659559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012388297,0.00016457985,0.013968043,0.00245435,0.0004426467,0.0022659209,0.0019308025,0.046485115,0.13873076,0.08054601,0.28477123,0.42700174],"study_design_scores_gemma":[0.00013980083,0.00019797374,0.06300413,0.00039885892,0.00028774753,0.0058309515,0.0004626114,0.09314125,0.03666343,0.038693145,0.76105607,0.0001240031],"about_ca_topic_score_codex":0.0040563834,"about_ca_topic_score_gemma":0.0073517715,"teacher_disagreement_score":0.02351533,"about_ca_system_score_codex":0.0007018406,"about_ca_system_score_gemma":0.0013002075,"threshold_uncertainty_score":0.07866669},"labels":[],"label_agreement":null},{"id":"W3042920381","doi":"10.1016/j.jneumeth.2020.108870","title":"Regional segmentation strategy for DTI analysis of human corpus callosum indicates motor function deficit in mild cognitive impairment","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; University of Warwick; National Institute on Aging; Alzheimer's Disease Neuroimaging Initiative","keywords":"Corpus callosum; White matter; Diffusion MRI; Fractional anisotropy; Ageing; Psychology; Audiology; Cognition; Neuroscience; Medicine; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.3033377687154771,"score_gpt":0.5005663825420017,"score_spread":0.19722861382652462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042920381","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51265115,0.0017370313,0.47765693,0.00036966836,0.00007166925,0.00028207936,0.0014184526,0.0017335718,0.0040794266],"genre_scores_gemma":[0.5898537,0.00083886925,0.40430453,0.00009296724,0.00003618324,0.00023345141,0.0012145172,0.00056404935,0.0028616737],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990666,0.000019343775,0.000011386877,0.000030070662,0.000015311352,0.000017267666],"domain_scores_gemma":[0.999731,0.000090923284,0.000032106534,0.000033941415,0.000084859974,0.000027258053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005761544,0.00045944165,0.000255922,0.0015269803,0.00045602067,0.0008833871,0.00035183015,0.00043315886,0.0016761778],"category_scores_gemma":[0.001153737,0.00027057691,0.00041219473,0.00072342803,0.00022352993,0.0003204284,0.0003390756,0.00026926753,0.00049224193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010626998,0.00011755635,0.009498385,0.00036808764,0.00015926563,0.0013761037,0.0006873622,0.014047402,0.6937752,0.005695095,0.003057228,0.27015558],"study_design_scores_gemma":[0.00013960515,0.00076668407,0.13011415,0.00021472441,0.0008651364,0.007080374,0.0009390796,0.31943864,0.5098543,0.010066249,0.020344343,0.00017669387],"about_ca_topic_score_codex":0.0059506013,"about_ca_topic_score_gemma":0.009941256,"teacher_disagreement_score":0.0059506013,"about_ca_system_score_codex":0.00035099714,"about_ca_system_score_gemma":0.0011664801,"threshold_uncertainty_score":0.011831939},"labels":[],"label_agreement":null},{"id":"W3043095919","doi":"10.1016/j.neuroimage.2020.117168","title":"Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; National Imaging Facility","keywords":"Diffusion MRI; White matter; Tractography; Neurite; Neuroscience; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.024381645378773905,"score_gpt":0.2909073755795447,"score_spread":0.2665257302007708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043095919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99887985,0.00020748889,0.00025352655,0.000014750683,0.0000011557441,0.0000025377255,0.00030657998,0.000007848461,0.00032620237],"genre_scores_gemma":[0.9983851,0.0002244383,0.0007271264,0.0000045709016,0.0000014116388,0.000008344073,0.00038390866,0.000006975192,0.0002581161],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997875,0.000026473315,0.000018274211,0.00006369384,0.0000610606,0.000043121916],"domain_scores_gemma":[0.9989115,0.0002064251,0.0005418232,0.00007451238,0.00017713702,0.000088574125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005888933,0.00025320513,0.00020186057,0.0007382551,0.00027129945,0.0004927468,0.00018225674,0.00023506432,0.001171004],"category_scores_gemma":[0.0018560535,0.00019555644,0.00017042857,0.0004502119,0.000358972,0.00036513305,0.00031607237,0.00025351337,0.00016384515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028415074,0.00003316581,0.97015667,0.00004279647,0.000059527498,0.00032296233,0.0006404584,0.00031393644,0.012255106,0.00013701298,0.00020190545,0.015552369],"study_design_scores_gemma":[6.494598e-7,0.000013952901,0.99884474,0.0000042810384,0.0000050487524,0.00021260534,0.00007969842,0.00007219955,0.00066710875,0.000024542158,0.00007361282,0.0000016200573],"about_ca_topic_score_codex":0.018072128,"about_ca_topic_score_gemma":0.028448762,"teacher_disagreement_score":0.018072128,"about_ca_system_score_codex":0.000550257,"about_ca_system_score_gemma":0.00045747924,"threshold_uncertainty_score":0.035933852},"labels":[],"label_agreement":null},{"id":"W3043265686","doi":"10.1016/j.neuroimage.2020.117172","title":"Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère de l'Enseignement Supérieur et de la Recherche; Max-Planck-Gesellschaft; Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur et de la Recherche Scientifique; Deutsche Forschungsgemeinschaft","keywords":"Diffusion MRI; Computer science; SIGNAL (programming language); Signal-to-noise ratio (imaging); Noise (video); Sensitivity (control systems); Monte Carlo method; Image quality; Algorithm; Artificial intelligence; Encoding (memory); Contrast (vision); Echo (communications protocol); Diffusion; Pattern recognition (psychology); Computer vision; Mathematics; Statistics; Magnetic resonance imaging; Image (mathematics); Physics; Radiology; Medicine; Telecommunications","score_opus":0.07418862732828188,"score_gpt":0.3405270439910454,"score_spread":0.2663384166627635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043265686","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10523636,0.0021609825,0.88925433,0.0002332615,0.00007201407,0.00006464263,0.00006350765,0.0008772071,0.0020377259],"genre_scores_gemma":[0.4391115,0.0013883619,0.55745304,0.00013192299,0.00006808218,0.00012480526,0.00010549039,0.0002646075,0.0013522306],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991874,0.00034975013,0.00004029619,0.00017796783,0.00020850048,0.00003611948],"domain_scores_gemma":[0.9982582,0.0012391644,0.000164386,0.00014158302,0.00015834498,0.000038386424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016774478,0.00068012706,0.0006210411,0.00049408514,0.00018340697,0.0008103708,0.0005979958,0.0009805579,0.0012775735],"category_scores_gemma":[0.0059027444,0.00045712307,0.00038320303,0.00041093412,0.000486689,0.0010310889,0.0009903673,0.0007958289,0.00061064557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005602259,0.00011084728,0.003442675,0.00080325006,0.00020286364,0.00093155797,0.00028394427,0.06309016,0.7618634,0.00955054,0.000708794,0.1584518],"study_design_scores_gemma":[0.00006752022,0.00093103596,0.011192585,0.00013683442,0.00023775776,0.0042257765,0.00008027114,0.43369147,0.52673596,0.011295443,0.011237289,0.00016820316],"about_ca_topic_score_codex":0.00028967438,"about_ca_topic_score_gemma":0.0005948594,"teacher_disagreement_score":0.0016774478,"about_ca_system_score_codex":0.00023241586,"about_ca_system_score_gemma":0.00024762237,"threshold_uncertainty_score":0.008871317},"labels":[],"label_agreement":null},{"id":"W3043374188","doi":"10.1111/ejn.15055","title":"Multivariate white matter alterations are associated with epilepsy duration","year":2020,"lang":"en","type":"preprint","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Univariate; White matter; Multivariate statistics; Epilepsy; Fractional anisotropy; Multivariate analysis; Univariate analysis; Temporal lobe; Mahalanobis distance; Psychology; Cingulum (brain); Diffusion MRI; Internal medicine; Medicine; Magnetic resonance imaging; Mathematics; Neuroscience; Statistics; Radiology","score_opus":0.09154424593793947,"score_gpt":0.33626451412927505,"score_spread":0.24472026819133558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043374188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991093,0.00019093434,0.00031289962,0.000019617306,0.0000028670238,0.0000017052403,0.00011052466,0.000012431214,0.00023961897],"genre_scores_gemma":[0.99959475,0.000044500204,0.00010362802,0.0000038849594,0.00000572073,0.0000015316411,0.000096313684,0.000005658613,0.00014412485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999765,0.000038413837,0.000038577164,0.00007570862,0.000047745143,0.000034496687],"domain_scores_gemma":[0.997869,0.0004759844,0.001138993,0.00015542532,0.00013092505,0.00022954648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029798885,0.00028843313,0.00032146106,0.0008117189,0.0002059801,0.0003421781,0.00013814917,0.00022026796,0.0025117598],"category_scores_gemma":[0.0020133953,0.000120665754,0.0004149529,0.00054880686,0.0002629724,0.00027009056,0.00046731622,0.0002994781,0.00018430436],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084440893,0.000029837465,0.98060846,0.000027315664,0.0003459484,0.00040466356,0.0001858849,0.00026700602,0.008356526,0.00006383101,0.0000857054,0.008780455],"study_design_scores_gemma":[0.000003701975,0.0000800887,0.9983203,0.0000027453214,0.000041578485,0.0006800512,0.000038567076,0.00028677777,0.00039454363,0.000068741516,0.00007815992,0.000004713381],"about_ca_topic_score_codex":0.0015042932,"about_ca_topic_score_gemma":0.0022573553,"teacher_disagreement_score":0.0025117598,"about_ca_system_score_codex":0.00012590771,"about_ca_system_score_gemma":0.00015873653,"threshold_uncertainty_score":0.008402705},"labels":[],"label_agreement":null},{"id":"W3043604393","doi":"10.1016/j.mri.2020.07.007","title":"Evaluation of discrete orthogonal versus polar Stockwell Transform for local multi-resolution texture analysis using brain MRI of multiple sclerosis patients","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Pattern recognition (psychology); Artificial intelligence; Fluid-attenuated inversion recovery; Random forest; Invariant (physics); Computer science; Texture (cosmology); Magnetic resonance imaging; Mathematics; Image (mathematics); Medicine; Radiology","score_opus":0.12231463983093242,"score_gpt":0.35843186599575555,"score_spread":0.2361172261648231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043604393","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98421115,0.00046850953,0.014240223,0.000086821856,0.000024015473,0.000029718287,0.00024326605,0.00005901412,0.0006372972],"genre_scores_gemma":[0.99214536,0.00025299194,0.007098285,0.00001792838,0.00001612966,0.0000120972145,0.00020756459,0.00001991046,0.00022982339],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997782,0.000078071134,0.000020792648,0.000039579918,0.000054268105,0.00002921431],"domain_scores_gemma":[0.99902844,0.0004685467,0.000090084926,0.00005156061,0.00026147583,0.00009986529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010113275,0.00031098918,0.0003575677,0.0008570922,0.00015650886,0.00083054346,0.00018129237,0.0003989892,0.0012178818],"category_scores_gemma":[0.003275482,0.0000899794,0.00036085004,0.00038092188,0.00020474981,0.0005603138,0.00027946554,0.00021175832,0.00020479334],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019431774,0.00081497594,0.23344037,0.00064851117,0.0006723561,0.0011657949,0.0006824315,0.016828505,0.20543517,0.0012725272,0.0015849185,0.51802266],"study_design_scores_gemma":[0.00041993026,0.0034869832,0.5355601,0.00010391442,0.001077509,0.003594109,0.0016483252,0.38600907,0.06454449,0.0015857469,0.001854299,0.00011558093],"about_ca_topic_score_codex":0.0011646609,"about_ca_topic_score_gemma":0.0016245958,"teacher_disagreement_score":0.0012178818,"about_ca_system_score_codex":0.0001189258,"about_ca_system_score_gemma":0.00026103298,"threshold_uncertainty_score":0.005348444},"labels":[],"label_agreement":null},{"id":"W3043810011","doi":"10.1016/j.schres.2020.05.044","title":"Altered structural connectivity and cytokine levels in Schizophrenia and Genetic high-risk individuals: Associations with disease states and vulnerability","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"National Key Research and Development Program of China; National Science Fund for Distinguished Young Scholars; National High-tech Research and Development Program; China Medical University; Liaoning Revitalization Talents Program; University of Science and Technology Liaoning; National Natural Science Foundation of China","keywords":"Schizophrenia (object-oriented programming); Disease; Vulnerability (computing); Psychology; Neuroscience; Medicine; Psychiatry; Internal medicine","score_opus":0.0964157235275952,"score_gpt":0.38364696221648326,"score_spread":0.28723123868888806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043810011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991991,0.00021786995,0.00011892358,0.00006692392,0.0000030845868,0.0000022769882,0.00016027903,0.000002436112,0.00022905177],"genre_scores_gemma":[0.9993248,0.0001666511,0.00023331582,0.000016910097,0.000008314162,0.0000041088592,0.00013474135,0.0000021304493,0.00010905195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987817,0.00003196905,0.000010950194,0.000034170724,0.000019067742,0.000025648225],"domain_scores_gemma":[0.99943155,0.00010287973,0.00030278202,0.0000348065,0.000036718808,0.000091327194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023523696,0.0003438767,0.00025925462,0.0007383135,0.00035163888,0.0005069207,0.00020090549,0.00039483584,0.0013648876],"category_scores_gemma":[0.0011157007,0.0002202308,0.00021466512,0.0006895859,0.00031295695,0.00038211717,0.00046296662,0.00043004967,0.00007958888],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011481162,0.00009619695,0.97596925,0.000038954728,0.00040958024,0.0004013556,0.00039975785,0.00026158398,0.014885315,0.0003672352,0.00013602218,0.0058867135],"study_design_scores_gemma":[0.000005843113,0.000048902188,0.9985728,0.0000042193906,0.000041235377,0.00023434422,0.00016007655,0.00022790687,0.00025401145,0.00040196566,0.000044588116,0.0000040493287],"about_ca_topic_score_codex":0.0038101585,"about_ca_topic_score_gemma":0.0070946617,"teacher_disagreement_score":0.0038101585,"about_ca_system_score_codex":0.00029682973,"about_ca_system_score_gemma":0.00026493712,"threshold_uncertainty_score":0.007575989},"labels":[],"label_agreement":null},{"id":"W3044661579","doi":"10.1007/s42952-020-00082-5","title":"Nonparametric matrix regression function estimation over symmetric positive definite matrices","year":2020,"lang":"en","type":"article","venue":"Journal of the Korean Statistical Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Research Foundation of Korea","keywords":"Mathematics; Cholesky decomposition; Positive-definite matrix; Applied mathematics; Smoothing; Estimator; Wishart distribution; Statistics; Eigenvalues and eigenvectors; Multivariate statistics","score_opus":0.04228050699660648,"score_gpt":0.3581747937036231,"score_spread":0.31589428670701664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044661579","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050345156,0.000093205315,0.9943785,0.000053417352,0.000011075982,0.000014507073,0.000032959633,0.00015853262,0.0002231885],"genre_scores_gemma":[0.42003298,0.00066781783,0.5723926,0.00012794728,0.00016648606,0.0003007653,0.0008048399,0.00036277875,0.005143771],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963666,0.0022859524,0.00015325315,0.00059253944,0.00046168105,0.0001400262],"domain_scores_gemma":[0.98562324,0.009947138,0.0012842885,0.0013983055,0.0015780815,0.00016883238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058041443,0.0009240716,0.001203082,0.0010295793,0.0003458333,0.0014534696,0.0014449891,0.0009846367,0.001860403],"category_scores_gemma":[0.031604674,0.0006386391,0.00094539695,0.0009644391,0.00087808346,0.0024069794,0.0013089591,0.0018036608,0.00085440907],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053496327,0.00025718834,0.0053258706,0.00040403855,0.00033717498,0.000296818,0.00020620316,0.49708313,0.014028739,0.13824761,0.0050461777,0.33823204],"study_design_scores_gemma":[0.00001198792,0.000043763466,0.0007927054,0.0000135586215,0.000015068317,0.000063624415,0.000011943644,0.97312385,0.0017331359,0.023389298,0.00078650424,0.00001452892],"about_ca_topic_score_codex":0.0023305072,"about_ca_topic_score_gemma":0.0021194445,"teacher_disagreement_score":0.0058041443,"about_ca_system_score_codex":0.00051288033,"about_ca_system_score_gemma":0.0018319173,"threshold_uncertainty_score":0.030695677},"labels":[],"label_agreement":null},{"id":"W3044899728","doi":"10.1016/j.neuroscience.2020.06.027","title":"Corrigendum to “Brain Structural Connectivity Predicts Brain Functional Complexity: Diffusion Tensor Imaging Derived Centrality Accounts for Variance in Fractal Properties of Functional Magnetic Resonance Imaging Signal” [Neuroscience 438C (2020) 1–8]","year":2020,"lang":"en","type":"erratum","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Diffusion MRI; Neuroscience; Functional magnetic resonance imaging; Functional connectivity; Centrality; Neuroimaging; Magnetic resonance imaging; Fractal; SIGNAL (programming language); Connectome; Statistical physics; Psychology; Nuclear magnetic resonance; Physics; Computer science; Mathematics; Medicine; Mathematical analysis","score_opus":0.09736855223200129,"score_gpt":0.3124164307252884,"score_spread":0.2150478784932871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044899728","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009623692,0.0011124605,0.00064703496,0.07855248,0.91180414,0.000033492313,0.0013429205,0.00028345632,0.0061277305],"genre_scores_gemma":[0.0065292693,0.00636128,0.004420046,0.17184979,0.37204725,0.00027078518,0.0045460844,0.0010644288,0.43291107],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972887,0.00040506295,0.00045646547,0.0005610661,0.0010479075,0.00024076371],"domain_scores_gemma":[0.97910875,0.0049551046,0.0005343867,0.0011238025,0.013513212,0.00076482573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003342011,0.002289626,0.00233267,0.0034367691,0.0035483525,0.0033926456,0.003269312,0.0069799055,0.07564882],"category_scores_gemma":[0.041756384,0.0012033983,0.0021708915,0.001832416,0.0018793491,0.0020531584,0.002041547,0.008871263,0.051863253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008140756,0.0000035605256,0.000023092845,0.000020561052,0.0000037619166,0.000044769382,0.000005793033,0.000016691216,0.00001779275,0.00035400348,0.9976458,0.0018559445],"study_design_scores_gemma":[0.000041056788,0.00002275321,0.0015621551,0.00019487602,0.000046529916,0.00028140427,0.000046602345,0.00051179004,0.00029588165,0.0040481617,0.99289304,0.000055695124],"about_ca_topic_score_codex":0.05825755,"about_ca_topic_score_gemma":0.07924774,"teacher_disagreement_score":0.07564882,"about_ca_system_score_codex":0.0045384015,"about_ca_system_score_gemma":0.005327736,"threshold_uncertainty_score":0.25307047},"labels":[],"label_agreement":null},{"id":"W3044930821","doi":"10.1097/j.pain.0000000000002023","title":"Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography","year":2020,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Trigeminal neuralgia; Tractography; Medicine; Diffusion MRI; Process (computing); Psychology; Artificial intelligence; Computer science; Anesthesia; Radiology; Magnetic resonance imaging","score_opus":0.14605535532845418,"score_gpt":0.3691009170761813,"score_spread":0.22304556174772713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044930821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7987349,0.0004575208,0.19851594,0.00011024726,0.000018960976,0.00017032801,0.00048386428,0.0008134952,0.0006947583],"genre_scores_gemma":[0.9143532,0.0000970158,0.084407926,0.000014454932,0.000017966035,0.00007554316,0.00043440837,0.00006405849,0.0005354598],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993932,0.0002266249,0.000039878414,0.00016137949,0.000117523356,0.000061385435],"domain_scores_gemma":[0.9986345,0.00051628216,0.00033107886,0.00018876868,0.00023198138,0.00009737368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020394053,0.00073578634,0.0007290283,0.0027460232,0.00032977117,0.0010207512,0.0004110987,0.0006495716,0.0010488569],"category_scores_gemma":[0.003618182,0.00023802099,0.0010227846,0.0011926577,0.00047272374,0.0007878285,0.0006561699,0.0004839471,0.00026919256],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035017477,0.00051342807,0.25681555,0.00031149245,0.0019707421,0.0007398731,0.00085233786,0.13905567,0.06618385,0.003205162,0.002230183,0.52461994],"study_design_scores_gemma":[0.00003481138,0.00025380688,0.0625374,0.000025265097,0.00012517911,0.00025137875,0.00009584434,0.92799205,0.0063619665,0.0018143496,0.00047256795,0.000035485853],"about_ca_topic_score_codex":0.009755883,"about_ca_topic_score_gemma":0.012129862,"teacher_disagreement_score":0.009755883,"about_ca_system_score_codex":0.0008870401,"about_ca_system_score_gemma":0.0008834065,"threshold_uncertainty_score":0.019398212},"labels":[],"label_agreement":null},{"id":"W3045895067","doi":"10.1126/sciadv.aba8245","title":"A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information","year":2020,"lang":"en","type":"article","venue":"Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Computer science; Human brain; Tractography; Diffusion MRI; Modality (human–computer interaction); Magnetic resonance imaging; Artificial intelligence; Neuroscience; Neuroimaging; Brain anatomy; Medicine; Psychology; Radiology","score_opus":0.08814232277767962,"score_gpt":0.4413802390142868,"score_spread":0.35323791623660716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045895067","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016582601,0.0001252219,0.99737024,0.00007584234,0.000043537228,0.000028392478,0.000047675185,0.0002905322,0.00036031226],"genre_scores_gemma":[0.02652207,0.00031341618,0.9711109,0.00007528059,0.000070103146,0.000090552865,0.00013388463,0.0001366975,0.0015470878],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996773,0.000054459008,0.000016420003,0.000099901474,0.00013262578,0.00001922782],"domain_scores_gemma":[0.99958986,0.0001339161,0.00005991498,0.00008183512,0.00010275942,0.000031763546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006225428,0.00087762426,0.00056347926,0.0011686205,0.0004747486,0.0007739238,0.0008529274,0.0012174862,0.0023817262],"category_scores_gemma":[0.0016093502,0.00046783817,0.0007615598,0.0008806881,0.0005992331,0.0014408352,0.0011850806,0.001383744,0.0009278865],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016879685,0.00010760398,0.0010778921,0.0004283049,0.000173218,0.0004688081,0.00028054026,0.069769755,0.16446337,0.028039582,0.008067247,0.7269549],"study_design_scores_gemma":[0.000051549738,0.0001419135,0.0018399112,0.000042007116,0.0000878879,0.002277295,0.00004289769,0.9188965,0.039485432,0.013147616,0.023903314,0.000083609986],"about_ca_topic_score_codex":0.0015067582,"about_ca_topic_score_gemma":0.0030718383,"teacher_disagreement_score":0.0023817262,"about_ca_system_score_codex":0.00027643767,"about_ca_system_score_gemma":0.0009060015,"threshold_uncertainty_score":0.007967591},"labels":[],"label_agreement":null},{"id":"W3046299915","doi":"10.1016/j.jpsychires.2020.07.034","title":"Progression of neuroanatomical abnormalities after first-episode of psychosis: A 3-year longitudinal sMRI study","year":2020,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Galway; Health Research Board","keywords":"Putamen; Psychosis; Internal medicine; Medicine; Cardiology; Thalamus; Nuclear medicine; Antipsychotic; Psychology; Schizophrenia (object-oriented programming); Psychiatry; Radiology","score_opus":0.1758948120279407,"score_gpt":0.4786170864389108,"score_spread":0.3027222744109701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046299915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99944824,0.000110827445,0.00006261523,0.000038451173,0.0000054861493,0.000012588545,0.00013444772,0.000004392345,0.00018295652],"genre_scores_gemma":[0.9986847,0.00011146551,0.000093951494,0.000039735532,0.000011536207,0.000026968788,0.0006076383,0.0000030931767,0.00042080926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994985,0.0001037085,0.00003548295,0.000121115205,0.000068993046,0.0001722266],"domain_scores_gemma":[0.9986119,0.00009196133,0.00038173515,0.000116764684,0.00033575142,0.00046182517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013505142,0.000697423,0.00077909126,0.0011476907,0.0017706562,0.0010173528,0.0006595106,0.0013127765,0.0009135851],"category_scores_gemma":[0.0020175972,0.0005550909,0.0013404922,0.00091517024,0.0006512403,0.0017523034,0.0013306114,0.0016634047,0.00057171116],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010193414,0.00061758916,0.9926292,0.000013327247,0.00014733944,0.0008106459,0.0010138588,0.000066310015,0.001030175,0.00002666765,0.00017105778,0.0024545381],"study_design_scores_gemma":[0.000011431417,0.00058851304,0.9979837,0.0000061689575,0.000052614163,0.00044401904,0.000534268,0.00010678186,0.000084551124,0.000026544518,0.00014789976,0.000013491407],"about_ca_topic_score_codex":0.018891858,"about_ca_topic_score_gemma":0.0250197,"teacher_disagreement_score":0.018891858,"about_ca_system_score_codex":0.0009213704,"about_ca_system_score_gemma":0.0010512242,"threshold_uncertainty_score":0.0375638},"labels":[],"label_agreement":null},{"id":"W3046367338","doi":"10.1016/j.neuroimage.2020.117201","title":"On the cortical connectivity in the macaque brain: A comparison of diffusion tractography and histological tracing data","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Deutsche Forschungsgemeinschaft; Istituto Italiano di Tecnologia; Biotechnology and Biological Sciences Research Council; Centre d'Imagerie BioMédicale; Ministero dell’Istruzione, dell’Università e della Ricerca; École Polytechnique Fédérale de Lausanne","keywords":"Macaque; Tractography; Tracing; Diffusion MRI; Neuroscience; Diffusion; Computer science; Psychology; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.23989418107237792,"score_gpt":0.4038346123790556,"score_spread":0.16394043130667768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046367338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94089776,0.0015828678,0.055628814,0.000116291536,0.00001587654,0.000048822247,0.00037801135,0.0005167057,0.0008147322],"genre_scores_gemma":[0.95624524,0.00069853483,0.041797493,0.000019682186,0.000013437197,0.000032081556,0.00091528706,0.00009199768,0.00018622291],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993975,0.00015287491,0.00006685071,0.00016483029,0.00018241709,0.000035517893],"domain_scores_gemma":[0.99643195,0.0019741047,0.00039790844,0.00040942078,0.0007055393,0.000080959275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002108001,0.00059214025,0.00039761205,0.004589117,0.00032929896,0.00077793736,0.0003766113,0.00048046047,0.00047336135],"category_scores_gemma":[0.009967954,0.00014086776,0.0006367887,0.0016839178,0.0006631097,0.0008686971,0.0005811138,0.0002451069,0.000112224785],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006451103,0.00021989211,0.1343348,0.0013529356,0.00086449954,0.0011634344,0.0014915048,0.2949574,0.13843566,0.006881436,0.001273016,0.41838035],"study_design_scores_gemma":[0.00003128653,0.00059875794,0.2566339,0.00015222913,0.0003112884,0.0012670062,0.00035808666,0.69478846,0.039083526,0.0043587326,0.002315123,0.000101622354],"about_ca_topic_score_codex":0.00978639,"about_ca_topic_score_gemma":0.009511774,"teacher_disagreement_score":0.00978639,"about_ca_system_score_codex":0.00046568003,"about_ca_system_score_gemma":0.0005287071,"threshold_uncertainty_score":0.01945889},"labels":[],"label_agreement":null},{"id":"W3046471534","doi":"10.1101/2020.08.03.197384","title":"TractoFlow-ABS (Atlas-Based Segmentation)","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"White matter; Tractography; Atlas (anatomy); Diffusion MRI; Hyperintensity; Segmentation; Computer science; Artificial intelligence; Anatomy; Pattern recognition (psychology); Magnetic resonance imaging; Biology; Medicine; Radiology","score_opus":0.05107801343008658,"score_gpt":0.3052864410448513,"score_spread":0.2542084276147647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046471534","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012932158,0.0002535705,0.8204689,0.00017502064,0.0002479674,0.0002687495,0.0046245386,0.15626076,0.0047683306],"genre_scores_gemma":[0.06603289,0.000200696,0.88391066,0.00018596198,0.00007451468,0.00030980766,0.010406829,0.03091382,0.007964916],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99917287,0.0000866685,0.00007475426,0.00025007813,0.0003149881,0.00010065753],"domain_scores_gemma":[0.9988294,0.00023117784,0.00011586113,0.00044795766,0.0002912143,0.00008432823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013952731,0.002155295,0.0010325566,0.0023793073,0.001185661,0.002598852,0.0023831257,0.0015670037,0.026663976],"category_scores_gemma":[0.0039187395,0.0013844353,0.002373762,0.001793522,0.0007680861,0.00165743,0.003395799,0.00163492,0.012515863],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016775498,0.00023426145,0.0045227567,0.0011704369,0.0009315532,0.0006855475,0.0007432966,0.07532786,0.09764274,0.035934385,0.17069885,0.6104308],"study_design_scores_gemma":[0.00013805492,0.00022911637,0.0030095577,0.00011605118,0.000100865196,0.000870186,0.00008448799,0.6508784,0.17141257,0.028478937,0.14450434,0.00017738984],"about_ca_topic_score_codex":0.008731163,"about_ca_topic_score_gemma":0.011674795,"teacher_disagreement_score":0.026663976,"about_ca_system_score_codex":0.0012045514,"about_ca_system_score_gemma":0.0020245055,"threshold_uncertainty_score":0.0891999},"labels":[],"label_agreement":null},{"id":"W3046971735","doi":"10.1101/2020.08.06.237271","title":"White Matter Disruption in Pediatric Traumatic Brain Injury: Results from ENIGMA Pediatric msTBI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Hospital for Sick Children; University of Toronto; University of Calgary","funders":"Brain Injury Research Center; National Health and Medical Research Council; Medical Research Council; Alberta Children's Hospital Foundation; Children's Hospital Foundation; National Alliance for Research on Schizophrenia and Depression","keywords":"Traumatic brain injury; White matter; Context (archaeology); Medicine; Neuropathology; Concussion; Psychology; Diffusion MRI; Injury prevention; Poison control; Magnetic resonance imaging; Clinical psychology; Psychiatry; Internal medicine; Emergency medicine; Disease; Radiology","score_opus":0.043232185945327774,"score_gpt":0.2990356973281166,"score_spread":0.2558035113827888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046971735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924143,0.003592156,0.00074327004,0.00014604453,0.000013951858,0.000019903004,0.0023285686,0.000017429364,0.00072443305],"genre_scores_gemma":[0.9925149,0.0028762794,0.0012472478,0.00007857535,0.000026306621,0.00004049792,0.0029695784,0.000027489528,0.0002191488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99908507,0.00023007074,0.00012675153,0.00022515198,0.00022234178,0.000110576904],"domain_scores_gemma":[0.9974954,0.00038000222,0.0010517836,0.00027724906,0.0006314039,0.00016421465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021574518,0.00042824456,0.00038705269,0.002284447,0.00042391528,0.0010952047,0.00050038163,0.0002695881,0.0009028143],"category_scores_gemma":[0.0030349498,0.00025884018,0.0007852041,0.0032800497,0.0004646398,0.0005961887,0.0016116665,0.00046726476,0.0002773143],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061684215,0.000014940526,0.9906323,0.00007002013,0.00023991743,0.00012703105,0.0005466701,0.00012049825,0.00023028669,0.000061213934,0.0004313412,0.007464051],"study_design_scores_gemma":[0.0000017553471,0.00003654878,0.9971269,0.0000647631,0.00013914466,0.00042684868,0.0009090972,0.00009793243,0.00018642694,0.0000512969,0.0009547695,0.000004569105],"about_ca_topic_score_codex":0.011897,"about_ca_topic_score_gemma":0.016711919,"teacher_disagreement_score":0.011897,"about_ca_system_score_codex":0.00046337437,"about_ca_system_score_gemma":0.00089715084,"threshold_uncertainty_score":0.023655474},"labels":[],"label_agreement":null},{"id":"W3047160690","doi":"10.1101/2020.08.06.237941","title":"The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fondation EDF; Fondation Institut de Cardiologie de Montréal; Agence Nationale de la Recherche; Réseau en Bio-Imagerie du Quebec; Wellcome Trust; Institut de Cardiologie de Montréal; Fondation Brain Canada","keywords":"Connectome; Diffusion MRI; Connectomics; Tractography; White matter; Human Connectome Project; Myelin; Neuroscience; Metric (unit); Computer science; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Central nervous system","score_opus":0.041626246456411706,"score_gpt":0.2811708767039073,"score_spread":0.23954463024749556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047160690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78285414,0.00097610644,0.21213105,0.00034407605,0.00004109236,0.000053019372,0.00076892663,0.0003184313,0.0025130734],"genre_scores_gemma":[0.97396654,0.0002114216,0.024815686,0.000030498513,0.000053019627,0.000039667055,0.00032741073,0.000053711254,0.00050200487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993938,0.00026477798,0.000030646384,0.00014569463,0.00012048483,0.000044684013],"domain_scores_gemma":[0.9941847,0.0029445072,0.001448669,0.00061506225,0.00056083885,0.00024629355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020072304,0.0006666594,0.0004926888,0.004160835,0.00031082763,0.0010997275,0.0005026507,0.0005889991,0.0020738947],"category_scores_gemma":[0.008924798,0.00017298771,0.0005578572,0.0017970325,0.0009381469,0.0017826536,0.0009804309,0.00055807363,0.00028449137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001662427,0.00027828442,0.14110352,0.0011192041,0.0016867563,0.0014901451,0.0009633661,0.43447068,0.1162653,0.08293104,0.0040164227,0.21401282],"study_design_scores_gemma":[0.000027201759,0.00040346506,0.11721045,0.00012793964,0.00020236628,0.0009656566,0.00024150097,0.7791017,0.012093956,0.086943984,0.0025337255,0.00014798023],"about_ca_topic_score_codex":0.0011427086,"about_ca_topic_score_gemma":0.0011152767,"teacher_disagreement_score":0.004160835,"about_ca_system_score_codex":0.00037118047,"about_ca_system_score_gemma":0.00029028315,"threshold_uncertainty_score":0.010615408},"labels":[],"label_agreement":null},{"id":"W3047356090","doi":"10.1101/2020.08.06.234526","title":"Neurofeedback fMRI in the motor system elicits bi-directional changes in activity and white-matter structure in the healthy adult human brain","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"University of Oxford; National Institute for Health and Care Research; Wellcome Trust","keywords":"White matter; Neurofeedback; Neuroscience; Corpus callosum; Neuromodulation; Brain activity and meditation; Motor cortex; Psychology; Diffusion MRI; Fractional anisotropy; Neuroplasticity; Cortex (anatomy); Human brain; Electroencephalography; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.03378423704196926,"score_gpt":0.29339073948751343,"score_spread":0.2596065024455442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047356090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730286,0.0013467311,0.02030534,0.00080142287,0.00013447899,0.000087776614,0.0004235031,0.00030237754,0.0035698623],"genre_scores_gemma":[0.9889325,0.00066812383,0.007297262,0.00026349528,0.00008168863,0.00014066692,0.00019257754,0.00003827056,0.0023855371],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999045,0.000023599847,0.000004685096,0.000026701253,0.000022979753,0.00001746438],"domain_scores_gemma":[0.9999056,0.000031769396,0.000020302805,0.000011182299,0.000010663409,0.000020614703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002552779,0.0003528131,0.00020465573,0.00017502482,0.00015084792,0.00020638097,0.0001571074,0.00040376376,0.0021600823],"category_scores_gemma":[0.0005555771,0.00012509918,0.00011342392,0.000110262496,0.00036604496,0.00024360583,0.00025948955,0.0003001627,0.0003222349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003880939,0.0000736141,0.00067374815,0.000080260805,0.000018844103,0.0000985933,0.00007279631,0.00018915324,0.9868128,0.00016888822,0.0004616227,0.010961731],"study_design_scores_gemma":[0.00019956904,0.003162642,0.17001016,0.00008304722,0.00014796975,0.0018299422,0.0001884779,0.011345159,0.80348414,0.0025894975,0.00691954,0.000039896302],"about_ca_topic_score_codex":0.00042696096,"about_ca_topic_score_gemma":0.001024282,"teacher_disagreement_score":0.0021600823,"about_ca_system_score_codex":0.0001143747,"about_ca_system_score_gemma":0.00017330305,"threshold_uncertainty_score":0.007226169},"labels":[],"label_agreement":null},{"id":"W3047649979","doi":"10.1016/j.neuroimage.2021.118312","title":"Permutation-based inference for spatially localized signals in longitudinal MRI data","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Computer science; Univariate; Permutation (music); Neuroimaging; Multiple comparisons problem; False discovery rate; Inference; Artificial intelligence; Alzheimer's Disease Neuroimaging Initiative; Pattern recognition (psychology); Statistical hypothesis testing; Resampling; Statistical power; Spatial analysis; Statistic; Data mining; Machine learning; Mathematics; Disease; Statistics; Alzheimer's disease; Multivariate statistics; Medicine; Neuroscience; Psychology; Pathology; Biology","score_opus":0.18553309047076086,"score_gpt":0.4322014754127328,"score_spread":0.24666838494197194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047649979","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011979801,0.00013339755,0.98637474,0.00013186844,0.00003814308,0.00010753453,0.00023790008,0.0008262208,0.00017044845],"genre_scores_gemma":[0.23558128,0.00018825495,0.7601781,0.00031144964,0.00013461344,0.0009273642,0.0016474914,0.0004547352,0.000576706],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9896165,0.0069770357,0.0005099311,0.0020792752,0.00058853277,0.0002287349],"domain_scores_gemma":[0.9131406,0.0740983,0.0030365258,0.0075938804,0.0016337938,0.00049691845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025657088,0.0011117132,0.002001116,0.0027716523,0.0013767882,0.0013057913,0.0028575542,0.0015430422,0.0029972957],"category_scores_gemma":[0.10603337,0.0010249126,0.0026190844,0.002904489,0.0021823645,0.0015207322,0.0019035718,0.0030647365,0.00067233294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018318059,0.00040020296,0.060048044,0.0012856164,0.0044977586,0.0020104977,0.0011012707,0.36660072,0.016818577,0.09298227,0.010745493,0.44167775],"study_design_scores_gemma":[0.00023012733,0.00018982618,0.005140357,0.000052571653,0.00029318174,0.00023029199,0.000074736425,0.85165167,0.0037542868,0.13593572,0.002392139,0.000055183966],"about_ca_topic_score_codex":0.006693558,"about_ca_topic_score_gemma":0.009155856,"teacher_disagreement_score":0.025657088,"about_ca_system_score_codex":0.0008421928,"about_ca_system_score_gemma":0.0026412571,"threshold_uncertainty_score":0.13568926},"labels":[],"label_agreement":null},{"id":"W3049013229","doi":"10.1371/journal.pone.0233244","title":"Multimodal principal component analysis to identify major features of white matter structure and links to reading","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"White matter; Principal component analysis; Diffusion MRI; Neuroscience; Fractional anisotropy; Myelin; Corpus callosum; Superior longitudinal fasciculus; Biology; Nuclear magnetic resonance; Artificial intelligence; Psychology; Computer science; Anatomy; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.0615144840601415,"score_gpt":0.33687436669054377,"score_spread":0.2753598826304023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049013229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8656918,0.0011882714,0.12408923,0.00026804948,0.000083397055,0.00041242215,0.004033099,0.0010087903,0.0032250918],"genre_scores_gemma":[0.9472118,0.00031880225,0.048613656,0.000021451197,0.00003717465,0.000230643,0.0021478343,0.000094499745,0.0013241562],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9994037,0.00015164132,0.000069913076,0.00017779699,0.00012341811,0.000073476935],"domain_scores_gemma":[0.9987373,0.00057442306,0.00019004138,0.00019811672,0.00023575568,0.00006439954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015556478,0.0010286091,0.0006123902,0.0028867715,0.00034663774,0.000922388,0.00025999796,0.0002500196,0.00414841],"category_scores_gemma":[0.004137016,0.00018182436,0.0010489123,0.0028856134,0.00036501454,0.00046628725,0.0006089462,0.0005891018,0.00066467375],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000880585,0.00044049887,0.36479616,0.0007013131,0.0018849106,0.0007980871,0.0017468854,0.011859083,0.08453849,0.0036739223,0.006542139,0.5221378],"study_design_scores_gemma":[0.000035827263,0.00045462282,0.9143737,0.00007696537,0.0004276013,0.0005821698,0.0005268276,0.062453073,0.008661715,0.006888412,0.00544418,0.00007488501],"about_ca_topic_score_codex":0.0043719485,"about_ca_topic_score_gemma":0.004704765,"teacher_disagreement_score":0.0043719485,"about_ca_system_score_codex":0.00032308578,"about_ca_system_score_gemma":0.00086771837,"threshold_uncertainty_score":0.013877869},"labels":[],"label_agreement":null},{"id":"W3049741828","doi":"10.1016/j.pscychresns.2020.111159","title":"Association of white matter microstructure and extracellular free-water with cognitive performance in the early course of schizophrenia","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"National Institute of Mental Health","keywords":"Fornix; White matter; Stria terminalis; Cingulum (brain); Schizophrenia (object-oriented programming); Psychology; Diffusion MRI; Neuroscience; Extracellular; Cognition; Magnetic resonance imaging; Physiology; Medicine; Fractional anisotropy; Hippocampus; Central nervous system; Chemistry; Psychiatry; Radiology","score_opus":0.044514291600237045,"score_gpt":0.34047741076813665,"score_spread":0.2959631191678996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049741828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99970657,0.00006788864,0.000028891027,0.000026278274,0.0000016753748,0.000001467672,0.000040506355,0.0000013985671,0.00012539091],"genre_scores_gemma":[0.9996673,0.000059082315,0.000047387577,0.0000071287095,0.0000036076376,0.0000012905784,0.00006526943,0.0000011807422,0.00014786454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998647,0.000025818119,0.000021572092,0.000024703224,0.000029250015,0.000034013938],"domain_scores_gemma":[0.99879766,0.00017570195,0.000634346,0.000047407528,0.000108408094,0.00023648763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035802103,0.00041405592,0.00033039486,0.0006737579,0.0004330259,0.0005347767,0.00031436753,0.0005043138,0.0012447105],"category_scores_gemma":[0.001518686,0.00031139387,0.00034715296,0.00050253066,0.00042682627,0.00048419257,0.000538665,0.00094257464,0.00013751714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011128349,0.00017432327,0.99027926,0.000018161418,0.0001289314,0.00040423637,0.00032838993,0.0001676791,0.004734689,0.00007258875,0.00005079826,0.0025281669],"study_design_scores_gemma":[0.0000025706568,0.000065134576,0.99937683,0.0000021440312,0.00001321632,0.000109635555,0.000120840654,0.00010464901,0.0001431971,0.00004477659,0.000014019064,0.0000031020581],"about_ca_topic_score_codex":0.011583607,"about_ca_topic_score_gemma":0.016388137,"teacher_disagreement_score":0.011583607,"about_ca_system_score_codex":0.0005183934,"about_ca_system_score_gemma":0.00051707966,"threshold_uncertainty_score":0.023032367},"labels":[],"label_agreement":null},{"id":"W3056775138","doi":"10.1002/alz.12150","title":"Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging","keywords":"Diffusion MRI; Voxel; Memory clinic; Disease; Diffusion; Alzheimer's disease; Medicine; Pathology; Magnetic resonance imaging; Radiology; Physics; Dementia","score_opus":0.08351238515880283,"score_gpt":0.3376425455055432,"score_spread":0.25413016034674035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3056775138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99960965,0.00013518911,0.00003240389,0.000023450375,0.0000026460943,0.0000024183155,0.00004257567,0.0000020278442,0.0001497178],"genre_scores_gemma":[0.9998053,0.000032669286,0.000039036753,0.000012940184,0.0000077739605,0.0000016437766,0.000056837478,8.9224363e-7,0.000043054548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971515,0.00006946008,0.000034694604,0.00009412883,0.000048829388,0.000037642574],"domain_scores_gemma":[0.9986117,0.00030483634,0.00073348725,0.00006760424,0.000114856965,0.00016753621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000435649,0.00032204817,0.00043073506,0.00076502754,0.00059762865,0.0006806014,0.00026879582,0.0006120553,0.0027572683],"category_scores_gemma":[0.0030450702,0.0001957891,0.00028408668,0.00067617075,0.00029985694,0.00040646983,0.00029439104,0.00033504431,0.00032446493],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018132302,0.00003727615,0.99763405,0.000010025289,0.00003161848,0.00013731852,0.00009514633,0.000015948917,0.000395301,0.0000127161675,0.00007263889,0.0013766815],"study_design_scores_gemma":[0.000009469222,0.00009794777,0.998703,0.0000063852426,0.00004208481,0.0006972641,0.00012633578,0.00010057613,0.00009648055,0.000052022246,0.00006476206,0.000003688284],"about_ca_topic_score_codex":0.0032188043,"about_ca_topic_score_gemma":0.0060171927,"teacher_disagreement_score":0.0032188043,"about_ca_system_score_codex":0.00021182476,"about_ca_system_score_gemma":0.0002754033,"threshold_uncertainty_score":0.009223998},"labels":[],"label_agreement":null},{"id":"W3080109194","doi":"10.1038/s41598-020-70805-5","title":"Extrapyramidal plasticity predicts recovery after spinal cord injury","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College","funders":"Staatssekretariat für Bildung, Forschung und Innovation; Canadian Institutes of Health Research; University of Toronto; Bundesministerium für Bildung und Forschung; Natural Sciences and Engineering Research Council of Canada; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Canada First Research Excellence Fund; Government of Ontario; International Foundation for Research in Paraplegia; Wellcome Trust; McGill University","keywords":"Basal ganglia; Striatum; Thalamus; Globus pallidus; Putamen; Spinal cord injury; Neuroscience; Neurodegeneration; Subthalamic nucleus; Caudate nucleus; Spinal cord; Medicine; Psychology; Internal medicine; Central nervous system; Parkinson's disease; Deep brain stimulation; Dopamine; Disease","score_opus":0.061134288468266074,"score_gpt":0.3448167550792492,"score_spread":0.2836824666109831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080109194","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992275,0.00018028887,0.00018807962,0.000015904981,0.0000015393975,0.0000058339438,0.00020097126,0.000010558267,0.00016921638],"genre_scores_gemma":[0.999416,0.00007598878,0.00009239454,0.0000038766193,0.0000024606466,0.000004018583,0.00031035885,0.0000013925954,0.00009340105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998405,0.00003710713,0.000019853756,0.000046277204,0.000030362213,0.000025737796],"domain_scores_gemma":[0.9991756,0.0001667138,0.00042498356,0.000063457934,0.00008411614,0.00008515225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035894683,0.00039737026,0.0003746922,0.00046920546,0.00013668659,0.00047750236,0.00020037194,0.00030002167,0.00082052144],"category_scores_gemma":[0.0019967402,0.00010642674,0.00022431198,0.00046326703,0.00022200916,0.00029117567,0.0003658074,0.00031774046,0.00021151235],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011102754,0.0001784563,0.97493523,0.00005296739,0.00020806865,0.00021479286,0.0001436651,0.0015253146,0.006249312,0.000021634489,0.00014124528,0.015219044],"study_design_scores_gemma":[0.0000017833001,0.00012486088,0.9988777,0.000002800924,0.000013394243,0.00008171235,0.000026017993,0.0006055876,0.00020786535,0.000026538895,0.000029025778,0.0000027001938],"about_ca_topic_score_codex":0.0030660129,"about_ca_topic_score_gemma":0.0050297524,"teacher_disagreement_score":0.0030660129,"about_ca_system_score_codex":0.00020432759,"about_ca_system_score_gemma":0.0001852874,"threshold_uncertainty_score":0.0060963035},"labels":[],"label_agreement":null},{"id":"W3080178531","doi":"10.1093/cercor/bhaa229","title":"Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Macaque; Magnetic resonance imaging; Brain size; White matter; Temporal lobe; Neuroimaging; Rhesus macaque; Primate; Brain morphometry; Neuroscience; Brain mapping; Population; Psychology; Biology; Medicine; Radiology; Epilepsy","score_opus":0.06908955090232012,"score_gpt":0.33725810792169447,"score_spread":0.26816855701937437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080178531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.830842,0.00051809,0.15673162,0.00014008448,0.000051643867,0.0002457467,0.005822521,0.0018515047,0.0037968946],"genre_scores_gemma":[0.89895225,0.00028631862,0.08850354,0.00008832478,0.000025087387,0.00069610565,0.009682825,0.00055676233,0.0012088321],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993813,0.000117839,0.00005958842,0.00024567603,0.00016153307,0.00003401754],"domain_scores_gemma":[0.9984816,0.0003035192,0.00022452038,0.00043237978,0.00050847785,0.000049555376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016583732,0.00030492654,0.00035241022,0.0018560924,0.0006087025,0.00075775204,0.0005186781,0.0003192827,0.0016113005],"category_scores_gemma":[0.0042146174,0.00020671221,0.0003555432,0.00095120753,0.0005148383,0.00028108808,0.0007080724,0.0003403982,0.0003382294],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006875419,0.00030394775,0.26815966,0.0005033686,0.00092562917,0.0017037772,0.0047077136,0.051781453,0.34402946,0.019748082,0.016122077,0.29132736],"study_design_scores_gemma":[0.00003407331,0.00035542878,0.77180976,0.00012208395,0.0003195016,0.005426057,0.0008878499,0.13041478,0.034099683,0.012717426,0.043685593,0.00012772698],"about_ca_topic_score_codex":0.011703175,"about_ca_topic_score_gemma":0.023085915,"teacher_disagreement_score":0.011703175,"about_ca_system_score_codex":0.0006614588,"about_ca_system_score_gemma":0.00062375795,"threshold_uncertainty_score":0.02327007},"labels":[],"label_agreement":null},{"id":"W3080288479","doi":"10.1007/s00429-020-02129-z","title":"Brain connections derived from diffusion MRI tractography can be highly anatomically accurate—if we know where white matter pathways start, where they end, and where they do not go","year":2020,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Vanderbilt Institute for Clinical and Translational Research; Foundation for the National Institutes of Health","keywords":"Tractography; Voxel; Diffusion MRI; Computer science; Artificial intelligence; Human Connectome Project; White matter; Segmentation; Connectomics; Pattern recognition (psychology); Neuroscience; Connectome; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Radiology","score_opus":0.02115534676963457,"score_gpt":0.2536576812219556,"score_spread":0.23250233445232102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080288479","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092318505,0.0023049207,0.89383847,0.0009684335,0.00027786466,0.00006367313,0.002621542,0.0026102709,0.004996351],"genre_scores_gemma":[0.6738877,0.0039242776,0.3141032,0.00045332487,0.00029623753,0.00009835022,0.0026560198,0.0017221833,0.0028586984],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990188,0.00024376571,0.00008736227,0.00030989543,0.00028229353,0.000057897498],"domain_scores_gemma":[0.9947366,0.002183642,0.0011921787,0.0010231449,0.00073190575,0.0001325169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020508263,0.0015338835,0.00088859576,0.002531645,0.00061122904,0.0032896476,0.0007493665,0.0017101681,0.0023226507],"category_scores_gemma":[0.02134962,0.00095215224,0.00053572765,0.0020114484,0.0013882291,0.0051079905,0.000867611,0.0018049679,0.0021732883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051174377,0.00011851079,0.07196093,0.0014615469,0.0012390006,0.0011026406,0.0011506112,0.16476373,0.18393897,0.04262911,0.016354153,0.5147691],"study_design_scores_gemma":[0.00010390239,0.00019134974,0.1381132,0.0005529169,0.00056914624,0.004392796,0.00044591716,0.42032248,0.096142024,0.30237374,0.036284808,0.00050769723],"about_ca_topic_score_codex":0.009257393,"about_ca_topic_score_gemma":0.019641493,"teacher_disagreement_score":0.009257393,"about_ca_system_score_codex":0.0006926348,"about_ca_system_score_gemma":0.0011034128,"threshold_uncertainty_score":0.018407047},"labels":[],"label_agreement":null},{"id":"W3080671127","doi":"10.1093/cercor/bhaa220","title":"Investigating Sexual Dimorphism of Human White Matter in a Harmonized, Multisite Diffusion Magnetic Resonance Imaging Study","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; National Research Foundation of Korea; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Sexual dimorphism; Fractional anisotropy; White matter; Diffusion MRI; Sex characteristics; Neuroimaging; Magnetic resonance imaging; Psychology; Neuroscience; Brain Structure and Function; Biology; Medicine; Endocrinology","score_opus":0.05893061070329219,"score_gpt":0.3263750090167659,"score_spread":0.2674443983134737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080671127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966581,0.00017095347,0.0023827192,0.000023975284,0.0000026220725,0.000016453365,0.00042900894,0.0000062179,0.00030998242],"genre_scores_gemma":[0.9967644,0.000089292036,0.0022923981,0.00003183572,0.000005309121,0.000027545737,0.0005426147,0.000009189661,0.00023730121],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996145,0.00014521142,0.000031690015,0.00013339832,0.000056391396,0.000018873698],"domain_scores_gemma":[0.99921477,0.00020324731,0.00021539442,0.0002436392,0.00007966675,0.000043225966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012348278,0.00012706158,0.00022320983,0.0004420758,0.00021183465,0.00026850126,0.00021400423,0.00018973333,0.00090726564],"category_scores_gemma":[0.0023839264,0.00010854153,0.00026958887,0.00046284107,0.00024067042,0.00019533989,0.000278521,0.00013490347,0.0001603714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066010276,0.0001614461,0.92220694,0.000098493605,0.0006389082,0.0006744053,0.0013522049,0.0016326548,0.034524415,0.0011962609,0.0007969455,0.03605732],"study_design_scores_gemma":[0.000012665562,0.0001690859,0.99287945,0.000008169214,0.000054169006,0.00076917355,0.0002367682,0.0019790565,0.0018818858,0.00070767914,0.0012918558,0.000010127319],"about_ca_topic_score_codex":0.0012463422,"about_ca_topic_score_gemma":0.0019524335,"teacher_disagreement_score":0.0012463422,"about_ca_system_score_codex":0.00010189436,"about_ca_system_score_gemma":0.00017789315,"threshold_uncertainty_score":0.0065304637},"labels":[],"label_agreement":null},{"id":"W3080676737","doi":"10.3174/ajnr.a6742","title":"Patterning Chronic Active Demyelination in Slowly Expanding/Evolving White Matter MS Lesions","year":2020,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; NeuroRx Research (Canada)","funders":"Biogen","keywords":"Magnetization transfer; Multiple sclerosis; White matter; Medicine; Magnetic resonance imaging; Lesion; Tolerability; Myelin; Diffusion MRI; Nuclear medicine; Pathology; Radiology; Internal medicine; Central nervous system","score_opus":0.0489425887480342,"score_gpt":0.349387086446717,"score_spread":0.3004444976986828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080676737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955472,0.0011600925,0.0009586265,0.00007323278,0.000009104996,0.00007112262,0.0007552841,0.000031539108,0.0013937895],"genre_scores_gemma":[0.996992,0.0003050411,0.001518246,0.00008889519,0.000015649373,0.000027659176,0.0006724043,0.000009886761,0.00037023914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997882,0.000054386463,0.000035810255,0.00006080084,0.000033749493,0.000027166418],"domain_scores_gemma":[0.9992887,0.00009432407,0.00040986534,0.0000622621,0.0000836132,0.00006117576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006862859,0.00027698404,0.0002712035,0.00043324972,0.00026696536,0.0005384835,0.00017736776,0.00026735687,0.002147651],"category_scores_gemma":[0.0007469702,0.000111903566,0.00023566998,0.00043096323,0.00028540826,0.0003975656,0.00026215808,0.00025936044,0.0002907504],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011906746,0.0004319574,0.57255006,0.001551512,0.0006321222,0.0020728873,0.00068821904,0.001278291,0.26776534,0.0006866129,0.0027339838,0.13770227],"study_design_scores_gemma":[0.00040515102,0.003101787,0.93040544,0.00019474782,0.00037285555,0.010815394,0.00046152849,0.0025247636,0.04346546,0.0013409129,0.006872345,0.000039589126],"about_ca_topic_score_codex":0.0018804003,"about_ca_topic_score_gemma":0.0034163098,"teacher_disagreement_score":0.002147651,"about_ca_system_score_codex":0.0002395539,"about_ca_system_score_gemma":0.0003480505,"threshold_uncertainty_score":0.007184565},"labels":[],"label_agreement":null},{"id":"W3081107373","doi":"10.1016/j.jneuroling.2020.100937","title":"Onset age of second language acquisition and fractional anisotropy variation in multilingual young adults","year":2020,"lang":"en","type":"article","venue":"Journal of Neurolinguistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Harvard Graduate School of Education; National Institutes of Health","keywords":"Corpus callosum; Fractional anisotropy; Psychology; Variation (astronomy); White matter; Neuroscience of multilingualism; Second-language acquisition; Linguistics; Medicine; Physics; Neuroscience; Astrophysics","score_opus":0.03194613666379724,"score_gpt":0.33819269978942673,"score_spread":0.3062465631256295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081107373","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999448,0.0001191336,0.000014972093,0.000014248046,0.0000025597087,0.000001273225,0.00011170325,0.0000022563297,0.0002859423],"genre_scores_gemma":[0.99920267,0.00007922046,0.000026472846,0.000011524481,0.0000050398226,0.000002660051,0.00014991025,0.0000027058677,0.0005197683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998698,0.000012844635,0.000020524358,0.00004314134,0.000019563144,0.00003408295],"domain_scores_gemma":[0.99898523,0.00020305166,0.00040854185,0.000034844783,0.00014160834,0.0002266493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022901683,0.00022335631,0.0002884007,0.00093824114,0.00041651892,0.00070128165,0.0001633617,0.0004493499,0.0028870981],"category_scores_gemma":[0.0014306423,0.00021635935,0.00024991474,0.0005082217,0.00020252085,0.0005168353,0.0003740425,0.00038378887,0.00061746396],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003096341,0.0000702243,0.99298286,0.0000131485795,0.000025859836,0.0011769205,0.00070334325,0.000016660704,0.0024459169,0.00003520864,0.00010870061,0.0021115697],"study_design_scores_gemma":[0.0000020155403,0.00005462729,0.9984341,0.0000027514768,0.000006188091,0.00093095965,0.00035956802,0.000025625182,0.00009395193,0.000015185662,0.0000725066,0.000002569016],"about_ca_topic_score_codex":0.011183271,"about_ca_topic_score_gemma":0.013756539,"teacher_disagreement_score":0.011183271,"about_ca_system_score_codex":0.00026131686,"about_ca_system_score_gemma":0.00039625622,"threshold_uncertainty_score":0.022236347},"labels":[],"label_agreement":null},{"id":"W3081243461","doi":"10.1101/2020.08.20.20176883","title":"Characterizing the spatiotemporal variability of Alzheimer’s disease pathology","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Temporal lobe; Pathological; Temporal cortex; Pathology; Disease; Alzheimer's disease; Tau pathology; Neuroscience; Population; Biology; Psychology; Medicine","score_opus":0.13374943599488678,"score_gpt":0.3728952556056796,"score_spread":0.23914581961079281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081243461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9779605,0.0008736118,0.018847696,0.000076764496,0.000005831451,0.000009866344,0.0013883212,0.00007324906,0.0007640443],"genre_scores_gemma":[0.9951277,0.00020405803,0.0037032,0.000011082212,0.000005358742,0.0000099006065,0.00072781375,0.000019141884,0.0001918118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998024,0.000061014187,0.00001769331,0.00007639286,0.000024830526,0.000017776],"domain_scores_gemma":[0.99931026,0.00023502082,0.00021278721,0.00011872432,0.00009234495,0.000030934603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010935226,0.00019502985,0.00023784381,0.0010364851,0.00015205245,0.0006065449,0.0002650973,0.000238928,0.000643302],"category_scores_gemma":[0.0018649395,0.00013801317,0.00019501553,0.0008988527,0.00027571118,0.00045749618,0.00036439914,0.00020287897,0.00020704478],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007865946,0.000074487056,0.83613276,0.00020352086,0.00048372056,0.00053627254,0.00057371025,0.020622227,0.08007064,0.0023118516,0.0014659967,0.056738257],"study_design_scores_gemma":[0.000012797159,0.000098591074,0.91343915,0.00003656832,0.00014216597,0.0013968041,0.0003333476,0.062771894,0.0126533825,0.0061015454,0.0029799638,0.000033729466],"about_ca_topic_score_codex":0.0025170795,"about_ca_topic_score_gemma":0.0034489364,"teacher_disagreement_score":0.0025170795,"about_ca_system_score_codex":0.00025144126,"about_ca_system_score_gemma":0.00017512264,"threshold_uncertainty_score":0.0057831407},"labels":[],"label_agreement":null},{"id":"W3081458935","doi":"10.1002/jmri.27322","title":"Diffusion Tensor Imaging for Quantitative Assessment of Anterior Cruciate Ligament Injury Grades and Graft","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Anterior cruciate ligament; Diffusion MRI; Medicine; Quantitative assessment; Radiology; Nuclear medicine; Magnetic resonance imaging; Risk analysis (engineering)","score_opus":0.04984523915810031,"score_gpt":0.3886791500666985,"score_spread":0.3388339109085982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081458935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7879942,0.06194176,0.12960948,0.0020758223,0.00061208743,0.0014119672,0.004667217,0.0006172694,0.011070213],"genre_scores_gemma":[0.8963701,0.008064722,0.09141962,0.00018367408,0.00023625979,0.0007087236,0.0012484705,0.00008310109,0.0016853797],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985556,0.0007243217,0.00019393662,0.00014355055,0.00032496615,0.000057691726],"domain_scores_gemma":[0.99536705,0.0012772746,0.0016913774,0.0003448651,0.0010589317,0.00026063333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056009544,0.0008305229,0.0006921263,0.0029555988,0.00030567692,0.0008604501,0.0005486013,0.0004601848,0.0018463808],"category_scores_gemma":[0.007296503,0.00026313143,0.0005557593,0.0015838515,0.0005618768,0.0010995374,0.0004773915,0.0007844245,0.00052861543],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002358452,0.0004483824,0.65830094,0.0015347389,0.0010232779,0.0010200558,0.00037551692,0.0021608341,0.040534467,0.0018839296,0.006070992,0.28428835],"study_design_scores_gemma":[0.000204772,0.003111515,0.938182,0.0005607137,0.00062134734,0.0062786033,0.0005310946,0.024987899,0.010127997,0.0039173067,0.011301927,0.00017476418],"about_ca_topic_score_codex":0.0017917004,"about_ca_topic_score_gemma":0.004406589,"teacher_disagreement_score":0.0056009544,"about_ca_system_score_codex":0.0005505636,"about_ca_system_score_gemma":0.0009963143,"threshold_uncertainty_score":0.029621065},"labels":[],"label_agreement":null},{"id":"W3081825606","doi":"10.3389/fneur.2020.00841","title":"Structural Network Analysis Using Diffusion MRI Tractography in Parkinson's Disease and Correlations With Motor Impairment","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Parkinson's disease; Grey matter; Psychology; Neuroscience; Correlation; Rating scale; Physical medicine and rehabilitation; Disease; Magnetic resonance imaging; Medicine; Pathology; Radiology; Mathematics; Developmental psychology","score_opus":0.019763466834476988,"score_gpt":0.27370152847529605,"score_spread":0.25393806164081906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081825606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99289095,0.0003443857,0.0058360826,0.000054660963,0.0000024549754,0.00001756388,0.00043986566,0.000028177708,0.00038582485],"genre_scores_gemma":[0.9959176,0.00012241176,0.0034003675,0.0000033455638,0.000002784093,0.000018275176,0.00040702967,0.000007938794,0.000120266515],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995183,0.00017861857,0.000049290637,0.00013957045,0.00006913484,0.00004514462],"domain_scores_gemma":[0.99840623,0.0007023508,0.000496582,0.00016937166,0.00011598912,0.000109435416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015496173,0.00027847107,0.00031905482,0.002215893,0.00029282708,0.00060842343,0.00024625022,0.0002570981,0.00070805417],"category_scores_gemma":[0.0043736943,0.00017528,0.00042507277,0.0015362515,0.00042214498,0.0004816357,0.00058549584,0.00025541132,0.00008679305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009134668,0.00005168572,0.9435558,0.00015573761,0.00083778315,0.0005386376,0.00074098253,0.012783199,0.012329686,0.001599847,0.00042336356,0.026069792],"study_design_scores_gemma":[0.000020105681,0.00010357006,0.95640445,0.000023417788,0.00015276302,0.00084384595,0.00024980828,0.037144817,0.0014615963,0.002999886,0.000576089,0.000019626938],"about_ca_topic_score_codex":0.015712386,"about_ca_topic_score_gemma":0.019846007,"teacher_disagreement_score":0.015712386,"about_ca_system_score_codex":0.0006302311,"about_ca_system_score_gemma":0.0005680353,"threshold_uncertainty_score":0.031241834},"labels":[],"label_agreement":null},{"id":"W3081934577","doi":"10.1016/j.neuroimage.2020.117301","title":"A probabilistic atlas of locus coeruleus pathways to transentorhinal cortex for connectome imaging in Alzheimer's disease","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; NIH Blueprint for Neuroscience Research; National Eye Institute; National Institute on Aging; Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; Johnson and Johnson; Janssen Research and Development; National Institutes of Health; H. Lundbeck A/S; IXICO; National Natural Science Foundation of China; Genentech; GE Healthcare; Fujirebio US; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Southern California; Merck","keywords":"Locus coeruleus; Neuroscience; Connectome; Brainstem; Human Connectome Project; Neuroimaging; Brain atlas; Diffusion MRI; Human brain; Psychology; Medicine; Pathology; Magnetic resonance imaging; Central nervous system; Radiology; Functional connectivity","score_opus":0.09872043544272853,"score_gpt":0.3453332707372245,"score_spread":0.24661283529449596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081934577","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17048612,0.0013413074,0.8022489,0.0005385234,0.000094071154,0.0007079108,0.013111804,0.003971738,0.007499606],"genre_scores_gemma":[0.40560633,0.0013504121,0.57189465,0.0002127834,0.00007726568,0.001569119,0.010504781,0.0011267433,0.007658015],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996631,0.000085403015,0.000024107941,0.000090562135,0.00010001502,0.00003688077],"domain_scores_gemma":[0.99968255,0.000085892636,0.000055980807,0.00007657809,0.00006342114,0.00003561405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087542395,0.00039793891,0.0003661013,0.0018385461,0.00071511726,0.0010767581,0.00075362105,0.0005896942,0.004153314],"category_scores_gemma":[0.0013922732,0.00044015414,0.0005550216,0.0012661881,0.00036383435,0.00030370854,0.001065434,0.00074456166,0.001061798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009574707,0.0004317661,0.07322818,0.0010735918,0.00077753596,0.0033706264,0.0028275382,0.14581619,0.17322882,0.051163282,0.0613873,0.48573768],"study_design_scores_gemma":[0.0001905457,0.00049701723,0.25164497,0.00035861647,0.0003115203,0.0124428775,0.0006599206,0.49365464,0.04285484,0.0652219,0.13189499,0.00026812145],"about_ca_topic_score_codex":0.009326066,"about_ca_topic_score_gemma":0.029017707,"teacher_disagreement_score":0.009326066,"about_ca_system_score_codex":0.0007520836,"about_ca_system_score_gemma":0.00208073,"threshold_uncertainty_score":0.018543601},"labels":[],"label_agreement":null},{"id":"W3082175322","doi":"10.1093/texcom/tgaa062","title":"Automatic Segmentation of the Dorsal Claustrum in Humans Using in vivo High-Resolution MRI","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"H2020 European Research Council; Israel Science Foundation; Iowa Science Foundation","keywords":"Claustrum; Connectomics; Neuroscience; Segmentation; Dorsum; Connectome; Magnetic resonance imaging; Anatomy; Biology; Diffusion MRI; Human Connectome Project; Artificial intelligence; Computer science; Functional connectivity; Medicine; Radiology","score_opus":0.10789577945727273,"score_gpt":0.36548442250502805,"score_spread":0.2575886430477553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082175322","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7798503,0.002405075,0.20745924,0.00054325955,0.00008706065,0.00030103658,0.0040223454,0.0026408762,0.0026907679],"genre_scores_gemma":[0.85279363,0.0007755422,0.1390792,0.00019404574,0.000048098125,0.00014318356,0.004857292,0.00043820852,0.001670771],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994717,0.000117404205,0.00003686337,0.00025218175,0.00006883806,0.000052976542],"domain_scores_gemma":[0.9995167,0.00017472071,0.00008909379,0.0001076689,0.00008333563,0.000028494505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009078299,0.0006137424,0.00050657964,0.0017091387,0.0003898671,0.001004771,0.0006321369,0.00096058124,0.0013586081],"category_scores_gemma":[0.0027224661,0.00045431615,0.0006034025,0.00073406415,0.0004608439,0.0003435041,0.0006361645,0.00037941962,0.0008156597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018105411,0.00025137098,0.06444972,0.0008434931,0.0008337687,0.0021516418,0.0017419708,0.043283597,0.46751308,0.0031907884,0.01341375,0.4005163],"study_design_scores_gemma":[0.00031253565,0.00049266906,0.37383398,0.00035466946,0.0005437179,0.010698162,0.0011373032,0.45257208,0.13216393,0.009807694,0.01785543,0.00022782297],"about_ca_topic_score_codex":0.008610145,"about_ca_topic_score_gemma":0.02478637,"teacher_disagreement_score":0.008610145,"about_ca_system_score_codex":0.0004363864,"about_ca_system_score_gemma":0.0007946039,"threshold_uncertainty_score":0.017120063},"labels":[],"label_agreement":null},{"id":"W3082607112","doi":"10.1101/2020.08.27.266551","title":"Bundle-specific associations between white matter microstructure and Aβ and tau pathology at their connecting cortical endpoints in older adults at risk of Alzheimer’s disease","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Université de Sherbrooke; McGill University; Douglas Mental Health University Institute","funders":"Université de Sherbrooke","keywords":"Fornix; Uncinate fasciculus; Fractional anisotropy; White matter; Cingulum (brain); Diffusion MRI; Pathology; Fasciculus; Alzheimer's disease; Neuroscience; Psychology; Medicine; Disease; Hippocampus; Magnetic resonance imaging; Radiology","score_opus":0.030335371247178125,"score_gpt":0.26959760588924453,"score_spread":0.23926223464206642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082607112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995852,0.00008628367,0.000104818166,0.00001114051,0.000001367646,0.0000022286652,0.000088648565,0.0000031079824,0.000117227326],"genre_scores_gemma":[0.99955195,0.000040687075,0.00014926081,0.0000055752485,0.000004299139,0.0000025001054,0.00011623046,0.0000018076738,0.0001277727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998945,0.00001977778,0.000013534318,0.000035417142,0.000017151619,0.000019513744],"domain_scores_gemma":[0.99940336,0.00006463132,0.00030699465,0.00006212375,0.00007353678,0.00008936857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035376154,0.00034764994,0.00033647657,0.0007606488,0.00029726527,0.00041760431,0.00012569262,0.0004526592,0.0014146577],"category_scores_gemma":[0.0013739511,0.00021734062,0.00019846653,0.00048814158,0.0002009298,0.00039588113,0.00041414457,0.0002753513,0.00018571207],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000865054,0.0000531839,0.9878522,0.00001744534,0.000118560776,0.00020020752,0.0003329038,0.00015767264,0.0069592423,0.00005004863,0.00010905532,0.0032843798],"study_design_scores_gemma":[0.0000043969962,0.000077641576,0.9992842,0.0000019222302,0.000016874419,0.00015323808,0.000061250204,0.00010964474,0.00017182862,0.000076773336,0.00004052803,0.0000018014166],"about_ca_topic_score_codex":0.0018832433,"about_ca_topic_score_gemma":0.0027692306,"teacher_disagreement_score":0.0018832433,"about_ca_system_score_codex":0.00010464192,"about_ca_system_score_gemma":0.000093175346,"threshold_uncertainty_score":0.0047324896},"labels":[],"label_agreement":null},{"id":"W3082755402","doi":"10.1109/embc44109.2020.9175469","title":"Modeling BOLD-fMRI Hemodynamics via Multidimensional Decomposition of Electrophysiology Data: A Simulation Study","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Electroencephalography; Initialization; Matrix decomposition; Computer science; Artificial intelligence; EEG-fMRI; Pattern recognition (psychology); Electrophysiology; Functional magnetic resonance imaging; Local field potential; Neuroscience; Psychology; Physics","score_opus":0.12756332576150622,"score_gpt":0.421047105388077,"score_spread":0.2934837796265708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082755402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77618027,0.00041102985,0.21790433,0.0012955177,0.000044498116,0.00010284952,0.0005746161,0.0002385435,0.0032484047],"genre_scores_gemma":[0.97231793,0.00012574294,0.026776431,0.0000661141,0.0000115622215,0.00009637837,0.00017699397,0.000022850993,0.00040592172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983,0.00009976905,0.000009178021,0.000024189745,0.000018800996,0.0000179754],"domain_scores_gemma":[0.9975177,0.0019826752,0.00014429385,0.00013415361,0.00014777895,0.000073432755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011916352,0.00031457288,0.00042756644,0.00030985926,0.00027438873,0.00053999765,0.00052907993,0.00095324015,0.0009147706],"category_scores_gemma":[0.004553861,0.0002207987,0.000650182,0.000365277,0.0005281513,0.00061977486,0.00041290498,0.00076757686,0.00008347224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005883769,0.000031952026,0.0015352895,0.000026463835,0.00002731222,0.000056260324,0.000031537787,0.99292654,0.0009708039,0.0027432535,0.00017903397,0.0014127996],"study_design_scores_gemma":[0.0000088537245,0.000012114874,0.00020620196,0.0000024063418,0.0000029055045,0.0000062315125,0.0000046094788,0.9986809,0.00014968628,0.00087506004,0.000047648547,0.0000034866255],"about_ca_topic_score_codex":0.010659097,"about_ca_topic_score_gemma":0.007578622,"teacher_disagreement_score":0.010659097,"about_ca_system_score_codex":0.00046521105,"about_ca_system_score_gemma":0.000492694,"threshold_uncertainty_score":0.0211941},"labels":[],"label_agreement":null},{"id":"W3083431556","doi":"10.1101/2022.02.10.479780","title":"Assessing Quantitative MRI Techniques using Multimodal Comparisons","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Concordia University","funders":"","keywords":"Fractional anisotropy; White matter; Neuroscience; Context (archaeology); Brain tissue; Diffusion MRI; Grey matter; Set (abstract data type); Psychology; Magnetization transfer; Cognitive neuroscience; Computer science; Contrast (vision); Cognition; Artificial intelligence; Biology; Medicine; Magnetic resonance imaging","score_opus":0.11313463343723394,"score_gpt":0.3854876880421872,"score_spread":0.27235305460495324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083431556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14874922,0.0015730549,0.8377092,0.00048595245,0.00015662021,0.00034315357,0.0014064311,0.002249142,0.007327227],"genre_scores_gemma":[0.700156,0.0005058688,0.2961375,0.0001304366,0.00014636264,0.0004238428,0.0007899562,0.00049196975,0.0012180456],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99479985,0.0021107653,0.00043406023,0.0010908443,0.0013862978,0.00017813618],"domain_scores_gemma":[0.98482597,0.00723895,0.0032796953,0.0017660869,0.0026404904,0.00024887035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010827081,0.0015222091,0.00065344205,0.006313975,0.00053396303,0.0037054536,0.0008518074,0.0010174206,0.0047148797],"category_scores_gemma":[0.036646415,0.00041063654,0.0006121496,0.0041842205,0.0015399298,0.002758189,0.0017852817,0.00089973403,0.0009922216],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080365647,0.0003124585,0.100580566,0.0021514583,0.0016495355,0.00044675864,0.0018578002,0.043952737,0.23266025,0.044622667,0.006947639,0.5640145],"study_design_scores_gemma":[0.00010744415,0.0017605444,0.26035088,0.0006760458,0.00077236677,0.0023776304,0.0022087723,0.4166148,0.15544012,0.13582456,0.023334954,0.0005319467],"about_ca_topic_score_codex":0.00088911795,"about_ca_topic_score_gemma":0.00089956814,"teacher_disagreement_score":0.010827081,"about_ca_system_score_codex":0.000742122,"about_ca_system_score_gemma":0.0006964155,"threshold_uncertainty_score":0.05725974},"labels":[],"label_agreement":null},{"id":"W3083554083","doi":"10.21105/joss.02343","title":"qMRLab: Quantitative MRI analysis, under one umbrella","year":2020,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré de Santé et Services Sociaux de Chaudière-Appalache; University of Calgary; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; McGill University; Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Institut de Cardiologie de Montréal; Fondation Institut de Cardiologie de Montréal; Canada First Research Excellence Fund; Réseau en Bio-Imagerie du Quebec","keywords":"Medicine; Computer science","score_opus":0.19900791780575466,"score_gpt":0.42082807363136354,"score_spread":0.22182015582560888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083554083","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039765416,0.0022594966,0.831142,0.0015158855,0.0010004673,0.0007448784,0.010652154,0.132218,0.016490662],"genre_scores_gemma":[0.04225615,0.0019159899,0.8798871,0.0024085462,0.0008998046,0.0040447,0.014006018,0.03973173,0.014849913],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98942274,0.0025489826,0.001635275,0.0018953446,0.0040651276,0.00043263065],"domain_scores_gemma":[0.9852009,0.0058383066,0.0022611367,0.00271772,0.003329333,0.0006525869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014942971,0.0037992985,0.0021797463,0.006258946,0.0013254131,0.007957013,0.0043325303,0.001955198,0.04210886],"category_scores_gemma":[0.0404104,0.0020286408,0.0019142466,0.003241497,0.0025836823,0.0050797793,0.0077403523,0.0029314903,0.028035963],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021259384,0.0002853059,0.007664674,0.003530449,0.0007097144,0.00046683368,0.0010952383,0.0043155793,0.035147026,0.052471884,0.24074191,0.6514455],"study_design_scores_gemma":[0.0005017278,0.0006636255,0.020231232,0.002339154,0.00075788517,0.0029586658,0.0003875559,0.070617415,0.056962978,0.117829725,0.7260914,0.0006585591],"about_ca_topic_score_codex":0.0015483688,"about_ca_topic_score_gemma":0.0015278653,"teacher_disagreement_score":0.04210886,"about_ca_system_score_codex":0.0008205942,"about_ca_system_score_gemma":0.003520005,"threshold_uncertainty_score":0.14086819},"labels":[],"label_agreement":null},{"id":"W3083577534","doi":"10.1212/wnl.0000000000010669","title":"Developmental neuroplasticity of the white matter connectome in children with perinatal stroke","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Connectomics; Connectome; Diffusion MRI; White matter; Psychology; Neuroscience; Stroke (engine); Neurology; Neuroplasticity; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.02191565561632836,"score_gpt":0.26123289282167006,"score_spread":0.2393172372053417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083577534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99928856,0.000049994756,0.00022759852,0.000020932563,9.029014e-7,0.0000042610714,0.00016164243,0.0000045969455,0.0002413335],"genre_scores_gemma":[0.9989008,0.000119712015,0.0005767308,0.0000059751865,8.341543e-7,0.000014528421,0.00018732387,0.0000030780775,0.00019108172],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987304,0.000020570415,0.000012862033,0.000034583132,0.00003474876,0.000024140176],"domain_scores_gemma":[0.9995303,0.000106144944,0.00023111778,0.000027007383,0.000056657565,0.000048675916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000394472,0.00029882186,0.00013262648,0.0007897414,0.00023833777,0.0004027278,0.0001719269,0.00015162968,0.0015446888],"category_scores_gemma":[0.0019490737,0.00012077833,0.00014105743,0.0003920289,0.0003630695,0.00038872127,0.000283921,0.00023162767,0.0001100733],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015176377,0.000043393564,0.9702977,0.000038502167,0.00006627477,0.001287418,0.0010960379,0.00056462584,0.0115977,0.00038796614,0.00022769018,0.0142408805],"study_design_scores_gemma":[0.0000019047797,0.00005538374,0.99626416,0.000009735211,0.000013438832,0.0010338194,0.00036635456,0.00029992723,0.0017119875,0.00011041569,0.00012982608,0.000003052585],"about_ca_topic_score_codex":0.010653963,"about_ca_topic_score_gemma":0.017915322,"teacher_disagreement_score":0.010653963,"about_ca_system_score_codex":0.0005035237,"about_ca_system_score_gemma":0.00043682862,"threshold_uncertainty_score":0.021183908},"labels":[],"label_agreement":null},{"id":"W3083589568","doi":"10.1007/978-3-030-73018-5_2","title":"Towards Learned Optimal q-Space Sampling in Diffusion MRI","year":2021,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Human Connectome Project; Tractography; Computer science; Sampling (signal processing); Diffusion MRI; SIGNAL (programming language); Artificial intelligence; Connectome; Machine learning; Data mining; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging; Functional connectivity","score_opus":0.12866222041710998,"score_gpt":0.4084565465148323,"score_spread":0.27979432609772237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083589568","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008077325,0.00054379535,0.99721414,0.00012179194,0.00004535123,0.000008024321,0.000018045735,0.00008997975,0.0011511379],"genre_scores_gemma":[0.048900235,0.002109078,0.941624,0.00020787731,0.00019273588,0.000071936316,0.00014648623,0.0003426757,0.0064048986],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994741,0.000258002,0.000031148607,0.00007416856,0.00013463637,0.000027955879],"domain_scores_gemma":[0.99836296,0.0011720381,0.000048749764,0.00014721477,0.00020334712,0.00006562364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018462428,0.0008237895,0.0010319267,0.0005396758,0.00034276352,0.0013683491,0.0014283668,0.001236462,0.004981277],"category_scores_gemma":[0.00683068,0.0007029223,0.0005935294,0.0010939201,0.0013941614,0.002017575,0.002137601,0.0025405213,0.0017425747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011144902,0.00006891675,0.0003465149,0.00046388694,0.00004957179,0.000080100435,0.00020045353,0.2344224,0.0062282123,0.4544979,0.01202711,0.29150352],"study_design_scores_gemma":[0.00001132984,0.000022672099,0.00006852684,0.000038153084,0.00000714819,0.0000466265,0.00001739189,0.7704829,0.0011559568,0.22044586,0.0076921782,0.000011300898],"about_ca_topic_score_codex":0.002735019,"about_ca_topic_score_gemma":0.0030203692,"teacher_disagreement_score":0.004981277,"about_ca_system_score_codex":0.00073432823,"about_ca_system_score_gemma":0.00087234593,"threshold_uncertainty_score":0.016664028},"labels":[],"label_agreement":null},{"id":"W3083911743","doi":"10.1101/2020.09.07.286807","title":"Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; Health Sciences Centre; University Health Network; Western University; University of Toronto; Centre for Addiction and Mental Health; Queen's University; Toronto Western Hospital; University of British Columbia; Sunnybrook Health Science Centre; St. Michael's Hospital; University of Alberta; University of Calgary; Baycrest Hospital","funders":"Canadian Open Neuroscience Platform; Temerty Family Foundation; University Health Network Foundation; H. Lundbeck A/S; Servier; Mitacs; Michael Smith Health Research BC; Strong; Government of Ontario; Canadian Institutes of Health Research; Sunovion; Centre for Addiction and Mental Health Foundation; Ontario Brain Institute; Pfizer; St. Jude Medical; Fondation Brain Canada; Allergan; National Institutes of Health; Canadian Network for Mood and Anxiety Treatments; Bristol-Myers Squibb","keywords":"Protocol (science); Computer science; Reliability (semiconductor); Visual inspection; Neuroimaging; Reproducibility; Artificial intelligence; Quality (philosophy); Psychology; Statistics; Medicine; Neuroscience; Mathematics; Pathology","score_opus":0.06980533340643963,"score_gpt":0.35876812307758255,"score_spread":0.2889627896711429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083911743","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010496737,0.00033348514,0.9261415,0.00047033356,0.00053136447,0.0029542737,0.007894692,0.04802369,0.0031539747],"genre_scores_gemma":[0.044090964,0.0003014542,0.87013274,0.000673821,0.0002212826,0.019056039,0.012630122,0.047501277,0.0053922753],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99275744,0.0018546361,0.0012514866,0.0012798203,0.002476918,0.00037976296],"domain_scores_gemma":[0.9633495,0.010690126,0.0021100754,0.009654326,0.013455073,0.00074089126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023919726,0.0019740176,0.0011873133,0.0036290265,0.0023290718,0.0035298632,0.003940684,0.0021099397,0.043100957],"category_scores_gemma":[0.06617346,0.0015887726,0.0011631991,0.0017782873,0.0021827237,0.0018994443,0.003538594,0.00393031,0.013933445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030109962,0.0004931303,0.007216827,0.0038198084,0.0005298898,0.0013014302,0.0029209955,0.013183836,0.22301872,0.03698287,0.35894668,0.34857485],"study_design_scores_gemma":[0.0007366621,0.0008444537,0.0235778,0.0012019104,0.0003209341,0.0029249964,0.0006591813,0.118824586,0.3400999,0.061795834,0.44794765,0.0010661968],"about_ca_topic_score_codex":0.0034709724,"about_ca_topic_score_gemma":0.0047297203,"teacher_disagreement_score":0.043100957,"about_ca_system_score_codex":0.0013845882,"about_ca_system_score_gemma":0.0052674413,"threshold_uncertainty_score":0.14418703},"labels":[],"label_agreement":null},{"id":"W3084002536","doi":"10.1016/j.nicl.2020.102413","title":"Cognitively supernormal older adults maintain a unique structural connectome that is resistant to Alzheimer’s pathology","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Rochester; F. Hoffmann-La Roche; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Connectome; Precuneus; Neuroscience; Psychology; Cognition; Posterior cingulate; Human Connectome Project; Neurodegeneration; Cognitive decline; Diffusion MRI; Alzheimer's disease; Default mode network; Disease; Medicine; Pathology; Functional connectivity; Dementia; Magnetic resonance imaging","score_opus":0.20755074661568657,"score_gpt":0.4352312524798014,"score_spread":0.2276805058641148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084002536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998317,0.00016156337,0.0006238731,0.00005742925,0.0000065039726,0.000009355677,0.0003791694,0.00001822641,0.00042683515],"genre_scores_gemma":[0.9976749,0.00014960882,0.0011083087,0.00004961707,0.000011541105,0.000011780007,0.0005682511,0.000013399757,0.00041253498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984586,0.0000147109195,0.000023290857,0.00006208934,0.000027953587,0.000026114516],"domain_scores_gemma":[0.9991208,0.000108003806,0.00035821076,0.00013679625,0.00015348064,0.0001226201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006086709,0.000512842,0.00047773906,0.0012599173,0.0005270753,0.00090076757,0.00030722917,0.00037649483,0.0020693117],"category_scores_gemma":[0.002344728,0.00022566946,0.00030530468,0.0006206737,0.0005626249,0.0009321936,0.0007814279,0.0004418679,0.00037965627],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005560672,0.00008232161,0.92133707,0.000096613854,0.00023256722,0.0013737893,0.0015524811,0.00041242337,0.040232535,0.00059157825,0.0008507681,0.03268187],"study_design_scores_gemma":[0.000006415712,0.00011311258,0.9947523,0.000013531033,0.00003598591,0.0015578916,0.00043831623,0.00049594656,0.0009037592,0.000989734,0.00068279466,0.000010236236],"about_ca_topic_score_codex":0.003967984,"about_ca_topic_score_gemma":0.010364737,"teacher_disagreement_score":0.003967984,"about_ca_system_score_codex":0.00026335756,"about_ca_system_score_gemma":0.00018988481,"threshold_uncertainty_score":0.007889748},"labels":[],"label_agreement":null},{"id":"W3084006768","doi":"10.1523/jneurosci.0364-20.2020","title":"Corticocortical and Thalamocortical Changes in Functional Connectivity and White Matter Structural Integrity after Reward-Guided Learning of Visuospatial Discriminations in Rhesus Monkeys","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; The Scarborough Hospital; University of Toronto","funders":"Medical Research Council; Wellcome Trust","keywords":"Uncinate fasciculus; Fornix; Neuroscience; Psychology; White matter; Thalamus; Prefrontal cortex; Orbitofrontal cortex; Macaque; Hippocampus; Fractional anisotropy; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.08927754114621453,"score_gpt":0.35651557856865457,"score_spread":0.26723803742244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084006768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991406,0.00010568133,0.0003673803,0.00003108949,0.0000020827783,0.000003580575,0.00010754333,0.000017338396,0.00022479416],"genre_scores_gemma":[0.99808097,0.00018067066,0.0007254789,0.000030775598,0.000003612884,0.000026689362,0.000250576,0.00001542786,0.0006859712],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999503,0.000002845717,0.0000028360557,0.000019870733,0.000007557307,0.000016616272],"domain_scores_gemma":[0.9998965,0.0000067877877,0.000048539358,0.000015919244,0.000011154633,0.000021074615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065785425,0.0002483165,0.00015841672,0.00026248395,0.00019522129,0.00020513184,0.0001266038,0.00015856847,0.00067774433],"category_scores_gemma":[0.00015970468,0.000117041374,0.00015649082,0.000085919586,0.00037051356,0.00020012983,0.00020429838,0.00031396525,0.00010273272],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002716623,0.000057813388,0.009596298,0.00002212823,0.00003269121,0.00022952529,0.00016149737,0.00015238569,0.9843962,0.00007286709,0.000056858105,0.004950031],"study_design_scores_gemma":[0.000030013407,0.0009694978,0.6363318,0.000013488206,0.00010919588,0.001523754,0.000377627,0.002059713,0.35641357,0.0005654518,0.0015751072,0.00003082521],"about_ca_topic_score_codex":0.002726625,"about_ca_topic_score_gemma":0.0044284663,"teacher_disagreement_score":0.002726625,"about_ca_system_score_codex":0.0002548081,"about_ca_system_score_gemma":0.00021336996,"threshold_uncertainty_score":0.0054214597},"labels":[],"label_agreement":null},{"id":"W3084284455","doi":"10.1016/j.pscychresns.2020.111184","title":"Cerebrovascular pathology in Alzheimer's disease: Hopes and gaps","year":2020,"lang":"en","type":"review","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Hyperintensity; Disease; Medicine; Diabetes mellitus; Fluid-attenuated inversion recovery; White matter; Vascular disease; Executive dysfunction; Leukoaraiosis; Pathology; Psychology; Bioinformatics; Intensive care medicine; Cardiology; Internal medicine; Magnetic resonance imaging; Cognition; Radiology; Neuropsychology; Psychiatry; Biology; Endocrinology","score_opus":0.23952392100853526,"score_gpt":0.48920274332569236,"score_spread":0.2496788223171571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084284455","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021890783,0.9992914,0.000028591427,0.0003307748,0.0001362584,8.9718225e-7,0.0000066381995,0.0000024611425,0.00018101299],"genre_scores_gemma":[0.00023742949,0.998949,0.000093761686,0.0002521393,0.00032589101,0.000001997382,0.00001046751,5.802943e-7,0.00012874565],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99968934,0.00006634769,0.0000596392,0.000050860162,0.000098953606,0.000035012392],"domain_scores_gemma":[0.99857616,0.0007778846,0.00017364163,0.000026288544,0.00033358415,0.00011244179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016581559,0.0010044106,0.0026622214,0.0026148665,0.00039922568,0.0024636292,0.0011832443,0.0021643024,0.0042716465],"category_scores_gemma":[0.002052491,0.00037655316,0.0007275226,0.00305442,0.00090754195,0.003378635,0.0011620473,0.002839412,0.0018717437],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016294925,0.00007299888,0.0003307692,0.028492104,0.00019363145,0.00025683627,0.00009125643,0.00036218576,0.00062569644,0.0055103106,0.05228219,0.911619],"study_design_scores_gemma":[0.000060630067,0.0001377258,0.0015596944,0.021369893,0.00058666104,0.0014385381,0.0002942519,0.00024596736,0.00014956568,0.008529256,0.96557117,0.000056753244],"about_ca_topic_score_codex":0.0025970617,"about_ca_topic_score_gemma":0.0071491897,"teacher_disagreement_score":0.0042716465,"about_ca_system_score_codex":0.001020197,"about_ca_system_score_gemma":0.0030339514,"threshold_uncertainty_score":0.014290094},"labels":[],"label_agreement":null},{"id":"W3084650047","doi":"10.1212/wnl.0000000000010804","title":"Teaching NeuroImages: Stroke With Nondecussating Corticospinal Tracts Causing Ipsilateral Weakness","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Weakness; Facial weakness; Medicine; Diffusion MRI; Stroke (engine); Corticospinal tract; Infarction; Dissection (medical); Anatomy; Magnetic resonance imaging; Radiology; Cardiology","score_opus":0.07169574233355873,"score_gpt":0.3386703085866711,"score_spread":0.26697456625311233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084650047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.899951,0.004154401,0.002204845,0.014626922,0.0008099611,0.0002641125,0.00070153276,0.00030266095,0.07698451],"genre_scores_gemma":[0.9826881,0.0023264661,0.00088938326,0.00304799,0.0014981809,0.000021300286,0.00022274502,0.000034344885,0.00927148],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99985313,0.00000801234,0.000019921225,0.00003416641,0.000025470425,0.000059239723],"domain_scores_gemma":[0.99972016,0.00006979949,0.000046811358,0.000020079317,0.000039929368,0.00010323165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016483596,0.0013618376,0.0005892043,0.0010903405,0.0015487066,0.00070155505,0.0006104233,0.0020358881,0.00935982],"category_scores_gemma":[0.0009621823,0.00046004096,0.00041215855,0.0011559019,0.000818321,0.0010050994,0.00047770631,0.0015896979,0.0024400197],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009137113,0.0001501908,0.01848979,0.000075536016,0.00002320828,0.9711727,0.00023718433,0.00014281862,0.0015127171,0.0003254313,0.0027103762,0.0050687753],"study_design_scores_gemma":[0.000058087047,0.00024098558,0.042562693,0.00009116962,0.000064397085,0.94912696,0.000298417,0.00076189527,0.0016544156,0.0014522644,0.0036639853,0.000024794801],"about_ca_topic_score_codex":0.004731114,"about_ca_topic_score_gemma":0.007420228,"teacher_disagreement_score":0.00935982,"about_ca_system_score_codex":0.0012721828,"about_ca_system_score_gemma":0.00087458896,"threshold_uncertainty_score":0.03131169},"labels":[],"label_agreement":null},{"id":"W3084811013","doi":"10.1101/2020.09.16.299784","title":"A method to remove the influence of fixative concentration on post-mortem T <sub>2</sub> maps using a Kinetic Tensor model","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Fixative; Diffusion MRI; White matter; Brain tissue; Chemistry; Fixation (population genetics); Diffusion; Anatomy; Physics; Magnetic resonance imaging; Biology; Thermodynamics; Medicine; Biochemistry","score_opus":0.05203366430860195,"score_gpt":0.3169298487756952,"score_spread":0.26489618446709323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084811013","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01826399,0.00009360298,0.97982806,0.000110289155,0.000043679338,0.000049587823,0.00009260727,0.0012685303,0.00024964102],"genre_scores_gemma":[0.26124194,0.00040701896,0.7307771,0.000195756,0.00005919491,0.00041053005,0.0006073617,0.001520903,0.0047802026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994924,0.00012657572,0.000043499243,0.00014150211,0.00014343495,0.00005250524],"domain_scores_gemma":[0.99843496,0.0005802428,0.00030515267,0.00032238074,0.00029227266,0.00006485598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022185356,0.0016672703,0.00073903607,0.000812911,0.0005220021,0.0011176942,0.0015303675,0.0014463781,0.0027358087],"category_scores_gemma":[0.0066715097,0.0008044131,0.0016881002,0.0007831753,0.0006346702,0.0010748841,0.0007984416,0.0015024178,0.0012301819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006904037,0.00030592538,0.0062980005,0.0005187805,0.0006793257,0.00047547714,0.0004425305,0.41835272,0.27615494,0.017328715,0.0047674873,0.2739858],"study_design_scores_gemma":[0.000018703848,0.00012710456,0.0027726006,0.00002311953,0.00011158811,0.00017868432,0.000022884025,0.9569612,0.03248194,0.0028770994,0.0043648635,0.000060183487],"about_ca_topic_score_codex":0.016234621,"about_ca_topic_score_gemma":0.014805599,"teacher_disagreement_score":0.016234621,"about_ca_system_score_codex":0.0012144899,"about_ca_system_score_gemma":0.0029689076,"threshold_uncertainty_score":0.032280266},"labels":[],"label_agreement":null},{"id":"W3085265452","doi":"10.1016/j.cortex.2020.08.021","title":"Network-level causal analysis of set-shifting during trail making test part B: A multimodal analysis of a glioma surgery case","year":2020,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Institut National de la Santé et de la Recherche Médicale; Assistance Publique - Hôpitaux de Paris; Agence Nationale de la Recherche","keywords":"Supramarginal gyrus; Diffusion MRI; Psychology; Neuroscience; Glioma; Tractography; White matter; Middle frontal gyrus; Resting state fMRI; Brain mapping; Default mode network; Functional connectivity; Medicine; Cognition; Functional magnetic resonance imaging; Magnetic resonance imaging; Radiology","score_opus":0.1616672584301673,"score_gpt":0.3648159502766758,"score_spread":0.2031486918465085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3085265452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9793376,0.00036567272,0.013003581,0.0026634089,0.000025615876,0.00006982528,0.0009383616,0.00009369104,0.0035023976],"genre_scores_gemma":[0.9963496,0.00016255397,0.0027656665,0.00007410576,0.00003924558,0.000010737395,0.00020668063,0.000017167049,0.00037438737],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99984455,0.000025976253,0.000011598657,0.000038752227,0.000038731312,0.00004035843],"domain_scores_gemma":[0.998722,0.00074967346,0.00016040965,0.000097022545,0.0001560378,0.00011480756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003549977,0.00039151835,0.0002332139,0.0017204046,0.000797325,0.00058340497,0.00068274717,0.00095116446,0.0023727878],"category_scores_gemma":[0.0032863817,0.00020726165,0.00046205687,0.0008537353,0.0007085986,0.00046011966,0.00047960388,0.0007613175,0.00020062046],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081437133,0.00027238403,0.40451324,0.00019069653,0.00024361652,0.4899803,0.0018779566,0.018306665,0.016827205,0.008651173,0.0050510545,0.053271297],"study_design_scores_gemma":[0.00008626758,0.00026107483,0.4250792,0.00015752134,0.0004752527,0.31068462,0.0033727486,0.19688624,0.013933934,0.041395295,0.0075263013,0.00014150952],"about_ca_topic_score_codex":0.023462927,"about_ca_topic_score_gemma":0.030211827,"teacher_disagreement_score":0.023462927,"about_ca_system_score_codex":0.0010217557,"about_ca_system_score_gemma":0.00087673654,"threshold_uncertainty_score":0.046652675},"labels":[],"label_agreement":null},{"id":"W3087146715","doi":"10.1101/2020.09.18.20196014","title":"Associations Between Physical Fitness and Brain Structure in Young Adulthood","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Human Connectome Project; Physical fitness; Brain size; Connectome; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Physical therapy","score_opus":0.055875665083657676,"score_gpt":0.3655477262436865,"score_spread":0.3096720611600288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087146715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99935275,0.00020203461,0.000065880544,0.000018938452,0.000002338454,0.0000020841726,0.00017430879,0.0000022596935,0.00017944654],"genre_scores_gemma":[0.99937123,0.00009811299,0.000098403114,0.000010270956,0.0000037329505,0.0000041461585,0.00021180163,0.0000015492797,0.0002007517],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982315,0.000032640008,0.000017519322,0.000067637346,0.000025892916,0.000033194632],"domain_scores_gemma":[0.9995566,0.000058649646,0.00018661372,0.00005073129,0.000054282573,0.000093042276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003709486,0.00020878813,0.00026702162,0.000502764,0.000284525,0.0003309806,0.00016251885,0.00038766698,0.0007795005],"category_scores_gemma":[0.0012656944,0.00022197378,0.00021495925,0.0003680654,0.00017127064,0.00020716857,0.00039627514,0.00029649766,0.00010529585],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071286784,0.000015956613,0.9967019,0.0000063753046,0.000077971315,0.00006291349,0.00012915523,0.000038253253,0.00068039645,0.000023400678,0.000063869506,0.0021284162],"study_design_scores_gemma":[4.2546714e-7,0.0000129358095,0.9998591,0.0000010993729,0.0000046972486,0.00003661022,0.000016682965,0.000020069836,0.000016417289,0.0000087064345,0.000022659553,5.159378e-7],"about_ca_topic_score_codex":0.0065473425,"about_ca_topic_score_gemma":0.015043172,"teacher_disagreement_score":0.0065473425,"about_ca_system_score_codex":0.00012361551,"about_ca_system_score_gemma":0.000093788636,"threshold_uncertainty_score":0.013018429},"labels":[],"label_agreement":null},{"id":"W3087638397","doi":"10.3389/fnins.2020.00767","title":"Identification and Classification of Alzheimer’s Disease Patients Using Novel Fractional Motion Model","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Identification (biology); Disease; Alzheimer's disease; Artificial intelligence; Medicine; Neuroscience; Computer science; Psychology; Internal medicine; Biology","score_opus":0.1489907095355701,"score_gpt":0.3591406228863468,"score_spread":0.2101499133507767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087638397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91413844,0.0009057662,0.08353788,0.00020456627,0.000043486896,0.00007162861,0.00026036013,0.0002154753,0.0006223608],"genre_scores_gemma":[0.9758168,0.00026824887,0.023116656,0.000026799638,0.000035764406,0.00003942385,0.00038467848,0.000010396447,0.00030126027],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997818,0.000051399504,0.000030205261,0.000067237284,0.000036700265,0.000032758373],"domain_scores_gemma":[0.99961144,0.00014781555,0.00008287084,0.000031326035,0.00009135531,0.000035286506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007622721,0.0005371832,0.00070833426,0.0017703932,0.00025091728,0.00063875,0.0002979346,0.00071621535,0.00041718053],"category_scores_gemma":[0.0017646991,0.00012679772,0.0006772972,0.0004254721,0.00018373359,0.0005074123,0.00030544124,0.0002820911,0.00019128679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001909738,0.00052219443,0.6084476,0.00019989914,0.00047942475,0.0019682224,0.0007951958,0.051955357,0.040240347,0.0015488777,0.0028002562,0.28913283],"study_design_scores_gemma":[0.00008243998,0.0004226518,0.17466858,0.000044464596,0.00021030438,0.0017926523,0.00031623128,0.81387055,0.0041887467,0.0029738292,0.001361056,0.000068485235],"about_ca_topic_score_codex":0.0023514156,"about_ca_topic_score_gemma":0.0016385168,"teacher_disagreement_score":0.0023514156,"about_ca_system_score_codex":0.00023121152,"about_ca_system_score_gemma":0.00034016525,"threshold_uncertainty_score":0.004675448},"labels":[],"label_agreement":null},{"id":"W3087674145","doi":"10.1111/jon.12778","title":"White Matter Lesions in Mild Cognitive Impairment and Idiopathic Parkinson's Disease: Multimodal Advanced MRI and Cognitive Associations","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Hyperintensity; Montreal Cognitive Assessment; Cognition; Medicine; Cognitive decline; Cardiology; White matter; Verbal fluency test; Disease; Internal medicine; Psychology; Neuropsychology; Neuroscience; Dementia; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.04168473048135788,"score_gpt":0.3349530886561303,"score_spread":0.2932683581747724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087674145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99817574,0.0011000101,0.00007866154,0.00005762965,0.0000031836908,0.000007609664,0.00008902884,0.0000027529748,0.0004853519],"genre_scores_gemma":[0.99937564,0.00024917987,0.0001114193,0.000018758377,0.00002100562,0.0000050316366,0.000107987784,7.021627e-7,0.00011028034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997923,0.00004751932,0.000026730715,0.00006465444,0.000037859987,0.000030912863],"domain_scores_gemma":[0.9990953,0.00017493127,0.0004517226,0.000053937452,0.000076850156,0.0001472549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067556725,0.0004908712,0.0004191871,0.0018986805,0.00036943553,0.0006268403,0.0003419865,0.0006593013,0.0010428558],"category_scores_gemma":[0.0021242232,0.00023945274,0.00036109315,0.00095990376,0.00046041058,0.0005356462,0.0007688722,0.00046108058,0.00009640972],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005372245,0.00009744123,0.9923564,0.000041257244,0.00018411402,0.0006510877,0.00013599858,0.00009752648,0.0011892096,0.00007328265,0.00006176777,0.0045747273],"study_design_scores_gemma":[0.000005066468,0.00005914865,0.99886453,0.0000050953518,0.000044664223,0.00052162143,0.00005610762,0.0001964244,0.000042422187,0.00014424816,0.000056884594,0.0000038015344],"about_ca_topic_score_codex":0.0037417554,"about_ca_topic_score_gemma":0.006871284,"teacher_disagreement_score":0.0037417554,"about_ca_system_score_codex":0.0002935466,"about_ca_system_score_gemma":0.0003433036,"threshold_uncertainty_score":0.0074399114},"labels":[],"label_agreement":null},{"id":"W3088376984","doi":"10.1007/s10517-020-04942-2","title":"Brain Changes in the White Matter of the Brain White Matter Changes and Cognitive Functions in Asymptomatic Patients","year":2020,"lang":"en","type":"article","venue":"Bulletin of Experimental Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Montreal Cognitive Assessment; White matter; Asymptomatic; Cognition; Medicine; Cardiology; Atrophy; Psychology; Magnetic resonance imaging; Leukoaraiosis; Neuroscience; Internal medicine; Pathology; Cognitive impairment; Radiology","score_opus":0.029962287783863634,"score_gpt":0.32236275373688467,"score_spread":0.29240046595302105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088376984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986583,0.00029838004,0.00007232741,0.00005070354,0.0000075281764,0.0000056178187,0.00008184459,0.000004437386,0.00082080066],"genre_scores_gemma":[0.999508,0.0001221506,0.000058696645,0.000019265897,0.00001899414,0.0000034729799,0.00008121742,0.0000013925298,0.00018688658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999063,0.000014057801,0.000013099537,0.000028380318,0.000019937963,0.000018233311],"domain_scores_gemma":[0.9997656,0.0000463826,0.00008186848,0.000009271788,0.000027600918,0.000069209666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016332681,0.00030355743,0.0003535852,0.0007304696,0.00046959514,0.00042468903,0.00021338057,0.0004452076,0.0014004062],"category_scores_gemma":[0.0010503408,0.00013619625,0.00022155262,0.0005395331,0.00028894923,0.00031448805,0.00021676198,0.00040057956,0.00011964809],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015345236,0.0003028765,0.9669389,0.000093392446,0.00015383531,0.009322898,0.0005544161,0.0001441258,0.008382531,0.00026318934,0.000413508,0.011895842],"study_design_scores_gemma":[0.000013255799,0.00018126627,0.99427336,0.000006877759,0.000052594765,0.004618652,0.00017951155,0.00011563993,0.00027216948,0.00016947386,0.00011104757,0.0000060019497],"about_ca_topic_score_codex":0.0021129537,"about_ca_topic_score_gemma":0.0015990379,"teacher_disagreement_score":0.0021129537,"about_ca_system_score_codex":0.00017364229,"about_ca_system_score_gemma":0.00024438492,"threshold_uncertainty_score":0.0046848655},"labels":[],"label_agreement":null},{"id":"W3088995957","doi":"10.1038/s41380-020-00882-5","title":"Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort","year":2020,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Health and Medical Research Council; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Percentile; Fractional anisotropy; Normative; Schizophrenia (object-oriented programming); Cohort; Psychology; Locus (genetics); Diffusion MRI; DISC1; Percentile rank; Magnetic resonance imaging; Medicine; Neuroscience; Internal medicine; Psychiatry; Biology; Genetics; Radiology; Statistics; Mathematics","score_opus":0.03462629792867275,"score_gpt":0.3347221910954875,"score_spread":0.30009589316681473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088995957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993703,0.000025423236,0.00030290466,0.000019853922,0.0000019995703,0.000001957095,0.00017718069,0.000005701833,0.00009476384],"genre_scores_gemma":[0.9993783,0.000022816565,0.00014724453,0.000007310257,0.0000013488587,0.000004354543,0.0003318925,0.000006009143,0.00010065163],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994429,0.00023607055,0.000035264806,0.0001865496,0.000061528735,0.000037713842],"domain_scores_gemma":[0.9984547,0.00048028992,0.00030655676,0.0004376427,0.00017608002,0.00014476421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018735104,0.00040182986,0.00025829882,0.0005838358,0.00055752264,0.00061414525,0.00053032325,0.00043545972,0.0013580136],"category_scores_gemma":[0.004334098,0.00034374621,0.0003346542,0.00044955875,0.00053346576,0.0003381306,0.00065736036,0.0005352339,0.00023263293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058854604,0.000095535506,0.98924494,0.000008884677,0.00045855905,0.00025067484,0.0010877226,0.0009529896,0.003113061,0.0005089503,0.0003982389,0.0032919464],"study_design_scores_gemma":[0.000009635282,0.00007883248,0.9964478,0.0000047227954,0.00006950716,0.00040732464,0.00046676758,0.0017944322,0.000142725,0.00039763178,0.00017258695,0.000007990674],"about_ca_topic_score_codex":0.013318097,"about_ca_topic_score_gemma":0.016408456,"teacher_disagreement_score":0.013318097,"about_ca_system_score_codex":0.00039530377,"about_ca_system_score_gemma":0.00030907858,"threshold_uncertainty_score":0.026481152},"labels":[],"label_agreement":null},{"id":"W3089590362","doi":"10.1101/2020.10.02.324004","title":"White matter microstructural changes in short-term learning of a continuous visuomotor sequence","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Max-Planck-Institut für demografische Forschung; Max-Planck-Gesellschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Heart and Stroke Foundation of Canada","keywords":"White matter; Neuroscience; Neuroplasticity; Psychology; Sequence learning; Functional magnetic resonance imaging; Motor learning; Magnetic resonance imaging; Medicine","score_opus":0.04116007597035395,"score_gpt":0.2983885784040618,"score_spread":0.2572285024337079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089590362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983259,0.00012214466,0.0010820304,0.000022736223,0.0000062852114,0.000011457256,0.00007259698,0.000026547745,0.0003302933],"genre_scores_gemma":[0.9973188,0.00011469415,0.0009800824,0.000030051213,0.000005308666,0.000038589504,0.00016070652,0.000013367257,0.0013384778],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99991333,0.0000071696245,0.000006957287,0.00003361561,0.000022299717,0.000016711914],"domain_scores_gemma":[0.99979025,0.00002066657,0.00008290084,0.000022663246,0.00003160621,0.000051954717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019357441,0.00026283078,0.00020351,0.00033165407,0.00012492824,0.00017930471,0.0001773801,0.00027592998,0.0010029753],"category_scores_gemma":[0.00029344723,0.00013077304,0.00015059412,0.000104363695,0.00037365418,0.00021647985,0.00024060388,0.00041801276,0.00014140744],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039056546,0.00016033636,0.0032816553,0.000052533404,0.0000397742,0.00020257708,0.00009652921,0.0002476215,0.9882383,0.00007243161,0.00007681674,0.0071408097],"study_design_scores_gemma":[0.0000500147,0.0042865425,0.6253008,0.00002015882,0.000104237704,0.002012148,0.0002799389,0.0034200482,0.36269936,0.0006261156,0.0011713308,0.000029275016],"about_ca_topic_score_codex":0.0010888376,"about_ca_topic_score_gemma":0.0013038999,"teacher_disagreement_score":0.0010888376,"about_ca_system_score_codex":0.00019499543,"about_ca_system_score_gemma":0.00018867274,"threshold_uncertainty_score":0.0033552647},"labels":[],"label_agreement":null},{"id":"W3090019135","doi":"10.1002/dneu.22784","title":"Reduced fractional anisotropy in projection, association, and commissural fiber networks in neonates with prenatal methamphetamine exposure","year":2020,"lang":"en","type":"article","venue":"Developmental Neurobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health","keywords":"Fractional anisotropy; Methamphetamine; White matter; Diffusion MRI; Tractography; Association (psychology); Neuroscience; Confounding; Biology; Internal medicine; Medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.03177529595980899,"score_gpt":0.28344449953862266,"score_spread":0.25166920357881367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090019135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999549,0.00012148329,0.00019400721,0.000011824893,8.7743797e-7,0.0000014369198,0.00003547933,0.0000027065526,0.000083228784],"genre_scores_gemma":[0.99921167,0.00018604014,0.0004268487,0.0000052935816,0.0000014333696,0.000005704572,0.000042977597,0.0000025479646,0.00011741811],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998171,0.000037416692,0.000021893882,0.000051830648,0.00004796085,0.000023888835],"domain_scores_gemma":[0.9990639,0.00021443557,0.0004957589,0.000060024682,0.00009125669,0.00007467201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039531864,0.00028271734,0.00020486992,0.00062172074,0.0001728212,0.0002561644,0.00014174088,0.00025157936,0.00069903967],"category_scores_gemma":[0.0023333381,0.00018366685,0.00022378606,0.00027162657,0.00031036895,0.00026064203,0.00032177658,0.0002672124,0.00006831054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030089606,0.00003050851,0.9473229,0.000050186325,0.0000759552,0.0024091287,0.0010216875,0.00023925713,0.038689952,0.0001049379,0.000059769347,0.009694845],"study_design_scores_gemma":[9.4278244e-7,0.000050560004,0.99440384,0.000010290929,0.00001789528,0.0017929045,0.0001971894,0.0002431184,0.0031449876,0.000050798273,0.00008448058,0.0000030368737],"about_ca_topic_score_codex":0.0048386133,"about_ca_topic_score_gemma":0.004362146,"teacher_disagreement_score":0.0048386133,"about_ca_system_score_codex":0.0002889776,"about_ca_system_score_gemma":0.00028070083,"threshold_uncertainty_score":0.009620905},"labels":[],"label_agreement":null},{"id":"W3090275975","doi":"10.1002/mrm.28543","title":"Myelin water imaging depends on white matter fiber orientation in the human brain","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Canadian Institutes of Health Research; Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Multiple Sclerosis Society","keywords":"White matter; Myelin; Voxel; Nuclear magnetic resonance; Orientation (vector space); Fiber tract; Chemistry; Magnetic resonance imaging; Biology; Physics; Neuroscience; Medicine; Mathematics; Central nervous system; Radiology; Geometry","score_opus":0.04368478821322771,"score_gpt":0.3485788716238089,"score_spread":0.3048940834105812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090275975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98466176,0.002240667,0.01227601,0.000040582134,0.000010170148,0.000013343443,0.00009301523,0.000047046837,0.00061742455],"genre_scores_gemma":[0.9953381,0.00078540394,0.0035095923,0.00001615136,0.00000972554,0.000005388885,0.00007708992,0.000024310244,0.0002342282],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998956,0.000024600451,0.000007440785,0.00003242834,0.000030207892,0.000009803494],"domain_scores_gemma":[0.9994386,0.00020431168,0.00022113304,0.000032582957,0.00007786106,0.000025407257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044368452,0.00027867215,0.0001295751,0.00048914325,0.000100222234,0.00031164897,0.00009713365,0.00020981966,0.00055806356],"category_scores_gemma":[0.0022170108,0.00012255766,0.00007758004,0.00031498703,0.00035308077,0.00053812715,0.0001659845,0.00013117357,0.00017911129],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013209513,0.000053694854,0.14159715,0.00038674567,0.00019385116,0.00036099026,0.0004417023,0.0016668619,0.73802215,0.0004594291,0.00028508762,0.11521139],"study_design_scores_gemma":[0.000020564317,0.0005312253,0.7540661,0.00006313798,0.00021925943,0.0024221998,0.00027042988,0.007098506,0.2321175,0.0016358289,0.0015174069,0.00003781938],"about_ca_topic_score_codex":0.0012792405,"about_ca_topic_score_gemma":0.0018749555,"teacher_disagreement_score":0.0012792405,"about_ca_system_score_codex":0.00011573445,"about_ca_system_score_gemma":0.00017037657,"threshold_uncertainty_score":0.0025435686},"labels":[],"label_agreement":null},{"id":"W3090779210","doi":"10.1101/2020.10.01.320507","title":"Axon Diameter Measurements using Diffusion MRI are Infeasible","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Axon; SIGNAL (programming language); Diffusion; Metric (unit); Diffusion MRI; Limit (mathematics); Computer science; Information transmission; Ideal (ethics); Physics; Biological system; Neuroscience; Algorithm; Magnetic resonance imaging; Mathematics; Mathematical analysis; Biology; Medicine","score_opus":0.13715317577371608,"score_gpt":0.3221292104715816,"score_spread":0.18497603469786553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090779210","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31365976,0.013196479,0.65139097,0.0022270598,0.0008105766,0.00008810183,0.0013419033,0.0027306776,0.014554504],"genre_scores_gemma":[0.85520035,0.0046965303,0.13362002,0.00048499345,0.00018744511,0.00014228192,0.0006539459,0.0005557058,0.004458726],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971993,0.00056334573,0.00016871902,0.0010711723,0.00085486786,0.00014272725],"domain_scores_gemma":[0.9895523,0.004728991,0.001835039,0.001590145,0.0017986718,0.00049484073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025595324,0.00092540606,0.0013042084,0.0015563567,0.00077824766,0.0018899956,0.0009218683,0.0016124402,0.0024920292],"category_scores_gemma":[0.009543336,0.0008647681,0.0003250148,0.0009881647,0.0019580277,0.003475293,0.0015709498,0.0014407069,0.0021707057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007948082,0.00008631878,0.012698898,0.0016360068,0.00014518938,0.0006422447,0.00048066073,0.0075389063,0.823165,0.028831493,0.0055997176,0.118380666],"study_design_scores_gemma":[0.00007625073,0.00078616064,0.04313279,0.00060337794,0.00017601665,0.0061382884,0.00093707704,0.13283673,0.6625462,0.10861151,0.043844342,0.00031128176],"about_ca_topic_score_codex":0.001034383,"about_ca_topic_score_gemma":0.0015399869,"teacher_disagreement_score":0.0025595324,"about_ca_system_score_codex":0.00089549366,"about_ca_system_score_gemma":0.0006504237,"threshold_uncertainty_score":0.013536215},"labels":[],"label_agreement":null},{"id":"W3091718754","doi":"10.1016/j.yebeh.2020.107467","title":"Language lateralization differences between left and right temporal lobe epilepsy as measured by overt word reading fMRI activation and DTI structural connectivity","year":2020,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lateralization of brain function; Inferior longitudinal fasciculus; Psychology; Temporal lobe; Arcuate fasciculus; Diffusion MRI; Uncinate fasciculus; Superior temporal gyrus; Epilepsy; Neuroscience; Audiology; Fasciculus; Functional magnetic resonance imaging; Fractional anisotropy; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.04927764500262327,"score_gpt":0.33239647774136977,"score_spread":0.2831188327387465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091718754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99758625,0.00005459641,0.00034687994,0.000057801524,0.0000059474783,0.0000102484855,0.00022993863,0.00001025486,0.0016980639],"genre_scores_gemma":[0.99863005,0.000029654964,0.00020398624,0.00003921016,0.0000066515695,0.0000138701635,0.00018554763,0.000010825576,0.0008802059],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998628,0.000018146944,0.000012311609,0.000053025637,0.000028132148,0.00002560201],"domain_scores_gemma":[0.9995129,0.00018875605,0.00016599844,0.000039454262,0.000033353506,0.000059549962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028957467,0.0002515307,0.00015225355,0.00045956016,0.00016032247,0.00051366043,0.00012823152,0.0002548878,0.0036769607],"category_scores_gemma":[0.0012150927,0.00014459755,0.00015084633,0.00017460393,0.00046550357,0.0006090437,0.00029272772,0.0002705439,0.00035356244],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049445545,0.00031228425,0.17596158,0.000120485376,0.00023437361,0.0016713729,0.0025221796,0.000461852,0.78995234,0.0020986816,0.0006005886,0.021119693],"study_design_scores_gemma":[0.00010131291,0.0003511197,0.9810011,0.000009929693,0.000052886066,0.0016460548,0.00059218373,0.00094266346,0.013767627,0.0010120829,0.000505744,0.000017281447],"about_ca_topic_score_codex":0.0024733008,"about_ca_topic_score_gemma":0.0048192316,"teacher_disagreement_score":0.0036769607,"about_ca_system_score_codex":0.00023722713,"about_ca_system_score_gemma":0.00031077518,"threshold_uncertainty_score":0.012300611},"labels":[],"label_agreement":null},{"id":"W3091774503","doi":"10.1016/j.neuroimage.2021.118502","title":"Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":187,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Calgary; Université de Sherbrooke","funders":"National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Fundação para a Ciência e a Tecnologia; National Health and Medical Research Council; Australian Research Council; Medical Research Council; Intellectual and Developmental Disabilities Research Center; National Institutes of Health; Deutsche Forschungsgemeinschaft; State Government of Victoria; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and Technology, Taiwan; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; University of Melbourne; University of Nottingham; European Commission; Vanderbilt Institute for Clinical and Translational Research; Murdoch Children's Research Institute; Children’s Hospital of Wisconsin Research Institute; National Institute on Aging; Royal Children's Hospital Foundation; National Institute for Health and Care Research; Waisman Center; Wellcome Trust; Université de Sherbrooke; National Science Foundation; Compute Canada; Vanderbilt University; Consejo Nacional de Ciencia y Tecnología; National Center for Research Resources; Agence Nationale de la Recherche; Agencia Nacional de Investigación y Desarrollo; National Institute of Mental Health; Children's Hospital Foundation","keywords":"Tractography; Segmentation; White matter; Diffusion MRI; Bundle; Computer science; Artificial intelligence; Fiber bundle; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.05183784141295804,"score_gpt":0.3204624886167076,"score_spread":0.26862464720374957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091774503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8574393,0.003338483,0.1303686,0.0012749631,0.0005302828,0.0005267952,0.0020347824,0.0012074941,0.0032792152],"genre_scores_gemma":[0.96859634,0.00028569935,0.026428001,0.0003643956,0.00012830725,0.00037894055,0.0028599284,0.00054321537,0.00041504862],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9499325,0.020012734,0.0061541377,0.015022713,0.0078008706,0.0010770741],"domain_scores_gemma":[0.82823056,0.10866197,0.0185958,0.025504919,0.017298149,0.0017085447],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.055853218,0.00080107455,0.001220265,0.002492065,0.0015607198,0.002575694,0.0012525694,0.0014582798,0.000760397],"category_scores_gemma":[0.16915311,0.00049708126,0.001394308,0.002109977,0.0028560234,0.0023386644,0.003113815,0.0013366553,0.0005927837],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027509995,0.0003281642,0.69686604,0.001363001,0.0038135098,0.000673885,0.018975653,0.014980379,0.020915082,0.0036585887,0.01017224,0.22550236],"study_design_scores_gemma":[0.0002540419,0.0010786982,0.8671554,0.0008069104,0.0015440377,0.0026336778,0.007661754,0.046826307,0.01880015,0.0330772,0.019796463,0.00036541358],"about_ca_topic_score_codex":0.0019509762,"about_ca_topic_score_gemma":0.002908629,"teacher_disagreement_score":0.94414675,"about_ca_system_score_codex":0.00092790637,"about_ca_system_score_gemma":0.0009539657,"threshold_uncertainty_score":0.29538357},"labels":[],"label_agreement":null},{"id":"W3092157907","doi":"10.1002/nbm.4427","title":"High spatial resolution nerve‐specific DTI protocol outperforms whole‐brain DTI protocol for imaging the trigeminal nerve in healthy individuals","year":2020,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta Hospital; University of Alberta","funders":"Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Medicine; Fluid-attenuated inversion recovery; Trigeminal neuralgia; Nuclear medicine; Magnetic resonance imaging; Radiology; Anesthesia","score_opus":0.12033944779443834,"score_gpt":0.42098188873727765,"score_spread":0.3006424409428393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092157907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9511201,0.0010014276,0.04517677,0.00014308344,0.000039937902,0.00034466488,0.00024255754,0.00016496594,0.0017664528],"genre_scores_gemma":[0.9428421,0.0004090144,0.05467278,0.00010139285,0.00002152611,0.00035580245,0.00030108853,0.00007426242,0.0012218858],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996511,0.0001237864,0.000045393263,0.00010805504,0.0000481475,0.000023578254],"domain_scores_gemma":[0.9995511,0.00012753604,0.00007536591,0.00009709438,0.000104008635,0.00004485244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014144294,0.00037617446,0.00029386496,0.00025104766,0.00032591738,0.000295588,0.00023964369,0.0005157288,0.0014627305],"category_scores_gemma":[0.0015111429,0.00020984467,0.0001814989,0.00016304565,0.00038157753,0.00048998225,0.0003156571,0.00032168577,0.00019747835],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014607344,0.00018540857,0.011841861,0.00030322952,0.00013767534,0.00041497228,0.00037560676,0.0022484025,0.9410723,0.00081003533,0.00053459883,0.040615305],"study_design_scores_gemma":[0.00047497175,0.0078011923,0.3732036,0.00011485868,0.0007971092,0.00818651,0.0005118404,0.025331918,0.5696545,0.0024807474,0.011260566,0.00018224768],"about_ca_topic_score_codex":0.0013915137,"about_ca_topic_score_gemma":0.0031280257,"teacher_disagreement_score":0.0014627305,"about_ca_system_score_codex":0.00031179134,"about_ca_system_score_gemma":0.00038953198,"threshold_uncertainty_score":0.0074803233},"labels":[],"label_agreement":null},{"id":"W3092191527","doi":"10.1016/j.media.2021.102126","title":"Filtering in tractography using autoencoders (FINTA)","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health","keywords":"Tractography; Artificial intelligence; Computer science; Pattern recognition (psychology); Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.350996486532398,"score_gpt":0.28753471244511597,"score_spread":0.06346177408728204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092191527","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005601659,0.0001474253,0.99324554,0.00004876592,0.000027743987,0.000015875217,0.000033505265,0.00055379653,0.00032574407],"genre_scores_gemma":[0.18652087,0.00069286115,0.8085894,0.00018197701,0.000082516344,0.00013413421,0.00036072845,0.00024010292,0.0031974805],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99956936,0.00008383121,0.00003984104,0.00014898679,0.00011501449,0.000043012093],"domain_scores_gemma":[0.9984256,0.00082945,0.00019996913,0.00022838778,0.00027744862,0.000039179824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013773915,0.0010947426,0.00082685775,0.0008959434,0.00043307917,0.0010372817,0.0009612446,0.0013299957,0.0012420731],"category_scores_gemma":[0.003602242,0.00080811244,0.0013995069,0.0008439276,0.00077707344,0.0013438943,0.00080100546,0.0017485047,0.0006859799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097008924,0.000054713637,0.0018363784,0.00018078029,0.00025546286,0.00013093864,0.0001700643,0.5931107,0.028300513,0.01150357,0.0019024542,0.36245748],"study_design_scores_gemma":[0.0000042873407,0.000023547724,0.00045394164,0.000015951171,0.000019042285,0.000055953235,0.000010680399,0.98882896,0.005883861,0.0031733166,0.0015189481,0.000011471484],"about_ca_topic_score_codex":0.010209483,"about_ca_topic_score_gemma":0.012690925,"teacher_disagreement_score":0.010209483,"about_ca_system_score_codex":0.00085915066,"about_ca_system_score_gemma":0.0010441899,"threshold_uncertainty_score":0.02030009},"labels":[],"label_agreement":null},{"id":"W3092450803","doi":"","title":"Zytoarchitektonische Charakterisierung und funktionelle Dekodierung des lateralen orbitofrontalen Kortex im humanen Gehirn","year":2020,"lang":"de","type":"dissertation","venue":"Univ. Duesseldorf: Duesseldorfer Dokumenten- und Publikationsserver","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Gynecology; Medicine","score_opus":0.07012353257058548,"score_gpt":0.3584591383864953,"score_spread":0.2883356058159098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092450803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9806662,0.0029615639,0.011446412,0.00011584054,0.000017621789,0.000042065363,0.001212868,0.0001424196,0.0033949902],"genre_scores_gemma":[0.987817,0.0016547103,0.007993682,0.00003400494,0.000010247926,0.000050893177,0.0007813737,0.000042879536,0.001615274],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99982196,0.000023481563,0.000012199619,0.000052081974,0.000061930084,0.000028379603],"domain_scores_gemma":[0.9996867,0.000073154115,0.00009490683,0.00004492767,0.00008209406,0.000018306344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034963485,0.00028118028,0.00024848228,0.0014452739,0.00020983207,0.00063463725,0.0001650077,0.00022327583,0.0021245],"category_scores_gemma":[0.00084587943,0.00024468498,0.00043740505,0.0011139866,0.0004914899,0.00035785398,0.00030304448,0.00026700634,0.00032261238],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009883558,0.00005657498,0.15605651,0.0009227275,0.00063629437,0.00048880454,0.0015583952,0.008399278,0.6646383,0.002838782,0.0014583443,0.16195767],"study_design_scores_gemma":[0.000015115957,0.00014319002,0.94128686,0.000047241214,0.00015586369,0.00080959906,0.0006172394,0.006383598,0.04422447,0.0019997344,0.0042656343,0.00005142099],"about_ca_topic_score_codex":0.011016101,"about_ca_topic_score_gemma":0.012647848,"teacher_disagreement_score":0.011016101,"about_ca_system_score_codex":0.00047567586,"about_ca_system_score_gemma":0.0003724997,"threshold_uncertainty_score":0.021903932},"labels":[],"label_agreement":null},{"id":"W3092996651","doi":"10.1038/s41598-020-70297-3","title":"HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Institut de Valorisation des Données; Agentura Pro Zdravotnický Výzkum České Republiky; Univerzita Palackého v Olomouci; Ministerstvo Školství, Mládeže a Tělovýchovy; Vysoké Učení Technické v Brně; Foundation for the National Institutes of Health; Ministerstvo Zdravotnictví Ceské Republiky; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; Government of Canada; Central European Institute of Technology; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; University of Pennsylvania Health System; University of Pennsylvania","keywords":"Medicine; White matter; Diffusion MRI; Voxel; Magnetic resonance imaging; Spinal cord; Neuroradiology; Reproducibility; Nuclear medicine; Radiology; Neurology","score_opus":0.05608075725010485,"score_gpt":0.34680466035739616,"score_spread":0.2907239031072913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092996651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9077944,0.0034268163,0.0832633,0.00030298156,0.00008223731,0.00028996548,0.000481425,0.0011487667,0.0032100233],"genre_scores_gemma":[0.90545434,0.0011601574,0.0897591,0.00019132157,0.00007441594,0.00024346563,0.00066518335,0.00029274056,0.0021593242],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973696,0.00008566245,0.0000280175,0.000067378125,0.000055653654,0.000026303192],"domain_scores_gemma":[0.9991748,0.00030820628,0.00016008907,0.000117319745,0.00018416179,0.00005542067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009347795,0.0006510814,0.00040676675,0.00082335476,0.00026880042,0.0007433833,0.00039369715,0.0006581569,0.002169193],"category_scores_gemma":[0.003085619,0.00035528193,0.00018284962,0.00023308805,0.0003210742,0.00075787737,0.0007394799,0.000491923,0.00036119542],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033640543,0.00029271303,0.022580136,0.0011491643,0.00022925493,0.0008407666,0.00037756137,0.0037461428,0.7817136,0.0009222772,0.0020068234,0.18277742],"study_design_scores_gemma":[0.0003049219,0.0032609284,0.28447407,0.00026669598,0.00059429766,0.011706439,0.0003796389,0.05531625,0.63149285,0.0024922392,0.009506129,0.00020535979],"about_ca_topic_score_codex":0.0004808891,"about_ca_topic_score_gemma":0.0014996999,"teacher_disagreement_score":0.002169193,"about_ca_system_score_codex":0.00021523407,"about_ca_system_score_gemma":0.00029191058,"threshold_uncertainty_score":0.0072566867},"labels":[],"label_agreement":null},{"id":"W3093377457","doi":"10.1002/jdn.10071","title":"Quantitative analyses of high‐angular resolution diffusion imaging (HARDI)‐derived long association fibers in children with sensorineural hearing loss","year":2020,"lang":"en","type":"article","venue":"International Journal of Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canada Foundation for Innovation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"Sensorineural hearing loss; Angular resolution (graph drawing); Audiology; Diffusion MRI; Diffusion imaging; Association (psychology); High resolution; Medicine; Hearing loss; Psychology; Magnetic resonance imaging; Geology; Remote sensing; Mathematics; Radiology","score_opus":0.07212138461958567,"score_gpt":0.3727756437675328,"score_spread":0.30065425914794713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093377457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996145,0.000047620648,0.00018886078,0.000003061364,3.8124935e-7,0.0000038273583,0.00006604867,0.0000041206235,0.00007161787],"genre_scores_gemma":[0.99905735,0.00005759804,0.00063759997,0.0000048987476,0.0000010959559,0.000014067542,0.00011496314,0.000006144277,0.00010637951],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998134,0.000024940302,0.00002375974,0.00006231274,0.000035538265,0.00004012859],"domain_scores_gemma":[0.9995085,0.0000918353,0.00021080453,0.00003229024,0.00008084668,0.000075670076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004722596,0.00033480962,0.00019328686,0.0011130335,0.0001781486,0.00028401898,0.00013971678,0.00026250473,0.00080152013],"category_scores_gemma":[0.00095580245,0.00015884373,0.00017667538,0.00034021036,0.0004098514,0.00028564237,0.00035903018,0.00015945468,0.00010375227],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007693686,0.000077426375,0.8969378,0.00010938233,0.000073202005,0.0027056283,0.002124072,0.00033082464,0.08447559,0.00012196571,0.000090397065,0.012184469],"study_design_scores_gemma":[0.000005368073,0.00012081799,0.99363047,0.0000057745115,0.000020899848,0.0018984956,0.00049525575,0.00030751756,0.0033111267,0.00003295935,0.00016480932,0.0000064836154],"about_ca_topic_score_codex":0.0028881992,"about_ca_topic_score_gemma":0.0032360982,"teacher_disagreement_score":0.0028881992,"about_ca_system_score_codex":0.0002292093,"about_ca_system_score_gemma":0.00017385386,"threshold_uncertainty_score":0.0057427883},"labels":[],"label_agreement":null},{"id":"W3093463881","doi":"10.3389/fnhum.2020.568395","title":"Myelin Water Imaging Demonstrates Lower Brain Myelination in Children and Adolescents With Poor Reading Ability","year":2020,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; University of Calgary; University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Multiple Sclerosis Society of Canada","keywords":"Reading (process); Myelin; Psychology; Neuroscience; Developmental psychology; Medicine; Audiology; Central nervous system; Philosophy; Linguistics","score_opus":0.019078799648959203,"score_gpt":0.2896266605610808,"score_spread":0.2705478609121216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093463881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954057,0.000101257436,0.000039823404,0.000015736026,0.0000016638324,0.0000038257617,0.000040841725,0.00000621428,0.00025005089],"genre_scores_gemma":[0.99953115,0.000083892955,0.00010032019,0.000013275742,0.000003510054,0.000006442827,0.00007614255,0.00000316763,0.00018222707],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976534,0.000030161988,0.000037815953,0.000059417205,0.000057004516,0.000050383464],"domain_scores_gemma":[0.9988908,0.00019792828,0.0005988036,0.000034746787,0.00012539055,0.00015234924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004014929,0.00045355025,0.00047161404,0.0022552847,0.0003311981,0.0006365069,0.00023302295,0.00052284915,0.0019087564],"category_scores_gemma":[0.0020703813,0.00033110403,0.000299959,0.0006536358,0.00064226054,0.00060461165,0.0005473707,0.00051823404,0.00032492398],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016371536,0.00007687621,0.9872356,0.000039123912,0.00003429737,0.0019362194,0.0014225745,0.0000450643,0.0055221785,0.000044829147,0.000102663,0.003376889],"study_design_scores_gemma":[0.0000029494868,0.0001437531,0.9962722,0.000005894927,0.000012949295,0.0024854445,0.0005227081,0.000049920865,0.00038198257,0.00002300826,0.00009665551,0.0000025692634],"about_ca_topic_score_codex":0.0044498327,"about_ca_topic_score_gemma":0.0037500353,"teacher_disagreement_score":0.0044498327,"about_ca_system_score_codex":0.00022481171,"about_ca_system_score_gemma":0.00022156633,"threshold_uncertainty_score":0.008847892},"labels":[],"label_agreement":null},{"id":"W3093517549","doi":"10.1002/hbm.25237","title":"Atypical measures of diffusion at the gray‐white matter boundary in autism spectrum disorder in adulthood","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; SickKids Foundation; Centre for Addiction and Mental Health","funders":"Medical Research Council; Department of Psychiatry, University of Toronto; Canadian Institutes of Health Research; Innovative Medicines Initiative; Dr Mortimer and Theresa Sackler Foundation; European Commission; Deutsche Forschungsgemeinschaft; King's College London; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; University of Toronto; European Federation of Pharmaceutical Industries and Associations; Autism Speaks; Simons Foundation Autism Research Initiative; National Institute of Mental Health; Institute of Psychiatry, Psychology and Neuroscience, King’s College London; Ontario Brain Institute; South London and Maudsley NHS Foundation Trust","keywords":"Neurotypical; White matter; Diffusion MRI; Fractional anisotropy; Autism spectrum disorder; Psychology; Neuroscience; Neuroimaging; Autism; Neuropathology; Developmental psychology; Magnetic resonance imaging; Pathology; Medicine","score_opus":0.058128630095982584,"score_gpt":0.3120987991457971,"score_spread":0.2539701690498145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093517549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990509,0.00023986194,0.00038401358,0.00001655666,0.0000023260477,0.0000038498015,0.000095896794,0.000009445962,0.00019697509],"genre_scores_gemma":[0.99913895,0.000099733086,0.00059445936,0.0000055939404,0.0000026426196,0.000004713639,0.000082156344,0.0000038477806,0.00006785398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976534,0.0000389213,0.00003764037,0.00008613527,0.000046089935,0.000025850486],"domain_scores_gemma":[0.99904853,0.0001443244,0.0005546033,0.00007646204,0.00007562862,0.00010045839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005347869,0.0002491641,0.00029213916,0.0011081442,0.000279298,0.0004156562,0.00015670001,0.00031361944,0.00078988896],"category_scores_gemma":[0.0025517314,0.00017149844,0.000107458334,0.00039645442,0.00034492865,0.0005535516,0.0006783068,0.00022327965,0.000116619376],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055723457,0.000049419916,0.9396742,0.000105522,0.00010065341,0.0008412495,0.0020456414,0.0002857429,0.03625667,0.00032266165,0.00025831172,0.019502578],"study_design_scores_gemma":[0.0000028413215,0.000051011266,0.99665713,0.00000955899,0.000010195016,0.001226003,0.00032236608,0.00023380967,0.00111687,0.0002182376,0.00014768285,0.0000043497034],"about_ca_topic_score_codex":0.0017111396,"about_ca_topic_score_gemma":0.002706569,"teacher_disagreement_score":0.0017111396,"about_ca_system_score_codex":0.00014093616,"about_ca_system_score_gemma":0.00013537097,"threshold_uncertainty_score":0.0034023523},"labels":[],"label_agreement":null},{"id":"W3093910113","doi":"10.1002/jmri.27408","title":"Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at <scp>3T</scp> : Reproducibility and Quality of Fit","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Fondation Brain Canada","keywords":"Reproducibility; Kurtosis; Human Connectome Project; White matter; Effective diffusion coefficient; Diffusion MRI; Diffusion imaging; Pearson product-moment correlation coefficient; Nuclear medicine; Medicine; Nuclear magnetic resonance; Mathematics; Statistics; Computer science; Magnetic resonance imaging; Physics; Radiology","score_opus":0.12096480288776339,"score_gpt":0.39249192652900705,"score_spread":0.27152712364124365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093910113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7701527,0.0019841518,0.21401538,0.00041010158,0.00009177661,0.00035547648,0.0076661464,0.0017657428,0.0035585267],"genre_scores_gemma":[0.93708324,0.0003376349,0.055533655,0.00010710095,0.000034977787,0.00025088002,0.005592325,0.0007004279,0.00035983475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969368,0.0010599869,0.00048095576,0.000629071,0.00080210646,0.00009108611],"domain_scores_gemma":[0.9820394,0.007009395,0.0031314604,0.002954243,0.0046110353,0.00025438704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010855117,0.00068195025,0.00055714464,0.0017959217,0.00061808777,0.0018308304,0.0008300431,0.0009120643,0.0014433366],"category_scores_gemma":[0.027553234,0.00035457002,0.0009442924,0.0015626432,0.0006265058,0.00079884485,0.00084008055,0.0004196791,0.0004925569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055201924,0.00033631077,0.46688637,0.0026941192,0.006368799,0.0011791851,0.001882766,0.067737274,0.19038829,0.0020813448,0.010584202,0.24434106],"study_design_scores_gemma":[0.0001797377,0.00086107315,0.7716304,0.00024853952,0.001432862,0.0045113736,0.00047511954,0.11243274,0.092665955,0.004022148,0.011165837,0.0003742056],"about_ca_topic_score_codex":0.0033835277,"about_ca_topic_score_gemma":0.0050136778,"teacher_disagreement_score":0.010855117,"about_ca_system_score_codex":0.00054639654,"about_ca_system_score_gemma":0.0007293963,"threshold_uncertainty_score":0.057408094},"labels":[],"label_agreement":null},{"id":"W3093955191","doi":"10.7554/elife.61523","title":"An interactive meta-analysis of MRI biomarkers of myelin","year":2020,"lang":"en","type":"review","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"National Institute of Mental Health; National Institutes of Health; Wellcome Trust; Wellcome","keywords":"Relaxometry; Myelin; Modalities; Meta-analysis; Pathology; Neuroscience; Magnetic resonance imaging; Medicine; Biology; Radiology","score_opus":0.3227273080608277,"score_gpt":0.5091560169898481,"score_spread":0.18642870892902041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093955191","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008379961,0.97439176,0.008025334,0.0011834416,0.00053608156,0.00043652835,0.005596749,0.00032507422,0.0011250911],"genre_scores_gemma":[0.47297275,0.47300798,0.03361803,0.0028512592,0.00096791255,0.0033773512,0.009733864,0.00062080886,0.0028500615],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9849526,0.009986602,0.0020474845,0.0015156711,0.001151698,0.00034588636],"domain_scores_gemma":[0.97137094,0.02410389,0.0017124272,0.0011792182,0.001432123,0.00020138924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017452147,0.0026437982,0.007884324,0.0063799364,0.00053149095,0.002683575,0.0018591081,0.0015734222,0.0075404546],"category_scores_gemma":[0.057826832,0.00095706724,0.032826424,0.006341622,0.00037693814,0.0013702974,0.0017248375,0.001694775,0.00071716943],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017709115,0.000019806954,0.0069498164,0.15364787,0.8024061,0.00019474242,0.00010425996,0.0011006803,0.00055795995,0.0006209886,0.0033303266,0.029296592],"study_design_scores_gemma":[0.0004916258,0.00011975447,0.0047152056,0.008216163,0.9785839,0.0001353301,0.00003666145,0.0006213497,0.00024908446,0.0009748564,0.005826557,0.000029467747],"about_ca_topic_score_codex":0.0067074304,"about_ca_topic_score_gemma":0.013927484,"teacher_disagreement_score":0.017452147,"about_ca_system_score_codex":0.0014590237,"about_ca_system_score_gemma":0.0028315184,"threshold_uncertainty_score":0.0922969},"labels":[],"label_agreement":null},{"id":"W3094034242","doi":"10.1093/brain/awaa316","title":"Diffuse axonal injury predicts neurodegeneration after moderate–severe traumatic brain injury","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Wolfson Foundation; UK Dementia Research Institute; National Institute for Health and Care Research; Imperial College Healthcare NHS Trust; Brain Research UK; Weston Brain Institute","keywords":"Diffuse axonal injury; Traumatic brain injury; Fractional anisotropy; Neurodegeneration; White matter; Chronic traumatic encephalopathy; Atrophy; Medicine; Neuroscience; Diffusion MRI; Pathology; Poison control; Magnetic resonance imaging; Psychology; Disease; Concussion; Injury prevention; Radiology","score_opus":0.06925358403255308,"score_gpt":0.3321054108816116,"score_spread":0.2628518268490585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094034242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99949145,0.000112044516,0.00006227598,0.00003101667,0.0000026974144,0.000005094919,0.00006907077,0.0000024407227,0.00022392719],"genre_scores_gemma":[0.99968994,0.000046045294,0.000039981274,0.00000600097,0.000006898477,0.0000021993371,0.00011510133,9.221903e-7,0.00009293346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998167,0.000036876165,0.000031425774,0.000045202392,0.000036988764,0.000032775824],"domain_scores_gemma":[0.99829715,0.00022416956,0.00085362286,0.0001241105,0.00015157978,0.00034932955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004865454,0.0005231447,0.00033073206,0.00069020194,0.00048949115,0.00043917992,0.00024189749,0.00055116846,0.0020266532],"category_scores_gemma":[0.0021382214,0.00023032262,0.0004579653,0.00044295212,0.00037926668,0.0003740145,0.0006249921,0.00066571566,0.0003730724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022147456,0.00004238372,0.997875,0.0000075862304,0.00005271249,0.00009238405,0.00005040204,0.0001020092,0.00047557594,0.000015322328,0.000043906428,0.001021281],"study_design_scores_gemma":[0.0000027588412,0.00009203275,0.9993579,0.000002310629,0.000011323444,0.0002382556,0.000046221663,0.00013860821,0.00004571437,0.000032700296,0.000029916211,0.000002271474],"about_ca_topic_score_codex":0.0027326893,"about_ca_topic_score_gemma":0.004208486,"teacher_disagreement_score":0.0027326893,"about_ca_system_score_codex":0.00017413606,"about_ca_system_score_gemma":0.00028444742,"threshold_uncertainty_score":0.00677979},"labels":[],"label_agreement":null},{"id":"W3094061741","doi":"10.1371/journal.pone.0239116","title":"White matter tract microstructure and cognitive performance after transient ischemic attack","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Children's Hospital; Foothills Medical Centre; University of Calgary","funders":"Heart and Stroke Foundation of Canada","keywords":"White matter; Microstructure; Cognition; Transient (computer programming); Medicine; Cardiology; Magnetic resonance imaging; Computer science; Materials science; Psychiatry; Radiology; Composite material","score_opus":0.06160278329870132,"score_gpt":0.28698949723346573,"score_spread":0.2253867139347644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094061741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993924,0.00017185148,0.00004179557,0.000021179207,0.0000027849617,0.0000031011718,0.000103594604,0.000003636996,0.0002597747],"genre_scores_gemma":[0.99960274,0.00005939825,0.000032429045,0.0000051104366,0.0000052624364,0.000002064736,0.00014928206,0.0000012508145,0.00014249199],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991286,0.000014141005,0.0000117890595,0.000024362846,0.000015737998,0.000021070335],"domain_scores_gemma":[0.9990337,0.00010599926,0.0006016732,0.00005133039,0.000085469954,0.000121857185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030193213,0.00026677633,0.00021417488,0.00045862581,0.00025973088,0.0005022508,0.00016592309,0.00028203917,0.0018412557],"category_scores_gemma":[0.0019334273,0.000115466035,0.0001865147,0.00039636865,0.00024506275,0.00027431495,0.00023350559,0.000234289,0.00026975267],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004638603,0.000056073517,0.99498403,0.000015088774,0.0001012136,0.00018000977,0.00009814619,0.00014047694,0.0012252582,0.000026773625,0.00009124652,0.002617943],"study_design_scores_gemma":[0.0000023652015,0.00006710415,0.99953735,0.0000023222633,0.000011068537,0.00017406205,0.000021783513,0.000079772166,0.00005385366,0.000018662871,0.000030503848,0.0000010697942],"about_ca_topic_score_codex":0.00416448,"about_ca_topic_score_gemma":0.0044568367,"teacher_disagreement_score":0.00416448,"about_ca_system_score_codex":0.00030091888,"about_ca_system_score_gemma":0.00019237712,"threshold_uncertainty_score":0.008280516},"labels":[],"label_agreement":null},{"id":"W3094366600","doi":"10.1016/j.dcn.2020.100875","title":"Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines","year":2020,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Voxel; Voxel-based morphometry; White matter; Grey matter; Psychology; Artificial intelligence; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.06792614884400805,"score_gpt":0.3383568891080774,"score_spread":0.2704307402640693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094366600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881798,0.00039214737,0.0090018,0.000059778173,0.000009323488,0.00003982263,0.0011091182,0.00034492172,0.00086333044],"genre_scores_gemma":[0.9796779,0.00041983812,0.016390862,0.000025383984,0.0000053242084,0.000075116506,0.0023677135,0.00038505063,0.0006526229],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909234,0.00021068825,0.00006738247,0.0002976796,0.00021164077,0.00012026781],"domain_scores_gemma":[0.99698704,0.0015877263,0.00037982885,0.0003842072,0.0005034262,0.0001577078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026569623,0.0005598481,0.00040536295,0.0014336373,0.0002685036,0.0009482783,0.00061264075,0.00043513378,0.0012354678],"category_scores_gemma":[0.008523771,0.0005357195,0.0007173315,0.0007214225,0.0004776207,0.00089961564,0.00079788396,0.00045305374,0.00035341352],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007119768,0.00028678,0.60145974,0.00067459187,0.0014494997,0.0008075386,0.0067569003,0.032305405,0.07909686,0.0033157838,0.0026751214,0.26405194],"study_design_scores_gemma":[0.00005687786,0.00067191577,0.9564739,0.000080134334,0.00032694355,0.00079884636,0.0008332323,0.020879153,0.015836395,0.0013317522,0.0026455936,0.000065210916],"about_ca_topic_score_codex":0.012626547,"about_ca_topic_score_gemma":0.014434748,"teacher_disagreement_score":0.012626547,"about_ca_system_score_codex":0.00067536667,"about_ca_system_score_gemma":0.0009642054,"threshold_uncertainty_score":0.025106132},"labels":[],"label_agreement":null},{"id":"W3095356774","doi":"10.3389/fnhum.2020.509258","title":"White Matter Neuroplasticity: Motor Learning Activates the Internal Capsule and Reduces Hemodynamic Response Variability","year":2020,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Fraser Health; Baycrest Hospital; University of Calgary; Simon Fraser University; University of British Columbia; Surrey Memorial Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroplasticity; Motor learning; Haemodynamic response; Internal capsule; Neuroscience; Psychology; White matter; Medicine; Internal medicine; Magnetic resonance imaging; Heart rate; Radiology","score_opus":0.030897466705632676,"score_gpt":0.303472759518954,"score_spread":0.2725752928133214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095356774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937775,0.00027901542,0.0049851956,0.000075342614,0.000008337086,0.000035020465,0.000052020197,0.00010081427,0.00068673637],"genre_scores_gemma":[0.9952113,0.00014050436,0.0033251273,0.000047191825,0.000013559113,0.00004404849,0.00009086483,0.00002635287,0.0011011838],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99987483,0.000023243423,0.000008891164,0.00004882596,0.00002255087,0.00002166548],"domain_scores_gemma":[0.99962294,0.000073515694,0.00018546007,0.0000422986,0.000018077772,0.000057663634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003611849,0.00033648475,0.00027871705,0.00018344056,0.00012051821,0.00027221613,0.00022075238,0.00026862827,0.0025122305],"category_scores_gemma":[0.00084246974,0.0001135592,0.0001145962,0.00012298918,0.00043301788,0.0003111879,0.0002760313,0.00019063895,0.00020069278],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088665786,0.00029350483,0.0026412893,0.00011274761,0.00003263934,0.00012600297,0.000058537225,0.00014907133,0.97721714,0.00008030283,0.00010291499,0.018299293],"study_design_scores_gemma":[0.00022440655,0.0106293615,0.55173177,0.000034745284,0.00012889596,0.0022091442,0.00009194076,0.0023662846,0.42966154,0.0007673061,0.002122245,0.000032283664],"about_ca_topic_score_codex":0.00040652076,"about_ca_topic_score_gemma":0.00072261156,"teacher_disagreement_score":0.0025122305,"about_ca_system_score_codex":0.00012683641,"about_ca_system_score_gemma":0.00025815357,"threshold_uncertainty_score":0.008404195},"labels":[],"label_agreement":null},{"id":"W3095563856","doi":"10.1016/j.neuroimage.2020.117513","title":"Plis de passage in the superior temporal sulcus: Morphology and local connectivity","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Mental Health; National Institutes of Health; NIH Blueprint for Neuroscience Research; Agence Nationale de la Recherche; McDonnell Center for Systems Neuroscience; Aix-Marseille Université","keywords":"Sulcus; Superior temporal sulcus; Anatomy; Functional connectivity; Central sulcus; White matter; Neuroscience; Psychology; Biology; Cartography; Geography; Medicine; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.06893601656193592,"score_gpt":0.33533053490757064,"score_spread":0.2663945183456347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095563856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926658,0.0004220678,0.0044362205,0.00007574052,0.0000051641023,0.000030706713,0.00047207542,0.00006116271,0.001831049],"genre_scores_gemma":[0.99824095,0.00013471066,0.0010582594,0.000006209651,0.0000066479765,0.000014735528,0.00024604506,0.000013557564,0.00027879496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986136,0.00003463613,0.000012701775,0.00004738227,0.000027457532,0.000016459937],"domain_scores_gemma":[0.99958915,0.00014315856,0.0001380379,0.00006458387,0.000035861078,0.0000293008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027809883,0.00023502173,0.00020203677,0.0012210627,0.00021360163,0.0005835501,0.00016525693,0.00020303573,0.0022255916],"category_scores_gemma":[0.0017561159,0.00015594116,0.00022890748,0.000922261,0.0007248192,0.00063566695,0.00045778745,0.00016635431,0.0002716162],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001914379,0.00009596445,0.600595,0.00050059863,0.00051009684,0.006002594,0.0035698481,0.004246239,0.19768852,0.005482102,0.001986574,0.17740802],"study_design_scores_gemma":[0.000015381916,0.00011848757,0.9856806,0.000016795371,0.000061541985,0.0040101036,0.0003314198,0.0030797902,0.00362592,0.002415811,0.00063310756,0.000010945697],"about_ca_topic_score_codex":0.0027150784,"about_ca_topic_score_gemma":0.004672417,"teacher_disagreement_score":0.0027150784,"about_ca_system_score_codex":0.00016584733,"about_ca_system_score_gemma":0.00026356656,"threshold_uncertainty_score":0.007445276},"labels":[],"label_agreement":null},{"id":"W3097263943","doi":"10.1093/schizbullopen/sgaa057","title":"Frontostriatal Structural Connectivity and Striatal Glutamatergic Levels in Treatment-Resistant Schizophrenia: An Integrative Analysis of DTI and 1H-MRS","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; McGill University; Douglas Mental Health University Institute","funders":"Japan Society for the Promotion of Science; Japan Agency for Medical Research and Development","keywords":"Caudate nucleus; Psychology; Internal medicine; Glutamatergic; Dorsolateral prefrontal cortex; Schizophrenia (object-oriented programming); Fractional anisotropy; Neuroscience; Prefrontal cortex; White matter; Medicine; Glutamate receptor; Endocrinology; Psychiatry; Magnetic resonance imaging; Cognition","score_opus":0.0678768236902872,"score_gpt":0.35222916742374144,"score_spread":0.28435234373345425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3097263943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99931955,0.00023185354,0.00021742667,0.000016416743,6.084755e-7,0.0000061290443,0.00005903124,0.000005542476,0.0001434512],"genre_scores_gemma":[0.9992176,0.00010744213,0.0004899239,0.0000062003983,0.0000024788317,0.000005506571,0.00011680932,0.0000024343387,0.000051501964],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998964,0.00003892143,0.000009674589,0.000024261866,0.000019055165,0.0000116728415],"domain_scores_gemma":[0.9997824,0.00004366238,0.00009816318,0.000018637635,0.000027431339,0.000029742094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005029701,0.0003911158,0.00042763268,0.0010492337,0.0002047426,0.00036949065,0.00018831814,0.0002579002,0.000642065],"category_scores_gemma":[0.0006480541,0.00017076723,0.0002886645,0.00044279764,0.00025023828,0.0002427137,0.0002995038,0.0001911754,0.00009729514],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013185855,0.00019837482,0.917883,0.00008354931,0.00057303376,0.00047435815,0.00066842034,0.00074916874,0.0567373,0.000119880475,0.00011996294,0.021074288],"study_design_scores_gemma":[0.00001041729,0.00019538315,0.9969181,0.0000065703966,0.00005666254,0.0003321605,0.00018932617,0.0015062202,0.000657532,0.00005710433,0.00006548911,0.000005074895],"about_ca_topic_score_codex":0.0032744608,"about_ca_topic_score_gemma":0.0077093034,"teacher_disagreement_score":0.0032744608,"about_ca_system_score_codex":0.0003336396,"about_ca_system_score_gemma":0.00017204335,"threshold_uncertainty_score":0.006510794},"labels":[],"label_agreement":null},{"id":"W3098627671","doi":"10.3389/fnana.2020.599701","title":"In vivo Population Averaged Stereotaxic T2w MRI Brain Template for the Adult Yucatan Micropig","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; Neurosurgery Research and Education Foundation; U.S. Department of Defense","keywords":"Template; Neuroimaging; Brain morphometry; Population; Computer science; Probabilistic logic; Diffusion MRI; Neuroscience; Psychology; Artificial intelligence; Magnetic resonance imaging; Medicine","score_opus":0.03105195263611685,"score_gpt":0.31518982359094383,"score_spread":0.28413787095482695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3098627671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32502803,0.00029219684,0.65180343,0.0002700489,0.00014961675,0.0008825558,0.008810522,0.0026096061,0.010153937],"genre_scores_gemma":[0.34798357,0.00040846365,0.6233706,0.00025682565,0.000025380305,0.0019053109,0.013516742,0.0012641811,0.011268969],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998684,0.000008294129,0.000014118291,0.00006500659,0.00003111234,0.000013168331],"domain_scores_gemma":[0.9997029,0.000029687671,0.000043572847,0.00009695643,0.000104803716,0.000022040555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041102542,0.0002915554,0.0002173195,0.0007798419,0.0004666178,0.00044148517,0.0005375735,0.0005292736,0.0053624543],"category_scores_gemma":[0.0005487883,0.00031152184,0.00027184084,0.0004924151,0.000319647,0.0004024154,0.0004278969,0.00054183806,0.0018780535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037996194,0.00014263489,0.012963364,0.00031406782,0.00008970194,0.0016390424,0.0009004406,0.0061028595,0.7779607,0.008232785,0.013849515,0.17742491],"study_design_scores_gemma":[0.000056808294,0.001053067,0.25407204,0.00026230066,0.00032099398,0.015611433,0.0011108262,0.07506707,0.39683107,0.009066259,0.24635065,0.00019753359],"about_ca_topic_score_codex":0.0042922394,"about_ca_topic_score_gemma":0.017948467,"teacher_disagreement_score":0.0053624543,"about_ca_system_score_codex":0.00032698677,"about_ca_system_score_gemma":0.0005903634,"threshold_uncertainty_score":0.01793921},"labels":[],"label_agreement":null},{"id":"W3099889620","doi":"10.3390/brainsci10110879","title":"Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Clinical Dementia Rating; Cognition; Dementia; Psychology; Diffusion MRI; Association (psychology); Cognitive test; Disease; Alzheimer's disease; Cohort; Physical medicine and rehabilitation; Cognitive psychology; Audiology; Neuroscience; Medicine; Cognitive impairment; Internal medicine; Magnetic resonance imaging","score_opus":0.14003187563627217,"score_gpt":0.4001416751281488,"score_spread":0.2601097994918766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099889620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987174,0.00014572119,0.00076179125,0.000035044166,0.000002624575,0.0000044837325,0.0000948518,0.000006878496,0.00023125226],"genre_scores_gemma":[0.9993006,0.000046829657,0.00050571153,0.0000039719203,0.000004212242,0.0000032518592,0.00008038906,0.0000015202834,0.0000534686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997925,0.000074006966,0.000018812936,0.0000640091,0.000027424578,0.000023231363],"domain_scores_gemma":[0.9990675,0.00036246955,0.00030398098,0.000097132586,0.000076409546,0.00009255163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078916404,0.0002918321,0.00019361668,0.0012040592,0.00021208545,0.00037676233,0.00018017019,0.0002528541,0.0009390273],"category_scores_gemma":[0.0029534341,0.000096366886,0.00025852994,0.0004873603,0.00031324354,0.00033185392,0.00039088156,0.00030633973,0.000062137304],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003461074,0.00006575902,0.98138535,0.000027211852,0.00028623428,0.00018697503,0.00015444098,0.0017096011,0.0024925652,0.00054923,0.00015700088,0.012639569],"study_design_scores_gemma":[0.0000055223186,0.000094734125,0.9910062,0.000008075786,0.00006131278,0.00038766884,0.00008972482,0.0066512283,0.00027310985,0.0013047422,0.000110691224,0.0000069434773],"about_ca_topic_score_codex":0.0026495592,"about_ca_topic_score_gemma":0.005352978,"teacher_disagreement_score":0.0026495592,"about_ca_system_score_codex":0.00017023252,"about_ca_system_score_gemma":0.00018281247,"threshold_uncertainty_score":0.0052682757},"labels":[],"label_agreement":null},{"id":"W3100033656","doi":"10.1101/2020.07.13.200972","title":"An interactive meta-analysis of MRI biomarkers of myelin","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"Wellcome Trust","keywords":"Myelin; Relaxometry; Modalities; Meta-analysis; Computer science; Pathology; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Radiology","score_opus":0.08975004590109842,"score_gpt":0.3442505196969797,"score_spread":0.25450047379588125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100033656","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076025285,0.8277477,0.056602094,0.004279233,0.0022486148,0.0011762091,0.02682392,0.0021470753,0.0029498183],"genre_scores_gemma":[0.91017807,0.045036916,0.03017466,0.0020115613,0.0008211914,0.0023410416,0.0069259093,0.00094457105,0.0015661694],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.95527434,0.03204942,0.0039942167,0.0053571383,0.00249568,0.0008292156],"domain_scores_gemma":[0.8998068,0.0870143,0.0044399295,0.005510394,0.0026216425,0.00060692214],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.037405733,0.003438179,0.009720578,0.007792081,0.0009404151,0.004178252,0.0026892677,0.0024536944,0.009815715],"category_scores_gemma":[0.1064038,0.0013566621,0.055604555,0.0071971673,0.00073516706,0.0019370137,0.0026162534,0.0025672587,0.00079527433],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023412732,0.000018753099,0.0118652,0.030704083,0.9438474,0.00017785185,0.00006926809,0.0016283555,0.0005882582,0.00037252883,0.0016683544,0.006718748],"study_design_scores_gemma":[0.00058268185,0.00018698671,0.0071232873,0.0017244153,0.9850211,0.00012427701,0.000036945785,0.0015626752,0.0003175005,0.0010551699,0.0022300913,0.000034883262],"about_ca_topic_score_codex":0.0064054993,"about_ca_topic_score_gemma":0.008385285,"teacher_disagreement_score":0.9625943,"about_ca_system_score_codex":0.0015592248,"about_ca_system_score_gemma":0.0020308034,"threshold_uncertainty_score":0.19782275},"labels":[],"label_agreement":null},{"id":"W3100567746","doi":"10.1016/j.nicl.2020.102508","title":"Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Neuroimaging; Neuroplasticity; Stroke (engine); White matter; Neuroscience; Physical medicine and rehabilitation; Tractography; Corticospinal tract; Diffusion MRI; Motor learning; Psychology; Machine learning; Medicine; Artificial intelligence; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.14074226609155271,"score_gpt":0.3935484635267317,"score_spread":0.25280619743517896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100567746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974058,0.00021155308,0.0020154999,0.0000821332,0.000002630549,0.000008667341,0.00010580716,0.00001299116,0.00015491642],"genre_scores_gemma":[0.99789494,0.00019082907,0.0015528831,0.00001247312,0.000006615535,0.0000129925975,0.00022781428,0.0000052907976,0.00009615899],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972576,0.0001141766,0.000019680843,0.00006149142,0.000037596903,0.00004138331],"domain_scores_gemma":[0.99801624,0.0013626284,0.0002911896,0.00015361392,0.000091965136,0.00008431399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010395631,0.0003025866,0.00028315946,0.0010450458,0.00023748353,0.00031191888,0.00035031434,0.00031698405,0.0006414888],"category_scores_gemma":[0.005181635,0.00015961047,0.00039777128,0.0006588271,0.00046828276,0.0003799666,0.00021374464,0.0004938022,0.00015560769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081811484,0.0004522305,0.88186705,0.00008790791,0.000496057,0.0013767645,0.00043482182,0.015223147,0.0062562036,0.0006281255,0.0005202504,0.09183927],"study_design_scores_gemma":[0.000021804859,0.00054596126,0.91886693,0.000025630145,0.000105094114,0.0015045546,0.00021781614,0.07532126,0.0020498144,0.0010100178,0.0003118415,0.000019235931],"about_ca_topic_score_codex":0.0037812144,"about_ca_topic_score_gemma":0.003582673,"teacher_disagreement_score":0.0037812144,"about_ca_system_score_codex":0.0003749314,"about_ca_system_score_gemma":0.00029586148,"threshold_uncertainty_score":0.007518351},"labels":[],"label_agreement":null},{"id":"W3100851471","doi":"10.1101/867606","title":"Diffusion MRI free water is a sensitive marker of age-related changes in the cingulum","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Caisse nationale de solidarité pour l'autonomie; Mitacs; Fondation de France; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale; Fondation Vaincre Alzheimer; CHIST-ERA; Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Mutuelle Générale de l'Education Nationale; Université de Sherbrooke; Sanofi","keywords":"Cingulum (brain); White matter; Splenium; Diffusion MRI; Inferior longitudinal fasciculus; Hyperintensity; Psychology; Verbal fluency test; Cognitive decline; Audiology; Neuroscience; Magnetic resonance imaging; Cognition; Fractional anisotropy; Neuropsychology; Medicine; Dementia; Pathology; Radiology; Disease","score_opus":0.02285288681428393,"score_gpt":0.26263929191258667,"score_spread":0.23978640509830274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100851471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853204,0.0031541795,0.010248412,0.000041109055,0.000023515493,0.00003414186,0.0004523862,0.000104973245,0.0006209044],"genre_scores_gemma":[0.9893483,0.0007519909,0.008455031,0.000032307875,0.0000161482,0.000049422488,0.00040788433,0.000040057843,0.0008988054],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99981767,0.000035545774,0.000019428426,0.000054116488,0.000045238536,0.000027953836],"domain_scores_gemma":[0.9996489,0.00006732254,0.00015059994,0.00003891361,0.00006626104,0.000027936914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051103864,0.0005342048,0.00039898045,0.0009908902,0.00025029533,0.0003943481,0.00019787002,0.00039125604,0.0013266223],"category_scores_gemma":[0.0009845791,0.00021111724,0.00021399035,0.0004949478,0.00027942983,0.00035475954,0.0003008876,0.00020502292,0.00019543807],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033988594,0.00015460253,0.12148239,0.0004838437,0.00060009974,0.0005331827,0.00040810223,0.0015050357,0.7679439,0.000333397,0.0009933946,0.102163196],"study_design_scores_gemma":[0.000052711668,0.0011689109,0.8658531,0.00005560972,0.00028840743,0.000986684,0.0001531802,0.005858059,0.12228333,0.0006448494,0.00260732,0.000047918187],"about_ca_topic_score_codex":0.0018432172,"about_ca_topic_score_gemma":0.0038793338,"teacher_disagreement_score":0.0018432172,"about_ca_system_score_codex":0.00012915864,"about_ca_system_score_gemma":0.00012549394,"threshold_uncertainty_score":0.004437983},"labels":[],"label_agreement":null},{"id":"W3102547238","doi":"10.1101/2020.11.16.385229","title":"Track-To-Learn: A general framework for tractography with deep reinforcement learning","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Tractography; Artificial intelligence; Computer science; Prior probability; Leverage (statistics); Deep learning; Machine learning; Diffusion MRI; Bayesian probability","score_opus":0.03895521377875129,"score_gpt":0.2981409867084565,"score_spread":0.25918577292970524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102547238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004907831,0.00014835566,0.9983924,0.00012715517,0.000018785999,0.000024481707,0.00004025292,0.00031158145,0.00044619746],"genre_scores_gemma":[0.15812433,0.0010285242,0.8314027,0.00035665068,0.00019174915,0.00086484186,0.00043911455,0.0006259232,0.0069662128],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902153,0.00040951787,0.000060716047,0.00021176285,0.00020526326,0.00009118906],"domain_scores_gemma":[0.9983109,0.0009484489,0.00018104381,0.00022171653,0.00020243025,0.00013546541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032885722,0.0016489523,0.0016026077,0.0009220272,0.0005201589,0.0018944461,0.0033610128,0.0026238784,0.004898658],"category_scores_gemma":[0.0070227343,0.000943367,0.0015171083,0.0010191211,0.0022758588,0.002124291,0.0032610605,0.0037209485,0.0012738087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006423224,0.000060495306,0.00043486437,0.00013472741,0.00007847444,0.00010917168,0.00007173254,0.80069864,0.00091507455,0.13916448,0.002670878,0.05559721],"study_design_scores_gemma":[0.000008307307,0.000014700661,0.000022008491,0.000010028777,0.000004305465,0.000010741908,0.0000022198872,0.96055484,0.00016276627,0.038037714,0.0011676601,0.000004734707],"about_ca_topic_score_codex":0.006398875,"about_ca_topic_score_gemma":0.006927178,"teacher_disagreement_score":0.006398875,"about_ca_system_score_codex":0.0020147928,"about_ca_system_score_gemma":0.002252487,"threshold_uncertainty_score":0.0173918},"labels":[],"label_agreement":null},{"id":"W3102824520","doi":"10.1016/j.euroneuro.2020.09.370","title":"P.506 Altered neurite density and dispersion in the white matter of carriers of 16p11.2 copy number variants","year":2020,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medicine; Periprosthetic; Predictive value; Humanities; Internal medicine; Surgery; Philosophy; Arthroplasty","score_opus":0.03874976731888263,"score_gpt":0.33990631581404457,"score_spread":0.30115654849516194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102824520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979468,0.0002687091,0.00040016277,0.00007594816,0.000025354288,0.0000044023113,0.00064711575,0.00002402415,0.00060758996],"genre_scores_gemma":[0.9976833,0.00017365835,0.00044437672,0.00003272951,0.000019472187,0.000009813751,0.00027830456,0.000031176376,0.0013271718],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99980396,0.000022947157,0.000027851725,0.00008412032,0.000040245373,0.000020846435],"domain_scores_gemma":[0.99943715,0.00017290542,0.00024005905,0.000048011992,0.00003897778,0.00006292018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017960211,0.00083380775,0.00043578632,0.0008880275,0.00041606807,0.00049293076,0.00037013422,0.0010121858,0.00677755],"category_scores_gemma":[0.0010673505,0.00026042247,0.0003313617,0.0006025838,0.00042639035,0.00028235154,0.0003638791,0.0005267278,0.00061595277],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009552958,0.0003038031,0.2775202,0.00043792868,0.0012615118,0.055778243,0.0029123165,0.0015102619,0.6084157,0.001716372,0.0018582873,0.038732346],"study_design_scores_gemma":[0.00014400552,0.0005664571,0.92113817,0.000121243414,0.00068936415,0.045926888,0.000640919,0.0029946584,0.022315264,0.0028767874,0.002503607,0.00008253611],"about_ca_topic_score_codex":0.004143681,"about_ca_topic_score_gemma":0.0026479808,"teacher_disagreement_score":0.00677755,"about_ca_system_score_codex":0.00017603103,"about_ca_system_score_gemma":0.00013783299,"threshold_uncertainty_score":0.02267319},"labels":[],"label_agreement":null},{"id":"W3102841078","doi":"10.1002/hbm.25253","title":"Patch‐wise brain age longitudinal reliability","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Pfizer Canada; Fonds de Recherche du Québec - Santé; Alzheimer's Society; Pfizer","keywords":"Longitudinal study; Reliability (semiconductor); Magnetic resonance imaging; Longitudinal data; Neuroimaging; Volunteer; Psychology; Computer science; Audiology; Statistics; Medicine; Data mining; Mathematics; Neuroscience; Radiology; Biology","score_opus":0.17760902915917862,"score_gpt":0.3756412571497676,"score_spread":0.19803222799058898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102841078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68780935,0.002575249,0.30162063,0.00029451255,0.00016393875,0.00008829556,0.0037315616,0.0014213049,0.0022951968],"genre_scores_gemma":[0.9777027,0.00025046442,0.019247299,0.000040600902,0.00006231855,0.000034307297,0.0018244684,0.00009066249,0.0007471368],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990522,0.00025682026,0.000041351486,0.00049418357,0.00009855377,0.000056800247],"domain_scores_gemma":[0.9951887,0.0017928818,0.00053693174,0.0013067847,0.0010743157,0.00010033784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004101873,0.00046710603,0.00065243925,0.00086323963,0.00021351142,0.0005218917,0.0007063514,0.0005413711,0.0016917984],"category_scores_gemma":[0.009322538,0.0002445954,0.0006255839,0.0005228354,0.00035814886,0.00080113753,0.0005738531,0.000512603,0.0008569121],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014293563,0.00012139776,0.5199301,0.00039155813,0.002418169,0.00040305624,0.00064463937,0.122812465,0.03363359,0.002292166,0.013003238,0.3029202],"study_design_scores_gemma":[0.00003776614,0.00037530053,0.4037086,0.0000607708,0.00048695898,0.0014611591,0.0002056787,0.56496805,0.017028736,0.005957939,0.0056032497,0.000105783896],"about_ca_topic_score_codex":0.00436208,"about_ca_topic_score_gemma":0.0038222624,"teacher_disagreement_score":0.00436208,"about_ca_system_score_codex":0.00020766993,"about_ca_system_score_gemma":0.00026981567,"threshold_uncertainty_score":0.02169305},"labels":[],"label_agreement":null},{"id":"W3102888858","doi":"10.1007/s12021-020-09497-1","title":"Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography","year":2020,"lang":"en","type":"article","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; U.S. Department of Defense","keywords":"Tractography; Diffusion MRI; White matter; Fiber tract; Bundle; Population; Neuroscience; Computer science; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Radiology; Materials science","score_opus":0.0401730737370954,"score_gpt":0.2885568518185119,"score_spread":0.24838377808141648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102888858","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022165515,0.0003344408,0.9013792,0.00027236194,0.00015918488,0.00040889528,0.023704952,0.042902198,0.00867327],"genre_scores_gemma":[0.13989817,0.0006568131,0.8156788,0.00014424336,0.00006872627,0.0014480051,0.024428366,0.0096152965,0.008061642],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997788,0.000042888543,0.00001924155,0.00008063843,0.00005633449,0.00002209004],"domain_scores_gemma":[0.9996086,0.00012503914,0.0000624497,0.00008558523,0.000092690025,0.000025707639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007004811,0.001170728,0.0006716836,0.0018464986,0.0008472585,0.0027154062,0.0014051596,0.0013460264,0.02237489],"category_scores_gemma":[0.0025534169,0.0011418691,0.0012148693,0.0017835551,0.00043500957,0.0014586903,0.0016517729,0.0015916063,0.0069913836],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012745857,0.0002916558,0.008331858,0.0015671632,0.0008221397,0.001282061,0.0013884746,0.10382627,0.048205752,0.05306927,0.21560128,0.56433946],"study_design_scores_gemma":[0.00032493,0.00037741335,0.01845048,0.00038421078,0.00051912747,0.0053061405,0.00036478916,0.53000623,0.033452217,0.089178406,0.32124344,0.0003926353],"about_ca_topic_score_codex":0.010353098,"about_ca_topic_score_gemma":0.023609778,"teacher_disagreement_score":0.02237489,"about_ca_system_score_codex":0.0005523665,"about_ca_system_score_gemma":0.0023959067,"threshold_uncertainty_score":0.07485151},"labels":[],"label_agreement":null},{"id":"W3103593486","doi":"10.3389/fpsyg.2020.608049","title":"Associations Between Physical Fitness and Brain Structure in Young Adulthood","year":2020,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Fractional anisotropy; Psychology; Diffusion MRI; White matter; Physical fitness; Connectome; Human Connectome Project; Brain size; Magnetic resonance imaging; Neuroscience; Physical therapy; Medicine","score_opus":0.03718807847145747,"score_gpt":0.3773504608082844,"score_spread":0.34016238233682694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3103593486","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993611,0.0002044547,0.00006496705,0.000018626368,0.000002349568,0.0000021078229,0.00016876629,0.0000021850228,0.00017541806],"genre_scores_gemma":[0.99938774,0.000098585275,0.00009782161,0.000010304169,0.0000037284972,0.0000040636783,0.00020723023,0.0000014774554,0.00018890564],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982244,0.000033349774,0.000017665456,0.00006774639,0.000025865282,0.000033033142],"domain_scores_gemma":[0.9995597,0.00005837823,0.00018529578,0.00005015624,0.000054297863,0.00009213257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037558016,0.00021126805,0.00026906992,0.000519365,0.00028664686,0.00033245844,0.0001642285,0.00038994406,0.0007540556],"category_scores_gemma":[0.001276586,0.00022374296,0.00021824331,0.00037533356,0.0001746294,0.00021011196,0.00040034897,0.00029585583,0.00010137401],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006694387,0.000015185493,0.9968094,0.0000061339433,0.00007812585,0.00006152654,0.00012503623,0.000037462858,0.0006460815,0.000022563763,0.00006123887,0.002070269],"study_design_scores_gemma":[4.2696396e-7,0.000012492564,0.9998596,0.000001083522,0.000004700325,0.000037079673,0.000016640008,0.000020459558,0.00001591225,0.000008666908,0.000022236469,5.169596e-7],"about_ca_topic_score_codex":0.0065955617,"about_ca_topic_score_gemma":0.015155483,"teacher_disagreement_score":0.0065955617,"about_ca_system_score_codex":0.00012647228,"about_ca_system_score_gemma":0.00009300499,"threshold_uncertainty_score":0.013114333},"labels":[],"label_agreement":null},{"id":"W3105764270","doi":"","title":"Holonomy spin foam models: Asymptotic geometry of the partition function","year":2013,"lang":"en","type":"article","venue":"MPG.PuRe (Max Planck Society)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Narodowe Centrum Nauki; Institut Périmètre de physique théorique; Industry Canada; Government of Canada","keywords":"Partition function (quantum field theory); Spin foam; Holonomy; Immirzi parameter; Curvature; Mathematics; Partition (number theory); Boundary (topology); Spin network; Spins; Geometry; Mathematical analysis; Loop quantum gravity; Physics; Combinatorics; Quantum mechanics; Quantum; Quantum gravity","score_opus":0.054361670690449636,"score_gpt":0.28978365419648305,"score_spread":0.2354219835060334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105764270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8707097,0.0010628557,0.09375504,0.0018316051,0.000067555964,0.00003683379,0.00011992221,0.00024561374,0.032170866],"genre_scores_gemma":[0.99403524,0.00021644119,0.0035554352,0.00006507983,0.000054881173,0.000031521256,0.00006889184,0.000032259653,0.0019402801],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99967587,0.00011610793,0.000010639011,0.000030797622,0.00006971337,0.000096960845],"domain_scores_gemma":[0.99905556,0.00036291868,0.00015831618,0.000118922144,0.000093849165,0.00021052122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010181837,0.0007085716,0.0007506805,0.0018228595,0.0011322567,0.0019238786,0.0013540527,0.0014167023,0.0033924473],"category_scores_gemma":[0.003575198,0.00031329252,0.00074550876,0.00060301006,0.002712366,0.0026889187,0.0017689696,0.0012277769,0.0003966546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056752495,0.000033852477,0.00085603044,0.000049731978,0.000014254484,0.00029027235,0.00026773094,0.014135338,0.0022004712,0.9794439,0.00066973956,0.0019819196],"study_design_scores_gemma":[0.000020907095,0.000025451613,0.0008741482,0.000027513612,0.000010671162,0.00021468174,0.00011488172,0.1924997,0.0007132811,0.80511665,0.00036442286,0.000017655593],"about_ca_topic_score_codex":0.0013921731,"about_ca_topic_score_gemma":0.000999198,"teacher_disagreement_score":0.0033924473,"about_ca_system_score_codex":0.0011819877,"about_ca_system_score_gemma":0.0004910752,"threshold_uncertainty_score":0.011348903},"labels":[],"label_agreement":null},{"id":"W3106311311","doi":"10.1371/journal.pone.0242696","title":"Free water: A marker of age-related modifications of the cingulum white matter and its association with cognitive decline","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Caisse nationale de solidarité pour l'autonomie; Fondation Plan Alzheimer; Mitacs; Fondation de France; Fondation pour la Recherche Médicale; Fondation Vaincre Alzheimer; Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Sanofi","keywords":"Cingulum (brain); White matter; Splenium; Inferior longitudinal fasciculus; Hyperintensity; Diffusion MRI; Cognitive decline; Psychology; Verbal fluency test; Neuroscience; Cognition; Audiology; Tractography; Neuropsychology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Internal medicine; Dementia; Radiology","score_opus":0.05795097177639184,"score_gpt":0.27184873032045265,"score_spread":0.21389775854406082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106311311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99292964,0.0033356587,0.00280317,0.000020603478,0.000014656579,0.000028372013,0.00038021008,0.000060809718,0.00042698462],"genre_scores_gemma":[0.9943515,0.00077491946,0.003714268,0.000022898208,0.000015546975,0.00004157084,0.00041222773,0.000024482884,0.0006425368],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998274,0.00002317066,0.000023905035,0.000051023144,0.00004684572,0.000027620346],"domain_scores_gemma":[0.999526,0.00007811458,0.00023372385,0.000040090246,0.00008381407,0.000038278395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050591474,0.0006611449,0.0005144459,0.0012680612,0.0003590478,0.0004701261,0.00027871755,0.00043726832,0.00079379947],"category_scores_gemma":[0.0012677273,0.00018124346,0.0003497002,0.00075415656,0.0002742023,0.00049196236,0.00037154407,0.0002100823,0.00012605895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0071218535,0.0003523553,0.62046933,0.0011653658,0.0016468597,0.0013645508,0.0016956459,0.00208139,0.18893455,0.00051181123,0.0011563173,0.17349994],"study_design_scores_gemma":[0.000018627125,0.00069751,0.98104024,0.00003914675,0.0002521975,0.00078057474,0.00017604291,0.0021100102,0.013238315,0.00042922335,0.0011885316,0.000029625055],"about_ca_topic_score_codex":0.003400865,"about_ca_topic_score_gemma":0.00584527,"teacher_disagreement_score":0.003400865,"about_ca_system_score_codex":0.00017053992,"about_ca_system_score_gemma":0.00016865243,"threshold_uncertainty_score":0.006762147},"labels":[],"label_agreement":null},{"id":"W3106722478","doi":"10.21203/rs.3.rs-108135/v1","title":"Hippocampal Volume Influences The Correlations Between White Matter Disruption and Tau Protein in aMCI and mild AD","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Hippocampal formation; White matter; Neuroscience; Psychology; Brain size; Medicine; Magnetic resonance imaging","score_opus":0.1586051461463248,"score_gpt":0.45053634798170455,"score_spread":0.2919312018353798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106722478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99886537,0.0001757623,0.00012407107,0.000064007094,0.0000129720975,0.0000022761888,0.00014567871,0.000012095073,0.00059785513],"genre_scores_gemma":[0.99910575,0.00006939298,0.00011060482,0.000016189044,0.000026031976,0.0000021185601,0.00014497401,0.000009318759,0.00051548815],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997249,0.00007613175,0.000025811065,0.000082327235,0.00004962674,0.00004119517],"domain_scores_gemma":[0.9981304,0.0005175069,0.00074015924,0.00020237431,0.00012613252,0.00028336523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005687575,0.00047796228,0.00032359688,0.0009476858,0.00023306049,0.0008745139,0.00035362886,0.0005402592,0.0030804323],"category_scores_gemma":[0.0039111865,0.0003473776,0.00038585148,0.00055385847,0.00055636244,0.00044946704,0.0004883152,0.00059041486,0.00044204632],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030134395,0.00021592953,0.97211415,0.00003436641,0.000390955,0.00058029813,0.00033088124,0.00035151973,0.012632838,0.00027825742,0.00044323594,0.009614201],"study_design_scores_gemma":[0.000007079526,0.000087418775,0.99856913,0.0000030358083,0.00005787133,0.0002317875,0.0000793689,0.00022597895,0.00037876202,0.000291322,0.00006433769,0.000003959104],"about_ca_topic_score_codex":0.0031892206,"about_ca_topic_score_gemma":0.0031129448,"teacher_disagreement_score":0.0031892206,"about_ca_system_score_codex":0.00018208912,"about_ca_system_score_gemma":0.00024278685,"threshold_uncertainty_score":0.010305047},"labels":[],"label_agreement":null},{"id":"W3107476337","doi":"10.1093/schbul/sbaa169","title":"Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; McGill University","keywords":"Schizophrenia spectrum; Schizophrenia (object-oriented programming); Psychology; Clinical psychology; Orbitofrontal cortex; Psychiatry; Neuroscience; Medicine; Psychosis; Cognition; Prefrontal cortex","score_opus":0.02775570877029532,"score_gpt":0.28608482051685186,"score_spread":0.25832911174655654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107476337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996295,0.000057657304,0.000061013758,0.000010066468,6.1682175e-7,0.0000021833869,0.00013782733,0.0000025583406,0.00009858166],"genre_scores_gemma":[0.9994795,0.00005046729,0.00015149149,0.000009519809,9.900646e-7,0.0000032695023,0.0002372042,0.0000021397511,0.0000654994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990916,0.000012038709,0.000009905067,0.000029842473,0.000017121163,0.000021873693],"domain_scores_gemma":[0.999708,0.000021446136,0.00017474797,0.000027477261,0.00001908112,0.000049309725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020405599,0.00030144895,0.00022354122,0.0008980848,0.00033370894,0.00039773106,0.00015346623,0.00026211858,0.00093642913],"category_scores_gemma":[0.00042102026,0.0001903017,0.0002742258,0.00037810695,0.00032489703,0.0001481211,0.00055015,0.00026298923,0.00008495497],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021827614,0.00006588333,0.8731605,0.00006654942,0.00032730697,0.0010390135,0.00074092246,0.0004413567,0.11194925,0.00018709064,0.00020589003,0.009633527],"study_design_scores_gemma":[0.0000068098034,0.000035252884,0.99874,0.0000037607344,0.00002118204,0.00041111754,0.000079750505,0.00010394684,0.0005016625,0.00004995078,0.00004383938,0.0000026388],"about_ca_topic_score_codex":0.007774671,"about_ca_topic_score_gemma":0.0152699165,"teacher_disagreement_score":0.007774671,"about_ca_system_score_codex":0.0003365733,"about_ca_system_score_gemma":0.00021421532,"threshold_uncertainty_score":0.015458882},"labels":[],"label_agreement":null},{"id":"W3107809671","doi":"10.1101/2020.11.27.401950","title":"Predicting Brain Regions Related to Alzheimer’s Disease Based on Global Feature","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences; Institute of Biophysics, Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Betweenness centrality; Centrality; Diffusion MRI; Correlation; Feature (linguistics); Computer science; Pattern recognition (psychology); Graph; Artificial intelligence; Medicine; Mathematics; Theoretical computer science; Magnetic resonance imaging; Statistics","score_opus":0.04347364630648888,"score_gpt":0.3096060437629206,"score_spread":0.26613239745643175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107809671","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95884883,0.0018359224,0.03371276,0.00024134113,0.00007660634,0.00007727922,0.0024612406,0.000318178,0.002427806],"genre_scores_gemma":[0.99227023,0.0003194237,0.0054643285,0.000026936103,0.0000582365,0.00002758813,0.0013785177,0.000011587703,0.0004432607],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997569,0.000031928128,0.000027239475,0.00008485399,0.000060429327,0.0000386158],"domain_scores_gemma":[0.99905604,0.00023604288,0.00022614091,0.000067657995,0.000297752,0.00011631359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005690845,0.00078507204,0.000539689,0.0039537055,0.00025896213,0.0006650206,0.00028945325,0.00054976967,0.0015116567],"category_scores_gemma":[0.0021387078,0.000106684725,0.0006600177,0.0015185232,0.0002577266,0.00073687994,0.00047748137,0.00035073055,0.0004045102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000728594,0.00024823193,0.8028995,0.00033903762,0.00076625176,0.0008947765,0.00017457172,0.021099882,0.014857659,0.001161395,0.006783721,0.1500464],"study_design_scores_gemma":[0.000055346776,0.0006216658,0.73927474,0.00011857006,0.000836309,0.002069778,0.0005065287,0.23858616,0.008649221,0.0062338063,0.0029463787,0.00010141631],"about_ca_topic_score_codex":0.0032172794,"about_ca_topic_score_gemma":0.0045037917,"teacher_disagreement_score":0.0039537055,"about_ca_system_score_codex":0.00022261814,"about_ca_system_score_gemma":0.00033065895,"threshold_uncertainty_score":0.006397128},"labels":[],"label_agreement":null},{"id":"W3108047961","doi":"10.3389/fnagi.2020.594002","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Royal Golden Jubilee (RGJ) Ph.D. Programme; Thailand Research Fund; Chiang Mai University","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Psychology; Cognition; Neuroscience; Executive functions; Cognitive impairment; Dementia; Hippocampus; Audiology; Medicine; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.04357388248549012,"score_gpt":0.3245562028634962,"score_spread":0.2809823203780061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108047961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997998,0.00003478142,0.00003171742,0.0000043552204,9.264464e-7,0.000004778519,0.00003149671,6.2573673e-7,0.00009147575],"genre_scores_gemma":[0.99961615,0.000045602334,0.000068840396,0.0000070860365,0.0000043117625,0.0000067582814,0.00010942257,0.0000010557847,0.00014076773],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987733,0.000019069072,0.000020556148,0.000036860325,0.00001729102,0.000028934046],"domain_scores_gemma":[0.99944454,0.000068978,0.0002359062,0.000040248517,0.000072802635,0.00013754448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002813436,0.00046753034,0.0003103524,0.00081047264,0.00048345467,0.0005549603,0.00019512266,0.00037811973,0.0010721526],"category_scores_gemma":[0.00095606345,0.00029366248,0.0003151198,0.0006882679,0.00051408313,0.00047963613,0.0004465573,0.0002386475,0.00018852673],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009417373,0.0002323145,0.9877389,0.0000532057,0.00008824335,0.0010333934,0.0025118156,0.000042029926,0.004195612,0.000024664683,0.000055522534,0.0030824712],"study_design_scores_gemma":[0.000011810154,0.00030038174,0.9979119,0.0000033343917,0.0000268118,0.000772879,0.00070352206,0.00007048935,0.00011567238,0.000023021812,0.000055618264,0.000004455408],"about_ca_topic_score_codex":0.007584703,"about_ca_topic_score_gemma":0.006930308,"teacher_disagreement_score":0.007584703,"about_ca_system_score_codex":0.00022990025,"about_ca_system_score_gemma":0.00022814638,"threshold_uncertainty_score":0.015081108},"labels":[],"label_agreement":null},{"id":"W3108455943","doi":"10.1101/2020.11.23.20237099","title":"Rapid Microscopic Fractional Anisotropy Imaging via an Optimized Kurtosis Formulation","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Fractional anisotropy; Anisotropy; Diffusion MRI; Kurtosis; Isotropy; Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Orientation (vector space); Thermal diffusivity; Metric (unit); SIGNAL (programming language); Algorithm; Mathematics; Biological system; Computer science; Statistics; Optics; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.08020277305073353,"score_gpt":0.36899173637777877,"score_spread":0.28878896332704523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108455943","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023229288,0.00012196677,0.97473913,0.00011820082,0.00001875286,0.000056371722,0.00011248917,0.0005497056,0.0010540712],"genre_scores_gemma":[0.16638085,0.00026523875,0.82987344,0.000066792425,0.00003481442,0.00018191627,0.00023344885,0.0004495493,0.0025139726],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970895,0.000089826026,0.000018884395,0.00004313222,0.00011465292,0.000024582867],"domain_scores_gemma":[0.99931777,0.00027524837,0.00010288685,0.00008890658,0.00018812693,0.00002704576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084352284,0.001350248,0.00039662133,0.00065255555,0.00020755293,0.0007242717,0.0006567145,0.00060003,0.0018392316],"category_scores_gemma":[0.0025779083,0.00037839756,0.00061209267,0.0005350622,0.00044467126,0.0013802949,0.00097233546,0.0007742458,0.00073108135],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042780334,0.00018407473,0.0017594299,0.00036187863,0.00022640821,0.00045299158,0.00027687728,0.32329985,0.398672,0.049214408,0.0039846785,0.22113952],"study_design_scores_gemma":[0.00002480439,0.00011340948,0.0004576207,0.000013899825,0.000024318415,0.00022817527,0.000012297111,0.9418859,0.04972608,0.004953123,0.0025139742,0.000046344503],"about_ca_topic_score_codex":0.0013899853,"about_ca_topic_score_gemma":0.0019656566,"teacher_disagreement_score":0.0018392316,"about_ca_system_score_codex":0.0005691962,"about_ca_system_score_gemma":0.00086007174,"threshold_uncertainty_score":0.0061528087},"labels":[],"label_agreement":null},{"id":"W3108924128","doi":"10.1038/s41598-020-77675-x","title":"Diffusion tensor imaging and arterial tissue: establishing the influence of arterial tissue microstructure on fractional anisotropy, mean diffusivity and tractography","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"European Research Council; European Commission","keywords":"Fractional anisotropy; Elastin; Diffusion MRI; Tractography; Biomedical engineering; Anisotropy; Chemistry; Materials science; Thermal diffusivity; Ex vivo; Nuclear magnetic resonance; Pathology; Medicine; Magnetic resonance imaging; Radiology; Biochemistry; Physics; In vitro; Optics","score_opus":0.018435339693126662,"score_gpt":0.29386585819326205,"score_spread":0.2754305185001354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108924128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96055275,0.002957922,0.03509297,0.00009158893,0.0000149008065,0.000025546584,0.00015739177,0.00010145011,0.0010054841],"genre_scores_gemma":[0.98282295,0.0010263688,0.015524644,0.000015758116,0.0000119413935,0.000023923762,0.00009845385,0.000032769956,0.00044313428],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966323,0.00014452741,0.000020695777,0.000054324155,0.00008235529,0.00003484436],"domain_scores_gemma":[0.9986852,0.00061404274,0.00033603012,0.00010319679,0.00017169205,0.0000898631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013036284,0.00036847108,0.00038279992,0.0006980407,0.00018046764,0.0005948591,0.00016308141,0.00043093672,0.0008370525],"category_scores_gemma":[0.0033423891,0.00022141871,0.00020300632,0.00042211555,0.00057179155,0.00087360403,0.0002644584,0.00027807444,0.00014019187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044482065,0.0000301737,0.01412856,0.00017699177,0.00007203133,0.00016018967,0.000117425254,0.0012891354,0.9681255,0.00028039585,0.000059443333,0.015115286],"study_design_scores_gemma":[0.000029602472,0.0013096015,0.2846543,0.000072239694,0.0002519483,0.0025803687,0.00019922978,0.039189223,0.66843057,0.0011050407,0.0021006598,0.00007714401],"about_ca_topic_score_codex":0.001945215,"about_ca_topic_score_gemma":0.0024502035,"teacher_disagreement_score":0.001945215,"about_ca_system_score_codex":0.00027445337,"about_ca_system_score_gemma":0.00026261312,"threshold_uncertainty_score":0.00689435},"labels":[],"label_agreement":null},{"id":"W3109069154","doi":"10.1101/2020.11.24.396119","title":"Longitudinal white matter changes associated with cognitive training","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada Excellence Research Chairs, Government of Canada; Canadian Institute for Advanced Research","keywords":"Working memory; Task (project management); Cognitive psychology; Psychology; Cognition; Working memory training; Memory span; Transfer of learning; n-back; White matter; Audiology; Neuroscience; Developmental psychology; Medicine","score_opus":0.079318831608745,"score_gpt":0.29595090333812246,"score_spread":0.21663207172937746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109069154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989083,0.0002272779,0.00021647336,0.000029637355,0.0000053492254,0.000015410096,0.00009516207,0.000013751795,0.0004887359],"genre_scores_gemma":[0.99842095,0.00010233421,0.00014139574,0.000018673876,0.0000060095504,0.00002018111,0.0001854352,0.000003839215,0.0011012075],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985015,0.000020697022,0.000012477527,0.000044191722,0.00003455145,0.000037900907],"domain_scores_gemma":[0.99898773,0.00008640621,0.00044829963,0.00006424998,0.00022658719,0.00018672446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046447088,0.00027787092,0.00030584188,0.00047929384,0.00025367463,0.00032807374,0.00020160052,0.00046795298,0.0015248909],"category_scores_gemma":[0.0010013107,0.00014761448,0.00018036443,0.00028112455,0.00026065423,0.0002943032,0.00036493797,0.000569028,0.0002578483],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0059849056,0.0029988121,0.36485347,0.00027168516,0.0004750268,0.00077949825,0.00096984877,0.0013761101,0.5685943,0.00022486747,0.0005497833,0.052921735],"study_design_scores_gemma":[0.000012020666,0.002007216,0.98329645,0.000015727954,0.00006028244,0.00021291988,0.00012146442,0.00044612857,0.013351064,0.00009347177,0.0003735357,0.000009786928],"about_ca_topic_score_codex":0.0020063356,"about_ca_topic_score_gemma":0.0023080332,"teacher_disagreement_score":0.0020063356,"about_ca_system_score_codex":0.00029441153,"about_ca_system_score_gemma":0.0001949038,"threshold_uncertainty_score":0.0051012635},"labels":[],"label_agreement":null},{"id":"W3109238976","doi":"10.2478/awutp-2020-0007","title":"Diffusion Magnetic Resonance Imaging with Applications to Cardiac Muscle: Short Review","year":2020,"lang":"en","type":"article","venue":"Annals of West University of Timisoara - Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Tractography; Effective diffusion coefficient; Nuclear magnetic resonance; Medicine; Translation (biology); Biomedical engineering; Nuclear medicine; Radiology; Physics; Chemistry","score_opus":0.0801239907144819,"score_gpt":0.32308060343652434,"score_spread":0.24295661272204244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109238976","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020132304,0.9972881,0.00049438165,0.0003433437,0.00070284767,0.000006119099,0.00002522597,0.000013337076,0.0009254234],"genre_scores_gemma":[0.0011945355,0.9956102,0.00061592006,0.00037723558,0.001454393,0.000010780474,0.000062043255,0.0000068720938,0.0006680809],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997739,0.000035093588,0.00005407703,0.000060457794,0.000057535828,0.000018902956],"domain_scores_gemma":[0.99904376,0.0004967737,0.0001252417,0.000029429417,0.0002366876,0.000068103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006876542,0.0012362608,0.0013138052,0.0035204848,0.00030738153,0.0011507762,0.00079055305,0.0012371701,0.003277662],"category_scores_gemma":[0.0012683903,0.00041810478,0.000613545,0.0030350233,0.00065095146,0.0018416765,0.0007451384,0.0016214278,0.002889912],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009021555,0.00006747007,0.00043354582,0.021551358,0.000126176,0.0005131516,0.00009707345,0.00066211633,0.0033146853,0.0034644753,0.049153116,0.9205266],"study_design_scores_gemma":[0.000015028643,0.00017831856,0.0021446738,0.0053871428,0.00017961365,0.004492447,0.00008436357,0.00030475724,0.0012015612,0.00332671,0.98263365,0.00005171245],"about_ca_topic_score_codex":0.00096229964,"about_ca_topic_score_gemma":0.0011116592,"teacher_disagreement_score":0.0035204848,"about_ca_system_score_codex":0.00049550144,"about_ca_system_score_gemma":0.0008625559,"threshold_uncertainty_score":0.01096487},"labels":[],"label_agreement":null},{"id":"W3109249627","doi":"10.1101/2020.11.24.396549","title":"Processing the diffusion-weighted magnetic resonance imaging of the PING dataset","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke; McGill University Health Centre","funders":"Canada First Research Excellence Fund; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Diffusion MRI; White matter; Ping (video games); Computer science; Artificial intelligence; Magnetic resonance imaging; Neuroimaging; Visualization; Pattern recognition (psychology); Neuroscience; Medicine; Psychology; Radiology","score_opus":0.031629990539753836,"score_gpt":0.28046295915850156,"score_spread":0.2488329686187477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109249627","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19878383,0.0021184436,0.032135475,0.0015731741,0.00076902076,0.0009583196,0.7429035,0.013068194,0.0076900176],"genre_scores_gemma":[0.10366298,0.0004790317,0.03775295,0.0002284633,0.0001309603,0.00088407757,0.85242295,0.0007653302,0.0036732873],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99922955,0.0001727136,0.00007257959,0.00025898518,0.00015759427,0.00010865561],"domain_scores_gemma":[0.99909234,0.00021148764,0.000057477962,0.00036150214,0.0002182072,0.00005896493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014175295,0.0013594221,0.00073173275,0.001986925,0.00047858938,0.0012142916,0.0010274119,0.0010514185,0.005270143],"category_scores_gemma":[0.005028225,0.00026918566,0.0011421014,0.0013160594,0.00042533118,0.00044636324,0.0014774463,0.00079899485,0.005356699],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016492077,0.00060877844,0.038425013,0.0018561312,0.0011593748,0.0028599235,0.00055811374,0.021353591,0.02422067,0.0040698177,0.67185503,0.23138438],"study_design_scores_gemma":[0.0007370301,0.0006517904,0.14616238,0.0005897445,0.0005189163,0.0058546625,0.0009950149,0.0587503,0.036608055,0.01883117,0.7299767,0.0003242257],"about_ca_topic_score_codex":0.00648292,"about_ca_topic_score_gemma":0.010555653,"teacher_disagreement_score":0.00648292,"about_ca_system_score_codex":0.00046183844,"about_ca_system_score_gemma":0.0011893581,"threshold_uncertainty_score":0.017630398},"labels":[],"label_agreement":null},{"id":"W3110641764","doi":"10.1101/2020.12.03.408567","title":"MASiVar: Multisite, Multiscanner, and Multisubject Acquisitions for Studying Variability in Diffusion Weighted Magnetic Resonance Imaging","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Diffusion MRI; Connectomics; Fractional anisotropy; Connectome; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Orientation (vector space); Nuclear magnetic resonance; Computer science; Mathematics; Psychology; Medicine; Neuroscience; Physics; Radiology; Functional connectivity","score_opus":0.03137716795229804,"score_gpt":0.2888891434856524,"score_spread":0.25751197553335436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110641764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66240543,0.0007339661,0.2911135,0.00026416784,0.00012684864,0.00059147517,0.032714628,0.010940179,0.0011098868],"genre_scores_gemma":[0.6430848,0.00025490392,0.29360223,0.00013187692,0.00012227088,0.0021753376,0.057400145,0.0018024074,0.0014260656],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990658,0.00025797653,0.00008742722,0.00037025602,0.00016087353,0.00005766228],"domain_scores_gemma":[0.9969503,0.0009309269,0.0007552397,0.00089092663,0.00032194346,0.00015064456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027949973,0.0010865637,0.0007888821,0.001971358,0.0005193774,0.0007994674,0.0010283049,0.0007308529,0.0016755181],"category_scores_gemma":[0.0057428274,0.0003844568,0.0008845225,0.0011382521,0.0004941313,0.0007145229,0.0013719288,0.0008026727,0.0004933371],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004913899,0.0014288423,0.17054407,0.0012802612,0.003944758,0.0011860752,0.0010284864,0.08813615,0.33072457,0.005299564,0.06533351,0.3261798],"study_design_scores_gemma":[0.00064129784,0.0017896338,0.43061432,0.00012850444,0.000697541,0.002970341,0.0003508912,0.43940014,0.08626611,0.01033644,0.026314056,0.0004907379],"about_ca_topic_score_codex":0.002611645,"about_ca_topic_score_gemma":0.00813882,"teacher_disagreement_score":0.0027949973,"about_ca_system_score_codex":0.00029140478,"about_ca_system_score_gemma":0.0008621291,"threshold_uncertainty_score":0.014781535},"labels":[],"label_agreement":null},{"id":"W3110682263","doi":"10.1002/alz.038868","title":"White matter texture abnormalities are associated with delusional severity in a cognitively mixed sample of older adults","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"","keywords":"White matter; Correlation; Psychology; Fluid-attenuated inversion recovery; Audiology; Medicine; Magnetic resonance imaging; Radiology; Mathematics","score_opus":0.03937792891805645,"score_gpt":0.2859561669282072,"score_spread":0.24657823801015075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110682263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999627,0.000047244655,0.00004739421,0.000010214362,0.0000012487781,0.0000050643425,0.00014965331,0.0000026858634,0.000109474706],"genre_scores_gemma":[0.999603,0.000024970937,0.00007330818,0.000008468996,0.0000042932866,0.000005092126,0.00020660603,0.0000013542422,0.00007290444],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998634,0.000016657617,0.000022968294,0.000036639296,0.000041454186,0.000018868426],"domain_scores_gemma":[0.9994419,0.000059490787,0.000284308,0.000046480127,0.00007230027,0.000095539624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023687317,0.0003395809,0.00029063347,0.0013067822,0.00033989412,0.0005086959,0.00017981167,0.00034080975,0.002133914],"category_scores_gemma":[0.0012626937,0.0001707039,0.0002852173,0.0005853561,0.0002459628,0.00030089507,0.00045807485,0.00028121486,0.0002695285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024936337,0.000032037995,0.9957016,0.000009615166,0.000046548063,0.00013638494,0.0001708298,0.000018681985,0.0019953854,0.00000927982,0.0000669747,0.0015632631],"study_design_scores_gemma":[0.0000020767636,0.000036612582,0.99948883,0.0000018336833,0.000008653256,0.00023898139,0.000098857745,0.00004877682,0.00004731563,0.0000101769765,0.000016806289,0.000001105815],"about_ca_topic_score_codex":0.0019967451,"about_ca_topic_score_gemma":0.003195659,"teacher_disagreement_score":0.002133914,"about_ca_system_score_codex":0.00011462451,"about_ca_system_score_gemma":0.00007166372,"threshold_uncertainty_score":0.00713861},"labels":[],"label_agreement":null},{"id":"W3110789430","doi":"10.1162/netn_a_00179","title":"The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure","year":2021,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fondation EDF; Fondation Institut de Cardiologie de Montréal; Agence Nationale de la Recherche; Réseau en Bio-Imagerie du Quebec; Wellcome Trust; Canadian Open Neuroscience Platform; Wellcome","keywords":"Connectome; Tractography; White matter; Diffusion MRI; Connectomics; Myelin; Neuroscience; Human Connectome Project; Computer science; Measure (data warehouse); Biology; Magnetic resonance imaging; Functional connectivity; Data mining; Central nervous system; Medicine","score_opus":0.05441997733237597,"score_gpt":0.3290948789170651,"score_spread":0.27467490158468916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110789430","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41363713,0.0016435223,0.57840794,0.00045083408,0.00005874436,0.00009428647,0.0014888851,0.00062673376,0.003591988],"genre_scores_gemma":[0.90683633,0.00078616577,0.08983807,0.00006401844,0.00011617707,0.0001222041,0.0009319457,0.000167453,0.0011375261],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922407,0.0003391419,0.00004856156,0.0001921204,0.00013656585,0.000059571656],"domain_scores_gemma":[0.9949008,0.0024615668,0.0013607261,0.00069999264,0.00036444483,0.00021245242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025572244,0.0011393158,0.000695301,0.0056832037,0.0004137594,0.0012371653,0.0006478294,0.00083266996,0.0021862618],"category_scores_gemma":[0.010312217,0.0002704,0.00070091453,0.0027150733,0.0011930031,0.002825415,0.0012780208,0.000762643,0.0003981863],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017290278,0.00025302256,0.07947656,0.0019019761,0.0018767455,0.0015221977,0.0015705997,0.32851955,0.13359848,0.1411955,0.004409593,0.3039467],"study_design_scores_gemma":[0.000050911058,0.0006901683,0.094439946,0.0002271746,0.00039405935,0.0020270785,0.00038770866,0.6868083,0.017368164,0.1916117,0.0056971693,0.00029763847],"about_ca_topic_score_codex":0.0013672333,"about_ca_topic_score_gemma":0.0012391584,"teacher_disagreement_score":0.0056832037,"about_ca_system_score_codex":0.00039814532,"about_ca_system_score_gemma":0.00039349456,"threshold_uncertainty_score":0.013523996},"labels":[],"label_agreement":null},{"id":"W3111014536","doi":"10.1002/alz.040586","title":"Accounting for systematic spatiotemporal variation improves connectome‐based models of tau spreading in human Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Connectome; Entorhinal cortex; Context (archaeology); Human Connectome Project; Neuroscience; Tractography; Inference; Computer science; Diffusion MRI; Biology; Psychology; Artificial intelligence; Hippocampus; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.11507118169260591,"score_gpt":0.3566954503454146,"score_spread":0.2416242686528087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111014536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7487127,0.00046743714,0.24678001,0.0009949355,0.000055199125,0.00005939864,0.0005175269,0.0005840733,0.0018286754],"genre_scores_gemma":[0.9787961,0.00011145265,0.01987916,0.0000664528,0.000026987134,0.00003913446,0.00029370838,0.000062184496,0.0007248733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9995615,0.00021238915,0.000028170216,0.00012714366,0.000037081878,0.000033766202],"domain_scores_gemma":[0.9978661,0.001392991,0.00021059187,0.0002466249,0.00019078425,0.00009297292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025331937,0.00081959035,0.0007118179,0.0007793067,0.0006172989,0.0010573601,0.0009623143,0.0009911353,0.0010802612],"category_scores_gemma":[0.009127112,0.00053103163,0.0014183802,0.0005855048,0.00044673312,0.0011839906,0.000776286,0.00089810666,0.00018662376],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038906142,0.000021895583,0.0073007178,0.000012591731,0.00011042541,0.000028144637,0.000034653378,0.9864847,0.0005047083,0.0011514506,0.00020958878,0.0041022887],"study_design_scores_gemma":[0.0000054206093,0.000010665677,0.0009877143,0.0000031940506,0.000012380782,0.000007940228,0.000006964675,0.9967675,0.000098631375,0.002021867,0.00007375702,0.000003960556],"about_ca_topic_score_codex":0.0355959,"about_ca_topic_score_gemma":0.02415344,"teacher_disagreement_score":0.0355959,"about_ca_system_score_codex":0.0011730694,"about_ca_system_score_gemma":0.0013904512,"threshold_uncertainty_score":0.070777416},"labels":[],"label_agreement":null},{"id":"W3111428740","doi":"10.18060/24617","title":"Distinctive Patterns of Tau Accumulation and White-Matter Degeneration on Domain-Specific Neuropsychiatric Test Scores","year":2020,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Degeneration (medical); Domain (mathematical analysis); Neuroscience; Test (biology); Psychology; Pathology; Medicine; Biology; Magnetic resonance imaging; Mathematics; Paleontology; Radiology; Mathematical analysis","score_opus":0.05973680750076982,"score_gpt":0.31552738750129644,"score_spread":0.2557905800005266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111428740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994454,0.000037277718,0.00006238242,0.0000038666753,8.3437743e-7,0.000008070626,0.0001285909,0.0000023741293,0.00031121212],"genre_scores_gemma":[0.9996618,0.000015371488,0.00006470269,0.0000034851207,0.0000015797308,0.0000048937336,0.00017465626,9.579979e-7,0.00007259569],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997937,0.000031449697,0.000031530424,0.00006171962,0.000044752906,0.000036883863],"domain_scores_gemma":[0.99880373,0.0002530903,0.0005442883,0.00007998243,0.00015651676,0.00016236055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039140973,0.00044396415,0.00027121796,0.0010560559,0.00018895576,0.00032116668,0.00020799987,0.00028118512,0.002035553],"category_scores_gemma":[0.0018898625,0.000116097,0.00020318039,0.00046817094,0.00029203863,0.00026655258,0.00044747983,0.00018827055,0.000310353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016609042,0.000023327548,0.9967428,0.000005832221,0.000044839515,0.00011804224,0.000068816145,0.000060937957,0.0013675966,0.00001053394,0.000032153144,0.0013590059],"study_design_scores_gemma":[0.0000026024782,0.000060551545,0.99932563,0.0000014437034,0.0000078436415,0.00029424374,0.000045370994,0.00008263409,0.00014612859,0.00001493555,0.000017482373,0.0000011970378],"about_ca_topic_score_codex":0.0011772582,"about_ca_topic_score_gemma":0.0025524502,"teacher_disagreement_score":0.002035553,"about_ca_system_score_codex":0.000175631,"about_ca_system_score_gemma":0.00014252152,"threshold_uncertainty_score":0.0068095922},"labels":[],"label_agreement":null},{"id":"W3111440933","doi":"10.1002/alz.045489","title":"Fractional anisotropy in white matter hyperintensities is linked to associative memory performance","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of Ottawa; Baycrest Hospital; Thunder Bay Regional Health Sciences Centre; Health Sciences Centre; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Sunnybrook Health Science Centre; Western University","funders":"","keywords":"Fractional anisotropy; Hyperintensity; Diffusion MRI; White matter; Neuroimaging; Cognition; Dementia; Stroke (engine); Medicine; Psychology; Neuroscience; Cardiology; Pathology; Magnetic resonance imaging; Radiology; Disease","score_opus":0.06798351974009484,"score_gpt":0.3225189420411973,"score_spread":0.2545354223011025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111440933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988696,0.0002683619,0.0000711424,0.00002657771,0.000003825127,0.0000033170897,0.00015035587,0.0000065097393,0.00060034444],"genre_scores_gemma":[0.9995859,0.00006908145,0.00008397712,0.000006950686,0.00000677892,0.0000021528217,0.00010579904,0.0000014914065,0.00013769335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998975,0.000016861091,0.000015824324,0.00003194782,0.000019151179,0.000018649132],"domain_scores_gemma":[0.9987172,0.00026876834,0.0007016479,0.00008666253,0.000106562984,0.000119291624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034805003,0.00033674535,0.00025368744,0.00096263934,0.0003272032,0.00055738847,0.00022309324,0.00040253415,0.0023013677],"category_scores_gemma":[0.0018792474,0.00013223854,0.00018928105,0.0006544755,0.0003148564,0.00025283312,0.00023351738,0.00032536138,0.00027159575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035254675,0.00009305933,0.99061173,0.000029307314,0.00015101004,0.000139163,0.00014598297,0.00016844297,0.0023947817,0.000056326873,0.0001629687,0.005694808],"study_design_scores_gemma":[0.0000028154695,0.000031340925,0.9993067,0.0000030495135,0.000016358923,0.00017049217,0.000030535255,0.00014279036,0.00017542121,0.00007331232,0.000045279277,0.000001924871],"about_ca_topic_score_codex":0.0059881024,"about_ca_topic_score_gemma":0.0060406583,"teacher_disagreement_score":0.0059881024,"about_ca_system_score_codex":0.00023709258,"about_ca_system_score_gemma":0.00017444602,"threshold_uncertainty_score":0.011906445},"labels":[],"label_agreement":null},{"id":"W3111443408","doi":"10.21203/rs.3.rs-115308/v2","title":"Plasma neurofilament light is associated with white matter damage in Alzheimer's disease","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Biomarker; Neurodegeneration; Diffusion MRI; Atrophy; Pathology; Internal medicine; Cognitive decline; Psychology; Medicine; Neuroscience; Disease; Magnetic resonance imaging; Dementia; Chemistry","score_opus":0.146440074814421,"score_gpt":0.42906368619181134,"score_spread":0.28262361137739034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111443408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99878854,0.0004164588,0.00023857743,0.000034501205,0.0000064809587,0.0000032294795,0.00016168779,0.000010753922,0.00033984106],"genre_scores_gemma":[0.9991605,0.00008992122,0.00023007188,0.00000976559,0.000009878771,0.000003181572,0.00013468349,0.0000039664924,0.00035801978],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998666,0.000032489712,0.000011784536,0.000045021457,0.000028894221,0.000015171841],"domain_scores_gemma":[0.9993899,0.00013686037,0.00029229728,0.000044183773,0.00006581931,0.00007105751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003978877,0.00032971456,0.0003366075,0.000700429,0.00022123384,0.00050861057,0.00014987183,0.00033684538,0.0025106776],"category_scores_gemma":[0.0014452559,0.00014770433,0.00016218571,0.0005341587,0.0002477936,0.00020899487,0.00026457213,0.00028085744,0.00030538708],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021096894,0.00014198212,0.96789247,0.00007079307,0.00022997888,0.0004679955,0.0003394362,0.00015475786,0.018473042,0.00011408822,0.00029623238,0.00970959],"study_design_scores_gemma":[0.000008409474,0.00008403882,0.99802196,0.0000045876827,0.000034663797,0.00044411825,0.000066074135,0.00025681368,0.00072732376,0.00020288858,0.00014617208,0.0000029638109],"about_ca_topic_score_codex":0.00133944,"about_ca_topic_score_gemma":0.000707315,"teacher_disagreement_score":0.0025106776,"about_ca_system_score_codex":0.00012761235,"about_ca_system_score_gemma":0.00011942832,"threshold_uncertainty_score":0.00839901},"labels":[],"label_agreement":null},{"id":"W3111518281","doi":"10.1002/alz.039184","title":"Accumulating and heterogeneous network‐knockout profiles in amnestic mild cognitive impairment and Alzheimer’s disease dementia","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Heart and Stroke Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Baycrest Hospital; Ontario Brain Institute","funders":"","keywords":"Diffusion MRI; Dementia; Neuroimaging; Neuroscience; White matter; Psychology; Alzheimer's disease; Disease; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.10004396811114852,"score_gpt":0.35210788709395857,"score_spread":0.25206391898281005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111518281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99949133,0.00005319061,0.00020154896,0.000013284306,9.213356e-7,0.0000035284468,0.000108541135,0.0000046136024,0.00012300753],"genre_scores_gemma":[0.9994906,0.000027200269,0.0002086845,0.000006202459,0.0000022368006,0.000005454475,0.00019925619,0.0000024134108,0.000057851255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996319,0.000090507325,0.000048640904,0.000105870924,0.00007172903,0.00005136901],"domain_scores_gemma":[0.9974654,0.00041653504,0.0012751132,0.0003256339,0.00026994353,0.00024733428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009824838,0.00042684865,0.00041675064,0.0019861874,0.00054211984,0.00062134664,0.00038729995,0.0003211924,0.0010027881],"category_scores_gemma":[0.004532348,0.00027199194,0.00024257766,0.00077800406,0.0004979278,0.00058730895,0.00093342137,0.0004073387,0.00012267412],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009547378,0.000111411704,0.9848192,0.000024756278,0.00017439004,0.00034868243,0.00047419884,0.0003728719,0.007838762,0.00014329058,0.000116257586,0.004621486],"study_design_scores_gemma":[0.000005135581,0.000056019155,0.9984668,0.0000031993097,0.00003344862,0.0003181347,0.00009956653,0.0004517321,0.00028505392,0.00023194484,0.000044753266,0.00000411521],"about_ca_topic_score_codex":0.007009299,"about_ca_topic_score_gemma":0.007237932,"teacher_disagreement_score":0.007009299,"about_ca_system_score_codex":0.00040441015,"about_ca_system_score_gemma":0.00028489306,"threshold_uncertainty_score":0.013936996},"labels":[],"label_agreement":null},{"id":"W3111638781","doi":"10.1002/alz.046324","title":"White matter disintegration along tracts measured by diffusion tensor imaging in people with MCI","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Multivariate analysis of variance; Psychology; Neuroimaging; Medicine; Nuclear medicine; Magnetic resonance imaging; Neuroscience; Radiology; Mathematics","score_opus":0.03570444177021237,"score_gpt":0.2891566206616676,"score_spread":0.2534521788914552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111638781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993549,0.00020831081,0.00004393822,0.000023999955,0.0000026592588,0.0000053065783,0.00009405104,0.0000038495705,0.0002630803],"genre_scores_gemma":[0.9995758,0.00008458157,0.000095429394,0.000008440522,0.000005304619,0.000004463517,0.0001090935,9.862705e-7,0.00011593743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998534,0.000017366263,0.00002426987,0.000043851476,0.000036244204,0.00002489299],"domain_scores_gemma":[0.99957556,0.000036295904,0.0002251068,0.000025996893,0.00006902397,0.00006807534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042651675,0.00042719385,0.0004419382,0.0016128616,0.00048036227,0.0005863651,0.00018020163,0.00043321255,0.0010521635],"category_scores_gemma":[0.0012409018,0.00020973205,0.0002636231,0.00094051624,0.00038225108,0.0005969828,0.00038989141,0.00027390182,0.00017853515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054964074,0.00007442191,0.98696125,0.000044038716,0.00015205251,0.0006523974,0.0009670144,0.00015972303,0.0038232266,0.00005957642,0.00017816912,0.006378565],"study_design_scores_gemma":[0.0000047643666,0.00007788712,0.99898106,0.000005364308,0.000021898202,0.00038019402,0.000177185,0.00011848718,0.000116245305,0.000058447466,0.00005506667,0.0000033991319],"about_ca_topic_score_codex":0.010709362,"about_ca_topic_score_gemma":0.011830266,"teacher_disagreement_score":0.010709362,"about_ca_system_score_codex":0.000319537,"about_ca_system_score_gemma":0.00022344428,"threshold_uncertainty_score":0.021294057},"labels":[],"label_agreement":null},{"id":"W3111672628","doi":"10.1097/j.pain.0000000000002164","title":"Brainstem trigeminal fiber microstructural abnormalities are associated with treatment response across subtypes of trigeminal neuralgia","year":2020,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Trigeminal neuralgia; Brainstem; Medicine; Diffusion MRI; Fractional anisotropy; Neuroimaging; Lesion; Nociception; Multiple sclerosis; Population; Anesthesia; Pathology; Radiology; Internal medicine; Magnetic resonance imaging","score_opus":0.0669004528063973,"score_gpt":0.33416476945746376,"score_spread":0.2672643166510665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111672628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995433,0.00011599315,0.00007992387,0.000011945926,0.0000012378462,0.000007339016,0.000050116785,0.0000018647567,0.00018843445],"genre_scores_gemma":[0.99982053,0.000021053507,0.000050719816,0.0000043538985,0.0000021159838,0.0000044823837,0.00005422482,6.7278376e-7,0.000042006483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974734,0.000058219048,0.000043559743,0.000064527725,0.000053765307,0.00003269058],"domain_scores_gemma":[0.99925345,0.00012475284,0.00040921583,0.000061558094,0.000075441916,0.00007559898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038009917,0.00024438842,0.00033040336,0.0005998159,0.00027182707,0.0002573939,0.00019468018,0.00026824797,0.0011978751],"category_scores_gemma":[0.0015337346,0.00009071179,0.00020855753,0.00039398344,0.00025589563,0.0003016315,0.00026018993,0.0002397481,0.00012342494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006321206,0.00006084946,0.98327476,0.000030335737,0.00011595533,0.00019555383,0.00018798016,0.00012315724,0.008662361,0.000022841887,0.00005988517,0.0066341385],"study_design_scores_gemma":[0.000004884448,0.00008699639,0.9989838,0.000002618604,0.0000132399555,0.0003270843,0.00007751882,0.00015859917,0.00029577603,0.00001677788,0.000030950847,0.0000017033749],"about_ca_topic_score_codex":0.0017535366,"about_ca_topic_score_gemma":0.0022569925,"teacher_disagreement_score":0.0017535366,"about_ca_system_score_codex":0.00028015889,"about_ca_system_score_gemma":0.00010413515,"threshold_uncertainty_score":0.00400728},"labels":[],"label_agreement":null},{"id":"W3111682232","doi":"10.1002/alz.046670","title":"Tau deposition assessed by [<sup>18</sup>F]MK6240 PET is associated with longitudinal decrease in grey matter density across the spectrum of Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Voxel; Grey matter; Voxel-based morphometry; Nuclear medicine; Atrophy; Standardized uptake value; Alzheimer's Disease Neuroimaging Initiative; Temporal lobe; Medicine; Positron emission tomography; Psychology; Internal medicine; Alzheimer's disease; Pathology; White matter; Magnetic resonance imaging; Neuroscience; Radiology; Disease","score_opus":0.05190336960134045,"score_gpt":0.3251726335937415,"score_spread":0.27326926399240103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111682232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993474,0.00016958502,0.0001117553,0.000016325397,0.0000021059975,0.0000018390677,0.000107005304,0.000011624685,0.00023231618],"genre_scores_gemma":[0.9993617,0.000073401156,0.0001273658,0.000010379766,0.0000030974234,0.000002977658,0.00015663452,0.0000047330523,0.00025975087],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999262,0.000012197622,0.000007796359,0.000026161733,0.000012001944,0.000015595804],"domain_scores_gemma":[0.9994808,0.00007067561,0.00026469093,0.00005110795,0.00006959887,0.000063136504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036485726,0.0002637659,0.00027203967,0.0004396983,0.0002419427,0.00046575526,0.00020115831,0.00041712268,0.0017780244],"category_scores_gemma":[0.0006563272,0.00028092437,0.00016772741,0.00025507231,0.0002445024,0.0003289284,0.00016053402,0.00032932282,0.0003727912],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004997495,0.0001820025,0.903686,0.00005254439,0.00016423075,0.0008547782,0.00032489825,0.00030261354,0.07841231,0.000061421946,0.00035659788,0.010605154],"study_design_scores_gemma":[0.000011110548,0.00028560904,0.995415,0.0000047916337,0.000034147946,0.00089324743,0.000063467494,0.0003179606,0.0027989943,0.000053272175,0.00011849454,0.0000039048996],"about_ca_topic_score_codex":0.003339347,"about_ca_topic_score_gemma":0.002412338,"teacher_disagreement_score":0.003339347,"about_ca_system_score_codex":0.00018457291,"about_ca_system_score_gemma":0.00010264587,"threshold_uncertainty_score":0.006639838},"labels":[],"label_agreement":null},{"id":"W3111845248","doi":"10.1016/j.neuroimage.2020.117619","title":"A simple estimate of axon size with diffusion MRI","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Canada Excellence Research Chairs, Government of Canada","keywords":"Axon; White matter; Diffusion MRI; Diffusion; Spherical mean; Myelin; Nuclear magnetic resonance; Neuroscience; Physics; Mathematics; Magnetic resonance imaging; Biology; Central nervous system; Mathematical analysis; Medicine","score_opus":0.050465161706964676,"score_gpt":0.3405098164690698,"score_spread":0.2900446547621051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111845248","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13335869,0.0011728421,0.8571762,0.00021003207,0.00009104165,0.00009847799,0.00052266044,0.0010331034,0.0063369903],"genre_scores_gemma":[0.6310015,0.001272864,0.36309096,0.00008420972,0.000028061413,0.00018099962,0.0004298837,0.00016421071,0.003747337],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998313,0.000023065368,0.000011358776,0.00006261834,0.000060174454,0.000011500498],"domain_scores_gemma":[0.99964297,0.00016368962,0.000060112303,0.000047085596,0.0000705082,0.000015651067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043613726,0.00055873976,0.0004942304,0.00060556555,0.00024989853,0.00048054152,0.00058519153,0.0006644787,0.0018994169],"category_scores_gemma":[0.0020536557,0.00029618744,0.00033410304,0.00040339693,0.0004784432,0.001329679,0.0004664893,0.00044150034,0.0006388382],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025465497,0.0001006801,0.011701171,0.0010534624,0.00016729596,0.0003966629,0.00028464352,0.28688475,0.48504013,0.054332584,0.0033116913,0.15647236],"study_design_scores_gemma":[0.000026388976,0.00022749684,0.010981821,0.0000819241,0.000058614438,0.0005875217,0.000068191344,0.86542815,0.09249057,0.019703725,0.010232148,0.00011348357],"about_ca_topic_score_codex":0.0013234899,"about_ca_topic_score_gemma":0.002270472,"teacher_disagreement_score":0.0018994169,"about_ca_system_score_codex":0.0003836835,"about_ca_system_score_gemma":0.00044899667,"threshold_uncertainty_score":0.0063542128},"labels":[],"label_agreement":null},{"id":"W3111905944","doi":"10.1002/alz.047386","title":"Longitudinal assessment of neuroinflammation and axonal loss in white matter tracts in Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Inferior longitudinal fasciculus; Splenium; White matter; Cingulum (brain); Corpus callosum; Uncinate fasciculus; Psychology; Fasciculus; Neuroinflammation; Fractional anisotropy; Internal medicine; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Disease; Radiology","score_opus":0.07919082554819575,"score_gpt":0.3548226206176054,"score_spread":0.27563179506940966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111905944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99913377,0.00032330124,0.00015676644,0.000012126415,0.0000018891977,0.000006029559,0.00018934601,0.0000058026853,0.0001709718],"genre_scores_gemma":[0.9989504,0.0001297076,0.00027430383,0.0000071122063,0.0000040424698,0.000010553547,0.0004162497,0.0000020033865,0.00020564717],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998772,0.000026225425,0.000013204173,0.000039894832,0.000022519418,0.000020837584],"domain_scores_gemma":[0.9993685,0.000048393627,0.00025354198,0.00004732582,0.00016874242,0.00011359577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008159641,0.0002466111,0.00023735766,0.00093797565,0.00048515166,0.00044669927,0.00015572095,0.0003319172,0.00042573054],"category_scores_gemma":[0.0010407071,0.00014511579,0.00023635813,0.00045696777,0.00016831506,0.00037368,0.00033419862,0.00030945567,0.00013259285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005556494,0.00008222133,0.9862997,0.000026094736,0.00012207219,0.00015797107,0.00024853475,0.00016625236,0.0058430657,0.000018710152,0.00013056232,0.006349251],"study_design_scores_gemma":[0.0000031554248,0.00015084668,0.99879646,0.000004698665,0.000026749382,0.0002064856,0.000058436886,0.00016341181,0.00042990645,0.00002717026,0.00012978002,0.0000028575398],"about_ca_topic_score_codex":0.0043495726,"about_ca_topic_score_gemma":0.0057828827,"teacher_disagreement_score":0.0043495726,"about_ca_system_score_codex":0.00024704295,"about_ca_system_score_gemma":0.00020605278,"threshold_uncertainty_score":0.008648455},"labels":[],"label_agreement":null},{"id":"W3111920673","doi":"10.1002/alz.043961","title":"Pilot study of MRI white matter tissue properties in Alzheimer’s, vascular and mixed dementias","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia; Simon Fraser University; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"","keywords":"Hyperintensity; White matter; Fractional anisotropy; Diffusion MRI; Medicine; Dementia; Vascular dementia; Atrophy; Nuclear medicine; Cardiology; Internal medicine; Pathology; Magnetic resonance imaging; Radiology; Disease","score_opus":0.11386046946623982,"score_gpt":0.3237406453365572,"score_spread":0.2098801758703174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111920673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937314,0.00007780512,0.00009080201,0.0000072713515,0.000004804599,0.0000583384,0.000082547835,0.0000050417502,0.00030035578],"genre_scores_gemma":[0.9988932,0.000039712002,0.00037086118,0.000023988936,0.000010917563,0.00007779023,0.00015738218,0.0000033149292,0.0004228347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997727,0.000063746185,0.00002039208,0.00006348254,0.000045026114,0.00003459995],"domain_scores_gemma":[0.9989146,0.00027044248,0.00012415815,0.00013261221,0.00024687743,0.00031132135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001342119,0.0008845065,0.0005391632,0.0009828728,0.00074351014,0.000649441,0.0003784791,0.000633817,0.0030665188],"category_scores_gemma":[0.0022804986,0.000452243,0.00036552447,0.0003642963,0.00045520047,0.00072466384,0.0005055852,0.00047114203,0.0007643586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.023252945,0.0155826565,0.89257944,0.00027665257,0.00037683983,0.004071081,0.005200818,0.00019358363,0.022942929,0.00021890218,0.0007897696,0.034514442],"study_design_scores_gemma":[0.0008211606,0.020966692,0.9682585,0.000024713212,0.00017665687,0.0037149342,0.0018619489,0.00069124135,0.0019744514,0.0002654254,0.0012134532,0.000030816278],"about_ca_topic_score_codex":0.0022902284,"about_ca_topic_score_gemma":0.0024327186,"teacher_disagreement_score":0.0030665188,"about_ca_system_score_codex":0.0003147751,"about_ca_system_score_gemma":0.00025162593,"threshold_uncertainty_score":0.010258496},"labels":[],"label_agreement":null},{"id":"W3112025802","doi":"10.1002/alz.041245","title":"Alterations of cortical thickness and gray‐white matter contrast in Alzheimer’s disease and Lewy body‐related cognitive impairment","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Gray (unit); Psychology; Grey matter; Temporal lobe; Pathology; Neuroscience; Magnetic resonance imaging; Medicine; Epilepsy; Nuclear medicine; Radiology","score_opus":0.039967246285615064,"score_gpt":0.32078841250019363,"score_spread":0.2808211662145786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112025802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991732,0.00010901524,0.00016850524,0.0000054718394,0.0000016480208,0.00000685731,0.00016874372,0.000008745743,0.00035783194],"genre_scores_gemma":[0.99942315,0.00003158403,0.00025558544,0.0000046175137,0.0000020927746,0.000004825706,0.00014961851,0.000002719396,0.0001258329],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983525,0.000035652185,0.000027287348,0.000043034986,0.00003596983,0.000022702425],"domain_scores_gemma":[0.9991248,0.00021229434,0.00039053903,0.00007671432,0.00010632462,0.00008929554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005654322,0.00044646516,0.00029459404,0.0015705512,0.0002416771,0.0005631786,0.00022126445,0.00024074201,0.0020058977],"category_scores_gemma":[0.0018874686,0.00020173895,0.00018161228,0.0007089451,0.0003269366,0.00024957996,0.00037704923,0.0002463728,0.00017601726],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002623634,0.00014346346,0.9597427,0.000106844134,0.00036701243,0.00065455155,0.00045265604,0.00065266626,0.02156664,0.000100371835,0.0002219862,0.013367644],"study_design_scores_gemma":[0.000007996147,0.0000636087,0.9972492,0.0000049314062,0.000028203747,0.0005587321,0.000055630593,0.00036017306,0.0015412536,0.000073155796,0.000054078664,0.0000029758585],"about_ca_topic_score_codex":0.0035524617,"about_ca_topic_score_gemma":0.0037412166,"teacher_disagreement_score":0.0035524617,"about_ca_system_score_codex":0.00020800305,"about_ca_system_score_gemma":0.00015477135,"threshold_uncertainty_score":0.0070635676},"labels":[],"label_agreement":null},{"id":"W3112093090","doi":"10.1002/alz.044897","title":"Intrinsic connectivity of the human brain provides scaffold for tau aggregation in clinical variants of Alzheimer's disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill Genome Centre; Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Voxel; Tractography; Neuroscience; Population; Psychology; Clinical Dementia Rating; Diffusion MRI; Alzheimer's disease; Medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.11289535342124848,"score_gpt":0.38447076426931176,"score_spread":0.27157541084806325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112093090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99680907,0.00007199788,0.002603571,0.00003055142,0.000001372747,0.000004818848,0.00012716424,0.0000222992,0.00032916616],"genre_scores_gemma":[0.99940026,0.000022637863,0.00043229535,0.000002428064,0.00000262167,0.0000033659248,0.000078402976,0.0000049456507,0.0000529676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998128,0.00008423474,0.000011317131,0.000049547773,0.000020676973,0.000021557647],"domain_scores_gemma":[0.99935645,0.0003114626,0.00019312189,0.00007306413,0.000036661637,0.000029166695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039582772,0.00029861167,0.00028545206,0.0005502753,0.00013076505,0.00032476732,0.00017624465,0.00017349499,0.0012486718],"category_scores_gemma":[0.002331779,0.0001548958,0.00019836759,0.00032139977,0.0003061777,0.00027685412,0.00021195569,0.00017194412,0.0001043427],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020905102,0.0001331332,0.81773496,0.00014939575,0.00086227007,0.001889688,0.000987624,0.020220341,0.09691085,0.002640637,0.0007542481,0.055626415],"study_design_scores_gemma":[0.000013132416,0.00013402871,0.9732849,0.0000061229853,0.0000682805,0.00094546407,0.00008447114,0.021087607,0.0019995898,0.0021273603,0.00023991542,0.000009121108],"about_ca_topic_score_codex":0.0033152197,"about_ca_topic_score_gemma":0.0053866417,"teacher_disagreement_score":0.0033152197,"about_ca_system_score_codex":0.000182817,"about_ca_system_score_gemma":0.0001586043,"threshold_uncertainty_score":0.0065918565},"labels":[],"label_agreement":null},{"id":"W3112400091","doi":"10.1002/mrm.28620","title":"Apparent propagator anisotropy from single‐shell diffusion MRI acquisitions","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; Ministerio de Ciencia e Innovación; Wellcome Trust","keywords":"Fractional anisotropy; Propagator; Anisotropy; Diffusion MRI; Metric (unit); White matter; Diffusion; Computer science; Computation; Physics; Nuclear magnetic resonance; Algorithm; Magnetic resonance imaging; Medicine; Quantum mechanics; Radiology","score_opus":0.06999343753765516,"score_gpt":0.32322286937153166,"score_spread":0.2532294318338765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112400091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12689137,0.0052676424,0.845609,0.0005888269,0.00021444776,0.00015613866,0.007449339,0.0075090937,0.0063141463],"genre_scores_gemma":[0.572206,0.006436789,0.40017986,0.0002200204,0.00037495003,0.00031530237,0.013585664,0.0022204772,0.004460941],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993766,0.00010505315,0.000063862804,0.00019635518,0.00021912629,0.000039054637],"domain_scores_gemma":[0.9966478,0.0013639834,0.0008407262,0.00045670493,0.0005753564,0.00011538491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019357152,0.0012018976,0.0010428573,0.0027578664,0.0003943156,0.0019857688,0.00070925325,0.0006791383,0.0036254385],"category_scores_gemma":[0.010267149,0.0004148024,0.0009446123,0.0023657829,0.00060172926,0.0018137798,0.00087046454,0.0008761508,0.0022870153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015122163,0.00022087322,0.022906471,0.00427467,0.0013657659,0.001368776,0.0005885337,0.06652426,0.20347938,0.023199962,0.026516784,0.64804226],"study_design_scores_gemma":[0.00013572504,0.00057630247,0.06949661,0.001076626,0.0014239817,0.009051483,0.0003159966,0.5310409,0.22450477,0.09783849,0.06400715,0.00053204474],"about_ca_topic_score_codex":0.0015664531,"about_ca_topic_score_gemma":0.002117862,"teacher_disagreement_score":0.0036254385,"about_ca_system_score_codex":0.00039596774,"about_ca_system_score_gemma":0.001331736,"threshold_uncertainty_score":0.012128353},"labels":[],"label_agreement":null},{"id":"W3112713264","doi":"10.21203/rs.3.rs-115308/v1","title":"Plasma neurofilament light and cerebrospinal fluid biomarkers are associated with white matter damage in Alzheimer's disease","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Cerebrospinal fluid; Biomarker; Diffusion MRI; Neurodegeneration; Pathology; Apolipoprotein E; Fractional anisotropy; Internal medicine; Cognitive decline; Medicine; Psychology; Disease; Neuroscience; Magnetic resonance imaging; Dementia; Chemistry","score_opus":0.10977057880377683,"score_gpt":0.39961585327443805,"score_spread":0.2898452744706612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112713264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988097,0.0005453978,0.00017442786,0.000027065957,0.0000056876347,0.0000036238723,0.000170785,0.00000792717,0.00025534088],"genre_scores_gemma":[0.9991866,0.00012219204,0.00025265088,0.00001027092,0.00000933394,0.000004474068,0.0001451256,0.0000031485515,0.00026621702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999853,0.000038361388,0.000016265212,0.000043145348,0.000033306198,0.00001603693],"domain_scores_gemma":[0.99920803,0.00019434487,0.0003682201,0.000052866937,0.00009032516,0.000086317435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048410302,0.00038853087,0.0003971512,0.0007257347,0.00023825374,0.00060744834,0.00015884056,0.0004041063,0.002073349],"category_scores_gemma":[0.0021010572,0.00018618545,0.0001563287,0.00056143943,0.00023814471,0.00028804375,0.00027366192,0.00027871729,0.0003125473],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018745022,0.00015391722,0.9758119,0.000073249874,0.00024836964,0.00033151516,0.00032337304,0.00016202788,0.012055103,0.0000734026,0.0002164937,0.008676115],"study_design_scores_gemma":[0.000010586955,0.00011779484,0.9981725,0.000005885115,0.00004070174,0.0003168158,0.0000807839,0.00022916675,0.00070020807,0.00018014129,0.00014153388,0.000003796626],"about_ca_topic_score_codex":0.0014094355,"about_ca_topic_score_gemma":0.0008817263,"teacher_disagreement_score":0.002073349,"about_ca_system_score_codex":0.00012032955,"about_ca_system_score_gemma":0.00014511857,"threshold_uncertainty_score":0.0069360137},"labels":[],"label_agreement":null},{"id":"W3112764738","doi":"10.1002/alz.040838","title":"Apathy and white matter integrity in amnestic mild cognitive impairment: A whole brain analysis with tract‐based spatial statistics","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; Mental Health Research Canada; University of Ottawa","funders":"","keywords":"Apathy; Fractional anisotropy; Diffusion MRI; White matter; Psychology; Cingulum (brain); Superior longitudinal fasciculus; Corpus callosum; Alzheimer's disease; Geriatric Depression Scale; Audiology; Medicine; Psychiatry; Internal medicine; Cognition; Magnetic resonance imaging; Disease; Neuroscience; Depressive symptoms; Radiology","score_opus":0.049397566919885484,"score_gpt":0.3266559427858993,"score_spread":0.2772583758660138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112764738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99424756,0.0002525367,0.0043978356,0.00002159133,0.000005931848,0.000027970875,0.0007331977,0.00007832613,0.0002350074],"genre_scores_gemma":[0.99658453,0.00006137805,0.0026191177,0.0000043289438,0.0000065899385,0.0000386777,0.00050242594,0.000015543774,0.00016748067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996512,0.00008623959,0.00005844742,0.00010064369,0.000066548644,0.000037033504],"domain_scores_gemma":[0.9983594,0.0005006253,0.00050738646,0.00032902288,0.00019302787,0.00011052853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012832377,0.00054000696,0.0006797723,0.0021167325,0.00031487385,0.0006658638,0.00041747594,0.00026492853,0.0019288833],"category_scores_gemma":[0.0032676077,0.00015816407,0.0011174477,0.001530501,0.000356406,0.00031205837,0.00044355573,0.00027275414,0.0001731511],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004439926,0.00019618998,0.91775185,0.00036640532,0.0039182524,0.0010830059,0.000578138,0.007410339,0.017344594,0.00071014254,0.0011038955,0.045097392],"study_design_scores_gemma":[0.000050354116,0.0005058537,0.96097267,0.000027390115,0.0005800819,0.0011976005,0.0002358654,0.033059742,0.0016718336,0.0009793737,0.0006871321,0.000032199536],"about_ca_topic_score_codex":0.0067103915,"about_ca_topic_score_gemma":0.0053389417,"teacher_disagreement_score":0.0067103915,"about_ca_system_score_codex":0.00030536758,"about_ca_system_score_gemma":0.00058345724,"threshold_uncertainty_score":0.013342619},"labels":[],"label_agreement":null},{"id":"W3112901064","doi":"10.1093/neuonc/noaa222.673","title":"QOL-09. WHOLE-BRAIN WHITE MATTER NETWORK CONNECTIVITY IS DISRUPTED BY PEDIATRIC BRAIN TUMOR TREATMENT","year":2020,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"White matter; Magnetic resonance imaging; Medicine; Psychology; Neuroscience; Nuclear medicine; Audiology; Radiology","score_opus":0.04164659635995809,"score_gpt":0.3417017554282418,"score_spread":0.3000551590682837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112901064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953713,0.00011371355,0.00039802332,0.00012262636,0.0000073934257,0.000018699937,0.0024439574,0.000053946103,0.0014703983],"genre_scores_gemma":[0.99678016,0.00008938871,0.0006604096,0.000029366909,0.000003840326,0.000040917053,0.001816803,0.000022244349,0.00055697944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983156,0.00003165693,0.000011531878,0.000044782526,0.00003728622,0.000043134463],"domain_scores_gemma":[0.9989961,0.00014725223,0.00056254567,0.000046341953,0.00009159821,0.00015616637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034093455,0.00019614074,0.00017135982,0.00036892376,0.00022413775,0.0004587231,0.00022223151,0.00016588956,0.006518879],"category_scores_gemma":[0.0022293206,0.00010283525,0.00030093495,0.0004448818,0.00024125143,0.00037185734,0.00047492873,0.00030846772,0.00040148714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029205976,0.000114471106,0.9534404,0.00010396266,0.0002094607,0.00020085153,0.0003662036,0.0013146305,0.0031190095,0.0004661266,0.0035748524,0.03679804],"study_design_scores_gemma":[0.000007139704,0.00007982965,0.99714595,0.000010151127,0.00003253169,0.0002501699,0.00010572261,0.0005605256,0.0005720594,0.00016996785,0.0010607573,0.000005241363],"about_ca_topic_score_codex":0.0039022518,"about_ca_topic_score_gemma":0.004059879,"teacher_disagreement_score":0.006518879,"about_ca_system_score_codex":0.0004996951,"about_ca_system_score_gemma":0.0005415342,"threshold_uncertainty_score":0.02180779},"labels":[],"label_agreement":null},{"id":"W3113026871","doi":"10.1002/alz.041213","title":"Associations between amyloid‐β, white matter disease, functional brain networks, and mobility function: Possible indicators of reserve and resilience","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pittsburgh compound B; Hyperintensity; Digit symbol substitution test; White matter; Cognitive reserve; Cognition; Psychology; Physical medicine and rehabilitation; Dementia; Cardiology; Medicine; Internal medicine; Magnetic resonance imaging; Neuroscience; Cognitive impairment; Disease; Pathology; Radiology","score_opus":0.04768940530050129,"score_gpt":0.308054198797472,"score_spread":0.26036479349697067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113026871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993255,0.00011415527,0.00010599484,0.00002768645,0.0000016154946,0.000002950735,0.00012996298,0.0000025414158,0.00028943917],"genre_scores_gemma":[0.99969304,0.000029554218,0.00008358659,0.0000057612956,0.000003208268,0.000004120311,0.00007735968,7.015903e-7,0.00010264984],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998604,0.000033900644,0.000016895328,0.00003910635,0.000016405807,0.000033172924],"domain_scores_gemma":[0.99909925,0.00017571897,0.0004641727,0.000066659086,0.00006244015,0.00013179131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055088376,0.0003914532,0.00020444082,0.0007376563,0.00034268197,0.00061262964,0.00031636178,0.0003219116,0.002241638],"category_scores_gemma":[0.002316999,0.0002000207,0.000241053,0.0005037289,0.0003101749,0.00049173355,0.00061069475,0.00032910312,0.000124009],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041141346,0.00005149946,0.9959565,0.000013102358,0.00012766155,0.00008085199,0.000101591744,0.00014745511,0.00081512047,0.000061006547,0.000049187176,0.0021845922],"study_design_scores_gemma":[0.0000028574784,0.000044186072,0.9992409,0.000003272309,0.000023826438,0.00008547334,0.00006416155,0.00029117594,0.00008142345,0.0001267829,0.000034000823,0.000001929567],"about_ca_topic_score_codex":0.0030621614,"about_ca_topic_score_gemma":0.0050574495,"teacher_disagreement_score":0.0030621614,"about_ca_system_score_codex":0.0001692288,"about_ca_system_score_gemma":0.00019733304,"threshold_uncertainty_score":0.007499039},"labels":[],"label_agreement":null},{"id":"W3113161003","doi":"10.1016/j.pscychresns.2020.111234","title":"White matter microstructure across brain-based biotypes for psychosis – findings from the bipolar-schizophrenia network for intermediate phenotypes","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Royal Ottawa Mental Health Centre","funders":"National Institute of Mental Health","keywords":"Schizoaffective disorder; Fornix; Bipolar disorder; Fractional anisotropy; White matter; Corpus callosum; Psychosis; Schizophrenia (object-oriented programming); Proband; Medicine; Bipolar I disorder; Internal medicine; Psychology; Psychiatry; Biology; Pathology; Mania; Magnetic resonance imaging; Hippocampus; Genetics; Cognition","score_opus":0.08299371878723376,"score_gpt":0.40371902954084254,"score_spread":0.32072531075360877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113161003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986615,0.00012448861,0.00024952096,0.0000982796,0.0000061088954,0.000007781273,0.00036635224,0.000004014163,0.00048208612],"genre_scores_gemma":[0.9992107,0.00004649828,0.00017627637,0.000028822305,0.000005915687,0.000005646791,0.00036923544,0.000007461488,0.00014933612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99933237,0.00014400212,0.000066782886,0.00026069698,0.00008987512,0.00010625911],"domain_scores_gemma":[0.9985512,0.0001776443,0.0006321439,0.00021269576,0.00018048601,0.0002458011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011534012,0.00082246045,0.00057498156,0.0017224434,0.0014870699,0.0015066335,0.000818031,0.0006909348,0.0033558446],"category_scores_gemma":[0.003095527,0.0004236313,0.0008627376,0.0013545816,0.001119696,0.0009880334,0.002737644,0.0010596138,0.00023692219],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001141627,0.000060379447,0.98519635,0.000032928514,0.00069310964,0.00043142997,0.0013568357,0.00022929009,0.005786124,0.00067377574,0.00036236376,0.0040358766],"study_design_scores_gemma":[0.000008418122,0.00003668366,0.998038,0.000014656983,0.00006696855,0.00028877528,0.0004959157,0.00021431221,0.00009136464,0.0006579303,0.000080527665,0.0000064660476],"about_ca_topic_score_codex":0.021508288,"about_ca_topic_score_gemma":0.033714637,"teacher_disagreement_score":0.021508288,"about_ca_system_score_codex":0.0006862411,"about_ca_system_score_gemma":0.0005691146,"threshold_uncertainty_score":0.042766154},"labels":[],"label_agreement":null},{"id":"W3113293558","doi":"10.1186/s41983-020-00232-w","title":"Association between microstructural white matter abnormalities and cognitive functioning in patients with type 2 diabetes mellitus: a diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"The Egyptian Journal of Neurology Psychiatry and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Cognition; Medicine; Internal medicine; Type 2 Diabetes Mellitus; Type 2 diabetes; Diabetes mellitus; Audiology; Cognitive impairment; Psychology; Psychiatry; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.015475455242107337,"score_gpt":0.25217148923505595,"score_spread":0.2366960339929486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113293558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993974,0.0002487019,0.000039043312,0.00002900379,0.0000050226517,0.000005938636,0.00009501637,0.00000110367,0.0001787875],"genre_scores_gemma":[0.99962723,0.00009358549,0.000052328254,0.000015847983,0.000013627773,0.000004539518,0.0001066316,6.269792e-7,0.000085564956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997708,0.0000451584,0.00003987336,0.000064279564,0.000042410455,0.000037444446],"domain_scores_gemma":[0.9993156,0.00012186368,0.00029297825,0.000046595007,0.00007349849,0.0001494722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004358162,0.00041181003,0.00034695677,0.0009882329,0.0004407867,0.00057274284,0.00023624615,0.00047613608,0.0014806957],"category_scores_gemma":[0.0011392534,0.00029000264,0.00041068095,0.0008919711,0.0002539786,0.0003676612,0.00030251103,0.00042339673,0.0001646872],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017367813,0.00007332963,0.99866796,0.000009668214,0.00007299911,0.0001806523,0.000044917255,0.000013995766,0.0002148315,0.00000917506,0.000031977226,0.00050681544],"study_design_scores_gemma":[0.000012437476,0.00013178546,0.9987987,0.0000051311144,0.000055400662,0.00064515363,0.000118779826,0.000093091774,0.000049479204,0.000019615172,0.00006744623,0.0000030155984],"about_ca_topic_score_codex":0.0023636017,"about_ca_topic_score_gemma":0.0025486313,"teacher_disagreement_score":0.0023636017,"about_ca_system_score_codex":0.00020847062,"about_ca_system_score_gemma":0.00023354343,"threshold_uncertainty_score":0.004953444},"labels":[],"label_agreement":null},{"id":"W3114615555","doi":"10.1007/s00429-020-02181-9","title":"Diffusion properties of the fornix assessed by deterministic tractography shows age, sex, volume, cognitive, hemispheric, and twin relationships in young adults from the Human Connectome Project","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Canada Excellence Research Chairs, Government of Canada; Fondation Brain Canada","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Psychology; Hippocampus; Tractography; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.04028816794297815,"score_gpt":0.28474210046871945,"score_spread":0.2444539325257413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114615555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99895847,0.0001305946,0.0002772913,0.00002441708,0.0000042359407,0.0000040756854,0.0003874911,0.000003254841,0.00021023292],"genre_scores_gemma":[0.9986474,0.00008264766,0.00035753724,0.0000073643523,0.0000035598132,0.0000073343754,0.00045306448,0.00001005889,0.00043112127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997291,0.000051090043,0.00004314724,0.00009777304,0.000048877682,0.000030006628],"domain_scores_gemma":[0.99908173,0.00021690983,0.00025690306,0.00019597028,0.0001399666,0.00010857904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000863194,0.00038094964,0.0005439558,0.0009959143,0.0008606108,0.00066473393,0.0002839402,0.00046857816,0.0020490843],"category_scores_gemma":[0.0038377794,0.00042044534,0.0004340064,0.00078066794,0.0003648684,0.00043734527,0.0006121994,0.00042038463,0.0002732776],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016137293,0.00007850803,0.97309816,0.000050467672,0.0006155561,0.00093013054,0.001995453,0.00034583022,0.010446729,0.00050076033,0.00056513975,0.00975955],"study_design_scores_gemma":[0.0000106006,0.00005489969,0.9973328,0.0000077303985,0.00009825776,0.0010641344,0.00017405205,0.00022027268,0.0005096315,0.00022586541,0.0002932193,0.000008635538],"about_ca_topic_score_codex":0.011846359,"about_ca_topic_score_gemma":0.016401516,"teacher_disagreement_score":0.011846359,"about_ca_system_score_codex":0.00029071132,"about_ca_system_score_gemma":0.0002750923,"threshold_uncertainty_score":0.023554802},"labels":[],"label_agreement":null},{"id":"W3116014849","doi":"10.3171/2020.7.jns201287","title":"Deciphering the frontostriatal circuitry through the fiber dissection technique: direct structural evidence on the morphology and axonal connectivity of the fronto-caudate tract","year":2021,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Anatomy; Neuroscience; Diffusion MRI; Medicine; Caudate nucleus; Fiber tract; Arcuate fasciculus; Biology; Tractography; Magnetic resonance imaging","score_opus":0.1053400262046791,"score_gpt":0.34775164194616287,"score_spread":0.2424116157414838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116014849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98319614,0.0015805353,0.013433679,0.000055127315,0.000010050571,0.000036196918,0.0001370362,0.000030925537,0.0015202599],"genre_scores_gemma":[0.97127265,0.0018151046,0.025462039,0.000036506248,0.000011150055,0.000035919093,0.0002625779,0.0000124708795,0.0010915812],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999386,0.0000048451325,0.0000060017765,0.000024630735,0.000014224431,0.000011739606],"domain_scores_gemma":[0.9998406,0.00003495533,0.000045665627,0.000028294302,0.000035559475,0.000014947523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023315719,0.00030911158,0.00015198084,0.00072405254,0.00026457614,0.00021797775,0.00018854704,0.00038174907,0.0015757963],"category_scores_gemma":[0.00033629427,0.00017384955,0.00012687717,0.00017807135,0.00059155666,0.00041115886,0.00018747307,0.00020040001,0.0004645178],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017881197,0.000027280432,0.024762636,0.00015333007,0.00004099283,0.001626527,0.0003038099,0.00020739387,0.9464844,0.0004311292,0.000059405735,0.02572432],"study_design_scores_gemma":[0.000056722994,0.0015062527,0.537183,0.00020158425,0.00016142952,0.03292489,0.0008883502,0.0035519728,0.41476437,0.0011033503,0.0076207197,0.000037414353],"about_ca_topic_score_codex":0.002014137,"about_ca_topic_score_gemma":0.005751348,"teacher_disagreement_score":0.002014137,"about_ca_system_score_codex":0.00021916229,"about_ca_system_score_gemma":0.0003207955,"threshold_uncertainty_score":0.005271554},"labels":[],"label_agreement":null},{"id":"W3116037206","doi":"10.1073/pnas.2012533117","title":"Axon morphology is modulated by the local environment and impacts the noninvasive investigation of its structure–function relationship","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Vetenskapsrådet; European Synchrotron Radiation Facility","keywords":"Axon; White matter; Soma; Corpus callosum; Magnetic resonance imaging; Diffusion MRI; Biophysics; Nuclear magnetic resonance; Neuroscience; Anatomy; Biology; Physics; Medicine","score_opus":0.09483896768030663,"score_gpt":0.3204994083299202,"score_spread":0.22566044064961355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116037206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9648455,0.0027696863,0.02579071,0.0005126633,0.00006061311,0.000016028253,0.00027139924,0.00018303716,0.0055503873],"genre_scores_gemma":[0.9887772,0.002015507,0.007438029,0.00012972015,0.000036424437,0.00002144826,0.000103167295,0.000046086796,0.001432334],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981123,0.000030436442,0.00000890173,0.000056497458,0.000066755216,0.000026142989],"domain_scores_gemma":[0.99966717,0.000113776114,0.00008830009,0.000027859842,0.00006379493,0.000039149872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021820025,0.00019617741,0.00019727924,0.00025311872,0.00033591938,0.00073395047,0.00014680778,0.00038075814,0.0010026094],"category_scores_gemma":[0.0006943657,0.00016737051,0.000086659325,0.00025473497,0.0005809103,0.00069308444,0.00040028756,0.0003479903,0.00032520757],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054081476,0.000013045836,0.005195946,0.0000630276,0.000009189323,0.00012421593,0.00007999343,0.00062456535,0.98285866,0.0010832802,0.00023790948,0.009656084],"study_design_scores_gemma":[0.000018716704,0.00043440372,0.20360745,0.000099737306,0.00008498275,0.0026744122,0.0008151527,0.02682122,0.7491011,0.0048020226,0.011441968,0.000098752964],"about_ca_topic_score_codex":0.001012917,"about_ca_topic_score_gemma":0.002182863,"teacher_disagreement_score":0.001012917,"about_ca_system_score_codex":0.0003550339,"about_ca_system_score_gemma":0.000255761,"threshold_uncertainty_score":0.0033540726},"labels":[],"label_agreement":null},{"id":"W3117135956","doi":"10.1101/2020.12.17.423333","title":"Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; London Health Sciences Centre; Western University","funders":"","keywords":"Fiducial marker; Artificial intelligence; Computer science; Image registration; Preprocessor; Neuroimaging; Workflow; Magnetic resonance imaging; Medical physics; Computer vision; Pattern recognition (psychology); Medicine; Radiology; Image (mathematics)","score_opus":0.04189763959645309,"score_gpt":0.3309519131999461,"score_spread":0.289054273603493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117135956","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58855337,0.0021241552,0.3753333,0.001926516,0.00040444057,0.0013784934,0.017473562,0.008576803,0.0042293835],"genre_scores_gemma":[0.7399702,0.00037196698,0.23627955,0.00041266548,0.00010799623,0.0008938661,0.020224728,0.000600224,0.0011387997],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99690115,0.0011744276,0.00045913848,0.0007421605,0.00060884585,0.00011422704],"domain_scores_gemma":[0.9958704,0.0013522694,0.0003856006,0.0013663911,0.00089559454,0.00012975956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00530397,0.00076899835,0.0007206021,0.0022477391,0.0007825557,0.0014901594,0.001209346,0.0013647616,0.0015935692],"category_scores_gemma":[0.014992009,0.00037995208,0.00095499784,0.0011999506,0.0009338412,0.0005044061,0.0018302691,0.0011473726,0.0008713739],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032955012,0.0010044334,0.082318604,0.0018913402,0.0017285265,0.0032622481,0.0025391781,0.1231432,0.08167907,0.008729287,0.047097266,0.64331126],"study_design_scores_gemma":[0.0010142548,0.0025412024,0.23517706,0.0005373119,0.00065311446,0.014985855,0.0018813054,0.5201034,0.099240184,0.031267297,0.09210292,0.0004961784],"about_ca_topic_score_codex":0.0075472835,"about_ca_topic_score_gemma":0.010749519,"teacher_disagreement_score":0.0075472835,"about_ca_system_score_codex":0.0007054755,"about_ca_system_score_gemma":0.0014164575,"threshold_uncertainty_score":0.028050363},"labels":[],"label_agreement":null},{"id":"W3119396371","doi":"10.1007/s00429-020-02185-5","title":"Poorer clinical outcomes for older adult monolinguals when matched to bilinguals on brain health","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; York University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Neuroscience of multilingualism; Dementia; Psychology; White matter; Neuroimaging; Cognition; Propensity score matching; Boston Naming Test; Clinical psychology; Neuropsychology; Developmental psychology; Audiology; Medicine; Disease; Psychiatry; Magnetic resonance imaging","score_opus":0.06766428675002974,"score_gpt":0.42087342849979886,"score_spread":0.35320914174976914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119396371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99883217,0.0001322097,0.00001598843,0.00003597654,0.000010588751,0.0000024068622,0.00017411186,0.0000013927458,0.0007951992],"genre_scores_gemma":[0.99922955,0.00006955789,0.000013091159,0.000026458416,0.000011620854,0.000002080544,0.0002135759,0.0000011521411,0.00043282562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998591,0.000017460205,0.0000150811065,0.000041357187,0.000017636243,0.000049310973],"domain_scores_gemma":[0.99941254,0.000062262035,0.0002333757,0.000023050252,0.000067694404,0.00020107848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022669467,0.0003467377,0.00045179593,0.00086041185,0.0006525854,0.00067399006,0.00016231071,0.00047118517,0.0035346532],"category_scores_gemma":[0.0012780287,0.00015320115,0.00026597403,0.00059829943,0.00027951697,0.0005427038,0.0005491784,0.0003654156,0.00044046436],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010501569,0.00007474878,0.9936094,0.000014299643,0.0000788327,0.00055842753,0.00033833671,0.000024954536,0.0016170391,0.000038471906,0.00017478009,0.0024205418],"study_design_scores_gemma":[0.0000078849935,0.0001064192,0.9989384,0.0000042025313,0.000020223348,0.00034378658,0.00036539952,0.000035387424,0.000049924976,0.000051216943,0.000074213756,0.0000031241702],"about_ca_topic_score_codex":0.013545701,"about_ca_topic_score_gemma":0.019897092,"teacher_disagreement_score":0.013545701,"about_ca_system_score_codex":0.00038792926,"about_ca_system_score_gemma":0.00036724348,"threshold_uncertainty_score":0.02693367},"labels":[],"label_agreement":null},{"id":"W3120110232","doi":"10.1101/2021.01.12.21249706","title":"Diffusion basis spectrum imaging in post-hemorrhagic hydrocephalus of prematurity","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Intellectual and Developmental Disabilities Research Center; Doris Duke Charitable Foundation; Child Neurology Foundation; Cerebral Palsy International Research Foundation; Dana Foundation; National Institutes of Health; March of Dimes Foundation","keywords":"White matter; Intraventricular hemorrhage; Fractional anisotropy; Corpus callosum; Hydrocephalus; Diffusion MRI; Medicine; Fiber tract; Pathology; Magnetic resonance imaging; Radiology; Biology; Gestational age","score_opus":0.03179120281831256,"score_gpt":0.3206358706912859,"score_spread":0.28884466787297336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120110232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99850106,0.0005124584,0.00065026415,0.000016219012,0.0000027135932,0.0000053403587,0.00006509258,0.000007849594,0.0002389942],"genre_scores_gemma":[0.99858177,0.00039554297,0.00087677664,0.000005798954,0.0000030888903,0.000004769066,0.000050422685,0.0000020421694,0.000079787926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999198,0.000022293143,0.000009380148,0.000018388344,0.000018093491,0.0000119670985],"domain_scores_gemma":[0.9997249,0.00005388874,0.00013827221,0.000018465644,0.000035440597,0.000029049566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041618373,0.00024209062,0.00015853143,0.0011966502,0.0001379987,0.0002186159,0.00012273063,0.00015969037,0.00037606887],"category_scores_gemma":[0.00091054355,0.00008924469,0.00009565132,0.00032877448,0.00022224827,0.00015729672,0.00028591184,0.00012868793,0.000050865037],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034582647,0.000025182802,0.917066,0.000096121876,0.000061554085,0.00486022,0.0003909712,0.0006398773,0.050774936,0.00034566422,0.00019957758,0.02519412],"study_design_scores_gemma":[0.000004743245,0.00022146649,0.9827405,0.000031995554,0.000022627095,0.006948068,0.00030895218,0.0015957773,0.00724919,0.0003413038,0.00052923156,0.000006236478],"about_ca_topic_score_codex":0.0017903978,"about_ca_topic_score_gemma":0.0015412911,"teacher_disagreement_score":0.0017903978,"about_ca_system_score_codex":0.00016887933,"about_ca_system_score_gemma":0.00017047196,"threshold_uncertainty_score":0.003559947},"labels":[],"label_agreement":null},{"id":"W3120177330","doi":"10.1609/aaai.v35i12.17258","title":"Towards Generalized Implementation of Wasserstein Distance in GANs","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Shanghai Jiao Tong University; National Natural Science Foundation of China","keywords":"Duality (order theory); Lipschitz continuity; Mathematics; Constraint (computer-aided design); Duality gap; Sobolev space; Strong duality; Applied mathematics; Perturbation function; Mathematical optimization; Pure mathematics; Mathematical analysis; Optimization problem; Geometry","score_opus":0.16416688522055034,"score_gpt":0.41593591733574564,"score_spread":0.2517690321151953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120177330","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070818323,0.00020504392,0.9896017,0.00017943479,0.000039737566,0.000026253656,0.000051714196,0.0006688381,0.002145537],"genre_scores_gemma":[0.44290158,0.0005641292,0.548641,0.0007022523,0.00011588462,0.00020390033,0.0005751141,0.00067308237,0.0056230384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987864,0.0006000501,0.000046462847,0.00021298479,0.00025257524,0.0001016535],"domain_scores_gemma":[0.9989918,0.0004992772,0.00006643944,0.0002025967,0.0001749445,0.000064995824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022701737,0.0010276062,0.0010694243,0.00046296333,0.00027675543,0.0009815299,0.0015560618,0.001224206,0.0021612563],"category_scores_gemma":[0.0051828367,0.00044157103,0.0006346572,0.0005384052,0.0008249442,0.0020322043,0.0021406512,0.002679479,0.00076541735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001565392,0.000102383055,0.00097559736,0.00014720077,0.000074794894,0.000120264995,0.00015067644,0.6282478,0.0067729503,0.19102892,0.00606282,0.16616015],"study_design_scores_gemma":[0.0000066034663,0.000020360623,0.000052178493,0.000007487327,0.0000036980005,0.000022357015,0.000005563737,0.9683415,0.00089105417,0.029285353,0.0013592137,0.0000046176806],"about_ca_topic_score_codex":0.0021482622,"about_ca_topic_score_gemma":0.0031539206,"teacher_disagreement_score":0.0022701737,"about_ca_system_score_codex":0.0009821352,"about_ca_system_score_gemma":0.00101814,"threshold_uncertainty_score":0.012005985},"labels":[],"label_agreement":null},{"id":"W3120261134","doi":"10.1038/s41598-020-79540-3","title":"An atlas for human brain myelin content throughout the adult life span","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Vancouver Coastal Health Research Institute; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"Myelin; Neuroimaging; Context (archaeology); White matter; Content (measure theory); Biology; Life span; Neuroscience; Magnetic resonance imaging; Medicine; Evolutionary biology; Central nervous system; Mathematics","score_opus":0.13032617741329613,"score_gpt":0.4150828116473342,"score_spread":0.2847566342340381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120261134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16767207,0.0035589547,0.65548813,0.00067030237,0.0002810461,0.001036103,0.112882406,0.017681437,0.04072958],"genre_scores_gemma":[0.35856292,0.0019687205,0.55436635,0.00028582753,0.000095779316,0.0027371934,0.053615976,0.0042023705,0.024164887],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997178,0.00006070409,0.00003558665,0.000084759035,0.000076420794,0.000024713236],"domain_scores_gemma":[0.99941635,0.00013873534,0.000088074186,0.00011601128,0.00020985222,0.00003104609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009018587,0.00047312246,0.0003449928,0.0022598933,0.00051278895,0.0010612113,0.0006102211,0.0005503579,0.013493281],"category_scores_gemma":[0.0019216521,0.00032761335,0.0004725809,0.0019276968,0.00027946127,0.00062931277,0.00080856733,0.00048850256,0.0040121623],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012554319,0.00016913761,0.04428543,0.0024328595,0.00057697156,0.0017577853,0.0032214357,0.017659133,0.09609188,0.035482936,0.22548367,0.5715834],"study_design_scores_gemma":[0.00016777574,0.0005020771,0.28254744,0.0006119262,0.00045472803,0.012312459,0.0009337971,0.04734953,0.04107379,0.040102206,0.5736749,0.00026932906],"about_ca_topic_score_codex":0.0046258434,"about_ca_topic_score_gemma":0.007990901,"teacher_disagreement_score":0.013493281,"about_ca_system_score_codex":0.00058450253,"about_ca_system_score_gemma":0.0012608375,"threshold_uncertainty_score":0.04513949},"labels":[],"label_agreement":null},{"id":"W3120303568","doi":"10.1016/j.jns.2021.117317","title":"Peri-hematoma corticospinal tract integrity in intracerebral hemorrhage patients: A diffusion-tensor imaging study","year":2021,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; The Speech and Stuttering Institute; Women and Children’s Health Research Institute; University of Alberta","funders":"Canada Excellence Research Chairs, Government of Canada; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Medicine; Fractional anisotropy; Corticospinal tract; Intracerebral hemorrhage; Edema; White matter; Diffusion MRI; Hematoma; Brain edema; Nuclear medicine; Magnetic resonance imaging; Anesthesia; Radiology; Surgery; Glasgow Coma Scale","score_opus":0.058631785819977515,"score_gpt":0.3563733135864293,"score_spread":0.2977415277664518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120303568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994417,0.00008233775,0.000030711784,0.000032743665,0.0000031006475,0.000006487356,0.000053921478,8.3422805e-7,0.0003482789],"genre_scores_gemma":[0.9996555,0.00007799361,0.00003823559,0.000017597238,0.000018477027,0.0000033808612,0.000096347554,7.6005745e-7,0.00009180056],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998504,0.000021039063,0.000026888796,0.000035298708,0.00002773078,0.000038539827],"domain_scores_gemma":[0.9994259,0.00010537472,0.00018696408,0.000044054505,0.00006854529,0.00016932603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029586797,0.00046535852,0.00038653793,0.001001232,0.00069114263,0.00064486364,0.00039981294,0.00064973877,0.001577558],"category_scores_gemma":[0.0015608817,0.00033843616,0.00032996992,0.0008148658,0.000692711,0.00105437,0.00040157078,0.00048740365,0.00032146656],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087258616,0.00029723693,0.9777524,0.000034221073,0.000112585716,0.013863278,0.00054213294,0.0000754382,0.003908615,0.000061433384,0.000107319756,0.0023728074],"study_design_scores_gemma":[0.000023642348,0.0003144851,0.9907945,0.000004798244,0.000058793605,0.007740673,0.0005012728,0.00013604361,0.0002403761,0.000069007816,0.000106193664,0.000010274583],"about_ca_topic_score_codex":0.0042033875,"about_ca_topic_score_gemma":0.004439787,"teacher_disagreement_score":0.0042033875,"about_ca_system_score_codex":0.0003518828,"about_ca_system_score_gemma":0.00049442693,"threshold_uncertainty_score":0.008357823},"labels":[],"label_agreement":null},{"id":"W3120843416","doi":"10.1007/s00234-021-02635-9","title":"Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation","year":2021,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Sunnybrook Health Science Centre; Sunnybrook Hospital; University of Toronto; University of Waterloo","funders":"FedDev Ontario; Mitacs","keywords":"Tractography; Diffusion MRI; White matter; Spinal cord; Anatomy; Neuroradiology; Medicine; Magnetic resonance imaging; Neurology; Radiology","score_opus":0.048857378659725975,"score_gpt":0.3565472024058139,"score_spread":0.3076898237460879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120843416","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3988138,0.0009546486,0.5921097,0.0002349142,0.00005536538,0.0002237127,0.0015378636,0.0032400046,0.0028298902],"genre_scores_gemma":[0.7273974,0.00057693763,0.26790658,0.00003413784,0.000041650816,0.000086497035,0.0013184852,0.0006630004,0.0019753003],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991948,0.00017108042,0.00006004251,0.0002728336,0.00023033554,0.000070859925],"domain_scores_gemma":[0.99822074,0.0005723244,0.00035528163,0.00029996652,0.00045454738,0.00009708433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017633043,0.0006270458,0.0007755251,0.0045862384,0.00083239545,0.002711525,0.00059772376,0.00087711087,0.001499992],"category_scores_gemma":[0.0060629593,0.00049144466,0.0008873449,0.0026684273,0.00061485183,0.0012972387,0.0007245026,0.0006513353,0.0008431721],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018701914,0.0003345339,0.07924447,0.00064458436,0.000665559,0.00083613495,0.0012513865,0.12716365,0.2114675,0.0161435,0.0043707886,0.5560077],"study_design_scores_gemma":[0.000078660196,0.00024942931,0.13727815,0.00010026033,0.00030081513,0.0030363426,0.00035066323,0.76029384,0.07239349,0.020773161,0.0050008814,0.00014440228],"about_ca_topic_score_codex":0.017135149,"about_ca_topic_score_gemma":0.025254013,"teacher_disagreement_score":0.017135149,"about_ca_system_score_codex":0.00085897755,"about_ca_system_score_gemma":0.0029902179,"threshold_uncertainty_score":0.03407079},"labels":[],"label_agreement":null},{"id":"W3121662764","doi":"10.1038/s41380-021-01018-z","title":"Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia—a multicenter harmonized diffusion tensor imaging study","year":2021,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Center for Advancing Translational Sciences; National Institute of Mental Health; National Research Foundation of Korea; U.S. Department of Health and Human Services","keywords":"Fractional anisotropy; White matter; Corpus callosum; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Confounding; Population; Magnetic resonance imaging; Medicine; Internal medicine; Clinical psychology; Psychiatry; Neuroscience; Radiology","score_opus":0.03999007663752993,"score_gpt":0.3587815498532476,"score_spread":0.31879147321571766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121662764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996152,0.000033605782,0.000119449796,0.000028550003,0.0000021444669,0.000014927203,0.00012859495,0.0000015855644,0.000055861045],"genre_scores_gemma":[0.9989893,0.00003063235,0.0003969572,0.000030479941,0.000009391702,0.00002069009,0.00046183093,0.000003834834,0.00005696005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985551,0.00075288845,0.0001464837,0.00026941858,0.00012813754,0.00014798358],"domain_scores_gemma":[0.99780005,0.00020546814,0.00079002086,0.00047092672,0.00034311655,0.00039030213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053325794,0.0006840136,0.0006303038,0.00075985596,0.0011298901,0.0007503189,0.00062611006,0.00075512024,0.00042732075],"category_scores_gemma":[0.002978942,0.0004406733,0.00052000897,0.000825118,0.0007368276,0.0009193167,0.0013309498,0.00055032986,0.00017989073],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027078905,0.00065803435,0.9810007,0.000024610577,0.0005879646,0.00019095028,0.001066931,0.00025361925,0.008049004,0.00017917054,0.00039929984,0.004881863],"study_design_scores_gemma":[0.00010546375,0.00055529695,0.997095,0.0000056189024,0.00013640139,0.0002544008,0.00071947125,0.00046268918,0.00032939026,0.00005699063,0.00026619158,0.000013131279],"about_ca_topic_score_codex":0.0064792973,"about_ca_topic_score_gemma":0.010629454,"teacher_disagreement_score":0.0064792973,"about_ca_system_score_codex":0.00068768795,"about_ca_system_score_gemma":0.0011576016,"threshold_uncertainty_score":0.0282017},"labels":[],"label_agreement":null},{"id":"W3122552454","doi":"10.1016/j.nicl.2021.102567","title":"Widespread white matter aberration is associated with the severity of apathy in amnestic Mild Cognitive Impairment: Tract-based spatial statistics analysis","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Lembaga Pengelola Dana Pendidikan; Universitair Medisch Centrum Groningen; ZonMw","keywords":"Apathy; White matter; Psychology; Cognitive impairment; Cognition; Medicine; Audiology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.07147150062390782,"score_gpt":0.39279993927548174,"score_spread":0.3213284386515739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122552454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99934345,0.00004672763,0.00040968772,0.000007642027,7.09799e-7,0.000003966295,0.00008490453,0.000010460804,0.000092405986],"genre_scores_gemma":[0.9995968,0.000013081715,0.00025171635,0.0000018818896,0.0000014304568,0.000003191113,0.00009116094,0.0000020635387,0.000038726957],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976915,0.00004637264,0.000048977257,0.00005608265,0.0000521059,0.000027381628],"domain_scores_gemma":[0.9982839,0.000255384,0.00094581296,0.00019586255,0.00016389495,0.00015505783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053288793,0.00025584808,0.00027967957,0.0014205553,0.0002484503,0.00038887822,0.00019622978,0.00023384868,0.00087383465],"category_scores_gemma":[0.0027853346,0.00013750259,0.00035066353,0.0007721426,0.00030792298,0.00022438983,0.000447821,0.00015029687,0.00010691733],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006915434,0.000042883104,0.98169416,0.000027695072,0.00024113686,0.0005261195,0.00020961085,0.0006678636,0.008069636,0.000074232645,0.000090561654,0.0076646004],"study_design_scores_gemma":[0.00000604121,0.00008233187,0.99553114,0.0000029920336,0.000040527077,0.0009884688,0.00008788429,0.0026450702,0.00044036686,0.00010997466,0.000058786984,0.0000064086043],"about_ca_topic_score_codex":0.0056543616,"about_ca_topic_score_gemma":0.005633923,"teacher_disagreement_score":0.0056543616,"about_ca_system_score_codex":0.00023340518,"about_ca_system_score_gemma":0.00026217333,"threshold_uncertainty_score":0.011242926},"labels":[],"label_agreement":null},{"id":"W3122665304","doi":"10.3390/electronics10030249","title":"An Ensemble Learning Approach Based on Diffusion Tensor Imaging Measures for Alzheimer’s Disease Classification","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Ministero dello Sviluppo Economico; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Artificial intelligence; Computer science; Machine learning; Concatenation (mathematics); Diffusion MRI; Feature selection; Ensemble learning; Exploit; Neuroimaging; Curse of dimensionality; Pattern recognition (psychology); Magnetic resonance imaging; Mathematics","score_opus":0.07979652277542423,"score_gpt":0.3556719242560934,"score_spread":0.27587540148066914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122665304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05950258,0.0010577239,0.93738085,0.00023815829,0.00013314254,0.000052210322,0.0001343794,0.00048140323,0.0010194874],"genre_scores_gemma":[0.7477927,0.00069570774,0.24850993,0.00012277611,0.00022103326,0.00011544323,0.0006140445,0.00006843321,0.0018599054],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929357,0.00020009601,0.00006573769,0.00016215183,0.00019684093,0.0000816278],"domain_scores_gemma":[0.99903154,0.00033599217,0.00007246265,0.00014884047,0.000353029,0.000058232537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020131203,0.00072230306,0.001131371,0.0015200835,0.00049879064,0.0007823965,0.0007827254,0.0006922385,0.00082199345],"category_scores_gemma":[0.0027798354,0.00017591474,0.000948686,0.0009946224,0.00025174758,0.00089035823,0.0007248817,0.00091780524,0.00034395372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023540563,0.00019850343,0.007542688,0.00006245491,0.0003218227,0.00010765266,0.00011727563,0.1546838,0.012472978,0.0052826833,0.0032032584,0.8157715],"study_design_scores_gemma":[0.000005056289,0.00008326087,0.0013068259,0.000009580448,0.000059460177,0.00005038102,0.0000184382,0.99184895,0.0023916485,0.0032979546,0.00091625267,0.000012147372],"about_ca_topic_score_codex":0.0020660353,"about_ca_topic_score_gemma":0.0026552735,"teacher_disagreement_score":0.0020660353,"about_ca_system_score_codex":0.00027630117,"about_ca_system_score_gemma":0.0005087143,"threshold_uncertainty_score":0.010646522},"labels":[],"label_agreement":null},{"id":"W3123502171","doi":"10.1007/s00701-020-04672-4","title":"Uncrossed corticospinal tracts presenting as transient tumor-related symptomatology","year":2021,"lang":"en","type":"article","venue":"Acta Neurochirurgica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Royal University Hospital","funders":"","keywords":"Medicine; Corticospinal tract; Hemiparesis; Diffusion MRI; Pyramidal tracts; Neurosurgery; Neuroradiology; Neurology; Stroke (engine); Radiology; Magnetic resonance imaging; Anatomy; Angiography","score_opus":0.03697971929130505,"score_gpt":0.33792618323306256,"score_spread":0.3009464639417575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123502171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9684522,0.004476038,0.003973843,0.0010628725,0.00018580054,0.00012532964,0.0003435953,0.00021927632,0.021161146],"genre_scores_gemma":[0.9975745,0.0007767049,0.00047082792,0.00025275492,0.00012438929,0.000013197228,0.0001080479,0.000014316839,0.00066520687],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99978787,0.00001873032,0.000021317017,0.000046567442,0.000031102954,0.00009441115],"domain_scores_gemma":[0.9991572,0.00021715595,0.0002898348,0.0000842293,0.000059875452,0.00019174714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000175036,0.0010188658,0.0005109595,0.0011225021,0.0006973353,0.0006328205,0.0005627874,0.0014453607,0.0031376265],"category_scores_gemma":[0.0022602149,0.00031130895,0.0002540028,0.001262158,0.0011717667,0.00097049517,0.0005075127,0.0012234126,0.0008884933],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024040605,0.00006629236,0.027365366,0.00010827707,0.000034644116,0.95929927,0.00017900833,0.00019695592,0.006505546,0.0004375797,0.0005927803,0.0049738386],"study_design_scores_gemma":[0.000027685928,0.0001368618,0.037230816,0.00003001029,0.00003341545,0.9590005,0.0001247212,0.00041021217,0.0017910326,0.00054297893,0.0006580489,0.0000135783175],"about_ca_topic_score_codex":0.0018188901,"about_ca_topic_score_gemma":0.0026974587,"teacher_disagreement_score":0.0031376265,"about_ca_system_score_codex":0.0006692133,"about_ca_system_score_gemma":0.0006719237,"threshold_uncertainty_score":0.010496378},"labels":[],"label_agreement":null},{"id":"W3124084750","doi":"10.1089/brain.2020.0907","title":"Hierarchical Microstructure Informed Tractography","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Tractography; Diffusion MRI; White matter; Computer science; Artificial intelligence; Magnetic resonance imaging; Radiomics; Pattern recognition (psychology); Radiology; Medicine","score_opus":0.04658254528705097,"score_gpt":0.3559203308303244,"score_spread":0.30933778554327346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124084750","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052234316,0.00019887407,0.9922198,0.00013997291,0.000016783755,0.000033490556,0.00024242555,0.00055955903,0.0013655614],"genre_scores_gemma":[0.35361946,0.00069365127,0.6361464,0.00024393121,0.000111093264,0.00028240628,0.0019068335,0.00046034277,0.006535855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994442,0.00016315607,0.000028495779,0.00013894669,0.00016903451,0.00005611422],"domain_scores_gemma":[0.99864966,0.00069179415,0.00021393412,0.00019935242,0.00018683294,0.000058479978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072723394,0.0009230874,0.0008544474,0.0011657403,0.00042482407,0.0010811152,0.0009516123,0.0012946941,0.004699831],"category_scores_gemma":[0.0029250807,0.0005759894,0.0012701246,0.0012385572,0.0007731278,0.0010219656,0.0011031632,0.0011262026,0.0013500551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008733474,0.000024057948,0.0011088076,0.000136866,0.000090981666,0.00015255959,0.00008698653,0.8791763,0.006225022,0.027164714,0.003534282,0.082212046],"study_design_scores_gemma":[0.00000521314,0.000009501464,0.00018234219,0.0000062015706,0.000006997674,0.000029333269,0.0000032985677,0.99043065,0.000621799,0.0076401667,0.0010598205,0.000004674415],"about_ca_topic_score_codex":0.008889503,"about_ca_topic_score_gemma":0.012999985,"teacher_disagreement_score":0.008889503,"about_ca_system_score_codex":0.0013571202,"about_ca_system_score_gemma":0.0017197833,"threshold_uncertainty_score":0.017675519},"labels":[],"label_agreement":null},{"id":"W3124741176","doi":"10.1021/acschemneuro.0c00801","title":"Radiosynthesis, <i>In Vitro</i> and <i>In Vivo</i> Evaluation of [<sup>18</sup>F]CBD-2115 as a First-in-Class Radiotracer for Imaging 4R-Tauopathies","year":2021,"lang":"en","type":"article","venue":"ACS Chemical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Center for Scientific Review; National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Radioligand; Progressive supranuclear palsy; Radiosynthesis; In vivo; In vitro; Chemistry; Biochemistry; Biology; Molecular biology; Genetics","score_opus":0.049462504594981166,"score_gpt":0.34279656570751943,"score_spread":0.29333406111253824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124741176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95619935,0.010576028,0.018885894,0.00029774453,0.00009557943,0.0004068356,0.0018780428,0.00037833833,0.0112821665],"genre_scores_gemma":[0.9738877,0.0049539497,0.013199676,0.00017752977,0.000036646383,0.00024777238,0.0022716657,0.00013529744,0.0050896876],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998816,0.000038311882,0.000007235895,0.000025906238,0.000016488299,0.000030435622],"domain_scores_gemma":[0.9998946,0.00002254022,0.000026099184,0.00001240485,0.000025443538,0.00001888291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003406821,0.000782269,0.00038376433,0.00035480232,0.0003853115,0.0004183494,0.00040281995,0.00042281792,0.0016568525],"category_scores_gemma":[0.00024003835,0.0002942406,0.0003444763,0.00029383693,0.00036390527,0.0002564217,0.00013445245,0.0004869595,0.0005906913],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009934084,0.000118834534,0.0002990952,0.00022407029,0.000024480714,0.00017360561,0.00006457811,0.0014242517,0.99096537,0.0002880417,0.00039696108,0.005027373],"study_design_scores_gemma":[0.000067897236,0.001997573,0.0012469416,0.000012570571,0.00008496582,0.0006591422,0.000044471697,0.0010451115,0.9904103,0.00005141278,0.00436277,0.000016796692],"about_ca_topic_score_codex":0.004900799,"about_ca_topic_score_gemma":0.0038709736,"teacher_disagreement_score":0.004900799,"about_ca_system_score_codex":0.0007068379,"about_ca_system_score_gemma":0.0005193457,"threshold_uncertainty_score":0.009744585},"labels":[],"label_agreement":null},{"id":"W3125305379","doi":"10.1371/journal.pcbi.1008584","title":"Voxelized simulation of cerebral oxygen perfusion elucidates hypoxia in aged mouse cortex","year":2021,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"Cerebral blood flow; Computer science; Blood flow; Discretization; Hypoxia (environmental); Neuroscience; Perfusion; Biomedical engineering; Chemistry; Oxygen; Biology; Mathematics; Medicine; Cardiology","score_opus":0.0630287532450022,"score_gpt":0.3519936065417261,"score_spread":0.28896485329672394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125305379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9645685,0.00015553134,0.033000253,0.00015834003,0.000018102972,0.000021069203,0.00034075696,0.00026397518,0.0014735942],"genre_scores_gemma":[0.98454916,0.0001609038,0.014114384,0.000036136313,0.0000048748816,0.000039516886,0.00021089475,0.000046381276,0.00083770585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99997246,0.0000046873993,0.0000013859573,0.000005043388,0.000008862993,0.0000075962485],"domain_scores_gemma":[0.99992406,0.00002730961,0.000022648495,0.0000051153957,0.000009481007,0.000011352486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011583172,0.00022761557,0.00018427942,0.00020168492,0.000093471055,0.00018487657,0.00035013503,0.00035722562,0.00079042057],"category_scores_gemma":[0.00026502655,0.000107546395,0.00022829477,0.00014065369,0.00017532379,0.00013469433,0.00024070645,0.00026519666,0.0000534694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003473437,0.00011788339,0.003672379,0.00010175984,0.000052675987,0.0006039242,0.00018908881,0.809177,0.17481479,0.0046979627,0.00054488174,0.005680284],"study_design_scores_gemma":[0.000019531499,0.00010517054,0.0022438674,0.0000064341134,0.000015534684,0.00004606916,0.00002696252,0.9826637,0.01340029,0.0010924764,0.00037267993,0.000007236463],"about_ca_topic_score_codex":0.003722959,"about_ca_topic_score_gemma":0.002850129,"teacher_disagreement_score":0.003722959,"about_ca_system_score_codex":0.00025433942,"about_ca_system_score_gemma":0.00037463647,"threshold_uncertainty_score":0.007402599},"labels":[],"label_agreement":null},{"id":"W3125928972","doi":"10.1101/2021.01.25.428063","title":"NOMIS: Quantifying morphometric deviations from normality over the lifetime of the adult human brain","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institute of Mental Health; Sanofi Genzyme; Genentech; Fundamental Research Funds for the Central Universities; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Fok Ying Tung Education Foundation; Southwest University; Engineering and Physical Sciences Research Council; Natural Science Foundation of Chongqing; Eisai; National Natural Science Foundation of China; Pfizer; Biogen; BioClinica; Child Mind Institute; University of Southern California; Chongqing Postdoctoral Science Foundation; Northern California Institute for Research and Education; University of Texas at San Antonio; China Postdoctoral Science Foundation; National Center for Research Resources; F. Hoffmann-La Roche; Stavros Niarchos Foundation; Foundation for the National Institutes of Health; Leon Levy Foundation; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Sanofi; Alzheimer's Association","keywords":"Normality; Normative; Pipeline (software); Standard deviation; Quality (philosophy); Human brain; Statistics; Sample (material); Psychology; Artificial intelligence; Computer science; Mathematics; Neuroscience","score_opus":0.05474295651427723,"score_gpt":0.31098378771361856,"score_spread":0.2562408311993413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125928972","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7808368,0.0021379841,0.1494697,0.00041663312,0.00018334611,0.00035024853,0.050856143,0.007675746,0.00807326],"genre_scores_gemma":[0.9183756,0.00058155425,0.058721893,0.000100445664,0.00007806001,0.00053107843,0.019121815,0.0008429577,0.0016466617],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923813,0.00016267005,0.000058436864,0.00021722369,0.00028219508,0.000041346677],"domain_scores_gemma":[0.99631554,0.0015513408,0.0009685885,0.0005671525,0.00045910908,0.00013827298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024316101,0.00092611654,0.0005093009,0.0026912456,0.00032771894,0.0012933188,0.00070127763,0.00046633257,0.00453116],"category_scores_gemma":[0.015293825,0.00026135772,0.0006912668,0.0013253954,0.0005376988,0.00080331543,0.0013468426,0.00040100634,0.0007897425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017764521,0.00012662774,0.646768,0.0011420738,0.0018483738,0.00053083256,0.0013175574,0.022454856,0.0098562455,0.008700541,0.02982118,0.2756572],"study_design_scores_gemma":[0.0000911595,0.00065831427,0.8769811,0.00020764602,0.00049961003,0.0035444591,0.0005111184,0.052855592,0.015007289,0.021681048,0.027764462,0.0001983257],"about_ca_topic_score_codex":0.0020532277,"about_ca_topic_score_gemma":0.003916514,"teacher_disagreement_score":0.00453116,"about_ca_system_score_codex":0.00041892304,"about_ca_system_score_gemma":0.0004863312,"threshold_uncertainty_score":0.015158296},"labels":[],"label_agreement":null},{"id":"W3126252517","doi":"10.1007/s00429-020-02211-6","title":"A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Tractography; Ising model; Diffusion MRI; Statistical physics; Predictability; White matter; Criticality; Fractional anisotropy; Mathematics; Computer science; Artificial intelligence; Physics; Statistics; Magnetic resonance imaging","score_opus":0.04812751800487218,"score_gpt":0.352832356194857,"score_spread":0.3047048381899848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126252517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3536924,0.0015261943,0.63923824,0.00045942786,0.00013201045,0.00014946124,0.00031620855,0.0016313052,0.0028547328],"genre_scores_gemma":[0.7382328,0.0011283117,0.25870758,0.00006546456,0.000032525215,0.00009913545,0.00030144936,0.00037734697,0.0010553905],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996923,0.00015443716,0.000024387877,0.000044109638,0.00006407739,0.000020553343],"domain_scores_gemma":[0.9961921,0.0027782633,0.0001482833,0.000223801,0.00053185923,0.00012557473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016342106,0.0007273607,0.000610382,0.0012594686,0.00044881096,0.00087504735,0.00078513636,0.001582256,0.0008301127],"category_scores_gemma":[0.008936147,0.00032177812,0.00056027883,0.000982635,0.00033168503,0.0011029636,0.00048618054,0.00072260184,0.00019343529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072041893,0.00014985728,0.0066082063,0.0001721685,0.0002576601,0.00013046773,0.00019718216,0.903057,0.008899669,0.0055285706,0.00053502177,0.07374372],"study_design_scores_gemma":[0.000016068263,0.0000384602,0.0005571498,0.000008242845,0.000015183587,0.00003834988,0.000016658198,0.99714154,0.0012047945,0.0007693346,0.00018296299,0.0000112108555],"about_ca_topic_score_codex":0.02870868,"about_ca_topic_score_gemma":0.019801196,"teacher_disagreement_score":0.02870868,"about_ca_system_score_codex":0.0007904887,"about_ca_system_score_gemma":0.001308169,"threshold_uncertainty_score":0.05708313},"labels":[],"label_agreement":null},{"id":"W3126656652","doi":"10.1038/s41390-021-01379-9","title":"Fronto-temporal horn ratio: yet another marker of ventriculomegaly?","year":2021,"lang":"en","type":"article","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"French horn; Ventriculomegaly; Psychology; Biology; Genetics; Pregnancy; Fetus","score_opus":0.15807117622504274,"score_gpt":0.444093068563404,"score_spread":0.2860218923383613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126656652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92671037,0.02215526,0.012539004,0.007232381,0.00059998763,0.00006991061,0.0008381336,0.0004088342,0.029446164],"genre_scores_gemma":[0.9891271,0.0038758086,0.00487164,0.00047292517,0.00055125944,0.000012782827,0.00017073995,0.00003182724,0.00088587764],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996904,0.000052194697,0.00004010036,0.00006059774,0.00009660422,0.00006013861],"domain_scores_gemma":[0.9986847,0.0003752328,0.0004714373,0.00006864899,0.00020746594,0.00019241705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006282278,0.00076415436,0.0005703448,0.0018716307,0.00026613992,0.0013183985,0.0009757706,0.0012840788,0.0029524122],"category_scores_gemma":[0.0036666163,0.0002788425,0.00022578094,0.0009064103,0.0010995064,0.0019904738,0.00035608167,0.0011178278,0.00064947165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000722458,0.00013180019,0.75925654,0.00031224728,0.00025251915,0.05877234,0.00046713193,0.00058695045,0.07927944,0.004691121,0.003561879,0.09196562],"study_design_scores_gemma":[0.000057614736,0.0005229842,0.689411,0.00035200396,0.000418032,0.2607486,0.0025806131,0.004787304,0.024095936,0.008345227,0.00859064,0.00009009105],"about_ca_topic_score_codex":0.0023022264,"about_ca_topic_score_gemma":0.0023636052,"teacher_disagreement_score":0.0029524122,"about_ca_system_score_codex":0.0002994019,"about_ca_system_score_gemma":0.00049658876,"threshold_uncertainty_score":0.009876847},"labels":[],"label_agreement":null},{"id":"W3126696394","doi":"10.1177/1535759721991161","title":"Emerging Trends in Neuroimaging of Epilepsy","year":2021,"lang":"en","type":"article","venue":"Epiliepsy currents/Epilepsy currents","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Canada First Research Excellence Fund; Institute of Neurosciences, Mental Health and Addiction; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Prognostics; Medicine; Epilepsy; Brain function; Magnetic resonance imaging; Neuroscience; Artificial intelligence; Computer science; Psychiatry; Psychology; Radiology; Data mining","score_opus":0.07205264821945591,"score_gpt":0.3910501762932826,"score_spread":0.3189975280738267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126696394","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005881307,0.8837777,0.006534773,0.09224863,0.0021587275,0.000024271409,0.00025918058,0.00015501225,0.008960527],"genre_scores_gemma":[0.042657524,0.90601295,0.017063143,0.019684354,0.012124069,0.000075050375,0.00043565864,0.000060209397,0.0018870748],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980556,0.00053455005,0.00035325045,0.00040909633,0.0005171854,0.00013035856],"domain_scores_gemma":[0.9843179,0.007921789,0.0014632558,0.00050555513,0.004657865,0.0011336275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005663269,0.00058695447,0.0008544925,0.0034156328,0.0004887014,0.0032319222,0.0012312949,0.0030692562,0.005088344],"category_scores_gemma":[0.011460274,0.00034576622,0.00050386,0.0035891407,0.0030917549,0.009380171,0.0013214881,0.0038663486,0.0013254117],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028932135,0.00014705138,0.012300333,0.005694061,0.00010266095,0.00051097316,0.0005426074,0.000773868,0.0037369747,0.053194948,0.043342616,0.8793646],"study_design_scores_gemma":[0.000059069363,0.00035556147,0.036402013,0.008105746,0.00017129426,0.005685225,0.0023847,0.0032896355,0.00203055,0.10100245,0.8403942,0.00011963423],"about_ca_topic_score_codex":0.0026684313,"about_ca_topic_score_gemma":0.0056864866,"teacher_disagreement_score":0.005663269,"about_ca_system_score_codex":0.002733672,"about_ca_system_score_gemma":0.0033846244,"threshold_uncertainty_score":0.029950619},"labels":[],"label_agreement":null},{"id":"W3126779283","doi":"10.1101/2021.02.01.21250951","title":"Diffusion kurtosis imaging of white matter in bipolar disorder","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hotchkiss Brain Institute; University of Calgary; University of Toronto","funders":"Canadian Institutes of Health Research; Pfizer Canada; Pfizer","keywords":"White matter; Diffusion MRI; Kurtosis; Fractional anisotropy; Voxel; Magnetic resonance imaging; Bipolar disorder; Nuclear medicine; Tractography; Medicine; Nuclear magnetic resonance; Neuroscience; Psychology; Physics; Radiology; Mathematics; Statistics","score_opus":0.029009777133778905,"score_gpt":0.3198153474433404,"score_spread":0.2908055703095615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126779283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901866,0.0008802009,0.007684446,0.000051947976,0.000009789663,0.00001886998,0.00036062242,0.000088633016,0.000718853],"genre_scores_gemma":[0.9936799,0.00043452505,0.0053831157,0.000014708289,0.000010134478,0.000013467089,0.00023128567,0.000022045568,0.00021069165],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998746,0.000035872894,0.000019324054,0.000029894536,0.000025507412,0.000014812282],"domain_scores_gemma":[0.9996024,0.00009020479,0.00017411637,0.00003505816,0.00006685,0.000031465697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057085167,0.0005127217,0.00025895276,0.0017671755,0.00023415123,0.00048355723,0.00012382622,0.0002051381,0.0011208843],"category_scores_gemma":[0.0013207097,0.0002056812,0.0002105323,0.0005430225,0.00029064398,0.000331921,0.00031563514,0.00018224928,0.00015457725],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035503919,0.00018157829,0.4026893,0.0006406489,0.000859501,0.001954958,0.0011920291,0.009067584,0.4550602,0.0023990276,0.0013360945,0.12106863],"study_design_scores_gemma":[0.00007136347,0.00033712614,0.9521572,0.000066348846,0.00016125993,0.0031166628,0.00029203907,0.021054957,0.019050676,0.002831694,0.00080607977,0.000054501863],"about_ca_topic_score_codex":0.0020411857,"about_ca_topic_score_gemma":0.0020796482,"teacher_disagreement_score":0.0020411857,"about_ca_system_score_codex":0.00024344143,"about_ca_system_score_gemma":0.0001430116,"threshold_uncertainty_score":0.00405854},"labels":[],"label_agreement":null},{"id":"W3126805281","doi":"10.1016/j.psychres.2021.113797","title":"Diffusion Tensor Imaging Reveals White Matter Differences in Military Personnel Exposed to Trauma with and without Post-traumatic Stress Disorder","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Armed Forces; University of Toronto; SickKids Foundation; St Joseph's Health Care; Lawson Health Research Institute; McMaster University; Western University","funders":"Defence Research and Development Canada","keywords":"Diffusion MRI; White matter; Traumatic stress; Psychology; White (mutation); Clinical psychology; Military personnel; Medicine; Magnetic resonance imaging; Radiology; History; Biology","score_opus":0.07344670041803703,"score_gpt":0.3809140165962125,"score_spread":0.30746731617817546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126805281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994861,0.00008726896,0.000057652607,0.000027434351,0.0000031324182,0.000004157901,0.000050616032,0.0000016698172,0.00028196193],"genre_scores_gemma":[0.9995383,0.00009926699,0.00010320598,0.000016381906,0.0000072109906,0.0000046683613,0.00010088533,0.0000014017807,0.00012859427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998877,0.000018092012,0.000013198735,0.00002441559,0.000020180174,0.00003642057],"domain_scores_gemma":[0.99963224,0.000030418052,0.00021514704,0.000020286689,0.000033623088,0.00006839977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032719853,0.0002952897,0.00014684236,0.00085371366,0.0003560119,0.0003446555,0.00012964406,0.00030220055,0.0019542435],"category_scores_gemma":[0.001216578,0.00011314242,0.0001658372,0.0003759228,0.00031674266,0.00027453553,0.00038721543,0.0002229482,0.00027418163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011277088,0.00022818743,0.9571728,0.00008869571,0.00020160797,0.0010242277,0.0023489746,0.000105568906,0.02404336,0.00019008294,0.00037126287,0.013097455],"study_design_scores_gemma":[0.0000056476106,0.00021135564,0.9978053,0.000009085217,0.00001662701,0.0008776947,0.00053310214,0.00006764235,0.00028997063,0.000064178035,0.0001162767,0.0000030386109],"about_ca_topic_score_codex":0.0029691125,"about_ca_topic_score_gemma":0.004037535,"teacher_disagreement_score":0.0029691125,"about_ca_system_score_codex":0.00022367682,"about_ca_system_score_gemma":0.0002257168,"threshold_uncertainty_score":0.0065376163},"labels":[],"label_agreement":null},{"id":"W3127043227","doi":"10.1002/mrm.29124","title":"Characterization and correction of time‐varying eddy currents for diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Eddy current; Diffusion; Metric (unit); Diffusion MRI; Mean squared error; Pulsed field gradient; Field (mathematics); Algorithm; Computer science; Physics; Nuclear magnetic resonance; Mathematics; Statistics; Magnetic resonance imaging; Engineering","score_opus":0.041512890690050215,"score_gpt":0.3459751873676657,"score_spread":0.3044622966776155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127043227","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13044596,0.0010046308,0.8674764,0.00011690569,0.000036086134,0.00009857328,0.00007294329,0.00047528176,0.00027321212],"genre_scores_gemma":[0.32000518,0.00081089424,0.6779587,0.000060984592,0.000025710426,0.000085829925,0.000221869,0.00013943773,0.00069140596],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996364,0.00007800016,0.00002796802,0.00007902496,0.00016038834,0.000018178149],"domain_scores_gemma":[0.9985012,0.00053432886,0.0002295778,0.00020645112,0.00048153778,0.00004702069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013372705,0.00086539,0.0004424871,0.00055000104,0.00016868122,0.00068473496,0.000645925,0.00079796993,0.00055733876],"category_scores_gemma":[0.0060183816,0.0002675481,0.00034628512,0.00027139488,0.00036336467,0.0007776683,0.00039284892,0.00051809946,0.00029491607],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002441973,0.00009077873,0.0065703574,0.00041881454,0.000099436955,0.00020340097,0.00011817499,0.014354454,0.78207904,0.000794823,0.00032794016,0.19469857],"study_design_scores_gemma":[0.000059259768,0.0003996033,0.016142951,0.00004945147,0.00011423468,0.0017160428,0.00005061714,0.25160512,0.7252715,0.000970444,0.0035634378,0.000057298228],"about_ca_topic_score_codex":0.00091567263,"about_ca_topic_score_gemma":0.0018257517,"teacher_disagreement_score":0.0013372705,"about_ca_system_score_codex":0.00028126474,"about_ca_system_score_gemma":0.0007340736,"threshold_uncertainty_score":0.00707227},"labels":[],"label_agreement":null},{"id":"W3127196273","doi":"10.21203/rs.3.rs-151934/v1","title":"Regional cerebral blood flow decline can predict atrophy in Alzheimer’s disease spectrum","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cerebral blood flow; Atrophy; Dementia; Cardiology; Psychology; Medicine; Internal medicine; Neuroscience; Neurodegeneration; Alzheimer's disease; Biomarker; Cerebral atrophy; Pathology; Disease; Biology","score_opus":0.1582735723650386,"score_gpt":0.4389821395994455,"score_spread":0.28070856723440685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127196273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99807835,0.00040131857,0.00029426493,0.000050064813,0.0000130687085,0.000009858834,0.00022902321,0.000016495616,0.0009076306],"genre_scores_gemma":[0.9992003,0.00007939363,0.00023077764,0.000017623648,0.000014042811,0.000007059318,0.00019262695,0.0000024054957,0.00025577692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999006,0.000028355322,0.000009516666,0.00002686408,0.000018986204,0.000015706377],"domain_scores_gemma":[0.99947375,0.00015986782,0.00013970034,0.00003053241,0.00007917306,0.00011686712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005277759,0.0003601587,0.00028439835,0.0012123084,0.00015406076,0.00032369312,0.00016489241,0.0003892853,0.0021304109],"category_scores_gemma":[0.0012151131,0.00007887683,0.00014735531,0.00036261807,0.00018563027,0.00025620422,0.00021027829,0.00033080933,0.00037238433],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013890216,0.00021978647,0.9840134,0.00003477905,0.00008380604,0.00026640057,0.00009539911,0.00020777076,0.005333283,0.000066987755,0.00042239242,0.007867048],"study_design_scores_gemma":[0.000010206763,0.0001808197,0.9979559,0.000006967807,0.000024869976,0.0003303841,0.00007265075,0.0005595382,0.00050827465,0.00020434818,0.00014272604,0.0000032870648],"about_ca_topic_score_codex":0.0010858683,"about_ca_topic_score_gemma":0.0008344432,"teacher_disagreement_score":0.0021304109,"about_ca_system_score_codex":0.000121850455,"about_ca_system_score_gemma":0.00008271268,"threshold_uncertainty_score":0.007126987},"labels":[],"label_agreement":null},{"id":"W3127414577","doi":"10.1093/neuonc/noab017","title":"Longitudinal change in fine motor skills after brain radiotherapy and in vivo imaging biomarkers associated with decline","year":2021,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; University of California, San Diego; National Cancer Institute; National Institutes of Health; Centre Technologique des Résidus Industriels; American Cancer Society; U.S. Department of Veterans Affairs; Moores Cancer Center, UC San Diego Health; Georgia Clinical and Translational Science Alliance","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Medicine; Nuclear medicine; Motor cortex; Precentral gyrus; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.03285513162950509,"score_gpt":0.3542082188403241,"score_spread":0.321353087210819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127414577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99908495,0.000278363,0.00011714843,0.00001945938,0.0000019619326,0.0000137151155,0.00027855713,0.0000073248502,0.00019866046],"genre_scores_gemma":[0.9992113,0.00007065131,0.00011646565,0.000012556369,0.00000360351,0.00001583619,0.00038260015,0.000001970766,0.00018496551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998406,0.000037441132,0.0000148269,0.000050341197,0.00003004987,0.000026802],"domain_scores_gemma":[0.9990615,0.00013070976,0.00051569723,0.00007642266,0.000115014285,0.00010062165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006833063,0.000257895,0.00034543723,0.00030558804,0.00016688749,0.00034043452,0.00020906281,0.00029001676,0.00088606746],"category_scores_gemma":[0.0016489397,0.000105878804,0.00026376641,0.00030978952,0.00017575864,0.00026141055,0.00020623322,0.00037598802,0.00018433688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002010359,0.0001913457,0.9847558,0.000033490214,0.00019287805,0.000050543887,0.00005841666,0.00042677732,0.0032641585,0.0000126701925,0.00010445844,0.008899038],"study_design_scores_gemma":[0.000017107675,0.00086340244,0.9980205,0.0000031508212,0.000040883195,0.00011129581,0.000015764297,0.00016013213,0.00064143346,0.00001847073,0.00010565158,0.0000021539133],"about_ca_topic_score_codex":0.0019225085,"about_ca_topic_score_gemma":0.002313498,"teacher_disagreement_score":0.0019225085,"about_ca_system_score_codex":0.00029629646,"about_ca_system_score_gemma":0.00023224995,"threshold_uncertainty_score":0.0038226247},"labels":[],"label_agreement":null},{"id":"W3127794038","doi":"10.1007/s10143-021-01489-2","title":"The corticotegmental connectivity as an integral component of the descending extrapyramidal pathway: novel and direct structural evidence stemming from focused fiber dissections","year":2021,"lang":"en","type":"article","venue":"Neurosurgical Review","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Neuroscience; Anatomy; Internal capsule; White matter; Supplementary motor area; Medicine; Primary motor cortex; Motor cortex; Psychology; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.1187212393359757,"score_gpt":0.380482071698672,"score_spread":0.2617608323626963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127794038","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21054323,0.691667,0.06427163,0.0052691055,0.00065959577,0.00009447539,0.00049644004,0.00014516547,0.026853312],"genre_scores_gemma":[0.45263445,0.52053946,0.022128103,0.000626976,0.0009038504,0.00005359323,0.00032841842,0.000028640465,0.0027565605],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999949,0.000007116709,0.0000038984267,0.000019167108,0.000013243145,0.0000075498774],"domain_scores_gemma":[0.9998272,0.00006962419,0.00003861417,0.000011491196,0.000041091324,0.0000119410715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023658744,0.00047876206,0.00032032974,0.00077136635,0.00023085532,0.0007128949,0.0004600063,0.00044857914,0.0012310839],"category_scores_gemma":[0.00047408248,0.00014531297,0.00026569475,0.0006996905,0.0010127308,0.001197542,0.00036241487,0.00082698814,0.00019184955],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006790021,0.0001143095,0.0080335485,0.0059986254,0.00061766885,0.006889569,0.00051609514,0.001880237,0.31981108,0.03668757,0.0031933773,0.615579],"study_design_scores_gemma":[0.00023844847,0.0021271254,0.2748208,0.003871525,0.0029847277,0.061265077,0.0016199395,0.009138885,0.2382212,0.1831835,0.22215341,0.00037534806],"about_ca_topic_score_codex":0.0019246927,"about_ca_topic_score_gemma":0.002455127,"teacher_disagreement_score":0.0019246927,"about_ca_system_score_codex":0.0004665925,"about_ca_system_score_gemma":0.0006937258,"threshold_uncertainty_score":0.004118383},"labels":[],"label_agreement":null},{"id":"W3128247838","doi":"10.1038/s41398-021-01222-z","title":"Integrity of the uncinate fasciculus is associated with the onset of bipolar disorder: a 6-year followed-up study","year":2021,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Brain and Cognition Discovery Foundation; University Health Network","funders":"National Natural Science Foundation of China","keywords":"Bipolar disorder; Uncinate fasciculus; Psychology; Psychiatry; Fasciculus; Schizophrenia (object-oriented programming); Research integrity; Medicine; Clinical psychology; Diffusion MRI; Magnetic resonance imaging; Cognition","score_opus":0.03653144571639505,"score_gpt":0.3266151584246547,"score_spread":0.29008371270825967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128247838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994373,0.00017283701,0.00004312716,0.000016095906,0.0000043524205,0.0000053847525,0.00014359264,0.0000017005601,0.00017563297],"genre_scores_gemma":[0.99920803,0.00012357059,0.000062636675,0.00001557906,0.0000072998996,0.0000055677947,0.0003360233,0.0000016192887,0.00023965772],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998118,0.000027037462,0.000021065212,0.00006954203,0.00003424074,0.000036347683],"domain_scores_gemma":[0.99939704,0.0000419987,0.00023149856,0.00005010434,0.00012909768,0.00015020261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003293071,0.00035132925,0.0004357591,0.0007539184,0.0008500172,0.00053008896,0.00024154074,0.00062434387,0.00087722164],"category_scores_gemma":[0.0007946179,0.00035312504,0.0005382441,0.0005979084,0.00021610492,0.00041718173,0.00039104183,0.0007132093,0.00025753258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023684057,0.000064014894,0.9976209,0.000005349152,0.000056867004,0.00038413133,0.00015236902,0.000017000106,0.00043023663,0.0000052729856,0.000047835874,0.0009793116],"study_design_scores_gemma":[0.00000387722,0.00009485286,0.9992601,0.0000028505735,0.000029048357,0.00038062208,0.000085693806,0.000039213955,0.000029655259,0.000007952338,0.00006388576,0.00000236153],"about_ca_topic_score_codex":0.0066106124,"about_ca_topic_score_gemma":0.00800234,"teacher_disagreement_score":0.0066106124,"about_ca_system_score_codex":0.00027946846,"about_ca_system_score_gemma":0.00018496455,"threshold_uncertainty_score":0.013144255},"labels":[],"label_agreement":null},{"id":"W3128346820","doi":"10.1016/j.neurobiolaging.2020.12.020","title":"Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture","year":2021,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; White matter; Tensor (intrinsic definition); Computer science; Nuclear magnetic resonance; Neuroscience; Mathematics; Physics; Psychology; Medicine; Magnetic resonance imaging; Optics; Pure mathematics; Radiology","score_opus":0.04822668176364864,"score_gpt":0.3458820593126448,"score_spread":0.2976553775489962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128346820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9763566,0.0006135185,0.021598004,0.00013339966,0.00001816913,0.000011372803,0.0005943568,0.000113550464,0.00056102336],"genre_scores_gemma":[0.98821646,0.00056148495,0.009928488,0.000022108094,0.00001619582,0.000010667281,0.000379024,0.000038300077,0.00082724576],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999516,0.000008348801,0.0000053984268,0.000014027248,0.0000107156575,0.000009924398],"domain_scores_gemma":[0.99954826,0.00006954014,0.00017267183,0.00007947537,0.00008420523,0.000045806435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039802465,0.00031611545,0.00018208183,0.00095999934,0.00014250507,0.000419353,0.00014248159,0.00030081047,0.0009977606],"category_scores_gemma":[0.001119447,0.00017689081,0.0001672593,0.0006152121,0.00025420633,0.0007880128,0.00026141453,0.00033179254,0.00017339924],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011975635,0.00017005994,0.076255865,0.00021294138,0.00021658411,0.00083347975,0.00064830674,0.006859664,0.7664312,0.003971023,0.0025552136,0.14064808],"study_design_scores_gemma":[0.000043363805,0.00046030432,0.8021763,0.000072792245,0.00020833114,0.004056212,0.00045100172,0.08413708,0.09029628,0.01417462,0.0038117142,0.0001120489],"about_ca_topic_score_codex":0.0013221634,"about_ca_topic_score_gemma":0.0022808178,"teacher_disagreement_score":0.0013221634,"about_ca_system_score_codex":0.0001413457,"about_ca_system_score_gemma":0.00025860782,"threshold_uncertainty_score":0.0033378005},"labels":[],"label_agreement":null},{"id":"W3128914311","doi":"10.1038/s41598-021-82187-3","title":"Elucidating the complex organization of neural micro-domains in the locust Schistocerca gregaria using dMRI","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Desert locust; Locust; Kurtosis; Schistocerca; Diffusion MRI; Fractional anisotropy; Computer science; Neuroscience; Magnetic resonance imaging; Artificial intelligence; Neuroimaging; Functional magnetic resonance imaging; Biology; Biological system; Pattern recognition (psychology); Nuclear magnetic resonance; Physics; Medicine; Mathematics; Ecology; Radiology","score_opus":0.08739159166132505,"score_gpt":0.35022054871930064,"score_spread":0.2628289570579756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128914311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.968649,0.0012308196,0.027794423,0.00007203262,0.0000063843995,0.000033034372,0.00053663534,0.00017756877,0.0015001267],"genre_scores_gemma":[0.9593963,0.0008004394,0.03821115,0.000044967233,0.000005490086,0.000032551096,0.0004847448,0.000037614693,0.0009868297],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99996495,0.000004263239,0.000002542545,0.000013799308,0.000008239487,0.000006308548],"domain_scores_gemma":[0.9998876,0.000018056675,0.000049083505,0.000010870616,0.00001857913,0.000015826643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000107158725,0.00021288553,0.00013392937,0.00065948605,0.00015595692,0.00025018962,0.00013717466,0.0002620661,0.0005536555],"category_scores_gemma":[0.00019832107,0.00017921242,0.00013801607,0.00025303572,0.00026055606,0.00026029386,0.0002403606,0.00025953262,0.00016460712],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022539312,0.000006424126,0.0025087749,0.000058574584,0.000010999144,0.000105188294,0.000063073414,0.0008714767,0.9913526,0.0001442745,0.000043144988,0.004812885],"study_design_scores_gemma":[0.000019543984,0.0002942394,0.6434775,0.00007985936,0.000098182325,0.0027836317,0.00048691116,0.055239636,0.2908519,0.0013686706,0.005231911,0.000067946865],"about_ca_topic_score_codex":0.002733008,"about_ca_topic_score_gemma":0.007909585,"teacher_disagreement_score":0.002733008,"about_ca_system_score_codex":0.00018627566,"about_ca_system_score_gemma":0.00014969574,"threshold_uncertainty_score":0.0054341555},"labels":[],"label_agreement":null},{"id":"W3129666823","doi":"10.1089/brain.2020.0939","title":"Impaired Structural Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment: A Study Based on Probabilistic Tractography","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Diffusion MRI; Fractional anisotropy; Connectome; Connectomics; Parkinson's disease; Neuroscience; Psychology; White matter; Magnetic resonance imaging; Artificial intelligence; Pathology; Medicine; Functional connectivity; Disease; Computer science; Radiology","score_opus":0.03133652534068452,"score_gpt":0.3133172704049345,"score_spread":0.28198074506424997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129666823","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957925,0.000090684,0.000097045646,0.0000115673265,0.0000010555342,0.000008904181,0.000041367028,0.0000018540668,0.00016823821],"genre_scores_gemma":[0.9997948,0.000029924751,0.00007666692,0.0000053690565,0.000003871127,0.000005314608,0.000059166196,0.000001038611,0.00002392905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998167,0.00004424473,0.000022749662,0.000059277856,0.000034369514,0.000022686356],"domain_scores_gemma":[0.9989944,0.00033025167,0.00037220857,0.00009184139,0.0000906932,0.0001206008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000541059,0.00037899974,0.00034793542,0.0012027469,0.0005244626,0.00046357958,0.0002424031,0.0005141586,0.0013103456],"category_scores_gemma":[0.002667439,0.00024682612,0.00035699224,0.00063246104,0.0004986288,0.0005173087,0.0003623898,0.00024995452,0.00019824145],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078379,0.0001420597,0.99160427,0.000039972983,0.00018166435,0.000940257,0.00060157455,0.00018604424,0.0013198622,0.00006712517,0.0000683926,0.0040649697],"study_design_scores_gemma":[0.000028099894,0.00029356225,0.997071,0.0000052745245,0.00005367438,0.0015683606,0.00013936755,0.00056046713,0.000085343214,0.000095024734,0.00009499184,0.000004771174],"about_ca_topic_score_codex":0.0033674194,"about_ca_topic_score_gemma":0.0031396882,"teacher_disagreement_score":0.0033674194,"about_ca_system_score_codex":0.00032468463,"about_ca_system_score_gemma":0.00022800046,"threshold_uncertainty_score":0.006695628},"labels":[],"label_agreement":null},{"id":"W3129895777","doi":"10.1007/s00429-020-02190-8","title":"Mapping the living mouse brain neural architecture: strain-specific patterns of brain structural and functional connectivity","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"National Institute on Alcohol Abuse and Alcoholism; Erasmus+","keywords":"Neuroscience; Corpus callosum; Splenium; Forebrain; Connectome; Biology; Diffusion MRI; Brain mapping; Resting state fMRI; Human Connectome Project; Functional magnetic resonance imaging; Brain morphometry; Psychology; Functional connectivity; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.04202876236868999,"score_gpt":0.2736536775241867,"score_spread":0.23162491515549669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129895777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97357607,0.00075526023,0.023130273,0.00011065377,0.000036747886,0.000022888396,0.00078047905,0.00021416311,0.0013733923],"genre_scores_gemma":[0.98131794,0.0009112978,0.012714422,0.00010159559,0.000013749232,0.00010665734,0.00067504606,0.00021096255,0.0039482154],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99986446,0.00001445144,0.000009125046,0.0000613821,0.000031388907,0.00001911892],"domain_scores_gemma":[0.99972004,0.000052240466,0.000110166635,0.000041821037,0.000033286848,0.00004247071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002831708,0.00043794746,0.00025067027,0.000974547,0.00020137285,0.00048096405,0.00035384062,0.00039837463,0.0016041151],"category_scores_gemma":[0.00043515407,0.00029512617,0.000287526,0.00040952122,0.0006447598,0.000489285,0.00029398434,0.00076691294,0.0001706546],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085946434,0.000024241057,0.0010551921,0.000021963071,0.000020004643,0.000038475766,0.000027486325,0.00020638706,0.9958047,0.00025742667,0.00006192946,0.0023961782],"study_design_scores_gemma":[0.00003476627,0.00053696625,0.10171671,0.00002980241,0.00017175473,0.0010139092,0.00018901851,0.004858218,0.888447,0.0010824526,0.0018845891,0.000034802797],"about_ca_topic_score_codex":0.0013562784,"about_ca_topic_score_gemma":0.0037134767,"teacher_disagreement_score":0.0016041151,"about_ca_system_score_codex":0.00024936683,"about_ca_system_score_gemma":0.00017695558,"threshold_uncertainty_score":0.005366266},"labels":[],"label_agreement":null},{"id":"W3130159341","doi":"10.5167/uzh-44356","title":"Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: an update","year":2010,"lang":"en","type":"article","venue":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Frontotemporal lobar degeneration; Nosology; Nomenclature; Frontotemporal dementia; Degeneration (medical); Neuroscience; Medicine; Psychology; Pathology; Dementia; Disease; Biology; Taxonomy (biology)","score_opus":0.0933618304806381,"score_gpt":0.3342238781920364,"score_spread":0.2408620477113983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130159341","genre_codex":"review","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058488157,0.94467115,0.013203583,0.014172552,0.0128037855,0.000103599836,0.0004903305,0.0004750514,0.008231096],"genre_scores_gemma":[0.025633298,0.8806762,0.058436755,0.012630757,0.012921116,0.00021811225,0.0026904952,0.00024397662,0.006549268],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99738246,0.00044980305,0.0010201847,0.00037952064,0.00058765325,0.00018030281],"domain_scores_gemma":[0.99065316,0.0028899813,0.0010563766,0.00050693937,0.0044668284,0.00042678113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008628708,0.002026334,0.0046431967,0.008455296,0.0016465676,0.0035399927,0.006462029,0.0031568815,0.0029467356],"category_scores_gemma":[0.011021016,0.0007596553,0.0019274381,0.0053760572,0.0030097268,0.0072041275,0.0018772216,0.0047839233,0.0031166642],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001917368,0.00018079883,0.0064669535,0.0031869367,0.00019192159,0.0019089216,0.00053840986,0.00040439377,0.0019420806,0.004212273,0.13474493,0.84603065],"study_design_scores_gemma":[0.00020665987,0.00025481684,0.009936873,0.007819549,0.0008918307,0.032465026,0.0014030166,0.0010754582,0.001039682,0.009462842,0.93522143,0.00022271542],"about_ca_topic_score_codex":0.0088055795,"about_ca_topic_score_gemma":0.018164048,"teacher_disagreement_score":0.0088055795,"about_ca_system_score_codex":0.0024812804,"about_ca_system_score_gemma":0.0051161926,"threshold_uncertainty_score":0.045633554},"labels":[],"label_agreement":null},{"id":"W3130233450","doi":"10.1016/j.nicl.2021.102587","title":"Disruption of brainstem monoaminergic fibre tracts in multiple sclerosis as a putative mechanism for cognitive fatigue: a fixel-based analysis","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Wellcome Trust","keywords":"Monoaminergic; Locus coeruleus; Brainstem; Neuroscience; Ventral tegmental area; White matter; Prefrontal cortex; Diffusion MRI; Dopaminergic; Serotonergic; Psychology; Anatomy; Biology; Dopamine; Medicine; Central nervous system; Internal medicine; Serotonin; Cognition; Magnetic resonance imaging","score_opus":0.3259403742709406,"score_gpt":0.4623823037733691,"score_spread":0.1364419295024285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130233450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9903814,0.0005462469,0.008546101,0.000011891915,0.000002475491,0.000018190438,0.00018485966,0.000034835415,0.00027395991],"genre_scores_gemma":[0.99298614,0.00024221031,0.0060030785,0.0000056616814,0.0000039769543,0.000019344023,0.00027098163,0.000010580118,0.00045799292],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999424,0.000009928492,0.0000030961094,0.000016654834,0.000016259733,0.000011721136],"domain_scores_gemma":[0.999866,0.00004491439,0.00003270076,0.000015386171,0.000027325661,0.000013743783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029632216,0.00034639853,0.00023882093,0.0012917805,0.0002055669,0.00029179844,0.00016813174,0.00025525308,0.0011452312],"category_scores_gemma":[0.00034508193,0.00008267207,0.0002777888,0.00042506325,0.00028611117,0.00019913547,0.0003110025,0.00012823567,0.00014616847],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025256046,0.00010266593,0.15863758,0.00041565314,0.0005788261,0.0014548189,0.00061208033,0.009721718,0.7189618,0.0009176811,0.00021215742,0.10585936],"study_design_scores_gemma":[0.00002223487,0.000642493,0.9179951,0.00004030118,0.0002460877,0.0032551736,0.00037071022,0.03320995,0.042196605,0.0007110725,0.0012713909,0.00003879162],"about_ca_topic_score_codex":0.0032589145,"about_ca_topic_score_gemma":0.004128901,"teacher_disagreement_score":0.0032589145,"about_ca_system_score_codex":0.00025451067,"about_ca_system_score_gemma":0.00015712251,"threshold_uncertainty_score":0.006479919},"labels":[],"label_agreement":null},{"id":"W3130324448","doi":"10.1101/2021.02.13.431081","title":"Characterizing white matter alterations in drug-naïve de novo Parkinson’s disease with diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Canadian Institutes of Health Research; Sanofi Genzyme; Genentech; H. Lundbeck A/S; Teva Pharmaceutical Industries; Sanofi; Biogen; GlaxoSmithKline; Servier; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; Michael J. Fox Foundation for Parkinson's Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Disease; Neuroscience; Parkinson's disease; Medicine; Laterality; Psychology; Neuroimaging; Magnetic resonance imaging; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.018291322791883106,"score_gpt":0.25894241843590715,"score_spread":0.24065109564402404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130324448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976357,0.0005125761,0.00088515936,0.00005157754,0.0000099187655,0.000021307736,0.00027030805,0.000016571723,0.00059695006],"genre_scores_gemma":[0.9979869,0.00028353801,0.00089942286,0.000041066334,0.000010763516,0.000009571561,0.0003622357,0.0000076031906,0.00039889498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998448,0.0000326268,0.000022018954,0.00005928099,0.00002715881,0.000014067276],"domain_scores_gemma":[0.99942684,0.00014068848,0.0001657924,0.00008614651,0.00010773112,0.00007281996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006234581,0.0003249463,0.00032003608,0.00075726665,0.00029942417,0.00046189615,0.00018245722,0.00033450365,0.0010291105],"category_scores_gemma":[0.0012043827,0.0001727698,0.00017846248,0.00024012766,0.00031537705,0.00034192327,0.00027708148,0.00021846025,0.00025568297],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030291348,0.0004278229,0.78049266,0.00023190092,0.00042009196,0.010925117,0.00087807176,0.00054609124,0.16997811,0.00034718294,0.0009763384,0.03174741],"study_design_scores_gemma":[0.00004029979,0.00072608487,0.9716583,0.000029904568,0.00012401248,0.012506584,0.00024380937,0.001231789,0.011116687,0.00041002152,0.0018937482,0.000018794963],"about_ca_topic_score_codex":0.0011419648,"about_ca_topic_score_gemma":0.0020534084,"teacher_disagreement_score":0.0011419648,"about_ca_system_score_codex":0.00019330753,"about_ca_system_score_gemma":0.00014727341,"threshold_uncertainty_score":0.0034427047},"labels":[],"label_agreement":null},{"id":"W3130351912","doi":"10.1007/978-3-030-56215-1_7","title":"Challenges for Tractogram Filtering","year":2021,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; VINNOVA; National Institutes of Health; Université de Sherbrooke","keywords":"Tractography; Perspective (graphical); Computer science; Streamlines, streaklines, and pathlines; Field (mathematics); Artificial intelligence; Diffusion MRI; Mathematics; Engineering; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.24558234345467547,"score_gpt":0.4255824634097051,"score_spread":0.18000011995502965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130351912","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009980612,0.08768853,0.8163472,0.032185286,0.00526916,0.000049515555,0.0004369093,0.002304413,0.054720894],"genre_scores_gemma":[0.022784665,0.13231811,0.68145305,0.007980452,0.0089462865,0.00021764483,0.0009734199,0.0033051658,0.14202124],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988703,0.00025543437,0.00006550906,0.00017827991,0.0005962158,0.000034221153],"domain_scores_gemma":[0.99437755,0.0038505525,0.00011288132,0.0004960139,0.0010381486,0.00012478758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029511843,0.0010251137,0.0009197903,0.0017490442,0.0007312699,0.0048616603,0.0017779481,0.002624551,0.018201388],"category_scores_gemma":[0.009241941,0.0005639274,0.00087253295,0.0021007953,0.0023336445,0.0056562223,0.0017177614,0.005275303,0.017146643],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027968454,0.000017621021,0.00012983408,0.0006962968,0.00003659436,0.00023962634,0.00026051086,0.004667397,0.0020450368,0.3619077,0.17059737,0.45937413],"study_design_scores_gemma":[0.0000065908766,0.000012646876,0.00014711478,0.00040039368,0.0000128781585,0.0007033235,0.00007372093,0.012528953,0.0014385354,0.32209545,0.66254854,0.000031854972],"about_ca_topic_score_codex":0.0017134954,"about_ca_topic_score_gemma":0.0018628654,"teacher_disagreement_score":0.018201388,"about_ca_system_score_codex":0.0016063451,"about_ca_system_score_gemma":0.0014830176,"threshold_uncertainty_score":0.06088966},"labels":[],"label_agreement":null},{"id":"W3131390801","doi":"10.1101/2021.02.19.432024","title":"Structural connectome fingerprinting and age prediction in pediatric development: assessing voxel- and surface-based white matter connectivity","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Connectome; Voxel; Connectomics; Computer science; Tractography; White matter; Human Connectome Project; Artificial intelligence; Pattern recognition (psychology); Representation (politics); Functional connectivity; Neuroscience; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.031631753544426267,"score_gpt":0.27295943503408027,"score_spread":0.241327681489654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131390801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9167573,0.00057510776,0.07734934,0.00019113018,0.00005457245,0.00006444929,0.00260908,0.000476897,0.0019221654],"genre_scores_gemma":[0.95624113,0.00021769683,0.041518938,0.000040995208,0.000018077475,0.00009673698,0.0010339168,0.00017828697,0.00065421226],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988625,0.0003375703,0.00007268001,0.00041526448,0.00024146744,0.000070545466],"domain_scores_gemma":[0.9933689,0.002580494,0.0013444733,0.0012537343,0.0011609527,0.00029130589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003475985,0.0006588356,0.0003938997,0.001725829,0.0003151342,0.0011553784,0.00059966586,0.00056827575,0.0023497015],"category_scores_gemma":[0.013017126,0.00027157014,0.0004951141,0.0009922585,0.0006814373,0.0008501565,0.0009067174,0.0009561285,0.00054830074],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065591186,0.00014070768,0.80026776,0.0003651556,0.000798785,0.0004131422,0.0012313887,0.009415317,0.048197575,0.0027087037,0.002210844,0.13359463],"study_design_scores_gemma":[0.0000260516,0.00048876874,0.9195422,0.00013811507,0.00023781807,0.0016913643,0.00045112384,0.029883767,0.039550934,0.0048169256,0.0031062793,0.00006677846],"about_ca_topic_score_codex":0.002819899,"about_ca_topic_score_gemma":0.0053076264,"teacher_disagreement_score":0.003475985,"about_ca_system_score_codex":0.0002568029,"about_ca_system_score_gemma":0.0006195924,"threshold_uncertainty_score":0.018382967},"labels":[],"label_agreement":null},{"id":"W3132247007","doi":"10.1089/neur.2020.0035","title":"Changes in White Matter of the Cervical Spinal Cord after a Single Season of Collegiate Football","year":2021,"lang":"en","type":"article","venue":"Neurotrauma Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Spinal cord; Diffusion MRI; Concussion; Spinal cord injury; Medicine; Poison control; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.06885494946166848,"score_gpt":0.3379647180896366,"score_spread":0.2691097686279681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132247007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995957,0.00006309693,0.000040568317,0.000011683005,0.0000036920035,0.000017565133,0.00006197326,0.0000028196914,0.00020280521],"genre_scores_gemma":[0.9988398,0.00008635938,0.00006506718,0.000028550501,0.000009135667,0.000024237615,0.00023186869,0.0000014415106,0.000713521],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980694,0.000014610048,0.000011120188,0.000055632183,0.00004855802,0.00006320248],"domain_scores_gemma":[0.9993224,0.000037930895,0.0002571748,0.000028417735,0.00016050042,0.0001936014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019301486,0.00036131975,0.00040024385,0.0007697828,0.0005690801,0.00029990898,0.00023970856,0.0006355843,0.0014187997],"category_scores_gemma":[0.0008350048,0.00022157562,0.00023260718,0.00033682483,0.00031086468,0.00018023101,0.00045468137,0.00033472505,0.0002552514],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004153293,0.0015492735,0.7303749,0.00023194421,0.0003711272,0.005995404,0.001735469,0.0003568568,0.23005119,0.00003183992,0.00043985236,0.024708875],"study_design_scores_gemma":[0.0000028184306,0.0006359424,0.9983487,0.0000039786332,0.0000055127703,0.0002783532,0.00011748912,0.000029997047,0.00052120915,0.000003956894,0.00004942853,0.0000026950756],"about_ca_topic_score_codex":0.018441612,"about_ca_topic_score_gemma":0.039898746,"teacher_disagreement_score":0.018441612,"about_ca_system_score_codex":0.00038938684,"about_ca_system_score_gemma":0.00037856714,"threshold_uncertainty_score":0.03666854},"labels":[],"label_agreement":null},{"id":"W3132513078","doi":"10.1101/2021.02.24.432740","title":"Evaluating the reliability of human brain white matter tractometry","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Washington Research Foundation; Alfred P. Sloan Foundation; University of Washington; McDonnell Center for Systems Neuroscience; Gordon and Betty Moore Foundation","keywords":"Human Connectome Project; Reliability (semiconductor); Computer science; Robustness (evolution); White matter; Reproducibility; Neuroimaging; Reliability engineering; Psychology; Data science; Functional connectivity; Statistics; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.07024448435956597,"score_gpt":0.366954333194649,"score_spread":0.296709848835083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132513078","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44029242,0.0050441767,0.5389327,0.00104368,0.0006463599,0.0005233853,0.0034868836,0.0025542646,0.0074762255],"genre_scores_gemma":[0.89987993,0.000948602,0.093203075,0.0002442038,0.00020122345,0.0003100796,0.0029851466,0.0013215366,0.00090614054],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9630833,0.017738497,0.004318234,0.0070673837,0.007121103,0.0006714776],"domain_scores_gemma":[0.7851026,0.121867195,0.018731842,0.041870914,0.030913023,0.0015143546],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.060581964,0.001389291,0.0011514566,0.0045303022,0.0013442789,0.003603245,0.0015527863,0.0021690126,0.0020613002],"category_scores_gemma":[0.26579374,0.0009598735,0.0016228333,0.0036297005,0.004459982,0.0027746193,0.0032243333,0.0012928761,0.0017038106],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024538925,0.00028848276,0.6085231,0.0032553596,0.0066208113,0.00067934766,0.007910385,0.065914094,0.03003559,0.013287077,0.010231264,0.25080064],"study_design_scores_gemma":[0.0003224434,0.0014191733,0.6341815,0.0015666313,0.0021614924,0.0033164383,0.0021903997,0.19596376,0.0451805,0.07901664,0.034085155,0.00059585855],"about_ca_topic_score_codex":0.003976062,"about_ca_topic_score_gemma":0.0037974885,"teacher_disagreement_score":0.939418,"about_ca_system_score_codex":0.0007044724,"about_ca_system_score_gemma":0.0015776398,"threshold_uncertainty_score":0.3203919},"labels":[],"label_agreement":null},{"id":"W3133182125","doi":"10.3389/fnhum.2021.641616","title":"Stable Anatomy Detection in Multimodal Imaging Through Sparse Group Regularization: A Comparative Study of Iron Accumulation in the Aging Brain","year":2021,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; McGill University; University of Alberta","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Interpretability; Neuroimaging; Lasso (programming language); Modalities; Regularization (linguistics); Voxel; Artificial intelligence; Generalizability theory; Computer science; Pattern recognition (psychology); Machine learning; Mathematics; Psychology; Neuroscience; Statistics","score_opus":0.09828210427483391,"score_gpt":0.40152863449063597,"score_spread":0.30324653021580206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133182125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88255084,0.0013903743,0.11491569,0.00032844988,0.000015111973,0.000035101555,0.0001268565,0.00015719728,0.0004803429],"genre_scores_gemma":[0.95982045,0.0003595427,0.039086405,0.000043308723,0.000042306205,0.000024672236,0.00019497822,0.000054756125,0.00037359295],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995896,0.00021082426,0.000014206047,0.000107349166,0.00005121359,0.000026853599],"domain_scores_gemma":[0.9986733,0.00068987807,0.00022288946,0.00021106192,0.00013521481,0.00006767214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030237194,0.00049491075,0.0005450519,0.0012153763,0.00021685584,0.0004648622,0.0004028952,0.0006275552,0.0004935123],"category_scores_gemma":[0.00536821,0.00017563936,0.00066146196,0.00052794995,0.00067556946,0.00061171304,0.00051865855,0.0004499176,0.00011500354],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034314422,0.0007570333,0.09581872,0.0008722965,0.0022996971,0.0013559695,0.0027686702,0.16050552,0.23747939,0.0063685696,0.0025383048,0.48580447],"study_design_scores_gemma":[0.00012823798,0.0013681424,0.12757772,0.00006734576,0.00060955225,0.0013893921,0.0005522797,0.8148645,0.03568928,0.015059206,0.0025944405,0.00009990499],"about_ca_topic_score_codex":0.0017502585,"about_ca_topic_score_gemma":0.0017492356,"teacher_disagreement_score":0.0030237194,"about_ca_system_score_codex":0.00024238694,"about_ca_system_score_gemma":0.00031735867,"threshold_uncertainty_score":0.015991092},"labels":[],"label_agreement":null},{"id":"W3133319420","doi":"10.1002/cjs.11588","title":"A Bayesian latent spatial model for mapping the cortical signature of progression to Alzheimer's disease","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Neuroimaging; Magnetic resonance imaging; Dementia; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Bayesian probability; Atrophy; Statistical power; Disease; Computer science; Medicine; Psychology; Artificial intelligence; Pathology; Radiology; Mathematics","score_opus":0.10094646596468872,"score_gpt":0.34908440290176074,"score_spread":0.24813793693707203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133319420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048302382,0.00045891534,0.9486282,0.0006611567,0.000043140695,0.000068011934,0.00071619486,0.00029885353,0.00082317565],"genre_scores_gemma":[0.7740028,0.000962035,0.21657784,0.0002523444,0.00017389137,0.00051672984,0.002149331,0.00015141262,0.0052136206],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980082,0.0011636287,0.00006799608,0.00039463438,0.00020322505,0.0001623591],"domain_scores_gemma":[0.99224246,0.005780759,0.0007197396,0.00051520386,0.000542501,0.00019940335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006562726,0.00085313676,0.0012743135,0.0016349218,0.0006860312,0.0015444887,0.0027420735,0.0013790729,0.0029871757],"category_scores_gemma":[0.016216293,0.0010106936,0.0016575907,0.0018070578,0.0017830458,0.001955384,0.0015230464,0.0023029516,0.0006300795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044378056,0.0001247608,0.016445706,0.000114320675,0.00028159475,0.0002350648,0.00032396926,0.8410401,0.0015170681,0.08881712,0.0026553194,0.048001125],"study_design_scores_gemma":[0.000042990014,0.000035283356,0.0018999305,0.000019656489,0.00003416797,0.000060122933,0.000027987744,0.9643355,0.0001454052,0.032753922,0.0006210561,0.000024084551],"about_ca_topic_score_codex":0.027478075,"about_ca_topic_score_gemma":0.023626981,"teacher_disagreement_score":0.027478075,"about_ca_system_score_codex":0.0014113367,"about_ca_system_score_gemma":0.0020009198,"threshold_uncertainty_score":0.05463624},"labels":[],"label_agreement":null},{"id":"W3133409953","doi":"10.3389/fnagi.2021.637002","title":"Structural Network Efficiency Predicts Resilience to Cognitive Decline in Elderly at Risk for Alzheimer’s Disease","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Deutsche Forschungsgemeinschaft; Bundesministerium für Bildung und Forschung; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Janssen Alzheimer Immunotherapy Research And Development; European Commission; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Leibniz-Gemeinschaft; Alzheimer's Association","keywords":"Cognitive decline; Dementia; Cognition; Effects of sleep deprivation on cognitive performance; Psychological resilience; Psychology; Neuroscience; Alzheimer's disease; Internal medicine; Medicine; Disease; Gerontology","score_opus":0.040494512516950125,"score_gpt":0.3454419679452108,"score_spread":0.3049474554282607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133409953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992022,0.000092324575,0.00015169245,0.000043235355,0.0000025135223,0.0000050832346,0.0001405552,0.000005075014,0.00035729178],"genre_scores_gemma":[0.99956995,0.00004116075,0.000107777676,0.0000057892516,0.0000039923157,0.0000036650958,0.0001448716,9.2372557e-7,0.000121755045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999107,0.000017672306,0.0000116917045,0.000026554435,0.000013729279,0.000019623982],"domain_scores_gemma":[0.9985831,0.00034026385,0.0006297181,0.00011384224,0.0001206542,0.00021239261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006287816,0.00038246214,0.00023021502,0.0007954013,0.00021188859,0.00042333617,0.00025338482,0.00040696046,0.0029466865],"category_scores_gemma":[0.0035419718,0.00014810062,0.00025432196,0.00035490838,0.00032725278,0.00045171112,0.00039665005,0.00028316354,0.0002120151],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002976375,0.00007092781,0.9948325,0.000016445782,0.00016142518,0.0000927766,0.00013847662,0.00064837595,0.00073983934,0.000079490244,0.00012888263,0.002793211],"study_design_scores_gemma":[0.0000027762278,0.000059447873,0.9988238,0.000003636539,0.00001818365,0.000082878076,0.000052458912,0.00067073776,0.00005203296,0.00018749048,0.000044330773,0.0000021333894],"about_ca_topic_score_codex":0.002344757,"about_ca_topic_score_gemma":0.0035644341,"teacher_disagreement_score":0.0029466865,"about_ca_system_score_codex":0.00019862327,"about_ca_system_score_gemma":0.00012909979,"threshold_uncertainty_score":0.009857595},"labels":[],"label_agreement":null},{"id":"W3134068182","doi":"10.1038/s41598-021-01773-7","title":"The trajectory of putative astroglial dysfunction in first episode schizophrenia: a longitudinal 7-Tesla MRS study","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; St Joseph's Health Care; Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Compute Canada; Schulich School of Medicine and Dentistry; Academic Medical Organization of Southwestern Ontario; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Medicine; Neuroscience; Longitudinal study; Psychiatry; Trajectory; Physical medicine and rehabilitation; Bioinformatics; Psychology; Biology; Pathology; Physics","score_opus":0.045310519100202104,"score_gpt":0.330401593415809,"score_spread":0.2850910743156069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134068182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994061,0.00016917594,0.00006460408,0.000025045194,0.000001640518,0.00000756734,0.00017429997,0.0000033869294,0.00014817835],"genre_scores_gemma":[0.99913186,0.00010970542,0.00009841623,0.000011601835,0.0000029420041,0.000009750616,0.00037503903,0.0000020952916,0.00025853666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998417,0.00003685747,0.000012252364,0.0000420133,0.000028303994,0.0000388964],"domain_scores_gemma":[0.99925727,0.00006128063,0.00030674084,0.00006326751,0.00013845752,0.00017296035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057252555,0.00025341645,0.00034880172,0.000602448,0.00065218593,0.00056618184,0.00024824857,0.00058768445,0.000858476],"category_scores_gemma":[0.0012750741,0.00027583845,0.00026032538,0.00046427187,0.00021987454,0.00044643047,0.00045221756,0.0005387831,0.00031536532],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013584774,0.00029936523,0.98742604,0.00002162069,0.00009981967,0.00033237672,0.00071029604,0.000098454,0.0052746,0.000033292283,0.000121867335,0.0042237705],"study_design_scores_gemma":[0.000004672907,0.00024042003,0.99907184,0.0000037329,0.000021568763,0.00014577624,0.00015775989,0.00007446175,0.00015003479,0.000017713004,0.00010723688,0.000004791502],"about_ca_topic_score_codex":0.009189256,"about_ca_topic_score_gemma":0.012600441,"teacher_disagreement_score":0.009189256,"about_ca_system_score_codex":0.00038978868,"about_ca_system_score_gemma":0.0004735764,"threshold_uncertainty_score":0.018271506},"labels":[],"label_agreement":null},{"id":"W3134107863","doi":"10.1016/j.neuroimage.2021.117919","title":"Structural alterations in cortical and thalamocortical white matter tracts after recovery from prefrontal cortex lesions in macaques","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Fondation Brain Canada","keywords":"White matter; Neuroscience; Lesion; Prefrontal cortex; Fractional anisotropy; Psychology; Cortex (anatomy); Superior longitudinal fasciculus; Diffusion MRI; Tractography; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.03504598857505999,"score_gpt":0.31963753046350757,"score_spread":0.2845915418884476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134107863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992955,0.00014205884,0.00031544914,0.000027720094,0.0000024748624,0.0000046758705,0.000061127714,0.00002369599,0.00012728742],"genre_scores_gemma":[0.99787354,0.00017074263,0.00073524663,0.000026199341,0.0000023914438,0.000016213904,0.00017614695,0.000016030555,0.0009833574],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991083,0.000005150592,0.000006348703,0.000032624226,0.000017243285,0.00002773227],"domain_scores_gemma":[0.9997514,0.000021927443,0.0001155488,0.000034622743,0.000031783526,0.00004469109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013126704,0.0002490876,0.00021760377,0.0005696532,0.0001830127,0.00023141465,0.00018227742,0.00027944078,0.0008858741],"category_scores_gemma":[0.00037531104,0.00019304761,0.00018026933,0.00009767041,0.00043743424,0.00020241855,0.0002125002,0.00038496035,0.00014357782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020409275,0.000037534264,0.0043023136,0.000033418703,0.000024125746,0.00049686263,0.00024153177,0.00012935553,0.99035734,0.000054109885,0.000038359267,0.0040809363],"study_design_scores_gemma":[0.000039979077,0.0015627824,0.6660656,0.000037163874,0.00009963588,0.007891666,0.0007712915,0.0028480964,0.31828064,0.00048051798,0.0018775865,0.000045018664],"about_ca_topic_score_codex":0.004923926,"about_ca_topic_score_gemma":0.0066481032,"teacher_disagreement_score":0.004923926,"about_ca_system_score_codex":0.000342031,"about_ca_system_score_gemma":0.00021863863,"threshold_uncertainty_score":0.00979054},"labels":[],"label_agreement":null},{"id":"W3134935651","doi":"10.3390/jpm11030174","title":"Mapping Brain Microstructure and Network Alterations in Depressive Patients with Suicide Attempts Using Generalized Q-Sampling MRI","year":2021,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"Ministry of Science and Technology, Taiwan","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Major depressive disorder; Voxel; Magnetic resonance imaging; Internal medicine; Psychology; Medicine; Psychiatry; Mood; Radiology","score_opus":0.06340629866114098,"score_gpt":0.3641723758974253,"score_spread":0.30076607723628435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134935651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99940205,0.00006681978,0.00039305704,0.000010519423,8.812745e-7,0.000009976587,0.000026740672,0.0000039998113,0.000085976775],"genre_scores_gemma":[0.9994168,0.00005347671,0.00043410197,0.0000072639273,0.0000011547763,0.000006476877,0.000043937296,8.2246464e-7,0.00003593915],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999027,0.000031599488,0.000013728359,0.000028049633,0.000014179253,0.000009721856],"domain_scores_gemma":[0.9997906,0.000028041832,0.00009628957,0.000028418039,0.000032382846,0.00002427596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026975496,0.0002476965,0.00018166668,0.0006098877,0.00013280631,0.00024985612,0.00013214212,0.00016402913,0.0003950858],"category_scores_gemma":[0.001013081,0.00011650267,0.00019932409,0.00029704146,0.00019944843,0.00016823997,0.00025717067,0.00012635584,0.00006450363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005646645,0.00011409108,0.95095694,0.00008800651,0.00023266324,0.0006837362,0.0010377472,0.00061257335,0.019444915,0.00016618306,0.00016303876,0.025935562],"study_design_scores_gemma":[0.00001748619,0.00019615579,0.9962845,0.000009339444,0.000044047232,0.00062463386,0.00030260565,0.0016552935,0.00053374295,0.00021477893,0.0001119689,0.000005463867],"about_ca_topic_score_codex":0.0019244363,"about_ca_topic_score_gemma":0.0026637462,"teacher_disagreement_score":0.0019244363,"about_ca_system_score_codex":0.00013645206,"about_ca_system_score_gemma":0.00010750568,"threshold_uncertainty_score":0.003826499},"labels":[],"label_agreement":null},{"id":"W3135033332","doi":"10.1101/2021.03.09.434656","title":"Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Engineering and Physical Sciences Research Council; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Glioblastoma; Connectome; Overall survival; Computer science; Functional connectivity; Medicine; Biology; Neuroscience; Oncology; Cancer research","score_opus":0.034687329390828775,"score_gpt":0.27299088888515644,"score_spread":0.23830355949432766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135033332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970757,0.00031811136,0.0009285327,0.00016191033,0.0000112721,0.0000058549813,0.0007730758,0.000030006207,0.0006956067],"genre_scores_gemma":[0.9985946,0.000110010806,0.00031836328,0.000018477564,0.000012066657,0.0000058577916,0.00068692863,0.000005351392,0.00024832448],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999335,0.000013916494,0.0000058579476,0.000018015086,0.000015293639,0.000013506968],"domain_scores_gemma":[0.9995389,0.00007851741,0.00019962816,0.00004255488,0.000053196185,0.00008734943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002276551,0.00033327052,0.00023031076,0.0009049226,0.00015421287,0.00038339957,0.00012755358,0.00030411797,0.0022084739],"category_scores_gemma":[0.0012187259,0.0000816252,0.00021872055,0.0005475213,0.00023507797,0.0003055079,0.00037783006,0.00034888618,0.00028205692],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000800865,0.00007294188,0.96526295,0.000050734045,0.00024667074,0.00020687302,0.00007000998,0.0022180644,0.012081525,0.00031604987,0.0014196545,0.017253814],"study_design_scores_gemma":[0.000013293818,0.00012702598,0.9894757,0.000012353608,0.00007668391,0.0005397716,0.000086589665,0.005749969,0.0022001737,0.0011194405,0.0005862636,0.000012709692],"about_ca_topic_score_codex":0.0014524742,"about_ca_topic_score_gemma":0.002372078,"teacher_disagreement_score":0.0022084739,"about_ca_system_score_codex":0.00022107613,"about_ca_system_score_gemma":0.00016314627,"threshold_uncertainty_score":0.0073880553},"labels":[],"label_agreement":null},{"id":"W3135193725","doi":"10.1210/clinem/dgab158","title":"Decreased Microstructural Integrity of the Central Somatosensory Tracts in Diabetic Peripheral Neuropathy","year":2021,"lang":"en","type":"article","venue":"The Journal of Clinical Endocrinology & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Somatosensory system; Medicine; Somatosensory evoked potential; Peripheral neuropathy; Internal medicine; Peripheral; Diabetes mellitus; Thalamus; Endocrinology; Anesthesia; Radiology; Psychiatry","score_opus":0.09294132401905102,"score_gpt":0.40400837755605107,"score_spread":0.31106705353700004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135193725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927133,0.00034759197,0.00014152897,0.000010932534,0.0000014720994,0.0000027829892,0.000057280467,0.0000036116571,0.0001635043],"genre_scores_gemma":[0.9996532,0.00010175851,0.0001436441,0.0000055864903,0.0000030638719,0.0000015302766,0.00004500601,5.9412747e-7,0.00004547508],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986994,0.000030867297,0.000017430832,0.00003648514,0.00002782672,0.00001747274],"domain_scores_gemma":[0.9991812,0.000106743326,0.00053506816,0.0000321179,0.000075020274,0.00006978175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004075873,0.00031157292,0.00019247088,0.000996528,0.00020491231,0.00035070814,0.00017364361,0.00026618486,0.0016272152],"category_scores_gemma":[0.00089964824,0.00013100606,0.00016552946,0.0005934341,0.0002990168,0.0001848986,0.00022624769,0.00020788232,0.00008302514],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033505095,0.000035675836,0.99008405,0.00004864325,0.0000887464,0.00044031872,0.000070309645,0.00010347954,0.0048156134,0.000017460374,0.000036783076,0.003923751],"study_design_scores_gemma":[0.0000030960305,0.00006302475,0.9981077,0.0000057647294,0.000030664298,0.0011720407,0.00004096178,0.00015219787,0.00036737518,0.000022791142,0.000032966112,0.0000015348476],"about_ca_topic_score_codex":0.0022297513,"about_ca_topic_score_gemma":0.002601684,"teacher_disagreement_score":0.0022297513,"about_ca_system_score_codex":0.00020794693,"about_ca_system_score_gemma":0.00015366347,"threshold_uncertainty_score":0.005443573},"labels":[],"label_agreement":null},{"id":"W3135454107","doi":"10.1002/mrm.28694","title":"A simulation study of cell size and volume fraction mapping for tissue with two underlying cell populations using diffusion‐weighted MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Diffusion MRI; Volume fraction; Stability (learning theory); RADIUS; Range (aeronautics); Population; Biological system; Diffusion; Volume (thermodynamics); Microstructure; Biomedical engineering; Computer science; Algorithm; Materials science; Magnetic resonance imaging; Artificial intelligence; Physics; Radiology; Biology; Medicine","score_opus":0.11005256753542923,"score_gpt":0.3968923909314867,"score_spread":0.28683982339605746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135454107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74552643,0.0004347337,0.25044292,0.00048059569,0.000027714232,0.000083926796,0.00025709093,0.00020610138,0.0025404776],"genre_scores_gemma":[0.95814407,0.0001606604,0.040377893,0.0000443952,0.0000063813936,0.00008064226,0.00011837299,0.00002264382,0.0010449175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988127,0.000032206957,0.0000059876543,0.000030059004,0.000033285865,0.000017257085],"domain_scores_gemma":[0.9991574,0.0005815771,0.00010281797,0.000050303683,0.00007264734,0.000035228524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053263706,0.00027190434,0.00029993415,0.00034059846,0.00023764002,0.00045017802,0.0004868639,0.000711167,0.0004667593],"category_scores_gemma":[0.0021422848,0.0002237916,0.00043551307,0.0002670071,0.0004160112,0.00036194496,0.00033715088,0.00029473196,0.00009817314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086488675,0.000042488413,0.0049942797,0.00006135095,0.000023753171,0.00023711403,0.00012419913,0.963856,0.022100596,0.0029874784,0.00016134775,0.0053249607],"study_design_scores_gemma":[0.0000066980833,0.00002810277,0.0007223631,0.0000027002068,0.0000051940247,0.00005431207,0.000012245747,0.99571157,0.002776677,0.00046275105,0.00021129385,0.000006117746],"about_ca_topic_score_codex":0.0086793285,"about_ca_topic_score_gemma":0.00496011,"teacher_disagreement_score":0.0086793285,"about_ca_system_score_codex":0.00063097064,"about_ca_system_score_gemma":0.000569651,"threshold_uncertainty_score":0.01725763},"labels":[],"label_agreement":null},{"id":"W3135501797","doi":"10.1002/cjs.11607","title":"Rejoinder: “Statistical disease mapping for heterogeneous neuroimaging studies”","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Viewpoints; Neuroimaging; Disease; Data science; Computer science; Medicine; Psychology; Neuroscience; Pathology","score_opus":0.15595903467508232,"score_gpt":0.37626923437290294,"score_spread":0.22031019969782062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135501797","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019293815,0.002541812,0.005300856,0.9587674,0.0324176,0.00003006538,0.00005683141,0.000073320094,0.00061916333],"genre_scores_gemma":[0.008819023,0.0015648529,0.013267043,0.897602,0.074402735,0.00027331628,0.000044244567,0.00027699783,0.0037496751],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.92831045,0.043465123,0.007037531,0.008537498,0.011497064,0.0011523381],"domain_scores_gemma":[0.68236035,0.24593365,0.0057090265,0.013012868,0.048731465,0.0042526266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09650328,0.0018137979,0.0028093848,0.0019945456,0.0059376736,0.0073950086,0.0066704536,0.03322336,0.0036187202],"category_scores_gemma":[0.29861498,0.001237163,0.0031345733,0.0013796503,0.020719344,0.012467107,0.0074787755,0.082141764,0.0032231507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071934206,0.000016225975,0.00027683892,0.00016384185,0.00006599978,0.00029233942,0.0016503619,0.00036060662,0.00023425298,0.07139283,0.91613984,0.009334929],"study_design_scores_gemma":[0.000107317544,0.00005096988,0.00052454876,0.0007084215,0.00007448558,0.0006898964,0.0012337676,0.0023860992,0.00045794516,0.20358881,0.7899386,0.00023908984],"about_ca_topic_score_codex":0.00941375,"about_ca_topic_score_gemma":0.006816445,"teacher_disagreement_score":0.09650328,"about_ca_system_score_codex":0.006231034,"about_ca_system_score_gemma":0.007174073,"threshold_uncertainty_score":0.51036423},"labels":[],"label_agreement":null},{"id":"W3136007397","doi":"10.5114/fn.2021.104396","title":"Globular glial tauopathy, a newly recognized white matter tauopathy, with depression/anxiety disorder: report and review of classification","year":2021,"lang":"en","type":"article","venue":"Folia Neuropathologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Tauopathy; White matter; Depression (economics); Neuroscience; Biology; Pathology; Medicine; Neurodegeneration; Disease; Magnetic resonance imaging","score_opus":0.03477739766586134,"score_gpt":0.3124173073285762,"score_spread":0.27763990966271485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136007397","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037216449,0.99278283,0.0008696806,0.0006469707,0.00034175874,0.000022055345,0.00006564558,0.000026355538,0.0015230668],"genre_scores_gemma":[0.017292177,0.9784918,0.0014417627,0.0007364319,0.0011517367,0.000030047864,0.00023683032,0.000013444465,0.00060576276],"study_design_codex":"design_other","study_design_gemma":"case_report","domain_scores_codex":[0.999213,0.00008353737,0.00027798585,0.0002188267,0.00014671194,0.00005990604],"domain_scores_gemma":[0.9992113,0.0002238798,0.00025011328,0.00004067282,0.0001913029,0.00008270616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006555951,0.001030838,0.001639244,0.009869617,0.00053759245,0.0012849817,0.0018417177,0.0009168565,0.00075709994],"category_scores_gemma":[0.0014524382,0.00032733206,0.00065435946,0.0059789163,0.0013751934,0.0021490352,0.00091559935,0.0010039088,0.00058550364],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017254884,0.0001458449,0.018853609,0.017238123,0.00036356502,0.03422821,0.0009909237,0.0006038126,0.0045366343,0.0040070913,0.03966493,0.87919474],"study_design_scores_gemma":[0.000031743544,0.00021701714,0.03921678,0.006163873,0.0008362445,0.45295227,0.00121054,0.0005799492,0.0014807486,0.004533379,0.49262762,0.00014986319],"about_ca_topic_score_codex":0.001925292,"about_ca_topic_score_gemma":0.0022612894,"teacher_disagreement_score":0.009869617,"about_ca_system_score_codex":0.00091573544,"about_ca_system_score_gemma":0.001277576,"threshold_uncertainty_score":0.0066441894},"labels":[],"label_agreement":null},{"id":"W3136241235","doi":"10.1101/2021.03.12.21253413","title":"Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Kurtosis; Diffusion MRI; Medicine; Magnetic resonance imaging; Spinal cord; Computer science; Neuroimaging; Medical physics; Radiology; Statistics","score_opus":0.10223331618829953,"score_gpt":0.42916084790211523,"score_spread":0.3269275317138157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136241235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7138958,0.02291514,0.24301614,0.0019035031,0.00054030033,0.0004434442,0.004437023,0.0024636402,0.010385022],"genre_scores_gemma":[0.8497261,0.009236364,0.13655333,0.00033783764,0.0002824255,0.00023413963,0.0016033603,0.0004687699,0.001557747],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99864215,0.0005048739,0.00021085676,0.00027816958,0.00028995296,0.00007401091],"domain_scores_gemma":[0.9966647,0.0013140342,0.00056737213,0.00031636405,0.000905242,0.00023234595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032384603,0.0007149455,0.00059701124,0.0033662047,0.00035622955,0.0017705981,0.000682351,0.0007887937,0.0027137813],"category_scores_gemma":[0.012018737,0.00030505037,0.0003003482,0.0014141505,0.0008130799,0.0010214283,0.001181454,0.0007636746,0.00095224753],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00174775,0.00024331089,0.33577123,0.004187927,0.00047514454,0.01385451,0.0029989108,0.010316251,0.16710427,0.0074735554,0.013008928,0.44281828],"study_design_scores_gemma":[0.00014872206,0.0016882523,0.59660274,0.0030471627,0.00065286044,0.06987382,0.0036995853,0.07686296,0.17033619,0.025088761,0.051545117,0.00045386117],"about_ca_topic_score_codex":0.0023362793,"about_ca_topic_score_gemma":0.0019695987,"teacher_disagreement_score":0.0033662047,"about_ca_system_score_codex":0.00044372425,"about_ca_system_score_gemma":0.00094791525,"threshold_uncertainty_score":0.017126799},"labels":[],"label_agreement":null},{"id":"W3136806534","doi":"10.1111/ncn3.12495","title":"Diffusion tensor imaging‐based magnetic resonance imaging‐guided focused ultrasound thalamotomy for tremor recurrence after radiofrequency thalamotomy: A case report","year":2021,"lang":"en","type":"article","venue":"Neurology and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Thalamotomy; Medicine; Diffusion MRI; Magnetic resonance imaging; Essential tremor; Focused ultrasound; Radiology; Ultrasound; Nuclear medicine; Physical medicine and rehabilitation; Parkinson's disease; Deep brain stimulation; Pathology","score_opus":0.06493877437241999,"score_gpt":0.3903144337174694,"score_spread":0.3253756593450494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136806534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97070575,0.0082338145,0.0069678766,0.0049754377,0.00044920767,0.0002550877,0.00018853921,0.00032843335,0.007895899],"genre_scores_gemma":[0.9945445,0.001209564,0.001216758,0.00093264057,0.00081893796,0.000037526534,0.00007411831,0.000032196614,0.0011338118],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99926347,0.00007795745,0.00008057988,0.00019320654,0.00011150213,0.00027332685],"domain_scores_gemma":[0.9986376,0.00029821484,0.00040219844,0.00017378635,0.000100533594,0.00038770007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043295597,0.0022566423,0.0017219933,0.0025632093,0.002757578,0.0013996643,0.0015015226,0.0056222994,0.0019459976],"category_scores_gemma":[0.0023271346,0.001183175,0.0021618826,0.0014333335,0.0016746313,0.0017912681,0.0014360395,0.0031876264,0.000937198],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001432424,0.000017908033,0.0015633204,0.000015432552,0.000009361995,0.9971835,0.00008634792,0.000027200005,0.00044421406,0.000047856327,0.00008914015,0.00050150056],"study_design_scores_gemma":[0.0000132436235,0.000036126046,0.0013938185,0.000009984263,0.000023244123,0.9977969,0.000055466728,0.0001852624,0.00026125985,0.00005463737,0.00016151248,0.000008653549],"about_ca_topic_score_codex":0.0027956779,"about_ca_topic_score_gemma":0.0035415508,"teacher_disagreement_score":0.0056222994,"about_ca_system_score_codex":0.0014648981,"about_ca_system_score_gemma":0.0008522008,"threshold_uncertainty_score":0.010628641},"labels":[],"label_agreement":null},{"id":"W3137094901","doi":"10.1016/j.neuroimage.2021.117977","title":"The ventral pathway of the human brain: A continuous association tract system","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft","keywords":"Fascicle; Anatomy; Neuroscience; Diffusion MRI; Tractography; External capsule; Internal capsule; White matter; Occipital lobe; Biology; Fiber tract; Connectome; Fractional anisotropy; Magnetic resonance imaging; Functional connectivity; Medicine","score_opus":0.0347466807069396,"score_gpt":0.3143478938263358,"score_spread":0.27960121311939623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137094901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5095691,0.0045823855,0.43143356,0.0012585863,0.00010260166,0.00021657374,0.0015613644,0.0013849295,0.04989098],"genre_scores_gemma":[0.9262654,0.00091962464,0.0664714,0.00011321177,0.000042087366,0.000086773085,0.0007155982,0.00013779795,0.00524797],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996804,0.00009141957,0.00001910472,0.00011377317,0.00007035815,0.000025049843],"domain_scores_gemma":[0.99959797,0.00009647414,0.00007025005,0.00008308813,0.000096692245,0.000055591707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026420082,0.0002265363,0.00020724938,0.0007016216,0.00038230338,0.0014298864,0.00035294195,0.00046300702,0.0037773673],"category_scores_gemma":[0.0013165798,0.00013345589,0.00022517768,0.00075868703,0.0019078101,0.0011481155,0.00055656687,0.00035444784,0.0006988069],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005940374,0.00008043494,0.058094293,0.00063248887,0.0002317305,0.0021917273,0.004325477,0.014641016,0.15047692,0.3102124,0.007198029,0.45132145],"study_design_scores_gemma":[0.00013147818,0.0008570798,0.41749972,0.00037634175,0.00021848541,0.019769665,0.0016576987,0.07927716,0.025846133,0.3435701,0.11057654,0.00021960793],"about_ca_topic_score_codex":0.0038727724,"about_ca_topic_score_gemma":0.0035764617,"teacher_disagreement_score":0.0038727724,"about_ca_system_score_codex":0.0004461201,"about_ca_system_score_gemma":0.00090939295,"threshold_uncertainty_score":0.012636483},"labels":[],"label_agreement":null},{"id":"W3138439593","doi":"10.1101/2021.03.25.436908","title":"Brain virtual histology with X-ray phase-contrast tomography Part II: 3D morphologies of amyloid-β plaques in Alzheimer’s disease models","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"LabEx PRIMES; Université de Lyon; University of Manchester; European Synchrotron Radiation Facility; Agence Nationale de la Recherche; Mitacs","keywords":"Pathology; Histology; Genetically modified mouse; Biology; Medicine; Transgene","score_opus":0.0469539166426776,"score_gpt":0.29177883625519424,"score_spread":0.24482491961251665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138439593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46091223,0.004480246,0.5223291,0.000431934,0.00022144882,0.00034734717,0.0017863514,0.0032043692,0.0062869764],"genre_scores_gemma":[0.6287234,0.0069694016,0.35170746,0.0002462905,0.00007506941,0.00049737364,0.0020223996,0.0010357243,0.008722875],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997782,0.000040992203,0.000013704987,0.000040122817,0.00010398238,0.000023074326],"domain_scores_gemma":[0.99967194,0.00007122508,0.00006561686,0.00008164111,0.00008421982,0.000025251758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006340227,0.000844576,0.00032905984,0.0010351258,0.00024420602,0.0008055603,0.00047193447,0.0006064946,0.0024991266],"category_scores_gemma":[0.00044922315,0.0005168917,0.00050266244,0.0003996268,0.0005023307,0.00051646004,0.00066899555,0.0008274608,0.0008042564],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009367607,0.000042420357,0.0006660244,0.00025068992,0.000031990712,0.0002627779,0.00009720132,0.0020746717,0.98362595,0.0006862975,0.00054975157,0.011618596],"study_design_scores_gemma":[0.000021065596,0.0002972237,0.009324631,0.00009675999,0.00008439556,0.0030425417,0.000110511704,0.02157426,0.95178884,0.0010072618,0.012582646,0.00006979098],"about_ca_topic_score_codex":0.00055225333,"about_ca_topic_score_gemma":0.0007371556,"teacher_disagreement_score":0.0024991266,"about_ca_system_score_codex":0.0003399006,"about_ca_system_score_gemma":0.00038629092,"threshold_uncertainty_score":0.0083604455},"labels":[],"label_agreement":null},{"id":"W3139317540","doi":"10.1002/mrm.28734","title":"Efficient whole‐brain tract‐specific T<sub>1</sub> mapping at 3T with slice‐shuffled inversion‐recovery diffusion‐weighted imaging","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Hotchkiss Brain Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Voxel; Corticospinal tract; Imaging phantom; White matter; Corpus callosum; Cingulum (brain); Physics; Nuclear magnetic resonance; Computer science; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Anatomy; Fractional anisotropy; Biology; Optics; Medicine; Radiology","score_opus":0.025301290685456404,"score_gpt":0.27333365642935303,"score_spread":0.24803236574389664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139317540","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10416143,0.0002817338,0.89146185,0.00023090364,0.000018487632,0.000095758885,0.00023656427,0.0015905494,0.0019226964],"genre_scores_gemma":[0.6291421,0.00031267444,0.3682999,0.00010921818,0.000011593568,0.00020734766,0.00029048824,0.0003677008,0.0012588955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991465,0.000022306298,0.0000039325146,0.000014639686,0.000035458448,0.000009021322],"domain_scores_gemma":[0.9997143,0.000114862676,0.00006344796,0.000042306103,0.000042731903,0.000022275091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005690638,0.0006267799,0.00034188887,0.00029568296,0.000314292,0.00052563543,0.00078764907,0.0006776232,0.0011131163],"category_scores_gemma":[0.0013254611,0.00039550298,0.00043777778,0.0003580888,0.00038187177,0.0006303696,0.00044345533,0.0005078367,0.0004085729],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028571207,0.00008291225,0.0021473737,0.00022671022,0.000086618755,0.0004465897,0.0002231252,0.86142135,0.08175758,0.0048860065,0.0017052197,0.046730775],"study_design_scores_gemma":[0.000023360317,0.000077650446,0.0007031741,0.0000091903985,0.0000177005,0.00021251857,0.000016627384,0.9757958,0.018940413,0.0030567774,0.0011224711,0.000024323132],"about_ca_topic_score_codex":0.0045996807,"about_ca_topic_score_gemma":0.004899841,"teacher_disagreement_score":0.0045996807,"about_ca_system_score_codex":0.00058602425,"about_ca_system_score_gemma":0.0009659294,"threshold_uncertainty_score":0.009145856},"labels":[],"label_agreement":null},{"id":"W3139494368","doi":"10.1101/2021.03.18.21253884","title":"A ketogenic supplement improves white matter energy supply and processing speed in mild cognitive impairment","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centres Intégré Universitaires de Santé et de Services Sociaux; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"","keywords":"Ketone bodies; Ketogenic diet; White matter; Fornix; Neurocognitive; Medicine; Glucose uptake; Neuroimaging; Positron emission tomography; Nuclear medicine; Internal medicine; Psychology; Neuroscience; Cognition; Insulin; Magnetic resonance imaging; Radiology; Metabolism; Epilepsy","score_opus":0.03849697187696032,"score_gpt":0.33235289532017587,"score_spread":0.29385592344321554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139494368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99861693,0.00086417346,0.00009700743,0.000046854824,0.000018752022,0.000030877814,0.00009178262,0.000025355012,0.00020821257],"genre_scores_gemma":[0.9973943,0.00082818395,0.00049565785,0.00006549697,0.000018749024,0.000055231878,0.0001575431,0.000003910307,0.0009807443],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999472,0.000011246411,0.000008812218,0.000010750597,0.000010043734,0.000011975168],"domain_scores_gemma":[0.9998838,0.000015122295,0.000028821454,0.0000084152825,0.000020099196,0.000043650693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015149095,0.00047353713,0.0007307805,0.00028537397,0.0001836369,0.00025756523,0.00024530655,0.00037821778,0.0024060614],"category_scores_gemma":[0.00030287405,0.000112897775,0.00025319596,0.00017209142,0.00017407381,0.00018339159,0.00023100327,0.00035984247,0.00022618902],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.34861895,0.033707045,0.013639081,0.0022328517,0.0011014452,0.00035812493,0.00036949126,0.00079314905,0.4464495,0.00012189445,0.0012353949,0.15137306],"study_design_scores_gemma":[0.02698442,0.3770629,0.42240238,0.0005320281,0.0027617451,0.00053599256,0.0007251463,0.0034393636,0.16043487,0.0006200968,0.0044189855,0.000082108774],"about_ca_topic_score_codex":0.0016366544,"about_ca_topic_score_gemma":0.0017898261,"teacher_disagreement_score":0.0024060614,"about_ca_system_score_codex":0.0001773507,"about_ca_system_score_gemma":0.00022215037,"threshold_uncertainty_score":0.008049071},"labels":[],"label_agreement":null},{"id":"W3139861652","doi":"10.1016/j.intell.2021.101541","title":"No evidence for an effect of a working memory training program on white matter microstructure","year":2021,"lang":"en","type":"article","venue":"Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Alberta Health Services","funders":"Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Canadian Psychological Association","keywords":"Working memory; Fractional anisotropy; Diffusion MRI; Psychology; White matter; Working memory training; Neuroimaging; Cognition; Cognitive psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.22426969416796966,"score_gpt":0.44995420595229985,"score_spread":0.2256845117843302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139861652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939767,0.0011565775,0.00050476706,0.00042931677,0.0003442281,0.00011953636,0.00033619156,0.00010144164,0.0030312145],"genre_scores_gemma":[0.9883079,0.00062092533,0.0014826631,0.0004631056,0.00019747189,0.00023755616,0.00037035818,0.00008188859,0.008238215],"study_design_codex":"randomized_trial","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.9988279,0.0002318971,0.00009130285,0.0004072367,0.00024981302,0.00019190014],"domain_scores_gemma":[0.98683435,0.008561627,0.0011486408,0.0010492365,0.00059363106,0.0018125593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023679966,0.0009346486,0.0019659146,0.00039910106,0.00057777856,0.00086471206,0.00132872,0.001752215,0.01107883],"category_scores_gemma":[0.009165045,0.00039671172,0.0012170874,0.00052498374,0.0010555218,0.0011179316,0.00080775877,0.0020927666,0.0008939459],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.53535837,0.073039666,0.09767705,0.0038982108,0.00685677,0.0020232834,0.002064543,0.0012323379,0.123373866,0.0012181351,0.0023635253,0.15089422],"study_design_scores_gemma":[0.005318697,0.13677604,0.8200942,0.00040930748,0.0064232405,0.0003174814,0.0005262151,0.0012266448,0.021762643,0.0012799705,0.0057690153,0.00009649532],"about_ca_topic_score_codex":0.0026830442,"about_ca_topic_score_gemma":0.0038843711,"teacher_disagreement_score":0.01107883,"about_ca_system_score_codex":0.00062663713,"about_ca_system_score_gemma":0.0017938756,"threshold_uncertainty_score":0.037062407},"labels":[],"label_agreement":null},{"id":"W3143007731","doi":"10.1016/j.neuroimage.2021.117980","title":"Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; National Institute on Aging; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Washington; Centre d'Imagerie BioMédicale; Pfizer; Biogen; BioClinica; Massachusetts General Hospital; University of Minnesota; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics; F. Hoffmann-La Roche; Agence Nationale de la Recherche; University of Southern California; National Institutes of Health; University of California; National Institute of Dental and Craniofacial Research; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Janssen Alzheimer Immunotherapy Research And Development; AbbVie; Fujirebio Europe; Université Côte d’Azur; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Bayesian inference; Neurodegeneration; Artificial intelligence; Bayesian probability; Computer science; Inference; Expectation propagation; Parametric statistics; Belief propagation; Neuroscience; Propagation of uncertainty; Formalism (music); Machine learning; Biology; Mathematics; Physics; Disease; Algorithm; Medicine; Pathology","score_opus":0.05664511417678205,"score_gpt":0.3206182696660025,"score_spread":0.26397315548922046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143007731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029758157,0.0003328004,0.96816564,0.00066764373,0.000017793698,0.000026348189,0.00009646815,0.00007941318,0.00085575547],"genre_scores_gemma":[0.82275003,0.0013357688,0.17262477,0.000261415,0.00017485885,0.00025207494,0.00031618463,0.00008454388,0.0022002815],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993512,0.0002959398,0.00003558704,0.00017076764,0.000094796924,0.000051616636],"domain_scores_gemma":[0.9923948,0.005930167,0.0010097453,0.0002334376,0.00023881691,0.00019307768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003658122,0.0008859066,0.0009436943,0.0019124447,0.0005232029,0.0017344045,0.0017892434,0.0018210115,0.001587726],"category_scores_gemma":[0.0136606,0.0007586411,0.0012918925,0.00066308497,0.0030352555,0.0029326978,0.0017949055,0.0015872024,0.00020866313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003005929,0.000026776443,0.0022164385,0.00009340587,0.00008486124,0.00009479223,0.00012427734,0.8116583,0.0019470371,0.17485845,0.00024209554,0.008623514],"study_design_scores_gemma":[0.0000044496437,0.000022319327,0.00023978816,0.000010551122,0.0000071107547,0.000016753942,0.000009902801,0.9077072,0.00016919091,0.091627486,0.00017497962,0.000010174579],"about_ca_topic_score_codex":0.0037415936,"about_ca_topic_score_gemma":0.0024652516,"teacher_disagreement_score":0.0037415936,"about_ca_system_score_codex":0.0014872142,"about_ca_system_score_gemma":0.0011984571,"threshold_uncertainty_score":0.019346178},"labels":[],"label_agreement":null},{"id":"W3143481006","doi":"","title":"White matter imaging correlates of early cognitive impairment detected by the MoCA after TIA and minor stroke","year":2017,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Medicine; Minor stroke; Montreal Cognitive Assessment; Stroke (engine); Cognitive impairment; White matter; Leukoaraiosis; Hyperintensity; Cognition; Ischemic stroke; Neuroimaging; Cardiology; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology; Ischemia; Stenosis","score_opus":0.026834965760165214,"score_gpt":0.28905289281901914,"score_spread":0.26221792705885394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143481006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995024,0.00007233327,0.000018765248,0.00002480159,0.0000040966534,0.0000063178254,0.00007378482,0.0000019911834,0.00029554093],"genre_scores_gemma":[0.999694,0.000022736482,0.000020846586,0.0000138714,0.000013088092,0.0000035886035,0.00012373777,0.0000010836256,0.00010710021],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998153,0.000037089703,0.000027564358,0.000045160108,0.000026495116,0.00004845471],"domain_scores_gemma":[0.99804735,0.00032196165,0.0009072814,0.00009738932,0.00017506836,0.00045093175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004043246,0.00028323615,0.00030980754,0.0010680777,0.0004181576,0.0004814358,0.00033389957,0.00047697645,0.0022341795],"category_scores_gemma":[0.0037129705,0.00019741303,0.00024444528,0.0005598155,0.0004221355,0.00041105735,0.00047797483,0.00048599218,0.00030126248],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004885405,0.000055633143,0.99763834,0.00000645174,0.000036973,0.00023938714,0.000047196783,0.00004503806,0.0003259924,0.0000151924105,0.00007739958,0.001023768],"study_design_scores_gemma":[0.00000681988,0.000062938234,0.9995427,0.000001616934,0.000008571602,0.00021765595,0.000028556211,0.000052115363,0.00003180639,0.000022703252,0.000022791066,0.0000017994837],"about_ca_topic_score_codex":0.005941165,"about_ca_topic_score_gemma":0.00789418,"teacher_disagreement_score":0.005941165,"about_ca_system_score_codex":0.0003710772,"about_ca_system_score_gemma":0.0003328149,"threshold_uncertainty_score":0.011813164},"labels":[],"label_agreement":null},{"id":"W3144676319","doi":"10.1002/hbm.25398","title":"Beware of white matter hyperintensities causing systematic errors in <scp>FreeSurfer</scp> gray matter segmentations!","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centres Intégré Universitaires de Santé et de Services Sociaux; Université Laval; University of Alberta","funders":"National Institute on Aging; Canadian Institutes of Health Research; Alzheimer Society; Sanofi","keywords":"White matter; Hyperintensity; Gray (unit); Neuroscience; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.0652553427233796,"score_gpt":0.3261504929430581,"score_spread":0.26089515021967846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144676319","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10381581,0.0029547657,0.68239564,0.02290002,0.010969777,0.0013609411,0.013517757,0.1291312,0.032954127],"genre_scores_gemma":[0.28222916,0.0015805538,0.59862256,0.011876818,0.0015281797,0.0035909384,0.007859849,0.048628706,0.044083234],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953367,0.001704744,0.00063344144,0.0008346931,0.0013241129,0.00016623728],"domain_scores_gemma":[0.9583541,0.015562536,0.0046658497,0.014316377,0.0064846096,0.00061639806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019495608,0.0013753138,0.0012421636,0.0023136388,0.0016036173,0.0024535763,0.0019940538,0.0022450523,0.058347963],"category_scores_gemma":[0.066210225,0.0015388905,0.0011144106,0.001797628,0.0020964334,0.0027385773,0.0022088774,0.0024207858,0.022759728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010111835,0.00015804317,0.026087603,0.0024203607,0.00064075337,0.0024373927,0.0034660508,0.0029721963,0.0348188,0.011659023,0.59899426,0.31533426],"study_design_scores_gemma":[0.00045363465,0.000487536,0.08482313,0.0024519048,0.00051111024,0.00905341,0.0015596614,0.051016554,0.10718834,0.062259387,0.6796223,0.00057297887],"about_ca_topic_score_codex":0.0032110952,"about_ca_topic_score_gemma":0.010202754,"teacher_disagreement_score":0.058347963,"about_ca_system_score_codex":0.0006312067,"about_ca_system_score_gemma":0.0021936074,"threshold_uncertainty_score":0.19519341},"labels":[],"label_agreement":null},{"id":"W3148107305","doi":"10.1016/j.neuropsychologia.2021.107847","title":"Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition","year":2021,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Psychology; Precuneus; Mnemonic; Superior longitudinal fasciculus; Arcuate fasciculus; Neuroscience; Cognitive psychology; Inferior longitudinal fasciculus; Fractional anisotropy; Metacognition; Functional magnetic resonance imaging; Diffusion MRI; Cognition; Magnetic resonance imaging","score_opus":0.14087174292486895,"score_gpt":0.3699412326271836,"score_spread":0.22906948970231464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148107305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891145,0.00034119416,0.008871702,0.00017602424,0.000008278103,0.000008821767,0.00017976326,0.00002935842,0.0012704326],"genre_scores_gemma":[0.99784505,0.00010610016,0.0016397837,0.000011319227,0.000006916363,0.0000050922536,0.00006317189,0.000009455711,0.0003132015],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993265,0.000013797126,0.0000050474114,0.000024988705,0.000011048812,0.000012429006],"domain_scores_gemma":[0.99915123,0.00031907586,0.00028470822,0.00012259354,0.000057058183,0.00006539171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029430992,0.00017807932,0.00014246989,0.0004997158,0.00018136413,0.00060149963,0.00021443315,0.0002787545,0.0015002034],"category_scores_gemma":[0.0028178468,0.00022700006,0.00011042959,0.0003595844,0.0007120778,0.0011971634,0.00042352872,0.0003772306,0.00010993735],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019817997,0.00020679472,0.22903553,0.0004103092,0.00042920557,0.00094521855,0.0033222833,0.013420211,0.59149176,0.02370895,0.0012599904,0.133788],"study_design_scores_gemma":[0.000054249456,0.00016831304,0.8979643,0.000042459193,0.00009931777,0.0013771291,0.00053712266,0.025665717,0.030714354,0.041552875,0.0017651333,0.0000590493],"about_ca_topic_score_codex":0.004010383,"about_ca_topic_score_gemma":0.005695215,"teacher_disagreement_score":0.004010383,"about_ca_system_score_codex":0.000216637,"about_ca_system_score_gemma":0.00030657582,"threshold_uncertainty_score":0.007974088},"labels":[],"label_agreement":null},{"id":"W3148237534","doi":"10.1101/2021.04.07.438845","title":"Enabling constrained spherical deconvolution and diffusional variance decomposition with tensor-valued diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Deconvolution; Fractional anisotropy; Tensor (intrinsic definition); Anisotropy; Orientation (vector space); Diffusion; Computer science; Angular resolution (graph drawing); White matter; Computation; Variance (accounting); Tractography; Algorithm; Mathematics; Physics; Magnetic resonance imaging; Geometry; Optics","score_opus":0.02162703153090347,"score_gpt":0.27457103590002124,"score_spread":0.2529440043691178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148237534","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015891002,0.00011245456,0.98269546,0.00013495589,0.000026274862,0.0000535147,0.00008058616,0.00046833907,0.00053739245],"genre_scores_gemma":[0.11911211,0.00020464016,0.8791424,0.00006869855,0.000024688658,0.00011076493,0.00022950917,0.00023167129,0.00087549555],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999331,0.00022867843,0.00004580002,0.000106125495,0.00023364883,0.000054895016],"domain_scores_gemma":[0.99830246,0.0009199379,0.00017575458,0.00028287075,0.0002243855,0.00009464291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016333106,0.00097261573,0.0006154402,0.00065591885,0.00032708593,0.0011737132,0.0007851028,0.0011441283,0.002004535],"category_scores_gemma":[0.006346122,0.0004974927,0.00067073555,0.00078668026,0.0009574978,0.0011358043,0.0024075876,0.0012780221,0.0007800991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000703512,0.00015844834,0.0015123847,0.00065013027,0.00020984928,0.0004262126,0.00035901857,0.3243937,0.35944328,0.05859257,0.003346056,0.25020498],"study_design_scores_gemma":[0.000029871662,0.00007770853,0.00042915362,0.000031498814,0.00002241763,0.00021746891,0.000028126375,0.8763886,0.10637897,0.012700507,0.003654611,0.000041043157],"about_ca_topic_score_codex":0.0025797174,"about_ca_topic_score_gemma":0.0023709857,"teacher_disagreement_score":0.0025797174,"about_ca_system_score_codex":0.0005742156,"about_ca_system_score_gemma":0.0013965553,"threshold_uncertainty_score":0.008637905},"labels":[],"label_agreement":null},{"id":"W3148446709","doi":"10.1101/2021.03.26.21254351","title":"In Vivo Cortical Microstructure: A Proxy for Tauopathy and Cognitive impairment in the Elderly with and without MCI/Dementia","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Japan Atomic Energy Agency; National Institutes of Health; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; BioClinica; U.S. Department of Defense; Canon Medical Systems USA; Alzheimer's Disease Neuroimaging Initiative; University of Toronto; Bristol-Myers Squibb; National Alliance for Research on Schizophrenia and Depression; Biogen; National Institute on Aging; Alzheimer's Association; Brain and Behavior Research Foundation","keywords":"Dementia; Psychology; Tauopathy; Fractional anisotropy; Diffusion MRI; Cognitive impairment; Neuroscience; Cognitive decline; Positron emission tomography; Audiology; Correlation; Proxy (statistics); Cognition; Internal medicine; Nuclear medicine; Medicine; Disease; Magnetic resonance imaging; Radiology; Statistics; Neurodegeneration","score_opus":0.027234502302790314,"score_gpt":0.33433572023084923,"score_spread":0.3071012179280589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148446709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99910754,0.00023321662,0.00015651764,0.000010635194,0.0000028602403,0.000010691042,0.00016584522,0.000005478581,0.00030715414],"genre_scores_gemma":[0.99953175,0.000046957404,0.00016376386,0.000008195707,0.0000051610277,0.000008239548,0.00011137146,0.0000014555793,0.00012321868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980396,0.00003968685,0.00003228845,0.000056451376,0.00004080713,0.00002683831],"domain_scores_gemma":[0.9991697,0.00010695608,0.0004058521,0.000093668794,0.000114157825,0.00010982263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007489238,0.0005571577,0.00035609386,0.0014809001,0.0004195789,0.0006734026,0.0002390745,0.0004817737,0.0009497391],"category_scores_gemma":[0.0022909923,0.00028648786,0.0002075003,0.0006446184,0.0003659448,0.0004250606,0.0004944658,0.00029447442,0.0001807075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058917236,0.00006451969,0.99266523,0.00002127027,0.0001443884,0.00019877522,0.00021480452,0.00014915116,0.0035645335,0.000039346214,0.00008728199,0.0022615974],"study_design_scores_gemma":[0.00000332477,0.00007402861,0.9991411,0.0000022465902,0.000016108732,0.00023769513,0.00007808406,0.00017406922,0.00019059639,0.000044937377,0.00003537807,0.000002393258],"about_ca_topic_score_codex":0.0045506107,"about_ca_topic_score_gemma":0.006502901,"teacher_disagreement_score":0.0045506107,"about_ca_system_score_codex":0.00021389652,"about_ca_system_score_gemma":0.00014695527,"threshold_uncertainty_score":0.0090482235},"labels":[],"label_agreement":null},{"id":"W3152388697","doi":"10.1101/2021.04.01.21254814","title":"Multi-tract multi-symptom relationships in pediatric concussion","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Toronto; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital; Hospital for Sick Children; McGill University","funders":"","keywords":"Concussion; White matter; Diffusion MRI; Psychopathology; Psychology; Connectome; Medicine; Clinical psychology; Neuroscience; Poison control; Functional connectivity; Injury prevention; Magnetic resonance imaging; Radiology","score_opus":0.15730719273781815,"score_gpt":0.3896156803775997,"score_spread":0.23230848763978154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152388697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835634,0.0004792693,0.014004706,0.00018325503,0.000010043898,0.000020999027,0.0012552305,0.00009560608,0.00038736901],"genre_scores_gemma":[0.99242026,0.0001271446,0.006409245,0.00001952412,0.000014981673,0.000014278363,0.00082923356,0.000024181443,0.00014104419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99929535,0.00024777223,0.000054664917,0.00023121046,0.00008953524,0.000081405145],"domain_scores_gemma":[0.99560684,0.0015602711,0.0018996422,0.00036047222,0.00034456977,0.00022817106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015306554,0.0005085912,0.0004450313,0.0017113204,0.00036879507,0.00077977765,0.00038213158,0.00046371834,0.0019830463],"category_scores_gemma":[0.008198876,0.0002786429,0.0004310115,0.001768706,0.00053663994,0.000675601,0.0012034419,0.0006855064,0.0002310339],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034433175,0.00006392384,0.9537334,0.00016258506,0.00034463796,0.0005776809,0.00039403624,0.0098524755,0.0068948762,0.0012661472,0.0009844815,0.025381451],"study_design_scores_gemma":[0.000018848948,0.00015161315,0.9331465,0.00006452531,0.00013717408,0.0015685462,0.00042121392,0.05381854,0.003347272,0.006231168,0.0010666866,0.000027946133],"about_ca_topic_score_codex":0.0041130707,"about_ca_topic_score_gemma":0.006256209,"teacher_disagreement_score":0.0041130707,"about_ca_system_score_codex":0.00036755786,"about_ca_system_score_gemma":0.00048171953,"threshold_uncertainty_score":0.008178294},"labels":[],"label_agreement":null},{"id":"W3152390874","doi":"10.1080/01616412.2021.1910903","title":"Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease","year":2021,"lang":"en","type":"article","venue":"Neurological Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Gyrus; Fractional anisotropy; Diffusion MRI; Internal medicine; Posterior cingulate; Cingulate cortex; Anterior cingulate cortex; Psychology; Medicine; Cardiology; Lingual gyrus; Montreal Cognitive Assessment; Cognitive impairment; Cognition; Neuroscience; Disease; Magnetic resonance imaging; Radiology; Central nervous system","score_opus":0.13667093288349458,"score_gpt":0.40059210810136614,"score_spread":0.26392117521787156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152390874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986835,0.00039963794,0.00012085497,0.00004860009,0.00001078364,0.000012958868,0.00014963472,0.000006193687,0.0005677271],"genre_scores_gemma":[0.9994149,0.00014895057,0.00011533456,0.000021997945,0.000011118108,0.00000583693,0.00012415163,0.0000021681976,0.0001555441],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999461,0.00000944845,0.0000063113957,0.000015922538,0.000009371803,0.000012715433],"domain_scores_gemma":[0.999851,0.000017952083,0.000066847446,0.000011563498,0.000018159904,0.000034449648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001258819,0.0003446468,0.00021378174,0.00056233053,0.00024706768,0.00022902428,0.000103221646,0.00024308865,0.0010680528],"category_scores_gemma":[0.0005190223,0.00013988581,0.0001823953,0.00027652254,0.00027361052,0.00017484784,0.00016390422,0.00018918977,0.00011391167],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048378124,0.00016009819,0.8946947,0.0002188982,0.00044370003,0.006843874,0.0008065401,0.00034841913,0.06612515,0.00016810757,0.0008098458,0.02454293],"study_design_scores_gemma":[0.0000098794935,0.0000916726,0.9985077,0.000003569479,0.00002991477,0.0007064803,0.00007313351,0.00008671295,0.00033962383,0.000039831073,0.00010751395,0.0000040035748],"about_ca_topic_score_codex":0.0059299394,"about_ca_topic_score_gemma":0.009343806,"teacher_disagreement_score":0.0059299394,"about_ca_system_score_codex":0.0002073158,"about_ca_system_score_gemma":0.00014228675,"threshold_uncertainty_score":0.011790872},"labels":[],"label_agreement":null},{"id":"W3152927637","doi":"10.1017/cjn.2021.64","title":"Corpus Callosum Remodeling in Glioma: Constancy of Fiber Density and Anisotropy in MRI","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Brain Research Centre","keywords":"Corpus callosum; Glioma; Medicine; Anisotropy; Nuclear magnetic resonance; Neuroscience; Pathology; Physics; Psychology; Optics; Cancer research","score_opus":0.0583567899094615,"score_gpt":0.3174384119447719,"score_spread":0.2590816220353104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152927637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968996,0.0004479248,0.0012682044,0.00006819419,0.000005024041,0.000010416073,0.00012232206,0.000061007733,0.0011173276],"genre_scores_gemma":[0.9990839,0.00012204031,0.00046847572,0.000007749882,0.000005031406,0.000006041292,0.00005987991,0.0000072555613,0.00023977378],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994946,0.000008319138,0.0000044456665,0.000014000074,0.0000119606075,0.0000118843145],"domain_scores_gemma":[0.9998041,0.000030154555,0.00007817865,0.000028750283,0.000025272973,0.000033600114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001698426,0.00018421511,0.00009743264,0.00093368604,0.00018736675,0.0002725906,0.00017157875,0.00024941794,0.0012465162],"category_scores_gemma":[0.00074419915,0.0001023993,0.0000955977,0.0004030264,0.00034771653,0.00033061166,0.00018931608,0.00021496703,0.00020717985],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002391838,0.0000971394,0.31771785,0.00017312377,0.00011671967,0.0039634304,0.0008463018,0.0013493833,0.61023414,0.00084502675,0.0007877222,0.06147742],"study_design_scores_gemma":[0.000008730011,0.0001715926,0.95804626,0.000009232732,0.000034498444,0.0056926287,0.00025830514,0.002013864,0.03239411,0.0005291431,0.0008262777,0.00001531107],"about_ca_topic_score_codex":0.003334716,"about_ca_topic_score_gemma":0.0024554632,"teacher_disagreement_score":0.003334716,"about_ca_system_score_codex":0.0002093894,"about_ca_system_score_gemma":0.0002122483,"threshold_uncertainty_score":0.0066305995},"labels":[],"label_agreement":null},{"id":"W3153160982","doi":"10.1016/j.pscychresns.2021.111289","title":"White matter microstructure in youth at risk for serious mental illness: A comparative analysis","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Ottawa; Queen's University; University of Alberta; University Health Network; Health Sciences Centre; University of Toronto; St. Michael's Hospital; Sunnybrook Health Science Centre; McMaster University; University of British Columbia; St. Joseph’s Healthcare Hamilton; University of Calgary; Ontario Brain Institute; Baycrest Hospital; Alberta Children's Hospital","funders":"Mathison Centre for Mental Health Research and Education; Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Fractional anisotropy; Fasciculus; White matter; Uncinate fasciculus; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Diffusion MRI; Medicine; Psychology; Internal medicine; Cardiology; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.09192182509794831,"score_gpt":0.4323466069880066,"score_spread":0.34042478189005826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153160982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976355,0.000060185983,0.000022794406,0.0000043541777,8.400605e-7,0.0000020268146,0.000057818615,5.042553e-7,0.00008795753],"genre_scores_gemma":[0.99970156,0.00006900864,0.000046771438,0.0000041682556,0.0000019334414,0.0000031957234,0.000093261806,9.526261e-7,0.00007911879],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980646,0.000041953528,0.00001661168,0.00005162459,0.000030168409,0.00005327105],"domain_scores_gemma":[0.99958426,0.0000706735,0.00014591015,0.000041379342,0.00007260549,0.00008527469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054766715,0.00027245318,0.0004162381,0.0014300817,0.0005736918,0.0005089685,0.0002949366,0.00038746928,0.0015940708],"category_scores_gemma":[0.0014847798,0.00018552004,0.0005155494,0.0010967295,0.0004321424,0.00045275048,0.0007117989,0.00026712986,0.00014792786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068660785,0.000116531075,0.99215794,0.00001818935,0.00015474341,0.00031638937,0.0011181869,0.000039755458,0.0014383198,0.00013057534,0.00006070308,0.0037621593],"study_design_scores_gemma":[0.0000046665227,0.00016394103,0.9987207,0.000003668718,0.000049274935,0.00019738812,0.0006691933,0.000035592413,0.000070899965,0.000029516463,0.000053239288,0.0000018860482],"about_ca_topic_score_codex":0.01089417,"about_ca_topic_score_gemma":0.014412588,"teacher_disagreement_score":0.01089417,"about_ca_system_score_codex":0.0005529499,"about_ca_system_score_gemma":0.0004515585,"threshold_uncertainty_score":0.02166152},"labels":[],"label_agreement":null},{"id":"W3153408593","doi":"10.1007/s00429-021-02267-y","title":"White matter microstructural changes in short-term learning of a continuous visuomotor sequence","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Max-Planck-Institut für demografische Forschung; Fonds de recherche du Québec – Nature et technologies; Max-Planck-Gesellschaft; Heart and Stroke Foundation of Canada; Réseau en Bio-Imagerie du Quebec; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"White matter; Neuroscience; Neuroplasticity; Psychology; Sequence learning; Functional magnetic resonance imaging; Motor learning; Magnetic resonance imaging; Medicine","score_opus":0.02711165707829397,"score_gpt":0.3069827895872639,"score_spread":0.2798711325089699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153408593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990079,0.000048520462,0.00067497714,0.00001664081,0.0000038054027,0.0000055867454,0.00004140367,0.000009659136,0.00019159219],"genre_scores_gemma":[0.9989831,0.000041124542,0.0002866856,0.000007488371,0.0000031983825,0.000008176365,0.000075388925,0.0000047841913,0.00059011223],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994755,0.000006158896,0.0000049413984,0.0000141183045,0.000013121935,0.000014190711],"domain_scores_gemma":[0.9996333,0.00013143565,0.000085650056,0.00003299302,0.000049852955,0.00006671107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002255419,0.00014820021,0.00015457459,0.00026354217,0.00015080233,0.00021174701,0.00023255417,0.00027448975,0.0019536596],"category_scores_gemma":[0.0009141789,0.000120125485,0.00011170995,0.00016380985,0.00034856205,0.0003085283,0.0002443204,0.00046398677,0.00019052955],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049630655,0.0008229581,0.026123088,0.00013163901,0.00016308586,0.0016649503,0.0003049063,0.0038956106,0.91789204,0.00051341014,0.00031512315,0.04321027],"study_design_scores_gemma":[0.0001411841,0.004649516,0.7406303,0.00001966268,0.00011718365,0.005081876,0.00044812745,0.026501015,0.2193796,0.002138231,0.00085529475,0.000037970778],"about_ca_topic_score_codex":0.0025809559,"about_ca_topic_score_gemma":0.0027407645,"teacher_disagreement_score":0.0025809559,"about_ca_system_score_codex":0.00020798977,"about_ca_system_score_gemma":0.00033456364,"threshold_uncertainty_score":0.0065356493},"labels":[],"label_agreement":null},{"id":"W3155343819","doi":"10.1038/s41598-021-87801-y","title":"A longitudinal analysis of brain extracellular free water in HIV infected individuals","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Cart; Neuroinflammation; White matter; Human immunodeficiency virus (HIV); Biomarker; Medicine; Grey matter; Internal medicine; Antiretroviral therapy; Inflammation; Immunology; Viral load; Biology; Magnetic resonance imaging","score_opus":0.047501977787179815,"score_gpt":0.3340657475831126,"score_spread":0.2865637697959328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155343819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99858403,0.0003463341,0.00036466515,0.000030213041,0.0000060852803,0.0000072439616,0.00044032407,0.000009347762,0.00021172423],"genre_scores_gemma":[0.99880445,0.00012644348,0.00041739366,0.000018041072,0.000005209264,0.000010255405,0.00040767284,0.0000024747344,0.00020811192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999908,0.000026374564,0.0000071076406,0.000027263812,0.000015470892,0.000015738371],"domain_scores_gemma":[0.9995999,0.000046982954,0.00016595796,0.000049981296,0.000079790705,0.000057347133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042484165,0.00014954295,0.0001313518,0.00041916475,0.00029521654,0.00029739,0.00014207036,0.00029823242,0.0005261272],"category_scores_gemma":[0.0010130358,0.0001263879,0.00018423618,0.00040006326,0.00010587063,0.00027123553,0.0002422728,0.0003125324,0.00011374311],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006709885,0.00008922821,0.9828903,0.000040021834,0.00021316284,0.00014033218,0.00021270613,0.00015749603,0.006264159,0.000046024186,0.00025122878,0.009024411],"study_design_scores_gemma":[0.000005372452,0.00026006898,0.99784863,0.0000070972383,0.00005640904,0.0002760329,0.000102057886,0.00038346,0.00068990164,0.000047907295,0.00031814852,0.000004896396],"about_ca_topic_score_codex":0.0036580611,"about_ca_topic_score_gemma":0.0043660244,"teacher_disagreement_score":0.0036580611,"about_ca_system_score_codex":0.00015327509,"about_ca_system_score_gemma":0.00019149319,"threshold_uncertainty_score":0.007273555},"labels":[],"label_agreement":null},{"id":"W3155614392","doi":"10.1016/j.nicl.2021.102682","title":"Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Gates Cambridge Trust; Evelyn Trust; Royal College of Anaesthetists; National Institute for Health and Care Research; UCLH Biomedical Research Centre; Medical Research Council; Canadian Institute for Advanced Research; Cambridge Trust; University of Cambridge","keywords":"Consciousness; Covert; Psychology; Diffusion MRI; Neuroscience; Connectome; Human brain; Wakefulness; Minimally conscious state; Insula; Persistent vegetative state; Traumatic brain injury; Connectomics; Brain Structure and Function; Cognition; Medicine; Functional connectivity; Psychiatry; Electroencephalography; Magnetic resonance imaging; Philosophy; Radiology","score_opus":0.061548807699788086,"score_gpt":0.39124322639458503,"score_spread":0.32969441869479693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155614392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994023,0.000054249147,0.00040718575,0.000011241655,8.239451e-7,0.0000015510901,0.000017311624,0.0000036310435,0.00010180207],"genre_scores_gemma":[0.99980515,0.000024401726,0.000109677516,0.0000024036165,0.0000016044769,0.0000013770753,0.000028553575,9.959707e-7,0.000025883908],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994206,0.000008385091,0.00000816893,0.000014920553,0.0000117073905,0.000014675439],"domain_scores_gemma":[0.999332,0.00013748062,0.00034716103,0.00006082569,0.0000423017,0.000080212536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012601184,0.0001444961,0.00020139705,0.00082293357,0.00016237526,0.00026495708,0.00011059293,0.00018478528,0.0006359566],"category_scores_gemma":[0.0011826521,0.00010019004,0.00010485248,0.00028104894,0.0003868909,0.0002408258,0.000288659,0.00018049982,0.000046550776],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015010579,0.00013139934,0.7439232,0.00011515579,0.00029215537,0.0025187589,0.0015024283,0.0016625681,0.20508964,0.0008212769,0.0002693233,0.04217303],"study_design_scores_gemma":[0.0000048389793,0.000119108954,0.99316376,0.000004467964,0.000019205105,0.0016106399,0.00014953637,0.0014623153,0.0028117462,0.00055605423,0.00009231014,0.000005972356],"about_ca_topic_score_codex":0.00061303354,"about_ca_topic_score_gemma":0.0008350501,"teacher_disagreement_score":0.00082293357,"about_ca_system_score_codex":0.0001445154,"about_ca_system_score_gemma":0.000075936325,"threshold_uncertainty_score":0.0021274686},"labels":[],"label_agreement":null},{"id":"W3155621432","doi":"10.1101/2021.04.15.440008","title":"Analyzing Brain Morphology in Alzheimer’s Disease Using Discriminative and Generative Spiral Networks","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Quest High Performance Computing; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Biogen; Northwestern University; Pfizer; BioClinica; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Discriminative model; Artificial intelligence; Computer science; Pattern recognition (psychology); Brain morphometry; Deep learning; Polygon mesh; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.06827813142636037,"score_gpt":0.3267201999764108,"score_spread":0.2584420685500504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155621432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72608346,0.00027367676,0.271794,0.00030620807,0.000020383823,0.000026439122,0.0001743989,0.00038323711,0.0009381948],"genre_scores_gemma":[0.9838209,0.000065061875,0.015391865,0.000025429925,0.000006556556,0.000009281583,0.00014193443,0.000010484364,0.0005285227],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999031,0.000023342847,0.000004220517,0.000031355805,0.000019357878,0.00001867426],"domain_scores_gemma":[0.99967635,0.00012507767,0.000066373796,0.00004037678,0.00005984079,0.000031962816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004261136,0.00042014362,0.00025774038,0.0007687297,0.00014717614,0.0003334739,0.0004534359,0.00039400748,0.000511824],"category_scores_gemma":[0.0010961827,0.00024156123,0.00042577335,0.0004442857,0.00038376087,0.00041045513,0.00047075553,0.0003612868,0.00009338998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036899847,0.00012771391,0.023772644,0.000042628035,0.00008724254,0.00023173557,0.00010043901,0.826066,0.024460731,0.0038413561,0.0006660974,0.12023435],"study_design_scores_gemma":[0.0000023672228,0.000021666925,0.0021096114,0.0000017969475,0.0000048911547,0.00002719666,0.000006098971,0.99502337,0.001088018,0.0016566119,0.00005556215,0.0000028552008],"about_ca_topic_score_codex":0.00406944,"about_ca_topic_score_gemma":0.00503112,"teacher_disagreement_score":0.00406944,"about_ca_system_score_codex":0.0006329465,"about_ca_system_score_gemma":0.00026534588,"threshold_uncertainty_score":0.008091509},"labels":[],"label_agreement":null},{"id":"W3156076616","doi":"10.1016/j.neuroimage.2021.118084","title":"Association between breastfeeding during infancy and white matter microstructure in early childhood","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Alberta Children's Hospital Foundation; Alberta Innovates; Alberta Innovates - Health Solutions; Fondation pour la Recherche Médicale; Children's Hospital Foundation","keywords":"Breastfeeding; Association (psychology); White matter; White (mutation); Psychology; Developmental psychology; Pediatrics; Medicine; Genetics; Biology; Magnetic resonance imaging","score_opus":0.013563087550743673,"score_gpt":0.27665195303463025,"score_spread":0.2630888654838866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156076616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99903464,0.0005965714,0.000052819618,0.000016116202,0.0000013277267,0.0000013435313,0.00010652957,0.0000015365573,0.00018912907],"genre_scores_gemma":[0.99902225,0.0004793838,0.00021319707,0.000011027998,0.0000035473336,0.0000048002375,0.0001235218,0.0000017359629,0.00014051248],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997919,0.000045406327,0.000020382984,0.000051494517,0.000047087044,0.000043767523],"domain_scores_gemma":[0.9989548,0.00018646472,0.0006087476,0.00004788956,0.000112953756,0.000089047695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000500436,0.00016990367,0.00022118914,0.0003806088,0.00025545855,0.00042653142,0.00016368182,0.00024973013,0.00087899884],"category_scores_gemma":[0.0015498379,0.00015641293,0.0001942352,0.00043922348,0.00019750358,0.00023491352,0.0002722784,0.00020599483,0.00010972924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006951724,0.000014838202,0.9954678,0.000022753917,0.0000502689,0.000077457924,0.00014437466,0.000022862849,0.0009182163,0.000017264187,0.000029780838,0.003164866],"study_design_scores_gemma":[2.9244032e-7,0.000017683253,0.99963737,0.000004798093,0.000008766001,0.000117741794,0.00004268463,0.000015271404,0.00010463446,0.0000067746223,0.00004346429,5.217058e-7],"about_ca_topic_score_codex":0.0042221947,"about_ca_topic_score_gemma":0.008203208,"teacher_disagreement_score":0.0042221947,"about_ca_system_score_codex":0.00020351331,"about_ca_system_score_gemma":0.0002892946,"threshold_uncertainty_score":0.008395195},"labels":[],"label_agreement":null},{"id":"W3157261413","doi":"10.1016/j.media.2021.102093","title":"Track-to-Learn: A general framework for tractography with deep reinforcement learning","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Tractography; Reinforcement learning; Artificial intelligence; Computer science; Leverage (statistics); Deep learning; Machine learning; Artificial neural network; Prior probability; Diffusion MRI; Bayesian probability; Magnetic resonance imaging","score_opus":0.02872814233882151,"score_gpt":0.36618501131255343,"score_spread":0.33745686897373195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157261413","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001051401,0.00009472924,0.9973699,0.000075550095,0.000026329906,0.000024061103,0.000069816466,0.0010189415,0.0002692428],"genre_scores_gemma":[0.16867432,0.0004169835,0.82168823,0.0002358453,0.00013675075,0.0004316814,0.00067147875,0.0009811494,0.006763577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996364,0.00010203531,0.000021358432,0.00010232433,0.000085448715,0.00005249298],"domain_scores_gemma":[0.9990376,0.00045279888,0.00007476346,0.0001506999,0.00018368714,0.000100477795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016606341,0.0013741835,0.0014636096,0.0006660152,0.00051251776,0.0013166198,0.0035409064,0.0027597672,0.00506652],"category_scores_gemma":[0.004783224,0.00095208065,0.0010175442,0.0008953486,0.00091929524,0.0017241053,0.00263017,0.0034161117,0.0017042138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014822255,0.00007655396,0.00055673753,0.00009571309,0.000099256955,0.00008707806,0.00004527293,0.8090463,0.00167176,0.024349239,0.00566022,0.15816359],"study_design_scores_gemma":[0.0000059131985,0.000008901915,0.000019414756,0.0000030860049,0.000003391114,0.000006850056,0.0000010929589,0.9930375,0.0002803346,0.0062236665,0.00040673505,0.0000030490598],"about_ca_topic_score_codex":0.012970424,"about_ca_topic_score_gemma":0.01586726,"teacher_disagreement_score":0.012970424,"about_ca_system_score_codex":0.0011179487,"about_ca_system_score_gemma":0.002037788,"threshold_uncertainty_score":0.025789857},"labels":[],"label_agreement":null},{"id":"W3157623118","doi":"10.1002/dev.22125","title":"Prenatal antidepressant exposure and sex differences in neonatal corpus callosum microstructure","year":2021,"lang":"en","type":"article","venue":"Developmental Psychobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; BC Children's Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Serotonin reuptake inhibitor; Diffusion MRI; White matter; Psychology; Offspring; Sertraline; Prenatal cocaine exposure; Internal medicine; Physiology; Antidepressant; Medicine; Pregnancy; Prenatal exposure; Neuroscience; Biology; Hippocampus; Magnetic resonance imaging; Genetics","score_opus":0.03536373551815285,"score_gpt":0.3114868481929179,"score_spread":0.276123112674765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157623118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99873334,0.0004231704,0.00026664266,0.000018017265,0.0000037260024,0.000003932104,0.00019170565,0.0000066327148,0.00035289163],"genre_scores_gemma":[0.9984016,0.0004525719,0.00033744765,0.000018569306,0.00000241108,0.000018857054,0.00015303341,0.0000044779263,0.0006110819],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99988556,0.000016757316,0.000011193801,0.00004394897,0.000028217213,0.0000142082745],"domain_scores_gemma":[0.9997087,0.000050922496,0.0001456319,0.000028647783,0.00003332471,0.00003263602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001456816,0.00018962103,0.00017314598,0.00032126805,0.0001054876,0.0002005954,0.00012157365,0.00018698444,0.0011114648],"category_scores_gemma":[0.000563976,0.00009816238,0.000115337614,0.00012568255,0.00018318118,0.00009040445,0.00016112722,0.00017388054,0.00009268175],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011901112,0.00012373074,0.32590514,0.000108051485,0.00009331602,0.0013484344,0.00058994984,0.00013974983,0.6314067,0.00026605377,0.00020194106,0.038626794],"study_design_scores_gemma":[0.0000024637718,0.00021625047,0.9760299,0.0000091487855,0.000024964454,0.0005781243,0.000115205396,0.0001210231,0.022574672,0.00004765334,0.00027580018,0.00000480496],"about_ca_topic_score_codex":0.001441866,"about_ca_topic_score_gemma":0.0021651646,"teacher_disagreement_score":0.001441866,"about_ca_system_score_codex":0.00016079738,"about_ca_system_score_gemma":0.0001550387,"threshold_uncertainty_score":0.003718257},"labels":[],"label_agreement":null},{"id":"W3157703355","doi":"10.1503/jpn.200167","title":"Acute conceptual disorganization in untreated first-episode psychosis: a combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum","year":2021,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Dalhousie University; Western University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Chrysalis","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Glutamate receptor; Neuroscience; Glutathione; Psychology; Anterior cingulate cortex; Internal medicine; Oxidative stress; Psychosis; Diffusion MRI; Chemistry; Magnetic resonance imaging; Pathology; Medicine; Psychiatry; Cognition; Biochemistry; Radiology","score_opus":0.01456719505833476,"score_gpt":0.2988177442904961,"score_spread":0.28425054923216136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157703355","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99955326,0.00011209142,0.00008184813,0.000029764586,0.0000021825435,0.000010949184,0.000020443502,0.0000024983547,0.00018713437],"genre_scores_gemma":[0.99967515,0.00006446027,0.00014068317,0.000014719776,0.0000037632003,0.0000065629624,0.00003639908,0.0000013343631,0.000056820652],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998852,0.00002373015,0.000010135694,0.000020449843,0.000027968206,0.00003242024],"domain_scores_gemma":[0.99967766,0.00006000705,0.000117454714,0.000028075188,0.000035153913,0.00008160787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040206013,0.00035337155,0.0002217149,0.0009901955,0.0006812159,0.00052251585,0.00025773648,0.0004572512,0.001094666],"category_scores_gemma":[0.0010344352,0.0003147511,0.00018219072,0.0005316804,0.00047681644,0.00033280218,0.00053361326,0.00043160148,0.00009924798],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030571618,0.0008131598,0.84404033,0.00019574579,0.00030109633,0.02036535,0.0030769345,0.00045421437,0.09876339,0.0003576542,0.00038871082,0.02818617],"study_design_scores_gemma":[0.00003381456,0.00023457142,0.9944636,0.000009399559,0.000031392432,0.0038463236,0.00035242233,0.0002634597,0.0005403237,0.00009066115,0.00012719685,0.000006713265],"about_ca_topic_score_codex":0.004806736,"about_ca_topic_score_gemma":0.010327217,"teacher_disagreement_score":0.004806736,"about_ca_system_score_codex":0.00038172107,"about_ca_system_score_gemma":0.00035426405,"threshold_uncertainty_score":0.009557486},"labels":[],"label_agreement":null},{"id":"W3157720323","doi":"10.3389/fnagi.2021.644137","title":"Automated Midline Estimation for Symmetry Analysis of Cerebral Hemispheres in FLAIR MRI","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Toronto; Toronto Metropolitan University","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Consortium canadien en neurodégénérescence associée au vieillissement; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Sagittal plane; Neuroimaging; Curvature; Artificial intelligence; Hausdorff distance; Pattern recognition (psychology); Mathematics; Computer science; Medicine; Anatomy; Neuroscience; Psychology; Geometry","score_opus":0.032223451133355986,"score_gpt":0.3523278105059971,"score_spread":0.3201043593726411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157720323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15310596,0.0008712784,0.83841884,0.00011806922,0.00007339493,0.00023919155,0.00095987314,0.004655826,0.0015574328],"genre_scores_gemma":[0.4225416,0.0005129759,0.5729178,0.00006571585,0.00007839225,0.00015952339,0.0020144512,0.0005998843,0.0011097157],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928504,0.00014875589,0.000058048234,0.0002005134,0.00020995676,0.00009769354],"domain_scores_gemma":[0.998877,0.00024867672,0.00029125763,0.00016063955,0.00035696945,0.0000654827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018497,0.00086357206,0.00063245295,0.0027054455,0.00041397067,0.0010297877,0.00089757924,0.0005556057,0.001907379],"category_scores_gemma":[0.0031291875,0.00033395083,0.0008375471,0.0007711249,0.00030089507,0.0009187712,0.0010783143,0.0005593246,0.0011643043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068373693,0.00011504187,0.013718049,0.0003217647,0.00021786954,0.0006096112,0.00034676678,0.010802856,0.26556346,0.0026194695,0.00452281,0.7004786],"study_design_scores_gemma":[0.00016612599,0.0005691715,0.104659595,0.00012798484,0.00027589285,0.0051148576,0.0008412608,0.5789171,0.28548825,0.011871861,0.011717112,0.00025083558],"about_ca_topic_score_codex":0.0018568328,"about_ca_topic_score_gemma":0.0030026939,"teacher_disagreement_score":0.0027054455,"about_ca_system_score_codex":0.00031163293,"about_ca_system_score_gemma":0.000776418,"threshold_uncertainty_score":0.0063807964},"labels":[],"label_agreement":null},{"id":"W3157741688","doi":"10.1101/2021.04.30.442198","title":"Multimodal brain features at preschool age and the relationship with pre-reading measures one year later: an exploratory study","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Psychology; White matter; Fasciculus; Reading (process); Diffusion MRI; Association (psychology); Default mode network; Uncinate fasciculus; Developmental psychology; Cognitive psychology; Grey matter; Superior longitudinal fasciculus; Neuroscience; Audiology; Functional connectivity; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.049359507871745915,"score_gpt":0.29129701714609696,"score_spread":0.24193750927435104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157741688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994783,0.00006658093,0.000055124197,0.000007357256,0.0000012980447,0.0000067593473,0.00023893215,0.0000043040604,0.0001414792],"genre_scores_gemma":[0.99899656,0.000059496444,0.00017810597,0.000006552268,0.0000024203152,0.000021479287,0.00041602942,0.0000026980233,0.00031661685],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996885,0.00004548488,0.000026165968,0.000092343966,0.00005846889,0.000089010835],"domain_scores_gemma":[0.99901414,0.00018020895,0.00034047922,0.000085875654,0.00018064497,0.00019857289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007648173,0.0005774554,0.00053450227,0.0017572072,0.00068428315,0.0008289606,0.00043898175,0.0009115556,0.001296021],"category_scores_gemma":[0.0018547898,0.00027149168,0.00073877344,0.0008595805,0.00051496277,0.00070075615,0.00068348576,0.0008061581,0.00036886593],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000469803,0.0004122795,0.98523986,0.000033319342,0.00008594487,0.001728447,0.0018146018,0.00013521193,0.0044394326,0.00008606191,0.00014326733,0.0054118414],"study_design_scores_gemma":[0.0000020949312,0.00024278881,0.9986229,0.0000042746133,0.000016135422,0.00024031545,0.00040674832,0.00004953423,0.0003008926,0.000026577633,0.000083017774,0.0000047042276],"about_ca_topic_score_codex":0.012730161,"about_ca_topic_score_gemma":0.012739291,"teacher_disagreement_score":0.012730161,"about_ca_system_score_codex":0.00060147635,"about_ca_system_score_gemma":0.0005705794,"threshold_uncertainty_score":0.025312126},"labels":[],"label_agreement":null},{"id":"W3157892933","doi":"10.1016/j.neuroimage.2021.118105","title":"Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Artificial intelligence; Sulcus; Cortex (anatomy); Segmentation; Pattern recognition (psychology); Computer vision; Computer science; Neuroscience; Physics; Nuclear magnetic resonance; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.062893996120765,"score_gpt":0.36465059032077024,"score_spread":0.3017565942000052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157892933","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30885178,0.0018666912,0.684973,0.00010807618,0.000057792826,0.00019864267,0.00040541735,0.0018135422,0.0017250584],"genre_scores_gemma":[0.6697261,0.0007262267,0.3273171,0.00005368666,0.000034959205,0.0001818248,0.0005043903,0.0002644539,0.0011912491],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99959666,0.000094039795,0.000023955974,0.0001464108,0.00009424791,0.00004467403],"domain_scores_gemma":[0.99952674,0.00014511381,0.00008557813,0.00008057836,0.0001390214,0.00002292192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007539536,0.0005983924,0.0006049907,0.0017018205,0.00039551806,0.00075359584,0.0005035395,0.00055366766,0.0010704773],"category_scores_gemma":[0.0018454944,0.00035860942,0.0006329715,0.00078612723,0.0003925798,0.0006844593,0.0004886984,0.00030325574,0.0004806437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046102464,0.00006608308,0.009308904,0.00039200808,0.0002672995,0.00039675628,0.0004947169,0.0217915,0.6108983,0.002464465,0.0013805989,0.3520783],"study_design_scores_gemma":[0.00011155049,0.00031923928,0.08763853,0.00009602828,0.00033083628,0.0019800034,0.00028327937,0.56442916,0.3311135,0.007938045,0.0055708615,0.00018889093],"about_ca_topic_score_codex":0.0045804475,"about_ca_topic_score_gemma":0.006855657,"teacher_disagreement_score":0.0045804475,"about_ca_system_score_codex":0.00039436316,"about_ca_system_score_gemma":0.00088692567,"threshold_uncertainty_score":0.00910753},"labels":[],"label_agreement":null},{"id":"W3158036197","doi":"10.3174/ajnr.a7135","title":"Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Cincinnati Children's Hospital Medical Center","keywords":"Bayley Scales of Infant Development; Medicine; Toddler; Corpus callosum; Corticospinal tract; Gestational age; White matter; Diffusion MRI; Pediatrics; Superior longitudinal fasciculus; Fornix; Inferior longitudinal fasciculus; Cohort; Motor skill; Audiology; Cognition; Fractional anisotropy; Psychomotor learning; Psychology; Magnetic resonance imaging; Internal medicine; Developmental psychology; Pathology; Radiology; Psychiatry; Hippocampus","score_opus":0.027758594541992417,"score_gpt":0.30327428062151734,"score_spread":0.2755156860795249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158036197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996327,0.0001129189,0.000054761553,0.000012841503,0.0000012611893,0.0000016663902,0.0000892322,0.000002628569,0.00009202356],"genre_scores_gemma":[0.9995883,0.00007448383,0.000101829275,0.0000060249076,0.000002610643,0.0000039327233,0.00015380571,0.0000017652067,0.00006733149],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997136,0.00005180572,0.000044807442,0.00007119307,0.00006434537,0.000054249693],"domain_scores_gemma":[0.9980775,0.00022375547,0.0011998191,0.00008052133,0.00019309504,0.00022532877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062025886,0.0003725974,0.00024486048,0.0011244119,0.00033543297,0.00042791627,0.00039010597,0.00048101472,0.0008013506],"category_scores_gemma":[0.0028411099,0.00019990899,0.00036259784,0.0005320363,0.0003786915,0.00026971768,0.0005790888,0.00044721097,0.00013201579],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000107352236,0.000016459104,0.99573624,0.000011233493,0.000043749067,0.000489325,0.00013489265,0.00009280935,0.0016815903,0.000020892492,0.00005515479,0.0016102728],"study_design_scores_gemma":[6.284582e-7,0.000027128794,0.99912554,0.0000040309046,0.0000105149375,0.00048211284,0.000044182365,0.000067550965,0.00019741841,0.0000123374975,0.000026881324,0.0000016267267],"about_ca_topic_score_codex":0.010524209,"about_ca_topic_score_gemma":0.011465587,"teacher_disagreement_score":0.010524209,"about_ca_system_score_codex":0.00048341916,"about_ca_system_score_gemma":0.0004058064,"threshold_uncertainty_score":0.02092594},"labels":[],"label_agreement":null},{"id":"W3158162652","doi":"10.1101/2021.05.04.442563","title":"BigBrainWarp: Toolbox for integration of BigBrain 3D histology with multimodal neuroimaging","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canada Research Chairs; Canada First Research Excellence Fund; Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada","keywords":"Toolbox; Neuroimaging; Computer science; Cytoarchitecture; Workflow; Neuroanatomy; Data science; Neuroscience; Psychology","score_opus":0.040886385645263826,"score_gpt":0.29584191244531444,"score_spread":0.2549555268000506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158162652","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021658354,0.00031567313,0.7781721,0.0002509738,0.00015687157,0.00019544928,0.006067106,0.20967014,0.0030058492],"genre_scores_gemma":[0.046063196,0.0011513964,0.78584915,0.00092245865,0.00013716395,0.0018807856,0.020662205,0.13378099,0.009552711],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931,0.00013068582,0.00007814359,0.0001402942,0.00026319822,0.00007774147],"domain_scores_gemma":[0.99792373,0.001011203,0.00016799224,0.0003905453,0.00032607384,0.00018046398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002352858,0.0021530103,0.00097183255,0.0020864566,0.00064809184,0.0029755433,0.003286288,0.0015164814,0.060605653],"category_scores_gemma":[0.0070381723,0.0018186944,0.0018828658,0.0009199283,0.0009864992,0.0022385314,0.0044264696,0.0030542386,0.023095427],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012693593,0.00027295735,0.0053368555,0.00369325,0.0009670595,0.0021259864,0.0019589157,0.038464542,0.055282857,0.05553972,0.43940347,0.39568505],"study_design_scores_gemma":[0.0004884918,0.00020111632,0.0052243867,0.00079354417,0.00014944255,0.002464977,0.00032750232,0.3302104,0.091624014,0.12953945,0.43853134,0.00044533436],"about_ca_topic_score_codex":0.0017562605,"about_ca_topic_score_gemma":0.0034122681,"teacher_disagreement_score":0.060605653,"about_ca_system_score_codex":0.0007333251,"about_ca_system_score_gemma":0.0016954947,"threshold_uncertainty_score":0.2027461},"labels":[],"label_agreement":null},{"id":"W3158290997","doi":"10.21203/rs.3.rs-134624/v1","title":"Alterations of White Matter Integrity in Cerebral Small Vessel Disease and Their Correlation with Cognitive Performance: A Trace-Based Spatial Statistics Study","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Anhui University of Science and Technology; Anhui University","keywords":"Internal capsule; White matter; Fasciculus; Hyperintensity; Corona radiata (embryology); Cognition; Diffusion MRI; Psychology; Neuropsychology; Cardiology; Medicine; Audiology; Internal medicine; Magnetic resonance imaging; Neuroscience; Radiology; Fractional anisotropy","score_opus":0.10786503691275992,"score_gpt":0.4086379345883682,"score_spread":0.30077289767560833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158290997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987691,0.00009569928,0.00079262396,0.000012063957,0.000002085241,0.0000044430194,0.00010064612,0.00001347067,0.00020964553],"genre_scores_gemma":[0.99953115,0.000022022547,0.0002600019,0.0000019071387,0.0000044471644,0.0000023844807,0.000112408474,0.0000024480817,0.00006343174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977046,0.000054725555,0.000042174568,0.00005227719,0.000054786233,0.000025569685],"domain_scores_gemma":[0.99769336,0.0006545606,0.00085822295,0.00030346215,0.0002618076,0.00022863399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083428656,0.00028149545,0.00022543933,0.0014169039,0.00018612706,0.00043095765,0.00028331717,0.00028196335,0.0015085413],"category_scores_gemma":[0.0036875587,0.00010463055,0.00035076332,0.0010139225,0.00035848003,0.00038523015,0.00037821278,0.000224654,0.00018697999],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073549163,0.0000889712,0.9856419,0.00004081148,0.00021797999,0.0002479253,0.00016635568,0.0005430279,0.003232809,0.000110664274,0.00007677452,0.00889732],"study_design_scores_gemma":[0.000010162425,0.00039473505,0.9921293,0.0000063047537,0.00008556603,0.001043386,0.00016281959,0.004584648,0.0011318201,0.00028481486,0.00015690182,0.000009464358],"about_ca_topic_score_codex":0.0014966462,"about_ca_topic_score_gemma":0.0012773832,"teacher_disagreement_score":0.0015085413,"about_ca_system_score_codex":0.00013397893,"about_ca_system_score_gemma":0.00023617927,"threshold_uncertainty_score":0.0050465465},"labels":[],"label_agreement":null},{"id":"W3158401871","doi":"10.1093/neuros/nyab129","title":"Enhanced Fiber Tractography Using Edema Correction: Application and Evaluation in High-Grade Gliomas","year":2021,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; Diffusion MRI; Edema; Fractional anisotropy; Magnetic resonance imaging; Tractography; Fiber tract; Functional magnetic resonance imaging; Radiology; Nuclear medicine; Surgery","score_opus":0.06992008219545898,"score_gpt":0.3594106578960899,"score_spread":0.2894905757006309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158401871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9819509,0.0002588174,0.017452963,0.000019239225,0.0000038195685,0.000041436142,0.00005122818,0.00007941461,0.0001421326],"genre_scores_gemma":[0.97949684,0.00019889104,0.020010928,0.0000059926356,0.0000038540484,0.000021056412,0.0000978787,0.000017608767,0.00014689745],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998404,0.000061608764,0.000014754676,0.00002640983,0.000042375035,0.000014356215],"domain_scores_gemma":[0.9989286,0.00035688086,0.00026448868,0.000120802586,0.0002500294,0.00007915645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097420113,0.00032837663,0.00016398926,0.00053661206,0.00013768036,0.00032708936,0.00024935446,0.00030226857,0.00043890724],"category_scores_gemma":[0.00329589,0.00011097948,0.00014547019,0.00026379735,0.00018097855,0.00032279053,0.00024100681,0.00015112954,0.00009916162],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0047149397,0.0007366806,0.426865,0.0005264942,0.00025631662,0.0022168874,0.0006150634,0.04544655,0.18853332,0.00046164147,0.00040363395,0.32922345],"study_design_scores_gemma":[0.00021833158,0.00469433,0.5414363,0.00006862225,0.00033964953,0.010523738,0.00027549997,0.2632479,0.17570396,0.00069604744,0.0027102863,0.000085408115],"about_ca_topic_score_codex":0.0019168184,"about_ca_topic_score_gemma":0.003611182,"teacher_disagreement_score":0.0019168184,"about_ca_system_score_codex":0.00028981443,"about_ca_system_score_gemma":0.00041394087,"threshold_uncertainty_score":0.005152166},"labels":[],"label_agreement":null},{"id":"W3158565540","doi":"10.1038/s41598-021-93804-6","title":"Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Diffusion MRI; Medicine; Convolutional neural network; Tumour heterogeneity; Pathology; Radiology; Magnetic resonance imaging; Artificial intelligence; Computer science; Cancer; Internal medicine","score_opus":0.021725531046511117,"score_gpt":0.2862008277712664,"score_spread":0.2644752967247553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158565540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9415944,0.0008473378,0.055601016,0.00016121064,0.000022041871,0.000042055115,0.0004324051,0.000380982,0.00091857824],"genre_scores_gemma":[0.9893991,0.00016640907,0.009268845,0.000047044938,0.000009707152,0.00002181324,0.0006180341,0.000021819358,0.0004472921],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998417,0.000029700943,0.000011752167,0.000043313394,0.0000323878,0.00004109897],"domain_scores_gemma":[0.99977916,0.00006222201,0.000059897302,0.000022862121,0.000043349035,0.000032469652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046981743,0.0005300208,0.00043076382,0.0009380673,0.00011393047,0.00048297792,0.00035262565,0.00034476098,0.00033305486],"category_scores_gemma":[0.000988887,0.00018188488,0.00037688212,0.000344398,0.0002517879,0.00045552122,0.0005248922,0.00040337213,0.00017804724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013603268,0.0003531038,0.13717791,0.00035347676,0.00030774213,0.0009227604,0.00032335793,0.21014713,0.29959032,0.001905538,0.002393351,0.34516492],"study_design_scores_gemma":[0.000018317905,0.00013254283,0.04283422,0.000029517134,0.0000631247,0.0003656813,0.00008921012,0.9207886,0.032786276,0.0019824067,0.0008829934,0.000027123097],"about_ca_topic_score_codex":0.005441623,"about_ca_topic_score_gemma":0.006916722,"teacher_disagreement_score":0.005441623,"about_ca_system_score_codex":0.00046550983,"about_ca_system_score_gemma":0.00036085158,"threshold_uncertainty_score":0.010819912},"labels":[],"label_agreement":null},{"id":"W3158925026","doi":"10.1016/j.mri.2021.04.015","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Linear regression; Kurtosis; Tensor (intrinsic definition); Mathematics; Nuclear magnetic resonance; Orientation (vector space); Physics; Algorithm; Biological system; Statistics; Optics; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.033325878600253406,"score_gpt":0.3471952327520925,"score_spread":0.31386935415183914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158925026","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013815962,0.00008943813,0.997375,0.0001418724,0.000018301394,0.0000178844,0.00003930936,0.00026862562,0.0006679268],"genre_scores_gemma":[0.06406989,0.0004314345,0.9251904,0.00015853708,0.00010618147,0.00020895743,0.00023808087,0.00068455265,0.008911824],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996489,0.00012050455,0.000015787353,0.00007107158,0.00011534946,0.00002843255],"domain_scores_gemma":[0.9990108,0.0006176402,0.000114377435,0.00006744454,0.00015125405,0.000038500744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012242532,0.0012211185,0.0010831563,0.000541679,0.0003534637,0.0010734316,0.00124766,0.0015863405,0.0038495446],"category_scores_gemma":[0.0028909636,0.0010065042,0.00073800224,0.0007336701,0.0007180739,0.0017695777,0.0013656216,0.0019115038,0.0014729707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001391074,0.00007591095,0.00029098158,0.00025337192,0.00009810303,0.00017110142,0.00009518743,0.7966661,0.01926015,0.06566849,0.0063799927,0.11090155],"study_design_scores_gemma":[0.000006654091,0.00001292329,0.000026146703,0.00000435859,0.000006833562,0.000026693871,0.0000037307814,0.9932186,0.001316707,0.004100527,0.0012696196,0.0000072562325],"about_ca_topic_score_codex":0.0039666872,"about_ca_topic_score_gemma":0.0053990926,"teacher_disagreement_score":0.0039666872,"about_ca_system_score_codex":0.00070500706,"about_ca_system_score_gemma":0.0017293056,"threshold_uncertainty_score":0.012878001},"labels":[],"label_agreement":null},{"id":"W3159817322","doi":"10.1002/hbm.25447","title":"Surface‐Based Connectivity Integration: An atlas‐free approach to jointly study functional and structural connectivity","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Connectomics; Connectome; Atlas (anatomy); Human Connectome Project; Computer science; Functional connectivity; Diffusion MRI; Brain atlas; Artificial intelligence; White matter; Tractography; Neuroscience; Machine learning; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Biology; Medicine","score_opus":0.16487722636405025,"score_gpt":0.3651398220156734,"score_spread":0.20026259565162316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159817322","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005812496,0.00010181532,0.9927787,0.000053307715,0.000013651936,0.000049141505,0.00018953375,0.0006118061,0.00038958155],"genre_scores_gemma":[0.1531456,0.00038515805,0.8425739,0.00008486526,0.00009665076,0.00036382055,0.0015351924,0.00078961166,0.0010252538],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884915,0.00035211325,0.0000559795,0.00026516998,0.00040047665,0.000077121564],"domain_scores_gemma":[0.9982053,0.00076281495,0.00027385258,0.0003853655,0.0002887353,0.000084058745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019705927,0.0012224772,0.0014032332,0.005185736,0.0006111891,0.0016397405,0.0015102624,0.0010238215,0.0017633556],"category_scores_gemma":[0.0060750456,0.0006496146,0.0015533534,0.0044036675,0.0011220783,0.0017454181,0.002421106,0.0013807814,0.00054804055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025720175,0.00015734234,0.008535063,0.00046860095,0.0010752745,0.00051085063,0.00081450795,0.28359577,0.067781284,0.09101316,0.008422122,0.5373688],"study_design_scores_gemma":[0.000024302797,0.00011478619,0.0058104615,0.000024078397,0.000104394385,0.00038692323,0.00008580167,0.90547925,0.0070047486,0.07466416,0.0062162704,0.00008485592],"about_ca_topic_score_codex":0.0051934905,"about_ca_topic_score_gemma":0.008089975,"teacher_disagreement_score":0.0051934905,"about_ca_system_score_codex":0.00092411175,"about_ca_system_score_gemma":0.0016774023,"threshold_uncertainty_score":0.010421574},"labels":[],"label_agreement":null},{"id":"W3159963675","doi":"10.1007/s11682-021-00474-z","title":"Microstructural white matter alterations in Alzheimer’s disease and amnestic mild cognitive impairment and its diagnostic value based on diffusion kurtosis imaging: a tract-based spatial statistics study","year":2021,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Psychology; Corpus callosum; Montreal Cognitive Assessment; Receiver operating characteristic; Splenium; Kurtosis; Audiology; Alzheimer's disease; Internal medicine; Cognition; Medicine; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Neuroscience; Disease; Radiology; Statistics; Mathematics","score_opus":0.031105694128074186,"score_gpt":0.34146480268428503,"score_spread":0.31035910855621085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159963675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991345,0.00019612067,0.00040309472,0.000014599747,0.0000026398395,0.0000071236327,0.000040490053,0.000004387922,0.0001971124],"genre_scores_gemma":[0.99951863,0.000060591257,0.0003131508,0.0000036532074,0.0000069810208,0.000003871475,0.0000331533,0.000002156585,0.000057763616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99962926,0.000114417795,0.0000745684,0.000056440975,0.00008796358,0.000037274836],"domain_scores_gemma":[0.9979079,0.0008151134,0.00063036755,0.00017706015,0.0002786655,0.00019083628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020051217,0.00052219495,0.00032338192,0.0030347605,0.00035100835,0.0005313154,0.0003279746,0.00047521922,0.00068888674],"category_scores_gemma":[0.0045003253,0.00027684914,0.00042738143,0.00070206804,0.00084949046,0.00090215734,0.0006195401,0.00028305638,0.00014386288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038320257,0.00024298894,0.962689,0.00007312437,0.0004220335,0.0012784248,0.0005582707,0.00091797306,0.014491398,0.00036035216,0.000105029605,0.015029331],"study_design_scores_gemma":[0.00003191284,0.0005189179,0.98837495,0.000011443276,0.00015516875,0.002486776,0.00039174204,0.0058895396,0.0014658712,0.0005336409,0.00011763956,0.000022493352],"about_ca_topic_score_codex":0.0027671852,"about_ca_topic_score_gemma":0.002167624,"teacher_disagreement_score":0.0030347605,"about_ca_system_score_codex":0.00034711923,"about_ca_system_score_gemma":0.00039039092,"threshold_uncertainty_score":0.010604203},"labels":[],"label_agreement":null},{"id":"W3160785216","doi":"10.1089/brain.2020.0919","title":"Selective Effects of Healthy Cognitive Aging and Catechol- <i>O</i> -Methyl Transferase Polymorphism on Limbic White Matter Tracts","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Uncinate fasciculus; Cingulum (brain); White matter; Fractional anisotropy; Psychology; Fasciculus; Diffusion MRI; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.02791763727745839,"score_gpt":0.32847616901103766,"score_spread":0.30055853173357927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160785216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993586,0.00019983231,0.00010011899,0.0000147289575,0.0000031456868,0.000003726572,0.00010433867,0.0000034014151,0.00021222437],"genre_scores_gemma":[0.99954224,0.000053766937,0.00012876574,0.000014073537,0.0000057068837,0.0000031887848,0.000082022416,0.0000032269272,0.00016704877],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985135,0.000026770049,0.000015929125,0.00006548391,0.000017461069,0.000022945424],"domain_scores_gemma":[0.99945396,0.00009808191,0.00027778253,0.000052480547,0.000041492374,0.00007628421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041353054,0.0003550268,0.0002721183,0.00034104803,0.0002598582,0.0003458109,0.00011564818,0.0002925801,0.0013742383],"category_scores_gemma":[0.00077828806,0.00013253116,0.00023294277,0.00027737278,0.00024805526,0.0001632801,0.00020769468,0.00014894482,0.00013048867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034752698,0.00013455532,0.958656,0.000042957392,0.00035797403,0.0005651497,0.00031165546,0.000101928454,0.029730314,0.000099369696,0.00013463169,0.0063902833],"study_design_scores_gemma":[0.0000063091597,0.00011365627,0.9991763,0.0000013264519,0.000035118694,0.00016734088,0.000017425202,0.000057905083,0.00033789413,0.000031948835,0.000052989075,0.0000016829665],"about_ca_topic_score_codex":0.0025766422,"about_ca_topic_score_gemma":0.0032956598,"teacher_disagreement_score":0.0025766422,"about_ca_system_score_codex":0.00014821421,"about_ca_system_score_gemma":0.00017099094,"threshold_uncertainty_score":0.0051233172},"labels":[],"label_agreement":null},{"id":"W3161462824","doi":"10.7554/elife.62929","title":"Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Université de Sherbrooke; McGill University; Douglas Mental Health University Institute","funders":"National Institute on Aging; Canadian Institutes of Health Research; Canada Foundation for Innovation; Fondation Jean-Louis Lévesque; Douglas Foundation","keywords":"Uncinate fasciculus; White matter; Fractional anisotropy; Cingulum (brain); Pathology; Diffusion MRI; Pathological; Fasciculus; Senile plaques; Medicine; Alzheimer's disease; Neuroscience; Disease; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.10071480621012831,"score_gpt":0.3869831842590818,"score_spread":0.2862683780489535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161462824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993206,0.00019578997,0.00021113831,0.000019707066,0.0000014636646,0.0000032071646,0.000038605685,0.00000523561,0.00020430646],"genre_scores_gemma":[0.99927276,0.00012539736,0.00035023983,0.00001163098,0.000004271232,0.0000034197922,0.000060359987,0.0000023902203,0.00016955116],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987316,0.00002375679,0.000014915542,0.0000415314,0.000023674576,0.00002295678],"domain_scores_gemma":[0.99952126,0.000036662546,0.00028351662,0.000043826378,0.000049898306,0.00006485408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049562525,0.00032484686,0.00024114794,0.0008148798,0.00027035153,0.0003489454,0.00016882025,0.0003287309,0.00082015555],"category_scores_gemma":[0.001073966,0.00026564457,0.0001570641,0.00038855826,0.00029356,0.00043024737,0.00038375353,0.00022682938,0.00012682735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016280474,0.00012429713,0.91652215,0.000051589184,0.00025241266,0.0004034774,0.00045696052,0.00039768298,0.06739512,0.00024836336,0.000187874,0.012332082],"study_design_scores_gemma":[0.000007698832,0.00010876208,0.9983713,0.000002912315,0.000019620638,0.00025128073,0.00004597281,0.00019030557,0.0007885942,0.00014430266,0.00006697724,0.0000022536542],"about_ca_topic_score_codex":0.0022951358,"about_ca_topic_score_gemma":0.0047094095,"teacher_disagreement_score":0.0022951358,"about_ca_system_score_codex":0.0001807485,"about_ca_system_score_gemma":0.00015200042,"threshold_uncertainty_score":0.00456357},"labels":[],"label_agreement":null},{"id":"W3161498656","doi":"10.1016/j.euroneuro.2021.04.007","title":"White matter microstructure alterations in cortico-striatal networks are associated with parkinsonism in schizophrenia spectrum disorders","year":2021,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Canadian Institutes of Health Research; Bundesministerium für Bildung und Forschung; Bundesministerium für Forschung und Technologie; Paul Scherrer Institut; Deutsche Forschungsgemeinschaft","keywords":"Parkinsonism; Fractional anisotropy; White matter; Corpus callosum; Neuroscience; Psychology; Diffusion MRI; Medicine; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.016529657064770126,"score_gpt":0.2938555308694761,"score_spread":0.27732587380470597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161498656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995907,0.000077035205,0.00013081804,0.000009899041,4.9844977e-7,0.0000029894868,0.00006372596,0.0000034236023,0.0001210033],"genre_scores_gemma":[0.99958175,0.00005744774,0.00022158252,0.000004246287,8.46379e-7,0.0000028984402,0.00007692586,0.0000013595578,0.000053072643],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990046,0.000017425376,0.000017283195,0.000028264549,0.000023215352,0.000013371232],"domain_scores_gemma":[0.99961424,0.000043306267,0.00024548595,0.000022233768,0.000026373405,0.00004832923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020201191,0.0003090373,0.00017729201,0.0010997541,0.00031057114,0.00033609653,0.00009225252,0.00017378193,0.0008462512],"category_scores_gemma":[0.00065531395,0.00017942941,0.00021413507,0.00044325987,0.00033822842,0.00021012015,0.00041700582,0.00016882105,0.00005850489],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010481639,0.000056157405,0.90840423,0.000088116685,0.00023522826,0.00082878285,0.000751677,0.0006025612,0.07611491,0.0001972784,0.00009853404,0.011574417],"study_design_scores_gemma":[0.000004115199,0.000046922145,0.99819946,0.0000042420893,0.000022782588,0.00046168503,0.00011424085,0.00034125816,0.0006755746,0.00009330987,0.00003385918,0.0000024853055],"about_ca_topic_score_codex":0.00903194,"about_ca_topic_score_gemma":0.018819587,"teacher_disagreement_score":0.00903194,"about_ca_system_score_codex":0.00032033463,"about_ca_system_score_gemma":0.00026079244,"threshold_uncertainty_score":0.01795876},"labels":[],"label_agreement":null},{"id":"W3161771687","doi":"10.1016/j.ynirp.2021.100010","title":"Diffusion imaging changes in the treated tract following focused ultrasound thalamotomy for tremor","year":2021,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; Hotchkiss Brain Institute; University of Alberta; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Thalamotomy; Medicine; Diffusion MRI; Thalamus; Dentate nucleus; Lesion; Fractional anisotropy; Internal capsule; Essential tremor; White matter; Magnetic resonance imaging; Tractography; Neuroscience; Radiology; Psychology; Pathology; Cerebellum; Parkinson's disease; Deep brain stimulation; Internal medicine; Physical medicine and rehabilitation","score_opus":0.054547398926522266,"score_gpt":0.34742060279631054,"score_spread":0.29287320386978827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161771687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99715304,0.0006551736,0.0016338169,0.000024078778,0.000003724466,0.00002845332,0.000079466,0.000036531546,0.0003857415],"genre_scores_gemma":[0.9985753,0.00017424497,0.0007222652,0.000010878674,0.0000022692388,0.000014441469,0.00010854098,0.0000074177337,0.00038466664],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999372,0.000011042499,0.000005758675,0.000013743373,0.00001846997,0.000013837326],"domain_scores_gemma":[0.9998616,0.000022656932,0.00006518563,0.000011999177,0.000019623842,0.00001886994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000123324,0.0001931371,0.0002701892,0.0003259612,0.00012378974,0.00015959144,0.00012434162,0.00024550522,0.00073212234],"category_scores_gemma":[0.00033541184,0.00011638697,0.0002099912,0.00013742276,0.00020046387,0.00013867805,0.00010965498,0.00022149304,0.00011016203],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013926564,0.00013587975,0.01569494,0.00011232954,0.00009410472,0.0016658554,0.00031384785,0.00057390676,0.96090096,0.00005287997,0.000069413356,0.018993106],"study_design_scores_gemma":[0.000086244196,0.007578308,0.76568764,0.000026784608,0.00030193714,0.010284337,0.00030726957,0.0031149092,0.21072179,0.00014687571,0.001700093,0.000043737953],"about_ca_topic_score_codex":0.002235752,"about_ca_topic_score_gemma":0.004366321,"teacher_disagreement_score":0.002235752,"about_ca_system_score_codex":0.00024615866,"about_ca_system_score_gemma":0.00012939039,"threshold_uncertainty_score":0.004445493},"labels":[],"label_agreement":null},{"id":"W3161909371","doi":"10.21203/rs.3.rs-115316/v3","title":"Plasma P-tau181 levels reflects white matter microstructural changes across Alzheimer’s disease progression","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Biomarker; Dementia; Alzheimer's Disease Neuroimaging Initiative; Internal medicine; Cognitive decline; Prospective cohort study; Psychology; Medicine; Neuroimaging; Cohort; Disease; Cardiology; Oncology; Neuroscience; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.2598738981199028,"score_gpt":0.531342639002622,"score_spread":0.2714687408827192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161909371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99888986,0.00035573024,0.00021603443,0.000017030385,0.000004261492,0.0000061553274,0.00018782628,0.000006224393,0.0003168325],"genre_scores_gemma":[0.9993211,0.00012045481,0.00018099954,0.000012108914,0.000009083414,0.0000069095454,0.0001766075,0.0000019987513,0.00017073676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998901,0.000019936613,0.00001572552,0.000038628754,0.000019211382,0.000016401116],"domain_scores_gemma":[0.9996599,0.000054902768,0.00017511826,0.000026537951,0.00004537981,0.000038202004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027506583,0.0004001254,0.0002722356,0.000707408,0.00028748956,0.00040417063,0.00015825276,0.00031833776,0.0015647947],"category_scores_gemma":[0.00059992966,0.00016106192,0.00019066076,0.00044689688,0.00016720829,0.00030903643,0.00021657647,0.0002724046,0.00027547762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016398203,0.00010005377,0.95878845,0.00006631047,0.0001970981,0.00047726973,0.00015592307,0.00012682973,0.030435083,0.00004020273,0.00021733744,0.0077556465],"study_design_scores_gemma":[0.000010514356,0.00023145422,0.9957022,0.000005927126,0.000044815653,0.0009216901,0.00007851617,0.0002417532,0.0024492154,0.000080055666,0.0002310198,0.0000029102018],"about_ca_topic_score_codex":0.000729381,"about_ca_topic_score_gemma":0.0006180736,"teacher_disagreement_score":0.0015647947,"about_ca_system_score_codex":0.000100340905,"about_ca_system_score_gemma":0.00008378828,"threshold_uncertainty_score":0.005234778},"labels":[],"label_agreement":null},{"id":"W3162365865","doi":"10.1089/brain.2020.0930","title":"Cortical Surfaces Integration with Tractography for Structural Connectivity Analysis","year":2021,"lang":"en","type":"review","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Computer science; Neuroscience; Artificial intelligence; Magnetic resonance imaging; Psychology","score_opus":0.12736148527299299,"score_gpt":0.4353202302168239,"score_spread":0.3079587449438309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162365865","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000611707,0.95757467,0.035235893,0.00085401704,0.0005212872,0.00005164259,0.00011459638,0.0001548937,0.0048813806],"genre_scores_gemma":[0.010662391,0.95478684,0.03121334,0.0002392654,0.00052734534,0.00013079467,0.00021087409,0.00006374088,0.0021655043],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99964726,0.00010193623,0.00003357002,0.00005684275,0.00014626596,0.000014143896],"domain_scores_gemma":[0.9989334,0.0006412997,0.00009595823,0.00006005841,0.00024521517,0.0000241243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087493774,0.000985266,0.0010389542,0.004467084,0.00021851795,0.0011084023,0.0008695807,0.001019871,0.0058084885],"category_scores_gemma":[0.0024069268,0.00033653385,0.0013156584,0.0037348277,0.0007070087,0.0012550475,0.00065511104,0.0013810154,0.0023801315],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027621472,0.000021080306,0.0002720376,0.01356773,0.00020295377,0.00012311093,0.000061132996,0.004216104,0.0019662515,0.017951306,0.013173234,0.9484173],"study_design_scores_gemma":[0.00003165576,0.00015997587,0.0027147646,0.011292146,0.0006132648,0.0025280425,0.00010876941,0.012052671,0.0050266082,0.042555023,0.9228194,0.00009767179],"about_ca_topic_score_codex":0.0018708798,"about_ca_topic_score_gemma":0.0021100924,"teacher_disagreement_score":0.0058084885,"about_ca_system_score_codex":0.00088123576,"about_ca_system_score_gemma":0.0014414247,"threshold_uncertainty_score":0.019431353},"labels":[],"label_agreement":null},{"id":"W3162628709","doi":"10.1002/hbm.25459","title":"De‐identification procedures for magnetic resonance images and the impact on structural brain measures at different ages","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Norman Cousins Center for Psychoneuroimmunology; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; Genentech; National Institutes of Health; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Association; Fujirebio US; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Merck; Alzheimer's Drug Discovery Foundation; AbbVie; Foundation for the National Institutes of Health; Meso Scale Diagnostics","keywords":"Voxel; Intraclass correlation; Psychology; Brain size; Magnetic resonance imaging; Neuroimaging; Audiology; Medicine; Neuroscience; Developmental psychology; Radiology; Psychometrics","score_opus":0.05968867952673323,"score_gpt":0.3625555965484898,"score_spread":0.30286691702175655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162628709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5441214,0.0051787295,0.4374655,0.0010297301,0.000877585,0.0010413537,0.0015365258,0.0023826482,0.0063665234],"genre_scores_gemma":[0.552452,0.002345055,0.43433818,0.0008029221,0.00019127867,0.0014887608,0.0019914461,0.0018893637,0.0045010974],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99665904,0.0010545268,0.00044585095,0.00066613866,0.0010001288,0.00017422966],"domain_scores_gemma":[0.98335004,0.008649857,0.0025048424,0.0032214571,0.0020794568,0.0001943788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011613153,0.0011365408,0.00061192614,0.0011570068,0.00083220116,0.0013607084,0.0008195153,0.0010172529,0.0034984995],"category_scores_gemma":[0.03836827,0.00060576526,0.0007374792,0.0008435554,0.0011112039,0.0015756493,0.0012707841,0.0010403383,0.001114226],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025897915,0.0003290829,0.051459137,0.0024240788,0.0009557602,0.0013021806,0.005433212,0.010244164,0.37884504,0.012397779,0.0073735574,0.5266462],"study_design_scores_gemma":[0.00018856337,0.002049296,0.39687946,0.0008985344,0.0009314475,0.013222361,0.0023401575,0.044799022,0.45774788,0.021663483,0.05878157,0.00049821887],"about_ca_topic_score_codex":0.0011718699,"about_ca_topic_score_gemma":0.003135332,"teacher_disagreement_score":0.011613153,"about_ca_system_score_codex":0.00045544788,"about_ca_system_score_gemma":0.00080867327,"threshold_uncertainty_score":0.061416924},"labels":[],"label_agreement":null},{"id":"W3162733792","doi":"10.1002/hbm.25455","title":"Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Canadian Institutes of Health Research; School of Medicine, Indiana University; National Institute on Aging; National Institutes of Health","keywords":"Atrophy; Magnetic resonance imaging; Neuroimaging; Brain size; Alzheimer's disease; Cognitive impairment; Neuroscience; Psychology; Cognition; Medicine; Pathology; Disease; Radiology","score_opus":0.07463761926639617,"score_gpt":0.35159303328661884,"score_spread":0.27695541402022267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162733792","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61211056,0.0012561937,0.38332388,0.00019620363,0.000033758908,0.000098999124,0.0005914221,0.0013562604,0.0010325907],"genre_scores_gemma":[0.771389,0.00040171942,0.22647206,0.000055258686,0.000041751202,0.00016444514,0.0006656599,0.00015387141,0.0006562009],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99963796,0.00016103184,0.000026043308,0.00007689828,0.00007157414,0.0000263685],"domain_scores_gemma":[0.9994142,0.00019214541,0.0001460369,0.00012337785,0.00010231008,0.000021871205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017449603,0.00043069338,0.00038373235,0.0015243966,0.00021678102,0.00065141753,0.0003820198,0.00041786415,0.0007257419],"category_scores_gemma":[0.0037711135,0.0003615587,0.00043097697,0.0010864395,0.00032877573,0.00069521455,0.000631467,0.00040875265,0.0002296111],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015721502,0.00024708404,0.07121638,0.00050696754,0.00073151704,0.0006644956,0.0009927349,0.0538963,0.49134624,0.005713955,0.0026918773,0.37042028],"study_design_scores_gemma":[0.00010233215,0.0008381762,0.22527659,0.00007611442,0.00032034246,0.0027238922,0.00021400057,0.66968375,0.08102464,0.014297505,0.005299721,0.00014297337],"about_ca_topic_score_codex":0.0020980511,"about_ca_topic_score_gemma":0.0041109133,"teacher_disagreement_score":0.0020980511,"about_ca_system_score_codex":0.00021984016,"about_ca_system_score_gemma":0.0004597133,"threshold_uncertainty_score":0.009228289},"labels":[],"label_agreement":null},{"id":"W3163201789","doi":"10.3389/fnins.2021.634063","title":"Advanced Analysis of Diffusion Tensor Imaging Along With Machine Learning Provides New Sensitive Measures of Tissue Pathology and Intra-Lesion Activity in Multiple Sclerosis","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"NIH Blueprint for Neuroscience Research; Division of Graduate Education; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; Alberta Innovates; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Government of Alberta","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Lesion; White matter; Medicine; Voxel; Receiver operating characteristic; Multiple sclerosis; Orientation (vector space); Artificial intelligence; Magnetic resonance imaging; Pattern recognition (psychology); Nuclear medicine; Radiology; Computer science; Pathology; Mathematics","score_opus":0.05387696443768367,"score_gpt":0.29893961324391133,"score_spread":0.24506264880622766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163201789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6279828,0.003087997,0.36581254,0.00037045116,0.000060388644,0.00007483368,0.00054097327,0.0009017765,0.0011681913],"genre_scores_gemma":[0.8752978,0.0012442345,0.122262836,0.00004490653,0.00008035783,0.000032114684,0.0004020897,0.00006262938,0.0005730461],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992925,0.00027697353,0.00005744865,0.00015908088,0.0001781166,0.000035907033],"domain_scores_gemma":[0.996831,0.0013223916,0.0009507704,0.00035183708,0.00042683881,0.00011717142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002289236,0.0011455902,0.00073427055,0.0019271354,0.00021987328,0.0011361393,0.00027712877,0.00051258394,0.00042095047],"category_scores_gemma":[0.0057038297,0.00024096269,0.00057307753,0.0010183108,0.00054927025,0.0014387477,0.00053424074,0.0007816077,0.00029714088],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007467948,0.00036546442,0.15865712,0.0005513706,0.00083276787,0.00039959172,0.00036965287,0.104235716,0.20619692,0.0039031846,0.0013222309,0.5224192],"study_design_scores_gemma":[0.000031239222,0.0010659734,0.18123636,0.00007614576,0.00024166232,0.001326626,0.0001492754,0.7450952,0.056382332,0.011666258,0.002535455,0.00019339735],"about_ca_topic_score_codex":0.0011229888,"about_ca_topic_score_gemma":0.00269577,"teacher_disagreement_score":0.002289236,"about_ca_system_score_codex":0.0003091882,"about_ca_system_score_gemma":0.00033769727,"threshold_uncertainty_score":0.012106776},"labels":[],"label_agreement":null},{"id":"W3163549178","doi":"10.3389/fneur.2021.631330","title":"Case Report: An MRI Traumatic Brain Injury Longitudinal Case Study at 7 Tesla: Pre- and Post-injury Structural Network and Volumetric Reorganization and Recovery","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Institute of Mental Health; National Institutes of Health; U.S. Department of Defense","keywords":"Traumatic brain injury; White matter; Fractional anisotropy; Neuroimaging; Diffuse axonal injury; Diffusion MRI; Blast injury; Connectome; Medicine; Tractography; Psychology; Poison control; Physical medicine and rehabilitation; Magnetic resonance imaging; Neuroscience; Radiology; Functional connectivity; Psychiatry","score_opus":0.02542905139534749,"score_gpt":0.3231293955100278,"score_spread":0.29770034411468027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163549178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98709214,0.0012202758,0.0025932516,0.002730481,0.00013357557,0.00034898132,0.0006662632,0.000058253645,0.005156756],"genre_scores_gemma":[0.99442613,0.000641627,0.0019354303,0.0007142735,0.0001995571,0.00008152091,0.00023938951,0.000021049556,0.0017410702],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9994253,0.000064408836,0.000076883465,0.00017068668,0.00010870219,0.00015416535],"domain_scores_gemma":[0.99846554,0.0002405231,0.00049874204,0.00016221072,0.0003081564,0.00032484884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006196092,0.00086844014,0.0007005603,0.0018005086,0.0032580425,0.0011534507,0.0014091287,0.0024238867,0.0027380174],"category_scores_gemma":[0.002823821,0.00065488636,0.00080764096,0.001253175,0.0012994442,0.0017590155,0.0016750412,0.0021495342,0.00089230185],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013120401,0.0004340802,0.11115802,0.00011890248,0.00005193806,0.87054914,0.0053330488,0.00018654553,0.0027619526,0.0006841873,0.0017805595,0.0068103876],"study_design_scores_gemma":[0.000008641446,0.00025190527,0.036770348,0.00005294451,0.000024108333,0.95840067,0.0016892769,0.00021611631,0.0005214675,0.00034461723,0.0016910331,0.000028893546],"about_ca_topic_score_codex":0.008448032,"about_ca_topic_score_gemma":0.01577144,"teacher_disagreement_score":0.008448032,"about_ca_system_score_codex":0.0015165024,"about_ca_system_score_gemma":0.0013174007,"threshold_uncertainty_score":0.016797721},"labels":[],"label_agreement":null},{"id":"W3163922138","doi":"10.1176/appi.ajp.2020.20111581r","title":"Ubiquitous Dopamine Deficit Hypotheses in Cocaine Use Disorder Lack Support: Response to Leyton","year":2021,"lang":"en","type":"letter","venue":"American Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal College of Physicians and Surgeons of Canada","funders":"National Institute of Mental Health","keywords":"Dopamine; Psychology; Addiction; Neuroscience; Psychiatry; Psychoanalysis; Medicine","score_opus":0.05656430066100987,"score_gpt":0.35209508265787426,"score_spread":0.2955307819968644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163922138","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005790586,0.0010271526,0.000069692,0.98339254,0.013934793,0.000012027771,0.00003870246,0.000016689353,0.0009293907],"genre_scores_gemma":[0.006388167,0.0009490182,0.0002592681,0.9526052,0.03799557,0.000028049008,0.000028651693,0.000021100459,0.0017249539],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99778384,0.0006513469,0.0003621183,0.00044794305,0.00044919903,0.00030555684],"domain_scores_gemma":[0.9803075,0.012975034,0.0009547402,0.00053363206,0.0029881522,0.0022408685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003737639,0.0008992399,0.0022403863,0.0011394758,0.004554827,0.0035746577,0.0032847873,0.065227374,0.003886359],"category_scores_gemma":[0.033557903,0.0009768863,0.0011591932,0.0010703105,0.0026962508,0.003841726,0.0019439501,0.053505328,0.0031642367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100019264,0.00005289422,0.0016422833,0.00007129564,0.000045718498,0.006975722,0.00017329278,0.00006136182,0.00016758527,0.0014482772,0.9820211,0.0072404365],"study_design_scores_gemma":[0.00068628805,0.0002685916,0.008236934,0.001579757,0.00032878504,0.02366705,0.0031031955,0.0027908536,0.0009156605,0.025651857,0.9323995,0.0003716159],"about_ca_topic_score_codex":0.0061646113,"about_ca_topic_score_gemma":0.010895928,"teacher_disagreement_score":0.065227374,"about_ca_system_score_codex":0.0038074013,"about_ca_system_score_gemma":0.0045620645,"threshold_uncertainty_score":0.027624726},"labels":[],"label_agreement":null},{"id":"W3163936868","doi":"10.1002/hbm.25473","title":"Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Medical Research Council; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Age UK; Medical Research Council Canada; Mrs Gladys Row Fogo Charitable Trust; Wellcome Trust; University of Texas at Austin","keywords":"Cohort; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology; Pathology","score_opus":0.25965208150653385,"score_gpt":0.44026309963532184,"score_spread":0.180611018128788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163936868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963122,0.00017345641,0.0006004575,0.000053145104,0.00000608853,0.00001040938,0.0021996775,0.000013576649,0.0006310806],"genre_scores_gemma":[0.9962366,0.000101070385,0.0004943057,0.00006764107,0.000009182378,0.000046697023,0.0020395312,0.000017219685,0.0009877378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961275,0.000095226096,0.000034293458,0.00012266048,0.0000950343,0.000039937033],"domain_scores_gemma":[0.9989072,0.0001873113,0.00035123722,0.0002654635,0.00021533531,0.0000734557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011794498,0.00028393345,0.00027818847,0.0009932776,0.0006782881,0.00038287143,0.00057852414,0.0004644018,0.002719817],"category_scores_gemma":[0.0022229361,0.00033088156,0.00047678553,0.0009880041,0.0003472018,0.00037029907,0.00050820445,0.00046310655,0.0007685631],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022149144,0.000028975435,0.9926536,0.000020921776,0.00019905022,0.00023006089,0.0006095934,0.00006464939,0.0019458856,0.00013418336,0.00090756814,0.0029840085],"study_design_scores_gemma":[0.000003783967,0.000019989639,0.99934775,0.0000045340353,0.00001873093,0.00011202809,0.000097129356,0.00005343717,0.00009047332,0.000024202276,0.00022359946,0.0000043697432],"about_ca_topic_score_codex":0.03225811,"about_ca_topic_score_gemma":0.04117572,"teacher_disagreement_score":0.03225811,"about_ca_system_score_codex":0.00037394124,"about_ca_system_score_gemma":0.00025526452,"threshold_uncertainty_score":0.06414068},"labels":[],"label_agreement":null},{"id":"W3164344838","doi":"10.1017/s1092852921000584","title":"Investigation of endophenotype potential of decreased fractional anisotropy in pediatric bipolar disorder patients and unrelated offspring of bipolar disorder patients","year":2021,"lang":"en","type":"article","venue":"CNS Spectrums","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Endophenotype; Fractional anisotropy; Bipolar disorder; Bipolar I disorder; Offspring; Medicine; Psychology; Internal medicine; Cardiology; Diffusion MRI; Magnetic resonance imaging; Neuroscience; Mania; Lithium (medication); Pregnancy; Cognition; Biology; Radiology; Genetics","score_opus":0.014430948029039365,"score_gpt":0.2563086905501126,"score_spread":0.24187774252107322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164344838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997609,0.00003141156,0.000037719692,0.000004986543,9.321789e-7,0.0000017984077,0.000057153415,0.000001318621,0.00010364318],"genre_scores_gemma":[0.99964845,0.00003530333,0.00010349611,0.000007024673,0.0000026661885,0.000005894312,0.00013574254,0.0000020956074,0.000059286536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998462,0.000037922455,0.0000146249395,0.00004726155,0.000029159735,0.000024734427],"domain_scores_gemma":[0.99952245,0.00011073668,0.00022021378,0.00003273651,0.000055256638,0.00005856978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022550578,0.00038261677,0.00021435834,0.00088662654,0.00035056256,0.00028049244,0.00015918353,0.00026589315,0.001485852],"category_scores_gemma":[0.0010068527,0.00018771918,0.00016069988,0.00039234667,0.00021927955,0.00014364958,0.00023685512,0.00022231565,0.00012914793],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018066206,0.000020270763,0.9951356,0.0000054313664,0.000023223618,0.0006024788,0.00016693248,0.00002074067,0.0025468383,0.000018813516,0.000044440105,0.0012345145],"study_design_scores_gemma":[0.000005144823,0.000065746615,0.99780065,0.000002466508,0.000018111088,0.001539936,0.00011000861,0.000059877417,0.00029095128,0.000014330603,0.00009118434,0.0000014342068],"about_ca_topic_score_codex":0.00229729,"about_ca_topic_score_gemma":0.002136567,"teacher_disagreement_score":0.00229729,"about_ca_system_score_codex":0.00017310915,"about_ca_system_score_gemma":0.0001231765,"threshold_uncertainty_score":0.0049706697},"labels":[],"label_agreement":null},{"id":"W3164541516","doi":"10.1038/s41380-021-01128-8","title":"White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis","year":2021,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; National Institute of General Medical Sciences; National Health and Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; U.S. Department of Health and Human Services","keywords":"Psychosis; White matter; Prodrome; Fractional anisotropy; Psychology; Internal medicine; Cohort; Prospective cohort study; Magnetic resonance imaging; Young adult; Medicine; Pediatrics; Psychiatry","score_opus":0.015880431222333433,"score_gpt":0.2987346395342591,"score_spread":0.28285420831192565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164541516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976019,0.00032868923,0.00018395326,0.00015982443,0.000015894653,0.000007695679,0.00016051132,0.00001112321,0.0015303314],"genre_scores_gemma":[0.99910164,0.00014072211,0.00013626489,0.000026891272,0.000011034651,0.0000035044325,0.0001423076,0.000007456193,0.0004301871],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99952006,0.00011050674,0.000033789544,0.000103020604,0.00011196344,0.00012059201],"domain_scores_gemma":[0.9970969,0.00032575615,0.0016247814,0.00021221084,0.0002628616,0.0004776024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055129617,0.0003539741,0.00047265753,0.00078661775,0.00062566175,0.0015239496,0.00047662147,0.00069876586,0.0025635909],"category_scores_gemma":[0.004711433,0.00037892966,0.00045068038,0.0009009578,0.0007087502,0.000997207,0.0008850435,0.0012629121,0.00037921334],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011591592,0.0001457022,0.9796212,0.000036067602,0.00019582042,0.00091447757,0.0003892906,0.00012658705,0.0054855677,0.0004042972,0.00023659026,0.011285169],"study_design_scores_gemma":[0.0000030660603,0.000064182066,0.99891436,0.00000883425,0.000015881526,0.00029559754,0.00010287652,0.00005473154,0.0001794609,0.00028420534,0.00007365924,0.0000031272189],"about_ca_topic_score_codex":0.0073998156,"about_ca_topic_score_gemma":0.009412496,"teacher_disagreement_score":0.0073998156,"about_ca_system_score_codex":0.0005674847,"about_ca_system_score_gemma":0.0008834292,"threshold_uncertainty_score":0.014713526},"labels":[],"label_agreement":null},{"id":"W3164886172","doi":"10.1016/j.jneumeth.2021.109226","title":"Label-free assessment of myelin status using birefringence microscopy","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Myelin; Luxol fast blue stain; White matter; Birefringence; Electron microscope; Pathology; Microscopy; Staining; Anatomy; Neuroscience; Biology; Magnetic resonance imaging; Central nervous system; Medicine; Optics; Radiology; Physics","score_opus":0.28839138692666705,"score_gpt":0.5819041405328899,"score_spread":0.2935127536062228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164886172","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7680365,0.005442637,0.21390451,0.00042782878,0.00015103447,0.00019191965,0.0006464937,0.0008157845,0.010383309],"genre_scores_gemma":[0.8566259,0.0033863068,0.13306072,0.00023361972,0.000061060986,0.00025311077,0.0005915962,0.00019739602,0.005590218],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995603,0.00012046284,0.000025145753,0.000082393315,0.00013140586,0.00008027931],"domain_scores_gemma":[0.99947065,0.00012053408,0.00011737822,0.00009012789,0.00015148928,0.000049954626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009916046,0.0005072583,0.00029571852,0.0009371637,0.0006915096,0.0007808499,0.0005175479,0.00096968125,0.0014869409],"category_scores_gemma":[0.000970841,0.0003077812,0.00018647825,0.00040849947,0.00056988996,0.0013864731,0.00064511935,0.00074829604,0.0004263182],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014408147,0.000026944812,0.00047413353,0.000114174734,0.0000109738,0.000054245225,0.000064750275,0.0000916832,0.9925466,0.00059031474,0.00014456734,0.005737498],"study_design_scores_gemma":[0.00002014714,0.0002451909,0.0064268573,0.00004241841,0.000051535124,0.0006465128,0.0001272564,0.004623387,0.9842733,0.0007807701,0.0027275472,0.00003515597],"about_ca_topic_score_codex":0.0015084709,"about_ca_topic_score_gemma":0.0026141342,"teacher_disagreement_score":0.0015084709,"about_ca_system_score_codex":0.00039804456,"about_ca_system_score_gemma":0.00053081097,"threshold_uncertainty_score":0.005244136},"labels":[],"label_agreement":null},{"id":"W3165679058","doi":"10.3389/fncom.2021.659838","title":"Predicting Brain Regions Related to Alzheimer's Disease Based on Global Feature","year":2021,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences; Institute of Biophysics, Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Betweenness centrality; Centrality; Diffusion MRI; Neurology; Neuroimaging; Computer science; Feature (linguistics); Connectome; Graph; Connectomics; Artificial intelligence; Medicine; Neuroscience; Pattern recognition (psychology); Psychology; Functional connectivity; Magnetic resonance imaging; Mathematics; Theoretical computer science; Statistics","score_opus":0.03708595069693046,"score_gpt":0.34776959948722636,"score_spread":0.3106836487902959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165679058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97592133,0.0017376128,0.018890593,0.0002605173,0.000045939327,0.000065170025,0.0012580006,0.00014374254,0.0016770719],"genre_scores_gemma":[0.99290365,0.00044006892,0.0052676112,0.000034316312,0.000044542423,0.000024864285,0.0008719121,0.000007951886,0.00040516196],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985003,0.000021630487,0.000017029337,0.000057366462,0.000026487016,0.000027465783],"domain_scores_gemma":[0.99943835,0.00015667209,0.00015551927,0.00004293302,0.00012246506,0.00008408412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005263416,0.0007816044,0.00046632567,0.003279013,0.000259569,0.0006358478,0.00028743612,0.00059715606,0.0009726019],"category_scores_gemma":[0.0015930223,0.00013541745,0.00075162,0.0010998772,0.00025356436,0.00071976375,0.00043013558,0.00038808977,0.00027573563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064973254,0.0002186102,0.87882215,0.00020200081,0.0006845366,0.0008671838,0.00022777265,0.0106253885,0.009163774,0.0010082554,0.003884516,0.09364601],"study_design_scores_gemma":[0.000066184686,0.00059251045,0.84538573,0.00010125064,0.00093089615,0.0023680872,0.0005686025,0.13554879,0.004851265,0.007269212,0.0022431784,0.00007426527],"about_ca_topic_score_codex":0.0035884052,"about_ca_topic_score_gemma":0.006487762,"teacher_disagreement_score":0.0035884052,"about_ca_system_score_codex":0.00026548203,"about_ca_system_score_gemma":0.0002874232,"threshold_uncertainty_score":0.0071350336},"labels":[],"label_agreement":null},{"id":"W3165788838","doi":"10.1037/cap0000275","title":"A brief introduction to intraindividual variability and spin.","year":2021,"lang":"en","type":"article","venue":"Canadian Psychology/Psychologie canadienne","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology","score_opus":0.07052637932699653,"score_gpt":0.3777353813754468,"score_spread":0.3072090020484503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165788838","genre_codex":"review","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004053578,0.5760263,0.31453192,0.012553787,0.011087039,0.0005487668,0.005868045,0.0014619861,0.07386851],"genre_scores_gemma":[0.05119383,0.5379636,0.25578016,0.015845718,0.029220574,0.0014672194,0.00605809,0.0013243976,0.10114644],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999076,0.00030058707,0.00011659167,0.00021318739,0.00022979893,0.000063835076],"domain_scores_gemma":[0.9974529,0.001790435,0.00013070494,0.00020771578,0.00033906972,0.00007914979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022733037,0.0010933502,0.00077550777,0.0029557098,0.0006621179,0.0015663272,0.0014693618,0.0019196905,0.021154858],"category_scores_gemma":[0.0055030384,0.00076298433,0.0010609613,0.0025677362,0.0015510456,0.0019187964,0.0011218592,0.002820265,0.00856993],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015818898,0.00016509842,0.002874914,0.0036676573,0.00015551224,0.0010374025,0.0007362005,0.0017488071,0.011197752,0.1460968,0.21904445,0.61311716],"study_design_scores_gemma":[0.0000064882142,0.00014994535,0.008106179,0.00089999306,0.000041407377,0.0029620219,0.00014209488,0.0015215501,0.0014750675,0.084999934,0.8995998,0.0000955537],"about_ca_topic_score_codex":0.0065411488,"about_ca_topic_score_gemma":0.009309405,"teacher_disagreement_score":0.021154858,"about_ca_system_score_codex":0.0011355863,"about_ca_system_score_gemma":0.0014451452,"threshold_uncertainty_score":0.070770025},"labels":[],"label_agreement":null},{"id":"W3166306566","doi":"10.1101/2021.05.14.444187","title":"The structure of hippocampal circuitry relates to rapid category learning in humans","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Categorization; Hippocampal formation; White matter; Concept learning; Association (psychology); Hippocampus; Mnemonic; Cognition","score_opus":0.02551244806637266,"score_gpt":0.27511098520776806,"score_spread":0.2495985371413954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166306566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9953467,0.000041179923,0.0034048008,0.00007191707,0.000004536157,0.0000056080185,0.000080493,0.00003405039,0.0010107654],"genre_scores_gemma":[0.99839056,0.000018106197,0.0013097799,0.000021617998,0.0000028104107,0.0000034061993,0.000049166614,0.000006721192,0.00019781028],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988425,0.000017022483,0.0000046195646,0.000059560327,0.00002213723,0.0000123455],"domain_scores_gemma":[0.999129,0.00021953294,0.0002967987,0.00019076501,0.00007838865,0.00008552361],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041233381,0.00011821721,0.00012193228,0.00028983958,0.00011650544,0.00044965005,0.00015056842,0.0002686037,0.001849924],"category_scores_gemma":[0.002456642,0.00014039373,0.000074118354,0.00012302566,0.0006719995,0.00050650723,0.00028751476,0.0003571257,0.00015244719],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009983405,0.00038794012,0.5826397,0.00017226169,0.00020118931,0.00081570464,0.0032093178,0.007773638,0.26408407,0.0059218127,0.0025113265,0.13128474],"study_design_scores_gemma":[0.000012756607,0.00023945628,0.96948606,0.000013818301,0.000017829423,0.00074315025,0.00027206968,0.0053541064,0.0125159705,0.010273989,0.001047652,0.000023128634],"about_ca_topic_score_codex":0.0007422705,"about_ca_topic_score_gemma":0.0013159115,"teacher_disagreement_score":0.001849924,"about_ca_system_score_codex":0.00010994637,"about_ca_system_score_gemma":0.00010454039,"threshold_uncertainty_score":0.0061885715},"labels":[],"label_agreement":null},{"id":"W3166979605","doi":"10.1002/hbm.25558","title":"Characterizing white matter alterations subject to clinical laterality in drug‐naïve de novo Parkinson's disease","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Laterality; Disease; Psychology; Neuroscience; Parkinson's disease; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.10862896568650543,"score_gpt":0.40270430730402984,"score_spread":0.2940753416175244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166979605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99901867,0.0002850668,0.00023336272,0.000016591643,0.0000028686177,0.000011489177,0.00010677707,0.000005938792,0.0003193023],"genre_scores_gemma":[0.9990351,0.00016448728,0.0002968351,0.00002806228,0.0000064497713,0.000009996234,0.0002086292,0.000005276801,0.00024516854],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997899,0.000044674744,0.00002839472,0.00008639538,0.000033997578,0.000016707572],"domain_scores_gemma":[0.99926203,0.00016192325,0.0003012202,0.000098841345,0.00010566675,0.00007024439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054260454,0.0002969568,0.00034163863,0.0008474971,0.00032530492,0.0005003723,0.0001901586,0.00034227094,0.0007919235],"category_scores_gemma":[0.0015959282,0.00016904977,0.0001597778,0.00029357063,0.00044743487,0.00035219494,0.00037733294,0.0001816684,0.00020086393],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016567244,0.00015796549,0.9156356,0.00010669455,0.0002002466,0.0060867793,0.0008306504,0.00021624581,0.05501386,0.00017525569,0.00033028628,0.019589772],"study_design_scores_gemma":[0.000015790214,0.00033906678,0.99114144,0.000012717278,0.0000445571,0.0054253372,0.00018859172,0.00028844253,0.0017819296,0.0001654591,0.0005867078,0.000009977509],"about_ca_topic_score_codex":0.0012467633,"about_ca_topic_score_gemma":0.0028845668,"teacher_disagreement_score":0.0012467633,"about_ca_system_score_codex":0.00015902225,"about_ca_system_score_gemma":0.0001569807,"threshold_uncertainty_score":0.002869606},"labels":[],"label_agreement":null},{"id":"W3168177125","doi":"10.21203/rs.3.rs-147275/v1","title":"Reorganisation of diffusion microstructure in the precuneus is associated with preserved cognitive function in Parkinson’s disease","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke; Centre Hospitalier de l’Université de Montréal; McGill University","funders":"","keywords":"Precuneus; Posterior cingulate; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Cortex (anatomy); Cognition; Radiology","score_opus":0.0950145283492425,"score_gpt":0.40520083031699733,"score_spread":0.3101863019677548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168177125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993204,0.0002597587,0.00014565671,0.00002306046,0.0000021641586,0.0000020163598,0.000049210666,0.000005869943,0.00019186425],"genre_scores_gemma":[0.99966156,0.00005864322,0.0001447516,0.0000051209927,0.0000038879616,9.63666e-7,0.00005370054,0.0000012545775,0.00007006062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999224,0.000013549884,0.000010609633,0.000029153141,0.000013104022,0.000011187148],"domain_scores_gemma":[0.9993661,0.0001005934,0.00035082264,0.00005725772,0.000056289387,0.000068958776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023905854,0.0002742258,0.00027199613,0.0008387564,0.00023914517,0.00046766762,0.00013437119,0.00026062143,0.0008035046],"category_scores_gemma":[0.000887134,0.00013127041,0.00012927914,0.00039104797,0.0003842796,0.00022138705,0.00023933678,0.00025382583,0.00008204574],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021123355,0.00014795527,0.89274985,0.0000939879,0.00024126732,0.0022608463,0.00085182337,0.0003036995,0.084486976,0.00020661936,0.00019731256,0.016347336],"study_design_scores_gemma":[0.0000052332553,0.00007641786,0.99727315,0.0000036181007,0.000017806335,0.0009924064,0.00007080496,0.00015248668,0.0012012263,0.00012747713,0.00007716072,0.0000021159656],"about_ca_topic_score_codex":0.0020698013,"about_ca_topic_score_gemma":0.0023120518,"teacher_disagreement_score":0.0020698013,"about_ca_system_score_codex":0.00016759026,"about_ca_system_score_gemma":0.00010008461,"threshold_uncertainty_score":0.0041155815},"labels":[],"label_agreement":null},{"id":"W3170550114","doi":"10.1016/j.dcn.2021.101008","title":"Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies","year":2021,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute of Mental Health; Helse Sør-Øst RHF; Brain and Behavior Research Foundation; Norges Forskningsråd; Canada Research Chairs; National Alliance for Research on Schizophrenia and Depression; National Institute for Health and Care Research","keywords":"Psychology; White matter; Executive functions; Diffusion MRI; Cognition; Extant taxon; Working memory; Concordance; Cognitive psychology; Developmental psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.06617718641593107,"score_gpt":0.37325152030611547,"score_spread":0.3070743338901844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170550114","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009794368,0.99949026,0.000052405427,0.00013210165,0.000033599725,0.000002151795,0.000018712712,0.0000026743835,0.00017010672],"genre_scores_gemma":[0.00047160636,0.99924433,0.00010259271,0.000047753696,0.00005482408,0.0000036041,0.00001737804,6.494161e-7,0.000057309357],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99967396,0.000052824595,0.000097304415,0.00008653221,0.00007135399,0.000018004917],"domain_scores_gemma":[0.9986607,0.000882027,0.00018855807,0.000022778688,0.00020335791,0.0000425415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011250001,0.0010827756,0.001597507,0.0037799354,0.00026137193,0.00097015896,0.0008143038,0.0010240225,0.00203467],"category_scores_gemma":[0.0023757017,0.00040740607,0.00075000053,0.0033261788,0.00058996317,0.0012642882,0.0006469486,0.0010460917,0.0008705544],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000745979,0.000040827734,0.0010612176,0.044484522,0.00023509935,0.00018809365,0.00013350841,0.00027628444,0.0006002224,0.0016568437,0.009664542,0.94158435],"study_design_scores_gemma":[0.000032903765,0.00025800627,0.016798174,0.0630569,0.0015160146,0.0056006517,0.00038380458,0.00028581033,0.0010290806,0.005863863,0.9050726,0.000102083315],"about_ca_topic_score_codex":0.0034382166,"about_ca_topic_score_gemma":0.004428704,"teacher_disagreement_score":0.0037799354,"about_ca_system_score_codex":0.00064018276,"about_ca_system_score_gemma":0.0019055696,"threshold_uncertainty_score":0.0068363547},"labels":[],"label_agreement":null},{"id":"W3170936042","doi":"10.1002/nbm.4564","title":"MRI of healthy brain aging: A review","year":2021,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Brain aging; Hyperintensity; Aging brain; White matter; Magnetic resonance imaging; Neuroscience; Healthy aging; Human brain; Brain size; Psychology; Medicine; Cognition; Gerontology; Radiology","score_opus":0.20429981294684432,"score_gpt":0.5203831557151053,"score_spread":0.316083342768261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170936042","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000060058497,0.9992131,0.00007001863,0.00016211745,0.0001444385,0.0000034444993,0.000017393846,0.0000050631293,0.00032431728],"genre_scores_gemma":[0.0003550276,0.999054,0.00013440712,0.00013186569,0.00014958992,0.0000050285216,0.00002128127,0.00000124846,0.00014758203],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997483,0.000044999135,0.00006382955,0.000049707287,0.000072901625,0.000020171665],"domain_scores_gemma":[0.9988991,0.0006509652,0.00014658141,0.000024065796,0.00023097072,0.000048258193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000725863,0.0012259935,0.0015560492,0.005299222,0.00032245033,0.0010351208,0.0008565248,0.001242115,0.004012671],"category_scores_gemma":[0.0018442807,0.00046163358,0.0008210834,0.004345306,0.00044344793,0.0018710626,0.00063739804,0.0011068264,0.001807924],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008298226,0.000050838058,0.00030652195,0.0664676,0.00020832394,0.00035145564,0.00011659387,0.00030889706,0.0010159009,0.0016710788,0.04370854,0.8857113],"study_design_scores_gemma":[0.000021374177,0.00015172202,0.0024775171,0.03382231,0.0005973419,0.0039488985,0.00012503781,0.00012684203,0.000502447,0.0018681554,0.9563133,0.00004499941],"about_ca_topic_score_codex":0.0018804488,"about_ca_topic_score_gemma":0.0023311058,"teacher_disagreement_score":0.005299222,"about_ca_system_score_codex":0.00067049684,"about_ca_system_score_gemma":0.0016683819,"threshold_uncertainty_score":0.013423741},"labels":[],"label_agreement":null},{"id":"W3171044630","doi":"10.1093/brain/awab232","title":"Potential optimization of focused ultrasound capsulotomy for obsessive compulsive disorder","year":2021,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University Health Network; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Deutsche Forschungsgemeinschaft","keywords":"Lesion; Medicine; Internal capsule; Magnetic resonance imaging; Deep brain stimulation; Diffusion MRI; Tractography; Radiology; Psychology; Surgery; Internal medicine; White matter; Parkinson's disease","score_opus":0.03192254523100007,"score_gpt":0.3354573587349589,"score_spread":0.30353481350395883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171044630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99293715,0.0027969254,0.0028871736,0.00016933166,0.000007177243,0.000048913676,0.000027777196,0.00004422735,0.0010813328],"genre_scores_gemma":[0.99644864,0.0009658605,0.0022350207,0.000047526086,0.0000108621125,0.000031273023,0.000032070595,0.0000040591303,0.00022461866],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999461,0.000015561365,0.000004116483,0.000007320838,0.0000162752,0.00001051637],"domain_scores_gemma":[0.999905,0.000027923716,0.000037851798,0.000005553684,0.000010822519,0.000012812824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015714725,0.00022786659,0.00014657642,0.0002224172,0.0000777048,0.00016925785,0.0001773216,0.00011369128,0.0007419003],"category_scores_gemma":[0.0005979394,0.000072094044,0.00015088072,0.00011515475,0.00012577079,0.00014870909,0.00013518985,0.00011987899,0.00008801743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004086369,0.0012488927,0.055033296,0.00046539935,0.00032773954,0.0012120295,0.0002300381,0.0102091925,0.31636903,0.00067199004,0.0008247728,0.6093213],"study_design_scores_gemma":[0.0013465311,0.039011568,0.79498065,0.00032529794,0.00080106774,0.0072687548,0.00074967975,0.03620118,0.109209314,0.0020289437,0.007975271,0.00010168013],"about_ca_topic_score_codex":0.0012024948,"about_ca_topic_score_gemma":0.003423623,"teacher_disagreement_score":0.0012024948,"about_ca_system_score_codex":0.00019845764,"about_ca_system_score_gemma":0.00033159365,"threshold_uncertainty_score":0.0024818778},"labels":[],"label_agreement":null},{"id":"W3171052867","doi":"","title":"A generalized SMT-based framework for Diusion MRI microstructural model estimation","year":2017,"lang":"en","type":"article","venue":"Medical Image Computing and Computer-Assisted Intervention","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Estimation; Estimation theory; Artificial intelligence; Algorithm; Materials science; Mathematical optimization; Applied mathematics; Mathematics; Engineering","score_opus":0.06444238563923192,"score_gpt":0.4156114653257816,"score_spread":0.35116907968654965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171052867","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007876548,0.00010882741,0.99855477,0.00004546151,0.000013753971,0.000014314953,0.000053776817,0.00022386119,0.00019751085],"genre_scores_gemma":[0.0848059,0.00074180873,0.9087953,0.00021229213,0.0001473312,0.00023105532,0.0010551808,0.00052256713,0.0034885504],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994524,0.00018466765,0.000039198803,0.00010991773,0.00016935458,0.00004451509],"domain_scores_gemma":[0.99896383,0.00042935868,0.00010518466,0.00012502618,0.00030844958,0.00006819372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014423288,0.0011603555,0.0011997804,0.0012558678,0.0004529853,0.0011600201,0.002137543,0.0018668682,0.00366678],"category_scores_gemma":[0.0040970626,0.00088895235,0.0016354355,0.0015644856,0.0005283265,0.0011944927,0.0018161098,0.002053552,0.0020420155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017583245,0.00009064433,0.0006551386,0.00022181099,0.00018638713,0.00021037123,0.000065001266,0.64359033,0.014345041,0.02039815,0.0051529487,0.3149083],"study_design_scores_gemma":[0.0000030429662,0.000010632873,0.00005899487,0.0000049076402,0.000008314363,0.000040858275,0.0000029935675,0.9952591,0.00045952483,0.0033708806,0.0007738251,0.000006792771],"about_ca_topic_score_codex":0.009066301,"about_ca_topic_score_gemma":0.011256225,"teacher_disagreement_score":0.009066301,"about_ca_system_score_codex":0.0005007156,"about_ca_system_score_gemma":0.0015666373,"threshold_uncertainty_score":0.018027067},"labels":[],"label_agreement":null},{"id":"W3171255193","doi":"10.3389/fnagi.2021.639795","title":"Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; National Natural Science Foundation of China; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Genentech; IXICO; University of Houston; University of Southern California; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Betweenness centrality; Clustering coefficient; Modularity (biology); Neuroscience; Diffusion MRI; Neuroimaging; Psychology; Tractography; Centrality; Computer science; Cluster analysis; Magnetic resonance imaging; Medicine; Artificial intelligence; Biology; Mathematics; Statistics; Evolutionary biology","score_opus":0.060436463965796064,"score_gpt":0.3658315133192387,"score_spread":0.30539504935344264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171255193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99483997,0.0004963274,0.003225038,0.00006043585,0.0000029437865,0.0000076987035,0.00046750228,0.000023315946,0.00087674026],"genre_scores_gemma":[0.99840826,0.00018329504,0.0009442822,0.000005950477,0.0000050078374,0.0000072271964,0.00031516637,0.0000059647155,0.00012484149],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959534,0.00015888132,0.0000297991,0.00011482305,0.00005483287,0.000046353834],"domain_scores_gemma":[0.9978617,0.00127732,0.0004235899,0.00019025215,0.000146551,0.00010062692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075518433,0.0002665584,0.00024991448,0.0009722386,0.00020280838,0.00046216327,0.00016009502,0.00016599051,0.0008231288],"category_scores_gemma":[0.003907801,0.00012115922,0.00033467336,0.0007994823,0.00034869617,0.00071424956,0.00045801527,0.0002003723,0.00009498289],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007874246,0.00006512826,0.926539,0.000110233595,0.00074188696,0.0005030128,0.00070797594,0.009367916,0.014701325,0.002559272,0.0005617853,0.0433551],"study_design_scores_gemma":[0.0000038568437,0.0000705292,0.9853425,0.000008320723,0.00013397307,0.00027523877,0.00010652272,0.010674156,0.0007034393,0.002328114,0.00034253954,0.000010834036],"about_ca_topic_score_codex":0.0036734268,"about_ca_topic_score_gemma":0.009145281,"teacher_disagreement_score":0.0036734268,"about_ca_system_score_codex":0.00034893045,"about_ca_system_score_gemma":0.00026034747,"threshold_uncertainty_score":0.007304132},"labels":[],"label_agreement":null},{"id":"W3171260877","doi":"10.1016/j.neuroimage.2021.118250","title":"Multi-modal imaging of a single mouse brain over five orders of magnitude of resolution","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Argonne National Laboratory; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; National Cancer Institute; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; McKnight Foundation; National Institute of Mental Health; Ontario Ministry of Research, Innovation and Science","keywords":"Connectomics; Micrometer; Diffusion MRI; Neuroimaging; Scale (ratio); Resolution (logic); Neuroscience; Computer science; Connectome; Physics; Magnetic resonance imaging; Artificial intelligence; Optics; Biology; Medicine","score_opus":0.05473079709339063,"score_gpt":0.34866846951896274,"score_spread":0.2939376724255721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171260877","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5811317,0.0033966484,0.39268026,0.001345789,0.00016326722,0.00020210362,0.00404417,0.0033231555,0.013712993],"genre_scores_gemma":[0.6625518,0.002401664,0.32223663,0.0006587557,0.000057606765,0.00026051136,0.001859125,0.00072152884,0.009252323],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998851,0.000008631404,0.000009582701,0.000037367492,0.000044082728,0.0000152569755],"domain_scores_gemma":[0.99969697,0.000050516366,0.000065895445,0.000048064103,0.000087371234,0.000051199942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004862308,0.00041727244,0.00021671178,0.0010229729,0.00034802614,0.00053557195,0.00040609567,0.0007212359,0.0027226873],"category_scores_gemma":[0.00032789892,0.00039845362,0.00026416554,0.00039766435,0.00035053663,0.00063453626,0.0006041281,0.0010870674,0.0005216179],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033007236,0.000015085204,0.0005043453,0.000056272962,0.000013336918,0.000057983285,0.000029806135,0.00047604524,0.99343663,0.0007323266,0.00032069223,0.004324447],"study_design_scores_gemma":[0.00004070812,0.00035981485,0.034951717,0.000184176,0.00013192852,0.0024259088,0.00020777866,0.022976538,0.91647464,0.0026751324,0.019519107,0.00005250127],"about_ca_topic_score_codex":0.0016543855,"about_ca_topic_score_gemma":0.004946286,"teacher_disagreement_score":0.0027226873,"about_ca_system_score_codex":0.00040868137,"about_ca_system_score_gemma":0.00049070275,"threshold_uncertainty_score":0.009108245},"labels":[],"label_agreement":null},{"id":"W3171357627","doi":"10.1101/2020.05.04.076521","title":"Multimodal principal component analysis to identify major features of white matter structure and links to reading","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"White matter; Principal component analysis; Diffusion MRI; Neuroscience; Fractional anisotropy; Corpus callosum; Artificial intelligence; Psychology; Computer science; Nuclear magnetic resonance; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine","score_opus":0.0253761641619497,"score_gpt":0.30986733703346947,"score_spread":0.28449117287151976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171357627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96844864,0.00036338263,0.028188525,0.00010650902,0.00003002191,0.00009711306,0.001498942,0.00029261544,0.00097425346],"genre_scores_gemma":[0.98769,0.00009777919,0.0107780965,0.000006973527,0.000014965124,0.00004933005,0.0008645091,0.000031334206,0.00046697163],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949026,0.00013900982,0.000051746552,0.00014578931,0.00010723852,0.000066023145],"domain_scores_gemma":[0.9983866,0.0008083757,0.00025150372,0.00019488823,0.00026127344,0.00009739752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012284764,0.0008705478,0.0005313605,0.0027091263,0.0003084386,0.00089208415,0.00024245444,0.00025807557,0.0035438554],"category_scores_gemma":[0.0038768784,0.0001624324,0.0008698596,0.0020971417,0.00030769262,0.0003776894,0.0005839262,0.00047731507,0.00047192903],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011117858,0.00033291077,0.66095245,0.00030168667,0.0015911795,0.0007539075,0.0011458043,0.010129302,0.05517044,0.0015844818,0.0038239583,0.26310208],"study_design_scores_gemma":[0.000022495906,0.0002563781,0.9376774,0.000034747467,0.00026580127,0.0003512859,0.00034938153,0.053362228,0.0041792984,0.0019852405,0.00147413,0.000041608935],"about_ca_topic_score_codex":0.004274186,"about_ca_topic_score_gemma":0.0036237317,"teacher_disagreement_score":0.004274186,"about_ca_system_score_codex":0.00027909517,"about_ca_system_score_gemma":0.0005575949,"threshold_uncertainty_score":0.011855364},"labels":[],"label_agreement":null},{"id":"W3172378891","doi":"10.31234/osf.io/468xa","title":"Using Diffusion Tensor Imaging to examine brain structural plasticity and language experience","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Neuroimaging; White matter; Variation (astronomy); Computer science; Psychology; Neuroscience; Physics; Magnetic resonance imaging; Medicine","score_opus":0.08196933927449837,"score_gpt":0.4069727400210898,"score_spread":0.3250034007465914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172378891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77186126,0.0034118737,0.2142973,0.0013382015,0.00009158213,0.000225022,0.0010470151,0.0003068242,0.0074210726],"genre_scores_gemma":[0.8698796,0.0050362484,0.12102872,0.0002313713,0.0001271353,0.0003168004,0.00050787407,0.00011777856,0.0027543763],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997032,0.00010569003,0.0000321114,0.00006514516,0.00006262028,0.000031319592],"domain_scores_gemma":[0.99930406,0.00026100752,0.00021918793,0.000087253306,0.000053227883,0.00007520715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013913255,0.0005328702,0.00027128315,0.0023158577,0.00028258556,0.0011291379,0.00026780792,0.0005188801,0.0013925796],"category_scores_gemma":[0.0030911402,0.00024266464,0.00031319575,0.0014946702,0.0009627462,0.0013966903,0.0006714042,0.000658033,0.00024231091],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067036506,0.00032370753,0.14424568,0.0008940212,0.0008178214,0.0018542295,0.003032435,0.008765499,0.44465563,0.01852656,0.0022702771,0.37394378],"study_design_scores_gemma":[0.00015292608,0.0021046868,0.74050236,0.00027922684,0.00042938985,0.010606567,0.002617275,0.04340889,0.095118016,0.0886809,0.015821531,0.00027812124],"about_ca_topic_score_codex":0.0022915713,"about_ca_topic_score_gemma":0.0042343913,"teacher_disagreement_score":0.0023158577,"about_ca_system_score_codex":0.00027184316,"about_ca_system_score_gemma":0.0005627365,"threshold_uncertainty_score":0.007358074},"labels":[],"label_agreement":null},{"id":"W3172893236","doi":"10.1016/j.media.2021.102126","title":"Filtering in tractography using autoencoders (FINTA)","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health","keywords":"Tractography; Streamlines, streaklines, and pathlines; Artificial intelligence; Autoencoder; Pattern recognition (psychology); Computer science; Deep learning; Filter (signal processing); Diffusion MRI; Human Connectome Project; Voxel; Computer vision; Physics; Magnetic resonance imaging; Functional connectivity","score_opus":0.08399795419258586,"score_gpt":0.4187703104105577,"score_spread":0.3347723562179718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172893236","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032095269,0.00024388143,0.99552804,0.00006355981,0.0000555026,0.000011497044,0.00003970373,0.0004958493,0.00035236095],"genre_scores_gemma":[0.15181218,0.0009568939,0.8391259,0.00019183083,0.00017241598,0.00017555857,0.0004297928,0.00035543155,0.006779967],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961936,0.000094300216,0.00003405856,0.00011532427,0.00009003864,0.00004682485],"domain_scores_gemma":[0.99840254,0.0008898158,0.00012586635,0.00020041736,0.00032821004,0.000053063904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001222546,0.0008476053,0.0010168828,0.00074552296,0.00055478944,0.0010932086,0.0009761843,0.0017263457,0.0022008063],"category_scores_gemma":[0.002833765,0.0008445124,0.0015071916,0.0007174812,0.0006700235,0.001146426,0.0011699409,0.002042273,0.0012072588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012058657,0.00007528634,0.0009613743,0.00019652862,0.00024029972,0.00014128687,0.00013897284,0.48609728,0.014833478,0.023619728,0.0036565112,0.4699187],"study_design_scores_gemma":[0.0000043755686,0.000019768358,0.00022415562,0.000018028653,0.000018600414,0.00004630806,0.000008316978,0.98992187,0.0031096644,0.005108628,0.0015105368,0.000009763227],"about_ca_topic_score_codex":0.013357692,"about_ca_topic_score_gemma":0.015907355,"teacher_disagreement_score":0.013357692,"about_ca_system_score_codex":0.00058773736,"about_ca_system_score_gemma":0.0011109001,"threshold_uncertainty_score":0.02655989},"labels":[],"label_agreement":null},{"id":"W3173340191","doi":"10.1101/2021.06.29.450089","title":"Not all voxels are created equal: reducing estimation bias in regional NODDI metrics using tissue-weighted means","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; UK Dementia Research Institute; University College London Hospitals NHS Foundation Trust; Brain Research Trust; Wolfson Foundation; British Heart Foundation; University College London; National Institute for Health and Care Research; Brain Research UK; Wellcome Trust; Alzheimer's Society; Weston Brain Institute; Alzheimer's Association","keywords":"Region of interest; Voxel; Pattern recognition (psychology); Neuroimaging; Metric (unit); Partial volume; Artificial intelligence; Brain tissue; Brain size; Statistics; Computer science; Nuclear medicine; Mathematics; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology","score_opus":0.15899215065156422,"score_gpt":0.35014540538944305,"score_spread":0.19115325473787884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173340191","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06475938,0.0010550793,0.9318164,0.00023018902,0.00014495316,0.00013848476,0.0001946533,0.0011278515,0.00053303427],"genre_scores_gemma":[0.35167566,0.00043478076,0.64479184,0.00022226833,0.00016468976,0.00043779504,0.0006228859,0.00093677663,0.00071325805],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9931098,0.0036287347,0.00060883106,0.0012445373,0.001198165,0.00020986471],"domain_scores_gemma":[0.9625277,0.026556408,0.0029345592,0.004485067,0.003177565,0.0003186692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016565958,0.00088331517,0.0012460224,0.0016523533,0.00073112844,0.0017909117,0.0015937354,0.00097458035,0.0010854044],"category_scores_gemma":[0.0741654,0.00064045493,0.0008222508,0.0019204088,0.0010145821,0.0014508069,0.0021147432,0.001067497,0.00040016833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015380132,0.00017099714,0.050499994,0.0013185526,0.0018713532,0.0005026557,0.002746707,0.0643823,0.05439359,0.019060416,0.008025623,0.79548985],"study_design_scores_gemma":[0.00031003295,0.000990122,0.09082085,0.000444493,0.0010453803,0.001472434,0.00086192,0.72518337,0.07083355,0.08267625,0.02501104,0.0003505346],"about_ca_topic_score_codex":0.0031689224,"about_ca_topic_score_gemma":0.0049663363,"teacher_disagreement_score":0.016565958,"about_ca_system_score_codex":0.00061234564,"about_ca_system_score_gemma":0.0011921449,"threshold_uncertainty_score":0.087610245},"labels":[],"label_agreement":null},{"id":"W3173857605","doi":"10.1002/hbm.25569","title":"<scp>R2</scp>* and quantitative susceptibility mapping in deep gray matter of 498 healthy controls from 5 to 90 years","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Globus pallidus; Putamen; Quantitative susceptibility mapping; Thalamus; Grey matter; Basal ganglia; Psychology; Caudate nucleus; Neuroscience; Physiology; White matter; Biology; Magnetic resonance imaging; Medicine; Central nervous system; Radiology","score_opus":0.08088783876411572,"score_gpt":0.36662992453581006,"score_spread":0.28574208577169435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173857605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995974,0.00007171232,0.000059138492,0.000003283525,0.0000012602972,0.000004420523,0.00011633433,0.00000442569,0.00014188659],"genre_scores_gemma":[0.9994653,0.0000311073,0.0000615256,0.0000037239713,0.0000021649514,0.0000052879413,0.00018211274,0.0000024019034,0.00024640557],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999853,0.000016951999,0.000018390905,0.00006308765,0.000019172965,0.000029365721],"domain_scores_gemma":[0.9997563,0.000046716184,0.00007893741,0.000033389097,0.00004247456,0.00004227537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022004294,0.00047891404,0.00036750053,0.00090962916,0.00039921005,0.0003188535,0.00019790039,0.0004058753,0.0014140421],"category_scores_gemma":[0.00083218416,0.00023329974,0.00023092159,0.00031811933,0.00039255543,0.00023964161,0.0003155488,0.00020229603,0.00022460132],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013847884,0.00015250492,0.97741586,0.000032267762,0.00017049488,0.0013478975,0.0010399655,0.00014768954,0.0103803035,0.000073585616,0.0001609299,0.0076938267],"study_design_scores_gemma":[0.00001038007,0.0002634006,0.9985623,0.0000016961507,0.000024100002,0.00054183445,0.00011582484,0.00007737682,0.00026413664,0.000019611221,0.00011633684,0.0000029911712],"about_ca_topic_score_codex":0.009074046,"about_ca_topic_score_gemma":0.0077084345,"teacher_disagreement_score":0.009074046,"about_ca_system_score_codex":0.00021800745,"about_ca_system_score_gemma":0.00007626754,"threshold_uncertainty_score":0.018042445},"labels":[],"label_agreement":null},{"id":"W3174049805","doi":"10.1101/2021.06.22.449454","title":"Prevalence of white matter pathways coming into a single diffusion MRI voxel orientation: the bottleneck issue in tractography","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; National Center for Research Resources; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; Voxel; White matter; Diffusion MRI; Bottleneck; Neuroscience; Human Connectome Project; Human brain; Computer science; Orientation (vector space); Artificial intelligence; Psychology; Pattern recognition (psychology); Magnetic resonance imaging; Functional connectivity; Medicine; Mathematics","score_opus":0.025976492956288122,"score_gpt":0.2696573909334546,"score_spread":0.24368089797716647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174049805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.932066,0.002662312,0.06324098,0.00026362244,0.000019139608,0.000036788286,0.00033620693,0.0003255627,0.0010493464],"genre_scores_gemma":[0.99242073,0.00027367292,0.00695779,0.000015078346,0.0000261411,0.000013977038,0.00014676916,0.000046923396,0.00009892002],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99554175,0.0013248707,0.00051855325,0.0013176671,0.0009251188,0.00037213],"domain_scores_gemma":[0.90594476,0.06441248,0.016305137,0.007198978,0.0045585223,0.0015801062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010419125,0.00056747417,0.0010838169,0.006200413,0.0006318213,0.0017672209,0.0007551102,0.0013570272,0.0017964124],"category_scores_gemma":[0.06379449,0.00064700935,0.00035912672,0.002012218,0.002410645,0.004299231,0.002470104,0.0007345358,0.00041651214],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018228533,0.0001453166,0.80069524,0.0007326467,0.000746353,0.0009920886,0.00198453,0.016163709,0.05892776,0.007751805,0.0012602055,0.108777545],"study_design_scores_gemma":[0.00008049437,0.00065084425,0.77825594,0.00040763573,0.00041660308,0.010096286,0.0013631363,0.12962009,0.038263783,0.037720993,0.0029220604,0.00020220754],"about_ca_topic_score_codex":0.0015752488,"about_ca_topic_score_gemma":0.0010288493,"teacher_disagreement_score":0.010419125,"about_ca_system_score_codex":0.0006079403,"about_ca_system_score_gemma":0.00038871888,"threshold_uncertainty_score":0.05510229},"labels":[],"label_agreement":null},{"id":"W3174077831","doi":"10.1093/rheumatology/keab511","title":"Brain white matter extracellular free-water increases are related to reduced neurocognitive function in systemic lupus erythematosus","year":2021,"lang":"en","type":"article","venue":"Lara D. Veeken","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sleep & Circadian Network","funders":"Ministry of Health","keywords":"Extracellular; Medicine; Neurocognitive; White matter; Diffusion MRI; Atrophy; Neuroinflammation; Brain size; Internal medicine; Pathology; Endocrinology; Magnetic resonance imaging; Inflammation; Cognition; Biology; Psychiatry; Radiology","score_opus":0.02265788854553042,"score_gpt":0.2786848351868136,"score_spread":0.25602694664128317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174077831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99947256,0.00024408143,0.00008709725,0.000018118337,0.0000017335318,0.0000026693779,0.000038444407,0.000005631511,0.00012962967],"genre_scores_gemma":[0.9997172,0.00007613116,0.00007807307,0.000010450096,0.000006488841,0.000002518689,0.00004373884,0.0000011624857,0.00006435444],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982005,0.000044617205,0.000034205645,0.000045733024,0.000036738158,0.00001867702],"domain_scores_gemma":[0.99888796,0.00018282536,0.00071933016,0.000040769155,0.0000667117,0.00010240005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003207698,0.0004530717,0.0002728894,0.000584456,0.00022462338,0.00033780353,0.00016461671,0.0003299721,0.0015016848],"category_scores_gemma":[0.0014303733,0.00017576352,0.00018330733,0.0003985275,0.00030065162,0.00025763697,0.0002511061,0.00034604804,0.00016446719],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012073909,0.00010591356,0.9727559,0.000073871146,0.0001697126,0.000754257,0.00023197805,0.00014207065,0.017272487,0.000023557015,0.00008958455,0.0071732597],"study_design_scores_gemma":[0.000010328977,0.00013832147,0.99838877,0.0000048659863,0.000026046757,0.0007980674,0.00005999796,0.00009742783,0.0004155254,0.000022051798,0.00003648655,0.000002043904],"about_ca_topic_score_codex":0.00077087106,"about_ca_topic_score_gemma":0.0007813184,"teacher_disagreement_score":0.0015016848,"about_ca_system_score_codex":0.00012547779,"about_ca_system_score_gemma":0.0000946749,"threshold_uncertainty_score":0.0050235987},"labels":[],"label_agreement":null},{"id":"W3174282872","doi":"","title":"Perfusion/diffusion mismatchに関する最近の話題","year":2010,"lang":"ja","type":"article","venue":"Canadian parliamentary review","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Perfusion; Diffusion; Cardiology; Internal medicine; Medicine; Physics; Thermodynamics","score_opus":0.04829081779812482,"score_gpt":0.33282828308288426,"score_spread":0.2845374652847594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174282872","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009381445,0.93885666,0.0009354813,0.03363282,0.0059094443,0.000048305286,0.00036822452,0.000047780548,0.019263184],"genre_scores_gemma":[0.012310843,0.96718407,0.0018635145,0.0071054776,0.0027745957,0.000039202434,0.00022157097,0.000025490323,0.008475146],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975198,0.00033404646,0.00030309038,0.00023345456,0.0013251,0.0002845677],"domain_scores_gemma":[0.98911,0.002766458,0.00072272576,0.00021717386,0.006796487,0.00038719637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0089478735,0.0008992776,0.00121387,0.0050240955,0.0021361937,0.002433192,0.0020074444,0.0024614178,0.006909222],"category_scores_gemma":[0.015752414,0.00041751988,0.00057089736,0.0061157513,0.0034879243,0.0018202048,0.001007955,0.0027995384,0.0017495747],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017049548,0.00003084721,0.0013407567,0.0069149886,0.000079081066,0.0010813797,0.00020660608,0.00022367264,0.00084007013,0.012293388,0.30052626,0.67629254],"study_design_scores_gemma":[0.000023564373,0.00002889889,0.0038627607,0.002990462,0.00013429746,0.0015619316,0.00021628804,0.000059294412,0.00080797164,0.0014622093,0.98880464,0.00004770751],"about_ca_topic_score_codex":0.5164556,"about_ca_topic_score_gemma":0.6863577,"teacher_disagreement_score":0.5164556,"about_ca_system_score_codex":0.016550032,"about_ca_system_score_gemma":0.0591079,"threshold_uncertainty_score":0.9727842},"labels":[],"label_agreement":null},{"id":"W3174344947","doi":"10.1161/str.48.suppl_1.wp442","title":"Abstract WP442: Diffusion Tensor Imaging of White Matter Tracts in Transient Ischemic Attack Patients","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; White matter; Uncinate fasciculus; Cardiology; Superior longitudinal fasciculus; Dementia; Internal medicine; Cognitive decline; Magnetic resonance imaging; Radiology","score_opus":0.03859279093100426,"score_gpt":0.3377309742285529,"score_spread":0.29913818329754865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174344947","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995304,0.0004528511,0.00024624233,0.00021987133,0.000016718006,0.000049652055,0.0016325176,0.000013591682,0.0020645044],"genre_scores_gemma":[0.99566394,0.0003101698,0.00053995947,0.000041285784,0.000041278618,0.000059437243,0.0021959185,0.000006538904,0.0011415139],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998456,0.000034368768,0.000034976183,0.000028211834,0.000031942353,0.000024949812],"domain_scores_gemma":[0.99962854,0.000044382017,0.00016389237,0.000020143874,0.000075519325,0.0000674827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039720495,0.0003471649,0.00024663276,0.0011271074,0.00037937824,0.00046326924,0.00018669407,0.00030828954,0.004506621],"category_scores_gemma":[0.0013703476,0.0001112294,0.00020923172,0.0009734004,0.00013621793,0.00044143826,0.00031224437,0.00025625137,0.0008370426],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005299052,0.00014537247,0.9723384,0.00010646708,0.00011183595,0.0010396573,0.00029655814,0.0001567359,0.0038819562,0.00006987731,0.0024357154,0.018887632],"study_design_scores_gemma":[0.000009968622,0.00011407375,0.9972415,0.000011146647,0.000017469853,0.001533341,0.00008919678,0.00015832347,0.00021377043,0.00006335008,0.0005442946,0.0000035127036],"about_ca_topic_score_codex":0.0020956495,"about_ca_topic_score_gemma":0.0018262871,"teacher_disagreement_score":0.004506621,"about_ca_system_score_codex":0.0001965097,"about_ca_system_score_gemma":0.00024208645,"threshold_uncertainty_score":0.01507616},"labels":[],"label_agreement":null},{"id":"W3174662759","doi":"10.1161/circ.140.suppl_2.286","title":"Abstract 286: Cerebral Microstructure Disruptions are Associated With Poor Neurologic Outcomes in Comatose Cardiac Arrest Patients","year":2019,"lang":"en","type":"article","venue":"Circulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Medicine; Fractional anisotropy; Kurtosis; Cardiology; Logistic regression; Diffusion MRI; Prospective cohort study; Internal medicine; Anesthesia; Magnetic resonance imaging; Radiology","score_opus":0.02416700681812992,"score_gpt":0.29152147231346537,"score_spread":0.2673544654953354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174662759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99965024,0.000054955723,0.00003398573,0.0000193345,0.0000021351261,0.00000277875,0.000093539726,0.0000020603218,0.00014096183],"genre_scores_gemma":[0.99975675,0.000021539649,0.000027373639,0.000005055474,0.000005455912,0.000002463935,0.00012211074,6.650769e-7,0.000058664915],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999094,0.000013952117,0.000015345457,0.000024347153,0.000015009534,0.000021869902],"domain_scores_gemma":[0.999255,0.000067756126,0.00043806076,0.00002845145,0.00008331166,0.0001275035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019105604,0.00029864698,0.00019955229,0.00056171964,0.00038351215,0.00041905168,0.00015242858,0.00025785493,0.0027609786],"category_scores_gemma":[0.00096819724,0.00011212339,0.00018626962,0.0003944344,0.0002698957,0.00027772895,0.00032063585,0.00031526762,0.0002813149],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025826923,0.000025440593,0.9973162,0.000011141254,0.0000378174,0.00022302342,0.0000497906,0.000043354023,0.0008313369,0.000012022787,0.00010175451,0.0010898481],"study_design_scores_gemma":[0.000004266538,0.000067188186,0.9992204,0.000004386919,0.000011788583,0.0003663084,0.000072898016,0.00010148211,0.00009109863,0.000018279072,0.00004003066,0.0000018872815],"about_ca_topic_score_codex":0.0021418445,"about_ca_topic_score_gemma":0.0024605703,"teacher_disagreement_score":0.0027609786,"about_ca_system_score_codex":0.00021349084,"about_ca_system_score_gemma":0.0002159206,"threshold_uncertainty_score":0.009236395},"labels":[],"label_agreement":null},{"id":"W3175695364","doi":"10.3389/fnins.2021.646034","title":"Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"EPSRC Centre for Doctoral Training in Medical Imaging; Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca; Engineering and Physical Sciences Research Council; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Wolfson Foundation; Wellcome Trust; National Science Foundation","keywords":"White matter; Voxel; Axon; Diffusion MRI; Corpus callosum; Internal capsule; Tractography; Bundle; Spherical mean; Neuroscience; Magnetic resonance imaging; Anatomy; Computer science; Artificial intelligence; Biology; Mathematics; Materials science; Mathematical analysis; Medicine; Radiology","score_opus":0.045165965578742466,"score_gpt":0.3122785943264132,"score_spread":0.2671126287476707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175695364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.110932104,0.0010355524,0.8843241,0.00012763492,0.000060528106,0.00004253266,0.0003898216,0.0005967926,0.002490945],"genre_scores_gemma":[0.48220614,0.0010885588,0.5127169,0.00008906279,0.00019240096,0.00008707378,0.000634471,0.0003830673,0.002602259],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99981886,0.000042356227,0.000016405518,0.00005442134,0.00005571148,0.000012282009],"domain_scores_gemma":[0.9992353,0.00028748356,0.00020300876,0.000078647325,0.00013840682,0.00005723739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005163719,0.0004989673,0.00034547923,0.0014951149,0.00021286725,0.0008415422,0.00035795724,0.0005200531,0.0010913548],"category_scores_gemma":[0.0022465524,0.00018429208,0.00022675433,0.0008119963,0.0004861189,0.00122583,0.00080424413,0.00054039905,0.0002666596],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000582853,0.00009305884,0.02306575,0.0006541001,0.00021625079,0.0005394649,0.0007270191,0.057113905,0.5650391,0.057407312,0.0033264924,0.2912348],"study_design_scores_gemma":[0.0000488628,0.0005354686,0.069453366,0.0001403245,0.00022103002,0.0029808704,0.00022243368,0.71220785,0.1430446,0.049029447,0.021939384,0.00017638456],"about_ca_topic_score_codex":0.0005127865,"about_ca_topic_score_gemma":0.0012261121,"teacher_disagreement_score":0.0014951149,"about_ca_system_score_codex":0.00023947831,"about_ca_system_score_gemma":0.000335151,"threshold_uncertainty_score":0.0036509633},"labels":[],"label_agreement":null},{"id":"W3176867663","doi":"10.1111/pcn.13284","title":"White matter volume not associated with hallucinations in clinical high risk and first‐episode psychosis: A voxel‐based morphometry study","year":2021,"lang":"en","type":"letter","venue":"Psychiatry and Clinical Neurosciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Psychosis; White matter; Voxel; Voxel-based morphometry; Psychology; Psychiatry; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07058490476996315,"score_gpt":0.38631676436407925,"score_spread":0.3157318595941161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176867663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994512,0.000081834776,0.0000978492,0.000013580696,0.0000021084672,0.00001752567,0.0001671338,0.0000033500776,0.00016532184],"genre_scores_gemma":[0.9994986,0.0000290549,0.0001261144,0.000011091101,0.000005535292,0.000012923329,0.00021480893,0.0000030551182,0.00009884004],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983144,0.000024665798,0.000019485287,0.00006281374,0.00003064335,0.000030988216],"domain_scores_gemma":[0.999456,0.000103677296,0.00017577334,0.00008191989,0.000050801365,0.0001319532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044665163,0.0004040647,0.00036834725,0.00084457075,0.0005118069,0.00042607464,0.00033508008,0.00058228115,0.0023663964],"category_scores_gemma":[0.0011490696,0.0003770115,0.0003559011,0.0006485191,0.00054415286,0.00042455283,0.000591877,0.0003389048,0.00031968264],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029873578,0.00041361482,0.9738888,0.00012309615,0.00027026958,0.0037307679,0.0009153249,0.0002199528,0.011943894,0.00015756748,0.00028169653,0.0050676325],"study_design_scores_gemma":[0.000045663837,0.00026882824,0.9966,0.0000051461107,0.00004617101,0.0022122627,0.00013987627,0.00026192283,0.00022286497,0.00007791704,0.00011303439,0.000006409143],"about_ca_topic_score_codex":0.0024068465,"about_ca_topic_score_gemma":0.0025674405,"teacher_disagreement_score":0.0024068465,"about_ca_system_score_codex":0.00025146306,"about_ca_system_score_gemma":0.00028154484,"threshold_uncertainty_score":0.007916391},"labels":[],"label_agreement":null},{"id":"W3177104451","doi":"10.1016/j.tins.2021.06.002","title":"An X-ray for myelin","year":2021,"lang":"en","type":"letter","venue":"Trends in Neurosciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Women and Children’s Health Research Institute; University of Alberta","funders":"","keywords":"Remyelination; Myelin; Neuroscience; Central nervous system; Multiple sclerosis; White matter; Disease treatment; Myelin sheath; Computer science; Medicine; Magnetic resonance imaging; Psychology; Immunology; Radiology; Intensive care medicine","score_opus":0.18808728128717964,"score_gpt":0.43850808719444506,"score_spread":0.25042080590726545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177104451","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005537373,0.0056287274,0.00030046486,0.9526702,0.03403533,0.000015382839,0.000020445133,0.000031045987,0.0067447308],"genre_scores_gemma":[0.00815395,0.004279886,0.00080604054,0.8942877,0.06954294,0.000052727453,0.00002418087,0.00003737571,0.02281515],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984037,0.00044382332,0.00022767234,0.00023638419,0.00045255348,0.00023592026],"domain_scores_gemma":[0.9954346,0.0030939514,0.00024885396,0.0002998596,0.00041329785,0.0005094833],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021623333,0.0008119708,0.0012877929,0.0006411194,0.00440437,0.0035306031,0.0015984542,0.07172893,0.006830871],"category_scores_gemma":[0.015957586,0.0005768561,0.0016817622,0.00041226583,0.004642862,0.0036016635,0.0025555475,0.06353906,0.0038578329],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009525183,0.00004359803,0.00034270485,0.00013783781,0.00004071266,0.013654296,0.00018467919,0.00012932929,0.00048447918,0.02664868,0.9425964,0.015641961],"study_design_scores_gemma":[0.00013261185,0.000095833886,0.00038980693,0.00035711844,0.00004185818,0.009968433,0.0002847597,0.00025676657,0.00033835118,0.03985664,0.94823337,0.000044543274],"about_ca_topic_score_codex":0.002671311,"about_ca_topic_score_gemma":0.005459373,"teacher_disagreement_score":0.07172893,"about_ca_system_score_codex":0.0043677455,"about_ca_system_score_gemma":0.0037096648,"threshold_uncertainty_score":0.0316903},"labels":[],"label_agreement":null},{"id":"W3177207463","doi":"10.1002/mrm.28886","title":"Design and characterization of a 3D‐printed axon‐mimetic phantom for diffusion MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fondation Brain Canada","keywords":"Kurtosis; Imaging phantom; Materials science; Biomedical engineering; Diffusion MRI; Reproducibility; Thermal diffusivity; Diffusion; Effective diffusion coefficient; Nuclear magnetic resonance; Nuclear medicine; Chemistry; Magnetic resonance imaging; Physics; Mathematics; Medicine; Radiology","score_opus":0.051198182673256036,"score_gpt":0.33682873781737016,"score_spread":0.2856305551441141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177207463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3522814,0.002119193,0.63541764,0.0006115983,0.00016235182,0.0011722519,0.00094255625,0.0024793933,0.004813581],"genre_scores_gemma":[0.4313925,0.0013478787,0.5599634,0.0003064449,0.00004896889,0.0015421227,0.0008320699,0.00028407277,0.004282551],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995603,0.000076947035,0.000028567061,0.0000975242,0.00020460977,0.00003199872],"domain_scores_gemma":[0.99892586,0.00044681132,0.000253501,0.000118406766,0.00016096885,0.00009439148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012065305,0.0008398364,0.00041751572,0.0005640728,0.00027885791,0.0006289419,0.0006979041,0.00081844465,0.00097415515],"category_scores_gemma":[0.0017468092,0.0004989155,0.0003392858,0.00027361236,0.00049263437,0.00057191687,0.00033274412,0.000490885,0.00066404976],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048410704,0.00003458952,0.00017027963,0.00009440133,0.0000054859784,0.00010919961,0.000038668004,0.0015676963,0.9927362,0.00036715792,0.00015096444,0.004677066],"study_design_scores_gemma":[0.0000182707,0.00027161822,0.0009137125,0.000012837832,0.000017186961,0.00045912463,0.000014871438,0.01205552,0.98011214,0.00017693035,0.0059200074,0.000027809961],"about_ca_topic_score_codex":0.00040454644,"about_ca_topic_score_gemma":0.00048935565,"teacher_disagreement_score":0.0012065305,"about_ca_system_score_codex":0.0006073487,"about_ca_system_score_gemma":0.00059955585,"threshold_uncertainty_score":0.006380856},"labels":[],"label_agreement":null},{"id":"W3178219752","doi":"10.1002/hbm.25580","title":"Longitudinal white matter changes associated with cognitive training","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Working memory; Psychology; White matter; Cognitive psychology; Task (project management); Cognition; n-back; Diffusion MRI; Neuroscience; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.17053381450328395,"score_gpt":0.3590997047724677,"score_spread":0.18856589026918377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178219752","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998374,0.00033726668,0.0002786795,0.000047329162,0.0000081204325,0.00002128332,0.0001122277,0.000020740941,0.0008002754],"genre_scores_gemma":[0.9975533,0.00015664734,0.00022389958,0.00003104267,0.000008334593,0.000024062772,0.00024149918,0.000005051148,0.0017561566],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99983275,0.000020145606,0.000013675053,0.000057729612,0.000036662186,0.000038978527],"domain_scores_gemma":[0.9992507,0.000056262812,0.0003188077,0.000062722735,0.00016736404,0.00014416073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040907876,0.00029556602,0.00028821215,0.00042462163,0.00028727693,0.00027698773,0.00018455848,0.00042006874,0.0015000077],"category_scores_gemma":[0.00090078,0.00015643696,0.00020191273,0.00023779075,0.00027082596,0.00027718983,0.00035879135,0.00058921694,0.00029629364],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048771817,0.0022403796,0.43972415,0.00024329714,0.00042372796,0.00083895656,0.0010337349,0.0008571949,0.47545415,0.00023331202,0.0006860934,0.07338771],"study_design_scores_gemma":[0.000009216627,0.0012885513,0.9883498,0.000009730411,0.000046482146,0.00021625639,0.00009772318,0.00020621913,0.009340294,0.00007589851,0.00035383037,0.000006169743],"about_ca_topic_score_codex":0.0021591554,"about_ca_topic_score_gemma":0.0031872885,"teacher_disagreement_score":0.0021591554,"about_ca_system_score_codex":0.00024713294,"about_ca_system_score_gemma":0.00022588944,"threshold_uncertainty_score":0.0050180554},"labels":[],"label_agreement":null},{"id":"W3179211250","doi":"10.3389/fneur.2021.673060","title":"Peripheral Nerve Focused Ultrasound Lesioning—Visualization and Assessment Using Diffusion Weighted Imaging","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Toronto Western Hospital; Hospital for Sick Children; University of Toronto; University Health Network","funders":"Hospital for Sick Children; Mitacs; Fondation Brain Canada","keywords":"Diffusion MRI; Tractography; Fractional anisotropy; Magnetic resonance imaging; Medicine; Sciatic nerve; Lesion; Biomedical engineering; Ultrasound; Magnetic resonance neurography; Radiology; Nuclear medicine; Pathology; Anatomy","score_opus":0.03251555172701872,"score_gpt":0.34715136693088894,"score_spread":0.31463581520387024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179211250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9281451,0.003961909,0.06536671,0.000072460825,0.00002601172,0.00025900465,0.00022195482,0.00033125826,0.0016155388],"genre_scores_gemma":[0.95375043,0.0020564827,0.04193936,0.00003589271,0.000016640544,0.00015224483,0.00022973646,0.000031143172,0.0017880831],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99980015,0.000039483373,0.000018027189,0.000053443928,0.000073176234,0.000015713715],"domain_scores_gemma":[0.9996685,0.00005949287,0.00012817218,0.00002846694,0.000079590136,0.000035697067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009610806,0.00042939038,0.00020338624,0.00088153646,0.000135268,0.00027345223,0.00021790709,0.00055702915,0.0016719397],"category_scores_gemma":[0.0007061925,0.00020880622,0.00016985022,0.00023906516,0.00047410734,0.0006003178,0.00026332642,0.0003171908,0.00031655398],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057301245,0.0001343754,0.0067117987,0.00023769673,0.000027941205,0.00043064883,0.000074515854,0.00052379625,0.9573796,0.000103076454,0.0000915439,0.03371192],"study_design_scores_gemma":[0.00013567797,0.008906805,0.2625026,0.00018455423,0.00021382935,0.010697087,0.00022412842,0.0170756,0.6962465,0.00041644374,0.0033113172,0.00008553341],"about_ca_topic_score_codex":0.0006265073,"about_ca_topic_score_gemma":0.0007279654,"teacher_disagreement_score":0.0016719397,"about_ca_system_score_codex":0.00018758429,"about_ca_system_score_gemma":0.00019642447,"threshold_uncertainty_score":0.0055931807},"labels":[],"label_agreement":null},{"id":"W3179308066","doi":"10.3389/fnhum.2021.662031","title":"Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review","year":2021,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Russian Science Foundation; Russian Foundation for Basic Research","keywords":"White matter; Cognition; Psychology; Neuroimaging; Developmental psychology; Brain Structure and Function; Neuroscience; Lateralization of brain function; Cognitive psychology; Medicine; Magnetic resonance imaging","score_opus":0.12143790301349104,"score_gpt":0.41143635391207445,"score_spread":0.2899984508985834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179308066","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006814608,0.9994955,0.000036935013,0.00009540098,0.000062040424,0.0000028614768,0.000027678274,0.0000028947209,0.00020855402],"genre_scores_gemma":[0.00040547262,0.9992569,0.00007360654,0.00006372595,0.00006676097,0.0000046743794,0.000028087656,8.4639123e-7,0.00009992147],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99973935,0.00004672804,0.00007357399,0.00005560068,0.00006655292,0.000018318939],"domain_scores_gemma":[0.9986505,0.0008835262,0.00020778633,0.000025015806,0.00018877961,0.00004449299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008323257,0.001043563,0.0018383283,0.004053566,0.00025477944,0.0011323079,0.0009022712,0.0008809504,0.0042543546],"category_scores_gemma":[0.002799195,0.00033249808,0.0009543633,0.004226688,0.00042599303,0.0013644516,0.00064157293,0.00092624273,0.0013027367],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001149488,0.000037455433,0.00044146655,0.1164938,0.0003962972,0.00018776808,0.00009942204,0.0002607583,0.00069639797,0.0014759162,0.023727138,0.8560686],"study_design_scores_gemma":[0.00003544499,0.00019478113,0.0062929634,0.08092583,0.0024202918,0.0032976307,0.00019683015,0.000117519994,0.0005442479,0.0030388876,0.9028782,0.000057297126],"about_ca_topic_score_codex":0.0020607107,"about_ca_topic_score_gemma":0.0033119742,"teacher_disagreement_score":0.0042543546,"about_ca_system_score_codex":0.00057916524,"about_ca_system_score_gemma":0.0021692023,"threshold_uncertainty_score":0.014232218},"labels":[],"label_agreement":null},{"id":"W3179371357","doi":"10.1002/mrm.28926","title":"MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Connectomics; Diffusion MRI; Fractional anisotropy; Connectome; Pattern recognition (psychology); Artificial intelligence; Orientation (vector space); Data set; Computer science; Nuclear magnetic resonance; Mathematics; Statistics; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Physics; Functional connectivity; Radiology","score_opus":0.046346992715682184,"score_gpt":0.3551013306261533,"score_spread":0.30875433791047113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179371357","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41844225,0.000692908,0.563602,0.00019049447,0.000072189585,0.0005286122,0.0054934635,0.00958881,0.0013893645],"genre_scores_gemma":[0.5109428,0.00029400032,0.4792753,0.00009649966,0.000091673704,0.001476535,0.005006026,0.0016184897,0.0011986961],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99932075,0.00025066917,0.000042518983,0.00020919637,0.00014650867,0.000030291696],"domain_scores_gemma":[0.9977048,0.0008721118,0.00066004554,0.0004289149,0.00020271949,0.00013141171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031848517,0.0011151397,0.00058738707,0.0016582459,0.00041390376,0.000840772,0.0008161032,0.000557841,0.0021443907],"category_scores_gemma":[0.005759018,0.00046792935,0.0006512657,0.0008405929,0.00041410525,0.0010068229,0.0010710158,0.00060572167,0.00046343246],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040709274,0.00067379494,0.09069951,0.000977046,0.0025070705,0.00081121013,0.00096791727,0.04295943,0.3973816,0.0059309797,0.01674735,0.43627313],"study_design_scores_gemma":[0.00059985043,0.0033912114,0.42093432,0.00016219619,0.00075306115,0.005853732,0.00039484835,0.41653374,0.11606438,0.013664093,0.021148669,0.0004999054],"about_ca_topic_score_codex":0.0011410378,"about_ca_topic_score_gemma":0.0041250596,"teacher_disagreement_score":0.0031848517,"about_ca_system_score_codex":0.0002597881,"about_ca_system_score_gemma":0.0006494388,"threshold_uncertainty_score":0.016843319},"labels":[],"label_agreement":null},{"id":"W3183527235","doi":"10.3389/fnagi.2021.711579","title":"Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer’s Disease","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; National Institute of General Medical Sciences; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Inferior longitudinal fasciculus; Fasciculus; Neuroscience; Posterior cingulate; Superior longitudinal fasciculus; Alzheimer's disease; Psychology; Medicine; Cardiology; Disease; Internal medicine; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.05234523500382029,"score_gpt":0.29539372389360896,"score_spread":0.24304848888978867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183527235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995228,0.00011344202,0.00016902796,0.000013442717,0.0000017471527,0.0000033897131,0.00002838061,0.0000030017677,0.00014467741],"genre_scores_gemma":[0.99955577,0.000045964014,0.00024719356,0.000004969342,0.0000027679005,0.0000018963763,0.00006957363,5.876504e-7,0.00007141008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999236,0.000015075522,0.000013857885,0.000019425815,0.000013134666,0.000014958888],"domain_scores_gemma":[0.9995473,0.000118202785,0.00017639161,0.000035749796,0.00005609732,0.000066217406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029194707,0.0003164526,0.0002449282,0.0007503858,0.0002116344,0.000390291,0.000109420165,0.0002849186,0.00061921746],"category_scores_gemma":[0.0016731014,0.000118425945,0.00019730219,0.00026560863,0.00022104684,0.00025468448,0.00023371629,0.00025385682,0.00013735556],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022679,0.00004251394,0.9860291,0.000013567708,0.00005327898,0.000183159,0.0001190188,0.00028318755,0.0030685023,0.000032177166,0.00007187592,0.0098768305],"study_design_scores_gemma":[0.0000061414103,0.00009772139,0.9976699,0.0000040408318,0.000016901344,0.00041167636,0.000113450835,0.0010051384,0.00048751011,0.00010771817,0.00007663097,0.0000031833763],"about_ca_topic_score_codex":0.0017928436,"about_ca_topic_score_gemma":0.0038433417,"teacher_disagreement_score":0.0017928436,"about_ca_system_score_codex":0.000117649426,"about_ca_system_score_gemma":0.00012687186,"threshold_uncertainty_score":0.0035648346},"labels":[],"label_agreement":null},{"id":"W3183649267","doi":"10.3174/ajnr.a7221","title":"Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; Selegiline; Atlas (anatomy); Spinal cord; Disease; Parkinson's disease; Internal medicine; Psychiatry; Anatomy","score_opus":0.11762002267790271,"score_gpt":0.3967953965679264,"score_spread":0.27917537389002367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183649267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6115928,0.00069984875,0.37967363,0.00010804013,0.000029016193,0.00025527834,0.003162034,0.002444455,0.0020348683],"genre_scores_gemma":[0.69835776,0.0003470028,0.29767188,0.000028063017,0.000009934939,0.00024291905,0.0024358183,0.00026111162,0.00064555963],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99942577,0.00012530798,0.00006328946,0.00019017237,0.00016423069,0.00003130881],"domain_scores_gemma":[0.9987381,0.00035941656,0.00034314545,0.00022039759,0.00029436426,0.000044624256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015345169,0.00043934488,0.00027204878,0.0014036895,0.00030213402,0.00084882055,0.000554183,0.00032944497,0.0016156035],"category_scores_gemma":[0.0042641205,0.0002416195,0.00032613124,0.0008471394,0.00028016983,0.00048381631,0.0005495805,0.00035215396,0.0005059548],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007966963,0.00017326447,0.23184864,0.00062181085,0.00047244818,0.0008609412,0.0013363156,0.03808609,0.20297818,0.005614144,0.0044502155,0.51276124],"study_design_scores_gemma":[0.000043686454,0.0005347258,0.68755794,0.0001569598,0.00024639844,0.004277977,0.0005499416,0.14884205,0.14432663,0.0042351712,0.009103811,0.00012474034],"about_ca_topic_score_codex":0.004806743,"about_ca_topic_score_gemma":0.011312341,"teacher_disagreement_score":0.004806743,"about_ca_system_score_codex":0.00069487677,"about_ca_system_score_gemma":0.0012739652,"threshold_uncertainty_score":0.009557545},"labels":[],"label_agreement":null},{"id":"W3183779008","doi":"10.3390/brainsci11070943","title":"Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment","year":2021,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Dementia; Psychology; Cognition; Montreal Cognitive Assessment; Magnetic resonance imaging; Audiology; Neuroimaging; Neuroscience; Cognitive impairment; Medicine; Pathology; Disease; Radiology","score_opus":0.03887840872240967,"score_gpt":0.32956948718832185,"score_spread":0.2906910784659122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183779008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995301,0.000050851137,0.00004845646,0.000012236216,0.0000014497529,0.0000040501427,0.000054425134,0.0000028397183,0.00029575406],"genre_scores_gemma":[0.99980396,0.000017903933,0.00003837502,0.0000051350053,0.0000026459677,0.0000035075282,0.00007643065,8.3456223e-7,0.000051190727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983394,0.00002841721,0.000021306903,0.00005596548,0.000026442878,0.000033906956],"domain_scores_gemma":[0.9996044,0.00009692655,0.00015461765,0.000032282434,0.000035052886,0.00007669847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023665106,0.0003900855,0.00036165863,0.0021048186,0.0004440596,0.0005331384,0.00019680822,0.00034074692,0.0014651798],"category_scores_gemma":[0.0017735368,0.00014402841,0.0002203961,0.0007919612,0.00049348763,0.00038949674,0.00038185573,0.00021302726,0.00012830735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005816473,0.00009896494,0.98855734,0.000030397923,0.0001431373,0.0013816904,0.0007654949,0.00027819458,0.0020114963,0.00016518375,0.00015385343,0.005832571],"study_design_scores_gemma":[0.000010624685,0.000112356596,0.9979405,0.0000025423653,0.00002427568,0.001069558,0.00023056296,0.00026394048,0.00010462474,0.00017505414,0.00006196789,0.0000039233437],"about_ca_topic_score_codex":0.0040583196,"about_ca_topic_score_gemma":0.0049340297,"teacher_disagreement_score":0.0040583196,"about_ca_system_score_codex":0.00040150632,"about_ca_system_score_gemma":0.00018960077,"threshold_uncertainty_score":0.008069396},"labels":[],"label_agreement":null},{"id":"W3184054006","doi":"10.1016/j.neubiorev.2021.07.020","title":"White matter integrity differences in obesity: A meta-analysis of diffusion tensor imaging studies","year":2021,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Fondation Institut Universitaire de Cardiologie et de Pneumologie de Québec","keywords":"Fractional anisotropy; Diffusion MRI; Corpus callosum; White matter; Meta-analysis; Obesity; Medicine; Psychology; Neuroscience; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.6445659611611562,"score_gpt":0.5369526380442776,"score_spread":0.10761332311687855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184054006","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005327617,0.99394894,0.00029190967,0.0001049807,0.000058286747,0.000017300858,0.00016984613,0.000008507659,0.00007262625],"genre_scores_gemma":[0.100396946,0.89631015,0.0018875689,0.00035822936,0.00021396505,0.000063522326,0.0005852548,0.000018907711,0.0001654116],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99780256,0.00079641736,0.00055958,0.000480027,0.00025858794,0.00010284407],"domain_scores_gemma":[0.99553525,0.003130616,0.0007131143,0.00021347187,0.0003249564,0.00008260693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005424334,0.002159516,0.007636726,0.0026397817,0.0003509133,0.0020533262,0.0012269083,0.0011883995,0.0015238458],"category_scores_gemma":[0.008753722,0.0008586596,0.01394498,0.0041249534,0.0004301741,0.00095383514,0.0011653956,0.0012301093,0.00016915491],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004165036,0.000083835046,0.025231192,0.142009,0.72225004,0.00031131913,0.00015991695,0.0008019433,0.0015755745,0.00031976937,0.0017337784,0.10135858],"study_design_scores_gemma":[0.00043355665,0.0002835988,0.04036756,0.011631139,0.9399004,0.00035431705,0.00009543901,0.0002765723,0.0003651183,0.00072623277,0.0055010524,0.000065061904],"about_ca_topic_score_codex":0.0043585068,"about_ca_topic_score_gemma":0.009855485,"teacher_disagreement_score":0.007636726,"about_ca_system_score_codex":0.0006967388,"about_ca_system_score_gemma":0.0015058109,"threshold_uncertainty_score":0.028687},"labels":[],"label_agreement":null},{"id":"W3184630054","doi":"10.3389/fnhum.2021.681634","title":"Effect of Aerobic Exercise on White Matter Tract Microstructure in Young and Middle-Aged Healthy Adults","year":2021,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé; National Institute on Aging; National Institutes of Health; Réseau québécois de recherche sur le vieillissement","keywords":"Fractional anisotropy; Cardiorespiratory fitness; Aerobic exercise; White matter; Fasciculus; Medicine; Psychology; Physical therapy; Internal medicine; Magnetic resonance imaging","score_opus":0.019214955661276026,"score_gpt":0.3080646965863459,"score_spread":0.2888497409250699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184630054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99813974,0.0011888788,0.000044869827,0.000049561095,0.000029324292,0.00006108217,0.000087694076,0.0000044010544,0.0003945159],"genre_scores_gemma":[0.99811894,0.0006691572,0.00021058276,0.000120043886,0.000049098373,0.00009823352,0.00014809257,0.0000013743412,0.0005844148],"study_design_codex":"randomized_trial","study_design_gemma":"observational","domain_scores_codex":[0.99987686,0.00003329188,0.000013655378,0.000032217104,0.0000145046815,0.000029413284],"domain_scores_gemma":[0.9996822,0.00006320255,0.00007170664,0.000018152094,0.000025036657,0.00013966458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000476642,0.00039664403,0.0005182165,0.0002281827,0.0002819542,0.00027430948,0.00011477741,0.0005418654,0.0017400509],"category_scores_gemma":[0.00089676416,0.00017306906,0.00042085658,0.00013298892,0.00018569364,0.00023594609,0.00025698292,0.000268282,0.00019062932],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.44713435,0.041925397,0.26554367,0.0025699213,0.005768754,0.00048318485,0.00084953965,0.0010670355,0.040665876,0.00020972107,0.001529781,0.19225276],"study_design_scores_gemma":[0.00552334,0.06556812,0.9259643,0.00008841672,0.00083926733,0.000066648725,0.00008585167,0.0003002949,0.0009041334,0.00011789115,0.000528224,0.000013464779],"about_ca_topic_score_codex":0.001159084,"about_ca_topic_score_gemma":0.0023695717,"teacher_disagreement_score":0.0017400509,"about_ca_system_score_codex":0.00013583037,"about_ca_system_score_gemma":0.00016154596,"threshold_uncertainty_score":0.0058209896},"labels":[],"label_agreement":null},{"id":"W3184734890","doi":"10.15829/1728-8800-2021-2915","title":"White matter integrity of watershed areas is potentially influenced by hypoperfusion in the presence permanent atrial fibrillation","year":2021,"lang":"en","type":"article","venue":"CARDIOVASCULAR THERAPY AND PREVENTION","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Russian Foundation for Basic Research","keywords":"Medicine; White matter; Atrial fibrillation; Cardiology; Internal medicine; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Nuclear medicine; Radiology","score_opus":0.041633377116252576,"score_gpt":0.306946594806841,"score_spread":0.2653132176905884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184734890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995845,0.000101199126,0.00013074688,0.000014614057,0.0000020983089,0.0000043256705,0.00003315372,0.0000015321397,0.0001279012],"genre_scores_gemma":[0.9998018,0.000033311957,0.000086704706,0.000004447944,0.00000770034,0.000004128186,0.000035980807,5.085545e-7,0.000025338826],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999741,0.00007361517,0.000032872103,0.00007199133,0.000037654176,0.000042782962],"domain_scores_gemma":[0.9988225,0.00035379696,0.0005899822,0.000057360056,0.00006001842,0.000116373936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004611643,0.00020509741,0.00021664897,0.00053108705,0.00023504616,0.0003163615,0.00014887552,0.00027984014,0.0015700997],"category_scores_gemma":[0.0022084643,0.00010328437,0.00017470586,0.00029370925,0.00041233975,0.0002829069,0.00025005726,0.00018541659,0.00010756712],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009960528,0.0000899394,0.9872705,0.000039703245,0.000058614052,0.000768833,0.00014959901,0.000083126186,0.0045184325,0.000052062613,0.000050652663,0.0059226076],"study_design_scores_gemma":[0.000012824033,0.0004919202,0.99702257,0.000005227796,0.000032866647,0.0014879587,0.00010414909,0.00021082521,0.00047275893,0.00010597834,0.000050774433,0.0000022580825],"about_ca_topic_score_codex":0.00031007762,"about_ca_topic_score_gemma":0.00046632477,"teacher_disagreement_score":0.0015700997,"about_ca_system_score_codex":0.00009432346,"about_ca_system_score_gemma":0.00015156767,"threshold_uncertainty_score":0.00525254},"labels":[],"label_agreement":null},{"id":"W3185192526","doi":"10.1002/hbm.25574","title":"Improving the predictive potential of diffusion <scp>MRI</scp> in schizophrenia using normative models—Towards subject‐level classification","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Advancing Translational Sciences; Medical Research Council; National Institute of Mental Health; Ministry of Health, State of Israel; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Fractional anisotropy; Normative; White matter; Diffusion MRI; Psychology; Raw score; Magnetic resonance imaging; Statistics; Artificial intelligence; Computer science; Medicine; Mathematics; Radiology","score_opus":0.12060438267775916,"score_gpt":0.32961247517300546,"score_spread":0.2090080924952463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185192526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8966666,0.0011931513,0.0952041,0.00084402354,0.0000963549,0.00010005822,0.0021608765,0.0021477183,0.0015872254],"genre_scores_gemma":[0.9850702,0.00016972392,0.011087049,0.000086876265,0.000047490812,0.000044019107,0.0031087995,0.00008492174,0.0003010298],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984756,0.0007155855,0.00008674359,0.0004153751,0.00018752614,0.0001192324],"domain_scores_gemma":[0.9932335,0.004379495,0.00054403755,0.00076165714,0.00080226647,0.00027893425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006761439,0.0012550654,0.0011579522,0.0016841792,0.00042774927,0.0018246259,0.00064983696,0.0009508568,0.0007824088],"category_scores_gemma":[0.013043147,0.00035823783,0.00092345855,0.0005209908,0.00055655173,0.0011283826,0.0011572626,0.0016252749,0.0006968052],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023592953,0.00085272826,0.40491697,0.00027507066,0.0010549339,0.0005630718,0.00046539423,0.35830787,0.011781641,0.0026323881,0.008565286,0.20822531],"study_design_scores_gemma":[0.000030159386,0.00017496139,0.029772291,0.00006649391,0.00010518302,0.00014612828,0.00009012409,0.9611446,0.0026770087,0.0048869024,0.00086509145,0.000040945946],"about_ca_topic_score_codex":0.007055235,"about_ca_topic_score_gemma":0.006306056,"teacher_disagreement_score":0.007055235,"about_ca_system_score_codex":0.00057926186,"about_ca_system_score_gemma":0.0011853087,"threshold_uncertainty_score":0.035758376},"labels":[],"label_agreement":null},{"id":"W3186594303","doi":"10.1186/s12938-021-00909-0","title":"ABrainVis: an android brain image visualization tool","year":2021,"lang":"en","type":"article","venue":"BioMedical Engineering OnLine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Horizon 2020 Framework Programme; Horizon 2020; Agencia Nacional de Investigación y Desarrollo; Centre for Biotechnology and Bioengineering; European Commission","keywords":"Visualization; Computer science; Android (operating system); Computer vision; Human–computer interaction; Artificial intelligence; Computer graphics (images); Operating system","score_opus":0.03580716144072872,"score_gpt":0.36973839245388457,"score_spread":0.33393123101315586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186594303","genre_codex":"software","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045460425,0.0065622227,0.30921093,0.0013194164,0.0006237985,0.0015231651,0.021866687,0.5711944,0.04223893],"genre_scores_gemma":[0.4909063,0.0058626,0.33445978,0.0024346877,0.00060952525,0.0047123535,0.03320467,0.059467368,0.06834265],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996376,0.000049163235,0.000028689461,0.00006685351,0.00015830164,0.00005934444],"domain_scores_gemma":[0.99905735,0.0004813559,0.00006469557,0.00012156409,0.000169089,0.00010589447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042722112,0.00193959,0.0006947387,0.0013896755,0.00031049474,0.0011212683,0.0015333067,0.0008094168,0.032593563],"category_scores_gemma":[0.0032840893,0.00055754464,0.0009863225,0.0003901755,0.0003093837,0.0011812774,0.0023821555,0.00074530137,0.009147328],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003904336,0.00019374138,0.0037721994,0.0038802247,0.00031942158,0.0030983195,0.002313357,0.002309666,0.05236668,0.0054818112,0.36367625,0.558684],"study_design_scores_gemma":[0.001365986,0.001023525,0.033279344,0.0019661991,0.00047496674,0.009478065,0.0008977109,0.059491005,0.07680232,0.013398816,0.8008472,0.00097492634],"about_ca_topic_score_codex":0.0018933285,"about_ca_topic_score_gemma":0.0023303076,"teacher_disagreement_score":0.032593563,"about_ca_system_score_codex":0.00023115818,"about_ca_system_score_gemma":0.0005389079,"threshold_uncertainty_score":0.109036386},"labels":[],"label_agreement":null},{"id":"W3186964932","doi":"10.82308/16280","title":"This is your brain on disk: the impact of numerical instabilities in neuroscience","year":2021,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Health Canada; Canada First Research Excellence Fund; Canadian Open Neuroscience Platform; Compute Canada; Mitacs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Neuroscience; Computational neuroscience; Computer science; Psychology; Cognitive science","score_opus":0.07802095761333774,"score_gpt":0.3609086670552924,"score_spread":0.2828877094419546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186964932","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.085146815,0.15553768,0.10444066,0.3741003,0.027687129,0.00022925225,0.00343538,0.0051236534,0.24429917],"genre_scores_gemma":[0.6188985,0.09188457,0.07219079,0.036550965,0.014100557,0.00050517253,0.0025264325,0.007701753,0.15564123],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955461,0.0014975574,0.00024804825,0.0007870247,0.0017073448,0.00021390805],"domain_scores_gemma":[0.95317334,0.0274372,0.0027218398,0.0053453003,0.009349039,0.0019732697],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005551573,0.0008508903,0.0011704208,0.0040620086,0.0031581828,0.01600715,0.0022906088,0.0035060134,0.056657955],"category_scores_gemma":[0.1159268,0.0006234186,0.00080861314,0.004154288,0.005798891,0.020069791,0.0066473507,0.003592732,0.024321567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083582767,0.00010161448,0.010063188,0.0014630441,0.00022239075,0.0008334362,0.0038922974,0.0043904115,0.0024754626,0.19584417,0.32697892,0.45289925],"study_design_scores_gemma":[0.00010535108,0.0001407793,0.008959472,0.0022369274,0.00015198141,0.0018567573,0.004472432,0.015528593,0.0027288361,0.5269472,0.43663764,0.00023401296],"about_ca_topic_score_codex":0.0048793335,"about_ca_topic_score_gemma":0.004051499,"teacher_disagreement_score":0.9944484,"about_ca_system_score_codex":0.0030330976,"about_ca_system_score_gemma":0.0030469743,"threshold_uncertainty_score":0.18953973},"labels":[],"label_agreement":null},{"id":"W3187151879","doi":"10.21203/rs.3.rs-747810/v1","title":"The Value of Diffusion Kurtosis Imaging In Detecting Delayed Brain Development of Premature Infants","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Kurtosis; Diffusion MRI; Value (mathematics); Diffusion; Brain development; Medicine; Psychology; Neuroscience; Physics; Radiology; Mathematics; Statistics; Magnetic resonance imaging","score_opus":0.08059295761425733,"score_gpt":0.4464782498589613,"score_spread":0.36588529224470395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187151879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970927,0.0013076545,0.0009282104,0.000039381674,0.000011586375,0.000008620451,0.00011610992,0.00002122483,0.00047454622],"genre_scores_gemma":[0.9984475,0.00032592565,0.0010186337,0.000007864173,0.000011753969,0.000008225384,0.00008368707,0.000003632691,0.00009283451],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993882,0.00025899566,0.00009165654,0.00010737955,0.00010403295,0.000049793172],"domain_scores_gemma":[0.9971595,0.0011265875,0.0010383665,0.000117580494,0.00032946118,0.00022851602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015437191,0.0007265135,0.00037069907,0.0016685535,0.0001845803,0.000737527,0.00031870764,0.00041853567,0.0006708631],"category_scores_gemma":[0.007601361,0.00023836232,0.0002944699,0.00043414393,0.0003430857,0.00054206484,0.0005220262,0.0003841406,0.00015616571],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081343454,0.00003173483,0.97665477,0.00007482281,0.00008954486,0.00072536635,0.00011432032,0.00035003843,0.005787119,0.000060658404,0.00010353236,0.015194634],"study_design_scores_gemma":[0.000013606085,0.00046343505,0.9896408,0.000038767044,0.00007862775,0.002371533,0.00023043915,0.0036061688,0.0030021372,0.00020109517,0.00033455587,0.00001887588],"about_ca_topic_score_codex":0.00082433445,"about_ca_topic_score_gemma":0.0006836271,"teacher_disagreement_score":0.0016685535,"about_ca_system_score_codex":0.00021157831,"about_ca_system_score_gemma":0.00023374193,"threshold_uncertainty_score":0.008164048},"labels":[],"label_agreement":null},{"id":"W3187199062","doi":"10.3389/fnins.2021.665017","title":"Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"White matter; Fornix; Diffusion MRI; Fractional anisotropy; Multiple sclerosis; Tractography; Medicine; Superior longitudinal fasciculus; Corticospinal tract; Uncinate fasciculus; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Psychology; Internal medicine; Hippocampus; Psychiatry","score_opus":0.0393002842218396,"score_gpt":0.2780610686705374,"score_spread":0.23876078444869783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187199062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99899703,0.00035987078,0.00034294848,0.00004107549,0.0000022525346,0.00000803646,0.000041645177,0.000013219489,0.0001939687],"genre_scores_gemma":[0.9985942,0.00024376763,0.00085454073,0.000026735064,0.000006911503,0.000008144766,0.00008322783,0.0000021603473,0.00018020555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985456,0.000029549834,0.000022317128,0.000041279094,0.000038566865,0.000013662003],"domain_scores_gemma":[0.9995571,0.00008380452,0.00023847517,0.000032008596,0.000049940656,0.000038694077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047338093,0.00027155614,0.00020271096,0.0005071205,0.00016307877,0.00026285034,0.0001556914,0.00036330216,0.0014200893],"category_scores_gemma":[0.0013872056,0.00016388734,0.00013510957,0.00030663077,0.00019639301,0.00037364935,0.0002582848,0.00016646378,0.0003825608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025815069,0.000111471534,0.94259584,0.000088100125,0.00005816652,0.0008986376,0.0005143672,0.00011743172,0.034423634,0.000033421213,0.00012887933,0.020771857],"study_design_scores_gemma":[0.000008775652,0.00027875096,0.9951675,0.0000098774435,0.000015994769,0.002706025,0.00011569425,0.00015061154,0.0013095756,0.000027556478,0.0002072015,0.00000236102],"about_ca_topic_score_codex":0.0006239405,"about_ca_topic_score_gemma":0.0011902336,"teacher_disagreement_score":0.0014200893,"about_ca_system_score_codex":0.00009010116,"about_ca_system_score_gemma":0.00011527669,"threshold_uncertainty_score":0.004750669},"labels":[],"label_agreement":null},{"id":"W3187359846","doi":"10.1109/isbi52829.2022.9761680","title":"Reproducibility and Evolution of Diffusion Mri Measurements Within the Cervical Spinal Cord in Multiple Sclerosis","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"EMI","keywords":"Multiple sclerosis; Spinal cord; Diffusion MRI; Reproducibility; Diffusion; Magnetic resonance imaging; Medicine; Computer science; Radiology; Physics; Mathematics","score_opus":0.09399315719702295,"score_gpt":0.3408187529118911,"score_spread":0.24682559571486817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187359846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912164,0.00070654164,0.0070348717,0.000052018277,0.000028621582,0.00002220456,0.00023338977,0.000121551915,0.0005844878],"genre_scores_gemma":[0.9978241,0.00006917922,0.0017372088,0.000010996142,0.000011159106,0.0000090088415,0.00019634745,0.000028300026,0.00011372837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99711525,0.0010214626,0.0002991358,0.0008756418,0.0005649036,0.00012361178],"domain_scores_gemma":[0.98417306,0.00696184,0.0021125204,0.003510666,0.0029035027,0.00033836445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046686158,0.0004991562,0.0004111963,0.0011839755,0.00042907652,0.00076892355,0.00052224426,0.000788834,0.00032139762],"category_scores_gemma":[0.02740302,0.00021989718,0.00033927266,0.00069520425,0.00076138024,0.0004663701,0.00070027256,0.00039374523,0.00022959142],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033377758,0.00022444867,0.7053815,0.00052390585,0.0011933899,0.0007527304,0.003978955,0.01389468,0.15194866,0.00035676998,0.000699493,0.11770763],"study_design_scores_gemma":[0.00003063914,0.0010515447,0.94283825,0.000039269395,0.00029564105,0.0018261459,0.0005178911,0.01649691,0.03548244,0.00050914055,0.00082409737,0.000088081615],"about_ca_topic_score_codex":0.0037459987,"about_ca_topic_score_gemma":0.00438489,"teacher_disagreement_score":0.0046686158,"about_ca_system_score_codex":0.00033572922,"about_ca_system_score_gemma":0.00024253626,"threshold_uncertainty_score":0.02469027},"labels":[],"label_agreement":null},{"id":"W3187580021","doi":"10.1101/2021.08.08.455570","title":"Empirical Transmit Field Bias Correction of T1w/T2w Myelin Maps","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Japan Agency for Medical Research and Development","keywords":"Spurious relationship; Myelin; Field (mathematics); Computer science; Statistics; Psychology; Mathematics; Neuroscience","score_opus":0.06883031625254665,"score_gpt":0.3200902671224307,"score_spread":0.25125995086988406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187580021","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09072285,0.0009750911,0.90296566,0.000399847,0.00021779376,0.000101381105,0.00039170773,0.002594934,0.0016307324],"genre_scores_gemma":[0.3238491,0.0009805051,0.6685895,0.00031766592,0.00011471845,0.00027769047,0.0008272137,0.0024005945,0.002643077],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998781,0.0004750769,0.0000862274,0.00026927816,0.00032556444,0.000062911684],"domain_scores_gemma":[0.99368346,0.0021989911,0.0013297212,0.001229906,0.0014261444,0.0001318731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004953271,0.0011090455,0.00046117505,0.0012384452,0.0005233423,0.0012996484,0.0012994658,0.0009662718,0.0023604038],"category_scores_gemma":[0.022316702,0.00044712276,0.0004858435,0.0012120428,0.0007907448,0.0014065257,0.001043544,0.0013906487,0.0007518335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011911881,0.00024398102,0.037848294,0.0017025297,0.00097347103,0.00063896546,0.0013205172,0.052139025,0.31536806,0.025762849,0.012696693,0.55011433],"study_design_scores_gemma":[0.00015517084,0.0004368257,0.083885856,0.00042315832,0.00059390446,0.0030710516,0.00040313636,0.4177204,0.41708457,0.042290468,0.033571795,0.00036370635],"about_ca_topic_score_codex":0.001721818,"about_ca_topic_score_gemma":0.0032628928,"teacher_disagreement_score":0.004953271,"about_ca_system_score_codex":0.0005032411,"about_ca_system_score_gemma":0.0009949494,"threshold_uncertainty_score":0.026195705},"labels":[],"label_agreement":null},{"id":"W3188867876","doi":"10.1101/2021.08.04.455122","title":"Test-retest reproducibility of <i>in vivo</i> oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Reproducibility; Diffusion MRI; Kurtosis; Voxel; Fractional anisotropy; Anisotropy; Nuclear magnetic resonance; Isotropy; Materials science; Sample size determination; Region of interest; Thermal diffusivity; Sensitivity (control systems); Biomedical engineering; Nuclear medicine; Mathematics; Physics; Magnetic resonance imaging; Statistics; Computer science; Medicine; Artificial intelligence; Radiology; Optics","score_opus":0.023801361879635646,"score_gpt":0.27499152429824186,"score_spread":0.2511901624186062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188867876","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.949462,0.0007151692,0.046395,0.00010863357,0.0000995018,0.00018584543,0.00084952015,0.0008611972,0.0013230996],"genre_scores_gemma":[0.97059256,0.00021221532,0.02539148,0.00018953341,0.000035443638,0.00054308935,0.0008741757,0.0004306068,0.001730891],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99699473,0.0007032433,0.00033300568,0.001068058,0.0006993428,0.00020162846],"domain_scores_gemma":[0.9891551,0.001964928,0.002324399,0.0024374947,0.0037408953,0.00037717188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006336717,0.0006221457,0.0005817131,0.00078839844,0.00045125623,0.0006575509,0.0006469384,0.00056804885,0.0007191398],"category_scores_gemma":[0.006558257,0.0005206284,0.00051940314,0.00033089292,0.00076313707,0.00057361554,0.00049803004,0.0008329636,0.0003852847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019073976,0.0002823568,0.022143647,0.00014247761,0.00038087193,0.00008129526,0.0004465891,0.0010536213,0.9559605,0.00016104967,0.0005637824,0.016876366],"study_design_scores_gemma":[0.0001594782,0.0050129476,0.37139004,0.000051633375,0.0007637839,0.0005455184,0.00016207939,0.010187199,0.60799384,0.0005007174,0.0030655211,0.00016730539],"about_ca_topic_score_codex":0.0011216972,"about_ca_topic_score_gemma":0.0024819355,"teacher_disagreement_score":0.006336717,"about_ca_system_score_codex":0.00037526217,"about_ca_system_score_gemma":0.00031341112,"threshold_uncertainty_score":0.033512175},"labels":[],"label_agreement":null},{"id":"W3188868842","doi":"10.1002/brb3.3159","title":"Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord","year":2023,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Région Bretagne; Mitacs; Institut National de la Santé et de la Recherche Médicale; Conseil Régional de Bretagne; European Commission","keywords":"Multiple sclerosis; Diffusion MRI; Spinal cord; Medicine; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Physical medicine and rehabilitation; Psychology; Psychiatry","score_opus":0.1573476211009158,"score_gpt":0.3692881384332028,"score_spread":0.211940517332287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188868842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9161003,0.0064810645,0.07341832,0.00028404762,0.00006375667,0.00016933476,0.00075989205,0.00044110446,0.0022820812],"genre_scores_gemma":[0.9785865,0.00063686696,0.020274451,0.000021612583,0.000022689486,0.000021739612,0.00023328906,0.000026144719,0.0001767869],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986462,0.0004914912,0.00013859221,0.00031795006,0.0003484022,0.000057345773],"domain_scores_gemma":[0.99342936,0.0040791687,0.0009350965,0.00049469934,0.00081764767,0.00024404643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047851056,0.0010831614,0.0007850216,0.0036951238,0.0003391307,0.0015413249,0.0004320508,0.0007736281,0.0007511063],"category_scores_gemma":[0.012982461,0.00020887234,0.00066292926,0.0014018667,0.0005474148,0.0012151164,0.00065131544,0.0004427812,0.00029289577],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002757511,0.00041670023,0.45614228,0.0011253799,0.0027306261,0.00034294647,0.00040746646,0.07195031,0.05940491,0.0012214923,0.0014784047,0.402022],"study_design_scores_gemma":[0.00007628181,0.0020102125,0.4349003,0.00023599464,0.0012859637,0.0014771281,0.0003502304,0.51508164,0.038693007,0.003658025,0.002030044,0.00020119021],"about_ca_topic_score_codex":0.0027296944,"about_ca_topic_score_gemma":0.003844888,"teacher_disagreement_score":0.0047851056,"about_ca_system_score_codex":0.0005113271,"about_ca_system_score_gemma":0.00064798683,"threshold_uncertainty_score":0.025306344},"labels":[],"label_agreement":null},{"id":"W3189777777","doi":"10.3389/fnimg.2022.930496","title":"Manifold-aware synthesis of high-resolution diffusion from structural imaging","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Fractional anisotropy; Diffusion; Metric (unit); Computer science; Tractography; Voxel; Artificial intelligence; Similarity (geometry); Resolution (logic); Image resolution; Anisotropic diffusion; Euclidean space; Mathematics; Computer vision; Image (mathematics); Mathematical analysis; Physics","score_opus":0.019672773296069864,"score_gpt":0.2769453763328992,"score_spread":0.2572726030368293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3189777777","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010851507,0.000121204816,0.9870673,0.00012742948,0.000033349163,0.00002348314,0.00008745622,0.0008509391,0.00083739427],"genre_scores_gemma":[0.36565426,0.0004433484,0.6279317,0.00019743571,0.00006400563,0.00015188796,0.000850237,0.0007608069,0.003946426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979705,0.000042355587,0.000010181804,0.00006598455,0.00006653823,0.000018032635],"domain_scores_gemma":[0.99954504,0.00018993243,0.00005805791,0.00008238074,0.000094101146,0.00003048733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056491996,0.0009059665,0.00047866392,0.00053513004,0.0002505183,0.0006004754,0.00073411304,0.0008115523,0.0017429007],"category_scores_gemma":[0.002313796,0.00041557994,0.0009817221,0.00042508618,0.00053496816,0.00088431523,0.00087831944,0.0012868146,0.00070587866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007634201,0.000046773872,0.0006606168,0.00021923175,0.00009035629,0.00018247322,0.00015806897,0.74400955,0.06219303,0.018885171,0.0032786047,0.17019984],"study_design_scores_gemma":[0.0000045421525,0.000021850292,0.00013299583,0.0000065414174,0.0000075448584,0.000057637284,0.0000075615417,0.98465353,0.007447333,0.0061998786,0.0014530594,0.0000075883577],"about_ca_topic_score_codex":0.0020194685,"about_ca_topic_score_gemma":0.003719363,"teacher_disagreement_score":0.0020194685,"about_ca_system_score_codex":0.00060744653,"about_ca_system_score_gemma":0.00074346265,"threshold_uncertainty_score":0.005830586},"labels":[],"label_agreement":null},{"id":"W3190336459","doi":"10.3389/fnagi.2021.681208","title":"The Associations Between White Matter Disruptions and Cognitive Decline at the Early Stage of Subcortical Vascular Cognitive Impairment: A Case–Control Study","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"China-Japan Friendship Hospital; National Natural Science Foundation of China","keywords":"Cognition; Audiology; Psychology; White matter; Cognitive decline; Montreal Cognitive Assessment; Diffusion MRI; Neuropsychology; Cognitive impairment; Neuroscience; Medicine; Internal medicine; Disease; Dementia","score_opus":0.02873667231514283,"score_gpt":0.337903273763327,"score_spread":0.3091666014481842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190336459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99844897,0.00046492307,0.00054384134,0.000018778375,0.000013304844,0.000096088035,0.00007475326,0.00000673551,0.00033257323],"genre_scores_gemma":[0.99899346,0.00015030714,0.00042227327,0.000026032325,0.00002985418,0.000063397674,0.0001412724,0.0000036902259,0.00016970595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99796057,0.00045911255,0.00023860004,0.0009245407,0.00026760038,0.00014960999],"domain_scores_gemma":[0.99828404,0.00051336037,0.00040473224,0.00036625285,0.00021349001,0.00021813424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024102987,0.0009920775,0.000993405,0.0021603268,0.0016795292,0.00094792293,0.00087831396,0.0011189721,0.0018540953],"category_scores_gemma":[0.0035005813,0.0010801577,0.0007390466,0.0014651723,0.0011472321,0.000700041,0.0007438471,0.00060006557,0.00024299273],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013730307,0.0011400864,0.9864356,0.00008722988,0.000677141,0.002779327,0.0009514421,0.00008316939,0.002574104,0.00021049392,0.00019392923,0.00349443],"study_design_scores_gemma":[0.0002401653,0.0021224641,0.98824,0.000023672648,0.00058357837,0.006080782,0.0005163053,0.0007548687,0.0004457348,0.00018097137,0.00078051345,0.0000308832],"about_ca_topic_score_codex":0.0040702038,"about_ca_topic_score_gemma":0.0033144683,"teacher_disagreement_score":0.0040702038,"about_ca_system_score_codex":0.0004098192,"about_ca_system_score_gemma":0.00032786798,"threshold_uncertainty_score":0.01274699},"labels":[],"label_agreement":null},{"id":"W3190769832","doi":"10.1007/s00429-021-02358-w","title":"Dissecting whole-brain conduction delays through MRI microstructural measures","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Wellcome Trust; Wellcome","keywords":"Thermal conduction; Tractography; Nerve conduction velocity; Neuroscience; White matter; Constant (computer programming); Statistical physics; Physics; Computer science; Psychology; Magnetic resonance imaging","score_opus":0.04994246506520538,"score_gpt":0.3266202289761371,"score_spread":0.2766777639109317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190769832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7292542,0.00044195718,0.26839235,0.000109491964,0.000019515504,0.00003972743,0.0004228816,0.00028827376,0.0010316484],"genre_scores_gemma":[0.9738013,0.00022315266,0.025543816,0.000011261628,0.000008084355,0.000024768222,0.00015637973,0.000050544906,0.00018059653],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99989223,0.000028221115,0.0000079872625,0.00003798714,0.000020297326,0.000013238075],"domain_scores_gemma":[0.99847525,0.0010107493,0.00025687471,0.00011492443,0.0000850507,0.00005704411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006983332,0.00054007646,0.00018151152,0.001758823,0.00014866643,0.0006307467,0.00029313687,0.00041153588,0.00090900314],"category_scores_gemma":[0.004827916,0.00021266175,0.00022572711,0.0008828575,0.00041899655,0.0014392663,0.00034573837,0.0005103846,0.00014126566],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005850667,0.00017564959,0.049860977,0.0005463919,0.00043978536,0.00063507416,0.0009955063,0.5423664,0.29271665,0.03210749,0.0008081346,0.07876288],"study_design_scores_gemma":[0.00002267039,0.00025154563,0.06023665,0.000041944386,0.000106226566,0.00049583975,0.00019517328,0.86065704,0.040581837,0.036072735,0.0012600139,0.00007840533],"about_ca_topic_score_codex":0.001642098,"about_ca_topic_score_gemma":0.0024079746,"teacher_disagreement_score":0.001758823,"about_ca_system_score_codex":0.00029490818,"about_ca_system_score_gemma":0.0003490424,"threshold_uncertainty_score":0.0036931634},"labels":[],"label_agreement":null},{"id":"W3190885595","doi":"10.3389/fsurg.2021.646465","title":"Constrained-Spherical Deconvolution Tractography in the Evaluation of the Corticospinal Tract in Glioma Surgery","year":2021,"lang":"en","type":"article","venue":"Frontiers in Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"ETH Zürich Foundation; Henan Provincial People's Hospital; Eidgenössische Technische Hochschule Zürich","keywords":"Tractography; Corticospinal tract; Fractional anisotropy; Diffusion MRI; Glioma; Medicine; Superior longitudinal fasciculus; White matter; Precentral gyrus; Motor cortex; Brain tumor; Nuclear medicine; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.1080247719335625,"score_gpt":0.35704447353103375,"score_spread":0.24901970159747125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190885595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9416463,0.0014477939,0.05585424,0.00008303438,0.000006896194,0.000057518424,0.00020283283,0.00014133126,0.0005600704],"genre_scores_gemma":[0.9830404,0.0004125914,0.016190514,0.0000081684375,0.0000047734625,0.000025468704,0.000110210305,0.000012528599,0.00019536147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998628,0.00007521843,0.000010933227,0.000017575425,0.000023762726,0.000009708571],"domain_scores_gemma":[0.99948716,0.00021116482,0.0001377591,0.000034929515,0.00007390165,0.00005506216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007349629,0.00037000826,0.00021323169,0.000977722,0.00013275858,0.00029536235,0.00019265155,0.00033884018,0.00079079455],"category_scores_gemma":[0.0024311626,0.00015366288,0.00021629232,0.00043874537,0.00039521544,0.00035830066,0.00030966668,0.00017461776,0.00020144353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045612454,0.00018002385,0.49644625,0.00092655787,0.000544044,0.0029732464,0.000618164,0.09591277,0.16176619,0.0018647241,0.0007652265,0.23344162],"study_design_scores_gemma":[0.000103878054,0.0011377475,0.5632633,0.000096882075,0.00016855204,0.008402664,0.00035232314,0.3865317,0.033395912,0.004396507,0.0020399904,0.00011063152],"about_ca_topic_score_codex":0.005812148,"about_ca_topic_score_gemma":0.007911808,"teacher_disagreement_score":0.005812148,"about_ca_system_score_codex":0.0003679407,"about_ca_system_score_gemma":0.0008110965,"threshold_uncertainty_score":0.011556625},"labels":[],"label_agreement":null},{"id":"W3191188472","doi":"10.3389/fnagi.2021.700764","title":"White Matter Integrity Underlies the Physical-Cognitive Correlations in Subjective Cognitive Decline","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan; Ministry of Education, India; Chang Gung Memorial Hospital; Chang Gung Medical Foundation; Shanghai Educational Development Foundation; Ministry of Education","keywords":"Montreal Cognitive Assessment; Cognitive decline; Cognition; Fractional anisotropy; Diffusion MRI; White matter; Effects of sleep deprivation on cognitive performance; Psychology; Dementia; Medicine; Physical medicine and rehabilitation; Gerontology; Internal medicine; Neuroscience; Magnetic resonance imaging; Cognitive impairment; Disease","score_opus":0.04874514009417484,"score_gpt":0.35189715554083767,"score_spread":0.3031520154466628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191188472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985228,0.00059301243,0.00026004048,0.00006260907,0.0000042153783,0.000008959285,0.00014360706,0.0000051486545,0.0003996954],"genre_scores_gemma":[0.99967647,0.00007319733,0.00008351731,0.000008613225,0.000008631957,0.0000030784765,0.00007972144,5.4855576e-7,0.00006626779],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976915,0.000052764823,0.00003776456,0.000059629736,0.000049926202,0.000030689258],"domain_scores_gemma":[0.99746823,0.00041722524,0.0015853106,0.00014162691,0.00026358722,0.0001240207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000894937,0.00033677794,0.00020753908,0.0007268216,0.00017231621,0.0004075605,0.00024844462,0.00022146749,0.0013250901],"category_scores_gemma":[0.0037850041,0.00015850768,0.00022413324,0.00046009553,0.00048250007,0.0003599471,0.00046781142,0.00029782043,0.00009912569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001151813,0.000034537556,0.9962249,0.000021395766,0.000073572606,0.000088463195,0.00007147862,0.00008060491,0.00070952653,0.000033926983,0.00004042515,0.0025060389],"study_design_scores_gemma":[0.0000019486765,0.000037616122,0.99948055,0.0000037858197,0.000017898737,0.000121671954,0.0000235338,0.00014373328,0.000096446245,0.000036405043,0.00003549948,9.2913814e-7],"about_ca_topic_score_codex":0.0023422886,"about_ca_topic_score_gemma":0.003957871,"teacher_disagreement_score":0.0023422886,"about_ca_system_score_codex":0.00019399366,"about_ca_system_score_gemma":0.00021332726,"threshold_uncertainty_score":0.004732907},"labels":[],"label_agreement":null},{"id":"W3191534335","doi":"10.1016/j.pscychresns.2021.111341","title":"Diffusion kurtosis imaging of white matter in bipolar disorder","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hotchkiss Brain Institute; University of Calgary; University of Toronto","funders":"Canadian Institutes of Health Research; Pfizer Canada","keywords":"Diffusion MRI; White matter; Kurtosis; Fractional anisotropy; Voxel; Magnetic resonance imaging; Tractography; Nuclear magnetic resonance; Nuclear medicine; Medicine; Neuroscience; Physics; Psychology; Radiology; Mathematics; Statistics","score_opus":0.06794406722086672,"score_gpt":0.4084647973020994,"score_spread":0.3405207300812327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191534335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919813,0.0024888865,0.0027608944,0.00036316356,0.000025903324,0.000013647555,0.000108897126,0.000041193147,0.0022160916],"genre_scores_gemma":[0.9964115,0.0013437821,0.0016175127,0.00004862145,0.00004600569,0.000006391556,0.00005832215,0.00002191507,0.00044585226],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992037,0.000022369335,0.000012974372,0.000009624611,0.000015255739,0.000019396504],"domain_scores_gemma":[0.9996822,0.00011082802,0.00008719165,0.00001912769,0.00005663311,0.00004408497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057154417,0.00047394467,0.00020791162,0.0016712284,0.00039409666,0.0007278482,0.00020867765,0.00041383415,0.001701227],"category_scores_gemma":[0.0017601178,0.0003028859,0.00017454849,0.00047358585,0.00043632754,0.00095281296,0.00040446472,0.00040454936,0.00022106284],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010790456,0.0003904058,0.23565051,0.00081473275,0.0006103571,0.029438108,0.002167231,0.0057077473,0.5631839,0.004948924,0.0032070677,0.14309056],"study_design_scores_gemma":[0.00033321002,0.0010154131,0.82491875,0.0002529989,0.0003838914,0.050132234,0.0025323355,0.032851417,0.07290148,0.011820482,0.002722286,0.00013557872],"about_ca_topic_score_codex":0.0018562822,"about_ca_topic_score_gemma":0.0015455076,"teacher_disagreement_score":0.0018562822,"about_ca_system_score_codex":0.0002717584,"about_ca_system_score_gemma":0.00020720197,"threshold_uncertainty_score":0.0056912303},"labels":[],"label_agreement":null},{"id":"W3191793176","doi":"10.1155/2021/2120130","title":"Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination","year":2021,"lang":"en","type":"article","venue":"Contrast Media & Molecular Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Corpus callosum; Magnetic resonance imaging; Psychology; Frontal lobe; Internal medicine; Medicine; Audiology; Cardiology; Cognition; Psychiatry; Neuroscience; Cognitive impairment; Radiology","score_opus":0.007086150495768873,"score_gpt":0.25996472607507454,"score_spread":0.25287857557930565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191793176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99807054,0.00085760106,0.00023269276,0.000081357255,0.00001775445,0.000013863462,0.00007477383,0.0000064869937,0.0006449517],"genre_scores_gemma":[0.9990858,0.00027658898,0.0003762668,0.000018905193,0.000040143506,0.000007140575,0.00009537633,0.0000011072472,0.00009873536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994684,0.00015846032,0.00009829562,0.00010651426,0.00011994419,0.000048404465],"domain_scores_gemma":[0.9989693,0.00025708074,0.00030309256,0.0000633281,0.0002240353,0.00018315612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008882022,0.0005460279,0.00042535347,0.0017836848,0.00031009922,0.00055050006,0.00029094453,0.00043309506,0.0006100252],"category_scores_gemma":[0.0028458135,0.00017956205,0.0002913884,0.0006569583,0.00026099067,0.00072369515,0.00046407498,0.00037857294,0.0002214639],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027285833,0.000053745287,0.9922052,0.000019416586,0.000051097235,0.0003170384,0.00006487595,0.00005631244,0.0012678724,0.0000071926925,0.00005578365,0.005628662],"study_design_scores_gemma":[0.000028382598,0.0005572401,0.9947514,0.000021590757,0.00011168577,0.0021015839,0.00045428053,0.00097261637,0.0006438274,0.000046193083,0.0002965386,0.000014653395],"about_ca_topic_score_codex":0.0010582181,"about_ca_topic_score_gemma":0.0019953933,"teacher_disagreement_score":0.0017836848,"about_ca_system_score_codex":0.00014595175,"about_ca_system_score_gemma":0.00022287425,"threshold_uncertainty_score":0.004697323},"labels":[],"label_agreement":null},{"id":"W3192358327","doi":"10.1002/hipo.23382","title":"The structure of hippocampal circuitry relates to rapid category learning in humans","year":2021,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Ontario Research Foundation; Fondation Brain Canada","keywords":"Psychology; Categorization; White matter; Entorhinal cortex; Hippocampal formation; Neuroscience; Cognitive psychology; Cognitive science; Artificial intelligence; Computer science","score_opus":0.03010554406010817,"score_gpt":0.31270841839144264,"score_spread":0.28260287433133446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192358327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971539,0.000032294054,0.0020178636,0.000044159267,0.0000030795238,0.0000049288055,0.000050490897,0.000022290304,0.0006710006],"genre_scores_gemma":[0.99894875,0.000014412314,0.0008597004,0.000013179702,0.0000017463658,0.000002582419,0.000031724954,0.000004235972,0.00012355477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999007,0.000013544628,0.0000047633575,0.000048213245,0.000021458087,0.00001126839],"domain_scores_gemma":[0.9991302,0.00020440998,0.0003287529,0.00017402717,0.00007809736,0.00008455216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037221395,0.0001122188,0.000117631804,0.0003107266,0.00012256537,0.00042509873,0.00015252671,0.00023864863,0.0014653724],"category_scores_gemma":[0.0023753785,0.00015495165,0.00007303519,0.00012042665,0.000631485,0.00051550835,0.00029003998,0.00034700954,0.00010771359],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083473127,0.00036549295,0.6148209,0.00016263178,0.00023098926,0.00063245354,0.0030077663,0.0076502403,0.2551052,0.0042047263,0.0017642701,0.11122047],"study_design_scores_gemma":[0.000010617656,0.00023341719,0.97610885,0.000010899227,0.000017793456,0.0005374635,0.00024412436,0.0047511486,0.010932363,0.006472481,0.00066075294,0.000020227746],"about_ca_topic_score_codex":0.0009262864,"about_ca_topic_score_gemma":0.0019935644,"teacher_disagreement_score":0.0014653724,"about_ca_system_score_codex":0.00011271029,"about_ca_system_score_gemma":0.00011267944,"threshold_uncertainty_score":0.004902184},"labels":[],"label_agreement":null},{"id":"W3193894044","doi":"10.1093/biostatistics/kxab031","title":"Estimation for the bivariate quantile varying coefficient model with application to diffusion tensor imaging data analysis","year":2021,"lang":"en","type":"article","venue":"Biostatistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; National Cancer Institute; National Institute of Mental Health; Canadian Statistical Sciences Institute; Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Interpretability; Bivariate analysis; Computer science; Quantile; Diffusion MRI; Quantile regression; Data set; Artificial intelligence; Mathematics; Econometrics; Machine learning","score_opus":0.085489773200644,"score_gpt":0.39188917805165296,"score_spread":0.30639940485100897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193894044","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007793241,0.00014022161,0.9914239,0.00023961894,0.0000113315255,0.00002419043,0.00007365872,0.0001508634,0.00014305708],"genre_scores_gemma":[0.36065337,0.0012796421,0.63251114,0.00025515174,0.00011907396,0.00045729018,0.00086128246,0.00043916146,0.0034238694],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99775535,0.0015023106,0.000071193135,0.00031531372,0.00021674378,0.00013913747],"domain_scores_gemma":[0.9867025,0.010597913,0.00085720257,0.0007345704,0.000911575,0.00019620372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01034898,0.00078507845,0.001203145,0.0011447273,0.0004220884,0.001081039,0.0020495593,0.0014665624,0.0021753055],"category_scores_gemma":[0.03232351,0.00072686805,0.0013374852,0.0016330532,0.0011450693,0.0013558348,0.0016610294,0.002609167,0.00050392485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013855954,0.00006137762,0.007274163,0.0001509094,0.00016173317,0.00026537938,0.0002261233,0.80830634,0.0025522101,0.10341648,0.002445938,0.07500079],"study_design_scores_gemma":[0.0000088738025,0.0000140853035,0.0005363326,0.000010689975,0.000010515324,0.00003437998,0.000014269736,0.98062,0.00022248493,0.017887777,0.0006278786,0.0000127461435],"about_ca_topic_score_codex":0.010972941,"about_ca_topic_score_gemma":0.0071777413,"teacher_disagreement_score":0.010972941,"about_ca_system_score_codex":0.0009561882,"about_ca_system_score_gemma":0.001923201,"threshold_uncertainty_score":0.05473125},"labels":[],"label_agreement":null},{"id":"W3194483091","doi":"10.1007/s13365-021-01000-z","title":"Long-term sequelae of herpes simplex virus encephalitis–related white matter injury: correlation of neuropsychological outcome and diffusion tensor imaging","year":2021,"lang":"en","type":"article","venue":"Journal of NeuroVirology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Inferior longitudinal fasciculus; Fornix; Fractional anisotropy; Uncinate fasciculus; White matter; Corpus callosum; Diffusion MRI; Fasciculus; Cingulum (brain); Medicine; Psychology; Splenium; Neuropsychology; Neuroscience; Audiology; Magnetic resonance imaging; Radiology; Hippocampus; Cognition","score_opus":0.04289657789806872,"score_gpt":0.3650554783402334,"score_spread":0.32215890044216466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194483091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99916804,0.00026062378,0.000046929305,0.000047705442,0.000007760343,0.000005007712,0.000045978923,0.0000014351685,0.00041649703],"genre_scores_gemma":[0.99954635,0.00015310165,0.000025502832,0.000013647089,0.000021059119,0.0000028250079,0.000108296466,7.554063e-7,0.00012840878],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967563,0.00006145802,0.000053065785,0.000041564002,0.00006261909,0.00010577574],"domain_scores_gemma":[0.9971149,0.00041359535,0.0014787101,0.00013981207,0.00028284916,0.00057009136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006999673,0.00042956273,0.00037967184,0.0008520075,0.0005871159,0.0007349318,0.00047149922,0.00053167384,0.001121522],"category_scores_gemma":[0.003761529,0.00018628295,0.00030633388,0.0007163757,0.0008289428,0.0010259114,0.0008136344,0.00093250984,0.00020419575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027044665,0.00009711606,0.9961901,0.000007742719,0.00005732674,0.0011148108,0.00006496739,0.000042439937,0.000403551,0.000023062183,0.0000413154,0.0016871166],"study_design_scores_gemma":[0.000003400943,0.00017810603,0.9972339,0.0000064302512,0.000026564296,0.0019424274,0.0002449444,0.000113704686,0.00010435672,0.00007939578,0.00006182029,0.0000050190633],"about_ca_topic_score_codex":0.0030818295,"about_ca_topic_score_gemma":0.0059910403,"teacher_disagreement_score":0.0030818295,"about_ca_system_score_codex":0.00039398886,"about_ca_system_score_gemma":0.0007476271,"threshold_uncertainty_score":0.0061277747},"labels":[],"label_agreement":null},{"id":"W3194760139","doi":"10.1038/s41597-021-00941-8","title":"Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Centre Hospitalier Universitaire de Sherbrooke; International Collaboration On Repair Discoveries; University of British Columbia; Université de Montréal; Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute","funders":"National Institute of Neurological Disorders and Stroke; Staatssekretariat für Bildung, Forschung und Innovation; Economic and Social Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; CRIS Cancer Foundation; Regione Puglia; University College London Hospitals NHS Foundation Trust; Ministero dell’Istruzione, dell’Università e della Ricerca; Ministero della Salute; Concordia University; Agentura Pro Zdravotnický Výzkum České Republiky; National Institutes of Health; Rosetrees Trust; European Commission; Multiple Sclerosis Society; Bundesministerium für Bildung und Forschung; National Imaging Facility; National Institute for Health and Care Research; University of Pennsylvania; SpinalCure Australia; University of Minnesota; National Science Foundation; Compute Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Polytechnique Montréal; Wellcome Trust; Institut de Valorisation des Données; AstraZeneca; Craig H. Neilsen Foundation; McGill University; Canada First Research Excellence Fund; Max-Planck-Gesellschaft","keywords":"Protocol (science); Reproducibility; Computer science; Spinal cord; Documentation; Data mining; Medicine; Statistics; Mathematics; Pathology","score_opus":0.6245720496163727,"score_gpt":0.5767339061992035,"score_spread":0.04783814341716919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194760139","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07016648,0.0068310634,0.39781493,0.005560696,0.0033227778,0.0073589515,0.45325306,0.018452251,0.037239723],"genre_scores_gemma":[0.20424879,0.003007717,0.32081735,0.0035610315,0.0011805277,0.03874187,0.39438957,0.016666891,0.017386245],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9727237,0.008445717,0.0047874767,0.0047021736,0.00871706,0.0006239324],"domain_scores_gemma":[0.8460825,0.05748343,0.012050132,0.046009578,0.036949597,0.0014247403],"candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.045483172,0.0017158035,0.0014566878,0.004205148,0.0014444222,0.0041127563,0.0033708054,0.002448414,0.045224566],"category_scores_gemma":[0.1963131,0.0012397546,0.00200293,0.004819531,0.0018156222,0.0030422937,0.004322847,0.0017663267,0.018530851],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044510895,0.0006130082,0.060122952,0.012328694,0.0034578694,0.0008517175,0.0034683074,0.003684344,0.017278546,0.013361889,0.47890958,0.401472],"study_design_scores_gemma":[0.0017068062,0.0010428225,0.17642672,0.005143375,0.002153533,0.0038703308,0.0011578329,0.0054794275,0.020277044,0.043906722,0.73797184,0.00086354883],"about_ca_topic_score_codex":0.0030438055,"about_ca_topic_score_gemma":0.006465805,"teacher_disagreement_score":0.9966292,"about_ca_system_score_codex":0.0009324423,"about_ca_system_score_gemma":0.0039415765,"threshold_uncertainty_score":0.24054086},"labels":[{"model":"gemma","categories":["metaresearch","open_science"],"domain":"reproducibility","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":["metaresearch","open_science"],"domain":"reproducibility","study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W3194855278","doi":"10.7554/elife.70119","title":"The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging","year":2021,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Sick Kids Foundation; Canadian Institutes of Health Research; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Helmholtz Association; Natural Sciences and Engineering Research Council of Canada","keywords":"Toolbox; Neuroimaging; Workflow; Computer science; Data science; Artificial intelligence; Human–computer interaction; Neuroscience; Psychology; Database","score_opus":0.06421679196745048,"score_gpt":0.3615662247518344,"score_spread":0.29734943278438397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194855278","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015244042,0.0010643924,0.8126137,0.00054805743,0.00029469855,0.00018834983,0.00957213,0.16752428,0.0066699637],"genre_scores_gemma":[0.022695422,0.0022846935,0.8646084,0.0011919646,0.00018476523,0.0016071631,0.015718853,0.08256894,0.009139776],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999172,0.0001746801,0.00009167027,0.00015719238,0.00031552813,0.000088999215],"domain_scores_gemma":[0.9970362,0.0015645741,0.00020665431,0.00053457683,0.00040489127,0.00025304992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003276751,0.002085743,0.0011708294,0.0032747951,0.0008665534,0.004024192,0.0038613933,0.002142401,0.0830021],"category_scores_gemma":[0.008149231,0.0023735883,0.002043563,0.0015779779,0.0011406047,0.0032307163,0.005358005,0.0039583803,0.032628696],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056297466,0.00011707901,0.002413994,0.005121691,0.00066860404,0.0015558844,0.0021054738,0.014079427,0.028607434,0.057653233,0.5360167,0.35109752],"study_design_scores_gemma":[0.00026061106,0.00010326818,0.00416958,0.001032255,0.00015286768,0.002774124,0.0004150125,0.072836064,0.04347114,0.14634132,0.7280288,0.0004149941],"about_ca_topic_score_codex":0.0021481335,"about_ca_topic_score_gemma":0.005275077,"teacher_disagreement_score":0.0830021,"about_ca_system_score_codex":0.00083756674,"about_ca_system_score_gemma":0.0021285424,"threshold_uncertainty_score":0.27766967},"labels":[],"label_agreement":null},{"id":"W3194917267","doi":"10.1002/ana.26201","title":"Interaction between Preterm White Matter Injury and Childhood Thalamic Growth","year":2021,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; SickKids Foundation; Hospital for Sick Children; BC Children's Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Kids Brain Health Network","keywords":"Gestational age; White matter; Medicine; Fractional anisotropy; Brain size; Thalamus; Magnetic resonance imaging; Diffusion MRI; Pediatrics; Cohort; Psychology; Internal medicine; Radiology","score_opus":0.06890977092527792,"score_gpt":0.37642765328013633,"score_spread":0.30751788235485844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194917267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987103,0.00033240562,0.00026151497,0.000092738854,0.000004713437,0.0000020873008,0.00027192762,0.000013310408,0.00031100278],"genre_scores_gemma":[0.999171,0.00013331625,0.00020199537,0.000015215461,0.0000056487643,0.0000053112926,0.00024395822,0.000006373484,0.00021730315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99933404,0.00015594844,0.000046886275,0.00020194147,0.00012632788,0.0001347886],"domain_scores_gemma":[0.99643826,0.0008283043,0.0019219527,0.00020311367,0.00029214166,0.00031630456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007533855,0.0005287044,0.00029364062,0.0006057777,0.0002681633,0.000774648,0.0005866297,0.00044037006,0.0016835204],"category_scores_gemma":[0.0054489262,0.00019622192,0.0006168813,0.00051469554,0.00036619083,0.00042821377,0.00071518513,0.00071145064,0.0002556313],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069139685,0.000015516878,0.99740976,0.000006822255,0.00006816607,0.00020153858,0.00004297192,0.000099052486,0.000393689,0.000033366083,0.000035826088,0.0016242004],"study_design_scores_gemma":[8.3592465e-7,0.000045506207,0.99891615,0.000008091763,0.000026037065,0.00032795416,0.00006338067,0.000274453,0.00023309988,0.00004238188,0.000060012197,0.0000022035006],"about_ca_topic_score_codex":0.009921695,"about_ca_topic_score_gemma":0.007884495,"teacher_disagreement_score":0.009921695,"about_ca_system_score_codex":0.00047996358,"about_ca_system_score_gemma":0.00071012974,"threshold_uncertainty_score":0.019727886},"labels":[],"label_agreement":null},{"id":"W3196049305","doi":"10.1101/2021.08.18.456666","title":"Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Université de Montréal; Heart and Stroke Foundation; York University; Montreal Heart Institute; Toronto Western Hospital; University Health Network; Ottawa Hospital; Thunder Bay Regional Research Institute; University of Ottawa; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Western University; University of Toronto","funders":"Faculty of Health Sciences, Queen's University; Canadian Institutes of Health Research; London Health Sciences Foundation; Temerty Family Foundation; Health Sciences Centre Foundation; University of Ottawa; Ontario Brain Institute; Government of Ontario; Queen's University; Centre for Addiction and Mental Health Foundation; McMaster University","keywords":"Segmentation; Artificial intelligence; Computer science; Robustness (evolution); Pattern recognition (psychology); Convolutional neural network; Neuroimaging; Bayesian probability; Hyperintensity; Deep learning; Hausdorff distance; Pipeline (software); Machine learning; Magnetic resonance imaging; Medicine","score_opus":0.019726898143484255,"score_gpt":0.2693101865244165,"score_spread":0.24958328838093227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196049305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047885388,0.0007583837,0.94762963,0.00062794564,0.000070005546,0.00007833552,0.00019861544,0.00087504723,0.00187664],"genre_scores_gemma":[0.8700943,0.00037392654,0.12446476,0.00037640097,0.000077924844,0.00017040913,0.00044387407,0.00018537614,0.0038130686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991559,0.0003530965,0.000042689466,0.00019498335,0.00015154186,0.00010192938],"domain_scores_gemma":[0.9961241,0.002786101,0.00035202442,0.0001750551,0.00044220756,0.000120529156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031150146,0.0013730113,0.0011505011,0.0010332223,0.00045429924,0.0010341194,0.0016130636,0.0020141928,0.0018056665],"category_scores_gemma":[0.00815462,0.0009639041,0.0010962909,0.00043703584,0.0012989059,0.001149888,0.0018715032,0.0026378238,0.0003835749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056323963,0.00001399958,0.00037993866,0.000019764368,0.000025490279,0.000031445812,0.000020832713,0.9829185,0.00051177066,0.0024112342,0.00027900908,0.013331774],"study_design_scores_gemma":[0.000001206739,0.000004661664,0.000035431534,0.0000032469293,0.0000015933026,0.000003859591,8.7557095e-7,0.99877757,0.000151071,0.00097156136,0.000047064757,0.0000017957943],"about_ca_topic_score_codex":0.016497472,"about_ca_topic_score_gemma":0.012226765,"teacher_disagreement_score":0.016497472,"about_ca_system_score_codex":0.0022115905,"about_ca_system_score_gemma":0.0013649253,"threshold_uncertainty_score":0.03280288},"labels":[],"label_agreement":null},{"id":"W3196211813","doi":"10.1101/2020.10.07.321083","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Calgary; Université de Sherbrooke","funders":"National Institutes of Health; Ministry of Science and Technology, Taiwan; University of Melbourne; Consejo Nacional de Ciencia y Tecnología; Agence Nationale de la Recherche; State Government of Victoria; European Commission; Children's Hospital Foundation; Royal Children's Hospital Foundation; Murdoch Children's Research Institute; Medical Research Council; Children’s Hospital of Wisconsin Research Institute; Agencia Nacional de Investigación y Desarrollo; Vanderbilt University","keywords":"Tractography; Segmentation; White matter; Diffusion MRI; Bundle; Computer science; Artificial intelligence; Pattern recognition (psychology); Medicine; Magnetic resonance imaging; Radiology","score_opus":0.042360413678278766,"score_gpt":0.2801282551985172,"score_spread":0.23776784152023844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196211813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9217205,0.0013221701,0.0723119,0.0005324475,0.00025845156,0.00026347468,0.0012174055,0.00068230147,0.001691325],"genre_scores_gemma":[0.980719,0.000116345116,0.016144881,0.00016399547,0.00007034086,0.00022718131,0.0019629225,0.00033286656,0.00026244792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9581354,0.01829836,0.0048323637,0.011365498,0.0064453953,0.00092301756],"domain_scores_gemma":[0.84620214,0.09385514,0.01838534,0.022548242,0.017438086,0.0015711057],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04789079,0.0007111246,0.0010231468,0.0022055695,0.0014553359,0.0024431415,0.0012058072,0.0012854064,0.00081655796],"category_scores_gemma":[0.14108594,0.00041549004,0.0012140283,0.0017853208,0.0024046826,0.0017745849,0.0028605205,0.0012803992,0.0004587769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004094856,0.000419395,0.7460354,0.0010961444,0.0041800067,0.00062468904,0.016403435,0.020125149,0.028418107,0.0030724104,0.008753501,0.16677685],"study_design_scores_gemma":[0.00022783501,0.0012297706,0.8633124,0.00063268794,0.0013182238,0.0016623831,0.006650852,0.066893585,0.023279985,0.022547884,0.011923303,0.00032103024],"about_ca_topic_score_codex":0.0016448542,"about_ca_topic_score_gemma":0.0021270774,"teacher_disagreement_score":0.9521092,"about_ca_system_score_codex":0.0007933979,"about_ca_system_score_gemma":0.0007238921,"threshold_uncertainty_score":0.2532738},"labels":[],"label_agreement":null},{"id":"W3196689162","doi":"10.1002/hbm.25625","title":"A <scp>meta‐analysis</scp> of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the <scp>ENIGMA Consortium</scp>","year":2021,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Instituto de Salud Carlos III; Medical Research Council; National Institutes of Health; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; National Health and Medical Research Council; Norges Forskningsråd; Fundação Amazônia Paraense de Amparo à Pesquisa; National Center for Advancing Translational Sciences; Commonwealth Health Research Board; Wellcome Trust; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Department of Energy, Labor and Economic Growth; Center for Integrated Healthcare, U.S. Department of Veterans Affairs; U.S. Department of Veterans Affairs; Eunice Kennedy Shriver National Institute of Child Health and Human Development; U.S. Department of Energy; Science Foundation Ireland; National Science Foundation","keywords":"Putamen; Thalamus; Neuroscience; Psychology; Schizophrenia (object-oriented programming); Amygdala; Ventral striatum; Hippocampus; Striatum; Caudate nucleus; Nucleus accumbens; Psychosis; Psychiatry; Central nervous system; Dopamine","score_opus":0.09715958766816828,"score_gpt":0.36313971700197795,"score_spread":0.26598012933380966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196689162","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4352883,0.5186105,0.010865493,0.0024106586,0.0007403653,0.00070557545,0.027579779,0.0005408101,0.0032585834],"genre_scores_gemma":[0.9675711,0.021107582,0.003731446,0.0010113907,0.00014479014,0.0005568594,0.0051222905,0.00012268485,0.00063181424],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99471277,0.0026399535,0.0007875908,0.0011180132,0.0005151475,0.00022655979],"domain_scores_gemma":[0.9935702,0.0038386045,0.001017662,0.000875501,0.0005546222,0.00014336868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074077137,0.0014066369,0.0033965283,0.0019770155,0.00083404017,0.001998307,0.001061675,0.0011934538,0.0027230382],"category_scores_gemma":[0.01534638,0.0007303809,0.018637607,0.0031363142,0.00051650166,0.00067797495,0.0013108442,0.0012133648,0.00033986237],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054275407,0.00003395629,0.10974326,0.02377961,0.8369903,0.0005367962,0.00021679356,0.0010066272,0.0027559015,0.00034349744,0.003759169,0.015406666],"study_design_scores_gemma":[0.0010665405,0.00031985552,0.091539875,0.0015135896,0.89948624,0.00033683682,0.00008295436,0.00049755955,0.00067331654,0.000588092,0.0038599279,0.00003521135],"about_ca_topic_score_codex":0.011315626,"about_ca_topic_score_gemma":0.024875242,"teacher_disagreement_score":0.011315626,"about_ca_system_score_codex":0.00089520094,"about_ca_system_score_gemma":0.0013731879,"threshold_uncertainty_score":0.039176166},"labels":[],"label_agreement":null},{"id":"W3197146939","doi":"10.3389/fnins.2021.716538","title":"Tractography in Curvilinear Coordinates","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Canadian Open Neuroscience Platform; Natural Sciences and Engineering Research Council of Canada; NIH Blueprint for Neuroscience Research; Canada Research Chairs","keywords":"Curvilinear coordinates; Bipolar coordinates; Orthogonal coordinates; Log-polar coordinates; Cartesian coordinate system; Parabolic coordinates; Context (archaeology); Action-angle coordinates; Spherical coordinate system; Coordinate system; Tractography; Cartesian tensor; Parallel coordinates; Computer science; Generalized coordinates; Spatial reference system; Polar coordinate system; Visualization; Artificial intelligence; Mathematics; Geometry; Mathematical analysis; Diffusion MRI; Data visualization; Geology; Tensor field","score_opus":0.0487326283880001,"score_gpt":0.3453726620877228,"score_spread":0.29664003369972275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197146939","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02165956,0.00019864929,0.97370255,0.00016326923,0.000043383094,0.00002898383,0.0003507512,0.0007187636,0.0031340371],"genre_scores_gemma":[0.31096113,0.0009049909,0.6800703,0.00009736623,0.00005130346,0.00012387036,0.0006367416,0.000755694,0.0063986736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997192,0.0000906207,0.000025235016,0.00008855229,0.00005402046,0.000022349142],"domain_scores_gemma":[0.9986431,0.000538943,0.0002673611,0.00030004824,0.00019586465,0.000054668224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000681906,0.0005071017,0.0003070889,0.0008976168,0.00035156898,0.0012696142,0.0004312887,0.00053986517,0.0049168663],"category_scores_gemma":[0.0034811937,0.0002879482,0.0006063354,0.0011876023,0.0008432596,0.001282725,0.00085511606,0.0006613198,0.0013223831],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017943943,0.000023703124,0.004777152,0.00020683027,0.000114530616,0.00062216417,0.00057368237,0.51280314,0.04839248,0.3461304,0.005444528,0.080732],"study_design_scores_gemma":[0.000022424902,0.00006585736,0.0030570638,0.00003250945,0.000028269764,0.00043692032,0.00009166893,0.85738057,0.012141752,0.106657624,0.020038225,0.000047128477],"about_ca_topic_score_codex":0.00631616,"about_ca_topic_score_gemma":0.0064006024,"teacher_disagreement_score":0.00631616,"about_ca_system_score_codex":0.00059029396,"about_ca_system_score_gemma":0.00075446605,"threshold_uncertainty_score":0.016448617},"labels":[],"label_agreement":null},{"id":"W3199529899","doi":"10.1002/jnr.24956","title":"Decline in executive function in patients with white matter hyperintensities from the static and dynamic perspectives of amplitude of low‐frequency fluctuations","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Hyperintensity; Psychology; Cardiology; Neuropsychology; Internal medicine; Montreal Cognitive Assessment; Audiology; Thalamus; Executive dysfunction; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Cognitive impairment; Radiology","score_opus":0.06153936429534189,"score_gpt":0.3895119271631789,"score_spread":0.327972562867837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199529899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996865,0.00008986547,0.00003186696,0.000010627989,0.0000021415315,0.000003976642,0.00003287661,0.0000020308144,0.00014015887],"genre_scores_gemma":[0.99970156,0.000047776186,0.000046749097,0.00001195339,0.00000808086,0.0000032861353,0.000084011255,7.576745e-7,0.000095765434],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989176,0.000016751572,0.000020977343,0.00003075716,0.000019546993,0.000020148447],"domain_scores_gemma":[0.9996803,0.000042258976,0.00016009157,0.000020536912,0.000028709079,0.00006822911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022025096,0.0006429884,0.00045176124,0.00095015357,0.00047678308,0.0004008317,0.00017097627,0.00028208786,0.0013560312],"category_scores_gemma":[0.00090582494,0.00021406302,0.000247132,0.0004832075,0.00027823434,0.0003655691,0.0003133173,0.00032052767,0.00018121634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077964226,0.00015277769,0.9897249,0.000021169177,0.000099597295,0.0010948417,0.0002565848,0.000077932076,0.002402153,0.000033590197,0.0000915508,0.0052652233],"study_design_scores_gemma":[0.000020917245,0.00025558381,0.9977482,0.0000045038355,0.000030199326,0.0013781836,0.00016390764,0.00012030811,0.00014922452,0.00005947533,0.00006514556,0.000004321848],"about_ca_topic_score_codex":0.0020714812,"about_ca_topic_score_gemma":0.00270323,"teacher_disagreement_score":0.0020714812,"about_ca_system_score_codex":0.00018119371,"about_ca_system_score_gemma":0.00013244158,"threshold_uncertainty_score":0.0045363903},"labels":[],"label_agreement":null},{"id":"W3199608123","doi":"10.1007/s00406-021-01333-0","title":"Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness","year":2021,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Douglas Mental Health University Institute; Douglas College","funders":"National Health and Medical Research Council; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); White matter; Neuroscience; Psychology; Schizophrenia spectrum; Cognitive psychology; Psychiatry; Audiology; Medicine; Psychosis; Magnetic resonance imaging","score_opus":0.026608320910158332,"score_gpt":0.34983101417011303,"score_spread":0.3232226932599547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199608123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995326,0.00010686939,0.00010058953,0.000029586216,0.0000018779608,0.0000025246227,0.000060275404,0.0000034761667,0.00016214978],"genre_scores_gemma":[0.9995807,0.000061730134,0.0001050189,0.000012812565,0.0000028757881,0.0000023514785,0.00007592024,0.0000027101873,0.0001559728],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999124,0.000013092249,0.0000140596285,0.00001921562,0.000021836935,0.000019461848],"domain_scores_gemma":[0.99948287,0.000045648114,0.0003354417,0.000027115393,0.000035804063,0.00007304489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019379659,0.00037263398,0.00018893198,0.0010126266,0.00040003064,0.00037606258,0.000236499,0.0003540515,0.0020077655],"category_scores_gemma":[0.00059885083,0.0002596873,0.0001691333,0.00047812608,0.0004729394,0.00022978194,0.00040235365,0.0003396816,0.00013510312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0063666757,0.0004249086,0.60517234,0.00021805354,0.0006426963,0.0049168305,0.0012454822,0.001468089,0.35613424,0.0007107164,0.00039737,0.022302613],"study_design_scores_gemma":[0.000009968109,0.00008704407,0.9960485,0.000006014862,0.0000413409,0.00093226176,0.00017195045,0.00030786722,0.0020721857,0.00025707012,0.000060824415,0.0000049596947],"about_ca_topic_score_codex":0.0077457856,"about_ca_topic_score_gemma":0.00827955,"teacher_disagreement_score":0.0077457856,"about_ca_system_score_codex":0.00033851585,"about_ca_system_score_gemma":0.00030840628,"threshold_uncertainty_score":0.015401363},"labels":[],"label_agreement":null},{"id":"W3199893527","doi":"10.1101/2021.09.17.460781","title":"Mapping pontocerebellar connectivity with diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Cerebellum; Pons; Neuroscience; Diffusion MRI; Tractography; Context (archaeology); Anatomy; Biology; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.029267526832652456,"score_gpt":0.2656240162776656,"score_spread":0.2363564894450131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199893527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72007114,0.00058298366,0.2722819,0.00023272878,0.000026223994,0.00016225719,0.001469227,0.00084718765,0.004326242],"genre_scores_gemma":[0.8524759,0.0005290843,0.14453118,0.000039300496,0.000019354005,0.00010616802,0.0008122206,0.0001519227,0.001334929],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998661,0.000027871683,0.0000065028116,0.000058433285,0.00002460024,0.000016391372],"domain_scores_gemma":[0.99973935,0.0000822887,0.00008334259,0.000033143235,0.00003684252,0.000025079913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041790196,0.00036462376,0.00019806821,0.0023819664,0.00025484286,0.0006082241,0.00024395932,0.0003229478,0.0022698087],"category_scores_gemma":[0.0011320281,0.00020131719,0.00016462064,0.0008709622,0.0005088113,0.0004244545,0.0002789063,0.00038067374,0.00035091417],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004288861,0.00008935856,0.04717491,0.000361868,0.00017344975,0.0009681292,0.00053211546,0.010177986,0.81855416,0.009532667,0.0015936017,0.110412784],"study_design_scores_gemma":[0.00008897164,0.000413904,0.52533495,0.00015839929,0.00016521182,0.005618831,0.0005488443,0.1379628,0.2878183,0.025700973,0.016062155,0.00012664912],"about_ca_topic_score_codex":0.0059773996,"about_ca_topic_score_gemma":0.0076177274,"teacher_disagreement_score":0.0059773996,"about_ca_system_score_codex":0.0004252904,"about_ca_system_score_gemma":0.0004883003,"threshold_uncertainty_score":0.011885226},"labels":[],"label_agreement":null},{"id":"W3200681050","doi":"10.1002/hbm.25661","title":"A method to remove the influence of fixative concentration on postmortem <scp> T <sub>2</sub> </scp> maps using a kinetic tensor model","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Wellcome; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Fixative; Diffusion MRI; White matter; Chemistry; Brain tissue; Anatomy; Biology; Magnetic resonance imaging; Biochemistry; Medicine","score_opus":0.09044121792273278,"score_gpt":0.36699808206781487,"score_spread":0.27655686414508207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200681050","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032647613,0.0000861643,0.9655985,0.00011408027,0.000040665287,0.000052279138,0.00009691806,0.001089263,0.00027447642],"genre_scores_gemma":[0.32848677,0.0003353122,0.66550434,0.00012992094,0.000040677733,0.00033265408,0.0004837213,0.0009613995,0.0037252167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997009,0.00007612215,0.000025805572,0.000084785745,0.000080369275,0.00003200499],"domain_scores_gemma":[0.99902356,0.00033591132,0.00018909072,0.00020660287,0.00019742368,0.000047401703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016507879,0.001409206,0.000559223,0.0006572423,0.00042541165,0.0009004823,0.0011287277,0.0010519816,0.0021384696],"category_scores_gemma":[0.004846129,0.0006210574,0.0012900868,0.00057647686,0.0004947117,0.00080301316,0.00060516346,0.0011222722,0.00078279845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005443971,0.0002649028,0.006887421,0.00039433752,0.0005700324,0.00038190355,0.00034672196,0.37647468,0.355721,0.012661759,0.0033190104,0.24243385],"study_design_scores_gemma":[0.000017208495,0.00014371444,0.003767526,0.000021202288,0.00009559222,0.00018517433,0.000023429257,0.9536106,0.036852717,0.0021068412,0.0031230547,0.00005307378],"about_ca_topic_score_codex":0.012605699,"about_ca_topic_score_gemma":0.011435199,"teacher_disagreement_score":0.012605699,"about_ca_system_score_codex":0.0010272587,"about_ca_system_score_gemma":0.002509566,"threshold_uncertainty_score":0.025064647},"labels":[],"label_agreement":null},{"id":"W3202356255","doi":"10.1016/j.nicl.2021.102843","title":"White matter alterations and cognitive outcomes in children born very low birth weight","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Low birth weight; Birth weight; Psychology; Cognition; Pediatrics; Developmental psychology; Medicine; Neuroscience; Biology; Magnetic resonance imaging; Pregnancy; Genetics","score_opus":0.051137502502351204,"score_gpt":0.3935662870963747,"score_spread":0.3424287845940235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202356255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99941456,0.00030022932,0.000071588045,0.000015981877,0.0000024060757,0.0000020599343,0.00010242854,0.000004095403,0.00008662897],"genre_scores_gemma":[0.9991252,0.00029747907,0.00023483168,0.000011720405,0.000004682052,0.000007777383,0.00022386735,0.0000034804077,0.00009098716],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998116,0.000023350864,0.000022862207,0.000048864564,0.000050900442,0.000042485215],"domain_scores_gemma":[0.9989317,0.00014023883,0.0006815906,0.00003743575,0.00008676071,0.00012219467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044458715,0.0003620692,0.00035620082,0.0009848975,0.0002960127,0.00053417456,0.00031520933,0.00039751784,0.0007421326],"category_scores_gemma":[0.0018536804,0.00019644246,0.00033687495,0.00061431236,0.0005379451,0.0003530323,0.00041509612,0.0004628129,0.00012088064],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018166049,0.000031288015,0.9945247,0.000034980378,0.00005761457,0.00035055858,0.00022273754,0.00005804856,0.0018897371,0.000035977406,0.000052259926,0.0025603264],"study_design_scores_gemma":[0.0000010984991,0.0000428373,0.9993055,0.0000062006247,0.000011002946,0.00033701072,0.000085350075,0.000026358573,0.0001347809,0.000014761952,0.000033564593,0.000001608739],"about_ca_topic_score_codex":0.007373531,"about_ca_topic_score_gemma":0.0053160363,"teacher_disagreement_score":0.007373531,"about_ca_system_score_codex":0.00039523462,"about_ca_system_score_gemma":0.00031626408,"threshold_uncertainty_score":0.0146612525},"labels":[],"label_agreement":null},{"id":"W3202656322","doi":"10.3174/ajnr.a7295","title":"Filtered Diffusion-Weighted MRI of the Human Cervical Spinal Cord: Feasibility and Application to Traumatic Spinal Cord Injury","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"Rehabilitation Research and Development Service; Bryon Riesch Paralysis Foundation; Medical College of Wisconsin; Craig H. Neilsen Foundation; U.S. Department of Veterans Affairs","keywords":"Medicine; Spinal cord; Spinal cord injury; Diffusion MRI; Magnetic resonance imaging; Anesthesia; Radiology","score_opus":0.062088821371703184,"score_gpt":0.3950407478468111,"score_spread":0.3329519264751079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202656322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98506594,0.0020444817,0.011355844,0.0001346578,0.000014098947,0.00014113983,0.00014641647,0.00007204984,0.0010252753],"genre_scores_gemma":[0.98414695,0.0010124218,0.014209953,0.00006937564,0.000013423952,0.000063249936,0.0001333678,0.000011533069,0.00033976953],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994755,0.000014223934,0.000004142469,0.000013935494,0.000010215339,0.000009836576],"domain_scores_gemma":[0.99984896,0.000041851566,0.000019964582,0.000018592254,0.000049983835,0.000020558446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004667911,0.00021853608,0.0001120396,0.00039941256,0.0001839576,0.0002902386,0.0001846007,0.00047825303,0.0014285729],"category_scores_gemma":[0.00086480763,0.00015775154,0.000107621585,0.00017711156,0.00028402117,0.00030063698,0.00016350368,0.00016131921,0.00022411424],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029768967,0.00024362755,0.028455094,0.00031472594,0.00006967079,0.00089563034,0.00027497078,0.00142249,0.89672357,0.00032394606,0.00031574993,0.06798353],"study_design_scores_gemma":[0.00044773376,0.010840336,0.5730214,0.00017001733,0.00036675757,0.016406791,0.00071505806,0.023258373,0.3640676,0.0015986639,0.008980675,0.0001266655],"about_ca_topic_score_codex":0.0036372722,"about_ca_topic_score_gemma":0.0046023116,"teacher_disagreement_score":0.0036372722,"about_ca_system_score_codex":0.00026400466,"about_ca_system_score_gemma":0.0004171712,"threshold_uncertainty_score":0.007232249},"labels":[],"label_agreement":null},{"id":"W3203270152","doi":"10.1016/j.nicl.2021.102837","title":"Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"UCLH Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research","keywords":"Epilepsy; Lesion; Parametric statistics; Diffusion MRI; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Physical medicine and rehabilitation; Radiology; Psychiatry; Mathematics; Statistics","score_opus":0.14676615194554532,"score_gpt":0.45722586180286245,"score_spread":0.31045970985731713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203270152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9745973,0.00030747784,0.023910217,0.00003420361,0.0000072145635,0.00006230501,0.0002359732,0.00014942161,0.00069605134],"genre_scores_gemma":[0.99313426,0.00005167704,0.0064130058,0.0000048290435,0.000005866449,0.000048960304,0.00019929328,0.000017664699,0.00012441198],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910104,0.0004226217,0.000060171114,0.00018926994,0.00017578567,0.00005117177],"domain_scores_gemma":[0.9978491,0.0012488938,0.00031841276,0.00026507233,0.00026074483,0.000057732286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020648863,0.00042201095,0.00046507493,0.0010952262,0.00020396165,0.00041795615,0.00028222156,0.00019194782,0.0010603626],"category_scores_gemma":[0.0068412535,0.00015141122,0.00039237118,0.00047705305,0.00026182536,0.00039521858,0.0005987535,0.000266179,0.00025513483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0052261767,0.00036653614,0.3609787,0.00042114287,0.0022778432,0.0010157586,0.000982718,0.011180481,0.21296173,0.0005382255,0.001073985,0.4029767],"study_design_scores_gemma":[0.00010119662,0.0016751251,0.8468305,0.00004285572,0.0007636934,0.004732811,0.00051632803,0.09779022,0.0437887,0.0016828798,0.0019630447,0.00011269377],"about_ca_topic_score_codex":0.00084010174,"about_ca_topic_score_gemma":0.0021150734,"teacher_disagreement_score":0.0020648863,"about_ca_system_score_codex":0.00014368423,"about_ca_system_score_gemma":0.00025193344,"threshold_uncertainty_score":0.010920286},"labels":[],"label_agreement":null},{"id":"W3203635121","doi":"10.1002/hipo.23388","title":"High resolution diffusion tensor imaging of the hippocampus across the healthy lifespan","year":2021,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Diffusion MRI; Hippocampus; Hippocampal formation; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology","score_opus":0.03252926129270064,"score_gpt":0.33305139974362924,"score_spread":0.3005221384509286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203635121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.972712,0.011021139,0.008621715,0.0005487429,0.0000614183,0.00009311647,0.002414469,0.00014281135,0.0043844855],"genre_scores_gemma":[0.9811358,0.0050217663,0.011046727,0.00021213375,0.000045079818,0.00004392172,0.00086844456,0.000024736783,0.001601527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998691,0.000024044088,0.000019409184,0.00003816339,0.00003325151,0.000015925094],"domain_scores_gemma":[0.9998047,0.000018030916,0.0000668557,0.000026648473,0.000063267646,0.000020492236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005377567,0.00026819602,0.00018637658,0.001260011,0.00025994418,0.00035372918,0.00014775462,0.00027223222,0.0008784931],"category_scores_gemma":[0.0009318463,0.0001622185,0.00020945887,0.0006444421,0.00024943886,0.00048246948,0.0002774365,0.00017593437,0.0002751975],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097288145,0.00015965497,0.36716273,0.0010983066,0.0013190877,0.0026899085,0.00222916,0.0017404379,0.27299842,0.0020377394,0.009255922,0.33833584],"study_design_scores_gemma":[0.00002562904,0.00029344452,0.9818632,0.000121861056,0.00018127797,0.0031091836,0.0004806229,0.00076015136,0.0057463427,0.0019029982,0.0054868134,0.00002847227],"about_ca_topic_score_codex":0.007821885,"about_ca_topic_score_gemma":0.01759973,"teacher_disagreement_score":0.007821885,"about_ca_system_score_codex":0.00020109945,"about_ca_system_score_gemma":0.00033069897,"threshold_uncertainty_score":0.0155527},"labels":[],"label_agreement":null},{"id":"W3203853664","doi":"10.1101/2021.09.30.462636","title":"Normalizing automatic spinal cord cross-sectional area measures","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Institut de Valorisation des Données; Canada First Research Excellence Fund","keywords":"Spinal cord; Medicine; Normalization (sociology); Correlation; Cohort; Cross-sectional study; Atrophy; Pathology; Mathematics","score_opus":0.08411689390072308,"score_gpt":0.3385049444262137,"score_spread":0.2543880505254906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203853664","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4636888,0.0017678058,0.50989854,0.00035297964,0.00039648626,0.00049232016,0.0076076156,0.011579037,0.0042164447],"genre_scores_gemma":[0.67894244,0.00052601367,0.30833605,0.00018740693,0.00012082028,0.0008702014,0.0063142413,0.0012815992,0.0034211555],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838805,0.00034122498,0.00010512223,0.0006338923,0.00044785108,0.00008385776],"domain_scores_gemma":[0.99649495,0.0011195416,0.00042954067,0.0005972671,0.0012937741,0.000064948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028339212,0.0007282957,0.00067824515,0.001529586,0.0003672482,0.0008974667,0.00091659266,0.0005583256,0.0037810225],"category_scores_gemma":[0.0106337825,0.00037005005,0.0006315651,0.0013379666,0.000428126,0.0005580904,0.0006733923,0.00053875486,0.0017667103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012635078,0.00033577433,0.14644521,0.0013767174,0.0009667802,0.00038240541,0.0010768361,0.028748108,0.1569466,0.0037556628,0.019536873,0.6391655],"study_design_scores_gemma":[0.00012977424,0.00084691413,0.48319614,0.00024550073,0.00039861127,0.0014684586,0.00054492534,0.33602646,0.14065607,0.007919701,0.02834665,0.00022075509],"about_ca_topic_score_codex":0.0038069598,"about_ca_topic_score_gemma":0.007426587,"teacher_disagreement_score":0.0038069598,"about_ca_system_score_codex":0.0004603048,"about_ca_system_score_gemma":0.0007893641,"threshold_uncertainty_score":0.0149873495},"labels":[],"label_agreement":null},{"id":"W3203992831","doi":"","title":"Frequency tuned bipolar oscillating gradients for mapping diffusion kurtosis dispersion in the human brain","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Kurtosis; Dispersion (optics); Thermal diffusivity; Diffusion; Oscillation (cell signaling); Waveform; Weighting; Physics; Nuclear magnetic resonance; Biological system; Acoustics; Mathematics; Chemistry; Statistics; Optics; Voltage","score_opus":0.16218353994770468,"score_gpt":0.2735423262054324,"score_spread":0.11135878625772772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203992831","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4352014,0.003362783,0.55718213,0.00040470788,0.000097744574,0.00037068798,0.00022711669,0.00048729504,0.002666144],"genre_scores_gemma":[0.71389604,0.0013234259,0.28331885,0.00016809873,0.00004597532,0.00021557728,0.00012500881,0.000098449535,0.00080862106],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99991465,0.000027721535,0.000005201604,0.0000180866,0.000029157645,0.0000051013362],"domain_scores_gemma":[0.9998456,0.00006122468,0.000039302846,0.000012335503,0.000028038536,0.000013420143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035174648,0.0003501185,0.00011996064,0.00026601664,0.00012519382,0.0003385194,0.00022171806,0.00037411452,0.0007307049],"category_scores_gemma":[0.0013629269,0.00018064375,0.00009101956,0.00017535055,0.00024771705,0.0002953277,0.00019054608,0.00020565257,0.00017024016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063531665,0.00009399768,0.002059069,0.0002768445,0.00003297685,0.000226187,0.000072751485,0.009257631,0.8963116,0.0015207134,0.000625612,0.08888722],"study_design_scores_gemma":[0.00034688812,0.0046198326,0.0388288,0.00023246484,0.00028809972,0.0054103592,0.000120215576,0.17799927,0.7554073,0.007396177,0.009194479,0.00015622767],"about_ca_topic_score_codex":0.000475757,"about_ca_topic_score_gemma":0.0012028293,"teacher_disagreement_score":0.0007307049,"about_ca_system_score_codex":0.00016262302,"about_ca_system_score_gemma":0.00027752088,"threshold_uncertainty_score":0.0024443865},"labels":[],"label_agreement":null},{"id":"W3204608968","doi":"10.1007/978-3-030-87615-9_13","title":"Accelerating Geometry-Based Spherical Harmonics Glyphs Rendering for dMRI Using Modern OpenGL","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"OpenGL; Computer science; Spherical harmonics; Rendering (computer graphics); Slicing; Computer graphics (images); Ellipsoid; Voxel; Shader; Visualization; Spline (mechanical); Computer vision; Artificial intelligence; Computational science; Physics","score_opus":0.15591232312858366,"score_gpt":0.3677652341556015,"score_spread":0.2118529110270178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204608968","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042200945,0.00024482503,0.9637459,0.00021042193,0.00017365796,0.000080902064,0.0006378383,0.019025655,0.01166068],"genre_scores_gemma":[0.07461763,0.000659796,0.8998623,0.00026264,0.000111775924,0.00016591961,0.0016699488,0.0092198225,0.013430206],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975187,0.000025134483,0.0000133444955,0.000027081673,0.00014978109,0.00003276614],"domain_scores_gemma":[0.9996325,0.00014361931,0.0000136463395,0.00007817433,0.00009617789,0.000035893056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003375962,0.0011970111,0.0004885717,0.0007447394,0.0002933566,0.0019261946,0.0011638602,0.00070037466,0.036941048],"category_scores_gemma":[0.0014308215,0.0004947367,0.000766662,0.0005771041,0.00026485452,0.0008316071,0.0016704641,0.0013955124,0.008181372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037530402,0.000086716056,0.00072045554,0.0006344001,0.000100033496,0.00052026036,0.0006686662,0.034416918,0.11796738,0.04527791,0.09175478,0.7074773],"study_design_scores_gemma":[0.00015239579,0.0001140333,0.0010490279,0.00016596876,0.00005987127,0.0010773042,0.00021127715,0.5975691,0.13637501,0.0393692,0.2237409,0.00011595462],"about_ca_topic_score_codex":0.002123641,"about_ca_topic_score_gemma":0.0032913743,"teacher_disagreement_score":0.036941048,"about_ca_system_score_codex":0.00049080333,"about_ca_system_score_gemma":0.0006372168,"threshold_uncertainty_score":0.12358016},"labels":[],"label_agreement":null},{"id":"W3204968122","doi":"10.1016/j.radonc.2021.09.020","title":"Accuracy and precision of apparent diffusion coefficient measurements on a 1.5 T MR-Linac in central nervous system tumour patients","year":2021,"lang":"en","type":"article","venue":"Radiotherapy and Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Terry Fox Research Institute","keywords":"Nuclear medicine; Repeatability; Effective diffusion coefficient; Medicine; White matter; Linear particle accelerator; Magnetic resonance imaging; Diffusion MRI; Radiology; Physics; Beam (structure); Chemistry; Optics","score_opus":0.055838435799754865,"score_gpt":0.35810832614363014,"score_spread":0.3022698903438753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204968122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878604,0.0050163087,0.0049290783,0.0001634591,0.00004701005,0.000012002084,0.00034427087,0.00022663662,0.0014009028],"genre_scores_gemma":[0.9978818,0.00030926242,0.0014074313,0.000038631217,0.000013199382,0.0000030450028,0.00014954912,0.000033187196,0.00016383112],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984509,0.00052302354,0.00018913757,0.0004755637,0.00027359778,0.00008778752],"domain_scores_gemma":[0.9924589,0.004347639,0.0010529066,0.00070451444,0.0012894922,0.00014654528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026712841,0.0003075668,0.00050041266,0.0009972887,0.00039463842,0.0015711279,0.0005918756,0.00093627744,0.0003804006],"category_scores_gemma":[0.01585593,0.00027656552,0.00035411245,0.0005919295,0.00046488747,0.0007582389,0.00046229214,0.0005713821,0.0002940945],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005401518,0.00006653013,0.8431423,0.00033749396,0.0007940024,0.00047364706,0.0012167941,0.00929235,0.040678207,0.00037731408,0.0010206593,0.097199194],"study_design_scores_gemma":[0.00009524242,0.001085145,0.9109791,0.00012176059,0.0011899077,0.0034197078,0.00043920323,0.026525289,0.053007662,0.00035645624,0.002683522,0.00009696802],"about_ca_topic_score_codex":0.008115991,"about_ca_topic_score_gemma":0.007387039,"teacher_disagreement_score":0.008115991,"about_ca_system_score_codex":0.00074460707,"about_ca_system_score_gemma":0.00043978108,"threshold_uncertainty_score":0.01613748},"labels":[],"label_agreement":null},{"id":"W3205458840","doi":"10.1101/2021.10.07.463554","title":"The Role of the Temporal Pole in Temporal Lobe Epilepsy: A Diffusion Kurtosis Imaging Study","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Temporal lobe; Uncinate fasciculus; White matter; Kurtosis; Diffusion MRI; Epilepsy; Magnetic resonance imaging; Lobe; Medicine; Nuclear medicine; Anatomy; Fractional anisotropy; Radiology","score_opus":0.019207167610335946,"score_gpt":0.2722601760187516,"score_spread":0.2530530084084156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205458840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927443,0.00018944834,0.00017457844,0.000017563509,0.0000016519912,0.0000035595763,0.000025825944,0.0000022327195,0.00031081217],"genre_scores_gemma":[0.9996698,0.00009085938,0.00011830807,0.0000052033265,0.000004104692,0.0000013269702,0.000027820619,0.0000011199814,0.000081555256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999336,0.000012214242,0.000010798128,0.000016761222,0.000015172685,0.000011412113],"domain_scores_gemma":[0.99966156,0.00006818009,0.00015114532,0.000026137179,0.000056437253,0.000036503498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030168644,0.00029576136,0.00018471603,0.0005730041,0.00020067001,0.00036834867,0.0001042691,0.0001902576,0.0013140072],"category_scores_gemma":[0.00090113806,0.00011962824,0.000119840595,0.00023572662,0.00040980708,0.00041031424,0.00024093835,0.00011049584,0.00022322005],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026032894,0.00012080613,0.7990551,0.00018144265,0.00015780948,0.0065990854,0.0013302591,0.00036695198,0.16289875,0.00023817549,0.0001480742,0.026300205],"study_design_scores_gemma":[0.000028691638,0.00059908506,0.98126584,0.000013487804,0.000067098816,0.011137418,0.0005859382,0.00078685815,0.004887935,0.00014619935,0.00047079596,0.000010613821],"about_ca_topic_score_codex":0.0014559694,"about_ca_topic_score_gemma":0.001487324,"teacher_disagreement_score":0.0014559694,"about_ca_system_score_codex":0.00012869688,"about_ca_system_score_gemma":0.00014741448,"threshold_uncertainty_score":0.0043958426},"labels":[],"label_agreement":null},{"id":"W3205614966","doi":"10.1016/j.media.2021.102257","title":"Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia","year":2022,"lang":"en","type":"article","venue":"Amsterdam UMC (VU Amsterdam) - Institutional Repository","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; Nvidia; University of Southern California; UK Research and Innovation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; University College London Hospitals NHS Foundation Trust; European Commission; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Benchmark (surveying); Neuroimaging; Machine learning; Set (abstract data type); Deep learning; Categorization; Psychology; Neuroscience","score_opus":0.03671884635202357,"score_gpt":0.32375161572273836,"score_spread":0.2870327693707148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205614966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20147912,0.0015026414,0.7875855,0.0015927462,0.00019926966,0.00014594682,0.00048572582,0.002017187,0.004991852],"genre_scores_gemma":[0.8797214,0.00042972004,0.11581834,0.0004981826,0.000053423977,0.00010040793,0.00038730408,0.00017072457,0.0028206345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997383,0.000116938085,0.000013150969,0.000050099607,0.000053736218,0.000027857413],"domain_scores_gemma":[0.998898,0.00074696715,0.000085905645,0.00008597514,0.00011135054,0.000071777606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013974281,0.0008257527,0.00050616916,0.00046550698,0.00023835825,0.00056666933,0.0009872735,0.0012053933,0.0014104324],"category_scores_gemma":[0.0041068797,0.0003695579,0.0006200741,0.00026852175,0.0007327687,0.0004739745,0.0010760122,0.0012135995,0.00022447779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006740142,0.000021064812,0.00064247876,0.00003091529,0.00002718165,0.00009166164,0.000028629625,0.9841929,0.0011813478,0.0012026223,0.00048787124,0.012025856],"study_design_scores_gemma":[0.0000037027892,0.000013716054,0.00011066897,0.0000048947722,0.0000029632145,0.000024791887,0.000004088764,0.9978459,0.0006779829,0.0011438106,0.00016467282,0.0000028743423],"about_ca_topic_score_codex":0.006409573,"about_ca_topic_score_gemma":0.006333371,"teacher_disagreement_score":0.006409573,"about_ca_system_score_codex":0.000976269,"about_ca_system_score_gemma":0.00067231245,"threshold_uncertainty_score":0.012744546},"labels":[],"label_agreement":null},{"id":"W3206070921","doi":"10.1007/s00429-021-02408-3","title":"Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Fiducial marker; Computer science; Artificial intelligence; Image registration; Preprocessor; Neuroimaging; Workflow; Neurology; Parkinson's disease; Magnetic resonance imaging; Medical physics; Pattern recognition (psychology); Computer vision; Medicine; Radiology; Pathology; Psychology; Neuroscience; Image (mathematics); Disease","score_opus":0.025050995292173212,"score_gpt":0.34424131761762145,"score_spread":0.31919032232544825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206070921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34384033,0.0019624515,0.625027,0.0013844146,0.00037418338,0.001942913,0.013415692,0.0075361435,0.004516799],"genre_scores_gemma":[0.60879415,0.00042890073,0.36985984,0.00033569554,0.000096105025,0.0014660201,0.017165571,0.0006386145,0.0012151254],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99690574,0.0010445772,0.00048284937,0.00085271156,0.0005966723,0.00011736508],"domain_scores_gemma":[0.9960672,0.0011241505,0.00041414466,0.0014666148,0.00081732776,0.00011055854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004735987,0.0008834208,0.0007371844,0.0022432576,0.00081925734,0.0014645417,0.001240624,0.0013656814,0.0016578906],"category_scores_gemma":[0.015911588,0.00038693793,0.0010256447,0.0014328744,0.0010622779,0.0006202698,0.0018528504,0.0012721749,0.0010839521],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021075986,0.0007375331,0.06314285,0.0017438398,0.0012697802,0.0023471098,0.002704203,0.0781029,0.06487635,0.010276048,0.03070247,0.74198943],"study_design_scores_gemma":[0.00085626193,0.0027947936,0.25622654,0.0006161774,0.0008398301,0.021138702,0.0022355139,0.43105173,0.10823077,0.0502994,0.12515089,0.0005594709],"about_ca_topic_score_codex":0.0067357444,"about_ca_topic_score_gemma":0.012466038,"teacher_disagreement_score":0.0067357444,"about_ca_system_score_codex":0.0007669802,"about_ca_system_score_gemma":0.0017637643,"threshold_uncertainty_score":0.025046587},"labels":[],"label_agreement":null},{"id":"W3206188152","doi":"","title":"脳卒中をめぐる最近の話題 超急性期診断の最前線-Diffusion,Perfusion MRIを中心に-","year":2004,"lang":"zh","type":"article","venue":"Pharma Medica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion; Medicine; Computer science; Physics","score_opus":0.06127557304407322,"score_gpt":0.382143045496436,"score_spread":0.3208674724523628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206188152","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44166058,0.05813643,0.26165968,0.010829686,0.0022255227,0.0005954495,0.0017713836,0.0012809722,0.22184034],"genre_scores_gemma":[0.8499423,0.018382298,0.09007631,0.0017231178,0.00087244157,0.00022667351,0.0006520441,0.00026069742,0.037864022],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99977344,0.000041500807,0.000023790442,0.00006619577,0.00006270458,0.000032295407],"domain_scores_gemma":[0.9993463,0.00018671846,0.00010035474,0.000067733636,0.00022700946,0.00007189335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012393532,0.0004440945,0.00033960727,0.0006684036,0.0007742414,0.0010795355,0.0003978871,0.0009383087,0.007699858],"category_scores_gemma":[0.0016768978,0.00035911266,0.00030546833,0.00040905125,0.0013057777,0.0019250893,0.0003399683,0.0012312493,0.0023690308],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012373917,0.00020005488,0.009444203,0.0018192662,0.0002374716,0.00288728,0.0010102284,0.0009213769,0.6596614,0.033603277,0.00885256,0.28012547],"study_design_scores_gemma":[0.0003246457,0.0013429036,0.06550146,0.00055387965,0.00076767564,0.025248963,0.0019682467,0.007013273,0.73580676,0.05443054,0.10678165,0.0002599641],"about_ca_topic_score_codex":0.00225601,"about_ca_topic_score_gemma":0.0032642533,"teacher_disagreement_score":0.007699858,"about_ca_system_score_codex":0.00053783745,"about_ca_system_score_gemma":0.00078274024,"threshold_uncertainty_score":0.025758564},"labels":[],"label_agreement":null},{"id":"W3206632789","doi":"10.1016/j.mri.2021.10.014","title":"Axon diameter inferences in the human corpus callosum using oscillating gradient spin echo sequences","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Corpus callosum; Axon; Echo (communications protocol); Gradient echo; Spin echo; Physics; Anatomy; Nuclear magnetic resonance; Neuroscience; Biology; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09164087711832948,"score_gpt":0.37349322110462685,"score_spread":0.2818523439862974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206632789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651765,0.00081402244,0.032041095,0.00009540199,0.000014188695,0.000018711527,0.00013967647,0.00010097545,0.0015993748],"genre_scores_gemma":[0.97556394,0.00049826095,0.023159074,0.00002486863,0.000015079848,0.000013553088,0.00008719831,0.00004704193,0.0005910289],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999331,0.0000174248,0.0000051542647,0.000022008722,0.000017740196,0.000004556355],"domain_scores_gemma":[0.9991198,0.0005558099,0.000080436395,0.00006554292,0.00013852274,0.000039875184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042319435,0.00018702136,0.00012087211,0.0010942791,0.0003072535,0.0006216967,0.00023636152,0.0004775704,0.0008144439],"category_scores_gemma":[0.0028899575,0.0001779926,0.00008118652,0.00041019754,0.00040710057,0.0006498657,0.00023387455,0.0002980988,0.0001073771],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014100159,0.000043669734,0.031591382,0.00044674982,0.00009519245,0.0014204013,0.0011800453,0.014783315,0.8415107,0.0053168475,0.00063662307,0.10156503],"study_design_scores_gemma":[0.00013313032,0.00051267067,0.40927348,0.00016448117,0.00030376264,0.0077355537,0.0014001481,0.15990347,0.39638677,0.017842961,0.006135946,0.00020769153],"about_ca_topic_score_codex":0.003689402,"about_ca_topic_score_gemma":0.006062531,"teacher_disagreement_score":0.003689402,"about_ca_system_score_codex":0.00017516423,"about_ca_system_score_gemma":0.00034145243,"threshold_uncertainty_score":0.0073358417},"labels":[],"label_agreement":null},{"id":"W3207240923","doi":"10.1016/j.pscychresns.2021.111396","title":"Association between frontal cortico-limbic white-matter microstructure and risk for pediatric depression","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; CBCL; White matter; Psychology; Uncinate fasciculus; Cingulum (brain); Diffusion MRI; Child Behavior Checklist; Anxiety; Major depressive disorder; Clinical psychology; Psychiatry; Magnetic resonance imaging; Medicine; Radiology; Mood","score_opus":0.05857890424942056,"score_gpt":0.3986610323987461,"score_spread":0.34008212814932554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207240923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998487,0.00032402042,0.0001430089,0.00010352167,0.000006080124,0.0000034448694,0.0002852672,0.000007068002,0.0006405789],"genre_scores_gemma":[0.99919015,0.00019102082,0.00022483875,0.000017158345,0.000007838481,0.0000033443225,0.00015079866,0.0000027369829,0.00021201887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983346,0.000027545491,0.000014051845,0.000057525427,0.00003180597,0.00003558897],"domain_scores_gemma":[0.9990386,0.00015149284,0.0005700713,0.000044022738,0.00009066329,0.000105250736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002281938,0.00026566838,0.00017769531,0.00048429964,0.00026834797,0.00046944703,0.0002631638,0.00033136836,0.0024129841],"category_scores_gemma":[0.0012987222,0.00019730933,0.00030183833,0.0005261713,0.00021316766,0.00026248247,0.00020499965,0.0005765024,0.00015181674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004151349,0.000018920971,0.99736834,0.0000068408513,0.000057574794,0.0001839216,0.00003901465,0.00003297885,0.00067916204,0.000057272122,0.00007559105,0.0014388444],"study_design_scores_gemma":[8.250112e-7,0.0000134243655,0.99935645,0.0000033029635,0.000017632134,0.00032619064,0.000040414856,0.00007224936,0.00009108645,0.000026041937,0.000051523857,8.3659785e-7],"about_ca_topic_score_codex":0.006832874,"about_ca_topic_score_gemma":0.011692558,"teacher_disagreement_score":0.006832874,"about_ca_system_score_codex":0.00032598732,"about_ca_system_score_gemma":0.00033129062,"threshold_uncertainty_score":0.0135861635},"labels":[],"label_agreement":null},{"id":"W3207755099","doi":"10.1101/2021.10.13.464139","title":"An atlas of white matter anatomy, its variability, and reproducibility based on Constrained Spherical Deconvolution of diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek; National Institutes of Health","keywords":"Diffusion MRI; Tractography; White matter; Fornix; Anatomy; Fractional anisotropy; Human Connectome Project; Computer science; Reproducibility; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Cartography; Psychology; Biology; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Functional connectivity","score_opus":0.02369214734514877,"score_gpt":0.2909940875997623,"score_spread":0.2673019402546135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207755099","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42961645,0.0005559025,0.5569267,0.0001342857,0.00004954249,0.0001430563,0.005010385,0.004622569,0.0029411449],"genre_scores_gemma":[0.7525311,0.00034486235,0.23946768,0.000042351876,0.000021869844,0.0002319679,0.0049606455,0.001056597,0.0013429165],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921,0.00018508208,0.000074192605,0.00030082557,0.00019331266,0.000036483565],"domain_scores_gemma":[0.998083,0.00049422705,0.00027773427,0.0006871905,0.00039846115,0.00005941755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021472455,0.00044350902,0.00034751275,0.0020265393,0.0004469022,0.0013275191,0.0005212608,0.0004597216,0.0014528587],"category_scores_gemma":[0.003911073,0.0003696779,0.0004360265,0.0015047194,0.0006258368,0.0005434715,0.0010385286,0.00044078438,0.0006228752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009838174,0.00019623735,0.062305637,0.00068431674,0.0007256495,0.00097207224,0.0021441504,0.15640438,0.31521475,0.01839922,0.011956551,0.4300133],"study_design_scores_gemma":[0.00008022476,0.00056941586,0.28267163,0.0001842503,0.00041052324,0.0051698447,0.0004089988,0.48258993,0.16973905,0.029377908,0.028453328,0.00034495982],"about_ca_topic_score_codex":0.003569276,"about_ca_topic_score_gemma":0.0046952334,"teacher_disagreement_score":0.003569276,"about_ca_system_score_codex":0.00055703154,"about_ca_system_score_gemma":0.000822297,"threshold_uncertainty_score":0.011355817},"labels":[],"label_agreement":null},{"id":"W3208508987","doi":"10.5281/zenodo.4157687","title":"avdvorak/multivariate-template: version 1.0.0","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Multivariate statistics; Artificial intelligence; Machine learning","score_opus":0.12869363969680372,"score_gpt":0.33034807317076487,"score_spread":0.20165443347396114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208508987","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020085683,0.0003339481,0.25671774,0.00021003591,0.00026925327,0.00037261064,0.029015379,0.7036015,0.0074709677],"genre_scores_gemma":[0.024328964,0.0006011881,0.27662736,0.0006692349,0.00017360545,0.0017436073,0.06549676,0.6107892,0.019570109],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892646,0.0001450261,0.00017228338,0.00025413436,0.00032094237,0.00018109553],"domain_scores_gemma":[0.99677175,0.0013736713,0.0002544748,0.0005829724,0.0008164057,0.00020064911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028593931,0.002969526,0.0014869021,0.0017781969,0.00073568575,0.002767255,0.004350614,0.0019400645,0.21499065],"category_scores_gemma":[0.0123498775,0.0026329698,0.0023095238,0.0015795759,0.0008666174,0.0028517789,0.0031942101,0.0036639415,0.1304437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015050552,0.00019196288,0.003004694,0.002366292,0.00032707155,0.000768832,0.00064543576,0.00677913,0.0115051875,0.013068766,0.8194473,0.1403903],"study_design_scores_gemma":[0.0011278169,0.00019454164,0.0045565534,0.0007852622,0.00017790262,0.0018212132,0.00017734228,0.05735163,0.055854544,0.03210084,0.8453653,0.0004870048],"about_ca_topic_score_codex":0.0031563235,"about_ca_topic_score_gemma":0.0026367425,"teacher_disagreement_score":0.21499065,"about_ca_system_score_codex":0.000981804,"about_ca_system_score_gemma":0.0018095054,"threshold_uncertainty_score":0.7192154},"labels":[],"label_agreement":null},{"id":"W3208639644","doi":"","title":"Characterizing Peritumoral Tissue Using Free Water Elimination in Clinical DTI","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Diffusion MRI; Infiltration (HVAC); Brain tissue; Initialization; Computer science; Tractography; Free water; Compartment (ship); Biomedical engineering; Magnetic resonance imaging; Radiology; Materials science; Medicine; Geology","score_opus":0.19620907455896044,"score_gpt":0.4656549720747833,"score_spread":0.2694458975158228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208639644","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03933755,0.002015509,0.9569707,0.00028502752,0.000036010842,0.000074172065,0.00012725864,0.0006510602,0.0005026778],"genre_scores_gemma":[0.30242553,0.0032246967,0.69087005,0.0002408817,0.00007395458,0.00025721567,0.0004791135,0.00066614785,0.001762546],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996568,0.0001378925,0.000028558816,0.00007555712,0.00007150495,0.000029606997],"domain_scores_gemma":[0.9992079,0.00040005374,0.00015740565,0.000099902674,0.00009407981,0.00004067191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015828934,0.0010339352,0.0005620996,0.0012200141,0.00038537578,0.0013856244,0.0006808135,0.0011784245,0.0007333817],"category_scores_gemma":[0.00403863,0.00058879924,0.00062708464,0.00088884484,0.00069422903,0.0014740904,0.000888055,0.000863714,0.0004261398],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008564796,0.0001694638,0.008169726,0.0008863447,0.00029862789,0.0014428621,0.0006518519,0.3419688,0.23214331,0.010259643,0.0035595745,0.39959326],"study_design_scores_gemma":[0.00003813837,0.00030339026,0.0064685764,0.00008245944,0.00016219143,0.0018370217,0.00010762649,0.85497427,0.11405853,0.011388202,0.010443408,0.00013630952],"about_ca_topic_score_codex":0.0037261262,"about_ca_topic_score_gemma":0.006411763,"teacher_disagreement_score":0.0037261262,"about_ca_system_score_codex":0.00047752899,"about_ca_system_score_gemma":0.0012725887,"threshold_uncertainty_score":0.008371234},"labels":[],"label_agreement":null},{"id":"W3208816240","doi":"10.1089/neur.2021.0036","title":"Decreases in Dorsal Cervical Spinal Cord White Matter Tract Integrity Are Associated with Elevated Levels of Serum MicroRNA Biomarkers in NCAA Division I Collegiate Football Players","year":2021,"lang":"en","type":"article","venue":"Neurotrauma Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Medicine; White matter; Corticospinal tract; Spinal cord; Diffusion MRI; Fasciculus; Spinal cord injury; Concussion; Anatomy; Magnetic resonance imaging; Internal medicine; Poison control; Radiology; Injury prevention","score_opus":0.08260471337765157,"score_gpt":0.3508856733318611,"score_spread":0.26828095995420953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208816240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996629,0.000046709898,0.000041558873,0.00000819311,0.0000024748565,0.000007553017,0.000110698165,0.0000020221066,0.000117799835],"genre_scores_gemma":[0.99954766,0.000025030378,0.0000552349,0.000010524266,0.0000049986,0.000012125123,0.00019846362,0.0000011904392,0.00014477267],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996698,0.000054968168,0.000033183594,0.00012341376,0.000060511367,0.000058178954],"domain_scores_gemma":[0.99898523,0.00013778935,0.00050080277,0.00009505601,0.00011914409,0.00016205356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003578658,0.00040929287,0.00034402503,0.0005421064,0.00046076422,0.0005769831,0.00038167488,0.0006373285,0.001043898],"category_scores_gemma":[0.0016193814,0.00033453075,0.00024002256,0.0005478763,0.0002915993,0.0002827928,0.00035183603,0.0004832669,0.00021760562],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005153335,0.00015523157,0.99667263,0.0000107748565,0.0001022517,0.000090081274,0.00010199255,0.00002897897,0.0014818729,0.000010344996,0.000054966833,0.0007755951],"study_design_scores_gemma":[0.00000810092,0.00015557623,0.9994821,0.0000017555291,0.000023642171,0.000098425095,0.000059872767,0.00006419423,0.00006633717,0.0000052363057,0.000033175053,0.0000015829391],"about_ca_topic_score_codex":0.00932751,"about_ca_topic_score_gemma":0.009195983,"teacher_disagreement_score":0.00932751,"about_ca_system_score_codex":0.0002395146,"about_ca_system_score_gemma":0.00026752846,"threshold_uncertainty_score":0.018546402},"labels":[],"label_agreement":null},{"id":"W3208866695","doi":"10.5281/zenodo.19460155","title":"neurostuff/NiMARE: 0.0.8","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Computer science","score_opus":0.19147225510793817,"score_gpt":0.4414745749230314,"score_spread":0.25000231981509324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208866695","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007172693,0.00094880175,0.017398732,0.0020698,0.001132219,0.00089565344,0.046042666,0.7104487,0.22034618],"genre_scores_gemma":[0.009166891,0.001078608,0.024047015,0.0072346567,0.0010460799,0.001691284,0.06173735,0.60689217,0.28710598],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99844825,0.00019335293,0.00013910336,0.00025909627,0.00066669076,0.00029352066],"domain_scores_gemma":[0.9875629,0.0022785005,0.00057097507,0.0026618293,0.0046729017,0.0022528865],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0035104793,0.00238916,0.001622119,0.0035530187,0.0011989465,0.006048422,0.0058933254,0.003079409,0.83064735],"category_scores_gemma":[0.023516906,0.0026841508,0.0017168132,0.0022052366,0.0009978128,0.0074759624,0.0075400225,0.0024668365,0.8123733],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017106989,0.000014464579,0.000086481945,0.00018280138,0.000012986607,0.00002354472,0.000038981918,0.000029849734,0.00027597183,0.00040137777,0.9749781,0.023784425],"study_design_scores_gemma":[0.00028330158,0.000060445822,0.0011589958,0.0002808276,0.00003186717,0.00027155408,0.000058498277,0.0003173435,0.00271678,0.0033699507,0.9913328,0.000117711876],"about_ca_topic_score_codex":0.005555225,"about_ca_topic_score_gemma":0.006997067,"teacher_disagreement_score":0.83064735,"about_ca_system_score_codex":0.002074768,"about_ca_system_score_gemma":0.002323021,"threshold_uncertainty_score":0.24156094},"labels":[],"label_agreement":null},{"id":"W3209571802","doi":"10.1016/j.neubiorev.2021.10.028","title":"Neuromelanin accumulation in patients with schizophrenia: A systematic review and meta-analysis","year":2021,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; Royal Ottawa Mental Health Centre; University of Ottawa; Centre for Addiction and Mental Health; Ontario Institute for Cancer Research; University of Toronto","funders":"National Institute of Mental Health","keywords":"Neuromelanin; Substantia nigra; Dopamine; Schizophrenia (object-oriented programming); Biomarker; Striatum; Meta-analysis; Magnetic resonance imaging; Neuroscience; Internal medicine; Neuroimaging; Medicine; Psychology; Neurology; Pathology; Psychiatry; Dopaminergic; Chemistry; Radiology","score_opus":0.40284195319826493,"score_gpt":0.48643771540453445,"score_spread":0.08359576220626952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209571802","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069946195,0.99207276,0.00023557778,0.00008597217,0.00008806753,0.0000862755,0.00030188326,0.000013331519,0.000121372985],"genre_scores_gemma":[0.16467528,0.8317916,0.0015280882,0.0007319342,0.00017452006,0.00023492349,0.0005538752,0.000018195815,0.00029167134],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99766773,0.0007240656,0.00081373414,0.00040708407,0.00026311574,0.00012423765],"domain_scores_gemma":[0.99650687,0.0020853146,0.00088212674,0.00016733128,0.00028791954,0.00007031898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042656106,0.0021671557,0.011717236,0.003022761,0.00043862575,0.0022377125,0.0014034263,0.001873109,0.0028307885],"category_scores_gemma":[0.010446525,0.0012754634,0.02022792,0.0039557116,0.00055457425,0.0013529152,0.001498655,0.0014032418,0.00027597157],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035759385,0.000058366626,0.00972625,0.3522687,0.6055526,0.00025175206,0.00012888685,0.00043238665,0.0005980691,0.00012575407,0.000935765,0.026345488],"study_design_scores_gemma":[0.00076511316,0.00022476187,0.009866485,0.014661173,0.9719415,0.0001754475,0.00007283948,0.00012180089,0.00012469647,0.00016427864,0.0018411228,0.000040839066],"about_ca_topic_score_codex":0.005326536,"about_ca_topic_score_gemma":0.018115757,"teacher_disagreement_score":0.011717236,"about_ca_system_score_codex":0.001225738,"about_ca_system_score_gemma":0.002039343,"threshold_uncertainty_score":0.022558928},"labels":[],"label_agreement":null},{"id":"W3209666936","doi":"10.1016/j.celrep.2021.109890","title":"fMRI neurofeedback in the motor system elicits bidirectional changes in activity and in white matter structure in the adult human brain","year":2021,"lang":"en","type":"article","venue":"Cell Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"FP7 People: Marie-Curie Actions; NIHR Oxford Biomedical Research Centre; H2020 Marie Skłodowska-Curie Actions; National Institute for Health and Care Research; Wellcome Trust","keywords":"Neurofeedback; White matter; Neuroscience; Corpus callosum; Brain activity and meditation; Psychology; Human brain; Neuroplasticity; Brain mapping; Electroencephalography; Medicine; Magnetic resonance imaging","score_opus":0.02481250611896547,"score_gpt":0.3001290599775655,"score_spread":0.27531655385860004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209666936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99263215,0.0003767331,0.005798083,0.00013553393,0.000028723949,0.000047663805,0.000073597635,0.000070194284,0.0008372901],"genre_scores_gemma":[0.9961241,0.00018225916,0.0029120112,0.00005532665,0.000018379053,0.00007258333,0.000040334417,0.000011951018,0.0005830536],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992216,0.000018579009,0.0000046427153,0.000022194703,0.000015060269,0.000017402705],"domain_scores_gemma":[0.99987745,0.000042538897,0.000037087415,0.0000119130755,0.000011708085,0.000019351477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017754288,0.00031991926,0.00013707764,0.000116084375,0.00011515948,0.00011318116,0.00018021178,0.00022654429,0.0016232342],"category_scores_gemma":[0.0006350251,0.00009255942,0.0000788369,0.000053542208,0.00031601542,0.00017021192,0.00022650197,0.00021345727,0.000118708245],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048062985,0.00010972807,0.00072282425,0.000053181142,0.000010230077,0.00003173018,0.00006187669,0.00012559013,0.9892519,0.000067135574,0.00009538196,0.008989699],"study_design_scores_gemma":[0.0002194914,0.007894453,0.15174723,0.00005757435,0.00012938525,0.0008982461,0.00021273388,0.005639326,0.82853335,0.0011074471,0.003532052,0.000028673401],"about_ca_topic_score_codex":0.00037376714,"about_ca_topic_score_gemma":0.00094903895,"teacher_disagreement_score":0.0016232342,"about_ca_system_score_codex":0.000094783834,"about_ca_system_score_gemma":0.00015991819,"threshold_uncertainty_score":0.005430281},"labels":[],"label_agreement":null},{"id":"W3209702035","doi":"10.5281/zenodo.580063","title":"Tractography Challenge ISMRM 2015 Code of the Scoring System","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Code (set theory); Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging; Programming language; Set (abstract data type)","score_opus":0.13340641378992615,"score_gpt":0.34685046412274023,"score_spread":0.21344405033281408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209702035","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0131865265,0.001023446,0.4163365,0.012902343,0.009517159,0.003772275,0.23491189,0.23075499,0.07759483],"genre_scores_gemma":[0.04228668,0.00077603525,0.2571068,0.004423101,0.002052438,0.0050164894,0.48480108,0.10999811,0.093539245],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9853418,0.003267902,0.0020634038,0.001375596,0.006825913,0.0011253486],"domain_scores_gemma":[0.9341627,0.009006387,0.002278389,0.013926098,0.03760701,0.0030193478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012788417,0.0019504386,0.0015404578,0.003604555,0.0020223833,0.0059380936,0.0032510739,0.004035518,0.104021],"category_scores_gemma":[0.08146952,0.001463496,0.0013685197,0.0024006253,0.0011888858,0.0037327395,0.0063335923,0.0045204335,0.15192875],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003284172,0.000051241026,0.0008728287,0.00024233636,0.00002374438,0.00013883942,0.000106901236,0.0012049581,0.0020120523,0.0048500844,0.94735104,0.04281739],"study_design_scores_gemma":[0.0003093295,0.00025686342,0.00612992,0.00078585296,0.000043522166,0.0013281925,0.00016319635,0.016668038,0.009338128,0.020191316,0.9444651,0.00032052925],"about_ca_topic_score_codex":0.011706308,"about_ca_topic_score_gemma":0.011393423,"teacher_disagreement_score":0.104021,"about_ca_system_score_codex":0.0022413607,"about_ca_system_score_gemma":0.008032808,"threshold_uncertainty_score":0.3479849},"labels":[],"label_agreement":null},{"id":"W3209967316","doi":"10.1016/j.neuroimage.2021.118687","title":"Recycling diagnostic MRI for empowering brain morphometric research – Critical &amp; practical assessment on learning-based image super-resolution","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Key Medical Subjects of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Xuzhou Medical University; Hospital for Sick Children; National Natural Science Foundation of China; Azrieli Foundation; China Postdoctoral Science Foundation; Ministry of Science and Technology of the People's Republic of China; Jiangsu Province Postdoctoral Science Foundation","keywords":"Voxel; Computer science; Artificial intelligence; Isotropy; Resolution (logic); Ground truth; Pattern recognition (psychology); Image quality; Sample (material); Image (mathematics); Computer vision; Data mining; Physics; Optics","score_opus":0.25825090133019807,"score_gpt":0.5526592950398811,"score_spread":0.294408393709683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209967316","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030187035,0.005368129,0.9580583,0.0029427153,0.00015042945,0.00014482121,0.00016162521,0.00068152946,0.0023053954],"genre_scores_gemma":[0.2293399,0.0073604803,0.760107,0.00055324455,0.00026580633,0.00021371909,0.00030884088,0.00030051515,0.0015505566],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99770737,0.001063454,0.000110743866,0.00037062992,0.0006402625,0.00010758556],"domain_scores_gemma":[0.99326926,0.0031411734,0.0005267674,0.0012374532,0.0015732909,0.00025208713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008048614,0.0010653137,0.0006774198,0.001404072,0.0003608566,0.001593894,0.0014640111,0.00116023,0.0019396686],"category_scores_gemma":[0.022411948,0.00057013985,0.0007583296,0.0010910035,0.0015399035,0.0030855527,0.0021646183,0.0015988438,0.0006182065],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044752387,0.00013705523,0.011794647,0.0015768599,0.00029689117,0.000788266,0.00092861924,0.07603764,0.07238526,0.04517117,0.008873518,0.78156257],"study_design_scores_gemma":[0.000042682906,0.000346931,0.008160766,0.00037263005,0.00019334658,0.0024903263,0.00044698702,0.8269652,0.0700612,0.06139476,0.029394126,0.0001310546],"about_ca_topic_score_codex":0.001639144,"about_ca_topic_score_gemma":0.0026637702,"teacher_disagreement_score":0.008048614,"about_ca_system_score_codex":0.000549601,"about_ca_system_score_gemma":0.0011592977,"threshold_uncertainty_score":0.042565644},"labels":[],"label_agreement":null},{"id":"W3210063353","doi":"10.1371/journal.pone.0255711","title":"Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Reproducibility; Kurtosis; Diffusion MRI; Fractional anisotropy; Voxel; Nuclear magnetic resonance; Region of interest; Sample size determination; Materials science; Biomedical engineering; Mathematics; Physics; Computer science; Statistics; Magnetic resonance imaging; Artificial intelligence; Medicine; Radiology","score_opus":0.06626205067740572,"score_gpt":0.30785945127531145,"score_spread":0.24159740059790574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210063353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9525375,0.0010619084,0.042889595,0.000112953065,0.00012404745,0.00024206958,0.0010546448,0.0007011426,0.0012762358],"genre_scores_gemma":[0.9661908,0.00027389277,0.028526135,0.00019351207,0.0000467492,0.00093288475,0.0012495753,0.0004934539,0.002092931],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99571216,0.0009791963,0.00041559915,0.0015816323,0.0010562371,0.00025519825],"domain_scores_gemma":[0.9833755,0.0030237245,0.0032305303,0.0040593767,0.0056786803,0.0006320624],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009521694,0.00074400374,0.00078622915,0.0010515172,0.0005342405,0.0007660803,0.00076003914,0.00068750675,0.00089679315],"category_scores_gemma":[0.011372137,0.00064501946,0.000625218,0.0003953337,0.00097626576,0.0006680039,0.000692888,0.0009399112,0.00048462057],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045064217,0.000667064,0.056234777,0.00023626444,0.0008620184,0.00014601712,0.001074976,0.0014727699,0.90368366,0.00024319564,0.0007890314,0.030083667],"study_design_scores_gemma":[0.00025021832,0.008037877,0.5883313,0.00007213555,0.0011408187,0.0007138336,0.00022842053,0.010613337,0.38626498,0.0008099953,0.0033341516,0.00020301269],"about_ca_topic_score_codex":0.0009454118,"about_ca_topic_score_gemma":0.002172944,"teacher_disagreement_score":0.9904783,"about_ca_system_score_codex":0.00044972743,"about_ca_system_score_gemma":0.0004241129,"threshold_uncertainty_score":0.05035615},"labels":[],"label_agreement":null},{"id":"W3210569499","doi":"10.5281/zenodo.4314291","title":"dMRIPrep: a robust preprocessing pipeline for diffusion MRI","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Pipeline (software); Preprocessor; Computer science; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.1353888152438295,"score_gpt":0.3273362676861259,"score_spread":0.19194745244229638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210569499","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003655635,0.0010483422,0.880199,0.00036366147,0.00025953437,0.00038138972,0.011549161,0.099327855,0.0032154282],"genre_scores_gemma":[0.020203054,0.0009539434,0.90950435,0.0006868261,0.00021197426,0.0014402913,0.028186623,0.030939285,0.00787364],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99883014,0.00017180838,0.00014713373,0.00035909557,0.00036792047,0.00012390706],"domain_scores_gemma":[0.9979962,0.0005959133,0.00017688678,0.00053614017,0.00057821383,0.00011667043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027528233,0.0028442715,0.0015015547,0.0031342322,0.0013594112,0.003565715,0.0031216298,0.002188068,0.03976324],"category_scores_gemma":[0.008784778,0.0018405934,0.0019261562,0.0021094459,0.0006564786,0.001710681,0.004075447,0.003353973,0.03606835],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009908335,0.00016509545,0.0019256063,0.002213548,0.0006684218,0.0009070271,0.00068974594,0.0053944276,0.15101369,0.009618442,0.32865727,0.49775586],"study_design_scores_gemma":[0.00040478702,0.0003454451,0.011022483,0.0005532603,0.00044471744,0.0044918703,0.00032132916,0.11851275,0.2606552,0.045589663,0.556856,0.000802468],"about_ca_topic_score_codex":0.002571027,"about_ca_topic_score_gemma":0.0051580104,"teacher_disagreement_score":0.03976324,"about_ca_system_score_codex":0.0005837996,"about_ca_system_score_gemma":0.002554726,"threshold_uncertainty_score":0.1330213},"labels":[],"label_agreement":null},{"id":"W3211014836","doi":"10.1136/bmjresp-2021-bssconf.32","title":"36 Literature review on the effects of acute and chronic alcohol use on the glymphatic transport system","year":2021,"lang":"en","type":"article","venue":"Abstracts","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Clinical trial; Medicine; Clinical study design; Disease; Clinical research; Intensive care medicine; Internal medicine","score_opus":0.03487616025582492,"score_gpt":0.32028279475918303,"score_spread":0.2854066345033581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211014836","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003192056,0.9986266,0.000038450573,0.00041254258,0.000118267926,0.00001857305,0.00007601469,0.0000024026751,0.00038791986],"genre_scores_gemma":[0.0023364446,0.996779,0.000117259435,0.00041769352,0.00017743747,0.000023152816,0.00007649043,0.0000020020404,0.000070532784],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99669564,0.0011073808,0.0012014838,0.0002793801,0.0005970548,0.00011912534],"domain_scores_gemma":[0.9634681,0.028867077,0.00454566,0.0004065309,0.002408541,0.00030411335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049841967,0.00095604884,0.0037867145,0.010166481,0.0006012291,0.0026176786,0.0014848369,0.0020921663,0.012682485],"category_scores_gemma":[0.021386215,0.0007348509,0.004338477,0.010779629,0.0010000146,0.0022190614,0.0011618537,0.0014080784,0.0011914927],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005961633,0.00012813947,0.002619906,0.6532976,0.004535497,0.00033914548,0.0003738937,0.00020216596,0.000257194,0.0012602177,0.014395893,0.3219941],"study_design_scores_gemma":[0.00016665636,0.00043728037,0.01707572,0.80205023,0.0207759,0.0013918845,0.00063502864,0.00010035268,0.00035858457,0.0011552268,0.1557707,0.00008228856],"about_ca_topic_score_codex":0.008987561,"about_ca_topic_score_gemma":0.018278798,"teacher_disagreement_score":0.012682485,"about_ca_system_score_codex":0.0023233825,"about_ca_system_score_gemma":0.008464403,"threshold_uncertainty_score":0.042427182},"labels":[],"label_agreement":null},{"id":"W3211352396","doi":"10.7759/cureus.19355","title":"Diagnostic Implications of White Matter Tract Involvement by Intra-axial Brain Tumors","year":2021,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Diffusion MRI; White matter; Infiltration (HVAC); Astrocytoma; Brain tumor; Radiology; Magnetic resonance imaging; Pathology; Glioma","score_opus":0.04048906555426739,"score_gpt":0.33835216436658977,"score_spread":0.29786309881232237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211352396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978278,0.0011237542,0.00029016528,0.00003207388,0.0000055730884,0.000006282692,0.00008324513,0.000005106799,0.0006258888],"genre_scores_gemma":[0.9993886,0.0002999196,0.00016644984,0.000008748638,0.000012672083,0.0000023726136,0.00006899171,0.0000012246011,0.000051089442],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996045,0.00009862772,0.00007170387,0.000077982426,0.000079710306,0.000067394256],"domain_scores_gemma":[0.9972696,0.0006843893,0.0015448154,0.00011041008,0.0001961214,0.00019468614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006995548,0.00025614144,0.00014531949,0.0009532688,0.00018521074,0.00040318392,0.00023427403,0.000206673,0.0012354779],"category_scores_gemma":[0.0027951607,0.00009224416,0.00013522543,0.0005689513,0.00065288495,0.00036410568,0.00035372024,0.00016412754,0.00018475128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009160281,0.000005376233,0.9928383,0.00002162815,0.000011996735,0.0010799868,0.000028661552,0.000025543608,0.0016297862,0.000013082231,0.000027967055,0.0042260885],"study_design_scores_gemma":[0.000003520903,0.000111279034,0.977002,0.000019330464,0.00003831478,0.02076983,0.00015119564,0.00014597629,0.0014363339,0.000060812577,0.0002575199,0.0000038617554],"about_ca_topic_score_codex":0.0007168743,"about_ca_topic_score_gemma":0.0010661762,"teacher_disagreement_score":0.0012354779,"about_ca_system_score_codex":0.00014483076,"about_ca_system_score_gemma":0.00019258303,"threshold_uncertainty_score":0.0041331053},"labels":[],"label_agreement":null},{"id":"W3211737115","doi":"10.1002/trc2.12217","title":"A ketogenic supplement improves white matter energy supply and processing speed in mild cognitive impairment","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Translational Research & Clinical Interventions","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Ketone bodies; White matter; Neurocognitive; Ketogenic diet; Medicine; Glucose uptake; Fornix; Positron emission tomography; Neuroimaging; Cognition; Internal medicine; Psychology; Nuclear medicine; Neuroscience; Insulin; Magnetic resonance imaging; Radiology; Metabolism; Epilepsy; Hippocampus","score_opus":0.32843368658637434,"score_gpt":0.5277430677723072,"score_spread":0.19930938118593283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211737115","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998798,0.0007225314,0.00007286179,0.000039310857,0.00001697238,0.000030477651,0.000092959875,0.000022012311,0.00020482237],"genre_scores_gemma":[0.99752825,0.0008200236,0.00047431496,0.00007074687,0.000017665307,0.00005674417,0.00016293743,0.000003237627,0.00086601847],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999535,0.0000095743035,0.000008579968,0.000008624934,0.0000097434295,0.000009904836],"domain_scores_gemma":[0.9998728,0.000017830207,0.000034275825,0.000007712101,0.000022826047,0.000044411707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013105341,0.00045563048,0.0006625029,0.00031252403,0.00018613701,0.00023378448,0.00024098084,0.00037761524,0.0021997415],"category_scores_gemma":[0.00034027846,0.000118360236,0.00027438847,0.00019134134,0.00014486002,0.00017132453,0.00020802983,0.0003464392,0.00020091757],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.33993033,0.04243,0.020938577,0.002964861,0.0014954992,0.0003862525,0.00046733106,0.0009055527,0.4061651,0.00012966106,0.0014393067,0.18274757],"study_design_scores_gemma":[0.029131124,0.28981853,0.55938566,0.0005492071,0.0029873599,0.00043798043,0.0006632256,0.0033007087,0.10945478,0.00044780617,0.0037448613,0.00007881712],"about_ca_topic_score_codex":0.002190613,"about_ca_topic_score_gemma":0.0026511615,"teacher_disagreement_score":0.0021997415,"about_ca_system_score_codex":0.00018579532,"about_ca_system_score_gemma":0.00022608165,"threshold_uncertainty_score":0.007358849},"labels":[],"label_agreement":null},{"id":"W3212030657","doi":"10.1212/wnl.94.15_supplement.2728","title":"Braak Neurofibrillary Tangle Staging Prediction Using In Vivo MRI Metrics (2728)","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Hôpital de l'Enfant-Jésus","funders":"","keywords":"Tangle; Neurofibrillary tangle; Neuroscience; Alzheimer's disease; Medicine; In vivo; Audiology; Psychology; Pathology; Disease; Biology; Mathematics; Senile plaques","score_opus":0.09292557713855468,"score_gpt":0.3396425162714804,"score_spread":0.24671693913292572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212030657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9557181,0.0022285786,0.03586293,0.00016486575,0.00010128954,0.00018246277,0.0010167522,0.00044251286,0.0042825486],"genre_scores_gemma":[0.97668546,0.0005447853,0.020843823,0.00006723968,0.0000363185,0.00009205083,0.0006889856,0.000049187267,0.0009920952],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994386,0.00020676735,0.00007651991,0.000119920594,0.00012073891,0.000037479156],"domain_scores_gemma":[0.99721503,0.0006759105,0.00084921764,0.0003515424,0.00075331144,0.0001549509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002907205,0.001344393,0.00057835825,0.0019226612,0.00030790272,0.0012513663,0.000603366,0.0007015002,0.0011520403],"category_scores_gemma":[0.007272679,0.00037498216,0.00035521438,0.0005281075,0.00039451546,0.0010048456,0.0003909125,0.0005790968,0.000714043],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008830329,0.0003095399,0.8234695,0.000353708,0.00062022597,0.0003431042,0.00030455703,0.007391027,0.09328996,0.00094569236,0.0014229055,0.07066681],"study_design_scores_gemma":[0.000047762864,0.0018114345,0.88555104,0.00013597166,0.00047132798,0.0029342188,0.00029032884,0.052874222,0.05108802,0.0011305481,0.0035558792,0.00010918327],"about_ca_topic_score_codex":0.0025486264,"about_ca_topic_score_gemma":0.005471555,"teacher_disagreement_score":0.002907205,"about_ca_system_score_codex":0.00026532693,"about_ca_system_score_gemma":0.0002867693,"threshold_uncertainty_score":0.0153749585},"labels":[],"label_agreement":null},{"id":"W3212499163","doi":"10.1016/j.nano.2021.102478","title":"Superparamagnetic iron oxide nanoparticles-based detection of neuronal activity","year":2021,"lang":"en","type":"article","venue":"Nanomedicine Nanotechnology Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal","funders":"Savoy Foundation; Réseau en Bio-Imagerie du Quebec","keywords":"Dynamic light scattering; Magnetic resonance imaging; Iron oxide nanoparticles; Premovement neuronal activity; Superparamagnetism; Chemistry; Biophysics; Brain activity and meditation; Nanoparticle; Nuclear magnetic resonance; Materials science; Neuroscience; Nanotechnology; Magnetic field; Biology; Electroencephalography; Medicine; Magnetization; Physics","score_opus":0.03365988542931305,"score_gpt":0.33988345502532513,"score_spread":0.3062235695960121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212499163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9487237,0.0024140903,0.040312387,0.00044050536,0.00012933572,0.00008957731,0.00016130175,0.0001884967,0.007540584],"genre_scores_gemma":[0.97097415,0.0009144555,0.022482118,0.00022368539,0.000041952833,0.000084938336,0.00012668503,0.000028005308,0.00512402],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99989724,0.000018145649,0.0000032437533,0.00003148654,0.000032908356,0.000017006445],"domain_scores_gemma":[0.99992085,0.00003323231,0.0000148217705,0.000005439121,0.000013874336,0.000011843718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020970605,0.00022744744,0.00017325347,0.00019108791,0.00013908857,0.0002831576,0.00043856978,0.00056603993,0.0006434231],"category_scores_gemma":[0.00031021956,0.00015486863,0.000117957214,0.000103589344,0.00026332468,0.0003552108,0.00026683178,0.0004158924,0.00020521361],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008972745,0.000015686644,0.00007632709,0.000037840255,0.0000032195608,0.000049307502,0.00001841215,0.000086879794,0.99650663,0.00020042327,0.00009406299,0.0028215991],"study_design_scores_gemma":[0.000013203438,0.000112929876,0.0011681317,0.000006003529,0.00000923348,0.00014594992,0.000016217198,0.0059923637,0.9915537,0.00012411487,0.0008519266,0.0000061616674],"about_ca_topic_score_codex":0.0005326432,"about_ca_topic_score_gemma":0.001137417,"teacher_disagreement_score":0.0006434231,"about_ca_system_score_codex":0.00030382007,"about_ca_system_score_gemma":0.00016409798,"threshold_uncertainty_score":0.0022043586},"labels":[],"label_agreement":null},{"id":"W3213266407","doi":"10.1038/s41598-021-01476-z","title":"Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"European Research Council","keywords":"Magnetic resonance imaging; Diffusion; Diffusion MRI; Gaussian; Nuclear magnetic resonance; Computer science; Statistical physics; Medicine; Physics; Chemistry; Radiology; Computational chemistry; Thermodynamics","score_opus":0.07428836332777075,"score_gpt":0.3216931236854927,"score_spread":0.24740476035772194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213266407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58302087,0.0006241626,0.41505748,0.00010907469,0.000011087149,0.00005096383,0.00009447138,0.00027109042,0.00076077634],"genre_scores_gemma":[0.8226195,0.0005672777,0.17560932,0.000021590644,0.0000057636657,0.000041196625,0.000095603864,0.000034766083,0.0010048668],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992096,0.000022087304,0.000004707159,0.000018559544,0.00002402049,0.000009612417],"domain_scores_gemma":[0.9996456,0.0001426248,0.00008139035,0.000048242888,0.00006509644,0.000017114118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005190577,0.00030251476,0.00014442559,0.0003976291,0.00009836159,0.00035661826,0.00027766064,0.00036114393,0.0004780131],"category_scores_gemma":[0.0011944114,0.00014822296,0.00018111391,0.0002604925,0.00027324137,0.00058120355,0.0002618498,0.00026145394,0.00011453077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018033032,0.000062157735,0.0025077641,0.0001649639,0.000031590742,0.00009943412,0.0001413031,0.03387281,0.92870915,0.0022403477,0.000102478334,0.03188772],"study_design_scores_gemma":[0.000021758351,0.00032964937,0.015191567,0.00002043587,0.00005486888,0.00053784455,0.00007363838,0.63914233,0.33995655,0.0026105864,0.0020118505,0.00004882569],"about_ca_topic_score_codex":0.0012692708,"about_ca_topic_score_gemma":0.0022727437,"teacher_disagreement_score":0.0012692708,"about_ca_system_score_codex":0.00029004275,"about_ca_system_score_gemma":0.00028966332,"threshold_uncertainty_score":0.0027450323},"labels":[],"label_agreement":null},{"id":"W3213593937","doi":"10.1101/2021.11.13.468500","title":"Home literacy environment mediates the relationship between socioeconomic status and white matter structure in infants","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"White matter; Fractional anisotropy; Developmental psychology; Psychology; Association (psychology); Socioeconomic status; Fasciculus; Reading (process); Diffusion MRI; Phonological awareness; Superior longitudinal fasciculus; Literacy; Medicine; Population; Magnetic resonance imaging; Environmental health","score_opus":0.02378477614273908,"score_gpt":0.27320301918842405,"score_spread":0.24941824304568497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213593937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995407,0.00005977757,0.00006840199,0.000025038655,0.0000016833491,0.0000015618535,0.000075072174,0.000002098421,0.00022563111],"genre_scores_gemma":[0.9995023,0.000057925958,0.00012261745,0.000009254048,0.0000017878954,0.0000057605916,0.00007358742,0.0000018465466,0.00022480734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998423,0.00004047293,0.000011534081,0.00004205197,0.00002540012,0.00003821455],"domain_scores_gemma":[0.9990778,0.0002431059,0.00040745086,0.00005352621,0.00007724839,0.00014076063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041313432,0.00022463771,0.00015911326,0.00024077782,0.00018632949,0.000413092,0.00018326851,0.00024012948,0.0029513484],"category_scores_gemma":[0.0021623776,0.00015038074,0.00018643381,0.00015982747,0.00020532578,0.00021379437,0.00040170248,0.0002645199,0.00018051635],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021606324,0.00009782548,0.98736817,0.00002730398,0.00008023119,0.0005651787,0.00049391185,0.00008342533,0.006687942,0.00015415977,0.0001366443,0.004089144],"study_design_scores_gemma":[8.5265174e-7,0.00003759589,0.9992717,0.0000069916273,0.000009430137,0.00008290828,0.00011448108,0.00013931475,0.00024354157,0.00003593379,0.00005553695,0.0000017113259],"about_ca_topic_score_codex":0.0050098496,"about_ca_topic_score_gemma":0.0070571634,"teacher_disagreement_score":0.0050098496,"about_ca_system_score_codex":0.00017230833,"about_ca_system_score_gemma":0.00023052913,"threshold_uncertainty_score":0.009961426},"labels":[],"label_agreement":null},{"id":"W3214279120","doi":"10.52294/e6198273-b8e3-4b63-babb-6e6b0da10669","title":"Evaluating the Reliability of Human Brain White Matter Tractometry","year":2021,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIH Blueprint for Neuroscience Research; National Institute of Mental Health; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Washington Research Foundation; Alfred P. Sloan Foundation; University of Washington; McDonnell Center for Systems Neuroscience; Gordon and Betty Moore Foundation","keywords":"Human Connectome Project; Reliability (semiconductor); Computer science; White matter; Neuroimaging; Reproducibility; Robustness (evolution); Reliability engineering; Diffusion MRI; Psychology; Functional connectivity; Statistics; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.09514027686437139,"score_gpt":0.42951816728008857,"score_spread":0.3343778904157172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214279120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.490187,0.0043610767,0.4891273,0.0007164218,0.0005623197,0.0006523937,0.0038104285,0.0027323475,0.007850795],"genre_scores_gemma":[0.8958789,0.0009751321,0.09643365,0.00021074736,0.00017308249,0.0004056917,0.0036317068,0.0012561225,0.001034915],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9714245,0.0127065,0.0036385534,0.005769474,0.00584623,0.00061486615],"domain_scores_gemma":[0.86966926,0.07409601,0.012261944,0.020315396,0.02259672,0.001060603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04126512,0.0012256859,0.00091831957,0.0039262106,0.0011285153,0.003249571,0.0013386002,0.0017552803,0.0022415356],"category_scores_gemma":[0.18492085,0.00077062397,0.0016532415,0.0029898025,0.002935397,0.002373664,0.0028069469,0.0008508105,0.0018338994],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002112806,0.00023507762,0.5951062,0.0028984754,0.0049050064,0.0005915371,0.005890157,0.05421506,0.032328423,0.007263849,0.008983297,0.28547013],"study_design_scores_gemma":[0.00023653591,0.0014193576,0.73574424,0.0012623131,0.0018369078,0.0027042816,0.0017958052,0.15403116,0.039848443,0.030520143,0.03005794,0.00054294546],"about_ca_topic_score_codex":0.0043612206,"about_ca_topic_score_gemma":0.004404146,"teacher_disagreement_score":0.04126512,"about_ca_system_score_codex":0.0006522167,"about_ca_system_score_gemma":0.0013047465,"threshold_uncertainty_score":0.2182334},"labels":[],"label_agreement":null},{"id":"W3214837645","doi":"10.1101/2021.11.23.21266731","title":"In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of British Columbia Hospital; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Hyperintensity; Neuroimaging; Myelin; Pathology; Medicine; Magnetic resonance imaging; Internal medicine; Radiology; Central nervous system","score_opus":0.01906411290487649,"score_gpt":0.3011506869429577,"score_spread":0.28208657403808124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214837645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99806505,0.00034627196,0.001323101,0.00000785721,0.000001983394,0.0000066987955,0.00007036112,0.00001051412,0.00016808351],"genre_scores_gemma":[0.9976037,0.00013549355,0.0018348921,0.000006057511,0.0000031440645,0.000011340388,0.00008141977,0.000004342986,0.00031968704],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999925,0.000013556872,0.0000075783487,0.000029480669,0.000012984051,0.000011311204],"domain_scores_gemma":[0.99984837,0.00002172002,0.000059768834,0.00001537421,0.000030013014,0.000024730376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031925808,0.00019113693,0.00013206818,0.0004924036,0.00013993158,0.00030674276,0.00008228126,0.00026895374,0.00091368775],"category_scores_gemma":[0.0004396681,0.00012187915,0.00010750527,0.00026181986,0.00017768751,0.0002971984,0.00016452286,0.00012953939,0.00014209801],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020523516,0.00017841542,0.2295234,0.00022054864,0.00022988218,0.00036552156,0.00063285494,0.0013201445,0.7172743,0.00029439316,0.00019789356,0.047710232],"study_design_scores_gemma":[0.000019412495,0.00077167293,0.9058788,0.000019536146,0.000106727995,0.0010692509,0.00025735027,0.00485385,0.085928746,0.00035804728,0.0007228892,0.0000137682755],"about_ca_topic_score_codex":0.001383334,"about_ca_topic_score_gemma":0.0022744061,"teacher_disagreement_score":0.001383334,"about_ca_system_score_codex":0.00014912088,"about_ca_system_score_gemma":0.00012102331,"threshold_uncertainty_score":0.0030565858},"labels":[],"label_agreement":null},{"id":"W3214870749","doi":"10.1016/j.neuroimage.2021.118749","title":"Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; UK Dementia Research Institute; British Heart Foundation; University College London; National Institute for Health and Care Research; Alzheimer's Society; Wellcome Trust; Weston Brain Institute; Wolfson Foundation; Brain Research Trust; Brain Research UK; Alzheimer's Association; University College London Hospitals NHS Foundation Trust; U.S. Department of Defense","keywords":"Voxel; Region of interest; Pattern recognition (psychology); Neuroimaging; Metric (unit); Partial volume; Artificial intelligence; Brain tissue; Brain size; Statistics; Computer science; Psychology; Magnetic resonance imaging; Mathematics; Neuroscience; Medicine; Radiology","score_opus":0.3020479958614572,"score_gpt":0.41969500748286503,"score_spread":0.11764701162140784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214870749","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05360556,0.0011201055,0.94248897,0.0002769603,0.00015689948,0.00015220132,0.00020522592,0.0013106774,0.00068331824],"genre_scores_gemma":[0.28182796,0.0005696346,0.71356785,0.0003039119,0.00019377294,0.0005034315,0.00080158754,0.0012420659,0.0009897723],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9934174,0.003184916,0.0005796184,0.001357367,0.0012321286,0.00022870602],"domain_scores_gemma":[0.9697379,0.020124145,0.0026323413,0.0041230246,0.0030521573,0.0003304622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016091395,0.0010150253,0.001409322,0.0016951801,0.0008695708,0.0019869201,0.0016505042,0.0010683837,0.0012435106],"category_scores_gemma":[0.07101259,0.0007583516,0.00092842337,0.0021647823,0.0011089942,0.0017586758,0.0023552545,0.0012193448,0.00052192126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012588786,0.00013427845,0.03730917,0.0010123529,0.0013405525,0.00043565483,0.0030193038,0.050599087,0.040780246,0.01784724,0.007983758,0.8382794],"study_design_scores_gemma":[0.00041444317,0.0009892699,0.092266016,0.00048890745,0.0012507166,0.0019939083,0.0012149618,0.67656326,0.07789166,0.10769817,0.03878422,0.00044451986],"about_ca_topic_score_codex":0.004418263,"about_ca_topic_score_gemma":0.0073390007,"teacher_disagreement_score":0.016091395,"about_ca_system_score_codex":0.0007221513,"about_ca_system_score_gemma":0.0016246886,"threshold_uncertainty_score":0.08510041},"labels":[],"label_agreement":null},{"id":"W3215234842","doi":"10.1007/s00429-021-02407-4","title":"Imaging functional neuroplasticity in human white matter tracts","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria; University of Calgary; Surrey Memorial Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Fraser Health Authority","keywords":"Corpus callosum; Neuroplasticity; Diffusion MRI; White matter; Internal capsule; Neuroscience; Functional magnetic resonance imaging; Fractional anisotropy; Magnetic resonance imaging; Psychology; Tractography; Medicine; Radiology","score_opus":0.025644029195805183,"score_gpt":0.2894671375390891,"score_spread":0.26382310834328393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215234842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9330616,0.004841296,0.058625277,0.00013149845,0.000021599477,0.00008128858,0.00047066575,0.00015420685,0.00261259],"genre_scores_gemma":[0.9665695,0.0021672375,0.029377393,0.000074472184,0.00002838672,0.00009908676,0.00027555853,0.000042299478,0.001366206],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999255,0.000020027708,0.0000055233204,0.000024390587,0.000014840325,0.000009801525],"domain_scores_gemma":[0.9998728,0.00004360528,0.000030764233,0.000011125492,0.00002773587,0.000013957781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003545651,0.00023067932,0.00013871692,0.00070947496,0.00016150407,0.00032250752,0.00011840991,0.00029386018,0.0012540616],"category_scores_gemma":[0.00084393326,0.00012228018,0.000088311084,0.00036101777,0.00028902444,0.0003668941,0.00019417334,0.00015972556,0.00015389998],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003460027,0.000048413633,0.009316815,0.00038667922,0.00008029915,0.00032401521,0.00031309566,0.00094382605,0.9114025,0.0006265001,0.00037171418,0.07584003],"study_design_scores_gemma":[0.00005786523,0.0013653479,0.62738967,0.0002230311,0.00027927905,0.0055598957,0.00057155936,0.01932026,0.3328376,0.006079207,0.006248092,0.00006822613],"about_ca_topic_score_codex":0.0010496656,"about_ca_topic_score_gemma":0.0022468613,"teacher_disagreement_score":0.0012540616,"about_ca_system_score_codex":0.00010303451,"about_ca_system_score_gemma":0.00021578291,"threshold_uncertainty_score":0.0041952133},"labels":[],"label_agreement":null},{"id":"W3215319807","doi":"10.1101/2021.11.22.469616","title":"mrHARDIflow : A pipeline tailored for the preprocessing and analysis of Multi-Resolution High Angular diffusion MRI and its application to a variability study of the PRIME-DE database","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Computer science; Scanner; Robustness (evolution); Scalability; Pipeline (software); Computer vision; Artificial intelligence; Database; Magnetic resonance imaging","score_opus":0.031154277854292922,"score_gpt":0.3048001280941482,"score_spread":0.27364585023985527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215319807","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03722218,0.00047517748,0.76987505,0.0003526474,0.00011659349,0.00057824294,0.012900094,0.1767667,0.0017132928],"genre_scores_gemma":[0.16719393,0.00044185715,0.76321477,0.00038704937,0.000077291996,0.0016268323,0.04612896,0.016858414,0.0040708836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999353,0.00006886599,0.00005435056,0.0002726546,0.00016295801,0.000088222696],"domain_scores_gemma":[0.9988727,0.00032934622,0.00010633611,0.00034471008,0.0002350537,0.00011179994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023007724,0.0013207733,0.0007982156,0.0019032502,0.00058632594,0.001795779,0.0020601675,0.0009621874,0.0091943145],"category_scores_gemma":[0.0051734014,0.0006771468,0.0009915843,0.00096580095,0.0005988808,0.0016616628,0.0023127364,0.0011961237,0.005219039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033176572,0.00044230447,0.009743291,0.0011257476,0.00059770787,0.0015155585,0.0012238336,0.023733472,0.1938663,0.008933885,0.1274648,0.6280354],"study_design_scores_gemma":[0.00048247725,0.0005769251,0.02617921,0.00021880635,0.00017356299,0.002155708,0.0002994207,0.5295585,0.2619267,0.022699287,0.15533562,0.00039377427],"about_ca_topic_score_codex":0.0032083762,"about_ca_topic_score_gemma":0.0028851565,"teacher_disagreement_score":0.0091943145,"about_ca_system_score_codex":0.0005764963,"about_ca_system_score_gemma":0.0015666806,"threshold_uncertainty_score":0.030758023},"labels":[],"label_agreement":null},{"id":"W3215445514","doi":"10.1093/neuonc/noab196.915","title":"ITVT-03. Use of Functional MRI and DTI for Surgical Planning of Maximal Extent of Resection of CNS Tumors - A Single Neurosurgical Center’s Experience","year":2021,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Medicine; Magnetic resonance imaging; Diffusion MRI; Neuronavigation; Surgical planning; Functional imaging; Functional magnetic resonance imaging; Neuroimaging; Radiology; Nuclear medicine","score_opus":0.1644279284472633,"score_gpt":0.3897089641072013,"score_spread":0.22528103565993798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215445514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96056473,0.0026670129,0.021740599,0.00073406106,0.00013533632,0.00025919368,0.0003665422,0.00046499041,0.013067428],"genre_scores_gemma":[0.96447253,0.0014903555,0.030498054,0.00025543413,0.00010416137,0.00007832928,0.0004950443,0.00020107179,0.002405016],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996499,0.00007238114,0.000056364035,0.000074906005,0.00006226935,0.00008408426],"domain_scores_gemma":[0.9990458,0.000112158086,0.00012660738,0.00012365932,0.00013044184,0.0004613979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086602673,0.0005231348,0.00022105842,0.00084965647,0.00043168233,0.00073890574,0.00066374004,0.0004433433,0.0026845632],"category_scores_gemma":[0.001567826,0.00026371362,0.00043171755,0.00054414093,0.00041967048,0.00046392108,0.0008540233,0.0006704355,0.0011027656],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005823585,0.0012478308,0.22890179,0.00032162957,0.00018384421,0.096655615,0.0032380598,0.0042779236,0.047236618,0.0006425985,0.0055501345,0.6111616],"study_design_scores_gemma":[0.00012805371,0.003883538,0.37018624,0.00046443683,0.00022455209,0.5306665,0.0042289454,0.009293899,0.04071172,0.001550339,0.038448576,0.00021329496],"about_ca_topic_score_codex":0.0028408545,"about_ca_topic_score_gemma":0.006296892,"teacher_disagreement_score":0.0028408545,"about_ca_system_score_codex":0.00053494517,"about_ca_system_score_gemma":0.0013960833,"threshold_uncertainty_score":0.008980751},"labels":[],"label_agreement":null},{"id":"W3215447310","doi":"10.1101/2021.11.29.470422","title":"<i>TractoInferno</i> : A large-scale, open-source, multi-site database for machine learning dMRI tractography","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Sherbrooke","funders":"","keywords":"Computer science; Tractography; Benchmarking; Artificial intelligence; Diffusion MRI; Database; Pipeline (software); Human Connectome Project; Artificial neural network; Data mining; Machine learning; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging","score_opus":0.047021800294677674,"score_gpt":0.3130632676630124,"score_spread":0.2660414673683347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215447310","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013955899,0.0014832777,0.08917413,0.0004789257,0.00034167725,0.00050126074,0.5607907,0.32469195,0.008582212],"genre_scores_gemma":[0.032523397,0.0004773401,0.06703231,0.00025815406,0.000090218164,0.0008915336,0.86279446,0.03210386,0.0038288003],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987191,0.00015212706,0.0001431998,0.00041055668,0.0004477653,0.0001272305],"domain_scores_gemma":[0.99620193,0.0009356102,0.00033671065,0.0015535081,0.00054283685,0.00042943444],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0023803068,0.002675892,0.0018117893,0.003559484,0.00089798943,0.0030362543,0.0045719324,0.0018735076,0.04125382],"category_scores_gemma":[0.008141506,0.0012357208,0.001488359,0.0038118549,0.0007935166,0.0029762166,0.0037069814,0.0017483484,0.037201118],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010033199,0.00015951015,0.003397758,0.0017291092,0.00036803205,0.00051470427,0.00021894298,0.008095439,0.009156789,0.005183636,0.9037449,0.06642791],"study_design_scores_gemma":[0.0011324281,0.00035776768,0.014807048,0.00050724373,0.00021056924,0.0020523935,0.0001669614,0.07783411,0.037703738,0.019814972,0.844926,0.00048670976],"about_ca_topic_score_codex":0.0062702973,"about_ca_topic_score_gemma":0.010845972,"teacher_disagreement_score":0.9954281,"about_ca_system_score_codex":0.0009999993,"about_ca_system_score_gemma":0.0020172824,"threshold_uncertainty_score":0.13800782},"labels":[],"label_agreement":null},{"id":"W3215549172","doi":"10.48550/arxiv.2111.12187","title":"Input Convex Gradient Networks","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Mathematics; Regular polygon; Parameterized complexity; Convex hull; Convex combination; Pure mathematics; Vector space; Balanced flow; Computer science; Geometry; Combinatorics; Mathematical analysis; Convex optimization","score_opus":0.15044413650334715,"score_gpt":0.24829550352961968,"score_spread":0.09785136702627253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215549172","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015224058,0.0003131638,0.97681046,0.0004902162,0.000045927187,0.000025618117,0.00025372484,0.00047651376,0.0063603614],"genre_scores_gemma":[0.7652337,0.001104209,0.21505931,0.0005187836,0.00015789385,0.00017909078,0.0007828092,0.000542922,0.016421292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99957114,0.00013231269,0.000020599318,0.0001360044,0.000094460294,0.000045392404],"domain_scores_gemma":[0.9991779,0.00032884665,0.000107598324,0.00015739506,0.00016104277,0.000067296336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082987465,0.0012921946,0.000752237,0.00051322416,0.00037689615,0.0015740066,0.0014376307,0.0012009339,0.0044905967],"category_scores_gemma":[0.004579669,0.0004897504,0.0006761865,0.0005240391,0.0016030609,0.0034575462,0.0015565353,0.0019474233,0.000804905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008007748,0.00003149726,0.0010337739,0.00016047763,0.00006581317,0.00015534856,0.00015361192,0.41893798,0.003790405,0.5164539,0.00418517,0.054951932],"study_design_scores_gemma":[0.0000053997733,0.000021283668,0.0001755156,0.000019578489,0.000010608612,0.00004582647,0.000013163442,0.8239293,0.0011680798,0.17208226,0.0025201992,0.000008843715],"about_ca_topic_score_codex":0.0024057364,"about_ca_topic_score_gemma":0.0026613746,"teacher_disagreement_score":0.0044905967,"about_ca_system_score_codex":0.0014721951,"about_ca_system_score_gemma":0.0006030385,"threshold_uncertainty_score":0.015022516},"labels":[],"label_agreement":null},{"id":"W3216140919","doi":"10.1002/brb3.2433","title":"Frontal interhemispheric structural connectivity, attention, and executive function in children with perinatal stroke","year":2021,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; Alberta Innovates; Heart and Stroke Foundation of Canada","keywords":"Executive dysfunction; Tractography; Stroke (engine); White matter; Cognition; Diffusion MRI; Psychology; Executive functions; Attention deficit hyperactivity disorder; Rating scale; Frontal lobe; Neuroimaging; Medicine; Neuroscience; Clinical psychology; Neuropsychology; Magnetic resonance imaging; Developmental psychology; Radiology","score_opus":0.01785670701827037,"score_gpt":0.2981783903366468,"score_spread":0.2803216833183764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216140919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996006,0.000109005305,0.00003509948,0.000015892147,9.175429e-7,0.000002504874,0.00008616584,0.0000014945864,0.00014826473],"genre_scores_gemma":[0.9994382,0.00019644616,0.000103248516,0.000008733841,0.0000016968502,0.000006085539,0.00012919291,0.0000014753912,0.00011481038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998584,0.000027661006,0.00001657967,0.00003429816,0.000031193675,0.000031801785],"domain_scores_gemma":[0.99961615,0.00007954006,0.00018675801,0.000021003585,0.00003860793,0.000057932728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002742407,0.0002606741,0.00023484991,0.00084619236,0.0002918669,0.00039266923,0.00022364463,0.00026240764,0.0010027827],"category_scores_gemma":[0.0013028751,0.0001910411,0.00018075334,0.00058914337,0.00033633132,0.00027425247,0.00029775457,0.00032273575,0.00013324963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007331466,0.00003363229,0.9960294,0.000010480384,0.000026763824,0.00043240498,0.00026108252,0.000050121813,0.000710186,0.000028847277,0.000045924367,0.0022978436],"study_design_scores_gemma":[0.0000010043759,0.000039772567,0.99911803,0.000004484329,0.000010099435,0.0003911501,0.00020926945,0.000049101982,0.000124148,0.000016560647,0.000035139725,0.000001137839],"about_ca_topic_score_codex":0.018469442,"about_ca_topic_score_gemma":0.020297766,"teacher_disagreement_score":0.018469442,"about_ca_system_score_codex":0.00039708932,"about_ca_system_score_gemma":0.0002855732,"threshold_uncertainty_score":0.03672391},"labels":[],"label_agreement":null},{"id":"W3216458294","doi":"10.1016/j.compbiomed.2021.105090","title":"Dual feature correlation guided multi-task learning for Alzheimer's disease prediction","year":2021,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Liaoning Revitalization Talents Program; National Natural Science Foundation of China","keywords":"Correlation; Computer science; Artificial intelligence; Cognition; Alzheimer's Disease Neuroimaging Initiative; Machine learning; Neuroimaging; Multi-task learning; Feature (linguistics); Task (project management); Curse of dimensionality; Pattern recognition (psychology); Cognitive impairment; Psychology; Mathematics; Neuroscience","score_opus":0.07918633278049354,"score_gpt":0.4018860805692192,"score_spread":0.3226997477887257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216458294","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25948623,0.0061798757,0.7242364,0.0014311332,0.000480611,0.0001942735,0.0021782804,0.0036549848,0.002158263],"genre_scores_gemma":[0.89474565,0.0007620256,0.09722678,0.00056701864,0.00029199044,0.00016617356,0.0024958802,0.00011691091,0.0036275885],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936825,0.00016853878,0.000045015157,0.00018083451,0.00008757588,0.00014977717],"domain_scores_gemma":[0.99825877,0.0009467448,0.00011823722,0.00016363252,0.0003674348,0.00014505086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021203372,0.0015294228,0.0019671463,0.0014525591,0.00065389625,0.0009830283,0.0015366933,0.0022626133,0.0015464843],"category_scores_gemma":[0.0036246188,0.00043181836,0.0015082798,0.0011585117,0.00037209596,0.0009114332,0.0014010846,0.0020146852,0.0009438247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027149084,0.002128001,0.016346315,0.00030892523,0.00070869643,0.0005267361,0.00011516797,0.11912853,0.023692701,0.001530056,0.01817703,0.814623],"study_design_scores_gemma":[0.000048985192,0.00025768406,0.0026436432,0.00001896655,0.00011426268,0.00014989039,0.000022646276,0.98818725,0.005196104,0.0024552676,0.00087943743,0.000025878304],"about_ca_topic_score_codex":0.0064481883,"about_ca_topic_score_gemma":0.007148841,"teacher_disagreement_score":0.0064481883,"about_ca_system_score_codex":0.00046302774,"about_ca_system_score_gemma":0.0015051457,"threshold_uncertainty_score":0.012821317},"labels":[],"label_agreement":null},{"id":"W3216761169","doi":"10.1177/02841851211056471","title":"Factors associated with brain white matter damage in type 2 diabetes mellitus: a tract-based spatial statistics study","year":2021,"lang":"en","type":"article","venue":"Acta Radiologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Corpus callosum; Fractional anisotropy; White matter; Internal medicine; Cardiology; Fasciculus; Diabetes mellitus; Type 2 Diabetes Mellitus; Superior longitudinal fasciculus; Diffusion MRI; Body mass index; Blood pressure; Corona radiata (embryology); Audiology; Pathology; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.07034474516005974,"score_gpt":0.32769987980378895,"score_spread":0.2573551346437292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216761169","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99856734,0.00012600663,0.0010096051,0.00002394738,0.0000021187802,0.0000044043177,0.00016639382,0.000008778031,0.00009146717],"genre_scores_gemma":[0.998973,0.000051839077,0.00067731005,0.0000038593303,0.000005804032,0.000004810321,0.00022780629,0.0000038641547,0.00005168299],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997534,0.00010564656,0.000026169466,0.000054281147,0.000028790473,0.00003164314],"domain_scores_gemma":[0.99860126,0.0005087137,0.00047091558,0.00015786255,0.00009558297,0.00016564816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008055296,0.00027288758,0.00031501826,0.0011381903,0.0002700509,0.0004348831,0.00021159626,0.0002367736,0.001301162],"category_scores_gemma":[0.0021721201,0.00012659366,0.0006888118,0.0011518114,0.00027114764,0.0002504837,0.00035079673,0.0001896344,0.00013673185],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003691777,0.00003340141,0.9924689,0.000016662294,0.0002290691,0.00017424133,0.00006721408,0.00073098444,0.0012961878,0.000054554734,0.000094503,0.0044650915],"study_design_scores_gemma":[0.000011523689,0.0001742663,0.98591655,0.0000087540775,0.00014785911,0.00081056857,0.00018054605,0.01202453,0.00034660398,0.00019005539,0.00017939782,0.0000094506495],"about_ca_topic_score_codex":0.0051678224,"about_ca_topic_score_gemma":0.004623146,"teacher_disagreement_score":0.0051678224,"about_ca_system_score_codex":0.00021189547,"about_ca_system_score_gemma":0.00035838422,"threshold_uncertainty_score":0.010275483},"labels":[],"label_agreement":null},{"id":"W33447915","doi":"10.1007/s00234-021-02635-9","title":"288. 炎症性動脈硬化指標と生活習慣における検討 : 飲酒、喫煙、運動、食習慣(栄養・消化,一般口演,第63回日本体力医学会大会)","year":2008,"lang":"en","type":"article","venue":"体力科學","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FedDev Ontario; Mitacs","keywords":"Computer science","score_opus":0.17646132887085025,"score_gpt":0.3917036621466515,"score_spread":0.21524233327580122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W33447915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68842113,0.0060161394,0.15274012,0.0033463757,0.0010002425,0.0003406181,0.0017781095,0.0010045347,0.14535272],"genre_scores_gemma":[0.9362763,0.0009889768,0.039445624,0.0003326663,0.00013713786,0.0000653421,0.0005935613,0.000121413905,0.02203885],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995838,0.00006384182,0.000031926742,0.00011078752,0.0001734188,0.000036238303],"domain_scores_gemma":[0.9988159,0.00044471724,0.00013037228,0.00009441512,0.00045371323,0.00006089356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010559512,0.00027098635,0.00021500456,0.00072297273,0.00047917865,0.0006199982,0.0003669413,0.00065646577,0.008642281],"category_scores_gemma":[0.0024014441,0.00017780616,0.00023687114,0.00037401734,0.001684605,0.0007791262,0.00032523516,0.00046636103,0.0026605888],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015754191,0.00026465053,0.047802683,0.0012341195,0.00020209218,0.003774465,0.0019058429,0.0076543214,0.33200023,0.06850986,0.02236639,0.51270986],"study_design_scores_gemma":[0.00021023685,0.00086580525,0.19280577,0.00023936584,0.00025309005,0.01818815,0.0011809127,0.040645,0.5822885,0.06163683,0.10143286,0.00025345804],"about_ca_topic_score_codex":0.0033195538,"about_ca_topic_score_gemma":0.00508394,"teacher_disagreement_score":0.008642281,"about_ca_system_score_codex":0.0007663205,"about_ca_system_score_gemma":0.0006378593,"threshold_uncertainty_score":0.028911352},"labels":[],"label_agreement":null},{"id":"W38132263","doi":"10.3390/diagnostics13243679","title":"桃李不言 大音希声——记叶世昌先生对中国货币史的研究","year":2008,"lang":"en","type":"article","venue":"钱币博览","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.18060222629279177,"score_gpt":0.3952616925043475,"score_spread":0.21465946621155574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W38132263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936633,0.0016639226,0.0030517401,0.000105706116,0.000019678106,0.00001922965,0.00020298563,0.000019842202,0.0012535943],"genre_scores_gemma":[0.9948815,0.00037380616,0.0043329964,0.000025371806,0.000020056821,0.000010874754,0.00013950077,0.0000033948102,0.00021254375],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998166,0.00004269566,0.000029328436,0.000057532852,0.000034582627,0.00001931372],"domain_scores_gemma":[0.9992549,0.0001856678,0.00028243594,0.00007513105,0.0001345768,0.00006726873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008016618,0.00036241088,0.00029991672,0.00093449414,0.0003276808,0.0005462226,0.00018091316,0.00030876315,0.0011584846],"category_scores_gemma":[0.002086151,0.00012714653,0.00022777582,0.000601048,0.0005096525,0.0006508364,0.00020898151,0.00022826409,0.0002893357],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001236962,0.00019142086,0.7023879,0.0004717581,0.0004767249,0.0009556633,0.0010382776,0.00083192857,0.083357066,0.0010100576,0.0007571481,0.20728496],"study_design_scores_gemma":[0.000039809325,0.0010382716,0.9652938,0.00005208198,0.0002169799,0.007838189,0.0007185658,0.0017280424,0.017898334,0.0018839437,0.0032482399,0.000043703607],"about_ca_topic_score_codex":0.0017120162,"about_ca_topic_score_gemma":0.0029972242,"teacher_disagreement_score":0.0017120162,"about_ca_system_score_codex":0.00021990576,"about_ca_system_score_gemma":0.00027727653,"threshold_uncertainty_score":0.0042396784},"labels":[],"label_agreement":null},{"id":"W4200038265","doi":"10.1016/j.jneumeth.2021.109435","title":"A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved: A 20-year perspective","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Tractography; Computer science; Modalities; Human Connectome Project; Connectomics; False positive paradox; Data science; Psychology; Artificial intelligence; Diffusion MRI; Connectome; Functional connectivity; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.39824712150147756,"score_gpt":0.5446234452325527,"score_spread":0.14637632373107512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200038265","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026081858,0.9855886,0.0027783432,0.00865869,0.0018693891,0.0002062737,0.00015555172,0.000021873275,0.0004603302],"genre_scores_gemma":[0.0049315174,0.9770582,0.010333109,0.005042897,0.0013002306,0.0007520436,0.00028850877,0.00004180513,0.00025172633],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.928076,0.0296474,0.028443046,0.0035286038,0.009325608,0.0009794832],"domain_scores_gemma":[0.53576934,0.34263808,0.032131124,0.012376369,0.07481151,0.0022735626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.17286892,0.0020110616,0.007181834,0.020101983,0.002120172,0.010225696,0.005487778,0.0066392007,0.0029761516],"category_scores_gemma":[0.39075267,0.0022334813,0.0073720934,0.015855901,0.0041404334,0.010590936,0.005985574,0.0066245776,0.0014004717],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003710659,0.000070617985,0.0014100072,0.37257022,0.0041464516,0.00022596192,0.0016746167,0.00056318054,0.0010254754,0.009575658,0.026778884,0.5815879],"study_design_scores_gemma":[0.000070304275,0.00019167869,0.002222883,0.8269015,0.007103237,0.0003222055,0.00078213925,0.00034940706,0.00046486527,0.009299421,0.15219598,0.00009636574],"about_ca_topic_score_codex":0.012551172,"about_ca_topic_score_gemma":0.038605258,"teacher_disagreement_score":0.17286892,"about_ca_system_score_codex":0.010336899,"about_ca_system_score_gemma":0.04409242,"threshold_uncertainty_score":0.91422915},"labels":[],"label_agreement":null},{"id":"W4200205313","doi":"10.1002/nbm.4685","title":"Validation of cardiac diffusion tensor imaging sequences: A multicentre test–retest phantom study","year":2021,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Office of AIDS Research; NIHR Oxford Biomedical Research Centre; National Heart, Lung, and Blood Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute of Biomedical Imaging and Bioengineering; British Heart Foundation; National Institute for Health and Care Research","keywords":"Reproducibility; Repeatability; Diffusion MRI; Imaging phantom; Fractional anisotropy; Materials science; Biomedical engineering; Nuclear medicine; Nuclear magnetic resonance; Artifact (error); Analytical Chemistry (journal); Medicine; Chemistry; Magnetic resonance imaging; Computer science; Radiology; Physics; Artificial intelligence; Chromatography","score_opus":0.04574986128022169,"score_gpt":0.3680587431632073,"score_spread":0.3223088818829856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200205313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9586209,0.0007869161,0.037999,0.000101522506,0.00013982118,0.0005341227,0.00035999037,0.00032685208,0.0011307508],"genre_scores_gemma":[0.9631021,0.00022036543,0.032870248,0.00021406224,0.000065263135,0.0006715041,0.0010117647,0.00033704782,0.0015077069],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9776669,0.011925531,0.0014707474,0.0049674027,0.0034412968,0.00052820216],"domain_scores_gemma":[0.944018,0.023256814,0.0068769925,0.01341356,0.011451237,0.0009835652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027150692,0.0014578174,0.0010447378,0.00081520714,0.00082008325,0.0010880699,0.0013263229,0.0015302021,0.00062182854],"category_scores_gemma":[0.04724441,0.0010599802,0.0010986851,0.00088350836,0.0018244149,0.0008964779,0.001177371,0.0010367408,0.0006471046],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.014212592,0.005494485,0.15960154,0.00071949005,0.003462646,0.00054741965,0.012432331,0.0114564495,0.7197664,0.0007215384,0.0016234674,0.06996172],"study_design_scores_gemma":[0.001374146,0.06449839,0.6541159,0.00013192902,0.0030003004,0.0028613387,0.0014887288,0.02901647,0.22786714,0.000797049,0.014295271,0.00055337435],"about_ca_topic_score_codex":0.0023787913,"about_ca_topic_score_gemma":0.0036980584,"teacher_disagreement_score":0.027150692,"about_ca_system_score_codex":0.00089215604,"about_ca_system_score_gemma":0.00072678144,"threshold_uncertainty_score":0.1435883},"labels":[],"label_agreement":null},{"id":"W4200321350","doi":"10.1093/cercor/bhab439","title":"Spatial probability maps of the segments of the postcentral sulcus in the human brain","year":2021,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Postcentral gyrus; Somatosensory system; Sulcus; Central sulcus; Anatomy; Functional magnetic resonance imaging; Magnetic resonance imaging; Parietal lobe; Cortex (anatomy); Neuroscience; Psychology; Biology; Medicine; Motor cortex; Radiology","score_opus":0.04755524965718038,"score_gpt":0.32514418009237955,"score_spread":0.27758893043519917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200321350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80647254,0.0019648669,0.17344534,0.00049581827,0.000040886247,0.00022333261,0.006930662,0.0016257425,0.008800876],"genre_scores_gemma":[0.97636527,0.0005232152,0.020222919,0.00002109726,0.000028464345,0.000099068755,0.001776464,0.0001413346,0.00082214695],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997905,0.000045497633,0.00001528119,0.000054392294,0.00006884945,0.00002549391],"domain_scores_gemma":[0.99807954,0.0011705761,0.00023716786,0.00012425588,0.00033852222,0.000049990063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075688306,0.00027794298,0.0001803983,0.0031483485,0.00021975717,0.0011296667,0.0002467546,0.00034124186,0.0032205577],"category_scores_gemma":[0.0057553547,0.00018972537,0.00032176828,0.001961824,0.0005233081,0.0006780099,0.0004647986,0.00022130305,0.0004986687],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039527165,0.00015710657,0.16725844,0.000957618,0.0004410404,0.001528863,0.0035142978,0.17267214,0.052183524,0.030031705,0.013313226,0.55398935],"study_design_scores_gemma":[0.0001049086,0.00033499018,0.7021201,0.00011586262,0.0001654876,0.003851386,0.00087995856,0.20500664,0.01873812,0.055303417,0.013186294,0.00019285177],"about_ca_topic_score_codex":0.0054822327,"about_ca_topic_score_gemma":0.0037091891,"teacher_disagreement_score":0.0054822327,"about_ca_system_score_codex":0.00036755504,"about_ca_system_score_gemma":0.00055298494,"threshold_uncertainty_score":0.010900617},"labels":[],"label_agreement":null},{"id":"W4200330348","doi":"10.1016/j.pscychresns.2021.111428","title":"Four-modality imaging of unmedicated subjects with schizophrenia: 18F-fluorodeoxyglucose and 18F-fallypride PET, diffusion tensor imaging, and MRI","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Neuroscience; Dopaminergic; Magnetic resonance imaging; Medicine; Dopamine; Radiology","score_opus":0.05762162498280654,"score_gpt":0.37071795394895124,"score_spread":0.3130963289661447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200330348","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988782,0.0003906641,0.00016340055,0.000055115586,0.0000036979939,0.000013417134,0.00014861935,0.000005444545,0.00034150665],"genre_scores_gemma":[0.9986941,0.0003626691,0.00042660543,0.000051749877,0.000009001017,0.000010989317,0.00016555902,0.0000031664897,0.0002760966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993634,0.000014809157,0.000008080846,0.000013685029,0.000012301037,0.000014822325],"domain_scores_gemma":[0.999874,0.000029740422,0.000031545467,0.000011309193,0.000026284255,0.00002703141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035330854,0.0003300772,0.00027841268,0.00066152215,0.00034537536,0.00041662314,0.00017999917,0.00051917124,0.0006421972],"category_scores_gemma":[0.0005828389,0.00020467097,0.00014988927,0.0002607196,0.000272206,0.00045554296,0.00018258496,0.000232593,0.00016287861],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007888889,0.00063474476,0.8343966,0.00017672312,0.00023376112,0.004475659,0.0017658622,0.00050673104,0.11824377,0.00018435116,0.00060975837,0.030883215],"study_design_scores_gemma":[0.00005187557,0.0004567367,0.9937383,0.000009183806,0.000054853896,0.0016894748,0.0004860646,0.00050821004,0.0026616228,0.000096073105,0.00023594787,0.000011679803],"about_ca_topic_score_codex":0.0171274,"about_ca_topic_score_gemma":0.028459854,"teacher_disagreement_score":0.0171274,"about_ca_system_score_codex":0.00044638242,"about_ca_system_score_gemma":0.0004645156,"threshold_uncertainty_score":0.03405541},"labels":[],"label_agreement":null},{"id":"W4200417977","doi":"10.1007/s00406-021-01363-8","title":"Cognitive and functional deficits are associated with white matter abnormalities in two independent cohorts of patients with schizophrenia","year":2021,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Ludwig-Maximilians-Universität München","keywords":"Schizophrenia (object-oriented programming); White matter; Psychology; Cognition; Clinical psychology; Psychiatry; Medicine; Developmental psychology; Magnetic resonance imaging","score_opus":0.03436377019830333,"score_gpt":0.3209828638814905,"score_spread":0.28661909368318716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200417977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998246,0.000014859971,0.000019482368,0.000005234814,0.0000011786709,0.0000058978417,0.00008888315,9.3261525e-7,0.000039014096],"genre_scores_gemma":[0.99930334,0.000024044282,0.0000531728,0.000009784727,0.0000034123389,0.000015936146,0.0005304832,0.0000020776063,0.000057806774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995352,0.00006376698,0.0000617278,0.00015365696,0.00010135398,0.00008430095],"domain_scores_gemma":[0.9988331,0.00012438408,0.0004696127,0.00013798874,0.0001262554,0.00030871973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061756076,0.00093221886,0.0006060595,0.0016758282,0.0011434838,0.0007308603,0.0004524722,0.0007222642,0.0012582144],"category_scores_gemma":[0.0019836512,0.00041811875,0.00068171043,0.0007648166,0.0007587199,0.00038073852,0.0015250107,0.00069067575,0.00026733062],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011663216,0.00013451786,0.9920431,0.000012072008,0.00016151322,0.00041473756,0.0006698279,0.00006726634,0.0039137863,0.000029897406,0.00009032015,0.0012965909],"study_design_scores_gemma":[0.000025631518,0.00011889003,0.99903154,0.00000273284,0.00003217704,0.0003621067,0.00019457328,0.00007256928,0.00009555141,0.000021086486,0.000037766797,0.000005318833],"about_ca_topic_score_codex":0.00993263,"about_ca_topic_score_gemma":0.008779446,"teacher_disagreement_score":0.00993263,"about_ca_system_score_codex":0.00053861825,"about_ca_system_score_gemma":0.00048202838,"threshold_uncertainty_score":0.019749641},"labels":[],"label_agreement":null},{"id":"W4200455317","doi":"10.1101/2021.10.27.466088","title":"White matter microstructural integrity across the adult lifespan: Combined perspective of diffusion tensor and kurtosis imaging","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Canada Research Chairs; Compute Canada","keywords":"Kurtosis; Diffusion MRI; Thermal diffusivity; White matter; Fractional anisotropy; Gaussian; Diffusion; Statistical physics; Statistics; Physics; Mathematics; Medicine; Magnetic resonance imaging; Thermodynamics; Radiology","score_opus":0.01770437538986872,"score_gpt":0.2846548328734352,"score_spread":0.26695045748356644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200455317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94536847,0.0063114353,0.040428218,0.0012851901,0.00008115822,0.000019441097,0.0014841814,0.00027341367,0.004748645],"genre_scores_gemma":[0.977001,0.0021505277,0.01939884,0.00009559244,0.00011137372,0.000011823147,0.00035593432,0.000053094,0.0008218401],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998086,0.00005325268,0.000015511401,0.000057477442,0.00004797298,0.000017170341],"domain_scores_gemma":[0.99894446,0.00022059875,0.0004152855,0.00011488965,0.00020434296,0.00010048089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010242586,0.00059382303,0.0004852016,0.0020739331,0.00018412048,0.0012935158,0.00018991415,0.0004182447,0.0010788399],"category_scores_gemma":[0.0023638313,0.00019905536,0.00031754177,0.0008780546,0.00058762054,0.001559504,0.0007912212,0.0005362552,0.00019537138],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085554976,0.00017595796,0.41794685,0.000735223,0.0016996684,0.0017443753,0.0021055003,0.01426035,0.3209374,0.01098846,0.004754167,0.22379643],"study_design_scores_gemma":[0.000018351904,0.0004836884,0.9076155,0.00024088698,0.00043036838,0.0029249117,0.0011280519,0.032326758,0.03268528,0.01615852,0.00589082,0.000096888536],"about_ca_topic_score_codex":0.001510338,"about_ca_topic_score_gemma":0.0029410545,"teacher_disagreement_score":0.0020739331,"about_ca_system_score_codex":0.0002443502,"about_ca_system_score_gemma":0.00029186773,"threshold_uncertainty_score":0.00541687},"labels":[],"label_agreement":null},{"id":"W4200483886","doi":"10.1088/1361-6560/ac46de","title":"Biophysical compartment models for single-shell diffusion MRI in the human brain: a model fitting comparison","year":2021,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University Health Network; University of Toronto; McMaster University; University of Alberta; University of British Columbia; St. Joseph’s Healthcare Hamilton; Canadian Imperial Bank of Commerce (Canada); University of Calgary; Baycrest Hospital","funders":"National Center for Research Resources; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Markov chain Monte Carlo; Fractional anisotropy; Weighting; Computer science; Bayesian probability; Isotropy; Algorithm; Artificial intelligence; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.537934954370117,"score_gpt":0.4927854029736477,"score_spread":0.045149551396469256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200483886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1223485,0.0023498086,0.87087125,0.00045303398,0.00006826191,0.00026588616,0.0007438069,0.0013694983,0.0015299335],"genre_scores_gemma":[0.66275615,0.003815824,0.32409328,0.00036217133,0.000061528415,0.0011483916,0.0027974294,0.001370568,0.0035946106],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994313,0.00027438876,0.000041599124,0.00013980154,0.000081216145,0.00003161159],"domain_scores_gemma":[0.9978598,0.0015150015,0.00015443069,0.00016471044,0.000252198,0.000053930995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029857203,0.001189847,0.0010638954,0.0010161452,0.000371114,0.0013093974,0.0015095084,0.0014416381,0.0013479141],"category_scores_gemma":[0.010534562,0.00062670046,0.0015814368,0.0009401548,0.00036202156,0.0015752151,0.00071528053,0.0009907141,0.00082057546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009961895,0.00017824219,0.0064732293,0.00070259033,0.0009470363,0.00029125906,0.0007960036,0.87459767,0.012349769,0.008314621,0.002349556,0.09200393],"study_design_scores_gemma":[0.000028347837,0.00009307742,0.0012617009,0.00004083993,0.0000869162,0.0001436069,0.000039489638,0.9896653,0.0013646345,0.00602943,0.0011921941,0.000054527987],"about_ca_topic_score_codex":0.011964204,"about_ca_topic_score_gemma":0.010202402,"teacher_disagreement_score":0.011964204,"about_ca_system_score_codex":0.0011348083,"about_ca_system_score_gemma":0.0019565262,"threshold_uncertainty_score":0.023789108},"labels":[],"label_agreement":null},{"id":"W4200493340","doi":"10.1101/2021.12.07.471599","title":"Enabling complex fibre geometries using 3D printed axon-mimetic phantoms","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Imaging phantom; Diffusion MRI; Orientation (vector space); Curvature; Kurtosis; Ground truth; Thermal diffusivity; Physics; Geometry; Nuclear magnetic resonance; Materials science; Artificial intelligence; Mathematics; Optics; Computer science; Magnetic resonance imaging; Statistics","score_opus":0.08271906865514647,"score_gpt":0.3199696242514774,"score_spread":0.23725055559633093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200493340","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32492256,0.0006919682,0.66163605,0.00032626453,0.00018643061,0.0002749423,0.0006558597,0.004581746,0.006724245],"genre_scores_gemma":[0.6176662,0.00066228025,0.37400046,0.00020577974,0.00003099683,0.00044829946,0.00051134167,0.0005682454,0.005906373],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996762,0.000053670403,0.000023909173,0.000058463378,0.00016418396,0.000023496777],"domain_scores_gemma":[0.9986858,0.00058342994,0.0003067374,0.0002367258,0.00013015643,0.000057221194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009074883,0.00067011965,0.00025835028,0.000603546,0.00020117538,0.0008631373,0.0005817838,0.000723937,0.0017359481],"category_scores_gemma":[0.0021385879,0.00054376165,0.00043397187,0.00033563704,0.0004612674,0.00070704473,0.00064246595,0.00049218565,0.00077691127],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016447774,0.000077566,0.00096624607,0.00021718789,0.000027850838,0.0005517862,0.00022771949,0.036184594,0.93316805,0.0029080305,0.0007510399,0.024755469],"study_design_scores_gemma":[0.000025785446,0.00028403447,0.0015863979,0.000026248044,0.000032206368,0.00064914156,0.000042931075,0.069899954,0.9144396,0.0011584555,0.01179598,0.000059240643],"about_ca_topic_score_codex":0.00051264354,"about_ca_topic_score_gemma":0.0008267203,"teacher_disagreement_score":0.0017359481,"about_ca_system_score_codex":0.00053337426,"about_ca_system_score_gemma":0.00036909882,"threshold_uncertainty_score":0.00580734},"labels":[],"label_agreement":null},{"id":"W4200493474","doi":"10.1101/2021.12.17.473211","title":"Amyloid-PET of the white matter: relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Université de Montréal; Hotchkiss Brain Institute; Université Laval; University of Calgary; Sunnybrook Health Science Centre; Jewish General Hospital; Baycrest Hospital; McGill University; Montreal Heart Institute; University of British Columbia; Western University; University of Toronto; Université de Sherbrooke; McMaster University; Montreal Neurological Institute and Hospital; Lawson Health Research Institute","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Free water; Diffusion MRI; Positron emission tomography; Hyperintensity; Neuroscience; Psychology; Alzheimer's disease; Pathology; Medicine; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.023179154392127223,"score_gpt":0.2449430478635914,"score_spread":0.22176389347146416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200493474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996094,0.0001270843,0.0000744054,0.000006644303,0.0000024510064,0.0000042362844,0.00006993947,0.0000017958953,0.00010403653],"genre_scores_gemma":[0.9997855,0.000029035731,0.000049616734,0.0000055515,0.0000034767677,0.000003893153,0.00007492588,6.101513e-7,0.0000474194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997323,0.0000663403,0.000045283057,0.000076072654,0.00004702572,0.00003284947],"domain_scores_gemma":[0.9993886,0.00015732185,0.00021406097,0.000059926457,0.00008090176,0.000099118566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007384596,0.000573869,0.0005559283,0.0008930312,0.0005402,0.00065881107,0.00029869,0.000651317,0.0008996367],"category_scores_gemma":[0.0023342574,0.00029396106,0.00037388474,0.0006638068,0.00026845647,0.00039506904,0.00043289695,0.0004736646,0.00017810428],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006423139,0.00009032988,0.99677604,0.000015316245,0.0001239526,0.00019831707,0.00010230855,0.00010891385,0.0006813682,0.000014176509,0.00003362138,0.001213319],"study_design_scores_gemma":[0.00002117382,0.00029940958,0.99802965,0.0000052644214,0.00008308715,0.0005302236,0.00013139634,0.0005635867,0.00018557125,0.00006848126,0.000077447876,0.00000470333],"about_ca_topic_score_codex":0.0024861689,"about_ca_topic_score_gemma":0.0023657244,"teacher_disagreement_score":0.0024861689,"about_ca_system_score_codex":0.00020770876,"about_ca_system_score_gemma":0.00018661647,"threshold_uncertainty_score":0.004943371},"labels":[],"label_agreement":null},{"id":"W4200552231","doi":"10.31234/osf.io/7xcun","title":"Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Universitetet i Oslo; Wellcome Trust; British Heart Foundation; Academy of Medical Sciences; Diabetes UK; Alzheimer's Society","keywords":"Demography; Body mass index; Cohort; Waist–hip ratio; Risk factor; Menopause; Obesity; Medicine; Gerontology; Waist; Psychology; Internal medicine","score_opus":0.05854564324355751,"score_gpt":0.3373226994688593,"score_spread":0.2787770562253018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200552231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99278224,0.000798965,0.00012162451,0.00007841413,0.000015957361,0.000013400116,0.005714532,0.0000089580235,0.00046590282],"genre_scores_gemma":[0.99404764,0.00047704994,0.00015160102,0.00007253212,0.000020437563,0.00005646233,0.0043594255,0.000008530481,0.00080636994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99950516,0.00008805354,0.000074505195,0.00017842912,0.00006229394,0.00009161998],"domain_scores_gemma":[0.99885535,0.0001151097,0.0005108963,0.00023125617,0.0001482981,0.00013910195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000550924,0.00032310764,0.0005705087,0.0007289307,0.00037023073,0.00054226146,0.00037287438,0.0006216961,0.002687823],"category_scores_gemma":[0.0019119667,0.0005101023,0.0005469733,0.0010926703,0.00022743683,0.00046784795,0.0008080651,0.000473661,0.00047615083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060375937,0.000025176862,0.9930474,0.00006578029,0.00024450882,0.00021299627,0.0003849276,0.00007559389,0.0008963378,0.000083884464,0.0021491467,0.0022104303],"study_design_scores_gemma":[0.000011103084,0.000021791047,0.9993931,0.000014716282,0.000030262445,0.000111783964,0.00005789009,0.00004660631,0.000021678497,0.000015732625,0.00027136639,0.0000038933545],"about_ca_topic_score_codex":0.037607986,"about_ca_topic_score_gemma":0.035809495,"teacher_disagreement_score":0.037607986,"about_ca_system_score_codex":0.00037335846,"about_ca_system_score_gemma":0.00022409094,"threshold_uncertainty_score":0.0747782},"labels":[],"label_agreement":null},{"id":"W4200578182","doi":"10.1101/2021.12.17.472836","title":"Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; Massachusetts General Hospital","keywords":"Human Connectome Project; Tractography; Computer science; Diffusion MRI; Robustness (evolution); Connectome; Artificial intelligence; Voxel; Data mining; Pattern recognition (psychology); Functional connectivity; Neuroscience; Magnetic resonance imaging; Psychology","score_opus":0.08035216910427097,"score_gpt":0.3338652420559231,"score_spread":0.25351307295165215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200578182","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012675344,0.0011253924,0.98342,0.0015685067,0.000057288238,0.00002456548,0.0001049552,0.00037711245,0.0006469399],"genre_scores_gemma":[0.15606737,0.0015951673,0.83927697,0.0003232414,0.0001684671,0.000102523656,0.00033897886,0.00069543696,0.0014318037],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987857,0.00058172696,0.00006235499,0.00021725333,0.0003049578,0.00004805259],"domain_scores_gemma":[0.99378514,0.003686135,0.00049353327,0.0009981452,0.0008059294,0.00023114654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053288937,0.0010426745,0.00096455816,0.0013192062,0.0005665546,0.002039376,0.0014646483,0.0015437728,0.0018214918],"category_scores_gemma":[0.021482931,0.00077809376,0.00051083654,0.0007941286,0.0017017679,0.0023616033,0.0018337109,0.0024337787,0.0008927836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046349008,0.00017866802,0.004948852,0.0009151681,0.00027107762,0.0003307588,0.00045874034,0.45252877,0.039465506,0.16158484,0.013228232,0.32562593],"study_design_scores_gemma":[0.000031384345,0.000045760036,0.0009080123,0.00008330085,0.000020793936,0.0001136261,0.00005104268,0.8573122,0.007435638,0.1292801,0.00468737,0.000030783984],"about_ca_topic_score_codex":0.0030891586,"about_ca_topic_score_gemma":0.0039418535,"teacher_disagreement_score":0.0053288937,"about_ca_system_score_codex":0.0009757892,"about_ca_system_score_gemma":0.0022997174,"threshold_uncertainty_score":0.028182209},"labels":[],"label_agreement":null},{"id":"W4200585223","doi":"10.1002/hbm.25697","title":"Prevalence of white matter pathways coming into a single white matter voxel orientation: The bottleneck issue in tractography","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; White matter; Voxel; Diffusion MRI; Neuroscience; Bottleneck; Human brain; Human Connectome Project; Orientation (vector space); Computer science; Artificial intelligence; Psychology; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging; Medicine; Mathematics; Geometry","score_opus":0.05801554952653782,"score_gpt":0.32155955402790426,"score_spread":0.26354400450136645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200585223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7992952,0.005261887,0.1921769,0.00064337655,0.00003589111,0.00006320544,0.00037783687,0.0005772332,0.0015684774],"genre_scores_gemma":[0.9732317,0.0008135163,0.02523071,0.000045591652,0.00006581201,0.000040040497,0.00025168608,0.00013308042,0.0001879484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.993806,0.0018458327,0.00067269895,0.0018464965,0.0013787927,0.00045018812],"domain_scores_gemma":[0.8960447,0.074774615,0.014843048,0.008693504,0.0042059766,0.001438108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012954383,0.00069107505,0.0014636883,0.005667395,0.00088274264,0.0021562972,0.0009149335,0.0016112109,0.0013002346],"category_scores_gemma":[0.08787694,0.000837888,0.00051182305,0.002558895,0.0030414865,0.0061801868,0.0029893934,0.0011407704,0.00046340819],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001595449,0.00016351798,0.655523,0.0011334788,0.0009008482,0.0011532517,0.0038421017,0.03076746,0.059826177,0.01681079,0.0015579807,0.22672601],"study_design_scores_gemma":[0.00008946875,0.00063930254,0.6734844,0.0006023301,0.000535572,0.011075171,0.0017212422,0.17757563,0.040465266,0.088326134,0.005195548,0.00028990005],"about_ca_topic_score_codex":0.001737691,"about_ca_topic_score_gemma":0.0013548357,"teacher_disagreement_score":0.012954383,"about_ca_system_score_codex":0.0008221654,"about_ca_system_score_gemma":0.00060132134,"threshold_uncertainty_score":0.068510175},"labels":[],"label_agreement":null},{"id":"W4205229274","doi":"10.1002/alz.051360","title":"Analysis of brain structural connectivity networks and white matter integrity in patients with mild cognitive impairment","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cognitive impairment; White matter; Fractional anisotropy; Diffusion MRI; Cognition; Psychology; Medicine; Nuclear medicine; Internal medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.02606042901082808,"score_gpt":0.31049336192514965,"score_spread":0.2844329329143216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205229274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993831,0.000056234592,0.00012019204,0.000011967841,0.0000012156163,0.0000066028815,0.00023628483,0.000005621231,0.00017877504],"genre_scores_gemma":[0.9995704,0.000017463106,0.00012943865,0.0000038309877,0.0000028712043,0.000008659205,0.00020927479,0.0000012727011,0.000056701465],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988806,0.000020666464,0.000013480694,0.00004323946,0.000016217859,0.000018368519],"domain_scores_gemma":[0.9996593,0.00008124481,0.00012375627,0.000035658526,0.00003934896,0.000060810165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002933113,0.00030183286,0.00027305077,0.0011058563,0.0003341706,0.00037491697,0.00022476692,0.00032653255,0.0012962087],"category_scores_gemma":[0.0014341964,0.000110863126,0.0002127011,0.00050110836,0.0002098971,0.00023436162,0.00031493718,0.00017555448,0.00014430443],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012395466,0.00010391536,0.9828935,0.000049850052,0.00024811047,0.00051244436,0.00041447865,0.0006451643,0.0041534468,0.00009328327,0.00034913904,0.009297021],"study_design_scores_gemma":[0.000010083214,0.000079075064,0.99833846,0.000002792498,0.000028728431,0.00024020347,0.000083192084,0.0008555694,0.00020059457,0.00008510467,0.000072361916,0.000003721497],"about_ca_topic_score_codex":0.0054894076,"about_ca_topic_score_gemma":0.008770079,"teacher_disagreement_score":0.0054894076,"about_ca_system_score_codex":0.00024311205,"about_ca_system_score_gemma":0.00018828726,"threshold_uncertainty_score":0.010914922},"labels":[],"label_agreement":null},{"id":"W4205515100","doi":"10.31979/etd.w5fp-ccq6","title":"Prediction of Financial Capacity using Diffusion Compartment Imaging","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Eisai; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Cingulum (brain); Neuropsychology; Magnetic resonance imaging; Psychology; Cardiology; Orientation (vector space); Dementia; Cognition; Medicine; Neuroscience; Audiology; Cognitive psychology; Fractional anisotropy; Internal medicine; Disease; Radiology; Mathematics","score_opus":0.10866506152888376,"score_gpt":0.3604616811346808,"score_spread":0.251796619605797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205515100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960484,0.00031186454,0.0019206381,0.000040190404,0.000006076431,0.00002130439,0.00034905592,0.000017732542,0.0012847193],"genre_scores_gemma":[0.9981007,0.00015426219,0.0011569266,0.000004359166,0.0000041406065,0.000010033643,0.00022597787,0.0000019822944,0.0003416179],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999064,0.000024748471,0.000011935026,0.000021646938,0.000018316934,0.000016919987],"domain_scores_gemma":[0.9994917,0.00016813222,0.00015867662,0.00003333712,0.00008473906,0.00006345053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005852573,0.000380968,0.0001890127,0.0018258446,0.00017560202,0.00068097963,0.00016851739,0.00031130033,0.0012920616],"category_scores_gemma":[0.0018905553,0.000101882804,0.0002704972,0.0006366264,0.00016993203,0.00041985215,0.00026355902,0.0002241497,0.00025784338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038971842,0.00009009047,0.96012837,0.00003945675,0.000111814436,0.00025593676,0.00015450035,0.0019695489,0.0042275363,0.00031101154,0.00034382232,0.03197812],"study_design_scores_gemma":[0.000020004376,0.0002750632,0.95957404,0.00004938398,0.00008729073,0.0010695335,0.00053752266,0.031998705,0.0042789276,0.0010578379,0.0010217553,0.00003000413],"about_ca_topic_score_codex":0.0052067987,"about_ca_topic_score_gemma":0.0041497163,"teacher_disagreement_score":0.0052067987,"about_ca_system_score_codex":0.0002271122,"about_ca_system_score_gemma":0.0001974136,"threshold_uncertainty_score":0.010352969},"labels":[],"label_agreement":null},{"id":"W4205639396","doi":"10.3389/fnins.2021.799576","title":"Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure","year":2022,"lang":"en","type":"review","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":233,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Research Manitoba; Health Sciences Centre Foundation","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Context (archaeology); Voxel; Thermal diffusivity; Neuroscience; Population; Tractography; Psychology; Medicine; Computer science; Artificial intelligence; Physics; Magnetic resonance imaging; Biology; Radiology","score_opus":0.041825050475849765,"score_gpt":0.3434758084675319,"score_spread":0.3016507579916821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205639396","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042553958,0.37420106,0.2586999,0.28797862,0.015465243,0.0006163771,0.0011564188,0.0007257674,0.018602692],"genre_scores_gemma":[0.3685173,0.15843171,0.34360904,0.104541086,0.017804772,0.0016147763,0.00047082457,0.0007839607,0.0042266813],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.8835197,0.084294066,0.009627918,0.007139732,0.014658025,0.00076050306],"domain_scores_gemma":[0.6703552,0.26424152,0.01597365,0.016884776,0.030917164,0.0016276988],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.17017382,0.001891015,0.002809545,0.0043867035,0.0018073734,0.0054847654,0.0045662806,0.005311792,0.0014871046],"category_scores_gemma":[0.31298462,0.001070047,0.0014885595,0.003994086,0.020320067,0.0078295125,0.0047694403,0.008939831,0.0012500278],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001376008,0.0001695362,0.05000746,0.010334701,0.0021375038,0.0018302648,0.018294647,0.0028221107,0.007486054,0.13860086,0.05362427,0.71331656],"study_design_scores_gemma":[0.00022292961,0.00079229055,0.042797066,0.015213502,0.0011572172,0.009035764,0.008139637,0.010573964,0.011079325,0.714776,0.18552488,0.0006874755],"about_ca_topic_score_codex":0.006320932,"about_ca_topic_score_gemma":0.007284821,"teacher_disagreement_score":0.8298262,"about_ca_system_score_codex":0.0022066117,"about_ca_system_score_gemma":0.00404065,"threshold_uncertainty_score":0.89997596},"labels":[],"label_agreement":null},{"id":"W4205716735","doi":"10.1002/alz.051190","title":"White matter microstructure and cognitive functioning across healthy older adults with different APOE alleles","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Apolipoprotein E; Fractional anisotropy; White matter; Psychology; Diffusion MRI; Cognition; Episodic memory; Alzheimer's Disease Neuroimaging Initiative; Medicine; Internal medicine; Neuroscience; Disease; Cognitive impairment; Magnetic resonance imaging","score_opus":0.024305911436220465,"score_gpt":0.31245738016338737,"score_spread":0.2881514687271669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205716735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995315,0.00014177524,0.000031745396,0.000009144096,0.0000026798812,0.0000060964003,0.00012949904,0.0000015111799,0.00014615491],"genre_scores_gemma":[0.9993593,0.00006214305,0.00007712961,0.000021787277,0.0000061895907,0.000008993409,0.0002122984,9.0694044e-7,0.0002512844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998276,0.000016709813,0.00003114952,0.00006744453,0.000027447704,0.000029682516],"domain_scores_gemma":[0.9995914,0.000031459473,0.00018740102,0.00003520956,0.00006438637,0.000090181005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003794202,0.0004806247,0.0003929242,0.0006214461,0.00048713776,0.0005331605,0.00018850839,0.0004441665,0.0016536926],"category_scores_gemma":[0.0008957291,0.00015745353,0.00034072401,0.0004380861,0.00029382264,0.000517147,0.0004366964,0.00027882785,0.00026327546],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002345021,0.00032349533,0.9861274,0.00005268069,0.00031144175,0.0002600392,0.0005650528,0.00006046994,0.0050608227,0.000054527816,0.00014010535,0.004698896],"study_design_scores_gemma":[0.000012940687,0.00031469844,0.9990778,0.0000041468033,0.0000393924,0.00012903367,0.00014180526,0.000037848884,0.00013720414,0.00004707181,0.00005567438,0.0000024761175],"about_ca_topic_score_codex":0.0036620782,"about_ca_topic_score_gemma":0.0050999005,"teacher_disagreement_score":0.0036620782,"about_ca_system_score_codex":0.00022244308,"about_ca_system_score_gemma":0.00014300423,"threshold_uncertainty_score":0.007281542},"labels":[],"label_agreement":null},{"id":"W4205861790","doi":"10.1002/alz.049730","title":"The combined influence of beta‐amyloid and vascular risk on prospective brain atrophy in clinically normal individuals","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Atrophy; Fractional anisotropy; Medicine; Cardiology; White matter; Pittsburgh compound B; Internal medicine; Hyperintensity; Cerebral amyloid angiopathy; Pathology; Psychology; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.0271120764827758,"score_gpt":0.3268977708647837,"score_spread":0.2997856943820079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205861790","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989165,0.00042439916,0.00012260473,0.000030227884,0.000005674113,0.0000027760193,0.00017757207,0.000007300067,0.00031288873],"genre_scores_gemma":[0.9995617,0.00006490787,0.00008127633,0.000008067572,0.000008848461,0.0000034398272,0.0001311304,0.0000027947788,0.00013775846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994766,0.00021260191,0.00003341597,0.00016204146,0.000058528232,0.000056863028],"domain_scores_gemma":[0.99814475,0.00067069446,0.00050351355,0.00028456873,0.00013353044,0.00026299513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088655937,0.000539557,0.00037196954,0.0005015965,0.0003963276,0.0007731116,0.0003339878,0.0004759913,0.0018056657],"category_scores_gemma":[0.0023554661,0.00031517958,0.000715721,0.0005246393,0.0003498916,0.00039078767,0.00048172227,0.0006058236,0.00025061937],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068751816,0.000033866818,0.9967379,0.0000076149818,0.0002530664,0.00011178966,0.00003640083,0.00009301823,0.00068883045,0.000022354754,0.000049571932,0.0012781222],"study_design_scores_gemma":[0.000003834885,0.000073970856,0.9993685,0.0000017680748,0.00007158454,0.00014968296,0.000018952192,0.0001557331,0.00007680273,0.000044794022,0.000032277712,0.0000020970851],"about_ca_topic_score_codex":0.0041485676,"about_ca_topic_score_gemma":0.006052279,"teacher_disagreement_score":0.0041485676,"about_ca_system_score_codex":0.00018655258,"about_ca_system_score_gemma":0.0002768903,"threshold_uncertainty_score":0.008248866},"labels":[],"label_agreement":null},{"id":"W4205927150","doi":"10.1101/2022.01.10.475656","title":"Microstructural Impairments in a Topologically Distinct Prefrontal-Habenular Connection in Cocaine Addiction","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Drug Abuse; Canadian Institutes of Health Research; Icahn School of Medicine at Mount Sinai","keywords":"Ventral tegmental area; Neuroscience; Addiction; Prefrontal cortex; Diffusion MRI; Psychology; Habenula; Internal capsule; Thalamus; Tractography; Disconnection; Ventral pallidum; White matter; Cognition; Globus pallidus; Dopamine; Basal ganglia; Medicine; Central nervous system; Dopaminergic","score_opus":0.02543391117313611,"score_gpt":0.28640703832978925,"score_spread":0.26097312715665316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205927150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969056,0.00019887356,0.0022187347,0.0000612411,0.000004021166,0.0000045523434,0.00016692317,0.000029902598,0.00041010734],"genre_scores_gemma":[0.9984363,0.00010327178,0.0010415419,0.000013567215,0.0000025345237,0.0000034412535,0.00009015749,0.000010147555,0.00029911703],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999951,0.000007963188,0.000004219335,0.000017309407,0.000010771573,0.000008877878],"domain_scores_gemma":[0.99983656,0.000018826147,0.000082152575,0.000019128014,0.00001502117,0.000028329127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016272337,0.00019519373,0.00014470817,0.000606551,0.00017891637,0.00030145698,0.000119703895,0.00019115223,0.0019417577],"category_scores_gemma":[0.00028301292,0.00014599031,0.0001087199,0.00022232477,0.00038123448,0.00023618467,0.0003874102,0.00023523268,0.00010267905],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089730124,0.00009742849,0.13224979,0.00015440799,0.0003052278,0.0011495587,0.00044704493,0.0013055471,0.84122175,0.0020911666,0.00039171398,0.019689066],"study_design_scores_gemma":[0.000014066185,0.00008991679,0.960107,0.000023943365,0.00007092115,0.0025414599,0.00018307829,0.004463524,0.030111717,0.001801278,0.0005788197,0.000014236228],"about_ca_topic_score_codex":0.0026922133,"about_ca_topic_score_gemma":0.0046468475,"teacher_disagreement_score":0.0026922133,"about_ca_system_score_codex":0.00021027109,"about_ca_system_score_gemma":0.00021341922,"threshold_uncertainty_score":0.006495893},"labels":[],"label_agreement":null},{"id":"W4205978437","doi":"10.3389/fnins.2021.638175","title":"Combined Structural MR and Diffusion Tensor Imaging Classify the Presence of Alzheimer’s Disease With the Same Performance as MR Combined With Amyloid Positron Emission Tomography: A Data Integration Approach","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Fundação para a Ciência e a Tecnologia; F. Hoffmann-La Roche; University of Southern California; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Artificial intelligence; Pattern recognition (psychology); Positron emission tomography; Support vector machine; Neuroimaging; Computer science; Classifier (UML); Feature selection; Modality (human–computer interaction); Magnetic resonance imaging; Nuclear medicine; Medicine; Radiology","score_opus":0.03241276084161613,"score_gpt":0.28934658956922693,"score_spread":0.2569338287276108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205978437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7540875,0.0021448634,0.23784368,0.00057016633,0.00012931936,0.00032829525,0.0013249805,0.0015670911,0.0020040965],"genre_scores_gemma":[0.86163557,0.00047235226,0.1352886,0.000066381865,0.00009839265,0.00020003975,0.0016939848,0.000100066565,0.0004445455],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983053,0.0005079065,0.00017700621,0.0004754363,0.00037526342,0.00015912013],"domain_scores_gemma":[0.9957575,0.0017990016,0.0005019006,0.00049939775,0.001222609,0.0002195013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006280857,0.0019905488,0.0017657737,0.0036940516,0.00055643934,0.001822822,0.0009517971,0.0010086534,0.0010736459],"category_scores_gemma":[0.008388799,0.00037376228,0.0025097332,0.002035006,0.0004322265,0.0015532322,0.0012810248,0.0013813496,0.0007116863],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022053104,0.0010233272,0.16161837,0.0003410156,0.0034934948,0.00018501801,0.0003131065,0.09645975,0.034695875,0.0006338544,0.0029903399,0.6960405],"study_design_scores_gemma":[0.00006316652,0.00083042897,0.06842291,0.00010730148,0.0013058073,0.00023406598,0.00025307192,0.9098296,0.01436701,0.003397493,0.0011044275,0.00008476848],"about_ca_topic_score_codex":0.002741346,"about_ca_topic_score_gemma":0.0043384605,"teacher_disagreement_score":0.006280857,"about_ca_system_score_codex":0.0007233077,"about_ca_system_score_gemma":0.00096169603,"threshold_uncertainty_score":0.033216715},"labels":[],"label_agreement":null},{"id":"W4206092563","doi":"10.1002/alz.056416","title":"Myelin integrity in older adults with vascular cognitive impairment: Implications for mobility performance","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Positive Living Society of British Columbia; University of British Columbia; Vancouver Coastal Health","funders":"","keywords":"White matter; Myelin; Neurology; Medicine; Psychology; Magnetic resonance imaging; Nuclear medicine; Internal medicine; Audiology; Neuroscience; Radiology; Central nervous system","score_opus":0.04503786162681742,"score_gpt":0.3370960401804146,"score_spread":0.29205817855359717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206092563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99901783,0.00037391632,0.00006982739,0.00005459567,0.0000030694118,0.0000040960026,0.00020024007,0.0000033303445,0.00027297027],"genre_scores_gemma":[0.9996393,0.000080946986,0.00007106595,0.000011630809,0.000008287516,0.0000035296152,0.00011416007,8.826218e-7,0.00007013955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983656,0.000027817354,0.000027919357,0.000043728964,0.000028061955,0.00003595167],"domain_scores_gemma":[0.9988795,0.00016203936,0.00058831816,0.000048557824,0.0001859359,0.00013563798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050265784,0.00043112654,0.00034451834,0.0009266325,0.0004076592,0.00063517306,0.0003037372,0.00046151172,0.0014755805],"category_scores_gemma":[0.0028786547,0.00012134166,0.00026427285,0.00073699653,0.00025448907,0.00044138168,0.00048266517,0.0003370148,0.0001856317],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027395118,0.000054498767,0.9946327,0.00002769528,0.000095152915,0.00013763654,0.00014992815,0.00010888112,0.00054858834,0.000025108418,0.00009220233,0.0038536312],"study_design_scores_gemma":[0.0000027848187,0.000062366635,0.9992962,0.000007852781,0.000021024072,0.00015929416,0.000092755916,0.00018456343,0.000075685544,0.0000445806,0.000050942956,0.0000019018779],"about_ca_topic_score_codex":0.0068035354,"about_ca_topic_score_gemma":0.0069721825,"teacher_disagreement_score":0.0068035354,"about_ca_system_score_codex":0.0002443572,"about_ca_system_score_gemma":0.00021829763,"threshold_uncertainty_score":0.01352787},"labels":[],"label_agreement":null},{"id":"W4206153254","doi":"10.1101/2022.01.11.22268989","title":"Network-based spreading of grey matter changes across different stages of psychosis","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Grey matter; Psychosis; Antipsychotic; Schizophrenia (object-oriented programming); Psychology; Medicine; Psychiatry; White matter; Magnetic resonance imaging","score_opus":0.09373276968866529,"score_gpt":0.3875963083002898,"score_spread":0.2938635386116245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206153254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98436445,0.00005127291,0.015102967,0.000051463183,0.0000020932944,0.000017160619,0.000110386216,0.00003560724,0.00026459625],"genre_scores_gemma":[0.9980965,0.000021378533,0.0016648517,0.0000041680532,0.0000013935344,0.000009679108,0.00006769384,0.000003469276,0.00013092355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99985933,0.00006172973,0.0000053534145,0.000043957083,0.000013046847,0.000016613634],"domain_scores_gemma":[0.99946123,0.0002512472,0.00015138663,0.00005723647,0.000043878736,0.000035022807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049913547,0.00021942407,0.00021410975,0.0003898667,0.00014221974,0.00036792032,0.00025523774,0.0002212636,0.00078937423],"category_scores_gemma":[0.0016203275,0.00017562765,0.00035971453,0.0002452018,0.00037325473,0.00037901007,0.00033133646,0.00023704782,0.00006850729],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009573051,0.000091536225,0.25075746,0.00008130848,0.000408454,0.00031160432,0.0003954672,0.68736464,0.024692507,0.0032012032,0.00045926787,0.031279355],"study_design_scores_gemma":[0.000023681714,0.00012474335,0.15362321,0.000010579458,0.000038547365,0.000112651316,0.00007469516,0.8401489,0.0014402018,0.004236393,0.00014859626,0.000017909562],"about_ca_topic_score_codex":0.007342385,"about_ca_topic_score_gemma":0.00787478,"teacher_disagreement_score":0.007342385,"about_ca_system_score_codex":0.0005065505,"about_ca_system_score_gemma":0.00030642794,"threshold_uncertainty_score":0.014599323},"labels":[],"label_agreement":null},{"id":"W4206253725","doi":"10.1002/alz.058103","title":"Associations between iron deposition in the brain and grey matter volumes in cognitively unimpaired adults","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Grey matter; Magnetic resonance imaging; Voxel; Nuclear medicine; Voxel-based morphometry; Psychology; White matter; Cerebrospinal fluid; Brain size; Cohort; Medicine; Pathology; Internal medicine; Neuroscience; Radiology","score_opus":0.04714768964547058,"score_gpt":0.32440531956596186,"score_spread":0.2772576299204913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206253725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996203,0.00008002873,0.000013221557,0.000009751485,0.0000015198592,0.0000016429726,0.00012501962,0.000001629332,0.00014681026],"genre_scores_gemma":[0.9997192,0.000025468253,0.000030432362,0.000006393745,0.0000039299507,0.0000026029918,0.00011130474,7.2935165e-7,0.00009995169],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982554,0.000030389136,0.00002205659,0.000060833157,0.000029039524,0.000032190208],"domain_scores_gemma":[0.9991991,0.00016226055,0.00032284387,0.000065522065,0.00010267704,0.00014761824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034568118,0.00037081374,0.00028081966,0.0012615877,0.00045833085,0.00045585766,0.00032754152,0.0005283099,0.0019527986],"category_scores_gemma":[0.0015791722,0.00021948619,0.00022511093,0.000684411,0.00033077307,0.0002951304,0.00039923235,0.00033410688,0.0002111285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002110202,0.000062089195,0.99762505,0.0000122369,0.000050680606,0.00014097252,0.00015893421,0.000040394734,0.0005175622,0.000025560405,0.000087744105,0.0010678122],"study_design_scores_gemma":[0.0000026712385,0.00006466999,0.99953127,0.0000024893693,0.000012989462,0.00012031205,0.00008046377,0.00008133876,0.000044631295,0.000023173718,0.000034890967,0.0000010899827],"about_ca_topic_score_codex":0.010017622,"about_ca_topic_score_gemma":0.008673464,"teacher_disagreement_score":0.010017622,"about_ca_system_score_codex":0.00018791009,"about_ca_system_score_gemma":0.00015551485,"threshold_uncertainty_score":0.01991862},"labels":[],"label_agreement":null},{"id":"W4206560698","doi":"10.1002/alz.055678","title":"Ketones and improved cognition in MCI: Links to ApoE and white matter energetics","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Cognition; White matter; Placebo; Effects of sleep deprivation on cognitive performance; Psychology; Medicine; Verbal fluency test; Audiology; Nuclear medicine; Internal medicine; Neuroscience; Neuropsychology; Magnetic resonance imaging; Radiology; Pathology","score_opus":0.04084458212425861,"score_gpt":0.31930468599660033,"score_spread":0.2784601038723417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206560698","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928582,0.005328941,0.00016255121,0.00019680611,0.000021475991,0.0000224954,0.00025514283,0.00001621549,0.001138283],"genre_scores_gemma":[0.9979651,0.0008651464,0.0001661066,0.000097623975,0.00003775945,0.000017867065,0.00017946467,0.0000033230392,0.0006676913],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997707,0.00007836616,0.000026140482,0.00004153435,0.000041309657,0.000041995656],"domain_scores_gemma":[0.99891293,0.00027172666,0.00044152554,0.00010538654,0.00012767152,0.00014078493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011795548,0.0008038844,0.00071929954,0.0005600773,0.00028435333,0.00086355273,0.00029529506,0.0007366426,0.002621426],"category_scores_gemma":[0.0021404692,0.00025032274,0.000576645,0.000427479,0.00038925858,0.0003566577,0.00038270155,0.0006041486,0.00018603286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.2357947,0.004818393,0.6288063,0.0015045156,0.007443759,0.0009241887,0.0003818453,0.00067251,0.029744508,0.00057134574,0.0014011909,0.08793668],"study_design_scores_gemma":[0.0009619526,0.004132979,0.9901585,0.000069622634,0.0013796166,0.00012929527,0.00007485192,0.0003017286,0.0017519469,0.00056538713,0.0004574295,0.000016718901],"about_ca_topic_score_codex":0.0031305111,"about_ca_topic_score_gemma":0.0027189378,"teacher_disagreement_score":0.0031305111,"about_ca_system_score_codex":0.00036608492,"about_ca_system_score_gemma":0.00039001988,"threshold_uncertainty_score":0.008769512},"labels":[],"label_agreement":null},{"id":"W4206800957","doi":"10.1101/2022.01.17.476369","title":"A Whole-Brain 3D Myeloarchitectonic Atlas: Mapping the Vogt-Vogt Legacy to the Cortical Surface","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Institute for Basic Science; Deutsche Forschungsgemeinschaft; National Alliance for Research on Schizophrenia and Depression","keywords":"Brain atlas; Atlas (anatomy); Myelin; Neuroscience; Neuroimaging; White matter; Biology; Cartography; Computer science; Magnetic resonance imaging; Anatomy; Medicine; Geography; Central nervous system","score_opus":0.049788065188359466,"score_gpt":0.29421963033638515,"score_spread":0.2444315651480257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206800957","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10204705,0.010660918,0.5352936,0.0016707212,0.00059157325,0.0005701656,0.3017883,0.028149685,0.019228013],"genre_scores_gemma":[0.4491219,0.0065015582,0.4230294,0.00044482783,0.00017272167,0.0020884771,0.102335826,0.0073012346,0.009004037],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99936575,0.0001521717,0.0000730952,0.00019303992,0.0001757412,0.000040213698],"domain_scores_gemma":[0.9987218,0.00048111854,0.0002476938,0.00024263254,0.0002614185,0.00004533679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020825912,0.0006513312,0.0005248852,0.0041971407,0.0004599002,0.0019066319,0.0008356546,0.00050916837,0.017699212],"category_scores_gemma":[0.00472047,0.0005455405,0.00138275,0.003632554,0.00051774725,0.0005737908,0.0013720923,0.00066015136,0.0034383752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009880469,0.000068771355,0.07118113,0.009992624,0.004325389,0.0014979511,0.0032916872,0.05799088,0.04286861,0.03932174,0.20552912,0.56294405],"study_design_scores_gemma":[0.00023462133,0.00029852137,0.20334552,0.002185897,0.003183551,0.003857453,0.0012243928,0.059279285,0.026186414,0.0677061,0.63214856,0.00034963046],"about_ca_topic_score_codex":0.009848977,"about_ca_topic_score_gemma":0.022781178,"teacher_disagreement_score":0.017699212,"about_ca_system_score_codex":0.00077193184,"about_ca_system_score_gemma":0.0019066846,"threshold_uncertainty_score":0.059209764},"labels":[],"label_agreement":null},{"id":"W4206984152","doi":"10.3233/jad-215390","title":"Cognitive Improvement via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Amnesic Mild Cognitive Impairment Patients","year":2022,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Neuroplasticity; Transcranial magnetic stimulation; Angular gyrus; Cognition; Cognitive impairment; Intervention (counseling); Hippocampus","score_opus":0.028464114671112827,"score_gpt":0.3009957416685747,"score_spread":0.27253162699746186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206984152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993937,0.00017635373,0.00011698298,0.000020716538,0.000004313661,0.000017293192,0.000016153668,0.0000072634684,0.0002471615],"genre_scores_gemma":[0.99947566,0.000102788945,0.00018498022,0.000028316741,0.0000071902755,0.000018741945,0.000028862849,6.9396293e-7,0.00015291631],"study_design_codex":"bench_or_experimental","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.99997866,0.00000444633,0.000002292399,0.000005819929,0.000002681484,0.0000062239915],"domain_scores_gemma":[0.9999764,0.0000026302055,0.000007289402,0.0000021130788,0.0000030869098,0.000008509716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074979886,0.00025967567,0.00020915513,0.000117513075,0.00012089345,0.00011722533,0.00008831437,0.00010121744,0.0007426494],"category_scores_gemma":[0.00017503834,0.000046023524,0.00014302538,0.000065070846,0.00014690805,0.00006687902,0.00007645709,0.00012463245,0.00006923055],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.029722312,0.008177656,0.18651167,0.0007695839,0.0005431697,0.006703842,0.0013951707,0.001291092,0.54894024,0.000336791,0.0015276946,0.21408078],"study_design_scores_gemma":[0.0026185391,0.043745276,0.9034259,0.000051602896,0.0005882099,0.00659172,0.00056837103,0.002407897,0.036753945,0.00043922238,0.0027793641,0.000030041574],"about_ca_topic_score_codex":0.0012378969,"about_ca_topic_score_gemma":0.0023944948,"teacher_disagreement_score":0.0012378969,"about_ca_system_score_codex":0.0001355836,"about_ca_system_score_gemma":0.00018710377,"threshold_uncertainty_score":0.0024843812},"labels":[],"label_agreement":null},{"id":"W4210244170","doi":"10.1002/alz.056596","title":"Disintegration of anterior thalamic radiation fibers in cerebrovascular disease subjects with periventricular white matter hyperintensities leads to lower executive function performance","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Thunder Bay Regional Health Sciences Centre; McMaster University; Queen's University; University of Toronto; University of Ottawa; Baycrest Hospital; Robarts Clinical Trials; Sunnybrook Health Science Centre; Western University","funders":"","keywords":"Hyperintensity; White matter; Diffusion MRI; Fractional anisotropy; Cardiology; Medicine; Internal medicine; Cognitive decline; Cognition; Psychology; Magnetic resonance imaging; Disease; Radiology; Dementia; Psychiatry","score_opus":0.016608014104505017,"score_gpt":0.25779614916939525,"score_spread":0.24118813506489023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210244170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99950504,0.00010592312,0.000053732492,0.000013066427,0.0000023898708,0.0000027214944,0.00006339513,0.000004213039,0.00024946843],"genre_scores_gemma":[0.9996265,0.00004140012,0.000058604262,0.000007210479,0.000004827628,0.000001926356,0.000105195235,0.0000011952509,0.00015299745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998996,0.00001656142,0.000014476778,0.000029747795,0.000021307713,0.000018269864],"domain_scores_gemma":[0.9993826,0.00010656303,0.00029010983,0.000049595837,0.00006703191,0.00010398426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002399411,0.0002822369,0.0002348508,0.00062569155,0.00030873017,0.00047997432,0.00015788892,0.00025220044,0.0025376594],"category_scores_gemma":[0.0010858088,0.00016689513,0.00016122495,0.00029710942,0.00023748353,0.00018923594,0.00020768952,0.0003076272,0.00020054719],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056627445,0.00009555626,0.9864383,0.000026615431,0.00015040582,0.00034167836,0.00018036756,0.000060878087,0.007549073,0.000026776896,0.00013551617,0.0044286624],"study_design_scores_gemma":[0.0000031404218,0.000040147137,0.99936,0.0000017716382,0.000011103839,0.00025726738,0.000043603624,0.000058522855,0.00017670402,0.000017702878,0.00002909157,9.687244e-7],"about_ca_topic_score_codex":0.006180386,"about_ca_topic_score_gemma":0.009911625,"teacher_disagreement_score":0.006180386,"about_ca_system_score_codex":0.000184979,"about_ca_system_score_gemma":0.00014504054,"threshold_uncertainty_score":0.012288809},"labels":[],"label_agreement":null},{"id":"W4210253522","doi":"10.1002/alz.057516","title":"Melatonin mediates the reversibility of brain hyperphosphorylated tau protein induced by synthetic torpor in rats","year":2021,"lang":"en","type":"article","venue":"Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Melatonin; Torpor; Hypothermia; Tau protein; Neuroprotection; Microtubule; Hippocampal formation; Internal medicine; Hyperphosphorylation; Hibernation (computing); Chemistry; Endocrinology; Neuroscience; Biology; Cell biology; Medicine; Kinase; Alzheimer's disease; Thermoregulation","score_opus":0.026989462709062443,"score_gpt":0.2679016563641245,"score_spread":0.24091219365506206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210253522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99870825,0.00023388054,0.00055579265,0.000021638614,0.000007876496,0.000004658306,0.0001506216,0.000051578554,0.000265747],"genre_scores_gemma":[0.9988059,0.0002493558,0.00045180385,0.000008877045,0.0000030249666,0.0000115387065,0.0001644108,0.000011644576,0.00029352304],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999825,0.000002089904,8.9282145e-7,0.0000039236256,0.0000036365,0.000006928376],"domain_scores_gemma":[0.99995375,0.0000047300387,0.000020613494,0.000003855986,0.0000029882235,0.000014053977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004830965,0.0003304607,0.00019201738,0.000086779146,0.00009123567,0.000094527764,0.00017572664,0.00012307952,0.0013011215],"category_scores_gemma":[0.00008464017,0.00009018523,0.00028522112,0.000040502546,0.00014953638,0.00009577453,0.00013688668,0.0003100732,0.00014338108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015550529,0.00018469598,0.0023272345,0.00015190229,0.00005943714,0.0001290893,0.000032056225,0.0049482393,0.986592,0.00026902108,0.00015863815,0.00359272],"study_design_scores_gemma":[0.00019711281,0.005673345,0.0380031,0.00003394385,0.00016555215,0.0001733665,0.00009077446,0.038981117,0.91315323,0.0009445966,0.0025478646,0.000035977828],"about_ca_topic_score_codex":0.00078008237,"about_ca_topic_score_gemma":0.0010442048,"teacher_disagreement_score":0.0013011215,"about_ca_system_score_codex":0.00014809695,"about_ca_system_score_gemma":0.000106781816,"threshold_uncertainty_score":0.004352629},"labels":[],"label_agreement":null},{"id":"W4210319484","doi":"10.1002/alz.054719","title":"The relationship between brain‐age association and prediction: The impact of parameter selection","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Smoothing; Correlation; Brain atlas; Neuroimaging; Psychology; Pattern recognition (psychology); Artificial intelligence; Mathematics; Statistics; Neuroscience; Computer science","score_opus":0.09597595793657968,"score_gpt":0.3752855147917894,"score_spread":0.27930955685520975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210319484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66141176,0.021417266,0.28249747,0.01015154,0.0017138844,0.0007057261,0.007518407,0.009331653,0.005252359],"genre_scores_gemma":[0.95071787,0.0008696842,0.03780971,0.0015039025,0.00030261962,0.0003929803,0.0052456325,0.0017762328,0.0013814345],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9709534,0.02200095,0.0013724462,0.0043350314,0.00070633565,0.00063191075],"domain_scores_gemma":[0.7963405,0.18636182,0.0028365715,0.009746681,0.003418491,0.0012960053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0728839,0.0030220756,0.0029094175,0.0022401102,0.001924928,0.0036673185,0.0029932344,0.003569259,0.0050899712],"category_scores_gemma":[0.16463058,0.0009629008,0.0036844062,0.002352397,0.0020610227,0.0041343216,0.0022243897,0.0056188484,0.002308298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008640513,0.0009274537,0.48345953,0.0013349374,0.013094826,0.0011405606,0.00089267484,0.27013144,0.0051183826,0.0037890503,0.035491515,0.17597911],"study_design_scores_gemma":[0.00085358747,0.0010819404,0.06558598,0.00067819253,0.0037788397,0.0009476471,0.000495265,0.8911381,0.0049758535,0.022654122,0.007478947,0.00033158768],"about_ca_topic_score_codex":0.008825513,"about_ca_topic_score_gemma":0.006590736,"teacher_disagreement_score":0.0728839,"about_ca_system_score_codex":0.00093808695,"about_ca_system_score_gemma":0.00237163,"threshold_uncertainty_score":0.3854515},"labels":[],"label_agreement":null},{"id":"W4210405032","doi":"10.1002/alz.053965","title":"The role of Alzheimer’s disease pathology in frontotemporal dementia related syndromes","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute; Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"Progressive supranuclear palsy; Frontotemporal lobar degeneration; Frontotemporal dementia; Fractional anisotropy; Psychology; Default mode network; Corticobasal degeneration; Diffusion MRI; Biomarker; Boston Naming Test; Pathology; Dementia; Medicine; Neuroscience; Disease; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.044343327790258937,"score_gpt":0.324316545520545,"score_spread":0.27997321773028605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210405032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986481,0.00053528196,0.000063619314,0.00004013239,0.0000022120353,0.0000019497386,0.00003113278,0.0000026672978,0.0006748271],"genre_scores_gemma":[0.9996748,0.00012740072,0.00008439422,0.000008948142,0.0000048725797,0.0000014176974,0.000035887522,6.385476e-7,0.00006176345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999176,0.000019664545,0.000012137017,0.000018321367,0.000017218523,0.000015037439],"domain_scores_gemma":[0.99972755,0.00006136633,0.00011692879,0.000014245345,0.00003490448,0.000044954704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027886426,0.00038393724,0.00016773926,0.0012511881,0.0003608435,0.0004526577,0.00019462952,0.00025764998,0.0011941907],"category_scores_gemma":[0.0007008751,0.00011727532,0.00016796493,0.0003959277,0.0004201823,0.00036606027,0.00027087194,0.00012976576,0.000110433175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080334675,0.00007949436,0.95814663,0.00006593759,0.00014677148,0.005957278,0.0005011976,0.00020842317,0.016197335,0.00038771308,0.00017398703,0.01733184],"study_design_scores_gemma":[0.000013719995,0.00009335782,0.9925256,0.00001214457,0.000046557474,0.0055015734,0.00014945382,0.00026521288,0.0007022025,0.00052265066,0.00016431582,0.0000032227697],"about_ca_topic_score_codex":0.002542332,"about_ca_topic_score_gemma":0.0034069389,"teacher_disagreement_score":0.002542332,"about_ca_system_score_codex":0.00034942594,"about_ca_system_score_gemma":0.00024103645,"threshold_uncertainty_score":0.0050550103},"labels":[],"label_agreement":null},{"id":"W4210406453","doi":"10.1002/mp.15495","title":"Learning white matter subject‐specific segmentation from structural MRI","year":2022,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Tractography; Artificial intelligence; Computer science; Segmentation; Diffusion MRI; Human Connectome Project; Deep learning; Convolutional neural network; Context (archaeology); Voxel; Pattern recognition (psychology); Connectome; White matter; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Radiology","score_opus":0.031295192215812576,"score_gpt":0.32322768654696477,"score_spread":0.2919324943311522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210406453","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23459028,0.0013869947,0.75399077,0.00058380933,0.00008232776,0.00017566019,0.001114115,0.0062133055,0.0018627068],"genre_scores_gemma":[0.7434668,0.0008665128,0.24524064,0.00031089413,0.00009991717,0.00022322928,0.0047647636,0.00062227383,0.0044049826],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964345,0.000071416005,0.000017645021,0.0001759076,0.000058042366,0.000033584656],"domain_scores_gemma":[0.99938345,0.00020297828,0.00013170025,0.000112443755,0.00012658931,0.000042848613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013616689,0.0010860494,0.0005763565,0.0011701889,0.00032803247,0.0006538835,0.00085608586,0.0009433329,0.0012402572],"category_scores_gemma":[0.0034469229,0.00040519584,0.0008113443,0.00078768586,0.0005563386,0.0007142972,0.00068595994,0.00082577125,0.00086732913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041787038,0.00031292153,0.02857992,0.00030052415,0.00045445567,0.00031206486,0.00028374846,0.4113391,0.043696,0.0035445741,0.009632142,0.50112665],"study_design_scores_gemma":[0.000017457558,0.00008374651,0.005586281,0.00003747377,0.00004957744,0.00014587735,0.000033597804,0.97369915,0.012878987,0.005471309,0.00198169,0.000014826979],"about_ca_topic_score_codex":0.007875347,"about_ca_topic_score_gemma":0.013740155,"teacher_disagreement_score":0.007875347,"about_ca_system_score_codex":0.00078190875,"about_ca_system_score_gemma":0.0015069915,"threshold_uncertainty_score":0.015659034},"labels":[],"label_agreement":null},{"id":"W4210439792","doi":"10.3389/fnagi.2021.760663","title":"Tract Specific White Matter Lesion Load Affects White Matter Microstructure and Their Relationships With Functional Connectivity and Cognitive Decline","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"White matter; Hyperintensity; Cognition; Diffusion MRI; Psychology; Cognitive decline; Audiology; Neuropsychology; Effects of sleep deprivation on cognitive performance; Neuroscience; Cardiology; Internal medicine; Medicine; Magnetic resonance imaging; Dementia; Disease; Radiology","score_opus":0.03774630673990567,"score_gpt":0.2767593812260608,"score_spread":0.23901307448615514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210439792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99955624,0.00008671962,0.00011879806,0.000008311586,5.6635423e-7,0.0000035402106,0.000068989786,0.0000056036515,0.00015121733],"genre_scores_gemma":[0.9995503,0.00003919479,0.0001360576,0.00000363093,0.0000025482864,0.0000053846425,0.00010933234,0.0000025827221,0.0001510756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990284,0.000018836663,0.0000117923155,0.000035448593,0.000015928941,0.000015037789],"domain_scores_gemma":[0.9994941,0.00011017734,0.00025728202,0.000050983956,0.000041497362,0.000046002307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026828147,0.0002540859,0.00018899901,0.00056902564,0.0001785234,0.00027749257,0.00014214097,0.00035736716,0.0013383357],"category_scores_gemma":[0.0014258465,0.00013811376,0.00017617912,0.00040952102,0.00028121084,0.0002930899,0.00029177146,0.00016701214,0.0001428817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078270375,0.000098446006,0.9744192,0.000030038997,0.00021760119,0.00035178833,0.00034795393,0.00037807916,0.014070206,0.00009199362,0.00010448427,0.009107704],"study_design_scores_gemma":[0.0000025709428,0.000057329613,0.9989467,0.0000014663788,0.00001718077,0.00021663019,0.000035295303,0.00030592087,0.00029929768,0.00008657133,0.00002916842,0.0000018896548],"about_ca_topic_score_codex":0.0032000716,"about_ca_topic_score_gemma":0.005307684,"teacher_disagreement_score":0.0032000716,"about_ca_system_score_codex":0.00017471168,"about_ca_system_score_gemma":0.00011799546,"threshold_uncertainty_score":0.006362915},"labels":[],"label_agreement":null},{"id":"W4210500523","doi":"10.1007/s12975-022-00988-8","title":"Normal-Appearing White Matter Deteriorates over the Year After an Ischemic Stroke and Is Associated with Global Cognition","year":2022,"lang":"en","type":"article","venue":"Translational Stroke Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"White matter; Fractional anisotropy; Medicine; Diffusion MRI; Montreal Cognitive Assessment; Hyperintensity; Cardiology; Cognition; Neurology; Confounding; Internal medicine; Stroke (engine); Effects of sleep deprivation on cognitive performance; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.07415460791681681,"score_gpt":0.38086795688106484,"score_spread":0.306713348964248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210500523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942964,0.0019681961,0.00018070966,0.00015730556,0.000049879192,0.0000127628455,0.0004989221,0.00002496719,0.0028108014],"genre_scores_gemma":[0.9976107,0.00084863475,0.000105393294,0.000068132416,0.00007786741,0.000005006759,0.0007469798,0.000004455911,0.0005328892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996817,0.000050736868,0.00004482486,0.00007077266,0.00008081173,0.00007122958],"domain_scores_gemma":[0.99749446,0.00017008744,0.0016715283,0.00009909557,0.0002501306,0.0003146951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005011313,0.0005927193,0.0007286102,0.0013683112,0.00051250553,0.0010294013,0.00038615416,0.00065118354,0.0012562387],"category_scores_gemma":[0.002574948,0.00016505066,0.0004325892,0.0016944782,0.0005006407,0.0006847059,0.00053439254,0.0008046194,0.00030066393],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076003396,0.00018083578,0.98608506,0.000054787924,0.00023568433,0.0005849253,0.00011031163,0.0001227254,0.0007667076,0.000061370454,0.0004113743,0.01062618],"study_design_scores_gemma":[0.0000016830854,0.00007810946,0.999265,0.0000047168965,0.000023179236,0.00030792793,0.00004141255,0.000051217714,0.00004293237,0.00008291713,0.000097232434,0.0000036541162],"about_ca_topic_score_codex":0.008828104,"about_ca_topic_score_gemma":0.01257395,"teacher_disagreement_score":0.008828104,"about_ca_system_score_codex":0.00047341792,"about_ca_system_score_gemma":0.0005030145,"threshold_uncertainty_score":0.017553449},"labels":[],"label_agreement":null},{"id":"W4210549501","doi":"10.1002/alz.052413","title":"Sparse canonical correlation analysis reveals relationships between TDP‐43 within the entorhinal cortex and fractional anisotropy across widespread white matter tracts","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Fractional anisotropy; Entorhinal cortex; Alzheimer's Disease Neuroimaging Initiative; Dementia; Neuropathology; Diffusion MRI; Correlation; Psychology; Betweenness centrality; Neuroscience; Nuclear medicine; Medicine; Biology; Pathology; Disease; Magnetic resonance imaging; Mathematics; Statistics; Hippocampus; Radiology","score_opus":0.08395536839006018,"score_gpt":0.35662408367163384,"score_spread":0.27266871528157366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210549501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848564,0.00005473694,0.013839119,0.00005665454,0.000008216638,0.000011978282,0.000591093,0.00012635809,0.0004553831],"genre_scores_gemma":[0.99469167,0.00003161477,0.0044286684,0.00001099908,0.0000072044213,0.000012560744,0.00052207505,0.000022436494,0.0002727011],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970055,0.000109283304,0.000018866396,0.00010330625,0.000033295088,0.00003478889],"domain_scores_gemma":[0.9978326,0.0010141807,0.00037469086,0.0003382813,0.0002996609,0.00014061898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089732435,0.00028456136,0.00024120173,0.000744513,0.00023212178,0.0003668656,0.00015259057,0.0001306575,0.0021093837],"category_scores_gemma":[0.0043091155,0.00011922555,0.00034821947,0.0005716327,0.00036778534,0.0001734654,0.00031906698,0.00024142906,0.00024095166],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024762994,0.0002980171,0.6617543,0.00026445338,0.0014833345,0.0011370934,0.0014539252,0.049332384,0.10591399,0.0048635295,0.013271808,0.15775087],"study_design_scores_gemma":[0.00004085814,0.00018580475,0.72332484,0.000026290963,0.00018617634,0.00088538654,0.00033491853,0.25850227,0.010667931,0.0040399833,0.0017401031,0.00006547794],"about_ca_topic_score_codex":0.0060056844,"about_ca_topic_score_gemma":0.008670242,"teacher_disagreement_score":0.0060056844,"about_ca_system_score_codex":0.00018600412,"about_ca_system_score_gemma":0.0005604508,"threshold_uncertainty_score":0.011941433},"labels":[],"label_agreement":null},{"id":"W4210571894","doi":"10.1002/alz.055493","title":"Characterizing white matter hemodynamic markers of lesion burden and cognitive function using arterial spin labeling MRI","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Hyperintensity; Montreal Cognitive Assessment; Magnetic resonance imaging; Cardiology; Cerebral blood flow; Hemodynamics; Psychology; Medicine; Cognition; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Internal medicine; Neuroscience; Nuclear medicine; Cognitive impairment; Radiology","score_opus":0.049086049455011826,"score_gpt":0.3258690307130059,"score_spread":0.27678298125799405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210571894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99444073,0.00028067853,0.004482703,0.00003188399,0.0000041329686,0.000017742253,0.0002577312,0.000049046088,0.00043535055],"genre_scores_gemma":[0.99486405,0.00016261853,0.0044408026,0.000020496722,0.000014126084,0.000028889357,0.00018400859,0.000009264103,0.00027568825],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999899,0.00002946509,0.0000069270577,0.000030965497,0.000019256697,0.000014327841],"domain_scores_gemma":[0.9994985,0.000119717064,0.00020786977,0.00005329163,0.00007820963,0.000042397445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005681612,0.00025880933,0.0002016705,0.0006892732,0.00015030404,0.00050575874,0.00016378688,0.00024109987,0.001009195],"category_scores_gemma":[0.0010021214,0.000114206,0.00012275076,0.00039299374,0.0002074184,0.00031077754,0.00012505159,0.000161736,0.00013614274],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025545107,0.0004818029,0.5150463,0.00046553207,0.00050805084,0.00037742133,0.000588119,0.0037742942,0.38083526,0.000700423,0.001290987,0.09337728],"study_design_scores_gemma":[0.00004229216,0.00064362533,0.9617958,0.000025649924,0.00017620255,0.00063900463,0.00010154576,0.00968476,0.02496839,0.0010927479,0.0008020144,0.000027935179],"about_ca_topic_score_codex":0.0018486653,"about_ca_topic_score_gemma":0.0032949897,"teacher_disagreement_score":0.0018486653,"about_ca_system_score_codex":0.00017003722,"about_ca_system_score_gemma":0.00021939748,"threshold_uncertainty_score":0.0036757588},"labels":[],"label_agreement":null},{"id":"W4210845950","doi":"10.1016/j.nicl.2022.102955","title":"FLAIR MRI biomarkers of the normal appearing brain matter are related to cognition","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; St. Michael's Hospital; Université de Montréal; University of Toronto; Toronto Metropolitan University","funders":"National Institute on Aging; Canadian Institutes of Health Research; Canada Foundation for Innovation; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Fluid-attenuated inversion recovery; White matter; Kurtosis; Biomarker; Diffusion MRI; Magnetic resonance imaging; Brain size; Fractional anisotropy; Psychology; Voxel-based morphometry; Medicine; Nuclear medicine; Internal medicine; Pathology; Radiology; Chemistry; Mathematics","score_opus":0.07843850859328935,"score_gpt":0.40044685290848925,"score_spread":0.32200834431519987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210845950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9829336,0.001520365,0.013045736,0.00011172425,0.000017156652,0.00008144438,0.0009779204,0.00014256319,0.0011695849],"genre_scores_gemma":[0.9901994,0.00034342593,0.008302056,0.000055199886,0.000033911023,0.00006174328,0.00059663027,0.000011415838,0.0003962429],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967396,0.00006321878,0.00003150936,0.000096270356,0.00007821277,0.00005696893],"domain_scores_gemma":[0.9988519,0.00019634345,0.00051163376,0.000083882966,0.00027390744,0.000082350394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014000876,0.000836011,0.00068730174,0.0024070388,0.00021916436,0.00080731855,0.00036317835,0.00055505283,0.0006639469],"category_scores_gemma":[0.0026354864,0.00015909354,0.0004523012,0.0009321967,0.00032809091,0.0006849643,0.00050033303,0.00036425117,0.000269603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018048313,0.00023289045,0.68711126,0.000472286,0.0012426453,0.00048067575,0.0004114393,0.004985198,0.16192262,0.0005274837,0.0011148065,0.13969386],"study_design_scores_gemma":[0.000020265623,0.0006331812,0.97638595,0.000030909254,0.0002060777,0.00066824857,0.000097134915,0.006341106,0.013753623,0.000875045,0.0009538597,0.000034543245],"about_ca_topic_score_codex":0.0019492825,"about_ca_topic_score_gemma":0.0028537714,"teacher_disagreement_score":0.0024070388,"about_ca_system_score_codex":0.00031376208,"about_ca_system_score_gemma":0.00032109872,"threshold_uncertainty_score":0.0074044466},"labels":[],"label_agreement":null},{"id":"W4211031588","doi":"10.1002/hbm.25777","title":"Tractostorm 2: Optimizing tractography dissection reproducibility with segmentation protocol dissemination","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Mitacs; Fonds de Recherche du Québec - Santé; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; National Institute of General Medical Sciences; Vanderbilt Institute for Clinical and Translational Research; Instrumentariumin Tiedesäätiö; National Institutes of Health; Orionin Tutkimussäätiö; Emil Aaltosen Säätiö; Savoy Foundation; Fonds de recherche du Québec – Nature et technologies; Brain Research Foundation","keywords":"Tractography; Protocol (science); Computer science; Voxel; Reproducibility; Diffusion MRI; Neuroimaging; Artificial intelligence; Segmentation; Connectomics; Psychology; Connectome; Neuroscience; Magnetic resonance imaging; Medicine; Radiology; Pathology; Functional connectivity","score_opus":0.07698099408215822,"score_gpt":0.3921579084499347,"score_spread":0.3151769143677765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211031588","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048473846,0.00058746984,0.8758975,0.00065341097,0.0005689734,0.0054799295,0.0022137687,0.06336369,0.002761365],"genre_scores_gemma":[0.095509514,0.00022787874,0.8661818,0.00027008008,0.00015576035,0.014191784,0.0033272256,0.01755957,0.002576348],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9686166,0.018875247,0.0045497483,0.0036341203,0.0035800072,0.0007442646],"domain_scores_gemma":[0.84130824,0.10450031,0.008767614,0.019109951,0.024853373,0.0014605083],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.088779666,0.0029232136,0.0024855374,0.0037753396,0.0015767794,0.0038855374,0.00345859,0.0023306657,0.016602004],"category_scores_gemma":[0.23445281,0.0021527705,0.0030245534,0.0027851386,0.0016281806,0.003847824,0.004808913,0.0030221604,0.0064168987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0069578965,0.0010145517,0.019197261,0.006377245,0.0020534508,0.00076794554,0.0095884,0.05440476,0.05044104,0.011229235,0.07618229,0.761786],"study_design_scores_gemma":[0.007534499,0.0051885415,0.031984106,0.0018493488,0.0022870626,0.0014482575,0.0032400133,0.62011486,0.11982191,0.048245758,0.1569888,0.0012969238],"about_ca_topic_score_codex":0.0027001256,"about_ca_topic_score_gemma":0.0041534835,"teacher_disagreement_score":0.9112203,"about_ca_system_score_codex":0.0014795039,"about_ca_system_score_gemma":0.006024013,"threshold_uncertainty_score":0.46951735},"labels":[],"label_agreement":null},{"id":"W4212817125","doi":"10.3389/fninf.2022.777853","title":"Assessing the Reliability of Template-Based Clustering for Tractography in Healthy Human Adults","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Cluster analysis; Human Connectome Project; Tractography; Reliability (semiconductor); Pattern recognition (psychology); Computer science; Artificial intelligence; White matter; Centroid; Neuroscience; Psychology; Functional connectivity; Medicine; Magnetic resonance imaging; Physics","score_opus":0.05859852119323517,"score_gpt":0.3744245438312235,"score_spread":0.3158260226379883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212817125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9322977,0.0011440524,0.06258577,0.00016468408,0.000062781844,0.00016784796,0.0018433658,0.0004203603,0.0013134469],"genre_scores_gemma":[0.9770462,0.0002248611,0.020483369,0.000043651384,0.0000387046,0.00006418805,0.0016655838,0.00012039655,0.00031302945],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969958,0.00088333595,0.0003901719,0.0011976636,0.00043750825,0.00009548192],"domain_scores_gemma":[0.98494565,0.0068423687,0.0023533981,0.0026412897,0.0028674018,0.00034994644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008183837,0.0005787125,0.00052792503,0.0014869884,0.00054984196,0.0011276159,0.0005795308,0.0012700931,0.0011241174],"category_scores_gemma":[0.035337053,0.00038164505,0.0005440279,0.00089111825,0.0008074794,0.0009328284,0.00073792133,0.00045926124,0.0005672595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035923943,0.00023315322,0.7767659,0.000702225,0.0022605755,0.001168974,0.0056443587,0.020573925,0.042737667,0.0021555128,0.004827348,0.13933797],"study_design_scores_gemma":[0.0001114842,0.0012852334,0.8827669,0.00019922046,0.00049432495,0.004420045,0.001005858,0.0858712,0.015182651,0.0050303307,0.0034599276,0.00017294286],"about_ca_topic_score_codex":0.0031460794,"about_ca_topic_score_gemma":0.0058712,"teacher_disagreement_score":0.008183837,"about_ca_system_score_codex":0.00028234994,"about_ca_system_score_gemma":0.00043060264,"threshold_uncertainty_score":0.04328078},"labels":[],"label_agreement":null},{"id":"W4212975352","doi":"10.21203/rs.3.rs-310196/v1","title":"Stimulating Lifestyle is associated with Maintenance of White Matter Integrity with Age","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Structural integrity; White (mutation); Gerontology; Medicine; Engineering; Biology; Genetics","score_opus":0.13341940710485356,"score_gpt":0.44221142403800795,"score_spread":0.3087920169331544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212975352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99923754,0.00023328255,0.000111196285,0.00003448069,0.000004221064,0.0000023907787,0.00006394161,0.0000057581815,0.00030730487],"genre_scores_gemma":[0.9994531,0.00006984449,0.000102052305,0.000012608431,0.0000070834894,0.000002329782,0.000079460144,0.0000021306273,0.00027154348],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998313,0.00003086072,0.000020853884,0.000056045017,0.00003427094,0.000026618145],"domain_scores_gemma":[0.99734014,0.00035826818,0.0016951481,0.00020006439,0.00017795063,0.00022832779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031769197,0.0002753135,0.00027412438,0.00039463807,0.00018836914,0.000452894,0.000219603,0.0004868467,0.0024966886],"category_scores_gemma":[0.0023194398,0.0001935816,0.00021105101,0.00040091656,0.00025547997,0.0002758061,0.000316589,0.00036976952,0.00029231998],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057762465,0.00018655974,0.98716146,0.000039069782,0.00014583678,0.00014182745,0.00030290996,0.000064542655,0.004929395,0.000029561957,0.00011525114,0.006305995],"study_design_scores_gemma":[0.0000015802166,0.0000766977,0.9994868,0.000002503235,0.00001418531,0.00008693227,0.00003842113,0.000044284916,0.00018362889,0.00003033223,0.00003336377,0.0000012650235],"about_ca_topic_score_codex":0.0013771462,"about_ca_topic_score_gemma":0.0012671509,"teacher_disagreement_score":0.0024966886,"about_ca_system_score_codex":0.00010081296,"about_ca_system_score_gemma":0.00009313652,"threshold_uncertainty_score":0.00835228},"labels":[],"label_agreement":null},{"id":"W4212986928","doi":"10.1101/2022.01.31.478189","title":"Micapipe: A Pipeline for Multimodal Neuroimaging and Connectome Analysis","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Human Connectome Project; Connectome; Neuroimaging; Tractography; Connectomics; Computer science; Diffusion MRI; Artificial intelligence; Neuroscience; Pipeline (software); Functional connectivity; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Medicine","score_opus":0.03801779878377539,"score_gpt":0.31009455201891645,"score_spread":0.2720767532351411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212986928","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051767044,0.0008024189,0.41395,0.00061200385,0.0003076065,0.00049690885,0.07042962,0.5019938,0.006230963],"genre_scores_gemma":[0.058856003,0.0012355972,0.5707316,0.0012620728,0.00021455227,0.003973681,0.21473178,0.13515422,0.013840587],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991447,0.00011198876,0.00007381999,0.0003201772,0.00023581205,0.000113498325],"domain_scores_gemma":[0.9988586,0.00034805245,0.00009240009,0.00033552962,0.00027054053,0.0000949493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017280978,0.0038881737,0.0014976249,0.0025433868,0.0013339911,0.003764718,0.0031307852,0.001371383,0.059317388],"category_scores_gemma":[0.0067355693,0.0017023609,0.003082253,0.0020379364,0.0006364465,0.002270231,0.0050721355,0.0032464263,0.037483536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007396084,0.000106413405,0.0024913938,0.0015581377,0.00088744285,0.0006741984,0.00061930344,0.0073852977,0.023048382,0.008843934,0.76179165,0.19185425],"study_design_scores_gemma":[0.0005535363,0.0002333022,0.01459884,0.00048207366,0.00037446528,0.0016007712,0.0005460001,0.21963835,0.05720389,0.10024391,0.6039946,0.0005302295],"about_ca_topic_score_codex":0.0072838417,"about_ca_topic_score_gemma":0.014265275,"teacher_disagreement_score":0.059317388,"about_ca_system_score_codex":0.0009851481,"about_ca_system_score_gemma":0.0023349703,"threshold_uncertainty_score":0.19843638},"labels":[],"label_agreement":null},{"id":"W4213009037","doi":"10.1101/2022.02.17.480894","title":"Experience-dependent learning and myelin plasticity in individuals with stroke","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Myelin; Motor learning; Neuroplasticity; Stroke (engine); Psychology; Physical medicine and rehabilitation; Neuroscience; Medicine; Central nervous system; Physics","score_opus":0.02986012469849179,"score_gpt":0.29213734550915443,"score_spread":0.2622772208106626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213009037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997098,0.000048512986,0.00004894839,0.00001071041,8.271948e-7,0.000002372937,0.000024118977,0.0000026318776,0.0001520233],"genre_scores_gemma":[0.99972564,0.000028498665,0.00003969252,0.0000069895686,0.0000016266065,0.0000028446057,0.000029452509,6.8190104e-7,0.00016453207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999049,0.000012377845,0.000010295608,0.000032260803,0.000015490732,0.000024779558],"domain_scores_gemma":[0.99973875,0.00003386815,0.00013576593,0.000016206874,0.000027475773,0.000047891917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014400328,0.00024315402,0.00027908158,0.0003662645,0.00021938368,0.0002619562,0.0001088586,0.0002629446,0.0015618168],"category_scores_gemma":[0.00057299505,0.00009510134,0.00012377357,0.00020911844,0.00019430726,0.0002027643,0.00026857297,0.00016721291,0.00014073847],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014182698,0.00074550847,0.92310643,0.000103951264,0.00019062341,0.0016753981,0.0010397353,0.00036458237,0.041231144,0.00008347304,0.00022026135,0.029820673],"study_design_scores_gemma":[0.000005988618,0.0005998198,0.99732023,0.000004953417,0.000022096874,0.00073796196,0.00011744221,0.00011952556,0.00092182285,0.0000742675,0.000072104136,0.0000037918148],"about_ca_topic_score_codex":0.0015088329,"about_ca_topic_score_gemma":0.0022042792,"teacher_disagreement_score":0.0015618168,"about_ca_system_score_codex":0.00014942506,"about_ca_system_score_gemma":0.00009252827,"threshold_uncertainty_score":0.005224824},"labels":[],"label_agreement":null},{"id":"W4214809227","doi":"10.1093/braincomms/fcac053","title":"Symptoms reported by Canadians posted in Havana are linked with reduced white matter fibre density","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Nova Scotia Health Authority; Canadian Institutes of Health Research; Global Affairs Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Cohort; Medicine; Splenium; Fornix; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.04936856139944717,"score_gpt":0.3234184711738703,"score_spread":0.2740499097744231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214809227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981744,0.000089658555,0.00005074029,0.00008917267,0.0000063865446,0.000007646843,0.00055584847,0.0000046577165,0.0010214769],"genre_scores_gemma":[0.9986681,0.00007798236,0.000081644255,0.000029853336,0.0000033349872,0.000006401841,0.00047657866,0.0000025554048,0.00065353356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998235,0.000014345298,0.000007437489,0.000043357486,0.000030936713,0.00008045168],"domain_scores_gemma":[0.9995819,0.000019297184,0.00016914471,0.000020154,0.00012376378,0.00008575075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001652965,0.00029946584,0.00017038615,0.0008550806,0.0018294522,0.0006466047,0.0004689707,0.00029370026,0.0037638186],"category_scores_gemma":[0.00065990887,0.00017544252,0.00017392516,0.00084806216,0.00042865667,0.00016499574,0.0006427308,0.0003084292,0.00024952448],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012490882,0.000034349596,0.99248767,0.00002759473,0.00004445113,0.00028295754,0.0012527081,0.000047711983,0.0016423207,0.0000597767,0.00077315385,0.003222281],"study_design_scores_gemma":[0.0000018186919,0.000009627938,0.99771947,0.000010415814,0.000007822958,0.000109882334,0.0016999866,0.00003822288,0.00008216499,0.000012511738,0.00030461367,0.000003488069],"about_ca_topic_score_codex":0.8316307,"about_ca_topic_score_gemma":0.9087021,"teacher_disagreement_score":0.1683693,"about_ca_system_score_codex":0.0026884277,"about_ca_system_score_gemma":0.002106188,"threshold_uncertainty_score":0.3387217},"labels":[],"label_agreement":null},{"id":"W4214903121","doi":"10.1016/j.biopsych.2022.02.959","title":"Virtual Ontogeny of Cortical Growth Preceding Mental Illness","year":2022,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; University of Calgary; Centre Hospitalier Universitaire Sainte-Justine; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Cilag; Singapore Bioimaging Consortium; Scottish Mental Health Research Network; National Center for Complementary and Integrative Health; National Institute on Drug Abuse; European Regional Development Fund; H2020 Marie Skłodowska-Curie Actions; Horizon 2020; Medizinische Fakultät, Westfälische Wilhelms-Universität Münster; Instituto de Salud Carlos III; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Seventh Framework Programme; NIH Clinical Center; Ramsay Health Care; National Institute on Alcohol Abuse and Alcoholism; Stiftelsen för Strategisk Forskning; Medical Research Council; Siemens Healthineers; Innovative Medicines Initiative; Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg; Hartmann Müller-Stiftung für Medizinische Forschung; Medical Research Council Canada; University of Cape Town; Centro de Investigación Biomédica en Red de Salud Mental; Society for Mental Health Research; National Institute of Neurological Disorders and Stroke; Universität Zürich; Australian Schizophrenia Research Bank; Norges Forskningsråd; Ministerio de Ciencia e Innovación; Meath Foundation; Clinical and Translational Science Institute, University of California, San Francisco; National Institute of Mental Health; Helse Sør-Øst RHF; Hospital de Clínicas de Porto Alegre; Brain and Behavior Research Foundation; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Centre of Excellence in Cognition and its Disorders, Australian Research Council; Ministero della Salute; Macquarie University; Generalitat de Catalunya; Natural Sciences and Engineering Research Council of Canada; American Foundation for Suicide Prevention; Bundesministerium für Bildung und Forschung; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Deutsche Forschungsgemeinschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Institute of Biomedical Imaging and Bioengineering; University of Melbourne; Stiftelsen för Strategisk Forskning; National Institute for Health and Care Research; National Research Foundation; South African Medical Research Council; Swinburne University of Technology; Ministerio de Ciencia, Innovación y Universidades; Health Research Board; Pratt Foundation; Centres de Recerca de Catalunya; National Institutes of Health; Children's Hospital Foundation; Fundação Instituto de Pesquisas Econômicas; Wellcome Trust; University of California, San Francisco; Simons Foundation Autism Research Initiative; Schizophrenia Research Fund; Sylvia and Charles Viertel Charitable Foundation; Australian Research Council; Fresenius Medical Care North America; National Institute on Aging; Jack Brockhoff Foundation; EU Joint Programme – Neurodegenerative Disease Research; Bill and Melinda Gates Foundation; National Center for Research Resources; National Alliance for Research on Schizophrenia and Depression; Biogen; Hjärnfonden; Ministerstvo Zdravotnictví Ceské Republiky; European Commission; Russian Foundation for Basic Research; National Healthcare Group; European Federation of Pharmaceutical Industries and Associations; Carnegie Corporation of New York; Chiropractic and Osteopathic College of Australasia; Collier Charitable Fund; Indiana Clinical and Translational Sciences Institute; Autism Speaks; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Horizon 2020 Framework Programme; Vetenskapsrådet; University of Minnesota; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; U.S. Department of Veterans Affairs","keywords":"DISC1; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; Psychosis; Cerebral cortex; Neuroscience; Psychology; Autism; Biology; Gene; Psychiatry; Genetics","score_opus":0.07596099524132206,"score_gpt":0.3527165624234762,"score_spread":0.27675556718215416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214903121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9678523,0.0016757404,0.007181692,0.00037943965,0.000066940855,0.000018251701,0.0009210989,0.00013296814,0.021771686],"genre_scores_gemma":[0.99663913,0.00046207427,0.0009608914,0.000024988409,0.000012417082,0.000009999229,0.00018309557,0.00002899024,0.0016783081],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986994,0.000024011615,0.000004708854,0.000034246783,0.000032106098,0.00003491887],"domain_scores_gemma":[0.9993474,0.00025052502,0.00013264411,0.0000802508,0.00009346297,0.00009566972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649235,0.00016649617,0.00014814327,0.0012984879,0.00040498615,0.00095562683,0.00027099697,0.0003719373,0.006429202],"category_scores_gemma":[0.0016003805,0.00019808275,0.00023096366,0.0005679682,0.00089401583,0.0007721058,0.00088872784,0.00057575584,0.00057310105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035290564,0.00019155617,0.20812248,0.00052020035,0.00022523054,0.013419957,0.004477555,0.008446154,0.41513747,0.094999835,0.0030283278,0.24790217],"study_design_scores_gemma":[0.000015808922,0.00024815832,0.9429833,0.0001054869,0.000047232257,0.0055352575,0.0012930826,0.0026858365,0.019248974,0.01859773,0.009209844,0.000029311042],"about_ca_topic_score_codex":0.0035961678,"about_ca_topic_score_gemma":0.004475976,"teacher_disagreement_score":0.006429202,"about_ca_system_score_codex":0.00052789133,"about_ca_system_score_gemma":0.00058883347,"threshold_uncertainty_score":0.0215078},"labels":[],"label_agreement":null},{"id":"W4220706494","doi":"10.1016/j.nicl.2022.103001","title":"Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto; Montreal Neurological Institute and Hospital; Hospital for Sick Children; SickKids Foundation","funders":"","keywords":"White matter; Optic neuritis; Medicine; Multiple sclerosis; Diffusion MRI; Optic nerve; Pathology; Clinically isolated syndrome; Abnormality; Lesion; Ophthalmology; Neuroscience; Psychology; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.059620413644246334,"score_gpt":0.3791815617327682,"score_spread":0.3195611480885219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220706494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992644,0.00011717406,0.000109341105,0.00000992423,9.972355e-7,0.0000033361894,0.000187805,0.000006433152,0.00030061684],"genre_scores_gemma":[0.99905235,0.00020238575,0.0002925979,0.000008365487,0.0000032480393,0.000007530637,0.00030661156,0.0000050726617,0.00012196863],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937624,0.00009276397,0.00010856237,0.00016807063,0.00015732125,0.00009708202],"domain_scores_gemma":[0.9982741,0.00024320192,0.001095255,0.00008225669,0.00017739882,0.00012765171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032103414,0.00030831603,0.0002828012,0.002343645,0.00023645417,0.00039360224,0.00022219084,0.00026966393,0.0014180784],"category_scores_gemma":[0.0025162438,0.00021770896,0.0001762833,0.0016396107,0.0005537062,0.00028771083,0.00048126536,0.00020929877,0.00017435953],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013021762,0.00001801948,0.98479974,0.00004074718,0.000030337187,0.0012765066,0.00047044252,0.00018750086,0.0070452844,0.00007710991,0.00009951801,0.0058245845],"study_design_scores_gemma":[0.0000017311459,0.000045032037,0.9960601,0.0000053035133,0.000008871039,0.0030029893,0.00013182606,0.000056926914,0.0005251443,0.000023896479,0.00013583593,0.0000023780092],"about_ca_topic_score_codex":0.004329064,"about_ca_topic_score_gemma":0.0038953791,"teacher_disagreement_score":0.004329064,"about_ca_system_score_codex":0.00023843416,"about_ca_system_score_gemma":0.0002632077,"threshold_uncertainty_score":0.008607686},"labels":[],"label_agreement":null},{"id":"W4220724235","doi":"10.21203/rs.3.rs-1335010/v1","title":"Abnormal Brain Functional and Structural Connectivity Between the Left Supplementary Motor Area and Inferior Frontal Gyrus in Moyamoya Disease","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Zhejiang University; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Supramarginal gyrus; Superior frontal gyrus; White matter; Diffusion MRI; Neuroscience; Resting state fMRI; Middle frontal gyrus; Cognition; Functional magnetic resonance imaging; Supplementary motor area; Inferior frontal gyrus; Medial frontal gyrus; Psychology; Functional connectivity; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11024288447271696,"score_gpt":0.4234494933137933,"score_spread":0.3132066088410763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220724235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995521,0.00008468488,0.00017372747,0.0000145371605,0.0000011393477,0.0000027733704,0.000060312635,0.0000031466707,0.000107545246],"genre_scores_gemma":[0.9995751,0.000039523755,0.00025836512,0.0000059078748,0.0000036804142,0.000004010068,0.00007121858,9.634751e-7,0.00004120715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999923,0.0000133676585,0.0000099624995,0.000029965458,0.000011069968,0.000012607744],"domain_scores_gemma":[0.9997762,0.000063657775,0.00009602161,0.000015274385,0.0000147425335,0.000034048964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018815948,0.00026630744,0.00021681635,0.0009233724,0.00023632187,0.00024860242,0.000115185394,0.00024074821,0.001285289],"category_scores_gemma":[0.00064395927,0.00011113069,0.00013149541,0.0003192736,0.0003067135,0.00019612542,0.0002466678,0.00014134625,0.000065740336],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013857833,0.00011310331,0.9076865,0.0000942479,0.00031583832,0.0028051944,0.00041452312,0.00070751883,0.07070629,0.00027105794,0.00027154927,0.015228316],"study_design_scores_gemma":[0.000009905548,0.000054621138,0.9970515,0.0000045936886,0.000030223802,0.0009765294,0.000044532797,0.0007172607,0.00092001096,0.00012394784,0.00006408821,0.0000028046052],"about_ca_topic_score_codex":0.0024508599,"about_ca_topic_score_gemma":0.0038150107,"teacher_disagreement_score":0.0024508599,"about_ca_system_score_codex":0.00020377213,"about_ca_system_score_gemma":0.00012544835,"threshold_uncertainty_score":0.004873216},"labels":[],"label_agreement":null},{"id":"W4220726715","doi":"10.1016/j.neurobiolaging.2022.03.008","title":"DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants","year":2022,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Medical Research Council; Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Kurtosis; Diffusion MRI; Thermal diffusivity; Fractional anisotropy; White matter; Biobank; Statistics; Medicine; Physics; Mathematics; Magnetic resonance imaging; Biology; Radiology; Bioinformatics","score_opus":0.0469883646580052,"score_gpt":0.3343319057677442,"score_spread":0.287343541109739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220726715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97859335,0.0008079517,0.007961545,0.0008065021,0.00012058686,0.00009855237,0.0058590574,0.00021014262,0.005542271],"genre_scores_gemma":[0.98479015,0.0004065559,0.008421082,0.00022533962,0.00006338714,0.00008971456,0.003502038,0.000116573894,0.0023851746],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99772877,0.0010717144,0.0002981737,0.00051286205,0.00022271283,0.00016566689],"domain_scores_gemma":[0.9832787,0.0078006373,0.003329897,0.0024236748,0.0024745057,0.0006925473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009226485,0.00057156646,0.0006184063,0.0015969116,0.00051466684,0.002344835,0.0007052473,0.0011743412,0.0055113593],"category_scores_gemma":[0.046188455,0.00039456677,0.0002923657,0.0011285885,0.0006150816,0.0013767536,0.002540467,0.0007184935,0.0016752724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054808967,0.00022136461,0.84512854,0.0009847312,0.00063083804,0.0009830291,0.008048659,0.0022491484,0.024638288,0.0017484924,0.01122509,0.0986609],"study_design_scores_gemma":[0.00011212508,0.0002578529,0.9623708,0.00024410833,0.00031250351,0.0019178848,0.0020006148,0.0043415893,0.0070459894,0.0033421738,0.017945029,0.00010929638],"about_ca_topic_score_codex":0.008601381,"about_ca_topic_score_gemma":0.015556298,"teacher_disagreement_score":0.009226485,"about_ca_system_score_codex":0.00045754726,"about_ca_system_score_gemma":0.00050123065,"threshold_uncertainty_score":0.048794925},"labels":[],"label_agreement":null},{"id":"W4220833183","doi":"10.1109/tmi.2022.3161947","title":"Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Calgary Foundation; University of Calgary","keywords":"Brain morphometry; Neuroimaging; Computer science; Artificial intelligence; Generative model; Machine learning; Pattern recognition (psychology); Generative grammar; Psychology; Neuroscience; Magnetic resonance imaging","score_opus":0.051741779957651196,"score_gpt":0.3277829044766381,"score_spread":0.2760411245189869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220833183","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03948362,0.00017823816,0.9591564,0.00017586585,0.000016915621,0.000027300515,0.00006324611,0.000370934,0.0005275239],"genre_scores_gemma":[0.7039541,0.00065009523,0.29134163,0.000115081995,0.00006855882,0.0001384971,0.00025899897,0.00024020445,0.0032328642],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999796,0.00008421188,0.000010179143,0.000059733902,0.000031666794,0.000018293074],"domain_scores_gemma":[0.99929607,0.00035642786,0.00012263705,0.00007933039,0.000102055346,0.000043531363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012407652,0.00063957716,0.0004388037,0.0006368634,0.00026727022,0.00051206944,0.000603393,0.0006359684,0.00083366834],"category_scores_gemma":[0.0034872682,0.0003156496,0.0007537144,0.00045228653,0.0007322954,0.00080538035,0.00079300185,0.0007664936,0.00019906105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058020883,0.00005261874,0.0022314051,0.000036387435,0.000041430038,0.00013036447,0.00018295957,0.85096294,0.0067028613,0.029547093,0.0006587515,0.109395124],"study_design_scores_gemma":[0.0000017692039,0.000012000518,0.00019604438,0.0000022908173,0.0000043323325,0.000026003296,0.0000038558737,0.99263155,0.0005974388,0.006172559,0.00034733876,0.0000048315924],"about_ca_topic_score_codex":0.008865261,"about_ca_topic_score_gemma":0.0067785257,"teacher_disagreement_score":0.008865261,"about_ca_system_score_codex":0.00065229443,"about_ca_system_score_gemma":0.00089997274,"threshold_uncertainty_score":0.017627358},"labels":[],"label_agreement":null},{"id":"W4220882089","doi":"10.3389/fnana.2022.837485","title":"Cytoarchitectonic Maps of the Human Metathalamus in 3D Space","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada; Montreal Neurological Institute and Hospital","funders":"Max-Planck-Gesellschaft; Horizon 2020 Framework Programme; Forschungszentrum Jülich; Bundesministerium für Bildung und Forschung; European Commission","keywords":"Space (punctuation); Neuroscience; Psychology; Artificial intelligence; Cognitive science; Computer science","score_opus":0.025310085183022385,"score_gpt":0.30436510360463737,"score_spread":0.27905501842161495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220882089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80408067,0.0012023029,0.182053,0.000204428,0.000016442875,0.000078072815,0.0037874884,0.0011783805,0.0073991283],"genre_scores_gemma":[0.91748613,0.00076246075,0.07778449,0.000048569844,0.000010328343,0.000097121025,0.0017881384,0.00019238255,0.0018305139],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999292,0.000009704143,0.0000042973347,0.000017688684,0.000031092313,0.000008007861],"domain_scores_gemma":[0.99984324,0.000052679185,0.0000297883,0.000026978505,0.000036173325,0.000011174727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017598504,0.00017956631,0.0000950697,0.0013640079,0.00013394533,0.0005883146,0.00014769912,0.00019735016,0.0021308053],"category_scores_gemma":[0.00051146897,0.0001791393,0.00022655421,0.0006575991,0.0003120313,0.00021916624,0.00038540113,0.00017179648,0.00047567108],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086086773,0.00007972354,0.061579384,0.00063698326,0.00025658196,0.001605303,0.0031967065,0.08971964,0.48478898,0.020269578,0.0051320167,0.33187425],"study_design_scores_gemma":[0.00006702506,0.00032018893,0.594046,0.0002128992,0.00019661509,0.009426078,0.000963212,0.22586568,0.10541399,0.027688786,0.035584424,0.00021501728],"about_ca_topic_score_codex":0.005951137,"about_ca_topic_score_gemma":0.008942041,"teacher_disagreement_score":0.005951137,"about_ca_system_score_codex":0.00035114205,"about_ca_system_score_gemma":0.00043039047,"threshold_uncertainty_score":0.011833012},"labels":[],"label_agreement":null},{"id":"W4220892781","doi":"10.32920/19400750.v1","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Orientation (vector space); Metric (unit); Linear regression; Diffusion; Tensor (intrinsic definition); Dispersion (optics); SIGNAL (programming language); Biological system; Nuclear magnetic resonance; Physics; Materials science; Statistical physics; Mathematics; Computer science; Optics; Statistics; Magnetic resonance imaging; Geometry; Radiology; Medicine; Biology","score_opus":0.07503130547690681,"score_gpt":0.4057850943838871,"score_spread":0.33075378890698026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220892781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021449283,0.00009481197,0.9963749,0.00011842707,0.000015303234,0.000024198702,0.00008473511,0.00041089015,0.0007319082],"genre_scores_gemma":[0.050785705,0.0004991097,0.93946177,0.00013944905,0.000091522554,0.00023352075,0.00048577372,0.00079952914,0.0075035538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99959403,0.00011692266,0.000018320574,0.000084963,0.00015197179,0.000033855107],"domain_scores_gemma":[0.99948597,0.00022970805,0.000084715066,0.000055205797,0.00012282388,0.000021536998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011526154,0.0013338405,0.00066693145,0.0005577397,0.00021262992,0.00078843866,0.0011155476,0.0009894567,0.0037458548],"category_scores_gemma":[0.0021889315,0.00055312464,0.0007508522,0.00069864874,0.0005245046,0.0012291354,0.00089487736,0.0015867339,0.0018511246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017692016,0.00013783656,0.0005686124,0.0003370077,0.0002108135,0.00033526256,0.00013811472,0.5982505,0.085945584,0.10524804,0.011424625,0.1972267],"study_design_scores_gemma":[0.000009410983,0.00003518642,0.000104172126,0.000007651308,0.0000139965105,0.00006333845,0.0000056281574,0.9827124,0.005988104,0.00653539,0.004508533,0.00001619708],"about_ca_topic_score_codex":0.00235527,"about_ca_topic_score_gemma":0.0036253505,"teacher_disagreement_score":0.0037458548,"about_ca_system_score_codex":0.0005344111,"about_ca_system_score_gemma":0.0012459921,"threshold_uncertainty_score":0.012531102},"labels":[],"label_agreement":null},{"id":"W4220920055","doi":"10.1101/2022.03.28.485689","title":"Mapping the subcortical connectome using in vivo diffusion MRI: feasibility and reliability","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Tractography; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Thalamus; Connectomics; Computer science; Reliability (semiconductor); Artificial intelligence; Psychology; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.07093723532006117,"score_gpt":0.31211429899570076,"score_spread":0.24117706367563957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220920055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7282869,0.0011445148,0.26792315,0.00026314915,0.00004563182,0.00013993398,0.0006367694,0.00038890573,0.0011709916],"genre_scores_gemma":[0.93263876,0.00041645372,0.0659746,0.000059749178,0.00003370321,0.00007377285,0.00038761267,0.00012126651,0.0002941269],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99743015,0.0015169445,0.00016918608,0.00051720504,0.00031057422,0.000055887605],"domain_scores_gemma":[0.9896744,0.0057100942,0.0012367194,0.0018289996,0.001361224,0.00018851615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056825085,0.0006659228,0.0005107725,0.0013673968,0.00032689952,0.0013074664,0.00062229426,0.0008367411,0.0005712528],"category_scores_gemma":[0.018241968,0.00039812218,0.00028099108,0.00074461807,0.0010855829,0.00077393197,0.00080159836,0.0005734859,0.00028621373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026431188,0.00034413743,0.25008082,0.0010275383,0.0013020021,0.0007498109,0.0018890259,0.03574465,0.5330563,0.003049658,0.0014412359,0.1686717],"study_design_scores_gemma":[0.00014916743,0.0015838493,0.47120345,0.00020463076,0.0006146567,0.004602011,0.0008198269,0.33962455,0.16225557,0.013339623,0.0053933337,0.00020925661],"about_ca_topic_score_codex":0.001932787,"about_ca_topic_score_gemma":0.0033339444,"teacher_disagreement_score":0.0056825085,"about_ca_system_score_codex":0.0002298356,"about_ca_system_score_gemma":0.00041389352,"threshold_uncertainty_score":0.030052364},"labels":[],"label_agreement":null},{"id":"W4220973849","doi":"10.7554/elife.73153","title":"The Digital Brain Bank, an open access platform for post-mortem imaging datasets","year":2022,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Medical Research Council; Université de Lyon; Medical Research Council Canada; China Scholarship Council; Max-Planck-Gesellschaft; NIHR Oxford Biomedical Research Centre; Wellcome Trust; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; National Research Foundation; University of Oxford; Motor Neurone Disease Association; Cancer Research UK; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Alzheimer Society; Smithsonian Institution; Wellcome","keywords":"Neuroimaging; Neuroanatomy; Diffusion MRI; Magnetic resonance imaging; Human brain; Tractography; Neuroinformatics; Functional magnetic resonance imaging; Brain mapping","score_opus":0.14061197562562738,"score_gpt":0.46248749162799835,"score_spread":0.32187551600237096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220973849","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010042259,0.00055873254,0.012284453,0.00058300304,0.00029556884,0.00023464269,0.9677518,0.013521221,0.0037664992],"genre_scores_gemma":[0.0028141937,0.000671686,0.023877319,0.0004271667,0.000100912766,0.0019181253,0.9616758,0.0054852376,0.0030294221],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99610317,0.00056933594,0.0006280076,0.00086602743,0.0014826359,0.00035084164],"domain_scores_gemma":[0.98794216,0.0029113803,0.0014847869,0.004256118,0.0024184207,0.0009871335],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.007322872,0.0017786362,0.0024969142,0.005906498,0.0020063948,0.0053165685,0.0067880447,0.0033633488,0.10195016],"category_scores_gemma":[0.02454396,0.0015340421,0.0013481958,0.006492221,0.0012568951,0.005025252,0.0074754213,0.0034647074,0.13533287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038869062,0.00003576129,0.0009041698,0.0013280477,0.000108287786,0.00024173185,0.0001892254,0.0004324763,0.0028138817,0.0038511155,0.97505844,0.0146481255],"study_design_scores_gemma":[0.00033513422,0.00004158177,0.0049664243,0.0007445893,0.00009610688,0.00047952635,0.00014179261,0.0008494472,0.0040134117,0.011345173,0.9768481,0.0001386818],"about_ca_topic_score_codex":0.005148093,"about_ca_topic_score_gemma":0.013127874,"teacher_disagreement_score":0.993212,"about_ca_system_score_codex":0.0014730948,"about_ca_system_score_gemma":0.0052913935,"threshold_uncertainty_score":0.3410573},"labels":[],"label_agreement":null},{"id":"W4220984722","doi":"10.3389/fneur.2022.835050","title":"Alterations of the White Matter in Patients With Knee Osteoarthritis: A Diffusion Tensor Imaging Study With Tract-Based Spatial Statistics","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Health Commission of Sichuan Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Splenium; Corpus callosum; White matter; Diffusion MRI; Fractional anisotropy; Superior longitudinal fasciculus; Medicine; Corona radiata (embryology); Fasciculus; Cingulum (brain); Inferior longitudinal fasciculus; Magnetic resonance imaging; Anatomy; Internal medicine; Radiology","score_opus":0.0071472348454115755,"score_gpt":0.2394243477610844,"score_spread":0.23227711291567282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220984722","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993247,0.00020197597,0.00022150863,0.000022351509,0.0000018136823,0.000009553574,0.000095369935,0.000004189036,0.00011859352],"genre_scores_gemma":[0.99940085,0.00007100477,0.0003520617,0.000006571137,0.000005545576,0.0000057139287,0.000110136396,0.0000018351715,0.00004612259],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998072,0.00003901167,0.000047520207,0.00004812403,0.000029369612,0.000028882667],"domain_scores_gemma":[0.99885285,0.00012925461,0.00070300547,0.000079600555,0.00012931168,0.0001059152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064011867,0.00038783366,0.0003361816,0.0011416717,0.0003201499,0.0005290338,0.0002166781,0.0003264143,0.0009795869],"category_scores_gemma":[0.0019291056,0.00023716086,0.00033983254,0.000782499,0.00036104512,0.00048407025,0.00042455786,0.00020148733,0.00019130102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005290665,0.000065395514,0.9886594,0.000051785366,0.00017761058,0.0005187295,0.00026232674,0.00017462434,0.0053701773,0.00005879988,0.000094253446,0.0040377607],"study_design_scores_gemma":[0.000022303253,0.00022672646,0.9963174,0.000010569194,0.000073620155,0.0016193477,0.00019250596,0.0009932751,0.00030793037,0.00009794704,0.0001297209,0.000008722343],"about_ca_topic_score_codex":0.003533456,"about_ca_topic_score_gemma":0.0045642024,"teacher_disagreement_score":0.003533456,"about_ca_system_score_codex":0.00026283006,"about_ca_system_score_gemma":0.00029880705,"threshold_uncertainty_score":0.0070257783},"labels":[],"label_agreement":null},{"id":"W4221029104","doi":"10.1016/j.jmr.2022.107205","title":"Orientation dependence of inhomogeneous magnetization transfer and dipolar order relaxation rate in phospholipid bilayers","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries","funders":"Natural Sciences and Engineering Research Council of Canada; International Collaboration on Repair Discoveries","keywords":"Magnetization transfer; Nuclear magnetic resonance; Anisotropy; Dipole; Chemistry; Orientation (vector space); Condensed matter physics; Molecular physics; Materials science; Physics; Optics; Magnetic resonance imaging; Geometry","score_opus":0.021364488013100896,"score_gpt":0.2865378253357739,"score_spread":0.265173337322673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221029104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961576,0.00042495964,0.0021680754,0.00007151497,0.000009688048,0.00000811868,0.0000912541,0.000027736309,0.0010410118],"genre_scores_gemma":[0.9982323,0.0004551087,0.0007598547,0.000021123999,0.000005676004,0.0000053771937,0.00009460044,0.000017910548,0.00040801518],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999347,0.000016489994,0.00000398739,0.000012067672,0.000017357506,0.00001542868],"domain_scores_gemma":[0.99953663,0.00017671568,0.00012505733,0.000026546375,0.00007671185,0.00005822443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025792845,0.0001663164,0.00012130211,0.00025942473,0.0001817578,0.00027860544,0.00019550834,0.00015430289,0.0010395899],"category_scores_gemma":[0.0011815565,0.00019845951,0.000074455194,0.0001782895,0.00024903278,0.00045160326,0.00019052991,0.0005649923,0.00018458381],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014767867,0.0000214192,0.00046993897,0.000035724504,0.000007759756,0.000051937124,0.000056376783,0.00027316075,0.9972134,0.00040723506,0.000042591564,0.0012727547],"study_design_scores_gemma":[0.00002823387,0.00017500181,0.012713697,0.00001108894,0.000026610753,0.00014983724,0.0001374386,0.015333276,0.9703827,0.0003490826,0.00066226517,0.000030823976],"about_ca_topic_score_codex":0.0011377621,"about_ca_topic_score_gemma":0.00112514,"teacher_disagreement_score":0.0011377621,"about_ca_system_score_codex":0.00020065758,"about_ca_system_score_gemma":0.0001762712,"threshold_uncertainty_score":0.0034778118},"labels":[],"label_agreement":null},{"id":"W4221037987","doi":"10.1101/2022.03.22.22272765","title":"Generalized and specific whole-brain white matter abnormalities in human cocaine and heroin use disorders","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Cocaine dependence; Heroin; Diffusion MRI; Psychology; Craving; Medicine; Internal medicine; Psychiatry; Drug; Magnetic resonance imaging; Addiction; Radiology","score_opus":0.06394637745264112,"score_gpt":0.3343087726792535,"score_spread":0.27036239522661243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221037987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99945694,0.00017959897,0.00011702319,0.000006858302,7.6626907e-7,0.000004960163,0.00005138667,0.0000032822686,0.00017927229],"genre_scores_gemma":[0.9994992,0.000108539716,0.00019704223,0.000007675328,0.0000013110342,0.0000036350336,0.00008935908,0.0000018712745,0.0000912363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991584,0.000015317832,0.000009985505,0.00003529341,0.000014222289,0.000009293748],"domain_scores_gemma":[0.9998858,0.000014339941,0.000054753324,0.000017219849,0.000010747219,0.000017155773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017052203,0.00018952343,0.00017781787,0.00077378185,0.00024696995,0.00022224168,0.00009564374,0.00014400465,0.0009308446],"category_scores_gemma":[0.00043188693,0.00013374559,0.00011695647,0.000342754,0.00032036606,0.00013635789,0.00031756298,0.000112433016,0.00007739811],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013339643,0.000105160274,0.88571244,0.000117946234,0.00027349874,0.0019322549,0.00084918534,0.00035491915,0.08574709,0.00022376326,0.000263298,0.023086464],"study_design_scores_gemma":[0.000002792695,0.000043997043,0.9984213,0.0000025307954,0.000009892157,0.0009127648,0.000052450025,0.000095558375,0.00033139452,0.00005459659,0.00007114397,0.0000015516778],"about_ca_topic_score_codex":0.004172639,"about_ca_topic_score_gemma":0.00820123,"teacher_disagreement_score":0.004172639,"about_ca_system_score_codex":0.00014410973,"about_ca_system_score_gemma":0.0001205496,"threshold_uncertainty_score":0.008296728},"labels":[],"label_agreement":null},{"id":"W4221040583","doi":"10.21203/rs.3.rs-1393610/v1","title":"The Influence of Regions of Interest on Tractography Virtual Dissection Protocols: General Principles to Learn and to Follow","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université de Montréal","funders":"National Center for Research Resources; National Institutes of Health; Savoy Foundation; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; Dissection (medical); Computer science; Psychology; Artificial intelligence; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.32864026398653134,"score_gpt":0.5148451807995919,"score_spread":0.1862049168130605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221040583","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030637605,0.00011472148,0.995609,0.00012840061,0.000013346848,0.000042520685,0.000025701855,0.00019312328,0.00080940226],"genre_scores_gemma":[0.13754532,0.000848494,0.8568481,0.00013417406,0.00010773922,0.00046440275,0.00011400558,0.00069557654,0.0032421993],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947461,0.002538216,0.00031718472,0.0008305906,0.0013968752,0.00017103182],"domain_scores_gemma":[0.964528,0.025917362,0.001986265,0.0046297205,0.0023748663,0.0005637699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012358448,0.0016901353,0.0014850723,0.0014482106,0.0009682836,0.0035546334,0.002929757,0.0022089605,0.0033025197],"category_scores_gemma":[0.07552021,0.0015630889,0.0014493294,0.0010226162,0.004604077,0.0049200235,0.00422788,0.0034722972,0.0012055977],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004668646,0.00019882867,0.0038815865,0.0008653374,0.00029235988,0.00067216833,0.001705412,0.2767903,0.052649766,0.27104467,0.0044234726,0.38700917],"study_design_scores_gemma":[0.000058475132,0.00037690546,0.0022584025,0.00019255313,0.00016666102,0.0007138521,0.00015640445,0.65609264,0.043078132,0.28920877,0.0075987247,0.000098395016],"about_ca_topic_score_codex":0.0029088778,"about_ca_topic_score_gemma":0.0028707914,"teacher_disagreement_score":0.012358448,"about_ca_system_score_codex":0.0011386501,"about_ca_system_score_gemma":0.0025146394,"threshold_uncertainty_score":0.06535846},"labels":[],"label_agreement":null},{"id":"W4221046825","doi":"10.21203/rs.3.rs-1423555/v1","title":"The Structural Connectivity of The Human Angular Gyrus as Revealed by Microdissection and Diffusion Tractography","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Angular gyrus; Microdissection; Diffusion MRI; Diffusion; Neuroscience; Psychology; Computer science; Physics; Biology; Medicine; Radiology; Magnetic resonance imaging; Gene; Genetics; Cognition","score_opus":0.07222415710054751,"score_gpt":0.4551734764729809,"score_spread":0.38294931937243337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221046825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97640467,0.0011305232,0.017425459,0.00032085186,0.000018533894,0.00001606205,0.00047428647,0.0000915096,0.004118239],"genre_scores_gemma":[0.99068224,0.0005995679,0.00690776,0.000026900767,0.000018108818,0.000012478359,0.00019008935,0.00002127194,0.0015417067],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994695,0.000008916431,0.0000023775642,0.000023389284,0.0000110736955,0.0000073002207],"domain_scores_gemma":[0.9998116,0.00008711425,0.000047848793,0.00002265312,0.000016202504,0.000014618269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001308631,0.00013171414,0.0000831527,0.00055354263,0.0002231609,0.00043350586,0.00012120093,0.00017767091,0.001884502],"category_scores_gemma":[0.0010774384,0.0001431019,0.00008268177,0.00057565764,0.00055098307,0.00048685927,0.00020607971,0.00015541952,0.00032769705],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013427456,0.000052161977,0.052250274,0.00023133178,0.00013575063,0.001048578,0.0018775448,0.0045439685,0.80574703,0.018687109,0.001429517,0.11265408],"study_design_scores_gemma":[0.00006858902,0.00030207,0.82711446,0.000039195882,0.00014693305,0.00395114,0.0007847569,0.014587856,0.11848427,0.023829117,0.010639873,0.000051788327],"about_ca_topic_score_codex":0.005737195,"about_ca_topic_score_gemma":0.0076289927,"teacher_disagreement_score":0.005737195,"about_ca_system_score_codex":0.00022391495,"about_ca_system_score_gemma":0.0003439049,"threshold_uncertainty_score":0.011407554},"labels":[],"label_agreement":null},{"id":"W4221101861","doi":"10.3174/ajnr.a7472","title":"Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates—A Quantitative MRI Study","year":2022,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Child, Adolescent and Family Mental Health","funders":"","keywords":"Fractional anisotropy; Medicine; Internal capsule; Diffusion MRI; Gestational age; Effective diffusion coefficient; Pons; Gestation; Tegmentum; Nuclear medicine; Magnetic resonance imaging; Midbrain; Anatomy; Internal medicine; White matter; Radiology; Pregnancy; Central nervous system","score_opus":0.0733770881790462,"score_gpt":0.3562800812240091,"score_spread":0.2829029930449629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221101861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995721,0.000094997915,0.00008671049,0.00000606236,0.0000010245151,0.0000024321341,0.000079405974,0.0000014502757,0.00015574998],"genre_scores_gemma":[0.9996842,0.00005554483,0.00011983641,0.0000067677715,0.0000028520747,0.0000070597125,0.00006309397,0.0000025850352,0.000058005833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971336,0.00006460262,0.00004120939,0.00008819443,0.000059781167,0.000032742948],"domain_scores_gemma":[0.99847156,0.00029550708,0.0008488933,0.00012858365,0.00013536579,0.0001200902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068876456,0.000266487,0.00019751904,0.0010613697,0.00015006331,0.0004941961,0.00026085807,0.00030160992,0.0006924275],"category_scores_gemma":[0.0038616832,0.00011969042,0.00020588368,0.00038272914,0.0003062854,0.00038459754,0.00036802102,0.00018686094,0.00016984211],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035303563,0.000033861128,0.9870881,0.000025006711,0.000046455403,0.0005317625,0.00050473126,0.000059056434,0.0036418715,0.00007555184,0.00004201982,0.0075985934],"study_design_scores_gemma":[0.0000023474713,0.00016644954,0.9965031,0.000009795834,0.000015332991,0.0018747338,0.00037524404,0.00013137478,0.00072647247,0.000040337913,0.00014989727,0.0000048897004],"about_ca_topic_score_codex":0.0007606445,"about_ca_topic_score_gemma":0.0004701947,"teacher_disagreement_score":0.0010613697,"about_ca_system_score_codex":0.0002173599,"about_ca_system_score_gemma":0.00014637293,"threshold_uncertainty_score":0.003642559},"labels":[],"label_agreement":null},{"id":"W4221112866","doi":"10.1016/j.neuroimage.2022.119029","title":"An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek; National Institutes of Health","keywords":"Diffusion MRI; Tractography; White matter; Human Connectome Project; Fractional anisotropy; Anatomy; Computer science; Fornix; Artificial intelligence; Reproducibility; Pattern recognition (psychology); Neuroscience; Psychology; Biology; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Functional connectivity","score_opus":0.030804057224314514,"score_gpt":0.33078766648538926,"score_spread":0.29998360926107476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221112866","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0831788,0.0009752692,0.9037974,0.00018362989,0.00007421611,0.00013231991,0.0037398974,0.004214161,0.0037043586],"genre_scores_gemma":[0.36265916,0.00142344,0.6238523,0.000118029544,0.000042866715,0.00046980666,0.00645417,0.00233494,0.002645286],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989441,0.0002420883,0.00012090173,0.0003470423,0.00030230754,0.00004358955],"domain_scores_gemma":[0.9977259,0.0005284048,0.00029275526,0.0009200903,0.00047632208,0.00005659208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002735481,0.0005753241,0.0005862997,0.0023907812,0.0007100888,0.0020495076,0.00074684946,0.0006916226,0.0020289691],"category_scores_gemma":[0.005063137,0.0005592998,0.0006723996,0.0025262728,0.00088506716,0.0011622825,0.0012515873,0.00080662535,0.0011704782],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052621396,0.00013054952,0.034125756,0.0010852667,0.0007205506,0.0006977878,0.002252801,0.07340735,0.20407309,0.037916783,0.019372787,0.62569106],"study_design_scores_gemma":[0.00009468968,0.0006886058,0.25070858,0.00059504196,0.0008416876,0.010188644,0.00081114616,0.29813483,0.19813545,0.10222929,0.13699189,0.0005801408],"about_ca_topic_score_codex":0.003425506,"about_ca_topic_score_gemma":0.0065600434,"teacher_disagreement_score":0.003425506,"about_ca_system_score_codex":0.0007113842,"about_ca_system_score_gemma":0.0014705145,"threshold_uncertainty_score":0.014466763},"labels":[],"label_agreement":null},{"id":"W4223539301","doi":"10.1016/j.nicl.2022.103002","title":"Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; Alberta Health Services; University of Calgary; Women and Children’s Health Research Institute; University of Alberta","funders":"Consortium canadien en neurodégénérescence associée au vieillissement; Canada Research Chairs; Canadian Stroke Network; Heart and Stroke Foundation of Canada; Canadian Institutes of Health Research; Alzheimer Society; Fondation Brain Canada","keywords":"Cerebral amyloid angiopathy; Fornix; Diffusion MRI; Tractography; Medicine; Cognitive impairment; Disease; Neuroscience; Alzheimer's disease; Amyloid (mycology); Cognition; Psychology; Pathology; Magnetic resonance imaging; Dementia; Hippocampus; Radiology","score_opus":0.10528279284658656,"score_gpt":0.3941783179935285,"score_spread":0.28889552514694194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223539301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984786,0.000651664,0.0003764827,0.000039272658,0.0000034813145,0.000017372575,0.00009863706,0.000007513195,0.000327014],"genre_scores_gemma":[0.99885964,0.00019622048,0.00064962904,0.0000096180875,0.0000052788787,0.000011528141,0.00009355037,0.000003043676,0.00017163837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998627,0.000036220288,0.000017668053,0.000035899917,0.000026758664,0.000020820857],"domain_scores_gemma":[0.9994369,0.00006234307,0.00033723723,0.00004211501,0.000049480233,0.00007186449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006463795,0.00044321825,0.00024975205,0.0010378299,0.00032191587,0.0004195761,0.0002080106,0.00037047028,0.000882881],"category_scores_gemma":[0.0015983781,0.00015064338,0.00020559474,0.00043149968,0.00051655975,0.0004112857,0.00032590778,0.00017906501,0.00012767698],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002415904,0.000120073855,0.9137354,0.00029243092,0.00043279785,0.003205702,0.001271354,0.0010585785,0.051310398,0.00044084646,0.00045528857,0.02526124],"study_design_scores_gemma":[0.000023576817,0.00015388773,0.9941835,0.00002121008,0.000036415353,0.0028595147,0.00013350617,0.0006890859,0.0011290692,0.00043186094,0.00032967556,0.000008785974],"about_ca_topic_score_codex":0.0090250075,"about_ca_topic_score_gemma":0.013052411,"teacher_disagreement_score":0.0090250075,"about_ca_system_score_codex":0.00057874975,"about_ca_system_score_gemma":0.0004724933,"threshold_uncertainty_score":0.017944932},"labels":[],"label_agreement":null},{"id":"W4223585515","doi":"10.1101/2022.04.06.487283","title":"DeepParcellation: a novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Research Foundation; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; Ministry of Science and ICT, South Korea; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Korea Brain Research Institute; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Magnetic resonance imaging; Dementia; Similarity (geometry); Brain aging; Neuroscience; Psychology; Brain morphometry; Medicine; Artificial intelligence; Computer science; Pathology; Cognition; Disease; Radiology","score_opus":0.036701757709266446,"score_gpt":0.30073401899341573,"score_spread":0.2640322612841493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223585515","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22644335,0.0013102411,0.76110864,0.0006600399,0.00021372437,0.00011704353,0.0015030507,0.0066975346,0.0019464698],"genre_scores_gemma":[0.75601006,0.0003917311,0.23118521,0.000509761,0.00012454657,0.00016078008,0.0042209877,0.0005748681,0.006822058],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970907,0.000054098382,0.000016301927,0.000113276124,0.000042359574,0.00006486416],"domain_scores_gemma":[0.99959356,0.00010503919,0.000050552586,0.0000895489,0.00012449396,0.000036874335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010808768,0.0011961586,0.0008227991,0.0007826862,0.00047073507,0.000715826,0.0013838869,0.0008270106,0.0018209317],"category_scores_gemma":[0.0015834015,0.00035736017,0.0010420161,0.00070451206,0.00041861247,0.0007025205,0.0013787145,0.0014098837,0.00073574105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008013341,0.00023910655,0.018818337,0.00014589017,0.0005186738,0.0005164435,0.000528294,0.2668531,0.039136454,0.0036498047,0.019008834,0.64978373],"study_design_scores_gemma":[0.000020678586,0.00004879439,0.0028324923,0.000010011677,0.00003845719,0.00008771497,0.00004859211,0.9836963,0.008799386,0.001819811,0.0025790923,0.000018555389],"about_ca_topic_score_codex":0.018713767,"about_ca_topic_score_gemma":0.022590553,"teacher_disagreement_score":0.018713767,"about_ca_system_score_codex":0.00074909366,"about_ca_system_score_gemma":0.00091527926,"threshold_uncertainty_score":0.03720969},"labels":[],"label_agreement":null},{"id":"W4223652742","doi":"10.1093/brain/awac138","title":"Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; European Research Council; Stiftelsen för Gamla Tjänarinnor; Familjen Erling-Perssons Stiftelse; School of Medicine, Indiana University; Vetenskapsrådet; UK Dementia Research Institute; National Institutes of Health; Olav Thon Stiftelsen; Hjärnfonden; European Commission; Alzheimer's Drug Discovery Foundation; National Institute on Aging; Alzheimer's Association","keywords":"Hippocampal formation; Alzheimer's disease; Psychology; Dementia; Neuroscience; Pathology; Dentate gyrus; Medicine; Disease","score_opus":0.043931317747419346,"score_gpt":0.32520332046530426,"score_spread":0.2812720027178849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223652742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995634,0.00021438774,0.00009157396,0.000004867105,9.855436e-7,0.000003335915,0.000049091184,0.0000017126517,0.000070713955],"genre_scores_gemma":[0.99968266,0.000070680995,0.00014604827,0.000003291443,0.0000023280293,0.0000027972262,0.000049043083,6.8284265e-7,0.000042470903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991,0.00002149622,0.000013030061,0.000029706258,0.000016585378,0.000009214495],"domain_scores_gemma":[0.9994967,0.000085594336,0.0002610613,0.000049375292,0.00005573784,0.000051529023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036139102,0.00021885886,0.00024516042,0.00067850045,0.00021774882,0.0002848298,0.00014707695,0.00027787857,0.00055363495],"category_scores_gemma":[0.0012630762,0.00022449833,0.00014243483,0.00050355966,0.00017946858,0.0002462068,0.00023375574,0.0002007678,0.00007660875],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085335097,0.000057456215,0.9897871,0.000025125837,0.000111294925,0.0001446935,0.00028497312,0.00024287774,0.0049924017,0.000044795233,0.00003669753,0.0034192407],"study_design_scores_gemma":[0.0000068516324,0.00009621143,0.9987373,0.0000023759928,0.000021938169,0.0002487494,0.00006443844,0.00034765145,0.00033412132,0.00008661486,0.000051053616,0.0000027964443],"about_ca_topic_score_codex":0.0028194927,"about_ca_topic_score_gemma":0.0020963547,"teacher_disagreement_score":0.0028194927,"about_ca_system_score_codex":0.00016654175,"about_ca_system_score_gemma":0.00009867038,"threshold_uncertainty_score":0.005606115},"labels":[],"label_agreement":null},{"id":"W4223898804","doi":"10.1371/journal.pone.0265112","title":"Getting the nod: Pediatric head motion in a transdiagnostic sample during movie- and resting-state fMRI","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital; University of Waterloo","funders":"BC Children's Hospital","keywords":"Motion (physics); Artifact (error); Motion sickness; Artificial intelligence; Rotation (mathematics); Computer science; Translation (biology); Head (geology); Computer vision; Psychology; Biology","score_opus":0.08971848270196725,"score_gpt":0.30490450389511703,"score_spread":0.21518602119314978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223898804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931641,0.00033206996,0.003023504,0.00017228154,0.000019123434,0.000035683457,0.0025017322,0.000041498,0.00070983777],"genre_scores_gemma":[0.986906,0.00030220376,0.005303118,0.0001751383,0.000046092853,0.00011594153,0.006513383,0.000059550028,0.0005785843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995919,0.00010744753,0.000049740476,0.00013974562,0.00005596004,0.00005525753],"domain_scores_gemma":[0.9994029,0.000119391516,0.00017540163,0.00012047224,0.00012521638,0.00005670407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060865,0.00027173405,0.0002678286,0.00045947562,0.0003268147,0.00038029687,0.00029032023,0.00034287985,0.0011493373],"category_scores_gemma":[0.002425566,0.00014197409,0.00022083512,0.0004600517,0.00027164264,0.00031523488,0.00053852814,0.00024442477,0.0003706888],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001089941,0.00014177039,0.8778548,0.00038705178,0.0002307415,0.0025777542,0.004631381,0.00042980682,0.03964738,0.00058882806,0.00856607,0.063854374],"study_design_scores_gemma":[0.000016491114,0.0001004883,0.98764765,0.00004088057,0.00009028896,0.003416076,0.0015068984,0.0006313644,0.0030450507,0.00026060827,0.0032255726,0.000018649478],"about_ca_topic_score_codex":0.004814301,"about_ca_topic_score_gemma":0.016923836,"teacher_disagreement_score":0.004814301,"about_ca_system_score_codex":0.00020408927,"about_ca_system_score_gemma":0.00023386498,"threshold_uncertainty_score":0.009572566},"labels":[],"label_agreement":null},{"id":"W4223972788","doi":"10.31234/osf.io/kt5gz","title":"Beyond the brain localization of complex traits: Distributed white matter markers of personality","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Government of Canada; University of Oregon","keywords":"Neuroimaging; Neuroticism; Psychology; Big Five personality traits; Univariate; White matter; Personality; Diffusion MRI; Multivariate statistics; Openness to experience; Cognitive psychology; Computer science; Neuroscience; Machine learning; Social psychology; Magnetic resonance imaging; Medicine","score_opus":0.061644776505234054,"score_gpt":0.3498774670672752,"score_spread":0.28823269056204115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223972788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843106,0.00020785136,0.014250134,0.00027430835,0.00001248385,0.000016848513,0.00015176958,0.000036249316,0.0007396796],"genre_scores_gemma":[0.9977106,0.000045325934,0.0018757305,0.00003298142,0.000010164268,0.0000065321433,0.0000788564,0.00000981416,0.00022999867],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942565,0.00026203695,0.00001950943,0.0001941802,0.000052383955,0.000046180514],"domain_scores_gemma":[0.9942649,0.0023483532,0.00097424525,0.001770925,0.00030271278,0.00033880328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025908598,0.00051977974,0.0005675804,0.0005748207,0.00042271777,0.0014234227,0.00047225622,0.00038869126,0.0021983103],"category_scores_gemma":[0.009226733,0.00023434641,0.00041037897,0.0006063522,0.0009559983,0.0010440034,0.00080898573,0.0010549015,0.00024722322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084327307,0.00023163063,0.87022203,0.00015794543,0.0010096595,0.0004937497,0.0032032593,0.0064307465,0.035811994,0.004030046,0.0011167787,0.07644899],"study_design_scores_gemma":[0.000023470404,0.00015060253,0.9698146,0.000030695548,0.000105129286,0.0003292051,0.00046549513,0.016291365,0.0027506533,0.009521011,0.0004951842,0.00002269356],"about_ca_topic_score_codex":0.004290868,"about_ca_topic_score_gemma":0.0059223236,"teacher_disagreement_score":0.004290868,"about_ca_system_score_codex":0.0002679134,"about_ca_system_score_gemma":0.00040775072,"threshold_uncertainty_score":0.013701975},"labels":[],"label_agreement":null},{"id":"W4224041279","doi":"10.1101/2022.04.01.486632","title":"Microstructural alterations in tract development in college football: a longitudinal diffusion MRI study","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Diffusion MRI; Concussion; Fractional anisotropy; Football; Corpus callosum; Psychology; Cingulum (brain); White matter; Superior longitudinal fasciculus; Medicine; Fasciculus; American football; Physical therapy; Nuclear medicine; Magnetic resonance imaging; Anatomy; Poison control; Radiology; Injury prevention","score_opus":0.041154211829111435,"score_gpt":0.3058215730080448,"score_spread":0.26466736117893336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224041279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961674,0.00007782112,0.0001358461,0.00000815431,7.4244036e-7,0.000009083364,0.0000716043,0.0000032278324,0.00007675378],"genre_scores_gemma":[0.99945,0.000040866857,0.00019177132,0.0000051242073,0.0000023038403,0.000010084281,0.00013580931,0.0000016374358,0.00016248312],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998,0.000032991473,0.000015633103,0.00007045877,0.000022639317,0.000058252215],"domain_scores_gemma":[0.9992192,0.000066640714,0.0003587573,0.00007667417,0.00012627771,0.00015244962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060013786,0.00027993807,0.00018702011,0.0009240857,0.00047777986,0.00043369268,0.00024995595,0.00041713938,0.001249125],"category_scores_gemma":[0.0011524771,0.00024816123,0.00022868038,0.00045892384,0.00036803313,0.0004464537,0.00047866578,0.0002617622,0.00022984612],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005513727,0.00018790094,0.9864804,0.000021027265,0.00008132368,0.0003585458,0.00040218903,0.00013916484,0.006511984,0.00003238524,0.000059860442,0.0051738764],"study_design_scores_gemma":[0.0000047592785,0.00015357713,0.99871874,0.00000531518,0.000018141865,0.00031364587,0.000148289,0.00021490862,0.00031887417,0.000018722249,0.00008140241,0.0000035285818],"about_ca_topic_score_codex":0.01538744,"about_ca_topic_score_gemma":0.019114798,"teacher_disagreement_score":0.01538744,"about_ca_system_score_codex":0.0004684062,"about_ca_system_score_gemma":0.0005543879,"threshold_uncertainty_score":0.03059578},"labels":[],"label_agreement":null},{"id":"W4224122545","doi":"10.3390/curroncol29040230","title":"DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects","year":2022,"lang":"en","type":"article","venue":"Current Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Metastasis; Effective diffusion coefficient; Pathology; Lesion; White matter; Magnetic resonance imaging; Nuclear medicine; Glioblastoma; Internal medicine; Radiology; Cancer; Cancer research","score_opus":0.17464533463702409,"score_gpt":0.47267599084693895,"score_spread":0.29803065620991487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224122545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99964213,0.00008890753,0.000052696065,0.000005345268,0.0000028240208,0.000009208249,0.00006235158,0.0000011000656,0.00013553769],"genre_scores_gemma":[0.9995104,0.000057625366,0.00005108159,0.000016200576,0.000010930625,0.000012083243,0.00019879833,0.0000015878254,0.00014132584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997472,0.0000343804,0.000020325044,0.00011649367,0.000029631003,0.000051829553],"domain_scores_gemma":[0.99970883,0.00003822761,0.000080779784,0.000028472896,0.000028620614,0.00011507377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003349054,0.0004609274,0.00049223,0.0008577119,0.0008165466,0.00046557063,0.0001851998,0.00056022493,0.0019422338],"category_scores_gemma":[0.00069272256,0.00031384974,0.00035882127,0.0006799424,0.00040496085,0.0005179158,0.00046498206,0.00034303893,0.0004484329],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073863217,0.00020248251,0.995488,0.00001118115,0.000058337435,0.0005161728,0.00021998708,0.00001800241,0.0015338721,0.000021993916,0.00004124909,0.001149989],"study_design_scores_gemma":[0.000016840104,0.0006856853,0.99785525,0.0000019319789,0.000038836715,0.0008181454,0.00028731851,0.00004621215,0.00008712307,0.000021246005,0.00013759988,0.0000039204015],"about_ca_topic_score_codex":0.0022768248,"about_ca_topic_score_gemma":0.0022820516,"teacher_disagreement_score":0.0022768248,"about_ca_system_score_codex":0.00021166042,"about_ca_system_score_gemma":0.00022815987,"threshold_uncertainty_score":0.0064974427},"labels":[],"label_agreement":null},{"id":"W4224223785","doi":"10.3390/brainsci12040482","title":"Association between Changes in White Matter Microstructure and Cognitive Impairment in White Matter Lesions","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Fractional anisotropy; Inferior longitudinal fasciculus; Diffusion MRI; Fasciculus; White matter; Hyperintensity; Superior longitudinal fasciculus; Corticospinal tract; Uncinate fasciculus; Psychology; Medicine; Cardiology; Audiology; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.03759646584237306,"score_gpt":0.34284817022069564,"score_spread":0.30525170437832255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224223785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99953306,0.000172413,0.000058603368,0.0000129670225,0.000002104903,0.0000038878034,0.000057175166,0.000002424425,0.00015727544],"genre_scores_gemma":[0.9997404,0.00004814988,0.000051911364,0.0000055771934,0.0000065020936,0.000002466147,0.00007651871,7.4573853e-7,0.000067607885],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982136,0.00002863514,0.000031189986,0.000055327273,0.00003289472,0.000030629515],"domain_scores_gemma":[0.99906033,0.00013261348,0.0004966408,0.00005647538,0.00010170718,0.00015220199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003142318,0.00042825477,0.000348416,0.0011598041,0.00033894033,0.00040891478,0.0002033306,0.00041726645,0.00095792935],"category_scores_gemma":[0.0017903176,0.00017490136,0.00024110677,0.00056102965,0.0002921687,0.00034145842,0.00035306328,0.00033873957,0.0001669599],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004108557,0.000071559065,0.99449474,0.000019680976,0.00013009206,0.0003391312,0.0001230555,0.00006522763,0.0015303482,0.000026590445,0.000037443973,0.0027512927],"study_design_scores_gemma":[0.0000044924964,0.00012518022,0.999059,0.0000020216696,0.000020539012,0.0005023095,0.00004512827,0.00007622506,0.000096445205,0.000030069621,0.000036334553,0.0000022802324],"about_ca_topic_score_codex":0.0018976317,"about_ca_topic_score_gemma":0.0022999668,"teacher_disagreement_score":0.0018976317,"about_ca_system_score_codex":0.00017859167,"about_ca_system_score_gemma":0.00015469226,"threshold_uncertainty_score":0.0037731528},"labels":[],"label_agreement":null},{"id":"W4224248311","doi":"10.1111/ejn.15668","title":"Sulci and gyri are topological cerebral landmarks in individual subjects: a study of brain navigation during tumour resection","year":2022,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Neuronavigation; Corticospinal tract; Tractography; Diffusion MRI; Medicine; Lesion; Human brain; Magnetic resonance imaging; Cortex (anatomy); Resection; Transcranial magnetic stimulation; Pyramidal tracts; Neuroscience; Neuroplasticity; Anatomy; Brain mapping; Psychology; Radiology; Pathology; Surgery; Stimulation","score_opus":0.08499377395791288,"score_gpt":0.3500477181503772,"score_spread":0.2650539441924643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224248311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980678,0.00020203595,0.0010382003,0.000020027785,0.000006438391,0.000012788832,0.000052556006,0.000018135972,0.00058205996],"genre_scores_gemma":[0.9991272,0.00009246982,0.00042338212,0.0000079107385,0.00000848208,0.000005453095,0.000051203864,0.000008921194,0.00027504633],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.000023926255,0.000007671161,0.000043507946,0.000016869386,0.000015419955],"domain_scores_gemma":[0.99975497,0.000065590095,0.00006948451,0.00004764796,0.000030820425,0.000031445095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018307047,0.00028887566,0.00021575554,0.00045897966,0.00019351425,0.00027332085,0.000116212854,0.00027290266,0.00080192037],"category_scores_gemma":[0.0011144286,0.00012516398,0.00012498698,0.0003032381,0.0004984055,0.0003240124,0.0002440943,0.00016115716,0.00024341403],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013608771,0.00026743519,0.7211423,0.00024772566,0.00037282446,0.016024351,0.011743987,0.0011092124,0.12866697,0.0006246303,0.0008778509,0.11756181],"study_design_scores_gemma":[0.000007752694,0.00058171636,0.9821232,0.000008176241,0.000050879516,0.010185074,0.0013490238,0.0006384635,0.0035242997,0.0003008089,0.0012058226,0.000024853613],"about_ca_topic_score_codex":0.0014421949,"about_ca_topic_score_gemma":0.0028904015,"teacher_disagreement_score":0.0014421949,"about_ca_system_score_codex":0.000080441314,"about_ca_system_score_gemma":0.00013667709,"threshold_uncertainty_score":0.0028675795},"labels":[],"label_agreement":null},{"id":"W4224438895","doi":"10.1002/hbm.25885","title":"Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: An<scp>A‐CAP</scp>study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia; University of Alberta; Ontario Brain Institute; Université de Montréal; Hotchkiss Brain Institute; Centre Hospitalier Universitaire Sainte-Justine; University of Ottawa; Stollery Children's Hospital; Alberta Children's Hospital; Children's Hospital of Eastern Ontario; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Traumatic brain injury; Medicine; Superior longitudinal fasciculus; Concussion; Post-concussion syndrome; Poison control; Diffusion MRI; Uncinate fasciculus; Pediatrics; Anesthesia; Injury prevention; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.10865613396813091,"score_gpt":0.36390818923137197,"score_spread":0.2552520552632411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224438895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994093,0.000109551846,0.000053610038,0.00001567335,0.0000021526896,0.000009975869,0.00028763266,0.0000021674164,0.000109924],"genre_scores_gemma":[0.9986834,0.00022500222,0.00020973233,0.000025901783,0.000009821442,0.000030056395,0.0007223459,0.0000028475215,0.00009090825],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995536,0.00009775951,0.000051154002,0.0001246079,0.00009813006,0.00007463291],"domain_scores_gemma":[0.99833244,0.00015664178,0.0007292175,0.0002049027,0.00035363348,0.00022327156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081202335,0.00041116885,0.00030795674,0.00074526225,0.0005800497,0.0005680405,0.00034097,0.00034762276,0.00081276696],"category_scores_gemma":[0.0023134924,0.00031094888,0.0005537687,0.0010136106,0.00031317695,0.0004703617,0.0004156901,0.00045407476,0.00027607603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008151947,0.000050696886,0.9976687,0.000014947034,0.0000710894,0.00013971119,0.00014199594,0.00003055284,0.00020080553,0.000013415196,0.00012998258,0.0014565331],"study_design_scores_gemma":[0.000006707778,0.00017489026,0.99898213,0.000008495695,0.000032667336,0.00035649008,0.00014611555,0.000054765176,0.00006604921,0.000006501525,0.00016339854,0.0000018236907],"about_ca_topic_score_codex":0.029667538,"about_ca_topic_score_gemma":0.029278085,"teacher_disagreement_score":0.029667538,"about_ca_system_score_codex":0.0006438335,"about_ca_system_score_gemma":0.0009999488,"threshold_uncertainty_score":0.058989704},"labels":[],"label_agreement":null},{"id":"W4224927688","doi":"10.3389/fneur.2022.794618","title":"Superior Longitudinal Fasciculus: A Review of the Anatomical Descriptions With Functional Correlates","year":2022,"lang":"en","type":"review","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":181,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Arcuate fasciculus; Confusion; Uncinate fasciculus; Superior longitudinal fasciculus; Lateralization of brain function; Tractography; Diffusion MRI; Psychology; Neuroscience; Frontal lobe; Association (psychology); Anatomy; Medicine; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.09409050236680269,"score_gpt":0.34079267399001545,"score_spread":0.24670217162321276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224927688","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013655875,0.99896336,0.0000923217,0.00017129496,0.00011070883,0.000004620256,0.00003093227,0.000004644846,0.00048563362],"genre_scores_gemma":[0.00078841246,0.9984883,0.00024480827,0.000138046,0.00014271261,0.0000072945095,0.000042412074,0.0000016603128,0.00014633847],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996582,0.000052077765,0.00011746789,0.00006834071,0.00008236674,0.000021478472],"domain_scores_gemma":[0.99875855,0.0007350703,0.00022044225,0.00003102971,0.00020849708,0.000046330402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084508845,0.0012416348,0.0014977312,0.008241931,0.00037188127,0.001254337,0.0011289482,0.00086610933,0.0040020095],"category_scores_gemma":[0.002505593,0.0004323942,0.0008310292,0.0070885033,0.0008232135,0.0024373136,0.00079682027,0.0012702249,0.0014279583],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108129476,0.000052249463,0.0006878239,0.08106912,0.00025565253,0.0006118371,0.00031205188,0.0003112331,0.0011284502,0.003738673,0.026283165,0.8854416],"study_design_scores_gemma":[0.0000237734,0.0001341719,0.0050511756,0.05343615,0.0009276899,0.009015766,0.0004054364,0.0001373503,0.00050326105,0.0040447675,0.92625487,0.00006546604],"about_ca_topic_score_codex":0.002106532,"about_ca_topic_score_gemma":0.0033387472,"teacher_disagreement_score":0.008241931,"about_ca_system_score_codex":0.00071581407,"about_ca_system_score_gemma":0.002226837,"threshold_uncertainty_score":0.013388038},"labels":[],"label_agreement":null},{"id":"W4224938342","doi":"10.3389/fnagi.2022.787516","title":"Modeling the Properties of White Matter Tracts Using Diffusion Tensor Imaging to Characterize Patterns of Injury in Aging and Neurodegenerative Disease","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Meso Scale Diagnostics; Medical Research Council; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Ventriculomegaly; Tractography; Atlas (anatomy); Internal capsule; Magnetic resonance imaging; Neuroimaging; Neuroscience; Medicine; Psychology; Radiology; Anatomy; Biology","score_opus":0.04696226911690202,"score_gpt":0.2971753095410107,"score_spread":0.25021304042410863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224938342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.425086,0.00071851246,0.57155704,0.00015005922,0.000025388917,0.00016121742,0.0007401072,0.00062925793,0.00093249936],"genre_scores_gemma":[0.8710266,0.0006426498,0.12650873,0.000028173054,0.000020761327,0.00022837908,0.0005860228,0.00007495423,0.00088374515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998301,0.00006274415,0.000016027254,0.00004685322,0.000029025816,0.000015157202],"domain_scores_gemma":[0.99954,0.00021959981,0.00011557902,0.00005214764,0.000053701686,0.000018934956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009595101,0.00076311955,0.0004140567,0.0011179338,0.00021220197,0.0007820879,0.0004679082,0.0005843922,0.00043453602],"category_scores_gemma":[0.0022102937,0.00030823314,0.00081232056,0.00059930846,0.00031499605,0.0006536243,0.0003785933,0.00035404158,0.00019912806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000118289165,0.00008008228,0.024545075,0.0001390407,0.00019879581,0.00016546929,0.00016876859,0.9071952,0.025203433,0.0022046333,0.0004258595,0.03955547],"study_design_scores_gemma":[0.0000055535866,0.00005909573,0.0072589996,0.000010082655,0.000019906412,0.000075884534,0.000017968687,0.9885515,0.0017844182,0.0018307265,0.000372579,0.000013198759],"about_ca_topic_score_codex":0.008569861,"about_ca_topic_score_gemma":0.009446832,"teacher_disagreement_score":0.008569861,"about_ca_system_score_codex":0.0004569061,"about_ca_system_score_gemma":0.00074277894,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4224946110","doi":"10.1101/2022.01.27.477925","title":"High spatial overlap but diverging age-related trajectories of cortical MRI markers aiming to represent intracortical myelin and microstructure","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Weston Brain Institute","keywords":"White matter; Magnetic resonance imaging; Myelin; Correlation; Nuclear magnetic resonance; Neuroscience; Psychology; Medicine; Mathematics; Physics; Radiology; Central nervous system; Geometry","score_opus":0.017823158920201615,"score_gpt":0.2704345351924193,"score_spread":0.25261137627221764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224946110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978447,0.00026484323,0.0012925598,0.0000075874473,0.0000022338286,0.0000050110334,0.0001499304,0.000026596032,0.000406443],"genre_scores_gemma":[0.9986765,0.000061922874,0.00071563077,0.0000040721766,0.000003152895,0.0000057829575,0.00023879172,0.000012342494,0.00028185284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970347,0.00004851809,0.000026019345,0.00010262487,0.00007661235,0.00004273409],"domain_scores_gemma":[0.9983,0.0005143953,0.0005080457,0.00022506433,0.00033232704,0.00012017473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008018467,0.000306021,0.0003133122,0.0014761342,0.00016812787,0.0004133914,0.00018048656,0.00029636314,0.0010444705],"category_scores_gemma":[0.0023526442,0.00021838484,0.00014315922,0.00056310935,0.0003355017,0.00032864945,0.00063693285,0.0002285725,0.00026560153],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001808161,0.00007864903,0.67871135,0.00013573971,0.00024785628,0.00068650243,0.001984886,0.0014799674,0.26361728,0.00038958737,0.00029452055,0.050565556],"study_design_scores_gemma":[0.000003552572,0.00013642845,0.9919412,0.0000042835322,0.00001890111,0.00039197173,0.00014384699,0.0005417878,0.0064576976,0.0001617491,0.00019096055,0.0000076422175],"about_ca_topic_score_codex":0.0011037445,"about_ca_topic_score_gemma":0.0012569478,"teacher_disagreement_score":0.0014761342,"about_ca_system_score_codex":0.00012465562,"about_ca_system_score_gemma":0.000118242795,"threshold_uncertainty_score":0.004240632},"labels":[],"label_agreement":null},{"id":"W4224993524","doi":"10.1016/j.biopsych.2022.02.397","title":"P163. Fiber Density vs. Dispersion in 16p11.2 Deletion: A Multi-Site Study of Advanced Diffusion MRI Measures","year":2022,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Dispersion (optics); Kurtosis; White matter; Nuclear magnetic resonance; Fiber; Autism; Autism spectrum disorder; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Materials science; Physics; Mathematics; Statistics; Optics; Radiology; Developmental psychology","score_opus":0.07287817465902083,"score_gpt":0.34748943342616767,"score_spread":0.27461125876714687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224993524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993455,0.00007531938,0.00032900568,0.000009564649,0.0000018690482,0.0000029191044,0.00008996737,0.0000054267557,0.0001403463],"genre_scores_gemma":[0.99916124,0.000041526768,0.00038210166,0.000005740586,0.000005927858,0.0000071745967,0.00010246792,0.000015012299,0.0002788777],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967337,0.000088723034,0.000032233194,0.00011679296,0.000056454715,0.000032506705],"domain_scores_gemma":[0.997233,0.00086510176,0.0011737702,0.00022883687,0.00022084039,0.00027841437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010825167,0.0004582921,0.0003661182,0.0011988477,0.000247838,0.0005352854,0.0004395353,0.0007187353,0.0015860089],"category_scores_gemma":[0.0027876692,0.000290616,0.00025684453,0.0006787614,0.00047311524,0.00051862694,0.0005343362,0.00056878565,0.0002723654],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0052825254,0.00034125708,0.8548785,0.00008429115,0.0007315639,0.0032245698,0.0012902,0.0013721037,0.11575952,0.00038692457,0.00021185538,0.016436744],"study_design_scores_gemma":[0.00002563714,0.00039043053,0.9906465,0.000012849935,0.00011984443,0.0032267107,0.00026379773,0.0012073182,0.0037238519,0.00019376942,0.00017208555,0.000017207762],"about_ca_topic_score_codex":0.0017421999,"about_ca_topic_score_gemma":0.0015861365,"teacher_disagreement_score":0.0017421999,"about_ca_system_score_codex":0.00018124002,"about_ca_system_score_gemma":0.00012890444,"threshold_uncertainty_score":0.005724907},"labels":[],"label_agreement":null},{"id":"W4225269802","doi":"10.1002/hbm.25882","title":"Sex‐ and age‐specific associations between cardiometabolic risk and white matter brain age in the <scp>UK</scp> Biobank cohort","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"H2020 European Research Council; Helse Sør-Øst RHF; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Diabetes UK; Universitetet i Oslo; Fondation Leenaards; Horizon 2020 Framework Programme; Academy of Medical Sciences; Norges Forskningsråd; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Commission; Wellcome Trust; Alzheimer's Society; British Heart Foundation; National Science Foundation","keywords":"Body mass index; Demography; Cohort; Risk factor; Waist–hip ratio; Biobank; Gerontology; Waist; Medicine; Psychology; Internal medicine; Biology; Bioinformatics","score_opus":0.06227182811688249,"score_gpt":0.3181738456354622,"score_spread":0.2559020175185797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225269802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99629384,0.00027092142,0.00006840605,0.000047688674,0.0000088073275,0.0000070129468,0.0030481613,0.0000051061647,0.00024998424],"genre_scores_gemma":[0.99471706,0.00026765766,0.00015312523,0.000059697213,0.000020526575,0.00004128477,0.003993945,0.000007994539,0.00073876575],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999634,0.00007278811,0.000053495976,0.000118080985,0.00005017786,0.0000714635],"domain_scores_gemma":[0.9989311,0.00010283792,0.00047253817,0.00022719186,0.00011063381,0.00015572924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000517802,0.0003132226,0.0004193434,0.00059883855,0.00040321064,0.0006760567,0.00034083382,0.000611086,0.0022786397],"category_scores_gemma":[0.001534026,0.0004191565,0.0004988142,0.0010770772,0.00022606162,0.00037017092,0.00072369695,0.00047242644,0.00040776393],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007162374,0.000021329772,0.99456245,0.0000326242,0.00019668064,0.00017135954,0.00024498368,0.0000688693,0.0009424129,0.000051095,0.0012765141,0.0017153892],"study_design_scores_gemma":[0.000009999821,0.000024277708,0.99947935,0.000006681256,0.000028246342,0.00010598163,0.000042222327,0.00004912255,0.000030413948,0.000012912745,0.00020788504,0.0000029697017],"about_ca_topic_score_codex":0.032371417,"about_ca_topic_score_gemma":0.03746786,"teacher_disagreement_score":0.032371417,"about_ca_system_score_codex":0.00036499172,"about_ca_system_score_gemma":0.00027065174,"threshold_uncertainty_score":0.06436598},"labels":[],"label_agreement":null},{"id":"W4225585094","doi":"10.3389/fnagi.2022.793991","title":"Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Alzheimer's Disease Neuroimaging Initiative","keywords":"White matter; Diffusion MRI; Cognitive impairment; Cognition; Montreal Cognitive Assessment; Neuroscience; Psychology; Effects of sleep deprivation on cognitive performance; Cohort; Cognitive decline; Magnetic resonance imaging; Internal medicine; Medicine; Audiology; Dementia; Disease; Radiology","score_opus":0.017339194989355808,"score_gpt":0.29404084236498956,"score_spread":0.27670164737563374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225585094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991554,0.00008866252,0.00024628456,0.0000188871,9.907417e-7,0.0000069000835,0.00026914335,0.000006417426,0.0002073639],"genre_scores_gemma":[0.9992725,0.000043230935,0.00026665235,0.0000043487744,0.0000038865674,0.000007829996,0.00033917325,0.0000014714736,0.00006071879],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990344,0.000022354647,0.000011578861,0.000034724144,0.000015192962,0.000012739504],"domain_scores_gemma":[0.999721,0.000086617365,0.00009294565,0.000028673445,0.00003211087,0.000038738748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032587018,0.0002257719,0.00023743733,0.0010100511,0.00019773554,0.00035634654,0.00016884938,0.00024153726,0.00072841474],"category_scores_gemma":[0.0016528929,0.00008899772,0.00019394852,0.0005843471,0.00014964251,0.00023111785,0.00025643734,0.00014543386,0.00010167646],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00111841,0.0000869606,0.9692798,0.000072391944,0.00033401087,0.0005211603,0.00059200014,0.0012948525,0.007785637,0.0002157429,0.00037451243,0.018324492],"study_design_scores_gemma":[0.0000075998987,0.000058192338,0.9976804,0.0000031971072,0.00003103106,0.00023173763,0.00007958646,0.0013920612,0.00023534209,0.00017575517,0.000101234626,0.000003834736],"about_ca_topic_score_codex":0.0048356564,"about_ca_topic_score_gemma":0.008357438,"teacher_disagreement_score":0.0048356564,"about_ca_system_score_codex":0.00019405544,"about_ca_system_score_gemma":0.0001739235,"threshold_uncertainty_score":0.009615064},"labels":[],"label_agreement":null},{"id":"W4225621567","doi":"10.1161/circulationaha.122.059281","title":"What Turns the White Matter White? Metabolomic Clues to the Origin of Age-Related Cerebral White Matter Hyperintensities","year":2022,"lang":"en","type":"letter","venue":"Circulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Medical Research Council; Canadian Institutes of Health Research","keywords":"Hyperintensity; Medicine; White matter; White (mutation); Leukoaraiosis; Pathology; Magnetic resonance imaging; Radiology; Genetics; Biology","score_opus":0.04332406163886266,"score_gpt":0.3005223714069434,"score_spread":0.2571983097680807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225621567","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030669281,0.015777428,0.0017612561,0.9244646,0.019659122,0.000050423187,0.00027232585,0.00013968664,0.0072058463],"genre_scores_gemma":[0.28446698,0.017445382,0.0031670472,0.4354481,0.25265682,0.00007291304,0.00016375455,0.00009627294,0.006482739],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99944454,0.000130756,0.00008704881,0.00011535833,0.00010768485,0.000114513336],"domain_scores_gemma":[0.9977192,0.0013741119,0.0001740169,0.00013882188,0.00036245608,0.00023139949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010726352,0.000686506,0.001437572,0.00071982207,0.0010969427,0.0016447713,0.00079528906,0.011968183,0.0021911927],"category_scores_gemma":[0.008047431,0.00035585245,0.0008313266,0.00052709016,0.001572612,0.0024217847,0.00048244392,0.009657137,0.001338268],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022863767,0.00032685103,0.042878326,0.00052415876,0.0004181318,0.402417,0.0010358498,0.0007936828,0.012174426,0.018679842,0.426055,0.09241036],"study_design_scores_gemma":[0.0015582718,0.00086958933,0.048936523,0.001248736,0.0008294614,0.3351218,0.003123058,0.011542366,0.012953124,0.17672932,0.4067169,0.0003708608],"about_ca_topic_score_codex":0.0022202241,"about_ca_topic_score_gemma":0.0019746348,"teacher_disagreement_score":0.011968183,"about_ca_system_score_codex":0.0011673021,"about_ca_system_score_gemma":0.0006882682,"threshold_uncertainty_score":0.008469403},"labels":[],"label_agreement":null},{"id":"W4225657792","doi":"10.1093/cercor/bhac132","title":"Morphological patterns and spatial probability maps of the superior parietal sulcus in the human brain","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Sulcus; Superior parietal lobule; Central sulcus; Parietal lobe; Anatomy; Magnetic resonance imaging; Human brain; Biology; Intraparietal sulcus; Brain mapping; Superior temporal sulcus; Neuroscience; Posterior parietal cortex; Functional magnetic resonance imaging; Medicine; Motor cortex; Radiology","score_opus":0.05620476894711453,"score_gpt":0.3182109479310378,"score_spread":0.2620061789839233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225657792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96447253,0.00027054868,0.032034326,0.000069855385,0.000001938313,0.000027619712,0.00039259664,0.000083583465,0.0026469168],"genre_scores_gemma":[0.9943855,0.00011914622,0.005106896,0.000004015249,0.0000034318446,0.000012727426,0.00017294259,0.000012528684,0.00018277547],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99990976,0.000021942926,0.0000063150255,0.000024192159,0.000031121286,0.0000067039364],"domain_scores_gemma":[0.9996687,0.00013342717,0.000087959845,0.00004031264,0.000055485205,0.000014042403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002665696,0.00008541132,0.00007388942,0.0013014413,0.00009010828,0.0003455741,0.00009912957,0.0000996193,0.0008697639],"category_scores_gemma":[0.0013580181,0.00011127195,0.00013237845,0.0007937287,0.00049962837,0.0002408357,0.00022368047,0.00008648315,0.00012420937],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010793329,0.00005498138,0.27320677,0.0004345563,0.00028365993,0.0013342688,0.0036958635,0.031041764,0.32366258,0.023087824,0.0012769756,0.34084138],"study_design_scores_gemma":[0.000015747557,0.000111040834,0.9576429,0.00001513091,0.000026450278,0.0026048464,0.0003092901,0.018773567,0.0067672557,0.012462371,0.0012485866,0.000022853616],"about_ca_topic_score_codex":0.002056797,"about_ca_topic_score_gemma":0.0026526595,"teacher_disagreement_score":0.002056797,"about_ca_system_score_codex":0.00014610673,"about_ca_system_score_gemma":0.00022027365,"threshold_uncertainty_score":0.004089594},"labels":[],"label_agreement":null},{"id":"W4225907467","doi":"10.1371/journal.pone.0252736","title":"Comparison of CPU and GPU bayesian estimates of fibre orientations from diffusion MRI","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; University of California, Los Angeles; Massachusetts General Hospital; BC Children's Hospital; University of Minnesota","keywords":"Markov chain Monte Carlo; Computer science; Voxel; Diffusion; Central processing unit; Bayesian probability; Monte Carlo method; Markov chain; Algorithm; Diffusion MRI; Artificial intelligence; Statistics; Mathematics; Physics; Magnetic resonance imaging; Machine learning","score_opus":0.09944525400692586,"score_gpt":0.36143400305254497,"score_spread":0.2619887490456191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225907467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6217011,0.0015957804,0.34395018,0.0007432064,0.0002743046,0.0002039856,0.0018486184,0.01722494,0.0124579435],"genre_scores_gemma":[0.710129,0.0005056759,0.27945134,0.00021641469,0.000053581414,0.00019430245,0.0041050026,0.0024083257,0.002936277],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988281,0.00032462328,0.000093945004,0.00020214879,0.00046074824,0.00009036438],"domain_scores_gemma":[0.9961952,0.0018492294,0.00018134457,0.0005413318,0.0010871546,0.00014567583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00222852,0.0007221479,0.0007596565,0.0010393868,0.00040226238,0.0017615947,0.0011596223,0.0008951861,0.004868628],"category_scores_gemma":[0.0148186805,0.0004750406,0.00052632904,0.00093559484,0.00040513754,0.001139821,0.0011292251,0.0010791626,0.0012170307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0065755066,0.00049845496,0.023866022,0.00073460536,0.0005516738,0.00029933077,0.0007188078,0.25254598,0.029836684,0.009389346,0.01621329,0.6587703],"study_design_scores_gemma":[0.00023121011,0.000344898,0.013671749,0.0000809915,0.000079479236,0.00025771983,0.00011034199,0.95719355,0.019945452,0.0038718763,0.004152509,0.00006028106],"about_ca_topic_score_codex":0.00867462,"about_ca_topic_score_gemma":0.009426605,"teacher_disagreement_score":0.00867462,"about_ca_system_score_codex":0.00072401116,"about_ca_system_score_gemma":0.001187203,"threshold_uncertainty_score":0.017248273},"labels":[],"label_agreement":null},{"id":"W4226030876","doi":"10.3389/fnins.2022.833209","title":"Enabling Complex Fibre Geometries Using 3D Printed Axon-Mimetic Phantoms","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Imaging phantom; Diffusion MRI; Orientation (vector space); Kurtosis; Curvature; Nuclear magnetic resonance; Ground truth; Thermal diffusivity; Fractional anisotropy; Physics; Materials science; Magnetic resonance imaging; Geometry; Artificial intelligence; Optics; Mathematics; Computer science; Statistics","score_opus":0.11453495099876031,"score_gpt":0.36135206985105894,"score_spread":0.24681711885229862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226030876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3105688,0.0010156913,0.67486966,0.00037855934,0.00023266052,0.00029603552,0.0006985272,0.004385728,0.007554304],"genre_scores_gemma":[0.6245148,0.00094733195,0.36616734,0.00023756713,0.000036915306,0.0005436387,0.00061861693,0.0005075472,0.0064261793],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995635,0.00007318724,0.000031486088,0.000084675194,0.00021673665,0.000030356352],"domain_scores_gemma":[0.9985777,0.000632737,0.0003403448,0.00024305907,0.00013441763,0.00007174392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009944182,0.0007754032,0.00030472365,0.00056840526,0.00023564325,0.00091223296,0.00067792484,0.00086537475,0.0015018021],"category_scores_gemma":[0.0024551232,0.00059754093,0.000499189,0.00033298152,0.0005580997,0.00079606136,0.0007042915,0.00057459396,0.00077901373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016161009,0.000067165296,0.0008467557,0.0002716563,0.0000302181,0.0005703636,0.00025590128,0.031853825,0.9392454,0.0033815794,0.00079096,0.022524705],"study_design_scores_gemma":[0.000029980887,0.00037616384,0.0017368636,0.00003823462,0.000044843833,0.00089365203,0.00005586742,0.06981415,0.90903455,0.0015332848,0.016375061,0.000067284425],"about_ca_topic_score_codex":0.00067260244,"about_ca_topic_score_gemma":0.0010248125,"teacher_disagreement_score":0.0015018021,"about_ca_system_score_codex":0.0005936725,"about_ca_system_score_gemma":0.0003919616,"threshold_uncertainty_score":0.005259037},"labels":[],"label_agreement":null},{"id":"W4226193026","doi":"","title":"The Digital Brain Bank, an open access platform for post-mortem imaging datasets","year":2022,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; China Scholarship Council; Motor Neurone Disease Association; NIHR Oxford Biomedical Research Centre; Medical Research Council Canada; Cancer Research UK; Medical Research Council; Wellcome","keywords":"Neuroimaging; Neuroanatomy; Neuroinformatics; Magnetic resonance imaging; Computer science; Diffusion MRI; Brain atlas; Neuroscience; Artificial intelligence; Medicine; Data science; Biology; Radiology","score_opus":0.10528278185127639,"score_gpt":0.3835696911694888,"score_spread":0.2782869093182124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226193026","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011861337,0.0004681491,0.011681983,0.0006681776,0.0005456592,0.000271629,0.96777904,0.01077462,0.006624707],"genre_scores_gemma":[0.0030079861,0.00053658034,0.018606184,0.0004065805,0.0001345484,0.001505044,0.96815354,0.004070667,0.0035788983],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966068,0.0004963331,0.0005655198,0.0008291463,0.001243544,0.00025861943],"domain_scores_gemma":[0.9882102,0.0025793521,0.0012252348,0.004313277,0.0026964666,0.0009754552],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0059150183,0.0013682377,0.0020453152,0.004881756,0.0016078753,0.0048941015,0.005018604,0.0022420306,0.127114],"category_scores_gemma":[0.024660265,0.0010850214,0.0012155436,0.005352481,0.0010912077,0.0040994193,0.0069775335,0.0024955,0.1566519],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031014252,0.000028082613,0.00091566634,0.0008109403,0.00006580834,0.00016082203,0.00012503588,0.0003182215,0.0015670276,0.0029361926,0.9746596,0.018102381],"study_design_scores_gemma":[0.0001763482,0.000029724213,0.0038752789,0.0004940504,0.00004867168,0.0002921786,0.00009393252,0.00075698784,0.0023000394,0.0076821353,0.9841615,0.0000890938],"about_ca_topic_score_codex":0.0046849702,"about_ca_topic_score_gemma":0.010185986,"teacher_disagreement_score":0.9949814,"about_ca_system_score_codex":0.0010969783,"about_ca_system_score_gemma":0.0045351004,"threshold_uncertainty_score":0.42523867},"labels":[],"label_agreement":null},{"id":"W4226413061","doi":"10.3389/fneur.2021.789254","title":"The Value of Diffusion Kurtosis Imaging in Detecting Delayed Brain Development of Premature Infants","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Natural Science Foundation of China","keywords":"Kurtosis; Diffusion MRI; Neuroimaging; Neuroscience; Brain development; Medicine; Psychology; Magnetic resonance imaging; Radiology; Mathematics; Statistics","score_opus":0.014259231192256949,"score_gpt":0.2942469011439578,"score_spread":0.2799876699517008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226413061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969886,0.0017357699,0.00074066676,0.000042165695,0.000010903753,0.000010344457,0.00010214249,0.00001565559,0.00035382816],"genre_scores_gemma":[0.9980825,0.0005026723,0.0011903757,0.000010498353,0.000016534903,0.000012403631,0.00009096244,0.0000035334606,0.00009048812],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99952567,0.00018506554,0.00007116889,0.000094834635,0.00008392657,0.000039440733],"domain_scores_gemma":[0.99792814,0.00079483987,0.0007614023,0.00007977981,0.0002522831,0.0001835754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012762673,0.0006951791,0.00035962655,0.0014045561,0.00018564108,0.0005607597,0.00033550826,0.00047155068,0.0006946973],"category_scores_gemma":[0.0072422847,0.00019162726,0.00020941375,0.00035254715,0.00034873953,0.00052357005,0.00045854034,0.00034690305,0.00015019401],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011521154,0.000046501573,0.9626231,0.00013138424,0.00009047499,0.001065273,0.00016236989,0.0002645627,0.008105379,0.00005657468,0.00013628343,0.02616592],"study_design_scores_gemma":[0.00002483478,0.00074149674,0.9874098,0.000065851855,0.00009810026,0.0044030966,0.00027090823,0.0023792794,0.0039371415,0.00018344642,0.00046410292,0.000021828213],"about_ca_topic_score_codex":0.0006127823,"about_ca_topic_score_gemma":0.00050620874,"teacher_disagreement_score":0.0014045561,"about_ca_system_score_codex":0.0001892251,"about_ca_system_score_gemma":0.00020503074,"threshold_uncertainty_score":0.00674963},"labels":[],"label_agreement":null},{"id":"W4229022032","doi":"10.1093/noajnl/vdac064","title":"Abnormalities of structural brain connectivity in pediatric brain tumor survivors","year":2022,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Hospital for Sick Children; University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Context (archaeology); Sulcus; Right hemisphere; Lateralization of brain function; Nuclear medicine; Medicine; Brain tumor; Psychology; Internal medicine; Neuroscience; Pathology; Magnetic resonance imaging; Audiology; Biology; Radiology","score_opus":0.03163942454611122,"score_gpt":0.35211736591377624,"score_spread":0.320477941367665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229022032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995109,0.00006533439,0.0001267879,0.000013255054,6.3159956e-7,0.0000017203978,0.00016045263,0.000004270201,0.00011662718],"genre_scores_gemma":[0.9996269,0.000048589754,0.00009042233,0.0000025998438,0.0000013389782,0.000003488444,0.00018136064,0.000002167702,0.0000431052],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998951,0.000021955771,0.000007868361,0.00003231949,0.000021721655,0.00002107145],"domain_scores_gemma":[0.9993988,0.0001024488,0.0003548566,0.000036479985,0.000051326824,0.000055987664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019618544,0.00019210236,0.000152099,0.0005518148,0.00015067068,0.00021425514,0.00015147851,0.00011946589,0.0015453846],"category_scores_gemma":[0.0013552951,0.00008710887,0.00017028839,0.00050682476,0.00021223961,0.00020936163,0.00024137867,0.00017627978,0.00009728865],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014198908,0.000021815156,0.9833225,0.000033411787,0.00010046252,0.0002963014,0.00031540493,0.0006980194,0.004704589,0.000109717614,0.00019957249,0.010056125],"study_design_scores_gemma":[0.0000013771638,0.000038586128,0.998362,0.0000032100306,0.00001617866,0.00035424344,0.00010564773,0.00040105914,0.0005533753,0.000062102234,0.00010041023,0.0000017842536],"about_ca_topic_score_codex":0.0037969872,"about_ca_topic_score_gemma":0.004878778,"teacher_disagreement_score":0.0037969872,"about_ca_system_score_codex":0.00022221985,"about_ca_system_score_gemma":0.00024337227,"threshold_uncertainty_score":0.0075497627},"labels":[],"label_agreement":null},{"id":"W4229333559","doi":"10.1016/j.media.2022.102476","title":"Bridging the gap between constrained spherical deconvolution and diffusional variance decomposition via tensor‐valued diffusion MRI","year":2022,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Deconvolution; Fractional anisotropy; Computer science; Tensor (intrinsic definition); Anisotropy; Orientation (vector space); Algorithm; Diffusion; White matter; Mathematics; Artificial intelligence; Physics; Magnetic resonance imaging; Geometry; Optics","score_opus":0.02731257130503184,"score_gpt":0.34251903067927053,"score_spread":0.3152064593742387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229333559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00643749,0.006210263,0.9817546,0.0027106889,0.0001434574,0.0000172069,0.000053060463,0.00014312724,0.0025301217],"genre_scores_gemma":[0.28581673,0.025305618,0.68128675,0.0014314835,0.0014139768,0.00011499284,0.00030782528,0.00050742953,0.0038151352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974694,0.0011100931,0.0001515486,0.00034746784,0.0008148514,0.00010652773],"domain_scores_gemma":[0.99051356,0.0063472497,0.000603244,0.0014460767,0.00085884426,0.00023096021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006122601,0.0009644704,0.0015359803,0.0011498147,0.00047506142,0.0041846796,0.001803672,0.0025445507,0.0017801821],"category_scores_gemma":[0.020355504,0.00067882484,0.00061139127,0.0012716001,0.0028512704,0.0066672005,0.005703963,0.003548484,0.0005501754],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021260096,0.00007609799,0.00075018755,0.0008860208,0.0002476874,0.000207684,0.00059194764,0.03853648,0.015295451,0.6654638,0.004307482,0.27342454],"study_design_scores_gemma":[0.000028049342,0.000062023406,0.0008108192,0.00023642599,0.000060728307,0.00035782953,0.00016652979,0.37594017,0.005215257,0.6007367,0.016310643,0.00007480167],"about_ca_topic_score_codex":0.0017929085,"about_ca_topic_score_gemma":0.0017255972,"teacher_disagreement_score":0.006122601,"about_ca_system_score_codex":0.0006271465,"about_ca_system_score_gemma":0.0022434848,"threshold_uncertainty_score":0.032379806},"labels":[],"label_agreement":null},{"id":"W4229451685","doi":"10.1016/j.dscb.2022.100036","title":"Functional, but minimal microstructural brain changes present in aging Canadian football league players years after retirement","year":2022,"lang":"en","type":"article","venue":"Brain Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Psychology; Athletes; Neuropsychology; Football; Magnetic resonance imaging; Audiology; Medicine; Physical therapy; Neuroscience; Cognition; Radiology","score_opus":0.038363793545055834,"score_gpt":0.29983283175473396,"score_spread":0.26146903820967815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229451685","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99968946,0.0000640166,0.000017682927,0.000009873554,0.0000013657577,0.000005888087,0.00008832733,0.0000010837189,0.00012228887],"genre_scores_gemma":[0.99949217,0.000039650717,0.000038460497,0.000013949701,0.0000035057622,0.0000029752366,0.00020055249,5.139745e-7,0.00020823375],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998579,0.0000067904266,0.0000068714658,0.000027204143,0.00003864958,0.00006251415],"domain_scores_gemma":[0.9997372,0.000020696163,0.00009201414,0.000011710417,0.00007196339,0.00006640012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022439711,0.00032096618,0.00021042091,0.0007844562,0.0008199547,0.00036857207,0.00032738666,0.0003631543,0.00082391786],"category_scores_gemma":[0.0006836672,0.00014486114,0.00012865492,0.00041711674,0.00047253832,0.00017335427,0.00024022085,0.00020692142,0.00012580857],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003697259,0.00011432372,0.98646784,0.00002444899,0.000039369264,0.0005990966,0.0005097417,0.000058250735,0.005707046,0.000019412957,0.00017725304,0.0059134574],"study_design_scores_gemma":[0.0000015662896,0.000054013653,0.9995436,0.0000011130494,0.000004612313,0.00016081054,0.00010132053,0.000021706215,0.000053531967,0.000002867001,0.000053889242,0.0000010183743],"about_ca_topic_score_codex":0.30263168,"about_ca_topic_score_gemma":0.4234368,"teacher_disagreement_score":0.6973683,"about_ca_system_score_codex":0.0010499986,"about_ca_system_score_gemma":0.0011133575,"threshold_uncertainty_score":0.60174036},"labels":[],"label_agreement":null},{"id":"W4230255018","doi":"10.1016/s0304394002013332","title":"Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins","year":2003,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; McMaster University","funders":"","keywords":"Heritability; Corpus callosum; Concordance; Dizygotic twins; Trait; Magnetic resonance imaging; Dizygotic twin; Lateralization of brain function; Psychology; Twin study; Biology; Audiology; Developmental psychology; Neuroscience; Evolutionary biology; Genetics; Medicine","score_opus":0.05944971591487432,"score_gpt":0.35070261120484103,"score_spread":0.29125289528996673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230255018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996623,0.000057816345,0.000049181373,0.000016357177,0.0000036811668,0.0000049202417,0.000040299044,0.0000012069892,0.00016424511],"genre_scores_gemma":[0.9994362,0.00009883953,0.00012931775,0.000020147241,0.000010800086,0.000008690089,0.000055341046,0.000009522194,0.00023103917],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99954236,0.00010872176,0.000049255406,0.00015087124,0.00008706579,0.00006177741],"domain_scores_gemma":[0.99847347,0.0005972391,0.00034427096,0.00020305974,0.00012761306,0.0002544194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048971776,0.00083152665,0.0006729449,0.002328243,0.0012506775,0.0006175893,0.00078901777,0.0010698598,0.0019981395],"category_scores_gemma":[0.003698844,0.0006498769,0.00040773497,0.0011033067,0.0016135598,0.00042333637,0.001156159,0.0007262183,0.0002542303],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011979461,0.001606975,0.63579535,0.00018508248,0.0006751328,0.04822319,0.013516313,0.00058944646,0.26721182,0.002047592,0.0005594558,0.017610246],"study_design_scores_gemma":[0.00013000649,0.0010150294,0.93950933,0.000024645158,0.0003727998,0.045278262,0.0019096573,0.0005577261,0.0099567855,0.0004265683,0.0007591862,0.00005988805],"about_ca_topic_score_codex":0.0062624854,"about_ca_topic_score_gemma":0.0035546923,"teacher_disagreement_score":0.0062624854,"about_ca_system_score_codex":0.00039699825,"about_ca_system_score_gemma":0.00037293887,"threshold_uncertainty_score":0.012452066},"labels":[],"label_agreement":null},{"id":"W4230311787","doi":"10.21203/rs.3.rs-374535/v1","title":"Distinct Tumor Signatures using Deep Learning-based Characterization of the Peritumoral Microenvironment in Glioblastomas and Brain Metastases","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institutes of Health","keywords":"Diffusion MRI; Medicine; Convolutional neural network; Glioblastoma; Infiltration (HVAC); Pathology; Radiology; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Computer science; Cancer research; Materials science","score_opus":0.06634612594131742,"score_gpt":0.39094249697938477,"score_spread":0.3245963710380674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230311787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.954186,0.00044658693,0.043880288,0.00013713478,0.000016182645,0.000021877544,0.00036354968,0.0002023868,0.0007461184],"genre_scores_gemma":[0.9924907,0.00009302872,0.0066768886,0.000017399117,0.0000066230455,0.000009398902,0.00034431994,0.000010673442,0.00035090616],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999907,0.000021066917,0.0000062788813,0.000022547703,0.000018436293,0.000024529512],"domain_scores_gemma":[0.999808,0.000064885484,0.000046838915,0.000018642253,0.000037364898,0.000024330897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035250076,0.00039721653,0.00027234748,0.0007288376,0.0000958755,0.00040062578,0.00022983496,0.00025504897,0.00046760254],"category_scores_gemma":[0.0009121491,0.00012131865,0.00024837023,0.00030762338,0.00019613066,0.00033617503,0.00037934727,0.00025887007,0.00016111937],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013879255,0.00033911958,0.17854595,0.0002843668,0.0002485573,0.00072367344,0.00027191616,0.21532333,0.25051546,0.0023009276,0.00250098,0.34755784],"study_design_scores_gemma":[0.000013453559,0.000092203394,0.04880028,0.000018601551,0.00004476201,0.00027477514,0.00008185105,0.9208215,0.02734783,0.0018692729,0.0006193069,0.000016146996],"about_ca_topic_score_codex":0.004653882,"about_ca_topic_score_gemma":0.0052861986,"teacher_disagreement_score":0.004653882,"about_ca_system_score_codex":0.00035065316,"about_ca_system_score_gemma":0.000289628,"threshold_uncertainty_score":0.0092535615},"labels":[],"label_agreement":null},{"id":"W4231279597","doi":"10.1016/j.jalz.2013.05.849","title":"P2–203: Relationship between cortical thinning and cortical FDG hypometabolism in individuals with progressive MCI and Alzheimer's disease","year":2013,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Atrophy; Neuroimaging; Psychology; Cognitive impairment; Cohort; Alzheimer's Disease Neuroimaging Initiative; Medicine; Internal medicine; Disease; Nuclear medicine; Cardiology; Pathology; Neuroscience","score_opus":0.07706400431917466,"score_gpt":0.34619877079463623,"score_spread":0.2691347664754616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231279597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972791,0.00023992432,0.00031814072,0.00009668725,0.0000192772,0.000013590693,0.00047845588,0.000020070443,0.0015346329],"genre_scores_gemma":[0.9989103,0.000042358515,0.00030364143,0.000028230475,0.000019381161,0.000011790376,0.00034895126,0.000010289626,0.00032503012],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997429,0.000048778056,0.000027418144,0.00008962678,0.00006457416,0.000026708141],"domain_scores_gemma":[0.9990823,0.0002054144,0.000339782,0.00010115543,0.00012052897,0.00015079908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063639163,0.00059643935,0.00042290156,0.0012671219,0.00053479505,0.00065722445,0.0004986034,0.00063754537,0.0038539865],"category_scores_gemma":[0.002921731,0.00027952951,0.0005117901,0.0010161574,0.00043540867,0.0004485997,0.0006120122,0.0006856348,0.00046766608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012950507,0.00008574511,0.986654,0.00004544946,0.00026832614,0.0010301013,0.00019325057,0.0002456478,0.0027139294,0.00018153174,0.00059858046,0.0066883997],"study_design_scores_gemma":[0.0000076779515,0.00007968194,0.99755883,0.000004737969,0.00003150729,0.0013143471,0.0000621564,0.00039466197,0.00011569863,0.00030178006,0.00012458417,0.0000043134187],"about_ca_topic_score_codex":0.00507235,"about_ca_topic_score_gemma":0.0053502223,"teacher_disagreement_score":0.00507235,"about_ca_system_score_codex":0.00019590676,"about_ca_system_score_gemma":0.00036721057,"threshold_uncertainty_score":0.012892842},"labels":[],"label_agreement":null},{"id":"W4231317324","doi":"10.1101/2021.10.25.465703","title":"Investigating the genetic and environmental basis of head micromovements during MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Genome-wide association study; Impulsivity; Body mass index; Population; Genetic association; Neuroimaging; Psychology; Demography; Medicine; Biology; Clinical psychology; Internal medicine; Genetics; Psychiatry; Single-nucleotide polymorphism; Genotype; Environmental health","score_opus":0.025875395584793588,"score_gpt":0.25961296857272276,"score_spread":0.23373757298792916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231317324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9695976,0.018779544,0.008402641,0.00044865184,0.00009817829,0.00006879292,0.0015259467,0.00006116475,0.0010174564],"genre_scores_gemma":[0.9953133,0.0014198999,0.0022751992,0.00010454863,0.000044517103,0.00006072106,0.0004967116,0.000015594323,0.00026956206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984243,0.0007807147,0.00016035895,0.00041787632,0.00012808507,0.00008869495],"domain_scores_gemma":[0.99528,0.0026281967,0.0010679327,0.000693409,0.0002284275,0.00010202045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035946118,0.0006175728,0.0006723323,0.0009971339,0.0003817891,0.0008936308,0.00080554804,0.0007113453,0.0022585422],"category_scores_gemma":[0.0075350464,0.00046032062,0.0023458,0.001357881,0.00037073228,0.00046963818,0.0005300001,0.00047741065,0.00013996373],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002195424,0.000112580616,0.9305196,0.0010721724,0.030667795,0.00026523456,0.00026472512,0.0015204784,0.0066128257,0.0006775773,0.00078237633,0.025309375],"study_design_scores_gemma":[0.00010755527,0.0003707443,0.98388344,0.00014011646,0.010113452,0.00021944246,0.00009053961,0.0016117874,0.0017451035,0.00088148896,0.0008152265,0.000021080232],"about_ca_topic_score_codex":0.0043630926,"about_ca_topic_score_gemma":0.005238218,"teacher_disagreement_score":0.0043630926,"about_ca_system_score_codex":0.00032594445,"about_ca_system_score_gemma":0.00037393178,"threshold_uncertainty_score":0.019010305},"labels":[],"label_agreement":null},{"id":"W4231680536","doi":"10.1016/s0006-3223(11)00616-0","title":"Table of Contents","year":2011,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Linear regression; White matter; Statistics; Psychology; Scanner; Sample (material); Table of contents; Cover (algebra); Regression; Regression analysis; Table (database); Mathematics; Medicine; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Radiology; Data mining","score_opus":0.26798391095176916,"score_gpt":0.37317102709016786,"score_spread":0.1051871161383987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231680536","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007167031,0.003141628,0.002320388,0.0024615594,0.0072781467,0.00064588076,0.046813175,0.0016927167,0.9349298],"genre_scores_gemma":[0.0020508408,0.0023504922,0.0014239845,0.0012887315,0.0016970802,0.0002981751,0.02414766,0.0006311401,0.96611196],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961084,0.000047409583,0.00002190971,0.00006663848,0.00021787784,0.000035378373],"domain_scores_gemma":[0.9978563,0.00043503626,0.00009929284,0.00021863548,0.0010544216,0.0003362819],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00050166796,0.00094870495,0.0009166686,0.00431291,0.0012911636,0.002852632,0.001218169,0.000830931,0.8644743],"category_scores_gemma":[0.0044604666,0.00026839992,0.00050915603,0.0029231983,0.00027393157,0.001507852,0.0013679947,0.00093101925,0.8184517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024944173,0.000044331413,0.0001862036,0.0001739305,0.000004158064,0.000026595231,0.000012897879,0.000105390725,0.00021290341,0.001121274,0.9272068,0.070880495],"study_design_scores_gemma":[0.0000067571063,0.00001926208,0.0006374668,0.00014488364,0.000005142492,0.000047424917,0.000027563668,0.000062043924,0.00017613808,0.0010389263,0.997829,0.000005287396],"about_ca_topic_score_codex":0.0034607518,"about_ca_topic_score_gemma":0.0049412833,"teacher_disagreement_score":0.1355257,"about_ca_system_score_codex":0.001278408,"about_ca_system_score_gemma":0.0020839968,"threshold_uncertainty_score":0.19331092},"labels":[],"label_agreement":null},{"id":"W4232561243","doi":"10.1016/j.jalz.2019.06.2810","title":"P2‐403: CORTICAL IRON DEPOSITION IN ALZHEIMER'S DISEASE CONTRASTS WITH AGE‐RELATED SUBCORTICAL DEPOSITION","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University Health Centre; Douglas Mental Health University Institute; Douglas College; McGill University","funders":"","keywords":"Neuropathology; Putamen; Neuroimaging; Prefrontal cortex; Neuroscience; Postmortem studies; Alzheimer's Disease Neuroimaging Initiative; Psychology; Voxel; Amyloid (mycology); Medicine; Disease; Internal medicine; Cognition; Pathology; Cognitive impairment; Radiology","score_opus":0.026840669788554594,"score_gpt":0.3035336072908793,"score_spread":0.2766929375023247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232561243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917247,0.0004088705,0.00086447963,0.000053426364,0.000009056968,0.000019232115,0.00042311297,0.00003301909,0.006464066],"genre_scores_gemma":[0.9982236,0.00008203037,0.00037178447,0.00002244706,0.000010317816,0.000019325404,0.00019468812,0.000015193149,0.0010606715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999114,0.000010700001,0.000008361526,0.000024185301,0.000030033088,0.000015250279],"domain_scores_gemma":[0.99980396,0.000042411943,0.00005216673,0.00002188917,0.000034647393,0.000044851855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030190047,0.00029655336,0.000212546,0.0009077343,0.00031761173,0.00047230418,0.00021170321,0.0002799896,0.0068412856],"category_scores_gemma":[0.00089792523,0.0001390838,0.00013410264,0.0005834061,0.00034953255,0.0002757104,0.0003970804,0.00020291013,0.0007380205],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009016115,0.0004401634,0.49639717,0.0005586438,0.00046227503,0.009739566,0.002416712,0.00060945866,0.38606572,0.0016525005,0.004242934,0.0883987],"study_design_scores_gemma":[0.000033611916,0.00017993384,0.987107,0.000016706332,0.000035123143,0.004759266,0.00017766752,0.00041179216,0.004704476,0.0014597755,0.0011078358,0.000006672283],"about_ca_topic_score_codex":0.002285422,"about_ca_topic_score_gemma":0.0030861823,"teacher_disagreement_score":0.0068412856,"about_ca_system_score_codex":0.00013288256,"about_ca_system_score_gemma":0.00022093917,"threshold_uncertainty_score":0.022886336},"labels":[],"label_agreement":null},{"id":"W4232624499","doi":"10.1016/j.jalz.2014.05.1648","title":"P4‐132: WHITE MATTER ABNORMALITIES AND STRUCTURAL PARIETAL DISCONNECTIONS IN ALZHEIMER'S DISEASE","year":2014,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Supramarginal gyrus; Fractional anisotropy; Parietal lobe; Angular gyrus; White matter; Temporal lobe; Superior frontal gyrus; Psychology; Neuroscience; Diffusion MRI; Posterior parietal cortex; Middle frontal gyrus; Medicine; Magnetic resonance imaging; Radiology; Cognition; Epilepsy; Functional magnetic resonance imaging","score_opus":0.03596019351917197,"score_gpt":0.3119363544781281,"score_spread":0.27597616095895616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232624499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99555594,0.00058235496,0.0008360462,0.00013675765,0.000013066822,0.000016421616,0.00062195776,0.00007377796,0.0021637916],"genre_scores_gemma":[0.9965552,0.00026318803,0.0012001321,0.000030602736,0.000025632193,0.000023272944,0.0006298881,0.000029478766,0.0012426093],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999387,0.000014340728,0.0000067827423,0.000016963124,0.000016825337,0.0000063980465],"domain_scores_gemma":[0.9998325,0.00003434178,0.00006666941,0.00001410118,0.00002218901,0.000030265097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002490933,0.00040588726,0.0002518256,0.0007314169,0.000278075,0.00037300252,0.00021741731,0.00034814642,0.005209375],"category_scores_gemma":[0.0009129098,0.00013787691,0.00017559115,0.00046236662,0.0002761916,0.0002903717,0.00041558192,0.00020499731,0.00054633006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0077453298,0.00039238136,0.62173223,0.0010206095,0.00062564376,0.0116363205,0.0009453608,0.0017174082,0.21145943,0.0012987287,0.006928146,0.13449842],"study_design_scores_gemma":[0.00006392618,0.0002911341,0.98031324,0.000036125868,0.00010562768,0.010240013,0.000096257034,0.0018253691,0.0037299546,0.0014792414,0.0018069077,0.000012238853],"about_ca_topic_score_codex":0.0019627428,"about_ca_topic_score_gemma":0.002112826,"teacher_disagreement_score":0.005209375,"about_ca_system_score_codex":0.00012224544,"about_ca_system_score_gemma":0.00024510105,"threshold_uncertainty_score":0.017427146},"labels":[],"label_agreement":null},{"id":"W4233862762","doi":"10.7287/peerj.preprints.2323","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Corpus callosum; Diffusion MRI; Myelin; Ex vivo; Magnetic resonance imaging; Neuroscience; Hippocampus; Central nervous system; Thalamus; Cerebellum; Pathology; Nuclear magnetic resonance; Biology; Anatomy; Medicine; In vivo; Physics; Radiology","score_opus":0.09378277241434148,"score_gpt":0.3918385396305597,"score_spread":0.29805576721621824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233862762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8846141,0.0045121377,0.09046196,0.00069442124,0.00022488684,0.00021416899,0.011796512,0.002243451,0.005238176],"genre_scores_gemma":[0.84809655,0.004788698,0.11369855,0.0004093399,0.00008248569,0.00058702775,0.008749733,0.0013273444,0.022260204],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996031,0.000036565398,0.000048938033,0.0001605022,0.00010397805,0.00004680364],"domain_scores_gemma":[0.99894685,0.00013981403,0.00041901646,0.00014071133,0.00015900416,0.00019458722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094714336,0.0014113978,0.000544632,0.0028173458,0.000410615,0.000671745,0.0007823119,0.0012051401,0.0028104833],"category_scores_gemma":[0.00036566652,0.00051149284,0.000622779,0.00075130205,0.00087035995,0.00073315983,0.0005370304,0.001389022,0.0012235967],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017610432,0.00004115675,0.0001438479,0.00008752909,0.00001821816,0.00013283838,0.00006634104,0.00016396657,0.9975835,0.0002843157,0.00012900603,0.0011732302],"study_design_scores_gemma":[0.000039371458,0.00036846733,0.008286337,0.00006619323,0.00011744252,0.0011720035,0.00009379654,0.002214351,0.98170817,0.00036527577,0.0055310754,0.000037472],"about_ca_topic_score_codex":0.0014406081,"about_ca_topic_score_gemma":0.0018382575,"teacher_disagreement_score":0.0028173458,"about_ca_system_score_codex":0.0004670998,"about_ca_system_score_gemma":0.00022356809,"threshold_uncertainty_score":0.009401977},"labels":[],"label_agreement":null},{"id":"W4234003016","doi":"10.1007/s00429-021-02239-2","title":"Correction to: A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Tractography; Ising model; Diffusion MRI; Diffusion; Neuroscience; Computer science; Statistical physics; Psychology; Physics; Medicine; Magnetic resonance imaging; Thermodynamics; Radiology","score_opus":0.03754665196289863,"score_gpt":0.3380409139241214,"score_spread":0.30049426196122275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234003016","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008818186,0.004030491,0.06576249,0.029352104,0.85803646,0.0005777025,0.013842069,0.013174599,0.0064059244],"genre_scores_gemma":[0.24081206,0.007581457,0.31876564,0.020459976,0.11927942,0.0027882075,0.028288975,0.032476924,0.22954728],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.992691,0.0012056128,0.001631681,0.0013210732,0.0024968062,0.00065388106],"domain_scores_gemma":[0.9143287,0.021211803,0.0040222667,0.010260875,0.04760598,0.00257042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009637378,0.0033758087,0.0037218677,0.0062855845,0.0026251276,0.004634236,0.0052616512,0.0067796595,0.23408666],"category_scores_gemma":[0.13015094,0.001827415,0.0026201124,0.0068166326,0.0016484068,0.0034277025,0.0036744114,0.006267838,0.06255229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089010625,0.000089024754,0.0012887185,0.0015431012,0.00042685776,0.00066794234,0.0002116429,0.0019817827,0.00261768,0.005221561,0.89451486,0.09054686],"study_design_scores_gemma":[0.000917727,0.00043112258,0.019608816,0.0015689613,0.00063271757,0.005188093,0.000505516,0.06240603,0.015186003,0.03230195,0.86046195,0.0007910765],"about_ca_topic_score_codex":0.009486945,"about_ca_topic_score_gemma":0.013825472,"teacher_disagreement_score":0.23408666,"about_ca_system_score_codex":0.0027234112,"about_ca_system_score_gemma":0.004990853,"threshold_uncertainty_score":0.78309786},"labels":[],"label_agreement":null},{"id":"W4234641868","doi":"10.1109/cvpr.2009.5204044","title":"3D stochastic completion fields for fiber tractography","year":2009,"lang":"en","type":"article","venue":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Tractography; Random walk; Statistical physics; Stochastic differential equation; Brownian motion; Computer science; Diffusion; Monte Carlo method; Stochastic process; Algorithm; Voxel; Diffusion MRI; Mathematical optimization; Applied mathematics; Mathematics; Artificial intelligence; Physics; Statistics","score_opus":0.10372641488124447,"score_gpt":0.35089019035030916,"score_spread":0.2471637754690647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234641868","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023201993,0.00007083196,0.9968449,0.00011761169,0.000012234108,0.000015618409,0.000058969355,0.00017894262,0.0003807836],"genre_scores_gemma":[0.20395148,0.000600772,0.79013735,0.00014262511,0.00012200081,0.00038022047,0.0005340369,0.0003792192,0.0037522265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996216,0.00015419755,0.000018153713,0.000056374272,0.00012599048,0.000023691588],"domain_scores_gemma":[0.9982438,0.0009799517,0.00020876656,0.0002038908,0.00024356962,0.00011999069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015094278,0.0006915442,0.0007331022,0.001037257,0.0005553333,0.00093960407,0.0009911819,0.001367146,0.0026842619],"category_scores_gemma":[0.0046419343,0.0004956023,0.00093865837,0.0009058538,0.0012255424,0.0011718296,0.00133502,0.0015500165,0.0007242402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003246488,0.000022902184,0.0003010239,0.00005405349,0.000019071127,0.00006122389,0.00006137354,0.8072249,0.0023356075,0.16799463,0.001377142,0.020515604],"study_design_scores_gemma":[0.000003748931,0.000004386624,0.00003453106,0.0000039817746,0.0000011614975,0.00001038873,0.000002232155,0.9610999,0.00024628307,0.037809663,0.0007785487,0.0000051005395],"about_ca_topic_score_codex":0.005358381,"about_ca_topic_score_gemma":0.0038720919,"teacher_disagreement_score":0.005358381,"about_ca_system_score_codex":0.0012738906,"about_ca_system_score_gemma":0.0013108461,"threshold_uncertainty_score":0.01065433},"labels":[],"label_agreement":null},{"id":"W4234739227","doi":"10.3389/fnins.2020.00543","title":"Histological Correlates of Diffusion-Weighted Magnetic Resonance Microscopy in a Mouse Model of Mesial Temporal Lobe Epilepsy","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"BrainLinks-BrainTools; European Research Council; Albert-Ludwigs-Universität Freiburg; Deutsche Forschungsgemeinschaft","keywords":"Hippocampal formation; Diffusion MRI; Hippocampal sclerosis; Magnetic resonance imaging; Pathology; Temporal lobe; Granule cell; Pyramidal cell; Epilepsy; Fractional anisotropy; Nuclear magnetic resonance; Hippocampus; Neuroscience; Dentate gyrus; Medicine; Biology; Physics; Radiology","score_opus":0.039886745281695335,"score_gpt":0.29802722689831507,"score_spread":0.25814048161661973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234739227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890805,0.0020320902,0.00599418,0.00012991349,0.000041159263,0.000053869753,0.000790637,0.00018478383,0.0016927778],"genre_scores_gemma":[0.98683506,0.0015999895,0.005847509,0.000067526635,0.0000122282345,0.00009571265,0.0008683422,0.00005169518,0.004621992],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998621,0.000017159637,0.000015619973,0.000042234627,0.00003913884,0.00002374853],"domain_scores_gemma":[0.99964464,0.000028439508,0.00016148243,0.00003298506,0.00006014211,0.00007224084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023285572,0.00042698334,0.00021685315,0.0011020015,0.00016809037,0.00025834242,0.00017188872,0.0004367397,0.0009430337],"category_scores_gemma":[0.00019086339,0.00024677694,0.00019596708,0.0002368007,0.0003325266,0.00031725282,0.00021575432,0.00059431227,0.0002851711],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011071592,0.000029011888,0.000331037,0.00002369953,0.000007909028,0.000078269746,0.000020859383,0.000043332795,0.9987282,0.00005975274,0.000019731835,0.0005475943],"study_design_scores_gemma":[0.00004448102,0.0013886349,0.050511707,0.000025991194,0.0000982906,0.0020800668,0.0001404914,0.0015019369,0.9420982,0.00024657545,0.0018396608,0.000023954235],"about_ca_topic_score_codex":0.0008758494,"about_ca_topic_score_gemma":0.0016615844,"teacher_disagreement_score":0.0011020015,"about_ca_system_score_codex":0.00024766035,"about_ca_system_score_gemma":0.0001488771,"threshold_uncertainty_score":0.0031547546},"labels":[],"label_agreement":null},{"id":"W4235000785","doi":"10.1016/j.jalz.2017.06.2347","title":"[IC‐P‐074]: LONGITUDINAL DIFFUSION TENSOR IMAGING AS A PREDICTOR OF COGNITIVE DOMAINS DECLINE IN EARLY STAGE PARKINSON's DISEASE: ICICLE‐PD STUDY","year":2017,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Ontario Brain Institute","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Parkinson's disease; White matter; Cognition; Cognitive decline; Dementia; Internal medicine; Medicine; Population; Psychology; Disease; Cardiology; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.05910597243118143,"score_gpt":0.3704345674666382,"score_spread":0.3113285950354568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235000785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969542,0.00046149184,0.0000902933,0.000111840796,0.000022167203,0.00007717114,0.0014690193,0.000010671134,0.0008031826],"genre_scores_gemma":[0.99249345,0.00024863318,0.0003416925,0.00017570556,0.000070176844,0.00010278924,0.0053511313,0.000009417734,0.0012070938],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99965715,0.00009098092,0.00003441529,0.00011815874,0.000052909923,0.000046412482],"domain_scores_gemma":[0.998574,0.00011638138,0.00044676918,0.0001661856,0.00027322632,0.00042349045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011947555,0.00083897053,0.0007504245,0.00044270203,0.00087056274,0.0010314353,0.0008785541,0.0014905838,0.0014373071],"category_scores_gemma":[0.0021259766,0.00059458846,0.000621508,0.00073909457,0.00026068182,0.0005765502,0.0006043752,0.001371272,0.0006382424],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012360595,0.0010320623,0.97843564,0.00008567189,0.0007292111,0.00034297674,0.00014758909,0.00016871879,0.0014573621,0.00004002133,0.0012228688,0.003977339],"study_design_scores_gemma":[0.0008438514,0.00197812,0.9948431,0.000019603709,0.0003808004,0.0004873452,0.000081548555,0.0003610214,0.0001470082,0.000024901285,0.00082025916,0.000012432435],"about_ca_topic_score_codex":0.00754512,"about_ca_topic_score_gemma":0.007055913,"teacher_disagreement_score":0.00754512,"about_ca_system_score_codex":0.00035288124,"about_ca_system_score_gemma":0.0005126408,"threshold_uncertainty_score":0.01500237},"labels":[],"label_agreement":null},{"id":"W4235690983","doi":"10.1017/cjn.2019.81","title":"GP.05 Intraoperative acquisition of diffusion tensor imaging in cranial neurosurgery: readout-segmented DTI versus standard single-shot DTI","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton","funders":"","keywords":"Diffusion MRI; Medicine; White matter; Nuclear medicine; Artifact (error); Magnetic resonance imaging; Tractography; Radiology; Neuroscience","score_opus":0.07378926848671195,"score_gpt":0.32793155746016317,"score_spread":0.2541422889734512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235690983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9645603,0.0021695911,0.023513814,0.00039652552,0.00015332142,0.00019267162,0.00042379895,0.00060387945,0.007986105],"genre_scores_gemma":[0.97382337,0.00048891705,0.023594195,0.000104376784,0.00009969852,0.000120534234,0.00049301493,0.00012852505,0.0011472916],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963045,0.00015875907,0.000027673776,0.000070961905,0.00008466027,0.000027541264],"domain_scores_gemma":[0.9988618,0.0004983393,0.00016913589,0.00016234878,0.00019672007,0.000111708556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016826167,0.000250934,0.00017581765,0.00022355189,0.00009292317,0.00042908124,0.0003213149,0.00024418996,0.005268159],"category_scores_gemma":[0.0039362824,0.0001167843,0.00012625348,0.00019757252,0.00033639,0.00042237097,0.0003850534,0.00036189114,0.00092053105],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.025152294,0.0007249278,0.09619994,0.0007829711,0.0002656352,0.00081913796,0.00040447206,0.004696984,0.068849154,0.0012300443,0.009123586,0.7917508],"study_design_scores_gemma":[0.0027626902,0.052106693,0.70968854,0.00045882474,0.00066719716,0.019686999,0.0006849841,0.086160585,0.091243535,0.0035241302,0.032878492,0.00013722171],"about_ca_topic_score_codex":0.00069662853,"about_ca_topic_score_gemma":0.00071514794,"teacher_disagreement_score":0.005268159,"about_ca_system_score_codex":0.00019216591,"about_ca_system_score_gemma":0.0003947479,"threshold_uncertainty_score":0.017623723},"labels":[],"label_agreement":null},{"id":"W4236543179","doi":"10.31234/osf.io/eymkz","title":"Acute conceptual disorganization in untreated first-episode psychosis: A combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Lawson Health Research Institute; Western University","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Glutamate receptor; Psychology; Glutathione; Diffusion MRI; Neuroscience; Psychosis; Internal medicine; Magnetic resonance imaging; Chemistry; Medicine; Psychiatry; Radiology; Biochemistry","score_opus":0.025169377874137196,"score_gpt":0.31330688316521743,"score_spread":0.28813750529108023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236543179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957746,0.00012408588,0.00008171207,0.000024980734,0.0000019235829,0.00000924811,0.000019200064,0.0000023449074,0.00015912397],"genre_scores_gemma":[0.9996766,0.00006637558,0.00014165338,0.000012126329,0.00000341458,0.000005620148,0.000035087425,0.0000010629378,0.000058025696],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999045,0.000019969688,0.000008433294,0.000017280743,0.000022763423,0.000026974241],"domain_scores_gemma":[0.9997459,0.000040395727,0.00010178086,0.000020740603,0.000028401839,0.00006282676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003396314,0.00033286502,0.00019989755,0.0008743518,0.0005489209,0.0004275118,0.00020873835,0.00041211062,0.0010262111],"category_scores_gemma":[0.00077343616,0.00028815004,0.00015806757,0.00046486442,0.00036988538,0.00026663035,0.00045553385,0.00035688028,0.00008463863],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031480452,0.00069346384,0.84668165,0.000184806,0.0003037915,0.016018337,0.0024163306,0.0003406326,0.10519674,0.00024903682,0.00029056382,0.02447654],"study_design_scores_gemma":[0.000026165946,0.00025673278,0.99498147,0.000008142463,0.000026027768,0.0034691037,0.00026873258,0.00019008186,0.0006007975,0.00006336898,0.00010436855,0.0000050376643],"about_ca_topic_score_codex":0.003309551,"about_ca_topic_score_gemma":0.0068945107,"teacher_disagreement_score":0.003309551,"about_ca_system_score_codex":0.0003151859,"about_ca_system_score_gemma":0.00026582243,"threshold_uncertainty_score":0.006580591},"labels":[],"label_agreement":null},{"id":"W4237118391","doi":"10.31234/osf.io/wd98h","title":"An Initial Investigation of Disrupted Intracortical Myelin as a Novel Brain Marker of Alcohol Use Disorder","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Precuneus; White matter; Neuroscience; Psychology; Posterior cingulate; Anterior cingulate cortex; Ventromedial prefrontal cortex; Neuroimaging; Insula; Prefrontal cortex; Medicine; Magnetic resonance imaging; Cortex (anatomy); Functional magnetic resonance imaging; Cognition","score_opus":0.15440208597497676,"score_gpt":0.42620404116303323,"score_spread":0.2718019551880565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237118391","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99790585,0.00021944997,0.0010663265,0.000037424386,0.000003493395,0.000026939584,0.00006892687,0.000010608431,0.0006610968],"genre_scores_gemma":[0.997638,0.00010989894,0.0017941741,0.000034841192,0.0000057863563,0.000020996273,0.00005470213,0.0000050670455,0.0003365445],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992716,0.000022342345,0.0000049369264,0.000015864474,0.0000182912,0.000011509598],"domain_scores_gemma":[0.99973196,0.00006687742,0.000047165697,0.000031465217,0.000072458424,0.000050033115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003482699,0.000180186,0.00015226356,0.00037375375,0.0002562262,0.00024004845,0.00013327658,0.00021724863,0.0013341607],"category_scores_gemma":[0.0005182111,0.00008901419,0.000086744476,0.00019838178,0.00029696332,0.00014382419,0.00030365182,0.00023124923,0.000141709],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023400588,0.00032929576,0.30797198,0.0002391135,0.00010060657,0.0017077822,0.00096797483,0.00020561823,0.6530321,0.0004165944,0.00028939746,0.032399327],"study_design_scores_gemma":[0.000035114248,0.0017125646,0.9357035,0.000022070735,0.000060417293,0.0030048792,0.00053796754,0.0010139142,0.056262102,0.0003223125,0.0013152269,0.000009931859],"about_ca_topic_score_codex":0.0010396448,"about_ca_topic_score_gemma":0.0024272893,"teacher_disagreement_score":0.0013341607,"about_ca_system_score_codex":0.00017535221,"about_ca_system_score_gemma":0.00023012461,"threshold_uncertainty_score":0.004463196},"labels":[],"label_agreement":null},{"id":"W4237123821","doi":"10.31234/osf.io/kyxbq","title":"Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies","year":2020,"lang":"en","type":"review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Helse Sør-Øst RHF; Norges Forskningsråd; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"White matter; Diffusion MRI; Executive functions; Extant taxon; Psychology; Cognition; Working memory; Concordance; Cognitive psychology; Developmental psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.04825682532562744,"score_gpt":0.3622717479132317,"score_spread":0.3140149225876043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237123821","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010690408,0.9994937,0.000051207942,0.0001240497,0.00003388155,0.000002335868,0.000019201332,0.0000026454168,0.000166076],"genre_scores_gemma":[0.00048620423,0.99923754,0.00010330135,0.00004286835,0.000051859133,0.0000035462747,0.000017141248,6.276386e-7,0.00005695041],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99966085,0.000054698634,0.00010330195,0.00008687671,0.00007576335,0.000018462224],"domain_scores_gemma":[0.99863416,0.0008866661,0.00020702934,0.000023108161,0.00020675016,0.000042182273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011850771,0.0010931195,0.0016096375,0.0038513516,0.00025644933,0.0009978224,0.0007988372,0.0009562976,0.0022799312],"category_scores_gemma":[0.002466034,0.0004095114,0.00083635055,0.0033694059,0.00054515345,0.0012500795,0.00064617465,0.0009904428,0.00088205526],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000808384,0.000043018073,0.0011371978,0.051924646,0.0002766613,0.00019076062,0.00013993557,0.00028491963,0.00059946696,0.001490169,0.009257078,0.9345753],"study_design_scores_gemma":[0.000035799494,0.00027569066,0.01770444,0.071351305,0.0018041712,0.0055970815,0.0004089905,0.00030574552,0.0010760856,0.0052610743,0.8960727,0.00010677385],"about_ca_topic_score_codex":0.0033942421,"about_ca_topic_score_gemma":0.004472992,"teacher_disagreement_score":0.0038513516,"about_ca_system_score_codex":0.0006140396,"about_ca_system_score_gemma":0.001929595,"threshold_uncertainty_score":0.0076271296},"labels":[],"label_agreement":null},{"id":"W4237537945","doi":"10.21203/rs.3.rs-17303/v6","title":"Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Meso Scale Diagnostics; National Research Foundation of Korea; National Research Foundation; Korea Health Industry Development Institute; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; University of California, San Diego; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Orientation (vector space); Materials science; Neuroscience; Nanotechnology; Psychology; Mathematics; Geometry","score_opus":0.18775313634604998,"score_gpt":0.4719486250206884,"score_spread":0.2841954886746384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237537945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841158,0.0014965661,0.012986871,0.000059702837,0.000012225852,0.000040246607,0.00038414568,0.00007172784,0.0008326492],"genre_scores_gemma":[0.98593485,0.0006157985,0.012812148,0.00002062182,0.000022274358,0.000025646847,0.0002785013,0.000008748681,0.0002814222],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998727,0.000024939638,0.000013427905,0.000037994043,0.00002543124,0.000025543392],"domain_scores_gemma":[0.9996426,0.0000600783,0.00013686225,0.000026932119,0.00009669657,0.00003696882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005392912,0.00042171177,0.00026089814,0.002014162,0.00018981875,0.0005869516,0.00016662608,0.00030120648,0.00077518483],"category_scores_gemma":[0.0007243182,0.00016830576,0.00024435532,0.0007779804,0.00023792773,0.00047954562,0.00026461325,0.00016224773,0.0002101819],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011332688,0.00011534526,0.5487903,0.00047694385,0.0003544454,0.00048828684,0.00035810363,0.0028437104,0.33220118,0.0006167034,0.0006809789,0.111940816],"study_design_scores_gemma":[0.000025787953,0.00027759583,0.92495394,0.00007252572,0.00020776599,0.0017261503,0.00037466668,0.02088136,0.04860737,0.0013841816,0.0014453209,0.00004328726],"about_ca_topic_score_codex":0.0025521065,"about_ca_topic_score_gemma":0.0032567114,"teacher_disagreement_score":0.0025521065,"about_ca_system_score_codex":0.00022181237,"about_ca_system_score_gemma":0.000216025,"threshold_uncertainty_score":0.005074501},"labels":[],"label_agreement":null},{"id":"W4238246613","doi":"10.1093/oxfordhb/9780198827474.013.6","title":"Diffusion imaging perspectives on brain development in childhood and adolescence","year":2021,"lang":"en","type":"reference-entry","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Brain development; Diffusion imaging; Tractography; Reading (process); Psychology; Cognition; Neuroscience; Cognitive science; Computer science; Cognitive psychology; Magnetic resonance imaging; Medicine; Political science","score_opus":0.03218922117453214,"score_gpt":0.32445512791405023,"score_spread":0.2922659067395181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238246613","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0066325427,0.54585606,0.054660276,0.057413287,0.002642733,0.00004438844,0.00072230876,0.00023092495,0.33179745],"genre_scores_gemma":[0.15794559,0.6746869,0.061018758,0.005858927,0.0041214,0.00017595768,0.0005473569,0.00023986527,0.09540523],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961436,0.00016053952,0.000024204646,0.000079666854,0.000075019234,0.00004613086],"domain_scores_gemma":[0.99936765,0.0003831705,0.000046409397,0.000030889947,0.00012162504,0.000050195937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011940048,0.0007637496,0.0004201617,0.002255615,0.0008868762,0.0032849184,0.0007184528,0.0018614916,0.008261626],"category_scores_gemma":[0.0014383113,0.000299471,0.00037612877,0.0016536226,0.004237869,0.0036349522,0.0013049099,0.0027333964,0.0023602995],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011992317,0.000009011431,0.0004798819,0.000259243,0.000008808988,0.0002479269,0.0018540766,0.00034012724,0.0006786786,0.92964625,0.015244165,0.051219914],"study_design_scores_gemma":[0.000002503322,0.000024936331,0.0021410857,0.00081758207,0.000008894485,0.001016101,0.001112557,0.0003892159,0.00057656725,0.40999535,0.58389497,0.000020165975],"about_ca_topic_score_codex":0.004481593,"about_ca_topic_score_gemma":0.0064314166,"teacher_disagreement_score":0.008261626,"about_ca_system_score_codex":0.0022550551,"about_ca_system_score_gemma":0.0014830473,"threshold_uncertainty_score":0.027637899},"labels":[],"label_agreement":null},{"id":"W4240121982","doi":"10.21203/rs.3.rs-151934/v3","title":"Regional cerebral blood flow decline can predict atrophy in Alzheimer’s disease spectrum","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Cerebral blood flow; Medicine; Neuroscience; Cardiology; Disease; Neurodegeneration; Psychology; Internal medicine; Cerebral atrophy; Alzheimer's disease; Pathology","score_opus":0.1582735723650386,"score_gpt":0.4389821395994455,"score_spread":0.28070856723440685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240121982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986071,0.00027526703,0.0002233577,0.000031822507,0.000008350156,0.000007121441,0.0001461082,0.000009341241,0.0006915704],"genre_scores_gemma":[0.9994159,0.000055688597,0.00016195931,0.000014827968,0.000009912311,0.0000045797074,0.00015631068,0.0000016736535,0.00017934],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998895,0.000027014665,0.0000116047995,0.00003355322,0.0000204488,0.00001785482],"domain_scores_gemma":[0.99941635,0.00018112731,0.00015999375,0.000036747955,0.00008117087,0.00012465888],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055885053,0.00035879476,0.00029888964,0.0013777195,0.00017386729,0.00031738624,0.00016521047,0.0004076279,0.001902906],"category_scores_gemma":[0.0012746704,0.00008493357,0.00017015432,0.00037675622,0.00021375014,0.00027209648,0.0002529151,0.0003324375,0.00028822644],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000796558,0.00011719849,0.9907088,0.000017168484,0.00005934082,0.00019663492,0.000072610754,0.00012806646,0.0029899196,0.000044318007,0.00018372053,0.004685531],"study_design_scores_gemma":[0.000007183563,0.00012460467,0.99847597,0.0000048494276,0.00002275541,0.0002770887,0.000077111064,0.00039201367,0.0003625584,0.00016057353,0.00009254854,0.00000260403],"about_ca_topic_score_codex":0.0015858526,"about_ca_topic_score_gemma":0.0010485457,"teacher_disagreement_score":0.001902906,"about_ca_system_score_codex":0.000116258736,"about_ca_system_score_gemma":0.0000914496,"threshold_uncertainty_score":0.0063658357},"labels":[],"label_agreement":null},{"id":"W4243148449","doi":"10.14740/jnr498","title":"A Rare Case Presenting With Acute Stroke-Like Clinic: Todd’s Paralysis in the Setting of Frontal Dural-Based Tumor","year":2018,"lang":"en","type":"article","venue":"Journal of Neurology Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Neuroimaging; Stroke (engine); Lesion; Presentation (obstetrics); Paralysis; Radiology; Diffusion MRI; Surgery; Magnetic resonance imaging; Psychiatry","score_opus":0.13547468796090717,"score_gpt":0.4708616918822766,"score_spread":0.33538700392136944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243148449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95380247,0.012595908,0.0061036097,0.005762132,0.0009285376,0.00022030654,0.00040255196,0.0002539202,0.019930666],"genre_scores_gemma":[0.99047977,0.003183116,0.002134556,0.0012263277,0.0012484748,0.00003203532,0.00010828101,0.000024317183,0.0015630363],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.999556,0.000049477163,0.00005273069,0.00010554695,0.000039665163,0.00019648542],"domain_scores_gemma":[0.9992061,0.00016019045,0.00022529825,0.000072587856,0.000048605216,0.00028725978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002521545,0.0014485002,0.0010868385,0.0016942703,0.0022233445,0.0018632156,0.0008471959,0.0037321104,0.0024559223],"category_scores_gemma":[0.0020362427,0.00071522937,0.0006847222,0.001561043,0.0015511202,0.0024096533,0.0017313055,0.0024900057,0.0009825208],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017376891,0.000016411257,0.0042693275,0.000021014494,0.0000044299436,0.99413306,0.000101003476,0.000024233597,0.00029078088,0.00010744865,0.00023199526,0.000782955],"study_design_scores_gemma":[0.0000048567704,0.000017550135,0.0013383323,0.000007773697,0.000005191136,0.9978929,0.00009900411,0.000052018782,0.00009518073,0.00015454678,0.00032734935,0.0000052652767],"about_ca_topic_score_codex":0.0014471724,"about_ca_topic_score_gemma":0.0025077667,"teacher_disagreement_score":0.0037321104,"about_ca_system_score_codex":0.00078538817,"about_ca_system_score_gemma":0.0007233925,"threshold_uncertainty_score":0.008215845},"labels":[],"label_agreement":null},{"id":"W4244275492","doi":"10.22215/etd/2006-06365","title":"Rician noise corrected multi-component analysis of the MR diffusion signal decay for human brain in vivo","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Rician fading; Noise (video); Physics; Computer science; Telecommunications; Artificial intelligence","score_opus":0.037154925508596816,"score_gpt":0.36313552015658856,"score_spread":0.32598059464799173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244275492","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025921322,0.0011283642,0.96983945,0.00026413548,0.00009558474,0.000045057262,0.00021904994,0.001038051,0.0014489478],"genre_scores_gemma":[0.2664304,0.0036205074,0.7106765,0.00011537463,0.0001279902,0.0001173154,0.0016032684,0.0011079931,0.016200708],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999105,0.000024973166,0.000006794696,0.000018256476,0.00003024267,0.00000925547],"domain_scores_gemma":[0.9997352,0.00008287952,0.000024236448,0.000058803904,0.000087986584,0.000010961918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004366465,0.0004883245,0.00021995128,0.00075101934,0.00019710984,0.00041691077,0.00032414062,0.0004140287,0.0021104056],"category_scores_gemma":[0.0016885333,0.00019160185,0.00042506206,0.00051096437,0.00023444791,0.00045012098,0.00024036839,0.0004607196,0.0012811554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039402046,0.00009668659,0.00095909194,0.00045645627,0.00013583338,0.00018126487,0.000229395,0.082249135,0.30800363,0.017409898,0.01227823,0.57760644],"study_design_scores_gemma":[0.000019258536,0.00009147673,0.0075130053,0.0000367553,0.00011502237,0.00040079598,0.000055073095,0.8473879,0.11944133,0.0064203786,0.018460957,0.000058087175],"about_ca_topic_score_codex":0.002687294,"about_ca_topic_score_gemma":0.0052349167,"teacher_disagreement_score":0.002687294,"about_ca_system_score_codex":0.00030553297,"about_ca_system_score_gemma":0.00073004403,"threshold_uncertainty_score":0.0070599914},"labels":[],"label_agreement":null},{"id":"W4244753611","doi":"10.1002/0470018860.s00314","title":"Cerebral Commissures","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Cognitive Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Corpus callosum; Commissure; Neuroscience; Psychology; Brain asymmetry; Anatomy; Biology; Lateralization of brain function","score_opus":0.03512739118725164,"score_gpt":0.367432128356595,"score_spread":0.3323047371693434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244753611","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027391309,0.016034046,0.012767112,0.0024714335,0.0021533335,0.00012283953,0.004276457,0.0016034824,0.93318003],"genre_scores_gemma":[0.39947128,0.011680567,0.011192285,0.001008805,0.0011582646,0.00017824883,0.005631187,0.00046410755,0.56921524],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996767,0.000026665068,0.000018643592,0.00007993599,0.00014054848,0.00005760902],"domain_scores_gemma":[0.9996245,0.00005263401,0.00006130719,0.000073821495,0.00010775231,0.00008000525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014825165,0.0006115725,0.00023437927,0.0015247326,0.0013577505,0.0023981438,0.00070100866,0.0010041388,0.08780251],"category_scores_gemma":[0.0011799021,0.0001311393,0.00028019096,0.0013824155,0.0011211311,0.001094387,0.0010861326,0.0012569735,0.028924834],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030783983,0.000054974906,0.0033831128,0.0010931913,0.00007459814,0.0044022603,0.0010026848,0.0007054143,0.026858218,0.3192271,0.118314385,0.5245763],"study_design_scores_gemma":[0.00003870236,0.00008293238,0.014556121,0.00032712548,0.000033860488,0.006492534,0.00039326085,0.00045012758,0.012128637,0.040032275,0.9254302,0.00003425708],"about_ca_topic_score_codex":0.010304263,"about_ca_topic_score_gemma":0.010881194,"teacher_disagreement_score":0.08780251,"about_ca_system_score_codex":0.0013337435,"about_ca_system_score_gemma":0.0012812007,"threshold_uncertainty_score":0.29372865},"labels":[],"label_agreement":null},{"id":"W4246958620","doi":"10.1016/j.clinph.2014.10.202","title":"43. Cerebellar activity in cervical dystonia during a motor timing task: An fMRI study","year":2015,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Cervical dystonia; Dystonia; Cerebellum; Neuroscience; Neurology; Supplementary motor area; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Psychology; Movement disorders; Motor cortex; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.21298018463733398,"score_gpt":0.45605786596873243,"score_spread":0.24307768133139845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246958620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99179333,0.00068774924,0.0017271227,0.000384206,0.000033836193,0.00013674807,0.00027830197,0.000025899652,0.004932842],"genre_scores_gemma":[0.99708825,0.0003070284,0.000785024,0.0003518393,0.00006332573,0.00008029083,0.00012530031,0.000021255808,0.0011776669],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99984944,0.000033572553,0.000015497571,0.000040665625,0.000015785883,0.00004510414],"domain_scores_gemma":[0.9997068,0.00015627404,0.00003361242,0.000028415601,0.000028966408,0.00004597065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005889881,0.00045521607,0.0003444617,0.00034179387,0.00079004286,0.0003793967,0.00044725425,0.0018455946,0.0047166143],"category_scores_gemma":[0.0015855862,0.0004712999,0.00041794265,0.00029216617,0.0008713428,0.0008966949,0.0003838648,0.00086581183,0.0006323306],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.017104167,0.0012311131,0.02690225,0.0004634082,0.00029502687,0.028574297,0.0013315575,0.00043487034,0.89369583,0.00096274645,0.0008299935,0.028174747],"study_design_scores_gemma":[0.0022955867,0.008859041,0.804848,0.0001437718,0.0012716891,0.03219531,0.001134055,0.0044398503,0.13731581,0.001697982,0.0056946645,0.000104255116],"about_ca_topic_score_codex":0.0071363603,"about_ca_topic_score_gemma":0.0070614815,"teacher_disagreement_score":0.0071363603,"about_ca_system_score_codex":0.00038959458,"about_ca_system_score_gemma":0.00049436284,"threshold_uncertainty_score":0.015778601},"labels":[],"label_agreement":null},{"id":"W4247546798","doi":"10.1002/(sici)1520-6777(2000)19:2<176::aid-nau7>3.3.co;2-y","title":"Editorial comment","year":2000,"lang":"en","type":"editorial","venue":"Neurourology and Urodynamics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Misericordia Community Hospital","funders":"","keywords":"Citation; Library science; Center (category theory); Medicine; Computer science","score_opus":0.015255911939679404,"score_gpt":0.32280369128638764,"score_spread":0.30754777934670824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247546798","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008975829,0.0018977871,0.00008499813,0.18749467,0.80604285,0.00003658092,0.00008177294,0.00006610791,0.004205508],"genre_scores_gemma":[0.0015055884,0.0018059147,0.00019506835,0.33017847,0.62988156,0.000091050366,0.00009328632,0.000088517256,0.03616053],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9930568,0.0012431765,0.0008087846,0.00093594467,0.0030640573,0.0008912613],"domain_scores_gemma":[0.97785145,0.00629779,0.002304873,0.0009360736,0.009508256,0.0031015428],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009383885,0.0025911285,0.003768107,0.0029213768,0.0043260846,0.007448313,0.004298596,0.044251718,0.030071842],"category_scores_gemma":[0.05187673,0.0012252645,0.0030485278,0.0015707085,0.0025104913,0.0034271928,0.002486461,0.028091304,0.02135967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025153317,0.0000049317387,0.00002541545,0.000053128086,0.000009962566,0.00017265469,0.00001293217,0.000007783029,0.0000214883,0.00011344773,0.99814796,0.0014050985],"study_design_scores_gemma":[0.00013182631,0.000022678476,0.00036680038,0.0003213046,0.00007204689,0.0002969545,0.00006801036,0.00009768148,0.00012167396,0.0006356334,0.9978389,0.000026399126],"about_ca_topic_score_codex":0.004266431,"about_ca_topic_score_gemma":0.00935167,"teacher_disagreement_score":0.96992815,"about_ca_system_score_codex":0.0053057563,"about_ca_system_score_gemma":0.004974673,"threshold_uncertainty_score":0.10060036},"labels":[],"label_agreement":null},{"id":"W4248396262","doi":"10.1515/iupac.88.1498","title":"White Matter","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","score_opus":0.0487649783676308,"score_gpt":0.49893799785971954,"score_spread":0.45017301949208877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248396262","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029282123,0.0009076791,0.00024117848,0.00020778435,0.00011119074,0.00003841202,0.9929894,0.00043556647,0.0047759605],"genre_scores_gemma":[0.0012290053,0.00086429436,0.0008069023,0.0003430357,0.000072426126,0.00020605678,0.993238,0.00015764245,0.0030826684],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99886334,0.00013417286,0.00025329326,0.00043383133,0.00019041769,0.0001250395],"domain_scores_gemma":[0.99658316,0.00086480525,0.00058236596,0.0008222743,0.000917623,0.0002297313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083685276,0.001788311,0.0018208268,0.0050060335,0.00089984335,0.003416193,0.002474887,0.001951956,0.16259259],"category_scores_gemma":[0.011749063,0.0005369674,0.001511782,0.007820812,0.00044891532,0.0028116393,0.001985648,0.0018472687,0.16348602],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013135132,0.000013846243,0.001761129,0.0022611124,0.00008344446,0.000075178876,0.000027141034,0.000110728695,0.00014349597,0.0007385526,0.9787183,0.015935613],"study_design_scores_gemma":[0.00015107458,0.000023210763,0.00933619,0.0020423008,0.00010486989,0.00052846776,0.00008082623,0.00021301475,0.0002998537,0.0046442314,0.98252696,0.00004911807],"about_ca_topic_score_codex":0.012099679,"about_ca_topic_score_gemma":0.02538108,"teacher_disagreement_score":0.16259259,"about_ca_system_score_codex":0.0011085264,"about_ca_system_score_gemma":0.0025433712,"threshold_uncertainty_score":0.54392636},"labels":[],"label_agreement":null},{"id":"W4249581603","doi":"10.1017/cjn.2019.183","title":"P.087 The influence of disease lateralization in Parkinson’s Disease on tractography in DBS patients","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Motor cortex; Diffusion MRI; Parkinson's disease; Lateralization of brain function; Medicine; Neuroscience; Cortex (anatomy); Disease; Tractography; White matter; Psychology; Magnetic resonance imaging; Pathology; Stimulation; Radiology","score_opus":0.032662868879588206,"score_gpt":0.29722750021525907,"score_spread":0.2645646313356709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249581603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984989,0.00016271551,0.00015611945,0.000041692747,0.0000044435205,0.0000044182516,0.00015863759,0.0000048622,0.0009682587],"genre_scores_gemma":[0.99967325,0.000029242043,0.00007420287,0.000007991044,0.0000038988906,0.0000030745732,0.00008514007,0.0000027008757,0.00012045888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998517,0.000030711642,0.00002275519,0.00003588258,0.000037527807,0.000021409409],"domain_scores_gemma":[0.9991911,0.00026434282,0.0002910551,0.000032496388,0.00009306344,0.00012790917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023276605,0.0001939158,0.00017684646,0.00048054452,0.00020788665,0.00034055935,0.00009563353,0.00020619271,0.0056101535],"category_scores_gemma":[0.0015333067,0.00006355388,0.00018019338,0.00026592586,0.00028411055,0.00018648074,0.00021492975,0.00011832942,0.00048160128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012359575,0.000034122007,0.9699724,0.000044863187,0.00008751176,0.0019690522,0.00023830943,0.00018905353,0.0068450677,0.000099273675,0.00031622185,0.018968191],"study_design_scores_gemma":[0.000011839791,0.00019195248,0.99531245,0.000014171685,0.000026591277,0.003157794,0.00012700868,0.0003624303,0.00041909987,0.00014858649,0.00022330419,0.0000048001643],"about_ca_topic_score_codex":0.0021374463,"about_ca_topic_score_gemma":0.0028985692,"teacher_disagreement_score":0.0056101535,"about_ca_system_score_codex":0.00018880429,"about_ca_system_score_gemma":0.0002260282,"threshold_uncertainty_score":0.018767893},"labels":[],"label_agreement":null},{"id":"W4249932430","doi":"10.1007/s00062-015-0425-8","title":"Erratum to: Diagnostics to Look beyond the Normal Appearing Brain Tissue (NABT)? A Neuroimaging Study of Patients with Primary Headache and NABT Using Magnetization Transfer Imaging and Diffusion Magnetic Resonance","year":2015,"lang":"en","type":"erratum","venue":"Clinical Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Neuroimaging; Magnetic resonance imaging; Diffusion MRI; Medicine; Magnetization transfer; Nuclear magnetic resonance; Radiology; Physics; Psychiatry","score_opus":0.043791940382237465,"score_gpt":0.35648342893521096,"score_spread":0.31269148855297346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249932430","genre_codex":"editorial","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050652544,0.0073734587,0.00070278504,0.20069343,0.77561396,0.00011226012,0.00095928315,0.00024159365,0.009237943],"genre_scores_gemma":[0.056497276,0.015163007,0.005465369,0.38370487,0.40651065,0.00017149567,0.0023938902,0.000635673,0.12945783],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99847025,0.00019259857,0.00057394017,0.00017771123,0.00043501554,0.00015046413],"domain_scores_gemma":[0.9905025,0.0033645649,0.0010399404,0.00047174297,0.003954518,0.0006668166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014946096,0.00141623,0.0012474242,0.0025626156,0.0019905043,0.0014358043,0.0016086103,0.0083318455,0.012147193],"category_scores_gemma":[0.02429921,0.0008324228,0.0011570316,0.001092,0.0013177025,0.0016143295,0.0007503536,0.005388993,0.007874788],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013678455,0.00007108996,0.0022130557,0.00023979504,0.000028273049,0.02323133,0.00009201094,0.0000678452,0.00019609783,0.0006095321,0.96256495,0.010549318],"study_design_scores_gemma":[0.0002350259,0.00026124093,0.014217972,0.0011942461,0.00017003453,0.056733746,0.0006781306,0.00071724015,0.0012575336,0.0015526874,0.9228367,0.00014545184],"about_ca_topic_score_codex":0.0070429635,"about_ca_topic_score_gemma":0.00852895,"teacher_disagreement_score":0.012147193,"about_ca_system_score_codex":0.0016526687,"about_ca_system_score_gemma":0.0024652586,"threshold_uncertainty_score":0.04063642},"labels":[],"label_agreement":null},{"id":"W4250695708","doi":"10.1016/j.jalz.2019.06.4828","title":"F5‐02‐02: HIGHER LITERACY ASSOCIATES WITH BETTER BRAIN STRUCTURE AND COGNITION IN MIDDLE‐AGED INDIVIDUALS","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; White matter; Psychology; Literacy; Diffusion MRI; Logistic regression; Effects of sleep deprivation on cognitive performance; Medicine; Clinical psychology; Internal medicine; Gerontology; Neuroscience; Magnetic resonance imaging","score_opus":0.03492232176081524,"score_gpt":0.30974468124041904,"score_spread":0.2748223594796038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250695708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99871504,0.000071683055,0.00007994025,0.00014402383,0.000014981,0.000007393155,0.0002862186,0.00000615472,0.0006744058],"genre_scores_gemma":[0.9987722,0.000019951793,0.00010094616,0.00006651106,0.000020501084,0.0000105113395,0.0002792092,0.0000027291617,0.0007274489],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974245,0.00007056977,0.00003121669,0.000065957414,0.000029061379,0.000060675146],"domain_scores_gemma":[0.9988167,0.00024800713,0.00048638962,0.00006728581,0.00011320536,0.00026834282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073007675,0.0004279744,0.00034725954,0.0005528745,0.00054111134,0.0006811351,0.000370999,0.0011026531,0.010873453],"category_scores_gemma":[0.0025227966,0.00022061077,0.00060491345,0.00039152504,0.00040636075,0.0005348167,0.00060024485,0.00069451856,0.0011007609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010281634,0.00037196313,0.9931039,0.000027187049,0.00009574817,0.00020981042,0.00019243851,0.000035946916,0.00072770816,0.000059063033,0.0005219669,0.0036259908],"study_design_scores_gemma":[0.000029039375,0.0003020215,0.99869114,0.000007753547,0.000045856636,0.00025072705,0.00014230814,0.0001678211,0.00009232638,0.00007290452,0.00019390488,0.0000042199226],"about_ca_topic_score_codex":0.0047118952,"about_ca_topic_score_gemma":0.003282309,"teacher_disagreement_score":0.010873453,"about_ca_system_score_codex":0.00015354468,"about_ca_system_score_gemma":0.00031742555,"threshold_uncertainty_score":0.036375344},"labels":[],"label_agreement":null},{"id":"W4252126261","doi":"10.1017/s0317167100120591","title":"Program - 39th Canadian Congress of Neurological Sciences - Calgary, AB","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Pfizer (Canada)","funders":"","keywords":"Action (physics); Medicine; Neuroscience; Psychology; Political science; Physics","score_opus":0.07349139815938738,"score_gpt":0.34707564195235424,"score_spread":0.27358424379296686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252126261","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001674426,0.027066572,0.0011235594,0.008184682,0.010236352,0.00019193187,0.0028740745,0.00044649973,0.94820195],"genre_scores_gemma":[0.0019543353,0.012615911,0.00073575566,0.00084174477,0.00038401404,0.00004162905,0.0007083697,0.00010570352,0.9826126],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994968,0.00003162844,0.000022633594,0.00012465371,0.000221198,0.00010306627],"domain_scores_gemma":[0.99926966,0.000038290884,0.000017573964,0.000033693857,0.00038736645,0.00025329023],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00045660176,0.0015431835,0.0007348158,0.0015044207,0.0018480944,0.0027794244,0.0011030844,0.0019283621,0.61991316],"category_scores_gemma":[0.0008756242,0.00034290244,0.0005920621,0.001307175,0.0007109196,0.001120895,0.0020066719,0.0025288344,0.3015205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096948796,0.000068120076,0.0005404032,0.0002762378,0.000012838309,0.00040171825,0.00006897034,0.00014193084,0.00084878696,0.003909098,0.68787014,0.30576476],"study_design_scores_gemma":[0.000008324006,0.000011288767,0.0007586528,0.0001379991,0.0000026156376,0.0002079938,0.000045220353,0.000048556758,0.00007681033,0.0002985668,0.99839944,0.0000046194446],"about_ca_topic_score_codex":0.122412525,"about_ca_topic_score_gemma":0.30029497,"teacher_disagreement_score":0.9958274,"about_ca_system_score_codex":0.004172639,"about_ca_system_score_gemma":0.008768795,"threshold_uncertainty_score":0.54214776},"labels":[],"label_agreement":null},{"id":"W4252441736","doi":"10.1002/jmri.21928","title":"Response","year":2009,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; Diffusion MRI; Consistency (knowledge bases); White matter; Range (aeronautics); Statistics; Limit (mathematics); Psychology; Mathematics; Computer science; Medicine; Artificial intelligence; Neuroscience; Magnetic resonance imaging; Mathematical analysis; Radiology","score_opus":0.031608599297337725,"score_gpt":0.3474184962907703,"score_spread":0.3158098969934326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252441736","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009015741,0.0011266742,0.00059179193,0.8368395,0.13487694,0.00032899345,0.0017566241,0.00069004495,0.022887861],"genre_scores_gemma":[0.0046159457,0.0007417517,0.0005456679,0.904456,0.016165664,0.000525047,0.0004651113,0.00018898754,0.07229586],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973483,0.00079824653,0.00027465276,0.00039256888,0.0007746952,0.00041152682],"domain_scores_gemma":[0.9850154,0.0044315923,0.00065458525,0.0004692046,0.0071576075,0.002271467],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0034285008,0.0009951935,0.0009815113,0.000689088,0.002171314,0.002601971,0.0020361005,0.013881314,0.1579692],"category_scores_gemma":[0.039589424,0.00044934906,0.00089652534,0.0004413482,0.0012063651,0.002635083,0.00305209,0.014083046,0.09105782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021693317,0.000007281029,0.00009175779,0.00003444033,0.0000012257525,0.000062145205,0.000039864706,0.000008439186,0.000036997808,0.00027524677,0.9965167,0.0029042272],"study_design_scores_gemma":[0.000023642582,0.00003464047,0.00045030363,0.00016172713,0.0000033705185,0.00026547728,0.00041826448,0.000059783542,0.000106733336,0.00063957885,0.9978156,0.000020855217],"about_ca_topic_score_codex":0.0033747435,"about_ca_topic_score_gemma":0.0036232292,"teacher_disagreement_score":0.84203076,"about_ca_system_score_codex":0.0029389733,"about_ca_system_score_gemma":0.0034748705,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4252507602","doi":"10.1017/s0317167100000809","title":"35th Meeting of the Canadian Congress of Neurological Sciences June 13- 17, 2000 Ottawa, Ontario Program and Abstracts","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"Medical Research Council; University of Cambridge; Heart and Stroke Foundation of Canada","keywords":"Library science; Action (physics); Political science; Medicine; Computer science; Physics","score_opus":0.051961381451173516,"score_gpt":0.312746832703439,"score_spread":0.2607854512522655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252507602","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0112851625,0.07578519,0.0029401814,0.068425655,0.11233267,0.0008018971,0.013054998,0.0005713573,0.7148029],"genre_scores_gemma":[0.00786922,0.015529455,0.0007584221,0.001295569,0.0028306413,0.00008337476,0.0017391659,0.00011965102,0.96977454],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941945,0.000035293324,0.000034153058,0.00009105094,0.00024214416,0.00017791802],"domain_scores_gemma":[0.99847764,0.000034663193,0.000029440636,0.000029968436,0.00097568455,0.00045269745],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008142665,0.0014761812,0.0008124758,0.0016128254,0.0030649828,0.0023050078,0.0010820018,0.0019017208,0.36651745],"category_scores_gemma":[0.00097599556,0.00038214546,0.00071399065,0.0010054949,0.00087883597,0.0011117428,0.0014973183,0.0016770342,0.11531949],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014712103,0.000037652437,0.0011512459,0.00028652622,0.000018831293,0.00023685586,0.00012956618,0.00008355551,0.0009426135,0.00088026974,0.93578374,0.06030214],"study_design_scores_gemma":[0.000010072482,0.000019033938,0.0024319442,0.00014497412,0.00001092875,0.00011895578,0.000112958194,0.000051202216,0.00012028478,0.00015550977,0.9968129,0.000011199917],"about_ca_topic_score_codex":0.34394246,"about_ca_topic_score_gemma":0.78292316,"teacher_disagreement_score":0.990764,"about_ca_system_score_codex":0.009235997,"about_ca_system_score_gemma":0.014360992,"threshold_uncertainty_score":0.903586},"labels":[],"label_agreement":null},{"id":"W4253133942","doi":"10.1016/j.jalz.2016.06.1900","title":"P3‐238: Associations Between Quantitative Tractography at 3T MRI and Cognitive Function in Alzheimer’s Disease","year":2016,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Toronto","funders":"","keywords":"Tractography; Disease; Cognition; Medicine; Neuroscience; Diffusion MRI; Psychology; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.09366932744883896,"score_gpt":0.3640812705890986,"score_spread":0.2704119431402596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253133942","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99936134,0.00007689496,0.00023140883,0.00001785499,0.0000029211167,0.0000031527925,0.00012776369,0.000005799802,0.00017281383],"genre_scores_gemma":[0.99939835,0.000026946243,0.00019590642,0.0000056621107,0.000006887001,0.000005127892,0.00013661194,0.0000052229707,0.00021917307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985313,0.00003103692,0.0000149091275,0.00004541019,0.00003229152,0.000023252498],"domain_scores_gemma":[0.99893945,0.00021301967,0.00047862643,0.00010671129,0.00014077536,0.000121437115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046055607,0.000449017,0.0002587642,0.00056844397,0.00033654828,0.0004220214,0.00024995333,0.00040403966,0.0025612046],"category_scores_gemma":[0.0018750097,0.00013722267,0.00036314857,0.00039787876,0.0002853239,0.00036940663,0.0003148294,0.00027716128,0.00033950692],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020563304,0.00014082067,0.9639768,0.00006483669,0.00037247478,0.0010651627,0.000452741,0.00028646438,0.016523568,0.0001374909,0.00037162783,0.014551623],"study_design_scores_gemma":[0.000023001534,0.00024384512,0.99514353,0.0000070952046,0.000046149373,0.0020534082,0.00010958338,0.0006811624,0.001061546,0.00031773234,0.00030462365,0.000008304562],"about_ca_topic_score_codex":0.0029311283,"about_ca_topic_score_gemma":0.0022176523,"teacher_disagreement_score":0.0029311283,"about_ca_system_score_codex":0.00019124376,"about_ca_system_score_gemma":0.00019197051,"threshold_uncertainty_score":0.008568108},"labels":[],"label_agreement":null},{"id":"W4254125247","doi":"10.7287/peerj.preprints.2323v1","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Corpus callosum; Ex vivo; Diffusion MRI; Myelin; Magnetic resonance imaging; Central nervous system; Neuroscience; Hippocampus; Cerebellum; Thalamus; Pathology; Nuclear magnetic resonance; Medicine; Anatomy; Biology; In vivo; Physics; Radiology","score_opus":0.09378277241434148,"score_gpt":0.3918385396305597,"score_spread":0.29805576721621824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254125247","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8846141,0.0045121377,0.09046196,0.00069442124,0.00022488684,0.00021416899,0.011796512,0.002243451,0.005238176],"genre_scores_gemma":[0.84809655,0.004788698,0.11369855,0.0004093399,0.00008248569,0.00058702775,0.008749733,0.0013273444,0.022260204],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996031,0.000036565398,0.000048938033,0.0001605022,0.00010397805,0.00004680364],"domain_scores_gemma":[0.99894685,0.00013981403,0.00041901646,0.00014071133,0.00015900416,0.00019458722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094714336,0.0014113978,0.000544632,0.0028173458,0.000410615,0.000671745,0.0007823119,0.0012051401,0.0028104833],"category_scores_gemma":[0.00036566652,0.00051149284,0.000622779,0.00075130205,0.00087035995,0.00073315983,0.0005370304,0.001389022,0.0012235967],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017610432,0.00004115675,0.0001438479,0.00008752909,0.00001821816,0.00013283838,0.00006634104,0.00016396657,0.9975835,0.0002843157,0.00012900603,0.0011732302],"study_design_scores_gemma":[0.000039371458,0.00036846733,0.008286337,0.00006619323,0.00011744252,0.0011720035,0.00009379654,0.002214351,0.98170817,0.00036527577,0.0055310754,0.000037472],"about_ca_topic_score_codex":0.0014406081,"about_ca_topic_score_gemma":0.0018382575,"teacher_disagreement_score":0.0028173458,"about_ca_system_score_codex":0.0004670998,"about_ca_system_score_gemma":0.00022356809,"threshold_uncertainty_score":0.009401977},"labels":[],"label_agreement":null},{"id":"W4254767907","doi":"10.21203/rs.3.rs-276635/v1","title":"The trajectory of putative astroglial dysfunction in first episode schizophrenia: A longitudinal 7-Tesla MRS study","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Schulich School of Medicine and Dentistry; Canadian Institutes of Health Research; Academic Medical Organization of Southwestern Ontario; Natural Sciences and Engineering Research Council of Canada; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Inositol; Anterior cingulate cortex; Psychosis; Antipsychotic; Internal medicine; Psychology; Cortex (anatomy); Magnetic resonance imaging; Psychiatry; Medicine; Neuroscience; Endocrinology; Cognition; Receptor; Radiology","score_opus":0.14077035095529916,"score_gpt":0.44873519592468875,"score_spread":0.3079648449693896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254767907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994242,0.00012207724,0.00006120518,0.00002704191,0.0000016503271,0.0000066755942,0.00021645548,0.0000035873377,0.00013698927],"genre_scores_gemma":[0.99907875,0.000080736194,0.00009212725,0.000011036817,0.0000029078074,0.000009316385,0.0004284317,0.00000243329,0.00029433382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998305,0.000039674127,0.000012105234,0.000046671375,0.000028918428,0.00004205484],"domain_scores_gemma":[0.9991848,0.00007338206,0.00033068276,0.00007643441,0.00015128602,0.00018346279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005941143,0.00027651092,0.00035351745,0.00064054615,0.000806786,0.0006493401,0.00026963154,0.0006299696,0.0011319984],"category_scores_gemma":[0.0014474618,0.00030009632,0.0002788098,0.0005113444,0.00022656417,0.0005007302,0.0004806973,0.00058517227,0.0003790845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013887398,0.0003355469,0.9883483,0.000019070876,0.00010227642,0.00032874697,0.00067686965,0.00009902501,0.0046843872,0.00003925308,0.0001558762,0.00382184],"study_design_scores_gemma":[0.0000058326723,0.0002431211,0.99900025,0.0000039769225,0.000021790087,0.00015511671,0.00018177803,0.00008822099,0.00016387638,0.000023208195,0.00010758197,0.0000053013673],"about_ca_topic_score_codex":0.010743804,"about_ca_topic_score_gemma":0.012922486,"teacher_disagreement_score":0.010743804,"about_ca_system_score_codex":0.0004276826,"about_ca_system_score_gemma":0.00045612696,"threshold_uncertainty_score":0.021362543},"labels":[],"label_agreement":null},{"id":"W4255397424","doi":"10.1017/cbo9781316146187.006","title":"Neuroimaging","year":2015,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Neuroimaging; Psychology; Neuroscience","score_opus":0.11606178957780547,"score_gpt":0.2965323569849975,"score_spread":0.18047056740719206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255397424","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016520479,0.16055793,0.040838365,0.013210692,0.008812245,0.00027505678,0.016944688,0.003872687,0.7538362],"genre_scores_gemma":[0.012565678,0.1686597,0.03415772,0.0057346467,0.004233834,0.00032900242,0.017510688,0.001465685,0.755343],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99973196,0.00003634509,0.000020995403,0.00005679603,0.00013507935,0.000018901947],"domain_scores_gemma":[0.9995301,0.00011673057,0.000025154442,0.00007504511,0.00019887525,0.000054157554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065221207,0.000879137,0.00065785676,0.002472764,0.0004108076,0.0017740036,0.0011758903,0.0013265256,0.23422669],"category_scores_gemma":[0.0023727652,0.00034195735,0.00065404206,0.0017235834,0.0004910551,0.0016448927,0.0006393431,0.0013013943,0.1370605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032432305,0.000019141848,0.00018015825,0.000829109,0.000029645496,0.00018374517,0.00005815066,0.0001687368,0.00103436,0.010555675,0.5932135,0.39369535],"study_design_scores_gemma":[0.000005546822,0.000020248357,0.000832296,0.00052362174,0.000015513646,0.0013900893,0.00004230895,0.000115677554,0.00050080766,0.013530424,0.98301136,0.0000122690735],"about_ca_topic_score_codex":0.002763929,"about_ca_topic_score_gemma":0.005600471,"teacher_disagreement_score":0.23422669,"about_ca_system_score_codex":0.0008534909,"about_ca_system_score_gemma":0.0011849824,"threshold_uncertainty_score":0.78356636},"labels":[],"label_agreement":null},{"id":"W4280492380","doi":"10.1016/j.compbiomed.2022.105603","title":"Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation","year":2022,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Feature selection; Autoencoder; Generative model; Identification (biology); Regularization (linguistics); Inference; Machine learning; Data mining; Deep learning; Generative grammar","score_opus":0.10161320967396054,"score_gpt":0.4258322277452344,"score_spread":0.32421901807127385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280492380","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17367353,0.0069234753,0.80605924,0.0021178084,0.0006508691,0.00019042888,0.004803743,0.0028156384,0.0027652755],"genre_scores_gemma":[0.7368073,0.002220397,0.24996024,0.00047202245,0.00019009401,0.0002535659,0.006288134,0.0001430826,0.0036651809],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947864,0.00017861149,0.000042405583,0.00014790744,0.00009252069,0.000059868395],"domain_scores_gemma":[0.9990283,0.00041140683,0.000093051836,0.0001613227,0.0002678093,0.000038126425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001727907,0.0010889232,0.0010500862,0.0014022399,0.0004666732,0.0010076569,0.0006959776,0.0009857505,0.0016862554],"category_scores_gemma":[0.0049865055,0.0003974775,0.0016842907,0.0009421841,0.00046941594,0.0011611931,0.0014565125,0.0013068414,0.0007372115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016755182,0.00063256256,0.040831838,0.00054512627,0.0010448606,0.0006782921,0.00022681568,0.11316416,0.050222717,0.008641497,0.011442601,0.770894],"study_design_scores_gemma":[0.00006162467,0.00039818723,0.019198895,0.00012384276,0.00034187187,0.0008992854,0.00012683583,0.926507,0.026189875,0.018706758,0.007319989,0.00012586571],"about_ca_topic_score_codex":0.0026239532,"about_ca_topic_score_gemma":0.004593471,"teacher_disagreement_score":0.0026239532,"about_ca_system_score_codex":0.0002581004,"about_ca_system_score_gemma":0.0010733068,"threshold_uncertainty_score":0.009138167},"labels":[],"label_agreement":null},{"id":"W4280493865","doi":"10.1177/0271678x221101644","title":"Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance","year":2022,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Stroke (engine); Ischemic stroke; Neuroimaging; Cognition; Medicine; Neuroscience; Cardiology; Psychology; Magnetic resonance imaging; Ischemia; Radiology; Physics","score_opus":0.012207150588037046,"score_gpt":0.2742123465121005,"score_spread":0.26200519592406346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280493865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999335,0.00020480706,0.0000764537,0.00001638104,0.000003856953,0.000008335397,0.000117925614,0.000003554249,0.00023373825],"genre_scores_gemma":[0.9995845,0.00006375584,0.000055659973,0.000008737386,0.000010031334,0.000005434923,0.00017027486,0.0000012873052,0.00010027666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996464,0.00007076787,0.000047551825,0.000078998026,0.00008053991,0.000075674456],"domain_scores_gemma":[0.9979639,0.00024115568,0.0011747649,0.00014038317,0.00019497781,0.00028477234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091306685,0.0004972206,0.00039874908,0.00085775804,0.00021861505,0.0006040291,0.00027690324,0.0003539604,0.00067748246],"category_scores_gemma":[0.003121882,0.00017912478,0.00034768574,0.0007019573,0.00042102687,0.0006869046,0.0004696301,0.00042581154,0.00024005002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010892329,0.00008715354,0.99211794,0.000029859968,0.00019818195,0.00017820708,0.00016204444,0.00013380242,0.0011582254,0.000021837208,0.000081699865,0.004741802],"study_design_scores_gemma":[0.000005783295,0.00020828124,0.9993998,0.0000017050368,0.000018944509,0.000116614545,0.000026618864,0.00007054794,0.00010192237,0.000018329507,0.000028720737,0.0000028174725],"about_ca_topic_score_codex":0.0030877301,"about_ca_topic_score_gemma":0.00480936,"teacher_disagreement_score":0.0030877301,"about_ca_system_score_codex":0.0003185919,"about_ca_system_score_gemma":0.00029564943,"threshold_uncertainty_score":0.006139517},"labels":[],"label_agreement":null},{"id":"W4280537356","doi":"10.1101/2022.05.11.491489","title":"The length of the thalamo-cortical white matter fibers brings insight into sex differences in sleep spindle frequency","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Université de Montréal; Université de Sherbrooke; McGill University; École de Technologie Supérieure; Montreal Neurological Institute and Hospital; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Hôpital du Sacré-Cœur de Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Thalamus; Neuroscience; White matter; Sleep spindle; Gyrus; Psychology; Cortex (anatomy); Tractography; Superior frontal gyrus; Anatomy; Biology; Electroencephalography; Medicine; Functional magnetic resonance imaging; Slow-wave sleep; Magnetic resonance imaging","score_opus":0.024161190902236205,"score_gpt":0.26232258600818487,"score_spread":0.23816139510594866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280537356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969812,0.0001386684,0.0022786763,0.000025074869,0.0000039404335,0.000006958214,0.00022800281,0.000009693451,0.00032778314],"genre_scores_gemma":[0.998862,0.000053332813,0.0007807431,0.0000074786003,0.0000026664502,0.0000058883998,0.00009662751,0.0000052233445,0.00018610065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995935,0.00000905131,0.0000049576943,0.000015934538,0.000005691119,0.000004912517],"domain_scores_gemma":[0.99958104,0.00015530847,0.00015599203,0.00003926476,0.000034384164,0.000033965138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021760853,0.00019251787,0.00010005637,0.0002642507,0.00012719176,0.00022560234,0.00009208341,0.00018356933,0.0025676982],"category_scores_gemma":[0.00097416487,0.0001085407,0.00018083333,0.00011015647,0.00015722922,0.00014933219,0.00012944036,0.00012541427,0.00015907412],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008485308,0.000045711866,0.72006774,0.00019191878,0.00023874932,0.00034466095,0.0007181847,0.0016691567,0.2396355,0.0007389165,0.00020619946,0.03529466],"study_design_scores_gemma":[0.000010380638,0.00016536111,0.989131,0.000014042778,0.000044512664,0.00033204452,0.00017587481,0.0040936484,0.0052237366,0.0005789421,0.00022291511,0.00000763395],"about_ca_topic_score_codex":0.0010437325,"about_ca_topic_score_gemma":0.0022818833,"teacher_disagreement_score":0.0025676982,"about_ca_system_score_codex":0.0000719645,"about_ca_system_score_gemma":0.00009052953,"threshold_uncertainty_score":0.008589864},"labels":[],"label_agreement":null},{"id":"W4280549307","doi":"10.1101/2022.04.19.22274057","title":"Exploring biomarkers of processing speed and executive function: the role of the anterior thalamic radiations","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Vancouver Coastal Health; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Stroke (engine); Executive dysfunction; Diffusion MRI; Medicine; Trail Making Test; White matter; Executive functions; Cognition; Physical medicine and rehabilitation; Lesion; Psychology; Neuroscience; Magnetic resonance imaging; Cognitive impairment; Pathology; Neuropsychology; Radiology","score_opus":0.10194698660944355,"score_gpt":0.32275737196566856,"score_spread":0.220810385356225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280549307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99719304,0.0011176991,0.0007124421,0.00011895247,0.0000053500867,0.000008099659,0.0002282029,0.000010341094,0.00060595444],"genre_scores_gemma":[0.9990121,0.0002508045,0.00043348895,0.00001747017,0.000008642796,0.000005178159,0.000089116016,0.0000013365616,0.00018183896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986947,0.000046618523,0.000014298549,0.000033108437,0.000021556525,0.000014866932],"domain_scores_gemma":[0.9990502,0.00022757916,0.00046983256,0.00006557644,0.000105782376,0.00008107793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006640343,0.00053088943,0.00035044694,0.00064040365,0.000152041,0.0011402842,0.0002887845,0.0003298158,0.0011999552],"category_scores_gemma":[0.0022055558,0.000110500696,0.00031226283,0.0005498205,0.0003005768,0.00050080585,0.0002804074,0.00026652488,0.00013503061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026730073,0.000048478338,0.9736723,0.00010157315,0.0004285657,0.00016888764,0.00017100247,0.00088724645,0.004485166,0.000188083,0.00014384712,0.01943761],"study_design_scores_gemma":[0.000007679565,0.00017393588,0.9962947,0.000028822673,0.00009690403,0.0002652947,0.00011483848,0.0017071422,0.0006567146,0.00044128014,0.00020552886,0.0000070444235],"about_ca_topic_score_codex":0.0075512924,"about_ca_topic_score_gemma":0.009358923,"teacher_disagreement_score":0.0075512924,"about_ca_system_score_codex":0.00027876036,"about_ca_system_score_gemma":0.00042063696,"threshold_uncertainty_score":0.015014648},"labels":[],"label_agreement":null},{"id":"W4280562686","doi":"10.1212/wnl.0000000000200517","title":"Observational Study of Neuroimaging Biomarkers of Severe Upper Limb Impairment After Stroke","year":2022,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Nursing Research","keywords":"Motor impairment; Fractional anisotropy; Corpus callosum; Neuroimaging; Corticospinal tract; Physical medicine and rehabilitation; Diffusion MRI; Medicine; White matter; Psychology; Magnetic resonance imaging; Audiology; Neuroscience; Radiology","score_opus":0.0760459045021783,"score_gpt":0.3456945657486392,"score_spread":0.2696486612464609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280562686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987104,0.00007366225,0.00026098808,0.000018419814,0.0000040402733,0.000019396457,0.0007561532,0.0000041200196,0.00015283859],"genre_scores_gemma":[0.9988048,0.000024378496,0.00019497692,0.000028993752,0.000005600604,0.000024288409,0.0008428986,0.0000018705863,0.000072099785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991386,0.00032107238,0.00010473598,0.00025002446,0.00010891306,0.00007671809],"domain_scores_gemma":[0.9978225,0.00030076472,0.0009823025,0.0003831866,0.00021649455,0.0002947804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012898387,0.00022852891,0.0003404988,0.0003800653,0.00051122863,0.00039764048,0.00035970096,0.00046928664,0.00069248496],"category_scores_gemma":[0.0027724877,0.0002191326,0.00046995765,0.00066356675,0.0003286234,0.00030986042,0.0005021995,0.00042915158,0.00016467259],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002588168,0.000044169738,0.99823725,0.000009438918,0.00016801746,0.000035986224,0.00007271595,0.00005122387,0.00033132202,0.000019126326,0.00011880037,0.0006532021],"study_design_scores_gemma":[0.000016696269,0.00018260314,0.9991116,0.0000030560766,0.000048072117,0.000106924264,0.00007666855,0.0001521941,0.000108982116,0.000033841767,0.00015491077,0.000004287863],"about_ca_topic_score_codex":0.010595224,"about_ca_topic_score_gemma":0.009976489,"teacher_disagreement_score":0.010595224,"about_ca_system_score_codex":0.00025820575,"about_ca_system_score_gemma":0.00044309066,"threshold_uncertainty_score":0.021067142},"labels":[],"label_agreement":null},{"id":"W4280563409","doi":"10.1093/cercor/bhac180","title":"White matter microstructural variability linked to differential attentional skills and impulsive behavior in a pediatric population","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Cégep de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"National Institute of Environmental Health Sciences","keywords":"White matter; Impulsivity; Population; Psychology; Neuroscience; Functional magnetic resonance imaging; Neuroimaging; Magnetic resonance imaging; Cognitive psychology; Developmental psychology; Medicine; Radiology","score_opus":0.014650175285967577,"score_gpt":0.30153995045083176,"score_spread":0.2868897751648642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280563409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99944144,0.00007254508,0.00021114975,0.000010403337,9.4423984e-7,0.0000024577846,0.00015063662,0.000007125148,0.0001032202],"genre_scores_gemma":[0.99923563,0.00009296558,0.00035838605,0.000005384359,0.0000029927317,0.000005185945,0.0002235893,0.0000051491465,0.000070701826],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999777,0.000030833802,0.000022583246,0.00009586696,0.000039604227,0.00003419409],"domain_scores_gemma":[0.99935,0.00013569812,0.0003534434,0.000060006263,0.000044820114,0.00005597286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030504604,0.0004135583,0.00023575449,0.0017416227,0.00027735185,0.00046235137,0.00027784175,0.00027962998,0.0013681053],"category_scores_gemma":[0.0014549617,0.00022406895,0.00021868657,0.0010584696,0.00043541964,0.0002790438,0.00048593292,0.0002870434,0.000122045],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007337359,0.000020944482,0.9899747,0.00001835407,0.000061351544,0.00052435783,0.0002790569,0.00016754268,0.0040009078,0.00008604583,0.00008194874,0.004711327],"study_design_scores_gemma":[0.0000010411251,0.00001897258,0.9983753,0.000003210061,0.000016821186,0.0009132465,0.00014098344,0.00014626987,0.00028049218,0.00004630794,0.000055614382,0.000001647927],"about_ca_topic_score_codex":0.005277332,"about_ca_topic_score_gemma":0.0068333233,"teacher_disagreement_score":0.005277332,"about_ca_system_score_codex":0.0002662775,"about_ca_system_score_gemma":0.00024424118,"threshold_uncertainty_score":0.010493219},"labels":[],"label_agreement":null},{"id":"W4280598875","doi":"10.1002/ca.23914","title":"Preoperative and postoperative <scp>high angular resolution diffusion imaging</scp> tractography of cerebellar pathways in posterior fossa tumors","year":2022,"lang":"en","type":"article","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Tractography; Medicine; Fractional anisotropy; Effective diffusion coefficient; Magnetic resonance imaging; Diffusion MRI; Cerebellum; Diffusion imaging; Radiology; Posterior fossa; Nuclear medicine; Internal medicine","score_opus":0.04282424492428531,"score_gpt":0.3541130383842525,"score_spread":0.3112887934599672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280598875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99968994,0.00006798399,0.00013746953,0.0000027912215,4.8289627e-7,0.0000015975346,0.0000251043,0.000002056026,0.00007252479],"genre_scores_gemma":[0.99964285,0.00005936411,0.00013622185,0.0000017975266,0.0000013239084,0.0000020887599,0.000082782055,0.0000014676597,0.00007205569],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999905,0.000017134895,0.000012342037,0.000024757454,0.00002086334,0.00001983265],"domain_scores_gemma":[0.9995869,0.000100283694,0.00016054841,0.000041346873,0.00004763291,0.00006329665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002284851,0.00016415055,0.00012423283,0.0004171889,0.000112551235,0.00024127925,0.00008179739,0.00014761098,0.00071535923],"category_scores_gemma":[0.00083541457,0.000099408724,0.000098946635,0.00020558965,0.00022919924,0.00032038472,0.00014445078,0.00012409831,0.00012482608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012868895,0.00006409026,0.9312184,0.00005355508,0.000048985345,0.0020428437,0.00026325992,0.00023286394,0.04515019,0.000024597435,0.00006141104,0.019553015],"study_design_scores_gemma":[0.000007555029,0.00026506057,0.9937622,0.0000032510666,0.000018669367,0.0023545218,0.000094876814,0.00020695193,0.0031768738,0.0000144451,0.00009184268,0.000003842225],"about_ca_topic_score_codex":0.0019475215,"about_ca_topic_score_gemma":0.0036388468,"teacher_disagreement_score":0.0019475215,"about_ca_system_score_codex":0.00013888383,"about_ca_system_score_gemma":0.00017370572,"threshold_uncertainty_score":0.0038723946},"labels":[],"label_agreement":null},{"id":"W4280629767","doi":"10.1097/md.0000000000029214","title":"Correlations between COMT polymorphism and brain structure and cognition in elderly subjects","year":2022,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Catechol-O-methyl transferase; Cognition; Medicine; Montreal Cognitive Assessment; Cognitive decline; Superior longitudinal fasciculus; Caudate nucleus; Allele; Diffusion MRI; Audiology; Clinical psychology; Fractional anisotropy; Internal medicine; Psychiatry; Genetics; Cognitive impairment; Dementia; Magnetic resonance imaging; Biology; Gene","score_opus":0.044510029291516824,"score_gpt":0.33149150137047917,"score_spread":0.28698147207896235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280629767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995968,0.00014191018,0.000032631717,0.000012342422,0.0000027738436,0.000001670131,0.000083642335,0.0000014921739,0.00012682214],"genre_scores_gemma":[0.9996055,0.000043709933,0.000050733674,0.0000072423313,0.000004839525,0.000002281234,0.000094378884,8.563762e-7,0.0001904745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999933,0.000010460259,0.000010643005,0.000022748143,0.000012978905,0.000010225688],"domain_scores_gemma":[0.99970263,0.00005333933,0.00013091257,0.000024282206,0.000035256555,0.00005348358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018513534,0.0002383596,0.00022323709,0.0003734003,0.00019710476,0.00023417691,0.00011340478,0.00028395889,0.0012690345],"category_scores_gemma":[0.00073147484,0.00012791704,0.00016818575,0.00031847102,0.00012663435,0.00015042447,0.00013690365,0.00018853751,0.00014750236],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046238408,0.000043776163,0.99507195,0.000012514768,0.000102886304,0.00023014065,0.00007682355,0.00004875626,0.0022392555,0.000020678632,0.000053025564,0.0016376915],"study_design_scores_gemma":[0.000004557145,0.00010744679,0.99933714,0.000001579406,0.000023668881,0.00021568249,0.00003676113,0.00009313636,0.00011378704,0.000023650851,0.000041353454,0.0000012500698],"about_ca_topic_score_codex":0.0019901916,"about_ca_topic_score_gemma":0.002515417,"teacher_disagreement_score":0.0019901916,"about_ca_system_score_codex":0.00010037957,"about_ca_system_score_gemma":0.00008869374,"threshold_uncertainty_score":0.004245341},"labels":[],"label_agreement":null},{"id":"W4281289426","doi":"10.3389/fradi.2022.794981","title":"Diffusion Kurtosis Imaging of Neonatal Spinal Cord in Clinical Routine","year":2022,"lang":"en","type":"article","venue":"Frontiers in Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Università degli Studi di Genova","keywords":"Diffusion MRI; Kurtosis; Medicine; White matter; Magnetic resonance imaging; Spinal cord; Neuroimaging; Computer science; Radiology","score_opus":0.04729330494408518,"score_gpt":0.38113999078831995,"score_spread":0.33384668584423477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281289426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44011447,0.033149563,0.4990966,0.0024863358,0.0006974341,0.00065451866,0.0044083814,0.003937761,0.015454988],"genre_scores_gemma":[0.658133,0.022180349,0.3118874,0.0007141264,0.0004633726,0.00065870455,0.0023562813,0.0011277412,0.002479057],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988445,0.00041123407,0.00019686868,0.00022128545,0.0002546902,0.000071476425],"domain_scores_gemma":[0.9976561,0.0008614964,0.00037906872,0.00026580697,0.00067896326,0.00015852168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030447908,0.00090508256,0.0008268417,0.0029600777,0.00047863228,0.0018702479,0.00087483984,0.00097471965,0.0029791342],"category_scores_gemma":[0.010119114,0.00045503041,0.00043996956,0.0015106982,0.00079533376,0.0013337827,0.001419322,0.0010256389,0.0011845744],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014879623,0.00021024495,0.15408361,0.0047986913,0.0004758238,0.012293748,0.002986101,0.01057226,0.20914434,0.009267986,0.015604925,0.5790743],"study_design_scores_gemma":[0.0001814779,0.001712471,0.41147038,0.0045112893,0.00108946,0.0742905,0.0046652225,0.10341454,0.2522529,0.039895754,0.10584112,0.0006749319],"about_ca_topic_score_codex":0.0029808118,"about_ca_topic_score_gemma":0.0036462331,"teacher_disagreement_score":0.0030447908,"about_ca_system_score_codex":0.00045654192,"about_ca_system_score_gemma":0.0014264536,"threshold_uncertainty_score":0.016102552},"labels":[],"label_agreement":null},{"id":"W4281297704","doi":"10.1101/2022.05.04.22274510","title":"Altered Lateralization of the Cingulum in Deployment-Related Traumatic Brain Injury: An ENIGMA Military-Relevant Brain Injury Study","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Medical Research and Materiel Command; Clinical Science Research and Development; Ministerie van Defensie; Rehabilitation Research and Development Service; National Alliance for Research on Schizophrenia and Depression; National Institute of Mental Health; Health Services Research and Development; U.S. Department of Veterans Affairs; U.S. Department of Defense","keywords":"Traumatic brain injury; Fractional anisotropy; Cingulum (brain); Neuroimaging; Psychology; Concussion; Brain Structure and Function; White matter; Diffusion MRI; Lateralization of brain function; Brain size; Cognition; Magnetic resonance imaging; Medicine; Poison control; Neuroscience; Psychiatry; Injury prevention; Radiology","score_opus":0.06554209670476593,"score_gpt":0.38058240944582533,"score_spread":0.31504031274105937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281297704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94531864,0.048196588,0.0018071906,0.0003354553,0.00021932786,0.000093317605,0.002657267,0.000036815916,0.00133547],"genre_scores_gemma":[0.9966785,0.0015993229,0.00046534959,0.00009899676,0.000060626528,0.000041892206,0.0008736679,0.000010879278,0.00017089535],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99873537,0.000449111,0.00019908872,0.00040676235,0.00012515888,0.00008462594],"domain_scores_gemma":[0.99823606,0.00056907116,0.00054908055,0.00035951764,0.00021250354,0.000073717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034913237,0.0007691009,0.0009946745,0.0010262302,0.00061942235,0.0011702451,0.00067967444,0.0007112469,0.002254731],"category_scores_gemma":[0.0049505434,0.0003967119,0.0043994654,0.0016998671,0.00030284113,0.00040127212,0.0008741187,0.0005401323,0.00018134392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010763499,0.00013550273,0.8123287,0.003641413,0.14005712,0.00074812054,0.00044002166,0.00071338046,0.0039563086,0.00053355796,0.002196741,0.024485633],"study_design_scores_gemma":[0.00075327745,0.0005589976,0.90258193,0.00043359242,0.08953593,0.0008399803,0.0003268476,0.00070474035,0.0006222895,0.0006429116,0.0029582272,0.000041216776],"about_ca_topic_score_codex":0.0036118221,"about_ca_topic_score_gemma":0.004776095,"teacher_disagreement_score":0.0036118221,"about_ca_system_score_codex":0.0003163247,"about_ca_system_score_gemma":0.00031697677,"threshold_uncertainty_score":0.018464148},"labels":[],"label_agreement":null},{"id":"W4281570665","doi":"10.1016/j.neuroimage.2022.119327","title":"Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"H2020 Marie Skłodowska-Curie Actions; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Drug Abuse; National Institute of Mental Health; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institute on Aging; National Institute of Allergy and Infectious Diseases; Horizon 2020; Centre d'Imagerie BioMédicale; Eunice Kennedy Shriver National Institute of Child Health and Human Development; European Commission; Wellcome Trust; National Institute of Neurological Disorders and Stroke; Massachusetts General Hospital; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Tractography; Computer science; Diffusion MRI; Robustness (evolution); Connectome; Artificial intelligence; Voxel; Pattern recognition (psychology); Data mining; Functional connectivity; Neuroscience; Magnetic resonance imaging; Psychology","score_opus":0.13432231346441117,"score_gpt":0.3886919784398079,"score_spread":0.2543696649753967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281570665","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011440815,0.0025715923,0.9816953,0.0026877152,0.00007108653,0.000027233378,0.0001480517,0.00038028276,0.0009778935],"genre_scores_gemma":[0.15245439,0.0038199187,0.84001243,0.00051669276,0.0002694497,0.00012353752,0.000471708,0.00075424457,0.0015775914],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985409,0.0006230586,0.000077664736,0.0002764579,0.00042540353,0.000056613786],"domain_scores_gemma":[0.99228036,0.0047440073,0.0005573015,0.0012123793,0.0009502738,0.0002558103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067917528,0.0012483966,0.0010789206,0.0016378921,0.00066163973,0.0023720958,0.0016202157,0.0016793205,0.0020314232],"category_scores_gemma":[0.029026743,0.0008097277,0.00053751946,0.0009092002,0.001985509,0.003558361,0.0021292688,0.002682081,0.0009625151],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037618817,0.0001707133,0.0058393385,0.0011330782,0.00027242026,0.00038118855,0.0007482686,0.32467845,0.03425404,0.23014851,0.013971026,0.38802665],"study_design_scores_gemma":[0.000039872975,0.000071540446,0.0016126949,0.00017024667,0.000032600874,0.00022264209,0.000098447425,0.7256457,0.007709867,0.25366712,0.010673209,0.000056041998],"about_ca_topic_score_codex":0.004035919,"about_ca_topic_score_gemma":0.0056947586,"teacher_disagreement_score":0.0067917528,"about_ca_system_score_codex":0.0011154896,"about_ca_system_score_gemma":0.0024790731,"threshold_uncertainty_score":0.035918653},"labels":[],"label_agreement":null},{"id":"W4281657612","doi":"10.1007/s00429-022-02518-6","title":"The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow","year":2022,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt Institute for Clinical and Translational Research","keywords":"Neuroimaging; Set (abstract data type); Tractography; Neuroanatomy; Computer science; Psychology; Diffusion MRI; Data science; Cognitive psychology; Neuroscience; Medicine; Radiology","score_opus":0.07176942609469703,"score_gpt":0.34135799450916915,"score_spread":0.2695885684144721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281657612","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017330325,0.00006214407,0.9973999,0.00005554331,0.000008787623,0.000041205174,0.000014531807,0.00018792711,0.0004968864],"genre_scores_gemma":[0.07655731,0.0004850303,0.92005867,0.000074737334,0.000054318512,0.00040499563,0.00006439333,0.00048395075,0.001816611],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970294,0.0012480499,0.00021354751,0.0004794031,0.00092450733,0.00010504267],"domain_scores_gemma":[0.98548084,0.009993672,0.00090637075,0.0021029853,0.0012556163,0.00026051138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008108339,0.0014507496,0.0013519047,0.0011174323,0.000984694,0.0029611236,0.0025597163,0.0016907139,0.0023633004],"category_scores_gemma":[0.037012313,0.0013159259,0.0013430875,0.00070050085,0.0037198756,0.0033410438,0.0031029577,0.002814842,0.0010466654],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003911581,0.00018886923,0.0028810506,0.00087530405,0.00026022329,0.0007547644,0.001476994,0.2616177,0.07804006,0.19546889,0.0036429234,0.45440206],"study_design_scores_gemma":[0.00006004093,0.00048781594,0.002452412,0.0002288424,0.00020176443,0.0010955654,0.00016515753,0.6976372,0.07234212,0.21189855,0.013307525,0.00012290731],"about_ca_topic_score_codex":0.0030576973,"about_ca_topic_score_gemma":0.0035890415,"teacher_disagreement_score":0.008108339,"about_ca_system_score_codex":0.0008984237,"about_ca_system_score_gemma":0.0023973763,"threshold_uncertainty_score":0.04288149},"labels":[],"label_agreement":null},{"id":"W4281754482","doi":"10.1093/braincomms/fcac142","title":"In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of British Columbia Hospital; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Hyperintensity; Fractional anisotropy; Myelin; Pathology; Magnetic resonance imaging; Medicine; Internal medicine; Central nervous system; Radiology","score_opus":0.026915909698966844,"score_gpt":0.3236446105651628,"score_spread":0.29672870086619596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281754482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999488,0.00012210656,0.0002648961,0.0000041111375,6.0341785e-7,0.000002229609,0.000035778306,0.00000323567,0.00007902016],"genre_scores_gemma":[0.9994254,0.00004847611,0.00031622394,0.0000036039282,0.0000014144622,0.0000035742048,0.000045481887,0.0000018448696,0.00015393633],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999306,0.000011077909,0.000007533197,0.000025560954,0.000012020244,0.000013167467],"domain_scores_gemma":[0.999796,0.00002600786,0.00009100111,0.000018764908,0.000032226602,0.00003603853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027815584,0.00019478732,0.0001535526,0.0005654969,0.0001694647,0.00030020106,0.00007373822,0.00027407342,0.00096529647],"category_scores_gemma":[0.0005143245,0.0001322524,0.0001143928,0.0002600141,0.00020849807,0.00031870065,0.0002439768,0.00015746089,0.00013505071],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016599066,0.00018141198,0.58265907,0.00014615894,0.00039817547,0.00044215738,0.0010544485,0.0006935141,0.39110222,0.00019706521,0.00016734334,0.021298543],"study_design_scores_gemma":[0.000008174405,0.0003140569,0.98273647,0.0000071951645,0.0000625526,0.0006637846,0.00028314642,0.0010181991,0.014565264,0.00015548618,0.00017961735,0.0000060870893],"about_ca_topic_score_codex":0.0018572243,"about_ca_topic_score_gemma":0.0025585296,"teacher_disagreement_score":0.0018572243,"about_ca_system_score_codex":0.000113232214,"about_ca_system_score_gemma":0.00009824347,"threshold_uncertainty_score":0.0036928058},"labels":[],"label_agreement":null},{"id":"W4281954245","doi":"10.1016/j.neuroimage.2022.119360","title":"Empirical transmit field bias correction of T1w/T2w myelin maps","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institute on Aging; National Institutes of Health; Japan Agency for Medical Research and Development","keywords":"Spurious relationship; Myelin; Field (mathematics); Computer science; Statistics; Psychology; Mathematics; Neuroscience","score_opus":0.12724169319513529,"score_gpt":0.3814851359127153,"score_spread":0.25424344271758004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281954245","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09552191,0.0013487478,0.89767665,0.00041684628,0.0002238199,0.00014128872,0.00039718513,0.0024134037,0.0018600696],"genre_scores_gemma":[0.30469027,0.0012464261,0.68781674,0.00035272457,0.000114184004,0.00038198478,0.00079518714,0.0021825386,0.0024200028],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984421,0.00059290684,0.00012440892,0.00034481136,0.0004180163,0.00007780413],"domain_scores_gemma":[0.9923253,0.0027858114,0.0016546759,0.001327122,0.0017747349,0.00013232535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006125977,0.0011301414,0.00054998166,0.0013186949,0.000662068,0.0014157285,0.0015095911,0.0009833266,0.002412735],"category_scores_gemma":[0.029013542,0.0005067033,0.0005643516,0.001341257,0.00081289,0.001642334,0.0011708462,0.0015286971,0.0006794954],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013212876,0.0002478233,0.05084618,0.002207132,0.0011927206,0.0006952643,0.001988191,0.041885074,0.21890305,0.02349169,0.011600223,0.6456214],"study_design_scores_gemma":[0.00022210626,0.0007738936,0.14472933,0.0006656141,0.0011226258,0.0056898743,0.00079018576,0.3704442,0.37594116,0.05244583,0.046628784,0.0005463641],"about_ca_topic_score_codex":0.002377005,"about_ca_topic_score_gemma":0.005326164,"teacher_disagreement_score":0.006125977,"about_ca_system_score_codex":0.0005384966,"about_ca_system_score_gemma":0.0012059566,"threshold_uncertainty_score":0.032397628},"labels":[],"label_agreement":null},{"id":"W4281974427","doi":"10.1177/00048674211031477","title":"Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression","year":2022,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Science Fund for Distinguished Young Scholars; National Natural Science Foundation of China-Liaoning Joint Fund; Liaoning Revitalization Talents Program; China Medical University; Department of Science and Technology of Liaoning Province; Foundation of Liaoning Province Education Administration; Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Corpus callosum; White matter; Major depressive disorder; Diffusion MRI; Endophenotype; Bipolar disorder; Superior longitudinal fasciculus; Hyperintensity; Medicine; Psychology; Internal medicine; Psychiatry; Pathology; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.02563210456338421,"score_gpt":0.2948717239300923,"score_spread":0.2692396193667081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281974427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98257864,0.00027763742,0.014829815,0.0002000896,0.000021729435,0.000107189044,0.0012001358,0.00015015932,0.0006344575],"genre_scores_gemma":[0.99148995,0.00006097699,0.006830448,0.00003308575,0.000015674037,0.000060332663,0.0013751478,0.000016137921,0.00011815176],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996482,0.0017815836,0.00026358437,0.00078425277,0.00048323922,0.00020529245],"domain_scores_gemma":[0.99182725,0.0040380494,0.0014417683,0.0012995767,0.0010278948,0.00036539877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008146853,0.0015355613,0.0010374527,0.0026128714,0.00096181664,0.0015080465,0.00068853656,0.00093626365,0.002005678],"category_scores_gemma":[0.014309316,0.00047066735,0.0020595815,0.0013450935,0.00057603826,0.0007350067,0.0016278962,0.0012308788,0.00045139797],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090693845,0.00013755239,0.97236955,0.000042200496,0.001591826,0.00012924155,0.00012464673,0.0039765835,0.0036900996,0.00014945347,0.00048765252,0.016394245],"study_design_scores_gemma":[0.0000924416,0.00079208554,0.9257811,0.00006205407,0.0011744167,0.00054315565,0.00014794218,0.06687137,0.0025086177,0.0014765859,0.00048119266,0.000068973204],"about_ca_topic_score_codex":0.002568723,"about_ca_topic_score_gemma":0.0045251227,"teacher_disagreement_score":0.008146853,"about_ca_system_score_codex":0.00036703158,"about_ca_system_score_gemma":0.00079021684,"threshold_uncertainty_score":0.043085217},"labels":[],"label_agreement":null},{"id":"W4282822545","doi":"10.1101/2022.06.11.495736","title":"CAT – A Computational Anatomy Toolbox for the Analysis of Structural MRI Data","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":626,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Alexander von Humboldt-Stiftung; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Bristol-Myers Squibb; Royal Society; Northern California Institute for Research and Education; Royal Society Te Apārangi; Pfizer; BioClinica; Biogen; F. Hoffmann-La Roche; University of Auckland; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Computer science; Toolbox; Workflow; Suite; Preprocessor; Visualization; USable; Graphical user interface; Data science; Human–computer interaction; Data mining; Artificial intelligence; World Wide Web","score_opus":0.0678759867942592,"score_gpt":0.3525822282139926,"score_spread":0.2847062414197334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282822545","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017867973,0.0006165641,0.7934721,0.00043674704,0.00021297483,0.00024706576,0.019763846,0.17978492,0.0036790296],"genre_scores_gemma":[0.018475696,0.0010121875,0.87897587,0.0006992727,0.00013948226,0.0020753255,0.036868848,0.056214143,0.0055392096],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867886,0.00030231636,0.00018914955,0.00022430961,0.0005217021,0.00008363863],"domain_scores_gemma":[0.9952615,0.0021903256,0.00042709973,0.0009108311,0.0009330718,0.00027728768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033439223,0.0019848072,0.0010156516,0.0034491182,0.00067159807,0.0032700624,0.003327336,0.0013274091,0.05069039],"category_scores_gemma":[0.012610347,0.0014258532,0.0016730814,0.0021349785,0.0008241947,0.0024669042,0.0036590782,0.0027043587,0.030138783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041442743,0.00011057944,0.0019601705,0.0022218272,0.0004712898,0.0008797467,0.0005537843,0.020497665,0.024269737,0.03896328,0.6819858,0.22767165],"study_design_scores_gemma":[0.00034820093,0.00013367174,0.004147368,0.00083968265,0.00016996732,0.0031406768,0.00017240633,0.21246496,0.034621276,0.117478035,0.6261492,0.00033463974],"about_ca_topic_score_codex":0.0020784747,"about_ca_topic_score_gemma":0.004002078,"teacher_disagreement_score":0.05069039,"about_ca_system_score_codex":0.00054237543,"about_ca_system_score_gemma":0.0027881796,"threshold_uncertainty_score":0.16957623},"labels":[],"label_agreement":null},{"id":"W4282833640","doi":"10.1161/strokeaha.122.039723","title":"Detecting Silent Acute Microinfarcts in Cerebral Small Vessel Disease Using Submillimeter Diffusion-Weighted Magnetic Resonance Imaging: Preliminary Results","year":2022,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Ottawa; University of Toronto; University Health Network","funders":"Heart and Stroke Foundation of Canada","keywords":"Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Physics; Nuclear medicine; Radiology","score_opus":0.03517151638038429,"score_gpt":0.29654916584640717,"score_spread":0.2613776494660229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282833640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989673,0.0033375937,0.004757536,0.00017036627,0.000044427783,0.0003347067,0.00014559197,0.00006540958,0.0014713127],"genre_scores_gemma":[0.98833907,0.0018900421,0.008130722,0.00022782915,0.00016225514,0.00011549475,0.00044485557,0.000036446334,0.00065333775],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991035,0.00044361228,0.00006349112,0.00016561584,0.00011474642,0.00010904818],"domain_scores_gemma":[0.9972881,0.001899389,0.00008963893,0.00017644365,0.0003012623,0.0002451914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031885703,0.0017214647,0.00089906383,0.00050993846,0.0003391679,0.0008372555,0.00080994033,0.0012142793,0.0010998301],"category_scores_gemma":[0.00456906,0.0004258495,0.00052386406,0.00028780274,0.0010416673,0.0011173051,0.00032830934,0.0009961103,0.0004484515],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.08038647,0.014026275,0.30068055,0.0013620588,0.00090413034,0.0047114654,0.00225304,0.0025376547,0.38692978,0.00028285026,0.0009234601,0.2050023],"study_design_scores_gemma":[0.0045796246,0.078941606,0.63185054,0.00020324557,0.0030357714,0.008652645,0.0018787285,0.018885452,0.24571215,0.0012164129,0.0047615767,0.00028240183],"about_ca_topic_score_codex":0.0034838845,"about_ca_topic_score_gemma":0.0034038515,"teacher_disagreement_score":0.0034838845,"about_ca_system_score_codex":0.0002449735,"about_ca_system_score_gemma":0.00046107484,"threshold_uncertainty_score":0.016862929},"labels":[],"label_agreement":null},{"id":"W4283073900","doi":"10.1007/s12021-022-09590-7","title":"Fast Streamline Search: An Exact Technique for Diffusion MRI Tractography","year":2022,"lang":"en","type":"article","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Streamlines, streaklines, and pathlines; Tractography; Diffusion MRI; Cluster analysis; Computer science; Representation (politics); Artificial intelligence; Upper and lower bounds; Hierarchical clustering; Pattern recognition (psychology); Algorithm; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.07827359738203357,"score_gpt":0.3607827391509589,"score_spread":0.2825091417689253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283073900","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007493041,0.000062523286,0.99834037,0.000033449774,0.000011425125,0.000025705283,0.000039600644,0.0004686258,0.0002689679],"genre_scores_gemma":[0.031258214,0.00017779227,0.9666567,0.000040268616,0.000028361219,0.0001628745,0.00021528959,0.00026166666,0.0011989402],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923646,0.00017252481,0.000051610907,0.0001150703,0.00037117884,0.00005317979],"domain_scores_gemma":[0.9982724,0.0007478347,0.00017041224,0.0003517053,0.00038433948,0.00007326173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013635124,0.0010476311,0.0009785178,0.0021546439,0.0007694161,0.0014022345,0.0016811058,0.0014840184,0.0069186245],"category_scores_gemma":[0.006714683,0.00068330724,0.0009298495,0.0022111423,0.00076748437,0.0023610003,0.0016305883,0.0014575718,0.0033234342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031027792,0.000077659264,0.0011059825,0.00044469128,0.00012871502,0.00025718944,0.00036698882,0.3324061,0.025544694,0.1154767,0.011743804,0.5121372],"study_design_scores_gemma":[0.000029788749,0.000040866442,0.0001741877,0.00002240219,0.000010048015,0.00013767705,0.000021070515,0.96633655,0.004933796,0.021952292,0.0063214474,0.000019884317],"about_ca_topic_score_codex":0.0067983232,"about_ca_topic_score_gemma":0.00888461,"teacher_disagreement_score":0.0069186245,"about_ca_system_score_codex":0.0011275886,"about_ca_system_score_gemma":0.002211682,"threshold_uncertainty_score":0.02314514},"labels":[],"label_agreement":null},{"id":"W4283075736","doi":"10.3389/fneur.2022.850642","title":"Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; BC Children's Hospital; University of British Columbia; Stollery Children's Hospital; Hotchkiss Brain Institute; Centre Hospitalier Universitaire Sainte-Justine; Alberta Children's Hospital; University of Alberta; Université de Montréal; Children's Hospital of Eastern Ontario; University of Calgary","funders":"Canadian Institutes of Health Research; Killam Trusts; Alberta Children's Hospital Foundation; Scuola IMT Alti Studi Lucca; Children's Hospital Foundation","keywords":"Diffusion MRI; Adjacency matrix; Harmonization; Connectome; Computer science; Connectomics; Neuroimaging; Context (archaeology); Artificial intelligence; Fractional anisotropy; Data mining; Graph; Medicine; Psychology; Radiology; Theoretical computer science; Neuroscience; Functional connectivity; Magnetic resonance imaging; Biology; Psychiatry","score_opus":0.022990030547424906,"score_gpt":0.3128539605034561,"score_spread":0.28986392995603116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283075736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981762,0.000060255865,0.0009782938,0.00003194247,0.0000030445303,0.000037380407,0.0003270073,0.000012766749,0.00037307135],"genre_scores_gemma":[0.99609214,0.00008979241,0.0029363201,0.000025551764,0.000013117521,0.000056310866,0.0005730905,0.00001923627,0.00019439954],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879223,0.0003255541,0.00008578578,0.00041621755,0.00023245742,0.00014793602],"domain_scores_gemma":[0.997139,0.0005336584,0.0008545508,0.0006021003,0.00058260106,0.00028813488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016787337,0.0006239381,0.0004582893,0.0017224605,0.0008445185,0.000826989,0.0006281799,0.00064345344,0.0013266273],"category_scores_gemma":[0.006117015,0.0003793643,0.0005826248,0.0014452643,0.0010378768,0.0013615089,0.0011753399,0.0008577442,0.0002905725],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053650234,0.00047093356,0.9539399,0.0001598135,0.00027976657,0.0023923826,0.005259474,0.0015862443,0.004919559,0.0009811879,0.001219416,0.028254822],"study_design_scores_gemma":[0.000020938209,0.0007032708,0.9856129,0.000036457834,0.00009212496,0.0038876005,0.0036199621,0.0023001486,0.0013963053,0.0004842033,0.001815559,0.000030575928],"about_ca_topic_score_codex":0.01199572,"about_ca_topic_score_gemma":0.017309224,"teacher_disagreement_score":0.01199572,"about_ca_system_score_codex":0.00084031466,"about_ca_system_score_gemma":0.00090104144,"threshold_uncertainty_score":0.023851812},"labels":[],"label_agreement":null},{"id":"W4283212390","doi":"10.3389/fpain.2022.880831","title":"White Matter Diffusion Properties in Chronic Temporomandibular Disorders: An Exploratory Analysis","year":2022,"lang":"en","type":"article","venue":"Frontiers in Pain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta; Women and Children's Health Research Institute","keywords":"White matter; Diffusion MRI; Medicine; Diffusion; Orofacial pain; White (mutation); Psychology; Physics; Physical therapy; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.08547716123083193,"score_gpt":0.37210132091537773,"score_spread":0.2866241596845458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283212390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992643,0.000054790675,0.00029256003,0.0000110970805,5.16674e-7,0.000014495588,0.0002090651,0.0000051382767,0.00014802656],"genre_scores_gemma":[0.999253,0.000022175427,0.00039913712,0.0000028578702,0.0000018373304,0.000020121697,0.00021981852,0.0000026636499,0.00007849937],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997863,0.000053168264,0.00002246227,0.000051040704,0.000044690732,0.000042434334],"domain_scores_gemma":[0.9993291,0.00026108223,0.00020099382,0.00005704211,0.000076416516,0.00007552904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007542806,0.0005613196,0.00035606555,0.0017255923,0.00038764498,0.0004142936,0.00024294337,0.00026798414,0.0022010198],"category_scores_gemma":[0.0017940822,0.00015803156,0.0008672994,0.0008804854,0.0003384184,0.00029491325,0.00065251294,0.00019611756,0.00023378739],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055138156,0.000053919008,0.9876659,0.000051197756,0.0003138762,0.00040521874,0.00044435868,0.00023526004,0.004968024,0.000080619306,0.00011425425,0.0051160487],"study_design_scores_gemma":[0.000013038189,0.00030593466,0.9970132,0.000008814326,0.000082513514,0.000771898,0.00038600183,0.00077810575,0.00037948237,0.00008328139,0.00017108012,0.000006577531],"about_ca_topic_score_codex":0.0019892314,"about_ca_topic_score_gemma":0.0022687442,"teacher_disagreement_score":0.0022010198,"about_ca_system_score_codex":0.00026128374,"about_ca_system_score_gemma":0.00040775345,"threshold_uncertainty_score":0.0073631406},"labels":[],"label_agreement":null},{"id":"W4283271593","doi":"10.21203/rs.3.rs-1742219/v1","title":"Characterization of Extracellular Free Water Pathologies in Schizophrenia Using Multi-Site Diffusion MRI Harmonization","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Medical Research Council; National Alliance for Research on Schizophrenia and Depression; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Harmonization; Characterization (materials science); Schizophrenia (object-oriented programming); Diffusion; Extracellular; Nuclear magnetic resonance; Chemistry; Medicine; Materials science; Nanotechnology; Psychiatry; Physics; Biochemistry; Thermodynamics","score_opus":0.1785688321069545,"score_gpt":0.4328049450671547,"score_spread":0.2542361129602002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283271593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80227435,0.0017317516,0.19163439,0.0003403923,0.000038283393,0.00012865794,0.000935765,0.0005074295,0.0024090752],"genre_scores_gemma":[0.9395652,0.00077803846,0.05761297,0.000055434917,0.000036760608,0.000066496905,0.00051420694,0.00013230645,0.0012387045],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998807,0.000027960292,0.000010353866,0.000029874767,0.000025151583,0.000025913527],"domain_scores_gemma":[0.9996891,0.00006834139,0.00007491631,0.00005552265,0.000075712196,0.00003637426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065121887,0.00051706715,0.000362965,0.001573244,0.0003824357,0.00080059725,0.00036635756,0.00066568045,0.0013573135],"category_scores_gemma":[0.0010576069,0.00024339781,0.00044343676,0.00068658945,0.00032782488,0.0009075679,0.0007301776,0.00037612932,0.00026360902],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016511305,0.00018388256,0.026639763,0.00048564075,0.00034733122,0.0010113508,0.0005682921,0.0140242865,0.78628474,0.003423559,0.0012785147,0.16410142],"study_design_scores_gemma":[0.00012502025,0.0008466429,0.18019468,0.00010955755,0.0006267255,0.0076145045,0.0012083055,0.28209972,0.50717425,0.015648998,0.004162302,0.00018927194],"about_ca_topic_score_codex":0.0011997307,"about_ca_topic_score_gemma":0.0014838906,"teacher_disagreement_score":0.001573244,"about_ca_system_score_codex":0.00015806049,"about_ca_system_score_gemma":0.0003892512,"threshold_uncertainty_score":0.004540682},"labels":[],"label_agreement":null},{"id":"W4283688598","doi":"10.21203/rs.3.rs-1712962/v1","title":"Free water diffusion MRI differentiates suicide ideators from attempters with treatment-resistant depression","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"University of Ottawa","keywords":"Depression (economics); Diffusion; Psychology; Medicine; Physics; Economics; Thermodynamics; Keynesian economics","score_opus":0.10717113802621164,"score_gpt":0.4225724224553515,"score_spread":0.31540128442913984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283688598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99935097,0.0001663655,0.00012789914,0.0000203684,0.0000030180108,0.000014051145,0.000054779022,0.000007386829,0.00025527398],"genre_scores_gemma":[0.99935526,0.00009834966,0.00028207857,0.000015891339,0.0000033110143,0.000007945581,0.00011518598,0.0000019821227,0.000119918484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998859,0.000032883578,0.000024928555,0.000022445063,0.000021916469,0.000011880274],"domain_scores_gemma":[0.9995982,0.000067122,0.00017722667,0.000030921776,0.000054460517,0.00007209123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045620996,0.00034397372,0.0003230485,0.0010504628,0.00018308827,0.0004972862,0.00019201281,0.00033197037,0.0013634722],"category_scores_gemma":[0.0014214754,0.00019900867,0.00022668604,0.00023259633,0.00019565344,0.00027234256,0.0002968617,0.0002613338,0.00023940983],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006817547,0.000111854686,0.9709046,0.000065495304,0.00016720523,0.000496943,0.00048756978,0.0000747731,0.015156449,0.000072331444,0.0002116476,0.011569185],"study_design_scores_gemma":[0.000027002021,0.00028554967,0.99601704,0.000020482155,0.000036962196,0.001829922,0.00035151708,0.00043174298,0.00078561483,0.000072102135,0.00013605383,0.0000059530803],"about_ca_topic_score_codex":0.0008219198,"about_ca_topic_score_gemma":0.0019264146,"teacher_disagreement_score":0.0013634722,"about_ca_system_score_codex":0.000106985564,"about_ca_system_score_gemma":0.000073015,"threshold_uncertainty_score":0.004561305},"labels":[],"label_agreement":null},{"id":"W4283789043","doi":"10.1093/cercor/bhac236","title":"Optimal blocking of the cerebral cortex for cytoarchitectonic examination: a neuronavigation-based approach","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Human Frontier Science Program","keywords":"Cytoarchitecture; Sulcus; Cortex (anatomy); Central sulcus; Anatomy; Cerebral cortex; Neuroscience; Coronal plane; Somatosensory system; Neuroanatomy; Biology; Motor cortex","score_opus":0.05106301895722977,"score_gpt":0.3133843964435513,"score_spread":0.26232137748632156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283789043","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06034517,0.007197719,0.9269848,0.0005696202,0.00016002383,0.0005759688,0.00019744482,0.00071510224,0.0032541244],"genre_scores_gemma":[0.15788381,0.0055760616,0.83289826,0.00019298427,0.000043080654,0.00045414298,0.00021674599,0.00023937976,0.0024955603],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995821,0.0000733526,0.0000361435,0.000111398535,0.00013587766,0.00006113877],"domain_scores_gemma":[0.9995285,0.00012333113,0.00009372647,0.00011219024,0.00010133678,0.00004096684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011739978,0.0012141018,0.0007945937,0.0015026582,0.0006892144,0.001288272,0.0010758584,0.00088289275,0.001286866],"category_scores_gemma":[0.0011119551,0.0012061324,0.00034093976,0.0004720638,0.0011633409,0.0011056393,0.0010273018,0.0017785566,0.00070727017],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023475692,0.000059526752,0.0008220433,0.00037021044,0.000056676425,0.00023578542,0.000111575,0.0028554332,0.9533656,0.004783029,0.0003502255,0.03675504],"study_design_scores_gemma":[0.00012932176,0.0009040871,0.009972291,0.0003417282,0.00029919713,0.0067105456,0.00026713777,0.04690217,0.8897706,0.010174502,0.03437618,0.00015226917],"about_ca_topic_score_codex":0.0033263115,"about_ca_topic_score_gemma":0.011598034,"teacher_disagreement_score":0.0033263115,"about_ca_system_score_codex":0.00088016875,"about_ca_system_score_gemma":0.0026661213,"threshold_uncertainty_score":0.0066138506},"labels":[],"label_agreement":null},{"id":"W4283823743","doi":"10.1038/s41380-022-01636-1","title":"Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; White matter; Cognition; Autism; Autism spectrum disorder; Attention deficit hyperactivity disorder; Neuroscience; Developmental psychology; Psychiatry; Magnetic resonance imaging; Medicine","score_opus":0.03444389929824264,"score_gpt":0.283240859361831,"score_spread":0.24879696006358837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283823743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96245635,0.0013213463,0.02420434,0.0068612224,0.00007325542,0.000041100644,0.00042213398,0.00011235696,0.004508058],"genre_scores_gemma":[0.9957509,0.0002959061,0.0034927996,0.00016284501,0.000021945261,0.000012362623,0.00008494313,0.00001578793,0.00016246915],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909365,0.0003175058,0.00006868882,0.0002793425,0.00020202386,0.00003883495],"domain_scores_gemma":[0.9985153,0.0005861104,0.0003221848,0.00032614585,0.00015363841,0.00009653375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031632385,0.00042990767,0.0005498278,0.001237753,0.00035469868,0.001139941,0.0011458265,0.00054228265,0.00095010654],"category_scores_gemma":[0.0061629605,0.00014037207,0.00031257112,0.0005613696,0.0031006578,0.0015208799,0.0010354838,0.0013343889,0.00006453803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001121703,0.00033177086,0.49359083,0.00037572163,0.0010790388,0.0028625147,0.012947574,0.010824726,0.05325554,0.2812629,0.0028118966,0.13953577],"study_design_scores_gemma":[0.00003258506,0.00035607273,0.6329184,0.00011326134,0.00017132495,0.0063415235,0.0029590726,0.022475557,0.0029209491,0.3290014,0.002640338,0.00006953144],"about_ca_topic_score_codex":0.004953231,"about_ca_topic_score_gemma":0.00516678,"teacher_disagreement_score":0.004953231,"about_ca_system_score_codex":0.0007343216,"about_ca_system_score_gemma":0.0008490437,"threshold_uncertainty_score":0.016728997},"labels":[],"label_agreement":null},{"id":"W4284671617","doi":"10.1002/hbm.26003","title":"Memory retrieval brain–behavior disconnection in mild traumatic brain injury: A magnetoencephalography and diffusion tensor imaging study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; London Health Sciences Centre; SickKids Foundation; University of Toronto; Western University; Mental Health Research Canada; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Canadian Institute for Military and Veteran Health Research; Institute of Development and Economic Alternatives; Defence Research and Development Canada; Brain and Behavior Research Foundation","keywords":"Magnetoencephalography; Disconnection; Diffusion MRI; Traumatic brain injury; Psychology; Neuroscience; Tractography; Medicine; Magnetic resonance imaging; Electroencephalography; Psychiatry; Radiology","score_opus":0.09037558169320231,"score_gpt":0.3688843118268361,"score_spread":0.2785087301336338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284671617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99925333,0.00018525135,0.00020391431,0.000043066288,0.0000041900394,0.000025375524,0.000049153332,0.0000024161352,0.00023339929],"genre_scores_gemma":[0.9993148,0.00011532025,0.00020301505,0.000023498702,0.00002334015,0.000016870945,0.00014382803,0.0000020623702,0.00015721425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998354,0.000028581086,0.000024092902,0.00004489396,0.00003110114,0.000035899244],"domain_scores_gemma":[0.9994512,0.0000704981,0.00020048174,0.00006461525,0.00007722422,0.00013590134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007492504,0.00051723054,0.0004112853,0.0012212662,0.0005195205,0.00047769584,0.0004381249,0.0006354189,0.0011180327],"category_scores_gemma":[0.0018221177,0.00022584251,0.00028588102,0.0005894551,0.00071627507,0.00061290094,0.0006149767,0.00051344873,0.00029787127],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035599922,0.0028195675,0.9210247,0.0002097983,0.00040125125,0.013048687,0.0027320418,0.00037094267,0.034098748,0.00032822465,0.00032755936,0.021078557],"study_design_scores_gemma":[0.00004371075,0.00085993344,0.99262565,0.000009397069,0.00006603136,0.004659993,0.00038411558,0.00037647277,0.0005972515,0.00015819297,0.00020548268,0.000013668407],"about_ca_topic_score_codex":0.0030197948,"about_ca_topic_score_gemma":0.0029517428,"teacher_disagreement_score":0.0030197948,"about_ca_system_score_codex":0.00032085393,"about_ca_system_score_gemma":0.00044999784,"threshold_uncertainty_score":0.0060044527},"labels":[],"label_agreement":null},{"id":"W4284896909","doi":"10.1016/j.nicl.2022.103106","title":"The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"UCLH Biomedical Research Centre; Horizon 2020; Medical Research Council; University College London Hospitals Biomedical Research Centre; Innovative Medicines Initiative; Hartstichting; Alzheimer’s Research UK; ZonMw; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Nano-Convergence Foundation; Fondation Leducq; HORIZON EUROPE Framework Programme; Wellcome Trust; Alzheimer's Society; Rijksdienst voor Ondernemend Nederland; Velux Stiftung; National Institute for Health and Care Research; Alzheimer Society; Alzheimer Nederland; EU Joint Programme – Neurodegenerative Disease Research; UK Dementia Research Institute; Velux Fonden; University College London","keywords":"Computer science; Artificial intelligence; Neuroimaging; Fluid-attenuated inversion recovery; Pattern recognition (psychology); Pipeline (software); Magnetic resonance imaging; Medicine; Radiology; Psychiatry","score_opus":0.33589439662155296,"score_gpt":0.5270368599658383,"score_spread":0.1911424633442853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284896909","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016873434,0.0009114439,0.04153983,0.0008522558,0.0001892543,0.0018050697,0.9140542,0.019401105,0.0043734377],"genre_scores_gemma":[0.016179686,0.00028856655,0.04905999,0.00036010193,0.000059848546,0.003102266,0.9283238,0.0011358985,0.0014897104],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99857605,0.00026682988,0.00024670293,0.0005094891,0.00028115738,0.00011978385],"domain_scores_gemma":[0.99808,0.0003667545,0.00016732713,0.0005760575,0.00062647613,0.0001835116],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0038478095,0.0014406891,0.0012325529,0.0020814508,0.000711023,0.0018880231,0.0026585928,0.0013759434,0.013420955],"category_scores_gemma":[0.008184488,0.0006036878,0.0013160256,0.0014411446,0.00038187887,0.00079288695,0.0023485783,0.0012250172,0.016009463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003053991,0.00049864565,0.021835823,0.0021965858,0.0005721569,0.0011287639,0.0006255077,0.0046381876,0.013287254,0.0041076546,0.83493674,0.113118745],"study_design_scores_gemma":[0.0023572939,0.0005504785,0.061728083,0.0009582258,0.00044813272,0.0024800608,0.0005450151,0.023556057,0.01749188,0.018830886,0.87067556,0.00037843],"about_ca_topic_score_codex":0.011181448,"about_ca_topic_score_gemma":0.016712232,"teacher_disagreement_score":0.9973414,"about_ca_system_score_codex":0.000993839,"about_ca_system_score_gemma":0.0025102417,"threshold_uncertainty_score":0.044897616},"labels":[],"label_agreement":null},{"id":"W4284992187","doi":"10.1101/2022.07.06.22277331","title":"A dataset of multi-contrast unbiased average MRI templates of a Parkinson’s disease population","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fluid-attenuated inversion recovery; Template; Voxel; Parkinson's disease; Contrast (vision); Population; Magnetic resonance imaging; Nuclear medicine; Medicine; Computer science; Artificial intelligence; Pathology; Radiology; Disease","score_opus":0.08957193115287045,"score_gpt":0.3733878206738385,"score_spread":0.2838158895209681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284992187","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20934984,0.003168907,0.037822235,0.00064009224,0.00033356601,0.0011699469,0.7372549,0.0063465126,0.0039139627],"genre_scores_gemma":[0.13078934,0.0006115702,0.023857037,0.00015747968,0.00009844766,0.0007636619,0.84179705,0.00025482275,0.00167064],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989895,0.00015406449,0.000117346564,0.0004020498,0.00025542683,0.00008164687],"domain_scores_gemma":[0.9983633,0.0003529638,0.00014952585,0.0005522586,0.000431312,0.00015066109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010948824,0.0010849078,0.0010755853,0.0019521557,0.00042973823,0.0008593832,0.0022623818,0.0015140416,0.00389921],"category_scores_gemma":[0.0038220573,0.00044752145,0.0012600506,0.0018627349,0.00044519483,0.00035446289,0.0011150079,0.000771004,0.0052163657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001982217,0.0011379952,0.1229239,0.0017411899,0.0017870154,0.0057004807,0.0004534399,0.03546061,0.021222405,0.0022114855,0.49432313,0.31105617],"study_design_scores_gemma":[0.0009549754,0.0013019238,0.43444383,0.0006389129,0.0012509103,0.020348692,0.00070698856,0.13090931,0.024333788,0.009097057,0.3755205,0.00049315643],"about_ca_topic_score_codex":0.0122453,"about_ca_topic_score_gemma":0.016368441,"teacher_disagreement_score":0.0122453,"about_ca_system_score_codex":0.000802029,"about_ca_system_score_gemma":0.0010648135,"threshold_uncertainty_score":0.02434802},"labels":[],"label_agreement":null},{"id":"W4284994255","doi":"10.1016/j.nicl.2022.103105","title":"Volumetric and structural connectivity abnormalities co-localise in TLE","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"UCLH Biomedical Research Centre; Medical Research Council; University College London Hospitals NHS Foundation Trust; University of Western Australia; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; National Imaging Facility; UK Research and Innovation; Wellcome Trust","keywords":"White matter; Grey matter; Diffusion MRI; Temporal lobe; Tractography; Epilepsy; Lateralization of brain function; Neuroscience; Magnetic resonance imaging; Psychology; Anatomy; Medicine; Radiology","score_opus":0.1469820276962668,"score_gpt":0.4532205269882004,"score_spread":0.3062384992919336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284994255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993771,0.000075446784,0.00024591642,0.00002136008,0.0000013096769,0.0000042664296,0.00006284762,0.00001003682,0.0002017538],"genre_scores_gemma":[0.99970067,0.000025411155,0.00014345635,0.000005458989,0.00000293842,0.0000025897955,0.00007188003,0.0000030180163,0.000044610428],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997273,0.000057716534,0.000043305175,0.000072469076,0.000062630155,0.000036487938],"domain_scores_gemma":[0.99835783,0.0004150703,0.00090672186,0.00014888287,0.000091144466,0.00008020835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003752321,0.0002708239,0.00039489492,0.0014160859,0.00023209168,0.000436747,0.00018119768,0.0002912787,0.0015769266],"category_scores_gemma":[0.0034014245,0.00019909444,0.00024520134,0.0007744779,0.00075289025,0.0006301921,0.0006744939,0.00024346371,0.00013031097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010360933,0.000057724694,0.948711,0.00009844675,0.00042848883,0.0026980082,0.001031685,0.0016336157,0.025176967,0.0004069733,0.0002854898,0.0184355],"study_design_scores_gemma":[0.000011048275,0.00011085758,0.9946608,0.0000053667095,0.00004670509,0.0027539323,0.00022262402,0.0008472562,0.00082962646,0.00042015905,0.000083289735,0.000008368724],"about_ca_topic_score_codex":0.001701819,"about_ca_topic_score_gemma":0.0034144074,"teacher_disagreement_score":0.001701819,"about_ca_system_score_codex":0.0002239205,"about_ca_system_score_gemma":0.00011407299,"threshold_uncertainty_score":0.0052753687},"labels":[],"label_agreement":null},{"id":"W4285227449","doi":"10.2139/ssrn.4097565","title":"In-Vivo Along Muscle Fascicle Strain Heterogeneity is Not Affected by Image Registration Parameters: Robustness Testing of Combined Magnetic Resonance-Diffusion Tensor Imaging Method","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Fascicle; Robustness (evolution); Nuclear magnetic resonance; In vivo; Image registration; Biomedical engineering; Materials science; Medicine; Anatomy; Physics; Computer vision; Chemistry; Computer science; Radiology; Image (mathematics); Biology","score_opus":0.03139744674650294,"score_gpt":0.32171733679284575,"score_spread":0.29031989004634284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285227449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7964492,0.0008802634,0.19927599,0.00031516876,0.00020685342,0.00013318208,0.0005809858,0.00070832274,0.0014500536],"genre_scores_gemma":[0.96626854,0.00025338802,0.031955097,0.000090604204,0.0000377105,0.00005440295,0.00050010823,0.0002455963,0.00059461955],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985814,0.00054916256,0.00012597127,0.00037662184,0.0002783947,0.00008843936],"domain_scores_gemma":[0.99024,0.00541163,0.0013335819,0.0017721864,0.0009986657,0.0002439692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00389808,0.0007795336,0.0004992989,0.00056616834,0.0002966464,0.0011186533,0.0006602911,0.0012898484,0.0010672596],"category_scores_gemma":[0.02345643,0.00037749845,0.0006304279,0.00037045885,0.00080993,0.0010639426,0.00096791744,0.0008112349,0.00043999578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.015308802,0.00095720886,0.022575067,0.0014731536,0.0023142565,0.0007105447,0.00059111154,0.14384754,0.6645039,0.0022354987,0.001694078,0.14378881],"study_design_scores_gemma":[0.00032679984,0.0038670523,0.06459408,0.00019478987,0.0013973796,0.0025511498,0.00023762205,0.6507152,0.27069545,0.0024520156,0.0027266697,0.00024184075],"about_ca_topic_score_codex":0.001145042,"about_ca_topic_score_gemma":0.000991461,"teacher_disagreement_score":0.00389808,"about_ca_system_score_codex":0.00019024799,"about_ca_system_score_gemma":0.0005005954,"threshold_uncertainty_score":0.02061528},"labels":[],"label_agreement":null},{"id":"W4285490115","doi":"10.1016/j.nic.2022.05.001","title":"Cerebral White Matter Tract Anatomy","year":2022,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Medicine; Neuroscience; Tractography; Anatomy; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.11286402580904348,"score_gpt":0.42788729430903943,"score_spread":0.31502326849999596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285490115","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013097805,0.99659306,0.00016620172,0.00031997688,0.00024415072,0.000007643806,0.000050668365,0.000015692254,0.0024716444],"genre_scores_gemma":[0.00065747206,0.99734014,0.0003244929,0.00021555716,0.0003680835,0.0000072201533,0.00007280007,0.000002528327,0.001011652],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998795,0.000016887821,0.000024935935,0.000030243782,0.00003568605,0.000012770655],"domain_scores_gemma":[0.99966884,0.00011161387,0.00007317074,0.000012334627,0.00010680265,0.000027232583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004318122,0.0010918014,0.0011097387,0.0055060512,0.00028383167,0.0010911449,0.0005851918,0.00081484637,0.005846174],"category_scores_gemma":[0.0011359991,0.000328956,0.00041003275,0.0042180447,0.00053107366,0.0012761665,0.00071357295,0.0009932744,0.0028755672],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003365188,0.000024481795,0.00025374084,0.008162191,0.000059843933,0.00023769372,0.000038451228,0.00014105657,0.0005454795,0.0012984787,0.044744443,0.94446033],"study_design_scores_gemma":[0.00002131302,0.00006295531,0.003507299,0.008089853,0.000345786,0.0034701605,0.000083561856,0.00010597809,0.00042450445,0.0019710674,0.9818887,0.000028792656],"about_ca_topic_score_codex":0.0057709506,"about_ca_topic_score_gemma":0.013263799,"teacher_disagreement_score":0.005846174,"about_ca_system_score_codex":0.0008797798,"about_ca_system_score_gemma":0.003248524,"threshold_uncertainty_score":0.019557416},"labels":[],"label_agreement":null},{"id":"W4286236408","doi":"10.48550/arxiv.2207.07778","title":"High-resolution diffusion-weighted imaging at 7 Tesla: single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Sharpening; Image resolution; Diffusion MRI; Signal-to-noise ratio (imaging); Physics; Resolution (logic); Image quality; Nuclear magnetic resonance; Optics; Computer science; Magnetic resonance imaging; Artificial intelligence; Image (mathematics)","score_opus":0.088585658381082,"score_gpt":0.2588581358627997,"score_spread":0.1702724774817177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286236408","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7516258,0.012751524,0.23251615,0.00034506412,0.00004388937,0.00013995636,0.0005149043,0.0007424649,0.0013203806],"genre_scores_gemma":[0.68376154,0.008728782,0.3046363,0.00013249651,0.000027932469,0.00021427222,0.0009985289,0.00036628876,0.0011338086],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990275,0.0003893913,0.000078389574,0.00014436444,0.0003069963,0.00005340925],"domain_scores_gemma":[0.9973912,0.0012258956,0.0003976755,0.0002321413,0.0006389585,0.0001140478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028163907,0.0005701668,0.0006672229,0.00047689598,0.00023807955,0.0007471563,0.000596066,0.00075041805,0.00057577837],"category_scores_gemma":[0.00792643,0.0004709339,0.00022829304,0.0008853075,0.00035410756,0.001151733,0.00038040656,0.0004297319,0.0003151895],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012530251,0.000091007816,0.004586594,0.0008276811,0.00013970822,0.00060801854,0.00029844808,0.014166479,0.90969825,0.001702907,0.00041745006,0.06621039],"study_design_scores_gemma":[0.00010072855,0.0019668099,0.03831409,0.00018369565,0.00030459452,0.0052794754,0.0001499436,0.10946911,0.8351393,0.003588983,0.0053410763,0.00016214859],"about_ca_topic_score_codex":0.0012770535,"about_ca_topic_score_gemma":0.0012854224,"teacher_disagreement_score":0.0028163907,"about_ca_system_score_codex":0.00055072707,"about_ca_system_score_gemma":0.00042721888,"threshold_uncertainty_score":0.014894664},"labels":[],"label_agreement":null},{"id":"W4286252873","doi":"10.1016/j.neuroimage.2022.119495","title":"Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; Research to Prevent Blindness; National Science Foundation; National Institutes of Health; Foundation Fighting Blindness; Lions Clubs International Foundation","keywords":"Optic tract; Retinal ganglion cell; White matter; Retinal; Optic radiation; Optic nerve; Optic chiasm; Retina; Visual system; Biology; Diffusion MRI; Anatomy; Ophthalmology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.032697869291006966,"score_gpt":0.30696674204759333,"score_spread":0.27426887275658635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286252873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989343,0.00018185064,0.0003805729,0.000013601012,0.000002486106,0.0000018023098,0.000101719765,0.000010623012,0.00037296858],"genre_scores_gemma":[0.9993968,0.000039532042,0.00021931386,0.0000065395643,0.0000032437165,0.000002370263,0.000096103424,0.000005326108,0.00023079463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996649,0.00004807691,0.000034215762,0.00013900243,0.00007554044,0.000038240214],"domain_scores_gemma":[0.99667645,0.0007990362,0.0014031435,0.0005938355,0.00020289328,0.0003245743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005101193,0.00021991144,0.00028270602,0.0007316965,0.00016649712,0.00043469743,0.00018436906,0.00022793375,0.0016414876],"category_scores_gemma":[0.0028078626,0.00018130726,0.00025438136,0.00048303822,0.00037561884,0.00033902988,0.00037515865,0.00024182531,0.00021590557],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031201402,0.000016631428,0.9625373,0.000018394358,0.00024848565,0.0001372348,0.00010730435,0.00042827736,0.031493064,0.00010061228,0.00008466724,0.0045160386],"study_design_scores_gemma":[7.888188e-7,0.000024064271,0.9989882,0.0000012082211,0.000009828649,0.00020023929,0.000014349795,0.00015679997,0.00053746905,0.000027695296,0.000037465375,0.0000018781412],"about_ca_topic_score_codex":0.0023506864,"about_ca_topic_score_gemma":0.002888022,"teacher_disagreement_score":0.0023506864,"about_ca_system_score_codex":0.00017562462,"about_ca_system_score_gemma":0.00010770228,"threshold_uncertainty_score":0.0054913163},"labels":[],"label_agreement":null},{"id":"W4286255720","doi":"10.1016/j.neurobiolaging.2022.03.020","title":"Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment","year":2022,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Hospital and Health Sciences Centre; University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries; Vancouver Coastal Health","funders":"Canadian Institutes of Health Research","keywords":"Hyperintensity; White matter; Corpus callosum; Myelin; Cingulum (brain); Psychology; Gait; Posterior cingulate; Internal medicine; Cardiology; Magnetic resonance imaging; Medicine; Audiology; Physical medicine and rehabilitation; Cognition; Neuroscience; Radiology; Central nervous system; Fractional anisotropy","score_opus":0.03428768788565538,"score_gpt":0.2841490144208272,"score_spread":0.2498613265351718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286255720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99890924,0.00048717333,0.00002455882,0.00003738557,0.0000053630065,0.000004442973,0.00009963669,0.0000022439492,0.00042996646],"genre_scores_gemma":[0.9994398,0.0001731248,0.000042884876,0.000022088805,0.000013186684,0.0000031898144,0.000106475956,6.5686453e-7,0.00019848158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985886,0.00002534218,0.000028656648,0.00002467725,0.000034503217,0.00002808025],"domain_scores_gemma":[0.9993038,0.00008301387,0.00037622402,0.000020471542,0.00009102417,0.00012544492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003046827,0.00039953593,0.00045227964,0.0013114993,0.00040450657,0.0005646341,0.0002601423,0.0006236813,0.0012675945],"category_scores_gemma":[0.0021225864,0.00020738934,0.00027857625,0.0010980252,0.00027128574,0.0005954493,0.00047592146,0.00040205475,0.00017752494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049321353,0.00013680353,0.99492365,0.00003431445,0.00010770334,0.00040954305,0.00016799032,0.00007626989,0.0003757881,0.000022609092,0.00008582946,0.0031663098],"study_design_scores_gemma":[0.0000037469683,0.00012002444,0.999198,0.000005485916,0.000025322726,0.00033086125,0.00012561215,0.000096790725,0.00002375318,0.00003340258,0.000034503704,0.0000025032969],"about_ca_topic_score_codex":0.008159196,"about_ca_topic_score_gemma":0.010487958,"teacher_disagreement_score":0.008159196,"about_ca_system_score_codex":0.00030618673,"about_ca_system_score_gemma":0.00021027248,"threshold_uncertainty_score":0.016223371},"labels":[],"label_agreement":null},{"id":"W4286560425","doi":"10.1093/braincomms/fcac187","title":"Structural disconnection and functional reorganization in Fabry disease: a multimodal MRI study","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Connectome; Confounding; Disease; Functional connectivity; Fabry disease; Resting state fMRI; Diffusion MRI; Neuroscience; Medicine; Magnetic resonance imaging; Psychology; Cardiology; Internal medicine; Radiology","score_opus":0.08221085080168757,"score_gpt":0.3653587070523829,"score_spread":0.28314785625069533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286560425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99964297,0.00009958822,0.000103319304,0.000012156199,7.025086e-7,0.0000050619606,0.000033946482,0.0000014411955,0.0001008628],"genre_scores_gemma":[0.9997017,0.000044118173,0.00010981657,0.0000073534848,0.0000064516003,0.0000038825524,0.00007789686,9.005155e-7,0.000047961486],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987936,0.000028657618,0.000011223212,0.000040493233,0.000016213853,0.000024044104],"domain_scores_gemma":[0.9997117,0.000063214655,0.000108675595,0.000035286816,0.000027479693,0.00005359747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050437753,0.00041768333,0.0003359461,0.001180616,0.000375031,0.0002960889,0.00019214962,0.00045527512,0.0009851983],"category_scores_gemma":[0.0009939991,0.0002127729,0.0002060695,0.00040401096,0.00038261822,0.00038934714,0.00037931403,0.00023888561,0.0001314469],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018549503,0.00038590623,0.93564945,0.00007255086,0.0002446409,0.0061402414,0.0010815974,0.00035224273,0.04550542,0.00014379159,0.00016159848,0.00840762],"study_design_scores_gemma":[0.000021533355,0.0003451142,0.99494535,0.000006408811,0.000060862127,0.0032343464,0.00015651551,0.00046632384,0.0005693633,0.000079871716,0.00010671007,0.000007528637],"about_ca_topic_score_codex":0.0014806187,"about_ca_topic_score_gemma":0.0012705293,"teacher_disagreement_score":0.0014806187,"about_ca_system_score_codex":0.0002636887,"about_ca_system_score_gemma":0.00013962224,"threshold_uncertainty_score":0.0032958388},"labels":[],"label_agreement":null},{"id":"W4286630390","doi":"10.3389/fnagi.2022.859873","title":"Longitudinal Intraindividual Cognitive Variability Is Associated With Reduction in Regional Cerebral Blood Flow Among Alzheimer’s Disease Biomarker-Positive Older Adults","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Pfizer; Bristol-Myers Squibb; Eli Lilly and Company; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; University of Southern California; H. Lundbeck A/S; U.S. Department of Veterans Affairs; Foundation for the National Institutes of Health","keywords":"Biomarker; Medicine; Cerebral blood flow; Neuropsychology; Dementia; Magnetic resonance imaging; Alzheimer's Disease Neuroimaging Initiative; Cardiology; Internal medicine; Neuroimaging; Cerebrospinal fluid; Cognitive decline; Alzheimer's disease; Oncology; Disease; Psychology; Cognition; Radiology; Psychiatry","score_opus":0.040029280014623594,"score_gpt":0.3003318392567934,"score_spread":0.26030255924216983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286630390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99939144,0.00017762787,0.00011310771,0.000018798717,0.000003720118,0.0000036567892,0.000082638595,0.000006095198,0.00020283554],"genre_scores_gemma":[0.99961346,0.00004547084,0.00007737389,0.000014473242,0.0000066843445,0.0000052735804,0.0001185908,0.0000017890818,0.00011695861],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997261,0.00005851488,0.00003114977,0.00009769259,0.000050956125,0.000035524627],"domain_scores_gemma":[0.99831885,0.00030726282,0.0008622685,0.00018187088,0.00018714333,0.00014255646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007295263,0.00028836165,0.00029703014,0.0005551602,0.00035503475,0.0004286828,0.000267179,0.00047597662,0.00057654525],"category_scores_gemma":[0.0025246716,0.0002344566,0.00030788832,0.000433352,0.00018182819,0.00032866668,0.00035071012,0.0005268345,0.00016605336],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004573407,0.00007317423,0.99422485,0.000009929999,0.00011784785,0.00008484127,0.000184145,0.0000698673,0.0012930408,0.000012976158,0.00008475377,0.0033871566],"study_design_scores_gemma":[0.0000023236107,0.00007337963,0.9996025,0.0000012396503,0.000012879823,0.00007065316,0.000025349942,0.00010388323,0.00006144403,0.000015866235,0.000028608074,0.0000018736001],"about_ca_topic_score_codex":0.0033860288,"about_ca_topic_score_gemma":0.0039236583,"teacher_disagreement_score":0.0033860288,"about_ca_system_score_codex":0.00016023642,"about_ca_system_score_gemma":0.00012791874,"threshold_uncertainty_score":0.0067326427},"labels":[],"label_agreement":null},{"id":"W4286640335","doi":"10.1016/j.neuroimage.2022.119488","title":"Short-term repeatability and long-term reproducibility of quantitative MR imaging biomarkers in a single centre longitudinal study","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"Canadian Institutes of Health Research; University of Calgary","keywords":"Reproducibility; Repeatability; Fractional anisotropy; Coefficient of variation; Nuclear medicine; Medicine; Diffusion MRI; Cerebral blood flow; Biomedical engineering; Pathology; Radiology; Magnetic resonance imaging; Mathematics; Statistics; Internal medicine","score_opus":0.12233916128991092,"score_gpt":0.39077567043713873,"score_spread":0.26843650914722783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286640335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9869401,0.000880535,0.010681455,0.000047705726,0.000050384122,0.00011147109,0.000498527,0.000095501266,0.0006942923],"genre_scores_gemma":[0.99704164,0.00006393936,0.002002071,0.000027058066,0.000025492645,0.00009293546,0.0005269359,0.000036019304,0.00018390869],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9885308,0.0042409953,0.001414462,0.0031576285,0.0021592553,0.0004969099],"domain_scores_gemma":[0.95532364,0.015245323,0.007865216,0.010969343,0.009695351,0.0009011195],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.029170215,0.00053697306,0.00082975684,0.0011110594,0.00079495576,0.0013894069,0.00082384644,0.0010879486,0.00040184535],"category_scores_gemma":[0.038972355,0.0005288427,0.0009943717,0.0009903027,0.00089783064,0.0009635166,0.0009663518,0.0005507896,0.00037248392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017399145,0.00019987674,0.9679846,0.00012650507,0.0016702533,0.00025383613,0.001928174,0.001103023,0.010758896,0.00013357765,0.00039007413,0.01371119],"study_design_scores_gemma":[0.000030074205,0.0012005018,0.9940825,0.0000213456,0.0003599677,0.00034111348,0.00025358386,0.0012499022,0.0017130888,0.0001041375,0.0006070613,0.000036652855],"about_ca_topic_score_codex":0.0026122525,"about_ca_topic_score_gemma":0.0028458878,"teacher_disagreement_score":0.9708298,"about_ca_system_score_codex":0.00051132124,"about_ca_system_score_gemma":0.00052407105,"threshold_uncertainty_score":0.15426868},"labels":[],"label_agreement":null},{"id":"W4286714342","doi":"10.26599/bsa.2019.9050012","title":"Visualizing the neuroanatomical changes in Han Chinese adulthood: A pseudo-longitudinal study based on age-related large-scale statistical Chinese brain atlases","year":2019,"lang":"en","type":"article","venue":"Brain Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Atrophy; Neuroscience; Brain cortex; Neuropathology; Brain size; Cortex (anatomy); Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Pathology; Internal medicine","score_opus":0.029240193825797067,"score_gpt":0.40026859882694077,"score_spread":0.3710284050011437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286714342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942795,0.00012439577,0.0043810084,0.000049215418,0.000011618534,0.0000331634,0.0007818263,0.00003930953,0.00029997303],"genre_scores_gemma":[0.99231476,0.00012101017,0.0054391962,0.00002568722,0.000012955144,0.00007649184,0.0014463187,0.000023095326,0.0005404367],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987566,0.00002890013,0.000011780035,0.000039032355,0.000026153999,0.000018512848],"domain_scores_gemma":[0.99957234,0.000051480903,0.000091194015,0.00007660303,0.00015559592,0.00005275449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008104055,0.00026859474,0.00012667917,0.00070708554,0.0003711729,0.00024586104,0.00021211721,0.00015632794,0.0010028367],"category_scores_gemma":[0.000905277,0.0001587111,0.00031509335,0.00043950658,0.00027441935,0.00028460802,0.00037154977,0.0001426847,0.00012542839],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084343454,0.00020222786,0.82163954,0.00025517476,0.00047477597,0.0012725805,0.004007992,0.0046733213,0.0850502,0.0014541784,0.0034130297,0.07671347],"study_design_scores_gemma":[0.000008593796,0.0001432928,0.98572135,0.000011225582,0.00007758796,0.0005913154,0.00070807943,0.004594866,0.006053129,0.0002874326,0.0017795116,0.000023607272],"about_ca_topic_score_codex":0.019135986,"about_ca_topic_score_gemma":0.0335315,"teacher_disagreement_score":0.019135986,"about_ca_system_score_codex":0.00036577217,"about_ca_system_score_gemma":0.0005512683,"threshold_uncertainty_score":0.03804922},"labels":[],"label_agreement":null},{"id":"W4286718003","doi":"10.31083/j.jin2105129","title":"Gait Disorders and Magnetic Resonance Imaging Characteristics in Older Adults with Cerebral Small Vessel Disease","year":2022,"lang":"en","type":"article","venue":"Journal of Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Magnetic resonance imaging; Gait; Tinetti test; Fractional anisotropy; Diffusion MRI; Medicine; White matter; Internal medicine; Rating scale; Cardiology; Psychology; Physical medicine and rehabilitation; Radiology","score_opus":0.015324358451782647,"score_gpt":0.2831349522743294,"score_spread":0.26781059382254674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286718003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993648,0.00020672606,0.000025480844,0.000021233003,0.000004002608,0.000004612077,0.00008799097,0.0000012995074,0.00028394276],"genre_scores_gemma":[0.99953973,0.00010247927,0.000051215724,0.000021002297,0.000015151471,0.000005034806,0.00017710327,5.927448e-7,0.00008768034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998435,0.000023457002,0.000030598047,0.000031597614,0.00004021565,0.000030626277],"domain_scores_gemma":[0.99946886,0.0000570662,0.00026961399,0.000017551587,0.00006876956,0.000118182244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023919877,0.00027800817,0.000329902,0.0011084958,0.00033858832,0.00035531397,0.00012790387,0.00037744895,0.0011789466],"category_scores_gemma":[0.0011221012,0.000121765894,0.0002452392,0.0008327144,0.00020174589,0.00031748883,0.00024689792,0.00023379363,0.0002021709],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006285131,0.00002725785,0.9984469,0.000006201078,0.000017436008,0.00020852663,0.000038681155,0.000014705139,0.00017968663,0.000005259179,0.00003629263,0.00095628144],"study_design_scores_gemma":[0.000003530477,0.00007271925,0.9988902,0.0000033866374,0.000010187287,0.0008244604,0.00006569907,0.000040371084,0.000020729532,0.000009715948,0.000057856767,0.0000011819799],"about_ca_topic_score_codex":0.0022010396,"about_ca_topic_score_gemma":0.0035428384,"teacher_disagreement_score":0.0022010396,"about_ca_system_score_codex":0.00017752206,"about_ca_system_score_gemma":0.00016676103,"threshold_uncertainty_score":0.0043764114},"labels":[],"label_agreement":null},{"id":"W4286784827","doi":"10.48550/arxiv.1904.13281","title":"CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke\\n Lesion Segmentation","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Computer science; Artificial intelligence; Discriminator; Stroke (engine); Convolutional neural network; Ground truth; Pattern recognition (psychology); Magnetic resonance imaging; Diffusion MRI; Noise (video); Radiology; Medicine; Image (mathematics); Physics","score_opus":0.14085385024045802,"score_gpt":0.28094112281661066,"score_spread":0.14008727257615264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286784827","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.084799685,0.0008260234,0.9040682,0.0010164066,0.00011380568,0.00006919313,0.0004833604,0.004090753,0.0045326194],"genre_scores_gemma":[0.8873737,0.0003937863,0.10340869,0.00035531484,0.000076440665,0.00009641778,0.0010912342,0.00029911354,0.006905259],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971133,0.000101749196,0.000010813449,0.00007810478,0.0000544309,0.0000434216],"domain_scores_gemma":[0.99911374,0.0005500462,0.00008315052,0.00012053138,0.00009137812,0.000041233092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089981494,0.0009598164,0.0005031353,0.00043418992,0.00027567043,0.00055595953,0.0010035144,0.0009192672,0.0022649448],"category_scores_gemma":[0.003287011,0.0004638605,0.0006730183,0.0003556386,0.00088228344,0.00069050986,0.0012134433,0.001708043,0.00053367985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080959755,0.000019244779,0.00029721757,0.000018950086,0.000024318937,0.00004992302,0.000019916286,0.97650254,0.0018549421,0.002797833,0.00082409836,0.017510002],"study_design_scores_gemma":[0.0000016988897,0.0000050689446,0.00006129661,0.0000021264252,0.0000023629098,0.0000061085384,0.0000012955298,0.99758375,0.0006438639,0.0015901801,0.00010024426,0.0000018947823],"about_ca_topic_score_codex":0.008902267,"about_ca_topic_score_gemma":0.008166373,"teacher_disagreement_score":0.008902267,"about_ca_system_score_codex":0.0011715635,"about_ca_system_score_gemma":0.00074561,"threshold_uncertainty_score":0.017700851},"labels":[],"label_agreement":null},{"id":"W4287241074","doi":"10.48550/arxiv.2104.01708","title":"A unified framework for non-negative matrix and tensor factorisations\\n with a smoothed Wasserstein loss","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tensor (intrinsic definition); Metric (unit); Matrix (chemical analysis); Mathematics; Applied mathematics; Mathematical optimization; Dual (grammatical number); Space (punctuation); Regular polygon; Function (biology); Wasserstein metric; Algorithm; Computer science; Algebra over a field; Pure mathematics; Geometry","score_opus":0.12318298998261953,"score_gpt":0.2823722297802872,"score_spread":0.15918923979766766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287241074","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006366132,0.000083995554,0.998621,0.00013262597,0.000025270454,0.0000120273735,0.000023882409,0.000055032127,0.0004094632],"genre_scores_gemma":[0.07305433,0.0007572358,0.9175134,0.00032548897,0.0003989477,0.00027850803,0.0004196307,0.00052398746,0.006728459],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825853,0.00069906435,0.000116899486,0.00035980527,0.00044531276,0.00012041868],"domain_scores_gemma":[0.9975706,0.0010545214,0.00026593506,0.00041913576,0.0004686643,0.0002212139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004946887,0.002196191,0.0016221313,0.0019310364,0.0008146996,0.003596262,0.0031472086,0.002583385,0.0038721012],"category_scores_gemma":[0.009883635,0.0008797827,0.0020049175,0.0019503745,0.0032126491,0.0064864065,0.0044858176,0.005281725,0.0015049536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004568878,0.00006273257,0.00035354696,0.00012627871,0.00005663925,0.00013305509,0.000120126875,0.2526975,0.0028128654,0.6993722,0.004189025,0.040030442],"study_design_scores_gemma":[0.0000070269616,0.00004020435,0.00008056202,0.000019708486,0.00000939425,0.000056638695,0.000015873182,0.7893861,0.0006224647,0.20620988,0.0035339433,0.000018199891],"about_ca_topic_score_codex":0.0036884523,"about_ca_topic_score_gemma":0.004619277,"teacher_disagreement_score":0.004946887,"about_ca_system_score_codex":0.0023825385,"about_ca_system_score_gemma":0.0024013447,"threshold_uncertainty_score":0.026161969},"labels":[],"label_agreement":null},{"id":"W4288709490","doi":"10.1111/ejn.15785","title":"Effect of number of diffusion‐encoding directions in diffusion metrics of 5‐year‐olds using tract‐based spatial statistical analysis","year":2022,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Suomalainen Lääkäriseura Duodecim; Suomen Aivosäätiö; Signe ja Ane Gyllenbergin Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Juho Vainion Säätiö; Suomalais-Norjalainen Lääketieteen Säätiö; Suomen Lääketieteen Säätiö","keywords":"Diffusion MRI; Fractional anisotropy; Scalar (mathematics); Intraclass correlation; Mathematics; Statistics; Reproducibility; Psychology; Medicine; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.055459933730030775,"score_gpt":0.37664017462963556,"score_spread":0.3211802408996048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288709490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904799,0.0012840014,0.006863719,0.00010460194,0.00005652061,0.000025301119,0.00064545736,0.00016544189,0.000375054],"genre_scores_gemma":[0.99390066,0.00018460641,0.004917708,0.00002111967,0.0000179626,0.000033987308,0.0006599526,0.00010216044,0.00016187785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9923125,0.0031449618,0.0011911048,0.002343459,0.00075648935,0.00025152578],"domain_scores_gemma":[0.9290747,0.052156635,0.007873178,0.005717618,0.0037887627,0.0013891116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015755793,0.00092554576,0.0009801688,0.0012084985,0.00046343045,0.001449181,0.00056594313,0.0009172051,0.001329453],"category_scores_gemma":[0.06850403,0.00045992123,0.0015607405,0.00089983817,0.0010506726,0.0012933341,0.0010265387,0.0008795572,0.00035197157],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008961918,0.00015104539,0.9011734,0.00044871744,0.0035205574,0.0006288429,0.0030071095,0.0077225277,0.0105195185,0.000497069,0.0013755346,0.06199373],"study_design_scores_gemma":[0.00010160833,0.0022092478,0.96441346,0.00021692306,0.001926535,0.00075817306,0.0010149591,0.022043085,0.0046440098,0.0007233079,0.0018363456,0.00011245065],"about_ca_topic_score_codex":0.009966607,"about_ca_topic_score_gemma":0.011575295,"teacher_disagreement_score":0.015755793,"about_ca_system_score_codex":0.00045050876,"about_ca_system_score_gemma":0.0008956681,"threshold_uncertainty_score":0.083325565},"labels":[],"label_agreement":null},{"id":"W4289518521","doi":"10.1101/2022.07.29.502031","title":"Mapping the Macrostructure and Microstructure of the in vivo Human Hippocampus using Diffusion MRI","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; McGill University; Montreal Neurological Institute and Hospital; Western University","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Open Neuroscience Platform; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; University of Southern California","keywords":"Diffusion MRI; Neuroscience; Hippocampal formation; Subiculum; Neurite; Fractional anisotropy; Hippocampus; Psychology; Materials science; Biology; Magnetic resonance imaging; Medicine; Dentate gyrus","score_opus":0.029645112361038742,"score_gpt":0.2796732401389287,"score_spread":0.25002812777788996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289518521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96789616,0.0007087382,0.030222913,0.00006973368,0.000007037863,0.000035724555,0.00039818804,0.00008340356,0.0005782253],"genre_scores_gemma":[0.98578054,0.0004545041,0.013205019,0.00002761647,0.000007293446,0.000021019763,0.00012997567,0.000017519344,0.0003564772],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99996734,0.000008820451,0.0000028520606,0.000010950931,0.000006479493,0.0000036378426],"domain_scores_gemma":[0.9998902,0.000041046515,0.000024513874,0.000014809886,0.00002016916,0.000009252901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020805304,0.00018294012,0.00010239579,0.00043310682,0.000118347816,0.00029870222,0.000097261465,0.00018105745,0.00073390815],"category_scores_gemma":[0.0004938652,0.00017373422,0.00007389421,0.00017652518,0.00024366971,0.00024061832,0.00014604293,0.00012918179,0.00011745336],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038188905,0.000047942875,0.016359499,0.00016225332,0.00007593529,0.00034668698,0.0002617703,0.0053497227,0.9530563,0.00048110032,0.00031932988,0.023157664],"study_design_scores_gemma":[0.000101468206,0.0010360803,0.4377083,0.000071661445,0.00016952763,0.0072499085,0.00059364375,0.09414287,0.4507218,0.003150947,0.0049538296,0.00010005822],"about_ca_topic_score_codex":0.0022118294,"about_ca_topic_score_gemma":0.0030950163,"teacher_disagreement_score":0.0022118294,"about_ca_system_score_codex":0.00011226503,"about_ca_system_score_gemma":0.00013910556,"threshold_uncertainty_score":0.004397869},"labels":[],"label_agreement":null},{"id":"W4289526123","doi":"10.1016/j.jns.2022.120377","title":"Timing stroke: A review on stroke pathophysiology and its influence over time on diffusion measures","year":2022,"lang":"en","type":"review","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal","funders":"","keywords":"Diffusion MRI; Stroke (engine); Medicine; Pathophysiology; Neuroinflammation; Ischemia; Neuroscience; Pathology; Disease; Cardiology; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.16587531255986399,"score_gpt":0.40956497275471926,"score_spread":0.24368966019485527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289526123","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038344115,0.9997346,0.000034599885,0.00006342342,0.000049368817,0.0000022568604,0.000014593701,0.000001473965,0.00006134447],"genre_scores_gemma":[0.00035813433,0.999243,0.00011692721,0.00008268552,0.0001183635,0.0000056884965,0.000022345443,0.0000010457851,0.00005171683],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99945134,0.000102017,0.00016698499,0.000123908,0.00012497976,0.000030759187],"domain_scores_gemma":[0.99792457,0.0014232142,0.0003195274,0.000035716854,0.0002519314,0.000045029847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016436207,0.0017684174,0.004074189,0.004196768,0.0002550582,0.00174731,0.001412516,0.0016998962,0.0031473942],"category_scores_gemma":[0.0036698752,0.0006254212,0.001596014,0.00424772,0.00077536184,0.0018153137,0.00090441277,0.0015200279,0.0010954207],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032145216,0.00008617487,0.0007377774,0.09106468,0.00091869425,0.00018794107,0.00007491059,0.00039512358,0.0006044347,0.0012202461,0.015816389,0.8885722],"study_design_scores_gemma":[0.00029884969,0.0007519033,0.010957447,0.10685259,0.008103811,0.004376231,0.0002777492,0.0004295821,0.0012224776,0.005211241,0.86129487,0.00022335086],"about_ca_topic_score_codex":0.0025571962,"about_ca_topic_score_gemma":0.004933592,"teacher_disagreement_score":0.004196768,"about_ca_system_score_codex":0.00075880304,"about_ca_system_score_gemma":0.0023105654,"threshold_uncertainty_score":0.010529101},"labels":[],"label_agreement":null},{"id":"W4289653886","doi":"10.1101/2022.08.01.502396","title":"RELIEF: a structured multivariate approach for removal of latent inter-scanner effects","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; University of Toronto; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Scanner; Generalizability theory; Computer science; Harmonization; Univariate; Multivariate statistics; Data science; Artificial intelligence; Machine learning; Data mining; Statistics; Mathematics","score_opus":0.03422065117062607,"score_gpt":0.29290118778850355,"score_spread":0.2586805366178775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289653886","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031236853,0.00014727788,0.99538004,0.0001347093,0.000025991403,0.000058255224,0.00015997278,0.00080688886,0.00016328439],"genre_scores_gemma":[0.08577636,0.00025819908,0.9095976,0.00035311762,0.00020730207,0.0004953474,0.00123812,0.00081129814,0.0012627678],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99339736,0.0041752686,0.00028216708,0.001103402,0.0007635488,0.00027821536],"domain_scores_gemma":[0.98744816,0.007044248,0.0012938412,0.0025719549,0.0013211216,0.00032082133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01118141,0.0016778455,0.001944496,0.002006885,0.0007607721,0.0013711387,0.0031394674,0.0014644943,0.005827176],"category_scores_gemma":[0.024278028,0.0009779172,0.0031128917,0.0021866218,0.0017191587,0.0019484783,0.0036856707,0.002607036,0.0017751972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008321697,0.00039957595,0.006922946,0.001026234,0.0015816637,0.0006383997,0.0008704101,0.20807955,0.020635884,0.05114814,0.024805415,0.68305963],"study_design_scores_gemma":[0.0001708547,0.00033441457,0.0033815398,0.00009160224,0.00023975047,0.0003403274,0.00017497664,0.91700155,0.0060035987,0.058911677,0.013213916,0.0001357799],"about_ca_topic_score_codex":0.0016293647,"about_ca_topic_score_gemma":0.0023764193,"teacher_disagreement_score":0.01118141,"about_ca_system_score_codex":0.0004423161,"about_ca_system_score_gemma":0.001738756,"threshold_uncertainty_score":0.05913365},"labels":[],"label_agreement":null},{"id":"W4289824396","doi":"10.2139/ssrn.4157505","title":"Transformer-Based Framework for Fiber Orientation Estimation &amp; Tractography","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Tractography; Orientation (vector space); Transformer; Computer science; Artificial intelligence; Computer vision; Medicine; Diffusion MRI; Radiology; Mathematics; Engineering; Electrical engineering; Magnetic resonance imaging","score_opus":0.03911101223605253,"score_gpt":0.36791293678473064,"score_spread":0.3288019245486781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289824396","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004359843,0.00010160903,0.99872464,0.00003255754,0.000009623365,0.000008369676,0.0000618242,0.00039203034,0.00023336636],"genre_scores_gemma":[0.099452764,0.0011427419,0.8921825,0.00011675679,0.00010465193,0.00011724261,0.0009173129,0.000534163,0.005431881],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99967766,0.00009368147,0.000018341094,0.000078448065,0.00009951469,0.000032406126],"domain_scores_gemma":[0.9995227,0.00016715689,0.000054369946,0.00007015979,0.00014494146,0.00004074933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076988555,0.00097166124,0.0009934783,0.0010082902,0.00037900262,0.0014837182,0.0014952858,0.0015434214,0.0049831183],"category_scores_gemma":[0.0019404218,0.00059092976,0.0011500036,0.0013843563,0.0005330759,0.0012160444,0.0012658312,0.0019345944,0.0037043712],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019239295,0.00008382852,0.0006322147,0.0003673024,0.0001598592,0.00024361465,0.00008611882,0.34612405,0.025039526,0.041407302,0.010135356,0.5755284],"study_design_scores_gemma":[0.0000051654006,0.00002265864,0.00012390071,0.000015150124,0.00001919602,0.00013518464,0.000009031948,0.9839595,0.0026532935,0.009567725,0.003477,0.000012163336],"about_ca_topic_score_codex":0.010485223,"about_ca_topic_score_gemma":0.012829526,"teacher_disagreement_score":0.010485223,"about_ca_system_score_codex":0.00049795717,"about_ca_system_score_gemma":0.0018435656,"threshold_uncertainty_score":0.020848393},"labels":[],"label_agreement":null},{"id":"W4289842561","doi":"10.1162/netn_a_00271","title":"Coupling of the spatial distributions between sMRI and PET reveals the progression of Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Eisai; Servier; Beijing Normal University; Genentech; IXICO; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Atrophy; Dementia; Neuroimaging; Positron emission tomography; Biomarker; Coupling (piping); Neuroscience; Psychology; Disease; Cognition; Medicine; Internal medicine; Oncology; Biology","score_opus":0.07338864199117781,"score_gpt":0.3675490857390655,"score_spread":0.29416044374788763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289842561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964786,0.00015263233,0.0026943164,0.000010199277,0.0000030732854,0.000007002177,0.00008062335,0.000017466378,0.00055605086],"genre_scores_gemma":[0.99888307,0.000031992568,0.00084095803,0.0000033708375,0.0000040788227,0.0000050397007,0.00007663033,0.000003310321,0.00015156638],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971133,0.00011377018,0.000023731252,0.00007765558,0.000046222576,0.000027239716],"domain_scores_gemma":[0.9993647,0.00020256489,0.00022334006,0.000069036854,0.000087001514,0.000053412292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094585196,0.0003526105,0.00025324206,0.0010632494,0.00012228427,0.00037474057,0.00018982997,0.00027247058,0.00116151],"category_scores_gemma":[0.0018705496,0.00018016864,0.00022146052,0.0005099713,0.00018601619,0.00033186248,0.00035361215,0.0001479204,0.00018428329],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023996518,0.00015213214,0.8120706,0.00017632816,0.0008992929,0.00052306306,0.0007856312,0.0046909964,0.12883027,0.0007015312,0.00041144193,0.048359156],"study_design_scores_gemma":[0.00001289953,0.00031035612,0.9792286,0.000008516382,0.000103095066,0.0006777273,0.00021411254,0.013346234,0.005071508,0.0007479822,0.00026518005,0.000013750834],"about_ca_topic_score_codex":0.00085155386,"about_ca_topic_score_gemma":0.0012187801,"teacher_disagreement_score":0.00116151,"about_ca_system_score_codex":0.0001419278,"about_ca_system_score_gemma":0.000078842015,"threshold_uncertainty_score":0.0050022006},"labels":[],"label_agreement":null},{"id":"W4289929478","doi":"10.1016/j.wneu.2022.07.110","title":"The Central Sulcus of the Insula: A Highly Reliable Radiographic Landmark for Identification of the Rolandic Sulcus","year":2022,"lang":"en","type":"article","venue":"World Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Medicine; Sulcus; Sagittal plane; Anatomy; Radiography; Central sulcus; Magnetic resonance imaging; Nuclear medicine; Landmark; Radiology; Motor cortex; Cartography","score_opus":0.027592499231980566,"score_gpt":0.2773337247215422,"score_spread":0.24974122548956165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289929478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5904987,0.01394628,0.33068028,0.0050496915,0.00092098594,0.00047296434,0.0024530108,0.0039460394,0.05203206],"genre_scores_gemma":[0.9067067,0.0023448584,0.087321304,0.0002710369,0.0003373485,0.00011084246,0.00025613408,0.00030448922,0.0023473352],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997316,0.00005727079,0.000025677991,0.00004287883,0.00009627865,0.000046300152],"domain_scores_gemma":[0.99914277,0.00026405515,0.00013921737,0.00008178362,0.00029771792,0.000074411524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007330005,0.00082639226,0.00041662256,0.0031201078,0.0005337748,0.0011060428,0.0005297167,0.0012339397,0.0030582193],"category_scores_gemma":[0.003201864,0.00037059304,0.00022339997,0.0009086736,0.00097093533,0.002040742,0.0007703383,0.0009207982,0.0021378074],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016706381,0.000085886306,0.048345763,0.0010517397,0.00018052185,0.03849645,0.0011075308,0.0024759483,0.41129634,0.0093457,0.0165821,0.46936145],"study_design_scores_gemma":[0.00033087668,0.0013523613,0.19219482,0.00081385294,0.000802866,0.26739436,0.0018023101,0.031862747,0.41719276,0.014357018,0.07149763,0.00039851404],"about_ca_topic_score_codex":0.0043574497,"about_ca_topic_score_gemma":0.0071063135,"teacher_disagreement_score":0.0043574497,"about_ca_system_score_codex":0.0004030093,"about_ca_system_score_gemma":0.0021767716,"threshold_uncertainty_score":0.01023078},"labels":[],"label_agreement":null},{"id":"W4290098649","doi":"10.21203/rs.3.rs-1922630/v1","title":"Fast sensorimotor learning in middle-aged adults","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Psychology; Neuroplasticity; Fractional anisotropy; Cognition; Cognitive training; Effects of sleep deprivation on cognitive performance; Diffusion MRI; Physical medicine and rehabilitation; Audiology; Neuroscience; Cognitive psychology; Developmental psychology; Medicine","score_opus":0.20696149849299145,"score_gpt":0.4705725445906173,"score_spread":0.26361104609762587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290098649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99895823,0.00027954657,0.00007160014,0.00002663521,0.000008649264,0.0000138579935,0.00012007141,0.0000038426333,0.00051742885],"genre_scores_gemma":[0.99917006,0.00012352335,0.00007055029,0.000029519493,0.000009803026,0.000011865362,0.000107741755,8.57981e-7,0.0004760617],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998988,0.000011862358,0.000009412973,0.000031459967,0.000017312332,0.000031183063],"domain_scores_gemma":[0.9997619,0.000026515083,0.00006402814,0.000012446952,0.00003413242,0.000101018435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003067065,0.00038693938,0.00040976744,0.0006085296,0.00042380756,0.00043682693,0.00013261901,0.00041746598,0.0020529404],"category_scores_gemma":[0.0007754131,0.00012705819,0.00017400195,0.00027536444,0.00019264696,0.00037726172,0.0003095454,0.00021779472,0.00035597],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027079063,0.0019389833,0.9473452,0.00012865891,0.000116937765,0.0015363215,0.0011204799,0.00023763772,0.012667258,0.00018584004,0.000630148,0.03138464],"study_design_scores_gemma":[0.000035146903,0.001594876,0.9969356,0.0000079856245,0.000023392753,0.00026215898,0.00016193808,0.00012624578,0.00042676352,0.000114508795,0.00030717175,0.0000040078717],"about_ca_topic_score_codex":0.0038173506,"about_ca_topic_score_gemma":0.0046427557,"teacher_disagreement_score":0.0038173506,"about_ca_system_score_codex":0.00020486346,"about_ca_system_score_gemma":0.00017711459,"threshold_uncertainty_score":0.0075902343},"labels":[],"label_agreement":null},{"id":"W4290633165","doi":"10.1002/hbm.26018","title":"Automated slice‐specific z‐shimming for functional magnetic resonance imaging of the human spinal cord","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; Medical Research Council; Horizon 2020 Framework Programme; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Medical Research Council Canada; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Spinal cord; Magnetic resonance imaging; Functional magnetic resonance imaging; Nuclear magnetic resonance; Neuroscience; Medicine; Physics; Psychology; Radiology","score_opus":0.10556802429438292,"score_gpt":0.3559360423848104,"score_spread":0.2503680180904275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290633165","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21894051,0.0009007204,0.77500814,0.00009721102,0.000062897234,0.00030845834,0.0004427167,0.0033201952,0.00091911893],"genre_scores_gemma":[0.38356766,0.00042661797,0.61337197,0.00010210894,0.00003222587,0.0002727159,0.00069840916,0.0005029025,0.0010253772],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995691,0.00013193354,0.000030717078,0.00009411265,0.000149108,0.000025014018],"domain_scores_gemma":[0.9993235,0.00024919873,0.00011436545,0.00013690468,0.00015340524,0.000022646336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008172928,0.00059257384,0.0003566463,0.0006534455,0.0004064361,0.0004892171,0.0005487182,0.00042973846,0.0014697375],"category_scores_gemma":[0.0030855148,0.0003151357,0.0003293831,0.0003809678,0.00028003872,0.00040939415,0.00046313304,0.000434994,0.0005829892],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005253093,0.00020877723,0.0025863722,0.00053684565,0.00017704243,0.00012132775,0.00021816055,0.01745488,0.48026899,0.0007820062,0.002138519,0.49498186],"study_design_scores_gemma":[0.00015311482,0.0010068378,0.05844545,0.000060651273,0.00022138565,0.0012170894,0.000118582284,0.35908148,0.5676969,0.0022330557,0.009564771,0.00020062248],"about_ca_topic_score_codex":0.0020138964,"about_ca_topic_score_gemma":0.006318743,"teacher_disagreement_score":0.0020138964,"about_ca_system_score_codex":0.00022029801,"about_ca_system_score_gemma":0.00069057633,"threshold_uncertainty_score":0.0049167275},"labels":[],"label_agreement":null},{"id":"W4290793146","doi":"10.1016/j.neuroimage.2022.119553","title":"Mapping the subcortical connectome using in vivo diffusion MRI: Feasibility and reliability","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Tractography; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Thalamus; Connectomics; Reliability (semiconductor); Computer science; Psychology; Artificial intelligence; Magnetic resonance imaging; Functional connectivity; Medicine; Physics; Radiology","score_opus":0.11618284452136339,"score_gpt":0.3562926542491656,"score_spread":0.24010980972780221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290793146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63941264,0.0016218505,0.35579652,0.00026650538,0.00004747756,0.00019649178,0.0006021324,0.0004567499,0.0015996537],"genre_scores_gemma":[0.90326524,0.00079204736,0.094661444,0.00007379381,0.000035536254,0.000114707844,0.00049417565,0.00015999163,0.00040304504],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9978143,0.0011158211,0.00016463964,0.00050787313,0.00034071304,0.00005670812],"domain_scores_gemma":[0.9922092,0.004193377,0.00097577827,0.0013844358,0.0010761132,0.00016109797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0056053377,0.0007540664,0.00054063014,0.0015653163,0.00039726423,0.001302759,0.0006253765,0.0008847906,0.00053942745],"category_scores_gemma":[0.016298424,0.00044368283,0.00031832774,0.00077004114,0.0011195095,0.0010276302,0.0009272441,0.00058069965,0.0002952621],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018637415,0.00025762236,0.231231,0.001188702,0.0013606704,0.0008812201,0.0028589596,0.024272125,0.5182811,0.0031299524,0.0011905206,0.21348438],"study_design_scores_gemma":[0.00014616935,0.0015523725,0.58734185,0.00026488554,0.0007250614,0.0073377364,0.0011337812,0.24000044,0.1379947,0.014967922,0.008267094,0.00026796578],"about_ca_topic_score_codex":0.0022173335,"about_ca_topic_score_gemma":0.0061126654,"teacher_disagreement_score":0.0056053377,"about_ca_system_score_codex":0.00022707194,"about_ca_system_score_gemma":0.0005005326,"threshold_uncertainty_score":0.02964425},"labels":[],"label_agreement":null},{"id":"W4291002081","doi":"10.9734/indj/2022/v17i430208","title":"Early Detection of White Matter Changes with Cognitive Decline in Parkinson's Patients","year":2022,"lang":"en","type":"article","venue":"International Neuropsychiatric Disease Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Cingulum (brain); White matter; Diffusion MRI; Cognitive decline; Psychology; Dementia; Parkinson's disease; Cognition; Medicine; Audiology; Atrophy; Neuroscience; Disease; Fractional anisotropy; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.014975402961141188,"score_gpt":0.2894924931585816,"score_spread":0.2745170901974404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4291002081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99942774,0.0001814468,0.00005382686,0.000019307368,0.0000029071507,0.0000072273015,0.00003822079,0.000004065911,0.00026525554],"genre_scores_gemma":[0.99951434,0.000066590816,0.00013948687,0.000017918439,0.000009393467,0.0000047064245,0.00008999716,8.57483e-7,0.00015673271],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998573,0.00002876355,0.000017487218,0.000036049925,0.00003344869,0.000026870986],"domain_scores_gemma":[0.99951327,0.000085207095,0.00020587552,0.00001175308,0.00008156239,0.00010224062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035029647,0.0004325686,0.00030147366,0.00088090036,0.00031050955,0.00047335797,0.00018430736,0.00049271586,0.0011602222],"category_scores_gemma":[0.0012636044,0.0001294674,0.00019120637,0.00033027455,0.00025775537,0.00033762679,0.0003044272,0.00026292002,0.00022234871],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045219078,0.00006535813,0.9914567,0.000020700994,0.00002723065,0.00047920868,0.000112650785,0.000043599568,0.0031516461,0.000012144746,0.00007736581,0.004101181],"study_design_scores_gemma":[0.000010257633,0.00025203422,0.99803966,0.000005517643,0.000013824139,0.00092049467,0.000073127674,0.00011628361,0.0004596328,0.000014404459,0.00009196378,0.0000027748074],"about_ca_topic_score_codex":0.0021776024,"about_ca_topic_score_gemma":0.0033909287,"teacher_disagreement_score":0.0021776024,"about_ca_system_score_codex":0.00018380594,"about_ca_system_score_gemma":0.00017694513,"threshold_uncertainty_score":0.00432986},"labels":[],"label_agreement":null},{"id":"W4292014087","doi":"10.1159/000526000","title":"Ablation Surgeries for Treatment-Resistant Depression: A Meta-Analysis and Systematic Review of Reported Case Series","year":2022,"lang":"en","type":"review","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Adler; University of British Columbia","funders":"","keywords":"Medicine; Ablative case; Meta-analysis; Systematic review; Depression (economics); Anterior cingulate cortex; Surgery; MEDLINE; Internal medicine; Psychiatry; Cognition","score_opus":0.2617888168909946,"score_gpt":0.39205422181553734,"score_spread":0.13026540492454275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292014087","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036182425,0.99489874,0.0002727745,0.00012343253,0.00007455867,0.00021768788,0.00056156126,0.000010899538,0.00022211035],"genre_scores_gemma":[0.08436854,0.9118888,0.0012168944,0.0006723166,0.00017732347,0.00068734505,0.00081331184,0.000019392135,0.00015614185],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9933734,0.0020682372,0.002774641,0.00073689804,0.0008175564,0.00022924836],"domain_scores_gemma":[0.98181766,0.01221679,0.003735661,0.00049075286,0.0015634678,0.00017565831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077536143,0.0018224968,0.011004402,0.0061203674,0.0006810254,0.0022753056,0.001860789,0.0014685609,0.0040896875],"category_scores_gemma":[0.023874447,0.0009374079,0.024800649,0.007136323,0.00055277755,0.0014224687,0.0011831304,0.0014417898,0.00030395738],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017025131,0.00005726346,0.005485619,0.6814702,0.2824141,0.000244963,0.00014663093,0.00033746302,0.00030328994,0.00017021218,0.001303912,0.026363766],"study_design_scores_gemma":[0.00059740915,0.00031286437,0.008888571,0.1053318,0.8794518,0.00039319752,0.00014132651,0.00015578835,0.00021062972,0.00027804397,0.004194523,0.000044140917],"about_ca_topic_score_codex":0.004734025,"about_ca_topic_score_gemma":0.013058495,"teacher_disagreement_score":0.011004402,"about_ca_system_score_codex":0.0018313706,"about_ca_system_score_gemma":0.0032587505,"threshold_uncertainty_score":0.041005492},"labels":[],"label_agreement":null},{"id":"W4292413392","doi":"10.1038/s41380-022-01731-3","title":"Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Research Foundation of Korea; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Research Foundation; Medical Research Council; University of Cincinnati; Schizophrenia Research Fund; National Alliance for Research on Schizophrenia and Depression; U.S. Department of Veterans Affairs; Brain and Behavior Research Foundation; National Science Foundation","keywords":"Schizophrenia (object-oriented programming); Cognition; Psychology; Working memory; Mediation; Effects of sleep deprivation on cognitive performance; White matter; Fractional anisotropy; Verbal memory; Clinical psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.02501691172374539,"score_gpt":0.34480780221093577,"score_spread":0.3197908904871904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292413392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99979013,0.000013003773,0.000089858164,0.0000054587013,5.769473e-7,0.000007597957,0.000042289546,0.0000011566351,0.000049972314],"genre_scores_gemma":[0.99965036,0.000009815204,0.00013047087,0.0000051627826,0.0000016920517,0.000008594554,0.00012875262,0.0000022889465,0.00006295078],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99943596,0.00019641554,0.000055969245,0.00014736202,0.00008353959,0.0000807177],"domain_scores_gemma":[0.9989768,0.00014819468,0.0003489597,0.00024651308,0.00013991506,0.00013969107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017210337,0.00037366344,0.00059377716,0.0012012847,0.0008197587,0.0005495918,0.0004616712,0.00044030626,0.0007952914],"category_scores_gemma":[0.001535171,0.0002607693,0.000555391,0.0010697728,0.0007574088,0.0006761605,0.0012022108,0.0003644919,0.00014207538],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00369246,0.0006987586,0.9727517,0.000029976589,0.0008407639,0.00031221993,0.0014732567,0.00057282456,0.008798892,0.0001838449,0.00019793455,0.010447279],"study_design_scores_gemma":[0.000021989608,0.00020477491,0.9987256,0.0000019078018,0.000054930188,0.00014743491,0.00032825142,0.0002462009,0.000155298,0.000053678254,0.000054266522,0.0000056917784],"about_ca_topic_score_codex":0.008627,"about_ca_topic_score_gemma":0.010160259,"teacher_disagreement_score":0.008627,"about_ca_system_score_codex":0.0007109928,"about_ca_system_score_gemma":0.00080202706,"threshold_uncertainty_score":0.017153561},"labels":[],"label_agreement":null},{"id":"W4292566611","doi":"10.3389/fnhum.2022.965602","title":"Multimodal brain features at 3 years of age and their relationship with pre-reading measures 1 year later","year":2022,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Psychology; White matter; Diffusion MRI; Uncinate fasciculus; Default mode network; Reading (process); Superior longitudinal fasciculus; Functional connectivity; Developmental psychology; Association (psychology); Neuroscience; Audiology; Cognitive psychology; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.04279008716357276,"score_gpt":0.3086494361133311,"score_spread":0.2658593489497584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292566611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99885345,0.000112788366,0.00013372599,0.00002004917,0.0000025285872,0.0000058155533,0.00051176,0.000013915217,0.00034606745],"genre_scores_gemma":[0.9979761,0.00008621373,0.00032308622,0.000013649634,0.0000024938226,0.000015946414,0.00090849545,0.0000041394824,0.0006699275],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977154,0.000025156587,0.000016614425,0.00008075882,0.00004364076,0.000062395105],"domain_scores_gemma":[0.99935454,0.00007963666,0.00025000866,0.000049169517,0.00014609909,0.00012056515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059122103,0.0003970507,0.00032458495,0.0010620762,0.00036287814,0.0007082654,0.00028793665,0.0006673822,0.0011667574],"category_scores_gemma":[0.0014037952,0.00017624583,0.0005072629,0.0003892293,0.00035187794,0.00041906023,0.0005074583,0.0005843073,0.0003050952],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005248875,0.00015050733,0.9687608,0.00003726686,0.00011767165,0.002123835,0.0016589852,0.00049328,0.012271628,0.0001766154,0.00040404772,0.013280529],"study_design_scores_gemma":[0.0000012566547,0.000077440716,0.9985399,0.000004500648,0.000011047783,0.0003653015,0.00016284593,0.00006932082,0.0005961865,0.00003714119,0.00013053603,0.000004450863],"about_ca_topic_score_codex":0.011137967,"about_ca_topic_score_gemma":0.014751327,"teacher_disagreement_score":0.011137967,"about_ca_system_score_codex":0.00043780828,"about_ca_system_score_gemma":0.00036191405,"threshold_uncertainty_score":0.022146285},"labels":[],"label_agreement":null},{"id":"W4292623168","doi":"10.1101/2022.08.20.22279023","title":"Brain microstructural changes and fatigue after COVID-19","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Corpus callosum; Medicine; White matter; Diffusion MRI; Fractional anisotropy; Fornix; Magnetic resonance imaging; Internal medicine; Inferior longitudinal fasciculus; Neuropsychology; Cardiology; Audiology; Cognition; Pathology; Psychiatry; Radiology","score_opus":0.11186541563252606,"score_gpt":0.40289117827494497,"score_spread":0.2910257626424189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292623168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995851,0.00015440176,0.000037348196,0.000012714672,0.0000032646972,0.0000050596504,0.00006357918,0.0000013097272,0.00013731413],"genre_scores_gemma":[0.99966633,0.000036509657,0.000026227845,0.000014203751,0.0000060840957,0.0000031336288,0.00014481126,5.67063e-7,0.00010217888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999043,0.000018272578,0.000010111963,0.000027630113,0.000012047735,0.000027594957],"domain_scores_gemma":[0.9996661,0.000039851202,0.00015497014,0.000018461053,0.000044597997,0.000076142955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018242052,0.00027451984,0.0003378219,0.00033683173,0.0003315829,0.00024633994,0.000113462556,0.00026648398,0.0010769998],"category_scores_gemma":[0.00046400333,0.00009411682,0.00021156922,0.00018046799,0.00022916165,0.0001791183,0.00024711763,0.00029627667,0.00013449027],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014075077,0.00011534262,0.9810002,0.00003841153,0.00007862188,0.002013776,0.00020443807,0.00007528793,0.010514602,0.000021894872,0.00012135136,0.004408551],"study_design_scores_gemma":[0.000008756519,0.0005204201,0.9975624,0.0000041563585,0.000011183098,0.0013124825,0.00009226593,0.000061425446,0.00032276995,0.000014950275,0.00008716306,0.000001941986],"about_ca_topic_score_codex":0.0013710016,"about_ca_topic_score_gemma":0.0014308698,"teacher_disagreement_score":0.0013710016,"about_ca_system_score_codex":0.00023006408,"about_ca_system_score_gemma":0.00010873639,"threshold_uncertainty_score":0.003602922},"labels":[],"label_agreement":null},{"id":"W4292641174","doi":"10.48550/arxiv.1504.01800","title":"A Multicomponent Approach to Nonrigid Registration of Diffusion Tensor\\n Images","year":2015,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Affine transformation; Diffusion MRI; Structure tensor; Tensor (intrinsic definition); Distortion (music); Image registration; Computer vision; Mutual information; Diffusion; Orientation (vector space); Artificial intelligence; Computer science; Mathematics; Image (mathematics); Geometry; Physics; Medicine","score_opus":0.22305616961517938,"score_gpt":0.27127235530929783,"score_spread":0.04821618569411845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292641174","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019151655,0.00016196909,0.9972568,0.00008177729,0.00003301915,0.00002631924,0.000015738493,0.0001297646,0.00037953505],"genre_scores_gemma":[0.06439308,0.00059232925,0.93198264,0.00012584325,0.0001037282,0.00011163628,0.00012728709,0.00016782613,0.0023955042],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998505,0.0002617162,0.000109686676,0.0003989297,0.0006633343,0.000061403785],"domain_scores_gemma":[0.9992772,0.00013613606,0.00012417891,0.00028042286,0.00013883978,0.000043297732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011425115,0.000857122,0.00085651374,0.00183044,0.0006274879,0.0017406084,0.001564,0.00097266346,0.0016275259],"category_scores_gemma":[0.0026276945,0.0006312143,0.0013563132,0.001453132,0.0011131533,0.0018463192,0.0026161366,0.0013427486,0.000918177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001260114,0.00011945036,0.000656367,0.0003600809,0.00018043898,0.0004605448,0.00043315245,0.098466724,0.14477475,0.074623935,0.0026163687,0.67718214],"study_design_scores_gemma":[0.000017873932,0.00020174732,0.0012140411,0.000042125073,0.000059160953,0.0011930623,0.00007019108,0.8621031,0.06765601,0.049955033,0.017359657,0.00012794667],"about_ca_topic_score_codex":0.0011550027,"about_ca_topic_score_gemma":0.0018668487,"teacher_disagreement_score":0.00183044,"about_ca_system_score_codex":0.00052409456,"about_ca_system_score_gemma":0.0010663845,"threshold_uncertainty_score":0.0060423017},"labels":[],"label_agreement":null},{"id":"W4292641265","doi":"10.1007/s00429-022-02551-5","title":"The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography","year":2022,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Angular gyrus; Neuroscience; Microdissection; Tractography; Diffusion MRI; Anatomy; Psychology; Brainstem; Posterior parietal cortex; Biology; Medicine; Functional magnetic resonance imaging; Magnetic resonance imaging","score_opus":0.011173589145117246,"score_gpt":0.2782518399114742,"score_spread":0.26707825076635694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292641265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99085474,0.0007643041,0.006599127,0.00010142949,0.000005520427,0.000008787057,0.00015475356,0.000031496304,0.0014798424],"genre_scores_gemma":[0.9959661,0.00036857682,0.0029430576,0.000012778415,0.0000072156467,0.000007535111,0.000081368635,0.000008353439,0.0006050646],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999961,0.000007503147,0.0000018664292,0.000015761016,0.0000081271,0.0000056482563],"domain_scores_gemma":[0.99987555,0.000057071346,0.000034822962,0.000011266366,0.000012041462,0.000009299828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011529429,0.00010725205,0.000072588526,0.00051899115,0.00020538588,0.00029955205,0.000108738466,0.00013552932,0.0010016465],"category_scores_gemma":[0.0007365506,0.00011106099,0.00006305494,0.00045265857,0.00044835877,0.00039533185,0.00015592985,0.000120083794,0.00016659034],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011316742,0.000043989752,0.06025407,0.00017547824,0.00011895983,0.00090687914,0.0015879117,0.0031468356,0.8400419,0.0070867036,0.00059140654,0.08491422],"study_design_scores_gemma":[0.000044791956,0.00027281532,0.907402,0.000022840411,0.00009210727,0.0035797427,0.00057142973,0.009182346,0.06799795,0.006156393,0.0046438016,0.000033842516],"about_ca_topic_score_codex":0.006432712,"about_ca_topic_score_gemma":0.009238964,"teacher_disagreement_score":0.006432712,"about_ca_system_score_codex":0.00019056571,"about_ca_system_score_gemma":0.00028219435,"threshold_uncertainty_score":0.012790561},"labels":[],"label_agreement":null},{"id":"W4292801117","doi":"10.1101/2022.08.20.504656","title":"Is adiposity associated with white-matter microstructural health and intelligence differently in men and women?","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Obesity; Medicine; Cardiovascular health; Association (psychology); Physiology; Internal medicine; Psychology; Disease; Magnetic resonance imaging","score_opus":0.027059186536733584,"score_gpt":0.28264055320521936,"score_spread":0.2555813666684858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292801117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935487,0.0026049248,0.00039358012,0.0007035994,0.00009848037,0.0000064996793,0.0005396052,0.000013174906,0.0020915815],"genre_scores_gemma":[0.99854636,0.0004297785,0.000088627574,0.0001495186,0.00008355986,0.0000052725395,0.00013762758,0.000007807312,0.0005514977],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976224,0.00004745775,0.000016172145,0.000099012184,0.00002697588,0.000048198755],"domain_scores_gemma":[0.9994728,0.00013055051,0.00019688188,0.000078393714,0.0000330249,0.0000884373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006006469,0.000269593,0.00038395426,0.00059840863,0.00026717543,0.000865179,0.0002049891,0.00044118692,0.0034678897],"category_scores_gemma":[0.002319931,0.00021778849,0.00037685194,0.0006498815,0.00048199395,0.0003976689,0.00027314006,0.000424584,0.00049260876],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094790815,0.000052686075,0.98122495,0.000054016356,0.0003674671,0.00031758257,0.00084770186,0.00004655178,0.002336786,0.00047052815,0.00071208604,0.012621658],"study_design_scores_gemma":[0.000008107102,0.000068287816,0.99810374,0.000014932887,0.000061059814,0.00020589991,0.0003385976,0.000067632966,0.00012743022,0.0005004229,0.0004979723,0.0000059065082],"about_ca_topic_score_codex":0.0021417679,"about_ca_topic_score_gemma":0.0019786544,"teacher_disagreement_score":0.0034678897,"about_ca_system_score_codex":0.000097223536,"about_ca_system_score_gemma":0.00013929722,"threshold_uncertainty_score":0.011601269},"labels":[],"label_agreement":null},{"id":"W4293085811","doi":"10.32920/19400750","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Orientation (vector space); Metric (unit); Linear regression; Diffusion; Tensor (intrinsic definition); Dispersion (optics); SIGNAL (programming language); Diffusion imaging; Biological system; Anisotropic diffusion; Nuclear magnetic resonance; Materials science; Physics; Statistical physics; Mathematics; Optics; Computer science; Statistics; Magnetic resonance imaging; Geometry; Medicine; Radiology; Biology","score_opus":0.07503130547690681,"score_gpt":0.4057850943838871,"score_spread":0.33075378890698026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293085811","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021449283,0.00009481197,0.9963749,0.00011842707,0.000015303234,0.000024198702,0.00008473511,0.00041089015,0.0007319082],"genre_scores_gemma":[0.050785705,0.0004991097,0.93946177,0.00013944905,0.000091522554,0.00023352075,0.00048577372,0.00079952914,0.0075035538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99959403,0.00011692266,0.000018320574,0.000084963,0.00015197179,0.000033855107],"domain_scores_gemma":[0.99948597,0.00022970805,0.000084715066,0.000055205797,0.00012282388,0.000021536998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011526154,0.0013338405,0.00066693145,0.0005577397,0.00021262992,0.00078843866,0.0011155476,0.0009894567,0.0037458548],"category_scores_gemma":[0.0021889315,0.00055312464,0.0007508522,0.00069864874,0.0005245046,0.0012291354,0.00089487736,0.0015867339,0.0018511246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017692016,0.00013783656,0.0005686124,0.0003370077,0.0002108135,0.00033526256,0.00013811472,0.5982505,0.085945584,0.10524804,0.011424625,0.1972267],"study_design_scores_gemma":[0.000009410983,0.00003518642,0.000104172126,0.000007651308,0.0000139965105,0.00006333845,0.0000056281574,0.9827124,0.005988104,0.00653539,0.004508533,0.00001619708],"about_ca_topic_score_codex":0.00235527,"about_ca_topic_score_gemma":0.0036253505,"teacher_disagreement_score":0.0037458548,"about_ca_system_score_codex":0.0005344111,"about_ca_system_score_gemma":0.0012459921,"threshold_uncertainty_score":0.012531102},"labels":[],"label_agreement":null},{"id":"W4293228443","doi":"10.3917/pls.533.0062","title":"Matière noire : la piste de la gravité modifiée passe un test crucial","year":2022,"lang":"fr","type":"article","venue":"Pour la Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Political science","score_opus":0.02845197219609951,"score_gpt":0.3509279306608677,"score_spread":0.3224759584647682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293228443","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14022645,0.01847427,0.3756952,0.29200095,0.042084932,0.00030180078,0.0023003859,0.0037023297,0.1252137],"genre_scores_gemma":[0.8175773,0.0045523383,0.07675584,0.01930154,0.022135349,0.0005597579,0.0010894065,0.001677733,0.05635073],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941103,0.0014860878,0.00028774803,0.001972222,0.0018189792,0.00032467235],"domain_scores_gemma":[0.9599415,0.027193708,0.0019332437,0.004433237,0.0051706927,0.001327602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012230631,0.0023977377,0.0028219258,0.0013937723,0.0017948886,0.0052404227,0.0029609746,0.0055608964,0.028179403],"category_scores_gemma":[0.09344121,0.00042317677,0.0027349554,0.0007968472,0.006928808,0.011867315,0.0036369993,0.008346365,0.0075509455],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021646118,0.00022729035,0.009324571,0.00091210374,0.0008167933,0.0013147959,0.0011202462,0.0058843982,0.0068524857,0.73174965,0.07158618,0.16804679],"study_design_scores_gemma":[0.00042875225,0.0006219085,0.019671137,0.0006888671,0.00034689903,0.0016236339,0.00067093753,0.04032457,0.009853799,0.8126359,0.11282481,0.00030878815],"about_ca_topic_score_codex":0.0067957877,"about_ca_topic_score_gemma":0.0015903943,"teacher_disagreement_score":0.028179403,"about_ca_system_score_codex":0.0016857432,"about_ca_system_score_gemma":0.0037197622,"threshold_uncertainty_score":0.094269514},"labels":[],"label_agreement":null},{"id":"W4293516794","doi":"10.1016/j.neuro.2022.08.010","title":"Impact of chronic exposure to legacy environmental contaminants on the corpus callosum microstructure: A diffusion MRI study of Inuit adolescents","year":2022,"lang":"en","type":"article","venue":"NeuroToxicology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval; Centre hospitalier de l'Université Laval; Université du Québec à Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"National Institute of Environmental Health Sciences; Canadian Institutes of Health Research","keywords":"Corpus callosum; Fractional anisotropy; White matter; Diffusion MRI; Methylmercury; Medicine; Physiology; Population; Magnetic resonance imaging; Internal medicine; Pathology; Environmental health; Chemistry; Environmental chemistry; Bioaccumulation; Radiology","score_opus":0.02814817612175857,"score_gpt":0.3256252322540136,"score_spread":0.297477056132255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293516794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998348,0.000036631714,0.00001419447,0.0000083856785,5.102814e-7,0.0000015384803,0.000017275222,4.026734e-7,0.00008623659],"genre_scores_gemma":[0.9997043,0.000067944646,0.00003924497,0.000008365351,0.000001242596,0.0000023104603,0.000024973302,0.0000011726075,0.00015038095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992895,0.000009838776,0.0000037506143,0.0000267487,0.00001021893,0.000020454794],"domain_scores_gemma":[0.9998264,0.00002882648,0.000056542893,0.000010236803,0.00003532541,0.00004282699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001555709,0.00022445402,0.0002591506,0.000293358,0.00053528894,0.0005768577,0.00025394518,0.0003763974,0.00065538206],"category_scores_gemma":[0.00048070142,0.00020617562,0.00014991558,0.0003467324,0.00049548893,0.00030999753,0.00034588837,0.00033051046,0.00006517891],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065343955,0.00054674706,0.9644819,0.000073697964,0.00013016982,0.0041407067,0.00491101,0.000108153814,0.017896686,0.00025588716,0.00013138646,0.0066702557],"study_design_scores_gemma":[0.0000029318694,0.0002543058,0.9963691,0.000005867501,0.000049207367,0.00087030826,0.0015707924,0.000121546305,0.0005244963,0.000031926236,0.00019586325,0.0000035885034],"about_ca_topic_score_codex":0.05068344,"about_ca_topic_score_gemma":0.07352874,"teacher_disagreement_score":0.94931656,"about_ca_system_score_codex":0.0005616043,"about_ca_system_score_gemma":0.00059152796,"threshold_uncertainty_score":0.10077685},"labels":[],"label_agreement":null},{"id":"W4293660702","doi":"10.1016/j.nicl.2022.103174","title":"Exploring biomarkers of processing speed and executive function: The role of the anterior thalamic radiations","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Vancouver Coastal Health; University of British Columbia","funders":"Canadian Institutes of Health Research; University of British Columbia","keywords":"Diffusion MRI; Executive dysfunction; White matter; Hyperintensity; Stroke (engine); Psychology; Medicine; Trail Making Test; Superior longitudinal fasciculus; Lesion; Cognition; Neuroscience; Physical medicine and rehabilitation; Fractional anisotropy; Magnetic resonance imaging; Pathology; Cognitive impairment; Neuropsychology; Radiology","score_opus":0.18443924449726584,"score_gpt":0.38463418022909,"score_spread":0.20019493573182418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293660702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995937,0.0012151476,0.0017757948,0.000109221524,0.0000043026457,0.000013140268,0.0003201797,0.000018611578,0.0006066589],"genre_scores_gemma":[0.9982645,0.00032922166,0.0010261441,0.000016995038,0.0000076210963,0.000007754197,0.00016920926,0.0000022287365,0.00017639251],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986684,0.00005101946,0.000013117459,0.000032588647,0.000024540435,0.000011917971],"domain_scores_gemma":[0.99925226,0.00021651197,0.00033011328,0.00005930284,0.00008867432,0.00005314747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007793479,0.00065372116,0.00035014725,0.00060310925,0.00013881073,0.0008894235,0.0002931715,0.00024544785,0.001163863],"category_scores_gemma":[0.0022591206,0.00010271637,0.00036967525,0.0005482268,0.0002865179,0.000412589,0.0002893142,0.00022688496,0.00013670119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031783147,0.000060709546,0.95038164,0.00019354436,0.00070869917,0.00015245199,0.00026781124,0.002190603,0.0065655885,0.00024700814,0.00017408555,0.038740017],"study_design_scores_gemma":[0.000009714134,0.00028579557,0.9932573,0.00004319821,0.00016489501,0.0003143038,0.00013460881,0.0036267426,0.0010389306,0.0007766814,0.00033741444,0.00001040932],"about_ca_topic_score_codex":0.0068407287,"about_ca_topic_score_gemma":0.008205412,"teacher_disagreement_score":0.0068407287,"about_ca_system_score_codex":0.00026255002,"about_ca_system_score_gemma":0.0004858067,"threshold_uncertainty_score":0.01360184},"labels":[],"label_agreement":null},{"id":"W4294189365","doi":"10.1192/j.eurpsy.2022.429","title":"A multicentric multimodal in vivo microscopy MRI study of bipolar disorder reveals axonal loss and demyelination","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Ontario Brain Institute","funders":"","keywords":"Cingulum (brain); White matter; Corpus callosum; Splenium; Uncinate fasciculus; Inferior longitudinal fasciculus; Magnetic resonance imaging; Tractography; Arcuate fasciculus; Myelin; Medicine; Superior longitudinal fasciculus; Anatomy; Fornix; Neuroscience; Pathology; Fractional anisotropy; Psychology; Central nervous system; Radiology; Hippocampus","score_opus":0.019438719799737627,"score_gpt":0.3273875229278142,"score_spread":0.3079488031280766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294189365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993844,0.00011970945,0.00023711855,0.000009433791,0.0000014499757,0.0000078947305,0.00003763328,0.000003916559,0.00019849026],"genre_scores_gemma":[0.9992969,0.000084096915,0.00040967978,0.000008453703,0.000005162148,0.0000059627923,0.000057468354,0.0000018890016,0.0001304388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999374,0.000012431128,0.0000062565787,0.000019913748,0.0000085299735,0.000015477694],"domain_scores_gemma":[0.9999058,0.000012598537,0.000036406644,0.000009447016,0.0000134150005,0.000022305614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019394465,0.00028160497,0.00018081264,0.000765118,0.00033364657,0.00017902387,0.000079902486,0.00020532969,0.0010577479],"category_scores_gemma":[0.00030741552,0.00019081973,0.00010589648,0.00023503718,0.00016671207,0.00012032334,0.00019877353,0.000079885875,0.00017604127],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019941856,0.0001589357,0.7674892,0.00012755675,0.00023270599,0.006634009,0.0010361685,0.0005459324,0.18958567,0.00015864403,0.00040588068,0.031631175],"study_design_scores_gemma":[0.000018567252,0.0003215272,0.99212587,0.000007872103,0.000036179365,0.0052360888,0.00013205748,0.00038927433,0.0014762434,0.0000489539,0.00020241408,0.0000048903157],"about_ca_topic_score_codex":0.0021155896,"about_ca_topic_score_gemma":0.00339918,"teacher_disagreement_score":0.0021155896,"about_ca_system_score_codex":0.00018033398,"about_ca_system_score_gemma":0.000121922516,"threshold_uncertainty_score":0.004206598},"labels":[],"label_agreement":null},{"id":"W4294199809","doi":"10.1192/j.eurpsy.2022.251","title":"White matter microstructure associated with the range of attentional and impulsive performance in school-aged children","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"","keywords":"Impulsivity; Psychology; Neurocognitive; White matter; Endophenotype; Neuroimaging; Cognition; Neuroscience; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.009093180430131595,"score_gpt":0.24474063660160772,"score_spread":0.23564745617147612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294199809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99804604,0.00031417861,0.00017337821,0.000042512926,0.0000034913444,0.0000076559945,0.00093491166,0.000018043454,0.00045979535],"genre_scores_gemma":[0.99775547,0.00016209444,0.0004952298,0.000023617158,0.000006469688,0.000018761968,0.0007842009,0.000014958431,0.0007392584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974495,0.000018951341,0.000031618256,0.00011945197,0.000039362916,0.00004577322],"domain_scores_gemma":[0.999323,0.00007583822,0.00038048215,0.000048694557,0.00008413809,0.00008785859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003989911,0.00062698516,0.00033530346,0.0017805286,0.00047490842,0.0009874499,0.00035839394,0.0005403025,0.0050079413],"category_scores_gemma":[0.0010545227,0.00036071124,0.000394913,0.000929157,0.0005842274,0.0004877434,0.00071897433,0.00041176527,0.00043900518],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027863972,0.000067770634,0.9866318,0.00007121271,0.000118752454,0.00093620113,0.0005398281,0.00018891862,0.0045360974,0.00019537803,0.00042023897,0.006015104],"study_design_scores_gemma":[0.0000025176253,0.000027850712,0.9985623,0.00001578715,0.000027727534,0.0006234746,0.00016260282,0.0000736776,0.0002854416,0.00007781313,0.00013745925,0.0000033193091],"about_ca_topic_score_codex":0.013505918,"about_ca_topic_score_gemma":0.015994873,"teacher_disagreement_score":0.013505918,"about_ca_system_score_codex":0.000543736,"about_ca_system_score_gemma":0.00050286466,"threshold_uncertainty_score":0.026854575},"labels":[],"label_agreement":null},{"id":"W4294200726","doi":"10.1192/j.eurpsy.2022.555","title":"The effect of antidepressant treatment on white matter integrity in Major Depression","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Institut universitaire en santé mentale de Montréal","funders":"Pfizer Canada; Pfizer","keywords":"Fasciculus; White matter; Inferior longitudinal fasciculus; Fractional anisotropy; Uncinate fasciculus; Corpus callosum; Superior longitudinal fasciculus; Diffusion MRI; Major depressive disorder; Medicine; Medial longitudinal fasciculus; Depression (economics); Psychology; Internal medicine; Magnetic resonance imaging; Cardiology; Neuroscience; Radiology; Central nervous system","score_opus":0.021723174116192047,"score_gpt":0.3239204356339096,"score_spread":0.30219726151771753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294200726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99741226,0.0019199905,0.000034329198,0.00005173805,0.0000067549217,0.000015614458,0.000115497765,0.0000045760867,0.0004392616],"genre_scores_gemma":[0.99901175,0.00050497125,0.00013147597,0.000039401362,0.000011404398,0.000010472322,0.00011920578,8.705717e-7,0.00017037134],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998054,0.000105819636,0.000021400907,0.000021559996,0.000025704121,0.000020043737],"domain_scores_gemma":[0.9996909,0.00008927987,0.00013581809,0.00001651313,0.000020659198,0.000046807752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047132798,0.00014255631,0.00032461408,0.00016236395,0.000084147476,0.00014774123,0.00009815479,0.00021154643,0.0011088595],"category_scores_gemma":[0.0007076963,0.00006254799,0.00021731369,0.00009868656,0.000108052656,0.0000784536,0.0000816252,0.00012956977,0.00013592989],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.04854805,0.0011769072,0.64815557,0.00080108875,0.0017969565,0.0007120856,0.00019750373,0.00068141025,0.09790247,0.00007788962,0.0009844622,0.19896553],"study_design_scores_gemma":[0.00019010539,0.006426511,0.9909623,0.000022485403,0.0001674546,0.00034610974,0.000022737788,0.00013027045,0.0014051502,0.000022228696,0.00030173868,0.0000029015598],"about_ca_topic_score_codex":0.0004958402,"about_ca_topic_score_gemma":0.0010510851,"teacher_disagreement_score":0.0011088595,"about_ca_system_score_codex":0.00014026274,"about_ca_system_score_gemma":0.00006655785,"threshold_uncertainty_score":0.003709495},"labels":[],"label_agreement":null},{"id":"W4294308349","doi":"10.3390/life12091362","title":"Associations of Peak-Width Skeletonized Mean Diffusivity and Post-Stroke Cognition","year":2022,"lang":"en","type":"article","venue":"Life","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Edinburgh Imaging; Biotechnology and Biological Sciences Research Council; College of Medicine and Veterinary Medicine, University of Edinburgh; Medical Research Council; UK Dementia Research Institute; Fondation Leducq; University of Edinburgh; Economic and Social Research Council; Stroke Association; Scottish Funding Council; Dunhill Medical Trust; Wellcome Trust; Alzheimer's Society; Edinburgh and Lothians Health Foundation; British Heart Foundation; Mrs Gladys Row Fogo Charitable Trust; Alzheimer’s Society; Wellcome","keywords":"Montreal Cognitive Assessment; Stroke (engine); Cognition; Cognitive decline; Medicine; Internal medicine; Effects of sleep deprivation on cognitive performance; Physical therapy; Psychology; Cardiology; Cognitive impairment; Dementia; Psychiatry; Disease","score_opus":0.04974978913352166,"score_gpt":0.3303395844695595,"score_spread":0.28058979533603784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294308349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990094,0.0003007772,0.00006827037,0.000029068387,0.0000033245533,0.0000033047336,0.00033137598,0.0000045808533,0.00024984364],"genre_scores_gemma":[0.99927145,0.00009806905,0.00006450728,0.000009202219,0.000007887201,0.000004396676,0.00034213276,0.0000016476044,0.00020074927],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996457,0.00007029267,0.000055489007,0.00010573828,0.000050812516,0.00007192585],"domain_scores_gemma":[0.9981665,0.0003437969,0.0008186434,0.00019610359,0.00025204584,0.00022289282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008252044,0.00031275296,0.0004852016,0.0006693572,0.00035057493,0.0006788174,0.0003357993,0.0004829602,0.0014361351],"category_scores_gemma":[0.0030036045,0.00019500976,0.0005438013,0.0007091698,0.00022399951,0.0003941741,0.0004237217,0.0006211598,0.00016582645],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027590853,0.000037253583,0.9977035,0.000010306502,0.00026837623,0.00003995739,0.000043245505,0.00006172736,0.0001569925,0.0000178403,0.000057650803,0.0013272241],"study_design_scores_gemma":[0.0000020941611,0.00004077499,0.99976486,0.0000010339716,0.000022957402,0.00003880479,0.000012229639,0.00005781726,0.000021449547,0.000016482743,0.000020239924,0.0000012585083],"about_ca_topic_score_codex":0.009523961,"about_ca_topic_score_gemma":0.014676462,"teacher_disagreement_score":0.009523961,"about_ca_system_score_codex":0.0003391241,"about_ca_system_score_gemma":0.00039181256,"threshold_uncertainty_score":0.018937051},"labels":[],"label_agreement":null},{"id":"W4294718699","doi":"10.1016/j.ynirp.2022.100126","title":"Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study","year":2022,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College","funders":"Medical Research Council; Wellcome Trust","keywords":"Fractional anisotropy; Apolipoprotein E; Cingulum (brain); White matter; Psychology; Internal medicine; Medicine; Disease","score_opus":0.036526208518974874,"score_gpt":0.3096968281929188,"score_spread":0.27317061967394396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294718699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992411,0.0000674716,0.00024054448,0.000014945942,0.0000068947224,0.000057915408,0.0002022673,0.0000064617902,0.00016248775],"genre_scores_gemma":[0.99806076,0.000046962585,0.00062909495,0.000044031098,0.00001259817,0.0000991715,0.0003889969,0.0000109553785,0.0007074694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995485,0.00010463943,0.000049560946,0.00017698223,0.00005768013,0.000062600026],"domain_scores_gemma":[0.9980319,0.00022317668,0.00033390702,0.00090706965,0.00032529855,0.00017855904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021797805,0.00084215304,0.00054298324,0.0005271804,0.0010250009,0.0005270218,0.00060431845,0.0007199833,0.0016640313],"category_scores_gemma":[0.0032800434,0.0003766436,0.00076458196,0.00037834546,0.0007394778,0.00065306324,0.00056357944,0.000678679,0.0006410048],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00892876,0.0027982462,0.9045277,0.0002463307,0.0011612143,0.0027650958,0.009308427,0.00015215453,0.050267354,0.00038864085,0.0013471857,0.01810878],"study_design_scores_gemma":[0.00019469194,0.0019861553,0.9934083,0.000010303535,0.00021850613,0.00088040635,0.0007471409,0.00012916561,0.0011593727,0.00015227195,0.0010989122,0.000014778035],"about_ca_topic_score_codex":0.009816387,"about_ca_topic_score_gemma":0.009628067,"teacher_disagreement_score":0.009816387,"about_ca_system_score_codex":0.00041804003,"about_ca_system_score_gemma":0.00038965215,"threshold_uncertainty_score":0.019518495},"labels":[],"label_agreement":null},{"id":"W4294739485","doi":"10.1016/j.neuroimage.2022.119617","title":"A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Brain atlas; Atlas (anatomy); Myelin; Neuroscience; Retinotopy; Neuroimaging; Cortex (anatomy); Biology; Cartography; Brain mapping; White matter; Computer science; Anatomy; Magnetic resonance imaging; Medicine; Visual cortex; Geography; Central nervous system","score_opus":0.07721935417495718,"score_gpt":0.3325616364907312,"score_spread":0.25534228231577405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294739485","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023197202,0.00074078125,0.91307867,0.00043765825,0.0002518279,0.00030273866,0.020513158,0.032168537,0.009309328],"genre_scores_gemma":[0.13873619,0.0017456979,0.8120299,0.00029655715,0.0001101679,0.0010735053,0.01960913,0.014820145,0.011578703],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997236,0.00004277165,0.000029197787,0.00006556922,0.0001111084,0.000027703765],"domain_scores_gemma":[0.99959034,0.00013543299,0.00005916544,0.00007749719,0.00010223505,0.000035261306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006962486,0.00090054667,0.00054386375,0.0022744387,0.00048056166,0.0024042972,0.00086966826,0.0008503327,0.021070728],"category_scores_gemma":[0.0019045097,0.00076385186,0.00094046385,0.0015542227,0.00047722476,0.0009949313,0.0015100733,0.0012200983,0.0066436674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006546074,0.00012166026,0.011109921,0.0020786938,0.00041199333,0.001331869,0.0019440514,0.04703757,0.103786774,0.03869478,0.17103669,0.62179136],"study_design_scores_gemma":[0.00014279771,0.00037114453,0.04099765,0.00062969414,0.00038980442,0.007396409,0.00060820516,0.20563126,0.093511105,0.06190137,0.5880248,0.000395828],"about_ca_topic_score_codex":0.0037801187,"about_ca_topic_score_gemma":0.008315232,"teacher_disagreement_score":0.021070728,"about_ca_system_score_codex":0.0005032991,"about_ca_system_score_gemma":0.0017101518,"threshold_uncertainty_score":0.07048857},"labels":[],"label_agreement":null},{"id":"W4294897416","doi":"10.1089/neu.2022.0276","title":"White Matter Integrity Relates to Cognition in Service Members and Veterans after Complicated Mild, Moderate, and Severe Traumatic Brain Injury, But Not Uncomplicated Mild Traumatic Brain Injury","year":2022,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Traumatic brain injury; Fractional anisotropy; White matter; Diffusion MRI; Neuropsychology; Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Uncinate fasciculus; Cognition; Post-concussion syndrome; Medicine; Poison control; Audiology; Neuroscience; Concussion; Psychiatry; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.13366667320116277,"score_gpt":0.3737104255208235,"score_spread":0.24004375231966074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294897416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99983823,0.000031644522,0.000006515586,0.0000104998935,0.0000013428102,0.0000011051998,0.000016951748,4.8500067e-7,0.00009317257],"genre_scores_gemma":[0.9998074,0.000032102984,0.000014265749,0.0000068364957,0.000003714015,0.0000012948155,0.00006313245,5.0456026e-7,0.00007084456],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980694,0.000033630986,0.00002204674,0.000039582264,0.00004031187,0.000057571597],"domain_scores_gemma":[0.9990125,0.000071018214,0.0005627867,0.000048049977,0.00009013316,0.00021546277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032973656,0.00031571218,0.0002706556,0.00084059895,0.00059068337,0.00058763847,0.00024189659,0.00032837852,0.0012361811],"category_scores_gemma":[0.0026834463,0.00015985385,0.00023880684,0.0006821605,0.00045876292,0.00036656403,0.00067040033,0.0004235935,0.00018544293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016865045,0.000055380133,0.99665916,0.0000055921014,0.000036124075,0.000068923204,0.0005634491,0.000034367557,0.00028344637,0.000018707622,0.00005714381,0.0020490894],"study_design_scores_gemma":[0.00000151417,0.000101727856,0.9990957,0.0000029433374,0.0000064518663,0.00011451027,0.0005263907,0.00005283423,0.0000346422,0.00002444264,0.000036911893,0.000001878261],"about_ca_topic_score_codex":0.013699654,"about_ca_topic_score_gemma":0.022548683,"teacher_disagreement_score":0.013699654,"about_ca_system_score_codex":0.00047089267,"about_ca_system_score_gemma":0.00035069342,"threshold_uncertainty_score":0.0272398},"labels":[],"label_agreement":null},{"id":"W4295129670","doi":"10.1016/j.compbiomed.2022.106078","title":"Atlas-guided parcellation: Individualized functionally-homogenous parcellation in cerebral cortex","year":2022,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sport Centre Pacific; University of British Columbia","funders":"National Natural Science Foundation of China; Cyrus Tang Foundation","keywords":"Voxel; Artificial intelligence; Homogeneity (statistics); Pattern recognition (psychology); Functional magnetic resonance imaging; Correlation; Computer science; Resting state fMRI; Neuroimaging; Brain atlas; Functional connectivity; Default mode network; Psychology; Neuroscience; Machine learning; Mathematics","score_opus":0.07038896253105667,"score_gpt":0.3744579412408374,"score_spread":0.3040689787097808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295129670","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01832413,0.00045467576,0.97255707,0.00028178658,0.000078040786,0.0001047373,0.00079771527,0.0058985488,0.0015033599],"genre_scores_gemma":[0.21595204,0.0008648745,0.77389354,0.00033239395,0.00017228344,0.00045544247,0.002175522,0.0030306939,0.0031231344],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994475,0.00010244031,0.000023891214,0.00014319808,0.00016997021,0.000112839625],"domain_scores_gemma":[0.99918944,0.0002895908,0.00007501588,0.00020448276,0.00017648525,0.00006492963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010580951,0.0012804271,0.0012417117,0.0014374651,0.0008539586,0.0026176672,0.0014701063,0.0012722968,0.004431257],"category_scores_gemma":[0.0035115534,0.0006741812,0.0013008956,0.002524214,0.00064743345,0.0013541095,0.0022402862,0.0014840681,0.0023083482],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009180655,0.00013956803,0.0035539668,0.00039838484,0.0002978667,0.00039925313,0.001276284,0.06944844,0.13582003,0.013479005,0.024404118,0.74986494],"study_design_scores_gemma":[0.000105890256,0.0001868038,0.010246366,0.00004753279,0.00027497817,0.0010085668,0.0005352327,0.78653085,0.1304895,0.03789426,0.032511786,0.00016824473],"about_ca_topic_score_codex":0.009295761,"about_ca_topic_score_gemma":0.014987502,"teacher_disagreement_score":0.009295761,"about_ca_system_score_codex":0.00096478104,"about_ca_system_score_gemma":0.002293063,"threshold_uncertainty_score":0.018483281},"labels":[],"label_agreement":null},{"id":"W4295367041","doi":"10.1002/hbm.26064","title":"<scp>Test–retest</scp> reliability of diffusion tensor imaging scalars in 5‐year‐olds","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Varsinais-Suomen Rahasto; Varsinais-Suomen Sairaanhoitopiiri; Suomen Aivosäätiö; Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Juho Vainion Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Sigrid Juséliuksen Säätiö; Suomen Lääketieteen Säätiö","keywords":"Fractional anisotropy; Diffusion MRI; Repeatability; Intraclass correlation; Psychology; Reliability (semiconductor); Population; Statistics; Mathematics; Nuclear medicine; Reproducibility; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.04213064672382869,"score_gpt":0.3199502017890604,"score_spread":0.2778195550652317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295367041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835687,0.00069032464,0.0073564365,0.00012620937,0.00009557113,0.00016454198,0.002632654,0.00021585116,0.005149792],"genre_scores_gemma":[0.991975,0.0000750157,0.004623239,0.00005966412,0.000026261014,0.0001758947,0.002241193,0.000099322344,0.00072442315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954892,0.0010102581,0.0009405557,0.00089425675,0.0014235842,0.00024216916],"domain_scores_gemma":[0.9735771,0.013686488,0.0030004112,0.003887263,0.0055040573,0.00034474058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0117670195,0.0004135662,0.0005556401,0.0015688236,0.00055421254,0.00088356895,0.0006409599,0.0006475488,0.002733343],"category_scores_gemma":[0.027921068,0.00026861572,0.00091924536,0.0007997375,0.00092593965,0.0005484808,0.00079696416,0.00065318,0.00078715757],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010841019,0.00016312886,0.9060003,0.00044350803,0.001360463,0.0009807813,0.0058309045,0.0016845205,0.016835662,0.001062119,0.0078688655,0.05668569],"study_design_scores_gemma":[0.0000117414875,0.00011626101,0.9949399,0.00002829937,0.000054972887,0.0002255389,0.00015597582,0.0006822048,0.001686862,0.00015008549,0.0019312626,0.000016877293],"about_ca_topic_score_codex":0.0069488515,"about_ca_topic_score_gemma":0.010924955,"teacher_disagreement_score":0.0117670195,"about_ca_system_score_codex":0.00042068868,"about_ca_system_score_gemma":0.00048303572,"threshold_uncertainty_score":0.062230647},"labels":[],"label_agreement":null},{"id":"W4295709252","doi":"10.1016/j.nicl.2022.103201","title":"The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Temporal lobe; White matter; Epilepsy; Diffusion MRI; Uncinate fasciculus; Anatomy; Cortex (anatomy); Magnetic resonance imaging; Nuclear magnetic resonance; Pathology; Neuroscience; Fractional anisotropy; Medicine; Psychology; Physics; Radiology","score_opus":0.06548771072459326,"score_gpt":0.3982843438262933,"score_spread":0.33279663310170005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295709252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99900085,0.00033833648,0.00027718148,0.000022197884,0.0000018698761,0.0000046089776,0.000024140107,0.0000028397417,0.0003280114],"genre_scores_gemma":[0.9994814,0.0001874324,0.00019276512,0.000006110921,0.0000044832523,0.0000019240017,0.000030744275,0.000001688811,0.00009343131],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999298,0.00001348136,0.000011114271,0.000017274326,0.00001646458,0.000011873126],"domain_scores_gemma":[0.99967885,0.00007194101,0.00013336111,0.0000272578,0.000050924904,0.000037683443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035512462,0.00031243407,0.00018894259,0.00076054735,0.0001959611,0.00033745446,0.00011499729,0.00020862452,0.0009730254],"category_scores_gemma":[0.00092843705,0.00012224591,0.00013599769,0.00027254852,0.0004494928,0.0005046957,0.0002564469,0.00011968197,0.00020239578],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029136967,0.00014869506,0.70518064,0.0002510523,0.00021647345,0.008239291,0.0018953657,0.00059400534,0.23955105,0.00035351908,0.00015049489,0.040505752],"study_design_scores_gemma":[0.000029433615,0.0006783824,0.98063904,0.000013592527,0.000078615274,0.010507625,0.0005693552,0.0010967782,0.005580501,0.00023324546,0.0005585522,0.000014938467],"about_ca_topic_score_codex":0.0014151131,"about_ca_topic_score_gemma":0.0016156473,"teacher_disagreement_score":0.0014151131,"about_ca_system_score_codex":0.0001582333,"about_ca_system_score_gemma":0.00018162164,"threshold_uncertainty_score":0.0032550693},"labels":[],"label_agreement":null},{"id":"W4295747743","doi":"10.1007/978-3-031-16431-6_20","title":"Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression","year":2022,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Computer science; Normative; Bayesian probability; Diffusion MRI; Artificial intelligence; Regression; Tensor (intrinsic definition); Diffusion; Multilevel model; Pattern recognition (psychology); Data mining; Algorithm; Machine learning; Statistics; Mathematics; Magnetic resonance imaging","score_opus":0.06032372092394443,"score_gpt":0.35846170821556356,"score_spread":0.2981379872916191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295747743","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011455808,0.00011494443,0.9870803,0.00018459595,0.000022072507,0.00004812397,0.00016648123,0.00034688902,0.00058070984],"genre_scores_gemma":[0.53911126,0.0008363597,0.44643942,0.00020308717,0.00013863694,0.00075349543,0.0022308943,0.0010728748,0.009213949],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961371,0.0019341166,0.00018447015,0.00090986054,0.0006133274,0.00022122572],"domain_scores_gemma":[0.9804505,0.012149824,0.0017252248,0.0018664395,0.0033342305,0.00047377512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012119096,0.0015737871,0.0024332139,0.0024528052,0.0010405484,0.0028340858,0.0050072805,0.0031070965,0.003118951],"category_scores_gemma":[0.041901458,0.002512614,0.0020976798,0.0021745088,0.0024019661,0.0050821416,0.0027423552,0.0038710125,0.0012295827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011153527,0.00013410016,0.003153597,0.00011964346,0.00014955731,0.0001924545,0.00034057905,0.8308005,0.0014473802,0.1253164,0.0020013524,0.03623299],"study_design_scores_gemma":[0.000004697488,0.000009977888,0.00025887767,0.000010644181,0.000010591809,0.000024839925,0.000010416606,0.97589976,0.0001678787,0.023292068,0.00029425943,0.000015828748],"about_ca_topic_score_codex":0.024784913,"about_ca_topic_score_gemma":0.030766776,"teacher_disagreement_score":0.024784913,"about_ca_system_score_codex":0.0020641899,"about_ca_system_score_gemma":0.0035070197,"threshold_uncertainty_score":0.064092696},"labels":[],"label_agreement":null},{"id":"W4295993249","doi":"10.1016/j.neuroimage.2022.119600","title":"Bundle-o-graphy: improving structural connectivity estimation with adaptive microstructure-informed tractography","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Discriminative model; Computer science; Artificial intelligence; Bundle; Diffusion MRI; Bayes' theorem; Ground truth; Human Connectome Project; Fiber bundle; Pattern recognition (psychology); Generative model; Probabilistic logic; Bayesian probability; Representation (politics); Generative grammar; Machine learning; Magnetic resonance imaging; Neuroscience; Functional connectivity; Psychology","score_opus":0.03406274172665822,"score_gpt":0.31311198960471576,"score_spread":0.2790492478780575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295993249","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005009473,0.00009209298,0.99409467,0.00006147177,0.000008791776,0.000016861282,0.000026529151,0.0005423924,0.0001477424],"genre_scores_gemma":[0.17481534,0.00031999775,0.8223344,0.00012205953,0.000054556338,0.000092372036,0.00035762464,0.00060255534,0.0013011032],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994592,0.00020963799,0.000019666932,0.0001151425,0.00014959807,0.000046737765],"domain_scores_gemma":[0.99878687,0.000598263,0.00016784853,0.00023939706,0.0001292256,0.00007841032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012591106,0.0011472355,0.0011938706,0.0012243645,0.00047195834,0.0007760445,0.001667849,0.0016775165,0.0015750516],"category_scores_gemma":[0.0047046174,0.00060323684,0.0010469027,0.0013516092,0.0010220195,0.0015779381,0.0017552058,0.001552124,0.000691504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012341468,0.000075532014,0.0014265865,0.0001274093,0.00013354316,0.00018479483,0.0002004596,0.7053249,0.014116987,0.014295222,0.0030047912,0.26098633],"study_design_scores_gemma":[0.000010407788,0.000025915891,0.00016199611,0.000004438526,0.0000076051533,0.00005307873,0.0000069141174,0.9901342,0.001519083,0.0072245095,0.0008433252,0.000008508388],"about_ca_topic_score_codex":0.0058668344,"about_ca_topic_score_gemma":0.00819838,"teacher_disagreement_score":0.0058668344,"about_ca_system_score_codex":0.0004808772,"about_ca_system_score_gemma":0.0013581663,"threshold_uncertainty_score":0.011665344},"labels":[],"label_agreement":null},{"id":"W4296485917","doi":"10.26034/cortica.2022.3137","title":"Sex differences and symptom based gray and white matter densities in schizophrenia","year":2022,"lang":"en","type":"article","venue":"Cortica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Institute of Gender and Health; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"White matter; Frontal lobe; Superior frontal gyrus; Cerebellum; Voxel; Psychology; Gyrus; Gray (unit); Audiology; Parietal lobe; Anatomy; Medicine; Magnetic resonance imaging; Neuroscience; Nuclear medicine; Radiology; Cognition","score_opus":0.02989271862009877,"score_gpt":0.2875582029222318,"score_spread":0.257665484302133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296485917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99964786,0.00012671776,0.000028192053,0.000008744542,0.0000013395605,8.9298584e-7,0.000065653214,0.0000014864579,0.00011906472],"genre_scores_gemma":[0.9996712,0.00008782494,0.000037808175,0.0000059266376,0.000002072643,0.0000015770332,0.00007724763,0.0000015985744,0.00011489016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994373,0.000011107739,0.000008328354,0.000014773142,0.000013338074,0.00000866672],"domain_scores_gemma":[0.9997284,0.000045826884,0.00015288802,0.000014025039,0.000017815208,0.000041055613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013273035,0.00020965228,0.00015212351,0.0006215598,0.00013192242,0.00019956884,0.00007483759,0.00016050051,0.0015624297],"category_scores_gemma":[0.000535588,0.0001269136,0.00012306051,0.00025896708,0.00019041459,0.00015264442,0.00019876308,0.000118864795,0.00015223307],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089527963,0.000037905524,0.9661763,0.000033106997,0.00012096104,0.00075169123,0.00048413774,0.00008165385,0.023139471,0.00007883346,0.00006374345,0.0081369495],"study_design_scores_gemma":[0.0000046409364,0.000087889726,0.99883384,0.0000020563396,0.000011077404,0.0005883216,0.00007402427,0.000045610246,0.0002539749,0.000035394252,0.00006125133,0.0000019510703],"about_ca_topic_score_codex":0.000943827,"about_ca_topic_score_gemma":0.0014555196,"teacher_disagreement_score":0.0015624297,"about_ca_system_score_codex":0.00009543284,"about_ca_system_score_gemma":0.000075392505,"threshold_uncertainty_score":0.005226791},"labels":[],"label_agreement":null},{"id":"W4296618322","doi":"10.1002/jnr.25126","title":"Altered neurovascular coupling in thyroid‐associated ophthalmopathy: A combined resting‐state <scp>fMRI</scp> and arterial spin labeling study","year":2022,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cerebral blood flow; Neurovascular bundle; Cardiology; Medicine; Functional magnetic resonance imaging; Resting state fMRI; Internal medicine; Magnetic resonance imaging; Precuneus; Neuroscience; Psychology; Anatomy; Radiology","score_opus":0.17298659590854634,"score_gpt":0.43993548916888753,"score_spread":0.2669488932603412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296618322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99952435,0.00007886628,0.0002289551,0.000010796601,9.85821e-7,0.000005475428,0.0000155423,0.0000031962238,0.00013189416],"genre_scores_gemma":[0.99966455,0.000040133218,0.00021495916,0.000010259059,0.0000052542114,0.0000047715516,0.00002383795,0.000001127229,0.00003515667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999132,0.000019067027,0.000008953196,0.000027351694,0.000015750451,0.000015629685],"domain_scores_gemma":[0.9998197,0.00004982318,0.000046287805,0.000021508306,0.00002557116,0.00003716653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036126788,0.00025702163,0.00022747435,0.0005215893,0.0002788324,0.0002573171,0.00014617557,0.00030147165,0.00048821233],"category_scores_gemma":[0.00054531766,0.0001775798,0.00019880742,0.00021644786,0.0003649893,0.000193601,0.00018546432,0.00020486464,0.000056496963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003564313,0.00039730888,0.6220291,0.00016549027,0.00047640863,0.012647881,0.0010158563,0.0004709634,0.3365317,0.00015473376,0.00019593956,0.0223502],"study_design_scores_gemma":[0.0000573837,0.0007251462,0.9831929,0.000007238558,0.00018650496,0.0077779326,0.00024705776,0.0016426225,0.0058485256,0.000131954,0.00016738569,0.000015292157],"about_ca_topic_score_codex":0.0022984124,"about_ca_topic_score_gemma":0.0028671136,"teacher_disagreement_score":0.0022984124,"about_ca_system_score_codex":0.00020052673,"about_ca_system_score_gemma":0.00015478476,"threshold_uncertainty_score":0.004570067},"labels":[],"label_agreement":null},{"id":"W4296663335","doi":"10.3389/fnimg.2022.917806","title":"DORIS: A diffusion MRI-based 10 tissue class deep learning segmentation algorithm tailored to improve anatomically-constrained tractography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; National Institute of Biomedical Imaging and Bioengineering; NIH Blueprint for Neuroscience Research; Alzheimer's Association; National Institute on Aging; National Institutes of Health; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; European Commission; Agence Nationale de la Recherche; Medical Research Council; McDonnell Center for Systems Neuroscience","keywords":"Tractography; Doris (gastropod); Diffusion MRI; Segmentation; Artificial intelligence; Computer science; Class (philosophy); Algorithm; Computer vision; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.012902484986013471,"score_gpt":0.29168088301827916,"score_spread":0.2787783980322657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296663335","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022483276,0.00082679826,0.95687145,0.00049029104,0.00016463896,0.00025297288,0.0011802741,0.014761555,0.0029687926],"genre_scores_gemma":[0.10226223,0.0004975338,0.87793577,0.00075196614,0.00008480079,0.0005218627,0.005531442,0.0015396697,0.010874712],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946016,0.000068303205,0.000035631405,0.00019179868,0.00017446889,0.000069678994],"domain_scores_gemma":[0.99950886,0.00015454243,0.00006560954,0.00007438649,0.00015524603,0.0000413038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012491435,0.0017241908,0.0014789342,0.0016612025,0.0006453109,0.0011124897,0.0029550847,0.0018269435,0.0036766063],"category_scores_gemma":[0.0022744646,0.0007516798,0.0015688608,0.0010941379,0.000631784,0.0012350484,0.001943533,0.0021539778,0.0021654973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039655928,0.00020576127,0.002806051,0.00035761812,0.00040083335,0.00021574786,0.00018453276,0.16650683,0.025370594,0.010619669,0.030765247,0.7621705],"study_design_scores_gemma":[0.00010798655,0.00012263397,0.0009747026,0.00003603325,0.000056493856,0.00025222075,0.00002934521,0.9592076,0.01837088,0.0074094245,0.01339348,0.000039224997],"about_ca_topic_score_codex":0.0072922455,"about_ca_topic_score_gemma":0.01624954,"teacher_disagreement_score":0.0072922455,"about_ca_system_score_codex":0.001816012,"about_ca_system_score_gemma":0.0020716498,"threshold_uncertainty_score":0.014499605},"labels":[],"label_agreement":null},{"id":"W4297461623","doi":"10.1007/s10072-022-06408-x","title":"The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study","year":2022,"lang":"en","type":"article","venue":"Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cingulum (brain); Neuroradiology; Neurology; Cognitive impairment; Kurtosis; Medicine; Diffusion MRI; Neurosurgery; Cognition; Psychology; Radiology; Magnetic resonance imaging; Psychiatry; Fractional anisotropy","score_opus":0.024239557699782158,"score_gpt":0.3122071600327727,"score_spread":0.28796760233299057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297461623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993369,0.00031218035,0.000051255945,0.000021095184,0.00000391033,0.0000062027357,0.00006397176,0.0000022960153,0.00020216305],"genre_scores_gemma":[0.9996197,0.000099461766,0.00007699366,0.000010073553,0.000012823641,0.0000047679214,0.000098686716,8.1268405e-7,0.00007664429],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987733,0.000017283453,0.000020724347,0.000035167508,0.00002659534,0.000022866569],"domain_scores_gemma":[0.99951017,0.0000418401,0.00029974934,0.000027476066,0.00005962964,0.000061213126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021633315,0.0004047372,0.0003049056,0.00091062987,0.00039782494,0.00040060896,0.00019127422,0.00031287552,0.0013015096],"category_scores_gemma":[0.0010840074,0.00019134901,0.00026223384,0.000503885,0.00023978103,0.00027143344,0.000252657,0.00021968344,0.00017351867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045672254,0.000062757295,0.99095976,0.000037438476,0.00011980907,0.0012444659,0.00013346193,0.00006083887,0.0029366666,0.00003248257,0.00011475922,0.0038407901],"study_design_scores_gemma":[0.000009780755,0.0001159274,0.9977647,0.00000584769,0.000038229056,0.0014755309,0.000082667815,0.00014401595,0.00018888361,0.00003120802,0.00013889972,0.0000042142638],"about_ca_topic_score_codex":0.0018074405,"about_ca_topic_score_gemma":0.002821444,"teacher_disagreement_score":0.0018074405,"about_ca_system_score_codex":0.00016509803,"about_ca_system_score_gemma":0.00020476153,"threshold_uncertainty_score":0.0043539405},"labels":[],"label_agreement":null},{"id":"W4297822196","doi":"10.21203/rs.3.rs-2022169/v1","title":"Electrostimulation of the white matter of the posterior insula and medial operculum: perception of vibrations, heat, and pain","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Institut National de la Santé et de la Recherche Médicale","keywords":"Insula; Operculum (bryozoa); Somatosensory system; White matter; Sensory system; Medicine; Parietal lobe; Sensation; Hypoalgesia; Anatomy; Psychology; Audiology; Neuroscience; Magnetic resonance imaging; Radiology; Nociception; Hyperalgesia; Biology","score_opus":0.06407759378008372,"score_gpt":0.41256655149382077,"score_spread":0.34848895771373706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297822196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9855363,0.0013335728,0.007970169,0.00037037875,0.00008938987,0.000041791158,0.0001730318,0.000059419755,0.0044258707],"genre_scores_gemma":[0.9950046,0.0006491939,0.0019422083,0.000081976345,0.000054950513,0.00004076898,0.00006443645,0.000018639323,0.0021433167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99995863,0.000008562129,0.0000016600516,0.00001026057,0.000009923626,0.000010967255],"domain_scores_gemma":[0.99990726,0.000059781247,0.000012613271,0.0000049008904,0.000004115566,0.00001129311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001229689,0.00028833363,0.00011804171,0.00014071594,0.00012117054,0.00024255477,0.00017240233,0.0002861221,0.0040222835],"category_scores_gemma":[0.00042889192,0.000115045324,0.00012379789,0.00017130427,0.00040287484,0.0002601728,0.00022045267,0.00030632105,0.00013665533],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003705961,0.00016123687,0.0019972757,0.00017573865,0.00008570186,0.00063966296,0.00020000912,0.00075506803,0.9467372,0.0016091405,0.0006721686,0.043260887],"study_design_scores_gemma":[0.00080414006,0.0027455767,0.467754,0.00009249476,0.00028245125,0.002866551,0.000993272,0.01949727,0.47789007,0.02101381,0.006015877,0.00004448044],"about_ca_topic_score_codex":0.0008354811,"about_ca_topic_score_gemma":0.0012044648,"teacher_disagreement_score":0.0040222835,"about_ca_system_score_codex":0.00013689685,"about_ca_system_score_gemma":0.00019690077,"threshold_uncertainty_score":0.013455808},"labels":[],"label_agreement":null},{"id":"W4297911674","doi":"10.1016/j.neuroimage.2022.119644","title":"Increased myelination plays a central role in white matter neuroplasticity","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; Fraser Health; University of Calgary; University of Victoria; University of British Columbia; Surrey Memorial Hospital; Simon Fraser University","funders":"","keywords":"Diffusion MRI; White matter; Neuroplasticity; Neuroscience; Myelin; Central nervous system; Tractography; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.024190274219737764,"score_gpt":0.28991659301385425,"score_spread":0.2657263187941165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297911674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901598,0.0032024654,0.0054087127,0.00007055798,0.000009649639,0.000014583741,0.0000612051,0.00005862307,0.0010144515],"genre_scores_gemma":[0.99568164,0.0012181045,0.0026855443,0.000018758663,0.000009951683,0.000013595749,0.000026755859,0.0000080407235,0.00033755708],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99984574,0.00003521533,0.000015009236,0.000042811604,0.00003840525,0.000022831611],"domain_scores_gemma":[0.999548,0.00010284287,0.00022620198,0.00003797026,0.000049813105,0.00003517635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051582267,0.00037920955,0.0003164731,0.0006025528,0.0001902275,0.00039843447,0.00015265156,0.00029719385,0.0007459934],"category_scores_gemma":[0.00092879357,0.00012277557,0.00015898375,0.0003375066,0.0007609751,0.0005907521,0.00032059918,0.00032418882,0.000135996],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007985251,0.000071280985,0.018471489,0.00028178253,0.000070651586,0.00028574516,0.0002085711,0.0004908178,0.9591725,0.00076655485,0.00007914911,0.019302834],"study_design_scores_gemma":[0.000025529944,0.0020555973,0.46139276,0.000060319027,0.0001321131,0.002179084,0.00037088877,0.0030992418,0.5261577,0.002900953,0.0016049624,0.000020915593],"about_ca_topic_score_codex":0.00057744305,"about_ca_topic_score_gemma":0.00051486486,"teacher_disagreement_score":0.0007459934,"about_ca_system_score_codex":0.00020630934,"about_ca_system_score_gemma":0.00022395294,"threshold_uncertainty_score":0.0027279258},"labels":[],"label_agreement":null},{"id":"W4297963061","doi":"10.1101/2022.09.29.510004","title":"Sensitivity of diffusion-tensor and correlated diffusion imaging to white-matter microstructural abnormalities: application in COVID-19","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Waterloo; University of Toronto; Baycrest Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Coronavirus disease 2019 (COVID-19); Diffusion; Fractional anisotropy; Tractography; Medicine; Nuclear magnetic resonance; Diffusion imaging; Magnetic resonance imaging; Nuclear medicine; Physics; Radiology; Pathology","score_opus":0.01685869738868113,"score_gpt":0.2796618620612028,"score_spread":0.2628031646725217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297963061","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98121554,0.00067153084,0.0175307,0.000060262755,0.000013386367,0.000035874236,0.00015151182,0.000086786975,0.00023435257],"genre_scores_gemma":[0.9920597,0.00020180462,0.007475087,0.000014712819,0.0000050444155,0.000013251689,0.00013018977,0.000017216704,0.00008298095],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99964845,0.00014487815,0.00002884841,0.0000880089,0.00006137078,0.000028481605],"domain_scores_gemma":[0.9985349,0.0006844534,0.00036577886,0.00016125302,0.00017744263,0.00007615398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012338932,0.0006326465,0.00057954155,0.00065599446,0.0002379838,0.00053072954,0.0003341196,0.00053106406,0.0005698167],"category_scores_gemma":[0.0041882894,0.00034250022,0.0005842474,0.00037961322,0.00036315928,0.0005072895,0.0007311615,0.00041492417,0.00009896173],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037720827,0.00039592205,0.20295785,0.00077416346,0.001086279,0.0014758206,0.0005455524,0.1783963,0.55601895,0.0008805856,0.00045384504,0.05324255],"study_design_scores_gemma":[0.000075262746,0.0012251718,0.1548795,0.00008265791,0.0002747384,0.0021481183,0.00021583063,0.6485767,0.19022016,0.001397099,0.0007748123,0.00012987839],"about_ca_topic_score_codex":0.0030132858,"about_ca_topic_score_gemma":0.0022209648,"teacher_disagreement_score":0.0030132858,"about_ca_system_score_codex":0.00033556504,"about_ca_system_score_gemma":0.00027005273,"threshold_uncertainty_score":0.0065255165},"labels":[],"label_agreement":null},{"id":"W4298142118","doi":"10.3389/fnana.2022.894606","title":"Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Segmentation; Computer science; Artificial intelligence; Neuroanatomy; Neuroimaging; Software; Image segmentation; Pattern recognition (psychology); Computer vision; Neuroscience; Psychology","score_opus":0.030732867687438735,"score_gpt":0.34200946561814477,"score_spread":0.31127659793070606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298142118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0035174158,0.0012223584,0.98693687,0.0004782143,0.0001838294,0.00013727293,0.00079141476,0.005258477,0.0014741892],"genre_scores_gemma":[0.034638584,0.0025032908,0.94809663,0.00065412297,0.0002963255,0.00057248224,0.0062241107,0.0045743706,0.0024401294],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99440056,0.0011589028,0.0005869461,0.0016875966,0.0019246453,0.00024139918],"domain_scores_gemma":[0.9856023,0.004818371,0.0011807678,0.0051885326,0.0027488202,0.0004611807],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.007937345,0.0016403393,0.001846453,0.00461604,0.0014775314,0.0050701154,0.0053721126,0.0034302478,0.0043427693],"category_scores_gemma":[0.01870289,0.0017507026,0.0025833321,0.0035460065,0.0027889884,0.003866172,0.0051075006,0.0035344837,0.0050582127],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000294597,0.00027238185,0.0031721015,0.002566675,0.00054879993,0.001143955,0.0013319144,0.047231793,0.13721913,0.04804289,0.051241167,0.7069345],"study_design_scores_gemma":[0.0001327458,0.00035246988,0.012131098,0.0013404589,0.00032215158,0.0044816006,0.0005991993,0.30014908,0.15197757,0.17911243,0.3488135,0.0005877661],"about_ca_topic_score_codex":0.0037284652,"about_ca_topic_score_gemma":0.0062461374,"teacher_disagreement_score":0.9946279,"about_ca_system_score_codex":0.0013981921,"about_ca_system_score_gemma":0.004081172,"threshold_uncertainty_score":0.041977167},"labels":[],"label_agreement":null},{"id":"W4299506631","doi":"10.17615/ncz1-ak18","title":"Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Brain Science Foundation","keywords":"Tractography; Diffusion MRI; Nuclear magnetic resonance; Cluster analysis; Magnetic resonance imaging; Medicine; Computer science; Physics; Artificial intelligence; Radiology","score_opus":0.1799741018889793,"score_gpt":0.37187285938033854,"score_spread":0.19189875749135923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299506631","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5487888,0.0009443355,0.44651017,0.00013921152,0.000086613836,0.00027925608,0.0004472667,0.0010533768,0.0017509187],"genre_scores_gemma":[0.82229936,0.00017078748,0.17630948,0.000020819312,0.000042845506,0.00013987461,0.0003841282,0.00017990425,0.00045281724],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9963953,0.0010655748,0.00037613386,0.00081639976,0.0012143764,0.00013211425],"domain_scores_gemma":[0.9841101,0.0064231483,0.0028751353,0.0017474602,0.0045741103,0.0002699671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008975494,0.0007886171,0.0005966258,0.0030945248,0.0006671409,0.001353323,0.0007472464,0.0009161116,0.0007221981],"category_scores_gemma":[0.02474628,0.00036849373,0.00061650254,0.001416831,0.00090138364,0.0010351056,0.0009694997,0.0004985896,0.00030549744],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002084123,0.0002217634,0.1985583,0.0017233372,0.0022943923,0.0007497238,0.0041323765,0.06628785,0.3616188,0.0055550276,0.0020397163,0.3547346],"study_design_scores_gemma":[0.00014543935,0.0014021269,0.41521597,0.00025988722,0.00062632974,0.0032384184,0.0008163093,0.47153533,0.095252216,0.005895543,0.005119673,0.0004927592],"about_ca_topic_score_codex":0.0037809787,"about_ca_topic_score_gemma":0.0038479061,"teacher_disagreement_score":0.008975494,"about_ca_system_score_codex":0.00058833085,"about_ca_system_score_gemma":0.00064993167,"threshold_uncertainty_score":0.04746753},"labels":[],"label_agreement":null},{"id":"W4302027680","doi":"10.1002/mrm.29473","title":"Tuned bipolar oscillating gradients for mapping frequency dispersion of diffusion kurtosis in the human brain","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund","keywords":"Kurtosis; Dispersion (optics); Thermal diffusivity; Diffusion; Oscillation (cell signaling); Nuclear magnetic resonance; Biological system; Diffusion MRI; Chemistry; Computational physics; Acoustics; Physics; Optics; Mathematics; Magnetic resonance imaging; Statistics; Thermodynamics","score_opus":0.06187219147033289,"score_gpt":0.3443169510520472,"score_spread":0.2824447595817143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302027680","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7091466,0.003745556,0.28397515,0.00028377358,0.000074164134,0.0001876221,0.00018000988,0.00037551788,0.002031578],"genre_scores_gemma":[0.8819355,0.0014785824,0.115640044,0.00011848308,0.000031874904,0.000110857094,0.00007833651,0.00005413956,0.00055216136],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999967,0.000010875109,0.0000022096988,0.000007546371,0.000009519912,0.0000028564066],"domain_scores_gemma":[0.9999281,0.000027577908,0.000020532329,0.0000047816256,0.000010224263,0.000008815698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018021882,0.00027177553,0.00009428488,0.0001995209,0.000095147785,0.00021055757,0.0001713701,0.00025749256,0.00050439173],"category_scores_gemma":[0.00073791825,0.00012696952,0.000060012044,0.000105581195,0.00021635502,0.00021015282,0.0001542214,0.00014133626,0.00008482883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031617167,0.000038020593,0.0013736038,0.0002205761,0.000020305766,0.0002043514,0.000051491334,0.0058793626,0.9440913,0.0010044676,0.00035777505,0.046442714],"study_design_scores_gemma":[0.00031244283,0.0031701417,0.03448347,0.00020033398,0.00022858009,0.0049833106,0.00015963003,0.18129012,0.7582894,0.008138333,0.008609695,0.00013454868],"about_ca_topic_score_codex":0.00049226865,"about_ca_topic_score_gemma":0.000959959,"teacher_disagreement_score":0.00050439173,"about_ca_system_score_codex":0.00011119155,"about_ca_system_score_gemma":0.00017360605,"threshold_uncertainty_score":0.0016874075},"labels":[],"label_agreement":null},{"id":"W4302363019","doi":"10.1016/j.neuron.2022.09.011","title":"Prefrontal-habenular microstructural impairments in human cocaine and heroin addiction","year":2022,"lang":"en","type":"article","venue":"Neuron","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; Canadian Institutes of Health Research; Icahn School of Medicine at Mount Sinai; Harvard Medical School","keywords":"Addiction; Prefrontal cortex; Neuroscience; Cocaine dependence; Psychology; Habenula; Human brain; Heroin; Neuroimaging; Psychiatry; Drug; Cognition; Central nervous system","score_opus":0.028194442079618052,"score_gpt":0.3241973988713929,"score_spread":0.2960029567917748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302363019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99868387,0.0003185169,0.000289666,0.00004792477,0.0000025044033,0.000005996452,0.00006788293,0.000004592293,0.00057903427],"genre_scores_gemma":[0.99886864,0.00026064806,0.0002660189,0.000014196343,0.0000016660202,0.000004555608,0.000039158127,0.0000033383367,0.00054178934],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999685,0.000007020364,0.000001758576,0.000008190037,0.0000072086136,0.0000072695457],"domain_scores_gemma":[0.99989426,0.000020125339,0.00003975927,0.000015500484,0.000009804192,0.000020516874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019009132,0.00018151465,0.00013064778,0.0004674737,0.00031510176,0.00023591483,0.00019442492,0.00023187892,0.0025272376],"category_scores_gemma":[0.0002682633,0.00017898512,0.000079562844,0.00019138806,0.00062106544,0.00028457245,0.00030689104,0.00023593035,0.00012580198],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005677895,0.00066263264,0.33329448,0.00042926593,0.0006315321,0.008924,0.0013394932,0.002938273,0.5760614,0.0051757754,0.0009266019,0.06393856],"study_design_scores_gemma":[0.00001999653,0.00014754513,0.9854418,0.000013897291,0.00004999884,0.0038919593,0.0003412541,0.0014486504,0.007151988,0.0010832268,0.00040122189,0.0000085605025],"about_ca_topic_score_codex":0.0064096884,"about_ca_topic_score_gemma":0.0196778,"teacher_disagreement_score":0.0064096884,"about_ca_system_score_codex":0.00033564024,"about_ca_system_score_gemma":0.00025772245,"threshold_uncertainty_score":0.012744725},"labels":[],"label_agreement":null},{"id":"W4303432678","doi":"10.1093/cercor/bhac329","title":"Difference in axon diameter and myelin thickness between excitatory and inhibitory callosally projecting axons in mice","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council; Canadian Institutes of Health Research; European Commission; Medical Research Council Canada; McGill University","keywords":"Excitatory postsynaptic potential; Inhibitory postsynaptic potential; Axon; Neuroscience; Myelin; Soma; Chemistry; Biophysics; Biology; Central nervous system","score_opus":0.058794826539761064,"score_gpt":0.3208896550543648,"score_spread":0.26209482851460375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4303432678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921476,0.00013792388,0.006622569,0.000052964508,0.000008483838,0.000011449726,0.00027991837,0.000114426795,0.0006246389],"genre_scores_gemma":[0.9863452,0.00028525054,0.011220611,0.00003441,0.0000028202433,0.00010044703,0.00032311963,0.00014087703,0.0015473296],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998598,0.000019031186,0.000011680555,0.000051073042,0.000030358286,0.000027944514],"domain_scores_gemma":[0.9995493,0.00011235982,0.0002082121,0.000025538564,0.000016568618,0.00008801831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020499731,0.00037449755,0.0002426915,0.00059467484,0.00023895646,0.00045461094,0.00058750325,0.0007381246,0.0010386133],"category_scores_gemma":[0.00047926456,0.00045574663,0.00035018212,0.00021350774,0.00059604726,0.0002946693,0.00047991532,0.0006667296,0.0001653687],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046990364,0.000090326525,0.0013270848,0.000050612136,0.000020462981,0.000116150026,0.000063895095,0.0101035,0.98393434,0.0018699954,0.000049445785,0.0019043953],"study_design_scores_gemma":[0.00026856328,0.0010317356,0.020026993,0.000055065022,0.0001411264,0.00043813683,0.00013480122,0.1045143,0.86784256,0.002941112,0.0025336856,0.00007183148],"about_ca_topic_score_codex":0.0016011335,"about_ca_topic_score_gemma":0.0016073587,"teacher_disagreement_score":0.0016011335,"about_ca_system_score_codex":0.0005888956,"about_ca_system_score_gemma":0.0004009536,"threshold_uncertainty_score":0.004272759},"labels":[],"label_agreement":null},{"id":"W4304118622","doi":"10.1038/s42003-022-03983-9","title":"Specific disruption of the ventral anterior temporo-frontal network reveals key implications for language comprehension and cognition","year":2022,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Social Fund; State Scholarships Foundation; Hellenic Foundation for Research and Innovation; European Commission","keywords":"Cognition; Middle temporal gyrus; Lesion; Neuroscience; Internal capsule; Angular gyrus; Frontal lobe; Anterior cingulate cortex; Psychology; Prefrontal cortex; Inferior frontal gyrus; Diffusion MRI; Middle frontal gyrus; Comprehension; White matter; Medicine; Pathology; Magnetic resonance imaging; Computer science; Radiology","score_opus":0.1049965279805815,"score_gpt":0.39294438898633793,"score_spread":0.2879478610057564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304118622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976324,0.00025325656,0.0009408155,0.00008930964,0.000004266319,0.0000056281483,0.000053305015,0.000021756849,0.0009992319],"genre_scores_gemma":[0.9993357,0.0001051172,0.00029974792,0.000017261527,0.000007036996,0.0000030395906,0.000036707796,0.0000035800244,0.00019184378],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999449,0.000005778409,0.000004710581,0.000018562749,0.0000102429585,0.000015735652],"domain_scores_gemma":[0.9998636,0.000041420168,0.000049802944,0.000014457329,0.000009496776,0.000021162092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006639955,0.00043120733,0.0001832589,0.00041832429,0.0003176496,0.00030538123,0.00014299618,0.00033931326,0.0023095522],"category_scores_gemma":[0.0005186924,0.00010255438,0.00013286584,0.00017350377,0.00083260686,0.00024723075,0.0002164881,0.00022718043,0.00025102016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014084186,0.00019948857,0.2698132,0.0001994376,0.00019054276,0.097771436,0.0019597344,0.0007029757,0.55421036,0.002046659,0.0007724183,0.07072527],"study_design_scores_gemma":[0.000042132997,0.00078120525,0.748193,0.000027428809,0.00018710522,0.19596356,0.000972202,0.0016473789,0.04795806,0.0023807108,0.0018184903,0.000028630648],"about_ca_topic_score_codex":0.0017242013,"about_ca_topic_score_gemma":0.003181423,"teacher_disagreement_score":0.0023095522,"about_ca_system_score_codex":0.00021672953,"about_ca_system_score_gemma":0.00026379508,"threshold_uncertainty_score":0.007726252},"labels":[],"label_agreement":null},{"id":"W4304481348","doi":"10.1002/hbm.26104","title":"Identification of central amygdala and trigeminal motor nucleus connectivity in humans: An <scp>ultra‐high</scp> field diffusion <scp>MRI</scp> study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Krembil Foundation; Mount Sinai Hospital; Centre for Social Innovation; University of Toronto; University Health Network; Discovery Centre","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; University of Toronto; Faculty of Dentistry, University of Toronto; Natural Sciences and Engineering Research Council of Canada; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Neuroscience; Connectome; Tractography; Amygdala; Nucleus; Brainstem; Central nucleus of the amygdala; Stria terminalis; Diffusion MRI; Biology; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity","score_opus":0.043829506699589335,"score_gpt":0.3251770234243049,"score_spread":0.28134751672471553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304481348","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913059,0.00083070213,0.0051902873,0.00019619675,0.0000079726415,0.00002855249,0.00040210108,0.000034244495,0.0020040756],"genre_scores_gemma":[0.99668723,0.00030924944,0.0021652372,0.00007533483,0.00001991282,0.000015669408,0.00031932088,0.000020474956,0.00038760508],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988675,0.000020777401,0.0000060752204,0.000053494045,0.000020705025,0.000012197886],"domain_scores_gemma":[0.99971014,0.00006561887,0.00009118084,0.000057153837,0.000041651976,0.00003417596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003153449,0.00016907541,0.00018817402,0.0004337187,0.00025698903,0.0003729691,0.00020849745,0.00038779076,0.0020005647],"category_scores_gemma":[0.0009356955,0.00022235869,0.00012951382,0.00023841963,0.00053289556,0.00040932314,0.00028453124,0.00021529134,0.0002873465],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012844839,0.00033764276,0.5944693,0.0005537272,0.0006912164,0.0087692365,0.0033053039,0.0021861752,0.22955361,0.0029662068,0.0068231737,0.14906],"study_design_scores_gemma":[0.000014984032,0.00017245208,0.98485976,0.000022069002,0.00005258358,0.006913666,0.00027387962,0.0022537007,0.0021755674,0.0009909349,0.0022535815,0.000016782536],"about_ca_topic_score_codex":0.0023165792,"about_ca_topic_score_gemma":0.005930594,"teacher_disagreement_score":0.0023165792,"about_ca_system_score_codex":0.00013260005,"about_ca_system_score_gemma":0.00019505681,"threshold_uncertainty_score":0.0066925883},"labels":[],"label_agreement":null},{"id":"W4304783064","doi":"10.1038/s41597-022-01695-7","title":"An analysis-ready and quality controlled resource for pediatric brain white-matter research","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Montréal; Institut Universitaire en Santé Mentale de Québec; Western University; Polytechnique Montréal; Concordia University; University of Toronto","funders":"Child Mind Institute; University of Pennsylvania; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Quality (philosophy); Computer science; Medicine; Physics","score_opus":0.3514407486686759,"score_gpt":0.5218421750821093,"score_spread":0.17040142641343337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304783064","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05154036,0.0024652416,0.37607276,0.005547233,0.0012535503,0.0065098368,0.4683323,0.068557896,0.01972077],"genre_scores_gemma":[0.09046646,0.0008645186,0.48309982,0.0011537786,0.0006028876,0.009598222,0.39452657,0.0149878245,0.0046999073],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9816243,0.0065564425,0.0026267932,0.0035908835,0.0047900253,0.0008114847],"domain_scores_gemma":[0.86573744,0.03759652,0.01082791,0.040171087,0.03704304,0.008624049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03401476,0.0013038141,0.0016690205,0.006849507,0.0016857866,0.0030016834,0.004588642,0.0012283683,0.030278595],"category_scores_gemma":[0.09993859,0.0011310385,0.0014880027,0.0062017976,0.0016375912,0.0035132992,0.00872908,0.002352397,0.019685507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004593239,0.0010785243,0.047526892,0.0033039688,0.00085574656,0.001583197,0.0022216982,0.0066134003,0.03577932,0.016229007,0.5712679,0.30894703],"study_design_scores_gemma":[0.0019431453,0.00080576405,0.07305292,0.0019194899,0.0006714873,0.001268965,0.000980023,0.024882717,0.063025735,0.025917284,0.8050598,0.0004726678],"about_ca_topic_score_codex":0.0094089275,"about_ca_topic_score_gemma":0.013223936,"teacher_disagreement_score":0.03401476,"about_ca_system_score_codex":0.001992706,"about_ca_system_score_gemma":0.013449852,"threshold_uncertainty_score":0.17988938},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W4306173734","doi":"10.1016/j.neuroimage.2022.119684","title":"Mapping pontocerebellar connectivity with diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Concordia University","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada; McGill University; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Pons; Cerebellum; Neuroscience; Tractography; Diffusion MRI; Anatomy; Context (archaeology); Pontine nuclei; Psychology; Biology; Medicine; Magnetic resonance imaging","score_opus":0.04411292630631987,"score_gpt":0.30452868455082743,"score_spread":0.2604157582445076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306173734","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73275834,0.0006444157,0.2600509,0.00019247497,0.000017929273,0.0002704348,0.0011663998,0.00077713834,0.00412207],"genre_scores_gemma":[0.8566592,0.00085034553,0.14006512,0.000041047126,0.000018074874,0.00021270523,0.0007012565,0.0001817793,0.0012704952],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99984896,0.00002976814,0.00000725848,0.000059893428,0.000031114618,0.00002298707],"domain_scores_gemma":[0.9998178,0.0000683266,0.000051151128,0.000022541844,0.00002606007,0.0000141774535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040027895,0.00043323298,0.00019824468,0.0023448418,0.0002746633,0.0006409101,0.0003031037,0.00037103333,0.0017879913],"category_scores_gemma":[0.0012111692,0.00027387438,0.0002098783,0.00085059326,0.0004647993,0.0005410309,0.00031942246,0.0003756384,0.0002605608],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041337154,0.000112651265,0.03819675,0.00044381674,0.00024757118,0.0014262168,0.000658165,0.012107158,0.8008143,0.0073061683,0.0011874503,0.13708642],"study_design_scores_gemma":[0.00011072554,0.00056118733,0.5808184,0.00012680516,0.0002634394,0.008137276,0.0006605192,0.10953457,0.2677204,0.017936308,0.013990505,0.00013989187],"about_ca_topic_score_codex":0.008974371,"about_ca_topic_score_gemma":0.015534377,"teacher_disagreement_score":0.008974371,"about_ca_system_score_codex":0.00047305302,"about_ca_system_score_gemma":0.0006303311,"threshold_uncertainty_score":0.01784426},"labels":[],"label_agreement":null},{"id":"W4306176742","doi":"10.1002/jmri.28482","title":"Feasibility of <scp>MRI</scp> Quantification of Myelin Water Fraction in the Fetal Guinea Pig Brain","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children’s Health Research Institute; Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fetus; Myelin; Myelin basic protein; Medicine; White matter; Corpus callosum; Internal medicine; Coefficient of variation; Endocrinology; Pregnancy; Biology; Pathology; Magnetic resonance imaging; Central nervous system; Chemistry; Radiology","score_opus":0.05353232407632565,"score_gpt":0.34840714456400684,"score_spread":0.2948748204876812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306176742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8236195,0.002912407,0.16325244,0.0009254988,0.00017665255,0.000449659,0.0005766876,0.0011770657,0.006910175],"genre_scores_gemma":[0.9032352,0.0017875317,0.091469385,0.00035831388,0.000054160642,0.00039625456,0.0004281433,0.00016732095,0.0021037315],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99983525,0.000049663184,0.000007881678,0.000057105415,0.00003025257,0.0000198671],"domain_scores_gemma":[0.99950075,0.00017091604,0.00008553373,0.000085944856,0.00011656662,0.000040284463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011830138,0.00035216336,0.00016409562,0.0003518818,0.00013752567,0.0003693408,0.0004377592,0.0006760422,0.0019867218],"category_scores_gemma":[0.0009770003,0.00024070528,0.000151214,0.00008529891,0.00057553774,0.00042225703,0.00021633583,0.00045327644,0.00063965004],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000324373,0.00003272332,0.0015172978,0.00010897802,0.000010982043,0.00025352312,0.00003653782,0.00029149707,0.9800623,0.0003291802,0.00021845475,0.01681423],"study_design_scores_gemma":[0.00009139135,0.0036079513,0.026243292,0.00015376712,0.000108317014,0.0037634403,0.00013821282,0.009683546,0.94958425,0.00055570283,0.00603641,0.00003383503],"about_ca_topic_score_codex":0.0014926312,"about_ca_topic_score_gemma":0.00144915,"teacher_disagreement_score":0.0019867218,"about_ca_system_score_codex":0.0001952012,"about_ca_system_score_gemma":0.00032108524,"threshold_uncertainty_score":0.006646216},"labels":[],"label_agreement":null},{"id":"W4306931098","doi":"10.3233/atde220538","title":"Meridian Sinew Therapy for Cerebral Blood Flow and Brain Function in Sub-Healthy Individuals: A Study of ASL and rsfMRI","year":2022,"lang":"en","type":"book-chapter","venue":"Advances in transdisciplinary engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Traditional Chinese Medicine Bureau of Guangdong Province; Guangdong Science and Technology Department; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Cerebral blood flow; Medicine; Meridian (astronomy); Superior frontal gyrus; Acupuncture; Gyrus; Resting state fMRI; Montreal Cognitive Assessment; Frontal lobe; Cardiology; Physical therapy; Cognition; Functional magnetic resonance imaging; Cognitive impairment; Radiology; Pathology","score_opus":0.032346120394926334,"score_gpt":0.3186001702887488,"score_spread":0.28625404989382247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306931098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99838793,0.00087731273,0.00022797639,0.000041879022,0.0000069169055,0.000030286632,0.000013936282,0.0000029816497,0.00041069952],"genre_scores_gemma":[0.99878114,0.00036700565,0.00026034232,0.000058871345,0.000010414615,0.000027016238,0.000018108323,8.035838e-7,0.0004762453],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999367,0.000016291664,0.000004139103,0.000020699346,0.000011542476,0.000010564653],"domain_scores_gemma":[0.9999509,0.000008530486,0.000013986055,0.0000045248853,0.000008539302,0.000013474831],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001880759,0.000193434,0.00020606321,0.00016229306,0.00017574205,0.00012333447,0.0000795633,0.00023813768,0.0009524867],"category_scores_gemma":[0.00022964834,0.00006399772,0.00016013303,0.0000854685,0.00014711074,0.000120507066,0.000102978905,0.00014278351,0.00006266518],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018097255,0.009226343,0.30210763,0.0013688784,0.0010814699,0.0023527374,0.0030687908,0.00039383673,0.34354874,0.0005500061,0.0010648438,0.31713954],"study_design_scores_gemma":[0.00027099662,0.012029304,0.97934294,0.000028464561,0.0002506546,0.0007090375,0.00048835785,0.00065987883,0.0045329053,0.000192377,0.001481889,0.000013173238],"about_ca_topic_score_codex":0.00052709895,"about_ca_topic_score_gemma":0.0012901329,"teacher_disagreement_score":0.0009524867,"about_ca_system_score_codex":0.000101616264,"about_ca_system_score_gemma":0.00012465384,"threshold_uncertainty_score":0.003186345},"labels":[],"label_agreement":null},{"id":"W4307023621","doi":"10.1155/2022/5860364","title":"Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity","year":2022,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute; St Joseph's Health Care; Health Sciences Centre; Ottawa Hospital; Parkwood Institute; McMaster University; Thunder Bay Regional Research Institute; Queen's University; Public Health Ontario; Baycrest Hospital; Western University; University of Toronto; Sunnybrook Health Science Centre","funders":"Baycrest Foundation; London Health Sciences Foundation; Faculty of Health Sciences, Queen's University; Bruyère Research Institute; Centre for Addiction and Mental Health Foundation; McMaster University; Temerty Family Foundation; University of Ottawa; Ontario Brain Institute; Government of Ontario; Thunder Bay Regional Health Sciences Centre","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Medicine; Hyperintensity; Stroke (engine); Pathology; Magnetic resonance imaging; Radiology; Physics","score_opus":0.021862689021175837,"score_gpt":0.32708012986146767,"score_spread":0.30521744084029184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307023621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979851,0.0003802352,0.0006432006,0.000023692308,0.0000054363213,0.00001561151,0.00042089503,0.000015556374,0.000510239],"genre_scores_gemma":[0.99806124,0.00018694879,0.00092622347,0.000013349667,0.000008467328,0.00001479978,0.0005729789,0.0000069285043,0.00020909256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959594,0.00005455583,0.000063164436,0.000116396644,0.000114027716,0.00005596827],"domain_scores_gemma":[0.99858487,0.00018512901,0.0006265609,0.00013467291,0.0003130021,0.00015593544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010353338,0.00041408002,0.00038555072,0.0022726862,0.00031956745,0.00078369636,0.0002447538,0.00033828453,0.0006213244],"category_scores_gemma":[0.004037811,0.00017611228,0.00031169207,0.0011335431,0.00040640705,0.00049320003,0.0006047964,0.00025871932,0.00013737715],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035638205,0.00003464017,0.9751966,0.000088235676,0.0004901017,0.000140612,0.00040030168,0.00045831743,0.009846153,0.00013970242,0.00031990313,0.012529009],"study_design_scores_gemma":[0.0000042411093,0.00004395316,0.9983077,0.0000064366964,0.000034300265,0.00020184027,0.0000965434,0.0005523058,0.00047008693,0.00011205427,0.00016423527,0.0000062826034],"about_ca_topic_score_codex":0.016533045,"about_ca_topic_score_gemma":0.032567587,"teacher_disagreement_score":0.016533045,"about_ca_system_score_codex":0.00051771564,"about_ca_system_score_gemma":0.00048141216,"threshold_uncertainty_score":0.03287363},"labels":[],"label_agreement":null},{"id":"W4307114714","doi":"10.1111/jopy.12788","title":"Beyond the brain localization of complex traits: Distributed white matter markers of personality","year":2022,"lang":"en","type":"article","venue":"Journal of Personality","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; University of Oregon","keywords":"Neuroticism; Neuroimaging; Psychology; Big Five personality traits; Univariate; Personality; White matter; Facet (psychology); Diffusion MRI; Multivariate statistics; Cognitive psychology; Social psychology; Machine learning; Neuroscience; Magnetic resonance imaging; Computer science","score_opus":0.055804336765749675,"score_gpt":0.33999560487893665,"score_spread":0.28419126811318696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307114714","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989603,0.0001960264,0.009264817,0.00016166772,0.0000073887995,0.000015698757,0.0001066017,0.000024922767,0.0006199167],"genre_scores_gemma":[0.99837875,0.000035214263,0.0013911112,0.000015553873,0.000006005572,0.0000055503383,0.000045010493,0.000004063643,0.000118820724],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949574,0.00020682573,0.000023423856,0.00017814129,0.00006270151,0.000033134904],"domain_scores_gemma":[0.9949039,0.0022047951,0.0013909362,0.0009938118,0.0002475393,0.00025898044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022162336,0.00052384235,0.0003588526,0.00055246416,0.00030435927,0.00096091203,0.00041025225,0.00028739747,0.002322053],"category_scores_gemma":[0.007945241,0.00017764195,0.00031050097,0.00048329894,0.00085286045,0.00081890763,0.0007858737,0.00065856654,0.00017525259],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041440627,0.00016149167,0.91833025,0.00015439797,0.00053100556,0.000310721,0.0015563684,0.0041313227,0.017453868,0.0015342445,0.0004671747,0.054954782],"study_design_scores_gemma":[0.000019202127,0.00014513345,0.98057175,0.000037843358,0.00007634893,0.00033159813,0.00028281898,0.011589867,0.0018892632,0.004753511,0.00028954822,0.000013097823],"about_ca_topic_score_codex":0.0025004619,"about_ca_topic_score_gemma":0.004378462,"teacher_disagreement_score":0.0025004619,"about_ca_system_score_codex":0.00028562985,"about_ca_system_score_gemma":0.00045761402,"threshold_uncertainty_score":0.011720717},"labels":[],"label_agreement":null},{"id":"W4307340727","doi":"10.17116/jnevro202212210196","title":"Cerebral perfusion and tractography in obese children","year":2022,"lang":"en","type":"article","venue":"S S Korsakov Journal of Neurology and Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Fractional anisotropy; Raven's Progressive Matrices; Neuropsychological assessment; Tractography; Montreal Cognitive Assessment; Neuropsychology; Magnetic resonance imaging; Intelligence quotient; Audiology; Cognition; Psychiatry; Radiology; Cognitive impairment","score_opus":0.017065449582909144,"score_gpt":0.29665190567300537,"score_spread":0.27958645609009625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307340727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995142,0.00012085646,0.00007165044,0.000010072893,0.0000012806539,0.0000033269823,0.00010585411,0.0000032172682,0.00016947249],"genre_scores_gemma":[0.99917537,0.00018066999,0.00026056528,0.000010573192,0.0000052614555,0.000008657624,0.00020531914,0.0000034328687,0.00015022959],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999145,0.000014658516,0.000006613705,0.00002405454,0.000015837804,0.000024320847],"domain_scores_gemma":[0.99976426,0.000036967467,0.00011616948,0.000010166762,0.000026002866,0.000046448713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014501592,0.00029080725,0.00017097677,0.0010573625,0.00018785331,0.00019961508,0.00010022281,0.00026606763,0.0014844623],"category_scores_gemma":[0.0006740364,0.00017018126,0.00016468689,0.00040157346,0.00023777375,0.000201865,0.00016734339,0.00019865,0.0001804685],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024007463,0.00004709373,0.9843328,0.000033158634,0.000034592693,0.00420385,0.00019764202,0.0001275034,0.00614545,0.00004907787,0.000116803676,0.004472091],"study_design_scores_gemma":[0.00000861445,0.00014610717,0.9880235,0.000009044999,0.000018741333,0.010759165,0.00013516532,0.0001348477,0.00054595683,0.000019932246,0.00019569823,0.000003031218],"about_ca_topic_score_codex":0.0044421144,"about_ca_topic_score_gemma":0.0036910253,"teacher_disagreement_score":0.0044421144,"about_ca_system_score_codex":0.00015233428,"about_ca_system_score_gemma":0.00024247014,"threshold_uncertainty_score":0.008832514},"labels":[],"label_agreement":null},{"id":"W4307498148","doi":"10.1002/jmri.28424","title":"Intersession Repeatability of <scp>Diffusion‐Tensor</scp> Imaging in the Supraspinatus and the Infraspinatus Muscles of Volunteers","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec à Trois-Rivières; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Réseau en Bio-Imagerie du Quebec","keywords":"Fractional anisotropy; Diffusion MRI; Repeatability; Medicine; Nuclear medicine; Rotator cuff; Effective diffusion coefficient; Anatomy; Magnetic resonance imaging; Mathematics; Radiology","score_opus":0.017500954583511984,"score_gpt":0.29959514730501957,"score_spread":0.2820941927215076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307498148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979954,0.00018156902,0.0010560328,0.000014031898,0.000012859435,0.000028332755,0.0002715814,0.00003223238,0.00040807552],"genre_scores_gemma":[0.998971,0.000023383463,0.00041286356,0.0000097423535,0.000009899784,0.000025561398,0.0003433227,0.000011488366,0.0001927834],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990133,0.00032729618,0.00013327271,0.00030223274,0.00013997516,0.00008390451],"domain_scores_gemma":[0.99591345,0.0016110818,0.0007057097,0.0006407869,0.0008533475,0.00027562317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017608259,0.00022568755,0.00022387011,0.0003686938,0.00021326542,0.00031216047,0.00018940328,0.00041221807,0.0009705533],"category_scores_gemma":[0.007717898,0.00019262802,0.00016907591,0.0001704193,0.0003258422,0.0002190806,0.00029907012,0.00019497871,0.00033586286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005689,0.00031033615,0.8487211,0.00023448534,0.0005915268,0.0007316418,0.0021081443,0.00078110216,0.103807785,0.0001552457,0.0011366389,0.035733085],"study_design_scores_gemma":[0.000019945237,0.0007612015,0.99468994,0.000007941586,0.000052952157,0.0005679906,0.00012775113,0.0004796842,0.0028610234,0.000041518095,0.00037902163,0.000011139672],"about_ca_topic_score_codex":0.00096430327,"about_ca_topic_score_gemma":0.0013772643,"teacher_disagreement_score":0.0017608259,"about_ca_system_score_codex":0.000080036625,"about_ca_system_score_gemma":0.00012025063,"threshold_uncertainty_score":0.009312272},"labels":[],"label_agreement":null},{"id":"W4307658818","doi":"10.1038/s41537-022-00293-1","title":"In Vivo 7-Tesla MRI Investigation of Brain Iron and Its Metabolic Correlates in Chronic Schizophrenia","year":2022,"lang":"en","type":"article","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute on Drug Abuse; National Institute on Aging; National Health and Medical Research Council; National Institute of Mental Health; Medical Research Council; Brigham and Women's Hospital; National Imaging Facility; Compute Canada; University of Melbourne; Royal Melbourne Hospital; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Putamen; Schizophrenia (object-oriented programming); Quantitative susceptibility mapping; Oxidative stress; Magnetic resonance imaging; Neuroscience; Psychology; Phosphocreatine; Pathology; Medicine; Internal medicine; Nuclear magnetic resonance; Psychiatry; Radiology; Energy metabolism","score_opus":0.025750503139497286,"score_gpt":0.3004865554387543,"score_spread":0.274736052299257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307658818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996871,0.00004521171,0.0001415992,0.00000822747,4.7296632e-7,0.0000029359992,0.000025885563,0.0000021291148,0.0000865161],"genre_scores_gemma":[0.9995714,0.000031322183,0.00029668727,0.000005307728,0.0000014063864,0.0000040388427,0.000029336907,0.0000012213386,0.00005926913],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995923,0.000013515458,0.0000038757094,0.000007726344,0.00000530508,0.000010267291],"domain_scores_gemma":[0.9998179,0.00003129888,0.00006811119,0.000012160135,0.000036303878,0.00003424559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025327806,0.00019358104,0.00012824606,0.00060107175,0.00018434074,0.00016998875,0.000103434664,0.0002218824,0.0007622986],"category_scores_gemma":[0.0003872562,0.00015912662,0.000063450934,0.00017581563,0.00021703022,0.00013820888,0.00017388005,0.00014277914,0.000066439774],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032367294,0.00027111644,0.41375163,0.00013837373,0.00016421838,0.0013664358,0.00083381584,0.0006665035,0.5681475,0.00022404373,0.00018932486,0.011010363],"study_design_scores_gemma":[0.000035773766,0.0007494039,0.9838844,0.000009721225,0.0000495943,0.0014366863,0.00031082195,0.0015045261,0.0117495945,0.00011469034,0.00014590484,0.00000895089],"about_ca_topic_score_codex":0.0027217697,"about_ca_topic_score_gemma":0.0037965456,"teacher_disagreement_score":0.0027217697,"about_ca_system_score_codex":0.00017540823,"about_ca_system_score_gemma":0.000136727,"threshold_uncertainty_score":0.0054118633},"labels":[],"label_agreement":null},{"id":"W4307722372","doi":"10.1016/j.neuroimage.2022.119703","title":"CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; NIH Blueprint for Neuroscience Research; Horizon 2020; Medical Research Council; McDonnell Center for Systems Neuroscience; Bundesministerium für Bildung und Forschung; Alzheimer’s Society; Fundo Regional para a Ciência e Tecnologia; ZonMw; HORIZON EUROPE Framework Programme; University of Southern California; Alzheimer's Society; U.S. National Library of Medicine; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; EU Joint Programme – Neurodegenerative Disease Research; National Institutes of Health; National Ataxia Foundation; Deutsches Zentrum für Neurodegenerative Erkrankungen; GlaxoSmithKline","keywords":"Spinocerebellar ataxia; Human Connectome Project; Computer science; Artificial intelligence; Segmentation; Preprocessor; Deep learning; Mossy fiber (hippocampus); Cerebellum; Pattern recognition (psychology); Deep cerebellar nuclei; Normalization (sociology); Backbone network; Cerebellar cortex; Neuroscience; Ataxia; Biology; Functional connectivity","score_opus":0.035276769178398275,"score_gpt":0.3144704341371228,"score_spread":0.2791936649587245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307722372","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026550665,0.0021225829,0.87499183,0.0004564429,0.00031414305,0.00032707478,0.008528002,0.08301144,0.0036976712],"genre_scores_gemma":[0.22671458,0.0015234597,0.7053886,0.00076779054,0.00015129315,0.0010250396,0.039934598,0.009006964,0.015487781],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996277,0.000044097706,0.000021821745,0.0001697355,0.000087373606,0.000049298524],"domain_scores_gemma":[0.99960095,0.00011068698,0.00004454124,0.00007869989,0.00012518949,0.00003987761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008883067,0.002504048,0.00087038067,0.0015054467,0.0005061525,0.0012876715,0.002143247,0.0016721429,0.008307155],"category_scores_gemma":[0.00266594,0.0010095825,0.0013636741,0.00085496134,0.0004900292,0.0011508304,0.0017863519,0.001625802,0.004669389],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008950484,0.00022504466,0.0034567716,0.0007258582,0.0006047139,0.0006152121,0.00025528067,0.1338757,0.05042241,0.0073107695,0.106824055,0.6947891],"study_design_scores_gemma":[0.00010350122,0.000121959,0.0017051753,0.000074400894,0.000090496374,0.00033650495,0.0000438664,0.9364372,0.027109757,0.01115097,0.022753283,0.00007296686],"about_ca_topic_score_codex":0.013110243,"about_ca_topic_score_gemma":0.025143571,"teacher_disagreement_score":0.013110243,"about_ca_system_score_codex":0.0013424411,"about_ca_system_score_gemma":0.0024081853,"threshold_uncertainty_score":0.027790189},"labels":[],"label_agreement":null},{"id":"W4307829684","doi":"10.1101/2022.10.28.514160","title":"Linking Enlarged Choroid Plexus with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychosis; Choroid plexus; Ventricle; Neuroimaging; Cerebrospinal fluid; Internal medicine; Prodrome; Medicine; Lateral ventricles; White matter; Cardiology; Endocrinology; Pathology; Magnetic resonance imaging; Psychiatry; Radiology; Central nervous system","score_opus":0.03820997945918215,"score_gpt":0.3331895124935982,"score_spread":0.29497953303441604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307829684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995989,0.000060866772,0.00007265421,0.000016054399,0.000001446785,0.00000937627,0.000115506715,0.0000023392977,0.00012289624],"genre_scores_gemma":[0.999723,0.000018688372,0.00008812289,0.0000069417283,0.0000022776153,0.000007668223,0.000097939774,0.0000013245273,0.000053929252],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99950373,0.0001394084,0.00004736139,0.0001836546,0.00007280369,0.000053143813],"domain_scores_gemma":[0.99833906,0.00027393838,0.0007183592,0.0001947866,0.0002248856,0.00024891025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062984414,0.00043202235,0.0004125558,0.0010142811,0.00077085936,0.0007415052,0.00053774234,0.00065020646,0.0019193608],"category_scores_gemma":[0.0022143112,0.0004011916,0.0003861941,0.0007654852,0.00052448036,0.0005585558,0.0010554444,0.00061571534,0.00018191108],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046128035,0.00007422788,0.99462694,0.000021650962,0.00014777554,0.00053966226,0.00037225123,0.000050822564,0.0023685694,0.000031488926,0.00007693683,0.0012283571],"study_design_scores_gemma":[0.000013331909,0.000081637314,0.9988117,0.0000054569127,0.0000315667,0.0005853972,0.00018794562,0.000097913035,0.00009531763,0.000042221818,0.00004360194,0.000003939815],"about_ca_topic_score_codex":0.00838366,"about_ca_topic_score_gemma":0.010589152,"teacher_disagreement_score":0.00838366,"about_ca_system_score_codex":0.00045754266,"about_ca_system_score_gemma":0.0003620462,"threshold_uncertainty_score":0.01666975},"labels":[],"label_agreement":null},{"id":"W4307859783","doi":"10.1101/2022.10.27.22281560","title":"Estimation of free water-corrected microscopic fractional anisotropy","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Free water; Orientation (vector space); Diffusion; Dispersion (optics); Partial volume; Nuclear magnetic resonance; Materials science; Voxel; Metric (unit); Tensor (intrinsic definition); Biological system; Physics; Mathematics; Computer science; Optics; Magnetic resonance imaging; Artificial intelligence; Geology; Geometry; Medicine; Biology; Thermodynamics; Radiology","score_opus":0.04915096970614418,"score_gpt":0.35753922482154593,"score_spread":0.30838825511540174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307859783","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07618138,0.00027637358,0.92094713,0.0000851191,0.00005810616,0.0000504491,0.00018826559,0.0012113604,0.0010018258],"genre_scores_gemma":[0.5633551,0.000294341,0.43271852,0.000025671681,0.00003802019,0.000074019976,0.00033243414,0.00041012964,0.0027517567],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979764,0.000043167445,0.000010747183,0.000059923204,0.00006838226,0.000020119825],"domain_scores_gemma":[0.99942017,0.00019332512,0.00009630219,0.00012944918,0.00013351403,0.000027234899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007555712,0.0007490348,0.0005229501,0.0011820192,0.00025851096,0.00075075956,0.00052732206,0.0005275063,0.0016549866],"category_scores_gemma":[0.0035298716,0.0002622436,0.0004974038,0.00049212534,0.0004103223,0.0006966033,0.00047008492,0.00049684464,0.0004907954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005714978,0.00009868387,0.00992959,0.00040140233,0.00027447764,0.00044203768,0.00024165736,0.14753042,0.40426677,0.017793603,0.00400063,0.41444913],"study_design_scores_gemma":[0.000030812276,0.00015994677,0.013668714,0.000024244599,0.00009605747,0.00077716185,0.00005233034,0.7175298,0.24811438,0.012209019,0.007239733,0.00009785717],"about_ca_topic_score_codex":0.0021252949,"about_ca_topic_score_gemma":0.0017002732,"teacher_disagreement_score":0.0021252949,"about_ca_system_score_codex":0.00027864182,"about_ca_system_score_gemma":0.0005580072,"threshold_uncertainty_score":0.0055364966},"labels":[],"label_agreement":null},{"id":"W4307921398","doi":"10.1038/s41598-022-21615-4","title":"Author Correction: Speed-dependent and mode-dependent modulations of spatiotemporal modules in human locomotion extracted via tensor decomposition","year":2022,"lang":"en","type":"erratum","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Decomposition; Tensor (intrinsic definition); Computer science; Tensor decomposition; Mode (computer interface); Biological system; Artificial intelligence; Topology (electrical circuits); Pattern recognition (psychology); Mathematics; Biology; Pure mathematics; Human–computer interaction; Combinatorics; Ecology","score_opus":0.046317595438620435,"score_gpt":0.36548290600621053,"score_spread":0.3191653105675901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307921398","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00037098152,0.00091898657,0.00273369,0.016885407,0.97439414,0.000027071466,0.0020990975,0.0007723562,0.0017982796],"genre_scores_gemma":[0.05600276,0.011348237,0.034546237,0.045343444,0.41789088,0.0006144284,0.01113158,0.008665462,0.41445696],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958831,0.00046993865,0.00088960415,0.0007232413,0.0017418194,0.00029230735],"domain_scores_gemma":[0.9545088,0.00813499,0.0017867534,0.0045203394,0.0298948,0.0011542756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042326567,0.002653043,0.0022334037,0.0041983747,0.002882221,0.003258953,0.0035106426,0.0049033277,0.09713024],"category_scores_gemma":[0.0782932,0.0013275418,0.0017538471,0.003454735,0.0023959363,0.0022580288,0.002708807,0.0075535327,0.045090288],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005908446,0.0000057612847,0.00011985245,0.0002498473,0.00002209449,0.00031354855,0.00006224775,0.00007615125,0.00016378029,0.001078865,0.9874265,0.010422281],"study_design_scores_gemma":[0.000072760144,0.000033564615,0.0016204952,0.00050485256,0.00010467424,0.0017077778,0.00017657962,0.00082916947,0.0018474781,0.0038363563,0.989174,0.00009246442],"about_ca_topic_score_codex":0.013810398,"about_ca_topic_score_gemma":0.017881207,"teacher_disagreement_score":0.09713024,"about_ca_system_score_codex":0.0026415475,"about_ca_system_score_gemma":0.0053848894,"threshold_uncertainty_score":0.324933},"labels":[],"label_agreement":null},{"id":"W4307934660","doi":"10.1016/j.clinph.2022.10.012","title":"Integration of white matter architecture to stereo-EEG better describes epileptic spike propagation","year":2022,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Stereoelectroencephalography; Spike (software development); White matter; Tractography; Electroencephalography; Diffusion MRI; Epilepsy; Neuroscience; Connectome; Computer science; Pattern recognition (psychology); Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity; Epilepsy surgery; Radiology","score_opus":0.08989667930491678,"score_gpt":0.3891797241400694,"score_spread":0.2992830448351526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307934660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4699464,0.001323498,0.5089275,0.00034421124,0.00022705823,0.00020688266,0.0009504313,0.0014630742,0.016610876],"genre_scores_gemma":[0.9595293,0.0006885187,0.036698807,0.000102482445,0.00012486697,0.000031343796,0.00036678909,0.00034968182,0.0021081949],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998965,0.000026968366,0.00001403299,0.000018046852,0.000023617713,0.000020788564],"domain_scores_gemma":[0.99956137,0.00014143593,0.00007588735,0.00008755681,0.0001003524,0.00003339634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045938342,0.0008263726,0.00020484433,0.0018364184,0.00022617933,0.00096027594,0.0002568766,0.00057640346,0.002631076],"category_scores_gemma":[0.0015300201,0.00014531103,0.00033714078,0.0011327977,0.00043591013,0.0014119289,0.00040218854,0.00046738863,0.0005965462],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083646976,0.00012947203,0.08124896,0.00064262655,0.00035225844,0.0051196045,0.0008908328,0.026435548,0.44968417,0.02691326,0.0026612328,0.40508565],"study_design_scores_gemma":[0.00008032189,0.0009477334,0.4137809,0.0002270358,0.00061325973,0.021499135,0.00097356987,0.3092865,0.1278372,0.10717278,0.017437313,0.00014435194],"about_ca_topic_score_codex":0.0014801389,"about_ca_topic_score_gemma":0.0033268759,"teacher_disagreement_score":0.002631076,"about_ca_system_score_codex":0.00016913394,"about_ca_system_score_gemma":0.00033470782,"threshold_uncertainty_score":0.008801818},"labels":[],"label_agreement":null},{"id":"W4308327065","doi":"10.1016/j.brainres.2022.148152","title":"Diffusion tensor imaging of superficial prefrontal white matter in healthy aging","year":2022,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University Hospital Foundation","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Prefrontal cortex; Psychology; Neuroscience; Voxel; Orbitofrontal cortex; Tractography; Dorsolateral prefrontal cortex; Magnetic resonance imaging; Medicine; Cognition; Radiology","score_opus":0.11251255876961173,"score_gpt":0.4458502737399943,"score_spread":0.33333771497038256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308327065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99764425,0.0009791021,0.000472173,0.00011416511,0.000013248266,0.00000953892,0.0002136146,0.000008334718,0.00054559304],"genre_scores_gemma":[0.998059,0.00064285175,0.00054241525,0.000031968517,0.000018856354,0.0000047211342,0.00015910619,0.0000027081373,0.00053845905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994266,0.000008363796,0.000007815039,0.000016193339,0.00000954763,0.000015414495],"domain_scores_gemma":[0.99972266,0.00003427019,0.00010475173,0.000027573162,0.000060315277,0.00005043747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005590045,0.0003584433,0.00019089834,0.00074402394,0.00028807204,0.0004532071,0.00022654451,0.0004224219,0.0009161234],"category_scores_gemma":[0.0013837677,0.00019955782,0.0001568447,0.00040049484,0.00032115597,0.0007523976,0.00026303183,0.00026943703,0.00013681896],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006113069,0.00063989795,0.69336545,0.00046110034,0.0008304327,0.0041190535,0.0028662516,0.0020593216,0.1727591,0.0018956078,0.0025439754,0.1123467],"study_design_scores_gemma":[0.00002603011,0.00039248934,0.98954064,0.00002077985,0.00011623199,0.0018485805,0.000467217,0.0013369757,0.004132787,0.0015576114,0.0005464082,0.000014266889],"about_ca_topic_score_codex":0.013333363,"about_ca_topic_score_gemma":0.017398588,"teacher_disagreement_score":0.013333363,"about_ca_system_score_codex":0.00035284105,"about_ca_system_score_gemma":0.00036095906,"threshold_uncertainty_score":0.02651149},"labels":[],"label_agreement":null},{"id":"W4308510056","doi":"10.1148/radiol.222302","title":"Ultralow-Field-Strength MRI and Artificial Intelligence: How Low Can We Go and How High Can We Reach?","year":2022,"lang":"en","type":"letter","venue":"Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Artificial intelligence; Magnetic resonance imaging; MEDLINE; Nuclear medicine; Medical physics; Computer science; Radiology","score_opus":0.044520975019822495,"score_gpt":0.30500679687531934,"score_spread":0.26048582185549685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308510056","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015624442,0.0029602556,0.0001227021,0.99036,0.0052589667,0.0000025368251,0.000006365668,0.000009273385,0.0011234813],"genre_scores_gemma":[0.005773755,0.0044348063,0.00058306096,0.9284754,0.057395704,0.000026388107,0.000010565257,0.000017177192,0.00328322],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966186,0.0013208332,0.00030401885,0.0003084162,0.0010617465,0.00038625297],"domain_scores_gemma":[0.98597115,0.009754493,0.0005720406,0.0003523311,0.0015244207,0.0018255371],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043932707,0.0007292211,0.0015461058,0.0006460826,0.003744764,0.005631066,0.0015017528,0.055963423,0.004887829],"category_scores_gemma":[0.022397187,0.0005410206,0.0008875985,0.00050363695,0.006678629,0.008129514,0.00193916,0.055437036,0.005167689],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008477365,0.000064787244,0.00075785903,0.0001233107,0.000034318713,0.0032344016,0.00024194119,0.00008335723,0.00027104656,0.01798431,0.9487186,0.028401265],"study_design_scores_gemma":[0.00015121348,0.000085956286,0.0007785388,0.000554953,0.000040498344,0.0055184616,0.00096886134,0.0008829883,0.00030577468,0.13870497,0.85191953,0.00008817714],"about_ca_topic_score_codex":0.0029181992,"about_ca_topic_score_gemma":0.005874418,"teacher_disagreement_score":0.055963423,"about_ca_system_score_codex":0.0041054077,"about_ca_system_score_gemma":0.0036646747,"threshold_uncertainty_score":0.029786944},"labels":[],"label_agreement":null},{"id":"W4308890622","doi":"10.1038/s41380-022-01833-y","title":"Whole-brain white matter abnormalities in human cocaine and heroin use disorders: association with craving, recency, and cumulative use","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; Canadian Institutes of Health Research; National Institute on Drug Abuse; U.S. Department of Health and Human Services; Government of Canada; National Center for Advancing Translational Sciences","keywords":"Fractional anisotropy; White matter; Psychology; Cocaine dependence; Craving; Addiction; Diffusion MRI; Heroin; Psychiatry; Internal medicine; Medicine; Drug; Magnetic resonance imaging","score_opus":0.020536309574435675,"score_gpt":0.30000881505397486,"score_spread":0.27947250547953917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308890622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993247,0.00029602877,0.00007800245,0.000016204858,0.0000013723045,0.0000032979042,0.00008048781,0.0000018589479,0.0001981342],"genre_scores_gemma":[0.99913126,0.0003235706,0.00015784304,0.0000127656995,0.000003171089,0.000002918153,0.00011943501,0.000002030339,0.00024702825],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999629,0.000007532305,0.0000033894855,0.000011462,0.000008594602,0.0000061002306],"domain_scores_gemma":[0.99976295,0.00004579806,0.00011023989,0.000022021644,0.00002163009,0.000037392052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013704001,0.00018660384,0.00016552788,0.0006591794,0.00024892855,0.00023482999,0.00014749025,0.00024425398,0.0012329004],"category_scores_gemma":[0.00042665013,0.00016014463,0.00011983408,0.00038548437,0.00030114705,0.0001739434,0.00020018994,0.00023859517,0.000104038576],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017600185,0.00019109975,0.91433704,0.00010007236,0.0003473494,0.0017307955,0.00041268475,0.00026533043,0.065481566,0.00015105361,0.00015758944,0.015065438],"study_design_scores_gemma":[0.0000021990772,0.000034747536,0.99876946,0.000001735974,0.000015033857,0.0006599328,0.000040864004,0.00007211092,0.00032624847,0.000038241105,0.00003806725,0.0000013424575],"about_ca_topic_score_codex":0.0052320347,"about_ca_topic_score_gemma":0.013768565,"teacher_disagreement_score":0.0052320347,"about_ca_system_score_codex":0.00015482801,"about_ca_system_score_gemma":0.00016419783,"threshold_uncertainty_score":0.010403156},"labels":[],"label_agreement":null},{"id":"W4309047156","doi":"10.1016/j.neuroimage.2022.119750","title":"Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Philips (Canada)","funders":"Faculty of Medicine, Munich University of Technology; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Friedrich-Ebert-Stiftung; Deutsche Forschungsgemeinschaft","keywords":"Myelin; Multiple sclerosis; Magnetization transfer; Magnetic resonance imaging; White matter; Nuclear magnetic resonance; Chemistry; Nuclear medicine; Medicine; Central nervous system; Internal medicine; Physics; Radiology; Immunology","score_opus":0.11514152422329235,"score_gpt":0.31839195281027893,"score_spread":0.20325042858698658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309047156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99897397,0.00022215956,0.0006046663,0.0000049336695,0.0000011170276,0.000007647934,0.000066414126,0.00001859832,0.00010068021],"genre_scores_gemma":[0.9987821,0.00008494485,0.0009663522,0.0000057662314,0.0000030608398,0.000009932967,0.00009590821,0.000009863217,0.000042045973],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971026,0.00007785133,0.000037391328,0.00009251116,0.00005325434,0.000028626935],"domain_scores_gemma":[0.9991535,0.00036848945,0.00022750872,0.000092154696,0.00009568072,0.000062708925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007814372,0.00055878854,0.00040353002,0.002417495,0.00018138801,0.00037610455,0.00027781128,0.0004096409,0.00058798166],"category_scores_gemma":[0.0029840444,0.0002049901,0.00030457613,0.0006048171,0.00060365675,0.0004392268,0.00043189534,0.00018268668,0.0001390032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009074654,0.00034285476,0.49437124,0.0006547742,0.0018880864,0.0025529964,0.0031357594,0.007217651,0.40446815,0.0006602811,0.00033010467,0.075303435],"study_design_scores_gemma":[0.00005932357,0.00085377565,0.9581735,0.000021033706,0.0002746607,0.002569044,0.00055388646,0.0044374284,0.031725,0.0010265622,0.00026081095,0.000044944627],"about_ca_topic_score_codex":0.0009395114,"about_ca_topic_score_gemma":0.00075964816,"teacher_disagreement_score":0.002417495,"about_ca_system_score_codex":0.00020432057,"about_ca_system_score_gemma":0.00010483769,"threshold_uncertainty_score":0.0041326284},"labels":[],"label_agreement":null},{"id":"W4309508399","doi":"10.1093/brain/awac436","title":"Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status","year":2022,"lang":"en","type":"review","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Stichting MS Research; Fundação de Amparo à Pesquisa do Estado de São Paulo; Canada Research Chairs; Università degli Studi G. d'Annunzio Chieti - Pescara; ZonMw; Dipartimenti di Eccellenza","keywords":"Neuroscience; Positron emission tomography; Magnetic resonance imaging; Pet imaging; Myelin; Psychology; Medicine; Medical physics; Radiology; Central nervous system","score_opus":0.22788593565350854,"score_gpt":0.46522329672626705,"score_spread":0.23733736107275852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309508399","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001346679,0.99846673,0.00036187298,0.00018660215,0.00009684624,0.0000067835913,0.000027012884,0.000011288257,0.00070820993],"genre_scores_gemma":[0.0006829206,0.99779546,0.0008078728,0.00016026665,0.00016775679,0.000017732467,0.000050904982,0.0000047487656,0.00031240648],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995939,0.00007858091,0.00006574704,0.00008678833,0.00014364584,0.000031328476],"domain_scores_gemma":[0.99888617,0.0007368766,0.00007892748,0.000029490768,0.00023528768,0.00003326168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014514882,0.0010985316,0.0015315491,0.0032562981,0.000228435,0.001313595,0.0009218854,0.0013782635,0.0025659099],"category_scores_gemma":[0.0018675269,0.0004880874,0.0007616216,0.0029931972,0.0006703955,0.0021049909,0.0006416145,0.0018602277,0.0018183965],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103147955,0.000076168966,0.00031617805,0.022988737,0.0001176994,0.00021811531,0.00007321851,0.00036028825,0.0037368743,0.0036888276,0.0139256455,0.9543951],"study_design_scores_gemma":[0.000021796946,0.00023715178,0.001617918,0.006194633,0.00034314964,0.0040705907,0.00009074841,0.0003427838,0.0033070273,0.0034670555,0.98023486,0.00007212194],"about_ca_topic_score_codex":0.0012952985,"about_ca_topic_score_gemma":0.0012482604,"teacher_disagreement_score":0.0032562981,"about_ca_system_score_codex":0.00078363775,"about_ca_system_score_gemma":0.0014996899,"threshold_uncertainty_score":0.008583844},"labels":[],"label_agreement":null},{"id":"W4309772416","doi":"10.1016/j.pscychresns.2022.111568","title":"Better characterization of attention and hyperactivity/impulsivity in children with ADHD: The key to understanding the underlying white matter microstructure","year":2022,"lang":"en","type":"review","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health and Social Services Centre University Institute of Geriatrics of Sherbrooke; Q & T Research; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Endophenotype; Impulsivity; Diffusion MRI; Psychology; Attention deficit hyperactivity disorder; White matter; Cognitive psychology; Neuroscience; Clinical psychology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.2097419401037088,"score_gpt":0.4361291023351229,"score_spread":0.2263871622314141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309772416","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012463678,0.99903995,0.00012795681,0.0003652365,0.00006891431,0.0000028926952,0.000029672656,0.0000039199726,0.000236819],"genre_scores_gemma":[0.000963664,0.9978795,0.0005060885,0.0002249764,0.0002135725,0.000007499012,0.000053950014,0.000001756352,0.00014907403],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997855,0.000038813956,0.000034143774,0.00005381127,0.000069956055,0.00001789452],"domain_scores_gemma":[0.99917966,0.0004273073,0.000110266075,0.000020863063,0.00022718923,0.00003471579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001076107,0.0011685286,0.0025592234,0.0018693694,0.00015432306,0.0013098158,0.0010913538,0.0014268659,0.0013509684],"category_scores_gemma":[0.0016650282,0.00031343263,0.0008269587,0.0015022812,0.00058874174,0.001179366,0.00058294804,0.002147044,0.0007422985],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010967885,0.000059467515,0.0017623029,0.016047489,0.0005017146,0.00019247051,0.0000450716,0.0003079527,0.0021830953,0.0025634794,0.012576284,0.963651],"study_design_scores_gemma":[0.00012771857,0.0003292886,0.03494898,0.03283864,0.002693311,0.0051968554,0.00031662558,0.0006140196,0.0026805091,0.01607489,0.9040416,0.00013757669],"about_ca_topic_score_codex":0.0057653664,"about_ca_topic_score_gemma":0.009524617,"teacher_disagreement_score":0.0057653664,"about_ca_system_score_codex":0.0007125129,"about_ca_system_score_gemma":0.001787786,"threshold_uncertainty_score":0.011463642},"labels":[],"label_agreement":null},{"id":"W4309900061","doi":"10.21203/rs.3.rs-2259594/v1","title":"Corticostriatal Structural Connectivity and Integrity in Children with Hydrocephalus and Executive Dysfunction","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Executive dysfunction; Hydrocephalus; Psychology; Executive functions; Neuroscience; Cognition; Medicine; Psychiatry; Magnetic resonance imaging; Radiology; Neuropsychology","score_opus":0.09079463897647834,"score_gpt":0.42693618329914906,"score_spread":0.33614154432267074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309900061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99967074,0.000073323085,0.000031355394,0.000011011996,9.841392e-7,0.0000031172076,0.00007148276,0.0000027775907,0.00013521416],"genre_scores_gemma":[0.9997812,0.000042919906,0.000065494496,0.000004285363,0.0000017697937,0.0000036371932,0.00006657493,0.0000011400153,0.00003302425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974245,0.000037311136,0.000027505368,0.00008747793,0.00005514639,0.000050069913],"domain_scores_gemma":[0.9992124,0.000111223606,0.00046449093,0.000044492557,0.000063152715,0.00010413395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036811558,0.00043495564,0.0002851205,0.0017010156,0.00044789293,0.0004905884,0.00029159876,0.00035177835,0.0010019849],"category_scores_gemma":[0.0015119612,0.00018222565,0.00019724312,0.00062395155,0.00072743907,0.00042043813,0.00042214515,0.00031716147,0.000096195196],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089556546,0.000056671557,0.99348515,0.000021128464,0.000039675946,0.0020267237,0.00048176752,0.00007384727,0.0012635619,0.000057728932,0.000094372874,0.0023098702],"study_design_scores_gemma":[0.0000031280235,0.00005810532,0.9959045,0.0000062229415,0.000014904276,0.0033090846,0.00026647968,0.00009899255,0.00022647413,0.00003896489,0.00007071414,0.0000022638278],"about_ca_topic_score_codex":0.006753726,"about_ca_topic_score_gemma":0.0076668793,"teacher_disagreement_score":0.006753726,"about_ca_system_score_codex":0.00050750835,"about_ca_system_score_gemma":0.00044974993,"threshold_uncertainty_score":0.013428807},"labels":[],"label_agreement":null},{"id":"W4310030087","doi":"10.1101/2022.11.23.22282135","title":"Predicting cognitive decline in a low-dimensional representation of brain morphology","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Fundamental Research Funds for the Central Universities; Center for Advanced Brain Imaging; McDonnell Center for Systems Neuroscience; Alvin J. Siteman Cancer Center; Genentech; National Institutes of Health; IXICO; Servier; National Science Foundation; China Postdoctoral Science Foundation; Foundation for the National Institutes of Health; Stavros Niarchos Foundation; University of Southern California; Eisai; National Natural Science Foundation of China; U.S. Department of Defense; Commonwealth Scientific and Industrial Research Organisation; Northern California Institute for Research and Education; Dana Foundation; H. Lundbeck A/S; Bristol-Myers Squibb; Southwest University; Natural Science Foundation of Chongqing; Université Laval; Natural Sciences and Engineering Research Council of Canada; Child Mind Institute; Pfizer; Biogen; BioClinica; Canadian Institutes of Health Research; Foundation for Barnes-Jewish Hospital; F. Hoffmann-La Roche; Yale University; Novartis Pharmaceuticals Corporation; American Hearing Research Foundation; Biotechnology and Biological Sciences Research Council; Chongqing Postdoctoral Science Foundation; New York State Office of Mental Health; Alzheimer's Association; Leon Levy Foundation; Alzheimer's Disease Neuroimaging Initiative; James S. McDonnell Foundation; Eli Lilly and Company; Alliance de recherche numérique du Canada; Canada First Research Excellence Fund; Brain Research Foundation; Meso Scale Diagnostics; Fok Ying Tung Education Foundation","keywords":"Neurodegeneration; Cognitive decline; Neuroimaging; Cognition; Psychology; Representation (politics); Neuroscience; Cognitive neuroscience; Alzheimer's disease; Pattern recognition (psychology); Artificial intelligence; Medicine; Disease; Computer science; Cognitive psychology; Pathology; Dementia","score_opus":0.07750956191120476,"score_gpt":0.40477031115933704,"score_spread":0.3272607492481323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310030087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96835417,0.0001942367,0.030211229,0.000100546065,0.000019223144,0.000042210635,0.00043496693,0.00033957735,0.00030384993],"genre_scores_gemma":[0.98803353,0.000059755013,0.010675122,0.000013027726,0.000010048936,0.0000253883,0.00093465886,0.000011545459,0.00023692331],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946016,0.00019632891,0.00003390246,0.0001652686,0.0000858931,0.00005843469],"domain_scores_gemma":[0.9984397,0.000735995,0.00021290618,0.00019193956,0.00031724322,0.000102186736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021333962,0.00069241994,0.00050970085,0.0016398997,0.00024046695,0.000982788,0.00042042308,0.0005938103,0.00077848573],"category_scores_gemma":[0.0048532793,0.00019342717,0.0006556435,0.0007130332,0.00030084114,0.0006482157,0.00074595754,0.0006595178,0.00038412726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014553679,0.00083860813,0.5091517,0.00015916141,0.0007274494,0.0002635323,0.00047537597,0.19973284,0.019059096,0.0007574889,0.0035764475,0.26380298],"study_design_scores_gemma":[0.000015002477,0.00019362663,0.11309011,0.000015336487,0.000029649265,0.000102485195,0.0000950742,0.8835697,0.0018407111,0.0007689969,0.0002596341,0.000019719708],"about_ca_topic_score_codex":0.0051223435,"about_ca_topic_score_gemma":0.0034352916,"teacher_disagreement_score":0.0051223435,"about_ca_system_score_codex":0.0005164246,"about_ca_system_score_gemma":0.00040725502,"threshold_uncertainty_score":0.011282623},"labels":[],"label_agreement":null},{"id":"W4310060197","doi":"10.1038/s41380-022-01870-7","title":"Accelerated cortical thinning precedes and predicts conversion to psychosis: The NAPLS3 longitudinal study of youth at clinical high-risk","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Mental Health; U.S. Department of Health and Human Services; National Science Foundation","keywords":"Psychosis; Prodrome; Psychology; Neuroimaging; Medicine; Internal medicine; Neuroscience; Psychiatry","score_opus":0.08466840974853318,"score_gpt":0.38405835442455993,"score_spread":0.29938994467602675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310060197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996145,0.000044351014,0.000031677446,0.000026155773,0.0000014305531,0.000006348765,0.000137284,0.0000021772285,0.00013614072],"genre_scores_gemma":[0.99949884,0.000033657387,0.000059032205,0.000013455324,0.000001999816,0.0000073658316,0.00023845333,0.0000016144885,0.00014551956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997086,0.000084655025,0.000019903855,0.00006592506,0.00006628996,0.00005468732],"domain_scores_gemma":[0.99887556,0.00010137349,0.00046174356,0.00009375944,0.00017699065,0.00029054587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007874374,0.00030191173,0.00025296432,0.0006084249,0.00067417126,0.0006493327,0.00042832724,0.00055655127,0.0013612133],"category_scores_gemma":[0.0017333943,0.0003915846,0.00040333427,0.0004645377,0.00029771056,0.00043734486,0.0006590632,0.00097383175,0.00018759501],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015456515,0.00004796784,0.9982191,0.0000033492838,0.000024698109,0.00016430559,0.0001985341,0.000018351571,0.0005017735,0.0000119030965,0.000070457805,0.00058506994],"study_design_scores_gemma":[0.000002852024,0.000046289893,0.9995426,0.00000258494,0.0000058921983,0.00014919408,0.00011834153,0.00004810157,0.000041735846,0.00000940953,0.00003178959,0.0000012202277],"about_ca_topic_score_codex":0.0166323,"about_ca_topic_score_gemma":0.026935523,"teacher_disagreement_score":0.0166323,"about_ca_system_score_codex":0.00038756442,"about_ca_system_score_gemma":0.0004278506,"threshold_uncertainty_score":0.03307098},"labels":[],"label_agreement":null},{"id":"W4310060332","doi":"10.1038/s41597-022-01833-1","title":"TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada; Wellcome Trust","keywords":"Computer science; Tractography; Scale (ratio); Database; Artificial intelligence; Diffusion MRI; Cartography; Magnetic resonance imaging; Medicine; Geography","score_opus":0.17628452514973905,"score_gpt":0.40893639807620985,"score_spread":0.2326518729264708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310060332","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03144671,0.0033954068,0.17795327,0.0005302913,0.0004997774,0.0007537286,0.50942016,0.26459596,0.011404686],"genre_scores_gemma":[0.066949844,0.001058709,0.11020593,0.00032255377,0.00009971068,0.0011074381,0.7912237,0.023853337,0.0051788115],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99882776,0.00015277637,0.00014139374,0.00041051384,0.00036936344,0.00009823758],"domain_scores_gemma":[0.9967018,0.0008929997,0.00027903833,0.0012440505,0.00053101406,0.00035118105],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0021622488,0.0021808667,0.0019706658,0.0037634843,0.0007819169,0.0027087412,0.0042830845,0.0018499081,0.02711596],"category_scores_gemma":[0.008543902,0.0010882088,0.0016188486,0.0035646136,0.0005713143,0.0030231632,0.0029997502,0.0015239975,0.022153974],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018869534,0.00031313385,0.008408916,0.0028176026,0.00078450766,0.0010188412,0.00042795442,0.01888975,0.0103692375,0.007852771,0.7808417,0.16638862],"study_design_scores_gemma":[0.0012185171,0.00051863876,0.021411354,0.0007465009,0.00036347492,0.0040137656,0.0003172928,0.13655634,0.034973707,0.027416466,0.77188176,0.0005821644],"about_ca_topic_score_codex":0.0065324316,"about_ca_topic_score_gemma":0.01252851,"teacher_disagreement_score":0.9957169,"about_ca_system_score_codex":0.0009335543,"about_ca_system_score_gemma":0.001974867,"threshold_uncertainty_score":0.09071195},"labels":[],"label_agreement":null},{"id":"W4310191118","doi":"10.3389/fnana.2022.960475","title":"Histology-informed automatic parcellation of white matter tracts in the rat spinal cord","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Polytechnique Montréal; Réseau en Bio-Imagerie du Quebec","keywords":"White matter; Axon; Spinal cord; Morphometrics; Neuroscience; Anatomy; Segmentation; Biology; Myelin; Brain atlas; Corticospinal tract; Cluster analysis; Artificial intelligence; Diffusion MRI; Central nervous system; Pattern recognition (psychology); Computer science; Magnetic resonance imaging; Medicine; Zoology; Radiology","score_opus":0.033636958698236595,"score_gpt":0.3281442183020419,"score_spread":0.2945072596038053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310191118","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.342908,0.0003478993,0.6425722,0.00019676698,0.00009251591,0.00036312614,0.0025417942,0.008698815,0.0022788646],"genre_scores_gemma":[0.31698558,0.00028377995,0.675223,0.000068750174,0.000015229483,0.0004492426,0.002620655,0.0014476484,0.0029060603],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99969757,0.000034156208,0.000018612713,0.00011185354,0.0000926168,0.000045245226],"domain_scores_gemma":[0.9995295,0.00009467993,0.000100159894,0.00011445046,0.00013402863,0.000027135155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068477995,0.0006284428,0.0004880476,0.001145251,0.00044145275,0.0006959846,0.0006046457,0.0006162857,0.0021195002],"category_scores_gemma":[0.00089927285,0.00037944625,0.0008162463,0.0007119519,0.00046862994,0.00039871313,0.0005660712,0.00057435245,0.0008063791],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040484525,0.00019496704,0.004596587,0.00045411376,0.00014451875,0.00033383223,0.0005099493,0.10012526,0.7331438,0.006154466,0.0031484368,0.15078926],"study_design_scores_gemma":[0.000044290442,0.00038978358,0.01608116,0.00004212703,0.000077221506,0.000460193,0.00015753608,0.5774647,0.39517248,0.0034893688,0.00653615,0.00008494877],"about_ca_topic_score_codex":0.0044540255,"about_ca_topic_score_gemma":0.009412211,"teacher_disagreement_score":0.0044540255,"about_ca_system_score_codex":0.0007378978,"about_ca_system_score_gemma":0.0012283578,"threshold_uncertainty_score":0.008856177},"labels":[],"label_agreement":null},{"id":"W4310461041","doi":"10.1002/mpr.1955","title":"White‐matter correlates of anxiety: The contribution of the corpus‐callosum to the study of anxiety and stress‐related disorders","year":2022,"lang":"en","type":"article","venue":"International Journal of Methods in Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministry of Health, British Columbia; Ministry of Health, State of Israel; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Psychology; Fractional anisotropy; Anxiety; White matter; Cognition; Diffusion MRI; Neuropathology; Clinical psychology; Neuroscience; Internal medicine; Medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.06260866962514129,"score_gpt":0.48691996670838406,"score_spread":0.4243112970832428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310461041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9201646,0.07468431,0.0011361999,0.0012618967,0.0000996688,0.000031033094,0.00026343082,0.000025740172,0.0023330413],"genre_scores_gemma":[0.9832109,0.014658169,0.0012916982,0.00010490967,0.00022036205,0.000022776301,0.00014673384,0.0000052531477,0.00033923177],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999912,0.000038011887,0.000007800093,0.000013197142,0.000018295248,0.000010822636],"domain_scores_gemma":[0.99931264,0.00024023227,0.00026961602,0.00003377915,0.000060257313,0.00008344999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048465224,0.00030811797,0.00016863186,0.0015506439,0.00022706545,0.0006112433,0.00023214304,0.0002959715,0.0009221486],"category_scores_gemma":[0.0015477556,0.00008816452,0.00010971826,0.0009125772,0.0005329407,0.0004273248,0.00033248917,0.00033935905,0.00007754639],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077301293,0.0002004352,0.71618307,0.0014998487,0.00071356806,0.0015658269,0.0011195393,0.0006753672,0.025733048,0.002366821,0.0020136049,0.24715589],"study_design_scores_gemma":[0.000006306462,0.0001270064,0.9943137,0.00009267048,0.00007443847,0.0015008282,0.0002752644,0.00027740645,0.00042121782,0.0011783568,0.0017232355,0.000009586237],"about_ca_topic_score_codex":0.0023313619,"about_ca_topic_score_gemma":0.0033145973,"teacher_disagreement_score":0.0023313619,"about_ca_system_score_codex":0.00015813769,"about_ca_system_score_gemma":0.00033375635,"threshold_uncertainty_score":0.004635632},"labels":[],"label_agreement":null},{"id":"W4310490701","doi":"10.32473/ufjur.24.130754","title":"Evaluating Spatial Filtering on Diffusion MRI Data Harmonization in Parkinsonism","year":2022,"lang":"en","type":"article","venue":"UF Journal of Undergraduate Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Florida","keywords":"Parkinsonism; Filter (signal processing); Artificial intelligence; Progressive supranuclear palsy; Computer science; Gaussian filter; Pattern recognition (psychology); Atrophy; Machine learning; Data mining; Medicine; Computer vision; Disease; Pathology","score_opus":0.4707908280101828,"score_gpt":0.5337617081473054,"score_spread":0.0629708801371226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310490701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91288996,0.0012812244,0.08310478,0.00023862679,0.00007777369,0.0002782491,0.0003622044,0.00082234864,0.00094483554],"genre_scores_gemma":[0.9375946,0.00017640018,0.06108088,0.00006739053,0.000027850127,0.00010272664,0.00061678205,0.00007702224,0.0002564337],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9955688,0.0020545132,0.0006209233,0.000810839,0.00074233755,0.00020254144],"domain_scores_gemma":[0.9694723,0.024292853,0.0016619485,0.0013595484,0.0028849766,0.00032849298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017971687,0.00078767876,0.00085400295,0.002045538,0.00056693866,0.0013126183,0.0006060113,0.0012212633,0.0007954362],"category_scores_gemma":[0.044347186,0.00027331902,0.0009520148,0.0012466434,0.0007850717,0.0011792863,0.0008468686,0.0005325881,0.00026689895],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008110021,0.0010409096,0.23146988,0.0007451214,0.0018343214,0.00031278873,0.0008845317,0.20540763,0.030759083,0.00092735357,0.0024119865,0.5160964],"study_design_scores_gemma":[0.00017663957,0.0027367335,0.15245041,0.000109244575,0.0004856294,0.0005020484,0.00043839208,0.8055699,0.03441533,0.0017748015,0.0012656343,0.0000752277],"about_ca_topic_score_codex":0.0036061567,"about_ca_topic_score_gemma":0.0034347987,"teacher_disagreement_score":0.017971687,"about_ca_system_score_codex":0.0008786229,"about_ca_system_score_gemma":0.0010355382,"threshold_uncertainty_score":0.095044434},"labels":[],"label_agreement":null},{"id":"W4310540129","doi":"10.3390/brainsci12121651","title":"Beyond the Dorsal Column Medial Lemniscus in Proprioception and Stroke: A White Matter Investigation","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Medial lemniscus; Proprioception; Dorsum; White matter; Stroke (engine); Dorsal column nuclei; Anatomy; Physical medicine and rehabilitation; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Physics","score_opus":0.04855541148761758,"score_gpt":0.33101048278254025,"score_spread":0.28245507129492264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310540129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98008037,0.014733681,0.0018851361,0.0005666516,0.000023990013,0.000040277373,0.000078639074,0.00002004517,0.0025712594],"genre_scores_gemma":[0.9936265,0.0042142277,0.0010241214,0.00009399196,0.000064028274,0.000019301122,0.00004959414,0.0000033621411,0.00090479973],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993944,0.000012284018,0.0000052581827,0.000018280769,0.000011051648,0.000013674112],"domain_scores_gemma":[0.9998661,0.00003531327,0.000052397296,0.000010319332,0.000017410892,0.000018339706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002768475,0.0004121515,0.00018990564,0.0011032772,0.00025805685,0.00043639724,0.000282288,0.000513905,0.002036776],"category_scores_gemma":[0.00037880795,0.000106090636,0.00013397867,0.00074762566,0.00085374626,0.00063611486,0.00025615902,0.00022545288,0.0002447307],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028937322,0.00084313215,0.29713485,0.0021739001,0.0005995077,0.02015004,0.002089921,0.0014717041,0.3450449,0.0067906943,0.0017366813,0.319071],"study_design_scores_gemma":[0.00005246926,0.0012842079,0.9602406,0.00019392432,0.00019306994,0.013373449,0.00089691975,0.0016987708,0.012739876,0.004451703,0.004840675,0.00003438338],"about_ca_topic_score_codex":0.002966887,"about_ca_topic_score_gemma":0.0039068344,"teacher_disagreement_score":0.002966887,"about_ca_system_score_codex":0.00026347686,"about_ca_system_score_gemma":0.00041521227,"threshold_uncertainty_score":0.006813705},"labels":[],"label_agreement":null},{"id":"W4310700692","doi":"10.1002/hbm.26165","title":"Fast three‐dimensional image generation for healthy brain aging using diffeomorphic registration","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Center for Innovative Medicine; Eisai Incorporated; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; VINNOVA; Takeda Pharmaceuticals U.S.A.; Barncancerfonden; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; Eisai; Fundación CajaCanarias; Alzheimer's Association; Stiftelsen för Gamla Tjänarinnor; Fujirebio US; Pfizer; BioClinica; Biogen; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; AbbVie; Hjärnfonden; F. Hoffmann-La Roche; Merck; Alzheimerfonden; Alzheimer's Drug Discovery Foundation; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Demensfonden; Meso Scale Diagnostics","keywords":"Neuroimaging; Artificial intelligence; Image registration; Magnetic resonance imaging; Pattern recognition (psychology); Computer science; Computer vision; Psychology; Image (mathematics); Neuroscience; Medicine; Radiology","score_opus":0.20356372646919996,"score_gpt":0.39389332839480556,"score_spread":0.1903296019256056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310700692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05144021,0.00013883294,0.94545656,0.00011490757,0.00006278666,0.00012332134,0.00017883084,0.0018323956,0.0006520582],"genre_scores_gemma":[0.44554543,0.0001429751,0.5519068,0.00008064762,0.000025583005,0.00017562657,0.00069027435,0.00046762836,0.0009650245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996474,0.00010422321,0.000024086328,0.000084923864,0.00011336337,0.000026033471],"domain_scores_gemma":[0.9989557,0.00045188633,0.00010536272,0.00025301683,0.00019624816,0.00003775086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015100137,0.0006522652,0.00041906882,0.001006576,0.00023729792,0.00057863747,0.0008426544,0.0007062434,0.0018370409],"category_scores_gemma":[0.00397653,0.000382847,0.0010088264,0.00049636204,0.00038360286,0.0004899402,0.0008235564,0.0006610725,0.00054897455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005751089,0.0001849204,0.0041383975,0.00027521033,0.0002680682,0.00044403947,0.00027212728,0.62797976,0.054793585,0.009400231,0.004396381,0.29727218],"study_design_scores_gemma":[0.000022839136,0.00007854104,0.0007719447,0.0000075498,0.000015589398,0.00016507297,0.000015821595,0.98313576,0.012232065,0.0022550172,0.0012820775,0.00001765343],"about_ca_topic_score_codex":0.0019248383,"about_ca_topic_score_gemma":0.0016514261,"teacher_disagreement_score":0.0019248383,"about_ca_system_score_codex":0.00041040365,"about_ca_system_score_gemma":0.00054605654,"threshold_uncertainty_score":0.007985771},"labels":[],"label_agreement":null},{"id":"W4311103151","doi":"10.1101/2022.12.01.518514","title":"High-frequency longitudinal white matter diffusion- &amp; myelin-based MRI database: reliability and variability","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"","keywords":"Intraclass correlation; Reliability (semiconductor); Consistency (knowledge bases); Repeatability; White matter; Fiber bundle; Diffusion MRI; Diffusion; Fiber; Computer science; Nuclear medicine; Nuclear magnetic resonance; Statistics; Magnetic resonance imaging; Medicine; Materials science; Mathematics; Radiology; Physics; Artificial intelligence; Reproducibility","score_opus":0.030333482124366103,"score_gpt":0.28518161278224397,"score_spread":0.25484813065787787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311103151","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94032454,0.0005592272,0.028404878,0.0001573699,0.00003191826,0.00020857393,0.028192647,0.00073236134,0.0013884633],"genre_scores_gemma":[0.9448144,0.00016185253,0.015138214,0.00004172353,0.00004100727,0.00030329698,0.038854435,0.000099626806,0.0005454636],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996639,0.0011439915,0.0005618481,0.00088043744,0.0006779529,0.000096830896],"domain_scores_gemma":[0.98141956,0.0060847737,0.0033275038,0.004632383,0.0041260608,0.00040970155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070444974,0.00034130935,0.0006330488,0.0018172554,0.00033171318,0.0010755269,0.00070723955,0.0006713556,0.0014906257],"category_scores_gemma":[0.016190844,0.00017852272,0.00032818603,0.0017561201,0.00039577094,0.00062279473,0.0007199109,0.0003173118,0.0010886779],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026201352,0.00079465116,0.80855626,0.00073742034,0.0018460994,0.0004477635,0.00075774634,0.010014231,0.022837382,0.0010094227,0.016566945,0.13381185],"study_design_scores_gemma":[0.00010177564,0.00040493842,0.9621031,0.000055972836,0.00030106617,0.0010492881,0.00019477987,0.020268677,0.008549498,0.0010414621,0.005860027,0.000069410045],"about_ca_topic_score_codex":0.0019204327,"about_ca_topic_score_gemma":0.0025473395,"teacher_disagreement_score":0.0070444974,"about_ca_system_score_codex":0.00023949225,"about_ca_system_score_gemma":0.00046054705,"threshold_uncertainty_score":0.037255287},"labels":[],"label_agreement":null},{"id":"W4311287570","doi":"10.1002/mrm.29552","title":"Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; University of Toronto; University of British Columbia; International Collaboration On Repair Discoveries; Hospital for Sick Children; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Magnetization transfer; Reproducibility; Nuclear magnetic resonance; Correlation; Correlation coefficient; Nuclear medicine; Myelin; Chemistry; Magnetic resonance imaging; Physics; Medicine; Internal medicine; Mathematics; Chromatography; Central nervous system; Statistics; Radiology","score_opus":0.023432144280844287,"score_gpt":0.3453809960211719,"score_spread":0.3219488517403276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311287570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99514115,0.0011666035,0.0033007872,0.000034406763,0.0000090686535,0.000010366253,0.00008874785,0.000037905815,0.00021099606],"genre_scores_gemma":[0.9976204,0.00011570434,0.0020406968,0.000021782082,0.000018170282,0.000010077634,0.000087914326,0.000014236755,0.0000709317],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978415,0.0007573919,0.0002059807,0.00067446945,0.00042988284,0.0000907336],"domain_scores_gemma":[0.990682,0.0039618392,0.0031261458,0.0010647796,0.00094545854,0.00021962893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004643717,0.00063846173,0.000490808,0.00077391835,0.00018244263,0.0005219253,0.00033496096,0.0004822853,0.00026032515],"category_scores_gemma":[0.014174005,0.000285817,0.0002939695,0.00045438632,0.0006211637,0.0005394249,0.00046802394,0.0002651739,0.00015523736],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008033588,0.000050875773,0.9407516,0.000118002965,0.0007079729,0.00020043924,0.00035047816,0.0011191812,0.025950357,0.00008609068,0.0001219325,0.029739736],"study_design_scores_gemma":[0.000014996988,0.00049417245,0.9896741,0.000013577793,0.00013247784,0.0008103585,0.00006674084,0.0019542107,0.0063857706,0.00020143535,0.00023647334,0.000015647001],"about_ca_topic_score_codex":0.0012227958,"about_ca_topic_score_gemma":0.0014266832,"teacher_disagreement_score":0.004643717,"about_ca_system_score_codex":0.00017652097,"about_ca_system_score_gemma":0.00020398616,"threshold_uncertainty_score":0.024558663},"labels":[],"label_agreement":null},{"id":"W4311472414","doi":"10.52294/1cdce19c-e6db-4684-97cb-ae709da06a3f","title":"Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI","year":2022,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; Health Sciences Centre; University Health Network; Western University; University of Toronto; Centre for Addiction and Mental Health; Queen's University; Toronto Western Hospital; University of British Columbia; Sunnybrook Health Science Centre; St. Michael's Hospital; University of Alberta; University of Calgary; Baycrest Hospital","funders":"","keywords":"Protocol (science); Neuroimaging; Computer science; Reliability (semiconductor); Visual inspection; Artificial intelligence; Reproducibility; Quality (philosophy); Neuroscience; Psychology; Medicine; Statistics; Pathology; Mathematics","score_opus":0.07041366652472753,"score_gpt":0.4066132231350453,"score_spread":0.33619955661031775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311472414","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012917491,0.000544168,0.92921054,0.00054102397,0.0006046133,0.0048896796,0.007122747,0.039712742,0.004456917],"genre_scores_gemma":[0.040412225,0.0003877105,0.8849838,0.00083787047,0.00021193402,0.023567785,0.010128362,0.03416092,0.0053094816],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9942701,0.0016220781,0.0011030125,0.0009830827,0.0017471403,0.0002745843],"domain_scores_gemma":[0.9649556,0.011903649,0.0020490142,0.007905763,0.012524053,0.00066182076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021363614,0.002168735,0.0011950036,0.0036089986,0.002232335,0.0032636996,0.003567633,0.0023638795,0.043009236],"category_scores_gemma":[0.06434992,0.001596825,0.0012391915,0.0017095754,0.0020722868,0.0020189593,0.0033961441,0.0042434,0.013196946],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037491578,0.0006340324,0.010704178,0.0054693692,0.00063680235,0.0015189694,0.004402298,0.012645597,0.16858336,0.029397523,0.30769363,0.454565],"study_design_scores_gemma":[0.000935761,0.0012319641,0.03596022,0.0017795337,0.00055953185,0.0049078865,0.0011326009,0.1015913,0.23090811,0.061321866,0.55845636,0.0012148954],"about_ca_topic_score_codex":0.0035905442,"about_ca_topic_score_gemma":0.0058069103,"teacher_disagreement_score":0.043009236,"about_ca_system_score_codex":0.00131069,"about_ca_system_score_gemma":0.0057008425,"threshold_uncertainty_score":0.14388031},"labels":[],"label_agreement":null},{"id":"W4311574494","doi":"10.1038/s41398-022-02261-w","title":"Differential association of antioxidative defense genes with white matter integrity in youth bipolar disorder","year":2022,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Hospital for Sick Children; University of Toronto; Heart and Stroke Foundation; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; University of Toronto; Myriad Genetics; Fondation Brain Canada; Centre for Addiction and Mental Health Foundation; Temerty Faculty of Medicine, University of Toronto; Government of Canada; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; SOD2; White matter; Allele; Oxidative stress; Diffusion MRI; Internal medicine; Superoxide dismutase; Psychology; Endocrinology; Biology; Genetics; Medicine; Magnetic resonance imaging; Gene","score_opus":0.027996501178580567,"score_gpt":0.29947439151782645,"score_spread":0.2714778903392459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311574494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996056,0.000167213,0.000036745136,0.000016007525,0.0000021655587,0.0000019825093,0.000087689376,0.0000014934855,0.00008118778],"genre_scores_gemma":[0.999488,0.00011665744,0.00010717254,0.00001834993,0.0000039580414,0.000004512261,0.00014631603,0.0000020464372,0.000112963935],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998634,0.00002413138,0.0000193318,0.000050602943,0.000020517336,0.000021990865],"domain_scores_gemma":[0.9996983,0.000030338708,0.00018258514,0.00001611086,0.00003408809,0.00003869345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025006992,0.00032958004,0.00028806407,0.00043872633,0.00027640312,0.00034706513,0.00012057328,0.00029663704,0.0010870991],"category_scores_gemma":[0.0007465602,0.00021354399,0.00025103596,0.00042337293,0.0001787968,0.00014870286,0.00023657885,0.0002633606,0.00011056763],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040697612,0.000037810405,0.9922047,0.000018469544,0.00009112277,0.00017636768,0.00023343385,0.000035951754,0.0033638864,0.00004023768,0.00011486877,0.0032761414],"study_design_scores_gemma":[0.0000056072204,0.000041120027,0.9994223,0.000006350493,0.000028217484,0.0001829181,0.00007532624,0.000056715126,0.00009824488,0.000031188756,0.00005074523,0.0000012396005],"about_ca_topic_score_codex":0.0048389714,"about_ca_topic_score_gemma":0.009913515,"teacher_disagreement_score":0.0048389714,"about_ca_system_score_codex":0.0002105108,"about_ca_system_score_gemma":0.00012934179,"threshold_uncertainty_score":0.00962162},"labels":[],"label_agreement":null},{"id":"W4311877713","doi":"10.3389/fnins.2022.1040799","title":"Integration of structural brain networks is related to openness to experience: A diffusion MRI study with CSD-based tractography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Openness to experience; Connectome; Tractography; Psychology; Diffusion MRI; Connectomics; Trait; Personality; Cognitive psychology; Human Connectome Project; Neuroscience; Computer science; Social psychology; Magnetic resonance imaging; Medicine; Functional connectivity","score_opus":0.024578000767506724,"score_gpt":0.33974930545799886,"score_spread":0.31517130469049215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311877713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966101,0.00017004364,0.0027122346,0.000041587216,0.0000031034224,0.000018868546,0.00009908064,0.000011876072,0.0003330995],"genre_scores_gemma":[0.99789315,0.00013207685,0.0016514835,0.000007819874,0.00000870677,0.00001187955,0.00009268569,0.0000061680976,0.00019605248],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998596,0.000033058826,0.00001195691,0.00005236823,0.000021484337,0.00002159415],"domain_scores_gemma":[0.9994609,0.00013592688,0.00018930632,0.0000642977,0.000044772918,0.000104804625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005371015,0.00022851104,0.00023470062,0.0011915057,0.00025848998,0.00052525307,0.00014867267,0.00029993244,0.001332197],"category_scores_gemma":[0.0015799649,0.0001874493,0.00032472707,0.0006984723,0.00050256925,0.00042959323,0.0004921533,0.00034090644,0.00011709452],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027042446,0.0007063447,0.68075216,0.0003440662,0.0010943509,0.0063843913,0.00549277,0.003929733,0.2117454,0.0019098929,0.00072915136,0.08420749],"study_design_scores_gemma":[0.000033950146,0.00041342532,0.9785671,0.000024577801,0.00012769652,0.005402555,0.0005969675,0.008500547,0.0042352155,0.0014019215,0.00066102075,0.000035173183],"about_ca_topic_score_codex":0.0014523565,"about_ca_topic_score_gemma":0.0016980134,"teacher_disagreement_score":0.0014523565,"about_ca_system_score_codex":0.00016537738,"about_ca_system_score_gemma":0.00015532946,"threshold_uncertainty_score":0.0044566393},"labels":[],"label_agreement":null},{"id":"W4311924630","doi":"10.1101/2022.12.18.520881","title":"A Unified Filtering Method for Estimating Asymmetric Orientation Distribution Functions: Where and How Asymmetry Occurs in the Brain","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Computer science; Asymmetry; Voxel; Orientation (vector space); Diffusion MRI; Artificial intelligence; Human Connectome Project; Algorithm; Pattern recognition (psychology); Computer vision; Mathematics; Functional connectivity; Magnetic resonance imaging; Physics","score_opus":0.042332525860050964,"score_gpt":0.3286316681822924,"score_spread":0.2862991423222414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311924630","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010162811,0.00011527999,0.9887693,0.00007423145,0.000016468755,0.000020384294,0.0000834882,0.0004476932,0.00031035935],"genre_scores_gemma":[0.20164913,0.00045773925,0.7952451,0.00011249565,0.00009590985,0.00009112104,0.00054656464,0.00035337848,0.0014486003],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993723,0.0001162629,0.000054796077,0.00018063495,0.00020936503,0.00006668959],"domain_scores_gemma":[0.9985505,0.00052834745,0.00022838044,0.0002092178,0.00040184398,0.00008160056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017800676,0.00082704495,0.0007574286,0.0021682282,0.00054957136,0.0015850388,0.00084879267,0.0009890675,0.0015936837],"category_scores_gemma":[0.005631608,0.00038833404,0.0010291188,0.0014172447,0.0007083147,0.0014271839,0.0009314092,0.0010611892,0.00064943143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003040273,0.000097216114,0.008028246,0.0002724037,0.00019376427,0.00030432144,0.00035494563,0.1046595,0.11180917,0.018439353,0.0047982302,0.75073886],"study_design_scores_gemma":[0.000020933947,0.00004227096,0.006585084,0.000044424647,0.00007069798,0.00034001016,0.00005710797,0.94866014,0.027509307,0.012968259,0.003631385,0.00007035523],"about_ca_topic_score_codex":0.0061698896,"about_ca_topic_score_gemma":0.0067491313,"teacher_disagreement_score":0.0061698896,"about_ca_system_score_codex":0.0006039079,"about_ca_system_score_gemma":0.0011504682,"threshold_uncertainty_score":0.012267947},"labels":[],"label_agreement":null},{"id":"W4312086371","doi":"10.1002/alz.068292","title":"White Matter Correlates of Spoken Discourse in Cerebrovascular Disease","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Audiology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.033520605855789705,"score_gpt":0.3179134904236161,"score_spread":0.2843928845678264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99569976,0.0011333954,0.0001808062,0.00016626509,0.0000114150935,0.000012099116,0.0009324514,0.0000112949565,0.0018525487],"genre_scores_gemma":[0.9984609,0.00025870427,0.00023536586,0.000025233414,0.000027613944,0.0000104107785,0.00046671715,0.0000055217565,0.00050950394],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970335,0.00005090018,0.00003729474,0.000109369525,0.00006017054,0.000038871254],"domain_scores_gemma":[0.99762964,0.0005244801,0.001126311,0.00014704661,0.00042930737,0.00014311139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056714943,0.0003683411,0.00032157847,0.0012495761,0.0006408191,0.0011973076,0.00034827355,0.000504335,0.0040412163],"category_scores_gemma":[0.004846449,0.00013135631,0.00016008112,0.0011506638,0.00045936962,0.00053872686,0.0005926207,0.0004002442,0.0003464238],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010315652,0.00013522625,0.95260054,0.00035561415,0.00031332418,0.0013135609,0.0043901266,0.00038391424,0.010179505,0.00055468624,0.0014869221,0.027255062],"study_design_scores_gemma":[0.000005683959,0.000035972615,0.9972812,0.00003642067,0.000038756745,0.0003987981,0.00046583908,0.0003300282,0.0004644351,0.0005439616,0.00038818776,0.000010839675],"about_ca_topic_score_codex":0.023089394,"about_ca_topic_score_gemma":0.029140703,"teacher_disagreement_score":0.023089394,"about_ca_system_score_codex":0.00071645697,"about_ca_system_score_gemma":0.00059882825,"threshold_uncertainty_score":0.04591},"labels":[],"label_agreement":null},{"id":"W4312086405","doi":"10.1002/alz.068795","title":"Resistance training improves white matter structural connectivity in older adults at‐risk for cognitive decline","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Western University","funders":"","keywords":"Resistance training; White matter; Cognition; Cognitive decline; Psychology; Gerontology; Training (meteorology); Resistance (ecology); Cognitive training; Physical medicine and rehabilitation; Medicine; Cognitive psychology; Neuroscience; Physical therapy; Dementia; Internal medicine; Geography; Disease; Magnetic resonance imaging; Biology","score_opus":0.038947083124337915,"score_gpt":0.3301936722006875,"score_spread":0.2912465890763496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975363,0.0015109709,0.00013873607,0.00007534969,0.000055264663,0.00027323826,0.00009858091,0.000021953245,0.0002895344],"genre_scores_gemma":[0.9959573,0.0012885097,0.00078532053,0.00016973271,0.00009464832,0.00070203334,0.00018528767,0.000003624668,0.0008134907],"study_design_codex":"randomized_trial","study_design_gemma":"observational","domain_scores_codex":[0.9997768,0.00006890157,0.000029688736,0.000053646578,0.000020923166,0.000050043658],"domain_scores_gemma":[0.999617,0.000075480944,0.00007991422,0.000023086408,0.00005510572,0.00014946112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006765085,0.0006733916,0.0013588422,0.00031617997,0.00043833675,0.0003608493,0.00032089307,0.0008835505,0.0030889018],"category_scores_gemma":[0.00076138385,0.00033035706,0.00087248103,0.00016428881,0.0002643021,0.00031597717,0.0002854831,0.00066622946,0.00025784044],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.7204365,0.10271093,0.023589022,0.0030358245,0.005523403,0.00015639041,0.00043425855,0.0010223537,0.034509234,0.000107900385,0.0013663223,0.107107855],"study_design_scores_gemma":[0.23728172,0.5734121,0.17624497,0.00038034044,0.004282821,0.00012682634,0.00022199359,0.0018370483,0.004404407,0.0002536712,0.0015064327,0.00004762828],"about_ca_topic_score_codex":0.0012275979,"about_ca_topic_score_gemma":0.0018377142,"teacher_disagreement_score":0.0030889018,"about_ca_system_score_codex":0.0001440916,"about_ca_system_score_gemma":0.00034447157,"threshold_uncertainty_score":0.010333359},"labels":[],"label_agreement":null},{"id":"W4312086512","doi":"10.1002/alz.066686","title":"Cerebrovascular injury markers explain the effect of systemic vascular risk on cognitive decline in older adults with lower amyloid burden","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Sunnybrook Hospital","funders":"","keywords":"Pittsburgh compound B; Medicine; Cognitive decline; Internal medicine; Cardiology; Effects of sleep deprivation on cognitive performance; Cerebral amyloid angiopathy; Framingham Risk Score; Neuroimaging; Hyperintensity; Cognition; Dementia; Disease; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.010788339552064754,"score_gpt":0.27557401571480294,"score_spread":0.2647856761627382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98504144,0.002797655,0.0074996185,0.0007374305,0.00008070801,0.00004790047,0.0021206848,0.00017337478,0.0015012652],"genre_scores_gemma":[0.99627954,0.00028073502,0.0015591575,0.00012179343,0.000076991346,0.000039849558,0.0009077297,0.000037341917,0.00069692195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990965,0.00028944432,0.000078737474,0.00035574732,0.00007807044,0.00010152964],"domain_scores_gemma":[0.99537283,0.0021439288,0.00091182085,0.00088787015,0.000385653,0.000297925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003810669,0.0013903447,0.0009949025,0.0012651858,0.0005062688,0.0015451912,0.00091912795,0.0011181366,0.004807546],"category_scores_gemma":[0.009958232,0.0006188384,0.0031042208,0.00092205673,0.00043162823,0.00094421644,0.0011806963,0.0013909327,0.00073068094],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023431333,0.00033610698,0.9656803,0.0001816536,0.0041376273,0.0002566272,0.00029321332,0.005071551,0.0013419914,0.0006732131,0.0012294375,0.018455146],"study_design_scores_gemma":[0.00010717666,0.0005181301,0.9557524,0.00008725583,0.0024373853,0.0003334052,0.00014957659,0.034885596,0.0006379157,0.0035052486,0.0015494552,0.00003630239],"about_ca_topic_score_codex":0.012232151,"about_ca_topic_score_gemma":0.009132957,"teacher_disagreement_score":0.012232151,"about_ca_system_score_codex":0.00041312134,"about_ca_system_score_gemma":0.0006834392,"threshold_uncertainty_score":0.024321914},"labels":[],"label_agreement":null},{"id":"W4312086854","doi":"10.1002/alz.066978","title":"Lower myelin content is associated with poorer gait variability in older adults with cerebral small vessel disease and mild cognitive impairment","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health","funders":"","keywords":"White matter; Myelin; Cognitive decline; Corpus callosum; Hyperintensity; Cingulum (brain); Psychology; Internal medicine; Cardiology; Medicine; Magnetic resonance imaging; Disease; Neuroscience; Dementia; Radiology; Central nervous system; Fractional anisotropy","score_opus":0.039101377893707726,"score_gpt":0.2804363250279132,"score_spread":0.2413349471342055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937195,0.00021907575,0.000071828166,0.00004078187,0.0000054381007,0.0000024613219,0.00012719267,0.000004581476,0.00015667632],"genre_scores_gemma":[0.99965596,0.000051410192,0.000053768494,0.000013417559,0.0000074701043,0.0000025335332,0.00012900349,8.579497e-7,0.0000856163],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976903,0.0000562503,0.000037729707,0.000062542815,0.000038629638,0.000035817797],"domain_scores_gemma":[0.99882644,0.0001843998,0.00062515476,0.00007499764,0.0001462775,0.00014271631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005119089,0.0004111087,0.00038588716,0.0007020356,0.00034747017,0.0005649509,0.00032061356,0.0004959267,0.001573551],"category_scores_gemma":[0.0028486946,0.00019327509,0.00040760246,0.00073026674,0.00020880446,0.00033969665,0.00037752613,0.00045321937,0.00015512948],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025159566,0.000049279934,0.99714214,0.000015636575,0.00017396235,0.00007198629,0.00005282898,0.000084818144,0.000309913,0.000011172951,0.00009041003,0.0017462968],"study_design_scores_gemma":[0.000004041193,0.00005982869,0.9994809,0.0000040865916,0.000034201672,0.0000827939,0.00004299922,0.00021360374,0.000025875292,0.000021214804,0.00002872411,0.0000017565469],"about_ca_topic_score_codex":0.006538082,"about_ca_topic_score_gemma":0.0072677406,"teacher_disagreement_score":0.006538082,"about_ca_system_score_codex":0.00017350444,"about_ca_system_score_gemma":0.0001761667,"threshold_uncertainty_score":0.013000071},"labels":[],"label_agreement":null},{"id":"W4312087182","doi":"10.1002/alz.065756","title":"White Matter Correlates of Spoken Discourse in Cerebrovascular Disease","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Audiology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.033520605855789705,"score_gpt":0.3179134904236161,"score_spread":0.2843928845678264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99569976,0.0011333954,0.0001808062,0.00016626509,0.0000114150935,0.000012099116,0.0009324514,0.0000112949565,0.0018525487],"genre_scores_gemma":[0.9984609,0.00025870427,0.00023536586,0.000025233414,0.000027613944,0.0000104107785,0.00046671715,0.0000055217565,0.00050950394],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970335,0.00005090018,0.00003729474,0.000109369525,0.00006017054,0.000038871254],"domain_scores_gemma":[0.99762964,0.0005244801,0.001126311,0.00014704661,0.00042930737,0.00014311139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056714943,0.0003683411,0.00032157847,0.0012495761,0.0006408191,0.0011973076,0.00034827355,0.000504335,0.0040412163],"category_scores_gemma":[0.004846449,0.00013135631,0.00016008112,0.0011506638,0.00045936962,0.00053872686,0.0005926207,0.0004002442,0.0003464238],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010315652,0.00013522625,0.95260054,0.00035561415,0.00031332418,0.0013135609,0.0043901266,0.00038391424,0.010179505,0.00055468624,0.0014869221,0.027255062],"study_design_scores_gemma":[0.000005683959,0.000035972615,0.9972812,0.00003642067,0.000038756745,0.0003987981,0.00046583908,0.0003300282,0.0004644351,0.0005439616,0.00038818776,0.000010839675],"about_ca_topic_score_codex":0.023089394,"about_ca_topic_score_gemma":0.029140703,"teacher_disagreement_score":0.023089394,"about_ca_system_score_codex":0.00071645697,"about_ca_system_score_gemma":0.00059882825,"threshold_uncertainty_score":0.04591},"labels":[],"label_agreement":null},{"id":"W4312087263","doi":"10.1002/alz.066988","title":"Higher physical activity is associated with greater myelin content in older adults with cerebral small vessel disease and mild cognitive impairment","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health","funders":"","keywords":"Myelin; White matter; Hyperintensity; Corpus callosum; Cognitive decline; Psychology; Internal medicine; Population; Physiology; Medicine; Dementia; Magnetic resonance imaging; Endocrinology; Cardiology; Pathology; Disease; Radiology; Central nervous system","score_opus":0.05984605743675004,"score_gpt":0.2982998726162618,"score_spread":0.23845381517951175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99906737,0.0003723044,0.00009624433,0.00006284042,0.00000899766,0.0000035683613,0.00016033526,0.0000045589877,0.0002238228],"genre_scores_gemma":[0.99961627,0.00008148629,0.0000461765,0.000016844135,0.0000129069285,0.0000029020475,0.00012560924,9.429012e-7,0.00009683845],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996412,0.0001270802,0.000043546395,0.00008843988,0.00004026212,0.00005949448],"domain_scores_gemma":[0.9987031,0.00026509963,0.00054822426,0.00010311758,0.00014032915,0.00023997838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063107436,0.00035314052,0.00039365664,0.0006222237,0.0003388024,0.0006227933,0.00034451,0.00052609533,0.0018363056],"category_scores_gemma":[0.0024524552,0.0002679448,0.0005741442,0.0007692365,0.00022642424,0.00028483794,0.0004764191,0.0005601488,0.00017664001],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016675045,0.000040364233,0.99847406,0.000010708786,0.0001788161,0.00003374102,0.000028360757,0.000035486664,0.00014026297,0.0000071539466,0.000047426172,0.00083689333],"study_design_scores_gemma":[0.0000046889977,0.000050057108,0.99958116,0.0000033377437,0.0000472946,0.000044877237,0.000028469314,0.0001759463,0.00001513122,0.000013303147,0.000034506662,0.0000012134905],"about_ca_topic_score_codex":0.007927757,"about_ca_topic_score_gemma":0.007382083,"teacher_disagreement_score":0.007927757,"about_ca_system_score_codex":0.00014824912,"about_ca_system_score_gemma":0.00018592397,"threshold_uncertainty_score":0.015763223},"labels":[],"label_agreement":null},{"id":"W4312087292","doi":"10.1002/alz.066359","title":"An examination of white matter integrity and functional network organization in Subjective Cognitive Decline using Diffusional Kurtosis Imaging‐based tractography resting state fMRI","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Inferior longitudinal fasciculus; Fasciculus; Uncinate fasciculus; Fractional anisotropy; White matter; Cingulum (brain); Resting state fMRI; Medicine; Posterior cingulate; Boston Naming Test; Neuroscience; Cognition; Connectome; Clinical Dementia Rating; Diffusion MRI; Psychology; Audiology; Functional connectivity; Magnetic resonance imaging; Neuropsychology; Cognitive impairment; Radiology","score_opus":0.04443760373324732,"score_gpt":0.3156384580665687,"score_spread":0.27120085433332136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99940217,0.00002849885,0.00039187173,0.000005940205,4.2260592e-7,0.0000039877796,0.000059987884,0.0000037363998,0.0001032693],"genre_scores_gemma":[0.999546,0.000013340857,0.00029860454,0.0000025669663,0.0000014105683,0.0000040863974,0.00007003322,0.000001143908,0.000062810905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992573,0.000020921714,0.00000856143,0.000022027038,0.0000116475085,0.000010998273],"domain_scores_gemma":[0.99957687,0.00012298556,0.0001526082,0.000038700266,0.000053147094,0.000055667937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004551788,0.00025054242,0.0001354567,0.00085018855,0.00017853652,0.00035824926,0.00014101331,0.00021084365,0.0010794783],"category_scores_gemma":[0.0012026506,0.00011422832,0.00014807901,0.00023197907,0.0002670769,0.00032808562,0.00019951919,0.00014985153,0.000069492875],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079452747,0.00012362182,0.9516259,0.00004913249,0.00017039976,0.00045117806,0.0007757523,0.000908628,0.033751287,0.0002132668,0.00015870028,0.01097771],"study_design_scores_gemma":[0.000008704186,0.00012889897,0.9957931,0.0000029140504,0.000016174792,0.00048462366,0.00010625371,0.0022250284,0.0010132527,0.00014411833,0.0000713971,0.0000056518847],"about_ca_topic_score_codex":0.0033394613,"about_ca_topic_score_gemma":0.004701397,"teacher_disagreement_score":0.0033394613,"about_ca_system_score_codex":0.00016420675,"about_ca_system_score_gemma":0.0001211084,"threshold_uncertainty_score":0.0066400766},"labels":[],"label_agreement":null},{"id":"W4312087783","doi":"10.1002/alz.064157","title":"Plasma phospho‐tau predicts differences in white matter microstructural complexity and cognition in non‐demented older adults","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Dementia; Biomarker; Neuropsychology; Neuroimaging; Psychology; Internal medicine; Cognition; Medicine; Fornix; Magnetic resonance imaging; Audiology; Disease; Neuroscience; Biology; Hippocampus; Radiology","score_opus":0.04020375663040978,"score_gpt":0.2927602548210552,"score_spread":0.25255649819064546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99962366,0.00006785758,0.00002648799,0.000008016798,0.0000019030474,0.000004524962,0.00009997092,0.0000021000128,0.00016556511],"genre_scores_gemma":[0.99967873,0.000029961995,0.00004389235,0.000008941984,0.0000046017717,0.0000040260043,0.00011466509,5.1929845e-7,0.000114470604],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989915,0.000016567052,0.000016789345,0.000032221265,0.000019364727,0.000015981639],"domain_scores_gemma":[0.9995455,0.000084327956,0.00019357832,0.000032413373,0.0000474643,0.00009667601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031918107,0.0004633205,0.00027992687,0.0006151109,0.00033048683,0.0005116818,0.0001794655,0.00050690596,0.0015557456],"category_scores_gemma":[0.0013193293,0.00020468736,0.00022259563,0.00038938998,0.00017435472,0.00031522947,0.00031335495,0.00028005074,0.000261149],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038685757,0.00007530444,0.9968183,0.0000107678525,0.000060688373,0.00010165164,0.0001030312,0.000061159626,0.0011524106,0.000011767694,0.000052650295,0.0011653845],"study_design_scores_gemma":[0.0000029291625,0.000076539414,0.9996227,0.0000013215645,0.000009855058,0.000070739465,0.0000429271,0.00008410532,0.000052785977,0.000014801829,0.000020263273,0.0000010141981],"about_ca_topic_score_codex":0.0028421679,"about_ca_topic_score_gemma":0.0032522748,"teacher_disagreement_score":0.0028421679,"about_ca_system_score_codex":0.00013265102,"about_ca_system_score_gemma":0.00011530859,"threshold_uncertainty_score":0.005651295},"labels":[],"label_agreement":null},{"id":"W4312213372","doi":"10.1101/2022.12.24.22283926","title":"Multimodal Analysis of Secondary Cerebellar Alterations after Pediatric Traumatic Brain Injury","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Brain Injury Research Center; National Health and Medical Research Council; Medical Research Council; Helse Midt-Norge; South African Medical Research Council; Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Cerebellum; Traumatic brain injury; Neuroimaging; Diffusion MRI; White matter; Psychology; Neuroscience; Brain size; Voxel-based morphometry; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.04868032266590174,"score_gpt":0.3628992471601479,"score_spread":0.31421892449424615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312213372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909633,0.0009942336,0.0039786743,0.0000749725,0.000011108356,0.000024615487,0.0033554076,0.00011429369,0.00048337178],"genre_scores_gemma":[0.994796,0.0003171329,0.0021466347,0.000024075345,0.000011979374,0.00003085468,0.0024483015,0.00002594273,0.00019916084],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977237,0.000046678364,0.000027512253,0.00008466592,0.00003498526,0.00003378135],"domain_scores_gemma":[0.9994217,0.0000973946,0.00021064155,0.00006932952,0.00015037988,0.000050630155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006376365,0.0003677434,0.00043822432,0.001956312,0.00025621935,0.0005563386,0.0003715418,0.00028243448,0.0019229623],"category_scores_gemma":[0.001986715,0.00015660112,0.0004662999,0.00096064387,0.00022839603,0.0003168934,0.00067198736,0.00027212294,0.00025226633],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081983587,0.00007036064,0.9244237,0.00031378597,0.0008902349,0.0008920251,0.00026230683,0.0030540284,0.021230847,0.00021627512,0.0018525781,0.045974135],"study_design_scores_gemma":[0.000017623157,0.00014871688,0.986217,0.000056348566,0.00030899548,0.0014476912,0.00021976918,0.0068848245,0.0033811333,0.00043514633,0.00086564233,0.000017070673],"about_ca_topic_score_codex":0.0057487423,"about_ca_topic_score_gemma":0.010404705,"teacher_disagreement_score":0.0057487423,"about_ca_system_score_codex":0.00033613786,"about_ca_system_score_gemma":0.00033031046,"threshold_uncertainty_score":0.011430562},"labels":[],"label_agreement":null},{"id":"W4312278544","doi":"10.1007/978-3-031-21206-2_11","title":"Clustering in Tractography Using Autoencoders (CINTA)","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Cluster analysis; Artificial intelligence; Computer science; Pattern recognition (psychology); Streamlines, streaklines, and pathlines; Autoencoder; Thresholding; Diffusion MRI; Artificial neural network; Magnetic resonance imaging; Physics; Image (mathematics); Medicine; Radiology","score_opus":0.0737373760954931,"score_gpt":0.34269315229404446,"score_spread":0.2689557761985514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312278544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016400858,0.0006810725,0.995989,0.000069532485,0.00008364254,0.000013728761,0.000063481326,0.0006623558,0.0007970464],"genre_scores_gemma":[0.042815708,0.0014237508,0.94640285,0.00009309893,0.00016378248,0.00010730316,0.0003885811,0.00053723616,0.008067759],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99957913,0.000107440115,0.00002507429,0.00015369008,0.0001006396,0.000033981403],"domain_scores_gemma":[0.99889624,0.0005696572,0.00008275218,0.00020375749,0.00020577098,0.000041777173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009335206,0.0008192191,0.001117617,0.0011105738,0.00057300075,0.0013610454,0.0014586201,0.0015989298,0.0038609165],"category_scores_gemma":[0.0021440154,0.0009872759,0.0014781106,0.001791737,0.0007799203,0.0012402666,0.0012207638,0.0022310906,0.0021607894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000704456,0.00005069107,0.00056395784,0.00026055906,0.00019416405,0.00011674707,0.0001665179,0.38292447,0.011258277,0.050586257,0.012354119,0.54145384],"study_design_scores_gemma":[0.000003572385,0.000016372027,0.00030415368,0.000025054875,0.000019462408,0.000089937246,0.000013112369,0.971839,0.0031128246,0.019360533,0.0051979288,0.000018029938],"about_ca_topic_score_codex":0.009615598,"about_ca_topic_score_gemma":0.014572873,"teacher_disagreement_score":0.009615598,"about_ca_system_score_codex":0.0008855707,"about_ca_system_score_gemma":0.0009802502,"threshold_uncertainty_score":0.019119263},"labels":[],"label_agreement":null},{"id":"W4312612315","doi":"10.52547/nl.1.1.21","title":"Diffusion tensor imaging (DTI) and plasma p-tau 181 in Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Neurology Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Biomarker; White matter; Diffusion MRI; Disease; Internal medicine; Alzheimer's disease; Medicine; Pathogenesis; Tau protein; Psychology; Oncology; Neuroscience; Pathology; Magnetic resonance imaging; Biology; Biochemistry; Radiology","score_opus":0.03587092914053536,"score_gpt":0.3040637019575926,"score_spread":0.2681927728170572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312612315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791677,0.012680339,0.0025003087,0.0008953329,0.00012110932,0.0000390673,0.0008059807,0.000035314562,0.0037548342],"genre_scores_gemma":[0.9903396,0.004739926,0.0031036942,0.00011353333,0.00016007651,0.000026911319,0.00047285078,0.000008059171,0.00103537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998247,0.00005264149,0.000028778004,0.000040687235,0.00003880778,0.000014468516],"domain_scores_gemma":[0.9995072,0.000094299896,0.00022648783,0.000040653136,0.00008215826,0.000049188144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006593437,0.00048205574,0.0002942967,0.001063826,0.0002554381,0.00065728714,0.00019164334,0.0003492937,0.0009220668],"category_scores_gemma":[0.0015305381,0.000119246695,0.0002241527,0.0010162378,0.00030899077,0.00062312605,0.00027253997,0.00044353417,0.00022693386],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020402023,0.00029056292,0.8458059,0.0005947418,0.0005779098,0.0037674662,0.0006261643,0.0013701125,0.02698818,0.0015571376,0.002884408,0.11349729],"study_design_scores_gemma":[0.000028992383,0.0003277399,0.98413634,0.00007398975,0.00015640837,0.0047007725,0.00020841595,0.0018935994,0.002006228,0.0034270592,0.0030160954,0.000024262028],"about_ca_topic_score_codex":0.0025169454,"about_ca_topic_score_gemma":0.0021139414,"teacher_disagreement_score":0.0025169454,"about_ca_system_score_codex":0.00027514505,"about_ca_system_score_gemma":0.00038393083,"threshold_uncertainty_score":0.005004525},"labels":[],"label_agreement":null},{"id":"W4313038530","doi":"10.1016/j.procs.2022.11.103","title":"Reproduced correlations between integrity of white matter tracts and self-reported anxiety","year":2022,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Research Council Canada; National Research Center \"Kurchatov Institute\"","keywords":"White matter; Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); Anxiety; Fasciculus; Diffusion MRI; Psychology; Corpus callosum; Lateralization of brain function; Superior longitudinal fasciculus; Medicine; Audiology; Clinical psychology; Neuroscience; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.057215155383079114,"score_gpt":0.33287231757531144,"score_spread":0.27565716219223235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313038530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956293,0.00042807695,0.0023316152,0.0000466006,0.000012212571,0.000021500964,0.00035677876,0.000026815169,0.0011471129],"genre_scores_gemma":[0.9990374,0.000056176013,0.00056183495,0.000007631953,0.000006599326,0.0000073845817,0.00018078533,0.000005026405,0.0001371413],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883217,0.0003012908,0.0001887101,0.0003785631,0.00021344371,0.00008577866],"domain_scores_gemma":[0.9930488,0.0022278219,0.0026927048,0.0011613176,0.0006158912,0.00025341703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013890531,0.00029910775,0.00019575084,0.00072073017,0.00018737496,0.00052061625,0.00016649108,0.0002943492,0.001946821],"category_scores_gemma":[0.007330328,0.00014112295,0.0002408249,0.0004460353,0.0004985556,0.00033462935,0.0003739414,0.00035095934,0.00017345893],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000195563,0.000056178378,0.96999073,0.00007088945,0.00043403814,0.00026187324,0.00055773713,0.00023931717,0.016166648,0.00026914416,0.00013605616,0.011621818],"study_design_scores_gemma":[0.0000016701605,0.00007864731,0.99799323,0.0000042471875,0.00003528718,0.0004294229,0.00007123185,0.00018982193,0.000895456,0.00017116434,0.00012567516,0.00000427213],"about_ca_topic_score_codex":0.00089675555,"about_ca_topic_score_gemma":0.0020641221,"teacher_disagreement_score":0.001946821,"about_ca_system_score_codex":0.00014568312,"about_ca_system_score_gemma":0.00018473683,"threshold_uncertainty_score":0.0073460937},"labels":[],"label_agreement":null},{"id":"W4313252611","doi":"10.1016/j.nicl.2022.103309","title":"White matter microstructure predicts measures of clinical symptoms in chronic back pain patients","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Nova Scotia Health Authority","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Melbourne","keywords":"Corpus callosum; Splenium; White matter; Spinothalamic tract; Diffusion MRI; Psychology; Medicine; Physical medicine and rehabilitation; Magnetic resonance imaging; Neuroscience; Nociception; Internal medicine; Radiology","score_opus":0.10740137050114074,"score_gpt":0.4093564515229179,"score_spread":0.30195508102177715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313252611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994711,0.00017038255,0.000027918122,0.00002098252,0.0000021293756,0.0000054112256,0.00007155482,0.0000016162109,0.00022893482],"genre_scores_gemma":[0.99966455,0.00006268125,0.000043689095,0.000009838417,0.000006111953,0.0000052006594,0.00011977784,6.3988944e-7,0.0000874601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986136,0.000027270447,0.000023238901,0.000036431804,0.000028453785,0.000023245217],"domain_scores_gemma":[0.9988262,0.00023697097,0.0005831184,0.000057207246,0.00010605267,0.00019039065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033718065,0.00036218914,0.00026749558,0.0008528835,0.00030622116,0.00058519375,0.00020708168,0.0007173602,0.002114039],"category_scores_gemma":[0.0025919282,0.00016554557,0.00017881727,0.00046872866,0.0002973152,0.00029631285,0.0004053832,0.00034844957,0.00026165418],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024772176,0.00008217966,0.9959895,0.000018357041,0.000051530256,0.00009387118,0.000117753756,0.00007730755,0.0013424741,0.000013817995,0.00006189407,0.0019036627],"study_design_scores_gemma":[0.0000039623555,0.000058718502,0.9996828,0.0000030190274,0.000005910405,0.00008830813,0.000041878942,0.00006558286,0.000023929633,0.000010381704,0.000014449076,0.000001144572],"about_ca_topic_score_codex":0.0031165322,"about_ca_topic_score_gemma":0.0044938913,"teacher_disagreement_score":0.0031165322,"about_ca_system_score_codex":0.00021396813,"about_ca_system_score_gemma":0.00012634452,"threshold_uncertainty_score":0.0070721507},"labels":[],"label_agreement":null},{"id":"W4313334378","doi":"10.1016/j.dcn.2022.101193","title":"Longitudinal associations between adolescent catch-up sleep, white-matter maturation and internalizing problems","year":2022,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Trinity College","funders":"Horizon 2020; Medical Research Council; Université Paris-Sud; Fédération pour la Recherche sur le Cerveau; Emil Aaltosen Säätiö; Fondation pour la Recherche Médicale; Université de Strasbourg; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; GlaxoSmithKline; Deutsche Forschungsgemeinschaft; University College Dublin; European Commission; Jalmari ja Rauha Ahokkaan Säätiö; King's College London; Fondation de France; Bundesministerium für Bildung und Forschung; National Institute for Health and Care Research; Academy of Finland; King’s College London; National Institutes of Health; Fondation de l'Avenir pour la Recherche Médicale Appliquée; South London and Maudsley NHS Foundation Trust","keywords":"Fractional anisotropy; White matter; Psychology; Sleep (system call); Longitudinal study; Diffusion MRI; Population; Superior longitudinal fasciculus; Uncinate fasciculus; Developmental psychology; Demography; Medicine; Magnetic resonance imaging","score_opus":0.0980913715547408,"score_gpt":0.34515107974111536,"score_spread":0.24705970818637457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313334378","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999549,0.00017760912,0.000051880936,0.000014782428,0.0000017978756,0.0000019447846,0.0001127233,0.000001511019,0.00008878317],"genre_scores_gemma":[0.9993637,0.00013034667,0.00011130677,0.000007727179,0.0000030252825,0.00000490038,0.00022074206,0.0000013104064,0.0001569939],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988544,0.000022517863,0.000012304142,0.000039232767,0.000016505352,0.00002411429],"domain_scores_gemma":[0.9992642,0.000094928895,0.00038005356,0.00005154318,0.00008389431,0.00012544867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036948588,0.00013184219,0.00013260447,0.00035771859,0.0001777177,0.0002885008,0.0001554972,0.00016244045,0.0008604262],"category_scores_gemma":[0.0011427324,0.00015017668,0.00016659319,0.00030798902,0.000114475515,0.00021687963,0.00025806177,0.00033859946,0.00007278032],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032501852,0.000016321108,0.998321,0.000004061548,0.00002992738,0.000019172183,0.000067937006,0.000016736538,0.00037042573,0.000013958478,0.000024443634,0.0010835853],"study_design_scores_gemma":[3.642459e-7,0.000016751837,0.9998293,0.0000014824901,0.000005468315,0.00002403749,0.00003473008,0.000029404817,0.0000296238,0.000004499237,0.00002402012,3.230011e-7],"about_ca_topic_score_codex":0.00800825,"about_ca_topic_score_gemma":0.021233171,"teacher_disagreement_score":0.00800825,"about_ca_system_score_codex":0.00016986008,"about_ca_system_score_gemma":0.00018180495,"threshold_uncertainty_score":0.015923262},"labels":[],"label_agreement":null},{"id":"W4313419144","doi":"10.1016/j.psychres.2022.115039","title":"Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study","year":2022,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health","keywords":"Comorbidity; Neuropathology; Fractional anisotropy; Attention deficit hyperactivity disorder; Diffusion MRI; White matter; Autism spectrum disorder; Psychology; Cohort; Autism; Uncinate fasciculus; Clinical psychology; Psychiatry; Medicine; Disease; Internal medicine; Magnetic resonance imaging","score_opus":0.10049090643462247,"score_gpt":0.4031020353481133,"score_spread":0.30261112891349085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313419144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99884415,0.00013001414,0.00018040162,0.00011131078,0.000009563627,0.000020159727,0.0001663184,0.0000036151846,0.0005345547],"genre_scores_gemma":[0.99896264,0.00010143445,0.00047678855,0.000052985375,0.000024806901,0.00001111916,0.0002518104,0.0000060153684,0.00011240702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994324,0.000056381552,0.00007639191,0.00019732052,0.000119346994,0.00011808645],"domain_scores_gemma":[0.9984427,0.00037452203,0.0004891748,0.00011071879,0.000264203,0.00031858849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006783931,0.00089321757,0.00062725594,0.002118657,0.0015968371,0.0011772206,0.000748342,0.0010537951,0.0021015422],"category_scores_gemma":[0.003002063,0.0005212059,0.0006878774,0.0010043001,0.0013321248,0.0011581529,0.0013084387,0.00091169594,0.00026390728],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011508785,0.00055912323,0.915022,0.00008483157,0.00023058885,0.03777422,0.001701796,0.00009011073,0.036906995,0.00023903702,0.0002801281,0.0059603876],"study_design_scores_gemma":[0.000029912244,0.00028155572,0.9694074,0.00002634191,0.00015001146,0.026517555,0.0016628773,0.00021670753,0.0011545975,0.0002483702,0.00028550017,0.000019117544],"about_ca_topic_score_codex":0.011685088,"about_ca_topic_score_gemma":0.02682615,"teacher_disagreement_score":0.011685088,"about_ca_system_score_codex":0.000724698,"about_ca_system_score_gemma":0.0010918826,"threshold_uncertainty_score":0.023234129},"labels":[],"label_agreement":null},{"id":"W4313500687","doi":"10.1002/brb3.2863","title":"Whole‐brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Fornix; Cingulum (brain); White matter; Atrophy; Neuroscience; Hippocampal formation; Diffusion MRI; Temporal lobe; Psychology; Cerebrospinal fluid; Alzheimer's disease; Pathology; Disease; Hippocampus; Medicine; Fractional anisotropy; Epilepsy; Magnetic resonance imaging","score_opus":0.07152290366549785,"score_gpt":0.34101124241715397,"score_spread":0.2694883387516561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313500687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983065,0.0006363623,0.00036081494,0.000016589256,0.000008462352,0.0000062122917,0.00037529948,0.000011288577,0.00027842482],"genre_scores_gemma":[0.9991265,0.00010978405,0.00033521655,0.0000047907733,0.000006736925,0.0000050475965,0.00026143665,0.000003074017,0.00014748087],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999083,0.000018088227,0.000017142078,0.000030008774,0.000018098357,0.000008339161],"domain_scores_gemma":[0.99948347,0.0000960162,0.00024225598,0.00004859233,0.0000646521,0.00006493759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044255838,0.00043699998,0.00029968805,0.0010414171,0.00015838214,0.00039249222,0.00014796722,0.00022986124,0.00072895293],"category_scores_gemma":[0.0011792745,0.00010551668,0.00020404744,0.00063235714,0.0001697262,0.00019859127,0.00018988084,0.00022449662,0.00010904676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002028364,0.00012631255,0.963354,0.0001249702,0.00052865397,0.00026485143,0.00023159916,0.0011154736,0.019442683,0.00010503071,0.000373212,0.0123048145],"study_design_scores_gemma":[0.0000067347983,0.00012972562,0.9969715,0.0000070101382,0.000073274496,0.0003282401,0.00005252482,0.0012002196,0.000927028,0.00014360754,0.00015471198,0.000005405827],"about_ca_topic_score_codex":0.0018162151,"about_ca_topic_score_gemma":0.0013549358,"teacher_disagreement_score":0.0018162151,"about_ca_system_score_codex":0.00017978612,"about_ca_system_score_gemma":0.000104629755,"threshold_uncertainty_score":0.0036112666},"labels":[],"label_agreement":null},{"id":"W4313521977","doi":"10.21203/rs.3.rs-2411825/v1","title":"Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Computer science; Artificial intelligence; Imaging phantom; Ground truth; Segmentation; Machine learning; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.2766481564113543,"score_gpt":0.4807213100057173,"score_spread":0.20407315359436295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313521977","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19588852,0.0027457045,0.53309685,0.009345389,0.008371063,0.0035270746,0.067663975,0.1462943,0.033067234],"genre_scores_gemma":[0.2796432,0.0005657749,0.47877035,0.0023375337,0.0011104168,0.0029107453,0.1814656,0.03007034,0.023125984],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9792255,0.0064620585,0.0026990867,0.00284243,0.0077997497,0.00097109313],"domain_scores_gemma":[0.92149067,0.013684793,0.0033196888,0.017029641,0.040172536,0.004302692],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.028963061,0.0029488744,0.001811346,0.004335874,0.0018305567,0.005647518,0.0027301046,0.0028953282,0.015982052],"category_scores_gemma":[0.10125661,0.000911722,0.0019248511,0.0021464955,0.0015277752,0.004278674,0.006333371,0.0031324837,0.020999178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018247131,0.00070896884,0.030836042,0.0014168585,0.00060423225,0.0005652705,0.0007342602,0.02808874,0.016429648,0.0058979467,0.63585854,0.2770347],"study_design_scores_gemma":[0.0013115025,0.0025121195,0.09200597,0.0014856815,0.0004022236,0.0033598498,0.0010322133,0.36885548,0.086496234,0.027588775,0.41393018,0.0010197855],"about_ca_topic_score_codex":0.00620116,"about_ca_topic_score_gemma":0.008571295,"teacher_disagreement_score":0.9710369,"about_ca_system_score_codex":0.0018598913,"about_ca_system_score_gemma":0.0035018777,"threshold_uncertainty_score":0.15317315},"labels":[],"label_agreement":null},{"id":"W4313550273","doi":"10.7554/elife.82088.sa1","title":"Decision letter: Fiber-specific structural properties relate to reading skills in children and adolescents","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Reading (process); White matter; Psychology; Dyslexia; Cognitive psychology; Developmental psychology; Medicine; Linguistics","score_opus":0.037144882136376275,"score_gpt":0.3360365700604452,"score_spread":0.2988916879240689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313550273","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008379955,0.0017719989,0.0016839913,0.572884,0.3426282,0.00097520935,0.018915107,0.0007674911,0.05199396],"genre_scores_gemma":[0.11990413,0.004385924,0.010042472,0.2795914,0.24918789,0.0018426235,0.01242389,0.001484092,0.32113764],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963846,0.0006894185,0.0007016697,0.00056131167,0.0012385473,0.00042454767],"domain_scores_gemma":[0.9272964,0.02001859,0.0028455367,0.0047846762,0.035865575,0.009189133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0061493013,0.00053654227,0.0012040049,0.0016567111,0.0020611794,0.003376959,0.00214501,0.007578242,0.14082369],"category_scores_gemma":[0.12356199,0.00041426436,0.0008649597,0.0010034398,0.0011949827,0.0022907995,0.0017658628,0.0034445797,0.05787777],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017162347,0.000028812863,0.00064863235,0.00015289275,0.0000099629115,0.00006140328,0.000019615882,0.00003310886,0.00012760409,0.000856838,0.98486876,0.013020609],"study_design_scores_gemma":[0.0005938733,0.00016879586,0.011826953,0.001810664,0.000054546534,0.0006221956,0.00037551243,0.0017838982,0.0016377607,0.016888032,0.96414113,0.000096670046],"about_ca_topic_score_codex":0.002651309,"about_ca_topic_score_gemma":0.006581296,"teacher_disagreement_score":0.14082369,"about_ca_system_score_codex":0.0013113798,"about_ca_system_score_gemma":0.00417067,"threshold_uncertainty_score":0.47110218},"labels":[],"label_agreement":null},{"id":"W4313655558","doi":"10.1016/j.nicl.2023.103324","title":"Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Department of Psychiatry, University of Toronto; Ministry of Science and Technology, Taiwan; Chang Gung Memorial Hospital, Linkou; Chang Gung Medical Foundation; University of Toronto","keywords":"White matter; Psychology; Stimulation; Diffusion MRI; Transcranial magnetic stimulation; Autism; Magnetic resonance imaging; Randomized controlled trial; Audiology; Medicine; Neuroscience; Anesthesia; Internal medicine; Developmental psychology","score_opus":0.06673426277084818,"score_gpt":0.3888181888932402,"score_spread":0.322083926122392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313655558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994161,0.00025227646,0.000081087135,0.000025407096,0.000012012307,0.00007287781,0.000029679806,0.000006940835,0.00010348774],"genre_scores_gemma":[0.9983962,0.00032888475,0.0004470559,0.000043663927,0.000028327679,0.0004003825,0.00008998139,0.0000036806762,0.00026183022],"study_design_codex":"randomized_trial","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.9993868,0.0002628682,0.00007304573,0.00010897679,0.000083446466,0.00008496848],"domain_scores_gemma":[0.9993351,0.0001621445,0.00019456969,0.00009587167,0.000051889874,0.00016037685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000955512,0.00049852376,0.00095961476,0.00025343942,0.0002210599,0.00026730765,0.00040005828,0.00052359875,0.0012236807],"category_scores_gemma":[0.0010507145,0.00017700081,0.00060177455,0.00011490269,0.0006829733,0.00037869997,0.0003365327,0.000567864,0.00015601597],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.56948286,0.042977132,0.022586426,0.0025825351,0.0012121941,0.0005939927,0.0009970695,0.0009220686,0.20676914,0.00021386654,0.00046247186,0.15120025],"study_design_scores_gemma":[0.04678672,0.7612158,0.16987352,0.00011468895,0.00063026976,0.00040478163,0.0005167166,0.0005370569,0.018240651,0.00023306263,0.0014038194,0.00004293193],"about_ca_topic_score_codex":0.0005966915,"about_ca_topic_score_gemma":0.0013896669,"teacher_disagreement_score":0.0012236807,"about_ca_system_score_codex":0.00026142102,"about_ca_system_score_gemma":0.0005912019,"threshold_uncertainty_score":0.005053282},"labels":[],"label_agreement":null},{"id":"W4313830827","doi":"10.1016/j.mri.2023.01.004","title":"Mapping the impact of nonlinear gradient fields with noise on diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Diffusion MRI; Noise (video); Nonlinear system; Diffusion; Thermal diffusivity; SIGNAL (programming language); Statistical physics; Physics; Voxel; Scaling; Magnitude (astronomy); Tensor (intrinsic definition); Mathematics; Computer science; Artificial intelligence; Geometry","score_opus":0.03687265794660073,"score_gpt":0.32537116381545517,"score_spread":0.28849850586885445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313830827","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.563316,0.002923437,0.42662752,0.0010394074,0.00019544458,0.0001529993,0.00031156582,0.00066261215,0.0047710645],"genre_scores_gemma":[0.9402745,0.0017911596,0.053551517,0.00025621144,0.000102219135,0.00006503866,0.00038305696,0.00044935988,0.003126939],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994222,0.00018193477,0.000032185384,0.00008790779,0.00020202131,0.00007371201],"domain_scores_gemma":[0.9958852,0.0030687852,0.00027674082,0.00020813945,0.00042221238,0.00013897644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017364176,0.0008823705,0.00043207075,0.00074001605,0.0005064339,0.0016702462,0.00044490935,0.0009363787,0.0009484397],"category_scores_gemma":[0.023098914,0.00052694196,0.00032565743,0.00059359806,0.0009752171,0.0016561585,0.00086754694,0.0008650738,0.00033069708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027926373,0.00038725702,0.021507736,0.0010312337,0.0003627702,0.0019629125,0.00079694786,0.15719,0.6768801,0.01559487,0.0016963339,0.11979723],"study_design_scores_gemma":[0.00009083078,0.00080509495,0.048983943,0.0001648068,0.00046181178,0.0032359147,0.00026611294,0.567637,0.35574296,0.01808557,0.004396162,0.00012983516],"about_ca_topic_score_codex":0.002293986,"about_ca_topic_score_gemma":0.002468167,"teacher_disagreement_score":0.002293986,"about_ca_system_score_codex":0.0005797518,"about_ca_system_score_gemma":0.00079434505,"threshold_uncertainty_score":0.009183168},"labels":[],"label_agreement":null},{"id":"W4315499033","doi":"10.1101/2023.01.10.523345","title":"Associative white matter tracts selectively predict sensorimotor learning","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Kavli Foundation; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust; National Institutes of Health; National Science Foundation","keywords":"White matter; Psychology; Fractional anisotropy; Associative learning; Tractography; Cognitive psychology; Lateralization of brain function; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.04177059425958879,"score_gpt":0.2909614061685393,"score_spread":0.24919081190895054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315499033","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99693054,0.000028367755,0.002701084,0.00002663118,0.0000018204959,0.0000060283637,0.00007961528,0.000030843486,0.00019519358],"genre_scores_gemma":[0.9985733,0.000013340936,0.001181035,0.000005770406,0.0000015388666,0.0000054984775,0.00006426254,0.000005685258,0.00014958883],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981695,0.00002960728,0.000015262282,0.00008185996,0.00003256577,0.000023778777],"domain_scores_gemma":[0.998139,0.00038065796,0.0009231658,0.00026018088,0.00011821357,0.00017879275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007417151,0.00025752105,0.00020968387,0.0004290107,0.000119043,0.0003846181,0.00016505616,0.0003848587,0.0012749443],"category_scores_gemma":[0.002913444,0.00014861498,0.00019448927,0.00014642514,0.0004377709,0.00040099543,0.00033359823,0.00042239917,0.0001620058],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007107652,0.00029973185,0.8255199,0.0000514069,0.00025283464,0.00020715715,0.00022034845,0.0076165856,0.1432993,0.0004996339,0.00019159346,0.021130696],"study_design_scores_gemma":[0.0000073589727,0.0003272383,0.9676128,0.000008699838,0.00004334312,0.00026708105,0.00004412483,0.013548105,0.016932014,0.0010395149,0.00015881284,0.000010744434],"about_ca_topic_score_codex":0.0010517195,"about_ca_topic_score_gemma":0.0026495229,"teacher_disagreement_score":0.0012749443,"about_ca_system_score_codex":0.00019261646,"about_ca_system_score_gemma":0.00026493915,"threshold_uncertainty_score":0.0042651296},"labels":[],"label_agreement":null},{"id":"W4317103370","doi":"10.1016/j.jmbbm.2023.105681","title":"In-vivo along muscle fascicle strain heterogeneity is not affected by image registration parameters: Robustness testing of combined magnetic resonance-diffusion tensor imaging method","year":2023,"lang":"en","type":"article","venue":"Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Montreal Heart Institute","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Diffusion MRI; Magnetic resonance imaging; Robustness (evolution); Fascicle; Image registration; Nuclear magnetic resonance; Physics; Anatomy; Computer science; Medicine; Computer vision; Radiology; Image (mathematics); Chemistry","score_opus":0.05323243145861169,"score_gpt":0.3489436163711821,"score_spread":0.2957111849125704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317103370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8275301,0.00048689073,0.16961047,0.00012449498,0.00011840509,0.0001469462,0.00046332317,0.00079097884,0.0007284337],"genre_scores_gemma":[0.94798195,0.00012297265,0.050135314,0.000058771217,0.000029421994,0.00015798016,0.0007619947,0.00036922828,0.00038244802],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9961498,0.0016050346,0.00043380546,0.0010418369,0.0006191599,0.0001504237],"domain_scores_gemma":[0.98540455,0.00790342,0.0019974594,0.003143657,0.0012692017,0.00028165895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077183545,0.00086305756,0.00050459005,0.00071968895,0.00034146852,0.0008871551,0.0006712916,0.00083865685,0.00092562556],"category_scores_gemma":[0.030989643,0.00033389794,0.0010078091,0.00047726618,0.00084294355,0.0007100916,0.0010742004,0.0006773762,0.00045204343],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010518449,0.0007852935,0.040415302,0.001282089,0.0025123735,0.0005582948,0.00078719953,0.11774091,0.6599249,0.0010930987,0.0009993456,0.16338274],"study_design_scores_gemma":[0.00022770632,0.0056108376,0.12968576,0.0001466929,0.00123414,0.0014385212,0.00025814195,0.36969924,0.48620203,0.002014294,0.003240697,0.00024188939],"about_ca_topic_score_codex":0.000805492,"about_ca_topic_score_gemma":0.0006125555,"teacher_disagreement_score":0.0077183545,"about_ca_system_score_codex":0.00025508594,"about_ca_system_score_gemma":0.00037494858,"threshold_uncertainty_score":0.04081905},"labels":[],"label_agreement":null},{"id":"W4317659503","doi":"10.1101/2023.01.20.524929","title":"Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer’s Disease","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Alzheimer Society","keywords":"Hyperintensity; Fluid-attenuated inversion recovery; White matter; Magnetic resonance imaging; Atrophy; Disease; Psychology; Cardiology; Neuroimaging; Alzheimer's disease; Cognitive impairment; Neuroscience; Medicine; Audiology; Pathology; Radiology","score_opus":0.07256484529055424,"score_gpt":0.3385269432707606,"score_spread":0.26596209798020637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317659503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994382,0.00012770212,0.00014823145,0.000008781665,0.0000018774075,0.00001139764,0.00006857949,0.0000023383975,0.00019276452],"genre_scores_gemma":[0.99944526,0.000036184487,0.00030900672,0.000006224422,0.0000051824054,0.000010951301,0.00009017943,8.717688e-7,0.00009627807],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997305,0.00010238102,0.000041324307,0.000053193296,0.000044431017,0.000028072818],"domain_scores_gemma":[0.9995745,0.00008434005,0.00016746488,0.000032450494,0.000075003794,0.00006634462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010722056,0.00045931595,0.0003441251,0.001444641,0.0003698561,0.0003979484,0.00022999215,0.00035618318,0.0009807816],"category_scores_gemma":[0.0015206438,0.00015871746,0.00019101323,0.00042354382,0.0002185515,0.00036754872,0.0004195751,0.00026207085,0.00012717552],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002095776,0.0001907476,0.97783846,0.000052977488,0.00020607609,0.00021485735,0.00027342048,0.00023309494,0.009802234,0.000043075237,0.0001657424,0.008883418],"study_design_scores_gemma":[0.000022193764,0.000397966,0.99725634,0.000009145984,0.000043377346,0.00032403364,0.00015647322,0.00073052756,0.00084458606,0.00009597399,0.000113324124,0.0000061789697],"about_ca_topic_score_codex":0.0014672994,"about_ca_topic_score_gemma":0.002398638,"teacher_disagreement_score":0.0014672994,"about_ca_system_score_codex":0.00018932292,"about_ca_system_score_gemma":0.000100321005,"threshold_uncertainty_score":0.005670488},"labels":[],"label_agreement":null},{"id":"W4317778265","doi":"10.1016/j.neuroimage.2023.119892","title":"MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Coordination of Research Activities; National Institute on Aging; Agencia Estatal de Investigación; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Institució Catalana de Recerca i Estudis Avançats; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; Agence Nationale de la Recherche; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; European Commission; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Autoencoder; Modalities; Computer science; Artificial intelligence; Missing data; Set (abstract data type); Modality (human–computer interaction); Recurrent neural network; Data set; Pattern recognition (psychology); Baseline (sea); Machine learning; Artificial neural network","score_opus":0.22031147126135492,"score_gpt":0.42699075770952316,"score_spread":0.20667928644816824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317778265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021013143,0.0009656223,0.9758754,0.00028101573,0.00006304553,0.000036347326,0.0002064492,0.0008011495,0.00075789925],"genre_scores_gemma":[0.6983403,0.0009021873,0.29195282,0.00043304102,0.00009876118,0.0002410171,0.0013355782,0.00036812556,0.0063282335],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970967,0.00011559953,0.000016805,0.00007258074,0.000050204446,0.000035104516],"domain_scores_gemma":[0.9994211,0.00037987155,0.000040037063,0.000037525027,0.000097593605,0.00002391039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012476156,0.0008845292,0.0009479432,0.00038610207,0.00023359398,0.0005555072,0.0014234037,0.0011315914,0.0013521268],"category_scores_gemma":[0.0029499345,0.0006128352,0.0012044051,0.00034967388,0.00045309434,0.0006729673,0.0007945789,0.0018586357,0.00041860348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007157283,0.00003757919,0.00084025617,0.000049619437,0.000120615885,0.000064476735,0.00005006114,0.948358,0.0028948474,0.0031988036,0.0013501042,0.04296399],"study_design_scores_gemma":[0.0000019016071,0.000005629238,0.000066765744,0.0000031632894,0.0000042015463,0.0000072809135,0.0000017094017,0.99882907,0.00023794064,0.0006999183,0.00013982061,0.0000026026314],"about_ca_topic_score_codex":0.018784963,"about_ca_topic_score_gemma":0.021963445,"teacher_disagreement_score":0.018784963,"about_ca_system_score_codex":0.0006801747,"about_ca_system_score_gemma":0.0009710353,"threshold_uncertainty_score":0.03735125},"labels":[],"label_agreement":null},{"id":"W4317866086","doi":"10.1007/s00429-023-02609-y","title":"Correction to: Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological‑consistent iron‑rich deep brain nucleus subregion identification","year":2023,"lang":"en","type":"erratum","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Atlas (anatomy); Red nucleus; Identification (biology); Neurology; Neuroscience; Brain atlas; Nucleus; Biology; Psychology; Anatomy; Ecology","score_opus":0.04363649922660308,"score_gpt":0.31754877701462625,"score_spread":0.2739122777880232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317866086","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008909779,0.0014185158,0.012552515,0.03046614,0.92221856,0.00022148665,0.019518595,0.0049456116,0.007767498],"genre_scores_gemma":[0.052707277,0.005003059,0.10540861,0.058290813,0.17950079,0.0023092744,0.035656024,0.030994957,0.5301292],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953172,0.000636674,0.0011870556,0.0006310365,0.0018405317,0.00038747228],"domain_scores_gemma":[0.9631339,0.00972916,0.0020858457,0.0041812942,0.019963095,0.0009066508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037482453,0.002833765,0.0023983172,0.006221254,0.002950177,0.003252921,0.0031939023,0.005027054,0.21918614],"category_scores_gemma":[0.06993222,0.0020168552,0.0018638587,0.0037656499,0.0018535331,0.0019602627,0.0024943335,0.0064410185,0.075952664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042768304,0.000005349212,0.00008920347,0.00019521307,0.000015711837,0.00018846717,0.00002530603,0.0000619858,0.00008697161,0.00056321034,0.99194556,0.0067803427],"study_design_scores_gemma":[0.00013101281,0.000020754638,0.0013966846,0.00046023502,0.000073960284,0.0015874874,0.00010548511,0.0009987168,0.0009421353,0.005243355,0.98896515,0.00007500895],"about_ca_topic_score_codex":0.01892193,"about_ca_topic_score_gemma":0.036961485,"teacher_disagreement_score":0.21918614,"about_ca_system_score_codex":0.0025940174,"about_ca_system_score_gemma":0.005538352,"threshold_uncertainty_score":0.73325074},"labels":[],"label_agreement":null},{"id":"W4317930664","doi":"10.1177/0271678x231152001","title":"Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease","year":2023,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hotchkiss Brain Institute; Université Laval; University of Calgary; Baycrest Hospital; Health Sciences Centre; McGill University; Montreal Heart Institute; University of British Columbia; Western University; University of Toronto; Université de Sherbrooke; McMaster University; Montreal Neurological Institute and Hospital; Lawson Health Research Institute; Jewish General Hospital; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Esperion Therapeutics; Amarin Corporation; Biogen; National Institutes of Health; Canada Research Chairs; AstraZeneca; Eli Lilly and Company; Pfizer; Novo Nordisk; Eisai; U.S. Department of Defense; Sanofi; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Dementia; Fractional anisotropy; Free water; Diffusion MRI; Positron emission tomography; Neuroscience; Hyperintensity; Alzheimer's disease; Psychology; Cognitive decline; Medicine; Pathology; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.023072828295658956,"score_gpt":0.2654199776694309,"score_spread":0.24234714937377191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317930664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99945754,0.0002625268,0.000108773726,0.000009727384,0.0000022711938,0.0000041788667,0.00005218612,0.0000021724588,0.00010069379],"genre_scores_gemma":[0.9996203,0.0000823494,0.0001026089,0.000008630765,0.000005410521,0.000005202012,0.0001059508,9.794989e-7,0.00006866718],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971145,0.00007428621,0.00004399319,0.000089282046,0.000049401304,0.00003146769],"domain_scores_gemma":[0.9995043,0.00013181708,0.00017746455,0.000056166267,0.00005935152,0.00007094064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008510801,0.0006067149,0.00057863415,0.00085797714,0.00046343356,0.00060518994,0.00031252252,0.00068522024,0.00057042687],"category_scores_gemma":[0.002486332,0.00028486186,0.0003200791,0.00066990533,0.00027982146,0.00040886918,0.00047223532,0.00042407753,0.00014386671],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007940639,0.000097346754,0.9941759,0.000025870815,0.00016946177,0.00021890219,0.00016382981,0.00014754327,0.0010385382,0.000018316328,0.000038780327,0.0031114114],"study_design_scores_gemma":[0.00001918884,0.00027914235,0.9979247,0.0000060938373,0.000099543795,0.00056414417,0.0001244397,0.0005622812,0.0002214368,0.000088117435,0.00010629894,0.000004578617],"about_ca_topic_score_codex":0.0028302383,"about_ca_topic_score_gemma":0.0028681378,"teacher_disagreement_score":0.0028302383,"about_ca_system_score_codex":0.00021567779,"about_ca_system_score_gemma":0.00021670041,"threshold_uncertainty_score":0.0056275725},"labels":[],"label_agreement":null},{"id":"W4317933699","doi":"10.1016/j.ijrobp.2023.01.024","title":"Insult to Short-Range White Matter Connectivity in Childhood Brain Tumor Survivors","year":2023,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"White matter; Medicine; Fractional anisotropy; Diffusion MRI; Medulloblastoma; Typically developing; Brain tumor; Radiation therapy; Magnetic resonance imaging; Pathology; Surgery; Radiology; Psychiatry","score_opus":0.03820561362493503,"score_gpt":0.3736504431100189,"score_spread":0.33544482948508386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317933699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991671,0.00010311778,0.00002320492,0.000088580986,0.000005176286,0.0000020284472,0.00015166009,0.0000020690504,0.000457192],"genre_scores_gemma":[0.9993568,0.00011241502,0.000019873924,0.000018462946,0.000005495738,0.0000035662579,0.0001719867,0.0000023896143,0.00030908195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999329,0.000009472596,0.000002972132,0.000015186166,0.000011490997,0.00002808308],"domain_scores_gemma":[0.99952924,0.000089058034,0.00019986244,0.00001809098,0.000044323006,0.00011953969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080228194,0.0001394623,0.00014149565,0.00021625064,0.00044964044,0.0002957501,0.00022732346,0.00021704903,0.0034918066],"category_scores_gemma":[0.0010042225,0.000082950195,0.00017148911,0.0003708712,0.00026447326,0.00027511618,0.00038312812,0.0004737572,0.00019205015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005711752,0.00012260141,0.98343605,0.000042032418,0.00013118274,0.0014259396,0.00066381384,0.00037936025,0.0031899961,0.00024573604,0.000668392,0.0091238115],"study_design_scores_gemma":[0.0000034241127,0.0001208095,0.9979736,0.000008218688,0.000031415148,0.00047392928,0.0006306093,0.0001144085,0.0002761641,0.00012835514,0.00023525997,0.0000036535869],"about_ca_topic_score_codex":0.019112434,"about_ca_topic_score_gemma":0.03377202,"teacher_disagreement_score":0.019112434,"about_ca_system_score_codex":0.00050709274,"about_ca_system_score_gemma":0.0005054927,"threshold_uncertainty_score":0.03800237},"labels":[],"label_agreement":null},{"id":"W4318141881","doi":"10.21203/rs.3.rs-2451435/v1","title":"Redefining the connectome: A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Connectome; Modal; Computer science; Artificial intelligence; Functional connectivity; Neuroscience; Psychology","score_opus":0.31056101900612093,"score_gpt":0.4733101727138448,"score_spread":0.16274915370772386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318141881","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053834226,0.00047129267,0.93994284,0.0007630454,0.00011358565,0.00002894469,0.0011527281,0.00041358778,0.0032797821],"genre_scores_gemma":[0.6713666,0.0012773181,0.31636542,0.00040203615,0.00041074012,0.00018223317,0.0019703775,0.0005768158,0.007448563],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995778,0.00013972448,0.000028834049,0.00010762322,0.00011672067,0.000029262099],"domain_scores_gemma":[0.99873525,0.00041681604,0.00026313114,0.0003026568,0.00018325543,0.00009889321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010081015,0.00073752523,0.00047698646,0.002279726,0.00040330522,0.001504897,0.0010860246,0.001118117,0.003012226],"category_scores_gemma":[0.0046190815,0.0002993608,0.0006807522,0.001744374,0.001036034,0.0036001923,0.001381499,0.0014140919,0.0005281274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029429546,0.00008337139,0.003830091,0.00048166004,0.00017099375,0.00079950824,0.0005185395,0.13258258,0.059739873,0.571436,0.012990276,0.21707284],"study_design_scores_gemma":[0.000011273059,0.00006163701,0.002745925,0.00004641778,0.000038142152,0.0008448415,0.000088849265,0.6036098,0.0038359205,0.38214654,0.006507795,0.00006280068],"about_ca_topic_score_codex":0.0012521424,"about_ca_topic_score_gemma":0.0022069803,"teacher_disagreement_score":0.003012226,"about_ca_system_score_codex":0.00032107453,"about_ca_system_score_gemma":0.00045316646,"threshold_uncertainty_score":0.01007694},"labels":[],"label_agreement":null},{"id":"W4318240362","doi":"10.3233/jad-220519","title":"Fully Connected Multi-Kernel Convolutional Neural Network Based on Alzheimer’s Disease Diagnosis","year":2023,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Convolutional neural network; Artificial intelligence; Computer science; Diffusion MRI; Deep learning; Pattern recognition (psychology); Fractional anisotropy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.12976706223023116,"score_gpt":0.3755037390369411,"score_spread":0.24573667680670996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318240362","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30779356,0.006600622,0.6719668,0.0012878514,0.00049428287,0.00015155008,0.0009887865,0.003052488,0.0076640076],"genre_scores_gemma":[0.94684136,0.00085352757,0.046193592,0.00017092968,0.00006515319,0.000056862802,0.00081495795,0.00002853548,0.004975108],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980015,0.000026374011,0.000015355667,0.00006684417,0.00004498147,0.000046380934],"domain_scores_gemma":[0.9996891,0.00007447657,0.000034310866,0.000026506808,0.00015363343,0.000022043278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052804686,0.0007321461,0.0005213346,0.0006768065,0.00025922127,0.00046075278,0.0009062738,0.00079731893,0.0013374538],"category_scores_gemma":[0.0012830207,0.00028110656,0.0005561416,0.00042669364,0.00025519248,0.00068087125,0.00046105857,0.0006285006,0.000355711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005623421,0.00023105067,0.011473673,0.00014942471,0.00019606942,0.0003656389,0.00007254223,0.56859183,0.0077818106,0.0033353183,0.006838527,0.4004018],"study_design_scores_gemma":[0.0000039345987,0.000017629192,0.00063077675,0.0000057703623,0.000015182754,0.000027975791,0.000002470521,0.9977138,0.0008405582,0.0005016798,0.00023590725,0.0000042956312],"about_ca_topic_score_codex":0.027877567,"about_ca_topic_score_gemma":0.02230513,"teacher_disagreement_score":0.027877567,"about_ca_system_score_codex":0.0011446914,"about_ca_system_score_gemma":0.0010281653,"threshold_uncertainty_score":0.05543059},"labels":[],"label_agreement":null},{"id":"W4318700719","doi":"10.1101/2023.01.29.526138","title":"Sex differences, asymmetry and age-related white matter development in infants and 5-year-olds as assessed with Tract-Based Spatial Statistics","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Suomen Lääketieteen Säätiö; Suomen Kulttuurirahasto; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Suomalainen Lääkäriseura Duodecim; Alfred Kordelinin Säätiö; Juho Vainion Säätiö; National Alliance for Research on Schizophrenia and Depression","keywords":"Corpus callosum; Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Psychology; Developmental psychology; Gestational age; Early childhood; Brain asymmetry; Cognition; Audiology; Medicine; Pregnancy; Neuroscience; Magnetic resonance imaging; Biology","score_opus":0.02810981522604555,"score_gpt":0.2750988080261762,"score_spread":0.24698899280013065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318700719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954504,0.000089577174,0.000054271542,0.0000029135733,0.0000011435884,0.0000017005182,0.00020313659,0.0000022766212,0.000099845114],"genre_scores_gemma":[0.99951994,0.000049594473,0.00008575704,0.0000021327437,0.0000017648047,0.0000038090602,0.00022948309,0.0000018169818,0.00010567448],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977535,0.000033570515,0.00004047485,0.000054941953,0.00005399991,0.00004167651],"domain_scores_gemma":[0.9990657,0.00015765727,0.0005125628,0.00007284553,0.000096727716,0.000094565985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005083498,0.00020987129,0.00024792663,0.0011912606,0.00013756212,0.00032291547,0.00013727856,0.00022674762,0.0012795427],"category_scores_gemma":[0.0017698423,0.00011639518,0.00025608233,0.0004447461,0.00019026033,0.00021216029,0.0002818661,0.0001387496,0.00020199438],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024038531,0.000015123257,0.99184316,0.000013689449,0.0000484182,0.00030160623,0.0003632456,0.00005030472,0.0034236456,0.000039171195,0.00005013279,0.0036111157],"study_design_scores_gemma":[4.098605e-7,0.0000373637,0.99947757,0.0000014882669,0.000003760512,0.0001798711,0.00007266667,0.000045523706,0.00013632239,0.00000719483,0.000036774047,0.0000010629675],"about_ca_topic_score_codex":0.002203934,"about_ca_topic_score_gemma":0.0021221885,"teacher_disagreement_score":0.002203934,"about_ca_system_score_codex":0.00011377262,"about_ca_system_score_gemma":0.00009887928,"threshold_uncertainty_score":0.0043822527},"labels":[],"label_agreement":null},{"id":"W4318773574","doi":"10.1016/j.media.2023.102761","title":"Generative Sampling in Bundle Tractography using Autoencoders (GESTA)","year":2023,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Compute Canada; McDonnell Center for Systems Neuroscience; Réseau en Bio-Imagerie du Quebec; National Institutes of Health; Université de Sherbrooke","keywords":"Tractography; Streamlines, streaklines, and pathlines; Artificial intelligence; Human Connectome Project; White matter; Pattern recognition (psychology); Diffusion MRI; Computer science; Mathematics; Computer vision; Physics; Neuroscience; Psychology; Magnetic resonance imaging","score_opus":0.1638148958616718,"score_gpt":0.45533188993030915,"score_spread":0.29151699406863735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318773574","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003373184,0.00013672271,0.9958324,0.000073735275,0.000021221344,0.0000107618,0.000024772908,0.00026378635,0.00026333216],"genre_scores_gemma":[0.32533735,0.0006340277,0.667134,0.00021788449,0.00016200975,0.00020928343,0.00040002025,0.0005860628,0.0053193853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994522,0.00025474286,0.00002877011,0.000116058596,0.00009815922,0.00005016352],"domain_scores_gemma":[0.99687225,0.0023404143,0.0001789262,0.00027030942,0.0002243542,0.00011373892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017356226,0.0007836889,0.001281839,0.00070469064,0.0005445311,0.001068968,0.0012270561,0.0019397727,0.0021262234],"category_scores_gemma":[0.0049697612,0.0014029966,0.0015307064,0.0008926649,0.0012670506,0.0013503117,0.0017511668,0.0021809682,0.0008220612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007617212,0.00004254968,0.0006948689,0.000076711876,0.00010017574,0.00010922813,0.00013225115,0.8591357,0.0025569578,0.032847974,0.0015513354,0.10267604],"study_design_scores_gemma":[0.0000026842624,0.0000055070927,0.000049495862,0.000004151651,0.000003923184,0.000013908244,0.0000029340167,0.99267936,0.00026261533,0.0067300955,0.00024155472,0.0000037752177],"about_ca_topic_score_codex":0.009712264,"about_ca_topic_score_gemma":0.012651237,"teacher_disagreement_score":0.009712264,"about_ca_system_score_codex":0.0007389914,"about_ca_system_score_gemma":0.001142696,"threshold_uncertainty_score":0.019311488},"labels":[],"label_agreement":null},{"id":"W4318959460","doi":"10.1101/2023.01.23.525278","title":"White matter microstructure is associated with the precision of visual working memory","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"University of Queensland","keywords":"Working memory; White matter; Diffusion MRI; Visual memory; Association (psychology); Task (project management); Psychology; Neuroimaging; Cognitive psychology; Computer science; Neuroscience; Cognition; Magnetic resonance imaging; Medicine","score_opus":0.03186044187941617,"score_gpt":0.28591289136372405,"score_spread":0.2540524494843079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318959460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99774534,0.00015551649,0.0018413041,0.000018717046,0.000002012178,0.0000054234124,0.0001050739,0.000015977554,0.00011056994],"genre_scores_gemma":[0.999116,0.000035013574,0.0007042545,0.0000040060754,0.00000258645,0.000002759415,0.000053841843,0.0000044287635,0.00007707687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975604,0.00004906853,0.000041926694,0.00009196561,0.00004081517,0.000020185367],"domain_scores_gemma":[0.99466187,0.0017710357,0.0023270193,0.0008125314,0.0002964424,0.00013113816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011349623,0.00034002293,0.00035675275,0.0006496825,0.00013300528,0.00088624563,0.0002596279,0.00057130726,0.001355108],"category_scores_gemma":[0.009081166,0.00033582235,0.00016035931,0.00039018388,0.0005427118,0.0005461687,0.00038781666,0.0003816945,0.00017944275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038249013,0.0002256498,0.7057115,0.00024861217,0.0005577711,0.00035457438,0.0015022961,0.004450613,0.24789964,0.00082998746,0.00024276326,0.034151744],"study_design_scores_gemma":[0.000014322596,0.00031173514,0.9793005,0.00001774345,0.00005355106,0.0005516911,0.00013095066,0.0039319023,0.014311845,0.0012453126,0.000107043656,0.000023448243],"about_ca_topic_score_codex":0.0008819309,"about_ca_topic_score_gemma":0.00074456766,"teacher_disagreement_score":0.001355108,"about_ca_system_score_codex":0.0001437784,"about_ca_system_score_gemma":0.00010775539,"threshold_uncertainty_score":0.006002307},"labels":[],"label_agreement":null},{"id":"W4319441713","doi":"10.1115/1.4056848","title":"Wavelet-Based Methods to Partition Multibody Systems With Contact in Dynamic Simulation","year":2023,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CM Labs Simulations (Canada); McGill University","funders":"","keywords":"Multibody system; Partition (number theory); Dynamical systems theory; Computer science; Metric (unit); Topology (electrical circuits); Redundancy (engineering); Constraint (computer-aided design); Wavelet; Theoretical computer science; Mathematics; Artificial intelligence; Physics; Engineering; Classical mechanics; Geometry","score_opus":0.05140150529499968,"score_gpt":0.43491788771209844,"score_spread":0.38351638241709873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319441713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061500017,0.00013031262,0.9366137,0.00018336707,0.00003147175,0.000053771237,0.000029388802,0.00012495011,0.0013331374],"genre_scores_gemma":[0.708627,0.00020663135,0.28925717,0.00010213836,0.00005663972,0.00017891683,0.00008245607,0.00016513128,0.001324001],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997193,0.00011311018,0.00001480487,0.00002485784,0.00009955794,0.00002841184],"domain_scores_gemma":[0.9987943,0.00079136336,0.0001095096,0.00009630846,0.00011744486,0.00009109453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010472918,0.00051821925,0.0007288199,0.0007020991,0.00039221748,0.0007333786,0.00089550344,0.0010098818,0.0011408258],"category_scores_gemma":[0.0034733831,0.00041717,0.00059270096,0.0005466338,0.0009565714,0.0013431509,0.0015462877,0.0010826472,0.00017697887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038825317,0.00004594998,0.0005645741,0.000027048947,0.000020221414,0.00004276805,0.000061790306,0.9723884,0.0027076937,0.015370414,0.00018110988,0.008551254],"study_design_scores_gemma":[0.0000013427897,0.000003055716,0.00001454866,5.984186e-7,4.794334e-7,0.0000011221398,0.0000018485682,0.99911386,0.000093485076,0.0007310986,0.000037811355,7.866574e-7],"about_ca_topic_score_codex":0.0024763236,"about_ca_topic_score_gemma":0.0020370705,"teacher_disagreement_score":0.0024763236,"about_ca_system_score_codex":0.00057719677,"about_ca_system_score_gemma":0.00055978005,"threshold_uncertainty_score":0.005538702},"labels":[],"label_agreement":null},{"id":"W4319733470","doi":"10.1038/s41598-023-28560-w","title":"Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Université de Sherbrooke","keywords":"Tractography; Computer science; Artificial intelligence; Ground truth; Imaging phantom; Segmentation; White matter; Machine learning; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07451182870939092,"score_gpt":0.34913634223885504,"score_spread":0.2746245135294641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319733470","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16745861,0.0024361392,0.56881154,0.012009597,0.009167129,0.004943409,0.058954958,0.12908958,0.047129024],"genre_scores_gemma":[0.20934694,0.0007458827,0.57908875,0.003000822,0.0013364564,0.0044757486,0.13581769,0.036875352,0.02931248],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9804867,0.005421494,0.0028698456,0.0023775715,0.007861348,0.0009831097],"domain_scores_gemma":[0.90454215,0.017001325,0.0042918418,0.017955603,0.051112644,0.005096421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03623296,0.0028771972,0.0018248925,0.0049163857,0.0021511344,0.0059626373,0.0028582704,0.0031211474,0.019794848],"category_scores_gemma":[0.114711136,0.0010765868,0.0024513644,0.0020127678,0.0016193866,0.005019716,0.0063958284,0.0037512716,0.023318918],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015185903,0.00071321183,0.033749405,0.0013128511,0.00056137226,0.00058573566,0.0009646857,0.0164384,0.013974834,0.0049743038,0.6282065,0.29700008],"study_design_scores_gemma":[0.0012682265,0.002654327,0.112396784,0.001999592,0.00047834442,0.004506064,0.0012329172,0.2259375,0.07601437,0.029640289,0.5426599,0.0012117196],"about_ca_topic_score_codex":0.005406567,"about_ca_topic_score_gemma":0.010094865,"teacher_disagreement_score":0.03623296,"about_ca_system_score_codex":0.0019131366,"about_ca_system_score_gemma":0.0038171166,"threshold_uncertainty_score":0.19162053},"labels":[],"label_agreement":null},{"id":"W4319940240","doi":"10.1101/2023.02.09.527696","title":"Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Pennsylvania","keywords":"Covariance; White matter; Covariance function; Psychology; Fiber; Executive functions; Function (biology); Mathematics; Neuroscience; Cognition; Materials science; Medicine; Statistics; Biology; Cell biology","score_opus":0.04343906616440578,"score_gpt":0.2736918858668719,"score_spread":0.23025281970246608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319940240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988218,0.00007252092,0.000536889,0.00002600225,0.0000014893827,0.0000020106254,0.00031827844,0.000009599368,0.00021133925],"genre_scores_gemma":[0.99875355,0.00008257631,0.0005849479,0.0000055993173,0.0000032907872,0.0000045397055,0.00031168878,0.000009757396,0.00024397165],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998392,0.000026707938,0.000012061366,0.00006723506,0.00002196095,0.000032896314],"domain_scores_gemma":[0.99923456,0.000120250064,0.00039499928,0.000065940134,0.00010330469,0.00008097357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005914575,0.00023052386,0.00021117099,0.00060708367,0.00022618235,0.0005631786,0.00018400673,0.00021198983,0.0016384762],"category_scores_gemma":[0.0021604237,0.00018641017,0.00027562235,0.0004194841,0.00027149066,0.00036655497,0.00041079742,0.00031194952,0.00020315155],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098579985,0.000026381786,0.98469603,0.000013636933,0.000040426057,0.00012639187,0.00047860693,0.00043601537,0.003832726,0.00027583496,0.0002004183,0.009774952],"study_design_scores_gemma":[9.110934e-7,0.000015800091,0.99829584,0.000006346579,0.0000118066,0.000100580975,0.000114363174,0.00064909214,0.0005197788,0.0001522145,0.00013134317,0.0000018918665],"about_ca_topic_score_codex":0.009383335,"about_ca_topic_score_gemma":0.019925455,"teacher_disagreement_score":0.009383335,"about_ca_system_score_codex":0.00029614338,"about_ca_system_score_gemma":0.00037932993,"threshold_uncertainty_score":0.018657386},"labels":[],"label_agreement":null},{"id":"W4320491340","doi":"10.3390/biomedicines11020535","title":"Seeking the Amygdala: Novel Use of Diffusion Tensor Imaging to Delineate the Basolateral Amygdala","year":2023,"lang":"en","type":"article","venue":"Biomedicines","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute of Mental Health; University of California, Irvine; Loma Linda University","keywords":"Neuroscience; Diffusion MRI; Amygdala; Basolateral amygdala; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.1406367710354835,"score_gpt":0.3719878487178744,"score_spread":0.23135107768239088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320491340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17561936,0.0015571745,0.81886804,0.00068754784,0.00008216198,0.00020930433,0.0004475062,0.00052741566,0.0020015275],"genre_scores_gemma":[0.26816103,0.00163441,0.7281347,0.0001592453,0.00007011803,0.00018922087,0.00029381918,0.00018101874,0.0011763908],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99982613,0.00004619034,0.000014389387,0.000045341672,0.00005136003,0.000016607411],"domain_scores_gemma":[0.99973375,0.000051878997,0.00007486666,0.0000340945,0.00006738908,0.00003806318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007535855,0.00064207206,0.0002874046,0.0011104774,0.00031254577,0.0008368547,0.00044926084,0.00065999065,0.00083841867],"category_scores_gemma":[0.0012414047,0.0003800734,0.0002898357,0.0005100447,0.0004967651,0.0010185267,0.0006757588,0.0007645466,0.00035708345],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014950731,0.00006841054,0.0049304487,0.0003071712,0.00008990287,0.0004022036,0.00027446912,0.0042129774,0.90811986,0.0037907956,0.00068272074,0.07697169],"study_design_scores_gemma":[0.00013943188,0.00082770624,0.040655255,0.00016157715,0.0003366117,0.009284682,0.00047291326,0.30399758,0.60483944,0.016998345,0.021988051,0.00029834145],"about_ca_topic_score_codex":0.0016033791,"about_ca_topic_score_gemma":0.0036277077,"teacher_disagreement_score":0.0016033791,"about_ca_system_score_codex":0.0002448997,"about_ca_system_score_gemma":0.00061527215,"threshold_uncertainty_score":0.0039853454},"labels":[],"label_agreement":null},{"id":"W4320718974","doi":"10.1101/2023.02.10.23285704","title":"The genetic architecture of human cerebellar morphology supports a key role for the cerebellum in human evolution and psychopathology","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Helse Sør-Øst RHF; Nasjonalforeningen for Folkehelsen; Norges Forskningsråd; Universitetet i Oslo; Stiftelsen Kristian Gerhard Jebsen","keywords":"Cerebellum; Genetic architecture; Imaging genetics; Human Connectome Project; Neuroimaging; Psychopathology; Neuroscience; Brain morphometry; Biology; Genome-wide association study; Evolutionary biology; Psychology; Genetics; Single-nucleotide polymorphism; Gene; Functional connectivity; Phenotype; Medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.04637048212933488,"score_gpt":0.3531794992495026,"score_spread":0.3068090171201677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320718974","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99542713,0.00041090685,0.002114419,0.00023903543,0.000006646519,0.0000063589832,0.0010563064,0.00004699347,0.00069219986],"genre_scores_gemma":[0.9981249,0.00013980013,0.0009756435,0.00003150167,0.000009254551,0.000005351232,0.0003759422,0.000016636935,0.00032106062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996433,0.00007391863,0.00002752946,0.00017353914,0.000052646705,0.000028971612],"domain_scores_gemma":[0.9990452,0.00027175096,0.00038922817,0.00015885658,0.00006259727,0.00007236875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004930565,0.00032268558,0.00030184898,0.0011624674,0.00046098867,0.000984746,0.00029280223,0.00042890353,0.0050464123],"category_scores_gemma":[0.0020998619,0.00018014254,0.000416999,0.0011263127,0.00084680243,0.00024381356,0.0008457954,0.0005107114,0.00032690883],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009967496,0.00008435591,0.8227399,0.00019229596,0.001156991,0.0022916158,0.0010374085,0.0024649166,0.13523585,0.0026020783,0.0013085806,0.029889334],"study_design_scores_gemma":[0.000016314649,0.000045592045,0.9949126,0.000021573365,0.00008436991,0.0008024047,0.00010198444,0.0007304006,0.0016935148,0.00090999744,0.00067233073,0.00000875247],"about_ca_topic_score_codex":0.0055417093,"about_ca_topic_score_gemma":0.007014442,"teacher_disagreement_score":0.0055417093,"about_ca_system_score_codex":0.0002951557,"about_ca_system_score_gemma":0.00029465076,"threshold_uncertainty_score":0.016881883},"labels":[],"label_agreement":null},{"id":"W4320857731","doi":"10.1038/s41597-023-01942-5","title":"A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla","year":2023,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Congressionally Directed Medical Research Programs; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Government of Canada; U.S. Department of Defense","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Neuroimaging; Human Connectome Project; Computer science; Magnetization transfer; Nuclear magnetic resonance; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Radiology; Physics; Medicine; Biology; Functional connectivity","score_opus":0.20877625383579276,"score_gpt":0.4405094157300159,"score_spread":0.23173316189422313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320857731","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40675414,0.003213667,0.057699308,0.0007772492,0.00027003,0.00052864314,0.5202417,0.0050239894,0.0054913154],"genre_scores_gemma":[0.26038736,0.0019860908,0.07058014,0.000550897,0.000097710436,0.0010001503,0.6596695,0.0011164513,0.004611693],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997056,0.000038678685,0.000035294404,0.00010361284,0.00007664217,0.000040202212],"domain_scores_gemma":[0.999071,0.00012138583,0.00016838149,0.00023768481,0.00028976917,0.00011178215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077171857,0.0010684427,0.00073950464,0.0014860372,0.0004933129,0.0005614945,0.00070137624,0.0010371153,0.0028931538],"category_scores_gemma":[0.0009640487,0.0003688378,0.00067980174,0.0010899195,0.00042664888,0.00036427862,0.00071182,0.00080256065,0.0018421052],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003767632,0.0014975311,0.044250023,0.0032510662,0.0016369836,0.0026413465,0.0005163588,0.020228444,0.6388961,0.0022880498,0.1665693,0.11445725],"study_design_scores_gemma":[0.00072786584,0.0029352822,0.45214123,0.0008226308,0.0013967516,0.013481945,0.00062701455,0.04166577,0.18498184,0.010937639,0.2896877,0.00059432915],"about_ca_topic_score_codex":0.0040998263,"about_ca_topic_score_gemma":0.011571258,"teacher_disagreement_score":0.0040998263,"about_ca_system_score_codex":0.00039697537,"about_ca_system_score_gemma":0.00075457495,"threshold_uncertainty_score":0.009678543},"labels":[],"label_agreement":null},{"id":"W4320898602","doi":"10.1016/j.brs.2023.01.782","title":"Tractography analysis of subcallosal cingulate DBS for treatment-resistant depression using normative connectome data","year":2023,"lang":"en","type":"article","venue":"Brain stimulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Tractography; White matter; Connectome; Human Connectome Project; Neuroscience; Psychology; Depression (economics); Medicine; Magnetic resonance imaging; Functional connectivity; Radiology","score_opus":0.27062777260093585,"score_gpt":0.47059152272070376,"score_spread":0.1999637501197679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320898602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99555165,0.000026170404,0.0034567383,0.000012763247,0.0000015088478,0.000015908616,0.00067122414,0.00006751822,0.00019647244],"genre_scores_gemma":[0.9963224,0.000018852992,0.0021318982,0.0000029674502,0.0000015207115,0.000026592506,0.0013855742,0.000014947662,0.00009523751],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988437,0.000044938522,0.000012690636,0.000027117776,0.000018829543,0.000012075999],"domain_scores_gemma":[0.9995127,0.000221983,0.000073417774,0.000078257006,0.000086680455,0.000027127091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000402169,0.00021561734,0.00013853503,0.0008989173,0.0001625286,0.00022123786,0.00015122986,0.000116704585,0.0011605778],"category_scores_gemma":[0.002032208,0.00007397141,0.00021885343,0.0003845266,0.00014190195,0.0000972802,0.00017417093,0.00010067483,0.00017318477],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017496622,0.00018202067,0.81505376,0.00012705322,0.00063517166,0.0019348599,0.00076555193,0.025377862,0.07400906,0.001170751,0.0019339549,0.07706037],"study_design_scores_gemma":[0.000042369687,0.00022487924,0.8977333,0.000016048474,0.00010628907,0.0023631656,0.00022968139,0.08805974,0.009379195,0.0009346318,0.0008877076,0.000023036877],"about_ca_topic_score_codex":0.0081903115,"about_ca_topic_score_gemma":0.0094830245,"teacher_disagreement_score":0.0081903115,"about_ca_system_score_codex":0.000264414,"about_ca_system_score_gemma":0.00023681628,"threshold_uncertainty_score":0.01628524},"labels":[],"label_agreement":null},{"id":"W4320912460","doi":"10.1038/s41598-023-29557-1","title":"Relationship between manual dexterity and left–right asymmetry of anatomical and functional properties of corticofugal tracts revealed by T2-weighted brain images","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Left and right; Asymmetry; Anatomy; Brain asymmetry; Lateralization of brain function; Neuroscience; Computer science; Psychology; Biology; Artificial intelligence; Physics","score_opus":0.06480155682821778,"score_gpt":0.33021053953528096,"score_spread":0.26540898270706315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320912460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994223,0.000040864903,0.00019093406,0.000015918069,0.000002439365,0.0000039709494,0.00005150824,0.000007684969,0.00026443298],"genre_scores_gemma":[0.99973005,0.000011161639,0.00010764793,0.0000073351325,0.0000067791284,0.0000027434571,0.000039182254,0.0000027017993,0.00009238382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99950206,0.000101676196,0.0000841803,0.00016526891,0.00008731331,0.00005941935],"domain_scores_gemma":[0.9954065,0.0018325679,0.001676773,0.000426509,0.00022238378,0.00043523774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006832425,0.0005302282,0.00036340073,0.0013968193,0.0002497468,0.00038341383,0.00019275058,0.00051499414,0.0043136757],"category_scores_gemma":[0.0049439166,0.00030592122,0.00015813315,0.0003543877,0.0006897999,0.00042117602,0.00039859154,0.00043007222,0.00036438523],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026903069,0.00014552026,0.93911785,0.000049575414,0.0002457762,0.0034681312,0.00051972206,0.00042204536,0.04540413,0.00015207287,0.00013842565,0.0076465257],"study_design_scores_gemma":[0.000017664152,0.00023063185,0.992737,0.0000033410931,0.00002167744,0.004718795,0.00008098348,0.0006680154,0.0013609694,0.00010480272,0.000046132394,0.000009894415],"about_ca_topic_score_codex":0.0011622016,"about_ca_topic_score_gemma":0.0012139492,"teacher_disagreement_score":0.0043136757,"about_ca_system_score_codex":0.0001214843,"about_ca_system_score_gemma":0.000117132266,"threshold_uncertainty_score":0.014430702},"labels":[],"label_agreement":null},{"id":"W4321013998","doi":"10.1016/j.jagp.2022.12.219","title":"Brain-cognition relationships in late-life depression: a systematic review of magnetic resonance imaging studies","year":2023,"lang":"en","type":"review","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Occupational Cancer Research Centre; Toronto Dementia Research Alliance; St. Michael's Hospital; Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Late life depression; Precuneus; Dementia; Cognition; Medicine; Psychology; Anterior cingulate cortex; Entorhinal cortex; Posterior cingulate; Clinical psychology; Psychiatry; Internal medicine; Hippocampus; Disease","score_opus":0.09401243504466945,"score_gpt":0.4095725928797684,"score_spread":0.31556015783509894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321013998","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000643598,0.999106,0.00003872253,0.00005130601,0.000020598472,0.00001561866,0.00008117577,0.0000017120753,0.00004124516],"genre_scores_gemma":[0.009611008,0.98974776,0.00025240367,0.00017638052,0.00004760115,0.000031092597,0.00010066193,0.000001310846,0.000031699405],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9987907,0.0002805016,0.00045935117,0.00021675111,0.0002010814,0.000051594918],"domain_scores_gemma":[0.9954834,0.0032590015,0.00084575976,0.00006232546,0.0002794891,0.000070021546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023344674,0.0012509557,0.0063427133,0.003927221,0.00033104626,0.0015520215,0.0013264328,0.0013407181,0.0026332967],"category_scores_gemma":[0.007944508,0.00059162575,0.0061803744,0.0048210914,0.00048339635,0.0012126364,0.0011390038,0.00090188155,0.00017051991],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007318146,0.000071816634,0.005844938,0.79461795,0.05565822,0.00020938745,0.00016470188,0.0002966523,0.00052468985,0.0002828659,0.0026182558,0.13897863],"study_design_scores_gemma":[0.0011011827,0.00059911323,0.05636739,0.43284425,0.4688731,0.0012273478,0.0004954263,0.00037286145,0.00041893424,0.0010666988,0.036463395,0.00017035405],"about_ca_topic_score_codex":0.0050458377,"about_ca_topic_score_gemma":0.01955792,"teacher_disagreement_score":0.0063427133,"about_ca_system_score_codex":0.00083136023,"about_ca_system_score_gemma":0.0025292856,"threshold_uncertainty_score":0.01234597},"labels":[],"label_agreement":null},{"id":"W4321014026","doi":"10.1016/j.jagp.2022.12.218","title":"Brain-cognition associations in late-life depression or mild cognitive impairment: A multivariate analysis of white and gray matter integrity","year":2023,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Occupational Cancer Research Centre; Health Sciences Centre; Toronto Dementia Research Alliance; University of Toronto; University Health Network; St. Michael's Hospital; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; Dementia; White matter; Psychology; Cognition; Late life depression; Major depressive disorder; Hyperintensity; Cognitive decline; Effects of sleep deprivation on cognitive performance; Clinical psychology; Magnetic resonance imaging; Audiology; Psychiatry; Medicine; Internal medicine; Disease; Radiology","score_opus":0.03032322072128631,"score_gpt":0.36112719030288865,"score_spread":0.33080396958160235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321014026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991352,0.00019801277,0.00018744558,0.000057254096,0.000010072589,0.00000303118,0.00014100922,0.000005980311,0.00026195205],"genre_scores_gemma":[0.99952316,0.000046990688,0.00008476493,0.000009389743,0.000013785545,0.0000024308508,0.00012502953,0.0000033463111,0.00019096352],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99961734,0.00009939364,0.00003824314,0.00009747797,0.00005433067,0.00009312552],"domain_scores_gemma":[0.9990658,0.00021259359,0.0002910203,0.00013640276,0.00008222621,0.00021198462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000813784,0.00070546375,0.0005887275,0.0007760237,0.00056199706,0.0008528169,0.0005227602,0.0004931413,0.0017044547],"category_scores_gemma":[0.0019092215,0.00023179823,0.0015556167,0.0009828288,0.0003760271,0.00066826434,0.0007313047,0.0010082283,0.00017025559],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009392268,0.0001062577,0.9937499,0.000009988571,0.00087346,0.00013699236,0.00010337709,0.00016682968,0.00081620587,0.00005617937,0.00012878474,0.0029127218],"study_design_scores_gemma":[0.000006959013,0.000118512515,0.99842024,0.0000025821998,0.00016958448,0.00013330809,0.00011760886,0.00079955644,0.00007420851,0.000081332924,0.00007048592,0.000005648742],"about_ca_topic_score_codex":0.008973637,"about_ca_topic_score_gemma":0.013827034,"teacher_disagreement_score":0.008973637,"about_ca_system_score_codex":0.00029343858,"about_ca_system_score_gemma":0.0005667931,"threshold_uncertainty_score":0.01784277},"labels":[],"label_agreement":null},{"id":"W4321368652","doi":"10.1016/j.dib.2023.108999","title":"Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Institute for Basic Science; Albert-Ludwigs-Universität Freiburg; Sungkyunkwan University; Deutsche Forschungsgemeinschaft; National Alliance for Research on Schizophrenia and Depression","keywords":"Neuroimaging; Data science; Psychology; Neuroscience; Computer science","score_opus":0.2434314223278611,"score_gpt":0.41462192978624557,"score_spread":0.17119050745838446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321368652","genre_codex":"methods","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.117644735,0.0044770227,0.6164232,0.0024026248,0.0005361241,0.00039289042,0.20719293,0.038473893,0.012456643],"genre_scores_gemma":[0.18986875,0.0028232676,0.5451981,0.0005590787,0.00023767506,0.0018204638,0.24203998,0.011622263,0.0058304467],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992792,0.000114069444,0.00011929753,0.00020953629,0.00022248976,0.000055416527],"domain_scores_gemma":[0.9967937,0.00063526764,0.00035481213,0.0014695233,0.00062562816,0.00012103675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016329164,0.00075922656,0.00062495016,0.0031708165,0.0006615559,0.0026476684,0.001327438,0.00093630195,0.009380928],"category_scores_gemma":[0.0068991682,0.0005910768,0.00069950946,0.003216128,0.00080251705,0.001886401,0.0022004629,0.0013759048,0.0044000796],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096397183,0.00013902047,0.02553727,0.003131196,0.0004880536,0.0009761607,0.0022890358,0.020517994,0.11666509,0.02684971,0.2675344,0.5349081],"study_design_scores_gemma":[0.00009717038,0.0002076975,0.073526435,0.0010551442,0.00026563383,0.0053007933,0.0011245328,0.036061194,0.084472656,0.055637173,0.74189454,0.0003571034],"about_ca_topic_score_codex":0.0044650636,"about_ca_topic_score_gemma":0.01259362,"teacher_disagreement_score":0.009380928,"about_ca_system_score_codex":0.0006573137,"about_ca_system_score_gemma":0.0017911709,"threshold_uncertainty_score":0.031382382},"labels":[],"label_agreement":null},{"id":"W4321452105","doi":"10.1002/hbm.26239","title":"Integrated diffusion image operator (<scp>iDIO</scp>): A pipeline for automated configuration and processing of diffusion <scp>MRI</scp> data","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; National Institute on Aging; Chang Gung Medical Foundation; Shanghai Educational Development Foundation; Eisai; Servier; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Science and Technology Council; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Computer science; Human Connectome Project; Pipeline (software); Data mining; Preprocessor; Data processing; Image processing; Workflow; Artificial intelligence; Data pre-processing; Diffusion MRI; Image quality; Software; Pattern recognition (psychology); Computer vision; Image (mathematics); Database","score_opus":0.09895152468378401,"score_gpt":0.3742674330731081,"score_spread":0.27531590838932407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321452105","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0033720126,0.00047718541,0.72849447,0.00056033285,0.00018824352,0.0007979019,0.0069588474,0.2538742,0.0052767857],"genre_scores_gemma":[0.027349401,0.00068840873,0.8852028,0.0009064401,0.00015907577,0.0018229426,0.020619944,0.055851966,0.007398855],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981877,0.00028980637,0.00024614367,0.0004693433,0.0005850995,0.00022186642],"domain_scores_gemma":[0.99400395,0.0022459966,0.0005531182,0.0010920593,0.0015876275,0.0005172836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055357027,0.0030451529,0.0013366294,0.0037021048,0.0009851368,0.0033012829,0.003598925,0.0014792166,0.04359374],"category_scores_gemma":[0.014367586,0.0018041132,0.0017268134,0.0017480247,0.0010110788,0.0033951227,0.005474026,0.0028463386,0.029293168],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015264754,0.0001741182,0.003560303,0.0018546659,0.0003006663,0.001487595,0.0015376351,0.0029836532,0.06768309,0.013884992,0.41348314,0.49152365],"study_design_scores_gemma":[0.0006632971,0.00036621816,0.011981803,0.00062316767,0.00019070656,0.003632531,0.00054740644,0.10181579,0.20889913,0.035249624,0.63514477,0.0008855853],"about_ca_topic_score_codex":0.0025992102,"about_ca_topic_score_gemma":0.0035114936,"teacher_disagreement_score":0.04359374,"about_ca_system_score_codex":0.0008627319,"about_ca_system_score_gemma":0.0030286424,"threshold_uncertainty_score":0.14583558},"labels":[],"label_agreement":null},{"id":"W4321496860","doi":"10.3389/fnins.2023.1049609","title":"Effect of sex on the APOE4-aging interaction in the white matter microstructure of cognitively normal older adults using diffusion-tensor MRI with orthogonal-tensor decomposition (DT-DOME)","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Center for Advancing Translational Sciences; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Faculty of Medicine, Chiang Mai University; Thailand Research Fund; Canadian Institutes of Health Research; National Institutes of Health; Royal Golden Jubilee (RGJ) Ph.D. Programme; Chiang Mai University","keywords":"White matter; Diffusion MRI; Psychology; Fasciculus; Neuroscience; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.015611776959650317,"score_gpt":0.31666505784390103,"score_spread":0.3010532808842507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321496860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985582,0.000565346,0.0004631822,0.000025287043,0.000012628296,0.0000055042915,0.00012230982,0.0000067801448,0.0002406643],"genre_scores_gemma":[0.99877864,0.00012962171,0.0005842866,0.000019864285,0.0000125310535,0.000007751727,0.00008455425,0.0000081500775,0.00037454246],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996867,0.000097560165,0.00003724787,0.0001004255,0.000043773725,0.0000342586],"domain_scores_gemma":[0.998808,0.0003964503,0.00042972757,0.00017340473,0.00009127074,0.00010113383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011179706,0.00046614328,0.00032948673,0.00043596397,0.00019451893,0.0005519394,0.0001833477,0.00034908898,0.0013567253],"category_scores_gemma":[0.0032012155,0.00015309687,0.0005193155,0.00032458125,0.00027367444,0.00043197707,0.0003874006,0.00025602937,0.00013421905],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009490788,0.00017921357,0.9416967,0.000097380806,0.00097648555,0.00043423014,0.0006555542,0.00019824313,0.017997323,0.0002363186,0.00016869212,0.02786893],"study_design_scores_gemma":[0.000020610285,0.00051973504,0.9970139,0.000008194889,0.00022151654,0.00023420028,0.00008297292,0.00050883065,0.0009846542,0.00019434578,0.00020237191,0.000008586664],"about_ca_topic_score_codex":0.0014450385,"about_ca_topic_score_gemma":0.0023920576,"teacher_disagreement_score":0.0014450385,"about_ca_system_score_codex":0.00009034653,"about_ca_system_score_gemma":0.00022505232,"threshold_uncertainty_score":0.0059124827},"labels":[],"label_agreement":null},{"id":"W4321598136","doi":"10.3390/biology12030353","title":"Morphological Abnormalities in Early-Onset Schizophrenia Revealed by Structural Magnetic Resonance Imaging","year":2023,"lang":"en","type":"article","venue":"Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health; St. Francis Xavier University","keywords":"Neurotypical; Schizophrenia (object-oriented programming); Magnetic resonance imaging; Cuneus; Neuroscience; Superior temporal gyrus; Inferior temporal gyrus; Gyrus; Cortex (anatomy); Biology; Anatomy; Psychology; Functional magnetic resonance imaging; Temporal lobe; Precuneus; Medicine; Radiology; Epilepsy; Psychiatry","score_opus":0.039681147442310195,"score_gpt":0.3397763233286215,"score_spread":0.3000951758863113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321598136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994697,0.000133457,0.00019891027,0.000009690143,0.0000010302475,0.000003836879,0.000058633643,0.0000065740655,0.00011804311],"genre_scores_gemma":[0.9992212,0.00015942233,0.00041893675,0.0000083600025,0.0000021755438,0.000003546687,0.00008005753,0.00000358387,0.00010283945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998745,0.00002824824,0.000013875176,0.000028082617,0.000035615187,0.000019672681],"domain_scores_gemma":[0.9994824,0.00005374665,0.00031340535,0.000045706638,0.00003897,0.000065850516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033850907,0.0004274656,0.00019839634,0.0014482195,0.00020681789,0.0003522203,0.00012764934,0.00022884965,0.00063770096],"category_scores_gemma":[0.0007954634,0.00022761385,0.00017619558,0.00038495008,0.0004003578,0.00019903827,0.00032411682,0.0002267044,0.00008972818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009871987,0.000092465096,0.7259484,0.00009074985,0.00019616312,0.0030135526,0.0007918249,0.00036119786,0.2540502,0.00020092918,0.00011021975,0.014157077],"study_design_scores_gemma":[0.0000033315491,0.000061950086,0.9965592,0.0000048681577,0.000013541076,0.0012672914,0.00009319173,0.00012131378,0.0017530977,0.000056967994,0.00006147109,0.0000038029964],"about_ca_topic_score_codex":0.0021969574,"about_ca_topic_score_gemma":0.004701437,"teacher_disagreement_score":0.0021969574,"about_ca_system_score_codex":0.00023412399,"about_ca_system_score_gemma":0.00023965715,"threshold_uncertainty_score":0.004368365},"labels":[],"label_agreement":null},{"id":"W4321844994","doi":"10.1007/978-3-030-98661-2_108","title":"A Survey on Deep Learning-Based Diffeomorphic Mapping","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffeomorphism; Artificial intelligence; Computer science; Autoencoder; Deep learning; Polygon mesh; Convolutional neural network; Segmentation; Unsupervised learning; Pattern recognition (psychology); Machine learning; Mathematics","score_opus":0.16712890854143733,"score_gpt":0.3412837986051227,"score_spread":0.17415489006368537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321844994","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002088747,0.3727761,0.5599651,0.0018817538,0.0019554868,0.00007763223,0.00087487727,0.0013631126,0.059017275],"genre_scores_gemma":[0.021698477,0.5289936,0.36742184,0.0011236449,0.0021226811,0.00015560116,0.002789573,0.0008223707,0.07487228],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99977785,0.000027563327,0.000021784641,0.000046322126,0.00011449332,0.000011975171],"domain_scores_gemma":[0.99953794,0.0002459293,0.000020193364,0.00005236771,0.00012308755,0.000020552012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005700828,0.0008830278,0.0009892399,0.002119005,0.00024823152,0.001422262,0.0011219783,0.0009229998,0.013146871],"category_scores_gemma":[0.0016271485,0.00064369757,0.0006333771,0.004923625,0.00048608275,0.0022028522,0.0011022084,0.001506688,0.0070597995],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018377586,0.000032656622,0.00014646589,0.0012806881,0.000030983258,0.000058372447,0.000030987452,0.006500677,0.001479823,0.036317423,0.04588331,0.90822023],"study_design_scores_gemma":[0.000010370568,0.00008086145,0.0007594807,0.0008666013,0.00005059765,0.001139372,0.00004317211,0.06111663,0.0043142023,0.12394709,0.8076097,0.000061943414],"about_ca_topic_score_codex":0.0018452316,"about_ca_topic_score_gemma":0.0032355618,"teacher_disagreement_score":0.013146871,"about_ca_system_score_codex":0.00063653203,"about_ca_system_score_gemma":0.00070331764,"threshold_uncertainty_score":0.043980658},"labels":[],"label_agreement":null},{"id":"W4322630837","doi":"10.1101/2023.02.25.530046","title":"Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute on Aging; National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Tractography; Diffusion MRI; Context (archaeology); Convolutional neural network; Computer science; Artificial intelligence; Diffusion; Magnetic resonance imaging; Neuroscience; Medicine; Psychology; Radiology; Physics; Biology","score_opus":0.035304940686680525,"score_gpt":0.2762823238498559,"score_spread":0.24097738316317538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322630837","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06830267,0.0002533855,0.92839164,0.00021312873,0.00004116013,0.00002858244,0.00023080935,0.0013080742,0.0012304973],"genre_scores_gemma":[0.72613126,0.00046456038,0.26777232,0.000105182764,0.00006092529,0.000087155844,0.00089390855,0.00028262124,0.004202062],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984884,0.000029350706,0.000007589227,0.000054773445,0.000033882316,0.000025512447],"domain_scores_gemma":[0.9993747,0.0002478465,0.00013719493,0.000101201724,0.00011138987,0.000027700278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068610994,0.00076865766,0.0003432635,0.0004475993,0.000172173,0.0005407783,0.000949921,0.0006594091,0.0011407041],"category_scores_gemma":[0.0034813294,0.00035358654,0.00042855207,0.00049076474,0.00037458434,0.000926591,0.0005846992,0.00092672155,0.0005692678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001416779,0.00007160296,0.004508592,0.0001332893,0.000117148586,0.000225421,0.000110591376,0.7585202,0.033137947,0.015567013,0.0026513496,0.18481518],"study_design_scores_gemma":[0.0000029551231,0.000011037576,0.00043447834,0.000004822093,0.0000064165056,0.000025106952,0.0000036254537,0.9932287,0.0028210531,0.0030992883,0.0003589879,0.0000035549106],"about_ca_topic_score_codex":0.006382561,"about_ca_topic_score_gemma":0.015225754,"teacher_disagreement_score":0.006382561,"about_ca_system_score_codex":0.00070536556,"about_ca_system_score_gemma":0.00092322775,"threshold_uncertainty_score":0.012690783},"labels":[],"label_agreement":null},{"id":"W4322723775","doi":"10.1016/j.jmbbm.2023.105744","title":"Transversely-isotropic brain in vivo MR elastography with anisotropic damping","year":2023,"lang":"en","type":"article","venue":"Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Office of Naval Research; National Institutes of Health","keywords":"Transverse isotropy; Anisotropy; Elastography; Magnetic resonance elastography; Isotropy; Imaging phantom; Fractional anisotropy; Stiffness; Diffusion MRI; Physics; Population; Estimator; White matter; Biomedical engineering; Materials science; Nuclear magnetic resonance; Magnetic resonance imaging; Mathematics; Acoustics; Optics; Statistics; Ultrasound; Radiology; Medicine","score_opus":0.037647189582221526,"score_gpt":0.3225610409264671,"score_spread":0.28491385134424557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322723775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6767728,0.0011296144,0.31501216,0.00058616727,0.000055250533,0.00013390403,0.00032088044,0.00045928525,0.0055298773],"genre_scores_gemma":[0.85363585,0.0010753679,0.14140819,0.00013291456,0.000050911603,0.00010409358,0.00016577475,0.0002040607,0.0032229316],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986076,0.00005449789,0.000009482205,0.000022031109,0.000034336335,0.000018808101],"domain_scores_gemma":[0.9997032,0.0001548047,0.000050964092,0.000043650016,0.000027183598,0.000020080106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045597568,0.0005479303,0.00026736275,0.0003415815,0.00022567269,0.00052815233,0.00027676916,0.00068915397,0.0020970888],"category_scores_gemma":[0.0013200546,0.00048231843,0.00022248169,0.0004074362,0.0004915881,0.0005850195,0.0004995884,0.0005646112,0.0002834617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008300272,0.000120231634,0.0018021215,0.00021378406,0.000051086216,0.0005523882,0.00019685735,0.005079306,0.9686828,0.0013584504,0.00032789915,0.020785179],"study_design_scores_gemma":[0.00031445606,0.0014684141,0.029162332,0.00017614206,0.00039017972,0.011023225,0.00034818635,0.13539723,0.8105848,0.0034459159,0.0075893924,0.00009981025],"about_ca_topic_score_codex":0.0004930863,"about_ca_topic_score_gemma":0.0013766473,"teacher_disagreement_score":0.0020970888,"about_ca_system_score_codex":0.00008454546,"about_ca_system_score_gemma":0.00023218089,"threshold_uncertainty_score":0.0070155263},"labels":[],"label_agreement":null},{"id":"W4323066381","doi":"10.1093/schbul/sbac216","title":"Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls","year":2023,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Neurocognitive; Psychology; White matter; Cognition; Social cognition; Schizophrenia (object-oriented programming); Neuropsychology; Diffusion MRI; Corpus callosum; Developmental psychology; Cognitive psychology; Clinical psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.02368602726047368,"score_gpt":0.3091226926225757,"score_spread":0.285436665362102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323066381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99969804,0.000019941723,0.00008738608,0.000014165296,0.0000014509689,0.0000024348587,0.00010726245,0.0000017549643,0.000067693014],"genre_scores_gemma":[0.99975663,0.000011492073,0.000065896864,0.000004081315,0.0000018712335,0.0000036798751,0.00011825879,0.0000011738302,0.00003693825],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967015,0.00007375548,0.00003856954,0.00012380471,0.000041027663,0.000052643547],"domain_scores_gemma":[0.99916935,0.00017498777,0.00032718654,0.000116594005,0.00006099614,0.00015094243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074094575,0.00045246634,0.00022656805,0.0009040358,0.00038910945,0.00042729426,0.0002205416,0.00030568565,0.0016321315],"category_scores_gemma":[0.0020661515,0.00015263219,0.00033269753,0.0004904442,0.00060354685,0.00029847876,0.00075701583,0.00035209724,0.000104087],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021477023,0.000029012017,0.99676967,0.000005603447,0.00012957906,0.000036705416,0.00016761597,0.00008172075,0.0011832032,0.000060078703,0.000047599373,0.0012743332],"study_design_scores_gemma":[0.0000046698856,0.00004906866,0.99918395,0.0000021499536,0.000026456373,0.00007017321,0.00016912786,0.0002717501,0.00010145344,0.00008909939,0.000029744368,0.000002356646],"about_ca_topic_score_codex":0.009607478,"about_ca_topic_score_gemma":0.011911502,"teacher_disagreement_score":0.009607478,"about_ca_system_score_codex":0.00033882292,"about_ca_system_score_gemma":0.00031392695,"threshold_uncertainty_score":0.01910311},"labels":[],"label_agreement":null},{"id":"W4323073897","doi":"10.1101/2023.03.01.530710","title":"The Human Brain Connectome Weighted by the Myelin Content and Total Intra-Axonal Cross-Sectional Area of White Matter Tracts","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canadian Institutes of Health Research; Hospital for Sick Children; Fondation Brain Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Connectome; Diffusion MRI; Myelin; Neuroscience; Human brain; Human Connectome Project; Connectomics; Computer science; Psychology; Biology; Functional connectivity; Central nervous system; Medicine; Magnetic resonance imaging","score_opus":0.06648026584508343,"score_gpt":0.3067531004412651,"score_spread":0.24027283459618165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323073897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97587675,0.0000882915,0.022678211,0.00006480807,0.0000040892082,0.000010972258,0.00049103744,0.00004931175,0.00073659274],"genre_scores_gemma":[0.99425286,0.00004594649,0.0051757833,0.000008520948,0.0000026569721,0.0000137216475,0.00028842178,0.0000065838126,0.00020546533],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9999558,0.000010979782,0.000002199515,0.000018502717,0.0000082141805,0.000004418891],"domain_scores_gemma":[0.99968123,0.00015589688,0.000075921285,0.00002549319,0.000042056985,0.000019389241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017040223,0.00019759513,0.00012564324,0.00061803625,0.00011856831,0.00025241813,0.00015243627,0.0001667243,0.0013764317],"category_scores_gemma":[0.0012805308,0.00007869532,0.00016227976,0.00045369423,0.00021339665,0.0003057801,0.00018685167,0.000116012896,0.00009237346],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000578818,0.00014628825,0.1291299,0.00029631975,0.00060167606,0.0008116711,0.0004862163,0.6219796,0.1593198,0.027726166,0.0031157949,0.05580781],"study_design_scores_gemma":[0.000015020346,0.000095201496,0.115787074,0.000018612023,0.00007029781,0.00053965836,0.00013059146,0.84705806,0.012159157,0.023063619,0.001037096,0.000025724501],"about_ca_topic_score_codex":0.002277776,"about_ca_topic_score_gemma":0.0027421727,"teacher_disagreement_score":0.002277776,"about_ca_system_score_codex":0.00018774407,"about_ca_system_score_gemma":0.00015695451,"threshold_uncertainty_score":0.004604578},"labels":[],"label_agreement":null},{"id":"W4323269182","doi":"10.1016/j.nicl.2023.103367","title":"Aberrant frontal lobe “U”-shaped association fibers in first-episode schizophrenia: A 7-Tesla Diffusion Imaging Study","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Dalhousie University; Schulich School of Medicine and Dentistry; Western University; Canada Foundation for Innovation; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; McGill University; Chrysalis","keywords":"Frontal lobe; Schizophrenia (object-oriented programming); Diffusion MRI; Association (psychology); Neuroscience; Temporal lobe; Psychology; Medicine; Magnetic resonance imaging; Psychiatry; Epilepsy; Radiology","score_opus":0.08897231508810213,"score_gpt":0.4085580601756791,"score_spread":0.319585745087577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323269182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993038,0.00014546092,0.00015231328,0.000040269766,0.0000021439562,0.000017483506,0.00005429012,0.000003658952,0.00028058604],"genre_scores_gemma":[0.9993981,0.00015473722,0.00020701233,0.000019254816,0.000005346604,0.000005945798,0.0000711721,0.0000023664668,0.0001360029],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998876,0.000020445717,0.00001323198,0.000027280112,0.000018785517,0.000032593987],"domain_scores_gemma":[0.9995596,0.00006321589,0.00012970353,0.000041765306,0.000058446407,0.00014714376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007430596,0.00047527635,0.00023841459,0.00089661294,0.0006420644,0.00047574905,0.00024098589,0.0006869131,0.0013796955],"category_scores_gemma":[0.0009349065,0.00029266495,0.00025130608,0.00037675604,0.0005514591,0.00040963618,0.0004444344,0.0004093075,0.0003333493],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027553034,0.0013625589,0.7972649,0.00022456306,0.00019528433,0.029278249,0.004872982,0.00050182134,0.14887443,0.00037194023,0.00032853632,0.013969465],"study_design_scores_gemma":[0.000031012718,0.00076590275,0.985306,0.000021780586,0.000060691757,0.010584771,0.00073230336,0.00033672675,0.0016899146,0.00011112152,0.00034147257,0.000018261228],"about_ca_topic_score_codex":0.012188304,"about_ca_topic_score_gemma":0.015570412,"teacher_disagreement_score":0.012188304,"about_ca_system_score_codex":0.0005285779,"about_ca_system_score_gemma":0.00069988024,"threshold_uncertainty_score":0.024234772},"labels":[],"label_agreement":null},{"id":"W4323347970","doi":"10.1093/cercor/bhad052","title":"Loss of age-related laminar differentiation of intracortical myelin in bipolar disorder","year":2023,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McGill University; Montreal Neurological Institute and Hospital; St. Joseph’s Healthcare Hamilton","funders":"Canadian Institutes of Health Research; McMaster University; Brain and Behavior Research Foundation","keywords":"Myelin; Neuroscience; Bipolar disorder; Psychology; Medicine; Cognition; Central nervous system","score_opus":0.031139920224618242,"score_gpt":0.3214482965989662,"score_spread":0.2903083763743479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323347970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99919754,0.00023903913,0.0002164291,0.000011940564,0.0000035282374,0.000003092747,0.000098030294,0.0000056428084,0.00022474652],"genre_scores_gemma":[0.9988452,0.00017283662,0.00029661512,0.00002172303,0.00000473718,0.0000067548344,0.00021971394,0.0000057034586,0.0004266594],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992216,0.000012444983,0.000008647808,0.000024653173,0.000015374979,0.000016683016],"domain_scores_gemma":[0.9997317,0.000030608695,0.00014802717,0.000020219866,0.000033241427,0.00003615101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024141204,0.00022638192,0.00014104412,0.0006235921,0.00016128337,0.00028150753,0.00008458143,0.00024554477,0.0013083902],"category_scores_gemma":[0.00059093034,0.00018977984,0.000121834186,0.00024115253,0.00018754958,0.00018709234,0.00019491905,0.00016447659,0.00015805506],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0055661933,0.0001387713,0.7408036,0.00014000222,0.00027938705,0.0013443436,0.0011376028,0.00048691503,0.21347593,0.0001868578,0.00076984765,0.035670597],"study_design_scores_gemma":[0.000007458037,0.00006407962,0.9983847,0.000005409072,0.000013692335,0.0003864652,0.00006509611,0.00013185087,0.0008077361,0.000049063976,0.00008166641,0.000002830846],"about_ca_topic_score_codex":0.0055593443,"about_ca_topic_score_gemma":0.0086621065,"teacher_disagreement_score":0.0055593443,"about_ca_system_score_codex":0.00022157966,"about_ca_system_score_gemma":0.000106112195,"threshold_uncertainty_score":0.011053979},"labels":[],"label_agreement":null},{"id":"W4323364366","doi":"10.3389/fnins.2023.1074730","title":"Estimation of free water-corrected microscopic fractional anisotropy","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Orientation (vector space); Free water; Nuclear magnetic resonance; Partial volume; Diffusion; Dispersion (optics); SIGNAL (programming language); Voxel; Materials science; Biological system; Physics; Biomedical engineering; Computer science; Mathematics; Optics; Artificial intelligence; Geology; Magnetic resonance imaging; Geometry; Medicine; Biology; Radiology; Thermodynamics","score_opus":0.036493819689401505,"score_gpt":0.33623006747423156,"score_spread":0.29973624778483005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323364366","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058744013,0.00063920347,0.9374012,0.000087875436,0.00006593427,0.00008934521,0.00021662189,0.0012491804,0.0015065793],"genre_scores_gemma":[0.4535062,0.0009940834,0.54154,0.0000433577,0.000060891496,0.00016670443,0.0004907429,0.00050486816,0.002693229],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997485,0.000043520682,0.00001650632,0.0000663203,0.00009791481,0.000027227015],"domain_scores_gemma":[0.99930966,0.000208082,0.00012794386,0.00013227531,0.00019501576,0.000026997712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096332293,0.00075362565,0.0006824385,0.0016810457,0.00035138935,0.00093146245,0.0007023079,0.00055044185,0.0015463046],"category_scores_gemma":[0.004627539,0.00033530057,0.0006504336,0.00080263254,0.0004404803,0.0009486588,0.0005126518,0.0006673482,0.00048636989],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047841851,0.000083200044,0.012621027,0.00061805587,0.0003478581,0.00046361246,0.00035958842,0.053943258,0.33432692,0.016244926,0.0038183923,0.57669485],"study_design_scores_gemma":[0.00005781055,0.00038904962,0.0462162,0.00008914671,0.00041503808,0.0027102032,0.00015449616,0.5723292,0.32893535,0.024003573,0.024428394,0.00027157177],"about_ca_topic_score_codex":0.0025002467,"about_ca_topic_score_gemma":0.002381861,"teacher_disagreement_score":0.0025002467,"about_ca_system_score_codex":0.00032102157,"about_ca_system_score_gemma":0.00074182963,"threshold_uncertainty_score":0.0051728487},"labels":[],"label_agreement":null},{"id":"W4323364368","doi":"10.3389/fnut.2023.1108360","title":"Extended and replicated white matter changes in obesity: Voxel-based and region of interest meta-analyses of diffusion tensor imaging studies","year":2023,"lang":"en","type":"article","venue":"Frontiers in Nutrition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Voxel; White matter; Diffusion; Meta-analysis; Psychology; Computer science; Cognitive psychology; Medicine; Physics; Artificial intelligence; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.2617820086621642,"score_gpt":0.409704120920407,"score_spread":0.14792211225824276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323364368","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24897161,0.6874882,0.052641,0.0022164977,0.0010552221,0.0008078837,0.0045897495,0.0005777523,0.0016520725],"genre_scores_gemma":[0.94913316,0.029949958,0.017623357,0.0004746642,0.00025310743,0.0007280313,0.0013655241,0.00016501443,0.00030718438],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.97058994,0.019654848,0.0035054744,0.0040338533,0.0015957203,0.0006202652],"domain_scores_gemma":[0.95794606,0.030188994,0.004293656,0.005084096,0.002077652,0.00040955326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03948347,0.0026957584,0.006082372,0.0048691547,0.0008779467,0.0034199124,0.0022175044,0.0015988536,0.002431261],"category_scores_gemma":[0.060748763,0.0013200539,0.032080933,0.0054054977,0.0010361188,0.0015449551,0.0020712141,0.001993275,0.00021848879],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026225662,0.00003811639,0.067761816,0.012161564,0.9024841,0.00029613162,0.00020059597,0.00193933,0.0012596694,0.00055134704,0.0006302156,0.010054532],"study_design_scores_gemma":[0.0007949358,0.00035386995,0.055797465,0.001896981,0.9337332,0.00030801486,0.00010539773,0.0024000427,0.0006232202,0.002280571,0.0016595479,0.00004668458],"about_ca_topic_score_codex":0.005903198,"about_ca_topic_score_gemma":0.009162204,"teacher_disagreement_score":0.03948347,"about_ca_system_score_codex":0.0011288599,"about_ca_system_score_gemma":0.0019753408,"threshold_uncertainty_score":0.20881104},"labels":[],"label_agreement":null},{"id":"W4323534158","doi":"10.1002/oby.23686","title":"Is adiposity associated with white matter microstructural health and intelligence differently in males and females?","year":2023,"lang":"en","type":"article","venue":"Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; Biobank; Diffusion MRI; Medicine; Obesity; Fractional anisotropy; Abdominal obesity; Cardiovascular health; Physiology; Internal medicine; Demography; Metabolic syndrome; Magnetic resonance imaging; Bioinformatics; Biology","score_opus":0.06887097637335537,"score_gpt":0.347940609240043,"score_spread":0.2790696328666876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323534158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980837,0.0006604949,0.00010845941,0.00023591146,0.00001536783,0.000002744948,0.00016087732,0.0000027067197,0.000729746],"genre_scores_gemma":[0.999102,0.0002473185,0.000080191094,0.000066770684,0.000029414297,0.0000026711073,0.000097173746,0.0000031551713,0.00037139174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999762,0.000056656867,0.000018387145,0.00008216925,0.00003953254,0.000041271924],"domain_scores_gemma":[0.99923456,0.00014219574,0.00044941346,0.00005663281,0.000039262683,0.00007793259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054677005,0.00020375737,0.00025753456,0.0005611326,0.00020892013,0.0005686989,0.00015736287,0.0003052881,0.0034050501],"category_scores_gemma":[0.0020166459,0.00014814016,0.00030665475,0.00045317732,0.0004089526,0.00037125908,0.00028431727,0.00028045848,0.00042870062],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024997987,0.000025287167,0.99040866,0.00001835443,0.000105884275,0.00014280691,0.0003669656,0.00001879663,0.0013594955,0.00014025166,0.0001893227,0.006974155],"study_design_scores_gemma":[0.0000025560346,0.000046278805,0.9991105,0.000009343223,0.000015874255,0.00026521206,0.00016965254,0.000033509918,0.00008332362,0.000094964635,0.00016677562,0.0000020499142],"about_ca_topic_score_codex":0.0010728253,"about_ca_topic_score_gemma":0.0015436852,"teacher_disagreement_score":0.0034050501,"about_ca_system_score_codex":0.00008056783,"about_ca_system_score_gemma":0.000109737935,"threshold_uncertainty_score":0.011391103},"labels":[],"label_agreement":null},{"id":"W4323536554","doi":"10.1101/2023.03.03.23286579","title":"What has brain diffusion MRI taught us about chronic pain: a narrative review","year":2023,"lang":"en","type":"review","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arthritis Society","keywords":"Chronic pain; Diffusion MRI; Narrative review; Medicine; Neuroscience; White matter; Harmonization; Psychology; Intensive care medicine; Magnetic resonance imaging; Radiology","score_opus":0.15357747015557532,"score_gpt":0.43233466999705067,"score_spread":0.27875719984147534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323536554","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006521054,0.99881566,0.00004059171,0.0006321672,0.00017384285,0.000002459743,0.00001671788,0.00000201271,0.00025131996],"genre_scores_gemma":[0.00072214147,0.99847656,0.000060903527,0.00038010458,0.0002698533,0.000004364706,0.000015154405,9.968113e-7,0.00006991073],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99950254,0.00012223802,0.0001218179,0.00009777027,0.0001234708,0.000032219177],"domain_scores_gemma":[0.9964707,0.0026579758,0.0003753607,0.00004722686,0.0003674818,0.00008117689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012536956,0.0007707077,0.0017775876,0.0039200317,0.00045726213,0.0019555683,0.0010481937,0.0019444661,0.0037022613],"category_scores_gemma":[0.0056840423,0.00035072188,0.0009700666,0.00377468,0.0009240012,0.0026787543,0.00079568144,0.0015788776,0.00085493026],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014045018,0.00003665557,0.00050937274,0.20612466,0.00044736656,0.0004376926,0.00043435165,0.0003261237,0.0005561077,0.007169374,0.047175843,0.736642],"study_design_scores_gemma":[0.000040577877,0.0001356532,0.0034162018,0.2083903,0.001330312,0.0062004835,0.00063460553,0.00019699699,0.00034459843,0.0059967414,0.7732355,0.0000779731],"about_ca_topic_score_codex":0.002080616,"about_ca_topic_score_gemma":0.003014409,"teacher_disagreement_score":0.0039200317,"about_ca_system_score_codex":0.001013221,"about_ca_system_score_gemma":0.0029054445,"threshold_uncertainty_score":0.012385249},"labels":[],"label_agreement":null},{"id":"W4323665786","doi":"10.3389/fnimg.2023.1099301","title":"Optimizing automated white matter hyperintensity segmentation in individuals with stroke","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council; National Institute of Neurological Disorders and Stroke; Medical Research Council; National Institutes of Health; University of Melbourne; Canadian Institutes of Health Research; National Imaging Facility","keywords":"Segmentation; Hyperintensity; Stroke (engine); Artificial intelligence; Computer science; Machine learning; Medicine; Magnetic resonance imaging; Engineering","score_opus":0.031687756835165094,"score_gpt":0.3118026041172791,"score_spread":0.280114847282114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323665786","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47140753,0.002913882,0.487599,0.0018528801,0.00034452064,0.0005550451,0.004716097,0.026025979,0.004585159],"genre_scores_gemma":[0.5710914,0.00064024463,0.41415355,0.0008884356,0.00010169944,0.00044520324,0.0065028453,0.0032965443,0.002879962],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876237,0.00043160064,0.00010432218,0.00045313934,0.00015729407,0.00009137081],"domain_scores_gemma":[0.9979874,0.001051959,0.00018517216,0.00032452302,0.00037922172,0.000071693226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004063712,0.0013678826,0.0010313404,0.0012214431,0.00095954206,0.002229884,0.0013478423,0.0017570307,0.001903023],"category_scores_gemma":[0.011471079,0.0010066773,0.0013278928,0.00086689374,0.0006354068,0.0009947608,0.001405276,0.0009804206,0.0020194433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019009913,0.00039225206,0.040186733,0.0009926206,0.0016100734,0.0006822224,0.0014856148,0.2539699,0.081286654,0.0049661524,0.033026014,0.57950073],"study_design_scores_gemma":[0.00016444986,0.00031901852,0.023703037,0.00015774423,0.00037253567,0.0007328282,0.00031898686,0.8908311,0.05791529,0.012339406,0.012957479,0.00018817588],"about_ca_topic_score_codex":0.014745978,"about_ca_topic_score_gemma":0.031793628,"teacher_disagreement_score":0.014745978,"about_ca_system_score_codex":0.0011241939,"about_ca_system_score_gemma":0.0026170004,"threshold_uncertainty_score":0.0293203},"labels":[],"label_agreement":null},{"id":"W4323804540","doi":"10.1002/hbm.26259","title":"High spatial overlap but diverging age‐related trajectories of cortical magnetic resonance imaging markers aiming to represent intracortical myelin and microstructure","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Polytechnique Montréal; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Weston Brain Institute","keywords":"Cytoarchitecture; Magnetic resonance imaging; Myelin; White matter; Neuroscience; Neuroimaging; Nuclear magnetic resonance; Psychology; Medicine; Central nervous system; Physics; Radiology","score_opus":0.030363313889827343,"score_gpt":0.31018636863866406,"score_spread":0.27982305474883673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323804540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99512947,0.00038414105,0.0036841144,0.0000150116875,0.000003192523,0.000008167194,0.0002706257,0.000042829535,0.00046237602],"genre_scores_gemma":[0.99734026,0.00009574117,0.0016856425,0.000007244287,0.000003988222,0.000012509285,0.00049727334,0.000022771359,0.00033458837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999554,0.00006537964,0.000039098242,0.00020946082,0.00007762307,0.00005449733],"domain_scores_gemma":[0.9983034,0.0006529969,0.00042825728,0.0002761197,0.00026975092,0.00006939713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010853347,0.00031477568,0.0003635303,0.0010891716,0.00018719459,0.0004289874,0.00019627431,0.00033309296,0.0008977186],"category_scores_gemma":[0.0025469724,0.00021424882,0.00020188598,0.0006916852,0.00034224466,0.0003656768,0.00063298724,0.00021415549,0.00031954737],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016170938,0.000072904426,0.72293097,0.00024273404,0.0004021075,0.0005712495,0.0032006218,0.0017667053,0.19466865,0.0006898034,0.00038711957,0.073450014],"study_design_scores_gemma":[0.000004706569,0.0001135516,0.9920219,0.0000074034847,0.000041516225,0.00045929014,0.00020127687,0.0008917308,0.0054800245,0.00040143714,0.00036680995,0.000010369885],"about_ca_topic_score_codex":0.0015872297,"about_ca_topic_score_gemma":0.0027242287,"teacher_disagreement_score":0.0015872297,"about_ca_system_score_codex":0.00013605035,"about_ca_system_score_gemma":0.0001685587,"threshold_uncertainty_score":0.0057399273},"labels":[],"label_agreement":null},{"id":"W4323830526","doi":"10.1101/2023.03.07.531625","title":"Effect of number of diffusion encoding directions in Neonatal Diffusion Tensor Imaging using Tract-Based Spatial Statistical analysis","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Turun Yliopistollinen Keskussairaala; Alfred Kordelinin Säätiö; Varsinais-Suomen Sairaanhoitopiiri; Emil Aaltosen Säätiö; Jane ja Aatos Erkon Säätiö","keywords":"Diffusion MRI; Weighting; Scalar (mathematics); Fractional anisotropy; Mathematics; Statistics; Physics; Medicine; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.026794206629695828,"score_gpt":0.324801201422658,"score_spread":0.29800699479296217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323830526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8807251,0.0021635066,0.11491642,0.0003257115,0.00018319195,0.00007912118,0.00035822083,0.000729357,0.00051943574],"genre_scores_gemma":[0.9280751,0.00055495446,0.0701471,0.00007183312,0.000054013974,0.00009633514,0.00029508112,0.00042773498,0.00027793765],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9935314,0.0043624896,0.00059191306,0.0007067072,0.00067471457,0.00013269254],"domain_scores_gemma":[0.9257095,0.05867296,0.0064663338,0.004733644,0.0032551314,0.0011624664],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.012563979,0.0007924881,0.0009194714,0.00081902393,0.00039671262,0.0011253753,0.0004948711,0.0005996124,0.0010672057],"category_scores_gemma":[0.07322016,0.0003502282,0.0008994824,0.0007958062,0.0007709453,0.0010364841,0.0007690548,0.00091659225,0.00019883343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.031907514,0.0011002289,0.21524948,0.0012978325,0.0029144736,0.0016853499,0.0009794382,0.15276054,0.3137682,0.0023050946,0.0022052536,0.27382666],"study_design_scores_gemma":[0.0003555871,0.008895351,0.23830995,0.00040258057,0.0025983558,0.0019688176,0.0003445131,0.5633014,0.17574441,0.004376765,0.0033905145,0.00031179452],"about_ca_topic_score_codex":0.0021306411,"about_ca_topic_score_gemma":0.0019588256,"teacher_disagreement_score":0.987436,"about_ca_system_score_codex":0.0005172774,"about_ca_system_score_gemma":0.0008074147,"threshold_uncertainty_score":0.06644541},"labels":[],"label_agreement":null},{"id":"W4323832879","doi":"10.3233/jad-220476","title":"Localized White Matter Tract Integrity Measured by Diffusion Tensor Imaging Is Altered in People with Mild Cognitive Impairment and Associated with Dual-Task and Single-Task Gait Speed","year":2023,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkwood Institute; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Cognitive impairment; Task (project management); Dual (grammatical number); Gait; Physical medicine and rehabilitation; Cognition; Tractography; Psychology; Diffusion; Neuroscience; Medicine; Cognitive psychology; Magnetic resonance imaging; Physics; Engineering; Radiology; Art","score_opus":0.04157488697593542,"score_gpt":0.3099691442676982,"score_spread":0.2683942572917628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323832879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995815,0.00010833943,0.000065078,0.000013218851,0.0000014702508,0.000004473046,0.0000895415,0.000004113193,0.00013225048],"genre_scores_gemma":[0.99960357,0.00005077695,0.00013985591,0.000007589522,0.0000033510678,0.0000038477306,0.00011700287,0.0000011865195,0.00007279679],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999856,0.000014344642,0.000027052043,0.000046347704,0.000033759632,0.000022471464],"domain_scores_gemma":[0.9993179,0.000049367398,0.00047385631,0.000038487946,0.00006131691,0.00005898336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028077097,0.00037659533,0.00038762632,0.0012005331,0.0003497449,0.00044439858,0.00018144664,0.0003345062,0.0009603533],"category_scores_gemma":[0.0012558228,0.00017949134,0.0002336804,0.00064659666,0.0003555764,0.00029615356,0.00031041956,0.00022333735,0.00015040755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003463028,0.000051011415,0.98800755,0.000038619186,0.00015555578,0.00040671305,0.00029933333,0.00012875322,0.0054127807,0.000037298403,0.000092984796,0.005023191],"study_design_scores_gemma":[0.0000021637038,0.00004284197,0.99929714,0.0000024229814,0.000012959153,0.00035872802,0.000047644768,0.000071284594,0.00010948253,0.000031942276,0.000021835802,0.0000016104327],"about_ca_topic_score_codex":0.0055035716,"about_ca_topic_score_gemma":0.00776292,"teacher_disagreement_score":0.0055035716,"about_ca_system_score_codex":0.0002544704,"about_ca_system_score_gemma":0.00016954665,"threshold_uncertainty_score":0.010943055},"labels":[],"label_agreement":null},{"id":"W4323856839","doi":"10.3389/fnagi.2023.1065245","title":"White matter and gray matter changes related to cognition in community populations","year":2023,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences","keywords":"Cognition; White matter; Neurocognitive; Fractional anisotropy; Psychology; Verbal fluency test; Effects of sleep deprivation on cognitive performance; Montreal Cognitive Assessment; Memory span; Diffusion MRI; Audiology; Population; Neuropsychology; Working memory; Cognitive test; Neuroscience; Medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.0700859625679672,"score_gpt":0.3546782653068439,"score_spread":0.2845923027388767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323856839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994942,0.0001580046,0.00005701727,0.000014938554,0.0000026698096,0.000005415305,0.00008694394,0.0000022658533,0.00017866078],"genre_scores_gemma":[0.99962974,0.000070517686,0.000057567373,0.000009653862,0.000006792186,0.000004259531,0.00012491117,9.950136e-7,0.00009551148],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970764,0.00006180931,0.000026347638,0.00009636306,0.00006370685,0.00004407634],"domain_scores_gemma":[0.99935085,0.0000800486,0.0002730074,0.00006482978,0.00012471397,0.00010653424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047375518,0.00037842212,0.00031566163,0.0009539729,0.0004989697,0.00043771375,0.00026685974,0.00036802716,0.0023029153],"category_scores_gemma":[0.0016951722,0.00017037721,0.0002560008,0.0009093561,0.00044446808,0.0003666591,0.00036819087,0.0002887204,0.0001852579],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008448187,0.00004761814,0.99679935,0.000019837513,0.000093777075,0.00011642675,0.00011587556,0.000029414705,0.0005523358,0.000013224467,0.00005097535,0.0020767709],"study_design_scores_gemma":[0.0000017810526,0.000044780892,0.99959964,0.0000024626013,0.000010597553,0.00015675418,0.00007646899,0.000029744628,0.000033365883,0.000017527787,0.000025922382,9.3523306e-7],"about_ca_topic_score_codex":0.00642827,"about_ca_topic_score_gemma":0.009832516,"teacher_disagreement_score":0.00642827,"about_ca_system_score_codex":0.00018056144,"about_ca_system_score_gemma":0.0002532568,"threshold_uncertainty_score":0.012781739},"labels":[],"label_agreement":null},{"id":"W4323863580","doi":"10.1093/braincomms/fcad061","title":"Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Western University; Sunnybrook Health Science Centre; Toronto Western Hospital; Université Laval","funders":"NIHR Cambridge Biomedical Research Centre; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; UK Dementia Research Institute; Ministero della Salute; Brain Research UK; Deutsche Forschungsgemeinschaft; Wolfson Foundation; Wellcome Trust; Alzheimer's Society; Agence Nationale de la Recherche; University College London; National Institute for Health and Care Research; EU Joint Programme – Neurodegenerative Disease Research; Nvidia","keywords":"Frontotemporal dementia; Grey matter; White matter; Diffusion MRI; C9orf72; Dementia; Medicine; Psychology; Oncology; Internal medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.1365431826319456,"score_gpt":0.42514686797683204,"score_spread":0.28860368534488645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323863580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995926,0.00004208732,0.000025070014,0.000017602073,0.0000027618428,0.0000044032427,0.00016978198,0.0000020463197,0.00014371717],"genre_scores_gemma":[0.9994056,0.000025857827,0.000043972643,0.000012369365,0.0000053452163,0.0000047566828,0.00038982616,0.0000016913762,0.00011059424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996908,0.00006358906,0.000031430092,0.00009275477,0.00006900868,0.000052451698],"domain_scores_gemma":[0.99929154,0.000078611105,0.00023603615,0.0000747513,0.00010511637,0.00021407285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006983013,0.0005179659,0.00045697557,0.0008737127,0.00090129045,0.0007833424,0.0004962308,0.00061919214,0.001212924],"category_scores_gemma":[0.0019889476,0.0003355588,0.0005434515,0.00058640755,0.0003047777,0.00044708632,0.00062987354,0.00067160005,0.00026674147],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004531232,0.00006614168,0.99738675,0.000004313119,0.000088875706,0.00025938914,0.00012756075,0.000033382847,0.00057282,0.000014301781,0.00014243531,0.00085087353],"study_design_scores_gemma":[0.000009140313,0.000060622333,0.9992619,0.00000229602,0.000031209805,0.00027755127,0.00009659911,0.00013650474,0.000053385364,0.000015241215,0.000052638465,0.0000028732757],"about_ca_topic_score_codex":0.012105841,"about_ca_topic_score_gemma":0.013163592,"teacher_disagreement_score":0.012105841,"about_ca_system_score_codex":0.00027884304,"about_ca_system_score_gemma":0.00023098501,"threshold_uncertainty_score":0.0240708},"labels":[],"label_agreement":null},{"id":"W4324355161","doi":"10.1101/2023.03.14.532658","title":"In search of a unifying theory of white matter aging: improving the understanding of tract-wise degeneration using multi-parametric signatures of morphometry and microstructure","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Degeneration (medical); Parametric statistics; Human Connectome Project; Thermal diffusivity; Psychology; Biology; Neuroscience; Pathology; Medicine; Magnetic resonance imaging; Mathematics; Physics; Statistics; Functional connectivity; Radiology","score_opus":0.09189810883467651,"score_gpt":0.31844812878931894,"score_spread":0.2265500199546424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324355161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.082255654,0.006065692,0.9031256,0.0052221757,0.00016682188,0.000042565,0.00029265785,0.0005066181,0.0023223085],"genre_scores_gemma":[0.72762364,0.006525184,0.26212642,0.0009004083,0.00035878844,0.0001329566,0.0003616097,0.00017623651,0.0017947311],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9993617,0.00023288115,0.000044410557,0.00023982309,0.00008852856,0.000032691434],"domain_scores_gemma":[0.99706584,0.0009641849,0.00059656444,0.0008949678,0.00035381643,0.0001245884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006525231,0.0009800073,0.0012872037,0.0023372676,0.0005846159,0.0030851627,0.0010196107,0.001299813,0.0010837833],"category_scores_gemma":[0.0064536524,0.00038610795,0.0011018099,0.0013544178,0.0033451256,0.005790567,0.0018460248,0.0019478665,0.00034374621],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021917121,0.00015220005,0.08881797,0.00119949,0.0012668167,0.0006255748,0.002400746,0.11790915,0.06985923,0.46689093,0.0053744214,0.2452843],"study_design_scores_gemma":[0.000013644795,0.0001950463,0.03066443,0.00018372422,0.00013761227,0.00043741177,0.00042218788,0.2586653,0.0070516537,0.6955268,0.0066235377,0.00007871967],"about_ca_topic_score_codex":0.0023396192,"about_ca_topic_score_gemma":0.002261255,"teacher_disagreement_score":0.006525231,"about_ca_system_score_codex":0.0009624922,"about_ca_system_score_gemma":0.001669197,"threshold_uncertainty_score":0.034509122},"labels":[],"label_agreement":null},{"id":"W4324378556","doi":"10.1117/12.2649029","title":"Exploring the Allen mouse connectivity experiments with new neuroinformatic tools for neurophotonics, diffusion MRI and tractography applications","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Université de Bordeaux; Agence Nationale de la Recherche","keywords":"Python (programming language); Computer science; Visualization; Software; Diffusion MRI; Tractography; Brain atlas; Artificial intelligence; Atlas (anatomy); Data visualization; Computer graphics (images); Programming language; Biology","score_opus":0.30295458175807344,"score_gpt":0.3719235383472306,"score_spread":0.06896895658915714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324378556","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.094211474,0.0003441923,0.82986754,0.0008881226,0.00021409246,0.0004260048,0.013376174,0.052110393,0.008562038],"genre_scores_gemma":[0.11276725,0.0006112747,0.8604156,0.00034878662,0.00005181519,0.0018385777,0.0068787597,0.012350355,0.0047375932],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934965,0.00013032595,0.000058949867,0.0001563853,0.00024393947,0.000060665538],"domain_scores_gemma":[0.9977533,0.0009133223,0.00028517746,0.00056190934,0.00024413955,0.00024209461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023463368,0.0009504863,0.00063348876,0.0022486825,0.0006521365,0.0011298545,0.0017192193,0.0008365489,0.013648983],"category_scores_gemma":[0.0038371084,0.00071784743,0.0010325905,0.00091219944,0.000866748,0.0017537627,0.0021245293,0.0018410743,0.0021706542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009491505,0.0006228923,0.01224612,0.0018711023,0.00044827873,0.002407915,0.0028978304,0.021592211,0.63000447,0.06923036,0.061176434,0.19655326],"study_design_scores_gemma":[0.00037646387,0.0011157672,0.038326334,0.00078439846,0.0004468083,0.0031081813,0.0007472975,0.20879948,0.39043543,0.09838621,0.25691926,0.0005543482],"about_ca_topic_score_codex":0.0018966725,"about_ca_topic_score_gemma":0.0043604854,"teacher_disagreement_score":0.013648983,"about_ca_system_score_codex":0.000423788,"about_ca_system_score_gemma":0.0008138217,"threshold_uncertainty_score":0.045660436},"labels":[],"label_agreement":null},{"id":"W4353016846","doi":"10.1002/hbm.26238","title":"Sex differences, asymmetry, and age‐related white matter development in infants and 5‐year‐olds as assessed with <scp>tract‐based</scp> spatial statistics","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Suomen Lääketieteen Säätiö; Suomen Kulttuurirahasto; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Juho Vainion Säätiö; Suomalainen Lääkäriseura Duodecim; Suomen Aivosäätiö; Alfred Kordelinin Säätiö; National Alliance for Research on Schizophrenia and Depression","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Lateralization of brain function; Psychology; Gestational age; Developmental psychology; Cognition; Brain asymmetry; Audiology; Physiology; Medicine; Neuroscience; Pregnancy; Biology; Magnetic resonance imaging","score_opus":0.050480306237762694,"score_gpt":0.32137547676796113,"score_spread":0.27089517053019846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353016846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99951124,0.00009143418,0.00005312967,0.0000030492185,0.0000012756209,0.0000019123588,0.00020684947,0.0000029798223,0.00012807504],"genre_scores_gemma":[0.99935,0.00006797318,0.000113322305,0.0000033915876,0.0000021955052,0.0000064115793,0.00031270707,0.0000021980402,0.00014194322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997557,0.000035608475,0.000044938737,0.000058085432,0.0000558681,0.000049764665],"domain_scores_gemma":[0.9992482,0.00015642612,0.0003603791,0.00007559354,0.00007755604,0.00008182315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054372457,0.00019690544,0.00025778808,0.0011796358,0.00014118041,0.0003275793,0.00015037587,0.00022461438,0.0009941771],"category_scores_gemma":[0.0017754829,0.00012597052,0.00030877726,0.00040725348,0.00020631838,0.00020158745,0.00028830586,0.00013946323,0.00017787347],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027967227,0.000017114366,0.9896628,0.000014713753,0.000057343303,0.00037509465,0.00053549453,0.00006402992,0.0032553982,0.00005307416,0.00007069846,0.0056145387],"study_design_scores_gemma":[4.695449e-7,0.00003926193,0.99943453,0.0000016412924,0.000004846077,0.00021029079,0.00007513905,0.000042422398,0.00012946092,0.000007631107,0.00005286435,0.0000013777376],"about_ca_topic_score_codex":0.0031843176,"about_ca_topic_score_gemma":0.0029890921,"teacher_disagreement_score":0.0031843176,"about_ca_system_score_codex":0.00012677777,"about_ca_system_score_gemma":0.000115219336,"threshold_uncertainty_score":0.006331563},"labels":[],"label_agreement":null},{"id":"W4360604116","doi":"10.1016/j.mri.2023.03.014","title":"Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Voxel; Diffusion MRI; Orientation (vector space); Computer science; SIGNAL (programming language); Preprocessor; Weighting; Algorithm; Artificial intelligence; Mathematics; Physics; Magnetic resonance imaging; Geometry","score_opus":0.02409103062778193,"score_gpt":0.2986922381842282,"score_spread":0.27460120755644624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360604116","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042623417,0.00015802833,0.9950606,0.000053150725,0.000011188442,0.000012555809,0.000024960229,0.00017726423,0.00023985634],"genre_scores_gemma":[0.08543102,0.00041665172,0.9118056,0.000043621087,0.00002370882,0.000058196492,0.00018242658,0.00021372703,0.0018251169],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963415,0.00011111393,0.000021562839,0.000038407856,0.00016752856,0.000027218759],"domain_scores_gemma":[0.99918014,0.00040916455,0.00007275868,0.00013231758,0.00016580144,0.000039733943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090513384,0.00074251957,0.00074564485,0.0005568197,0.00039399357,0.000982474,0.0009436867,0.0011099471,0.002005825],"category_scores_gemma":[0.004356703,0.00055281154,0.0004921033,0.00086828374,0.0005394485,0.001346579,0.0012365998,0.0012615817,0.0009952697],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050719717,0.0001151478,0.00093806785,0.00048554898,0.00014228188,0.00024230746,0.00029620793,0.38633883,0.091249004,0.05224459,0.005184689,0.46225622],"study_design_scores_gemma":[0.000009655034,0.000025694582,0.000116578565,0.000010234849,0.000011024376,0.00010733587,0.000012586967,0.98064685,0.012005645,0.005310548,0.0017325396,0.000011400847],"about_ca_topic_score_codex":0.0030632317,"about_ca_topic_score_gemma":0.0041975416,"teacher_disagreement_score":0.0030632317,"about_ca_system_score_codex":0.00042544736,"about_ca_system_score_gemma":0.0012074204,"threshold_uncertainty_score":0.006710112},"labels":[],"label_agreement":null},{"id":"W4360839182","doi":"10.1016/j.nicl.2023.103385","title":"Alzheimer’s and vascular disease classification using regional texture biomarkers in FLAIR MRI","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Canada Research Chairs; St. Michael's Hospital","funders":"Alzheimer Society; Alzheimer's Society; Government of Ontario; Consortium canadien en neurodégénérescence associée au vieillissement; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Fluid-attenuated inversion recovery; White matter; Medicine; Biomarker; Vascular dementia; Dementia; Diffusion MRI; Hyperintensity; Disease; Pathology; Imaging biomarker; Magnetic resonance imaging; Radiology; Internal medicine; Oncology; Biology","score_opus":0.39486666729096026,"score_gpt":0.48821036076686747,"score_spread":0.09334369347590721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360839182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9820047,0.0009985982,0.015237183,0.00008460469,0.000027196378,0.00006512168,0.00038937345,0.00013747085,0.0010558183],"genre_scores_gemma":[0.99028134,0.00017310138,0.00893366,0.000021663616,0.00002287933,0.00002870532,0.0003260132,0.000010306092,0.00020228357],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994973,0.00012980755,0.00007273098,0.0001198859,0.000097651515,0.000082627084],"domain_scores_gemma":[0.99895656,0.0002782158,0.00035421888,0.00011094208,0.00021477987,0.00008517857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017554339,0.0005951639,0.0005888065,0.003623596,0.00022126654,0.0012842085,0.00026501445,0.00056909857,0.0006358766],"category_scores_gemma":[0.0033937031,0.00014839563,0.00062848325,0.0008579456,0.00030382266,0.0008092946,0.00048302786,0.00029834788,0.00028041514],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027184938,0.0002005696,0.74972856,0.00019379714,0.00064267596,0.000443398,0.0004072707,0.0048990226,0.040226825,0.0004952237,0.0010710832,0.1989731],"study_design_scores_gemma":[0.0000774186,0.00078170333,0.92063046,0.00009180648,0.0002692161,0.0012237539,0.0005514266,0.06391417,0.009519645,0.0018092507,0.0010608204,0.00007033129],"about_ca_topic_score_codex":0.0022309632,"about_ca_topic_score_gemma":0.0029157293,"teacher_disagreement_score":0.003623596,"about_ca_system_score_codex":0.0002609842,"about_ca_system_score_gemma":0.00027477488,"threshold_uncertainty_score":0.009283721},"labels":[],"label_agreement":null},{"id":"W4361007742","doi":"10.1002/uog.26208","title":"Diffusion tensor imaging of fetal spinal cord: feasibility and gestational‐age‐related changes","year":2023,"lang":"en","type":"article","venue":"Ultrasound in Obstetrics and Gynecology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Diffusion MRI; Effective diffusion coefficient; Spinal cord; Nuclear medicine; White matter; Magnetic resonance imaging; Gestational age; Fractional anisotropy; Sagittal plane; Radiology; Pregnancy","score_opus":0.06200324316163612,"score_gpt":0.3519602656798965,"score_spread":0.2899570225182604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361007742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946554,0.0026656801,0.0011464205,0.000095436364,0.000016507774,0.000069785456,0.00028428767,0.000010984139,0.0010554945],"genre_scores_gemma":[0.9978466,0.00061733945,0.0011644854,0.000011043462,0.000018510922,0.00004206308,0.00013320913,0.000004874126,0.00016186932],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991048,0.00043736215,0.000114553804,0.00013365303,0.00014642939,0.00006325357],"domain_scores_gemma":[0.99693143,0.0010767422,0.0014177312,0.00014703762,0.00029604425,0.00013103477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028253696,0.00040691468,0.00028554272,0.00097099313,0.00016286588,0.00050219405,0.00028075246,0.0003868164,0.0008095538],"category_scores_gemma":[0.010164859,0.00019982133,0.0002203543,0.0005893442,0.00044139766,0.00058005546,0.0003042096,0.0003039223,0.00012207223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003812636,0.00011158595,0.9564546,0.00020391033,0.000112208196,0.0010449312,0.00024439808,0.00038825427,0.011599795,0.0001647409,0.000121596924,0.02574147],"study_design_scores_gemma":[0.0000547802,0.0012112333,0.9931958,0.000032790427,0.0000730137,0.0017489047,0.000105393316,0.00072779314,0.0022621914,0.00007350163,0.0005007351,0.000013900505],"about_ca_topic_score_codex":0.0020287703,"about_ca_topic_score_gemma":0.0015277002,"teacher_disagreement_score":0.0028253696,"about_ca_system_score_codex":0.0002969452,"about_ca_system_score_gemma":0.00042202967,"threshold_uncertainty_score":0.01494211},"labels":[],"label_agreement":null},{"id":"W4361264359","doi":"10.1016/j.neuroimage.2023.120069","title":"White matter microstructure is associated with the precision of visual working memory","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Health and Medical Research Council; University of Queensland","keywords":"Working memory; Fasciculus; White matter; Inferior longitudinal fasciculus; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Computer science; Neuroscience; Artificial intelligence; Tractography; Cognition; Medicine; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.038105556396323445,"score_gpt":0.33059862579653004,"score_spread":0.2924930694002066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361264359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99842274,0.00008955488,0.0012728345,0.000014065016,0.0000014230816,0.00000546033,0.00006402854,0.0000116380215,0.00011827864],"genre_scores_gemma":[0.9994281,0.00002615601,0.00042499125,0.0000034733216,0.0000021142698,0.000003037223,0.000045773115,0.0000032720977,0.00006299334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999833,0.000027824153,0.000021755943,0.000067629226,0.000030458386,0.000019224233],"domain_scores_gemma":[0.9982035,0.00043810048,0.0008943294,0.00026537466,0.00011914832,0.00007955214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005250793,0.0003118068,0.0002193452,0.000498423,0.00014189356,0.00043078596,0.0001475876,0.000345957,0.0007719594],"category_scores_gemma":[0.0038024993,0.00024154903,0.00012460203,0.00026423708,0.00046240274,0.00036430967,0.00029997303,0.00027587527,0.00010200889],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018906138,0.00016597891,0.658752,0.00013388916,0.00042905417,0.00027706995,0.0012632221,0.0027429627,0.30303,0.00046885046,0.0001742569,0.030672032],"study_design_scores_gemma":[0.0000067478545,0.00009825306,0.9927578,0.000003983228,0.000023428935,0.00022269005,0.000045544784,0.001325822,0.0051638866,0.0003016406,0.0000428375,0.0000073147025],"about_ca_topic_score_codex":0.0020218175,"about_ca_topic_score_gemma":0.0027837192,"teacher_disagreement_score":0.0020218175,"about_ca_system_score_codex":0.00016208645,"about_ca_system_score_gemma":0.00013130622,"threshold_uncertainty_score":0.0040200353},"labels":[],"label_agreement":null},{"id":"W4362506763","doi":"10.7554/elife.83727","title":"Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain","year":2023,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Centre For Medical Engineering, King’s College London; NIHR Sheffield Biomedical Research Centre; European Research Council; Engineering and Physical Sciences Research Council; Menzies Centre for Australian Studies, King's College London, University of London; Medical Research Council Canada; Medical Research Council Centre for Neurodevelopmental Disorders; European Commission; National Institute for Health and Care Research; King's College London; King's College Hospital NHS Foundation Trust; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Subplate; Neuroscience; Thalamus; White matter; Biology; Human brain; Tractography; Cortex (anatomy); Cerebral cortex; Biological neural network; Connectome; Diffusion MRI; Anatomy; Magnetic resonance imaging; Medicine; Functional connectivity","score_opus":0.11742736846466226,"score_gpt":0.40423544583298354,"score_spread":0.28680807736832126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362506763","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98652554,0.00086680456,0.010828375,0.000066828965,0.0000029109383,0.000010989684,0.00029801682,0.000039594703,0.0013609071],"genre_scores_gemma":[0.99015546,0.0009873826,0.007932101,0.000020698822,0.000001964861,0.000017643506,0.00023923935,0.000028788738,0.00061663846],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994993,0.000008796491,0.000003332288,0.000013823943,0.00001581304,0.000008250773],"domain_scores_gemma":[0.99987805,0.00003079428,0.000041221367,0.000012462439,0.000025369533,0.000012065931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020853525,0.000088447196,0.00008557591,0.00043686692,0.00013466994,0.00031484052,0.000084431704,0.0001274703,0.00071783544],"category_scores_gemma":[0.0006859158,0.00014121637,0.00005842806,0.00017641934,0.00021461767,0.00019401511,0.0001660038,0.00017189658,0.00011069527],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028706095,0.000017379614,0.065583296,0.000112691734,0.000030480656,0.00073178764,0.0013203305,0.0018294996,0.8692031,0.002119585,0.00035343465,0.058411404],"study_design_scores_gemma":[0.000011042478,0.00019331965,0.7588413,0.00006681095,0.000049182752,0.0054368954,0.0009393329,0.0052368375,0.220612,0.0016479124,0.0069285515,0.000036797137],"about_ca_topic_score_codex":0.0044690203,"about_ca_topic_score_gemma":0.007873257,"teacher_disagreement_score":0.0044690203,"about_ca_system_score_codex":0.00021887264,"about_ca_system_score_gemma":0.00025971406,"threshold_uncertainty_score":0.00888598},"labels":[],"label_agreement":null},{"id":"W4362603986","doi":"10.1117/12.2653884","title":"Mapping the impact of approximate gradient nonlinearity fields correction on tractography","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Tractography; Diffusion MRI; Connectomics; Nonlinear system; Population; Voxel; Computer science; Statistical physics; Connectome; Artificial intelligence; Physics; Functional connectivity","score_opus":0.1186722705274807,"score_gpt":0.3889556291316619,"score_spread":0.2702833586041812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362603986","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24834101,0.000967088,0.7451867,0.0004759945,0.00019095595,0.00014019095,0.0007730589,0.0022628591,0.0016622167],"genre_scores_gemma":[0.7330152,0.00042034005,0.26232848,0.00015597246,0.00004408532,0.00013740022,0.0010918096,0.001218055,0.0015886797],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981552,0.0008358031,0.00013243382,0.00039740838,0.00038587648,0.000093233146],"domain_scores_gemma":[0.9911142,0.0051163062,0.00087147986,0.0017223752,0.0010585976,0.00011701321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004562799,0.00074413035,0.0005589597,0.0007312504,0.000528692,0.0013780391,0.0007042449,0.000582265,0.0022275057],"category_scores_gemma":[0.03248346,0.00030239482,0.00064516795,0.0009388632,0.00080739777,0.0012757836,0.00082002464,0.0007880286,0.0008569815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015920709,0.00012643496,0.08935648,0.00085918966,0.00084800477,0.00086527376,0.0013968494,0.19281104,0.11544322,0.018252715,0.0055760215,0.5728727],"study_design_scores_gemma":[0.00010388252,0.00094507536,0.16690549,0.0002360292,0.0004423999,0.0034139121,0.00052044645,0.66285527,0.114303775,0.029239722,0.020817684,0.00021627347],"about_ca_topic_score_codex":0.0048649996,"about_ca_topic_score_gemma":0.00797892,"teacher_disagreement_score":0.0048649996,"about_ca_system_score_codex":0.0005494619,"about_ca_system_score_gemma":0.0015082612,"threshold_uncertainty_score":0.024130642},"labels":[],"label_agreement":null},{"id":"W4362604797","doi":"10.1117/12.2654398","title":"Deep constrained spherical deconvolution for robust harmonization","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Computer science; Deconvolution; Artificial intelligence; Diffusion MRI; Regularization (linguistics); Scanner; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Algorithm","score_opus":0.11887214630771932,"score_gpt":0.36715950605732395,"score_spread":0.24828735974960464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362604797","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008217229,0.00013042048,0.989641,0.00008727954,0.000031235784,0.00003417036,0.00010898681,0.00070624123,0.0010434792],"genre_scores_gemma":[0.3558203,0.0004287815,0.63599294,0.00025373805,0.00005718444,0.00018530036,0.0013167129,0.00057193654,0.00537308],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993801,0.00014849096,0.00003722704,0.00014242738,0.00022507846,0.00006670982],"domain_scores_gemma":[0.9994135,0.00014582624,0.000076469696,0.00017255868,0.00016280073,0.000028954732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012650026,0.0010697647,0.00080646743,0.0006954717,0.0003993612,0.00083282555,0.0011008038,0.00092436356,0.0030272417],"category_scores_gemma":[0.0033984743,0.00032424228,0.0010255767,0.0011962411,0.00068563345,0.0012924671,0.0019927174,0.0013103168,0.0012619182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004333116,0.00015672932,0.0013409938,0.00021649881,0.0002498001,0.00016056468,0.00019985113,0.38162357,0.042026207,0.026760668,0.008582994,0.5382488],"study_design_scores_gemma":[0.000010635949,0.00003585818,0.00030234765,0.000008555808,0.0000183021,0.00007360189,0.000028754717,0.9764721,0.014124571,0.005976315,0.0029280584,0.000020911004],"about_ca_topic_score_codex":0.0045976895,"about_ca_topic_score_gemma":0.0059143673,"teacher_disagreement_score":0.0045976895,"about_ca_system_score_codex":0.00044555534,"about_ca_system_score_gemma":0.001852496,"threshold_uncertainty_score":0.010127068},"labels":[],"label_agreement":null},{"id":"W4362663285","doi":"10.1101/2023.04.03.535465","title":"Implementation considerations for deep learning with diffusion MRI streamline tractography","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Tractography; Diffusion MRI; Deep learning; Computer science; Artificial intelligence; Diffusion; Data science; Magnetic resonance imaging; Medicine; Radiology; Physics","score_opus":0.051166974466269,"score_gpt":0.32417606579841096,"score_spread":0.27300909133214196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362663285","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065988945,0.00054895505,0.9758406,0.002570242,0.00024032897,0.00009293649,0.00028219004,0.008819831,0.005006023],"genre_scores_gemma":[0.14725174,0.00087021885,0.8378449,0.0011355738,0.00015336329,0.0004370605,0.0010090413,0.002024887,0.009273124],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998626,0.00044765676,0.00012704515,0.0002075725,0.00044312293,0.00014871196],"domain_scores_gemma":[0.9966683,0.0013016997,0.00014098219,0.00084305985,0.00084065774,0.00020524819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002976071,0.001219759,0.00064800907,0.0005492928,0.00066204404,0.0024418843,0.0033550812,0.0016873435,0.016252825],"category_scores_gemma":[0.013952673,0.00081504905,0.00075388286,0.0008640692,0.00083355827,0.0044313874,0.0021139435,0.00441464,0.0076475963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087900885,0.00028517758,0.0029274682,0.00068073074,0.00023376901,0.00051023514,0.0003635132,0.30430844,0.020621423,0.16724877,0.06553059,0.43641084],"study_design_scores_gemma":[0.00012295943,0.00009156988,0.0002707597,0.00012896967,0.000036526668,0.00017318806,0.000057938083,0.87982494,0.015538386,0.06492901,0.038784843,0.000040937077],"about_ca_topic_score_codex":0.008451147,"about_ca_topic_score_gemma":0.011100788,"teacher_disagreement_score":0.016252825,"about_ca_system_score_codex":0.001705945,"about_ca_system_score_gemma":0.0021928884,"threshold_uncertainty_score":0.05437106},"labels":[],"label_agreement":null},{"id":"W4362696909","doi":"10.1016/j.mri.2023.03.023","title":"Neural network algorithms predict new diffusion MRI data for multi-compartmental analysis of brain microstructure in a clinical setting","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia; Hotchkiss Brain Institute; Ontario Brain Institute; St. Michael's Hospital; University of Calgary","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Multiple Sclerosis Society of Canada; McDonnell Center for Systems Neuroscience; NIH Blueprint for Neuroscience Research; University of Calgary; Biogen Idec; Biogen; Government of Alberta; Fondation Brain Canada; Roche","keywords":"Human Connectome Project; Diffusion MRI; Convolutional neural network; Computer science; Diffusion imaging; Pattern recognition (psychology); Artificial intelligence; Artificial neural network; Magnetic resonance imaging; Medicine; Neuroscience; Functional connectivity; Radiology; Psychology","score_opus":0.09936934055020735,"score_gpt":0.42619241693129273,"score_spread":0.3268230763810854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362696909","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3564349,0.0020961775,0.6367839,0.0013459267,0.0001885147,0.0001629602,0.0004982461,0.00091162015,0.0015777128],"genre_scores_gemma":[0.88522416,0.000729652,0.11157545,0.00018958437,0.00009366517,0.00013574256,0.00050638174,0.00010141964,0.0014438811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974734,0.000075442644,0.00002529529,0.000078687626,0.000047549955,0.000025737827],"domain_scores_gemma":[0.9971738,0.0020707287,0.00019494611,0.00010516344,0.00037797994,0.00007732105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017360366,0.0007841312,0.0005854314,0.0010671146,0.00029229015,0.0012643466,0.00060137693,0.001364069,0.0013815074],"category_scores_gemma":[0.008844931,0.00034168002,0.0004963531,0.0005268378,0.00031362663,0.0008942181,0.00049,0.0013940193,0.0004454521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001118325,0.0005037793,0.034450203,0.00017903611,0.00030684567,0.00042847154,0.000109368186,0.64841485,0.012630653,0.0025570947,0.0028891508,0.29641214],"study_design_scores_gemma":[0.000009633754,0.000033293538,0.0010550556,0.000008037167,0.000013529037,0.000044921744,0.0000067362794,0.99698347,0.0008701418,0.000867926,0.00010125675,0.0000059881036],"about_ca_topic_score_codex":0.005692362,"about_ca_topic_score_gemma":0.007883615,"teacher_disagreement_score":0.005692362,"about_ca_system_score_codex":0.00071033015,"about_ca_system_score_gemma":0.0007454779,"threshold_uncertainty_score":0.011318445},"labels":[],"label_agreement":null},{"id":"W4362704266","doi":"10.1038/s41598-023-33055-9","title":"Three-round learning strategy based on 3D deep convolutional GANs for Alzheimer’s disease staging","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; National Natural Science Foundation of China; Eisai; Genentech; IXICO; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Overfitting; Artificial intelligence; Computer science; Interpretability; Deep learning; Convolutional neural network; Machine learning; Task (project management); Discriminator; Transfer of learning; Feature (linguistics); Generative model; Generative adversarial network; Generative grammar; Pattern recognition (psychology); Artificial neural network","score_opus":0.12479615419464202,"score_gpt":0.3798533453630848,"score_spread":0.2550571911684428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362704266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04842658,0.0005555188,0.9453917,0.0003810571,0.000090543785,0.00009348605,0.0001220172,0.002223476,0.0027155639],"genre_scores_gemma":[0.867947,0.00027970917,0.12615706,0.00048563242,0.000060730374,0.00019409232,0.0003939032,0.00016517045,0.004316609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971837,0.00006790084,0.000014156279,0.000088969195,0.00006008577,0.000050512248],"domain_scores_gemma":[0.9996971,0.00011100314,0.000034722874,0.000052835792,0.00006821412,0.000036194262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007312559,0.0012004881,0.00086316443,0.0004142816,0.00030456335,0.00050252327,0.001622386,0.00091342966,0.001547539],"category_scores_gemma":[0.0011579522,0.0005684987,0.00095922814,0.00023724498,0.0006330551,0.0006568888,0.0013459956,0.0014339492,0.00043839688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019181977,0.00007685677,0.0020894753,0.000048644943,0.00009375236,0.00017739345,0.000085053536,0.88360095,0.008964441,0.0058393064,0.0026390455,0.09619326],"study_design_scores_gemma":[0.0000034268965,0.000013483839,0.000064185995,0.0000021217213,0.000005603431,0.000014896682,0.0000018370725,0.9982346,0.0006382909,0.00087792834,0.00014024979,0.0000033851572],"about_ca_topic_score_codex":0.006450501,"about_ca_topic_score_gemma":0.0075178817,"teacher_disagreement_score":0.006450501,"about_ca_system_score_codex":0.0007171883,"about_ca_system_score_gemma":0.0008739533,"threshold_uncertainty_score":0.012825906},"labels":[],"label_agreement":null},{"id":"W4363645571","doi":"10.1002/mrm.29666","title":"Single‐shot spiral diffusion‐weighted imaging at 7T using expanded encoding with compressed sensing","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Regularization (linguistics); Computer science; Diffusion MRI; Encoding (memory); Image resolution; Compressed sensing; Spiral (railway); Algorithm; Image quality; Iterative reconstruction; Wavelet; Conjugate gradient method; Artificial intelligence; Computer vision; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Image (mathematics); Mathematical analysis","score_opus":0.10138470792243831,"score_gpt":0.3523189457130428,"score_spread":0.2509342377906045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4363645571","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1326254,0.0006995449,0.8610243,0.00045426516,0.00004761988,0.00012904294,0.00029722063,0.0017776729,0.002944951],"genre_scores_gemma":[0.3325653,0.00069387874,0.66411513,0.0001759192,0.000045934914,0.0001745976,0.000686878,0.0003094135,0.0012330258],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985635,0.000037678023,0.000009101098,0.000019864261,0.000066279026,0.000010734908],"domain_scores_gemma":[0.99970394,0.00010384592,0.000052868614,0.000051322226,0.000057984686,0.000029958894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006931244,0.00057163625,0.0003251524,0.00037862183,0.00014286235,0.0005050325,0.0004910811,0.0005676532,0.0017118272],"category_scores_gemma":[0.0013744936,0.00032745503,0.00036979388,0.0004560978,0.00033590544,0.0007756637,0.00065025635,0.000688116,0.00040232716],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009860784,0.00018491287,0.0023321793,0.0009140326,0.00023798573,0.0010159323,0.00038094717,0.15273413,0.60526705,0.015709488,0.005124787,0.21511261],"study_design_scores_gemma":[0.0001112712,0.000545909,0.0017830646,0.000091199225,0.000107508655,0.0016851099,0.000049864368,0.7938784,0.18697116,0.0063155056,0.008358097,0.000102877246],"about_ca_topic_score_codex":0.0011037352,"about_ca_topic_score_gemma":0.0016057465,"teacher_disagreement_score":0.0017118272,"about_ca_system_score_codex":0.00025486085,"about_ca_system_score_gemma":0.0006515954,"threshold_uncertainty_score":0.005726576},"labels":[],"label_agreement":null},{"id":"W4363676591","doi":"10.1016/j.biopsych.2023.02.360","title":"120. Glymphatic Clearance Function in Schizophrenia Subtypes According to Treatment Response","year":2023,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Glymphatic system; Schizophrenia (object-oriented programming); Neurodegeneration; Neuroscience; Neuroimaging; Medicine; Pathology; Psychology; Cerebrospinal fluid; Psychiatry","score_opus":0.11014765128766592,"score_gpt":0.38029847410212214,"score_spread":0.27015082281445624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4363676591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941275,0.0012453184,0.0002989032,0.00010889163,0.000014331928,0.000015610098,0.0009418984,0.000036486133,0.0032109912],"genre_scores_gemma":[0.997863,0.00017483365,0.00018560042,0.000045700737,0.000006477566,0.000010152712,0.0008407713,0.000012620515,0.0008609555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986386,0.000029822002,0.00001555142,0.000026130556,0.000024647268,0.00003997931],"domain_scores_gemma":[0.9993968,0.00015133558,0.00018928119,0.000051242256,0.00011030771,0.000101017285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004530758,0.00027756323,0.0004722578,0.0006743887,0.00030816146,0.0007569037,0.00031133922,0.0004421553,0.0034139485],"category_scores_gemma":[0.0012438862,0.0001432753,0.0005701888,0.00039861148,0.00024173287,0.000476871,0.00029213357,0.0004995229,0.00070795766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.036587067,0.0003276929,0.74961144,0.0002529116,0.001165082,0.00080217613,0.0005221378,0.0008038923,0.10759034,0.0009019229,0.0017752727,0.09966002],"study_design_scores_gemma":[0.000104566425,0.00069412787,0.9911583,0.000017714681,0.00018220993,0.00067253126,0.00015616858,0.0009534925,0.0048473096,0.00036444192,0.0008314487,0.0000176036],"about_ca_topic_score_codex":0.005274577,"about_ca_topic_score_gemma":0.0032577808,"teacher_disagreement_score":0.005274577,"about_ca_system_score_codex":0.00059788785,"about_ca_system_score_gemma":0.0002452785,"threshold_uncertainty_score":0.011420786},"labels":[],"label_agreement":null},{"id":"W4365142548","doi":"10.1101/2023.04.10.23288366","title":"Cortical microstructural associations with CSF amyloid and pTau","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Amyloid (mycology); Neuroscience; Pathology; Psychology; Medicine","score_opus":0.08353576868100436,"score_gpt":0.36181041664311303,"score_spread":0.27827464796210866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365142548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99899155,0.00015612546,0.00022445923,0.000021259695,0.0000026802657,0.0000033194885,0.00022482258,0.000011184432,0.00036449925],"genre_scores_gemma":[0.9994733,0.000044534405,0.00016583393,0.00000650332,0.000003900368,0.0000025786053,0.00008334567,0.0000030021001,0.00021710247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989593,0.000014489874,0.000010068249,0.000039254028,0.000022792228,0.000017477725],"domain_scores_gemma":[0.9993181,0.00012151698,0.0003449872,0.00006135671,0.00007862369,0.00007539105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021803261,0.0004384567,0.0002321747,0.0009785775,0.00023957537,0.00071430876,0.00016234926,0.000265827,0.0026110613],"category_scores_gemma":[0.0014142112,0.0001938594,0.00013630513,0.0005034932,0.00034554544,0.00027818288,0.00034294592,0.00022466856,0.00029746714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016588089,0.000081371385,0.9310931,0.000100343495,0.00026141104,0.0013357416,0.0007781907,0.00052468485,0.052476786,0.00020218088,0.00036427018,0.011123089],"study_design_scores_gemma":[0.0000056805266,0.000070604234,0.9948775,0.00000465226,0.000026963413,0.0011000978,0.00013259774,0.00034663387,0.0030282738,0.00026455024,0.0001375161,0.0000048391535],"about_ca_topic_score_codex":0.0033454928,"about_ca_topic_score_gemma":0.0024013333,"teacher_disagreement_score":0.0033454928,"about_ca_system_score_codex":0.00017798817,"about_ca_system_score_gemma":0.0001409773,"threshold_uncertainty_score":0.008734882},"labels":[],"label_agreement":null},{"id":"W4366083018","doi":"10.1002/hbm.26310","title":"High‐frequency longitudinal white matter diffusion‐ and myelin‐based <scp>MRI</scp> database: Reliability and variability","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Intraclass correlation; Consistency (knowledge bases); White matter; Reliability (semiconductor); Diffusion MRI; Diffusion; Fiber; Nuclear magnetic resonance; Fiber tract; Effective diffusion coefficient; Data consistency; Psychology; Computer science; Magnetic resonance imaging; Chemistry; Statistics; Physics; Medicine; Mathematics; Database; Artificial intelligence; Radiology; Reproducibility","score_opus":0.061417180567841935,"score_gpt":0.32881093711402615,"score_spread":0.2673937565461842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366083018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86286074,0.0013758359,0.03809631,0.0002602735,0.00006669946,0.0007910608,0.09095419,0.001954225,0.003640813],"genre_scores_gemma":[0.8112796,0.0005741797,0.029408997,0.00012039213,0.00007527922,0.0013877768,0.1557495,0.00028901815,0.0011153641],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9964604,0.0008302224,0.00093008694,0.000725596,0.0009426143,0.00011113688],"domain_scores_gemma":[0.96800363,0.009676472,0.006302542,0.0077160513,0.007666913,0.0006343438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008046266,0.00041155686,0.0009067839,0.0030874251,0.00041606312,0.0013273307,0.0010999788,0.0008293406,0.0016261194],"category_scores_gemma":[0.020017201,0.00024104978,0.00046459198,0.0032810632,0.00044705885,0.00089730514,0.00085220276,0.00037551235,0.0012729743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029873855,0.0006812157,0.701595,0.0018659118,0.002619784,0.00091908936,0.00074896263,0.005996714,0.024969114,0.0011802382,0.032684248,0.22375232],"study_design_scores_gemma":[0.000118343916,0.00042007767,0.9630602,0.000120996556,0.00044083,0.0016915606,0.00015929712,0.01003904,0.009264034,0.0008249053,0.013774927,0.00008561909],"about_ca_topic_score_codex":0.0032367385,"about_ca_topic_score_gemma":0.0056747547,"teacher_disagreement_score":0.008046266,"about_ca_system_score_codex":0.0003034255,"about_ca_system_score_gemma":0.00094334007,"threshold_uncertainty_score":0.042553246},"labels":[],"label_agreement":null},{"id":"W4366738674","doi":"10.5281/zenodo.7853832","title":"What matters in reinforcement learning for tractography - Datasets","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Tractography; Reinforcement; Computer science; Artificial intelligence; Psychology; Social psychology; Diffusion MRI; Medicine","score_opus":0.09395881842475623,"score_gpt":0.34581672891885146,"score_spread":0.2518579104940952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366738674","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024668831,0.0031382546,0.027880978,0.005227894,0.001287686,0.00052073307,0.9140612,0.016625093,0.006589344],"genre_scores_gemma":[0.039073955,0.0005175628,0.040459473,0.0019649887,0.00021091224,0.0013099205,0.91169643,0.0019609216,0.0028057152],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99675757,0.0012590998,0.000294999,0.00081482285,0.0006634478,0.00020993965],"domain_scores_gemma":[0.9877439,0.0058504078,0.0006231009,0.0040733516,0.0011405083,0.00056866964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005593335,0.0020311542,0.0011809507,0.0011041999,0.0010099015,0.002148757,0.0034608059,0.0042342446,0.018424205],"category_scores_gemma":[0.03149973,0.00064350193,0.0021401676,0.0015084982,0.0011905102,0.0017176012,0.0016563358,0.0031932509,0.012018409],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009769351,0.0005459086,0.005244618,0.0020288257,0.0004681746,0.00017864327,0.00007560496,0.026877888,0.0013343785,0.005850958,0.932305,0.024113106],"study_design_scores_gemma":[0.0041005956,0.0008372114,0.022577688,0.0017270757,0.0005006668,0.001647702,0.000273977,0.14470023,0.017672988,0.09951071,0.7060437,0.00040740974],"about_ca_topic_score_codex":0.004354089,"about_ca_topic_score_gemma":0.010262973,"teacher_disagreement_score":0.018424205,"about_ca_system_score_codex":0.0013869619,"about_ca_system_score_gemma":0.0018754695,"threshold_uncertainty_score":0.061635137},"labels":[],"label_agreement":null},{"id":"W4366752941","doi":"10.1016/j.neuroimage.2023.120129","title":"Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; UCLH Biomedical Research Centre; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; H2020 Marie Skłodowska-Curie Actions; University of California, San Diego; Genentech; National Institutes of Health; Horizon 2020; UK Dementia Research Institute; National Institute of Neurological Disorders and Stroke; IXICO; HORIZON EUROPE Framework Programme; Servier; Eisai; Wolfson Foundation; Eli Lilly and Company; Brain Research UK; National Institute on Aging; National Institute for Health and Care Research; European Research Council; Northern California Institute for Research and Education; Alzheimer’s Research UK; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Alzheimer's Society; University College London; University of Southern California; Wellcome Trust; Synarc; Medpace; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; European Commission; Alzheimer's Disease Neuroimaging Initiative; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; Neuroimaging; Segmentation; White matter; Artificial intelligence; Thalamus; Computer science; Bayesian probability; Probabilistic logic; Magnetic resonance imaging; Pattern recognition (psychology); Brain atlas; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.08031163095989832,"score_gpt":0.3801650050487406,"score_spread":0.2998533740888423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366752941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009553651,0.00010989282,0.9885797,0.00009113563,0.000016941205,0.000052586645,0.00015529654,0.00095863483,0.00048212404],"genre_scores_gemma":[0.09351582,0.00028829198,0.9034232,0.00006912445,0.000028831988,0.00015374985,0.0007989421,0.0006381481,0.001083921],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99882966,0.00027466015,0.000108223154,0.0002861802,0.00042631986,0.0000750099],"domain_scores_gemma":[0.9981686,0.0005682965,0.0002770319,0.00039085388,0.0005208898,0.000074318625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021989848,0.00094963633,0.001102785,0.0020459595,0.00062274607,0.0024870571,0.0011823649,0.0014232005,0.0015135895],"category_scores_gemma":[0.0062101525,0.0011039176,0.0014665233,0.0011544978,0.0008418314,0.0013694911,0.001789378,0.0014282165,0.0015235164],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029993683,0.00010934753,0.005153078,0.0003510234,0.00016279872,0.00039582682,0.00064608845,0.54328626,0.12816545,0.0240023,0.004603536,0.2928244],"study_design_scores_gemma":[0.000022505099,0.000053561285,0.0017899051,0.000039434148,0.000034644912,0.00029631174,0.000057336525,0.9681786,0.016152173,0.009840714,0.003475347,0.000059556172],"about_ca_topic_score_codex":0.009395199,"about_ca_topic_score_gemma":0.0144192,"teacher_disagreement_score":0.009395199,"about_ca_system_score_codex":0.0015173936,"about_ca_system_score_gemma":0.002588543,"threshold_uncertainty_score":0.01868105},"labels":[],"label_agreement":null},{"id":"W4366827617","doi":"10.1038/s41380-023-02068-1","title":"Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Health and Medical Research Council; National Institute of Mental Health; Medical Research Council; Brain and Behavior Research Foundation; National Alliance for Research on Schizophrenia and Depression; National Institutes of Health; National Science Foundation; U.S. Department of Health and Human Services; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Brigham and Women's Hospital","keywords":"Schizophrenia (object-oriented programming); Harmonization; Extracellular; Neuroscience; Diffusion MRI; Nuclear magnetic resonance; Characterization (materials science); Psychology; Magnetic resonance imaging; Medicine; Biology; Psychiatry; Biochemistry; Nanotechnology; Materials science; Physics; Radiology","score_opus":0.030776632982658692,"score_gpt":0.29431359015335473,"score_spread":0.26353695717069603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366827617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9396397,0.0010406859,0.0572087,0.00013716116,0.000016333252,0.000059200745,0.00036817748,0.00016281287,0.0013672509],"genre_scores_gemma":[0.9769529,0.00052855484,0.02142128,0.000037805374,0.000014531745,0.00003560986,0.00025607305,0.000061910374,0.000691368],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999261,0.000017001355,0.0000061975325,0.000016892716,0.000015871994,0.00001797358],"domain_scores_gemma":[0.9998331,0.000038004244,0.000040470397,0.000022142347,0.000046179477,0.000020031663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046911734,0.00031104079,0.00021902588,0.0008903769,0.00027987696,0.0004495847,0.00027842275,0.0004310456,0.0009785113],"category_scores_gemma":[0.00064975425,0.0001668937,0.0002502946,0.00039932766,0.00023985146,0.0006866696,0.00041029413,0.00031379174,0.00015705827],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010036171,0.00009561547,0.010855617,0.0002316609,0.000137618,0.0005570782,0.00028318661,0.00358457,0.9254723,0.0012146108,0.0003569451,0.056207202],"study_design_scores_gemma":[0.00009063083,0.0008792358,0.14141409,0.000057169196,0.00034038964,0.005547546,0.00080765126,0.11200832,0.73149896,0.0039395485,0.0032966645,0.00011977425],"about_ca_topic_score_codex":0.0013854852,"about_ca_topic_score_gemma":0.0016122628,"teacher_disagreement_score":0.0013854852,"about_ca_system_score_codex":0.00013021447,"about_ca_system_score_gemma":0.0002611913,"threshold_uncertainty_score":0.0032734275},"labels":[],"label_agreement":null},{"id":"W4367053067","doi":"10.1002/hbm.26311","title":"Direct localization and delineation of human pedunculopontine nucleus based on a self‐supervised magnetic resonance image super‐resolution method","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Atlas (anatomy); Brain atlas; Magnetic resonance imaging; Image resolution; Artificial intelligence; Pedunculopontine nucleus; Computer science; Nuclear magnetic resonance; Neuroscience; Human brain; Pattern recognition (psychology); Computer vision; Physics; Deep brain stimulation; Parkinson's disease; Anatomy; Biology; Pathology; Medicine; Radiology","score_opus":0.061177494505413925,"score_gpt":0.35817446245265144,"score_spread":0.2969969679472375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367053067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06966408,0.00023194557,0.9278749,0.0001015036,0.000014113005,0.00009365873,0.00014154796,0.000966304,0.000911937],"genre_scores_gemma":[0.34113148,0.00034514818,0.6553261,0.000105826955,0.000028013688,0.00017328736,0.0004971698,0.0002652074,0.002127736],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971753,0.00005751201,0.000012816287,0.00010469077,0.000079076075,0.00002819133],"domain_scores_gemma":[0.9996138,0.00009804149,0.00007255966,0.00007440451,0.000114193754,0.000027050315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005654799,0.000537819,0.00038342612,0.000678763,0.00020752246,0.0004955702,0.0006856736,0.0006364572,0.00059953984],"category_scores_gemma":[0.0013885894,0.00031904294,0.00051163207,0.00040535405,0.00044508412,0.00043786544,0.0006370923,0.0004455532,0.00037710206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039830175,0.00013435027,0.00481483,0.00040116237,0.00014205735,0.0007328008,0.0006075031,0.21625818,0.3842203,0.006772732,0.003974384,0.38154343],"study_design_scores_gemma":[0.00001353398,0.00006887531,0.002384417,0.00001195833,0.00004281434,0.00053382287,0.000042534546,0.9383827,0.0549913,0.0016848622,0.0018217304,0.000021464071],"about_ca_topic_score_codex":0.0022538903,"about_ca_topic_score_gemma":0.0035346227,"teacher_disagreement_score":0.0022538903,"about_ca_system_score_codex":0.00030234607,"about_ca_system_score_gemma":0.0008126558,"threshold_uncertainty_score":0.004481554},"labels":[],"label_agreement":null},{"id":"W4367296532","doi":"10.1212/wnl.0000000000202734","title":"White Matter and Gray Matter Changes Related to Cognition in Community populations (P12-6.008)","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Neurocognitive; White matter; Cognition; Effects of sleep deprivation on cognitive performance; Fractional anisotropy; Psychology; Verbal fluency test; Diffusion MRI; Memory span; Population; Audiology; Cognitive test; Neuropsychology; Medicine; Neuroscience; Magnetic resonance imaging; Working memory; Cognitive impairment; Radiology","score_opus":0.0840708708878097,"score_gpt":0.367682698456357,"score_spread":0.2836118275685473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367296532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974139,0.00006919736,0.00008582071,0.000067819245,0.000013607589,0.000025917256,0.0005316666,0.0000087998405,0.0017834402],"genre_scores_gemma":[0.99675167,0.00005300365,0.00017044968,0.000042859036,0.000017839982,0.000038682712,0.0005131583,0.0000072525754,0.002405174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999918,0.000010994245,0.0000049077157,0.000016340216,0.000017968481,0.00003176355],"domain_scores_gemma":[0.99964833,0.00002205792,0.0000773802,0.0000140853035,0.00011026215,0.00012790548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020688177,0.00028557592,0.0002552594,0.00054738356,0.000520152,0.00037650234,0.00023669594,0.00045784828,0.0069980742],"category_scores_gemma":[0.00061468454,0.00007810679,0.00014975855,0.0007976423,0.00014162442,0.00029367677,0.0003474932,0.00048129083,0.000785651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040503745,0.0022916207,0.9244741,0.00016004553,0.00016465542,0.0031652695,0.00067388045,0.00019978789,0.01509197,0.00021300517,0.003457605,0.046057697],"study_design_scores_gemma":[0.000022503918,0.00046489426,0.9978264,0.000005856244,0.000012749623,0.0005259701,0.00020785499,0.00005600149,0.00037466455,0.00009085804,0.00040956974,0.0000027149476],"about_ca_topic_score_codex":0.0075643323,"about_ca_topic_score_gemma":0.012208362,"teacher_disagreement_score":0.0075643323,"about_ca_system_score_codex":0.00018011694,"about_ca_system_score_gemma":0.00029513013,"threshold_uncertainty_score":0.023410857},"labels":[],"label_agreement":null},{"id":"W4367320574","doi":"10.3174/ajnr.a7855","title":"Associating<i>IDH</i>and<i>TERT</i>Mutations in Glioma with Diffusion Anisotropy in Normal-Appearing White Matter","year":2023,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Fractional anisotropy; White matter; Medicine; Diffusion MRI; Bonferroni correction; Glioma; Nuclear medicine; Internal medicine; Mann–Whitney U test; Pathology; Gastroenterology; Magnetic resonance imaging; Radiology","score_opus":0.02101469649579027,"score_gpt":0.30984541082314465,"score_spread":0.2888307143273544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367320574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985617,0.00013181087,0.000332275,0.000025968395,0.0000038103544,0.00001118668,0.00043496655,0.00001023728,0.0004882124],"genre_scores_gemma":[0.999329,0.000041073115,0.00023749941,0.000012120806,0.0000063390335,0.000005518162,0.00029123912,0.0000032859887,0.00007404923],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997253,0.00003450071,0.00006254944,0.00007435876,0.000058856283,0.000044402484],"domain_scores_gemma":[0.9984035,0.00023426628,0.0009136909,0.00018483448,0.00015035481,0.000113380825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068457244,0.00014058143,0.00013840037,0.00084102474,0.0001998846,0.00045212102,0.00017887115,0.00028068316,0.0012435806],"category_scores_gemma":[0.0017231021,0.000115286595,0.0002838582,0.00081878086,0.00037030538,0.00033599418,0.0002684639,0.00018293278,0.00024716853],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013990696,0.000008168358,0.99676836,0.0000100922725,0.000028075534,0.0001359237,0.000039614035,0.000057357447,0.0012105271,0.0000249993,0.00007177268,0.0015052953],"study_design_scores_gemma":[0.0000040171312,0.00007887474,0.9960174,0.0000067140977,0.000041029092,0.0016432193,0.00011523959,0.00034161264,0.001443948,0.00005107702,0.00025197637,0.0000048320185],"about_ca_topic_score_codex":0.0028518548,"about_ca_topic_score_gemma":0.0045624613,"teacher_disagreement_score":0.0028518548,"about_ca_system_score_codex":0.0002302124,"about_ca_system_score_gemma":0.00038728482,"threshold_uncertainty_score":0.005670488},"labels":[],"label_agreement":null},{"id":"W4368339382","doi":"10.1016/j.bandl.2023.105270","title":"White matter correlates of reading subskills in children with and without reading disability","year":2023,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Brock University; SickKids Foundation; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Ontario; Canada First Research Excellence Fund; Nvidia","keywords":"Fractional anisotropy; Psychology; Reading (process); White matter; Diffusion MRI; Uncinate fasciculus; Fasciculus; Reading disability; Reading comprehension; Superior longitudinal fasciculus; Arcuate fasciculus; Dyslexia; Developmental psychology; Linguistics; Magnetic resonance imaging; Medicine","score_opus":0.014394871813121029,"score_gpt":0.314149667571959,"score_spread":0.29975479575883796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368339382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995408,0.000061882034,0.000010312896,0.000013176363,0.0000012488848,0.0000011388037,0.000110813075,0.0000017138008,0.00025888308],"genre_scores_gemma":[0.99941456,0.00006442374,0.000022868044,0.000009209947,0.0000043185714,0.0000036881286,0.00020638297,0.0000027636245,0.00027192742],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997427,0.00002513399,0.000032987475,0.000071669616,0.000051774135,0.000075728596],"domain_scores_gemma":[0.9986066,0.000249682,0.0007104235,0.00004135161,0.00016171695,0.00023023946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020399509,0.00043400782,0.0004088053,0.0020128703,0.00045643034,0.00078571757,0.00031869608,0.0004373321,0.002600594],"category_scores_gemma":[0.0019287824,0.00023459682,0.0003018337,0.001353343,0.0005934262,0.0006609417,0.00069960015,0.0004555349,0.00040995047],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028890232,0.00005935242,0.99322516,0.000021881895,0.000059561648,0.00092461094,0.0007870807,0.000056881297,0.0025510024,0.000044471308,0.000083842526,0.0018972036],"study_design_scores_gemma":[0.0000014323265,0.000030206515,0.9991866,0.0000017343552,0.0000075803537,0.00026007937,0.00038146015,0.000020571431,0.00007808359,0.000010213223,0.000020885045,0.000001236555],"about_ca_topic_score_codex":0.02380169,"about_ca_topic_score_gemma":0.027926676,"teacher_disagreement_score":0.02380169,"about_ca_system_score_codex":0.000470082,"about_ca_system_score_gemma":0.00038261386,"threshold_uncertainty_score":0.047326267},"labels":[],"label_agreement":null},{"id":"W4368362973","doi":"10.1016/j.jad.2023.04.136","title":"The relationship of white matter microstructure with psychomotor disturbance and relapse in remitted psychotic depression","year":2023,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University Health Network; University of Toronto","funders":"U.S. Public Health Service; National Institute of Mental Health; University of Toronto; Pfizer","keywords":"Psychology; Psychomotor learning; White matter; Psychomotor disorder; Fractional anisotropy; Psychiatry; Psychosis; Medicine; Cognition; Magnetic resonance imaging","score_opus":0.016400556689521555,"score_gpt":0.31944355355226056,"score_spread":0.303042996862739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368362973","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996489,0.00012819032,0.000031327872,0.000017005385,0.0000018166669,0.0000028157356,0.000019482197,0.0000015304772,0.00014895944],"genre_scores_gemma":[0.9998154,0.00004071566,0.000032929118,0.0000061119426,0.0000034731004,0.0000014332826,0.000029371535,7.823868e-7,0.00006985282],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988174,0.00003312261,0.000019353405,0.000021001671,0.000021852451,0.000022990169],"domain_scores_gemma":[0.9991799,0.00016820789,0.00041151518,0.00005243529,0.0000565459,0.00013132578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003336221,0.00016725452,0.0002421617,0.0005307131,0.0002767338,0.0004296907,0.00027407368,0.00036024355,0.00084456796],"category_scores_gemma":[0.0018798815,0.00019426964,0.00021541557,0.00043416547,0.00029851633,0.00032519392,0.0003215435,0.00048807528,0.000104615385],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011249022,0.00013666811,0.98805934,0.000014010651,0.00017561024,0.0005875593,0.00016645242,0.00014513601,0.004319772,0.000060955277,0.000051014482,0.005158586],"study_design_scores_gemma":[0.00000303006,0.00008080712,0.99938726,0.0000014355778,0.000010247424,0.00023011686,0.000053968753,0.00012233062,0.00006282561,0.000030703406,0.000015741716,0.0000014967378],"about_ca_topic_score_codex":0.0030270605,"about_ca_topic_score_gemma":0.005315167,"teacher_disagreement_score":0.0030270605,"about_ca_system_score_codex":0.00029373387,"about_ca_system_score_gemma":0.00019966476,"threshold_uncertainty_score":0.006018877},"labels":[],"label_agreement":null},{"id":"W4368372507","doi":"10.21203/rs.3.rs-2874508/v1","title":"Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; European Commission","keywords":"White matter; Tractography; Grey matter; Cognition; Computer science; Functional organization; Diffusion MRI; Voxel; Artificial intelligence; Prior probability; Pattern recognition (psychology); Neuroscience; Psychology; Magnetic resonance imaging; Bayesian probability","score_opus":0.1250502369518265,"score_gpt":0.44807553347470047,"score_spread":0.323025296522874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368372507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0384409,0.00012137078,0.95892894,0.000114619106,0.000022089229,0.0000356775,0.00016809738,0.0015345699,0.0006337775],"genre_scores_gemma":[0.17137995,0.00019145034,0.82361335,0.00008168835,0.0000520374,0.00013145244,0.0009118859,0.0013855125,0.0022526868],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997434,0.00008111972,0.000013676987,0.00007984897,0.00005326576,0.000028658586],"domain_scores_gemma":[0.9985281,0.00073582854,0.00016299376,0.00025825898,0.00021489178,0.00009994978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015644804,0.0011186016,0.0006925658,0.0014602197,0.00047824325,0.001153809,0.00071478647,0.00096776156,0.0041735885],"category_scores_gemma":[0.0040156106,0.00048651992,0.0007112537,0.00065283803,0.000763528,0.0013926903,0.00081770483,0.0013592959,0.0011713537],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001094975,0.00029882562,0.007126156,0.0005119961,0.00029185403,0.00034835842,0.00048444915,0.20555188,0.21706413,0.035547286,0.0056802663,0.52599984],"study_design_scores_gemma":[0.00004103499,0.00010015377,0.0051110946,0.000033575634,0.0000637649,0.00027359126,0.00003993035,0.9097729,0.058588583,0.017949108,0.007973867,0.000052465733],"about_ca_topic_score_codex":0.002764673,"about_ca_topic_score_gemma":0.004667355,"teacher_disagreement_score":0.0041735885,"about_ca_system_score_codex":0.0005491242,"about_ca_system_score_gemma":0.0013227258,"threshold_uncertainty_score":0.01396203},"labels":[],"label_agreement":null},{"id":"W4372218972","doi":"10.1016/j.neuroimage.2023.120159","title":"High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Sharpening; Image resolution; Diffusion MRI; Signal-to-noise ratio (imaging); Resolution (logic); Physics; Image quality; Nuclear magnetic resonance; Optics; Computer science; Magnetic resonance imaging; Artificial intelligence; Image (mathematics)","score_opus":0.052073682086251974,"score_gpt":0.32530789748682415,"score_spread":0.2732342154005722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372218972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77207124,0.005472442,0.21986486,0.00028131405,0.000031134277,0.0001061621,0.00039807416,0.0006960817,0.0010787423],"genre_scores_gemma":[0.7767224,0.0034755873,0.21821308,0.00006500776,0.000009483887,0.00012918502,0.00054455106,0.0001830947,0.0006576566],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994875,0.00018801683,0.000040113788,0.000072354815,0.00017562338,0.00003628662],"domain_scores_gemma":[0.99828464,0.0008984663,0.00025553376,0.0001348447,0.000351614,0.00007490766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018225419,0.0005101232,0.0004810019,0.0003516925,0.00021488649,0.0006084672,0.0006117384,0.0007181215,0.0004478253],"category_scores_gemma":[0.0071631717,0.00035648534,0.00021161664,0.0006682612,0.00030054757,0.0009500621,0.00029690328,0.00034155365,0.00022791572],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002566451,0.00020967297,0.009445323,0.0011575986,0.00019747134,0.0013486238,0.00054964086,0.19631858,0.68518573,0.005108063,0.00086798903,0.097044885],"study_design_scores_gemma":[0.0001240037,0.001332101,0.012892255,0.00013740889,0.00015572054,0.0018405657,0.000114161,0.5182532,0.45810536,0.0033026114,0.0036010472,0.00014156292],"about_ca_topic_score_codex":0.0022951216,"about_ca_topic_score_gemma":0.0018186244,"teacher_disagreement_score":0.0022951216,"about_ca_system_score_codex":0.0006491421,"about_ca_system_score_gemma":0.00052614044,"threshold_uncertainty_score":0.009638667},"labels":[],"label_agreement":null},{"id":"W4372403590","doi":"10.1101/2023.05.05.539590","title":"Predicting Parkinson’s disease progression using MRI-based white matter radiomic biomarker and machine learning: a reproducibility and replicability study","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"Michael J. Fox Foundation for Parkinson's Research","keywords":"Artificial intelligence; Replicate; Robustness (evolution); Neuroimaging; Machine learning; Magnetic resonance imaging; Biomarker; Cohort; Parkinson's disease; Imaging biomarker; Reproducibility; Population; Medicine; Computer science; Feature selection; Disease; Internal medicine; Statistics; Radiology; Mathematics; Biology","score_opus":0.07022890400720562,"score_gpt":0.32764046722167534,"score_spread":0.25741156321446973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372403590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7680161,0.0041787955,0.21930102,0.0007324365,0.0008591872,0.0010787538,0.0022273723,0.0007625132,0.002843915],"genre_scores_gemma":[0.9761613,0.0001846634,0.020709416,0.0001893948,0.00013577337,0.0004099778,0.0015927044,0.00022102495,0.00039570304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9223588,0.055471823,0.005576812,0.010870871,0.0052073523,0.0005143488],"domain_scores_gemma":[0.6731724,0.18991214,0.013663391,0.101335175,0.0207412,0.0011756847],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.13416903,0.0013456322,0.0010469272,0.0012880188,0.000788276,0.0025192879,0.001959024,0.0016701159,0.0012098609],"category_scores_gemma":[0.2229676,0.00061667414,0.003051101,0.0012404249,0.0024801276,0.001495006,0.0019765322,0.0019398218,0.00085574697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013558263,0.0021482105,0.71361476,0.0021650284,0.022775859,0.0008500734,0.002839876,0.06174855,0.028829793,0.00432128,0.005003874,0.1421444],"study_design_scores_gemma":[0.0016129462,0.022615617,0.530464,0.0012822545,0.013350349,0.0029621304,0.0013442872,0.30849057,0.075382635,0.01993093,0.021897947,0.00066635443],"about_ca_topic_score_codex":0.0014551121,"about_ca_topic_score_gemma":0.00083827134,"teacher_disagreement_score":0.86583096,"about_ca_system_score_codex":0.0005286164,"about_ca_system_score_gemma":0.0010173125,"threshold_uncertainty_score":0.7095621},"labels":[],"label_agreement":null},{"id":"W4376122082","doi":"10.1002/hbm.26322","title":"Feasibility of diffusion‐tensor and correlated diffusion imaging for studying white‐matter microstructural abnormalities: Application in <scp>COVID</scp>‐19","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Waterloo; Toronto Metropolitan University; University of Toronto; St. Michael's Hospital; Baycrest Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Magnetic resonance imaging; Fractional anisotropy; Diffusion; Tractography; Coronavirus disease 2019 (COVID-19); Diffusion imaging; Nuclear magnetic resonance; Medicine; Nuclear medicine; Pathology; Radiology; Physics","score_opus":0.07821745750001177,"score_gpt":0.3565695099885581,"score_spread":0.27835205248854633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376122082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8559885,0.0012335303,0.14033997,0.00029719225,0.000047403355,0.00015907198,0.00034650558,0.0004266892,0.0011610993],"genre_scores_gemma":[0.92377675,0.0005878229,0.07488976,0.000045949844,0.000017820621,0.00007807763,0.00022549549,0.000064819695,0.00031337418],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998134,0.00007542439,0.000011171174,0.000043391297,0.000040289073,0.00001633008],"domain_scores_gemma":[0.99943024,0.0002242137,0.00012212338,0.000075103126,0.00009062311,0.000057672154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008964289,0.00071416073,0.0005386809,0.0005573228,0.00024377496,0.0006106116,0.0004318338,0.0006804493,0.00057606545],"category_scores_gemma":[0.0018106798,0.00039719,0.0005196988,0.0003268188,0.0003478054,0.0005728678,0.00058912626,0.00039559082,0.00013638703],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016433421,0.00039204978,0.049425475,0.00066576235,0.00034758393,0.0015502952,0.00028707786,0.10511836,0.75444084,0.0017233972,0.0006754184,0.08373039],"study_design_scores_gemma":[0.00009527552,0.0010055695,0.038753707,0.00006021527,0.00015310747,0.001745927,0.00014631842,0.7839574,0.1707455,0.0016357072,0.0015898133,0.000111342495],"about_ca_topic_score_codex":0.003224162,"about_ca_topic_score_gemma":0.0038104572,"teacher_disagreement_score":0.003224162,"about_ca_system_score_codex":0.00029016667,"about_ca_system_score_gemma":0.0006583221,"threshold_uncertainty_score":0.0064107776},"labels":[],"label_agreement":null},{"id":"W4376224771","doi":"10.1093/cercor/bhad130","title":"Face recognition ability can be predicted by microstructural properties of white matter: a study of diffusion tensor imaging (DTI)","year":2023,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Hamilton Health Sciences","funders":"Natural Science Foundation of Zhejiang Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Fractional anisotropy; Corpus callosum; Inferior longitudinal fasciculus; Diffusion MRI; White matter; Lateralization of brain function; Psychology; Arcuate fasciculus; Fasciculus; Correlation; Tractography; Audiology; Neuroscience; Medicine; Mathematics; Magnetic resonance imaging; Geometry","score_opus":0.051613508482347005,"score_gpt":0.30152868559539225,"score_spread":0.24991517711304526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376224771","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984018,0.00014070794,0.0011279981,0.000029394916,0.0000028306272,0.000002221018,0.000041838008,0.000004433853,0.00024870236],"genre_scores_gemma":[0.99938154,0.00006437039,0.00041560928,0.000008265302,0.0000051012917,0.0000021179005,0.000038340775,0.0000027169963,0.00008195527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998336,0.000050520764,0.000010461822,0.00006429487,0.000024745228,0.00001630901],"domain_scores_gemma":[0.99864215,0.00074518326,0.00036212473,0.00013517811,0.00005932952,0.000056091656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010111387,0.0003611675,0.00017962043,0.0006841632,0.0001203627,0.0004140891,0.00013014457,0.00029214084,0.00051475613],"category_scores_gemma":[0.0037731435,0.00013359722,0.00028066282,0.00032342013,0.00034252013,0.000531084,0.00021593276,0.00036178282,0.000107712556],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004538353,0.0001353385,0.9285028,0.000043126045,0.000626889,0.00039816226,0.00072480075,0.0036208397,0.020052362,0.0006677611,0.00023931821,0.04453476],"study_design_scores_gemma":[0.0000051301113,0.00015484495,0.977996,0.000009576788,0.00006862513,0.00048509022,0.000108107764,0.01789425,0.0020358977,0.0010187685,0.00020860846,0.000015209787],"about_ca_topic_score_codex":0.0019908918,"about_ca_topic_score_gemma":0.0018007373,"teacher_disagreement_score":0.0019908918,"about_ca_system_score_codex":0.00012310347,"about_ca_system_score_gemma":0.00012394068,"threshold_uncertainty_score":0.0053474307},"labels":[],"label_agreement":null},{"id":"W4376270889","doi":"10.1101/2023.05.10.23289785","title":"Microscopic fractional anisotropy asymmetry in unilateral temporal lobe epilepsy","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fractional anisotropy; Temporal lobe; Diffusion MRI; Axon; Magnetic resonance imaging; Hippocampus; Subiculum; Anisotropy; Epilepsy; Neuroscience; Medicine; Psychology; Dentate gyrus; Radiology; Physics","score_opus":0.09615239241896996,"score_gpt":0.3864693774516486,"score_spread":0.29031698503267866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376270889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99882907,0.00012553751,0.000550151,0.000021296411,0.00000215668,0.0000042134034,0.00006937648,0.000013267998,0.00038497138],"genre_scores_gemma":[0.9997465,0.0000231759,0.00014071763,0.0000028389356,0.0000014973157,0.0000010785438,0.000026317797,0.0000015986308,0.000056137294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992704,0.000012176897,0.0000105766685,0.000021870017,0.000014922847,0.000013356257],"domain_scores_gemma":[0.9996308,0.000079994315,0.00017678931,0.000043590324,0.000032290252,0.000036445155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022271153,0.00026674656,0.00018700566,0.00071633206,0.00016536271,0.0002656408,0.000098252654,0.00013359352,0.0015254937],"category_scores_gemma":[0.0012370234,0.000121846606,0.00013267316,0.0002605521,0.00037191564,0.000287004,0.00021829492,0.00009982279,0.00011182026],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032773605,0.00010105452,0.73937374,0.00021630537,0.00031763085,0.010279166,0.00066262105,0.0035448647,0.1613874,0.00064083847,0.0006453561,0.0795536],"study_design_scores_gemma":[0.000037118447,0.00020601046,0.968635,0.000009774499,0.00007003781,0.015520256,0.00017666053,0.0037428685,0.010740518,0.00056606164,0.00028100907,0.000014601122],"about_ca_topic_score_codex":0.0031147003,"about_ca_topic_score_gemma":0.0034301076,"teacher_disagreement_score":0.0031147003,"about_ca_system_score_codex":0.0002461467,"about_ca_system_score_gemma":0.00019069367,"threshold_uncertainty_score":0.006193161},"labels":[],"label_agreement":null},{"id":"W4376277450","doi":"10.1038/s41380-023-02031-0","title":"The organization of frontostriatal brain wiring in non-affective early psychosis compared with healthy subjects using a novel diffusion imaging fiber cluster analysis","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"U.S. Department of Veterans Affairs; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression; U.S. Department of Health and Human Services","keywords":"Tractography; Diffusion MRI; Neuroscience; Psychology; Psychosis; White matter; Connectome; Magnetic resonance imaging; Fiber; Schizophrenia (object-oriented programming); Human Connectome Project; Medicine; Chemistry; Psychiatry; Functional connectivity; Radiology","score_opus":0.015669458494087435,"score_gpt":0.3155367137008391,"score_spread":0.2998672552067516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376277450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99789065,0.000079654346,0.0015943681,0.000024192837,0.000003450474,0.000011581843,0.00016051429,0.00001948939,0.00021609345],"genre_scores_gemma":[0.9982456,0.00004860617,0.0011839527,0.0000042365687,0.0000037439897,0.000010657541,0.00014274026,0.000010104925,0.00035032706],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99995255,0.000008119942,0.0000034305033,0.00001658191,0.000006723469,0.000012599703],"domain_scores_gemma":[0.999861,0.00003319592,0.000039497638,0.000018003544,0.000022060676,0.000026295345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022814117,0.00025187843,0.00015920993,0.00077009865,0.0003515507,0.00037423705,0.00016730573,0.00016758849,0.0013016522],"category_scores_gemma":[0.0005263326,0.00010496523,0.0001806155,0.00029839197,0.00023903737,0.00026824104,0.0003209775,0.00015842836,0.000085736254],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008703968,0.0003122044,0.40165982,0.00024351609,0.00067870825,0.0011830482,0.0029269014,0.004351511,0.47726166,0.0015518365,0.0010409585,0.10008588],"study_design_scores_gemma":[0.00004358611,0.0002385687,0.98062414,0.000012154019,0.00012446463,0.00063425314,0.0006525925,0.008368541,0.007988273,0.0008842524,0.00040826047,0.000020881078],"about_ca_topic_score_codex":0.0107625425,"about_ca_topic_score_gemma":0.01645468,"teacher_disagreement_score":0.0107625425,"about_ca_system_score_codex":0.0003068934,"about_ca_system_score_gemma":0.0002732685,"threshold_uncertainty_score":0.021399796},"labels":[],"label_agreement":null},{"id":"W4377014295","doi":"10.1212/wnl.0000000000207408","title":"Association of Cortical and Subcortical Microstructure With Clinical Progression and Fluid Biomarkers in Patients With Parkinson Disease","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Avid Radiopharmaceuticals; Sanofi Genzyme; Allergan; H. Lundbeck A/S; Higher Education Discipline Innovation Project; Servier; Genentech; National Natural Science Foundation of China; Voyager Therapeutics; Neurocrine Biosciences; Biogen; Celgene; Verily Life Sciences; Teva Pharmaceutical Industries; Sanofi; GlaxoSmithKline; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Internal medicine; Biomarker; Medicine; Montreal Cognitive Assessment; Parkinson's disease; Putamen; Diffusion MRI; Neurology; Psychology; Disease; Oncology; Cardiology; Magnetic resonance imaging; Psychiatry; Radiology; Cognitive impairment; Biology","score_opus":0.01979690020336478,"score_gpt":0.3407179896663006,"score_spread":0.32092108946293585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377014295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990627,0.00033190163,0.00008609616,0.00004080628,0.000002693456,0.0000056210906,0.00019110614,0.0000040814316,0.00027492768],"genre_scores_gemma":[0.99958175,0.00005022651,0.00009219138,0.000010363057,0.000004791644,0.000004599676,0.00013969476,0.0000010911432,0.00011533984],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998061,0.000042825053,0.000023241915,0.000063990374,0.00003531196,0.000028622526],"domain_scores_gemma":[0.99890506,0.00020946722,0.00051239005,0.00007594659,0.00018966896,0.00010737984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057034206,0.00026807896,0.00029706638,0.0006324406,0.00033696453,0.0005828953,0.00022933456,0.0004081999,0.001056874],"category_scores_gemma":[0.0022891937,0.00018069525,0.00022529882,0.00045400314,0.00022099057,0.0003653444,0.00032099403,0.0004895196,0.000110619825],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034722636,0.00003211676,0.9969137,0.000009324599,0.000080347694,0.00008664333,0.000063594096,0.0000670453,0.00054815394,0.000019626477,0.000063888314,0.001768409],"study_design_scores_gemma":[0.000005494793,0.00007801967,0.99928504,0.0000029431262,0.000020505293,0.0002104443,0.000042773845,0.00018011793,0.00008141424,0.000039077586,0.000052229087,0.0000019881625],"about_ca_topic_score_codex":0.0040113563,"about_ca_topic_score_gemma":0.0069226655,"teacher_disagreement_score":0.0040113563,"about_ca_system_score_codex":0.00029756443,"about_ca_system_score_gemma":0.00029632077,"threshold_uncertainty_score":0.007976055},"labels":[],"label_agreement":null},{"id":"W4377014380","doi":"10.1101/2023.05.17.541182","title":"Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Vanderbilt University; University of Southern California; Vanderbilt Memory and Alzheimer's Center; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Vanderbilt University Medical Center; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Diffusion; Longitudinal data; Materials science; Psychology; Magnetic resonance imaging; Medicine; Computer science; Physics; Data mining; Radiology; Thermodynamics","score_opus":0.0937509714158721,"score_gpt":0.3236515467001635,"score_spread":0.2299005752842914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377014380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9225412,0.0047211265,0.036187995,0.0006201417,0.00009343455,0.00017479324,0.03097242,0.00097585144,0.003712988],"genre_scores_gemma":[0.9343773,0.0015123244,0.029561192,0.0002605646,0.00010197775,0.0003631381,0.03199351,0.00026661725,0.0015633508],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992747,0.00016792027,0.00010880393,0.0002461869,0.00014302866,0.000059382724],"domain_scores_gemma":[0.9982375,0.00019621538,0.0007156714,0.00043328217,0.0003334847,0.000083855666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028838548,0.00057241315,0.0005513245,0.0021215535,0.00046394608,0.0010795292,0.0006001685,0.00043232657,0.0019095925],"category_scores_gemma":[0.004437543,0.00027525995,0.0005770334,0.0015259971,0.00044183043,0.0008788468,0.0010184719,0.00035508082,0.00055596296],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017550986,0.00020237401,0.74888325,0.0013051432,0.0035340507,0.00033658018,0.0006804841,0.0053373515,0.046730578,0.0012506854,0.019291142,0.17069337],"study_design_scores_gemma":[0.00007105378,0.00030659963,0.95484483,0.00022166403,0.0006373385,0.0010527977,0.00025014745,0.007821006,0.011835776,0.005018078,0.017853595,0.00008717837],"about_ca_topic_score_codex":0.004505492,"about_ca_topic_score_gemma":0.017374305,"teacher_disagreement_score":0.004505492,"about_ca_system_score_codex":0.00034283003,"about_ca_system_score_gemma":0.00068526174,"threshold_uncertainty_score":0.015251458},"labels":[],"label_agreement":null},{"id":"W4377103901","doi":"10.1002/dad2.12425","title":"White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Office of the Director; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; National Institute of General Medical Sciences; H. Lundbeck A/S; Servier; Eisai; Vanderbilt University Medical Center; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Vanderbilt University; University of Southern California; Vanderbilt Memory and Alzheimer's Center; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Neuroimaging; Diffusion MRI; Metric (unit); Magnetic resonance imaging; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Multivariate statistics; Medicine; Disease; Internal medicine; Psychology; Neuroscience; Statistics; Radiology; Mathematics","score_opus":0.11201449902615865,"score_gpt":0.41138578791807917,"score_spread":0.29937128889192055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377103901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99655956,0.0006534334,0.0011839905,0.00012819772,0.000022132092,0.000012960395,0.0005122312,0.000028203389,0.0008993008],"genre_scores_gemma":[0.9988483,0.00007275706,0.00052819314,0.000018151006,0.000013860354,0.000008167298,0.00028789835,0.000006618698,0.00021594201],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996153,0.0001016058,0.000055462984,0.00013213797,0.00005989103,0.000035614037],"domain_scores_gemma":[0.9975696,0.0005014147,0.0011021277,0.00030077397,0.0003895052,0.00013660693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001761739,0.00040405602,0.00025872275,0.00080478383,0.0003179856,0.00085593975,0.00035153393,0.00035258077,0.001373601],"category_scores_gemma":[0.0057498785,0.00014570369,0.00029020983,0.00073955255,0.00039698728,0.0006880911,0.00055069715,0.00030536146,0.00023301873],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035200137,0.000023359735,0.9792086,0.000043886812,0.00024127621,0.000054893524,0.00017869558,0.00060406467,0.0026482712,0.0002065773,0.00065894134,0.01577939],"study_design_scores_gemma":[0.0000030859321,0.00005595802,0.99793184,0.000012021493,0.00003386392,0.000081711936,0.00005859101,0.0008447709,0.0003966393,0.0003012639,0.00027580748,0.000004386103],"about_ca_topic_score_codex":0.0056454916,"about_ca_topic_score_gemma":0.008451043,"teacher_disagreement_score":0.0056454916,"about_ca_system_score_codex":0.00029711,"about_ca_system_score_gemma":0.00031017698,"threshold_uncertainty_score":0.011225224},"labels":[],"label_agreement":null},{"id":"W4377197047","doi":"10.1016/j.biopsych.2023.05.014","title":"Prenatal and Postnatal Maternal Depressive Symptoms Are Associated With White Matter Integrity in 5-Year-Olds in a Sex-Specific Manner","year":2023,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Suomen Aivosäätiö; Emil Aaltosen Säätiö; Sigrid Juséliuksen Säätiö; Brain and Behavior Research Foundation; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Alfred Kordelinin Säätiö; Varsinais-Suomen Sairaanhoitopiiri; Suomalainen Lääkäriseura Duodecim; Juho Vainion Säätiö; National Alliance for Research on Schizophrenia and Depression; Suomen Kulttuurirahasto; Suomen Lääketieteen Säätiö; Turun Yliopisto; Academy of Finland","keywords":"Edinburgh Postnatal Depression Scale; Offspring; Pregnancy; Anxiety; Child Behavior Checklist; Fractional anisotropy; Psychology; Medicine; White matter; Prenatal care; Obstetrics; Clinical psychology; Pediatrics; Psychiatry; Depressive symptoms","score_opus":0.04145281537157792,"score_gpt":0.30919734968013257,"score_spread":0.26774453430855466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377197047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99949014,0.0001902837,0.00002295105,0.000016369964,0.0000035236474,0.0000014408351,0.000120715325,0.0000021761211,0.0001523119],"genre_scores_gemma":[0.9995468,0.00009709656,0.00004041184,0.000011196585,0.0000042267297,0.0000022425822,0.00015342548,0.0000013655603,0.00014322365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984324,0.000022950007,0.000015494816,0.000051385603,0.000027791182,0.00003915031],"domain_scores_gemma":[0.99938464,0.000060081413,0.0003641914,0.000031590887,0.000041139698,0.00011832159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024209131,0.00026959224,0.00022247747,0.00055116374,0.00022178129,0.0004252803,0.00023100725,0.00041828834,0.0016135682],"category_scores_gemma":[0.0009829253,0.0002120507,0.0003725013,0.00031374325,0.00021321866,0.00019218295,0.00029639027,0.00027460465,0.00018650298],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084096464,0.000013843633,0.9978593,0.0000044583817,0.000043518547,0.00013516235,0.00008212847,0.000010061319,0.00087357505,0.0000113493525,0.000044576318,0.0008378706],"study_design_scores_gemma":[5.670529e-7,0.000015992511,0.99979335,0.0000012933904,0.000006127583,0.00009928796,0.00002495322,0.000009430012,0.000026749969,0.0000030809747,0.000018721243,4.6890472e-7],"about_ca_topic_score_codex":0.0032854117,"about_ca_topic_score_gemma":0.005678046,"teacher_disagreement_score":0.0032854117,"about_ca_system_score_codex":0.00012300923,"about_ca_system_score_gemma":0.00013403501,"threshold_uncertainty_score":0.00653255},"labels":[],"label_agreement":null},{"id":"W4377694396","doi":"10.21203/rs.3.rs-2950610/v1","title":"Radiomic tractometry: a rich and tract-specific class of imaging biomarkers for neuroscience and medical applications","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; Allergan; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Neurocrine Biosciences; Novartis Pharmaceuticals Corporation; Voyager Therapeutics; Biogen; BioClinica; F. Hoffmann-La Roche; Celgene; Meso Scale Diagnostics; Teva Pharmaceutical Industries; Verily Life Sciences; Northern California Institute for Research and Education; University of Southern California; Deutsche Forschungsgemeinschaft; GlaxoSmithKline; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Association; Michael J. Fox Foundation for Parkinson's Research; Foundation for the National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative","keywords":"Python (programming language); Computer science; Diffusion MRI; Neuroimaging; Data science; Neuroscience; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.210662261618314,"score_gpt":0.4964466536060208,"score_spread":0.2857843919877068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377694396","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007044474,0.0016216418,0.9666959,0.00065188576,0.00016936325,0.00009108283,0.007186689,0.0143853985,0.0021536332],"genre_scores_gemma":[0.15042822,0.004701389,0.8061648,0.0007821239,0.0006954987,0.0006431545,0.023039334,0.007904171,0.0056413384],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99880505,0.00029993092,0.00010652886,0.00036111666,0.00035524255,0.00007207485],"domain_scores_gemma":[0.9962656,0.0010463555,0.0008492421,0.0010624632,0.0005904003,0.00018596329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021698053,0.0018413836,0.0012115223,0.0043039015,0.0005948846,0.0033698636,0.0011538496,0.0014250999,0.006126659],"category_scores_gemma":[0.011721207,0.0007978893,0.001464428,0.0040125432,0.0013826664,0.003098321,0.002201887,0.00148611,0.006594696],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045543647,0.0001565569,0.018219562,0.002388835,0.0012008196,0.00083052553,0.0005934666,0.042403027,0.07670733,0.092259936,0.1060212,0.65876323],"study_design_scores_gemma":[0.000102520404,0.00032474578,0.027070777,0.0006950702,0.0004759285,0.0047013513,0.00021149858,0.3561389,0.06603198,0.34522456,0.1985894,0.00043320857],"about_ca_topic_score_codex":0.0018119091,"about_ca_topic_score_gemma":0.0028926395,"teacher_disagreement_score":0.006126659,"about_ca_system_score_codex":0.0005839031,"about_ca_system_score_gemma":0.0020764244,"threshold_uncertainty_score":0.020495772},"labels":[],"label_agreement":null},{"id":"W4377834853","doi":"10.1007/978-3-031-10909-6_29","title":"fMRI of Human Visual Pathways","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Island Health","funders":"","keywords":"Neuroscience; White matter; Functional magnetic resonance imaging; Diffusion MRI; Human brain; Visual system; Magnetic resonance imaging; Sensory system; Psychology; Visual cortex; Medicine; Radiology","score_opus":0.16550002138002212,"score_gpt":0.3929910768654471,"score_spread":0.22749105548542498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377834853","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004416221,0.06563532,0.29638088,0.004448443,0.0021001468,0.000068316316,0.00033611496,0.0013506438,0.6252639],"genre_scores_gemma":[0.07055687,0.062794976,0.15525423,0.0023410881,0.0015408434,0.0001324907,0.00038703383,0.00047758923,0.70651484],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99996257,0.000008305152,9.2530445e-7,0.000008938776,0.000015301772,0.000003948739],"domain_scores_gemma":[0.9999131,0.000060605398,0.000002583852,0.000007920647,0.00000923224,0.000006546438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015265796,0.00044488517,0.0002039138,0.00047750643,0.00018801313,0.0007744919,0.00051032094,0.0007643889,0.019223202],"category_scores_gemma":[0.00036901736,0.00028846477,0.00019142765,0.0003318166,0.0006298021,0.00093067513,0.00038597177,0.0006815062,0.005262577],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058467875,0.000028871193,0.00008276324,0.00071098056,0.00002862202,0.0002718629,0.00016931669,0.0027442886,0.06979086,0.18505633,0.13752334,0.60353434],"study_design_scores_gemma":[0.000012991398,0.000048380796,0.0008625003,0.00026169853,0.000018783428,0.0015845225,0.00007137886,0.0055228635,0.021990107,0.25519463,0.7144058,0.000026371998],"about_ca_topic_score_codex":0.0006793358,"about_ca_topic_score_gemma":0.0021468205,"teacher_disagreement_score":0.019223202,"about_ca_system_score_codex":0.00037763288,"about_ca_system_score_gemma":0.0002949408,"threshold_uncertainty_score":0.06430805},"labels":[],"label_agreement":null},{"id":"W4378472763","doi":"10.1016/j.neuroimage.2023.120198","title":"Cell specificity of Manganese-enhanced MRI signal in the cerebellum","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Ontario Institute for Cancer Research","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; School of Medicine, New York University; National Cancer Institute; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; New York State Stem Cell Science","keywords":"Cytoarchitecture; Cerebellum; Purkinje cell; Neuroscience; Cerebellar cortex; Biology; Anatomy; Cell type; Cell","score_opus":0.06808518125131767,"score_gpt":0.3376798203724341,"score_spread":0.2695946391211164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378472763","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913839,0.0010735772,0.006657867,0.0000261248,0.0000076305705,0.000025824895,0.00003426882,0.000043789125,0.00074691226],"genre_scores_gemma":[0.9940785,0.00047364077,0.0044824723,0.000024405326,0.0000030791894,0.0000287249,0.00007282882,0.000016608281,0.00081982027],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975604,0.00003916123,0.000018156084,0.00006765719,0.00007728779,0.000041757583],"domain_scores_gemma":[0.99971277,0.000093239985,0.00008133778,0.00003164007,0.00005531488,0.000025657779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033313202,0.0002889594,0.00027483277,0.00019906598,0.00011899816,0.00034977822,0.0001949761,0.0002784732,0.00034450486],"category_scores_gemma":[0.0006432977,0.00012813178,0.00010702556,0.00008894011,0.00046249203,0.0002974867,0.00022214549,0.0002889641,0.000105776286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032963657,0.000005283055,0.0005272682,0.00001992734,0.000004842205,0.00004882499,0.0000234249,0.000058874244,0.9984028,0.000047165515,0.0000047729477,0.0008238189],"study_design_scores_gemma":[0.0000057825687,0.00025460476,0.022109542,0.0000072229805,0.00003553689,0.00029295133,0.00005445917,0.0017178162,0.97480696,0.00007616779,0.00063414493,0.000004702899],"about_ca_topic_score_codex":0.0015611588,"about_ca_topic_score_gemma":0.0026682878,"teacher_disagreement_score":0.0015611588,"about_ca_system_score_codex":0.00021482995,"about_ca_system_score_gemma":0.00020456249,"threshold_uncertainty_score":0.0031041503},"labels":[],"label_agreement":null},{"id":"W4378575432","doi":"10.1016/j.nicl.2023.103444","title":"The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; University College London Hospitals NHS Foundation Trust; University College London Hospitals Biomedical Research Centre; Epilepsy Society; University of Western Australia; Medical Research Charities Group; University College London; National Imaging Facility; National Institute for Health and Care Research; UK Research and Innovation; Newton Fund; Epilepsy Research UK; UCLH Biomedical Research Centre; Academy of Medical Sciences; Wellcome Trust","keywords":"Temporal lobe; Tractography; Betweenness centrality; Diffusion MRI; Lateralization of brain function; Epilepsy; Psychology; White matter; Connectome; Feature selection; Artificial intelligence; Centrality; Pattern recognition (psychology); Cognitive psychology; Computer science; Mathematics; Statistics; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.3339156314521448,"score_gpt":0.48605804025157634,"score_spread":0.15214240879943153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378575432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99842983,0.00014127392,0.0005793059,0.00008733342,0.0000069565713,0.000008428602,0.00013796473,0.00001177015,0.0005972159],"genre_scores_gemma":[0.99955934,0.000036450507,0.00018350934,0.000007210874,0.0000051574016,0.0000062117065,0.000102267375,0.0000039818206,0.00009590333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996853,0.00008459437,0.000031829593,0.000057150348,0.00009811753,0.000043101263],"domain_scores_gemma":[0.9935702,0.0026037395,0.002473279,0.00039258547,0.0005715357,0.0003886294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009795825,0.0001866291,0.00016170608,0.00044208003,0.00018137485,0.00037856863,0.00022217685,0.00022525928,0.001228549],"category_scores_gemma":[0.0093689235,0.000045369605,0.00023449193,0.00035000674,0.0004389045,0.00045380733,0.0003240365,0.00044008868,0.00013098757],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020776181,0.00025377385,0.90559256,0.00009319505,0.00029697706,0.0007097465,0.0005926643,0.006985717,0.013917981,0.00028084955,0.0004400906,0.06875874],"study_design_scores_gemma":[0.000006068894,0.0006762369,0.9924648,0.000008014211,0.000049645547,0.00039105857,0.00013542516,0.003867561,0.0017614048,0.00041044367,0.00021726635,0.000012042039],"about_ca_topic_score_codex":0.0026380597,"about_ca_topic_score_gemma":0.0036506478,"teacher_disagreement_score":0.0026380597,"about_ca_system_score_codex":0.0005962333,"about_ca_system_score_gemma":0.00030164586,"threshold_uncertainty_score":0.0052453876},"labels":[],"label_agreement":null},{"id":"W4378746244","doi":"10.3389/fneur.2023.1167026","title":"A comparison of altered white matter microstructure in youth born with congenital heart disease or born preterm","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; McGill University; Philips (Canada); Jewish General Hospital; Montreal Children's Hospital; McGill University Health Centre","funders":"Canadian Institutes of Health Research; McGill University Health Centre; Alliance de recherche numérique du Canada; Centre hospitalier universitaire Sainte-Justine; Jewish General Hospital; McGill University","keywords":"White matter; Diffusion MRI; Medicine; Axon; Cardiology; Gestational age; Internal medicine; Magnetic resonance imaging; Anatomy; Biology; Pregnancy; Radiology; Genetics","score_opus":0.035608033584056654,"score_gpt":0.3282288594003829,"score_spread":0.2926208258163262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378746244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997292,0.0000627611,0.000049931918,0.0000036541057,0.0000012678789,0.0000031333714,0.00007338656,0.0000018141102,0.000074772135],"genre_scores_gemma":[0.9993556,0.00010002287,0.00026111584,0.000006708283,0.0000034559514,0.000009633542,0.000159417,0.0000014679656,0.000102562655],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988365,0.000013092123,0.000014563202,0.00003763061,0.000025489306,0.000025536167],"domain_scores_gemma":[0.9995882,0.00005025276,0.0001999295,0.00001994263,0.000052328407,0.00008930178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025013977,0.0002674484,0.00024219498,0.0008439127,0.00022863418,0.0003327064,0.00015389557,0.00030982232,0.0009632087],"category_scores_gemma":[0.000649862,0.00010169091,0.0001893854,0.000346822,0.00027591264,0.0002000869,0.00038643955,0.00018142916,0.0001006899],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005376317,0.00007085806,0.98131573,0.000037935944,0.000044287455,0.00094012474,0.0005558102,0.00003415373,0.010833326,0.000041003284,0.000041949475,0.0055471333],"study_design_scores_gemma":[0.0000021061062,0.00023396977,0.99772674,0.000005803954,0.0000145292515,0.00093740254,0.00029277423,0.000039115002,0.0006580626,0.00001531215,0.00007223597,0.0000018573884],"about_ca_topic_score_codex":0.0018263629,"about_ca_topic_score_gemma":0.0017522916,"teacher_disagreement_score":0.0018263629,"about_ca_system_score_codex":0.00016361533,"about_ca_system_score_gemma":0.00018142001,"threshold_uncertainty_score":0.003631413},"labels":[],"label_agreement":null},{"id":"W4379348402","doi":"10.1017/cjn.2023.205","title":"P.115 MRI based methodology for assessment of white matter neuroplasticity: preclinical validation using human motor training data","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Burnaby Hospital; University of Winnipeg","funders":"","keywords":"Diffusion MRI; White matter; Corticospinal tract; Medicine; Magnetic resonance imaging; Preclinical research; Physical medicine and rehabilitation; Nuclear medicine; Radiology; Medical physics","score_opus":0.5785829321442595,"score_gpt":0.5028159455403525,"score_spread":0.07576698660390702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379348402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17715503,0.008782801,0.7814813,0.00083447393,0.000677204,0.002543433,0.0042841365,0.0022669816,0.021974701],"genre_scores_gemma":[0.54380435,0.0064189686,0.43054077,0.00037987615,0.0001690228,0.003570783,0.0030835401,0.0007294675,0.011303252],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999049,0.00024026373,0.00007370782,0.00013818439,0.00047306292,0.000025758212],"domain_scores_gemma":[0.9973157,0.0006649046,0.00038093404,0.00039519975,0.0011664721,0.00007683892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004204621,0.00072158553,0.00032441513,0.0011452297,0.00031243436,0.0007798716,0.0006589972,0.0005104019,0.00691642],"category_scores_gemma":[0.004794819,0.00032342755,0.00032185632,0.0008972525,0.00086104183,0.00058219157,0.0005580984,0.000841438,0.003185397],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011663836,0.00081064506,0.024433991,0.0014372139,0.00025777434,0.00061512704,0.00032576968,0.008039723,0.5541918,0.004442159,0.0098425215,0.3944368],"study_design_scores_gemma":[0.0003918275,0.0147546,0.20097028,0.0011037881,0.00058555306,0.010297178,0.00034798513,0.09075031,0.5714974,0.00942504,0.09960633,0.00026974402],"about_ca_topic_score_codex":0.0016376871,"about_ca_topic_score_gemma":0.0019800984,"teacher_disagreement_score":0.00691642,"about_ca_system_score_codex":0.00029120175,"about_ca_system_score_gemma":0.00069644966,"threshold_uncertainty_score":0.023137748},"labels":[],"label_agreement":null},{"id":"W4379390288","doi":"10.1101/2023.06.01.543240","title":"A population-averaged structural connectomic brain atlas of 422 HCP-Aging subjects","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Alliance de recherche numérique du Canada","keywords":"Diffusion MRI; Connectome; Human Connectome Project; Population; White matter; Connectomics; Segmentation; Neuroscience; Artificial intelligence; Computer science; Deep brain stimulation; Orientation (vector space); Spatial normalization; Brain atlas; Pattern recognition (psychology); Voxel; Medicine; Psychology; Magnetic resonance imaging; Parkinson's disease; Pathology; Functional connectivity","score_opus":0.04262580790053069,"score_gpt":0.30554831055006126,"score_spread":0.26292250264953054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379390288","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13724838,0.00054345455,0.028876498,0.00030074356,0.000068661466,0.00032348817,0.8228564,0.003659681,0.006122716],"genre_scores_gemma":[0.15383546,0.00041394634,0.02536723,0.00013396592,0.000059428537,0.0013177514,0.8128949,0.0006747507,0.005302494],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99976236,0.000033069547,0.000021149861,0.00011829206,0.000043723925,0.000021499156],"domain_scores_gemma":[0.999546,0.000091673974,0.000051346964,0.00015072941,0.00012493785,0.00003526327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044087766,0.0005928091,0.000549711,0.0017094893,0.00040610225,0.0005789094,0.00084824045,0.00057018007,0.020887842],"category_scores_gemma":[0.0013468324,0.00029485338,0.0005310425,0.001939026,0.0002516811,0.0003723382,0.0007047162,0.00039970584,0.0077157146],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017375484,0.00036681417,0.06729795,0.0013839884,0.0007948798,0.003659382,0.0011389134,0.017314844,0.035093494,0.00659195,0.65159106,0.2130292],"study_design_scores_gemma":[0.00055088144,0.00048644192,0.4967721,0.0004682525,0.00064198574,0.015833091,0.0009389325,0.031199275,0.015901454,0.023695167,0.41318,0.0003324159],"about_ca_topic_score_codex":0.0118573485,"about_ca_topic_score_gemma":0.017977241,"teacher_disagreement_score":0.020887842,"about_ca_system_score_codex":0.0005110579,"about_ca_system_score_gemma":0.00075002265,"threshold_uncertainty_score":0.06987685},"labels":[],"label_agreement":null},{"id":"W4379928270","doi":"10.1016/j.cortex.2023.04.018","title":"Effects of anterior temporal lobe resection on cortical morphology","year":2023,"lang":"es","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; University College London Hospitals NHS Foundation Trust; University College London; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Instituto Serrapilheira; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Imaging Facility; UK Research and Innovation","keywords":"Supramarginal gyrus; Temporal lobe; Psychology; Epilepsy surgery; Anterior temporal lobectomy; Orbitofrontal cortex; Postcentral gyrus; Temporal cortex; Occipital lobe; Cortex (anatomy); Frontal lobe; Neuroscience; Superior temporal gyrus; Anatomy; Epilepsy; Functional magnetic resonance imaging; Medicine; Prefrontal cortex; Cognition","score_opus":0.04304128046949076,"score_gpt":0.37140187266760205,"score_spread":0.3283605921981113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379928270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981665,0.000091016605,0.0014129434,0.000021167494,0.0000019776398,0.0000045951874,0.0000973235,0.00001875964,0.00018578777],"genre_scores_gemma":[0.99904937,0.000052482068,0.0006413986,0.000005693939,0.0000031566724,0.0000037959046,0.00015928078,0.000008673033,0.0000760901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998097,0.000063763386,0.000020714548,0.00004937347,0.00004142197,0.000014945406],"domain_scores_gemma":[0.9988863,0.00043319634,0.00038409166,0.00018841297,0.00006179011,0.000046124307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004519241,0.00028365664,0.00020367559,0.0005072266,0.00014066845,0.0003133125,0.0001442655,0.00022424525,0.000778882],"category_scores_gemma":[0.0025667555,0.00016734161,0.0003574021,0.000405504,0.00047431866,0.000363029,0.00027801984,0.00020049808,0.00015921768],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017135334,0.000112982765,0.68579173,0.00015596766,0.00075640914,0.0014583005,0.00075956853,0.013260261,0.22554003,0.00031334936,0.0003605934,0.06977724],"study_design_scores_gemma":[0.0000052855034,0.00016426576,0.98880285,0.0000026404832,0.000039370618,0.00090017467,0.000080475074,0.0058253356,0.003778509,0.00026908272,0.00012401641,0.000007957851],"about_ca_topic_score_codex":0.002171247,"about_ca_topic_score_gemma":0.0054620584,"teacher_disagreement_score":0.002171247,"about_ca_system_score_codex":0.00016947716,"about_ca_system_score_gemma":0.00011767668,"threshold_uncertainty_score":0.0043171644},"labels":[],"label_agreement":null},{"id":"W4380185499","doi":"10.1055/s-0043-1767469","title":"Asymmetric hearing loss is associated with altered white matter mesostructure and cortical measures in temporal and occipital regions","year":2023,"lang":"en","type":"article","venue":"Laryngo-Rhino-Otologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Audiology; Hearing loss; Neuroscience; Structural integrity; Diffusion imaging; Occipital region; Magnetic resonance imaging; Medicine; Psychology; Anatomy; Radiology","score_opus":0.08130976247714956,"score_gpt":0.3346195078895302,"score_spread":0.25330974541238066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380185499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998968,0.00031521014,0.00017261553,0.000030106277,0.0000040127575,0.0000037588352,0.00008746495,0.000007211655,0.0004115152],"genre_scores_gemma":[0.9996333,0.00008105581,0.00008906876,0.00001532452,0.0000072333596,0.000002412432,0.00005787971,0.0000017537666,0.00011192958],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999032,0.000011019947,0.000010403312,0.000024431109,0.000027710115,0.000023338709],"domain_scores_gemma":[0.9994382,0.00006906287,0.00035508623,0.00002793417,0.000032285694,0.00007737124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001638378,0.0003236302,0.00025833008,0.0010824244,0.00021254782,0.00034305252,0.00017827828,0.00017028887,0.0017701944],"category_scores_gemma":[0.0006810562,0.000097048374,0.00013240926,0.00033405493,0.000458072,0.00026645145,0.00031609315,0.0001714422,0.00018456252],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002865479,0.0002156416,0.795446,0.00022086278,0.00026018193,0.0061603263,0.0004499349,0.00029027782,0.15488946,0.00030325862,0.00041278443,0.038485795],"study_design_scores_gemma":[0.000014300439,0.00013419389,0.9944193,0.000007252378,0.000026203761,0.0030038925,0.00018808305,0.00018017614,0.0017989884,0.00014099674,0.00008235796,0.0000042198144],"about_ca_topic_score_codex":0.0021339485,"about_ca_topic_score_gemma":0.0022391586,"teacher_disagreement_score":0.0021339485,"about_ca_system_score_codex":0.00016946957,"about_ca_system_score_gemma":0.00012293243,"threshold_uncertainty_score":0.0059219003},"labels":[],"label_agreement":null},{"id":"W4380272571","doi":"10.1101/2023.06.09.544263","title":"Gauge equivariant convolutional neural networks for diffusion mri","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Equivariant map; Convolutional neural network; Gauge (firearms); Diffusion MRI; Diffusion; Physics; Computer science; Quantum electrodynamics; Statistical physics; Mathematics; Artificial intelligence; Geography; Pure mathematics; Medicine; Magnetic resonance imaging; Quantum mechanics; Radiology","score_opus":0.060881123169515,"score_gpt":0.3081433741238512,"score_spread":0.24726225095433618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380272571","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041808687,0.0008408309,0.9532067,0.00037813743,0.000059971273,0.000027008959,0.00028275079,0.0013852001,0.0020108025],"genre_scores_gemma":[0.72939,0.0007661898,0.26155475,0.000178186,0.000070339804,0.0000868806,0.0009332327,0.00023524546,0.0067851306],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981445,0.000047258698,0.0000098072815,0.000047819234,0.000051106537,0.000029619576],"domain_scores_gemma":[0.9995919,0.0001711667,0.000050816223,0.000067853354,0.00009235899,0.000026030139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062299456,0.0006898814,0.00043401073,0.00041201993,0.00017066045,0.000408082,0.000720701,0.0005927133,0.0012239902],"category_scores_gemma":[0.0022665055,0.00028206743,0.00040758247,0.00049073505,0.0004946197,0.0005328275,0.0006787879,0.001031226,0.0004178283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006803545,0.00003523552,0.0009092163,0.0000513899,0.00005522877,0.00006488268,0.000035007488,0.86398417,0.0063725538,0.023923423,0.0023304322,0.10217033],"study_design_scores_gemma":[0.0000012066597,0.0000048639054,0.000072958625,0.0000020962132,0.0000020080877,0.0000040282143,0.0000012157467,0.995589,0.0005964971,0.0034185888,0.0003056122,0.0000018870644],"about_ca_topic_score_codex":0.009625808,"about_ca_topic_score_gemma":0.012200182,"teacher_disagreement_score":0.009625808,"about_ca_system_score_codex":0.00090888876,"about_ca_system_score_gemma":0.0006825829,"threshold_uncertainty_score":0.019139588},"labels":[],"label_agreement":null},{"id":"W4380716205","doi":"10.1016/j.psyneuen.2023.106193","title":"Sex/gender, sexual orientation, and gender-affirming hormones are associated with white matter microstructure in a Thai sample","year":2023,"lang":"en","type":"article","venue":"Psychoneuroendocrinology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Fractional anisotropy; Sexual orientation; White matter; Diffusion MRI; Transgender; Hormone; Testosterone (patch); Transgender women; Psychology; Physiology; Demography; Developmental psychology; Internal medicine; Medicine; Magnetic resonance imaging; Men who have sex with men; Social psychology; Psychoanalysis; Immunology","score_opus":0.07699350361168032,"score_gpt":0.35077397707625113,"score_spread":0.2737804734645708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380716205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999686,0.000046309964,0.000027696278,0.000012430563,0.0000021399605,0.0000024526394,0.000036726055,4.4183412e-7,0.00018576207],"genre_scores_gemma":[0.9995216,0.000063506784,0.000057436126,0.000020779304,0.0000068237628,0.00000392365,0.00008124246,0.0000014067753,0.00024328372],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989414,0.000018951348,0.000015121846,0.000030195752,0.000017130476,0.000024421313],"domain_scores_gemma":[0.9997297,0.000033950888,0.000101922764,0.000016883858,0.0000396432,0.000077875346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016928658,0.00027699355,0.00021827056,0.00038558693,0.0006590849,0.0004454738,0.00017737638,0.0002384967,0.0018292617],"category_scores_gemma":[0.00051608804,0.00027523556,0.0002532167,0.00057506753,0.00037340206,0.00030495386,0.00032053105,0.00033432222,0.00015203201],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000248434,0.00013680776,0.992816,0.000028977136,0.00008972637,0.0010040303,0.00150179,0.000027556855,0.0018939044,0.000051404437,0.000098795725,0.0021026211],"study_design_scores_gemma":[0.000006123201,0.00014825357,0.99629813,0.000008161951,0.00004287628,0.0011637316,0.0019273233,0.00010360354,0.00008918824,0.000073670424,0.00013378976,0.000005168151],"about_ca_topic_score_codex":0.008478991,"about_ca_topic_score_gemma":0.010238203,"teacher_disagreement_score":0.008478991,"about_ca_system_score_codex":0.00014686337,"about_ca_system_score_gemma":0.00024755343,"threshold_uncertainty_score":0.016859293},"labels":[],"label_agreement":null},{"id":"W4380793055","doi":"10.1016/j.neurobiolaging.2023.06.007","title":"Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis","year":2023,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; White (mutation); Fiber; Psychology; Medicine; Biology; Materials science; Genetics; Composite material; Magnetic resonance imaging","score_opus":0.04124017950903353,"score_gpt":0.3142781312652037,"score_spread":0.2730379517561702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380793055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962291,0.00040225155,0.0027193325,0.000024838073,0.000012612281,0.000007848878,0.00027296713,0.00003236571,0.00029866054],"genre_scores_gemma":[0.99622536,0.00029170257,0.0026203506,0.000021216645,0.000010818188,0.000010242902,0.00027207725,0.000027755475,0.0005205216],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999379,0.0000066535636,0.0000041029984,0.000029284312,0.000011675097,0.000010440826],"domain_scores_gemma":[0.9997774,0.000043182506,0.00006156582,0.000037287045,0.000057801386,0.000022753107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003918499,0.00029976977,0.00019645819,0.0007694106,0.00024088552,0.00030628924,0.0002101412,0.0002639045,0.0014155984],"category_scores_gemma":[0.00071737904,0.00012300714,0.00014154316,0.00038105264,0.00030741905,0.00056178926,0.00025840054,0.00018721654,0.00014981155],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005263885,0.00016153783,0.12724899,0.00022992745,0.0005672572,0.0007811656,0.0007911642,0.0014425486,0.7776155,0.0011475576,0.0011646379,0.083585866],"study_design_scores_gemma":[0.00002997432,0.00039692808,0.96183395,0.00002263869,0.00027419595,0.0013216143,0.00023432341,0.004212646,0.029761774,0.0009965885,0.0008903427,0.000025011279],"about_ca_topic_score_codex":0.0048250463,"about_ca_topic_score_gemma":0.008439839,"teacher_disagreement_score":0.0048250463,"about_ca_system_score_codex":0.00018439682,"about_ca_system_score_gemma":0.00015851132,"threshold_uncertainty_score":0.009593964},"labels":[],"label_agreement":null},{"id":"W4380869621","doi":"10.1097/j.pain.0000000000002936","title":"Challenges of brain white matter imaging: proceed with caution","year":2023,"lang":"en","type":"letter","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"White (mutation); Mount; Brain research; White paper; White matter; Dental research; Research centre; Medicine; Library science; Psychology; Geography; Dentistry; Engineering; Neuroscience; Archaeology; Magnetic resonance imaging","score_opus":0.06958421053355707,"score_gpt":0.3300524511057817,"score_spread":0.2604682405722246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380869621","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00038285172,0.014438281,0.0036006945,0.9668182,0.011778822,0.000032284126,0.000047884063,0.00011266269,0.002788294],"genre_scores_gemma":[0.013055814,0.034927197,0.022294745,0.7959942,0.1283348,0.00023625541,0.0000752788,0.00022052908,0.0048611853],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.98966205,0.0039254,0.0021266597,0.0008159647,0.0032123122,0.00025768476],"domain_scores_gemma":[0.930005,0.04841838,0.0020631151,0.0037774679,0.013494795,0.0022412327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.028944602,0.0011727639,0.0026287106,0.0032007196,0.0029862414,0.0061261537,0.0051886225,0.024072213,0.004686309],"category_scores_gemma":[0.0891201,0.0009609633,0.0017874459,0.0011760069,0.013001679,0.01326043,0.0035176908,0.052421927,0.008546262],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016765768,0.00009888521,0.0023548359,0.0012169987,0.00020561428,0.012746101,0.0014569727,0.00046557275,0.001558661,0.034602962,0.8037135,0.14141218],"study_design_scores_gemma":[0.00015655637,0.000092603485,0.0021560628,0.004771193,0.00013544678,0.029629672,0.0027091745,0.001441972,0.0008255502,0.22037801,0.7375023,0.00020152815],"about_ca_topic_score_codex":0.004365873,"about_ca_topic_score_gemma":0.009725876,"teacher_disagreement_score":0.028944602,"about_ca_system_score_codex":0.0020880955,"about_ca_system_score_gemma":0.0040257596,"threshold_uncertainty_score":0.15307552},"labels":[],"label_agreement":null},{"id":"W4380884179","doi":"10.1002/alz.060795","title":"Assessing neuroinflammatory differences in FTLD‐Tau vs FTLD‐TDP using free water diffusion","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkinson's Clinic of Eastern Toronto & Movement Disorders Centre; University of Toronto; University Health Network; Ontario Brain Institute; Baycrest Hospital; Toronto Western Hospital; Occupational Cancer Research Centre","funders":"","keywords":"Frontotemporal lobar degeneration; Neuroinflammation; Primary progressive aphasia; Diffusion MRI; Psychology; Neuroscience; Frontotemporal dementia; Pathological; Aphasia; Pathology; Medicine; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.13562524144025834,"score_gpt":0.36610717679689636,"score_spread":0.23048193535663802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380884179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927376,0.0019035097,0.0036541289,0.00006988364,0.00002973056,0.000074599055,0.0006820291,0.0000836152,0.00076502975],"genre_scores_gemma":[0.9926703,0.0005442242,0.0049873497,0.0000766491,0.000013496482,0.00013569901,0.0006326214,0.000030764568,0.000908987],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99977976,0.00003731815,0.000031761883,0.000068932604,0.000047642647,0.000034600158],"domain_scores_gemma":[0.99965036,0.000081389495,0.00010514819,0.00002120711,0.00007187497,0.00007009298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007612754,0.0006422636,0.00052304677,0.0010179324,0.00039106418,0.0006613945,0.00032991642,0.00073063845,0.0022802935],"category_scores_gemma":[0.0010877708,0.00015805416,0.00035744978,0.0004211429,0.00045452255,0.0005545785,0.0003877261,0.00037522925,0.00033358776],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03133479,0.0011435614,0.3105827,0.0011905556,0.00111979,0.002654125,0.0012285119,0.0032687634,0.537332,0.0010389778,0.001805706,0.1073005],"study_design_scores_gemma":[0.0005145592,0.006156562,0.79044896,0.0002479694,0.001261864,0.007477231,0.0014912151,0.021662824,0.1601779,0.00489931,0.0055189403,0.00014265157],"about_ca_topic_score_codex":0.0031702043,"about_ca_topic_score_gemma":0.0031450118,"teacher_disagreement_score":0.0031702043,"about_ca_system_score_codex":0.000504409,"about_ca_system_score_gemma":0.00025476803,"threshold_uncertainty_score":0.0076283216},"labels":[],"label_agreement":null},{"id":"W4380990775","doi":"10.1016/j.neuroimage.2023.120231","title":"Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Health and Medical Research Council; National Institute of Mental Health; Horizon 2020 Framework Programme; Narodowa Agencja Wymiany Akademickiej; Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Natural Sciences and Engineering Research Council of Canada; Centre Hospitalier Universitaire Vaudois; Centre d'Imagerie BioMédicale; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Université de Lausanne; Hôpitaux Universitaires de Genève; Nvidia; Université de Genève; Academic Computer Centre Cyfronet, AGH University of Science and Technology; Polska Akademia Nauk; National Natural Science Foundation of China; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute on Drug Abuse; École Polytechnique Fédérale de Lausanne; Fundacja na rzecz Nauki Polskiej; European Commission; Consejo Nacional de Ciencia y Tecnología; National Institute of Allergy and Infectious Diseases; Agence Nationale de la Recherche; Ministerstwo Edukacji i Nauki; Infrastruktura PL-Grid; National Science Foundation","keywords":"Diffusion MRI; Computer science; Ground truth; Tractography; Diffusion; Monte Carlo method; Binary number; Task (project management); Scale (ratio); Functional connectivity; Artificial intelligence; Data mining; Algorithm; Pattern recognition (psychology); Magnetic resonance imaging; Mathematics; Statistics; Physics; Neuroscience; Psychology","score_opus":0.09610758939185464,"score_gpt":0.35369401888435575,"score_spread":0.2575864294925011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380990775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76257,0.017138084,0.122982524,0.011399421,0.0031850273,0.0010578715,0.027771415,0.01488957,0.03900608],"genre_scores_gemma":[0.86578614,0.0011485493,0.06436528,0.0016135323,0.0004865293,0.0004197512,0.053356636,0.00298212,0.009841396],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99324375,0.0033156637,0.00043705115,0.0015064783,0.0010296585,0.0004673858],"domain_scores_gemma":[0.9383838,0.04528628,0.0017564122,0.008740194,0.0039481726,0.0018851626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011153292,0.0022087125,0.0018920512,0.0014129633,0.0013992405,0.0022886286,0.002114542,0.0033525021,0.0060438286],"category_scores_gemma":[0.07818089,0.0004945125,0.001811836,0.0011118234,0.0019741585,0.0035292762,0.002864514,0.0028815481,0.003665688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011456677,0.0024486776,0.064967245,0.0041172844,0.0027119282,0.0028854522,0.0017051019,0.21229415,0.008265278,0.020178795,0.32434994,0.3446195],"study_design_scores_gemma":[0.0016367394,0.0031598401,0.039763935,0.0006563111,0.0008087821,0.003376202,0.0019095106,0.8148633,0.011396469,0.05566747,0.06648448,0.00027688613],"about_ca_topic_score_codex":0.01121361,"about_ca_topic_score_gemma":0.013215788,"teacher_disagreement_score":0.01121361,"about_ca_system_score_codex":0.0013540605,"about_ca_system_score_gemma":0.0018689273,"threshold_uncertainty_score":0.058984995},"labels":[],"label_agreement":null},{"id":"W4381108580","doi":"10.1016/j.psychres.2023.115319","title":"Polygenic risk for schizophrenia and the language network: Putative compensatory reorganization in unaffected siblings","year":2023,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Western University","funders":"Xiangya Hospital, Central South University; Canada First Research Excellence Fund; Fonds de Recherche du Québec - Santé; Natural Science Foundation of Changzhou City; National Natural Science Foundation of China; McGill University","keywords":"Schizophrenia (object-oriented programming); Polygenic risk score; Cognition; Psychology; Developmental psychology; Neuroscience; Biology; Psychiatry; Genetics; Gene","score_opus":0.07738195335874927,"score_gpt":0.4386258022331791,"score_spread":0.36124384887442984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381108580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991103,0.00003533564,0.0002456113,0.00005482341,0.0000030145231,0.000002902034,0.00012079702,0.000007569849,0.00041966035],"genre_scores_gemma":[0.9994305,0.000029478484,0.000225397,0.000012709093,0.0000028480567,0.000004393825,0.00004885293,0.000007057315,0.00023881707],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996964,0.000079686164,0.000026183323,0.00009559385,0.000057059813,0.000045022723],"domain_scores_gemma":[0.9993166,0.00023014797,0.00018395532,0.00008452117,0.000046418754,0.00013833941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034462067,0.00076678477,0.00038180532,0.00096062693,0.00074513804,0.00048294387,0.0004106892,0.0005164748,0.0056463536],"category_scores_gemma":[0.0022447607,0.00035539118,0.00026606,0.0005315631,0.00079917756,0.00044790233,0.00047441517,0.000489823,0.00023669799],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034243427,0.0005672234,0.6605771,0.00014475947,0.0005714373,0.070703164,0.00672697,0.0023951156,0.2245765,0.0066285515,0.00090139994,0.022783421],"study_design_scores_gemma":[0.0000662037,0.00033334692,0.9656267,0.000027056763,0.00021031967,0.020356605,0.0014971271,0.002331465,0.005439239,0.0036797149,0.00039666193,0.000035542595],"about_ca_topic_score_codex":0.0075468873,"about_ca_topic_score_gemma":0.0064412295,"teacher_disagreement_score":0.0075468873,"about_ca_system_score_codex":0.0003647041,"about_ca_system_score_gemma":0.000587885,"threshold_uncertainty_score":0.01888889},"labels":[],"label_agreement":null},{"id":"W4381249848","doi":"10.3390/brainsci13060963","title":"Cortical Structure Differences in Relation to Age, Sexual Attractions, and Gender Dysphoria in Adolescents: An Examination of Mean Diffusivity and T1 Relaxation Time","year":2023,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; McGill University; Douglas Mental Health University Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Kids Brain Health Network; University of Toronto; Department of Psychiatry, University of Toronto; Fondation Brain Canada; Centre for Addiction and Mental Health Foundation; Government of Ontario; Centre for Addiction and Mental Health","keywords":"Relaxation (psychology); Psychology; Gender dysphoria; Diffusion MRI; Neuroscience; Gender identity; Medicine; Social psychology; Magnetic resonance imaging","score_opus":0.10824259226043619,"score_gpt":0.37907665755997794,"score_spread":0.27083406529954174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381249848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995516,0.00016751266,0.000049674385,0.000010513474,9.378452e-7,0.0000028302948,0.000064002284,0.0000019737097,0.0001509934],"genre_scores_gemma":[0.99966633,0.00009220402,0.00010420173,0.000006101656,0.0000024409615,0.0000044974786,0.00005920849,0.0000011022481,0.000063967105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999895,0.000019710926,0.000010008101,0.000028519671,0.000023421037,0.00002344591],"domain_scores_gemma":[0.9994542,0.00009951531,0.00029300014,0.000027059257,0.00004999031,0.000076257675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022497146,0.00018666932,0.00016144078,0.0009621172,0.0001514069,0.00032610298,0.00010972538,0.00026309505,0.0009308064],"category_scores_gemma":[0.0010057483,0.00017057423,0.00024049767,0.00043983138,0.0002406828,0.0001971589,0.0002540108,0.00020244152,0.000099445126],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009284986,0.000021187703,0.9933041,0.000017539041,0.00005799147,0.00024936267,0.00024664256,0.000052198222,0.0030882407,0.000031075815,0.000038700375,0.0028000942],"study_design_scores_gemma":[5.184936e-7,0.000016355649,0.99958974,0.0000015528923,0.000005674689,0.00016139797,0.00007436143,0.00003944187,0.00007897109,0.000008911522,0.000022403048,6.4392214e-7],"about_ca_topic_score_codex":0.0033559785,"about_ca_topic_score_gemma":0.0048075346,"teacher_disagreement_score":0.0033559785,"about_ca_system_score_codex":0.0001738474,"about_ca_system_score_gemma":0.00018040689,"threshold_uncertainty_score":0.006672919},"labels":[],"label_agreement":null},{"id":"W4381715047","doi":"10.1002/hbm.26402","title":"Striatonigrostriatal connectivity‐based cross‐species parcellation of human and macaque substantia nigra","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Biotechnology and Biological Sciences Research Council; Fundo para o Desenvolvimento das Ciências e da Tecnologia; Universidade de Macau; Wellcome Trust; Fondation Brain Canada","keywords":"Substantia nigra; Connectome; Macaque; Neuroscience; Pars compacta; Biology; Voxel; Functional connectivity; Computer science; Artificial intelligence","score_opus":0.15920522327381417,"score_gpt":0.3919901970006795,"score_spread":0.23278497372686532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381715047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8757033,0.0012188181,0.11448997,0.0001424995,0.000055303484,0.00017624807,0.0017505405,0.0009545981,0.0055086743],"genre_scores_gemma":[0.94597423,0.00031831162,0.04981711,0.00008481242,0.00001655669,0.00023704841,0.0019265211,0.00029570583,0.0013296629],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995716,0.000054499593,0.00003185792,0.00021155922,0.00008250134,0.000048035577],"domain_scores_gemma":[0.9995222,0.00007075542,0.00009696915,0.00012067338,0.00015918455,0.000030141657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008665725,0.00036368403,0.0003275612,0.0019227727,0.00067910826,0.0008220875,0.00043947707,0.00047637988,0.0022526165],"category_scores_gemma":[0.0019375788,0.00024582515,0.00051881804,0.00093148416,0.0006251679,0.0006221893,0.0009490403,0.0003797799,0.00036557834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070058584,0.00008332299,0.12819046,0.0007317856,0.00083385524,0.0011967878,0.005520415,0.0061070677,0.6491871,0.0077678617,0.0029506641,0.19673006],"study_design_scores_gemma":[0.000036737594,0.00032978482,0.800655,0.00014270439,0.0006812014,0.0042564636,0.0018216772,0.043732673,0.117981225,0.009918486,0.020335129,0.00010887638],"about_ca_topic_score_codex":0.0061441627,"about_ca_topic_score_gemma":0.018290404,"teacher_disagreement_score":0.0061441627,"about_ca_system_score_codex":0.00040246625,"about_ca_system_score_gemma":0.0005042564,"threshold_uncertainty_score":0.012216806},"labels":[],"label_agreement":null},{"id":"W4382200459","doi":"10.1055/s-0043-1766831","title":"Asymmetrischer Hörverlust ist mit veränderter Mesostruktur der weißen und grauen Substanz der temporalen und okzipitalen Region assoziiert","year":2023,"lang":"de","type":"article","venue":"Laryngo-Rhino-Otologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Art","score_opus":0.13940977563941614,"score_gpt":0.3903717349628948,"score_spread":0.25096195932347864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382200459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99767643,0.0006277033,0.00091800524,0.000032561074,0.000009559837,0.000019207315,0.00009415859,0.000029534373,0.0005929682],"genre_scores_gemma":[0.9983662,0.00024766178,0.00070919597,0.00002132108,0.000007934267,0.000013856002,0.000072454044,0.000006896613,0.00055449625],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998733,0.000013783155,0.000015337908,0.000041150273,0.0000350571,0.000021399748],"domain_scores_gemma":[0.9997055,0.00004298178,0.00016828273,0.000020903386,0.000027460479,0.000034872068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002457361,0.000426493,0.00023946984,0.0007563745,0.00016242264,0.0003513942,0.00015276455,0.00028855773,0.0022448301],"category_scores_gemma":[0.0003846678,0.00023471897,0.0002057534,0.00035986988,0.00060912,0.0003439245,0.00037580813,0.00023437013,0.0002995218],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021492564,0.00007805306,0.08694176,0.00020389623,0.00013232135,0.004526583,0.0003401135,0.0002053007,0.8822215,0.00028505895,0.00016017848,0.022756033],"study_design_scores_gemma":[0.000055383985,0.0014139883,0.85846126,0.000026700542,0.00017744607,0.021685284,0.00092677335,0.001158676,0.113443434,0.0007370186,0.0018824792,0.000031565844],"about_ca_topic_score_codex":0.00068113185,"about_ca_topic_score_gemma":0.0008914181,"teacher_disagreement_score":0.0022448301,"about_ca_system_score_codex":0.00024274449,"about_ca_system_score_gemma":0.00019369958,"threshold_uncertainty_score":0.0075097084},"labels":[],"label_agreement":null},{"id":"W4382894678","doi":"10.1101/2023.06.30.547294","title":"Variations in perfusion detectable in advance of microstructure in white matter aging","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"","keywords":"White matter; Microstructure; Perfusion; White (mutation); Psychology; Medicine; Internal medicine; Materials science; Biology; Composite material; Magnetic resonance imaging; Radiology; Genetics","score_opus":0.022167844420336084,"score_gpt":0.2790912591522365,"score_spread":0.2569234147319004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382894678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909809,0.00037798812,0.0063292007,0.00006459415,0.000008759794,0.000008867507,0.0010990665,0.00010186188,0.0010287581],"genre_scores_gemma":[0.9967435,0.00008924981,0.0024661932,0.000017757951,0.000008726481,0.000006801825,0.00031415813,0.000015240677,0.00033846492],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999014,0.000021751417,0.000007350718,0.000037990572,0.000018220497,0.000013216677],"domain_scores_gemma":[0.9993247,0.00013480445,0.00031406735,0.00010690761,0.00006763463,0.00005193622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005419248,0.0002177698,0.00021193185,0.0006585496,0.00012571012,0.00040051006,0.00009083297,0.00021959108,0.002616618],"category_scores_gemma":[0.0015836036,0.00012913032,0.00014402538,0.00055170245,0.00033176946,0.00033324605,0.00026731915,0.0002174196,0.00025435735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011553509,0.000080892176,0.68286514,0.00016683042,0.00031153669,0.000290438,0.0003445166,0.0031536643,0.27278572,0.0019655093,0.0012173855,0.03566298],"study_design_scores_gemma":[0.0000044627423,0.00011073221,0.9857496,0.000008661768,0.000029889787,0.00032228619,0.000049047838,0.0026199915,0.009162766,0.0014733927,0.00046065965,0.000008648728],"about_ca_topic_score_codex":0.0017746658,"about_ca_topic_score_gemma":0.0023234088,"teacher_disagreement_score":0.002616618,"about_ca_system_score_codex":0.00013629017,"about_ca_system_score_gemma":0.0002384951,"threshold_uncertainty_score":0.008753419},"labels":[],"label_agreement":null},{"id":"W4382933704","doi":"10.1101/2023.06.30.547270","title":"Delineation of the Trigeminal-Lateral Parabrachial-Central Amygdala Tract in Humans: An Ultra-High Field Diffusion MRI Study","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; University of Toronto","keywords":"Neuroscience; Psychology; Neuropsychology; Connectome; Trigeminal nerve; Diffusion MRI; Medicine; Audiology; Functional connectivity; Magnetic resonance imaging; Anesthesia; Cognition; Radiology","score_opus":0.04253121338777522,"score_gpt":0.31153391889512555,"score_spread":0.26900270550735034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382933704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896291,0.0005684812,0.008489524,0.000071512746,0.000005534687,0.00003734341,0.00016053063,0.000020557287,0.001017352],"genre_scores_gemma":[0.99616903,0.00020080489,0.0029319644,0.000023679007,0.000006147337,0.000017468283,0.00010132506,0.000014642056,0.00053485145],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989974,0.000020467074,0.000005534689,0.000045143508,0.000014631916,0.000014470307],"domain_scores_gemma":[0.99984384,0.000039043618,0.000045089484,0.000029248176,0.000023082532,0.000019637158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004568053,0.000212223,0.00017575413,0.00042130574,0.0002670629,0.00033688988,0.00019067367,0.0004026512,0.0020206335],"category_scores_gemma":[0.0007443289,0.00021971842,0.00011170858,0.00018606479,0.00052321085,0.00039548712,0.00023505178,0.000194513,0.00029513743],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015803656,0.00040262844,0.20126773,0.00048898044,0.00034569998,0.0076982975,0.003274347,0.0031344525,0.70034444,0.003215106,0.0010820638,0.07716597],"study_design_scores_gemma":[0.00005160484,0.0009902659,0.9409874,0.00006797821,0.00018657632,0.020192344,0.00079437875,0.008949862,0.019450996,0.0024245963,0.005850972,0.00005295345],"about_ca_topic_score_codex":0.002414741,"about_ca_topic_score_gemma":0.0063471803,"teacher_disagreement_score":0.002414741,"about_ca_system_score_codex":0.00017098524,"about_ca_system_score_gemma":0.00018735656,"threshold_uncertainty_score":0.0067596436},"labels":[],"label_agreement":null},{"id":"W4383199238","doi":"10.1162/netn_a_00327","title":"Epileptogenic networks in extra temporal lobe epilepsy","year":2023,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; National Imaging Facility; UK Research and Innovation; Medical Research Charities Group; Wellcome Trust","keywords":"Temporal lobe; Epilepsy; Abnormality; Epilepsy surgery; Fractional anisotropy; Connection (principal bundle); Medicine; Neuroscience; Diffusion MRI; Surgery; Psychology; Magnetic resonance imaging; Radiology; Mathematics; Psychiatry; Geometry","score_opus":0.08547255297895016,"score_gpt":0.35815739773133254,"score_spread":0.27268484475238236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383199238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992379,0.00008746005,0.00025049687,0.000019836418,7.959456e-7,0.0000021596338,0.00008681486,0.0000023267228,0.00031215386],"genre_scores_gemma":[0.9997459,0.000038935465,0.000073997944,0.0000032607568,0.0000014882152,0.0000016120841,0.00007301347,5.8168285e-7,0.0000612667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999138,0.000023659015,0.000007505498,0.000022361999,0.000015532143,0.000017144788],"domain_scores_gemma":[0.9994267,0.0001262972,0.00030935364,0.000045965877,0.000039683,0.000051979576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021888225,0.00017124173,0.00012695693,0.0007483631,0.00017819073,0.00029755224,0.00012627165,0.00012876194,0.0016243336],"category_scores_gemma":[0.001125972,0.00008111532,0.000111945184,0.0004714037,0.0003070942,0.0004899472,0.0003455214,0.00016021839,0.000108429595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000558557,0.00006167989,0.9593909,0.000066939356,0.00019302643,0.002005379,0.00058394426,0.0017836482,0.021406427,0.000977848,0.00025243527,0.01271918],"study_design_scores_gemma":[0.0000060162083,0.000066421824,0.99531615,0.000005031349,0.000022775894,0.0017578393,0.00018165862,0.00088808173,0.00072236895,0.00084642007,0.00018357571,0.0000036631325],"about_ca_topic_score_codex":0.001640465,"about_ca_topic_score_gemma":0.0037814693,"teacher_disagreement_score":0.001640465,"about_ca_system_score_codex":0.00019342294,"about_ca_system_score_gemma":0.00014892423,"threshold_uncertainty_score":0.0054339767},"labels":[],"label_agreement":null},{"id":"W4383217072","doi":"10.1093/braincomms/fcad195","title":"Longitudinal changes in hippocampal texture from healthy aging to Alzheimer’s disease","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; Eisai Incorporated; Fonds de Recherche du Québec - Santé; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Merck; Alzheimer's Drug Discovery Foundation; Janssen Alzheimer Immunotherapy Research And Development; AbbVie; Fujirebio Europe; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Hippocampal formation; Neuroimaging; Dementia; Neuroscience; Alzheimer's disease; Psychology; Neuropathology; Hippocampus; Cognitive decline; Atrophy; Cognition; Disease; Medicine; Pathology; Audiology","score_opus":0.2447787720848473,"score_gpt":0.451645994272378,"score_spread":0.2068672221875307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383217072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990472,0.0001424931,0.00026493263,0.000010321801,0.0000029104206,0.0000056532267,0.00034555327,0.000008930474,0.00017198852],"genre_scores_gemma":[0.9992731,0.000042175023,0.00024379567,0.0000062531735,0.0000033312972,0.000006026036,0.00030675274,0.0000023471305,0.000116201474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978095,0.000037760976,0.000021881151,0.00006489227,0.00006126003,0.00003317779],"domain_scores_gemma":[0.99900997,0.00013213215,0.00040265045,0.00016946907,0.00017571867,0.00011008481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006349582,0.0002603599,0.00026302206,0.0010336245,0.0003065159,0.00044103508,0.00025000458,0.00024374429,0.00097295304],"category_scores_gemma":[0.0017052428,0.00017004304,0.00038291232,0.0007573702,0.00023589842,0.00031270643,0.00036192767,0.00026316705,0.00014296074],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001280824,0.000070551214,0.98304605,0.000032274034,0.00025897686,0.00009747355,0.00019149296,0.00039829744,0.0053997855,0.000038084432,0.00018242717,0.00900379],"study_design_scores_gemma":[0.0000034978486,0.000089193396,0.99897027,0.0000018901138,0.000019458612,0.00012052891,0.000047051395,0.00033000694,0.00029557012,0.000053366883,0.0000661395,0.0000030627716],"about_ca_topic_score_codex":0.00473638,"about_ca_topic_score_gemma":0.005032108,"teacher_disagreement_score":0.00473638,"about_ca_system_score_codex":0.00021385634,"about_ca_system_score_gemma":0.00014156476,"threshold_uncertainty_score":0.009417653},"labels":[],"label_agreement":null},{"id":"W4383343678","doi":"10.3389/fnhum.2023.1196624","title":"Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks","year":2023,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Atlas (anatomy); White matter; Medicine; Anatomy; Radiology; Magnetic resonance imaging","score_opus":0.033435169892414504,"score_gpt":0.29862613712141606,"score_spread":0.26519096722900154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383343678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8393892,0.0021318705,0.115626335,0.00038286138,0.00012143388,0.0005130781,0.012173491,0.0013593046,0.028302286],"genre_scores_gemma":[0.90717584,0.00059468934,0.079533905,0.0000875522,0.00005324422,0.0006920351,0.007568808,0.00042807832,0.0038659326],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99966383,0.00005450987,0.00003505971,0.00010901158,0.000094488154,0.000043148702],"domain_scores_gemma":[0.99946696,0.00012850454,0.00010735994,0.00010785695,0.00013275023,0.000056632693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077396585,0.00043227922,0.00025832836,0.0020626276,0.00075534516,0.0016431496,0.0006445325,0.0004925287,0.0041624773],"category_scores_gemma":[0.0036850472,0.0002411385,0.000346457,0.0016548061,0.0004919232,0.00074854644,0.0014658684,0.00025482706,0.00069464534],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028150796,0.00014618486,0.20838596,0.0019340103,0.0007738934,0.0032844346,0.009157657,0.034716424,0.09872104,0.044624213,0.037343804,0.5580973],"study_design_scores_gemma":[0.00015592261,0.00034878857,0.672594,0.0006907351,0.0004930284,0.010714616,0.0024276085,0.08488406,0.067927,0.028582113,0.13093728,0.0002448134],"about_ca_topic_score_codex":0.021184474,"about_ca_topic_score_gemma":0.040701967,"teacher_disagreement_score":0.021184474,"about_ca_system_score_codex":0.0009587114,"about_ca_system_score_gemma":0.0013939084,"threshold_uncertainty_score":0.042122304},"labels":[],"label_agreement":null},{"id":"W4383497849","doi":"10.1016/j.neuroimage.2023.120248","title":"Randomized iterative spherical‐deconvolution informed tractogram filtering","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"National Institute of Mental Health","keywords":"Streamlines, streaklines, and pathlines; Deconvolution; Classifier (UML); Computer science; Tractography; Artificial intelligence; Scale-invariant feature transform; Pattern recognition (psychology); Diffusion MRI; Algorithm; Magnetic resonance imaging; Feature extraction; Physics","score_opus":0.09870090185074554,"score_gpt":0.3892425320522324,"score_spread":0.2905416302014869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383497849","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071709333,0.000061846025,0.9912655,0.000055093562,0.00001892491,0.000040910872,0.00009196944,0.0009121167,0.00038269255],"genre_scores_gemma":[0.16261877,0.00013452739,0.8327251,0.00009736618,0.000037338566,0.0003096707,0.0009809072,0.00037451473,0.0027218775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932456,0.00016826531,0.000052502135,0.0001715595,0.00020612462,0.0000769655],"domain_scores_gemma":[0.9982803,0.00081330555,0.0001819119,0.00030826,0.0003630781,0.00005314694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014986472,0.000943555,0.0011218729,0.00094103126,0.0005045783,0.0009094463,0.0012175617,0.0012245348,0.0034743932],"category_scores_gemma":[0.0056961766,0.00050196645,0.0013009029,0.000941892,0.00070732477,0.00076156965,0.0010634242,0.00091336796,0.0012607703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060587015,0.000090771704,0.001614223,0.00025495223,0.0002086471,0.00023707603,0.00018263629,0.6106854,0.028693836,0.01725064,0.0055820034,0.33459392],"study_design_scores_gemma":[0.000015658059,0.000030464136,0.00028339768,0.000005039353,0.000012089172,0.000048337963,0.00000928652,0.99112076,0.00496968,0.0023743154,0.0011197447,0.000011210487],"about_ca_topic_score_codex":0.00935046,"about_ca_topic_score_gemma":0.015652705,"teacher_disagreement_score":0.00935046,"about_ca_system_score_codex":0.0007133856,"about_ca_system_score_gemma":0.0025416345,"threshold_uncertainty_score":0.01859206},"labels":[],"label_agreement":null},{"id":"W4383987283","doi":"10.48550/arxiv.2307.03827","title":"Effect of Intensity Standardization on Deep Learning for WML Segmentation in Multi-Centre FLAIR MRI","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer Society Research Program; Alzheimer's Society; Government of Ontario","keywords":"Fluid-attenuated inversion recovery; Segmentation; Artificial intelligence; Normalization (sociology); Pattern recognition (psychology); Preprocessor; Computer science; Deep learning; Magnetic resonance imaging; Sørensen–Dice coefficient; Image segmentation; Medicine; Radiology","score_opus":0.1283769959695149,"score_gpt":0.2990233176373229,"score_spread":0.17064632166780802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383987283","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8586121,0.0019764167,0.13315542,0.00049079227,0.00021846234,0.0001258039,0.00023760182,0.0033055593,0.0018778418],"genre_scores_gemma":[0.9551545,0.00036197223,0.042587765,0.00019748251,0.00004572756,0.00005637351,0.0006609246,0.00019883958,0.00073633296],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836034,0.0006657661,0.00016018009,0.00037419036,0.00028663423,0.0001529423],"domain_scores_gemma":[0.99624795,0.001754419,0.0004109446,0.00069207005,0.0007304744,0.00016412963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006713685,0.0014695814,0.0008281072,0.0009086901,0.0004395359,0.0009047881,0.0008262702,0.0009421509,0.00061735534],"category_scores_gemma":[0.013288911,0.00038992695,0.0010663235,0.00066781486,0.00082660996,0.0013965613,0.0015415906,0.0013250741,0.0002532626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018074433,0.00058634597,0.043682046,0.00022987646,0.00087426347,0.00021937989,0.0003554759,0.44870913,0.031580195,0.0013524106,0.0033232877,0.46728018],"study_design_scores_gemma":[0.00007048904,0.0008378875,0.015765099,0.000053181437,0.00024051433,0.00011297488,0.00010557053,0.9456598,0.034734845,0.0011629645,0.0012108969,0.000045638233],"about_ca_topic_score_codex":0.0065068766,"about_ca_topic_score_gemma":0.0063047525,"teacher_disagreement_score":0.006713685,"about_ca_system_score_codex":0.00069327006,"about_ca_system_score_gemma":0.0009549641,"threshold_uncertainty_score":0.03550583},"labels":[],"label_agreement":null},{"id":"W4384263540","doi":"10.48550/arxiv.2307.05786","title":"Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet; VINNOVA; Université de Sherbrooke","keywords":"Streamlines, streaklines, and pathlines; Tractography; Artificial intelligence; Computer science; Filter (signal processing); Task (project management); Artificial neural network; Pattern recognition (psychology); Diffusion MRI; Computer vision; Magnetic resonance imaging; Radiology; Physics; Engineering","score_opus":0.23522085090293102,"score_gpt":0.2702087456932591,"score_spread":0.03498789479032807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384263540","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06882483,0.00021117194,0.9257775,0.00019830011,0.00004172642,0.00006666045,0.00022503544,0.0038282706,0.0008264326],"genre_scores_gemma":[0.6427545,0.00014645485,0.3521547,0.00015256458,0.000064794694,0.00012714273,0.0012642748,0.00040058867,0.0029350084],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992705,0.00011376199,0.000043276843,0.00026026252,0.0001842056,0.00012805336],"domain_scores_gemma":[0.99799037,0.00064301543,0.0002514389,0.00036629706,0.0005940084,0.00015497574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001991935,0.0012338221,0.0012272713,0.0015404666,0.00053647987,0.0015183844,0.0015897843,0.001388331,0.002454842],"category_scores_gemma":[0.0055466415,0.0006196015,0.000981666,0.0012146588,0.00088790385,0.0018587797,0.0016747556,0.0021996996,0.0009580129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094177964,0.00039692645,0.01083137,0.00018572297,0.00013438372,0.000264991,0.00034482198,0.292343,0.028950281,0.010617907,0.006368102,0.6486207],"study_design_scores_gemma":[0.000016281476,0.00007194351,0.0008765254,0.000012293925,0.000017713519,0.000036764537,0.000027260676,0.9850936,0.009321142,0.003709015,0.0008049826,0.0000124883],"about_ca_topic_score_codex":0.0076089334,"about_ca_topic_score_gemma":0.0100109,"teacher_disagreement_score":0.0076089334,"about_ca_system_score_codex":0.0011229529,"about_ca_system_score_gemma":0.0018444249,"threshold_uncertainty_score":0.015129268},"labels":[],"label_agreement":null},{"id":"W4384662966","doi":"10.1161/strokeaha.123.043713","title":"White Matter Integrity and Chronic Poststroke Upper Limb Function: An ENIGMA Stroke Recovery Analysis","year":2023,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Genentech; Biogen; U.S. Department of Veterans Affairs","keywords":"Medicine; Corticospinal tract; Stroke (engine); Upper limb; Physical medicine and rehabilitation; White matter; Stroke recovery; Motor function; Chronic stroke; Rehabilitation; Physical therapy; Magnetic resonance imaging; Diffusion MRI; Radiology","score_opus":0.037850526328610704,"score_gpt":0.32934969164532285,"score_spread":0.29149916531671216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384662966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99790585,0.000074173964,0.000576219,0.000015445661,0.000001481998,0.000018069002,0.0012549984,0.00001102566,0.00014275782],"genre_scores_gemma":[0.9971545,0.000021854785,0.0006069642,0.0000055421474,0.000003591904,0.0000346298,0.002015134,0.0000062817944,0.00015141885],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992944,0.00017077537,0.000097994176,0.00021955236,0.00013761775,0.000079587444],"domain_scores_gemma":[0.9970732,0.0007875774,0.0011802411,0.0004969785,0.0002662312,0.00019570092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027597265,0.00042317476,0.00050921453,0.0019151634,0.00039201375,0.0006307629,0.0005937271,0.00033791355,0.0016828465],"category_scores_gemma":[0.0036703984,0.00017299019,0.0009680317,0.0014537022,0.00039971044,0.00049926207,0.000966607,0.00041312486,0.00033083677],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005448855,0.000057697664,0.9948295,0.000027933675,0.00055529864,0.00007123522,0.00007809041,0.00040566878,0.0006421236,0.00004402596,0.0001954189,0.002548201],"study_design_scores_gemma":[0.000011190123,0.0001746804,0.9971433,0.000005036549,0.00013231131,0.00021444197,0.00006763242,0.0015651601,0.0003055684,0.000050701317,0.0003241057,0.000005751706],"about_ca_topic_score_codex":0.0038120127,"about_ca_topic_score_gemma":0.0035839959,"teacher_disagreement_score":0.0038120127,"about_ca_system_score_codex":0.00034140242,"about_ca_system_score_gemma":0.0005843719,"threshold_uncertainty_score":0.014594972},"labels":[],"label_agreement":null},{"id":"W4384943329","doi":"10.1212/wnl.0000000000207543","title":"Microstructural Alterations in Tract Development in College Football and Volleyball Players","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Football; Corpus callosum; Concussion; Superior longitudinal fasciculus; Medicine; Cingulum (brain); Psychology; Physical therapy; Physical medicine and rehabilitation; Poison control; Magnetic resonance imaging; Anatomy; Injury prevention; Radiology","score_opus":0.046859035886282846,"score_gpt":0.3331399991273095,"score_spread":0.2862809632410267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384943329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954885,0.00011377816,0.00012769397,0.000007109101,7.201023e-7,0.000005626487,0.00009048557,0.000004033913,0.00010168057],"genre_scores_gemma":[0.9994273,0.00003674121,0.00019140045,0.0000036473664,0.0000015804918,0.000009607561,0.00012060982,0.0000021206577,0.0002071181],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999754,0.000041229385,0.000023667919,0.00007955597,0.00003465974,0.00006686098],"domain_scores_gemma":[0.99893564,0.00018257152,0.0005542551,0.00006517652,0.0001029751,0.00015942221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005108855,0.00025264808,0.0002025674,0.0010389488,0.00035900399,0.00049959053,0.00025646717,0.00038280903,0.0018980289],"category_scores_gemma":[0.0014088034,0.0001910573,0.00023287126,0.0004746167,0.00038301307,0.0003490933,0.00048535934,0.00017723352,0.00014236613],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005327031,0.000041759868,0.98329306,0.000032282296,0.000096270574,0.00024071375,0.00025315658,0.00013966602,0.009436924,0.000043165663,0.000042239102,0.005848],"study_design_scores_gemma":[0.0000014090712,0.00006626555,0.99915373,0.0000032112775,0.000008099401,0.00018379226,0.00009428156,0.00014757915,0.00028798557,0.00001730245,0.000035027155,0.0000012743452],"about_ca_topic_score_codex":0.013287322,"about_ca_topic_score_gemma":0.022986665,"teacher_disagreement_score":0.013287322,"about_ca_system_score_codex":0.00046450915,"about_ca_system_score_gemma":0.00039512198,"threshold_uncertainty_score":0.026419997},"labels":[],"label_agreement":null},{"id":"W4385191001","doi":"10.1016/j.neuroimage.2023.120288","title":"FIESTA: Autoencoders for accurate fiber segmentation in tractography","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; National Institutes of Health; Québec Consortium for Drug Discovery; Alliance de recherche numérique du Canada; Alzheimer's Disease Neuroimaging Initiative; Michael J. Fox Foundation for Parkinson's Research; McDonnell Center for Systems Neuroscience; U.S. Department of Defense","keywords":"Artificial intelligence; Bundle; Tractography; Computer science; Segmentation; Autoencoder; Human Connectome Project; Pattern recognition (psychology); Atlas (anatomy); Fiber bundle; Computer vision; Deep learning; Diffusion MRI; Geology; Magnetic resonance imaging","score_opus":0.12328774493107689,"score_gpt":0.41035526311576037,"score_spread":0.28706751818468346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385191001","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055505657,0.0001635218,0.98908883,0.000086225096,0.000028703911,0.000031366613,0.0001779784,0.0043666973,0.0005060583],"genre_scores_gemma":[0.1460575,0.00035401704,0.84647065,0.00021465255,0.00005317576,0.0002474515,0.0012885905,0.0012261127,0.0040877946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948955,0.00010267692,0.000029074374,0.00016959733,0.00014826763,0.00006085518],"domain_scores_gemma":[0.99890745,0.0005224848,0.00012215313,0.00021539634,0.00018079198,0.000051749237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013977474,0.0013985931,0.00089210115,0.0008788681,0.0005540594,0.001020706,0.0015762593,0.0016322099,0.003576994],"category_scores_gemma":[0.0039479374,0.000951193,0.0013948459,0.00068314484,0.00087681675,0.0015831748,0.0015787361,0.0028540483,0.0019509057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022836406,0.00009138723,0.001581972,0.00016775135,0.00020736565,0.00020533362,0.00021438564,0.5871289,0.026309185,0.010283203,0.008826957,0.36475515],"study_design_scores_gemma":[0.0000071396234,0.000014559124,0.00026036217,0.000010528781,0.000007817307,0.00003476591,0.000006597942,0.99103606,0.0039122268,0.0032923915,0.0014081759,0.000009362304],"about_ca_topic_score_codex":0.010825462,"about_ca_topic_score_gemma":0.015469536,"teacher_disagreement_score":0.010825462,"about_ca_system_score_codex":0.0010488719,"about_ca_system_score_gemma":0.0016449153,"threshold_uncertainty_score":0.021524906},"labels":[],"label_agreement":null},{"id":"W4385230448","doi":"10.1111/ejn.16097","title":"Morphological alterations of contralesional hemisphere relate to functional outcomes after stroke","year":2023,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Health and Family Planning Commission of Sichuan Province; Shanghai Rising-Star Program; National Natural Science Foundation of China","keywords":"Gyrification; Precentral gyrus; Insula; Supplementary motor area; Psychology; Gyrus; Audiology; Functional magnetic resonance imaging; Physical medicine and rehabilitation; Neuroscience; Medicine; Magnetic resonance imaging; Cerebral cortex; Radiology","score_opus":0.09387910909969253,"score_gpt":0.3466624661524178,"score_spread":0.25278335705272525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385230448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99958605,0.00010577161,0.000069901165,0.000006684142,0.0000014002015,0.0000025873314,0.000041428342,0.000002308454,0.00018382515],"genre_scores_gemma":[0.9995956,0.000060688802,0.000057145433,0.000006274914,0.0000048314114,0.0000029821438,0.00008893842,0.0000014501036,0.00018211131],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990237,0.000012879927,0.000011651124,0.000034541987,0.000018144685,0.000020356443],"domain_scores_gemma":[0.99967515,0.000035331723,0.00019024796,0.000025085885,0.000035418154,0.000038819187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017466253,0.0002973747,0.00028989816,0.0006290741,0.00016145295,0.00027311844,0.000107923835,0.00023820398,0.0013411152],"category_scores_gemma":[0.0005851971,0.00008519526,0.00015494144,0.000281649,0.0002812811,0.0002063479,0.00022154351,0.00013167133,0.00016847163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016735761,0.0001686674,0.9267296,0.000086101536,0.0002023667,0.00224223,0.000438242,0.00026339557,0.04328403,0.00008401048,0.00015501928,0.024672741],"study_design_scores_gemma":[0.000002668627,0.00012979732,0.9984914,0.0000020997095,0.000011513137,0.0007456253,0.000050189195,0.00006779798,0.00041871582,0.00003731815,0.000040104132,0.0000026434693],"about_ca_topic_score_codex":0.0009132857,"about_ca_topic_score_gemma":0.0019096514,"teacher_disagreement_score":0.0013411152,"about_ca_system_score_codex":0.00013548796,"about_ca_system_score_gemma":0.00013759072,"threshold_uncertainty_score":0.0044864416},"labels":[],"label_agreement":null},{"id":"W4385351255","doi":"10.1016/j.nicl.2023.103483","title":"Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Science and Technology Department of Zhejiang Province; National Institute of Mental Health; Agencia Estatal de Investigación; Engineering and Physical Sciences Research Council; National Institute on Aging; Narodowa Agencja Wymiany Akademickiej; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; Ministerio de Ciencia e Innovación; National Institute of Biomedical Imaging and Bioengineering; Ministerio de Ciencia, Innovación y Universidades; Ministry of Science and Technology of the People's Republic of China; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Natural Science Foundation of China; National Institutes of Health; Canada Research Chairs; University College London Hospitals NHS Foundation Trust; European Commission; National Institute of Dental and Craniofacial Research; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Deutsche Forschungsgemeinschaft","keywords":"False positive paradox; Chronic Migraine; Diffusion MRI; Artificial intelligence; Generalization; Migraine; White matter; Deep learning; Medicine; Psychology; Pattern recognition (psychology); Computer science; Statistics; Magnetic resonance imaging; Mathematics; Radiology; Internal medicine","score_opus":0.45927752470318695,"score_gpt":0.6082723008100177,"score_spread":0.14899477610683076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385351255","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44493297,0.006938497,0.53461546,0.0017989755,0.000629769,0.0014264018,0.0011810611,0.0046706083,0.003806271],"genre_scores_gemma":[0.7814555,0.00085587817,0.2139939,0.00050292705,0.00010183336,0.000592921,0.0011942466,0.00022834934,0.001074393],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9951402,0.0028152359,0.0003831197,0.00062683766,0.0008291746,0.00020535161],"domain_scores_gemma":[0.9802012,0.011058593,0.0014130174,0.002479126,0.0043211537,0.000526827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01948195,0.001355512,0.0007456388,0.0012623233,0.00037407974,0.0016073381,0.0015289948,0.0017014684,0.0012941473],"category_scores_gemma":[0.05144957,0.00046459684,0.0008682258,0.0007623832,0.00095163495,0.0010969396,0.0020639002,0.002045357,0.00071943935],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003534694,0.001118049,0.036890835,0.0013429889,0.0010266778,0.00040783096,0.00057130016,0.2254304,0.03838835,0.0026125698,0.0057468484,0.6829295],"study_design_scores_gemma":[0.00026130927,0.0011549501,0.009708062,0.00021661396,0.00019414004,0.0003535509,0.000094054194,0.9543173,0.027974436,0.0026999891,0.0029716147,0.000053979365],"about_ca_topic_score_codex":0.0026586344,"about_ca_topic_score_gemma":0.0019690206,"teacher_disagreement_score":0.01948195,"about_ca_system_score_codex":0.00083651266,"about_ca_system_score_gemma":0.0015905919,"threshold_uncertainty_score":0.103031576},"labels":[],"label_agreement":null},{"id":"W4385460989","doi":"10.3389/fninf.2023.1208073","title":"CACTUS: a computational framework for generating realistic white matter microstructure substrates","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Diffusion MRI; Computer science; Robustness (evolution); Bundle; Monte Carlo method; Microstructure; Biological system; Materials science; Magnetic resonance imaging; Mathematics; Composite material; Chemistry; Biology","score_opus":0.03961584959815493,"score_gpt":0.3331354017896845,"score_spread":0.29351955219152953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385460989","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015552069,0.0001535836,0.9766431,0.0001513289,0.000058008492,0.0001112006,0.0004867295,0.0030472076,0.0037967695],"genre_scores_gemma":[0.20612934,0.00032421172,0.7881525,0.00010534109,0.000033537483,0.000660488,0.001020482,0.0014191032,0.0021550308],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997601,0.0000611205,0.000016588176,0.000037505695,0.000095215066,0.000029469511],"domain_scores_gemma":[0.9993795,0.00032757045,0.000058224214,0.000085725864,0.00009727215,0.00005166764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071485527,0.00091590214,0.0005945805,0.0007716428,0.00051982014,0.0010833085,0.0017313163,0.0012352472,0.003603103],"category_scores_gemma":[0.0023933698,0.0005990324,0.0009096876,0.00046501844,0.0007533528,0.00058733975,0.0012797791,0.0009864414,0.00062773586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049966042,0.000029046432,0.0005511978,0.00013314522,0.00003580412,0.0001619913,0.00008485766,0.94266754,0.008303151,0.028835459,0.0024576844,0.016690116],"study_design_scores_gemma":[0.000013177997,0.000010516641,0.00004721005,0.000009348673,0.0000032935382,0.000031747964,0.000006614582,0.9916517,0.0017330629,0.004199121,0.0022864544,0.000007665093],"about_ca_topic_score_codex":0.0040969886,"about_ca_topic_score_gemma":0.004359525,"teacher_disagreement_score":0.0040969886,"about_ca_system_score_codex":0.00063206465,"about_ca_system_score_gemma":0.0012714172,"threshold_uncertainty_score":0.012053549},"labels":[],"label_agreement":null},{"id":"W4385474130","doi":"10.48550/arxiv.2307.16421","title":"Wasserstein Mirror Gradient Flow as the limit of the Sinkhorn Algorithm","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Menzies School of Health Research; National Science Foundation","keywords":"Mathematics; Balanced flow; Wasserstein metric; Limit (mathematics); Flow (mathematics); Applied mathematics; Matrix norm; Mathematical analysis; Geometry; Eigenvalues and eigenvectors","score_opus":0.20654598876679478,"score_gpt":0.2640116044227801,"score_spread":0.05746561565598532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385474130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044100467,0.00030979328,0.95032424,0.0005029166,0.000037418,0.000045906174,0.000067835805,0.00027138207,0.004340022],"genre_scores_gemma":[0.5122256,0.0007234593,0.46633056,0.00050370547,0.00011447028,0.00031466558,0.00031885423,0.00056464307,0.018903933],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993381,0.00024569468,0.0000365947,0.00014501174,0.00015843543,0.000076135686],"domain_scores_gemma":[0.9972248,0.0013789939,0.00034283832,0.0002455205,0.0005419172,0.00026594155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028251105,0.00077652046,0.000717123,0.0011821813,0.00061198045,0.001450512,0.0010658457,0.0014511406,0.0037268254],"category_scores_gemma":[0.013001557,0.00043165107,0.0008332367,0.0005411717,0.0021219775,0.0031954085,0.0020073098,0.0014916749,0.00070839433],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015540823,0.00005199827,0.0018248761,0.00014938509,0.00004164347,0.0002586633,0.00035064595,0.11733929,0.0075126113,0.83403605,0.0021411034,0.036138203],"study_design_scores_gemma":[0.000015091029,0.000054721575,0.00034074113,0.00003482736,0.000010510299,0.00010944674,0.000029731349,0.7808422,0.0024829893,0.21404716,0.0020099615,0.00002257635],"about_ca_topic_score_codex":0.0017036987,"about_ca_topic_score_gemma":0.0013582264,"teacher_disagreement_score":0.0037268254,"about_ca_system_score_codex":0.0012203697,"about_ca_system_score_gemma":0.0012464017,"threshold_uncertainty_score":0.014940798},"labels":[],"label_agreement":null},{"id":"W4385497248","doi":"10.3389/fninf.2023.1197330","title":"Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Toronto; Sunnybrook Health Science Centre; Health Sciences Centre; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer's Society; Government of Ontario","keywords":"Artificial intelligence; Pattern recognition (psychology); Fractional anisotropy; Fluid-attenuated inversion recovery; Diffusion MRI; Computer science; Similarity (geometry); Mean squared error; Neuroimaging; Mathematics; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Medicine; Statistics; Biology; Image (mathematics); Radiology; Neuroscience","score_opus":0.02870131174365778,"score_gpt":0.2852937493741453,"score_spread":0.25659243763048756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385497248","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08010582,0.00034384168,0.9141788,0.0002475444,0.000077384924,0.00010221212,0.00020028507,0.0013975959,0.0033464355],"genre_scores_gemma":[0.8196952,0.0002761024,0.1744967,0.00021762002,0.00003804861,0.00016175168,0.0005481519,0.00019542225,0.0043711276],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99984205,0.00004225239,0.000006017358,0.00004953694,0.000040956365,0.000019149547],"domain_scores_gemma":[0.99953616,0.00028063223,0.00004940244,0.000050408824,0.00006609686,0.000017199895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006481737,0.0007675461,0.00028559117,0.00037462165,0.0001362521,0.00039829925,0.00053921103,0.00050407834,0.0014741017],"category_scores_gemma":[0.0013955402,0.00032199814,0.000578646,0.00020878832,0.00041014003,0.00032048183,0.0005813105,0.00074629247,0.00032591648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006115897,0.000025904616,0.0005679223,0.00003657717,0.000035743356,0.000048119917,0.000025240182,0.9495653,0.00698609,0.0016345917,0.00072059414,0.04029285],"study_design_scores_gemma":[0.0000020063678,0.000014906626,0.00010479049,0.0000033429405,0.0000038310704,0.000015965199,0.0000023533537,0.99664116,0.0023223693,0.00065070955,0.00023566464,0.0000027887397],"about_ca_topic_score_codex":0.0025508723,"about_ca_topic_score_gemma":0.0027598878,"teacher_disagreement_score":0.0025508723,"about_ca_system_score_codex":0.0004907416,"about_ca_system_score_gemma":0.00040261587,"threshold_uncertainty_score":0.005072117},"labels":[],"label_agreement":null},{"id":"W4385502630","doi":"10.48550/arxiv.2108.03827","title":"Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Multiple sclerosis; Spinal cord; Diffusion MRI; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.22780760721992005,"score_gpt":0.2714940281932386,"score_spread":0.04368642097331854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385502630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87205195,0.010027707,0.11102827,0.00041320623,0.0001417552,0.00017560928,0.0009765762,0.00095625286,0.004228678],"genre_scores_gemma":[0.9725701,0.0014039528,0.02493984,0.00003834771,0.000054907923,0.000021915748,0.00048797764,0.00008060889,0.00040229177],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99794835,0.00073368225,0.00019392186,0.0005136394,0.0005035441,0.00010680894],"domain_scores_gemma":[0.9890168,0.0076407026,0.0011536038,0.00087708666,0.00095705997,0.00035461408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005863089,0.0013406147,0.0011939371,0.0048968797,0.00043638868,0.0019781308,0.0004848179,0.0010409995,0.00063002063],"category_scores_gemma":[0.015835311,0.0002550981,0.00076842913,0.0018051493,0.0007286946,0.0016999834,0.00081722654,0.00068655045,0.00044268413],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031170023,0.00035563434,0.31815502,0.0008059649,0.002050274,0.00049864844,0.00047382584,0.086162515,0.062317558,0.0017046591,0.0020091971,0.5223498],"study_design_scores_gemma":[0.00007029357,0.0016910924,0.41594186,0.00024845253,0.0011914694,0.0013046355,0.00047674662,0.5269137,0.045097116,0.0039474433,0.0028731618,0.00024408774],"about_ca_topic_score_codex":0.0026751475,"about_ca_topic_score_gemma":0.0038877248,"teacher_disagreement_score":0.005863089,"about_ca_system_score_codex":0.0003689023,"about_ca_system_score_gemma":0.0006040855,"threshold_uncertainty_score":0.03100735},"labels":[],"label_agreement":null},{"id":"W4385544898","doi":"10.58530/2022/3044","title":"The value of diffusion kurtosis imaging in detecting delayed brain development of premature infants","year":2023,"lang":"en","type":"article","venue":"Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Kurtosis; Internal capsule; Diffusion MRI; White matter; Brain development; Medicine; Neuroscience; Magnetic resonance imaging; Radiology; Psychology; Mathematics; Statistics","score_opus":0.02677539768738765,"score_gpt":0.3046242485238211,"score_spread":0.27784885083643346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385544898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74252194,0.15070696,0.084636524,0.0037700406,0.001149991,0.00019676755,0.0024861738,0.0012053348,0.013326299],"genre_scores_gemma":[0.90149516,0.04613301,0.048168022,0.00033774337,0.0005215191,0.00010826145,0.0008297235,0.000102605016,0.0023038478],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993954,0.00020817269,0.000080067206,0.0001128061,0.00015861851,0.000045024877],"domain_scores_gemma":[0.9973773,0.0012920899,0.0004312523,0.000119626704,0.0005833975,0.00019637206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021241058,0.0010819488,0.0006344504,0.0028126116,0.0002655167,0.0012326298,0.0005484926,0.001013417,0.0012407936],"category_scores_gemma":[0.007749859,0.00031884137,0.00046701342,0.0008633256,0.0006114344,0.0013773161,0.00085670635,0.0009811813,0.0004940802],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014327292,0.00014876694,0.45406866,0.0014230676,0.0003663104,0.0033610028,0.00031952583,0.0025381264,0.062057417,0.0013745021,0.004907325,0.46800268],"study_design_scores_gemma":[0.00010833797,0.0022201745,0.77415264,0.0010891879,0.0014295643,0.031505905,0.0015211945,0.04687684,0.10183766,0.011429253,0.027363166,0.0004661185],"about_ca_topic_score_codex":0.0018084404,"about_ca_topic_score_gemma":0.0018707429,"teacher_disagreement_score":0.0028126116,"about_ca_system_score_codex":0.0004057004,"about_ca_system_score_gemma":0.0006510972,"threshold_uncertainty_score":0.011233449},"labels":[],"label_agreement":null},{"id":"W4385576122","doi":"10.1162/netn_a_00330","title":"The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts","year":2023,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canadian Institutes of Health Research; Hospital for Sick Children; Fondation Brain Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Myelin; Neuroscience; Connectome; Diffusion MRI; Fractional anisotropy; Niche; Grey matter; Biology; Psychology; Central nervous system; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.0908628506769586,"score_gpt":0.35195213523566127,"score_spread":0.2610892845587027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385576122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98524076,0.000523855,0.012004954,0.000092046525,0.0000049279693,0.000007608859,0.0007436564,0.00006873655,0.0013134668],"genre_scores_gemma":[0.9951219,0.00028528625,0.0038384902,0.000017759758,0.000009360377,0.000013200726,0.0004742835,0.000012989253,0.00022675155],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998908,0.000025725201,0.0000059371046,0.000043364416,0.00002209397,0.000012100148],"domain_scores_gemma":[0.99926156,0.0003139385,0.00025596342,0.00006682721,0.000060282626,0.000041406838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023091918,0.0002485555,0.00023590964,0.0018471208,0.00020749537,0.0003970668,0.00012661214,0.0002046932,0.001527021],"category_scores_gemma":[0.0020359105,0.00010968552,0.0001663164,0.0014257719,0.0003931378,0.0006966146,0.00041282037,0.00016282657,0.00015395253],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011407081,0.00009900333,0.47432294,0.00056632666,0.0014800414,0.0008349237,0.0012059832,0.037548896,0.32614097,0.017110473,0.0028987187,0.13665111],"study_design_scores_gemma":[0.000012403569,0.000114133676,0.92284983,0.00004225613,0.00015620455,0.0024671361,0.00030187998,0.032780375,0.012208453,0.026743794,0.002283209,0.000040367948],"about_ca_topic_score_codex":0.0011402869,"about_ca_topic_score_gemma":0.002105114,"teacher_disagreement_score":0.0018471208,"about_ca_system_score_codex":0.00015025475,"about_ca_system_score_gemma":0.0001213721,"threshold_uncertainty_score":0.0051083565},"labels":[],"label_agreement":null},{"id":"W4385728533","doi":"10.3389/fninf.2023.1191200","title":"versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Computer science; Fractional anisotropy; Artificial intelligence; Robustness (evolution); Image processing; Data mining; Computer vision; Magnetic resonance imaging; Medicine","score_opus":0.042022900369578196,"score_gpt":0.32039168386747907,"score_spread":0.2783687834979009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385728533","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013752292,0.0007917491,0.69766253,0.00050199655,0.00022987548,0.00046486963,0.022506401,0.26119587,0.0028944216],"genre_scores_gemma":[0.1261313,0.0010773335,0.74632937,0.00080350484,0.00015238638,0.0023319342,0.088790886,0.029610472,0.0047727637],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910307,0.000095915704,0.000107663865,0.00037699132,0.00021775512,0.00009871428],"domain_scores_gemma":[0.998345,0.00056840945,0.00014395674,0.0004682112,0.00033730853,0.00013712117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028041413,0.0022970964,0.0011641657,0.002268618,0.0010236816,0.0028272644,0.002740599,0.0011577294,0.016708095],"category_scores_gemma":[0.008660571,0.0011112081,0.001289098,0.0013870338,0.00074065314,0.0027065342,0.0031223972,0.0018852071,0.008989696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003231485,0.00033880273,0.0069384375,0.0014087072,0.0006899444,0.0010953783,0.0010112725,0.01922977,0.085363954,0.013652551,0.29268736,0.5743523],"study_design_scores_gemma":[0.0007592985,0.00043458043,0.013569241,0.00029162914,0.00019639047,0.0017771035,0.00029399124,0.542764,0.15294476,0.061775323,0.22466747,0.00052612677],"about_ca_topic_score_codex":0.0034689775,"about_ca_topic_score_gemma":0.0036218315,"teacher_disagreement_score":0.016708095,"about_ca_system_score_codex":0.0009349243,"about_ca_system_score_gemma":0.00239709,"threshold_uncertainty_score":0.055894196},"labels":[],"label_agreement":null},{"id":"W4385760990","doi":"10.1162/imag_a_00011","title":"RELIEF: A structured multivariate approach for removal of latent inter-scanner effects","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Mental Health; Centre for Addiction and Mental Health Foundation; Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada","keywords":"Scanner; Computer science; Generalizability theory; Harmonization; Univariate; Multivariate statistics; Artificial intelligence; Data mining; Machine learning; Context (archaeology); Data science; Statistics; Mathematics; Geography","score_opus":0.05939705709650033,"score_gpt":0.3652103886801835,"score_spread":0.3058133315836832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385760990","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032250136,0.00015599476,0.99539846,0.00013108319,0.0000255386,0.0000684122,0.00015247737,0.00068506575,0.000158003],"genre_scores_gemma":[0.09150237,0.00024951377,0.90429205,0.00032760983,0.00018097647,0.0005649626,0.0010934302,0.00067889586,0.0011102436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9927254,0.004710682,0.00031044873,0.0011836234,0.00076541805,0.00030446096],"domain_scores_gemma":[0.9858219,0.008580767,0.0013170136,0.0025397947,0.0013930304,0.00034740756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012947905,0.0016381518,0.0020778952,0.0018194062,0.000869215,0.001352691,0.0030298366,0.0015143299,0.0058063297],"category_scores_gemma":[0.027177835,0.0010150708,0.0033498807,0.0018980969,0.0017680479,0.001957626,0.0036948868,0.0026434122,0.0016462222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008934599,0.00038004393,0.0077305585,0.0011424337,0.0016630036,0.0007106449,0.0009227624,0.21606927,0.019444805,0.052824624,0.02269324,0.6755252],"study_design_scores_gemma":[0.00018794081,0.00037301602,0.003572009,0.0001083993,0.00027382543,0.00038538533,0.00017717035,0.91537327,0.0053010457,0.06191617,0.012189981,0.00014186827],"about_ca_topic_score_codex":0.0018320968,"about_ca_topic_score_gemma":0.0026028648,"teacher_disagreement_score":0.012947905,"about_ca_system_score_codex":0.00048390118,"about_ca_system_score_gemma":0.0019136373,"threshold_uncertainty_score":0.06847584},"labels":[],"label_agreement":null},{"id":"W4385829186","doi":"10.1101/2023.08.13.553149","title":"The Spatial Patterns and Determinants of Cerebrospinal Fluid Circulation in the Human Brain","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Centre for Addiction and Mental Health","funders":"Center for High Performance Computing; National Institutes of Health","keywords":"Circulation (fluid dynamics); Cerebrospinal fluid; Human brain; Geography; Neuroscience; Psychology; Mechanics; Physics","score_opus":0.05410492567857453,"score_gpt":0.32076372476245885,"score_spread":0.26665879908388435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385829186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701534,0.00056422374,0.028154,0.00009728121,0.000009974505,0.00001497168,0.0005084764,0.00006829957,0.00042939722],"genre_scores_gemma":[0.99195886,0.00020097828,0.007417003,0.000014465536,0.000012100362,0.000010073755,0.00024287475,0.000016832808,0.00012687466],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998417,0.000056499448,0.000011966027,0.000047955262,0.000026682776,0.000015251775],"domain_scores_gemma":[0.99946624,0.000229677,0.00013218555,0.000057326564,0.000081113394,0.000033553286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000518535,0.00019952774,0.00018217665,0.00088907557,0.00013966604,0.00054645486,0.00010802113,0.00018797873,0.0005851232],"category_scores_gemma":[0.002770983,0.00011231461,0.00015460835,0.0005622925,0.00044114314,0.00034357602,0.0002541855,0.00014364657,0.00016442187],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001368812,0.00013627009,0.319017,0.00052172336,0.00039690244,0.0011283947,0.0012459747,0.016030546,0.48560297,0.006710289,0.0028605182,0.1649806],"study_design_scores_gemma":[0.000028800128,0.00022697431,0.8320635,0.0000546619,0.000107240834,0.0024186866,0.0004001966,0.10890843,0.04109136,0.012111636,0.002518674,0.00006985019],"about_ca_topic_score_codex":0.0016087512,"about_ca_topic_score_gemma":0.0016194006,"teacher_disagreement_score":0.0016087512,"about_ca_system_score_codex":0.00012563642,"about_ca_system_score_gemma":0.00034992248,"threshold_uncertainty_score":0.0031987429},"labels":[],"label_agreement":null},{"id":"W4385897358","doi":"10.1002/jmri.28964","title":"Probing Evidence of Cerebral White Matter Microstructural Disruptions in Ischemic Heart Disease Before and Following Cardiac Rehabilitation: A Diffusion Tensor <scp>MR</scp> Imaging Study","year":2023,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; Medicine; White matter; Diffusion MRI; Cardiology; Internal medicine; Population; Disease; Magnetic resonance imaging; Radiology","score_opus":0.01711768691857494,"score_gpt":0.32055421633645953,"score_spread":0.30343652941788457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385897358","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974126,0.00008179048,0.000029625402,0.000008024083,0.0000012025976,0.000008294055,0.00003875332,6.149072e-7,0.000090510664],"genre_scores_gemma":[0.9996791,0.000061627914,0.00007116814,0.000013077079,0.000007096512,0.000008299362,0.00011098559,5.2892466e-7,0.00004800777],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998703,0.000026484724,0.000017673347,0.000037395497,0.000020024003,0.00002816143],"domain_scores_gemma":[0.999316,0.00006365044,0.00029912862,0.00005725184,0.000103914186,0.00016017616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049418735,0.00021653807,0.00022482456,0.0005635655,0.000301706,0.00024863397,0.00022399567,0.0004387861,0.0006511789],"category_scores_gemma":[0.0008505114,0.00013902043,0.00024728096,0.00031238224,0.00031769773,0.00030193073,0.00029996247,0.0003282064,0.00014037728],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010804259,0.00036397373,0.9894593,0.000035712943,0.00009132047,0.0005697882,0.0002497731,0.00004863982,0.005210002,0.000012589041,0.00006433009,0.0028142023],"study_design_scores_gemma":[0.000007280074,0.00052287226,0.99868816,0.0000028908273,0.00001821598,0.000383164,0.000094985524,0.000031673546,0.00019978169,0.000005593854,0.0000434841,0.0000019039645],"about_ca_topic_score_codex":0.0023151196,"about_ca_topic_score_gemma":0.0035189847,"teacher_disagreement_score":0.0023151196,"about_ca_system_score_codex":0.00023517887,"about_ca_system_score_gemma":0.00027343738,"threshold_uncertainty_score":0.0046032667},"labels":[],"label_agreement":null},{"id":"W4385970839","doi":"10.1093/braincomms/fcad225","title":"Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Avid Radiopharmaceuticals; Alzheimer’s Research UK; Wolfson Foundation; Dementias Platform UK; University College London; UK Dementia Research Institute; National Institute for Health and Care Research; California State University, Bakersfield; Brain Research UK; Alzheimer's Society; Weston Brain Institute; Eli Lilly and Company; Alzheimer's Association","keywords":"Fractional anisotropy; White matter; Brain size; Diffusion MRI; Cardiology; Medicine; Internal medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.12804861734077327,"score_gpt":0.4265769917215861,"score_spread":0.2985283743808128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385970839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99957067,0.00011495093,0.000013718538,0.000010661809,0.00000255286,0.0000021365286,0.00012411273,0.0000012246863,0.00016002807],"genre_scores_gemma":[0.99947745,0.00006599108,0.000028405722,0.000011501207,0.000005226952,0.0000028663903,0.00021693324,7.833301e-7,0.00019088961],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999018,0.000015179497,0.000011318202,0.000023903896,0.000017647695,0.000030178102],"domain_scores_gemma":[0.9993926,0.00005951498,0.00023788403,0.000039502374,0.000084846455,0.00018565248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034327857,0.00030900165,0.00029931258,0.0008407355,0.00049569656,0.0006041356,0.00023357951,0.00053008366,0.0015328483],"category_scores_gemma":[0.0012501058,0.0002638391,0.00021673141,0.00044209414,0.00036625715,0.00041507615,0.00033045092,0.00038620163,0.00030874606],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023235762,0.00007839068,0.99694,0.000009887991,0.000039770814,0.0002722293,0.0002284836,0.000028689148,0.0010598153,0.000017986285,0.00008074558,0.0010117556],"study_design_scores_gemma":[0.0000019953764,0.000050106788,0.9996203,0.0000013364689,0.0000055518326,0.00014181489,0.00008413881,0.000013101562,0.000035515513,0.000012161106,0.000032805536,0.0000011744069],"about_ca_topic_score_codex":0.008710478,"about_ca_topic_score_gemma":0.011592231,"teacher_disagreement_score":0.008710478,"about_ca_system_score_codex":0.00018377896,"about_ca_system_score_gemma":0.00017435655,"threshold_uncertainty_score":0.01731956},"labels":[],"label_agreement":null},{"id":"W4386057060","doi":"10.1016/j.dib.2023.109513","title":"A population-averaged structural connectomic brain atlas dataset from 422 HCP-aging subjects","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Alliance de recherche numérique du Canada","keywords":"Diffusion MRI; Human Connectome Project; Connectome; White matter; Connectomics; Population; Spatial normalization; Neuroscience; Deep brain stimulation; Neuroinformatics; Segmentation; Atlas (anatomy); Artificial intelligence; Brain atlas; Computer science; Brain mapping; Medicine; Voxel; Magnetic resonance imaging; Psychology; Pathology; Parkinson's disease; Functional connectivity; Anatomy","score_opus":0.10906075944420866,"score_gpt":0.4016066765765479,"score_spread":0.29254591713233924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386057060","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039385006,0.0006928179,0.005407218,0.0002940871,0.00007734103,0.00018434154,0.94980633,0.0016622271,0.002490603],"genre_scores_gemma":[0.029735196,0.0002906676,0.0050190277,0.0001009215,0.000041419993,0.0006358671,0.9620828,0.00018610145,0.0019080391],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99973184,0.000036831138,0.000029443929,0.00012449149,0.000050022227,0.000027286815],"domain_scores_gemma":[0.99940073,0.00011406841,0.00006252133,0.0002161985,0.00014792327,0.000058429207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048976165,0.0011666857,0.0008966928,0.0016061249,0.0005804108,0.00066661846,0.0014473124,0.0010665695,0.015495826],"category_scores_gemma":[0.0018493817,0.00037339138,0.00076266733,0.0021054568,0.0003212607,0.0005101086,0.0010904284,0.0006898265,0.010282132],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010061982,0.00026920222,0.024285266,0.0015565846,0.00079725555,0.0023414192,0.00045315525,0.004365649,0.011454108,0.002301049,0.87610984,0.07506035],"study_design_scores_gemma":[0.00097611465,0.0004505181,0.29589516,0.0006752124,0.0009014757,0.013826452,0.00068095577,0.012247034,0.007950778,0.017011987,0.6490286,0.00035573306],"about_ca_topic_score_codex":0.01578568,"about_ca_topic_score_gemma":0.033175487,"teacher_disagreement_score":0.01578568,"about_ca_system_score_codex":0.00066611514,"about_ca_system_score_gemma":0.0009990617,"threshold_uncertainty_score":0.051838756},"labels":[],"label_agreement":null},{"id":"W4386070150","doi":"10.1101/2023.08.21.554083","title":"Multimodal Imaging Investigation of Rich Club Alterations in Alzheimer’s Disease and Mild Cognitive Impairment: Amyloid Deposition, Structural Atrophy, and Functional Activation Differences","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Neuroscience; Disease; Neuroimaging; White matter; Psychology; Diffusion MRI; Grey matter; Pathology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.045014613908132474,"score_gpt":0.2864632776217589,"score_spread":0.24144866371362642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386070150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99103206,0.0030503361,0.003866575,0.00019085284,0.000015437667,0.000027304106,0.00061190705,0.000034999874,0.0011705206],"genre_scores_gemma":[0.9969188,0.0005587012,0.0020255109,0.00003745775,0.000025483356,0.000019687035,0.00024089876,0.000007378274,0.00016616807],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997749,0.000096612384,0.000018935036,0.000056883087,0.000032769298,0.000019895704],"domain_scores_gemma":[0.9990522,0.00039000524,0.0002992596,0.000110642155,0.00007818777,0.000069572416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013617281,0.00035333887,0.00047183933,0.0017930296,0.00020564788,0.0006820279,0.00027445258,0.00033820167,0.0015451845],"category_scores_gemma":[0.0027686344,0.00015402316,0.00044999848,0.0010804995,0.00029897175,0.00044765326,0.000503908,0.0002463538,0.00009868845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00266194,0.00039207487,0.8668035,0.0013695471,0.005964121,0.001103052,0.00065443263,0.0031473308,0.054143567,0.0014472427,0.0015357,0.06077755],"study_design_scores_gemma":[0.000054822227,0.00032463553,0.9789128,0.0001260033,0.0016385916,0.0010824394,0.0003026083,0.006617347,0.0050955117,0.004945946,0.00087773724,0.000021552862],"about_ca_topic_score_codex":0.0012221052,"about_ca_topic_score_gemma":0.0022642121,"teacher_disagreement_score":0.0017930296,"about_ca_system_score_codex":0.00022120455,"about_ca_system_score_gemma":0.00021516677,"threshold_uncertainty_score":0.007201612},"labels":[],"label_agreement":null},{"id":"W4386116634","doi":"10.1002/hbm.26461","title":"Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion <scp>MRI</scp>","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; McGill University; Montreal Neurological Institute and Hospital; Western University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Canadian Open Neuroscience Platform; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampus; Diffusion MRI; In vivo; Neuroscience; Microstructure; Diffusion; Nuclear magnetic resonance; Magnetic resonance imaging; Chemistry; Psychology; Biology; Medicine; Physics; Crystallography; Radiology","score_opus":0.058902106859095804,"score_gpt":0.32545130136221667,"score_spread":0.26654919450312087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386116634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9271313,0.0024818757,0.06668079,0.00028904364,0.000019403315,0.000062309555,0.0010014783,0.00028442216,0.0020492864],"genre_scores_gemma":[0.9636447,0.0017810067,0.032924898,0.000115654984,0.000026277254,0.000052719428,0.00050837017,0.0000599413,0.0008865326],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999591,0.000009283998,0.0000037718767,0.000012560758,0.000010908741,0.0000043153937],"domain_scores_gemma":[0.9998584,0.000044566732,0.000035921916,0.000021547736,0.00002626142,0.000013410463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023830893,0.00021598689,0.00010123665,0.0005082357,0.00014774728,0.00035917977,0.00012326639,0.00023562035,0.00088729116],"category_scores_gemma":[0.00052076566,0.00016196903,0.00009264544,0.00022953209,0.0003280515,0.00029037948,0.00016254194,0.00018918181,0.00019186511],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002765116,0.00003784173,0.014046602,0.00027338267,0.00008744562,0.00065019866,0.00022755463,0.004829017,0.93848586,0.0007379643,0.00075565197,0.039591942],"study_design_scores_gemma":[0.00005744783,0.00075188896,0.37691802,0.0001159677,0.00018002176,0.008518312,0.00045050998,0.05818843,0.5420281,0.003125807,0.009580456,0.00008511292],"about_ca_topic_score_codex":0.0035844794,"about_ca_topic_score_gemma":0.0063917935,"teacher_disagreement_score":0.0035844794,"about_ca_system_score_codex":0.00014886403,"about_ca_system_score_gemma":0.00025549167,"threshold_uncertainty_score":0.0071272254},"labels":[],"label_agreement":null},{"id":"W4386133788","doi":"10.1016/j.bandl.2023.105300","title":"Treatment-induced neuroplasticity after anomia therapy in post-stroke aphasia: A systematic review of neuroimaging studies","year":2023,"lang":"en","type":"review","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Heart and Stroke Foundation of Canada","keywords":"Aphasia; Neuroimaging; Supramarginal gyrus; Psychology; MEDLINE; CINAHL; PsycINFO; Stroke (engine); Neuroplasticity; Neurorehabilitation; Meta-analysis; Physical medicine and rehabilitation; Rehabilitation; Clinical psychology; Functional magnetic resonance imaging; Medicine; Psychiatry; Neuroscience; Psychological intervention; Internal medicine","score_opus":0.12666905364009645,"score_gpt":0.43671730503225054,"score_spread":0.3100482513921541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386133788","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006286714,0.9990808,0.000033542394,0.00003949434,0.000029049568,0.00003063077,0.00009168629,0.000001927327,0.000064194464],"genre_scores_gemma":[0.0071653128,0.99226886,0.00018191739,0.00017456377,0.000037148697,0.000053329954,0.00007596228,0.000001659531,0.000041214833],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9982577,0.00041366956,0.0007676102,0.00023991824,0.0002595048,0.000061587314],"domain_scores_gemma":[0.9937889,0.004483522,0.0012747479,0.00007558896,0.00031307427,0.000064107735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027670064,0.0010438777,0.0068958956,0.0044289227,0.0003534098,0.0019649859,0.0012308083,0.0015640112,0.0030075812],"category_scores_gemma":[0.010216227,0.00058098114,0.0057976185,0.0048222444,0.00062864285,0.0012296822,0.0011151698,0.000920567,0.00018957347],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048049682,0.000038443904,0.0010816413,0.89291143,0.017184388,0.00014149623,0.00013720224,0.000119121774,0.0003308959,0.00016907416,0.0013800596,0.08602579],"study_design_scores_gemma":[0.00092367386,0.00067850255,0.018779268,0.6951592,0.24362205,0.0014075548,0.00053322315,0.00017802809,0.00059063727,0.00065554056,0.03733955,0.00013282149],"about_ca_topic_score_codex":0.005143855,"about_ca_topic_score_gemma":0.017844867,"teacher_disagreement_score":0.0068958956,"about_ca_system_score_codex":0.0012018455,"about_ca_system_score_gemma":0.0036801852,"threshold_uncertainty_score":0.014633536},"labels":[],"label_agreement":null},{"id":"W4386243593","doi":"10.1101/2023.08.28.555179","title":"Mapping caudolenticular gray matter bridges in the human brain striatum through diffusion magnetic resonance imaging and tractography","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Diffusion MRI; Putamen; White matter; Human brain; Caudate nucleus; Magnetic resonance imaging; Striatum; Nuclear magnetic resonance; Fractional anisotropy; Computer science; Physics; Artificial intelligence; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.03394549049788514,"score_gpt":0.28610593598965606,"score_spread":0.2521604454917709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386243593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.853105,0.0018009054,0.141212,0.0002821198,0.000016130036,0.000108590466,0.0013979081,0.0006823762,0.0013948831],"genre_scores_gemma":[0.90918285,0.0008131116,0.08791863,0.00004709855,0.000012077236,0.000059154703,0.0011071909,0.000118368145,0.0007416037],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985945,0.000038227383,0.000009622602,0.00004965354,0.00003318071,0.000009803571],"domain_scores_gemma":[0.9997608,0.00006471051,0.00007533028,0.000038611313,0.000042203894,0.000018304383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041538267,0.0003505121,0.00032602213,0.0011313542,0.00023582758,0.000917296,0.00026878147,0.000429107,0.00076394685],"category_scores_gemma":[0.0015075448,0.00023715045,0.00052276696,0.00074405095,0.0002832367,0.00041177587,0.00055019744,0.0002645822,0.00029097864],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008973004,0.0001993996,0.12095928,0.0008210309,0.0014609466,0.0017888296,0.0009962311,0.08859579,0.39767322,0.005554729,0.0042774063,0.37677574],"study_design_scores_gemma":[0.00009590429,0.000331705,0.2893992,0.0002750108,0.00039598762,0.0046848888,0.00046670425,0.5727145,0.11141876,0.011016509,0.00904742,0.00015338197],"about_ca_topic_score_codex":0.009049895,"about_ca_topic_score_gemma":0.02283169,"teacher_disagreement_score":0.009049895,"about_ca_system_score_codex":0.00033350984,"about_ca_system_score_gemma":0.0005944063,"threshold_uncertainty_score":0.017994404},"labels":[],"label_agreement":null},{"id":"W4386252129","doi":"10.1111/ejn.16135","title":"Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract‐Based Spatial Statistical analysis","year":2023,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Turun Yliopistollinen Keskussairaala; Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Alfred Kordelinin Säätiö","keywords":"Diffusion MRI; Diffusion; Encoding (memory); Statistical physics; Neuroscience; Computer science; Medicine; Physics; Biology; Radiology; Magnetic resonance imaging","score_opus":0.04305764631367952,"score_gpt":0.3744289100689669,"score_spread":0.33137126375528736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386252129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94792366,0.0032018805,0.047203824,0.00029142876,0.00017332296,0.00008773265,0.00023953883,0.00029311035,0.0005854711],"genre_scores_gemma":[0.9493486,0.0010710281,0.04820318,0.00008717129,0.000060255064,0.00016569773,0.00033243006,0.00033203082,0.0003996262],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99088085,0.005773803,0.0010357177,0.0010514851,0.0010868651,0.0001713627],"domain_scores_gemma":[0.9389587,0.04786401,0.005465272,0.0040753703,0.0025972633,0.0010394349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015337785,0.00084501144,0.0011471808,0.0006480758,0.0003660865,0.0010555474,0.00049356197,0.0005929569,0.0009931339],"category_scores_gemma":[0.06755967,0.0004407027,0.0011349726,0.00068507274,0.0007332611,0.0010612862,0.0008053734,0.0009246665,0.00021633973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.052583095,0.0013228998,0.26673362,0.0015085653,0.004094135,0.002272971,0.0018843862,0.06405274,0.2479576,0.0015764604,0.0015063434,0.35450718],"study_design_scores_gemma":[0.00069529045,0.02864652,0.5533553,0.00062161067,0.004832066,0.0036292656,0.0006753276,0.25243995,0.1446013,0.0033775992,0.00663771,0.00048802345],"about_ca_topic_score_codex":0.0021206057,"about_ca_topic_score_gemma":0.0024884227,"teacher_disagreement_score":0.015337785,"about_ca_system_score_codex":0.00048794225,"about_ca_system_score_gemma":0.0010663037,"threshold_uncertainty_score":0.08111489},"labels":[],"label_agreement":null},{"id":"W4386362772","doi":"10.1109/isbi53787.2023.10230661","title":"Explaining Anatomical Shape Variability: Supervised Disentangling with A Variational Graph Autoencoder","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Autoencoder; Artificial intelligence; Pattern recognition (psychology); Computer science; Diffusion MRI; Neuroimaging; Population; Graph; Scalar (mathematics); Laplace operator; Nonlinear dimensionality reduction; Tensor (intrinsic definition); Deep learning; Machine learning; Mathematics; Theoretical computer science; Dimensionality reduction; Magnetic resonance imaging","score_opus":0.062415642846957504,"score_gpt":0.33950134789361214,"score_spread":0.27708570504665464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386362772","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033339534,0.00022071657,0.9652681,0.00022665254,0.000022350652,0.000017393631,0.00008243219,0.00038665102,0.0004362905],"genre_scores_gemma":[0.8106996,0.00036008292,0.1838929,0.0004113955,0.000077027165,0.00010205599,0.0007279108,0.0002502088,0.003478737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996444,0.00011643072,0.000014974191,0.00012302637,0.000057077857,0.000044061868],"domain_scores_gemma":[0.99909663,0.00052963785,0.00010190156,0.00012578531,0.000097264645,0.000048697086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011219409,0.0009406888,0.0009575475,0.00063183333,0.0002473859,0.0006080542,0.001494846,0.0010839443,0.0008576093],"category_scores_gemma":[0.0027524543,0.0007009546,0.001099981,0.0006014475,0.0010168793,0.0010831878,0.0012994034,0.0016396013,0.0002886912],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008565118,0.000058078094,0.002582864,0.000048096066,0.00010063717,0.000085601285,0.000099943936,0.88311845,0.0064929947,0.011569644,0.001499152,0.09425898],"study_design_scores_gemma":[0.0000020285206,0.0000069477132,0.00011209299,0.0000018740437,0.000003150088,0.000009916366,0.0000022761553,0.99664515,0.00023521404,0.0028744051,0.000104398096,0.0000025684658],"about_ca_topic_score_codex":0.006740477,"about_ca_topic_score_gemma":0.009430029,"teacher_disagreement_score":0.006740477,"about_ca_system_score_codex":0.0006909062,"about_ca_system_score_gemma":0.0009655889,"threshold_uncertainty_score":0.013402522},"labels":[],"label_agreement":null},{"id":"W4386549227","doi":"10.1162/imag_a_00019","title":"Dual-encoded magnetization transfer and diffusion imaging and its application to tract-specific microstructure mapping","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Calgary; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canada First Research Excellence Fund; Réseau en Bio-Imagerie du Quebec; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Magnetization transfer; White matter; Tractography; Diffusion MRI; Voxel; Partial volume; Fractional anisotropy; Nuclear magnetic resonance; Nuclear medicine; Biomedical engineering; Materials science; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.032787579445728084,"score_gpt":0.3107966841154105,"score_spread":0.2780091046696824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386549227","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09450922,0.00085138396,0.9030174,0.00016985525,0.00002525853,0.00005680959,0.00009126497,0.00031591888,0.0009629593],"genre_scores_gemma":[0.3079631,0.00047559862,0.68999434,0.00006255595,0.000029177489,0.0000947572,0.00012207174,0.00008343343,0.0011749606],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998241,0.000051972977,0.00000982372,0.000047348385,0.000053238473,0.000013587344],"domain_scores_gemma":[0.99969506,0.00010319501,0.00007277,0.000052431864,0.00004870995,0.000027819573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005662806,0.00045400832,0.000320225,0.00057237607,0.00018785725,0.00042654722,0.00048594773,0.0006629021,0.00080021436],"category_scores_gemma":[0.0017283561,0.0003501155,0.0002329632,0.0003833009,0.00044193843,0.00052539323,0.0006897893,0.0004627617,0.00023124392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027623278,0.00004642046,0.0014977058,0.00022721465,0.00004749832,0.00022215389,0.00007532744,0.010080047,0.86254543,0.003804654,0.00028296336,0.1208944],"study_design_scores_gemma":[0.00008986446,0.0006122992,0.010807263,0.000042707215,0.00011220392,0.004669075,0.00003942366,0.39161077,0.57261837,0.008490814,0.010788544,0.00011866136],"about_ca_topic_score_codex":0.00059001526,"about_ca_topic_score_gemma":0.0010726558,"teacher_disagreement_score":0.00080021436,"about_ca_system_score_codex":0.00019228781,"about_ca_system_score_gemma":0.0002906088,"threshold_uncertainty_score":0.0029947758},"labels":[],"label_agreement":null},{"id":"W4386638349","doi":"10.1038/s41467-023-40999-z","title":"Non-invasive assessment of normal and impaired iron homeostasis in the brain","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation; Israel Science Foundation","keywords":"Iron homeostasis; Homeostasis; Ferritin; Transferrin; Ferrous; Human brain; In vivo; Magnetic resonance imaging; Biology; Ex vivo; Neuroscience; Cell biology; Pathology; Medicine; Chemistry; Biochemistry; Metabolism; Biotechnology","score_opus":0.05750786017996696,"score_gpt":0.4104235801183071,"score_spread":0.35291571993834014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386638349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7328859,0.008059726,0.24950886,0.00059090456,0.00016116146,0.00022143753,0.00071551057,0.0009461435,0.006910348],"genre_scores_gemma":[0.8809864,0.0036676985,0.10826973,0.00042836802,0.000088024884,0.00032613624,0.00038676432,0.00016119,0.005685775],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999801,0.0000642266,0.000008236173,0.000049416285,0.00005815275,0.000018996701],"domain_scores_gemma":[0.9997278,0.00010721175,0.000050496732,0.000026285425,0.000054636654,0.000033609787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056018913,0.00046268667,0.00023585476,0.0006126448,0.00018255172,0.0003932493,0.00031330835,0.00056713837,0.001313463],"category_scores_gemma":[0.00054747664,0.0002150429,0.000108636785,0.00018048192,0.000436465,0.00052186433,0.00034765506,0.0004899162,0.00029148455],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012691661,0.000024151668,0.0005883302,0.00009177073,0.00000979945,0.00011110815,0.00002545505,0.00009817227,0.9935586,0.0001621829,0.00017746298,0.005025998],"study_design_scores_gemma":[0.000022521157,0.000581903,0.01664358,0.000039449074,0.00007537088,0.0023873283,0.00012945355,0.007938288,0.96779066,0.00086834165,0.003487453,0.00003572659],"about_ca_topic_score_codex":0.00048410697,"about_ca_topic_score_gemma":0.0009695519,"teacher_disagreement_score":0.001313463,"about_ca_system_score_codex":0.000176028,"about_ca_system_score_gemma":0.00029221966,"threshold_uncertainty_score":0.004393995},"labels":[],"label_agreement":null},{"id":"W4386727224","doi":"10.1101/2023.09.14.557689","title":"A hierarchical atlas of the human cerebellum for functional precision mapping","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Atlas (anatomy); Computer science; Cerebellum; Cartography; Artificial intelligence; Geography; Neuroscience; Biology; Anatomy","score_opus":0.0871225521308664,"score_gpt":0.31077201962532197,"score_spread":0.22364946749445558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386727224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014042893,0.00061922724,0.9576391,0.00038133227,0.00012248948,0.00027107482,0.009370378,0.0065437844,0.011009755],"genre_scores_gemma":[0.119364575,0.00087889377,0.85611266,0.0001927828,0.0000936088,0.0009175191,0.011274732,0.0029542192,0.008211069],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946886,0.00013419494,0.000056495184,0.00012254952,0.00017488771,0.000043067692],"domain_scores_gemma":[0.9993111,0.00018242218,0.00008809019,0.00021996406,0.0001461429,0.000052358322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008717315,0.00056981284,0.0005245286,0.002130367,0.0007221592,0.002119254,0.00083487143,0.0011330254,0.012785029],"category_scores_gemma":[0.0023745878,0.0006514896,0.00088342244,0.0020760628,0.0006159463,0.0009907542,0.0015177035,0.00150616,0.0036692165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005894611,0.00017020623,0.007859905,0.0014870611,0.00032720243,0.001252046,0.0017371435,0.074573964,0.18540424,0.16880788,0.13417228,0.4236187],"study_design_scores_gemma":[0.00027913591,0.00034987825,0.039623667,0.00040258528,0.00031647203,0.0059153326,0.00032008282,0.2564741,0.063299425,0.14924572,0.4835064,0.00026719013],"about_ca_topic_score_codex":0.0049345167,"about_ca_topic_score_gemma":0.010522785,"teacher_disagreement_score":0.012785029,"about_ca_system_score_codex":0.00084457116,"about_ca_system_score_gemma":0.0028473441,"threshold_uncertainty_score":0.042770147},"labels":[],"label_agreement":null},{"id":"W4386760135","doi":"10.1097/md.0000000000034979","title":"Combining ADC values in DWI with rCBF values in arterial spin labeling (ASL) for the diagnosis of mild cognitive impairment (MCI)","year":2023,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Frontal lobe; Medicine; Montreal Cognitive Assessment; Occipital lobe; Cerebral blood flow; Temporal lobe; Cardiology; Lobe; Nuclear medicine; Audiology; Cognitive impairment; Internal medicine; Cognition; Radiology; Psychiatry; Pathology; Epilepsy","score_opus":0.10525494736136358,"score_gpt":0.4050164015564453,"score_spread":0.2997614541950817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386760135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99576,0.0015912387,0.0014274262,0.000057712492,0.000021629929,0.000042517244,0.00020120502,0.000035063833,0.0008632031],"genre_scores_gemma":[0.99675435,0.0003135677,0.0024486664,0.000020646796,0.000026365855,0.000025385434,0.00019565347,0.000003578645,0.00021190986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993795,0.00024517401,0.000104324936,0.00010498136,0.00012055517,0.000045341305],"domain_scores_gemma":[0.998431,0.00046152357,0.00052196474,0.00010416928,0.00031480676,0.00016652491],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002027314,0.0006730901,0.00051473186,0.0028142224,0.00025967194,0.00065284944,0.00036773641,0.0005213681,0.0005788799],"category_scores_gemma":[0.003349693,0.0002906631,0.000267376,0.0009552553,0.00030660914,0.00059487554,0.0003770688,0.0003874957,0.00032472456],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069102045,0.000094174946,0.9703837,0.000086142,0.00017330826,0.0002982522,0.00008799637,0.00017855456,0.0055323914,0.000027676453,0.00017199303,0.022274733],"study_design_scores_gemma":[0.000050158098,0.0008230031,0.9894503,0.000032899065,0.00024285159,0.0021236667,0.00017041956,0.003437328,0.0027044655,0.00019594046,0.00074587355,0.0000230125],"about_ca_topic_score_codex":0.001265293,"about_ca_topic_score_gemma":0.0036289473,"teacher_disagreement_score":0.0028142224,"about_ca_system_score_codex":0.00018683831,"about_ca_system_score_gemma":0.00023462075,"threshold_uncertainty_score":0.010721624},"labels":[],"label_agreement":null},{"id":"W4387036902","doi":"10.21203/rs.3.rs-3361804/v1","title":"Application of Diffusion Tensor Imaging of the Facial Nerve in Preoperative Planning for Large Vestibular Schwannoma","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Diffusion MRI; Schwannoma; Facial nerve; Cochrane Library; Vestibular system; Neuronavigation; Fractional anisotropy; Acoustic neuroma; Radiology; Magnetic resonance imaging; Meta-analysis; Surgery; Internal medicine","score_opus":0.1504520102117505,"score_gpt":0.4763909987498768,"score_spread":0.3259389885381263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387036902","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010458531,0.98644173,0.00096738135,0.0005093745,0.00021239092,0.00014946474,0.0004294983,0.000012629775,0.00081895984],"genre_scores_gemma":[0.27316636,0.71733725,0.006901002,0.00064773014,0.0006837542,0.00035745153,0.00059856044,0.000019911204,0.00028807297],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.994553,0.0019580172,0.0018028487,0.00039625695,0.0011899817,0.00009992513],"domain_scores_gemma":[0.95965034,0.02859524,0.007944009,0.00068175566,0.002954524,0.00017419245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01118258,0.0006855064,0.0022559392,0.005211545,0.0002988099,0.0018261593,0.00069557346,0.00084703165,0.0017095178],"category_scores_gemma":[0.04380178,0.00037945257,0.00375916,0.003448681,0.0005343273,0.00148916,0.0007128841,0.00062355056,0.00017527364],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025057234,0.00009046811,0.04344773,0.41242418,0.020024149,0.0006021136,0.00043591225,0.001020043,0.0021336493,0.00049931253,0.0036324654,0.5131842],"study_design_scores_gemma":[0.001665396,0.003293246,0.19284414,0.5111871,0.21296968,0.0064797327,0.0017731168,0.002885726,0.007837943,0.003735568,0.054894783,0.0004335505],"about_ca_topic_score_codex":0.003489607,"about_ca_topic_score_gemma":0.006512557,"teacher_disagreement_score":0.01118258,"about_ca_system_score_codex":0.0009888503,"about_ca_system_score_gemma":0.0032269168,"threshold_uncertainty_score":0.059139848},"labels":[],"label_agreement":null},{"id":"W4387059333","doi":"10.1101/2023.09.25.559330","title":"White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"","keywords":"White matter; Tractography; Diffusion MRI; Neuroscience; Brain morphometry; Biology; Human brain; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.028387914403368672,"score_gpt":0.2979703062748655,"score_spread":0.2695823918714968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387059333","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691886,0.000601077,0.006260965,0.00016395134,0.0000075116204,0.000012027393,0.02264326,0.00014698143,0.000975654],"genre_scores_gemma":[0.97221047,0.00044442847,0.009035293,0.00003738687,0.000012468857,0.000041617353,0.017110428,0.00007889532,0.0010289914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980396,0.000045529585,0.000017675748,0.00008290451,0.00002940323,0.000020559228],"domain_scores_gemma":[0.9986922,0.00022311613,0.00046658982,0.0002831688,0.00023903449,0.00009585642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085354905,0.00028523986,0.00023934979,0.0013262162,0.00024134251,0.0005198749,0.00022226098,0.00028099993,0.0020918588],"category_scores_gemma":[0.0028014344,0.00018942621,0.00025233752,0.0009423888,0.00032497634,0.0004638375,0.0005251324,0.00026624932,0.00037173097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078458554,0.00011257468,0.8591694,0.00040893754,0.00094307266,0.00040029243,0.0010232994,0.00925244,0.052000683,0.0025849703,0.009896671,0.06342319],"study_design_scores_gemma":[0.000009565994,0.00005348984,0.98630905,0.00005798802,0.00008509262,0.0006034037,0.00011741651,0.0038191082,0.003188762,0.0031356355,0.0025986359,0.000021673357],"about_ca_topic_score_codex":0.0061770133,"about_ca_topic_score_gemma":0.013575291,"teacher_disagreement_score":0.0061770133,"about_ca_system_score_codex":0.00030449306,"about_ca_system_score_gemma":0.00042368963,"threshold_uncertainty_score":0.012282133},"labels":[],"label_agreement":null},{"id":"W4387059515","doi":"10.1038/s41537-023-00392-7","title":"A systematic review of neuroimaging studies of clozapine-resistant schizophrenia","year":2023,"lang":"en","type":"review","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Clozapine; Neuroimaging; Schizophrenia (object-oriented programming); Dorsolateral prefrontal cortex; Magnetic resonance imaging; Antipsychotic; Diffusion MRI; Psychology; Medicine; Neuroscience; Prefrontal cortex; Psychiatry; Cognition; Radiology","score_opus":0.1824756410072629,"score_gpt":0.44717568970011473,"score_spread":0.2647000486928518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387059515","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010840526,0.9977457,0.00011060942,0.00017658621,0.00008637106,0.000101833284,0.00048031702,0.000006906157,0.00020754425],"genre_scores_gemma":[0.009247503,0.98933744,0.00041750722,0.0003409812,0.00005820841,0.00020267558,0.00030804382,0.0000040426075,0.00008374788],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99629825,0.0010058234,0.0017636487,0.00034789907,0.00048044333,0.000103951825],"domain_scores_gemma":[0.9876909,0.008330761,0.002452302,0.00017972397,0.0011619537,0.00018430913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035693015,0.0013161114,0.006137409,0.011146536,0.0005168018,0.0017805225,0.0015417153,0.0012738549,0.0038407154],"category_scores_gemma":[0.01869184,0.0007593105,0.004372326,0.011749145,0.0006792108,0.0017504102,0.0012377441,0.0006823533,0.00028728106],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014228553,0.00000809167,0.0008118601,0.9565435,0.0063385936,0.00018534748,0.00014643063,0.00006565548,0.00023698596,0.00016379665,0.0018267148,0.03353075],"study_design_scores_gemma":[0.0002124018,0.00023500831,0.009574148,0.86432815,0.086818255,0.0010970032,0.00039647406,0.00006706659,0.00024879226,0.00033715367,0.036636785,0.000048724512],"about_ca_topic_score_codex":0.0099202385,"about_ca_topic_score_gemma":0.031250443,"teacher_disagreement_score":0.011146536,"about_ca_system_score_codex":0.0023023502,"about_ca_system_score_gemma":0.0088153,"threshold_uncertainty_score":0.019724965},"labels":[],"label_agreement":null},{"id":"W4387104808","doi":"10.31219/osf.io/qpmwk","title":"Diffusion MRI of the hippocampus","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Hippocampus; Neuroscience; Diffusion MRI; Cognition; Computer science; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.09679997249347998,"score_gpt":0.3746550518329754,"score_spread":0.27785507933949544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387104808","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12835425,0.3926282,0.3771392,0.010986522,0.0016963993,0.00020578383,0.0034697838,0.0017491668,0.083770685],"genre_scores_gemma":[0.55139446,0.2403086,0.18118031,0.0025427171,0.0018224531,0.00020424087,0.001789698,0.00046990768,0.020287618],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99987566,0.00003413012,0.000008999308,0.000033679742,0.00003480258,0.000012652653],"domain_scores_gemma":[0.9998173,0.000062956366,0.000025093472,0.000018660692,0.0000556274,0.000020336473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004345822,0.0004045401,0.00031551212,0.000925955,0.00018358963,0.0006568888,0.00027209026,0.00076893053,0.0022815631],"category_scores_gemma":[0.0011843961,0.00024507113,0.00018878377,0.0006489241,0.000445012,0.001065924,0.00048656674,0.00067441125,0.0010762659],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045991052,0.00005551308,0.004028089,0.004909798,0.00029626928,0.0022455382,0.00068324857,0.0049042106,0.53063995,0.04592563,0.03375485,0.37209705],"study_design_scores_gemma":[0.00016565014,0.0006500553,0.027987614,0.0022242873,0.00046751963,0.038899723,0.00070967246,0.018516762,0.2348671,0.11454421,0.5606848,0.0002825605],"about_ca_topic_score_codex":0.001107561,"about_ca_topic_score_gemma":0.0012692352,"teacher_disagreement_score":0.0022815631,"about_ca_system_score_codex":0.00026541573,"about_ca_system_score_gemma":0.00041045787,"threshold_uncertainty_score":0.007632613},"labels":[],"label_agreement":null},{"id":"W4387139287","doi":"10.1101/2023.09.26.559530","title":"Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute; Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; Université de Sherbrooke","funders":"National Institutes of Health","keywords":"Distortion (music); Image quality; Preprocessor; Artificial intelligence; Diffusion MRI; Computer vision; Spinal cord; Computer science; Tractography; White matter; Image processing; Contrast (vision); Pattern recognition (psychology); Image (mathematics); Medicine; Magnetic resonance imaging; Radiology; Neuroscience; Psychology","score_opus":0.05972007701938037,"score_gpt":0.3414014745011572,"score_spread":0.28168139748177684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387139287","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9604951,0.0020585856,0.035505433,0.0001963802,0.00015147065,0.0001591543,0.0003505165,0.0005290426,0.00055434066],"genre_scores_gemma":[0.9473608,0.0008121397,0.049827393,0.00018963798,0.000049691167,0.00010745573,0.0008641679,0.00031422474,0.00047449392],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989035,0.00040715336,0.00016473231,0.00019785739,0.00023322325,0.00009354377],"domain_scores_gemma":[0.99117076,0.0056236144,0.0012231068,0.00071244803,0.0010446802,0.00022542001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021398612,0.00090597983,0.00055887294,0.0006403655,0.00045092512,0.0010445258,0.0005345048,0.0007028359,0.0009211176],"category_scores_gemma":[0.01616749,0.00026893758,0.00049363344,0.0006106377,0.00051768555,0.00058235385,0.00047361926,0.00045631244,0.00023767425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00842064,0.00068492355,0.029984128,0.0016183585,0.00081123726,0.000671938,0.0003624678,0.045024674,0.8020902,0.00040855224,0.0010219454,0.10890082],"study_design_scores_gemma":[0.00041647977,0.010327894,0.13638306,0.00030478885,0.001373514,0.001580231,0.0003581491,0.118108995,0.7261491,0.0008221741,0.003951318,0.00022429164],"about_ca_topic_score_codex":0.0019899076,"about_ca_topic_score_gemma":0.0022248717,"teacher_disagreement_score":0.0021398612,"about_ca_system_score_codex":0.00028800365,"about_ca_system_score_gemma":0.0005276039,"threshold_uncertainty_score":0.011316836},"labels":[],"label_agreement":null},{"id":"W4387152047","doi":"10.48550/arxiv.2309.15053","title":"Thalamic nuclei segmentation from T$_1$-weighted MRI: unifying and benchmarking state-of-the-art methods with young and old cohorts","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Pfizer; Novartis Pharmaceuticals Corporation; Eisai; U.S. Department of Defense; Meso Scale Diagnostics; Servier; BioClinica; Bristol-Myers Squibb; Eli Lilly and Company; Biogen","keywords":"Human Connectome Project; Neuroimaging; Thalamus; Neuroscience; Segmentation; Cognition; Alzheimer's disease; Disease; Connectome; Psychology; Medicine; Artificial intelligence; Computer science; Pathology; Functional connectivity","score_opus":0.10626338864023957,"score_gpt":0.28069112688633996,"score_spread":0.1744277382461004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387152047","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8013934,0.022193285,0.15002091,0.0013156072,0.0009799744,0.00078215066,0.009241797,0.0072795344,0.0067932843],"genre_scores_gemma":[0.8175565,0.006195854,0.13489331,0.000870811,0.00051343854,0.00045727572,0.03227006,0.0032199076,0.004022889],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99809676,0.00043211007,0.00021291,0.00069484074,0.0004000533,0.00016344797],"domain_scores_gemma":[0.9966259,0.0012760635,0.00029683742,0.0006389756,0.00084879366,0.00031350512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069868728,0.0019109516,0.0012611666,0.0038916052,0.0007916892,0.0030346538,0.002334394,0.0022176492,0.0013217239],"category_scores_gemma":[0.013096497,0.0006518799,0.001932111,0.0012205662,0.0012292659,0.001599666,0.0025590395,0.0012614093,0.0014282573],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005021286,0.0006307014,0.16364233,0.0022849888,0.0049473243,0.0019464708,0.0025800178,0.16664468,0.040016845,0.0042492035,0.03129482,0.5767413],"study_design_scores_gemma":[0.0005394508,0.003276501,0.1388956,0.0013958556,0.0026590265,0.0061220285,0.0024892597,0.7276908,0.063314974,0.013246413,0.039815266,0.0005548746],"about_ca_topic_score_codex":0.017099522,"about_ca_topic_score_gemma":0.02616515,"teacher_disagreement_score":0.017099522,"about_ca_system_score_codex":0.0011598344,"about_ca_system_score_gemma":0.0014582318,"threshold_uncertainty_score":0.03695053},"labels":[],"label_agreement":null},{"id":"W4387187092","doi":"10.3390/brainsci13101386","title":"The Challenge of Diffusion Magnetic Resonance Imaging in Cerebral Palsy: A Proposed Method to Identify White Matter Pathways","year":2023,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université de Sherbrooke; Centre for Interdisciplinary Research in Rehabilitation","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"White matter; Magnetic resonance imaging; Diffusion MRI; Neuroimaging; Medicine; Cerebral palsy; Computer science; Medical physics; Nuclear medicine; Psychology; Radiology; Neuroscience; Physical medicine and rehabilitation","score_opus":0.07929878459541224,"score_gpt":0.40214479376355544,"score_spread":0.3228460091681432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387187092","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01440247,0.001297446,0.9812083,0.00086542155,0.000066217464,0.0000709987,0.00022648413,0.0011625768,0.00070004683],"genre_scores_gemma":[0.098480366,0.0020466135,0.8964889,0.00014444847,0.00007306482,0.00019090524,0.00044773513,0.00036269796,0.0017652826],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99921346,0.00021757242,0.00007087781,0.00023270187,0.0002147761,0.000050553317],"domain_scores_gemma":[0.9984785,0.0004744391,0.0001555235,0.00025662454,0.0005292039,0.00010567981],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002645046,0.0010064878,0.0007549245,0.0018820373,0.00069369504,0.0027579647,0.0012627166,0.0014219128,0.001764711],"category_scores_gemma":[0.0057386938,0.00055501924,0.0007082202,0.0015428961,0.00082104973,0.0015419363,0.0015042953,0.0013479488,0.0012608687],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028911387,0.000086236985,0.011141382,0.0009129326,0.0002730442,0.00083112426,0.0005534159,0.023444366,0.096359536,0.016840167,0.0065234615,0.8427452],"study_design_scores_gemma":[0.000108961096,0.00037850064,0.024525264,0.0004254104,0.00044261423,0.009106498,0.0006382233,0.730229,0.11955937,0.055128414,0.059178535,0.00027915672],"about_ca_topic_score_codex":0.003401345,"about_ca_topic_score_gemma":0.005622518,"teacher_disagreement_score":0.003401345,"about_ca_system_score_codex":0.0006049322,"about_ca_system_score_gemma":0.0023597023,"threshold_uncertainty_score":0.013988495},"labels":[],"label_agreement":null},{"id":"W4387211202","doi":"10.1007/978-3-031-43999-5_42","title":"InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University","funders":"","keywords":"Computer science; Generative model; Real-time MRI; Diffusion MRI; Artificial intelligence; Superresolution; Resolution (logic); Image resolution; Generative grammar; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging; Image (mathematics); Radiology","score_opus":0.09815763616661491,"score_gpt":0.33739609649054025,"score_spread":0.23923846032392534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387211202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010217463,0.0004822602,0.99596465,0.00012990122,0.000050928396,0.000012051326,0.00013366005,0.001175877,0.001028964],"genre_scores_gemma":[0.040742673,0.0021002954,0.9433848,0.00016077659,0.00013677138,0.000076781376,0.0009186894,0.0010184066,0.011460846],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982494,0.00003436065,0.000008749328,0.00004446527,0.000074449046,0.00001302037],"domain_scores_gemma":[0.99975985,0.00009986961,0.00002137032,0.00006244099,0.000039207345,0.000017252689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045805107,0.00082806655,0.00073275715,0.0005419718,0.00018585396,0.0011059237,0.001027636,0.00119136,0.0053892657],"category_scores_gemma":[0.000929718,0.0006340707,0.00097526633,0.00080736505,0.0004651417,0.0014640953,0.0012233427,0.0013925014,0.004223841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019141227,0.00007676909,0.00025471076,0.00049521675,0.0001316038,0.00034141794,0.00016493959,0.16122891,0.06447831,0.10132114,0.032777395,0.6385381],"study_design_scores_gemma":[0.00001715745,0.000039637805,0.00018585885,0.00002889115,0.000023095978,0.0005141123,0.000014799562,0.91809434,0.0147246625,0.04189963,0.024421,0.00003681158],"about_ca_topic_score_codex":0.0011136715,"about_ca_topic_score_gemma":0.0015011515,"teacher_disagreement_score":0.0053892657,"about_ca_system_score_codex":0.00029406033,"about_ca_system_score_gemma":0.00043993813,"threshold_uncertainty_score":0.018028915},"labels":[],"label_agreement":null},{"id":"W4387233484","doi":"10.1016/j.neuroimage.2023.120387","title":"High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Template; Spatial normalization; Diffusion MRI; Neuroimaging; Computer science; Artificial intelligence; Psychology; Voxel; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.025625918337278883,"score_gpt":0.3125989924006837,"score_spread":0.2869730740634048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387233484","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49608126,0.0013357333,0.47765315,0.0003560719,0.000119511045,0.00095997733,0.012183735,0.003019722,0.008290867],"genre_scores_gemma":[0.49701846,0.0006150169,0.48129413,0.00015924757,0.000039547198,0.0011424535,0.014975963,0.0008083805,0.003946813],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99934155,0.00014121654,0.0001207926,0.00018156409,0.00017917041,0.000035640598],"domain_scores_gemma":[0.9987256,0.00021647484,0.000218186,0.00043340723,0.0003401356,0.00006610142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001889874,0.0005500223,0.00050396426,0.0017086472,0.00052659,0.0015289366,0.0008201485,0.000571776,0.0021476327],"category_scores_gemma":[0.004620073,0.00048494153,0.00076017063,0.0015437353,0.0004572152,0.00081037683,0.0009602861,0.0005216843,0.0010213081],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018597796,0.0004167429,0.10880728,0.0016521381,0.00084792956,0.00280274,0.007313609,0.03990418,0.271707,0.037980337,0.039738376,0.48696992],"study_design_scores_gemma":[0.00019407792,0.0010108177,0.5571866,0.00035295356,0.0007079874,0.012747402,0.0021039704,0.12057893,0.12886396,0.02515612,0.15061498,0.00048213874],"about_ca_topic_score_codex":0.006316172,"about_ca_topic_score_gemma":0.013287922,"teacher_disagreement_score":0.006316172,"about_ca_system_score_codex":0.0006802162,"about_ca_system_score_gemma":0.0014050505,"threshold_uncertainty_score":0.012558818},"labels":[],"label_agreement":null},{"id":"W4387244433","doi":"10.1101/2023.09.29.560251","title":"Quantifying myelin density in the feline auditory cortex","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Auditory cortex; Neuroscience; Myelin; Cortex (anatomy); Cerebral cortex; Biology; Psychology; Central nervous system","score_opus":0.1024141935882349,"score_gpt":0.3348089771566043,"score_spread":0.2323947835683694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387244433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9818646,0.0011068414,0.014607862,0.00004716175,0.000008591087,0.00001932038,0.0004569071,0.00016859082,0.001720074],"genre_scores_gemma":[0.987323,0.00045621613,0.010711377,0.000025733782,0.000004301707,0.000016020596,0.00024749836,0.000028583561,0.0011872542],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999008,0.000011439065,0.000005498352,0.000039551644,0.000027850385,0.000014828557],"domain_scores_gemma":[0.9997067,0.00006784612,0.000100425976,0.000023290635,0.00006414684,0.00003756594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029429366,0.00020499536,0.00013391071,0.0015500844,0.00023552332,0.0003043616,0.00013715557,0.0003300857,0.0012578466],"category_scores_gemma":[0.00040628714,0.0000998027,0.000072079674,0.00027157273,0.00042476473,0.00028730734,0.0002915529,0.00023383109,0.00018067735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013827223,0.000011336412,0.005582786,0.000072965726,0.000015399475,0.00008071488,0.00011853462,0.00039439823,0.98593277,0.00030147762,0.000077176825,0.0072742286],"study_design_scores_gemma":[0.00000846131,0.00032242012,0.26621893,0.000066118366,0.00006358469,0.0013853098,0.00036529932,0.005836682,0.72176486,0.0008052148,0.0031356502,0.0000274987],"about_ca_topic_score_codex":0.0025394931,"about_ca_topic_score_gemma":0.0033707845,"teacher_disagreement_score":0.0025394931,"about_ca_system_score_codex":0.00031457888,"about_ca_system_score_gemma":0.00015016465,"threshold_uncertainty_score":0.005049467},"labels":[],"label_agreement":null},{"id":"W4387336768","doi":"10.1186/s13195-023-01309-3","title":"In vivo cortical diffusion imaging relates to Alzheimer’s disease neuropathology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s Research & Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; University of California, San Diego; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Neuropathology; Cerebral amyloid angiopathy; Diffusion MRI; Pathology; Neuroimaging; Neuroscience; White matter; Neurology; Neurodegeneration; Medicine; Lewy body; Alzheimer's disease; Psychology; Dementia; Disease; Magnetic resonance imaging; Radiology","score_opus":0.23715601182103507,"score_gpt":0.48136043609076024,"score_spread":0.24420442426972516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387336768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99675554,0.0015806457,0.0006820017,0.000040670948,0.0000040770346,0.000007811495,0.00015305322,0.000008744414,0.00076742755],"genre_scores_gemma":[0.9992712,0.00027112587,0.00026385245,0.0000061190526,0.000008944018,0.0000026431787,0.000091478665,0.000001861435,0.0000827654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99974245,0.00006977249,0.000045678476,0.00007229553,0.00004111096,0.000028773278],"domain_scores_gemma":[0.9984145,0.00035089444,0.0008486562,0.000121533376,0.00018598144,0.00007841428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006105894,0.00032864223,0.00023061421,0.0012669777,0.0001896534,0.00057125115,0.00016688065,0.00021912385,0.001245686],"category_scores_gemma":[0.0020073336,0.00015463916,0.00018154147,0.0006387651,0.00031497382,0.0003354259,0.00024257813,0.00019358308,0.00014840101],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058613624,0.00004221437,0.9665078,0.000113264614,0.00027500856,0.00046833363,0.00015954023,0.0003405889,0.021693923,0.0001183034,0.00013397785,0.009560932],"study_design_scores_gemma":[0.000002909813,0.000060732436,0.99611807,0.00000790381,0.000043358297,0.0011948114,0.00005686338,0.00031265407,0.0018919561,0.00015158349,0.00015566227,0.0000034663603],"about_ca_topic_score_codex":0.0013096854,"about_ca_topic_score_gemma":0.0015996699,"teacher_disagreement_score":0.0013096854,"about_ca_system_score_codex":0.00021648296,"about_ca_system_score_gemma":0.0001479352,"threshold_uncertainty_score":0.004167199},"labels":[],"label_agreement":null},{"id":"W4387429097","doi":"10.1007/s00429-023-02714-y","title":"Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation","year":2023,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; McDonnell Center for Systems Neuroscience; European Commission","keywords":"White matter; Tractography; Diffusion MRI; Neuroscience; Grey matter; Cognition; Voxel; Artificial intelligence; Computer science; Pattern recognition (psychology); Connectomics; Psychology; Connectome; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.018166065083697964,"score_gpt":0.2952964809994426,"score_spread":0.27713041591574467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387429097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30411103,0.00067262945,0.68797433,0.00040105556,0.0000823391,0.00006236728,0.0005902949,0.00211999,0.0039858646],"genre_scores_gemma":[0.61248493,0.00066472206,0.37682307,0.00026409843,0.00008582668,0.00017722142,0.0012109361,0.00168034,0.006609003],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999126,0.000017686909,0.000004827075,0.000028207052,0.000019050967,0.000017592518],"domain_scores_gemma":[0.9997396,0.00010357842,0.000036442136,0.00004997565,0.00004434413,0.000026102154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059508113,0.0010297779,0.0005257073,0.0009587444,0.00042114913,0.0012932362,0.00058203505,0.0010194941,0.0051199705],"category_scores_gemma":[0.0013085802,0.00041583553,0.00046828587,0.00048584052,0.00043964363,0.0015752284,0.0005595242,0.00094557484,0.00092744286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007007638,0.00026171576,0.006197385,0.0003417642,0.00022420623,0.0001847941,0.00018860497,0.019086529,0.71452975,0.006352349,0.002105345,0.24982676],"study_design_scores_gemma":[0.000117935364,0.0003839176,0.054128837,0.0000783618,0.0004164295,0.0015580502,0.0001921578,0.4402262,0.47135502,0.02115447,0.01025313,0.00013553683],"about_ca_topic_score_codex":0.0015083208,"about_ca_topic_score_gemma":0.004955067,"teacher_disagreement_score":0.0051199705,"about_ca_system_score_codex":0.00027789688,"about_ca_system_score_gemma":0.000635803,"threshold_uncertainty_score":0.01712805},"labels":[],"label_agreement":null},{"id":"W4387453483","doi":"10.1101/2023.10.04.560912","title":"Automated Surface-Based Segmentation of Deep Gray Matter Regions Based on Diffusion Tensor Images Reveals Unique Age Trajectories Over the Healthy Lifespan","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Globus pallidus; Human Connectome Project; Voxel; Segmentation; Fractional anisotropy; Artificial intelligence; Psychology; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Computer science; Medicine; Basal ganglia; Radiology; Functional connectivity","score_opus":0.03724042871984424,"score_gpt":0.3073455149282868,"score_spread":0.2701050862084426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387453483","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9232805,0.00064036,0.07370598,0.00008477071,0.000027008153,0.00006136628,0.000858696,0.0007336136,0.0006077522],"genre_scores_gemma":[0.9359132,0.00025899193,0.061609108,0.000027588498,0.000016306827,0.000040878316,0.001291124,0.00014704642,0.00069573644],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99976724,0.00005254643,0.000017988248,0.0000916025,0.000048302165,0.0000223248],"domain_scores_gemma":[0.9992859,0.0001688286,0.00018025695,0.0001343117,0.00019692429,0.000033898872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091445807,0.00042801828,0.00045488664,0.0017440626,0.00025162712,0.0007606474,0.00030778444,0.00049612555,0.0007563341],"category_scores_gemma":[0.0017545,0.00022092504,0.0004703684,0.0005287759,0.0002684145,0.00043781663,0.00040656532,0.00024750954,0.00044562307],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012327216,0.00020849405,0.17272611,0.00037176986,0.00071887183,0.000560534,0.001280176,0.070133634,0.35775325,0.0020724428,0.0037187324,0.38922325],"study_design_scores_gemma":[0.0000564549,0.00048267853,0.5083455,0.00009194067,0.00019630794,0.001223136,0.00047800812,0.4307203,0.051816404,0.0034222985,0.0030501059,0.000116988085],"about_ca_topic_score_codex":0.005344995,"about_ca_topic_score_gemma":0.008207142,"teacher_disagreement_score":0.005344995,"about_ca_system_score_codex":0.0003478895,"about_ca_system_score_gemma":0.00048793922,"threshold_uncertainty_score":0.010627747},"labels":[],"label_agreement":null},{"id":"W4387455999","doi":"10.1101/2023.10.05.561088","title":"Data-driven characterization and correction of the orientation dependence of magnetization transfer measures using diffusion MRI","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Voxel; Diffusion MRI; Characterization (materials science); Orientation (vector space); Deconvolution; Magnetization transfer; Diffusion; Nuclear magnetic resonance; White matter; Fiber; Materials science; Computer science; Artificial intelligence; Physics; Mathematics; Optics; Magnetic resonance imaging; Algorithm; Medicine; Geometry; Radiology","score_opus":0.06997759832150899,"score_gpt":0.299893503790892,"score_spread":0.22991590546938304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387455999","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10384268,0.00080976344,0.8917595,0.0002607956,0.00013376887,0.00011131439,0.0006371883,0.0019076376,0.00053736544],"genre_scores_gemma":[0.3809232,0.00048651377,0.61401135,0.00010475157,0.000076664204,0.00020642226,0.001719709,0.0010596184,0.0014117168],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990202,0.00030431757,0.00007974336,0.0002812948,0.00025012626,0.00006427567],"domain_scores_gemma":[0.9959044,0.001273603,0.0006397705,0.00084398495,0.001238216,0.00009995608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00241433,0.0011488671,0.0007812298,0.0012135654,0.00034830693,0.0011158112,0.0007413861,0.00073642324,0.00092497055],"category_scores_gemma":[0.00904148,0.00034931186,0.00065726734,0.0011930452,0.00052911596,0.0007596988,0.000741672,0.000934877,0.00061896053],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065655855,0.00017531308,0.012447677,0.0013580384,0.0004905235,0.0002716315,0.0003467669,0.059921406,0.48724174,0.0043043974,0.0034399324,0.42934608],"study_design_scores_gemma":[0.000051455252,0.00027148743,0.027489316,0.000103981336,0.00020878059,0.0008296692,0.00012002618,0.55571926,0.39555863,0.0062102918,0.013314928,0.00012214406],"about_ca_topic_score_codex":0.0017367343,"about_ca_topic_score_gemma":0.0029860467,"teacher_disagreement_score":0.00241433,"about_ca_system_score_codex":0.0004107117,"about_ca_system_score_gemma":0.0012024427,"threshold_uncertainty_score":0.012768328},"labels":[],"label_agreement":null},{"id":"W4387483302","doi":"10.1088/1361-6560/ad0216","title":"Implications of fitting a two-compartment model in single-shell diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Compartment (ship); Diffusion MRI; Diffusion; Isotropy; Shell (structure); Sensitivity (control systems); Cellular compartment; White matter; Biological system; Physics; Chemistry; Magnetic resonance imaging; Materials science; Biology; Geology; Medicine; Optics","score_opus":0.4875591039183781,"score_gpt":0.49224013986117326,"score_spread":0.004681035942795175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387483302","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19874229,0.00073760666,0.79518306,0.0022733128,0.00018957438,0.0001947956,0.00025243737,0.00062310457,0.0018037772],"genre_scores_gemma":[0.91770333,0.0004238304,0.07918766,0.00086400734,0.00007368138,0.00015412344,0.00025654255,0.00020972405,0.0011270161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958482,0.0023631828,0.00020165279,0.0008245598,0.00059232826,0.00016999306],"domain_scores_gemma":[0.97160655,0.023552313,0.001530806,0.0018236332,0.001219843,0.0002667873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010930552,0.0009467089,0.00083284103,0.00066846306,0.0004789768,0.0020805479,0.0011842698,0.0021464191,0.0009822708],"category_scores_gemma":[0.06282494,0.00061299466,0.00088090333,0.0006501591,0.001628886,0.0025164809,0.0016030822,0.0015333878,0.00038466888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009264802,0.00022272368,0.020804722,0.00043392685,0.0005358948,0.001337801,0.00051510194,0.8740522,0.03948825,0.024936426,0.0017234561,0.035022993],"study_design_scores_gemma":[0.000030476507,0.00014858397,0.0039932393,0.000048282796,0.00006600861,0.0006465116,0.00007304641,0.95733625,0.010446824,0.026031235,0.0011059887,0.00007363961],"about_ca_topic_score_codex":0.0060156384,"about_ca_topic_score_gemma":0.002085239,"teacher_disagreement_score":0.010930552,"about_ca_system_score_codex":0.0013327168,"about_ca_system_score_gemma":0.0012042377,"threshold_uncertainty_score":0.05780697},"labels":[],"label_agreement":null},{"id":"W4387519905","doi":"10.1016/j.nicl.2023.103529","title":"Impact of follow ups, time interval and study duration in diffusion &amp; myelin MRI clinical study in MS","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; CARE Canada; Q & T Research; Hôpital Fleurimont; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Centre Hospitalier Universitaire de Québec; Université de Sherbrooke","keywords":"Multiple sclerosis; Duration (music); Diffusion MRI; Medicine; White matter; Interval (graph theory); Confidence interval; Confounding; Affect (linguistics); Clinically isolated syndrome; Neurology; Internal medicine; Cardiology; Magnetic resonance imaging; Psychology; Radiology; Mathematics","score_opus":0.212553186826201,"score_gpt":0.5221445582839719,"score_spread":0.3095913714577709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387519905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94390154,0.01310228,0.037531663,0.0015003239,0.00052013044,0.00061911385,0.0009920961,0.00013756649,0.0016953993],"genre_scores_gemma":[0.98337585,0.00044934519,0.013548518,0.00029562597,0.00016059254,0.0012492309,0.0005330252,0.000052932097,0.0003348974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.8124843,0.14805041,0.01906197,0.011492944,0.0074521196,0.001458308],"domain_scores_gemma":[0.675801,0.2492264,0.036400132,0.027320804,0.0064161597,0.004835517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.16723812,0.00085846987,0.0017435157,0.0009027567,0.0017364532,0.002088206,0.0010430525,0.0024739467,0.0018307413],"category_scores_gemma":[0.21095435,0.00080876844,0.0031943289,0.0016513648,0.0016895658,0.0020619703,0.0017049464,0.001372304,0.0002769167],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.22724201,0.00243713,0.595199,0.0019438429,0.015162092,0.00071157457,0.0020317282,0.008980094,0.022004424,0.001933443,0.0010770549,0.121277645],"study_design_scores_gemma":[0.0052930512,0.040507644,0.9062235,0.00049518334,0.011402503,0.0011216343,0.000421989,0.012817079,0.010647267,0.00508218,0.0056941956,0.00029391778],"about_ca_topic_score_codex":0.0006218677,"about_ca_topic_score_gemma":0.0011183508,"teacher_disagreement_score":0.16723812,"about_ca_system_score_codex":0.00078539987,"about_ca_system_score_gemma":0.0013495616,"threshold_uncertainty_score":0.88445026},"labels":[],"label_agreement":null},{"id":"W4387662825","doi":"10.55458/neurolibre.00017","title":"A database of the healthy human spinal cord morphometryin the PAM50 template space","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada First Research Excellence Fund; Ministerstvo Zdravotnictví Ceské Republiky; European Commission; Natural Sciences and Engineering Research Council of Canada; Craig H. Neilsen Foundation","keywords":"Space (punctuation); Spinal cord; Computer science; Database; Medicine; Artificial intelligence; Operating system","score_opus":0.28777699163672305,"score_gpt":0.47059523930700226,"score_spread":0.1828182476702792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387662825","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1635467,0.010296666,0.17244837,0.00061021873,0.00062218006,0.001069976,0.61125124,0.026540495,0.013614247],"genre_scores_gemma":[0.19979689,0.0035070914,0.06778687,0.00022279444,0.00018407493,0.0010521511,0.718374,0.001372568,0.0077034445],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992674,0.00008077339,0.00009241975,0.00028730644,0.00020397379,0.000068197536],"domain_scores_gemma":[0.9986369,0.00022715288,0.0000872934,0.0006609766,0.00030187494,0.0000857668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005613155,0.0012736608,0.001462305,0.0031805027,0.0004843966,0.0011012937,0.0015563167,0.0016440041,0.017186387],"category_scores_gemma":[0.003539455,0.00058866094,0.0014467693,0.0034502002,0.0004767812,0.00078209647,0.0011681614,0.00067927426,0.013592273],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017724028,0.000756688,0.015539328,0.0032537575,0.00075495476,0.0024703534,0.00030879254,0.014698054,0.048149854,0.0036930135,0.247396,0.6612069],"study_design_scores_gemma":[0.00071810524,0.001636134,0.26102325,0.0010457241,0.0013648376,0.03807226,0.0006260462,0.09244198,0.093891345,0.02421981,0.48442882,0.0005316906],"about_ca_topic_score_codex":0.0071284045,"about_ca_topic_score_gemma":0.009092879,"teacher_disagreement_score":0.017186387,"about_ca_system_score_codex":0.0003590954,"about_ca_system_score_gemma":0.0014203226,"threshold_uncertainty_score":0.057494164},"labels":[],"label_agreement":null},{"id":"W4387703393","doi":"10.1101/2023.10.16.562599","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"UK Research and Innovation; Wellcome Trust","keywords":"Thalamus; Cerebellum; Neuroscience; Diffusion; Diffusion MRI; Biology; Anatomy; Psychology; Medicine; Physics; Magnetic resonance imaging","score_opus":0.04275811439867714,"score_gpt":0.27902090168843063,"score_spread":0.2362627872897535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387703393","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97944814,0.000705144,0.01879535,0.000032174008,0.000008286737,0.000014536857,0.0003969595,0.00017052432,0.00042884937],"genre_scores_gemma":[0.9792027,0.0011589951,0.017395731,0.000021415823,0.0000029661737,0.000056688703,0.0004244203,0.00008814978,0.0016490762],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994576,0.0000059661174,0.000003945981,0.000019932953,0.000016151558,0.000008338965],"domain_scores_gemma":[0.9998441,0.00002260534,0.00006482116,0.000012747425,0.000035622594,0.000020092762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018558002,0.00032239285,0.00022151247,0.00040159834,0.00008493738,0.00024187373,0.00021745669,0.00022322964,0.00041936096],"category_scores_gemma":[0.00029437305,0.00016732104,0.00017111491,0.00012569154,0.00020030966,0.0002156192,0.000260568,0.00024820454,0.00013038555],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061732164,0.0000040717937,0.0016087886,0.000031552983,0.000008204535,0.00010856817,0.00004912207,0.00030007208,0.9943072,0.00008072319,0.000019697882,0.003420334],"study_design_scores_gemma":[0.0000075406497,0.0004923167,0.06094315,0.00002575374,0.00007401986,0.0008092985,0.00026091468,0.0072508254,0.92874676,0.00021967135,0.0011423735,0.000027361586],"about_ca_topic_score_codex":0.0020768247,"about_ca_topic_score_gemma":0.002844109,"teacher_disagreement_score":0.0020768247,"about_ca_system_score_codex":0.00021342837,"about_ca_system_score_gemma":0.00020429584,"threshold_uncertainty_score":0.00412941},"labels":[],"label_agreement":null},{"id":"W4387708434","doi":"10.21203/rs.3.rs-2476133/v2","title":"Unveiling the Axonal Connectivity Between the Precuneus and Temporal Pole: Structural Evidence from the Cingulum Pathways","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Cingulum (brain); Precuneus; Neuroscience; Functional connectivity; Anatomy; Psychology; Biology; Medicine; Magnetic resonance imaging; Diffusion MRI; Radiology; Cognition","score_opus":0.39882975641039914,"score_gpt":0.4940464859210959,"score_spread":0.09521672951069676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387708434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9520898,0.0064570517,0.0285736,0.0031943514,0.000107755295,0.000020026815,0.0006193318,0.00010623687,0.008831996],"genre_scores_gemma":[0.981218,0.004017558,0.01313835,0.00016354058,0.00014489847,0.000017591092,0.00025771788,0.000049159546,0.0009931686],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999038,0.000021853954,0.00000408004,0.000026897875,0.000021515776,0.000021801185],"domain_scores_gemma":[0.9993475,0.0002873054,0.00015148912,0.00007645283,0.000070312926,0.0000668589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050232594,0.00048463026,0.0002686224,0.0013623657,0.0005679614,0.0012385071,0.00047769738,0.0007536644,0.0023910599],"category_scores_gemma":[0.0028580746,0.0002974076,0.00023313097,0.001317257,0.0011240927,0.0017181835,0.0008182014,0.00088229316,0.00024159487],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020619757,0.00017299847,0.07070818,0.0015387177,0.00079995353,0.004821637,0.0024374053,0.008997882,0.526028,0.07632032,0.0031937736,0.3029192],"study_design_scores_gemma":[0.00033357064,0.0004902771,0.5281259,0.0005448542,0.0010356914,0.0071200463,0.002257827,0.028566401,0.05549043,0.35592774,0.019942852,0.00016440662],"about_ca_topic_score_codex":0.002935965,"about_ca_topic_score_gemma":0.0074290824,"teacher_disagreement_score":0.002935965,"about_ca_system_score_codex":0.00028389014,"about_ca_system_score_gemma":0.0005077241,"threshold_uncertainty_score":0.007998943},"labels":[],"label_agreement":null},{"id":"W4387731161","doi":"10.1101/2023.10.16.562488","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"HORIZON EUROPE Framework Programme; European Synchrotron Radiation Facility; Deutsches Elektronen-Synchrotron; European Commission; Lundbeckfonden; Scleroseforeningen","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Biology; Fractional anisotropy; Tractography; Anatomy; Neuroscience; Computer science; Magnetic resonance imaging; Medicine; Artificial intelligence","score_opus":0.051955037456250894,"score_gpt":0.28919226864616354,"score_spread":0.23723723118991263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387731161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9246002,0.00083401107,0.07187206,0.00012460293,0.000010496607,0.000024779672,0.0004781555,0.00027552855,0.001780174],"genre_scores_gemma":[0.9461131,0.0005621554,0.05236198,0.00003933329,0.000009135087,0.000032923643,0.00022498667,0.00011669016,0.0005395796],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998591,0.000040147155,0.000008987546,0.000041372095,0.000033970147,0.000016486498],"domain_scores_gemma":[0.9994771,0.00012882489,0.00019313802,0.000081875696,0.00008328942,0.00003582729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040014525,0.00030452647,0.00025035642,0.0015737503,0.0002684337,0.0012084668,0.00021932198,0.00034968555,0.00096992886],"category_scores_gemma":[0.0008518196,0.00034444462,0.00019695784,0.00057967135,0.00068632315,0.0006985818,0.0007833104,0.00033672512,0.00020537003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017760112,0.00002249483,0.015426619,0.00022890481,0.00009717929,0.000266572,0.001041867,0.0072921496,0.9434153,0.0025061986,0.00019813348,0.0293271],"study_design_scores_gemma":[0.000024789213,0.00029230915,0.6587249,0.0002628963,0.00019229593,0.002429649,0.0013764746,0.06123456,0.24993828,0.015626336,0.00971287,0.00018465093],"about_ca_topic_score_codex":0.0016709483,"about_ca_topic_score_gemma":0.0033957697,"teacher_disagreement_score":0.0016709483,"about_ca_system_score_codex":0.00024311298,"about_ca_system_score_gemma":0.0002867816,"threshold_uncertainty_score":0.003322482},"labels":[],"label_agreement":null},{"id":"W4387772054","doi":"10.1093/braincomms/fcad279","title":"Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Fonds de Recherche du Québec - Santé; Alzheimer Society; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Jean-Louis Lévesque","keywords":"Hyperintensity; White matter; Fluid-attenuated inversion recovery; Magnetic resonance imaging; Medicine; Leukoaraiosis; Dementia; Pathology; Cognitive decline; Psychology; Cardiology; Radiology; Disease","score_opus":0.09996895150362162,"score_gpt":0.4101687974468111,"score_spread":0.3101998459431895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387772054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.999057,0.0001254765,0.00040367604,0.000009498667,0.000001943922,0.000019817153,0.0001637646,0.0000052513033,0.00021349278],"genre_scores_gemma":[0.99898356,0.000045232962,0.0006316305,0.0000089316,0.000004214875,0.000017902776,0.00017113808,0.0000014313392,0.00013603247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99975497,0.00007288035,0.000041760963,0.000067439374,0.000041054667,0.000022062419],"domain_scores_gemma":[0.999383,0.000097112024,0.00029125318,0.000043463962,0.00010845415,0.000076743076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088332786,0.00044645407,0.00022808179,0.0011299896,0.00025161848,0.00048385156,0.00020564141,0.0004032418,0.0012858454],"category_scores_gemma":[0.0014768365,0.00012651739,0.0002263886,0.00042961558,0.00021954083,0.0003989685,0.00035909694,0.0002069599,0.00015972738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008191097,0.00015791424,0.9759818,0.00005867693,0.00027871807,0.00011615651,0.0001924137,0.00029135426,0.014608727,0.0000391592,0.00012680613,0.0073291073],"study_design_scores_gemma":[0.000014195574,0.0004878487,0.9964988,0.0000076090178,0.000053178428,0.00028460252,0.000114420756,0.0006394281,0.0017334014,0.000060961345,0.00009871129,0.000006874188],"about_ca_topic_score_codex":0.0015651755,"about_ca_topic_score_gemma":0.002449889,"teacher_disagreement_score":0.0015651755,"about_ca_system_score_codex":0.00014807237,"about_ca_system_score_gemma":0.00009848764,"threshold_uncertainty_score":0.004671514},"labels":[],"label_agreement":null},{"id":"W4387799082","doi":"10.1097/j.pain.0000000000003069","title":"Electrostimulation of the white matter of the posterior insula and medial operculum: perception of vibrations, heat, and pain","year":2023,"lang":"en","type":"review","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Université du Québec en Outaouais; Montreal Neurological Institute and Hospital; Université de Sherbrooke; Université de Montréal","funders":"","keywords":"White matter; Operculum (bryozoa); Insula; Sensation; Medicine; Thalamus; Stimulation; Nociception; Neuroscience; Psychology; Audiology; Anesthesia; Magnetic resonance imaging; Radiology; Biology; Internal medicine","score_opus":0.05762826270974261,"score_gpt":0.3627086908064472,"score_spread":0.30508042809670455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387799082","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992173,0.00017729535,0.00029343902,0.0000069192984,0.0000019418749,0.0000057461007,0.000026420721,0.0000030281383,0.00026798923],"genre_scores_gemma":[0.999597,0.00010533106,0.00014526305,0.0000093290155,0.000004045048,0.000004157371,0.000029082546,0.0000010397235,0.00010470411],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999591,0.00000759677,0.000003207488,0.000008992543,0.0000092211885,0.000011842139],"domain_scores_gemma":[0.9999175,0.000033514058,0.000026533859,0.0000043599225,0.000007316831,0.00001072749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008257295,0.00017949544,0.00011108281,0.00026115894,0.00010075636,0.00012164102,0.00006812786,0.00009896918,0.0012613991],"category_scores_gemma":[0.00027844877,0.000060173294,0.000108888504,0.00017186119,0.00022496803,0.00010682623,0.0001209135,0.00008622417,0.0001120177],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002984999,0.00017327105,0.4485393,0.000443796,0.0002128173,0.026568571,0.001263699,0.00040346282,0.41565043,0.00011843846,0.00035621042,0.10328504],"study_design_scores_gemma":[0.000034608875,0.0010364009,0.96567106,0.00001790924,0.00006379433,0.0151408035,0.00044121096,0.00032096545,0.01661279,0.00006363161,0.00058717624,0.00000961856],"about_ca_topic_score_codex":0.00049522356,"about_ca_topic_score_gemma":0.0013280034,"teacher_disagreement_score":0.0012613991,"about_ca_system_score_codex":0.00009658013,"about_ca_system_score_gemma":0.000101998856,"threshold_uncertainty_score":0.00421983},"labels":[],"label_agreement":null},{"id":"W4387826906","doi":"10.1016/j.neurobiolaging.2023.10.007","title":"Frontoparietal function and underlying structure reflect capacity for motor skill acquisition during healthy aging","year":2023,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Mitacs; Michael Smith Health Research BC","keywords":"Motor skill; Psychology; Dreyfus model of skill acquisition; Diffusion MRI; White matter; Neuroscience; Physical medicine and rehabilitation; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.09228399696588749,"score_gpt":0.37213687519070904,"score_spread":0.2798528782248215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387826906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99794644,0.00030232026,0.00061776437,0.000023629947,0.0000042259467,0.000012740266,0.00028236405,0.000016640639,0.000793851],"genre_scores_gemma":[0.99839526,0.00019171863,0.00051938585,0.00001933066,0.000005267018,0.000010385186,0.0002254437,0.000005429855,0.0006278417],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999552,0.000004324461,0.0000032821674,0.000015336194,0.000010140454,0.000011738893],"domain_scores_gemma":[0.99973506,0.00004313927,0.000106932945,0.000028269927,0.000057369773,0.000029355146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024147604,0.0003403046,0.00027315647,0.0005481403,0.00017597094,0.0004921235,0.00019682024,0.00037824558,0.001209327],"category_scores_gemma":[0.00088156207,0.0001717796,0.00010795708,0.00026494623,0.0003079635,0.0006086085,0.00021309835,0.00033099923,0.00020931833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025554057,0.00036191652,0.5858376,0.00017868048,0.0003244545,0.00114443,0.0013841564,0.0010375917,0.33517936,0.0010781795,0.0007185307,0.07019962],"study_design_scores_gemma":[0.000002943586,0.000116873896,0.99605185,0.0000031436555,0.000017814524,0.00018949623,0.00009262608,0.0002982326,0.0028172429,0.0002789327,0.00012773345,0.0000031845423],"about_ca_topic_score_codex":0.0046595973,"about_ca_topic_score_gemma":0.00817012,"teacher_disagreement_score":0.0046595973,"about_ca_system_score_codex":0.0002634914,"about_ca_system_score_gemma":0.000205702,"threshold_uncertainty_score":0.009264946},"labels":[],"label_agreement":null},{"id":"W4387899515","doi":"10.3389/fnana.2023.1214629","title":"The anatomy of the four streams of the prefrontal cortex. Preliminary evidence from a population based high definition tractography study","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Uncinate fasciculus; Neuroscience; Prefrontal cortex; Tractography; Cingulum (brain); Connectome; Population; Psychology; Insula; Diffusion MRI; Functional connectivity; Fractional anisotropy; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.04578174593541029,"score_gpt":0.3191902104755592,"score_spread":0.2734084645401489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387899515","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94375247,0.0015403643,0.05075104,0.00041043747,0.000009103972,0.000063735664,0.0006022207,0.000113713904,0.0027569267],"genre_scores_gemma":[0.9820837,0.00044165214,0.016734848,0.000022217948,0.000006717732,0.000026608983,0.00019910846,0.000010651874,0.00047462113],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99987745,0.000035644003,0.0000060611937,0.000043130935,0.000022469481,0.000015112251],"domain_scores_gemma":[0.9996848,0.00009503345,0.00010148156,0.00004819622,0.000048145175,0.00002226186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005436899,0.00016797261,0.000115552495,0.0007159198,0.00020003044,0.00043366125,0.00029182684,0.0002540532,0.00085427106],"category_scores_gemma":[0.0012928427,0.00020905504,0.0002329632,0.000372311,0.0005818781,0.00057122746,0.00021096651,0.00022053126,0.0001272489],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093851995,0.00011548668,0.31538606,0.00063606416,0.00071230915,0.0014651347,0.002443156,0.019229908,0.42827952,0.02526076,0.0012399226,0.2042931],"study_design_scores_gemma":[0.000047203786,0.0002176165,0.93365884,0.00005165588,0.0001106552,0.0041141026,0.00024333666,0.020272601,0.02127288,0.01535885,0.004610176,0.00004213618],"about_ca_topic_score_codex":0.010122988,"about_ca_topic_score_gemma":0.0120610045,"teacher_disagreement_score":0.010122988,"about_ca_system_score_codex":0.0005656891,"about_ca_system_score_gemma":0.000715983,"threshold_uncertainty_score":0.02012813},"labels":[],"label_agreement":null},{"id":"W4388106547","doi":"10.1101/2023.10.29.23297734","title":"White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"National Health and Medical Research Council; Sociedade Beneficente Israelita Brasileira Albert Einstein; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; Michael Smith Health Research BC","keywords":"Corticospinal tract; Hyperintensity; Motor impairment; Stroke (engine); Physical medicine and rehabilitation; Lesion; Cardiology; White matter; Psychology; Internal medicine; Brain damage; Medicine; Magnetic resonance imaging; Psychiatry; Diffusion MRI; Radiology","score_opus":0.13948705139272027,"score_gpt":0.3540826914950334,"score_spread":0.21459564010231313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388106547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995403,0.00008746083,0.000062041494,0.00001780547,0.0000018328406,0.000002736159,0.00009920048,0.0000033485396,0.00018533636],"genre_scores_gemma":[0.999522,0.000031301613,0.000037821137,0.000008406769,0.0000041664894,0.0000028580287,0.00015687343,0.000002164719,0.00023454594],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996698,0.00009426209,0.000044646462,0.0000918447,0.0000406774,0.000058762278],"domain_scores_gemma":[0.9985843,0.0002979635,0.0006726088,0.0001885931,0.000091345544,0.00016534106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007378679,0.00034909233,0.00032849688,0.0005425117,0.00026859497,0.00045347246,0.0002704946,0.00037989632,0.0018929022],"category_scores_gemma":[0.0031065189,0.00014883593,0.00039746746,0.00045086342,0.00031851293,0.00035961097,0.00056804396,0.0004325624,0.00032722254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005951944,0.00010454065,0.9938601,0.000015452559,0.00033000202,0.00009845723,0.00013414852,0.00027390057,0.0011634369,0.000030875053,0.000080980055,0.003312835],"study_design_scores_gemma":[0.00000202451,0.000060245646,0.9996043,0.0000014582721,0.000025762505,0.000036873465,0.000023640552,0.0000982968,0.000078138735,0.00004356402,0.000024377892,0.0000013449578],"about_ca_topic_score_codex":0.0041802605,"about_ca_topic_score_gemma":0.0073429164,"teacher_disagreement_score":0.0041802605,"about_ca_system_score_codex":0.00021870993,"about_ca_system_score_gemma":0.00026684473,"threshold_uncertainty_score":0.008311868},"labels":[],"label_agreement":null},{"id":"W4388173883","doi":"10.1126/sciadv.adh9853","title":"The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity","year":2023,"lang":"en","type":"article","venue":"Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Myelin; Magnetic resonance imaging; Computer science; Context (archaeology); Spinal cord; Biomedical engineering; Artificial intelligence; Radiology; Medicine; Neuroscience; Biology; Central nervous system","score_opus":0.04572890420358438,"score_gpt":0.3791686319174054,"score_spread":0.333439727713821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388173883","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017005117,0.00019433419,0.99560153,0.00008134933,0.000021793549,0.000027841133,0.00011832748,0.0014595018,0.0007948083],"genre_scores_gemma":[0.033738893,0.00041834163,0.96262646,0.0001357404,0.0000482959,0.00016367612,0.00062651926,0.00081970025,0.0014223065],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990632,0.00020468848,0.000043521217,0.00017068797,0.00044673684,0.00007119569],"domain_scores_gemma":[0.9992518,0.00020804018,0.00010457256,0.00017202111,0.00019617476,0.000067301116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001846306,0.0010830412,0.0007362317,0.00076385296,0.00033666764,0.001508871,0.002067483,0.00087633025,0.0039650113],"category_scores_gemma":[0.0033435232,0.00044470708,0.0008852956,0.0007057556,0.0007764184,0.0012002055,0.0022839056,0.0019792411,0.0019380335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058619626,0.00015676755,0.0011144071,0.0008817817,0.00024279926,0.00067475083,0.00035534616,0.16925931,0.22958319,0.19730288,0.01903433,0.38080826],"study_design_scores_gemma":[0.00006243058,0.0002235529,0.0005891436,0.00006342443,0.000052155094,0.0006713005,0.00004416757,0.84959716,0.047269724,0.040132992,0.061191585,0.00010236355],"about_ca_topic_score_codex":0.0024132782,"about_ca_topic_score_gemma":0.0042159744,"teacher_disagreement_score":0.0039650113,"about_ca_system_score_codex":0.00057589,"about_ca_system_score_gemma":0.0014153644,"threshold_uncertainty_score":0.013264298},"labels":[],"label_agreement":null},{"id":"W4388266230","doi":"10.1016/j.jcjd.2023.10.278","title":"CEREBRAL WHITE MATTER LESIONS AND ITS ASSOCIATIONS WITH BRAIN PULSATILITY: AN MRI, NIRS, AND TCD STUDY","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Hyperintensity; Magnetic resonance imaging; Radiology","score_opus":0.044158514499392905,"score_gpt":0.31236585155468,"score_spread":0.2682073370552871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388266230","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990864,0.00017216626,0.00012767421,0.000048117872,0.0000056340505,0.000010822088,0.00006212905,0.0000026802566,0.00048444074],"genre_scores_gemma":[0.99918777,0.00018916473,0.00020511345,0.000033345546,0.00004352548,0.000009126413,0.00008467501,0.0000026227829,0.00024468044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997433,0.000058682082,0.000030051644,0.00006027862,0.00005876099,0.000048991875],"domain_scores_gemma":[0.9991937,0.0002463222,0.00017630686,0.000080583166,0.000101470985,0.00020159064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005405641,0.00053784024,0.00038738563,0.001267067,0.0005796999,0.0004961227,0.00036034003,0.00058764295,0.0011204104],"category_scores_gemma":[0.0015542435,0.00041224502,0.00046205687,0.0012107395,0.00070819753,0.0006390796,0.0003969366,0.0007699556,0.00027623374],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017339803,0.00094411714,0.9757446,0.000029254583,0.00017888162,0.008092442,0.00058233086,0.00011062708,0.007428529,0.000097422875,0.00012785921,0.004930089],"study_design_scores_gemma":[0.000031560558,0.00069978967,0.9910947,0.0000053903864,0.00011656806,0.006251426,0.0004940658,0.00036973692,0.0005575338,0.00013493893,0.00022756956,0.00001659599],"about_ca_topic_score_codex":0.0036056992,"about_ca_topic_score_gemma":0.002645266,"teacher_disagreement_score":0.0036056992,"about_ca_system_score_codex":0.00029100472,"about_ca_system_score_gemma":0.00048163524,"threshold_uncertainty_score":0.0071694255},"labels":[],"label_agreement":null},{"id":"W4388303642","doi":"10.1016/j.nicl.2023.103533","title":"Detecting conversion from mild cognitive impairment to Alzheimer’s disease using FLAIR MRI biomarkers","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; Baycrest Hospital; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Health Sciences Centre; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer Society; Alzheimer's Society; Consortium canadien en neurodégénérescence associée au vieillissement; Government of Ontario","keywords":"Fluid-attenuated inversion recovery; White matter; Medicine; Brain size; Cerebrospinal fluid; Neuroimaging; Magnetic resonance imaging; Grey matter; Nuclear medicine; Internal medicine; Radiology","score_opus":0.2626896449891431,"score_gpt":0.4752544071267235,"score_spread":0.2125647621375804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388303642","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946825,0.00170981,0.0020422658,0.000082582075,0.000021670845,0.000042472246,0.00031686758,0.00006112814,0.0010405702],"genre_scores_gemma":[0.99508613,0.00077275856,0.0032427036,0.000059534497,0.00003148076,0.00002630524,0.00031815187,0.000004959044,0.00045801088],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996687,0.00006354971,0.000054675853,0.00009244946,0.00007519242,0.000045398046],"domain_scores_gemma":[0.99874985,0.00021620654,0.0005891794,0.00008535039,0.00026199967,0.00009725944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012190702,0.00069659436,0.0004582391,0.0022224076,0.00025586394,0.0011498207,0.00031359371,0.0007105437,0.0005575904],"category_scores_gemma":[0.002784597,0.00020702386,0.00041302954,0.0007762464,0.0003066185,0.00080531737,0.00038789652,0.00042611503,0.00029924294],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012181526,0.0002707677,0.9207332,0.00013353078,0.00028918748,0.00040922113,0.00036566958,0.0006783698,0.01892643,0.000117347394,0.00034254987,0.05651543],"study_design_scores_gemma":[0.000016434116,0.0009475367,0.9873834,0.00004320557,0.00018308187,0.00085873745,0.00030599098,0.002440691,0.006656586,0.00034562955,0.00079039374,0.000028223629],"about_ca_topic_score_codex":0.002262148,"about_ca_topic_score_gemma":0.0036291971,"teacher_disagreement_score":0.002262148,"about_ca_system_score_codex":0.00023167446,"about_ca_system_score_gemma":0.00023029803,"threshold_uncertainty_score":0.006447077},"labels":[],"label_agreement":null},{"id":"W4388598265","doi":"10.1111/psyp.14483","title":"Brains of endurance athletes differ in the association areas but not in the primary areas","year":2023,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Brain size; Gray (unit); Athletes; Magnetic resonance imaging; Grey matter; Association (psychology); Neuroscience; Medicine; Physical therapy; Nuclear medicine","score_opus":0.053430097005919386,"score_gpt":0.3489260629725255,"score_spread":0.2954959659666061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388598265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974847,0.000634412,0.0004997032,0.000045606186,0.000009376002,0.0000107357455,0.00013718342,0.000008574029,0.0011697361],"genre_scores_gemma":[0.9976394,0.00046568498,0.0005684922,0.000057012232,0.000020063435,0.000019001895,0.00017858144,0.000007239097,0.0010444591],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992955,0.0000074411296,0.0000042737333,0.00003405292,0.000009582862,0.000015111857],"domain_scores_gemma":[0.9998882,0.000024146297,0.000044633354,0.000009711466,0.000012481893,0.000020808167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012228217,0.00023742986,0.00018174811,0.00036568902,0.00026072207,0.00027482124,0.00009446667,0.00022734034,0.0028300686],"category_scores_gemma":[0.00028767873,0.00011807515,0.00014115768,0.00020350148,0.0003620721,0.00024509663,0.00026171107,0.00014257371,0.00026704633],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017293711,0.00039245794,0.5029243,0.0006034317,0.0007618124,0.0022014065,0.0038245483,0.0006046915,0.36001426,0.0010916821,0.0010079682,0.124843955],"study_design_scores_gemma":[0.0000054573998,0.00015527652,0.9968786,0.0000109265,0.000025208496,0.0006830122,0.000303308,0.000059020073,0.0012367765,0.000233083,0.00040662574,0.0000026856717],"about_ca_topic_score_codex":0.0008935146,"about_ca_topic_score_gemma":0.0021009033,"teacher_disagreement_score":0.0028300686,"about_ca_system_score_codex":0.00008881222,"about_ca_system_score_gemma":0.000117335054,"threshold_uncertainty_score":0.009467483},"labels":[],"label_agreement":null},{"id":"W4388648711","doi":"10.1101/2023.11.13.23298482","title":"Connectome reorganization associated with temporal lobe pathology and its surgical resection","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Institute for Information and Communications Technology Promotion; National Science Foundation; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Institute for Basic Science; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Hospital for Sick Children; National Research Foundation of Korea; National Natural Science Foundation of China; Canada Research Chairs; China Postdoctoral Science Foundation; Inha University; National Research Foundation","keywords":"Connectome; Temporal lobe; Neuroscience; Psychology; Electrocorticography; Tractography; Diffusion MRI; Epilepsy; Medicine; Neuroimaging; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.09246074374099782,"score_gpt":0.3554091831884602,"score_spread":0.2629484394474624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388648711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993198,0.00003938218,0.00029714007,0.000016161086,0.0000012580705,0.000005213677,0.00012079757,0.000006681342,0.00019359996],"genre_scores_gemma":[0.99962926,0.000025673427,0.00010588024,0.0000060566904,0.0000020205293,0.0000069840244,0.00015098901,0.0000018326471,0.00007124134],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993527,0.000010488342,0.000008395532,0.00001957588,0.000013483619,0.000012877673],"domain_scores_gemma":[0.99975854,0.000029979508,0.00012985103,0.00002524234,0.000021780896,0.000034563578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013470872,0.0001662609,0.00014166441,0.00043868658,0.00016207501,0.00022539507,0.00008306323,0.0001257383,0.0013096281],"category_scores_gemma":[0.00044274193,0.00007693592,0.00012879423,0.00024564427,0.0003497884,0.00019270464,0.0002609153,0.00017514419,0.000100387224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002390379,0.00013519354,0.45120788,0.00010993955,0.00023510495,0.003328264,0.00062078866,0.0017888495,0.5207327,0.0005239179,0.00049555604,0.018431475],"study_design_scores_gemma":[0.000009985067,0.00025988056,0.9856047,0.0000057008124,0.000026694323,0.002395268,0.00018362205,0.0012036471,0.009813558,0.00024677094,0.00024187357,0.000008193213],"about_ca_topic_score_codex":0.001711798,"about_ca_topic_score_gemma":0.0026344114,"teacher_disagreement_score":0.001711798,"about_ca_system_score_codex":0.00023452794,"about_ca_system_score_gemma":0.00018106193,"threshold_uncertainty_score":0.00438118},"labels":[],"label_agreement":null},{"id":"W4388673090","doi":"10.1016/j.jadr.2023.100689","title":"A systematic review of abnormalities in intracortical myelin across psychiatric illnesses","year":2023,"lang":"en","type":"review","venue":"Journal of Affective Disorders Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"White matter; Neuroimaging; Neuroscience; Psychology; Schizophrenia (object-oriented programming); Major depressive disorder; Bipolar disorder; Temporal lobe; Psychiatry; Medicine; Cognition; Magnetic resonance imaging; Epilepsy","score_opus":0.05194091767584568,"score_gpt":0.44128540212396244,"score_spread":0.38934448444811676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388673090","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007935632,0.99723744,0.00016908371,0.00024317284,0.00010984947,0.00017268583,0.0009842229,0.000010617484,0.00027927032],"genre_scores_gemma":[0.007875854,0.99001324,0.0005531837,0.00047923124,0.00008895485,0.00033699322,0.00051896233,0.00000795549,0.00012570055],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9942245,0.0013443518,0.0028067573,0.000594095,0.00086103356,0.00016926056],"domain_scores_gemma":[0.98320067,0.011009439,0.0036383835,0.0003074332,0.0016378526,0.00020635247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005485837,0.0016587898,0.007986547,0.013753234,0.0006298261,0.0022228812,0.0016825253,0.0013838441,0.0055764234],"category_scores_gemma":[0.02376132,0.00095264363,0.0071521755,0.014180329,0.0007272637,0.0017994933,0.0015871819,0.00087532087,0.00049037195],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016427918,0.000009454424,0.0008973899,0.94852453,0.008585588,0.0001401165,0.00014036823,0.000082295344,0.00022961132,0.00020104939,0.0022575264,0.038767733],"study_design_scores_gemma":[0.00021252119,0.00017831937,0.008443974,0.85463583,0.09630034,0.00079525576,0.00025578024,0.000064260705,0.00025380528,0.0004910084,0.03831816,0.000050754803],"about_ca_topic_score_codex":0.009225591,"about_ca_topic_score_gemma":0.027983475,"teacher_disagreement_score":0.013753234,"about_ca_system_score_codex":0.0026504868,"about_ca_system_score_gemma":0.010309069,"threshold_uncertainty_score":0.029012203},"labels":[],"label_agreement":null},{"id":"W4388749509","doi":"10.1101/2023.11.17.23297145","title":"The bidirectional effects between cognitive ability and brain morphology: A life course Mendelian randomization analysis","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; University of Toronto","funders":"ZonMw; Wellcome Trust","keywords":"Brain size; Brain morphometry; Cognition; Psychology; Cortex (anatomy); Cingulate cortex; White matter; Neuroscience; Developmental psychology; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.06258386717102385,"score_gpt":0.3827562947394861,"score_spread":0.3201724275684622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388749509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5903231,0.0023629218,0.39391208,0.001360649,0.00032381288,0.0031283156,0.0046366234,0.0015092255,0.0024433008],"genre_scores_gemma":[0.8579644,0.0005163231,0.1307446,0.00037647333,0.00008417301,0.0058617797,0.0014343404,0.0002805082,0.0027374397],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9366712,0.047971267,0.0017046509,0.00804189,0.0039935163,0.0016175343],"domain_scores_gemma":[0.93477404,0.048846606,0.005118237,0.009861907,0.0009647259,0.0004345144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05545287,0.0017851077,0.0029734008,0.0024190017,0.0011743205,0.0015856049,0.002441032,0.0019426018,0.0100274775],"category_scores_gemma":[0.0721082,0.0007257585,0.005729891,0.0023420213,0.0022176534,0.0009821025,0.0015400633,0.0014214085,0.00057800906],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.044958718,0.0012661739,0.62678164,0.0026059977,0.05660954,0.008802427,0.0033290468,0.016175942,0.01903094,0.06793945,0.010678276,0.14182186],"study_design_scores_gemma":[0.008864285,0.014481042,0.57410324,0.00092064746,0.042124208,0.009623362,0.0009156839,0.22931913,0.014117197,0.08000038,0.02494605,0.0005847448],"about_ca_topic_score_codex":0.004327095,"about_ca_topic_score_gemma":0.0021005734,"teacher_disagreement_score":0.05545287,"about_ca_system_score_codex":0.0012628211,"about_ca_system_score_gemma":0.0023156516,"threshold_uncertainty_score":0.2932663},"labels":[],"label_agreement":null},{"id":"W4388806341","doi":"10.1016/j.media.2023.103041","title":"WarpDrive: Improving spatial normalization using manual refinements","year":2023,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; Toronto Rehabilitation Institute; McGill University; Douglas Mental Health University Institute; Krembil Foundation; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Eisai; Deutsche Forschungsgemeinschaft; Servier; EU Joint Programme – Neurodegenerative Disease Research; Northern California Institute for Research and Education; National Institute of Mental Health; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Spatial normalization; Normalization (sociology); Inference; Modalities; Pattern recognition (psychology); Neuroimaging; Process (computing); Computer vision; Machine learning; Neuroscience; Psychology","score_opus":0.05912185879799546,"score_gpt":0.42084703398665946,"score_spread":0.361725175188664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388806341","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059344675,0.00027447252,0.9689075,0.00012838679,0.000110103625,0.00010467518,0.0005243781,0.023186063,0.0008300665],"genre_scores_gemma":[0.052021302,0.00030174578,0.9348158,0.00019885738,0.00005295119,0.0003127911,0.001954277,0.008566546,0.0017757533],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9957487,0.001009851,0.00045817494,0.0009707272,0.0015951375,0.00021745476],"domain_scores_gemma":[0.9914402,0.0044870176,0.00083401875,0.0019643295,0.0011383822,0.00013605702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066589317,0.0028542858,0.001678817,0.0036212103,0.0008106499,0.002824925,0.003301589,0.0015704894,0.009529329],"category_scores_gemma":[0.034459546,0.0016450753,0.0020413625,0.0024882616,0.0011973429,0.002541522,0.0043665264,0.0025731837,0.005153246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006586176,0.00020954483,0.005161286,0.00073457713,0.00056820374,0.000511133,0.0011434258,0.033626623,0.042077236,0.009211241,0.040521078,0.865577],"study_design_scores_gemma":[0.00027189322,0.00038584825,0.007889916,0.00027500087,0.00026471584,0.0021702112,0.0006706959,0.68317825,0.14794023,0.036213253,0.12034172,0.00039827146],"about_ca_topic_score_codex":0.0049588275,"about_ca_topic_score_gemma":0.009891706,"teacher_disagreement_score":0.009529329,"about_ca_system_score_codex":0.0006001685,"about_ca_system_score_gemma":0.0018277585,"threshold_uncertainty_score":0.035216212},"labels":[],"label_agreement":null},{"id":"W4388887794","doi":"10.1093/braincomms/fcad313","title":"Longitudinal evolution of diffusion metrics after left hemisphere ischaemic stroke","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Toronto Rehabilitation Institute; Heart and Stroke Foundation; University of Toronto; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; University Health Network; Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Stroke (engine); Lesion; Medicine; Magnetic resonance imaging; Pathology; Radiology; Physics","score_opus":0.09061495565941778,"score_gpt":0.3774562144362619,"score_spread":0.28684125877684413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388887794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99889463,0.0002108787,0.000490899,0.000013314515,0.0000012919961,0.000004966861,0.00019337758,0.00001621767,0.00017447697],"genre_scores_gemma":[0.9988368,0.00011272843,0.00038976202,0.0000042518764,0.0000030290123,0.000007773025,0.00046085156,0.000006061483,0.00017868295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989676,0.000015339994,0.000013288756,0.000029586103,0.00002322479,0.000021848611],"domain_scores_gemma":[0.99949384,0.00008618688,0.00024633578,0.000039852883,0.000082550796,0.000051208193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029416545,0.00016746086,0.00028252817,0.00059560966,0.00016243628,0.0003239389,0.00006703348,0.00019111161,0.0005412904],"category_scores_gemma":[0.0011747271,0.00009031448,0.00015521914,0.0003932437,0.00015675454,0.00024916386,0.00020285985,0.00020880126,0.00017642186],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022017108,0.00015660208,0.75187045,0.00014791776,0.00044042093,0.0018963957,0.0014249437,0.0034323742,0.15939981,0.00013853048,0.0005700462,0.078320764],"study_design_scores_gemma":[0.00000389668,0.00025302963,0.99334234,0.0000054042594,0.000038715934,0.0008443581,0.00010339078,0.0009045005,0.0041837483,0.00005770561,0.00025156292,0.000011401509],"about_ca_topic_score_codex":0.001819,"about_ca_topic_score_gemma":0.002640908,"teacher_disagreement_score":0.001819,"about_ca_system_score_codex":0.0001992156,"about_ca_system_score_gemma":0.00014846936,"threshold_uncertainty_score":0.0036168694},"labels":[],"label_agreement":null},{"id":"W4388921312","doi":"10.1016/j.celrep.2023.113487","title":"Development of white matter fiber covariance networks supports executive function in youth","year":2023,"lang":"en","type":"article","venue":"Cell Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; University of Pennsylvania; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"White matter; Covariance; Function (biology); Fiber; White (mutation); Psychology; Covariance function; Neuroscience; Biology; Developmental psychology; Chemistry; Cell biology; Medicine; Mathematics; Genetics; Statistics; Gene; Magnetic resonance imaging","score_opus":0.040148557127289895,"score_gpt":0.29463122407197573,"score_spread":0.25448266694468585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388921312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986866,0.000100580524,0.0006123966,0.00004055698,0.0000022840654,0.0000031584646,0.00022019882,0.000013273812,0.0003208488],"genre_scores_gemma":[0.99879164,0.00008016939,0.00069786585,0.000009210362,0.000003597887,0.0000051352094,0.00019452897,0.000009138084,0.00020873814],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997676,0.000037834438,0.000018380566,0.000090867834,0.00004341282,0.00004201063],"domain_scores_gemma":[0.9982942,0.00022377845,0.0008905329,0.00012482805,0.00027578766,0.00019094693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069081597,0.00020856487,0.0002032583,0.0006997358,0.00024050547,0.0006867897,0.00021129526,0.00020284572,0.00092017814],"category_scores_gemma":[0.0031375177,0.0001675158,0.0002067595,0.0004129969,0.00036781022,0.000497437,0.00048497386,0.0003833168,0.00017194216],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013137252,0.00005638129,0.96325815,0.000024687177,0.00006411549,0.00027078253,0.0010072298,0.0005101644,0.014785733,0.0005215596,0.00025233475,0.019117437],"study_design_scores_gemma":[9.971152e-7,0.00002367708,0.9972914,0.00001066477,0.0000128026195,0.00013949558,0.00018834515,0.00056459324,0.001277192,0.0002851104,0.00020221212,0.000003513422],"about_ca_topic_score_codex":0.0062173666,"about_ca_topic_score_gemma":0.016628306,"teacher_disagreement_score":0.0062173666,"about_ca_system_score_codex":0.00039811115,"about_ca_system_score_gemma":0.0005605841,"threshold_uncertainty_score":0.012362361},"labels":[],"label_agreement":null},{"id":"W4389026709","doi":"10.1096/fasebj.30.1_supplement.1037.3","title":"Quantification of the 3D Orientation of Vascular Canals in Cortical Bone","year":2016,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orientation (vector space); Cortical bone; Perpendicular; Cortex (anatomy); Anatomy; Biomedical engineering; Materials science; Plane (geometry); Geometry; Geology; Biology; Mathematics; Medicine; Neuroscience","score_opus":0.06234886732221419,"score_gpt":0.3503181500232802,"score_spread":0.28796928270106603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389026709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79486823,0.0010770694,0.19998363,0.00007065416,0.000022363905,0.00008168294,0.00070154894,0.00096924196,0.0022254838],"genre_scores_gemma":[0.85508704,0.00081218255,0.14242427,0.000029280303,0.000011775988,0.00008770451,0.00036794756,0.00013263994,0.0010470496],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99970764,0.000025625492,0.000015654752,0.00005586531,0.00016480974,0.000030422842],"domain_scores_gemma":[0.9992636,0.00023910351,0.00018444339,0.000055831442,0.00021088579,0.00004619628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045224986,0.00031205808,0.00021344525,0.0020419096,0.00016127339,0.0010040413,0.00019375038,0.00033521076,0.000832914],"category_scores_gemma":[0.0010712903,0.00042717674,0.00018589206,0.0008681431,0.00036065056,0.00045214474,0.00038721506,0.00033811608,0.00021699151],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014887564,0.00003150776,0.02924352,0.00027391012,0.000048114714,0.00015242457,0.0004964952,0.012314289,0.884464,0.00175434,0.00031117708,0.070761375],"study_design_scores_gemma":[0.0000257979,0.00020099063,0.3323229,0.00013440932,0.0001534063,0.0017953599,0.00078028615,0.13098879,0.5233548,0.0021663404,0.0078588715,0.00021807759],"about_ca_topic_score_codex":0.002415951,"about_ca_topic_score_gemma":0.005094907,"teacher_disagreement_score":0.002415951,"about_ca_system_score_codex":0.00036522318,"about_ca_system_score_gemma":0.0006715254,"threshold_uncertainty_score":0.0048037767},"labels":[],"label_agreement":null},{"id":"W4389078794","doi":"10.1162/imag_a_00050","title":"White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"Vanderbilt University; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"White matter; Gray (unit); Morphology (biology); Brain morphometry; Anatomy; Biology; Paleontology; Medicine; Magnetic resonance imaging","score_opus":0.03056917881249906,"score_gpt":0.35186490783382746,"score_spread":0.3212957290213284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389078794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99076474,0.00034289103,0.00342075,0.000050897568,0.0000025001343,0.000008863197,0.004857806,0.00004522703,0.00050628907],"genre_scores_gemma":[0.9910193,0.00022027435,0.004615918,0.000014280292,0.0000041806184,0.000021125625,0.0036195272,0.00002591431,0.0004593995],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998528,0.000035896377,0.000015498244,0.000058262736,0.000023237837,0.000014358433],"domain_scores_gemma":[0.9986338,0.0002371577,0.00049386214,0.0002600709,0.0002841304,0.000090991074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008761127,0.00021825913,0.00018444694,0.0012717322,0.0002312664,0.00040957294,0.00017746654,0.00021977392,0.0013528952],"category_scores_gemma":[0.0025193933,0.00016734816,0.00021580946,0.00073590444,0.00028333312,0.00039993547,0.00044312846,0.00019914495,0.00018216137],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039773257,0.0000610821,0.91523975,0.00017638523,0.00071368617,0.00022514342,0.0008120023,0.004599317,0.04085001,0.0010504752,0.0019640815,0.033910416],"study_design_scores_gemma":[0.0000029434325,0.000031922835,0.9951492,0.000021101598,0.000042811396,0.00034100664,0.00007540919,0.0016059198,0.0013390766,0.00074335764,0.00063903176,0.000008169663],"about_ca_topic_score_codex":0.0057139555,"about_ca_topic_score_gemma":0.0154739665,"teacher_disagreement_score":0.0057139555,"about_ca_system_score_codex":0.00022603058,"about_ca_system_score_gemma":0.00030842892,"threshold_uncertainty_score":0.01136142},"labels":[],"label_agreement":null},{"id":"W4389082732","doi":"10.1002/pbc.30787","title":"Higher order neurocognition in pediatric brain tumor survivors: What can we learn from white matter microstructure?","year":2023,"lang":"en","type":"article","venue":"Pediatric Blood & Cancer","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"National Cancer Institute; St. Baldrick's Foundation","keywords":"Neurocognitive; Medicine; White matter; White (mutation); Pediatrics; Cognition; Psychiatry; Magnetic resonance imaging; Radiology; Genetics","score_opus":0.026041752452748448,"score_gpt":0.302363349720754,"score_spread":0.2763215972680056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389082732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96201795,0.032731783,0.00033235113,0.0038938972,0.00006014065,0.000013993998,0.00019477154,0.000015617732,0.0007396171],"genre_scores_gemma":[0.9689433,0.02881696,0.00097406714,0.00042786932,0.00025785607,0.000018844588,0.00027568475,0.0000061624874,0.00027935076],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990785,0.000020995773,0.000009825235,0.000022813572,0.000014724199,0.000023765748],"domain_scores_gemma":[0.99945766,0.00011075167,0.00024200034,0.00003195183,0.000072754876,0.00008484939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053416943,0.0003287055,0.00034593605,0.00065992365,0.00023146872,0.00077573577,0.0004695967,0.0007631981,0.0008269965],"category_scores_gemma":[0.0017476287,0.00014806418,0.00027441097,0.0005435049,0.00067743275,0.0015143896,0.00027079575,0.0005191331,0.0001719392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015269945,0.00011063099,0.9192027,0.0002681976,0.00010157164,0.00054799777,0.00063967734,0.0001838604,0.0011952227,0.0002232511,0.001101968,0.076272175],"study_design_scores_gemma":[0.000006698698,0.00024768338,0.99434257,0.0002355208,0.00006269588,0.0011034181,0.0014298233,0.00026115015,0.00029467852,0.0005511434,0.0014553261,0.00000931223],"about_ca_topic_score_codex":0.0067446386,"about_ca_topic_score_gemma":0.011147898,"teacher_disagreement_score":0.0067446386,"about_ca_system_score_codex":0.0004351392,"about_ca_system_score_gemma":0.0006276156,"threshold_uncertainty_score":0.013410807},"labels":[],"label_agreement":null},{"id":"W4389091910","doi":"10.3389/fnana.2023.1240545","title":"Structural connectivity of cytoarchitectonically distinct human left temporal pole subregions: a diffusion MRI tractography study","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Japan Society for the Promotion of Science; National Institutes of Health; Tokyo Medical and Dental University; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Cytoarchitecture; Tractography; Neuroscience; Diffusion MRI; Temporal lobe; Psychology; Magnetic resonance imaging; Medicine; Epilepsy","score_opus":0.03744864752543687,"score_gpt":0.3426132891846055,"score_spread":0.3051646416591686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389091910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973271,0.0001387259,0.0019561222,0.00003205769,0.0000014386728,0.000015092764,0.00018185542,0.000011450248,0.00033606475],"genre_scores_gemma":[0.99822336,0.00008024123,0.001175638,0.000012913429,0.0000033657338,0.0000130527205,0.00018238166,0.0000066916973,0.00030242783],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999471,0.000007709276,0.0000030466408,0.000025273794,0.0000074582404,0.000009378588],"domain_scores_gemma":[0.9998456,0.000053143845,0.000037546444,0.0000254486,0.000015364407,0.000022850387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016960844,0.00015842836,0.00020281652,0.00065685064,0.00026775277,0.00030414725,0.00013707332,0.00026313544,0.0015872016],"category_scores_gemma":[0.00064609305,0.00016992813,0.00017022571,0.0003596595,0.00043884513,0.00026983832,0.00019062078,0.00014202228,0.00024233773],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019282814,0.0003215608,0.34075046,0.00028426806,0.00046106637,0.0069862506,0.006032061,0.0034258761,0.5776331,0.003111102,0.0010211621,0.058044847],"study_design_scores_gemma":[0.00005592924,0.00016132933,0.9790339,0.000013417207,0.0000886204,0.0045435885,0.00044637462,0.007368582,0.005938624,0.0013700086,0.00095668604,0.000022927652],"about_ca_topic_score_codex":0.011302106,"about_ca_topic_score_gemma":0.022970434,"teacher_disagreement_score":0.011302106,"about_ca_system_score_codex":0.00034628218,"about_ca_system_score_gemma":0.0003265058,"threshold_uncertainty_score":0.02247268},"labels":[],"label_agreement":null},{"id":"W4389114783","doi":"","title":"Structural changes in white matter lesion patients and their correlation with cognitive impairment","year":2019,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cognitive impairment; White matter; Lesion; Cognition; Correlation; Medicine; Psychology; Neuroscience; Pathology; Magnetic resonance imaging; Radiology; Mathematics","score_opus":0.18009643986472218,"score_gpt":0.5104361970423364,"score_spread":0.33033975717761427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389114783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994562,0.00016957663,0.00004093061,0.000012464501,0.0000037374787,0.000004779943,0.000059264225,0.0000035511498,0.0002494715],"genre_scores_gemma":[0.9996861,0.00006051651,0.0000459169,0.00000726195,0.0000074590107,0.0000045394654,0.00009842492,9.594468e-7,0.0000887598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998259,0.000025437617,0.000035280005,0.000049851955,0.000035754445,0.00002779934],"domain_scores_gemma":[0.99932325,0.00012346513,0.00030306727,0.00003613738,0.00008022055,0.00013395268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028591347,0.0003899946,0.0003377071,0.0015142629,0.0003344912,0.00046849487,0.00023728867,0.0004655147,0.0014639184],"category_scores_gemma":[0.0013883593,0.00020977545,0.00020543074,0.00076686253,0.00037633211,0.00033917904,0.00034818426,0.00032357345,0.00018864793],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027181508,0.00004259488,0.99566984,0.000014658142,0.00006459659,0.0002961903,0.000094204115,0.000051009694,0.0009905209,0.000013120692,0.000043506134,0.002447843],"study_design_scores_gemma":[0.000006596175,0.00009472734,0.998869,0.0000022356269,0.000018867519,0.0006160576,0.00007683598,0.00011784387,0.00012998813,0.000027151225,0.000038152895,0.0000025697918],"about_ca_topic_score_codex":0.0014006543,"about_ca_topic_score_gemma":0.0015752796,"teacher_disagreement_score":0.0015142629,"about_ca_system_score_codex":0.00015809757,"about_ca_system_score_gemma":0.00014805007,"threshold_uncertainty_score":0.0048972964},"labels":[],"label_agreement":null},{"id":"W4389296200","doi":"10.1101/2023.12.02.569728","title":"Cortical Network Disruption is Minimal in Early Stages of Psychosis","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute; London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Psychosis; White matter; Voxel; Schizophrenia (object-oriented programming); Connectome; Neuroscience; Psychology; Diffusion MRI; Human Connectome Project; Magnetic resonance imaging; Medicine; Psychiatry; Functional connectivity; Radiology","score_opus":0.05740833260677875,"score_gpt":0.3263365423462528,"score_spread":0.26892820973947407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389296200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985032,0.00013477611,0.00045461615,0.000048734113,0.0000016851496,0.000009821226,0.00028407754,0.000015074435,0.00054805836],"genre_scores_gemma":[0.99963236,0.000031819225,0.000119195465,0.0000063104267,0.0000011935209,0.000003342119,0.00013949894,0.0000024789147,0.00006373627],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997328,0.00004322755,0.000019317886,0.000096608965,0.000051104653,0.00005689149],"domain_scores_gemma":[0.9984754,0.00024705497,0.00071308046,0.00019027258,0.00013023664,0.00024397818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004099395,0.00025318196,0.0004143805,0.0010787006,0.0004735143,0.0009439308,0.00029605758,0.00032541007,0.0018091394],"category_scores_gemma":[0.0025901848,0.00035554232,0.0002173626,0.0005812703,0.0009660738,0.0006089955,0.00081979966,0.0003913178,0.00013342651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027895232,0.00010023543,0.8923062,0.00021275181,0.00046064507,0.0015123448,0.0018242665,0.002996914,0.0769144,0.0012183131,0.00089885225,0.018765585],"study_design_scores_gemma":[0.000009117282,0.00006942174,0.99703217,0.000008956958,0.000022697732,0.00032661876,0.000214852,0.00068050413,0.0007650771,0.0007266915,0.00013860555,0.000005221135],"about_ca_topic_score_codex":0.014798889,"about_ca_topic_score_gemma":0.025043607,"teacher_disagreement_score":0.014798889,"about_ca_system_score_codex":0.0009275007,"about_ca_system_score_gemma":0.00047078042,"threshold_uncertainty_score":0.029425502},"labels":[],"label_agreement":null},{"id":"W4389327159","doi":"10.1162/imag_a_00055","title":"Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric modelling, and spatial regularization","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Congressionally Directed Medical Research Programs; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; U.S. Department of Defense","keywords":"Kurtosis; Computation; Rotational symmetry; Regularization (linguistics); Algorithm; Computer science; Scheme (mathematics); Mathematics; Applied mathematics; Statistical physics; Mathematical optimization; Physics; Mathematical analysis; Artificial intelligence; Statistics; Geometry","score_opus":0.1124566290593675,"score_gpt":0.34453630092826504,"score_spread":0.23207967186889755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389327159","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022957217,0.000051255884,0.97582495,0.000072402705,0.0000146944,0.000034660967,0.00004540318,0.00050009537,0.00049940264],"genre_scores_gemma":[0.15470111,0.00011700477,0.84334886,0.000036963396,0.000011736142,0.000105231666,0.00020585308,0.00028093855,0.0011921847],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996573,0.000085290274,0.000026141905,0.0000534128,0.0001516931,0.000026225705],"domain_scores_gemma":[0.99918085,0.00022035824,0.00015580337,0.00016982216,0.00021906354,0.000054067943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013167941,0.00095925835,0.00046276368,0.0006146594,0.00031258928,0.000751209,0.0008423593,0.00076525396,0.0012445742],"category_scores_gemma":[0.0032202334,0.00039906488,0.0006588783,0.00051804987,0.00050501205,0.0011022714,0.0008791961,0.0011301726,0.00063443376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023539388,0.00016557156,0.00220636,0.00022969824,0.00009757102,0.00017107656,0.00017529259,0.49462962,0.32346666,0.036805928,0.0021043997,0.13971241],"study_design_scores_gemma":[0.00000700847,0.000035149387,0.00025782792,0.0000061798,0.0000056894564,0.000041488882,0.000007553014,0.9758276,0.020849178,0.0017643766,0.001179291,0.000018661398],"about_ca_topic_score_codex":0.0016673998,"about_ca_topic_score_gemma":0.002196747,"teacher_disagreement_score":0.0016673998,"about_ca_system_score_codex":0.0004595715,"about_ca_system_score_gemma":0.0013455662,"threshold_uncertainty_score":0.0069639683},"labels":[],"label_agreement":null},{"id":"W4389393863","doi":"10.1101/2023.12.05.23299222","title":"BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; Alzheimer's Association","keywords":"Ethnic group; Voxel; Neuroimaging; Race (biology); Estimation; Field (mathematics); Stability (learning theory); Statistics; Psychology; Mathematics; Computer science; Artificial intelligence; Biology; Engineering; Machine learning; Neuroscience","score_opus":0.06594420547756673,"score_gpt":0.3812673033361469,"score_spread":0.31532309785858015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389393863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6143724,0.0056179008,0.36686024,0.0020143702,0.00081579894,0.00028484678,0.0021007704,0.0036536444,0.004280008],"genre_scores_gemma":[0.94291794,0.00032243252,0.050787687,0.00028592948,0.00007082389,0.00012482009,0.0012954893,0.0015183942,0.0026764735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9899087,0.006284122,0.0004453006,0.0021239,0.00084888935,0.0003889478],"domain_scores_gemma":[0.9357712,0.049670428,0.003491123,0.006725787,0.003546706,0.00079473207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031720206,0.0011951762,0.0009817358,0.0009643087,0.00082575786,0.0016971689,0.0015025825,0.0007181287,0.0035390866],"category_scores_gemma":[0.10750759,0.00041061811,0.0011828904,0.001009787,0.0011091221,0.0017315453,0.0011203769,0.0011052375,0.0009079636],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00584731,0.00018813327,0.6889632,0.0006710751,0.0062804935,0.0011020991,0.002752843,0.017084979,0.020682005,0.0042598643,0.01277349,0.23939458],"study_design_scores_gemma":[0.0002240856,0.00091017294,0.7955629,0.00034614603,0.0026561522,0.0030593167,0.001337749,0.14236209,0.02553111,0.012695745,0.0150998365,0.00021469095],"about_ca_topic_score_codex":0.017504366,"about_ca_topic_score_gemma":0.013308952,"teacher_disagreement_score":0.031720206,"about_ca_system_score_codex":0.00048729315,"about_ca_system_score_gemma":0.0013358244,"threshold_uncertainty_score":0.16775447},"labels":[],"label_agreement":null},{"id":"W4389438701","doi":"10.1212/wnl.90.15_supplement.p3.069","title":"Microstructural Changes in the Thalamus and Putamen, as Measured by Diffusion Tensor Imaging, Correlate with Gait Abnormalities in Parkinson’s Disease (P3.069)","year":2018,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Putamen; Diffusion MRI; Gait; Medicine; Thalamus; Parkinson's disease; Neuroscience; Physical medicine and rehabilitation; Disease; Psychology; Internal medicine; Radiology; Magnetic resonance imaging","score_opus":0.020025872185449416,"score_gpt":0.2813415149341007,"score_spread":0.26131564274865127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389438701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972447,0.0006355212,0.0005326891,0.00010227294,0.00001228072,0.000031834967,0.0003027428,0.000010616741,0.0011275146],"genre_scores_gemma":[0.9978241,0.00024865186,0.0009957905,0.000039656865,0.000010296685,0.00003120633,0.00022831377,0.000003828064,0.0006181238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999037,0.000018019911,0.00001568206,0.000017396178,0.000027887752,0.000017288376],"domain_scores_gemma":[0.99976224,0.000028963952,0.000119111864,0.000009578828,0.000040997216,0.00003916282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028551792,0.00032159532,0.00019586492,0.0005711902,0.00019578032,0.00036367797,0.00022365592,0.0003321258,0.002104327],"category_scores_gemma":[0.0005485456,0.00012428744,0.00019444348,0.00036304424,0.00021492483,0.00025165998,0.00024912824,0.0002676323,0.0002659999],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004779835,0.0010779273,0.7545919,0.0004846153,0.00048950856,0.0031188775,0.00028306598,0.00089075894,0.15829915,0.0006534272,0.0019256169,0.07340524],"study_design_scores_gemma":[0.0000857726,0.001082469,0.980455,0.000037211383,0.00009805838,0.0037559108,0.00010314251,0.0015046957,0.011840678,0.00034946908,0.00067833887,0.000009268353],"about_ca_topic_score_codex":0.0022721111,"about_ca_topic_score_gemma":0.0055082575,"teacher_disagreement_score":0.0022721111,"about_ca_system_score_codex":0.00028251202,"about_ca_system_score_gemma":0.00027739842,"threshold_uncertainty_score":0.0070396066},"labels":[],"label_agreement":null},{"id":"W4389447579","doi":"10.1212/wnl.88.16_supplement.p1.156","title":"Assessment of radiation-induced white matter changes using myelin water imaging (P1.156)","year":2017,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"White matter; Medicine; White (mutation); Myelin; Radiation; Nuclear medicine; Internal medicine; Magnetic resonance imaging; Chemistry; Radiology; Optics; Physics; Central nervous system; Biochemistry","score_opus":0.07265836014425912,"score_gpt":0.39479148758252247,"score_spread":0.32213312743826333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389447579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9005514,0.009366573,0.06459633,0.0006771215,0.00020641442,0.0005631074,0.0013284531,0.0010535496,0.021657117],"genre_scores_gemma":[0.92096776,0.0069335047,0.04956516,0.0005647898,0.00009063729,0.00062967447,0.0013201698,0.0002959514,0.019632222],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998952,0.000019356472,0.000009833558,0.000028067858,0.0000288006,0.000018726185],"domain_scores_gemma":[0.9998078,0.000021039228,0.000059666687,0.00001359674,0.00006345613,0.0000345031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049598556,0.00065256335,0.00022104662,0.000833977,0.00028551984,0.00044167583,0.00034900013,0.00097248005,0.0046482924],"category_scores_gemma":[0.00064243627,0.00024318948,0.0002791609,0.0003820225,0.0002863469,0.0010613872,0.00034871112,0.0007205585,0.0014050718],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007981118,0.00017966235,0.0079860715,0.00062970264,0.00007323738,0.0011148602,0.0001139362,0.00033659107,0.9312676,0.00054984196,0.0018230003,0.05512732],"study_design_scores_gemma":[0.00009900164,0.0027935698,0.06568923,0.00018120804,0.00025889138,0.007231255,0.00018512741,0.0033464285,0.90832573,0.0011932172,0.010643675,0.000052642394],"about_ca_topic_score_codex":0.0008514991,"about_ca_topic_score_gemma":0.000955274,"teacher_disagreement_score":0.0046482924,"about_ca_system_score_codex":0.00021267634,"about_ca_system_score_gemma":0.000325197,"threshold_uncertainty_score":0.015550077},"labels":[],"label_agreement":null},{"id":"W4389454614","doi":"10.1007/s10548-023-01020-4","title":"Correlation of Cognitive Reappraisal and the Microstructural Properties of the Forceps Minor: A Deductive Exploratory Diffusion Tensor Imaging Study","year":2023,"lang":"en","type":"article","venue":"Brain Topography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Statistical parametric mapping; Psychology; White matter; Correlation; Population; Medicine; Mathematics; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.03841103299032861,"score_gpt":0.31331938363475276,"score_spread":0.27490835064442415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389454614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99863774,0.000050213643,0.00053486944,0.000058559584,0.0000055560154,0.000031184965,0.00006926879,0.0000059536615,0.0006065347],"genre_scores_gemma":[0.9993358,0.00003275694,0.0003602473,0.000012962585,0.0000117285335,0.000010854168,0.000042329062,0.000005770177,0.00018767676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948645,0.00012671687,0.000048569218,0.000115958464,0.00015766741,0.000064655804],"domain_scores_gemma":[0.9901608,0.00446945,0.0026144555,0.0014494297,0.0009531517,0.00035262952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021112103,0.0007441874,0.0004057248,0.001218145,0.000646854,0.0010020073,0.00077284226,0.0005356016,0.002814569],"category_scores_gemma":[0.022077518,0.0004320014,0.0003552672,0.0006857936,0.001323439,0.0011728995,0.0007603876,0.0011040984,0.0003296536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029429207,0.0010851368,0.9119801,0.0001697157,0.0005895054,0.0031981787,0.009263186,0.0010558198,0.032882996,0.0014177174,0.00043686057,0.034977842],"study_design_scores_gemma":[0.000037847352,0.0005857702,0.9892532,0.000011149056,0.00014210602,0.0023408227,0.0017829138,0.0018793467,0.002305877,0.0013135285,0.00030763476,0.000039791743],"about_ca_topic_score_codex":0.0054844897,"about_ca_topic_score_gemma":0.0043580765,"teacher_disagreement_score":0.0054844897,"about_ca_system_score_codex":0.0003617759,"about_ca_system_score_gemma":0.0009771604,"threshold_uncertainty_score":0.011165261},"labels":[],"label_agreement":null},{"id":"W4389465228","doi":"10.1212/wnl.92.15_supplement.p5.1-025","title":"Diffusion Tensor Imaging in pre-dementia risk states: white matter atrophy findings in Mild Behavioral Impairment (P5.1-025)","year":2019,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Bible College; Centre for Addiction and Mental Health; Ontario Brain Institute","funders":"","keywords":"Diffusion MRI; Dementia; White matter; Atrophy; Medicine; Psychology; Psychiatry; Audiology; Neuroscience; Clinical psychology; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.015466424725711966,"score_gpt":0.3085858240965957,"score_spread":0.2931193993708837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389465228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998064,0.00017017724,0.00008708639,0.00007435543,0.0000065575923,0.000046098423,0.00031907565,0.0000050084122,0.0012276324],"genre_scores_gemma":[0.9986401,0.00010065405,0.0002511778,0.000033838285,0.0000066673683,0.000019615612,0.00034065847,0.000001803486,0.00060553045],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999006,0.000017519558,0.00001634629,0.000015299845,0.000021723205,0.000028589791],"domain_scores_gemma":[0.99968755,0.000015385434,0.000114948256,0.000012712409,0.00005745059,0.00011194921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039866145,0.0004711387,0.00022858316,0.000943836,0.0005865432,0.0005110367,0.0003649573,0.0004391259,0.0018788618],"category_scores_gemma":[0.00077309384,0.00016122864,0.00026495,0.000558947,0.00017374846,0.00042745232,0.00045983092,0.00045244864,0.0003493808],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009361294,0.0004052138,0.9864151,0.000042149208,0.0001059437,0.0012157062,0.00019078671,0.00010895525,0.0031099666,0.00009811141,0.0005027083,0.006869259],"study_design_scores_gemma":[0.000021509297,0.0004073579,0.99744487,0.00001440031,0.000037099897,0.000971314,0.00013833285,0.00020952438,0.00042116756,0.00009063978,0.00024061685,0.0000032150651],"about_ca_topic_score_codex":0.009394068,"about_ca_topic_score_gemma":0.018343396,"teacher_disagreement_score":0.009394068,"about_ca_system_score_codex":0.0003769182,"about_ca_system_score_gemma":0.00054301915,"threshold_uncertainty_score":0.018678784},"labels":[],"label_agreement":null},{"id":"W4389504585","doi":"10.1007/s00429-023-02729-5","title":"Ventral and dorsal aspects of the inferior frontal-occipital fasciculus support verbal semantic access and visually-guided behavioural control","year":2023,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"HORIZON EUROPE European Research Council","keywords":"Fasciculus; Psychology; Neuroscience; Lateralization of brain function; Cognitive psychology; Dorsum; White matter; Anatomy; Biology; Medicine; Magnetic resonance imaging","score_opus":0.034605007669759276,"score_gpt":0.32854251223875613,"score_spread":0.29393750456899687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389504585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99341303,0.00025077548,0.0036315585,0.000073468924,0.000009514529,0.000010908554,0.00012571526,0.00003524725,0.0024498682],"genre_scores_gemma":[0.99838066,0.000069518355,0.0009374338,0.000017463126,0.000003431568,0.000009499192,0.000082622595,0.000012803129,0.000486501],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999845,0.00002477472,0.000008940777,0.00003371429,0.00003119775,0.000056237248],"domain_scores_gemma":[0.99943465,0.000100232464,0.00026692206,0.00005026258,0.000050989875,0.00009691664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020820742,0.00027899112,0.00019548617,0.0002807573,0.00013941654,0.00047375177,0.00011713639,0.00021881025,0.0013537852],"category_scores_gemma":[0.0014105735,0.00010643029,0.00015118804,0.000101549915,0.00061649666,0.00032569034,0.00034855274,0.00026874125,0.00016772229],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015005361,0.0000907479,0.05001915,0.00015393709,0.000063837135,0.00041744314,0.00095792045,0.00072284916,0.91646075,0.0022506765,0.00025783174,0.027104339],"study_design_scores_gemma":[0.00006340511,0.00032970725,0.89384437,0.000043477445,0.000079644095,0.0008728677,0.0006715945,0.0033761938,0.09527622,0.0038857993,0.0015250918,0.000031587497],"about_ca_topic_score_codex":0.0037058247,"about_ca_topic_score_gemma":0.0048323856,"teacher_disagreement_score":0.0037058247,"about_ca_system_score_codex":0.0003232854,"about_ca_system_score_gemma":0.00036112656,"threshold_uncertainty_score":0.007368505},"labels":[],"label_agreement":null},{"id":"W4389685319","doi":"10.1038/s41380-023-02321-7","title":"Cortical microstructural associations with CSF amyloid and pTau","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Amyloid (mycology); Neuroscience; Amyloid β; Psychology; Medicine; Pathology; Disease","score_opus":0.021956056100683442,"score_gpt":0.3251232938679941,"score_spread":0.30316723776731064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389685319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99888784,0.00021554562,0.0002743374,0.00001795721,0.0000029557052,0.000004144157,0.00016650706,0.000011000896,0.00041968838],"genre_scores_gemma":[0.9996145,0.000044337907,0.00013685328,0.0000041937565,0.0000026612815,0.0000022337351,0.00004440256,0.0000016666474,0.00014913625],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999908,0.000012817116,0.000008123903,0.00003378245,0.000023388977,0.000013927291],"domain_scores_gemma":[0.9993286,0.00010752152,0.00036272942,0.00005022505,0.000085033564,0.000065907545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020155094,0.00046141955,0.0002026045,0.0009100942,0.00023290791,0.0005812138,0.00017216183,0.00021164185,0.0019327207],"category_scores_gemma":[0.001313159,0.00017382468,0.000119095566,0.0004570675,0.0003269322,0.00026988308,0.0003065662,0.00021613728,0.00021918087],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001470129,0.00009105159,0.9311977,0.000114559894,0.00029592944,0.0012584799,0.00072922907,0.00059471186,0.049291354,0.00019713864,0.00031844023,0.014441237],"study_design_scores_gemma":[0.000005807659,0.00007800885,0.9953556,0.0000048384236,0.00002617239,0.0010164496,0.00012470262,0.00042355846,0.0025994573,0.00022700973,0.0001335438,0.0000049189784],"about_ca_topic_score_codex":0.0039398526,"about_ca_topic_score_gemma":0.003133489,"teacher_disagreement_score":0.0039398526,"about_ca_system_score_codex":0.00018325822,"about_ca_system_score_gemma":0.00015148532,"threshold_uncertainty_score":0.007833898},"labels":[],"label_agreement":null},{"id":"W4389720650","doi":"10.1016/j.brainresbull.2023.110847","title":"Association between altered white matter networks and post operative ventricle volume in shunt-treated pediatric hydrocephalus","year":2023,"lang":"en","type":"article","venue":"Brain Research Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Tractography; Hydrocephalus; Fractional anisotropy; Diffusion MRI; Ventriculomegaly; Frontal lobe; Medicine; Psychology; Neuroscience; Radiology; Magnetic resonance imaging; Biology; Fetus","score_opus":0.059906250697530014,"score_gpt":0.39088964651261265,"score_spread":0.3309833958150826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389720650","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993363,0.00012299525,0.00033021162,0.000012849761,0.0000012419847,0.0000028382312,0.000095675954,0.000005431604,0.00009238629],"genre_scores_gemma":[0.99937135,0.00007948525,0.00036299878,0.0000036454132,0.0000021256978,0.0000059719328,0.00012721274,0.0000028835693,0.00004431681],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997832,0.000037887417,0.0000214735,0.00007627987,0.000056001343,0.000025167965],"domain_scores_gemma":[0.9984932,0.00025477118,0.0009823947,0.000057471058,0.0001148475,0.00009731108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030359972,0.00025152805,0.00021601078,0.00085295225,0.00020353231,0.00035682652,0.00018785633,0.0002201693,0.0009798902],"category_scores_gemma":[0.001971371,0.0001248393,0.00018268457,0.00049596454,0.0003644082,0.00043935806,0.00033903925,0.00022822883,0.000069912094],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013980032,0.00002115621,0.99119884,0.00002340522,0.000075930024,0.00038723517,0.00012340548,0.00049808266,0.0031013193,0.00007685892,0.00007074339,0.004283318],"study_design_scores_gemma":[0.000002701869,0.00007771046,0.9969823,0.000007207582,0.000022009206,0.0011527942,0.000121588986,0.0007792549,0.0007086324,0.00006226127,0.00008061611,0.000002962548],"about_ca_topic_score_codex":0.0017458352,"about_ca_topic_score_gemma":0.0028979657,"teacher_disagreement_score":0.0017458352,"about_ca_system_score_codex":0.00030908594,"about_ca_system_score_gemma":0.00034236786,"threshold_uncertainty_score":0.003471315},"labels":[],"label_agreement":null},{"id":"W4389912612","doi":"10.3390/diagnostics13243679","title":"Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment","year":2023,"lang":"en","type":"article","venue":"Diagnostics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Cognitive impairment; Percentile rank; Normative; Psychology; Percentile; Montreal Cognitive Assessment; Cognition; Population; Medicine; Audiology; Magnetic resonance imaging; Internal medicine; Psychiatry; Radiology; Neuroscience","score_opus":0.03263545401581467,"score_gpt":0.3120306757375723,"score_spread":0.2793952217217576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389912612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99948776,0.00012779678,0.000034434343,0.000013276673,0.0000024119772,0.0000031177665,0.000054377175,0.0000018987138,0.00027494153],"genre_scores_gemma":[0.9997557,0.00003618589,0.000050445287,0.0000074506356,0.000004079599,0.0000030380536,0.00006224542,7.8430025e-7,0.00008007309],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998447,0.000024797806,0.000028066841,0.000047973015,0.000029051105,0.000025411036],"domain_scores_gemma":[0.999295,0.00016335527,0.00031432736,0.000052324234,0.000085523134,0.000089417284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046342227,0.00042629807,0.00035650897,0.0014563993,0.0004047696,0.0004634722,0.00019439824,0.00048309538,0.0013507542],"category_scores_gemma":[0.0022798143,0.00015391187,0.00023394346,0.0006210701,0.0003570353,0.00045297062,0.00030366398,0.00029994446,0.00019314411],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087524834,0.00010590768,0.98735666,0.000040265626,0.00012729349,0.00083832425,0.00075567566,0.00013565371,0.0034970457,0.00006446652,0.00013067057,0.00607281],"study_design_scores_gemma":[0.0000062815498,0.00010819427,0.9984926,0.000004519463,0.000022542667,0.00080493494,0.00018421604,0.000099647856,0.00015627922,0.000053454623,0.00006390558,0.0000034099019],"about_ca_topic_score_codex":0.0034742001,"about_ca_topic_score_gemma":0.0037769885,"teacher_disagreement_score":0.0034742001,"about_ca_system_score_codex":0.000218022,"about_ca_system_score_gemma":0.00020070464,"threshold_uncertainty_score":0.00690794},"labels":[],"label_agreement":null},{"id":"W4389990655","doi":"10.1016/j.compbiomed.2023.107873","title":"Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN","year":2023,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"National Key Research and Development Program of China; Science and Technology Department of Gansu Province; National Natural Science Foundation of China","keywords":"Deep learning; Computer science; Artificial intelligence; Convolutional neural network; Context (archaeology); Feature engineering; Feature (linguistics); Feature extraction; Machine learning; Neuroimaging; Pattern recognition (psychology); Salient; Neuroscience; Psychology","score_opus":0.026409830575013792,"score_gpt":0.3527112814833023,"score_spread":0.3263014509082885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389990655","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22544394,0.011023976,0.7319333,0.0015952935,0.0016285762,0.00019222284,0.008060569,0.012673124,0.007449033],"genre_scores_gemma":[0.85346293,0.0026072226,0.12517199,0.0009718583,0.0005212217,0.00010114535,0.00671613,0.00033246935,0.01011509],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997179,0.000025972791,0.00001319014,0.000121027,0.00005470567,0.00006715091],"domain_scores_gemma":[0.99959797,0.00009647174,0.000039302966,0.000060677026,0.00017628248,0.00002932661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053707487,0.0015230473,0.0011793234,0.0015640924,0.00027480922,0.00064986973,0.0012284273,0.0013607376,0.0022566768],"category_scores_gemma":[0.0014032171,0.00046440953,0.0013269794,0.0009855983,0.00020780959,0.00086194597,0.0010296508,0.0009239413,0.0019709931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005074131,0.0002604067,0.018322155,0.00019761053,0.00033872976,0.00037410483,0.00005225542,0.07334155,0.024075394,0.0012912065,0.02822559,0.8530136],"study_design_scores_gemma":[0.000012989777,0.00006191766,0.005081316,0.000031475323,0.00011514414,0.00033813968,0.000015631229,0.9823653,0.007622301,0.0021338987,0.0022009728,0.000020830621],"about_ca_topic_score_codex":0.01703032,"about_ca_topic_score_gemma":0.02446776,"teacher_disagreement_score":0.01703032,"about_ca_system_score_codex":0.0005774582,"about_ca_system_score_gemma":0.00076788745,"threshold_uncertainty_score":0.033862412},"labels":[],"label_agreement":null},{"id":"W4390081233","doi":"10.1093/geroni/igad104.2230","title":"AGE EFFECTS ON WHITE MATTER TOPOLOGY IN OLDER ADULTS AT HIGH RISK OF ALZHEIMER’S DISEASE","year":2023,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Betweenness centrality; Medicine; Stroop effect; Cognition; Cohort; Psychology; Gerontology; Internal medicine; Centrality; Neuroscience; Magnetic resonance imaging","score_opus":0.032175810138589195,"score_gpt":0.34731557564005056,"score_spread":0.3151397655014614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390081233","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994073,0.00015552987,0.00006328823,0.000012065657,0.0000028223717,0.000002716854,0.00015131595,0.000002374958,0.0002026342],"genre_scores_gemma":[0.99961096,0.000054833785,0.00007218144,0.000005480166,0.0000045049,0.000002566663,0.00011761613,8.5589096e-7,0.00013092978],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989283,0.000021564965,0.000015413505,0.000033268447,0.000021843276,0.000015100152],"domain_scores_gemma":[0.9991197,0.00013473837,0.0004520935,0.000068476285,0.00010537459,0.00011950188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034628907,0.00025191205,0.00020521712,0.0006431227,0.00023566395,0.0003627612,0.00010871171,0.00029617135,0.0018662057],"category_scores_gemma":[0.0018130514,0.00013247985,0.00017569466,0.0004956403,0.00013043343,0.000357505,0.00026023728,0.00021264656,0.00017982179],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005142269,0.000067233246,0.9929725,0.00002031501,0.00011757533,0.00014500695,0.00022687695,0.00011009161,0.0023427387,0.000037111775,0.00010136119,0.0033449451],"study_design_scores_gemma":[0.0000016738032,0.00005420716,0.99963784,0.0000015564098,0.000012091965,0.00008177461,0.000031760646,0.0000693455,0.000046836794,0.000028113858,0.000033745473,9.942629e-7],"about_ca_topic_score_codex":0.0021260474,"about_ca_topic_score_gemma":0.0037763137,"teacher_disagreement_score":0.0021260474,"about_ca_system_score_codex":0.0000973666,"about_ca_system_score_gemma":0.00007370729,"threshold_uncertainty_score":0.00624305},"labels":[],"label_agreement":null},{"id":"W4390084724","doi":"10.1017/s135561772301130x","title":"48 Sex Differences and Longitudinal Changes in White Matter Microstructure in Healthy Older Adults","year":2023,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute of Aging; University of Victoria","funders":"","keywords":"Longitudinal study; White matter; Diffusion MRI; Cohort; Aging brain; Medicine; Population; Superior longitudinal fasciculus; Gerontology; Cohort study; Psychology; Disease; Magnetic resonance imaging; Fractional anisotropy; Pathology","score_opus":0.051027585576921296,"score_gpt":0.3635444276507216,"score_spread":0.3125168420738003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390084724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961572,0.0014420609,0.00017560435,0.0000891428,0.000021771384,0.000012021512,0.0008615271,0.0000067793603,0.0012338189],"genre_scores_gemma":[0.99796814,0.00045341635,0.00018751594,0.00006367897,0.000022506922,0.000015979063,0.00045582498,0.0000041486337,0.00082871655],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998696,0.00001754801,0.000019048839,0.000049998256,0.000024143754,0.00001957286],"domain_scores_gemma":[0.9996166,0.000050359162,0.00019844343,0.00003259796,0.00006313117,0.000038807735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004335137,0.00019168043,0.00016075154,0.00039671076,0.00023579385,0.00034606914,0.00012636223,0.00024259732,0.003312712],"category_scores_gemma":[0.0012861437,0.000100231126,0.0002416711,0.00030397475,0.00011773628,0.00035868873,0.00022206207,0.00013486102,0.00046529688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047716286,0.000052795407,0.9826434,0.000045584115,0.00010939244,0.00017398101,0.0005105417,0.000031171254,0.0015230605,0.000094442934,0.00042059747,0.013917806],"study_design_scores_gemma":[0.000006648547,0.00011376948,0.9990152,0.000013106499,0.000022513288,0.00018772128,0.00010225773,0.000040911225,0.00009382837,0.000071774186,0.0003300466,0.0000021603225],"about_ca_topic_score_codex":0.0014699391,"about_ca_topic_score_gemma":0.0023368606,"teacher_disagreement_score":0.003312712,"about_ca_system_score_codex":0.00008582869,"about_ca_system_score_gemma":0.00012310101,"threshold_uncertainty_score":0.011082113},"labels":[],"label_agreement":null},{"id":"W4390097831","doi":"10.1109/mercon60487.2023.10355503","title":"Exploring Asymmetrical White Matter Abnormalities in Alzheimer’s using Deep Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"White matter; Deep learning; Artificial intelligence; Computer science; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.3979311201407268,"score_gpt":0.39915428140046544,"score_spread":0.0012231612597386476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390097831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66976404,0.002431293,0.3223795,0.00082682126,0.00006888426,0.00005277064,0.0007113656,0.00054830546,0.0032170154],"genre_scores_gemma":[0.9637122,0.0005899858,0.03437419,0.00010913801,0.00002555512,0.000017999488,0.00033912246,0.000023104969,0.00080874626],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998952,0.000025423955,0.0000056996455,0.000029719959,0.000020344614,0.000023495224],"domain_scores_gemma":[0.9998093,0.000075400065,0.00004634276,0.000021339321,0.000029410065,0.000018111792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048112223,0.0005396061,0.0002642409,0.0010197457,0.00018594525,0.00060592266,0.0003299397,0.00036530348,0.00071070046],"category_scores_gemma":[0.0012492357,0.0001779885,0.00035753584,0.00051421917,0.0002814952,0.0007615711,0.00053206674,0.0005039921,0.00013160065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000682803,0.0002885721,0.11301664,0.00041515642,0.0006131496,0.0013669799,0.0006086955,0.18941739,0.09700491,0.011891105,0.0047845202,0.5799101],"study_design_scores_gemma":[0.000014566477,0.00008288927,0.026020216,0.00005382937,0.00008404971,0.0005332275,0.00014884981,0.9306598,0.013929953,0.026992306,0.001455369,0.000024993624],"about_ca_topic_score_codex":0.0037020643,"about_ca_topic_score_gemma":0.0076872287,"teacher_disagreement_score":0.0037020643,"about_ca_system_score_codex":0.00029399863,"about_ca_system_score_gemma":0.0003460647,"threshold_uncertainty_score":0.0073610544},"labels":[],"label_agreement":null},{"id":"W4390192459","doi":"10.1002/alz.071668","title":"The effect of computerized cognitive training and exercise on white matter integrity: a secondary analysis of a randomized controlled trial","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Randomized controlled trial; Fractional anisotropy; Medicine; Diffusion MRI; White matter; Cognition; Aerobic exercise; Physical therapy; Brain Structure and Function; Cognitive training; Cognitive decline; Physical medicine and rehabilitation; Psychology; Dementia; Internal medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.03995827972316692,"score_gpt":0.3412856810052768,"score_spread":0.3013274012821099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390192459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9498039,0.011106581,0.002212887,0.00080594077,0.0021887359,0.028175162,0.0026442064,0.00025076815,0.0028116913],"genre_scores_gemma":[0.9472899,0.0021157665,0.003665023,0.0008746463,0.0009533542,0.041412868,0.0009544895,0.000034583478,0.0026993211],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.99504364,0.002891627,0.00048473023,0.00073481136,0.0003515844,0.00049370626],"domain_scores_gemma":[0.9916231,0.0041606296,0.0017941747,0.0006211898,0.0009417511,0.00085905305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006491101,0.002402902,0.0073463763,0.0008884558,0.0008119073,0.0019591583,0.0012459797,0.0026544414,0.0099746715],"category_scores_gemma":[0.011114164,0.00079018215,0.006016511,0.001013014,0.0014412318,0.0016095672,0.00092148286,0.0028991355,0.0008039859],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.98416984,0.003332254,0.00072006346,0.0017730985,0.005570503,0.000027574131,0.00003621331,0.00014241316,0.0004296242,0.0000838487,0.0003983934,0.0033161764],"study_design_scores_gemma":[0.94328076,0.044178527,0.003490841,0.00017170415,0.00735579,0.00001634524,0.000033147175,0.0004726987,0.00028349564,0.00026139815,0.00043517735,0.000020183908],"about_ca_topic_score_codex":0.0017557524,"about_ca_topic_score_gemma":0.002236416,"teacher_disagreement_score":0.0099746715,"about_ca_system_score_codex":0.001307035,"about_ca_system_score_gemma":0.0025659145,"threshold_uncertainty_score":0.03432858},"labels":[],"label_agreement":null},{"id":"W4390194192","doi":"10.1002/alz.072638","title":"Longitudinal free‐water changes in dementia with Lewy bodies","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Dementia with Lewy bodies; White matter; Fractional anisotropy; Grey matter; Diffusion MRI; Medicine; Dementia; Putamen; Psychology; Internal medicine; Magnetic resonance imaging; Radiology; Disease","score_opus":0.09174883435333978,"score_gpt":0.3391665871301575,"score_spread":0.24741775277681774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99894685,0.00034793338,0.000121653735,0.000015700049,0.0000036992042,0.000009807802,0.00029389164,0.000011452013,0.00024897177],"genre_scores_gemma":[0.9988545,0.000089368405,0.00017600981,0.0000140977345,0.0000057932407,0.00001088157,0.00050261733,0.0000032129255,0.00034356926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998437,0.000023451843,0.000016302425,0.00004858982,0.000028821012,0.000039005987],"domain_scores_gemma":[0.9991473,0.00006175229,0.00039273617,0.000048513994,0.00020959195,0.00014010104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005166228,0.00038528797,0.00035041335,0.0011074055,0.0007311998,0.0006062005,0.00029944812,0.00045056423,0.0016769185],"category_scores_gemma":[0.0015809233,0.00024765375,0.00026828045,0.0005433446,0.00019960385,0.000670718,0.0004693573,0.00047209123,0.0003469232],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015340437,0.00028095357,0.9721728,0.00006007986,0.0002126472,0.00080224744,0.0006256857,0.00014203071,0.010577853,0.000026795804,0.00036383065,0.013201061],"study_design_scores_gemma":[0.0000078138355,0.00024062123,0.99793303,0.0000073093192,0.000038924987,0.0004993536,0.000119470984,0.00009429245,0.00085460104,0.00003822238,0.00016056398,0.0000057317748],"about_ca_topic_score_codex":0.008913013,"about_ca_topic_score_gemma":0.0102987215,"teacher_disagreement_score":0.008913013,"about_ca_system_score_codex":0.0003509235,"about_ca_system_score_gemma":0.00022480058,"threshold_uncertainty_score":0.017722249},"labels":[],"label_agreement":null},{"id":"W4390194261","doi":"10.1002/alz.080004","title":"Multivariate white matter differences links to cognition in individuals with family history of Alzheimer’s disease and APOE4 genetic risk","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Concordia University; McGill Genome Centre; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Multivariate statistics; Mahalanobis distance; Splenium; Univariate; Psychology; Neuropsychology; Corpus callosum; Multivariate analysis; Voxel; Cognition; White matter; Medicine; Clinical psychology; Artificial intelligence; Magnetic resonance imaging; Statistics; Internal medicine; Psychiatry; Neuroscience; Computer science; Mathematics; Radiology","score_opus":0.06582336743214791,"score_gpt":0.31374557819658794,"score_spread":0.24792221076444004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99905604,0.00009972082,0.00025283647,0.000031739255,0.0000028599347,0.0000013863626,0.00036610535,0.000010582622,0.00017875915],"genre_scores_gemma":[0.9994392,0.00002249747,0.00017760332,0.000004464781,0.0000057553298,0.0000019108134,0.0002497453,0.0000041051658,0.00009476008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971646,0.00006535904,0.00003194791,0.00011197017,0.000037924397,0.00003635725],"domain_scores_gemma":[0.9983182,0.00058536656,0.00064787036,0.0002090413,0.0001030513,0.0001364535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059933646,0.00046237872,0.00034297205,0.0014596316,0.00036207505,0.00054460607,0.00027151266,0.00036714214,0.0037304887],"category_scores_gemma":[0.002555921,0.00018369556,0.0006206506,0.0012518854,0.0002898509,0.00028813328,0.00041649071,0.00037264603,0.00021228007],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005315943,0.00004193063,0.9919442,0.000017250426,0.0005123644,0.00020790778,0.00010749208,0.00041716566,0.0018444377,0.00007766954,0.00018207861,0.0041160034],"study_design_scores_gemma":[0.000004104334,0.000030660427,0.99839276,0.0000027467515,0.000060212013,0.00020791467,0.00005724168,0.0007915769,0.00021346788,0.00015913392,0.00007584816,0.000004279918],"about_ca_topic_score_codex":0.00902964,"about_ca_topic_score_gemma":0.008032633,"teacher_disagreement_score":0.00902964,"about_ca_system_score_codex":0.0002208408,"about_ca_system_score_gemma":0.00019895668,"threshold_uncertainty_score":0.017954111},"labels":[],"label_agreement":null},{"id":"W4390194382","doi":"10.1002/alz.080407","title":"Visualizing Braak stages with deformation‐based morphometry in super‐sampled MRI","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; Entorhinal cortex; Voxel; Magnetic resonance imaging; Neocortex; Neurodegeneration; Neuroscience; Nuclear medicine; Hippocampus; Medicine; Pathology; Psychology; Alzheimer's disease; Radiology; Disease","score_opus":0.08663960118001099,"score_gpt":0.36831609014210415,"score_spread":0.2816764889620932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194382","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23044246,0.0005688637,0.76174426,0.00034073915,0.000060916806,0.00019504386,0.0011715004,0.0036122664,0.0018639591],"genre_scores_gemma":[0.644419,0.0004934266,0.35189435,0.00010104638,0.000050793948,0.00013080215,0.0011455304,0.0007279153,0.0010370879],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997677,0.000051321047,0.000015441368,0.000050466588,0.00008441317,0.000030637744],"domain_scores_gemma":[0.99911636,0.00031814468,0.00019254575,0.00016145945,0.00014442728,0.000066963265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008588503,0.00039252755,0.00029674993,0.0023677927,0.00018484044,0.0010723395,0.00057707523,0.00044769916,0.0020197],"category_scores_gemma":[0.0026888752,0.0004602721,0.00044630555,0.001093617,0.00047723297,0.00076163566,0.0007180397,0.0005285071,0.00042246337],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009937481,0.00022485151,0.025788877,0.0009703823,0.0003976448,0.0014060943,0.0025763242,0.17414874,0.40593132,0.01743392,0.008893201,0.36123496],"study_design_scores_gemma":[0.000037382968,0.00013357884,0.07758692,0.0000967933,0.00008044975,0.001638939,0.00033939304,0.8515003,0.0365098,0.023964465,0.007990313,0.000121794845],"about_ca_topic_score_codex":0.0029027397,"about_ca_topic_score_gemma":0.005379993,"teacher_disagreement_score":0.0029027397,"about_ca_system_score_codex":0.00040209366,"about_ca_system_score_gemma":0.0005549735,"threshold_uncertainty_score":0.0067566037},"labels":[],"label_agreement":null},{"id":"W4390194419","doi":"10.1002/alz.078896","title":"Amyloid and tau pathology are associated with white matter properties in cognitively unimpaired older adults at risk of AD dementia","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; Montreal Neurological Institute and Hospital; Université de Sherbrooke; Douglas College; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Psychology; Pathology; Neuropathology; Posterior cingulate; Medicine; Neuroscience; Magnetic resonance imaging; Cortex (anatomy); Disease","score_opus":0.03918809377620077,"score_gpt":0.27711028372746543,"score_spread":0.23792218995126466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996741,0.000053372918,0.000040434334,0.000013353145,0.0000015270895,0.0000020448322,0.00007776156,0.0000028119473,0.00013448633],"genre_scores_gemma":[0.99971944,0.000022359935,0.00006331693,0.0000069125763,0.0000043606724,0.0000022476122,0.00009468086,0.0000012275841,0.00008531339],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999811,0.000029858245,0.000033889075,0.000060547856,0.00003508341,0.000029732764],"domain_scores_gemma":[0.998184,0.0002681662,0.0010055259,0.00012267173,0.00018526572,0.00023429251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004513293,0.00055133743,0.00032190882,0.0014001649,0.00047795475,0.0006854505,0.00031228605,0.0007014561,0.0021126934],"category_scores_gemma":[0.0029862172,0.0003313497,0.00035498518,0.00079219596,0.00041219883,0.0004966032,0.00050965155,0.00048298435,0.0003290269],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024815966,0.000070065034,0.9972812,0.000008137199,0.00007551557,0.00011548687,0.0001304726,0.000083206665,0.0008585228,0.000019882056,0.000051603285,0.0010577618],"study_design_scores_gemma":[0.0000027357123,0.00005994292,0.99939716,0.000001921652,0.000014376562,0.00013889684,0.00006839386,0.00018994417,0.00006452469,0.00004187237,0.000018594614,0.0000017197099],"about_ca_topic_score_codex":0.004354753,"about_ca_topic_score_gemma":0.004703189,"teacher_disagreement_score":0.004354753,"about_ca_system_score_codex":0.0001807485,"about_ca_system_score_gemma":0.00016793545,"threshold_uncertainty_score":0.008658767},"labels":[],"label_agreement":null},{"id":"W4390194500","doi":"10.1002/alz.080381","title":"Subcortical deformation is uniquely related to cortical thickness among FTLD mutation carriers","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Putamen; Mutation; Grey matter; Frontotemporal lobar degeneration; Temporal lobe; Medicine; White matter; Magnetic resonance imaging; Anatomy; Pathology; Psychology; Neuroscience; Internal medicine; Biology; Frontotemporal dementia; Genetics; Dementia; Radiology; Epilepsy; Disease","score_opus":0.053309445814585944,"score_gpt":0.35127794575157967,"score_spread":0.2979684999369937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976057,0.000027770791,0.000037093934,0.000007065513,0.0000011726288,0.0000016133428,0.00006218259,0.0000022992524,0.000100212674],"genre_scores_gemma":[0.99979705,0.000011776368,0.000043038388,0.00000306329,0.0000021438302,0.0000022503302,0.00007650437,0.0000016396313,0.000062515945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997929,0.00003558817,0.000030591742,0.0000697345,0.00004269107,0.000028486807],"domain_scores_gemma":[0.99899894,0.00027151406,0.00044731025,0.00008833891,0.0000858822,0.00010803174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033938978,0.0005060635,0.00035849385,0.001208003,0.00042718792,0.00046317367,0.00024667697,0.0004917378,0.0031507502],"category_scores_gemma":[0.002587044,0.00019915066,0.00026510286,0.00065062393,0.0004414797,0.00031039442,0.0004079233,0.00027349993,0.00025911376],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041044632,0.000032049076,0.9922564,0.000009448704,0.00007280148,0.00073648756,0.00024091359,0.000091326925,0.0036584076,0.000039956038,0.000089561436,0.0023621854],"study_design_scores_gemma":[0.0000041736425,0.00006124713,0.99814534,0.000003049225,0.000018398388,0.0010819172,0.00010614636,0.00016886507,0.00030113474,0.00007041243,0.00003595081,0.0000034836262],"about_ca_topic_score_codex":0.0033991102,"about_ca_topic_score_gemma":0.003750805,"teacher_disagreement_score":0.0033991102,"about_ca_system_score_codex":0.00019175503,"about_ca_system_score_gemma":0.00013892475,"threshold_uncertainty_score":0.010540366},"labels":[],"label_agreement":null},{"id":"W4390194755","doi":"10.1002/alz.080772","title":"Antagonistic Amyloid‐β and tau interactions with T1‐weighted/T2‐weighted magnetic resonance ratio in Alzheimer’s disesase continuum","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Neurodegeneration; Psychology; Magnetic resonance imaging; Amyloid (mycology); Entorhinal cortex; Pittsburgh compound B; Alzheimer's disease; Neuroscience; Chemistry; Nuclear magnetic resonance; Internal medicine; Medicine; Pathology; Disease; Physics; Hippocampus","score_opus":0.047383722405745635,"score_gpt":0.3274654809087871,"score_spread":0.28008175850304146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991179,0.00020010129,0.0002869546,0.0000108154645,0.0000037095147,0.000005415631,0.00003961841,0.0000063991993,0.00032904497],"genre_scores_gemma":[0.9994293,0.000043044594,0.00025423974,0.0000066120847,0.0000055162745,0.0000048919046,0.000051739054,0.000003540247,0.00020116412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981517,0.000037993595,0.000030405923,0.00006025916,0.00003435599,0.000021943466],"domain_scores_gemma":[0.9994843,0.00012627001,0.00017355457,0.000057115427,0.00007082457,0.00008791552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059724425,0.0004322137,0.0002682229,0.0012774713,0.00034623858,0.000443259,0.00015238629,0.00031025033,0.0020209122],"category_scores_gemma":[0.00089604576,0.00020014223,0.00021807647,0.00051915017,0.00032186616,0.0002812607,0.0002909989,0.00025102208,0.00031552743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044523748,0.0005233868,0.8505517,0.00013300164,0.00044833892,0.002728781,0.0008853168,0.00032684955,0.12261152,0.00027538138,0.000278487,0.016784819],"study_design_scores_gemma":[0.000029368164,0.0003836394,0.98818666,0.0000059743334,0.00012216505,0.0032623624,0.00026759953,0.00055508653,0.006499817,0.00032021606,0.0003563347,0.000010635246],"about_ca_topic_score_codex":0.00048695857,"about_ca_topic_score_gemma":0.00044472804,"teacher_disagreement_score":0.0020209122,"about_ca_system_score_codex":0.00011210093,"about_ca_system_score_gemma":0.000077505356,"threshold_uncertainty_score":0.006760657},"labels":[],"label_agreement":null},{"id":"W4390194807","doi":"10.1002/alz.077371","title":"Voxel‐by‐Voxel regression analysis identifies association between postmortem TDP‐43 and antemortem fractional anisotropy within white matter fibers connected to the hippocampus","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Parahippocampal gyrus; Entorhinal cortex; Hippocampus; Fractional anisotropy; Voxel; Fornix; Pathology; Medicine; Grey matter; Neuroscience; Psychology; Magnetic resonance imaging; Temporal lobe; Radiology","score_opus":0.03679855996780896,"score_gpt":0.32985917308936996,"score_spread":0.293060613121561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99801826,0.000058838443,0.0016042226,0.00002125357,0.000004610209,0.0000032627522,0.00011394865,0.00004097925,0.00013452052],"genre_scores_gemma":[0.9988372,0.000019375695,0.0007821016,0.0000024090605,0.0000031862317,0.000002830552,0.0001232684,0.0000072507473,0.00022227896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978524,0.00006872949,0.0000137190245,0.00008223647,0.000023192963,0.000026798318],"domain_scores_gemma":[0.9985185,0.0008542096,0.0002958546,0.00010317504,0.000109463595,0.00011874468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084250944,0.0003252209,0.0003414036,0.00057036406,0.00018956642,0.00038950657,0.00030085692,0.00020450553,0.0023635847],"category_scores_gemma":[0.002782183,0.00016812049,0.0003437803,0.0002946002,0.0001999231,0.00021392915,0.00019566517,0.0003146896,0.0002538234],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020502473,0.00018131136,0.9480936,0.00005105039,0.00075851125,0.0006059759,0.00024675726,0.0030214442,0.021876838,0.00024730244,0.000756306,0.022110697],"study_design_scores_gemma":[0.000030433643,0.00033290745,0.9674109,0.000009601802,0.00018739764,0.0010425601,0.00018470886,0.027067807,0.0031365159,0.0002513773,0.00033219895,0.000013506508],"about_ca_topic_score_codex":0.0044106725,"about_ca_topic_score_gemma":0.0052620154,"teacher_disagreement_score":0.0044106725,"about_ca_system_score_codex":0.00013734403,"about_ca_system_score_gemma":0.00024801126,"threshold_uncertainty_score":0.008770049},"labels":[],"label_agreement":null},{"id":"W4390194918","doi":"10.1002/alz.080038","title":"White Matter Correlates of Speech in Cerebrovascular Disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Uncinate fasciculus; Hyperintensity; Diffusion MRI; Fasciculus; Psychology; Audiology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.04595456001111764,"score_gpt":0.3227140425372381,"score_spread":0.2767594825261205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974669,0.0006947272,0.00008467336,0.00007397014,0.0000068061645,0.0000071739287,0.00045410186,0.000007194078,0.0012044052],"genre_scores_gemma":[0.9991416,0.00019881387,0.00010921345,0.00001245895,0.00002156527,0.0000053757003,0.00026524917,0.000002574099,0.00024313347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972767,0.000048405385,0.000030424408,0.000098458586,0.00006169435,0.000033358127],"domain_scores_gemma":[0.99782026,0.00047603442,0.0010115776,0.00012948585,0.0004054625,0.00015716876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005130238,0.00034244178,0.00032459243,0.001602822,0.0005704233,0.0008417214,0.0002940707,0.00040163397,0.0031656688],"category_scores_gemma":[0.00308703,0.00013939143,0.0001489356,0.0011973702,0.0005112713,0.00030971543,0.00048519578,0.00033584237,0.00033347742],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004708238,0.00007239319,0.9808055,0.00011828932,0.00016092532,0.00093197916,0.0012802627,0.00022316331,0.0045940587,0.00016289882,0.00046164572,0.010718098],"study_design_scores_gemma":[0.0000022190266,0.00002745158,0.9987394,0.000010765254,0.000020069492,0.00028015062,0.0001869665,0.0001657547,0.00026058525,0.00016682928,0.00013507015,0.000004792046],"about_ca_topic_score_codex":0.014352057,"about_ca_topic_score_gemma":0.014705285,"teacher_disagreement_score":0.014352057,"about_ca_system_score_codex":0.00051328796,"about_ca_system_score_gemma":0.0004912302,"threshold_uncertainty_score":0.028537035},"labels":[],"label_agreement":null},{"id":"W4390196993","doi":"10.1002/alz.081758","title":"Voxel‐by‐Voxel regression analysis identifies association between postmortem TDP‐43 and antemortem fractional anisotropy within white matter fibers connected to the hippocampus","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Parahippocampal gyrus; Entorhinal cortex; Hippocampus; Voxel; Fractional anisotropy; Fornix; Pathology; Medicine; Neuroscience; Grey matter; Psychology; Magnetic resonance imaging; Temporal lobe; Radiology","score_opus":0.03679855996780896,"score_gpt":0.32985917308936996,"score_spread":0.293060613121561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390196993","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99796057,0.0000613462,0.001666926,0.000022250522,0.0000047578387,0.0000032545986,0.000110730354,0.000041756233,0.00012831563],"genre_scores_gemma":[0.9987973,0.000020289588,0.00081950775,0.0000025371623,0.0000033337494,0.0000028754755,0.00012301675,0.000007368795,0.00022375674],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978286,0.00007082317,0.0000135222535,0.00008299231,0.000023043405,0.00002689865],"domain_scores_gemma":[0.9985039,0.00085960777,0.00030325027,0.00010128939,0.00010956968,0.00012226481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008558228,0.00033310248,0.00034119273,0.0005760149,0.00019101614,0.00038678397,0.0003008655,0.0002093353,0.0023271856],"category_scores_gemma":[0.0028307133,0.00017072067,0.00034892128,0.00029651518,0.00020417062,0.0002187412,0.00019460704,0.00031710736,0.00025043424],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019696879,0.00018006182,0.94949573,0.000051077244,0.00076241704,0.00059700577,0.00023536774,0.0030329516,0.02059868,0.0002354569,0.00075839704,0.022083214],"study_design_scores_gemma":[0.0000315959,0.00034045416,0.9655678,0.000009946435,0.00019486707,0.001045565,0.0001893548,0.028879764,0.0031266306,0.0002625566,0.00033712323,0.000014268742],"about_ca_topic_score_codex":0.004384903,"about_ca_topic_score_gemma":0.0053297523,"teacher_disagreement_score":0.004384903,"about_ca_system_score_codex":0.00014015818,"about_ca_system_score_gemma":0.00024745008,"threshold_uncertainty_score":0.008718789},"labels":[],"label_agreement":null},{"id":"W4390197002","doi":"10.1002/alz.081960","title":"White Matter Correlates of Speech in Cerebrovascular Disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Western University; Robarts Clinical Trials","funders":"","keywords":"Fractional anisotropy; White matter; Uncinate fasciculus; Hyperintensity; Diffusion MRI; Fasciculus; Psychology; Audiology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.04595456001111764,"score_gpt":0.3227140425372381,"score_spread":0.2767594825261205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99731654,0.0007505912,0.00008994824,0.00007623724,0.000007223391,0.0000074525587,0.00047961526,0.000007253669,0.0012651607],"genre_scores_gemma":[0.99908924,0.00021378248,0.00011314685,0.000012637422,0.000021955111,0.0000055575415,0.00027613898,0.0000025955133,0.00026483389],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972457,0.000048442642,0.000030622283,0.00010088749,0.000062342566,0.00003318611],"domain_scores_gemma":[0.997881,0.00045912323,0.0009852939,0.00012610762,0.00040114505,0.00014734732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051149406,0.00034354,0.00031754785,0.0016136419,0.000578769,0.00086126785,0.0002931237,0.00039736668,0.003178562],"category_scores_gemma":[0.003038826,0.00013955875,0.00015212511,0.0012042444,0.0004968605,0.00031260776,0.00048479086,0.00033054705,0.00033822164],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004539722,0.00007148918,0.9803468,0.00012007608,0.00016455933,0.0009033655,0.0013156248,0.00022208212,0.0045181024,0.00017272892,0.00047529282,0.0112358825],"study_design_scores_gemma":[0.0000021806802,0.00002696485,0.9987055,0.000011421502,0.000020776815,0.00028302302,0.00019702758,0.0001686689,0.0002612353,0.00017614575,0.00014220236,0.0000048467414],"about_ca_topic_score_codex":0.014547871,"about_ca_topic_score_gemma":0.014792543,"teacher_disagreement_score":0.014547871,"about_ca_system_score_codex":0.00051382935,"about_ca_system_score_gemma":0.0004912695,"threshold_uncertainty_score":0.028926432},"labels":[],"label_agreement":null},{"id":"W4390197039","doi":"10.1002/alz.081879","title":"In vivo data‐driven patterns of Tau accumulation associated with AD progression using 18F‐MK‐6240 PET","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Standardized uptake value; Temporal lobe; Dementia; Positron emission tomography; Neuroscience; Cognitive impairment; Partial volume; Pathology; Alzheimer's disease; Psychology; Nuclear medicine; Medicine; Cognition; Disease","score_opus":0.19230463758943447,"score_gpt":0.431125597920623,"score_spread":0.23882096033118852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9821323,0.00038649197,0.015535298,0.000029523733,0.000007453003,0.000037753438,0.001278234,0.00016586453,0.00042709257],"genre_scores_gemma":[0.98352414,0.0002357507,0.0137577625,0.00002789581,0.000006673328,0.00010037509,0.0017218718,0.00009197751,0.0005336356],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998086,0.00005100934,0.0000131935885,0.00006969583,0.00003185599,0.000025598278],"domain_scores_gemma":[0.9997136,0.00009364304,0.00007598517,0.000038620903,0.000059321053,0.000018772686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005897218,0.000321645,0.00040318357,0.0006283353,0.00017511095,0.0006295602,0.0002067317,0.00038800674,0.00063113816],"category_scores_gemma":[0.0011981108,0.0003443497,0.00030526452,0.0005234942,0.00024581063,0.00020465048,0.00017812398,0.00025901277,0.00021447979],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016040457,0.00016762059,0.049023073,0.0002975035,0.00023627565,0.0003316028,0.00029301376,0.010393394,0.9036455,0.00029001824,0.000612929,0.033105046],"study_design_scores_gemma":[0.000080483645,0.00096017454,0.5669855,0.000040741994,0.00034557682,0.0031947023,0.0002526739,0.10106692,0.32219613,0.0015880683,0.0031599654,0.00012913176],"about_ca_topic_score_codex":0.0019302756,"about_ca_topic_score_gemma":0.0023305803,"teacher_disagreement_score":0.0019302756,"about_ca_system_score_codex":0.00029679463,"about_ca_system_score_gemma":0.0002840263,"threshold_uncertainty_score":0.003838122},"labels":[],"label_agreement":null},{"id":"W4390197060","doi":"10.1002/alz.081853","title":"Amyloid and tau pathology are associated with white matter properties in cognitively unimpaired older adults at risk of AD dementia","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; Université de Sherbrooke; McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Psychology; Pathology; Fascicle; Posterior cingulate; Medicine; Neuroscience; Magnetic resonance imaging; Cortex (anatomy); Disease; Anatomy","score_opus":0.03918809377620077,"score_gpt":0.27711028372746543,"score_spread":0.23792218995126466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996605,0.00005157306,0.0000412847,0.000013914764,0.0000015135962,0.0000019947468,0.000089204295,0.0000028585964,0.00013715801],"genre_scores_gemma":[0.999708,0.00002254042,0.000065511,0.0000070479737,0.0000043856076,0.000002397758,0.00010043511,0.0000011596426,0.00008852495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981993,0.00002859722,0.000032103177,0.00005717287,0.00003423377,0.000028010529],"domain_scores_gemma":[0.9983321,0.0002647614,0.00090794364,0.00011603206,0.00016518081,0.00021398666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043202052,0.00054713886,0.00030996208,0.0013534274,0.00046315556,0.0006678919,0.0002992207,0.0006864174,0.0022476963],"category_scores_gemma":[0.0027965766,0.00032189072,0.00035588583,0.0007881532,0.00040476152,0.00047402552,0.00049707276,0.0004917181,0.00033736328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026345658,0.000075265714,0.99717927,0.000008778101,0.00007925072,0.000118451935,0.00013528565,0.000088973386,0.0008872533,0.00002212447,0.000056723562,0.001085193],"study_design_scores_gemma":[0.0000028366965,0.00005977366,0.99935716,0.0000020377045,0.000015793119,0.00014028103,0.00007144446,0.00021663922,0.00006805592,0.000043720378,0.000020401185,0.0000017617716],"about_ca_topic_score_codex":0.0041912654,"about_ca_topic_score_gemma":0.0044937893,"teacher_disagreement_score":0.0041912654,"about_ca_system_score_codex":0.00017650363,"about_ca_system_score_gemma":0.00016152239,"threshold_uncertainty_score":0.008333743},"labels":[],"label_agreement":null},{"id":"W4390198288","doi":"10.1002/alz.081611","title":"Predicting cognitive decline in a low‐dimensional representation of brain morphology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Cognitive decline; Cognition; Representation (politics); Embedding; Neurodegeneration; Psychology; Nonlinear dimensionality reduction; Projection (relational algebra); Artificial intelligence; Pattern recognition (psychology); Cognitive psychology; Computer science; Dimensionality reduction; Neuroscience; Medicine; Dementia; Disease; Algorithm; Pathology","score_opus":0.0828630327894677,"score_gpt":0.3936465999757778,"score_spread":0.31078356718631006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9669251,0.00007156796,0.032219715,0.000053357428,0.000006585236,0.000023335513,0.00029133627,0.00012463963,0.0002843181],"genre_scores_gemma":[0.99035853,0.00003228595,0.009103288,0.0000039206093,0.0000041992575,0.0000151167715,0.00034988442,0.0000067883034,0.00012592897],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999762,0.000082054525,0.000017103192,0.00007118056,0.000038459613,0.00002907919],"domain_scores_gemma":[0.99903643,0.00046112304,0.00016015225,0.000108692024,0.00017697661,0.000056630757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006581841,0.00039561215,0.00025631124,0.0014030929,0.00017905358,0.00066027156,0.00020461575,0.00027317184,0.0011232258],"category_scores_gemma":[0.0030665451,0.00011135825,0.00032134156,0.0006367672,0.00023098612,0.00045702935,0.00047088767,0.00029693387,0.00024221113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009956453,0.00039614044,0.5628931,0.00016670002,0.00036213343,0.0003242571,0.0009158024,0.15026811,0.03483644,0.0021568688,0.002185784,0.24449909],"study_design_scores_gemma":[0.000011596044,0.0002159725,0.35628963,0.00001906004,0.00003652981,0.00022339674,0.00025837505,0.6364094,0.003530536,0.0023473918,0.0006306265,0.000027427486],"about_ca_topic_score_codex":0.0034230326,"about_ca_topic_score_gemma":0.0026166518,"teacher_disagreement_score":0.0034230326,"about_ca_system_score_codex":0.00038111166,"about_ca_system_score_gemma":0.00025284808,"threshold_uncertainty_score":0.006806195},"labels":[],"label_agreement":null},{"id":"W4390198417","doi":"10.1002/alz.081613","title":"Synthetic FDG‐PET hypometabolism sensitivity validation in AD","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Precuneus; Nuclear medicine; Positron emission tomography; Standardized uptake value; Posterior cingulate; Medicine; Pet imaging; Fluorodeoxyglucose; Radiology; Functional magnetic resonance imaging","score_opus":0.0779369262783936,"score_gpt":0.3501547217909986,"score_spread":0.272217795512605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.945578,0.0021079828,0.04805868,0.00012040668,0.000059244463,0.00017253596,0.001830355,0.00071641133,0.0013563591],"genre_scores_gemma":[0.9831661,0.00018733378,0.014479816,0.00006203429,0.000016644808,0.00008256615,0.0017503434,0.000055395085,0.00019972333],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991435,0.00038614066,0.000085828964,0.00022713986,0.00011155331,0.00004578051],"domain_scores_gemma":[0.99847656,0.0007681286,0.000176869,0.00027252932,0.00026239775,0.000043443266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033263476,0.00069308275,0.00051527744,0.0008854109,0.00021795489,0.0010574472,0.0007080005,0.0006206524,0.001210472],"category_scores_gemma":[0.008427541,0.00032277635,0.0005548222,0.00042228296,0.0005778075,0.00035745575,0.00054365775,0.00031468808,0.00029194454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008161281,0.000660319,0.2639769,0.0023372497,0.0036673597,0.0016021096,0.00065003085,0.19797693,0.18914065,0.0028543645,0.004458435,0.32451436],"study_design_scores_gemma":[0.00037473967,0.0018608619,0.25219983,0.00025191653,0.001323451,0.009952519,0.0003116125,0.56750274,0.14927444,0.0084501095,0.008334441,0.00016341606],"about_ca_topic_score_codex":0.0012367254,"about_ca_topic_score_gemma":0.0012721089,"teacher_disagreement_score":0.0033263476,"about_ca_system_score_codex":0.0004681366,"about_ca_system_score_gemma":0.00024489596,"threshold_uncertainty_score":0.017591596},"labels":[],"label_agreement":null},{"id":"W4390198436","doi":"10.1002/alz.081953","title":"Multivariate white matter differences links to cognition in individuals with family history of Alzheimer’s disease and APOE4 genetic risk","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; McGill Genome Centre; Montreal Neurological Institute and Hospital; Concordia University","funders":"","keywords":"Multivariate statistics; Mahalanobis distance; Univariate; Splenium; Psychology; Neuropsychology; Corpus callosum; Multivariate analysis; Voxel; Cognition; White matter; Medicine; Artificial intelligence; Statistics; Magnetic resonance imaging; Internal medicine; Computer science; Psychiatry; Mathematics; Neuroscience","score_opus":0.06582336743214791,"score_gpt":0.31374557819658794,"score_spread":0.24792221076444004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99905604,0.00009972082,0.00025283647,0.000031739255,0.0000028599347,0.0000013863626,0.00036610535,0.000010582622,0.00017875915],"genre_scores_gemma":[0.9994392,0.00002249747,0.00017760332,0.000004464781,0.0000057553298,0.0000019108134,0.0002497453,0.0000041051658,0.00009476008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971646,0.00006535904,0.00003194791,0.00011197017,0.000037924397,0.00003635725],"domain_scores_gemma":[0.9983182,0.00058536656,0.00064787036,0.0002090413,0.0001030513,0.0001364535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059933646,0.00046237872,0.00034297205,0.0014596316,0.00036207505,0.00054460607,0.00027151266,0.00036714214,0.0037304887],"category_scores_gemma":[0.002555921,0.00018369556,0.0006206506,0.0012518854,0.0002898509,0.00028813328,0.00041649071,0.00037264603,0.00021228007],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005315943,0.00004193063,0.9919442,0.000017250426,0.0005123644,0.00020790778,0.00010749208,0.00041716566,0.0018444377,0.00007766954,0.00018207861,0.0041160034],"study_design_scores_gemma":[0.000004104334,0.000030660427,0.99839276,0.0000027467515,0.000060212013,0.00020791467,0.00005724168,0.0007915769,0.00021346788,0.00015913392,0.00007584816,0.000004279918],"about_ca_topic_score_codex":0.00902964,"about_ca_topic_score_gemma":0.008032633,"teacher_disagreement_score":0.00902964,"about_ca_system_score_codex":0.0002208408,"about_ca_system_score_gemma":0.00019895668,"threshold_uncertainty_score":0.017954111},"labels":[],"label_agreement":null},{"id":"W4390198688","doi":"10.1002/alz.082001","title":"Subcortical deformation is uniquely related to cortical thickness among FTLD mutation carriers","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Putamen; Mutation; Grey matter; Frontotemporal lobar degeneration; Temporal lobe; Medicine; White matter; Magnetic resonance imaging; Pathology; Anatomy; Internal medicine; Psychology; Neuroscience; Frontotemporal dementia; Biology; Dementia; Genetics; Radiology; Epilepsy; Gene","score_opus":0.053309445814585944,"score_gpt":0.35127794575157967,"score_spread":0.2979684999369937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99976057,0.000027770791,0.000037093934,0.000007065513,0.0000011726288,0.0000016133428,0.00006218259,0.0000022992524,0.000100212674],"genre_scores_gemma":[0.99979705,0.000011776368,0.000043038388,0.00000306329,0.0000021438302,0.0000022503302,0.00007650437,0.0000016396313,0.000062515945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997929,0.00003558817,0.000030591742,0.0000697345,0.00004269107,0.000028486807],"domain_scores_gemma":[0.99899894,0.00027151406,0.00044731025,0.00008833891,0.0000858822,0.00010803174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033938978,0.0005060635,0.00035849385,0.001208003,0.00042718792,0.00046317367,0.00024667697,0.0004917378,0.0031507502],"category_scores_gemma":[0.002587044,0.00019915066,0.00026510286,0.00065062393,0.0004414797,0.00031039442,0.0004079233,0.00027349993,0.00025911376],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041044632,0.000032049076,0.9922564,0.000009448704,0.00007280148,0.00073648756,0.00024091359,0.000091326925,0.0036584076,0.000039956038,0.000089561436,0.0023621854],"study_design_scores_gemma":[0.0000041736425,0.00006124713,0.99814534,0.000003049225,0.000018398388,0.0010819172,0.00010614636,0.00016886507,0.00030113474,0.00007041243,0.00003595081,0.0000034836262],"about_ca_topic_score_codex":0.0033991102,"about_ca_topic_score_gemma":0.003750805,"teacher_disagreement_score":0.0033991102,"about_ca_system_score_codex":0.00019175503,"about_ca_system_score_gemma":0.00013892475,"threshold_uncertainty_score":0.010540366},"labels":[],"label_agreement":null},{"id":"W4390199074","doi":"10.1002/alz.074136","title":"Impact of White Matter Hyperintensity Changes on Cognition One Year After Mild Ischemic Stroke","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Diffusion MRI; Fractional anisotropy; Montreal Cognitive Assessment; Medicine; White matter; Cardiology; Stroke (engine); Cognitive decline; Internal medicine; Cognition; Dementia; Brain size; Physical therapy; Magnetic resonance imaging; Disease; Psychiatry; Radiology","score_opus":0.07915447804355537,"score_gpt":0.3430500800400003,"score_spread":0.26389560199644496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993136,0.00017690573,0.000023466784,0.000036611396,0.0000061750397,0.000004430391,0.000281047,0.00000366177,0.00015417473],"genre_scores_gemma":[0.99939,0.00004601985,0.000029208595,0.00001005244,0.000010189781,0.000004312617,0.00032590833,9.2165345e-7,0.00018325161],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995485,0.00011264846,0.00003347946,0.000121314086,0.00006863646,0.000115449795],"domain_scores_gemma":[0.9980641,0.00040730851,0.000744725,0.0001371298,0.00016707892,0.0004796796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000871181,0.00051015994,0.0005104469,0.0006126276,0.0004978108,0.00074513303,0.0004534679,0.0007012108,0.001541598],"category_scores_gemma":[0.002901724,0.0002464325,0.0008489362,0.0004778921,0.00033851116,0.0005011046,0.00046785668,0.00088208215,0.0002152983],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020953668,0.00039293923,0.9933697,0.000022063332,0.00037142364,0.000096716336,0.000071934985,0.0002171364,0.0003753189,0.000017820243,0.00012952695,0.0028401595],"study_design_scores_gemma":[0.000005085766,0.0002128178,0.9995159,0.0000015619994,0.000039429182,0.000024675162,0.000018330116,0.00009568256,0.00005095824,0.000012834567,0.000019941035,0.000002870905],"about_ca_topic_score_codex":0.013155697,"about_ca_topic_score_gemma":0.01580775,"teacher_disagreement_score":0.013155697,"about_ca_system_score_codex":0.0005739409,"about_ca_system_score_gemma":0.00051058654,"threshold_uncertainty_score":0.026158273},"labels":[],"label_agreement":null},{"id":"W4390199449","doi":"10.1002/alz.073422","title":"Synthetic FDG‐PET hypometabolism sensitivity validation in AD","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Precuneus; Nuclear medicine; Positron emission tomography; Standardized uptake value; Posterior cingulate; Medicine; Pet imaging; Fluorodeoxyglucose; Radiology; Functional magnetic resonance imaging","score_opus":0.0779369262783936,"score_gpt":0.3501547217909986,"score_spread":0.272217795512605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.945578,0.0021079828,0.04805868,0.00012040668,0.000059244463,0.00017253596,0.001830355,0.00071641133,0.0013563591],"genre_scores_gemma":[0.9831661,0.00018733378,0.014479816,0.00006203429,0.000016644808,0.00008256615,0.0017503434,0.000055395085,0.00019972333],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991435,0.00038614066,0.000085828964,0.00022713986,0.00011155331,0.00004578051],"domain_scores_gemma":[0.99847656,0.0007681286,0.000176869,0.00027252932,0.00026239775,0.000043443266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033263476,0.00069308275,0.00051527744,0.0008854109,0.00021795489,0.0010574472,0.0007080005,0.0006206524,0.001210472],"category_scores_gemma":[0.008427541,0.00032277635,0.0005548222,0.00042228296,0.0005778075,0.00035745575,0.00054365775,0.00031468808,0.00029194454],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008161281,0.000660319,0.2639769,0.0023372497,0.0036673597,0.0016021096,0.00065003085,0.19797693,0.18914065,0.0028543645,0.004458435,0.32451436],"study_design_scores_gemma":[0.00037473967,0.0018608619,0.25219983,0.00025191653,0.001323451,0.009952519,0.0003116125,0.56750274,0.14927444,0.0084501095,0.008334441,0.00016341606],"about_ca_topic_score_codex":0.0012367254,"about_ca_topic_score_gemma":0.0012721089,"teacher_disagreement_score":0.0033263476,"about_ca_system_score_codex":0.0004681366,"about_ca_system_score_gemma":0.00024489596,"threshold_uncertainty_score":0.017591596},"labels":[],"label_agreement":null},{"id":"W4390199460","doi":"10.1002/alz.076693","title":"Blood‐based markers of neurodegeneration linked with brain atrophy and cognition in aging","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Atrophy; Neurodegeneration; Neuropsychology; Psychology; Montreal Cognitive Assessment; Glial fibrillary acidic protein; Cognitive decline; Brain size; Magnetic resonance imaging; Audiology; Cognition; Neuropsychological assessment; Pathology; Medicine; Neuroscience; Internal medicine; Cognitive impairment; Dementia; Immunohistochemistry; Disease; Radiology","score_opus":0.049504536565580834,"score_gpt":0.3160257329354967,"score_spread":0.26652119636991584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99769706,0.0010853491,0.00040222294,0.000020036981,0.0000057387156,0.0000067485366,0.00034760166,0.00001727011,0.0004179331],"genre_scores_gemma":[0.9987419,0.00017977813,0.0005095939,0.000024099902,0.000010991214,0.000010014212,0.00020787831,0.0000019146519,0.00031386383],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998969,0.000024236855,0.000009788653,0.00003460936,0.000022202206,0.000012337759],"domain_scores_gemma":[0.9995384,0.00008371182,0.00022068845,0.000026405833,0.00007535612,0.000055561683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032005925,0.00030453663,0.00025115206,0.0007282738,0.0001372927,0.00029130312,0.000120545796,0.00028991557,0.0009983183],"category_scores_gemma":[0.0006846729,0.00011019995,0.00011151997,0.0005120319,0.00015168883,0.00020145641,0.00015860505,0.00023146629,0.00015002654],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088786404,0.000120389544,0.96274734,0.000049102488,0.00016956772,0.000106461266,0.00008556949,0.00015889782,0.027544705,0.00003164248,0.0001456929,0.00795284],"study_design_scores_gemma":[0.0000050641897,0.00019935718,0.99674857,0.000003420764,0.000033186643,0.00019495575,0.000025758454,0.00025481253,0.0023571297,0.0000642389,0.0001108862,0.0000026216403],"about_ca_topic_score_codex":0.0009735846,"about_ca_topic_score_gemma":0.0009734311,"teacher_disagreement_score":0.0009983183,"about_ca_system_score_codex":0.00012454382,"about_ca_system_score_gemma":0.000078562305,"threshold_uncertainty_score":0.0033397079},"labels":[],"label_agreement":null},{"id":"W4390199920","doi":"10.1002/alz.079169","title":"In vivo data‐driven patterns of Tau accumulation associated with AD progression using <sup>18</sup>F‐MK‐6240 PET","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Standardized uptake value; Temporal lobe; Dementia; Positron emission tomography; Cognitive impairment; Partial volume; Neuroscience; Pathology; Nuclear medicine; Alzheimer's disease; Psychology; Medicine; Cognition; Disease","score_opus":0.1895984076868383,"score_gpt":0.42421744955521273,"score_spread":0.23461904186837443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98229194,0.00031181937,0.015346861,0.000033435073,0.0000065935965,0.000030002837,0.001326615,0.00018840253,0.00046426096],"genre_scores_gemma":[0.9832593,0.0002249001,0.013884875,0.00002886311,0.0000065289846,0.000074136675,0.0018266796,0.000106215935,0.000588396],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99984276,0.00004244377,0.000010649041,0.000055525146,0.000025560268,0.000023136437],"domain_scores_gemma":[0.99975175,0.00007842523,0.00006808843,0.000033574073,0.00005120021,0.000016911465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005473118,0.00032534276,0.00035654873,0.0005737041,0.0001675492,0.0005980791,0.000223335,0.00038610425,0.00074089103],"category_scores_gemma":[0.0009514264,0.0003331447,0.00029183767,0.00047997708,0.0002520478,0.00020147082,0.00018720387,0.00023799897,0.00023361981],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014790858,0.00012638055,0.033968374,0.00029037616,0.00019974819,0.00033085854,0.00025484693,0.012449474,0.91885364,0.00028080228,0.0006558576,0.031110555],"study_design_scores_gemma":[0.00007751462,0.00089199346,0.5316408,0.000043358406,0.00035200603,0.0035606315,0.0002629483,0.11051814,0.34763518,0.001511467,0.003367305,0.00013857921],"about_ca_topic_score_codex":0.0023148672,"about_ca_topic_score_gemma":0.002791597,"teacher_disagreement_score":0.0023148672,"about_ca_system_score_codex":0.00028664357,"about_ca_system_score_gemma":0.000268742,"threshold_uncertainty_score":0.00460279},"labels":[],"label_agreement":null},{"id":"W4390199949","doi":"10.1002/alz.073341","title":"Predicting cognitive decline in a low‐dimensional representation of brain morphology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Cognitive decline; Representation (politics); Embedding; Cognition; Neurodegeneration; Psychology; Projection (relational algebra); Nonlinear dimensionality reduction; Artificial intelligence; Pattern recognition (psychology); Cognitive psychology; Computer science; Dimensionality reduction; Neuroscience; Medicine; Dementia; Disease; Algorithm; Pathology","score_opus":0.0828630327894677,"score_gpt":0.3936465999757778,"score_spread":0.31078356718631006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9657178,0.00007544867,0.03339094,0.00005607243,0.000006845825,0.000024060744,0.00030499793,0.00013009882,0.0002937442],"genre_scores_gemma":[0.99008524,0.00003378101,0.009360961,0.0000041017106,0.0000043306504,0.000015364958,0.00035940483,0.0000069151342,0.00012977637],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99976104,0.00008207081,0.00001730861,0.00007168187,0.000038790728,0.000029151857],"domain_scores_gemma":[0.9990337,0.00045879342,0.00016274197,0.00011001291,0.00017794892,0.000056971818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006603263,0.00039999766,0.0002569202,0.001426408,0.00017977446,0.0006637546,0.00020674098,0.00027319815,0.0011231749],"category_scores_gemma":[0.0030949719,0.00011156838,0.00032815288,0.00064450974,0.00023288147,0.00045985568,0.000476324,0.00030139464,0.00024472628],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009701092,0.00039431424,0.561354,0.000167258,0.0003661297,0.00032536715,0.00091361447,0.15226339,0.03370751,0.0022033183,0.0022261413,0.2451089],"study_design_scores_gemma":[0.000011506861,0.00021448181,0.34924808,0.00001954596,0.00003683284,0.00022206457,0.0002580223,0.6434241,0.0034589195,0.0024279673,0.00065096153,0.000027596758],"about_ca_topic_score_codex":0.003489574,"about_ca_topic_score_gemma":0.0026609926,"teacher_disagreement_score":0.003489574,"about_ca_system_score_codex":0.00038517636,"about_ca_system_score_gemma":0.00025711182,"threshold_uncertainty_score":0.006938517},"labels":[],"label_agreement":null},{"id":"W4390201829","doi":"10.1002/alz.082484","title":"DTI changes of thalamic subregions in genetic frontotemporal dementia: findings from the GENFI cohort","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Western University; Sunnybrook Health Science Centre; Toronto Western Hospital; Université Laval","funders":"","keywords":"C9orf72; Fractional anisotropy; Frontotemporal dementia; Diffusion MRI; Thalamus; Neuroscience; Psychology; Internal medicine; Medicine; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.08735111776774905,"score_gpt":0.3351516772999296,"score_spread":0.24780055953218055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390201829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989467,0.00008256921,0.00008047946,0.000016526665,0.000002293261,0.0000027706521,0.00065270957,0.0000055866217,0.00021046535],"genre_scores_gemma":[0.9987583,0.00004210275,0.00016475376,0.000014003642,0.0000038485637,0.000005941668,0.00085924024,0.000005127522,0.0001466557],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979633,0.000025174273,0.000017380115,0.000091785296,0.00004532761,0.000024061215],"domain_scores_gemma":[0.9995511,0.0000538712,0.00017959857,0.00008772691,0.00006015805,0.00006746595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005147603,0.0003862392,0.00028124114,0.0009134106,0.00045627457,0.0005497715,0.00039922906,0.00043444015,0.0013360338],"category_scores_gemma":[0.0014105237,0.00019833315,0.00043509543,0.0005686637,0.00032175204,0.00019205235,0.00038761192,0.0003562061,0.00023198882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037641881,0.000023133643,0.98992926,0.000016054371,0.00020063783,0.0006552883,0.00044241914,0.00010823331,0.004312662,0.000053823765,0.0003953743,0.003486721],"study_design_scores_gemma":[0.0000036482545,0.000030275323,0.99874914,0.000003502468,0.00004460288,0.0006876485,0.000097867225,0.00008053748,0.00015442364,0.000021346312,0.00012370704,0.0000033785175],"about_ca_topic_score_codex":0.020500353,"about_ca_topic_score_gemma":0.03405107,"teacher_disagreement_score":0.020500353,"about_ca_system_score_codex":0.00047026892,"about_ca_system_score_gemma":0.0002583764,"threshold_uncertainty_score":0.040762067},"labels":[],"label_agreement":null},{"id":"W4390263399","doi":"10.1523/eneuro.0363-23.2023","title":"Dissection of the Temporofrontal Extreme Capsule Fasciculus Using Diffusion MRI Tractography and Association with Lexical Retrieval","year":2023,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Alzheimer's Society; Alzheimer Society Research Program; Courtois Foundation; Government of Canada","keywords":"Arcuate fasciculus; Tractography; Diffusion MRI; Neuroscience; Uncinate fasciculus; White matter; Fasciculus; Anatomy; Psychology; Magnetic resonance imaging; Medicine; Fractional anisotropy; Radiology","score_opus":0.06248257841336648,"score_gpt":0.3156608470315914,"score_spread":0.25317826861822496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390263399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8860056,0.0012452147,0.1079398,0.00021599083,0.000032221218,0.00022342766,0.00051314826,0.0001517921,0.0036728175],"genre_scores_gemma":[0.9392763,0.00111162,0.05577888,0.00005572589,0.000015273612,0.0002555273,0.00043686497,0.0000791641,0.0029906237],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99985397,0.000019078358,0.00001406031,0.00005006184,0.00003334567,0.00002940459],"domain_scores_gemma":[0.99975115,0.000051926283,0.00010570336,0.000031945365,0.00003344629,0.000025784777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004216965,0.0004121185,0.00018145962,0.00083287666,0.00029436915,0.000381235,0.00017274014,0.00034802695,0.0009157158],"category_scores_gemma":[0.00078903395,0.00023242783,0.00018747413,0.00029109017,0.00069698546,0.0004052248,0.0003504498,0.0004249881,0.00022539764],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004944152,0.000065954155,0.009435832,0.00013856293,0.00006003665,0.0011235636,0.0003056211,0.0010580012,0.9598691,0.0019253282,0.00017337507,0.025350131],"study_design_scores_gemma":[0.00011345097,0.001269279,0.27147827,0.00014980757,0.00017550882,0.014263648,0.00051449746,0.021220969,0.67604893,0.0051578144,0.0095012905,0.000106504274],"about_ca_topic_score_codex":0.0046760645,"about_ca_topic_score_gemma":0.011211876,"teacher_disagreement_score":0.0046760645,"about_ca_system_score_codex":0.00039718224,"about_ca_system_score_gemma":0.0007198753,"threshold_uncertainty_score":0.009297729},"labels":[],"label_agreement":null},{"id":"W4390404629","doi":"10.1002/mrm.29975","title":"Tensor‐valued diffusion <scp>MRI</scp> of human acute stroke","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Canada Research Chairs; Medical College of Wisconsin; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Anisotropy; Diffusion; Isotropy; Monte Carlo method; Nuclear magnetic resonance; Chemistry; Physics; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Statistics; Optics; Quantum mechanics","score_opus":0.05297050507675024,"score_gpt":0.36571458095207504,"score_spread":0.3127440758753248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390404629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9746261,0.0008717182,0.022383345,0.00019402262,0.00001201456,0.000060012444,0.000412232,0.00012711616,0.001313462],"genre_scores_gemma":[0.9939469,0.00037536098,0.0049782195,0.000028585317,0.000009717153,0.000031955376,0.0002562226,0.000019355743,0.0003536391],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999629,0.000014152951,0.0000040380864,0.0000064558717,0.0000074723916,0.0000049594382],"domain_scores_gemma":[0.9997999,0.00006411038,0.00005221027,0.00003438828,0.000032863634,0.000016501737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026002846,0.0001946206,0.0001314751,0.0003140964,0.00012571468,0.00033517752,0.00011620122,0.00024217948,0.0012612429],"category_scores_gemma":[0.001162345,0.00013822877,0.00012858158,0.00021829034,0.00021421553,0.00027993674,0.0001248469,0.00013739211,0.00023799649],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003215927,0.00024156191,0.06450415,0.0008193057,0.00021233277,0.0033931925,0.0005829951,0.07468257,0.69611454,0.0040795347,0.0040157284,0.14813817],"study_design_scores_gemma":[0.00019349673,0.0017862034,0.37202305,0.00012398625,0.00017590173,0.011491577,0.00034106468,0.34108886,0.25302643,0.014527618,0.0051031667,0.00011865766],"about_ca_topic_score_codex":0.00189939,"about_ca_topic_score_gemma":0.0020983797,"teacher_disagreement_score":0.00189939,"about_ca_system_score_codex":0.00018951167,"about_ca_system_score_gemma":0.0002454879,"threshold_uncertainty_score":0.004219234},"labels":[],"label_agreement":null},{"id":"W4390426154","doi":"10.21037/qims-23-847","title":"U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities","year":2023,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Nanjing University; Nanjing University of Science and Technology; National Natural Science Foundation of China","keywords":"Neuroimaging; Hyperintensity; White matter; Diffusion MRI; Fiber; Medicine; Internal medicine; Psychology; Pathology; Neuroscience; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.13741435567307747,"score_gpt":0.40989301879934814,"score_spread":0.27247866312627067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390426154","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017592285,0.00028935925,0.9698527,0.00009259827,0.000032203807,0.00015892532,0.0008688153,0.010659144,0.00045390986],"genre_scores_gemma":[0.06847222,0.00022302078,0.9284734,0.000058796904,0.000027328528,0.00043506146,0.00086763414,0.00076126045,0.00068124675],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951184,0.00013917612,0.00005842211,0.00014945208,0.00010656786,0.00003468645],"domain_scores_gemma":[0.9984389,0.0006545165,0.00030206563,0.00016689286,0.00033031992,0.00010738543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020991086,0.0015026231,0.0007727245,0.0039280737,0.0007678673,0.0012654008,0.0010835083,0.0009381831,0.0055326824],"category_scores_gemma":[0.005115175,0.00064353074,0.0012478681,0.0012586166,0.0005620051,0.0011723991,0.0017165851,0.0008212963,0.0016778967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086194224,0.00023813883,0.022714159,0.00066733785,0.0006133031,0.00046712373,0.000593807,0.054006673,0.066297494,0.005658214,0.01579967,0.83208215],"study_design_scores_gemma":[0.00009983259,0.00014198943,0.016015735,0.00007722268,0.00009293244,0.0006348527,0.00012803328,0.94417727,0.02349821,0.0072549116,0.0077546076,0.00012434609],"about_ca_topic_score_codex":0.005186558,"about_ca_topic_score_gemma":0.007804127,"teacher_disagreement_score":0.0055326824,"about_ca_system_score_codex":0.0005349462,"about_ca_system_score_gemma":0.0015674641,"threshold_uncertainty_score":0.018508673},"labels":[],"label_agreement":null},{"id":"W4390489205","doi":"10.1109/sipaim56729.2023.10373434","title":"White Matter Bundles Linked to Cognitive Impairment in Alzheimer’s Patients and Intermediate Stages","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Cognitive impairment; Cognition; Psychology; Computer science; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.06008979235118269,"score_gpt":0.36432095769088163,"score_spread":0.30423116533969896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390489205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99914336,0.00021718112,0.00016090459,0.000010692486,0.0000020165255,0.0000049567016,0.00006723269,0.000004132515,0.00038961347],"genre_scores_gemma":[0.9994104,0.0000841855,0.00020640869,0.0000048073903,0.0000050556023,0.0000032597436,0.00012316942,0.0000016918649,0.00016109609],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998635,0.000021027943,0.000020164873,0.000037380694,0.000026096626,0.000031820575],"domain_scores_gemma":[0.9992519,0.00010573303,0.00037106563,0.00004088881,0.000068046415,0.00016239467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044724296,0.00036471765,0.00022202417,0.0019404783,0.00030465366,0.00046075345,0.00013821824,0.00029528321,0.0010896439],"category_scores_gemma":[0.0012480166,0.00017802195,0.00026331237,0.0007151077,0.00029700945,0.0004215315,0.00046084524,0.0002383778,0.0001793832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096308155,0.0000582568,0.985288,0.000032600474,0.00012506076,0.00050930784,0.00055675185,0.00014687749,0.0049795695,0.00009051344,0.000075849355,0.0071741166],"study_design_scores_gemma":[0.000003917681,0.00008579976,0.99874926,0.0000039876036,0.000020812848,0.0004838235,0.00015395474,0.0001381511,0.00017606143,0.00010858898,0.000073372394,0.0000023938187],"about_ca_topic_score_codex":0.002133169,"about_ca_topic_score_gemma":0.0037263206,"teacher_disagreement_score":0.002133169,"about_ca_system_score_codex":0.00021353159,"about_ca_system_score_gemma":0.00017459893,"threshold_uncertainty_score":0.004241526},"labels":[],"label_agreement":null},{"id":"W4390508574","doi":"10.3390/neurosci5010003","title":"Moving towards an Understanding of the Role of the Inferior Fronto-Occipital Fasciculus in Language Processing","year":2024,"lang":"en","type":"article","venue":"NeuroSci","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fasciculus; Fractional anisotropy; Dorsum; Diffusion MRI; Psychology; White matter; Superior longitudinal fasciculus; Anatomy; Biology; Medicine","score_opus":0.04862853014544044,"score_gpt":0.3477391946118507,"score_spread":0.29911066446641027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390508574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8251067,0.04889189,0.101470776,0.012191087,0.00029500978,0.00007351573,0.00029922376,0.00015556188,0.011516236],"genre_scores_gemma":[0.95513827,0.013175282,0.028662069,0.0008818857,0.00025387626,0.00003422796,0.00012628808,0.000021190048,0.0017068645],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999767,0.00004304247,0.000011068916,0.000117124044,0.000033184067,0.000028563109],"domain_scores_gemma":[0.9988355,0.0004948695,0.00035564386,0.00012923966,0.000114946386,0.00006982537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014792384,0.00045385907,0.00023936441,0.0009759259,0.00028397757,0.0015999897,0.00050483085,0.00088563235,0.0018804345],"category_scores_gemma":[0.0024950907,0.00017563568,0.00030183402,0.00040385325,0.002715342,0.00295537,0.0006738696,0.000899707,0.00026949894],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006838998,0.00026157504,0.1799434,0.0023569511,0.00024898138,0.0013049288,0.004731594,0.004503724,0.2719008,0.07932226,0.0019956797,0.45274618],"study_design_scores_gemma":[0.00006462489,0.0010651607,0.75548905,0.0013090698,0.00018452751,0.0031731513,0.0041288794,0.009215837,0.043049354,0.15385577,0.028295767,0.00016891569],"about_ca_topic_score_codex":0.0040983837,"about_ca_topic_score_gemma":0.0063334755,"teacher_disagreement_score":0.0040983837,"about_ca_system_score_codex":0.00063453027,"about_ca_system_score_gemma":0.00085884496,"threshold_uncertainty_score":0.008149087},"labels":[],"label_agreement":null},{"id":"W4390512644","doi":"10.1038/s41598-023-50768-z","title":"White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Diffusion MRI; Fiber tract; Medicine; Cognition; Type 2 Diabetes Mellitus; Internal medicine; Diabetes mellitus; Psychology; Cardiology; Pathology; Psychiatry; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.017234161584411295,"score_gpt":0.27283407408042254,"score_spread":0.2555999124960112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390512644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982451,0.0010556813,0.0001855198,0.000028334953,0.000008137943,0.000008689183,0.00012269948,0.0000051746865,0.0003407092],"genre_scores_gemma":[0.99875283,0.0004790169,0.00031793915,0.000018783605,0.000023861998,0.00000969354,0.00017594072,0.0000022866298,0.00021963372],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980885,0.000040179762,0.00002857354,0.000052937434,0.000040311486,0.000029195153],"domain_scores_gemma":[0.99938273,0.00008018471,0.0003414156,0.000046686793,0.000059126814,0.0000898661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004575968,0.00032509162,0.00021615809,0.00092772173,0.00024885594,0.0005546821,0.0001922891,0.00037383396,0.0010208008],"category_scores_gemma":[0.000921068,0.00019268168,0.00029148816,0.0010082796,0.0002473227,0.00024800203,0.00026987048,0.0003729858,0.00015601925],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050028996,0.00009454838,0.9921693,0.000031421427,0.00012744746,0.00018115353,0.000057649395,0.0000753722,0.0014033635,0.000023166102,0.00007129015,0.0052649304],"study_design_scores_gemma":[0.0000052892815,0.0000994423,0.9990086,0.0000046770874,0.000048337046,0.00029743303,0.000037992828,0.00020643849,0.00016974431,0.00004107413,0.00007797012,0.0000029417172],"about_ca_topic_score_codex":0.002800048,"about_ca_topic_score_gemma":0.0032423402,"teacher_disagreement_score":0.002800048,"about_ca_system_score_codex":0.00018693811,"about_ca_system_score_gemma":0.00021524885,"threshold_uncertainty_score":0.005567491},"labels":[],"label_agreement":null},{"id":"W4390537154","doi":"10.2139/ssrn.4668765","title":"Diffusion Tensor Imaging for Evaluation of Cortical Spinal Tract and Cerebral Infarction Lesion in Arterial Ischemic Stroke Pediatric Patients","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Diffusion MRI; Medicine; Stroke (engine); Infarction; Lesion; Cerebral infarction; Magnetic resonance imaging; Brain infarction; Radiology; Cardiology; Internal medicine; Ischemia; Pathology; Myocardial infarction","score_opus":0.03890195195586875,"score_gpt":0.3642319694553152,"score_spread":0.32533001749944646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390537154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937359,0.002196354,0.00041382326,0.0002815296,0.00002763294,0.000049878945,0.00054678513,0.000015087993,0.0027330627],"genre_scores_gemma":[0.99568367,0.0019750458,0.001076934,0.00006354993,0.00006076666,0.000043715856,0.00047762186,0.000009312633,0.0006093536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999835,0.00003100039,0.000028577422,0.00003341415,0.000031339736,0.000040558953],"domain_scores_gemma":[0.99969065,0.00008589858,0.00007109773,0.00001560647,0.00006485176,0.00007185134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042817215,0.0005863539,0.00042128022,0.0014328635,0.00031380367,0.0006007797,0.00028965034,0.00061829545,0.0022497408],"category_scores_gemma":[0.0018008668,0.00022707497,0.00030862776,0.0007161727,0.0003032942,0.0005157531,0.0002909628,0.0005904965,0.0003945096],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006047749,0.00025893148,0.9555694,0.00012597657,0.00009292695,0.0152970115,0.00022150879,0.00045848952,0.0038411177,0.00028019527,0.001511032,0.021738589],"study_design_scores_gemma":[0.00005978448,0.0005234527,0.9680651,0.00014041111,0.00022130419,0.022811249,0.00065980793,0.002370875,0.0031176514,0.0004216949,0.0015809437,0.000027885877],"about_ca_topic_score_codex":0.0031651934,"about_ca_topic_score_gemma":0.0032925287,"teacher_disagreement_score":0.0031651934,"about_ca_system_score_codex":0.0003737274,"about_ca_system_score_gemma":0.0010073896,"threshold_uncertainty_score":0.0075261593},"labels":[],"label_agreement":null},{"id":"W4390584905","doi":"10.3389/fnins.2023.1228952","title":"Evaluation of tractography-based myelin-weighted connectivity across the lifespan","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Myelin; Tractography; Connectome; Diffusion MRI; White matter; Neuroscience; Magnetic resonance imaging; Neuroplasticity; Computer science; Biology; Functional connectivity; Medicine; Central nervous system; Radiology","score_opus":0.08478501845121374,"score_gpt":0.40210080993244784,"score_spread":0.3173157914812341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390584905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.953669,0.0009050436,0.042710442,0.000043327727,0.000010545842,0.0000563734,0.0018605228,0.00022395291,0.00052072894],"genre_scores_gemma":[0.9835894,0.00020386292,0.015040321,0.0000056939757,0.000008077558,0.000051437964,0.0008259051,0.000025168993,0.0002501378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997086,0.00007970971,0.000030708357,0.000111535424,0.000048227525,0.000021079053],"domain_scores_gemma":[0.9985703,0.0005173074,0.00046866693,0.000116946365,0.00023803991,0.0000886292],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010278617,0.0005237395,0.00031160147,0.0025152601,0.00017360669,0.0004554444,0.00024025427,0.00034766915,0.001472446],"category_scores_gemma":[0.003884646,0.00011553311,0.00042610226,0.0010925605,0.00028430915,0.0004540631,0.0004642657,0.00012096216,0.00017242238],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012105117,0.00008032814,0.73803437,0.0006875775,0.0015628634,0.0004911799,0.0006356725,0.036029063,0.047867272,0.001476612,0.0008706906,0.17105395],"study_design_scores_gemma":[0.000026464457,0.0006781621,0.84887457,0.00009538701,0.00034217697,0.0018799519,0.00024916732,0.13081229,0.011772553,0.0035335242,0.0016713766,0.00006436076],"about_ca_topic_score_codex":0.002973562,"about_ca_topic_score_gemma":0.003243544,"teacher_disagreement_score":0.002973562,"about_ca_system_score_codex":0.00032423888,"about_ca_system_score_gemma":0.00025167558,"threshold_uncertainty_score":0.0059124827},"labels":[],"label_agreement":null},{"id":"W4390607650","doi":"10.1117/1.jmi.11.1.014005","title":"Robust fiber orientation distribution function estimation using deep constrained spherical deconvolution for diffusion-weighted magnetic resonance imaging","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Deconvolution; Diffusion MRI; Magnetic resonance imaging; Artificial intelligence; Regularization (linguistics); Tractography; Orientation (vector space); Deep learning; Computer science; Real-time MRI; Pattern recognition (psychology); Algorithm; Medicine; Mathematics","score_opus":0.03570822091407746,"score_gpt":0.3462099798567345,"score_spread":0.3105017589426571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390607650","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00970247,0.000276109,0.98909914,0.00014546413,0.000011948294,0.000019940533,0.000089738176,0.0004487196,0.00020649537],"genre_scores_gemma":[0.27938843,0.000760558,0.715627,0.0001877366,0.000057924935,0.00014669684,0.0012752922,0.00027816423,0.0022782052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970156,0.000073263414,0.000018645424,0.00007226438,0.00010363455,0.000030646468],"domain_scores_gemma":[0.99926907,0.0002861011,0.00013908422,0.00007757017,0.00018336701,0.000044806744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009591742,0.0009658368,0.00059795455,0.00081215875,0.00028893325,0.00047813452,0.0010211505,0.0008011166,0.0007627949],"category_scores_gemma":[0.0029284842,0.00042457084,0.00087572215,0.0007280625,0.0005689456,0.0007325564,0.001054114,0.0012747166,0.00042147102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018375614,0.00010359545,0.0017430974,0.00018153532,0.00017362212,0.00013030224,0.00010708543,0.6566178,0.03258571,0.008397351,0.0040614083,0.29571474],"study_design_scores_gemma":[0.000004322123,0.0000138993655,0.00018921017,0.000004852759,0.0000071174854,0.00002550066,0.000004762876,0.99428374,0.0025243957,0.0024653114,0.0004687054,0.000008157764],"about_ca_topic_score_codex":0.009285701,"about_ca_topic_score_gemma":0.00977735,"teacher_disagreement_score":0.009285701,"about_ca_system_score_codex":0.0007762601,"about_ca_system_score_gemma":0.0018458036,"threshold_uncertainty_score":0.018463254},"labels":[],"label_agreement":null},{"id":"W4390616343","doi":"10.1038/s41467-023-44591-3","title":"Radiomic tractometry reveals tract-specific imaging biomarkers in white matter","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Deutsches Krebsforschungszentrum; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Computational biology; Medicine; Magnetic resonance imaging; Biology; Radiology","score_opus":0.046331377153241295,"score_gpt":0.3832871021868001,"score_spread":0.3369557250335588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390616343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.274769,0.0030043114,0.7133219,0.0010880816,0.00014577195,0.00008765887,0.0019702425,0.0017979221,0.0038151045],"genre_scores_gemma":[0.8553631,0.0017160823,0.13881035,0.00032107907,0.00016731484,0.00009615177,0.0015491332,0.00036816584,0.0016086468],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999645,0.00012630441,0.000029402483,0.00011664361,0.000052137006,0.00003039295],"domain_scores_gemma":[0.9985469,0.00045600015,0.0005132914,0.00024917725,0.00016558073,0.00006901773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012573466,0.0008202615,0.00057128107,0.002253885,0.00033202133,0.0017701582,0.00043864042,0.0009551298,0.0019493994],"category_scores_gemma":[0.005658693,0.00035141633,0.0008427909,0.0015400985,0.0010184345,0.001231471,0.0007792743,0.0006939317,0.0009687759],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010995306,0.00018261457,0.13073128,0.001123903,0.0010755458,0.0015044655,0.0012827843,0.12839483,0.24675386,0.062133063,0.009703675,0.41601437],"study_design_scores_gemma":[0.000074352145,0.0007152221,0.16242614,0.0004682074,0.0007206557,0.0057688397,0.00059077534,0.5784492,0.086272255,0.13381758,0.03036016,0.00033655955],"about_ca_topic_score_codex":0.0017100355,"about_ca_topic_score_gemma":0.002309795,"teacher_disagreement_score":0.002253885,"about_ca_system_score_codex":0.0004701172,"about_ca_system_score_gemma":0.0006298237,"threshold_uncertainty_score":0.006649554},"labels":[],"label_agreement":null},{"id":"W4390666148","doi":"10.3389/fneur.2023.1322815","title":"Preoperative validation of edema-corrected tractography in neurosurgical practice: translating surgeon insights into novel software implementation","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Medicine; Radiology; Medical physics; Tractography; Magnetic resonance imaging; Diffusion MRI","score_opus":0.030109449360110303,"score_gpt":0.3629948687341775,"score_spread":0.33288541937406724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390666148","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67396593,0.00030843474,0.32083014,0.0005318708,0.00004663227,0.0003936124,0.00018573174,0.0019482234,0.0017894398],"genre_scores_gemma":[0.8293071,0.00013349412,0.16979623,0.00004867272,0.0000134168595,0.00014731975,0.00012345718,0.00018576701,0.000244462],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969522,0.0017797633,0.00028641752,0.00034486086,0.00055065507,0.000086113934],"domain_scores_gemma":[0.9677416,0.019711042,0.0032925934,0.0031371706,0.005525189,0.00059233484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008851157,0.0005220753,0.00022302539,0.00084311055,0.00026117562,0.0016360973,0.000706346,0.0004948048,0.0014618892],"category_scores_gemma":[0.06499925,0.0002697573,0.00025721383,0.00038217494,0.0006648302,0.001046122,0.001077205,0.00036900223,0.00046109682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015028681,0.0003470966,0.14498016,0.0006488039,0.00022211004,0.00051026244,0.004494626,0.031038078,0.08397595,0.0017384847,0.0014885954,0.729053],"study_design_scores_gemma":[0.00023908698,0.0030804882,0.23626162,0.0005451211,0.0003038321,0.0030193997,0.002983918,0.58973676,0.1471252,0.0080910195,0.008312196,0.00030141277],"about_ca_topic_score_codex":0.0015662666,"about_ca_topic_score_gemma":0.0034076564,"teacher_disagreement_score":0.008851157,"about_ca_system_score_codex":0.0005215175,"about_ca_system_score_gemma":0.0013894155,"threshold_uncertainty_score":0.04680997},"labels":[],"label_agreement":null},{"id":"W4390692324","doi":"10.1162/imag_a_00075","title":"A database of the healthy human spinal cord morphometry in the PAM50 template space","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"HORIZON EUROPE Framework Programme; Natural Sciences and Engineering Research Council of Canada; European Commission; Institut de Valorisation des Données; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Ministerstvo Zdravotnictví Ceské Republiky","keywords":"Spinal cord; Space (punctuation); Computer science; Database; Medicine; Artificial intelligence; Neuroscience; Biology; Operating system","score_opus":0.1230567045196196,"score_gpt":0.4452457757036849,"score_spread":0.3221890711840653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390692324","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3632579,0.0045926147,0.20248039,0.00051507464,0.00050972146,0.0021386198,0.39485958,0.013728155,0.017917944],"genre_scores_gemma":[0.40698057,0.0018313435,0.10458322,0.00028582,0.00013729902,0.0033408161,0.47627,0.0007208761,0.005850094],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99916434,0.00011435433,0.00014926084,0.00033247937,0.00019570072,0.00004393022],"domain_scores_gemma":[0.9983393,0.0002966702,0.00016884813,0.00060711,0.00048887794,0.00009911691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076947955,0.00063448003,0.0008718935,0.0019598298,0.00038272893,0.0008373329,0.0016052786,0.0010846665,0.008101444],"category_scores_gemma":[0.0049210717,0.00027469735,0.0008492137,0.002362,0.00048243432,0.0006039171,0.0012499968,0.00046422455,0.005122628],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020815122,0.0007820244,0.053074926,0.0041967477,0.00087008066,0.0033172248,0.0007980921,0.015558332,0.036721066,0.0057945717,0.17850779,0.6982977],"study_design_scores_gemma":[0.00045163737,0.0017474056,0.48760617,0.0012550737,0.00086375524,0.0321446,0.0010889595,0.07780796,0.039257646,0.01693189,0.34041327,0.00043163533],"about_ca_topic_score_codex":0.0043954216,"about_ca_topic_score_gemma":0.007739642,"teacher_disagreement_score":0.008101444,"about_ca_system_score_codex":0.0003807204,"about_ca_system_score_gemma":0.000930075,"threshold_uncertainty_score":0.027101994},"labels":[],"label_agreement":null},{"id":"W4390747482","doi":"10.1016/j.media.2024.103085","title":"What matters in reinforcement learning for tractography","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada","keywords":"Reinforcement learning; Tractography; Computer science; Codebase; Artificial intelligence; Function (biology); Machine learning; White matter; Software","score_opus":0.033939239268384484,"score_gpt":0.3895429358701114,"score_spread":0.3556036966017269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390747482","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08382233,0.008327368,0.85157377,0.04273351,0.0013875782,0.0000959847,0.00027921385,0.0010089413,0.010771354],"genre_scores_gemma":[0.880029,0.002491043,0.106644385,0.002636544,0.001988229,0.00009378916,0.00021765183,0.00055145985,0.0053478433],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99594915,0.0025145034,0.00016882196,0.00076157035,0.00042978962,0.0001760764],"domain_scores_gemma":[0.92697996,0.06392754,0.0015650664,0.0026648901,0.003241248,0.0016212987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008931934,0.00080056937,0.0019047027,0.00042950705,0.0010424372,0.0027730048,0.0015993059,0.003631248,0.0072167264],"category_scores_gemma":[0.095930725,0.00051667815,0.00048930995,0.000464098,0.003219274,0.010926872,0.0016686837,0.004057722,0.0009599979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015548881,0.0006154166,0.01208245,0.0014153367,0.00041670015,0.00029434965,0.000428701,0.191731,0.0039476464,0.30170256,0.029098365,0.45671257],"study_design_scores_gemma":[0.000090882044,0.0001803378,0.0012382368,0.00018368354,0.00004596757,0.000102352,0.0001070601,0.50633633,0.0013516865,0.48756292,0.0027570836,0.000043466633],"about_ca_topic_score_codex":0.0024049,"about_ca_topic_score_gemma":0.0026184218,"teacher_disagreement_score":0.008931934,"about_ca_system_score_codex":0.0011247746,"about_ca_system_score_gemma":0.0018536142,"threshold_uncertainty_score":0.047237158},"labels":[],"label_agreement":null},{"id":"W4390840316","doi":"10.1101/2024.01.11.575169","title":"Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; In utero; Fractional anisotropy; Diffusion MRI; Tractography; Macaque; Neuroscience; Cohort; Biology; Psychology; Medicine; Pregnancy; Internal medicine; Fetus; Magnetic resonance imaging; Genetics","score_opus":0.027320700792127606,"score_gpt":0.2577149400748102,"score_spread":0.2303942392826826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390840316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994609,0.00009065311,0.00022590267,0.000010509132,0.0000014408697,0.0000019703807,0.00008412956,0.0000037342895,0.00012079896],"genre_scores_gemma":[0.9991015,0.00011384182,0.000410293,0.000011909894,0.0000024680871,0.000009224165,0.00013142623,0.0000058595024,0.00021356625],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992454,0.000016242195,0.000004893699,0.00002415867,0.000013485352,0.000016741515],"domain_scores_gemma":[0.99968755,0.00007172878,0.00014636494,0.000028613673,0.000028025255,0.000037777114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018116727,0.00013879684,0.00013793253,0.00045851435,0.00016369132,0.00030376966,0.00012946776,0.00018833629,0.00096548814],"category_scores_gemma":[0.0010101493,0.000104348765,0.00010332397,0.0002281466,0.00021105706,0.00012946567,0.0002610208,0.00022902054,0.000079171106],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007871616,0.000099735844,0.8585282,0.00007149333,0.00009594301,0.0013571391,0.0011993615,0.00042535414,0.11570592,0.0003638974,0.00025727056,0.021108443],"study_design_scores_gemma":[0.0000012042253,0.0000581884,0.9946774,0.000008851268,0.0000122953215,0.00046758977,0.00025030997,0.0003781655,0.0038991258,0.000111115165,0.00013294953,0.0000028373438],"about_ca_topic_score_codex":0.002679311,"about_ca_topic_score_gemma":0.002756187,"teacher_disagreement_score":0.002679311,"about_ca_system_score_codex":0.00018294726,"about_ca_system_score_gemma":0.00016364406,"threshold_uncertainty_score":0.0053274035},"labels":[],"label_agreement":null},{"id":"W4390856523","doi":"","title":"A Riemannian framework for incorporating white matter bundle priors in ODF-based tractography algorithms.","year":2025,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Prior probability; Tractography; Bundle; Algorithm; Mathematics; White matter; Artificial intelligence; Computer science; Bayesian probability; Materials science; Medicine","score_opus":0.03347959620418627,"score_gpt":0.3156327220764811,"score_spread":0.2821531258722948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390856523","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00092275953,0.00013183011,0.9981913,0.00011426846,0.000017827522,0.000012655333,0.00004927865,0.00021402178,0.0003460672],"genre_scores_gemma":[0.07555325,0.0007035423,0.91861194,0.00016794582,0.00013587665,0.00014477297,0.0004976602,0.00064919755,0.0035357578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991667,0.00040802144,0.000050635004,0.00012458734,0.00019992032,0.000050150677],"domain_scores_gemma":[0.9975541,0.001024955,0.00022791007,0.0003576482,0.0005811252,0.00025416602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002616027,0.0011407791,0.0012405625,0.0010931523,0.0006025827,0.0017046608,0.0019392447,0.0016616983,0.0037437005],"category_scores_gemma":[0.011683844,0.0008200485,0.0010754203,0.0011911297,0.0010985453,0.0024854029,0.0027131333,0.0021780294,0.0018767918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013091536,0.00006990746,0.0011146626,0.00032788434,0.0001846764,0.00019215244,0.00028700833,0.54469866,0.00858347,0.16870686,0.011743759,0.26396012],"study_design_scores_gemma":[0.000008061034,0.000031182186,0.0002101397,0.000029142291,0.000013098957,0.00007047355,0.000014400348,0.9422261,0.00079112814,0.051028516,0.0055584046,0.000019337858],"about_ca_topic_score_codex":0.01142165,"about_ca_topic_score_gemma":0.013874585,"teacher_disagreement_score":0.01142165,"about_ca_system_score_codex":0.0009090188,"about_ca_system_score_gemma":0.0018951747,"threshold_uncertainty_score":0.022710323},"labels":[],"label_agreement":null},{"id":"W4390987871","doi":"10.1016/j.neuroimage.2024.120516","title":"A unified filtering method for estimating asymmetric orientation distribution functions","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; McDonnell Center for Systems Neuroscience; Université de Bordeaux; National Institutes of Health","keywords":"Computer science; Human Connectome Project; Orientation (vector space); Artificial intelligence; Robustness (evolution); Algorithm; Mathematics","score_opus":0.08145382950075854,"score_gpt":0.41301489582213924,"score_spread":0.3315610663213807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390987871","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011315487,0.000061546176,0.99817514,0.000032023014,0.000018268993,0.000014892668,0.000029061901,0.0003419734,0.00019562093],"genre_scores_gemma":[0.034540713,0.00021638423,0.9625401,0.0001045461,0.00008127823,0.00011451415,0.0003506717,0.00032963094,0.0017222059],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813324,0.00028571216,0.00016712681,0.000512874,0.00074859225,0.00015253015],"domain_scores_gemma":[0.9978796,0.000549816,0.00023786709,0.00039454136,0.00083118957,0.00010699499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030519888,0.0012599623,0.0013412826,0.0022561336,0.0007538825,0.0018227431,0.0018293791,0.0019438316,0.0028422677],"category_scores_gemma":[0.0076008146,0.00065572135,0.0019974625,0.0016302855,0.00085574976,0.0020185288,0.0017116097,0.0022568153,0.0017254411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013506741,0.00008944567,0.0025332572,0.00017561163,0.00019729807,0.00015268449,0.00021842655,0.12044748,0.047419574,0.027327675,0.0064411694,0.79486233],"study_design_scores_gemma":[0.000020079136,0.000040584808,0.0016561332,0.00003555769,0.00005466191,0.00021234095,0.000023729008,0.9684055,0.01413795,0.0084079,0.00693711,0.000068463385],"about_ca_topic_score_codex":0.008557602,"about_ca_topic_score_gemma":0.010155416,"teacher_disagreement_score":0.008557602,"about_ca_system_score_codex":0.0009738197,"about_ca_system_score_gemma":0.0019583185,"threshold_uncertainty_score":0.017015576},"labels":[],"label_agreement":null},{"id":"W4391014509","doi":"10.1088/1361-6560/ad209c","title":"High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling","year":2024,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute; National Institutes of Health","keywords":"Bicubic interpolation; Computer science; Artificial intelligence; Probabilistic logic; Noise reduction; Interpolation (computer graphics); Noise (video); Pattern recognition (psychology); Computer vision; Resolution (logic); Image (mathematics); Linear interpolation","score_opus":0.37939140524178533,"score_gpt":0.45162854348542714,"score_spread":0.07223713824364181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391014509","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040382934,0.00008744953,0.9949596,0.00010714642,0.000016908849,0.000015325702,0.000031304946,0.0002805442,0.00046344256],"genre_scores_gemma":[0.39914796,0.0004049085,0.5941911,0.00030212293,0.000085645865,0.00016392718,0.00042399822,0.00033024227,0.0049501443],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997254,0.00006872603,0.000013243973,0.00007038656,0.00010003852,0.000022206148],"domain_scores_gemma":[0.9994499,0.00025529414,0.00007143194,0.000055289365,0.00012901983,0.000039003196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000929768,0.0007401137,0.0006036527,0.00058308616,0.00023101167,0.0007410658,0.0010121694,0.0011611831,0.0015642399],"category_scores_gemma":[0.0015854668,0.0005487347,0.0010711618,0.0004282768,0.0005983171,0.00069042336,0.0009314598,0.0013006806,0.0005237632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004991131,0.000028436381,0.00025377385,0.00006174196,0.00003401608,0.0000684083,0.00003627442,0.9328762,0.010411665,0.0071046096,0.00077330397,0.04830168],"study_design_scores_gemma":[0.000001546067,0.000004597485,0.0000135908995,0.0000017210458,0.0000018431614,0.000007934241,9.116743e-7,0.99817336,0.0007242858,0.00086770067,0.00020060691,0.0000019766542],"about_ca_topic_score_codex":0.0037162672,"about_ca_topic_score_gemma":0.0037772863,"teacher_disagreement_score":0.0037162672,"about_ca_system_score_codex":0.0006945156,"about_ca_system_score_gemma":0.0008252811,"threshold_uncertainty_score":0.0073892474},"labels":[],"label_agreement":null},{"id":"W4391023660","doi":"10.1016/j.neuropsychologia.2024.108801","title":"Examining the consistency in bilingualism and white matter research: A meta-analysis","year":2024,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Neuroscience of multilingualism; White matter; Psychology; Fractional anisotropy; Operationalization; Cognition; Developmental psychology; Meta-analysis; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.5498971572156616,"score_gpt":0.5024093913961325,"score_spread":0.04748776581952907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391023660","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031853814,0.9605993,0.004678739,0.0006245408,0.0003669907,0.00019195618,0.00091480545,0.000066447756,0.0007035152],"genre_scores_gemma":[0.77557266,0.21090312,0.008490715,0.0017734799,0.0005738066,0.0007345785,0.0014785915,0.00012656715,0.00034653992],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.97443366,0.013253173,0.0068007093,0.0035422998,0.0015009135,0.0004693214],"domain_scores_gemma":[0.9303803,0.055784427,0.007362243,0.0036422224,0.0024180533,0.00041278164],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.038144317,0.0021848788,0.009138055,0.00634728,0.0009037077,0.004815855,0.0015420744,0.0019716178,0.0018614952],"category_scores_gemma":[0.07021207,0.0014109046,0.02660312,0.007837766,0.0010374474,0.0020550517,0.001845027,0.001608425,0.00021590537],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013366793,0.000022813996,0.04674272,0.061058354,0.8767747,0.00021959671,0.00020412097,0.0005923562,0.00072529877,0.0003454677,0.00041394436,0.011563887],"study_design_scores_gemma":[0.00033865526,0.0002096179,0.02563962,0.008928443,0.9609327,0.00025863206,0.000084525695,0.00034722194,0.00037937175,0.0007361541,0.002118921,0.000026236981],"about_ca_topic_score_codex":0.0042868094,"about_ca_topic_score_gemma":0.010607602,"teacher_disagreement_score":0.9618557,"about_ca_system_score_codex":0.0014313379,"about_ca_system_score_gemma":0.0024426093,"threshold_uncertainty_score":0.20172888},"labels":[],"label_agreement":null},{"id":"W4391055807","doi":"10.1093/nop/npae003","title":"Multimodal imaging with magnetization transfer and diffusion tensor imaging reveals evidence of myelin damage in children and youth treated for a brain tumor","year":2024,"lang":"en","type":"article","venue":"Neuro-Oncology Practice","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Magnetization transfer; Diffusion MRI; Neuroimaging; Myelin; Nuclear magnetic resonance; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Materials science; Physics; Radiology","score_opus":0.030584150671444557,"score_gpt":0.35576698830464343,"score_spread":0.3251828376331989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391055807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99971026,0.00008411044,0.000033522963,0.000014302422,8.08771e-7,0.0000024886565,0.000045903602,0.0000021327269,0.00010637394],"genre_scores_gemma":[0.9995915,0.00011686463,0.00011245966,0.000012325937,0.0000028459604,0.0000060563525,0.000088314635,0.0000015169368,0.00006808642],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988616,0.000023356524,0.000012184752,0.000024168365,0.000022521315,0.000031577485],"domain_scores_gemma":[0.9995517,0.000056658453,0.000250673,0.000014883313,0.000044666358,0.00008135671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025633836,0.00019290685,0.00022326219,0.0008187937,0.00031919417,0.00035667027,0.00014656218,0.00029585246,0.00071730616],"category_scores_gemma":[0.0008024398,0.0001497747,0.00017259542,0.00051078515,0.00031107105,0.00024307567,0.0002638791,0.0002753513,0.00012967175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011097551,0.000040947853,0.99271035,0.000012716945,0.000020610283,0.0007474673,0.0002545284,0.0000439282,0.0030021367,0.000019215038,0.000092684786,0.002944341],"study_design_scores_gemma":[0.0000034267582,0.00014324742,0.9963492,0.0000063097614,0.000016839675,0.002235059,0.00032207597,0.000109618355,0.00067052216,0.000013499506,0.00012805105,0.0000021242272],"about_ca_topic_score_codex":0.0043303138,"about_ca_topic_score_gemma":0.0059371083,"teacher_disagreement_score":0.0043303138,"about_ca_system_score_codex":0.00029625808,"about_ca_system_score_gemma":0.00032288686,"threshold_uncertainty_score":0.008610189},"labels":[],"label_agreement":null},{"id":"W4391055873","doi":"10.1093/brain/awae021","title":"Multimodal study of multilevel pulvino-temporal connections: a new piece in the puzzle of lexical retrieval networks","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; National Institute of Dental and Craniofacial Research; Institut National de la Santé et de la Recherche Médicale; University of Minnesota; University of Southern California; Massachusetts General Hospital","keywords":"Temporal lobe; Neuroscience; Temporal cortex; Inferior temporal gyrus; Superior temporal gyrus; Tractography; Middle temporal gyrus; Psychology; White matter; Superior temporal sulcus; Electrocorticography; Angular gyrus; Anatomy; Biology; Electroencephalography; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine","score_opus":0.09833140360147559,"score_gpt":0.3979470373016012,"score_spread":0.2996156337001256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391055873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90689427,0.0030839618,0.084673084,0.00074016,0.000018635421,0.000029342526,0.00043560212,0.00013814669,0.003986774],"genre_scores_gemma":[0.97755563,0.0009406673,0.019887641,0.00009008764,0.000031659314,0.00004072023,0.00023573032,0.000050759034,0.0011671055],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999516,0.000010028589,0.0000027071678,0.000017377777,0.000008103659,0.000010154712],"domain_scores_gemma":[0.9998486,0.000053632684,0.000034001652,0.000028968941,0.00001509158,0.000019628602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026688114,0.00016942967,0.00016389172,0.00046732667,0.00024177137,0.0005525271,0.00028046808,0.0003004728,0.0017690143],"category_scores_gemma":[0.00063084625,0.00013213279,0.00015650976,0.0003613001,0.00053918094,0.0013198296,0.00050726143,0.00040487846,0.00018283077],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002376643,0.00004028329,0.029583257,0.0004064927,0.00018135253,0.0010681001,0.002096965,0.0063613537,0.8061044,0.011727474,0.00095942174,0.14123324],"study_design_scores_gemma":[0.00006380645,0.00039453388,0.68773013,0.00026948864,0.0002987565,0.005047747,0.0023715894,0.07464467,0.09718875,0.1145971,0.017262528,0.00013092346],"about_ca_topic_score_codex":0.00087968126,"about_ca_topic_score_gemma":0.0020666283,"teacher_disagreement_score":0.0017690143,"about_ca_system_score_codex":0.00016414585,"about_ca_system_score_gemma":0.00019225023,"threshold_uncertainty_score":0.0059179068},"labels":[],"label_agreement":null},{"id":"W4391065342","doi":"10.1101/2024.01.18.576325","title":"The FinnBrain Multimodal Neonatal Template and Atlas Collection: T1, T2, and DTI brain templates, and accompanying cortical and subcortical atlases","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Hospital for Sick Children; Montreal Neurological Institute and Hospital","funders":"","keywords":"Spatial normalization; Diffusion MRI; Computer science; White matter; Artificial intelligence; Anterior commissure; Neuroimaging; Segmentation; Pattern recognition (psychology); Template; Neuroscience; Brain morphometry; Brain atlas; Computer vision; Psychology; Medicine; Magnetic resonance imaging; Voxel; Radiology","score_opus":0.030965555731908654,"score_gpt":0.2925237791060957,"score_spread":0.26155822337418705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391065342","genre_codex":"methods","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033463534,0.00063472125,0.8702232,0.00043249485,0.00021060332,0.0023046504,0.05601466,0.018700942,0.01801519],"genre_scores_gemma":[0.052945998,0.00049299747,0.87973154,0.00027145067,0.000036756974,0.006678104,0.041759472,0.0065533454,0.011530286],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99911124,0.00017256061,0.00016426058,0.00022177285,0.00027820023,0.00005194018],"domain_scores_gemma":[0.9983291,0.00032511965,0.00018757337,0.0005355459,0.00053065846,0.00009195712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003085647,0.0010188329,0.00077309756,0.0026835126,0.0009363265,0.0013575901,0.0017975988,0.0009783058,0.02076743],"category_scores_gemma":[0.0049840026,0.00087639916,0.000662585,0.0021227794,0.0005721099,0.001065128,0.001336283,0.0010294302,0.009796986],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010691168,0.00020371117,0.012712157,0.0012831514,0.0001644791,0.0028101944,0.001664623,0.015697138,0.11389569,0.03004279,0.28187704,0.5385798],"study_design_scores_gemma":[0.00014593078,0.00040949282,0.042491853,0.0008200294,0.00017466194,0.009252923,0.0004825483,0.04961868,0.20089757,0.016330453,0.67897147,0.0004043934],"about_ca_topic_score_codex":0.010143082,"about_ca_topic_score_gemma":0.02006582,"teacher_disagreement_score":0.02076743,"about_ca_system_score_codex":0.0011818762,"about_ca_system_score_gemma":0.0039277286,"threshold_uncertainty_score":0.06947392},"labels":[],"label_agreement":null},{"id":"W4391099314","doi":"10.3390/info15010066","title":"Baseline Structural Connectomics Data of Healthy Brain Development Assessed with Multi-Modal Magnetic Resonance Imaging","year":2024,"lang":"en","type":"article","venue":"Information","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University; Memorial University of Newfoundland","funders":"National Institutes of Health; Canada Foundation for Innovation; Nova Scotia Research Innovation Trust","keywords":"Connectomics; Diffusion MRI; Magnetic resonance imaging; Baseline (sea); Tractography; Neuroimaging; Medicine; Functional magnetic resonance imaging; Neuroscience; Connectome; Psychology; Biology; Radiology; Functional connectivity","score_opus":0.07220338928432064,"score_gpt":0.3798657373353466,"score_spread":0.307662348051026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391099314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98215216,0.00024205573,0.0041389023,0.00006285197,0.000009334185,0.000036466514,0.0122481445,0.00007764794,0.0010322601],"genre_scores_gemma":[0.9775729,0.00016436953,0.007176703,0.000033904787,0.000012580955,0.000167848,0.014068284,0.00005502398,0.0007483486],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99947435,0.00010259715,0.00006902652,0.00018366442,0.00011051686,0.00005984718],"domain_scores_gemma":[0.99716944,0.0006034897,0.00065996323,0.00054788525,0.00081500836,0.00020425646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010891929,0.00035805092,0.0003269098,0.0016249965,0.00041772134,0.00044958646,0.00032587734,0.00046264482,0.001962983],"category_scores_gemma":[0.0049308934,0.00013450554,0.00028854646,0.0009911985,0.00032410538,0.0004989599,0.00060749607,0.00042382497,0.00045344175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005502995,0.00013674401,0.9395869,0.00011150485,0.00023725761,0.00041631286,0.0007291966,0.0009672414,0.016954921,0.000623988,0.0015172898,0.03816851],"study_design_scores_gemma":[0.0000050371273,0.00014977677,0.9946268,0.0000119999295,0.000035093675,0.0004541591,0.00014040027,0.0004443982,0.0021369576,0.00041748383,0.0015662663,0.0000116826],"about_ca_topic_score_codex":0.005499999,"about_ca_topic_score_gemma":0.011815993,"teacher_disagreement_score":0.005499999,"about_ca_system_score_codex":0.00025710667,"about_ca_system_score_gemma":0.0004361269,"threshold_uncertainty_score":0.010935962},"labels":[],"label_agreement":null},{"id":"W4391116136","doi":"10.1101/2024.01.20.576373","title":"Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fibre calibre, and vascularization","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Canada Research Chairs; Washington University in St. Louis","keywords":"Caliber; White matter; Order (exchange); White (mutation); Neuroscience; Biology; Medicine; Engineering; Genetics; Magnetic resonance imaging; Business; Gene; Mechanical engineering","score_opus":0.0583193677192866,"score_gpt":0.2912724294215054,"score_spread":0.2329530617022188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391116136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94819367,0.01085712,0.035450295,0.0011341568,0.000091713126,0.00008340323,0.0022246167,0.00011786017,0.0018471879],"genre_scores_gemma":[0.9940952,0.00053786876,0.004513181,0.0001223531,0.000028078939,0.0000334409,0.0004805115,0.000028525932,0.0001607766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99803,0.000791061,0.00017408853,0.00078784244,0.00013853154,0.00007855395],"domain_scores_gemma":[0.98201525,0.008727295,0.0046319673,0.0032970111,0.00093744847,0.00039102486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009272695,0.0007207732,0.0004997444,0.0016284853,0.0004487023,0.0011204248,0.00080186623,0.0005757995,0.0027789555],"category_scores_gemma":[0.020178681,0.00029382043,0.0017257361,0.0015508669,0.0014543786,0.00194442,0.0010665654,0.0008510752,0.00022740451],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008284088,0.000055382636,0.9574576,0.00075321994,0.0062874467,0.00022556035,0.0008315516,0.0029829533,0.0033101721,0.0037686706,0.00040359638,0.023095299],"study_design_scores_gemma":[0.000044732882,0.00043318924,0.9658352,0.00019866336,0.0025218597,0.0003469353,0.0005295373,0.0069802008,0.0024348916,0.018476158,0.002159149,0.00003947264],"about_ca_topic_score_codex":0.00515781,"about_ca_topic_score_gemma":0.0061721355,"teacher_disagreement_score":0.009272695,"about_ca_system_score_codex":0.00046200844,"about_ca_system_score_gemma":0.000912073,"threshold_uncertainty_score":0.049039304},"labels":[],"label_agreement":null},{"id":"W4391264577","doi":"10.1016/j.media.2024.103093","title":"Neural deformation fields for template-based reconstruction of cortical surfaces from MRI","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Segmentation; Polygon mesh; Computer vision; Surface (topology); Flow (mathematics); Surface reconstruction; Pattern recognition (psychology); Mathematics; Geometry; Computer graphics (images)","score_opus":0.03829917376689692,"score_gpt":0.3651151343577,"score_spread":0.3268159605908031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391264577","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010380538,0.00020837384,0.9875822,0.00016716073,0.000031654577,0.00004385387,0.00015325115,0.0006640276,0.00076892064],"genre_scores_gemma":[0.35376891,0.0010387971,0.63774264,0.00015983656,0.00006822522,0.00024195843,0.0008852679,0.0006799905,0.0054144743],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997991,0.000042337495,0.000013225485,0.00003786497,0.00009007449,0.000017386397],"domain_scores_gemma":[0.99956757,0.00019898819,0.000048986956,0.00006958395,0.00009337059,0.000021422236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006958658,0.00045932032,0.00047135114,0.00088462245,0.00028554298,0.0008786789,0.0008575693,0.0011823468,0.0025656484],"category_scores_gemma":[0.00320976,0.0005339938,0.00084882736,0.0010843829,0.0004935507,0.0008711802,0.00083512446,0.0012840023,0.0010243796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002250699,0.00010659275,0.0011443256,0.00021733351,0.000081574944,0.0001300198,0.0001367848,0.4575572,0.04188629,0.030163743,0.0052277916,0.4631232],"study_design_scores_gemma":[0.0000074058466,0.000018255472,0.0003765123,0.000012452461,0.0000070252217,0.00008765927,0.000010726904,0.98433995,0.0057376157,0.008104313,0.0012854553,0.0000126486675],"about_ca_topic_score_codex":0.00431801,"about_ca_topic_score_gemma":0.0051930253,"teacher_disagreement_score":0.00431801,"about_ca_system_score_codex":0.0005991699,"about_ca_system_score_gemma":0.0011332715,"threshold_uncertainty_score":0.008585751},"labels":[],"label_agreement":null},{"id":"W4391289272","doi":"10.1016/j.bas.2024.102759","title":"Parcellating the vertical associative fiber network of the temporoparietal area: Evidence from focused anatomic fiber dissections","year":2024,"lang":"en","type":"article","venue":"Brain and Spine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Anatomy; Intraparietal sulcus; Neuroscience; Superior parietal lobule; Arcuate fasciculus; Sulcus; Inferior parietal lobule; Psychology; Posterior parietal cortex; Biology; Medicine; Cognition; White matter; Fractional anisotropy","score_opus":0.060246112724505016,"score_gpt":0.3435291800678275,"score_spread":0.2832830673433225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391289272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98035175,0.0020345452,0.014239689,0.000057092944,0.000011865156,0.000027353552,0.00013054952,0.000028114342,0.0031190277],"genre_scores_gemma":[0.98991287,0.0011277316,0.00783679,0.000029098132,0.000013284822,0.000022722634,0.00025982418,0.000008105482,0.0007895799],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992466,0.0000068127006,0.000006306802,0.000029603721,0.000017576227,0.000015094586],"domain_scores_gemma":[0.9995521,0.00011211822,0.00013715713,0.00008309192,0.00009621915,0.000019253303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033435892,0.00018272377,0.00008117351,0.00068775413,0.00027282358,0.00029342543,0.00028226676,0.0002794514,0.0018274662],"category_scores_gemma":[0.0004682832,0.00016471861,0.000108314685,0.00025793115,0.00103787,0.00034330325,0.00024100427,0.00020879807,0.0003889548],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006417286,0.00009234764,0.13645193,0.00033721235,0.00014994205,0.0032247717,0.0021009007,0.0005751897,0.79709166,0.0038705596,0.0003795302,0.055084117],"study_design_scores_gemma":[0.000053055177,0.0005552049,0.7398912,0.00022687654,0.00021586697,0.034909874,0.0014870636,0.0026683037,0.20652303,0.003070349,0.010369172,0.00002990505],"about_ca_topic_score_codex":0.0017095455,"about_ca_topic_score_gemma":0.0035929147,"teacher_disagreement_score":0.0018274662,"about_ca_system_score_codex":0.00016665421,"about_ca_system_score_gemma":0.00015309222,"threshold_uncertainty_score":0.006113529},"labels":[],"label_agreement":null},{"id":"W4391292901","doi":"10.1016/j.jad.2024.01.238","title":"White matter alterations in affective and non-affective early psychosis: A diffusion MRI study","year":2024,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministero dell'Istruzione e del Merito","keywords":"White matter; Psychosis; Diffusion MRI; Psychology; Affect (linguistics); Psychiatry; Neuroscience; Medicine; Magnetic resonance imaging; Radiology; Communication","score_opus":0.012224279075635993,"score_gpt":0.3390501681491027,"score_spread":0.3268258890734667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391292901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99905723,0.00031207807,0.00014432635,0.00002374843,0.000002050092,0.000022023527,0.00013583145,0.0000026372652,0.00030008075],"genre_scores_gemma":[0.9992142,0.00020485165,0.00021840913,0.000019873116,0.000005948083,0.000013097788,0.00017622067,0.000002034805,0.0001452664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998609,0.000028304243,0.000016835807,0.000047289926,0.000021951628,0.000024761648],"domain_scores_gemma":[0.9996753,0.000050923798,0.00013211589,0.000028141038,0.000038094946,0.00007535199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004923163,0.00042168764,0.00020827314,0.0011660825,0.0004117309,0.00051420665,0.0002763362,0.00035676514,0.0015186166],"category_scores_gemma":[0.0009151498,0.0003188909,0.00021553802,0.0006355752,0.00035871097,0.00043124944,0.000584838,0.0002642225,0.00023315784],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019290708,0.00044042995,0.95457834,0.00025780345,0.00038018162,0.0069902134,0.001281723,0.0002380205,0.01973714,0.00026766647,0.00030344183,0.013596065],"study_design_scores_gemma":[0.000029363195,0.00015498388,0.994938,0.000014947576,0.00005502712,0.003748727,0.00029394674,0.0001726026,0.00024705724,0.000111614296,0.000226505,0.000007123813],"about_ca_topic_score_codex":0.0036172385,"about_ca_topic_score_gemma":0.005071996,"teacher_disagreement_score":0.0036172385,"about_ca_system_score_codex":0.00036644525,"about_ca_system_score_gemma":0.00027273907,"threshold_uncertainty_score":0.0071923733},"labels":[],"label_agreement":null},{"id":"W4391467208","doi":"10.1101/2024.02.01.578366","title":"A Multimodal Characterization of Low-Dimensional Thalamocortical Structural Connectivity Patterns","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Canada Research Chairs; McGill University","keywords":"Neuroscience; Thalamus; Human Connectome Project; Connectome; Diffusion MRI; Tractography; Default mode network; Functional connectivity; Psychology; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.023777826702546957,"score_gpt":0.28422209264990594,"score_spread":0.260444265947359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391467208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92112106,0.0002180818,0.07673181,0.0001156567,0.0000038820485,0.000016876622,0.0006279474,0.000093120405,0.0010716458],"genre_scores_gemma":[0.99287933,0.00006367396,0.0067045433,0.000008465437,0.0000068969503,0.000008087796,0.00017316136,0.000012759177,0.00014307497],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999362,0.000017382994,0.000004090009,0.000018864906,0.000012551825,0.000010902687],"domain_scores_gemma":[0.9997913,0.00007427833,0.00005628837,0.000020788835,0.000030809584,0.000026515434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019014589,0.0001704375,0.00014766151,0.0010302995,0.00011005557,0.00057396037,0.000119410324,0.0001911548,0.001142207],"category_scores_gemma":[0.0008714242,0.000101767255,0.00016508621,0.0005959694,0.00033111506,0.00035230443,0.0002717859,0.00017252746,0.00011010154],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046488506,0.00006440459,0.11609181,0.00028552924,0.00024925068,0.0008496368,0.00088418793,0.035364207,0.72394496,0.014204219,0.0011573323,0.10643956],"study_design_scores_gemma":[0.000021734571,0.00017671961,0.64603794,0.000046462963,0.00012166744,0.0017254007,0.00045256224,0.2791782,0.0404984,0.030091178,0.0015748256,0.00007495435],"about_ca_topic_score_codex":0.0011185282,"about_ca_topic_score_gemma":0.0017013743,"teacher_disagreement_score":0.001142207,"about_ca_system_score_codex":0.00015165715,"about_ca_system_score_gemma":0.00013702264,"threshold_uncertainty_score":0.003821075},"labels":[],"label_agreement":null},{"id":"W4391484784","doi":"10.1016/j.mri.2024.01.008","title":"Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute; Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Distortion (music); Image quality; Preprocessor; Artificial intelligence; Diffusion MRI; Spinal cord; Computer vision; Computer science; Tractography; Image processing; White matter; Pattern recognition (psychology); Medicine; Image (mathematics); Magnetic resonance imaging; Radiology","score_opus":0.03561056874983854,"score_gpt":0.3677234859921943,"score_spread":0.33211291724235575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391484784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9567128,0.0034463753,0.03740536,0.00030734038,0.00018633707,0.00017665542,0.00039048,0.00055362965,0.0008210059],"genre_scores_gemma":[0.92358565,0.0017912122,0.07164924,0.00030815112,0.00006645501,0.00014628492,0.0012793101,0.00043059417,0.0007430509],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99890804,0.00037621637,0.00016709664,0.00023412061,0.00022083087,0.00009382081],"domain_scores_gemma":[0.99231285,0.0050755437,0.0009287534,0.0006056204,0.0008744506,0.00020280606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025025334,0.0008803814,0.0006108796,0.00060819305,0.000470272,0.0010976378,0.00049467135,0.0007697135,0.0007785666],"category_scores_gemma":[0.018660614,0.00028936274,0.00055985816,0.00060938334,0.0005489282,0.00067640474,0.00048808786,0.00048320863,0.0002658161],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009072606,0.0006521489,0.035397418,0.0021829915,0.0009947593,0.000985124,0.0006918758,0.050584525,0.7051093,0.0006026605,0.0013967401,0.19232975],"study_design_scores_gemma":[0.00054965576,0.010469391,0.18781663,0.00048059976,0.0021529314,0.0028439371,0.0006036278,0.13648164,0.64954346,0.0014354682,0.007279895,0.00034275142],"about_ca_topic_score_codex":0.0026904242,"about_ca_topic_score_gemma":0.0033120401,"teacher_disagreement_score":0.0026904242,"about_ca_system_score_codex":0.0002939703,"about_ca_system_score_gemma":0.00074215874,"threshold_uncertainty_score":0.013234794},"labels":[],"label_agreement":null},{"id":"W4391576525","doi":"10.1089/neu.2023.0208","title":"Advanced Magnetic Resonance Imaging Biomarkers of the Injured Spinal Cord: A Comparative Study of Imaging and Histology in Human Traumatic Spinal Cord Injury","year":2024,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; International Collaboration On Repair Discoveries; Vancouver Spine Surgery Institute; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Myelin; Spinal cord; Medicine; Magnetic resonance imaging; Pathology; Fractional anisotropy; Diffusion MRI; Luxol fast blue stain; White matter; Spinal cord injury; Central nervous system; Radiology; Internal medicine","score_opus":0.10837825317078192,"score_gpt":0.43644165587663486,"score_spread":0.32806340270585294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391576525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932133,0.003787697,0.0018787018,0.000047364367,0.000013333283,0.00006032271,0.0001576572,0.000017662418,0.0008239359],"genre_scores_gemma":[0.99424124,0.002375398,0.002198496,0.000059891456,0.000029446634,0.000060107748,0.00027114514,0.000009355376,0.0007550436],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99975616,0.00005797804,0.000029983385,0.00006517496,0.00006011533,0.000030600564],"domain_scores_gemma":[0.999519,0.00004919839,0.00015431926,0.000046482917,0.0001686951,0.00006233617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007387235,0.00030555043,0.0004054035,0.0016336085,0.0002420576,0.00042479308,0.00021527821,0.0005285262,0.0009304189],"category_scores_gemma":[0.0008699355,0.00016288497,0.00017775124,0.0008169774,0.00043979887,0.00046829143,0.00025821928,0.00023325658,0.00027709312],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035249942,0.0005723063,0.13494079,0.000712603,0.00027424013,0.0012009412,0.0008151829,0.00046911588,0.81935525,0.0003133341,0.000211185,0.03761003],"study_design_scores_gemma":[0.000046686895,0.0041245073,0.9102923,0.000054068776,0.0002033913,0.004552457,0.00063885975,0.00091619184,0.07704676,0.00029891252,0.0017894194,0.00003638608],"about_ca_topic_score_codex":0.00093881704,"about_ca_topic_score_gemma":0.0009359818,"teacher_disagreement_score":0.0016336085,"about_ca_system_score_codex":0.00017140851,"about_ca_system_score_gemma":0.00020771251,"threshold_uncertainty_score":0.0039067864},"labels":[],"label_agreement":null},{"id":"W4391585419","doi":"10.1007/978-3-031-47292-3","title":"Computational Diffusion MRI","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Diffusion; Thermodynamics; Physics","score_opus":0.03998252665559456,"score_gpt":0.34057089504401056,"score_spread":0.300588368388416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585419","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020936027,0.020247355,0.7174979,0.0019952906,0.0028428768,0.00008116517,0.0015037168,0.006990499,0.24674758],"genre_scores_gemma":[0.018129999,0.018520642,0.2542658,0.0006838377,0.001254045,0.00011974303,0.0030514025,0.0024406773,0.7015339],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999089,0.000007863151,0.0000033471176,0.000027255259,0.000046540266,0.000006163781],"domain_scores_gemma":[0.99978906,0.000058514655,0.000008765801,0.000050153973,0.00006594829,0.000027551336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002200975,0.0012463487,0.0006926051,0.0011358502,0.00034177743,0.0012853985,0.00086219853,0.0007659124,0.066683546],"category_scores_gemma":[0.000576509,0.00059933186,0.00051286496,0.0010112292,0.00041017914,0.0011255565,0.0010825725,0.0013105477,0.048568863],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000374617,0.000026487827,0.00007892759,0.00026628358,0.000031299707,0.0000992972,0.000041230676,0.007720559,0.009558426,0.041921914,0.36319703,0.5770211],"study_design_scores_gemma":[0.000010982416,0.0000403971,0.0004836115,0.00014286669,0.000034102708,0.0010829405,0.000029378085,0.036644094,0.01146867,0.086973466,0.8630469,0.0000425244],"about_ca_topic_score_codex":0.00067432027,"about_ca_topic_score_gemma":0.0021177772,"teacher_disagreement_score":0.066683546,"about_ca_system_score_codex":0.00031596815,"about_ca_system_score_gemma":0.0003824204,"threshold_uncertainty_score":0.22307867},"labels":[],"label_agreement":null},{"id":"W4391585483","doi":"10.1007/978-3-031-47292-3_4","title":"Improving Multi-Tensor Fitting with Global Information from Track Orientation Density Imaging","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Orientation (vector space); Track (disk drive); Tensor (intrinsic definition); Computer vision; Artificial intelligence; Geometry; Mathematics","score_opus":0.032347199288199166,"score_gpt":0.3066180835841583,"score_spread":0.27427088429595914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585483","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021687513,0.00018420923,0.99552345,0.0000875657,0.000047937632,0.000014781927,0.00009796807,0.0014951382,0.00038016788],"genre_scores_gemma":[0.023359153,0.00038289317,0.97178733,0.00009133798,0.000057803263,0.00003390963,0.00073409034,0.0011337488,0.0024197472],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999213,0.00018907752,0.00005566009,0.00018416443,0.00029544122,0.00006266877],"domain_scores_gemma":[0.9974367,0.0009081728,0.00024422063,0.00062831776,0.0006541704,0.0001284397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022544865,0.0032965748,0.0018329255,0.0013495917,0.00063766754,0.0019220007,0.0020402914,0.0026048461,0.004307786],"category_scores_gemma":[0.006770928,0.0015188891,0.0019519206,0.0023236433,0.00070145144,0.0031789383,0.002034328,0.0030172507,0.0046218424],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022161583,0.00015412859,0.0010286216,0.0003008241,0.00034271923,0.0001330194,0.0001448994,0.2028755,0.05284425,0.007700905,0.016749628,0.71750396],"study_design_scores_gemma":[0.000008751354,0.000044875716,0.00032922687,0.000019286876,0.000061463674,0.00016805051,0.000021846892,0.97531885,0.012042678,0.0074374313,0.0045187543,0.000028704602],"about_ca_topic_score_codex":0.005578597,"about_ca_topic_score_gemma":0.0089950515,"teacher_disagreement_score":0.005578597,"about_ca_system_score_codex":0.0005428621,"about_ca_system_score_gemma":0.0012972752,"threshold_uncertainty_score":0.014410973},"labels":[],"label_agreement":null},{"id":"W4391585496","doi":"10.1007/978-3-031-47292-3_5","title":"BundleSeg: A Versatile, Reliable and Reproducible Approach to White Matter Bundle Segmentation","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec en Outaouais","funders":"","keywords":"Computer science; Segmentation; Bundle; Artificial intelligence; Computer vision; Materials science","score_opus":0.05548664248652436,"score_gpt":0.3148966712500903,"score_spread":0.25941002876356595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585496","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011526628,0.00023927147,0.97112805,0.0000782617,0.00012968064,0.00006654005,0.00070604344,0.025404854,0.0010946041],"genre_scores_gemma":[0.01039048,0.00034804546,0.9652569,0.00011562563,0.00011353542,0.00021485158,0.0023138032,0.01672907,0.004517773],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982461,0.00026980517,0.000120567245,0.0003806583,0.00086091156,0.000122004276],"domain_scores_gemma":[0.99820614,0.0005852515,0.00015262002,0.00051145954,0.00042984312,0.000114659866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002346327,0.0026983826,0.0017963569,0.0035757073,0.0009579667,0.0042034253,0.0042177024,0.0025776424,0.02357466],"category_scores_gemma":[0.0056035705,0.0021393378,0.001743557,0.0030706907,0.0009293438,0.0028894162,0.005232494,0.0026276708,0.014439429],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040329326,0.00009682584,0.0009314959,0.0005836311,0.0003333363,0.00044845184,0.0003476387,0.0201896,0.04664259,0.016679466,0.11208539,0.8012583],"study_design_scores_gemma":[0.00022515506,0.00021060865,0.0025403537,0.00029246695,0.00016533038,0.0026920643,0.00014560595,0.5813315,0.12044008,0.079552755,0.2120841,0.00031995203],"about_ca_topic_score_codex":0.0018399417,"about_ca_topic_score_gemma":0.0040184646,"teacher_disagreement_score":0.02357466,"about_ca_system_score_codex":0.0005110956,"about_ca_system_score_gemma":0.0014452093,"threshold_uncertainty_score":0.07886505},"labels":[],"label_agreement":null},{"id":"W4391668587","doi":"10.1016/j.cobeha.2024.101353","title":"Cerebellar imaging with diffusion magnetic resonance imaging: approaches, challenges, and potential","year":2024,"lang":"en","type":"article","venue":"Current Opinion in Behavioral Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"H2020 European Research Council; European Research Council; Horizon 2020; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; European Commission; Canada Foundation for Innovation; Horizon 2020 Framework Programme; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; White matter; Magnetic resonance imaging; Cerebellum; Neuroscience; Computer science; Tractography; Diffusion imaging; Medicine; Psychology; Radiology","score_opus":0.22106940932986416,"score_gpt":0.4033958399592782,"score_spread":0.18232643062941403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391668587","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002476776,0.9247878,0.051624388,0.017609632,0.0007706156,0.000060951385,0.00009089319,0.00016005526,0.0024188538],"genre_scores_gemma":[0.023607159,0.89160246,0.076123565,0.004246411,0.002728169,0.00033879737,0.0001882722,0.00012241855,0.0010427362],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99549955,0.002087311,0.00030923315,0.0007702383,0.0011167186,0.00021690993],"domain_scores_gemma":[0.98456675,0.009985788,0.0008940611,0.0007752795,0.0032060426,0.0005721262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017215617,0.0015568221,0.0031173488,0.0033106538,0.0008330473,0.004556886,0.0034110523,0.0041653127,0.0018175478],"category_scores_gemma":[0.014806524,0.001131883,0.0011489465,0.0024662262,0.00544144,0.008945396,0.0031876492,0.0062449924,0.0011330761],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023271608,0.00015629035,0.005115676,0.014004835,0.0005402675,0.00073027774,0.0007305302,0.002523137,0.020401774,0.045559537,0.02040515,0.88959986],"study_design_scores_gemma":[0.00013334614,0.0011371883,0.01522155,0.01581436,0.0009861927,0.014236372,0.0022120627,0.021301271,0.030750366,0.24602678,0.6513863,0.0007942326],"about_ca_topic_score_codex":0.0037382354,"about_ca_topic_score_gemma":0.0079049235,"teacher_disagreement_score":0.017215617,"about_ca_system_score_codex":0.002129363,"about_ca_system_score_gemma":0.003362906,"threshold_uncertainty_score":0.091046035},"labels":[],"label_agreement":null},{"id":"W4391671707","doi":"10.1016/j.media.2024.103101","title":"Blurred streamlines: A novel representation to reduce redundancy in tractography","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Redundancy (engineering); Artificial intelligence; False positive paradox; Computer science; Tractography; Representation (politics); Pattern recognition (psychology); Algorithm; Mathematics; Computer vision; Diffusion MRI","score_opus":0.070228611807333,"score_gpt":0.4499603158126226,"score_spread":0.37973170400528955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391671707","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013679525,0.00036643757,0.9844146,0.00016561603,0.00005664878,0.000041595526,0.00022111968,0.0006441851,0.0004103585],"genre_scores_gemma":[0.16873945,0.0011889013,0.8262077,0.00015538013,0.0002711488,0.0002127632,0.00092967245,0.00046996961,0.0018250267],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949706,0.0001501695,0.00004061057,0.00008428616,0.00017968567,0.00004815501],"domain_scores_gemma":[0.99813074,0.00065481884,0.00039188747,0.000305666,0.00040401088,0.00011284163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009151294,0.0010795225,0.00072876364,0.0020514852,0.00041003077,0.0012434028,0.0009951569,0.0010727983,0.002075491],"category_scores_gemma":[0.0046166247,0.00044453586,0.00080246053,0.0020173427,0.00074548495,0.0022552782,0.0010069218,0.0010153054,0.0006711448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083626946,0.00015676249,0.0034737426,0.0006584971,0.00014635608,0.00069342065,0.0007519484,0.31140304,0.07650701,0.098138645,0.01397414,0.4932601],"study_design_scores_gemma":[0.000038396294,0.00015941342,0.00093047344,0.000042336258,0.000035674442,0.0003816533,0.000038473045,0.9551203,0.013152093,0.017394032,0.012659105,0.000047934936],"about_ca_topic_score_codex":0.002964662,"about_ca_topic_score_gemma":0.0026962261,"teacher_disagreement_score":0.002964662,"about_ca_system_score_codex":0.0006533179,"about_ca_system_score_gemma":0.0010636542,"threshold_uncertainty_score":0.006943226},"labels":[],"label_agreement":null},{"id":"W4391814809","doi":"10.1080/09297049.2024.2307662","title":"Assessing the impact of infantile hydrocephalus on visuomotor integration through behavioural and neuroimaging studies","year":2024,"lang":"en","type":"article","venue":"Child Neuropsychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Academic Medical Organization of Southwestern Ontario","keywords":"Psychology; Hydrocephalus; Precuneus; Neuroimaging; Functional neuroimaging; Neuroscience; Corticospinal tract; Audiology; Diffusion MRI; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Psychiatry","score_opus":0.13953132264676033,"score_gpt":0.4962925954373502,"score_spread":0.3567612727905899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391814809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99955136,0.0001032153,0.0000843159,0.000010043513,6.1735733e-7,0.0000035431046,0.000024051214,0.0000016119211,0.00022129639],"genre_scores_gemma":[0.99952555,0.00013325231,0.00021553993,0.0000057610273,0.000001862097,0.0000061280157,0.00005136428,9.70011e-7,0.0000596346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998217,0.000052932613,0.000017572977,0.00003491829,0.00003944275,0.00003353335],"domain_scores_gemma":[0.999435,0.00013209182,0.0002560027,0.000029748096,0.00006835772,0.000078695004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029947126,0.00028472772,0.0002544869,0.0006163559,0.00020915215,0.0002548878,0.00014821264,0.00019765148,0.0004971055],"category_scores_gemma":[0.0014639058,0.00007128273,0.00015217792,0.00024896106,0.00035162678,0.00023832734,0.00026399057,0.00017713674,0.000059740363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018739303,0.00007415224,0.9691405,0.00005180192,0.000067769324,0.001819416,0.00060685526,0.0001956366,0.009985548,0.00006334248,0.00008934706,0.017718242],"study_design_scores_gemma":[0.0000028400518,0.00025843165,0.99649316,0.00000825944,0.000017573067,0.0017305812,0.0003011588,0.000112346,0.00092339475,0.000028691935,0.00012036781,0.000003263793],"about_ca_topic_score_codex":0.0023235362,"about_ca_topic_score_gemma":0.0053063002,"teacher_disagreement_score":0.0023235362,"about_ca_system_score_codex":0.00023519635,"about_ca_system_score_gemma":0.00028043814,"threshold_uncertainty_score":0.004619956},"labels":[],"label_agreement":null},{"id":"W4391838314","doi":"10.3389/fnagi.2024.1301826","title":"Diffusion kurtosis imaging of brain white matter alteration in patients with coronary artery disease based on the TBSS method","year":2024,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corona radiata (embryology); Internal capsule; Fractional anisotropy; Superior longitudinal fasciculus; Corpus callosum; Diffusion MRI; Medicine; White matter; Optic radiation; Cardiology; Kurtosis; Anatomy; Internal medicine; Radiology; Magnetic resonance imaging","score_opus":0.01713418937310324,"score_gpt":0.2976968954639986,"score_spread":0.28056270609089534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391838314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97501636,0.0016485055,0.020904113,0.00006609594,0.00002735005,0.00009757268,0.0008326146,0.00019023265,0.0012171934],"genre_scores_gemma":[0.97937757,0.0007944041,0.018565224,0.00001811977,0.000024053239,0.0000864977,0.0005697967,0.000035009605,0.0005292929],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997396,0.000061226834,0.000055071287,0.000059397888,0.000059119953,0.000025580355],"domain_scores_gemma":[0.99948907,0.000075962744,0.00023118408,0.000055127155,0.00011126703,0.00003734304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008845714,0.00069403026,0.00039717104,0.0026138993,0.00029366443,0.00062514347,0.0002571827,0.0002685028,0.0014129707],"category_scores_gemma":[0.0015628345,0.00018726135,0.0004378398,0.0012083316,0.00033502965,0.0005269744,0.0005389855,0.00019946117,0.0002789568],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026799734,0.000206322,0.70372087,0.0008382525,0.000976991,0.0020075606,0.0009497639,0.0047155484,0.15535198,0.0015112328,0.0012383643,0.12580317],"study_design_scores_gemma":[0.000099400786,0.0009549381,0.9153128,0.00011372525,0.00055943534,0.0081568165,0.00076160155,0.03746128,0.030646732,0.0025126252,0.0033128194,0.000107667256],"about_ca_topic_score_codex":0.0011175175,"about_ca_topic_score_gemma":0.0019376563,"teacher_disagreement_score":0.0026138993,"about_ca_system_score_codex":0.00021657812,"about_ca_system_score_gemma":0.00032865632,"threshold_uncertainty_score":0.004726827},"labels":[],"label_agreement":null},{"id":"W4392011062","doi":"10.1016/s2589-7500(23)00250-9","title":"Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation","year":2024,"lang":"en","type":"review","venue":"The Lancet Digital Health","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"FP7 Euratom; HORIZON EUROPE Excellent Science; H2020 Excellent Science; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Knut och Alice Wallenbergs Stiftelse; National Cancer Institute; European Research Council; Seventh Framework Programme; Radboud Universiteit; Instituto de Salud Carlos III; Helse Sør-Øst RHF; National Center for Advancing Translational Sciences; Medical Research Council Canada; Medical Research Council; National Institutes of Health; Horizon 2020 Framework Programme; National Institute of Mental Health; Vetenskapsrådet; Norges Forskningsråd; Instituto de Investigación Marqués de Valdecilla; University of British Columbia; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Health and Medical Research Council; Russian Foundation for Basic Research; Bundesministerium für Bildung und Forschung; National Institute on Drug Abuse; Icahn School of Medicine at Mount Sinai","keywords":"Covariate; Normative; Benchmarking; Multivariate statistics; Neuroimaging; Robustness (evolution); Algorithm; Computer science; Artificial intelligence; Machine learning; Statistics; Mathematics; Econometrics; Psychology; Biology","score_opus":0.19398824350393468,"score_gpt":0.43477473142110357,"score_spread":0.2407864879171689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392011062","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023960598,0.016728763,0.9476185,0.0013861484,0.00019613904,0.00031547897,0.0021284814,0.003038484,0.004627352],"genre_scores_gemma":[0.2834218,0.017201718,0.684314,0.0005163751,0.00015263248,0.0028493656,0.0061073024,0.0018552735,0.0035814422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99767834,0.0012498606,0.00019755196,0.0003389546,0.00047594632,0.0000593998],"domain_scores_gemma":[0.9894303,0.007608986,0.00071559614,0.0008457666,0.0013070303,0.00009228433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012257228,0.0012686544,0.0016110559,0.002466123,0.00035287318,0.0028735718,0.003423791,0.001676774,0.002616872],"category_scores_gemma":[0.033521302,0.0007675319,0.0015067991,0.0019246166,0.00092119706,0.002154481,0.0018801948,0.0016176684,0.001201671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033571201,0.00009428832,0.008082261,0.0037805731,0.00083412504,0.00025870526,0.00070246204,0.5746639,0.0024830091,0.047740363,0.012737105,0.3482875],"study_design_scores_gemma":[0.0000754396,0.00026299513,0.0062312507,0.0017258313,0.00031876448,0.0008864192,0.0002244303,0.8756533,0.0037945372,0.06872396,0.041916534,0.0001865516],"about_ca_topic_score_codex":0.0066798287,"about_ca_topic_score_gemma":0.007880091,"teacher_disagreement_score":0.012257228,"about_ca_system_score_codex":0.0016146224,"about_ca_system_score_gemma":0.0024078372,"threshold_uncertainty_score":0.06482321},"labels":[],"label_agreement":null},{"id":"W4392033560","doi":"10.32920/25266748","title":"Flair MRI Biomarkers of the Normal Appearing Brain Matter are Related to Cognition","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fluid-attenuated inversion recovery; Montreal Cognitive Assessment; Biomarker; Cognition; Diffusion MRI; Correlation; White matter; Medicine; Psychology; Magnetic resonance imaging; Internal medicine; Nuclear medicine; Neuroscience; Audiology; Oncology; Cognitive impairment; Radiology; Chemistry; Mathematics","score_opus":0.034776849628172235,"score_gpt":0.33867864063516634,"score_spread":0.3039017910069941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392033560","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.943705,0.0036555713,0.04560233,0.0004648344,0.00007419058,0.00014888216,0.0015325024,0.00053090637,0.004285828],"genre_scores_gemma":[0.97662896,0.0006307228,0.02068603,0.00012695436,0.000055899436,0.00007389803,0.0006057939,0.000029740844,0.0011620483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996712,0.00007533833,0.000025109193,0.00011291495,0.000073518204,0.00004191634],"domain_scores_gemma":[0.99908316,0.00019535256,0.00036720608,0.00009134021,0.00017895931,0.00008396241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016436137,0.0009598617,0.0006312792,0.0016992674,0.00021820252,0.0010848509,0.00034044834,0.00064578187,0.0011987597],"category_scores_gemma":[0.0032311496,0.00023250897,0.00039449305,0.0006405288,0.0005458481,0.000823959,0.00059116073,0.0004401437,0.0003994158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002065658,0.00035261814,0.37586576,0.00070180953,0.0013095284,0.0008354463,0.0005763089,0.0064543723,0.3478856,0.002359499,0.002583415,0.25900996],"study_design_scores_gemma":[0.00006236672,0.0016303954,0.88206387,0.000088280256,0.00043949476,0.0019940713,0.00017013543,0.018523132,0.083122656,0.00732683,0.0044889594,0.0000898564],"about_ca_topic_score_codex":0.0015460014,"about_ca_topic_score_gemma":0.0019273049,"teacher_disagreement_score":0.0016992674,"about_ca_system_score_codex":0.00033777973,"about_ca_system_score_gemma":0.00046936318,"threshold_uncertainty_score":0.008692384},"labels":[],"label_agreement":null},{"id":"W4392082539","doi":"10.32920/25266655.v1","title":"DTI Metrics Correlation to FLAIR Biomarkers, Cognition, and Neurodegenerative Diseases","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fluid-attenuated inversion recovery; Diffusion MRI; Correlation; Cognition; Fractional anisotropy; Dementia; Cognitive impairment; Internal medicine; Neuroscience; Medicine; Psychology; Biomarker; Cardiology; Audiology; Radiology; Magnetic resonance imaging; Biology; Disease; Mathematics","score_opus":0.07290672667454942,"score_gpt":0.3706102512596073,"score_spread":0.2977035245850579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392082539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7346021,0.008346871,0.24077159,0.0011566995,0.00035329882,0.00034215424,0.0027276275,0.0010372691,0.0106623275],"genre_scores_gemma":[0.94582736,0.00085844717,0.050754506,0.0000729038,0.00011607774,0.000087667795,0.00058147707,0.0000618053,0.0016397865],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99960977,0.00010084406,0.000045119355,0.00011195149,0.00010065545,0.00003163687],"domain_scores_gemma":[0.998798,0.00027400107,0.00042548304,0.00015996095,0.00026271914,0.00007986733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014858872,0.0009148111,0.0005111093,0.0026834628,0.00021355499,0.0013665499,0.0003276077,0.0004819627,0.0014392738],"category_scores_gemma":[0.0047900043,0.00018199297,0.00044897656,0.0015096003,0.00052756816,0.000715378,0.00065986486,0.0004534726,0.00042390678],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006978295,0.00020112924,0.43819958,0.00085597485,0.0014228657,0.0009182884,0.0007018952,0.017641816,0.14855516,0.0121045755,0.0048395772,0.37386125],"study_design_scores_gemma":[0.00005221856,0.00089091324,0.7497705,0.00015530018,0.000520883,0.003374105,0.00033125584,0.15064698,0.058366276,0.024591317,0.011139939,0.00016031905],"about_ca_topic_score_codex":0.0024950039,"about_ca_topic_score_gemma":0.0029431442,"teacher_disagreement_score":0.0026834628,"about_ca_system_score_codex":0.00046819952,"about_ca_system_score_gemma":0.00071799284,"threshold_uncertainty_score":0.007858217},"labels":[],"label_agreement":null},{"id":"W4392163870","doi":"10.1007/s00406-024-01760-9","title":"Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI","year":2024,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Overweight; Fractional anisotropy; White matter; Obesity; Medicine; Diffusion MRI; Internal medicine; Psychology; Endocrinology; Magnetic resonance imaging","score_opus":0.08839282318214507,"score_gpt":0.43811346111972244,"score_spread":0.34972063793757735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392163870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996378,0.0014869975,0.0003478072,0.00013897587,0.000009191269,0.0000063359453,0.00037329478,0.000005919712,0.0012535633],"genre_scores_gemma":[0.99826556,0.0007631765,0.00036898063,0.000054320622,0.000015196149,0.000004139096,0.00020320942,0.000010406718,0.0003150297],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999813,0.00006985166,0.000017181294,0.000045532255,0.00003051677,0.00002398553],"domain_scores_gemma":[0.9991277,0.00028824375,0.00033189694,0.00012898215,0.00004723867,0.00007581645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005567101,0.00027133382,0.00023558912,0.0007134696,0.000306908,0.0006704863,0.00020263791,0.00037371618,0.0017962714],"category_scores_gemma":[0.0017262545,0.0002553497,0.00032117922,0.0009027171,0.00055731536,0.00040274797,0.00041413272,0.0003604048,0.0001587323],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029835482,0.00026472277,0.94870573,0.00014526972,0.0015418533,0.00048825,0.0003401934,0.00034114582,0.024343554,0.00045120448,0.00027719623,0.020117357],"study_design_scores_gemma":[0.0000044714693,0.000052176336,0.9987404,0.0000058984733,0.00013591236,0.0001674594,0.0000489138,0.00009484846,0.00036595564,0.00020547926,0.00017478243,0.0000037258794],"about_ca_topic_score_codex":0.006364405,"about_ca_topic_score_gemma":0.011888133,"teacher_disagreement_score":0.006364405,"about_ca_system_score_codex":0.00019003442,"about_ca_system_score_gemma":0.00027360427,"threshold_uncertainty_score":0.012654722},"labels":[],"label_agreement":null},{"id":"W4392189336","doi":"10.1101/2024.02.15.580574","title":"A Neural Network Approach to Identify Left-Right Orientation of Anatomical Brain MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Commonwealth Scientific and Industrial Research Organisation; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Orientation (vector space); Artificial intelligence; Temporal lobe; Corpus callosum; Convolutional neural network; Psychology; Planum temporale; Computer science; Lateralization of brain function; Neuroscience; Medicine","score_opus":0.031315591073945714,"score_gpt":0.3199626815194136,"score_spread":0.2886470904454679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392189336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32754815,0.0024585112,0.6576821,0.001186276,0.00031492388,0.00012992333,0.0006993678,0.0037277283,0.0062530725],"genre_scores_gemma":[0.92516744,0.0003852596,0.06890914,0.0002892368,0.000068782625,0.00005250412,0.00081094104,0.000069123394,0.004247471],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997527,0.000039713363,0.000015134739,0.000086872096,0.00004257876,0.00006297403],"domain_scores_gemma":[0.9995974,0.00012229977,0.00006327631,0.000041276977,0.00014220004,0.000033584744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006463006,0.0009248115,0.00057041843,0.00080194714,0.00031466017,0.0007588273,0.0008817717,0.00096492865,0.0014418344],"category_scores_gemma":[0.0014557324,0.0003581487,0.00061727274,0.0004966938,0.00033730635,0.00057354936,0.0008083,0.0009988871,0.0005112889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051128725,0.00028689875,0.0109977,0.00013812387,0.0002072532,0.00057140243,0.00014157048,0.46402135,0.028363405,0.0028250914,0.005737291,0.48619866],"study_design_scores_gemma":[0.00000473064,0.000027398657,0.0007621938,0.000009240413,0.000013862153,0.000033183784,0.00001362573,0.9960651,0.0020442866,0.00074727845,0.00027301873,0.0000060367934],"about_ca_topic_score_codex":0.01293191,"about_ca_topic_score_gemma":0.0132206455,"teacher_disagreement_score":0.01293191,"about_ca_system_score_codex":0.0006915326,"about_ca_system_score_gemma":0.0008978949,"threshold_uncertainty_score":0.025713265},"labels":[],"label_agreement":null},{"id":"W4392291576","doi":"10.1101/2024.02.27.582303","title":"The Douglas Bell Canada Brain Bank Post-mortem Brain Imaging Protocol","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Ex vivo; Magnetic resonance imaging; Fixation (population genetics); Pathology; In vivo; Medicine; Brain tissue; Biomedical engineering; Biology; Radiology","score_opus":0.0194784093903341,"score_gpt":0.2902365284055896,"score_spread":0.2707581190152555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392291576","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08491472,0.0078086513,0.390043,0.008967908,0.004107959,0.09041758,0.19208913,0.012947859,0.20870312],"genre_scores_gemma":[0.085332066,0.006271876,0.45559868,0.006020432,0.0005325804,0.109547645,0.14599124,0.0045504607,0.18615499],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977754,0.0002926701,0.00022450756,0.00034105088,0.0011199662,0.0002463418],"domain_scores_gemma":[0.99417263,0.00034284624,0.00020816392,0.0012946159,0.0035491725,0.00043262087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004575942,0.0013332418,0.0009236482,0.0022456965,0.003553519,0.0017590859,0.0033357637,0.0017503843,0.07617179],"category_scores_gemma":[0.00517271,0.00086159125,0.0005656405,0.0018637982,0.0016281675,0.0007444456,0.0018193471,0.0017472735,0.028592976],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040454566,0.00053357444,0.0038070981,0.0020221563,0.000117619114,0.0037518654,0.001993112,0.0016852869,0.16285487,0.027011111,0.6724118,0.119766064],"study_design_scores_gemma":[0.00030847098,0.0002738944,0.014163747,0.0006368601,0.00007644955,0.0025394089,0.0004008926,0.000904887,0.028411988,0.002955539,0.949208,0.00011976978],"about_ca_topic_score_codex":0.112878814,"about_ca_topic_score_gemma":0.32860294,"teacher_disagreement_score":0.112878814,"about_ca_system_score_codex":0.00622507,"about_ca_system_score_gemma":0.021180872,"threshold_uncertainty_score":0.25482},"labels":[],"label_agreement":null},{"id":"W4392344604","doi":"10.1101/2024.02.27.582381","title":"MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Canadian Institutes of Health Research","keywords":"Univariate; Multivariate statistics; Computer science; Toolbox; Artificial intelligence; Python (programming language); Voxel; Mahalanobis distance; Data mining; Pattern recognition (psychology); Machine learning","score_opus":0.041497693143805185,"score_gpt":0.3402944671751039,"score_spread":0.29879677403129873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392344604","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012684348,0.0003086837,0.9291413,0.00019423521,0.00013950083,0.00021640584,0.009298246,0.0464119,0.0016054088],"genre_scores_gemma":[0.090795346,0.0004470237,0.870201,0.0002471967,0.00014242501,0.0022312638,0.014772394,0.018783916,0.0023793918],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99823064,0.0005231446,0.00016666751,0.00048520387,0.0004865634,0.0001077223],"domain_scores_gemma":[0.99309254,0.004007349,0.00088946056,0.0010182656,0.0007724765,0.00021992158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004952594,0.0027897898,0.0015947204,0.0044393674,0.0007603597,0.002716362,0.0024197681,0.0010545976,0.030434567],"category_scores_gemma":[0.026831442,0.0007793041,0.0019060757,0.002197738,0.0009175731,0.002450846,0.0041971747,0.002161028,0.007938509],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012811933,0.00037090312,0.017993508,0.0034946385,0.0022013858,0.0009465387,0.0014027765,0.044763193,0.04326149,0.0423618,0.17877057,0.66315204],"study_design_scores_gemma":[0.00043176644,0.0008064605,0.04808388,0.00078099786,0.0005773256,0.0024116107,0.00074818084,0.5983236,0.059493277,0.14810489,0.13956782,0.0006701771],"about_ca_topic_score_codex":0.0018203354,"about_ca_topic_score_gemma":0.0030662082,"teacher_disagreement_score":0.030434567,"about_ca_system_score_codex":0.0004777853,"about_ca_system_score_gemma":0.002237095,"threshold_uncertainty_score":0.10181379},"labels":[],"label_agreement":null},{"id":"W4392344620","doi":"10.1101/2024.02.22.581646","title":"Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Canadian Institutes of Health Research; Directorate for Biological Sciences; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; National Institute of Mental Health; Pfizer; Novartis Pharmaceuticals Corporation; Medical Research Council; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; Alzheimer's Association","keywords":"White matter; Diffusion MRI; Diffusion; Medicine; Magnetic resonance imaging; Physics; Radiology; Thermodynamics","score_opus":0.10397147367815911,"score_gpt":0.31931693750610285,"score_spread":0.21534546382794373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392344620","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05240412,0.0014340747,0.88643694,0.00041472568,0.00021219984,0.0013013297,0.023149896,0.028425837,0.006220841],"genre_scores_gemma":[0.13613503,0.0005436443,0.82405484,0.00022535438,0.000052746385,0.0039656246,0.026200868,0.0071821236,0.0016397281],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9941075,0.002037872,0.0009469871,0.0015703215,0.0011472311,0.00019005874],"domain_scores_gemma":[0.97781914,0.007756881,0.0035289617,0.0049891598,0.005519848,0.00038590241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021231147,0.0016018525,0.0009612784,0.0068999166,0.0011596219,0.0032627503,0.0018067325,0.0014328443,0.0056323083],"category_scores_gemma":[0.08589892,0.0008928657,0.001917134,0.004621505,0.0008159434,0.0028694388,0.0043791775,0.0016673853,0.002493763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010443783,0.00042843114,0.09304658,0.002503912,0.0018022811,0.0006268194,0.004419741,0.06722652,0.015915068,0.040404685,0.085782304,0.6867993],"study_design_scores_gemma":[0.00062584406,0.0012610914,0.12919089,0.001897218,0.001162233,0.0023823467,0.0020839009,0.31801876,0.04525503,0.1327133,0.36463937,0.0007700433],"about_ca_topic_score_codex":0.0050647175,"about_ca_topic_score_gemma":0.009541447,"teacher_disagreement_score":0.021231147,"about_ca_system_score_codex":0.0011104489,"about_ca_system_score_gemma":0.0026216405,"threshold_uncertainty_score":0.112282395},"labels":[],"label_agreement":null},{"id":"W4392377681","doi":"10.1038/s41467-024-46023-2","title":"Genetic architecture of the structural connectome","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; Krembil Foundation; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Neuroscience; Connectome; Connectomics; Biology; Genome-wide association study; Diffusion MRI; Genetic architecture; Evolutionary biology; Phenotype; Genetics; Functional connectivity; Magnetic resonance imaging; Gene; Single-nucleotide polymorphism; Medicine","score_opus":0.04277835830423975,"score_gpt":0.38646626693332614,"score_spread":0.3436879086290864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392377681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99479216,0.0003656173,0.0017119044,0.00020381888,0.0000058295013,0.00001281139,0.0019123335,0.000025591533,0.00096989365],"genre_scores_gemma":[0.997682,0.00009734642,0.00078278885,0.000043380136,0.0000065257414,0.000019038183,0.0011301384,0.000009232738,0.0002295595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998844,0.0002840496,0.00008688225,0.0005463466,0.00013476942,0.00010383619],"domain_scores_gemma":[0.9980227,0.00087938877,0.0006456103,0.00021845265,0.00014294211,0.00009092117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005676338,0.00030268932,0.00031215718,0.0017611253,0.00041003057,0.0006783844,0.00029631256,0.0005769534,0.00405516],"category_scores_gemma":[0.0039514303,0.0002607191,0.0004388376,0.0017054034,0.0007203319,0.00036709927,0.000783774,0.00037307222,0.00028301292],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007274915,0.00005456632,0.89261913,0.00024369833,0.0017350162,0.0019993715,0.0008766553,0.0059223496,0.068264455,0.0052895863,0.0020713983,0.02019628],"study_design_scores_gemma":[0.000028744955,0.00007223842,0.9892986,0.000032162043,0.00017518892,0.0014435895,0.00011521571,0.0032448706,0.0010754325,0.00334638,0.0011462909,0.000021344393],"about_ca_topic_score_codex":0.005881364,"about_ca_topic_score_gemma":0.009405439,"teacher_disagreement_score":0.005881364,"about_ca_system_score_codex":0.0003919235,"about_ca_system_score_gemma":0.0003159326,"threshold_uncertainty_score":0.013565898},"labels":[],"label_agreement":null},{"id":"W4392455053","doi":"10.1016/j.media.2024.103134","title":"Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada); Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; European Commission; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Protocol (science); Computer science; Artificial intelligence; Relaxation (psychology); Machine learning; Diffusion; Algorithm; Magnetic resonance imaging; Physics; Medicine","score_opus":0.04037254488641366,"score_gpt":0.40363153447511524,"score_spread":0.36325898958870156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392455053","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017873676,0.00017357341,0.98077697,0.00010675726,0.000012814127,0.00012902767,0.000043357984,0.0005517372,0.00033214802],"genre_scores_gemma":[0.1814097,0.0001957335,0.8166838,0.00011393703,0.000019104049,0.00058666343,0.0002244573,0.00028322102,0.00048334582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991441,0.00036789186,0.00006069125,0.00019388592,0.00018853116,0.000044891207],"domain_scores_gemma":[0.9972709,0.0016502837,0.00035203865,0.00026510673,0.00039586582,0.00006586567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043995488,0.001729677,0.0009833351,0.00094660436,0.00042007858,0.0009198266,0.0013751843,0.0012477665,0.0008377395],"category_scores_gemma":[0.011417483,0.00085906923,0.00096518284,0.000643627,0.0008125853,0.0015831225,0.0013555875,0.0018130911,0.00043870058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038076116,0.00030461547,0.001598077,0.00045783224,0.00018568742,0.0001229391,0.000284988,0.70149624,0.07425004,0.0046077026,0.00097637164,0.21533474],"study_design_scores_gemma":[0.000046534984,0.00024146072,0.0009186268,0.000027706123,0.00004569815,0.00009163355,0.000021772184,0.971235,0.019285046,0.0068892376,0.0011494794,0.000047791375],"about_ca_topic_score_codex":0.0018337596,"about_ca_topic_score_gemma":0.0025044528,"teacher_disagreement_score":0.0043995488,"about_ca_system_score_codex":0.0008614685,"about_ca_system_score_gemma":0.0021207137,"threshold_uncertainty_score":0.023267329},"labels":[],"label_agreement":null},{"id":"W4392455528","doi":"10.21203/rs.3.rs-3855042/v1","title":"A hierarchical atlas of the human cerebellum for functional precision mapping","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Atlas (anatomy); Cerebellum; Computer science; Neuroscience; Cartography; Geography; Biology; Anatomy","score_opus":0.2571819720625176,"score_gpt":0.485651847083358,"score_spread":0.22846987502084043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392455528","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013446532,0.00093734736,0.9428357,0.00065431086,0.00018489281,0.0003750092,0.012291184,0.008728489,0.020546596],"genre_scores_gemma":[0.11762097,0.0012257808,0.8547531,0.00016809291,0.00008682994,0.0005798362,0.0067421636,0.0024912904,0.016331993],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995859,0.0000761187,0.00003652839,0.00011247737,0.00014120083,0.00004767472],"domain_scores_gemma":[0.9993648,0.00019322777,0.000063573236,0.00015431724,0.0001761911,0.00004785178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065847114,0.00070928066,0.0005640378,0.0026233993,0.00094424875,0.0030877287,0.0009551075,0.0015702606,0.0191224],"category_scores_gemma":[0.002246095,0.00067235215,0.00096806494,0.0026170476,0.00059104385,0.0009642261,0.0012144343,0.0016829241,0.005154053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057742593,0.00015606647,0.00478607,0.0013275484,0.0002535128,0.0011004844,0.0013430658,0.062257253,0.11206154,0.2181662,0.11351069,0.48446012],"study_design_scores_gemma":[0.00029083187,0.00032502334,0.032875706,0.0006273862,0.00035208787,0.004940793,0.0005175692,0.22820655,0.06876074,0.23099203,0.43188667,0.0002246344],"about_ca_topic_score_codex":0.018133434,"about_ca_topic_score_gemma":0.04159867,"teacher_disagreement_score":0.0191224,"about_ca_system_score_codex":0.001077675,"about_ca_system_score_gemma":0.005047569,"threshold_uncertainty_score":0.063970745},"labels":[],"label_agreement":null},{"id":"W4392462618","doi":"10.1016/j.neuroimage.2024.120555","title":"Associations of quantitative susceptibility mapping with cortical atrophy and brain connectome in Alzheimer's disease: A multi-parametric study","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Connectome; Neuroscience; Superior parietal lobule; Precuneus; Statistical parametric mapping; Inferior parietal lobule; Atrophy; Parahippocampal gyrus; Tractography; Resting state fMRI; Psychology; Diffusion MRI; Medicine; Pathology; Temporal lobe; Functional connectivity; Magnetic resonance imaging; Cognition","score_opus":0.14852974669698024,"score_gpt":0.4140012270818498,"score_spread":0.26547148038486956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392462618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971529,0.000040830048,0.0026592528,0.000012065739,8.0371274e-7,0.000005402259,0.000034980494,0.000010200458,0.0000836244],"genre_scores_gemma":[0.99923706,0.000010248914,0.0006825615,0.0000021447208,0.0000018002651,0.0000066706602,0.00003682152,0.0000032823352,0.000019442048],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990754,0.000443699,0.00007273385,0.00019769112,0.00014342625,0.00006702294],"domain_scores_gemma":[0.9916027,0.0051462334,0.0016571712,0.0009874094,0.00035282152,0.00025367283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022347549,0.0003415815,0.00035156074,0.0013205727,0.00024347044,0.00044555127,0.00038409317,0.00038242678,0.0004504435],"category_scores_gemma":[0.00997588,0.00022297353,0.00037918732,0.0008261698,0.0005717403,0.00046614656,0.0007517905,0.00043236744,0.000047746442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012138529,0.0002037653,0.9315544,0.000081899016,0.001437927,0.000589081,0.00094779104,0.009671493,0.032039195,0.00054047734,0.0001290415,0.021591084],"study_design_scores_gemma":[0.000014965998,0.00028589356,0.9600909,0.0000052377018,0.00012833485,0.001000033,0.00016535525,0.03489677,0.0025567028,0.0007077209,0.00011896934,0.00002906882],"about_ca_topic_score_codex":0.0009362543,"about_ca_topic_score_gemma":0.0008522085,"teacher_disagreement_score":0.0022347549,"about_ca_system_score_codex":0.00017545774,"about_ca_system_score_gemma":0.0001895818,"threshold_uncertainty_score":0.011818647},"labels":[],"label_agreement":null},{"id":"W4392592471","doi":"10.21037/qims-23-1397","title":"Knowledge atlas of white matter microstructure: a bibliometric analysis","year":2024,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Tongji University; National Natural Science Foundation of China","keywords":"White matter; Atlas (anatomy); White paper; Computer science; Data science; Medicine; Geography; Magnetic resonance imaging; Archaeology; Radiology","score_opus":0.09699502246704417,"score_gpt":0.42028256994744,"score_spread":0.32328754748039584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392592471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51543254,0.0975448,0.018778669,0.0060211993,0.0005175265,0.0018836797,0.3044334,0.0019323925,0.053455736],"genre_scores_gemma":[0.82312906,0.05160126,0.026004668,0.0002572853,0.0005564284,0.001810269,0.09320468,0.00023676458,0.003199515],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9872103,0.0020747152,0.002950551,0.0016036392,0.0055715037,0.000589209],"domain_scores_gemma":[0.93416256,0.039675094,0.010453596,0.0022705644,0.012226173,0.0012120117],"candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00913206,0.00096362765,0.0022159605,0.24688223,0.0016814219,0.0069520827,0.0011538194,0.0009436512,0.0072746347],"category_scores_gemma":[0.053431317,0.00036098887,0.0025006307,0.26548913,0.0010108516,0.004421897,0.0034870396,0.00062288763,0.0015484786],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043281328,0.00020722492,0.41802442,0.042945363,0.0040776962,0.00139695,0.0062016775,0.0047802324,0.0037347774,0.015080809,0.046205554,0.45691255],"study_design_scores_gemma":[0.00011202525,0.0003386598,0.72485083,0.010294045,0.005891073,0.0021388286,0.010549941,0.014169263,0.0034560054,0.015399685,0.2124819,0.0003178009],"about_ca_topic_score_codex":0.0063159023,"about_ca_topic_score_gemma":0.005998342,"teacher_disagreement_score":0.7531178,"about_ca_system_score_codex":0.0029608193,"about_ca_system_score_gemma":0.0069214166,"threshold_uncertainty_score":0.048295498},"labels":[],"label_agreement":null},{"id":"W4392637325","doi":"10.1038/s41598-024-56453-z","title":"Investigating female versus male differences in white matter neuroplasticity associated with complex visuo-motor learning","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia; Simon Fraser University","funders":"CIHR Skin Research Training Centre; University of British Columbia Graduate School; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; Michael Smith Health Research BC; University of British Columbia; Government of Canada","keywords":"Neuroplasticity; White matter; Corpus callosum; Brain Structure and Function; Psychology; Fractional anisotropy; Corticospinal tract; Motor learning; Myelin; Medicine; Physiology; Magnetic resonance imaging; Neuroscience; Neuroimaging; Diffusion MRI; Central nervous system","score_opus":0.09555926935103116,"score_gpt":0.33556858165550957,"score_spread":0.24000931230447842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392637325","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99725807,0.00061695743,0.00062348833,0.000105829844,0.000018655224,0.000012418017,0.0003115315,0.000007805446,0.0010452289],"genre_scores_gemma":[0.9960969,0.0003241261,0.000634263,0.00006404469,0.000016877962,0.000025711804,0.00020996763,0.000010222641,0.0026178136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986434,0.000018576022,0.000008426725,0.00006216509,0.00002701821,0.000019344174],"domain_scores_gemma":[0.999673,0.000049760885,0.00014584769,0.000024689092,0.000062318424,0.000044376164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037058792,0.00024643575,0.00019799364,0.0003170747,0.00020621887,0.00025816218,0.0001429621,0.00020755334,0.0032728687],"category_scores_gemma":[0.0008487595,0.00009363431,0.00014501925,0.00014346355,0.0002134874,0.0002257564,0.00016619828,0.00017840615,0.00041992823],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017436713,0.0004814736,0.82221633,0.00021686197,0.0001877765,0.0012660442,0.0013352334,0.00015413275,0.08588166,0.000495769,0.0010830595,0.08493791],"study_design_scores_gemma":[0.00001005453,0.00081754563,0.99249154,0.000017012038,0.000043217176,0.0010309973,0.00035628173,0.00011570735,0.0037123584,0.00016949522,0.0012281835,0.000007692713],"about_ca_topic_score_codex":0.00080620655,"about_ca_topic_score_gemma":0.001383699,"teacher_disagreement_score":0.0032728687,"about_ca_system_score_codex":0.00012298978,"about_ca_system_score_gemma":0.0001831059,"threshold_uncertainty_score":0.010948837},"labels":[],"label_agreement":null},{"id":"W4392697010","doi":"10.1371/journal.pone.0300139","title":"White matter microstructure in transmasculine and cisgender adolescents: A multiparametric and multivariate study","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Douglas Mental Health University Institute; Centre for Addiction and Mental Health; University of Toronto","funders":"University of Toronto; Canadian Institutes of Health Research; Department of Psychiatry, University of Toronto; Centre for Addiction and Mental Health Foundation","keywords":"Fractional anisotropy; Diffusion MRI; Transgender; White matter; Psychology; Multivariate analysis; Multivariate statistics; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.07905843093316198,"score_gpt":0.3259788032646483,"score_spread":0.2469203723314863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392697010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99977285,0.000028737926,0.000109633096,0.000004276427,4.943615e-7,0.0000015834902,0.000031287294,0.0000011332236,0.000050035636],"genre_scores_gemma":[0.9997222,0.00002221898,0.00013957868,0.0000028913653,0.0000016251976,0.0000033338877,0.000051631363,0.0000018282313,0.000054670385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997918,0.000060329516,0.000017927157,0.0000622726,0.000033409076,0.000034356763],"domain_scores_gemma":[0.9995214,0.00007429893,0.0002059803,0.00006600801,0.000047272697,0.000084956824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045765127,0.00028465496,0.00023513449,0.00060884055,0.00022942707,0.00039940362,0.00017947286,0.00022010904,0.0007961297],"category_scores_gemma":[0.0009843465,0.00012578123,0.0003231973,0.00042694245,0.00023781616,0.00026198968,0.00041823773,0.00033645492,0.00010293139],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001943194,0.00006151009,0.99136835,0.000010700538,0.00007851468,0.00014933509,0.0004933938,0.000075626594,0.0027477182,0.000051588402,0.00003372349,0.004735204],"study_design_scores_gemma":[0.0000019553281,0.00010430456,0.9985061,0.0000030573751,0.000027541028,0.00027303345,0.00033967028,0.00028671545,0.00033609357,0.000027367594,0.00009124289,0.0000028216673],"about_ca_topic_score_codex":0.0020085282,"about_ca_topic_score_gemma":0.0030556398,"teacher_disagreement_score":0.0020085282,"about_ca_system_score_codex":0.00015668057,"about_ca_system_score_gemma":0.00018763007,"threshold_uncertainty_score":0.0039937496},"labels":[],"label_agreement":null},{"id":"W4392765341","doi":"10.1016/j.neurobiolaging.2024.02.014","title":"Brain age of rhesus macaques over the lifespan","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute on Aging; Mitacs; Canadian Institutes of Health Research; National Institutes of Health; Liverpool University Hospitals NHS Foundation Trust; Brain and Behavior Research Foundation","keywords":"Macaque; Neuroimaging; Human brain; Neuroscience; Rhesus macaque; Cortex (anatomy); Brain morphometry; Primate; Psychology; Magnetic resonance imaging; Biology; Medicine","score_opus":0.05033033103707092,"score_gpt":0.36869562510107934,"score_spread":0.31836529406400843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392765341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975805,0.00030623958,0.0013467186,0.000049880895,0.0000034086038,0.000004479026,0.0002367393,0.000023811996,0.00044815638],"genre_scores_gemma":[0.9982481,0.00014230445,0.0010321058,0.000015419135,0.0000028754898,0.000010576061,0.00016371068,0.0000071630584,0.00037778288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999925,0.000018262539,0.0000028918441,0.000035311445,0.0000095860905,0.000009012438],"domain_scores_gemma":[0.99973637,0.000066792425,0.00008862292,0.000039334656,0.00004628951,0.000022560265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003963813,0.00017953414,0.00018500176,0.00054707396,0.00020102103,0.00022269393,0.00012287396,0.00019232447,0.0004243881],"category_scores_gemma":[0.0010481457,0.00008982894,0.00018952468,0.00012219917,0.00023249832,0.00019695784,0.00022425978,0.00020035931,0.00017968417],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005326522,0.000111444344,0.7789767,0.0000816214,0.00028856788,0.00063308905,0.0018215742,0.010869934,0.13536848,0.0014369574,0.0011984259,0.06868058],"study_design_scores_gemma":[0.000003750851,0.0002860688,0.97280836,0.000012390712,0.00007038445,0.00080830697,0.00023382636,0.016631728,0.005879712,0.0014111199,0.0018345935,0.000019799092],"about_ca_topic_score_codex":0.006547796,"about_ca_topic_score_gemma":0.006337105,"teacher_disagreement_score":0.006547796,"about_ca_system_score_codex":0.00024131192,"about_ca_system_score_gemma":0.00014543912,"threshold_uncertainty_score":0.013019383},"labels":[],"label_agreement":null},{"id":"W4392774425","doi":"10.1177/08830738241231343","title":"Structural Alterations of the Corpus Callosum in Children With Infantile Hydrocephalus","year":2024,"lang":"en","type":"article","venue":"Journal of Child Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Academic Medical Organization of Southwestern Ontario","keywords":"Corpus callosum; Diffusion MRI; Hydrocephalus; Magnetic resonance imaging; Psychology; Medicine; Neuroscience; Radiology; Psychiatry","score_opus":0.014382791236022189,"score_gpt":0.2956051249925846,"score_spread":0.2812223337565624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392774425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995523,0.00015528373,0.00004802384,0.000019182526,0.0000019213676,0.0000032414719,0.000050857023,0.000004204039,0.00016487688],"genre_scores_gemma":[0.99934334,0.00023996532,0.00023646973,0.000010379674,0.000004777207,0.0000065717486,0.00008516898,0.0000027540325,0.000070574635],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997811,0.000035552068,0.000021908176,0.00005501908,0.00005893922,0.000047442125],"domain_scores_gemma":[0.9991943,0.00014188362,0.0004590357,0.000038384955,0.00007523447,0.000091095564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002998129,0.00042824927,0.00033022702,0.0016158189,0.00038437065,0.00042975196,0.00027071085,0.00041027475,0.00097346306],"category_scores_gemma":[0.00184018,0.00021354074,0.00015965308,0.00066850096,0.0007394362,0.00051445374,0.00046452112,0.00033321558,0.00012891846],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022507145,0.000041120187,0.97063655,0.000083385785,0.00004531359,0.006580717,0.0019816898,0.00015666717,0.009356658,0.000080319915,0.0002161306,0.010596276],"study_design_scores_gemma":[0.0000024980604,0.00008229563,0.99100643,0.000011116651,0.000014312324,0.007214284,0.00078402227,0.000052747313,0.00061472855,0.000021921664,0.00019087121,0.000004604418],"about_ca_topic_score_codex":0.004469583,"about_ca_topic_score_gemma":0.005887166,"teacher_disagreement_score":0.004469583,"about_ca_system_score_codex":0.00030382615,"about_ca_system_score_gemma":0.0004168963,"threshold_uncertainty_score":0.008887112},"labels":[],"label_agreement":null},{"id":"W4392922065","doi":"10.1002/nbm.5142","title":"ComBating inter‐site differences in field strength: harmonizing preclinical traumatic brain injury MRI data","year":2024,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Island University","funders":"National Institute of Neurological Disorders and Stroke; National Health and Medical Research Council","keywords":"Traumatic brain injury; Medicine; Corpus callosum; Magnetic resonance imaging; Nuclear medicine; Neuroimaging; Effective diffusion coefficient; Diffusion MRI; Radiology; Pathology","score_opus":0.3168383269899163,"score_gpt":0.4728099251554381,"score_spread":0.1559715981655218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392922065","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6104476,0.0007969408,0.38468754,0.0003178959,0.000109046036,0.00050597324,0.00067590293,0.0010705659,0.0013886989],"genre_scores_gemma":[0.7525223,0.0003731888,0.24328855,0.00024738364,0.0000648257,0.0006299658,0.0019118969,0.00044475409,0.0005171259],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9956786,0.0018627418,0.0003367588,0.00084568234,0.0010871848,0.000189063],"domain_scores_gemma":[0.9931726,0.0023292657,0.0012154771,0.0018941836,0.001192576,0.00019590446],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.014828792,0.00093640015,0.0013469883,0.0015933834,0.00041106128,0.0011716651,0.0010389428,0.0006047356,0.0007182128],"category_scores_gemma":[0.020324945,0.00077136233,0.001036252,0.0013082187,0.0008122006,0.0014108823,0.0018819369,0.0009819387,0.00030357423],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0048782225,0.001588669,0.118329555,0.0012443957,0.0045733494,0.00047602787,0.0018023142,0.08444601,0.30098683,0.004128337,0.0031838792,0.4743623],"study_design_scores_gemma":[0.00055492297,0.010100629,0.4470237,0.00028949775,0.0031535628,0.00194883,0.0013319474,0.32829744,0.15717688,0.027559305,0.022107968,0.0004553264],"about_ca_topic_score_codex":0.0010575464,"about_ca_topic_score_gemma":0.0022731458,"teacher_disagreement_score":0.9851712,"about_ca_system_score_codex":0.00030018244,"about_ca_system_score_gemma":0.00096050114,"threshold_uncertainty_score":0.07842308},"labels":[],"label_agreement":null},{"id":"W4393097549","doi":"10.1101/2024.03.20.24304650","title":"Dissociation of white matter bundles in different recovery measures in post-stroke aphasia","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Eisai; Heart and Stroke Foundation of Canada","keywords":"Aphasia; White matter; Psychology; Dissociation (chemistry); Stroke (engine); Physical medicine and rehabilitation; Cognitive psychology; Medicine; Physics; Chemistry; Radiology","score_opus":0.042691644698238385,"score_gpt":0.328216887312799,"score_spread":0.28552524261456064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393097549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994911,0.000100367935,0.00016245354,0.000008889195,9.795917e-7,0.0000046706928,0.0000830764,0.000007645357,0.00014089193],"genre_scores_gemma":[0.999603,0.0000260578,0.00010602436,0.000003951285,0.0000018280238,0.000004599668,0.00011319726,0.0000021133837,0.00013930541],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980634,0.000038638966,0.000025087716,0.000054243552,0.000033087406,0.000042674223],"domain_scores_gemma":[0.9986829,0.00024106995,0.00064393494,0.000090291716,0.00017578114,0.00016592609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000657381,0.00031844096,0.00024177137,0.001120294,0.00019802742,0.00052025955,0.0002203938,0.00039674836,0.0018535622],"category_scores_gemma":[0.002481205,0.00014921305,0.0002197228,0.00047558814,0.00033974508,0.00061323104,0.00040276465,0.0002873079,0.00044284173],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010112021,0.00009316825,0.97782636,0.000034542976,0.00014316491,0.0004472112,0.0003672509,0.00033851975,0.01023538,0.000043585696,0.000109056724,0.009350431],"study_design_scores_gemma":[0.0000027317587,0.00009651663,0.99872017,0.0000033615693,0.000010249866,0.00027045174,0.000071965216,0.00034080798,0.00038408895,0.000061213184,0.00003629031,0.0000022842423],"about_ca_topic_score_codex":0.0031818044,"about_ca_topic_score_gemma":0.0038370339,"teacher_disagreement_score":0.0031818044,"about_ca_system_score_codex":0.00019190446,"about_ca_system_score_gemma":0.00017631844,"threshold_uncertainty_score":0.006326616},"labels":[],"label_agreement":null},{"id":"W4393111973","doi":"10.1002/hbm.26665","title":"Structural brain networks correlating with poststroke cognition","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council; Commonwealth Scientific and Industrial Research Organisation; Orionin Tutkimussäätiö; Signe ja Ane Gyllenbergin Säätiö; University of Queensland; Suomen Kulttuurirahasto","keywords":"Cognition; Connectome; Psychology; Montreal Cognitive Assessment; Diffusion MRI; Stroke (engine); White matter; Cognitive decline; Tractography; Neuroimaging; Neuroscience; Magnetic resonance imaging; Physical medicine and rehabilitation; Medicine; Dementia; Pathology; Disease; Radiology; Cognitive impairment; Functional connectivity","score_opus":0.06775704452473501,"score_gpt":0.34491150193225734,"score_spread":0.2771544574075223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393111973","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995598,0.000060153754,0.00011005164,0.0000180737,9.529381e-7,0.00000278211,0.000088961366,0.000003830432,0.00015536413],"genre_scores_gemma":[0.9996481,0.000036923957,0.000080771184,0.0000051272323,0.000003687063,0.0000035547828,0.00015228831,8.4512203e-7,0.000068631176],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.000018854102,0.000010323651,0.000030494237,0.000014992758,0.000032670923],"domain_scores_gemma":[0.9992224,0.00012141083,0.00040795509,0.00007574357,0.000067210494,0.00010532835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028044885,0.00021406403,0.00023032767,0.00065705285,0.00026747977,0.0004183548,0.00018285014,0.0003473809,0.0010625209],"category_scores_gemma":[0.0015985789,0.00013822601,0.00023816289,0.00046849373,0.0002646271,0.0003574968,0.00037300467,0.0003066717,0.00013613625],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032191,0.00006107988,0.9917046,0.000011826228,0.00012131048,0.00015710275,0.0001298875,0.00035225172,0.0024459932,0.00006951661,0.00009755662,0.004526933],"study_design_scores_gemma":[0.0000023825748,0.000045685796,0.999363,0.0000011275306,0.000011040201,0.00009447324,0.000033668894,0.00024969052,0.000089686335,0.00007616301,0.000031390675,0.000001740697],"about_ca_topic_score_codex":0.0043845423,"about_ca_topic_score_gemma":0.010540905,"teacher_disagreement_score":0.0043845423,"about_ca_system_score_codex":0.00023081835,"about_ca_system_score_gemma":0.0002683495,"threshold_uncertainty_score":0.008718073},"labels":[],"label_agreement":null},{"id":"W4393119485","doi":"10.1002/hbm.26654","title":"White adipose tissue distribution and amount are associated with increased white matter connectivity","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"White matter; Adipose tissue; Connectome; Orbitofrontal cortex; White adipose tissue; Prefrontal cortex; Anterior cingulate cortex; Insula; Psychology; Neuroscience; Nucleus accumbens; Medicine; Endocrinology; Magnetic resonance imaging; Cognition; Central nervous system; Functional connectivity; Radiology","score_opus":0.03683830063534014,"score_gpt":0.3110238852919262,"score_spread":0.27418558465658605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393119485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962353,0.00063447026,0.0019992692,0.00010774233,0.000010033418,0.0000059368926,0.00030001666,0.000023052784,0.00068419613],"genre_scores_gemma":[0.9984509,0.00022922475,0.00078899256,0.000024328987,0.000012411819,0.000008502928,0.00024089399,0.000011922792,0.00023283584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987304,0.000025486313,0.000012350238,0.000055313565,0.000016400649,0.000017339398],"domain_scores_gemma":[0.99938095,0.0001756353,0.00029405078,0.000055591354,0.00003946757,0.00005436213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021733898,0.00029537812,0.0002218003,0.0006178961,0.00019248445,0.00037453935,0.00013904124,0.00024199899,0.0022875518],"category_scores_gemma":[0.0012918056,0.00015693386,0.00029127256,0.00053453766,0.00026353792,0.00030259293,0.00037945982,0.00034019965,0.00013916525],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013771139,0.00010631955,0.9045316,0.0002335278,0.0013788308,0.0009335466,0.00040812284,0.0021218918,0.052837055,0.0012789002,0.00073506194,0.034058075],"study_design_scores_gemma":[0.000007970895,0.00005838351,0.99464524,0.000016815831,0.0001537054,0.0008818851,0.00009097837,0.0017275796,0.0010628763,0.0009995074,0.00034680753,0.000008246726],"about_ca_topic_score_codex":0.0016599576,"about_ca_topic_score_gemma":0.0029145207,"teacher_disagreement_score":0.0022875518,"about_ca_system_score_codex":0.000104956605,"about_ca_system_score_gemma":0.00009736094,"threshold_uncertainty_score":0.0076525807},"labels":[],"label_agreement":null},{"id":"W4393255309","doi":"10.1016/j.xcrp.2024.101892","title":"Quantifying synergy and redundancy between networks","year":2024,"lang":"en","type":"article","venue":"Cell Reports Physical Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Max-Planck-Institut für Mathematik in den Naturwissenschaften; Gates Cambridge Trust; Max-Planck-Gesellschaft; Universiteit van Amsterdam; German-Israeli Foundation for Scientific Research and Development; Tel Aviv University; University of Kent; McGill University; Bill and Melinda Gates Foundation","keywords":"Computer science; Range (aeronautics); Redundancy (engineering); Complex network; Key (lock); Network topology; Distributed computing; Data science; Theoretical computer science; Topology (electrical circuits); Computer network; Mathematics; Engineering; Computer security","score_opus":0.0735377796238917,"score_gpt":0.3862345241926942,"score_spread":0.31269674456880253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393255309","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31685144,0.0025952726,0.6675636,0.0009398191,0.000062504536,0.000103384984,0.0012985301,0.00055787794,0.010027539],"genre_scores_gemma":[0.9240161,0.00068829535,0.07376957,0.000077263496,0.000085560576,0.00009683936,0.0005680782,0.000052319196,0.0006460641],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99760205,0.00080770656,0.00017728396,0.0005875375,0.0006270229,0.00019840873],"domain_scores_gemma":[0.98804396,0.0067183455,0.0021812634,0.001633395,0.0009561642,0.00046688912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030616564,0.0008888647,0.0009967744,0.005973967,0.00062766526,0.002044738,0.0010815999,0.0008901551,0.0017589211],"category_scores_gemma":[0.017999513,0.0005797548,0.0006988691,0.0030544288,0.0018708176,0.0045699347,0.0026773585,0.0007261947,0.00028328397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037924876,0.000107277694,0.07790632,0.001313161,0.0014526255,0.0011619906,0.0019342895,0.32007635,0.030818487,0.3606688,0.0046827644,0.19949874],"study_design_scores_gemma":[0.00002048667,0.00015050828,0.036118936,0.00016702333,0.00037639576,0.0010381714,0.000606671,0.45858037,0.003849884,0.49317002,0.005826675,0.00009482385],"about_ca_topic_score_codex":0.0012004622,"about_ca_topic_score_gemma":0.0013631255,"teacher_disagreement_score":0.005973967,"about_ca_system_score_codex":0.0008581456,"about_ca_system_score_gemma":0.0007053609,"threshold_uncertainty_score":0.01619178},"labels":[],"label_agreement":null},{"id":"W4393270801","doi":"10.1002/hbm.26635","title":"The superior frontal sulcus in the human brain: Morphology and probability maps","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Sulcus; Central sulcus; Precentral gyrus; Brain morphometry; Neuroimaging; Inferior frontal gyrus; Human brain; Middle frontal gyrus; Frontal lobe; Neuroscience; Anatomy; Brain mapping; Superior temporal sulcus; Magnetic resonance imaging; Psychology; Biology; Medicine; Functional magnetic resonance imaging; Radiology","score_opus":0.08155849015715583,"score_gpt":0.35504833923048357,"score_spread":0.27348984907332774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393270801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8323912,0.004873358,0.15106642,0.0004072113,0.0000146120865,0.00012599165,0.0016755366,0.00040033608,0.009045413],"genre_scores_gemma":[0.98117834,0.0010883213,0.016988313,0.0000106246725,0.000016242491,0.000026121954,0.00034743248,0.0000324762,0.0003121537],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9997663,0.000074137264,0.000018564444,0.000048916998,0.00008047777,0.000011566578],"domain_scores_gemma":[0.99933285,0.00034106337,0.00015401693,0.000073889394,0.00007332249,0.00002482606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067950157,0.00022392349,0.00017816952,0.0029133374,0.00017868177,0.00088048296,0.00019663792,0.00020735276,0.0014476782],"category_scores_gemma":[0.0037633898,0.00015946533,0.00019297769,0.0027825402,0.0013010293,0.00078296184,0.00034932667,0.00012992993,0.00024130156],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055737677,0.00004521747,0.2822666,0.000707465,0.00034943703,0.0016095588,0.0034448442,0.05193774,0.045715235,0.03731963,0.0032338996,0.5728129],"study_design_scores_gemma":[0.00001574344,0.00010707092,0.90909886,0.000051020816,0.000049052484,0.004245742,0.00047789756,0.03385584,0.0031605947,0.042844117,0.0060489075,0.00004503722],"about_ca_topic_score_codex":0.0064959,"about_ca_topic_score_gemma":0.005598044,"teacher_disagreement_score":0.0064959,"about_ca_system_score_codex":0.00039411924,"about_ca_system_score_gemma":0.0003935617,"threshold_uncertainty_score":0.012916148},"labels":[],"label_agreement":null},{"id":"W4393276331","doi":"10.3389/fnimg.2024.1359589","title":"Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Nuclear medicine; Magnetic resonance imaging; Sampling (signal processing); Medicine; Nuclear magnetic resonance; Physics; Radiology; Optics","score_opus":0.06528717279994371,"score_gpt":0.3495831204202306,"score_spread":0.28429594762028687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393276331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96974844,0.0025047383,0.026694328,0.00006418771,0.000026994554,0.00008295994,0.00024304716,0.000071292176,0.00056400325],"genre_scores_gemma":[0.9818094,0.0006742328,0.016584212,0.000027778,0.00005151821,0.000057153407,0.00044949495,0.00006809438,0.0002781587],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857175,0.00067568535,0.000169563,0.00033019224,0.00018364824,0.00006921007],"domain_scores_gemma":[0.994148,0.0023044283,0.0015645295,0.0010085959,0.0006927759,0.00028170002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060687405,0.00069158536,0.0006155754,0.0013363131,0.00037609844,0.00076816994,0.00045044717,0.00040634893,0.0007828227],"category_scores_gemma":[0.010830365,0.00024493705,0.0004825166,0.0010101718,0.000509099,0.0006993145,0.00063812744,0.0003184452,0.00026019462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0044165347,0.00036120586,0.74194664,0.0006677063,0.0011216806,0.0018529693,0.001378035,0.007823628,0.09225512,0.0014994142,0.0007877207,0.14588945],"study_design_scores_gemma":[0.00014289487,0.003262112,0.8492282,0.00017217209,0.0014713821,0.009539991,0.0004604267,0.07357474,0.050117053,0.0029308652,0.008999857,0.000100297584],"about_ca_topic_score_codex":0.0014799484,"about_ca_topic_score_gemma":0.0012435628,"teacher_disagreement_score":0.0060687405,"about_ca_system_score_codex":0.00025405173,"about_ca_system_score_gemma":0.00033825374,"threshold_uncertainty_score":0.032094955},"labels":[],"label_agreement":null},{"id":"W4393388452","doi":"10.1007/s11682-024-00876-9","title":"Sleep disturbances, altered brain microstructure and chronic headache in youth","year":2024,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Alberta Bone and Joint Health Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Actigraphy; Medicine; Cingulum (brain); White matter; Diffusion MRI; Chronic pain; Pittsburgh Sleep Quality Index; Physical therapy; Psychology; Audiology; Internal medicine; Insomnia; Psychiatry; Magnetic resonance imaging; Radiology; Sleep quality","score_opus":0.03210649844894815,"score_gpt":0.33879631179786107,"score_spread":0.30668981334891293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393388452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99822646,0.0009934147,0.000053592616,0.000063134234,0.0000068529826,0.0000048988713,0.00016696734,0.0000032203782,0.00048142663],"genre_scores_gemma":[0.9986486,0.00076215365,0.00009057382,0.000022144986,0.000020310144,0.000004098239,0.00017912166,0.0000017278923,0.0002713016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998988,0.000015643953,0.0000134059665,0.000019288434,0.000019050305,0.000033814955],"domain_scores_gemma":[0.9996947,0.0000395625,0.00015972437,0.0000075113353,0.000029477,0.00006912145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021043817,0.00021056781,0.00025924522,0.00091986737,0.00036397658,0.0004778814,0.00018694648,0.00031516814,0.001524393],"category_scores_gemma":[0.0007944718,0.00017400394,0.00019775043,0.0007958023,0.00035967835,0.00033066364,0.00029652083,0.000259377,0.00011457686],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012699488,0.00006379465,0.99236214,0.00002599703,0.000028679951,0.0011410117,0.00021146012,0.000035992005,0.00073072914,0.00007843606,0.0001318596,0.0050628274],"study_design_scores_gemma":[0.0000017696701,0.000036586873,0.9988689,0.000005580702,0.000009225932,0.0007685844,0.00015372962,0.000035364825,0.00003519119,0.000027996964,0.000056219273,8.5667926e-7],"about_ca_topic_score_codex":0.013001906,"about_ca_topic_score_gemma":0.021118278,"teacher_disagreement_score":0.013001906,"about_ca_system_score_codex":0.00032249707,"about_ca_system_score_gemma":0.00046346957,"threshold_uncertainty_score":0.025852501},"labels":[],"label_agreement":null},{"id":"W4393507590","doi":"10.5281/zenodo.7608831","title":"Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – The Vogt-Vogt legacy in the 21st century","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroimaging; Neuroscience; Psychology","score_opus":0.17712244695351662,"score_gpt":0.3626593921002978,"score_spread":0.18553694514678118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393507590","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00451624,0.0010528257,0.0022673572,0.00035508684,0.00010156981,0.000054934073,0.98826015,0.0022321516,0.0011597242],"genre_scores_gemma":[0.0054316088,0.00032280775,0.002804569,0.000116175885,0.000025075056,0.00023040501,0.9898519,0.00023317143,0.0009841785],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895144,0.00015812556,0.00010694801,0.0003792559,0.00023142072,0.00017289523],"domain_scores_gemma":[0.9985588,0.0003012428,0.00016283753,0.0005105014,0.00032738887,0.00013922811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013773489,0.0022223261,0.0015649974,0.0024120994,0.000770219,0.0020743862,0.0036969585,0.0027802095,0.013067594],"category_scores_gemma":[0.004513526,0.00067340006,0.0017873199,0.003396196,0.0009936701,0.00091922295,0.0025717865,0.0020079424,0.024211446],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042345817,0.00010268222,0.0043230853,0.0020870215,0.00024771056,0.00028799727,0.00014375968,0.0031651559,0.0018022194,0.0018226393,0.95665115,0.028943092],"study_design_scores_gemma":[0.00051964103,0.000099835226,0.025757065,0.00092999224,0.00024540463,0.001584064,0.000292807,0.004437016,0.0037424592,0.009776391,0.9524583,0.0001569718],"about_ca_topic_score_codex":0.025738455,"about_ca_topic_score_gemma":0.06774481,"teacher_disagreement_score":0.025738455,"about_ca_system_score_codex":0.0016501208,"about_ca_system_score_gemma":0.002676472,"threshold_uncertainty_score":0.051177263},"labels":[],"label_agreement":null},{"id":"W4393598281","doi":"10.5281/zenodo.10458910","title":"White matter multi-scale dataset: Diffusion weighted MRI and synchrotron x-ray scans of vervet monkey-, healthy mouse-, and cuprizone mouse brains","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Synchrotron; Diffusion MRI; Diffusion; Nuclear magnetic resonance; Nuclear medicine; Anatomy; Biology; Magnetic resonance imaging; Physics; Medicine; Optics; Radiology","score_opus":0.04484241246136825,"score_gpt":0.316662184498596,"score_spread":0.27181977203722774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393598281","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014549376,0.0001977967,0.00088409433,0.00016456169,0.000066689354,0.00004531242,0.99435025,0.0017839008,0.0010524833],"genre_scores_gemma":[0.0012892715,0.00008538921,0.0011948989,0.00006396674,0.000011936498,0.00011476051,0.9962412,0.0002349049,0.00076373486],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994253,0.000084367835,0.00006945511,0.00018311587,0.00015238511,0.00008542294],"domain_scores_gemma":[0.9984901,0.00027455683,0.00014528773,0.00052990246,0.0003428619,0.000217315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014422019,0.0026779098,0.0017175113,0.002221845,0.0010197287,0.0019232286,0.0040319855,0.0027180898,0.039886024],"category_scores_gemma":[0.0034544459,0.00076044083,0.0012081291,0.0030829723,0.0006540826,0.0008950654,0.002174303,0.0019815632,0.066567175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002514257,0.00009118705,0.0013054899,0.0011118973,0.00013003265,0.00017325347,0.00005579221,0.0004991939,0.001404062,0.0005386025,0.9884594,0.005979751],"study_design_scores_gemma":[0.0007636332,0.00014193988,0.020388648,0.000625664,0.00021620016,0.0017523809,0.00021164375,0.0016974165,0.0060608997,0.0064119548,0.9616003,0.00012944014],"about_ca_topic_score_codex":0.009625894,"about_ca_topic_score_gemma":0.028979944,"teacher_disagreement_score":0.039886024,"about_ca_system_score_codex":0.0012519999,"about_ca_system_score_gemma":0.0020191704,"threshold_uncertainty_score":0.13343203},"labels":[],"label_agreement":null},{"id":"W4393610770","doi":"10.5281/zenodo.10458911","title":"White matter multi-scale dataset: Diffusion weighted MRI and synchrotron x-ray scans of vervet monkey-, healthy mouse-, and cuprizone mouse brains","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Synchrotron; Diffusion MRI; Anatomy; Biology; Nuclear medicine; Magnetic resonance imaging; Physics; Medicine; Optics; Radiology","score_opus":0.04484241246136825,"score_gpt":0.316662184498596,"score_spread":0.27181977203722774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393610770","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014549376,0.0001977967,0.00088409433,0.00016456169,0.000066689354,0.00004531242,0.99435025,0.0017839008,0.0010524833],"genre_scores_gemma":[0.0012892715,0.00008538921,0.0011948989,0.00006396674,0.000011936498,0.00011476051,0.9962412,0.0002349049,0.00076373486],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994253,0.000084367835,0.00006945511,0.00018311587,0.00015238511,0.00008542294],"domain_scores_gemma":[0.9984901,0.00027455683,0.00014528773,0.00052990246,0.0003428619,0.000217315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014422019,0.0026779098,0.0017175113,0.002221845,0.0010197287,0.0019232286,0.0040319855,0.0027180898,0.039886024],"category_scores_gemma":[0.0034544459,0.00076044083,0.0012081291,0.0030829723,0.0006540826,0.0008950654,0.002174303,0.0019815632,0.066567175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002514257,0.00009118705,0.0013054899,0.0011118973,0.00013003265,0.00017325347,0.00005579221,0.0004991939,0.001404062,0.0005386025,0.9884594,0.005979751],"study_design_scores_gemma":[0.0007636332,0.00014193988,0.020388648,0.000625664,0.00021620016,0.0017523809,0.00021164375,0.0016974165,0.0060608997,0.0064119548,0.9616003,0.00012944014],"about_ca_topic_score_codex":0.009625894,"about_ca_topic_score_gemma":0.028979944,"teacher_disagreement_score":0.039886024,"about_ca_system_score_codex":0.0012519999,"about_ca_system_score_gemma":0.0020191704,"threshold_uncertainty_score":0.13343203},"labels":[],"label_agreement":null},{"id":"W4393711011","doi":"10.5281/zenodo.8339143","title":"Painting a more complete picture of white matter microstructure with myelin water and tensor valued diffusion","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Anisotropy; Myelin; Microstructure; Fractional anisotropy; Painting; Materials science; Mineralogy; Chemistry; Physics; Psychology; White matter; Composite material; Art; Optics; Neuroscience; Art history; Medicine; Central nervous system","score_opus":0.04305434030819109,"score_gpt":0.28672485766181505,"score_spread":0.24367051735362397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393711011","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00060837646,0.00026194958,0.0006365888,0.00026686094,0.00014882981,0.00003937866,0.99519545,0.0012122948,0.0016302246],"genre_scores_gemma":[0.0016314944,0.00015719791,0.0018352281,0.00020587744,0.000042164316,0.00013716433,0.99325776,0.00028543698,0.0024476883],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99933547,0.00010888995,0.00007199383,0.00020489743,0.00016975061,0.00010901173],"domain_scores_gemma":[0.9981964,0.00037643051,0.00015966395,0.00061006995,0.00047657124,0.00018081238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001148511,0.002300177,0.0014546681,0.0022644028,0.0006042534,0.0019950457,0.002341,0.0022525492,0.11842749],"category_scores_gemma":[0.005348428,0.0006879898,0.0017350279,0.0031837225,0.00047553785,0.0012965463,0.0021527985,0.0019841073,0.122953534],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085583495,0.000030114057,0.00061454944,0.00052893645,0.00004343125,0.000040999937,0.000017540733,0.0002599471,0.00035254107,0.0003496723,0.992663,0.0050138216],"study_design_scores_gemma":[0.00046522374,0.000050987983,0.008419283,0.00048124578,0.000078875615,0.000469036,0.00007159161,0.000828743,0.0015098865,0.0052331234,0.98232645,0.000065533706],"about_ca_topic_score_codex":0.010172898,"about_ca_topic_score_gemma":0.03392583,"teacher_disagreement_score":0.11842749,"about_ca_system_score_codex":0.00095667306,"about_ca_system_score_gemma":0.0015695961,"threshold_uncertainty_score":0.39617938},"labels":[],"label_agreement":null},{"id":"W4393905672","doi":"10.59275/j.melba.2024-267f","title":"Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Mesh Variational Autoencoder with Contrastive Learning","year":2024,"lang":"en","type":"preprint","venue":"The Journal of Machine Learning for Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Canadian Institutes of Health Research; Women and Children's Health Research Institute; Canada Research Chairs; Children's Health Research Institute","keywords":"Autoencoder; Hippocampal formation; Neuroscience; Psychology; Graph; Artificial intelligence; Pattern recognition (psychology); Medicine; Computer science; Deep learning; Theoretical computer science","score_opus":0.03634657959718149,"score_gpt":0.3565907821513885,"score_spread":0.32024420255420705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393905672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45410436,0.0026832735,0.54025346,0.00076164363,0.00007397104,0.00004559279,0.00045064435,0.0003609665,0.001266106],"genre_scores_gemma":[0.9424269,0.0006140947,0.054413803,0.00013149585,0.000055828095,0.000026319067,0.0007638328,0.00007875667,0.0014889651],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973506,0.000091446105,0.000014268104,0.0000946697,0.000038416096,0.000026113637],"domain_scores_gemma":[0.9988778,0.00076414616,0.00010525397,0.00011833266,0.0000910674,0.000043358385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011338515,0.0006791008,0.00039705524,0.0007803545,0.0001557609,0.00042702653,0.0005183507,0.00061358034,0.00046048212],"category_scores_gemma":[0.0038309747,0.00027641444,0.00088817254,0.00038672995,0.00067456136,0.00075332593,0.0006590192,0.0010047877,0.00012209028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005149744,0.00014912966,0.05288216,0.00020002204,0.0006707661,0.0005935819,0.00043353473,0.69236493,0.022325711,0.0073881657,0.0021876667,0.2202893],"study_design_scores_gemma":[0.0000060659554,0.00004610207,0.005811503,0.000014160833,0.000030186018,0.00010971657,0.00003578755,0.9877079,0.0021967834,0.003524287,0.0005059034,0.000011669755],"about_ca_topic_score_codex":0.0060176775,"about_ca_topic_score_gemma":0.0067599057,"teacher_disagreement_score":0.0060176775,"about_ca_system_score_codex":0.00036304284,"about_ca_system_score_gemma":0.00035577474,"threshold_uncertainty_score":0.011965334},"labels":[],"label_agreement":null},{"id":"W4393991482","doi":"10.1093/schbul/sbae037","title":"Distinct Volume Alterations of Thalamic Nuclei Across the Schizophrenia Spectrum","year":2024,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Schizophrenia (object-oriented programming); Psychosis; Thalamus; Cognition; Neuroscience; Psychology; Schizophrenia spectrum; Brain size; Effects of sleep deprivation on cognitive performance; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.02594945853949701,"score_gpt":0.31769348464525154,"score_spread":0.29174402610575456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393991482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99884295,0.00014955617,0.0006020143,0.000014791327,9.241107e-7,0.000003949501,0.00014124869,0.000011210724,0.00023325626],"genre_scores_gemma":[0.99937505,0.00005638418,0.00034191657,0.0000064304163,9.092428e-7,0.0000042889233,0.00012334796,0.0000041731614,0.0000875409],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999027,0.000017189817,0.000008955442,0.000028418459,0.00002866225,0.000014103622],"domain_scores_gemma":[0.9997181,0.000056405363,0.00013821194,0.000023850804,0.000032885615,0.000030413179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022700895,0.00028837158,0.00015236784,0.0007777924,0.00011312505,0.0003163048,0.00019743147,0.00015016123,0.0010241322],"category_scores_gemma":[0.00068057084,0.00013508459,0.00019518257,0.00021150548,0.00041902892,0.00019151055,0.00031621766,0.0001343229,0.00009583994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011987166,0.000048535916,0.66741097,0.00012369565,0.00028767288,0.0010710047,0.00093615305,0.0013756432,0.3042256,0.00064718624,0.00017975672,0.02249514],"study_design_scores_gemma":[0.000011869127,0.00013417717,0.9917355,0.000011910468,0.000032935386,0.0014000762,0.00015881806,0.0006891108,0.005329982,0.0003467528,0.00014215668,0.0000066962534],"about_ca_topic_score_codex":0.0028245167,"about_ca_topic_score_gemma":0.004012749,"teacher_disagreement_score":0.0028245167,"about_ca_system_score_codex":0.0002798228,"about_ca_system_score_gemma":0.00017833165,"threshold_uncertainty_score":0.005616188},"labels":[],"label_agreement":null},{"id":"W4394120694","doi":"10.6084/m9.figshare.7603271","title":"White Matter Tractography Guides","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tractography; White matter; White (mutation); Psychology; Geology; Medicine; Biology; Radiology; Magnetic resonance imaging","score_opus":0.1394907963545433,"score_gpt":0.3862822743998692,"score_spread":0.24679147804532586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394120694","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043642716,0.00023673005,0.0031153595,0.00013971483,0.000056984674,0.00009686286,0.9870459,0.0063732355,0.0024986705],"genre_scores_gemma":[0.0009053046,0.00019856857,0.0069606546,0.000084667976,0.00001784142,0.0006185345,0.9865471,0.0018244098,0.0028429816],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99857354,0.00026194716,0.00019114105,0.0005480867,0.00028480202,0.00014040679],"domain_scores_gemma":[0.9961754,0.0014071056,0.00030936935,0.0012078778,0.0006637119,0.00023652494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022974296,0.0025160704,0.001822718,0.0049044746,0.0012377412,0.003351908,0.0038958201,0.0022663677,0.17721589],"category_scores_gemma":[0.010490071,0.0011520145,0.0021312828,0.005776436,0.00071680977,0.001695068,0.0024952877,0.0027383429,0.21718064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007090636,0.000028226263,0.00072379195,0.00067458145,0.000040853338,0.00006185094,0.00005116017,0.0004985485,0.00030003962,0.0011706532,0.9850263,0.011353005],"study_design_scores_gemma":[0.0002398361,0.000028051729,0.0027740523,0.00037467084,0.0000477486,0.00028715245,0.0000512667,0.0015434898,0.0010758087,0.005688534,0.98784965,0.000039617913],"about_ca_topic_score_codex":0.011233687,"about_ca_topic_score_gemma":0.04299202,"teacher_disagreement_score":0.17721589,"about_ca_system_score_codex":0.0014846135,"about_ca_system_score_gemma":0.0037611215,"threshold_uncertainty_score":0.5928462},"labels":[],"label_agreement":null},{"id":"W4394264727","doi":"10.6084/m9.figshare.12649388","title":"Multimodal adolescent white matter imaging dataset","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.08870218789884723,"score_gpt":0.3644682305331559,"score_spread":0.2757660426343087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394264727","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018823262,0.00029257804,0.0002301648,0.00012599921,0.00003801664,0.0000543736,0.9958818,0.00028810577,0.0012065307],"genre_scores_gemma":[0.0015953124,0.000110910216,0.0005354944,0.000063636406,0.000015262776,0.00012029928,0.99674004,0.00004044694,0.00077849627],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99956757,0.00008366725,0.00004475307,0.00014736429,0.000088879795,0.00006771136],"domain_scores_gemma":[0.9989506,0.00019162359,0.000097500226,0.00019909043,0.00039492187,0.00016620055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009284728,0.0020145492,0.0013395961,0.0019811399,0.0009022567,0.0013572165,0.003055124,0.001660668,0.032597907],"category_scores_gemma":[0.0032291505,0.00044153232,0.00089892896,0.0027515865,0.0003370704,0.00059211283,0.0014493397,0.0013257369,0.0352857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023934271,0.00009348505,0.004451965,0.00063888944,0.000120720484,0.00023557116,0.000048055204,0.00042385323,0.00034394,0.00044625645,0.9839737,0.008984156],"study_design_scores_gemma":[0.0006042332,0.00008986081,0.047711868,0.0005971268,0.00022372488,0.0013349946,0.00022691194,0.001600832,0.0009585985,0.002174806,0.9443956,0.00008140529],"about_ca_topic_score_codex":0.055841472,"about_ca_topic_score_gemma":0.15347531,"teacher_disagreement_score":0.055841472,"about_ca_system_score_codex":0.0012160282,"about_ca_system_score_gemma":0.0020294336,"threshold_uncertainty_score":0.1110329},"labels":[],"label_agreement":null},{"id":"W4394550046","doi":"10.6084/m9.figshare.1216667","title":"CST Mask in ICBM152 space","year":2014,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Space (punctuation); Computer science; Computer graphics (images); Operating system","score_opus":0.1273186298284547,"score_gpt":0.39074171810531044,"score_spread":0.26342308827685573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394550046","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00038329206,0.00008287391,0.00023738734,0.000046704372,0.000032698263,0.000038164428,0.99757993,0.00094860716,0.00065035076],"genre_scores_gemma":[0.0011931257,0.00004867094,0.00075382926,0.000042766307,0.00001493946,0.00024339878,0.9966175,0.00021273013,0.0008730198],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991961,0.00009308771,0.00009617552,0.0003350702,0.00013927753,0.00014036012],"domain_scores_gemma":[0.9984754,0.00032639108,0.00014869604,0.000500113,0.00040865704,0.00014080245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009349483,0.0027336732,0.0016622982,0.002674364,0.00078255386,0.0019222274,0.0035055985,0.0023432672,0.12876254],"category_scores_gemma":[0.0055371732,0.00074251567,0.0017064022,0.0034294326,0.000426557,0.0010375788,0.0018111919,0.0015217997,0.12808977],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018962413,0.000032773252,0.0012287955,0.0006328377,0.00006139227,0.000048519454,0.000026231655,0.00030349827,0.00028647165,0.0003091064,0.9915183,0.0053624636],"study_design_scores_gemma":[0.0006922426,0.000089195986,0.011281507,0.00040193147,0.00012289516,0.00043801218,0.00010919655,0.0011290575,0.0019066097,0.0019647593,0.98180103,0.00006366367],"about_ca_topic_score_codex":0.017685488,"about_ca_topic_score_gemma":0.033081446,"teacher_disagreement_score":0.12876254,"about_ca_system_score_codex":0.0013133091,"about_ca_system_score_gemma":0.002379005,"threshold_uncertainty_score":0.43075365},"labels":[],"label_agreement":null},{"id":"W4394683503","doi":"10.7554/elife.94917","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Mental Health; HORIZON EUROPE Framework Programme; McDonnell Center for Systems Neuroscience; Lundbeckfonden; National Institutes of Health; European Synchrotron Radiation Facility; Deutsches Elektronen-Synchrotron; European Commission; Scleroseforeningen","keywords":"White matter; Corpus callosum; Diffusion MRI; Biology; Voxel; Anatomy; Fractional anisotropy; Tractography; Neuroscience; Evolutionary biology; Magnetic resonance imaging; Medicine; Computer science; Artificial intelligence","score_opus":0.052240007719115585,"score_gpt":0.33678857049714667,"score_spread":0.2845485627780311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394683503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88937604,0.0011161302,0.105783165,0.00017051565,0.00001405806,0.00004224126,0.0006012477,0.00034585167,0.0025507705],"genre_scores_gemma":[0.9066932,0.00085097377,0.09113747,0.000060652004,0.0000102051135,0.00006441181,0.00028704634,0.00018446632,0.0007115531],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997812,0.00005402062,0.000015393689,0.000069386806,0.000052295203,0.000027725344],"domain_scores_gemma":[0.99937266,0.0001596487,0.00022517619,0.00010627404,0.000092888105,0.00004329902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055440114,0.0003866155,0.0002894055,0.0015835236,0.00033213245,0.001345979,0.0003277883,0.0004276031,0.0010455078],"category_scores_gemma":[0.001250892,0.0004084463,0.00026610997,0.00064265914,0.00081038696,0.0008938249,0.0010970926,0.00048592134,0.00022108351],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002481812,0.000032547334,0.022174267,0.00040010604,0.00017241068,0.00045315863,0.0023884976,0.009557878,0.9112228,0.004218125,0.00026368813,0.048868287],"study_design_scores_gemma":[0.000032781878,0.00039715072,0.6543144,0.00042504442,0.0003529658,0.0035804196,0.0021667436,0.0531605,0.24757831,0.020308036,0.017431006,0.00025271488],"about_ca_topic_score_codex":0.0024521193,"about_ca_topic_score_gemma":0.006258611,"teacher_disagreement_score":0.0024521193,"about_ca_system_score_codex":0.0003100797,"about_ca_system_score_gemma":0.00044113075,"threshold_uncertainty_score":0.0048757195},"labels":[],"label_agreement":null},{"id":"W4394691933","doi":"10.7554/elife.94917.1","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bridging (networking); White matter; Geography; Geology; Evolutionary biology; Biology; Computer science; Medicine","score_opus":0.06363895321397584,"score_gpt":0.34557660972726695,"score_spread":0.2819376565132911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394691933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8934999,0.0009069685,0.10227014,0.00015583758,0.000011610076,0.00002951129,0.000502291,0.00032251535,0.00230125],"genre_scores_gemma":[0.9293599,0.00059727073,0.069001265,0.000039763974,0.000009513939,0.000034392673,0.00021028824,0.00012687368,0.0006206448],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998381,0.000044713088,0.000010518434,0.000046402514,0.00004135809,0.000018939465],"domain_scores_gemma":[0.999395,0.0001620882,0.00020976292,0.00009682117,0.00009826478,0.000038023005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045028402,0.00031975398,0.00025044548,0.0017168934,0.0002687046,0.0013009761,0.00026549748,0.0003563136,0.001145341],"category_scores_gemma":[0.0010713578,0.00037437977,0.00021099587,0.00059586036,0.0007456498,0.0007749519,0.00091763126,0.00033454673,0.00023912216],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023278815,0.000025405401,0.017693657,0.00028808924,0.00012357085,0.0003613717,0.0012690302,0.01026876,0.9225396,0.0044217515,0.0002472826,0.04252868],"study_design_scores_gemma":[0.00003352997,0.00031213084,0.6259638,0.00029030157,0.00023034363,0.0034792896,0.001677643,0.07127221,0.2599841,0.02385196,0.012681808,0.00022288378],"about_ca_topic_score_codex":0.0015716524,"about_ca_topic_score_gemma":0.0031997126,"teacher_disagreement_score":0.0017168934,"about_ca_system_score_codex":0.00026639178,"about_ca_system_score_gemma":0.00031019057,"threshold_uncertainty_score":0.0038315058},"labels":[],"label_agreement":null},{"id":"W4394750715","doi":"10.1002/alz.13776","title":"Structural white matter properties and cognitive resilience to tau pathology","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Alzheimer's Society; Fondation Brain Canada; McGill University; National Institutes of Health; Alzheimer's Association","keywords":"White matter; Hyperintensity; Cognition; Psychology; Diffusion MRI; Default mode network; Psychological resilience; Effects of sleep deprivation on cognitive performance; Neuroscience; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.06274017266133386,"score_gpt":0.33435124625811335,"score_spread":0.2716110735967795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394750715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99864787,0.0002865782,0.00030639244,0.000041323357,0.0000037853433,0.0000073057568,0.0002136269,0.000009770134,0.0004833667],"genre_scores_gemma":[0.9992874,0.00008675667,0.00022970205,0.000012658554,0.0000054709835,0.000004888207,0.00012807849,0.0000027161602,0.0002424539],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990165,0.000013130396,0.000011685946,0.000036942307,0.000019026156,0.000017461514],"domain_scores_gemma":[0.99852365,0.00015981517,0.0009771938,0.00009363653,0.00011726566,0.00012858433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005301198,0.0004321585,0.00023311429,0.00091702555,0.00026759147,0.0006637764,0.00025194735,0.00031158215,0.002381393],"category_scores_gemma":[0.0019264725,0.00016305219,0.00026077576,0.00043234802,0.00041089085,0.0005780898,0.00034639542,0.0003607926,0.00022945223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008365647,0.00015950736,0.9734604,0.000089090914,0.0004186878,0.0002767323,0.0003131404,0.00066683104,0.009142327,0.0002517373,0.00020064793,0.014184437],"study_design_scores_gemma":[0.0000040352425,0.00014186461,0.99771994,0.000012713588,0.000049752976,0.00026504556,0.00005926625,0.0002828748,0.00096450414,0.00037515018,0.000119273245,0.000005472251],"about_ca_topic_score_codex":0.0018256683,"about_ca_topic_score_gemma":0.0030276247,"teacher_disagreement_score":0.002381393,"about_ca_system_score_codex":0.00029468953,"about_ca_system_score_gemma":0.00023765136,"threshold_uncertainty_score":0.007966518},"labels":[],"label_agreement":null},{"id":"W4395025790","doi":"10.1162/imag_a_00166","title":"Thalamic nuclei segmentation from T1-weighted MRI: Unifying and benchmarking state-of-the-art methods","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Universität Zürich; Eisai; Eidgenössische Technische Hochschule Zürich; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"Thalamus; Neuroscience; Neuroimaging; Segmentation; Cognition; Human Connectome Project; Brain morphometry; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Computer science; Radiology; Functional connectivity","score_opus":0.04700027216139852,"score_gpt":0.39394381173466353,"score_spread":0.346943539573265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395025790","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34569752,0.030274253,0.5870951,0.0015658771,0.0009760638,0.0015563664,0.005474645,0.017578794,0.009781371],"genre_scores_gemma":[0.5077855,0.0070678904,0.4600499,0.0006537555,0.00032763445,0.00058033457,0.016361244,0.0039669774,0.0032067187],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9956292,0.00090662786,0.0005917712,0.001284994,0.0012671446,0.00032027773],"domain_scores_gemma":[0.9951047,0.0022374208,0.00043232416,0.0007256069,0.0012741382,0.00022592414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008265267,0.002821974,0.0018844769,0.008116708,0.0010903063,0.004719849,0.00318849,0.0032838115,0.0014025604],"category_scores_gemma":[0.018220063,0.0008982281,0.0027586964,0.0027438644,0.001275585,0.002454579,0.0026478171,0.0016527907,0.0012477178],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002379036,0.0004244833,0.028732292,0.0031676707,0.0024047962,0.0006624606,0.0011202336,0.26706204,0.036759224,0.0049578543,0.012320083,0.6400098],"study_design_scores_gemma":[0.00012881344,0.0007032248,0.012763288,0.0004333254,0.00062540086,0.00095329044,0.0004708128,0.9309693,0.036245756,0.0063872393,0.010132581,0.00018694796],"about_ca_topic_score_codex":0.01750298,"about_ca_topic_score_gemma":0.022196107,"teacher_disagreement_score":0.01750298,"about_ca_system_score_codex":0.002020923,"about_ca_system_score_gemma":0.002410505,"threshold_uncertainty_score":0.043711483},"labels":[],"label_agreement":null},{"id":"W4395479506","doi":"10.21203/rs.3.rs-4260180/v1","title":"White Matter Microstructural Lateralization and Links to Language Function in Perinatal Stroke","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Oxford","keywords":"Arcuate fasciculus; Lateralization of brain function; White matter; Uncinate fasciculus; Psychology; Diffusion MRI; Verbal fluency test; Inferior longitudinal fasciculus; Fasciculus; Fluency; Fractional anisotropy; Stroke (engine); Neuroscience; Audiology; Medicine; Magnetic resonance imaging; Neuropsychology; Cognition; Radiology; Physics","score_opus":0.05516237733175905,"score_gpt":0.4333716100701113,"score_spread":0.3782092327383523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395479506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99455947,0.0011756395,0.0006158853,0.0002920893,0.000013251548,0.000009065887,0.00051617774,0.000011582801,0.0028067552],"genre_scores_gemma":[0.99545836,0.0016363624,0.000576941,0.00003789057,0.00002609399,0.000022023063,0.00036354747,0.000018997347,0.0018599407],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989617,0.000021162863,0.000011310694,0.000028675542,0.000020482272,0.000022197533],"domain_scores_gemma":[0.9991763,0.0003728432,0.00025312966,0.00006511952,0.00006300733,0.000069607275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040421187,0.00035848122,0.00018791117,0.0011758792,0.00030289456,0.0007289908,0.00030954983,0.00033654537,0.004395378],"category_scores_gemma":[0.0025449477,0.0002142384,0.000179147,0.00071209675,0.000549755,0.0003888538,0.00047776548,0.00037150638,0.00037360252],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034056308,0.0004453005,0.78121495,0.00054353545,0.00067626016,0.013664427,0.0025575797,0.0025223913,0.07681159,0.0091881165,0.002170481,0.10679985],"study_design_scores_gemma":[0.000014673692,0.00008014587,0.98677814,0.000069308626,0.00009305448,0.0021593608,0.00080218364,0.0006035626,0.004706716,0.004187851,0.00049479835,0.00001026985],"about_ca_topic_score_codex":0.0062759393,"about_ca_topic_score_gemma":0.005919447,"teacher_disagreement_score":0.0062759393,"about_ca_system_score_codex":0.00031754147,"about_ca_system_score_gemma":0.0005204014,"threshold_uncertainty_score":0.014703989},"labels":[],"label_agreement":null},{"id":"W4396589421","doi":"10.1101/2024.04.29.591421","title":"Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Mila - Quebec Artificial Intelligence Institute; CARE Canada; Montreal Neurological Institute and Hospital; International Collaboration On Repair Discoveries; University of British Columbia; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Université de Montréal; Polytechnique Montréal","funders":"Instituto de Salud Carlos III; Agència de Gestió d'Ajuts Universitaris i de Recerca; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; European Commission; Ministerstvo Zdravotnictví Ceské Republiky; Center for Neurobehavioral Development; Courtois Foundation; National Natural Science Foundation of China; Agentura Pro Zdravotnický Výzkum České Republiky; University College London Hospitals NHS Foundation Trust; National Imaging Facility; Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; University of Queensland; American Heart Association; SpinalCure Australia; University of Pennsylvania; Craig H. Neilsen Foundation; Deutsche Forschungsgemeinschaft; International Collaboration on Repair Discoveries; Bristol-Myers Squibb; Max-Planck-Gesellschaft; University of Minnesota","keywords":"Precentral gyrus; White matter; Fractional anisotropy; Diffusion MRI; Brain size; Anatomy; Neuroimaging; Magnetic resonance imaging; Grey matter; Neuroscience; Psychology; Nuclear medicine; Nuclear magnetic resonance; Medicine; Physics; Radiology","score_opus":0.019208700150429265,"score_gpt":0.27132429731497737,"score_spread":0.2521155971645481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396589421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996784,0.00006345887,0.00014264171,0.000007974094,0.0000012894658,0.000004472873,0.000024799287,0.0000014000262,0.0000755664],"genre_scores_gemma":[0.9996544,0.000028611388,0.00015457423,0.00001046343,0.0000069266775,0.0000053224335,0.00007230351,0.0000027591861,0.00006455465],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995617,0.00018818004,0.000022930311,0.0001415354,0.00004616267,0.000039540377],"domain_scores_gemma":[0.99858403,0.00031985505,0.00048566225,0.0003244233,0.00010376363,0.00018219942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010217499,0.00036421226,0.00038584357,0.0006474776,0.00041543317,0.0004041783,0.00030981848,0.000375142,0.0011087682],"category_scores_gemma":[0.0014405902,0.00028843756,0.00029855076,0.00050238677,0.0005650502,0.0005205324,0.00048774667,0.00026763714,0.00019848868],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001274167,0.00027754364,0.9812401,0.000030241601,0.0005085429,0.0002780149,0.0005225514,0.00014650665,0.0112679945,0.000069034104,0.00011206956,0.0042733504],"study_design_scores_gemma":[0.000009586761,0.0002434644,0.99897027,0.000001812586,0.000047362213,0.00023589974,0.00008094097,0.0001721356,0.00015223268,0.000018813282,0.000063639534,0.0000037690559],"about_ca_topic_score_codex":0.0015197347,"about_ca_topic_score_gemma":0.0021290977,"teacher_disagreement_score":0.0015197347,"about_ca_system_score_codex":0.00017306294,"about_ca_system_score_gemma":0.00014863852,"threshold_uncertainty_score":0.0054035783},"labels":[],"label_agreement":null},{"id":"W4396605090","doi":"10.1093/brain/awae141","title":"Connectome reorganization associated with temporal lobe pathology and its surgical resection","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Institute for Basic Science; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Hospital for Sick Children; National Research Foundation of Korea; National Natural Science Foundation of China; Canada Research Chairs; Institute for Information and Communications Technology Promotion; Canadian Open Neuroscience Platform; China Postdoctoral Science Foundation; Inha University; National Research Foundation; Canadian Institutes of Health Research; National Science Foundation","keywords":"Connectome; Temporal lobe; Neuroscience; Tractography; Psychology; Diffusion MRI; Electrocorticography; Neuroimaging; Epilepsy surgery; Medicine; Epilepsy; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.04241734601448008,"score_gpt":0.3426464226229718,"score_spread":0.30022907660849174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396605090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992136,0.00004903386,0.00037057008,0.000019784848,9.795392e-7,0.000006157522,0.000107786116,0.0000065257323,0.00022562762],"genre_scores_gemma":[0.99952006,0.00004747563,0.00016703215,0.0000070215933,0.0000021801372,0.000009276065,0.00016027609,0.0000021627131,0.00008463018],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993134,0.00001180298,0.000008166972,0.000022518423,0.000013330547,0.000012721284],"domain_scores_gemma":[0.9997886,0.000026207772,0.00012476146,0.000022983117,0.000013454386,0.000023945953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012039829,0.00015686968,0.000115145966,0.00044414893,0.00015369878,0.00019960898,0.000072746036,0.00011968163,0.00091826625],"category_scores_gemma":[0.00049072545,0.00008845673,0.00011955707,0.00026197743,0.00034117093,0.00020329184,0.00024814066,0.00016282505,0.00007859273],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016918947,0.00010823144,0.48491845,0.00009881217,0.0002045365,0.0041829036,0.00084627373,0.0016986593,0.48029724,0.0006942138,0.00043649436,0.02482228],"study_design_scores_gemma":[0.000005471956,0.00015180995,0.99136376,0.0000036876186,0.000017893784,0.0023815269,0.00013636985,0.0006624178,0.0048659123,0.00023841982,0.00016722314,0.0000054042457],"about_ca_topic_score_codex":0.0015461235,"about_ca_topic_score_gemma":0.003064014,"teacher_disagreement_score":0.0015461235,"about_ca_system_score_codex":0.00022161302,"about_ca_system_score_gemma":0.00016997334,"threshold_uncertainty_score":0.0030742884},"labels":[],"label_agreement":null},{"id":"W4396729524","doi":"10.1007/s11682-024-00889-4","title":"Structural network disruption of corticothalamic pathways in cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; National Natural Science Foundation of China","keywords":"Neuropsychology; Cognition; Disease; Neuroradiology; Cognitive impairment; Neurology; Effects of sleep deprivation on cognitive performance; Hippocampal formation; Neuroscience; Medicine; Internal medicine; Psychology","score_opus":0.050815154299471116,"score_gpt":0.33461832293080485,"score_spread":0.2838031686313337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396729524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99847203,0.00020377741,0.00096000126,0.000015706391,0.0000014352963,0.000005751905,0.00006180001,0.00000890977,0.00027050189],"genre_scores_gemma":[0.99927586,0.00007338813,0.00052581023,0.0000030937535,0.0000022781799,0.000003856346,0.00005185954,0.0000022750835,0.00006154345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99989104,0.000025784375,0.000011017585,0.00003450439,0.000020978847,0.000016654916],"domain_scores_gemma":[0.99963224,0.00009062448,0.00018108975,0.00003479049,0.000028991217,0.000032253116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024079757,0.00024945292,0.00020417276,0.0010829541,0.00021660744,0.0003666591,0.00016082513,0.0001675008,0.0008113937],"category_scores_gemma":[0.001118785,0.000115738425,0.00013113255,0.00056089065,0.00027290607,0.00033268644,0.00024769627,0.00014495538,0.000040681967],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080335775,0.00011099671,0.8696138,0.00014724533,0.0006066677,0.0015846217,0.000844218,0.0030000955,0.07535562,0.00105118,0.00028853,0.046593625],"study_design_scores_gemma":[0.000006674464,0.00007036357,0.99288577,0.0000072819485,0.00006691179,0.0011567507,0.00011570408,0.0026975248,0.002067415,0.00074449653,0.00017382397,0.000007186755],"about_ca_topic_score_codex":0.0035641717,"about_ca_topic_score_gemma":0.007945674,"teacher_disagreement_score":0.0035641717,"about_ca_system_score_codex":0.0002251004,"about_ca_system_score_gemma":0.00019149209,"threshold_uncertainty_score":0.007086873},"labels":[],"label_agreement":null},{"id":"W4396809662","doi":"10.1101/2024.05.08.593260","title":"Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Anisotropy; White matter; Magnetic resonance elastography; Isotropy; Fractional anisotropy; Diffusion MRI; Materials science; Elastography; Nuclear magnetic resonance; Composite material; Magnetic resonance imaging; Physics; Medicine; Optics; Ultrasound","score_opus":0.031360464034686994,"score_gpt":0.272409400664368,"score_spread":0.24104893662968097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396809662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936061,0.00094237534,0.004687971,0.000027739505,0.000006216424,0.000009530391,0.00021920339,0.00003930715,0.00046159115],"genre_scores_gemma":[0.9954556,0.00053919636,0.0033065805,0.000018902994,0.0000116102665,0.000013525371,0.00021833465,0.00001219515,0.00042400017],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998826,0.00002783631,0.000012059141,0.000032461925,0.00003309372,0.000011984859],"domain_scores_gemma":[0.9994791,0.00010358186,0.0002189,0.00006577574,0.00009309924,0.0000396471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006905859,0.00038267294,0.00029836383,0.0008540896,0.000119228505,0.00035634876,0.000094539304,0.00038406812,0.00062744424],"category_scores_gemma":[0.0016636732,0.00016692934,0.00015386654,0.0004938483,0.0002415405,0.00038954982,0.0002481591,0.00022521526,0.00017200726],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013301207,0.00019892932,0.52785784,0.00029374228,0.00045034857,0.0006043904,0.0013835175,0.003404479,0.3683529,0.0007138615,0.0008006544,0.09460918],"study_design_scores_gemma":[0.0000094633615,0.00034176125,0.9776403,0.000019326902,0.00007358362,0.0007846626,0.00017608517,0.004957315,0.014208968,0.001016216,0.00075018377,0.000022214577],"about_ca_topic_score_codex":0.0010107905,"about_ca_topic_score_gemma":0.00121421,"teacher_disagreement_score":0.0010107905,"about_ca_system_score_codex":0.00006841367,"about_ca_system_score_gemma":0.00008768994,"threshold_uncertainty_score":0.0036521554},"labels":[],"label_agreement":null},{"id":"W4397045463","doi":"10.1681/asn.20233411s1656a","title":"White Matter Alternation at Corpus Callosum and Stria Terminalis Contributes to the Cognitive Impairment in ESRD via Dysregulating Homeostasis of Calcium","year":2023,"lang":"en","type":"article","venue":"Journal of the American Society of Nephrology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Internal medicine; Homeostasis; Endocrinology; Medicine; Stria terminalis; White matter; Psychology; Anatomy; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.037516566927443186,"score_gpt":0.34884572460238994,"score_spread":0.31132915767494673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4397045463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977436,0.0013807394,0.00023602547,0.00007818691,0.000011624596,0.000017452216,0.00012513921,0.00000989916,0.000397246],"genre_scores_gemma":[0.9981597,0.0005994117,0.0004347815,0.000044120545,0.00002631068,0.00002261125,0.00018404998,0.0000028308586,0.00052619254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987197,0.00002032126,0.000015067127,0.00003497894,0.00003408553,0.000023622317],"domain_scores_gemma":[0.99953854,0.000025382284,0.00026841075,0.000021978018,0.000069287125,0.0000764759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035135853,0.0005113044,0.00039935755,0.0008122284,0.00056241127,0.0004120829,0.0003577208,0.00031774468,0.0019756265],"category_scores_gemma":[0.0005212459,0.00018907056,0.00032059097,0.00040973106,0.00043154965,0.00028631827,0.00037374735,0.00053511804,0.00016168389],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006714025,0.0010607311,0.90077037,0.0003785302,0.00055477355,0.0018847403,0.00046056404,0.00021689222,0.06355551,0.00023603365,0.00066875713,0.023499094],"study_design_scores_gemma":[0.000041757256,0.00044173043,0.9952135,0.00002265825,0.00014798882,0.0010916487,0.0000866464,0.0002812502,0.002146676,0.00018777214,0.00033004102,0.000008316583],"about_ca_topic_score_codex":0.002922298,"about_ca_topic_score_gemma":0.0037921795,"teacher_disagreement_score":0.002922298,"about_ca_system_score_codex":0.0003966109,"about_ca_system_score_gemma":0.00036584487,"threshold_uncertainty_score":0.006609142},"labels":[],"label_agreement":null},{"id":"W4398147234","doi":"10.1162/imag_x_00158","title":"Correction to: White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2024,"lang":"en","type":"erratum","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"","keywords":"Gray (unit); White matter; Morphology (biology); Evolutionary biology; Brain morphometry; Biology; Zoology; Medicine; Magnetic resonance imaging","score_opus":0.02008746994466979,"score_gpt":0.3418442102674843,"score_spread":0.3217567403228145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398147234","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087694544,0.0011033615,0.008763269,0.04002276,0.8690348,0.00015638089,0.051986832,0.0064809457,0.021574674],"genre_scores_gemma":[0.024768924,0.0063070706,0.048724744,0.03382797,0.096964024,0.0009866708,0.098584056,0.03556782,0.6542687],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99618125,0.00057285547,0.0008140287,0.00053007784,0.0016502778,0.00025149682],"domain_scores_gemma":[0.9509565,0.010540894,0.0023447028,0.005272652,0.029569993,0.0013152346],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004203178,0.0022184956,0.0015153136,0.0054034293,0.0025382133,0.0038856817,0.003504939,0.0033606933,0.36143765],"category_scores_gemma":[0.086565614,0.0013915363,0.0016893776,0.0049363757,0.0016374976,0.002836882,0.0026544214,0.0069401106,0.15303995],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019727711,0.000002518108,0.000064992426,0.00008728622,0.000005375079,0.000053304462,0.0000188082,0.000030746774,0.00003087174,0.0004352158,0.99489033,0.0043608057],"study_design_scores_gemma":[0.000051248237,0.000011522868,0.0010349611,0.00043043197,0.000030578292,0.0005972016,0.00009587845,0.00021534153,0.00031929812,0.0025083912,0.994663,0.00004215561],"about_ca_topic_score_codex":0.022059843,"about_ca_topic_score_gemma":0.02714122,"teacher_disagreement_score":0.36143765,"about_ca_system_score_codex":0.0024771849,"about_ca_system_score_gemma":0.005341614,"threshold_uncertainty_score":0.9108317},"labels":[],"label_agreement":null},{"id":"W4398768708","doi":"10.1016/j.appet.2024.107527","title":"Obesity and diffusion-weighted imaging of subcortical grey matter in young and older adults","year":2024,"lang":"en","type":"article","venue":"Appetite","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada","keywords":"Grey matter; Diffusion MRI; Obesity; Psychology; Medicine; Magnetic resonance imaging; Internal medicine; Radiology; White matter","score_opus":0.009810157193559783,"score_gpt":0.2867510256005421,"score_spread":0.27694086840698234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398768708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989581,0.0005595911,0.000028534936,0.000038308197,0.000004418648,0.0000026253476,0.000052409858,9.376603e-7,0.0003550076],"genre_scores_gemma":[0.9992449,0.0002945552,0.0000649523,0.00003230485,0.000013179889,0.000002640008,0.0000722965,9.4708315e-7,0.000274267],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99994254,0.000008357967,0.000009747263,0.0000132895675,0.00001243635,0.0000136432445],"domain_scores_gemma":[0.99965906,0.000054664844,0.00014641632,0.000010493528,0.000041945263,0.0000873351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027344155,0.00023848281,0.0002580266,0.0006385049,0.00025835718,0.0005110986,0.00013429766,0.00044460152,0.0008206582],"category_scores_gemma":[0.0012015409,0.00022347644,0.00024286786,0.00051381293,0.00023157422,0.0005180153,0.00031187697,0.0003605928,0.0001009233],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038793962,0.000089018344,0.9943586,0.000025657902,0.00008059028,0.00057936425,0.00028717337,0.000030013953,0.0011377393,0.000041998956,0.000070642825,0.002911181],"study_design_scores_gemma":[0.0000024497565,0.000047232836,0.99942076,0.0000032419198,0.000013159046,0.00026348606,0.00012967277,0.000041711104,0.000024860372,0.000023976692,0.000028063236,0.0000013893654],"about_ca_topic_score_codex":0.0074477103,"about_ca_topic_score_gemma":0.013670821,"teacher_disagreement_score":0.0074477103,"about_ca_system_score_codex":0.00020840643,"about_ca_system_score_gemma":0.00017339495,"threshold_uncertainty_score":0.014808714},"labels":[],"label_agreement":null},{"id":"W4399139593","doi":"10.1038/s41380-024-02604-7","title":"Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McGill University; McGill Genome Centre","funders":"Université de Bordeaux; Agence Nationale de la Recherche; McGill University","keywords":"Diffusion MRI; White matter; Genome-wide association study; Dementia; Hyperintensity; Locus (genetics); Neuroimaging; Biobank; Disease; Medicine; Neuroscience; Pathology; Magnetic resonance imaging; Biology; Genetics; Single-nucleotide polymorphism; Genotype; Gene","score_opus":0.017618381692906505,"score_gpt":0.2844274265415538,"score_spread":0.26680904484864726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399139593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8009396,0.041899636,0.12883769,0.0068148156,0.00028788706,0.00009131719,0.0072458424,0.0006383031,0.013244989],"genre_scores_gemma":[0.9519143,0.016198877,0.02676193,0.0009280376,0.00031265328,0.00006462015,0.0014953882,0.000091498776,0.0022326526],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996871,0.00006845704,0.00001913968,0.00013465222,0.00005417758,0.00003648494],"domain_scores_gemma":[0.99936396,0.00023822841,0.00018206719,0.00009084822,0.00007654003,0.000048513688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078665855,0.0004954847,0.0007124565,0.0010665887,0.00025074053,0.0012575598,0.00038324247,0.00072519435,0.0015581138],"category_scores_gemma":[0.0018280534,0.00034524183,0.0004059573,0.0007759391,0.00066041504,0.001241377,0.0006762845,0.00089294056,0.00023915201],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079818565,0.00026250075,0.29958978,0.0013554895,0.0014747923,0.0017576353,0.0020281605,0.008017468,0.31375897,0.092778385,0.008197003,0.26998168],"study_design_scores_gemma":[0.000113350885,0.00068164547,0.76050353,0.000541228,0.0006062605,0.0031141427,0.0010091559,0.01905526,0.03062116,0.13580932,0.04769695,0.00024804287],"about_ca_topic_score_codex":0.0028064155,"about_ca_topic_score_gemma":0.0031655983,"teacher_disagreement_score":0.0028064155,"about_ca_system_score_codex":0.00051487144,"about_ca_system_score_gemma":0.0003884146,"threshold_uncertainty_score":0.005580187},"labels":[],"label_agreement":null},{"id":"W4399346227","doi":"10.52294/001c.118427","title":"MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across measures","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Toolbox; Multivariate statistics; Computer science; Multivariate analysis; Artificial intelligence; Statistics; Econometrics; Accounting; Mathematics; Machine learning; Business; Programming language","score_opus":0.054598876583771785,"score_gpt":0.3866768930689983,"score_spread":0.3320780164852265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399346227","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015154386,0.00038982308,0.9336717,0.00022993158,0.00014013544,0.00023083393,0.011714881,0.036345292,0.0021229433],"genre_scores_gemma":[0.12458654,0.00039706228,0.84138185,0.00025925328,0.00012328425,0.0021581163,0.012447755,0.015636567,0.003009514],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99820006,0.0004893837,0.00014374763,0.00053495227,0.00052746385,0.00010438124],"domain_scores_gemma":[0.99405766,0.0034840663,0.0007973126,0.00078666233,0.0006915997,0.00018271696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004421631,0.002072848,0.0012735407,0.0024480633,0.00061528536,0.002165697,0.0021703918,0.000847311,0.0379127],"category_scores_gemma":[0.023993058,0.00056780956,0.0014293893,0.0016025634,0.0008848922,0.0015741775,0.0031269004,0.0016612436,0.007558919],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012684541,0.0002942666,0.01837739,0.003754039,0.0016723822,0.00093971397,0.0011050762,0.046618607,0.05015907,0.039072536,0.18366234,0.65307605],"study_design_scores_gemma":[0.00041083313,0.00078453263,0.066315286,0.0009820847,0.0006151681,0.003127368,0.0005790787,0.49765298,0.08893219,0.15296263,0.18685836,0.0007795306],"about_ca_topic_score_codex":0.0017457763,"about_ca_topic_score_gemma":0.0025966775,"teacher_disagreement_score":0.0379127,"about_ca_system_score_codex":0.00044114335,"about_ca_system_score_gemma":0.0018646786,"threshold_uncertainty_score":0.12683058},"labels":[],"label_agreement":null},{"id":"W4399363497","doi":"10.1101/2024.06.04.597406","title":"Age-trajectories of higher-order diffusion properties of major brain metabolites in cerebral and cerebellar grey matter using in vivo diffusion-weighted MR spectroscopy at 3T","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Diffusion; In vivo; Diffusion MRI; In vivo magnetic resonance spectroscopy; Grey matter; Nuclear magnetic resonance; Order (exchange); Nuclear magnetic resonance spectroscopy; Cerebellum; Chemistry; Neuroscience; Physics; Magnetic resonance imaging; Medicine; Biology; White matter; Radiology; Thermodynamics","score_opus":0.023919185767010236,"score_gpt":0.2713127150410414,"score_spread":0.24739352927403113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399363497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920271,0.000236211,0.0071383277,0.00001941386,0.0000033038245,0.000010224416,0.00029428434,0.000048914124,0.00022225529],"genre_scores_gemma":[0.99575245,0.00016141658,0.0035694,0.0000051781635,0.0000027811452,0.000009156627,0.00025665373,0.0000126683135,0.00023042392],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994683,0.000011042657,0.0000046096966,0.000018951174,0.000011363924,0.000007172053],"domain_scores_gemma":[0.99973875,0.000054237815,0.00009545141,0.00002782981,0.00006448053,0.000019193752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003615699,0.00032232833,0.00018334718,0.00048240993,0.00012870142,0.00029848388,0.00013274579,0.00030159613,0.00055339176],"category_scores_gemma":[0.00082826224,0.00012980982,0.00017569934,0.00027011297,0.00016176776,0.00025565785,0.00016463116,0.00016667678,0.00012796071],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012137577,0.000113454305,0.1791268,0.0002112073,0.00026703355,0.00081293157,0.0010029542,0.005988294,0.76486206,0.0005917828,0.00053466443,0.045274973],"study_design_scores_gemma":[0.000017736393,0.00042582126,0.8797021,0.000016464151,0.00018444417,0.0014213751,0.00024066244,0.020412093,0.096057035,0.00067193975,0.0008024629,0.000047760102],"about_ca_topic_score_codex":0.0036866546,"about_ca_topic_score_gemma":0.00498717,"teacher_disagreement_score":0.0036866546,"about_ca_system_score_codex":0.00015808552,"about_ca_system_score_gemma":0.00017345845,"threshold_uncertainty_score":0.0073304176},"labels":[],"label_agreement":null},{"id":"W4399401389","doi":"10.1523/jneurosci.1705-23.2024","title":"Diffusion MRI of the Hippocampus","year":2024,"lang":"en","type":"review","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canadian Open Neuroscience Platform; Health Canada; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Hippocampus; Diffusion MRI; Neuroscience; Medicine; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.12263189980638309,"score_gpt":0.43046578682198583,"score_spread":0.30783388701560277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399401389","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012252814,0.9973999,0.0003288597,0.00030644296,0.00023890716,0.0000044180797,0.000016734512,0.000009422954,0.0015727181],"genre_scores_gemma":[0.0011242302,0.9972119,0.00033675836,0.00021885401,0.00027435995,0.000007809142,0.000033658704,0.000002998972,0.00078944524],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99981254,0.00003755344,0.000024390623,0.000037077294,0.000069572925,0.000018848366],"domain_scores_gemma":[0.9996662,0.0001488988,0.0000422985,0.000012309318,0.00010054275,0.000029679932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006524225,0.0010392789,0.0012481177,0.002792812,0.00025181382,0.0009396542,0.0008462572,0.0015110514,0.002805104],"category_scores_gemma":[0.0009796004,0.0004250337,0.00048612122,0.0016484617,0.0008961197,0.0018044268,0.0007884229,0.002091375,0.0030977111],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091012975,0.000041589377,0.00020780772,0.016927036,0.000110161636,0.000378179,0.00008850672,0.0006848254,0.005817977,0.010939403,0.045236535,0.91947705],"study_design_scores_gemma":[0.000017189306,0.00009038,0.0011543646,0.0028522052,0.00007034628,0.0033620219,0.000048780727,0.00019361902,0.0022172963,0.005715274,0.98423994,0.00003848465],"about_ca_topic_score_codex":0.0020182445,"about_ca_topic_score_gemma":0.0025106622,"teacher_disagreement_score":0.002805104,"about_ca_system_score_codex":0.0007602811,"about_ca_system_score_gemma":0.0011485181,"threshold_uncertainty_score":0.009384036},"labels":[],"label_agreement":null},{"id":"W4399433832","doi":"10.7554/elife.96625.1","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Cerebellum; Thalamus; Neuroscience; Biology; Taurine; Diffusion MRI; Anatomy; Magnetic resonance imaging; Medicine; Biochemistry; Amino acid","score_opus":0.04930940267079468,"score_gpt":0.3312707699946626,"score_spread":0.2819613673238679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399433832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97944814,0.000705144,0.01879535,0.000032174008,0.000008286737,0.000014536857,0.0003969595,0.00017052432,0.00042884937],"genre_scores_gemma":[0.9792027,0.0011589951,0.017395731,0.000021415823,0.0000029661737,0.000056688703,0.0004244203,0.00008814978,0.0016490762],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99994576,0.0000059661174,0.000003945981,0.000019932953,0.000016151558,0.000008338965],"domain_scores_gemma":[0.9998441,0.00002260534,0.00006482116,0.000012747425,0.000035622594,0.000020092762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018558002,0.00032239285,0.00022151247,0.00040159834,0.00008493738,0.00024187373,0.00021745669,0.00022322964,0.00041936096],"category_scores_gemma":[0.00029437305,0.00016732104,0.00017111491,0.00012569154,0.00020030966,0.0002156192,0.000260568,0.00024820454,0.00013038555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061732164,0.0000040717937,0.0016087886,0.000031552983,0.000008204535,0.00010856817,0.00004912207,0.00030007208,0.9943072,0.00008072319,0.000019697882,0.003420334],"study_design_scores_gemma":[0.0000075406497,0.0004923167,0.06094315,0.00002575374,0.00007401986,0.0008092985,0.00026091468,0.0072508254,0.92874676,0.00021967135,0.0011423735,0.000027361586],"about_ca_topic_score_codex":0.0020768247,"about_ca_topic_score_gemma":0.002844109,"teacher_disagreement_score":0.0020768247,"about_ca_system_score_codex":0.00021342837,"about_ca_system_score_gemma":0.00020429584,"threshold_uncertainty_score":0.00412941},"labels":[],"label_agreement":null},{"id":"W4399433921","doi":"10.7554/elife.96625","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"UK Research and Innovation; Wellcome Trust","keywords":"Cerebellum; Thalamus; Neuroscience; Taurine; Biology; Diffusion MRI; Anatomy; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Medicine; Biochemistry; Amino acid","score_opus":0.04017943180066636,"score_gpt":0.32255769961411135,"score_spread":0.282378267813445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399433921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96127987,0.0010365912,0.036315676,0.000057276666,0.000012120597,0.000018183913,0.0004073372,0.00029452462,0.00057851797],"genre_scores_gemma":[0.9567332,0.002327144,0.038090657,0.000038649614,0.000005756554,0.00007968579,0.0005623783,0.0001432649,0.0020193073],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999347,0.000006691647,0.0000048234724,0.00002575188,0.000018458124,0.000009652057],"domain_scores_gemma":[0.9998511,0.00002019268,0.00006410938,0.000011667784,0.000034323366,0.000018589919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020466863,0.00039942225,0.00024813402,0.00042996873,0.000095127376,0.0002532493,0.00024125808,0.00027538018,0.00035921438],"category_scores_gemma":[0.00035729492,0.00020185192,0.00019613047,0.00014747184,0.00020831445,0.00028772702,0.00030468474,0.0002767855,0.00012874304],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006160221,0.0000043387167,0.001530628,0.0000373663,0.00000936541,0.00010923976,0.000058359463,0.00048128128,0.9927717,0.00012173344,0.00002762003,0.004786772],"study_design_scores_gemma":[0.000010391494,0.0005490291,0.04722035,0.000031019954,0.00010249817,0.00089662924,0.00026669397,0.011668627,0.93740356,0.00037286067,0.0014426885,0.00003570034],"about_ca_topic_score_codex":0.002317912,"about_ca_topic_score_gemma":0.003954958,"teacher_disagreement_score":0.002317912,"about_ca_system_score_codex":0.00022643566,"about_ca_system_score_gemma":0.00025668612,"threshold_uncertainty_score":0.00460881},"labels":[],"label_agreement":null},{"id":"W4399446846","doi":"10.1016/j.neuroimage.2024.120672","title":"Divergent functional connectivity changes associated with white matter hyperintensities","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Hjärnfonden; Alzheimerfonden; Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse; University Hospital Foundation; Vetenskapsrådet; Marcus och Amalia Wallenbergs minnesfond; Knut och Alice Wallenbergs Stiftelse","keywords":"Hyperintensity; White matter; Cognition; Diffusion MRI; Neuroscience; Voxel; Default mode network; Resting state fMRI; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.07126254151730615,"score_gpt":0.3015506494475971,"score_spread":0.23028810793029092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399446846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99970394,0.000038031165,0.00014363452,0.0000046656014,5.145685e-7,0.000001785853,0.000045536493,0.0000020235846,0.000059932845],"genre_scores_gemma":[0.9997013,0.000018457054,0.00013022056,0.0000024914054,0.0000017445191,0.000002394988,0.00010163141,0.0000010772791,0.000040683495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987125,0.000028614184,0.000014370973,0.000045880315,0.000015767826,0.000024102868],"domain_scores_gemma":[0.99951994,0.00018062306,0.0001708667,0.00005246574,0.000026593416,0.000049515784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029705363,0.00026813443,0.00022259986,0.00076159067,0.00020181437,0.00029286786,0.0001485627,0.00033200553,0.0008942198],"category_scores_gemma":[0.0013674436,0.00014079928,0.00017020314,0.00035470238,0.00040811527,0.00026144745,0.0002802123,0.00017809327,0.00006418634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016022848,0.00009796668,0.8937255,0.00008869073,0.00042609245,0.0015696165,0.0013947969,0.0011329927,0.087868586,0.00030519033,0.00010567217,0.01168254],"study_design_scores_gemma":[0.0000050337053,0.000048137314,0.99787664,0.0000016572778,0.000022197744,0.00053098856,0.00009986285,0.00033055575,0.0008862694,0.00015822968,0.000036753154,0.0000037608386],"about_ca_topic_score_codex":0.001948957,"about_ca_topic_score_gemma":0.004201865,"teacher_disagreement_score":0.001948957,"about_ca_system_score_codex":0.00013816723,"about_ca_system_score_gemma":0.000080708705,"threshold_uncertainty_score":0.003875196},"labels":[],"label_agreement":null},{"id":"W4399457528","doi":"10.1016/j.neurobiolaging.2024.05.017","title":"Menopause status- and sex-related differences in age associations with spatial context memory and white matter microstructure at midlife","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Douglas College; McGill University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Context (archaeology); Psychology; White matter; Corpus callosum; Menopause; Developmental psychology; Medicine; Neuroscience; Internal medicine; Biology; Magnetic resonance imaging","score_opus":0.018587480869495496,"score_gpt":0.2794575233510993,"score_spread":0.2608700424816038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399457528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984175,0.0008250336,0.00007614553,0.000021141726,0.0000049441715,0.00000679127,0.00016957674,0.000002335136,0.00047638413],"genre_scores_gemma":[0.9992824,0.00016441036,0.000060859344,0.000011494522,0.000007052576,0.0000067210467,0.00008023916,9.885721e-7,0.00038592544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999596,0.00000653991,0.000004042145,0.00001491181,0.0000062260633,0.000008674878],"domain_scores_gemma":[0.99977356,0.000027932912,0.00011470714,0.000022003824,0.000023651366,0.00003827729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016081777,0.00013290043,0.0001378108,0.00035543693,0.00014202892,0.00019889808,0.000108738044,0.00017890647,0.0017195204],"category_scores_gemma":[0.00067885197,0.00008704237,0.00010740875,0.00020206218,0.00014059295,0.00020480332,0.00016896454,0.00010856648,0.00012986874],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020577738,0.00013941074,0.9653359,0.00007951167,0.00013812125,0.0002664747,0.0010225424,0.000060815473,0.013661733,0.00013210175,0.00022978632,0.016875805],"study_design_scores_gemma":[0.0000027395165,0.000085550484,0.99950206,0.0000020386394,0.00001044173,0.000056488552,0.0000696222,0.000020131378,0.00011986429,0.000033520715,0.00009648678,9.958795e-7],"about_ca_topic_score_codex":0.0017581861,"about_ca_topic_score_gemma":0.0038688858,"teacher_disagreement_score":0.0017581861,"about_ca_system_score_codex":0.00008935283,"about_ca_system_score_gemma":0.00009959393,"threshold_uncertainty_score":0.0057524443},"labels":[],"label_agreement":null},{"id":"W4399466581","doi":"10.1101/2024.06.05.597645","title":"White Matter Microstructural Correlates of Cognitive and Motor Functioning Revealed via Multimodal Multivariate Analysis","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Psychology; Cognition; Multivariate statistics; Neuroimaging; Mahalanobis distance; Cognitive psychology; White matter; Multivariate analysis; Metric (unit); Neuroscience; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine; Machine learning","score_opus":0.01632460991388035,"score_gpt":0.2722177133181243,"score_spread":0.2558931034042439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399466581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96689445,0.0003064364,0.03056146,0.00013661089,0.000008143584,0.000017906326,0.0010273742,0.00017818113,0.0008694802],"genre_scores_gemma":[0.9923683,0.000074125455,0.0068858843,0.000014566687,0.000012449689,0.000012927777,0.0003279107,0.000039914,0.00026409398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996524,0.000108859684,0.000022781811,0.00012675024,0.000056046214,0.00003326289],"domain_scores_gemma":[0.9979552,0.00069988973,0.0007933785,0.00025728848,0.00017082923,0.00012340317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014850795,0.00050498894,0.00032502686,0.0016894902,0.0001890482,0.0007571144,0.00024618756,0.00032837444,0.0023032331],"category_scores_gemma":[0.0046539526,0.0001627471,0.00036974048,0.0014066369,0.0006189906,0.00047983893,0.0007161795,0.00040613595,0.00019952204],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016129798,0.00022311838,0.57593286,0.0004848159,0.0019619481,0.0007279472,0.0014767983,0.025588471,0.24956758,0.005069325,0.0021347795,0.13521942],"study_design_scores_gemma":[0.000008236912,0.00013915068,0.9503881,0.000025269283,0.00012775286,0.00039266123,0.00012654165,0.034839258,0.0068271523,0.006522658,0.00054970384,0.00005350895],"about_ca_topic_score_codex":0.0032900933,"about_ca_topic_score_gemma":0.0039483593,"teacher_disagreement_score":0.0032900933,"about_ca_system_score_codex":0.00023681762,"about_ca_system_score_gemma":0.0002913581,"threshold_uncertainty_score":0.007853925},"labels":[],"label_agreement":null},{"id":"W4399511621","doi":"10.1186/s12880-024-01324-2","title":"Alterations in structural integrity of superior longitudinal fasciculus III associated with cognitive performance in cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Anhui University; Anhui University of Science and Technology; National Natural Science Foundation of China","keywords":"Cognition; Structural integrity; Neuroscience; Disease; Computer science; Medicine; Pathology; Psychology","score_opus":0.052871482746483706,"score_gpt":0.34992412560570135,"score_spread":0.2970526428592176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399511621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993482,0.00025634814,0.00013080353,0.000016931486,0.0000015284023,0.0000050623607,0.00006343035,0.0000026075802,0.00017515117],"genre_scores_gemma":[0.9994961,0.00010930358,0.00017395464,0.000006204416,0.0000036038118,0.0000045504,0.00008035711,8.24568e-7,0.0001251446],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991167,0.0000147925875,0.000008417958,0.0000280593,0.000017009317,0.000019919826],"domain_scores_gemma":[0.99938595,0.00004981624,0.00041649552,0.000030765976,0.00005576186,0.00006117752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026382803,0.00026206585,0.00018689694,0.00054121634,0.00020232148,0.00027321273,0.00013365074,0.00023743439,0.0010848582],"category_scores_gemma":[0.00089072133,0.0001038558,0.00015564125,0.00034825367,0.0002598027,0.00019232064,0.00020105169,0.00022768026,0.00010041097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081875385,0.00010967014,0.97803193,0.0000637024,0.00014486069,0.00043957192,0.0002192379,0.00017618696,0.010178907,0.000055671113,0.000110698755,0.0096508665],"study_design_scores_gemma":[0.0000040661603,0.00008009258,0.9988944,0.0000042649626,0.000020611911,0.0003173801,0.000036056583,0.00012748726,0.0004051392,0.000054031207,0.00005434463,0.0000021189],"about_ca_topic_score_codex":0.004151918,"about_ca_topic_score_gemma":0.0064127687,"teacher_disagreement_score":0.004151918,"about_ca_system_score_codex":0.00024375149,"about_ca_system_score_gemma":0.00024255316,"threshold_uncertainty_score":0.008255482},"labels":[],"label_agreement":null},{"id":"W4399561968","doi":"10.1101/2024.06.10.598357","title":"Sex, racial, and <i>APOE</i> -ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer’s disease","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; Genentech; National Institutes of Health; H. Lundbeck A/S; Eisai; Siemens Medical Solutions USA; Vanderbilt University Medical Center; Novo Nordisk; Northern California Institute for Research and Education; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Pennsylvania; Vanderbilt University; University of Southern California; Bristol-Myers Squibb; Eli Lilly and Company; Vanderbilt Memory and Alzheimer's Center; Biogen; National Institute on Aging; Alzheimer's Association","keywords":"Allele; Apolipoprotein E; Longitudinal study; Disease; White (mutation); White matter; Gerontology; Medicine; Genetics; Biology; Internal medicine; Pathology; Gene","score_opus":0.03411138672146659,"score_gpt":0.2787128996092358,"score_spread":0.2446015128877692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399561968","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006570962,0.99044245,0.00029059732,0.0004492294,0.000118653974,0.0001954155,0.0012945173,0.000007789421,0.00063032727],"genre_scores_gemma":[0.11203493,0.8818368,0.0018356387,0.0011147677,0.00029452948,0.00078188255,0.0017022649,0.000015260697,0.0003838854],"study_design_codex":"systematic_review","study_design_gemma":"observational","domain_scores_codex":[0.99591076,0.0015597215,0.0012139173,0.00059155707,0.00056511676,0.00015898768],"domain_scores_gemma":[0.98505014,0.009090449,0.0034751804,0.00037410305,0.0018485062,0.00016161868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006350414,0.0007477279,0.0028106996,0.0041385996,0.0005394562,0.0014802226,0.0008777258,0.0009565363,0.003664088],"category_scores_gemma":[0.027723748,0.0006116635,0.004162564,0.0044717095,0.0005629816,0.0010694962,0.0009023211,0.0006368761,0.00030933917],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010936472,0.000059936036,0.046612132,0.61225057,0.046097323,0.00025113652,0.0010057025,0.0003180357,0.00045225077,0.0011560165,0.010428914,0.28027442],"study_design_scores_gemma":[0.00047070306,0.00057578756,0.24152416,0.5469328,0.14028487,0.0014946728,0.0012267337,0.0003207046,0.0005100616,0.0022326806,0.064287946,0.00013880704],"about_ca_topic_score_codex":0.019620711,"about_ca_topic_score_gemma":0.053782064,"teacher_disagreement_score":0.019620711,"about_ca_system_score_codex":0.0010191625,"about_ca_system_score_gemma":0.005466922,"threshold_uncertainty_score":0.03901303},"labels":[],"label_agreement":null},{"id":"W4399593070","doi":"10.3389/fnins.2024.1389680","title":"Tractometry of the Human Connectome Project: resources and insights","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Office of Science; National Science Foundation; National Institutes of Health; Amazon Web Services; Advanced Scientific Computing Research; University of Washington; U.S. Department of Energy","keywords":"Human Connectome Project; Computer science; Connectome; Diffusion MRI; White matter; Connectomics; Visualization; Artificial intelligence; Tractography; Voxel; Pattern recognition (psychology); Machine learning; Functional connectivity; Neuroscience; Biology; Magnetic resonance imaging","score_opus":0.05272257028497808,"score_gpt":0.35716659443240106,"score_spread":0.304444024147423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399593070","genre_codex":"dataset","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018915545,0.0009141178,0.07727821,0.00097410247,0.00015389209,0.00028102496,0.8695494,0.027966723,0.003966948],"genre_scores_gemma":[0.034103032,0.0006383355,0.07730286,0.00013960124,0.00009330077,0.001754667,0.87816656,0.006444123,0.0013575344],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9967173,0.0011050549,0.00036987884,0.0008410001,0.0007837574,0.00018303556],"domain_scores_gemma":[0.9892239,0.0036358554,0.0010614936,0.004297992,0.0012856887,0.00049509085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005611558,0.001472885,0.0008533896,0.0048736646,0.0009161923,0.0016098889,0.0021599394,0.001060012,0.021258168],"category_scores_gemma":[0.02769987,0.00094323134,0.0014473108,0.008837213,0.000713643,0.0014563252,0.004078378,0.0015667859,0.0144258365],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006925642,0.00017080433,0.027912363,0.0021175656,0.0007171284,0.000542799,0.0010114424,0.018791713,0.0054220324,0.011950818,0.8085265,0.12214429],"study_design_scores_gemma":[0.0006851445,0.0002411956,0.117014855,0.0011994002,0.00037194928,0.0019889493,0.00042359333,0.07003872,0.012721212,0.07683224,0.71802235,0.0004603336],"about_ca_topic_score_codex":0.010734844,"about_ca_topic_score_gemma":0.015479787,"teacher_disagreement_score":0.021258168,"about_ca_system_score_codex":0.0008467908,"about_ca_system_score_gemma":0.002377704,"threshold_uncertainty_score":0.07111567},"labels":[],"label_agreement":null},{"id":"W4399663873","doi":"10.1093/brain/awae192","title":"Explaining slow seizure propagation with white matter tractography","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; McGill University","keywords":"Stereoelectroencephalography; Tractography; White matter; Epilepsy; Epileptic seizure; Neuroscience; Electroencephalography; Connectome; Psychology; Medicine; Epilepsy surgery; Functional connectivity; Magnetic resonance imaging; Radiology","score_opus":0.032086412828542986,"score_gpt":0.32095522872762056,"score_spread":0.2888688158990776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399663873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67026365,0.0022524511,0.32363042,0.00088111754,0.000033613665,0.00007402546,0.00031496832,0.0004829295,0.002066931],"genre_scores_gemma":[0.97628105,0.00061757426,0.02245163,0.000025737954,0.000030852774,0.0000225637,0.00013916327,0.000055403914,0.00037608537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997987,0.00007983626,0.0000145596605,0.000048645776,0.000029648952,0.000028635584],"domain_scores_gemma":[0.99861157,0.0008176778,0.00033972462,0.0001291369,0.000058980022,0.000042890144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087026006,0.00050000666,0.00031959216,0.001389784,0.00017161638,0.000585126,0.00036366843,0.00037776123,0.0012026815],"category_scores_gemma":[0.0053870226,0.00029453842,0.0004951037,0.0011065971,0.0007436437,0.0012445173,0.0006169545,0.00040636832,0.00022614289],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00077927014,0.000082427076,0.44587442,0.0006400956,0.0012512025,0.004799639,0.0019985912,0.19545843,0.091809556,0.04396682,0.002259756,0.2110798],"study_design_scores_gemma":[0.00007052645,0.00019211927,0.21624544,0.00013521005,0.00019629972,0.0027046497,0.0003424426,0.64783126,0.0069561023,0.12223483,0.0030253227,0.000065810644],"about_ca_topic_score_codex":0.0036132194,"about_ca_topic_score_gemma":0.0038287677,"teacher_disagreement_score":0.0036132194,"about_ca_system_score_codex":0.00039078874,"about_ca_system_score_gemma":0.00029653046,"threshold_uncertainty_score":0.0071843863},"labels":[],"label_agreement":null},{"id":"W4399707580","doi":"10.1002/alz.13808","title":"In vivo effect of LATE‐NC on integrity of white matter connections to the hippocampus","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Science Foundation; National Institutes of Health; Rush University; National Institute on Aging","keywords":"Hippocampus; White matter; Neuroscience; In vivo; Psychology; Biology; Medicine; Genetics; Magnetic resonance imaging","score_opus":0.03451498303370768,"score_gpt":0.34629155188784105,"score_spread":0.31177656885413335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399707580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963246,0.0005973946,0.0014922486,0.00004828342,0.000019355455,0.000012781857,0.00039496407,0.000038621467,0.001071825],"genre_scores_gemma":[0.9959531,0.00028275247,0.00072769675,0.000034294997,0.0000075574435,0.000022509425,0.00048620242,0.000025093508,0.0024608064],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99994683,0.0000066572543,0.0000029816017,0.000019545496,0.000010251275,0.000013672336],"domain_scores_gemma":[0.99975365,0.000039558046,0.00007202863,0.00002549494,0.000059270275,0.000050108403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023789077,0.00026155115,0.0001578844,0.0002200652,0.00016007516,0.00037795072,0.00019974912,0.00024116838,0.0022746897],"category_scores_gemma":[0.0005213179,0.00012597279,0.00012795949,0.00011964683,0.00023838277,0.00019783416,0.00012796474,0.0003571596,0.0003592094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0064291563,0.0002575167,0.011754138,0.00015258043,0.00012856086,0.00027603752,0.00013630916,0.00047039488,0.96755266,0.00016228415,0.00035451388,0.012325851],"study_design_scores_gemma":[0.00020444865,0.0031301999,0.45549005,0.00006521299,0.00036032428,0.0014410286,0.00024228108,0.0068052756,0.529519,0.0006795161,0.0020338462,0.000028791146],"about_ca_topic_score_codex":0.0057155513,"about_ca_topic_score_gemma":0.006179133,"teacher_disagreement_score":0.0057155513,"about_ca_system_score_codex":0.0002882726,"about_ca_system_score_gemma":0.00032476542,"threshold_uncertainty_score":0.011364579},"labels":[],"label_agreement":null},{"id":"W4399749900","doi":"10.20944/preprints202301.0571.v3","title":"Spin Helicity","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Helicity; Physics; Spin (aerodynamics); Condensed matter physics; Particle physics","score_opus":0.28031779554085823,"score_gpt":0.46344382454692906,"score_spread":0.18312602900607083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399749900","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2710006,0.0039628963,0.2679265,0.0051072473,0.004555093,0.00024909212,0.0022287795,0.0010032229,0.44396648],"genre_scores_gemma":[0.94358855,0.001328091,0.020021724,0.0010987824,0.0007221491,0.0001202228,0.0004999295,0.00021925094,0.03240129],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999358,0.00011459398,0.000031950716,0.00021441872,0.00016947201,0.00011153725],"domain_scores_gemma":[0.9993606,0.0001069658,0.00012028956,0.00018047598,0.00014776266,0.000083846004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007090576,0.00041617104,0.00033559158,0.0006691964,0.0009632711,0.0020243996,0.00030505648,0.0006402798,0.018584507],"category_scores_gemma":[0.0015919397,0.00020470374,0.00023978743,0.00038930183,0.0025406168,0.0022860048,0.0011467349,0.0010623838,0.0023450626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006734162,0.000018673129,0.00038265568,0.00006762434,0.000007377534,0.00011581088,0.00022460097,0.0002627858,0.020244079,0.9575732,0.0032589415,0.017776905],"study_design_scores_gemma":[0.00003879776,0.00022464263,0.002394388,0.000079607074,0.00002106579,0.0011109079,0.00032406542,0.0037600747,0.028389193,0.8747599,0.088817924,0.00007943197],"about_ca_topic_score_codex":0.00037700377,"about_ca_topic_score_gemma":0.00029189195,"teacher_disagreement_score":0.018584507,"about_ca_system_score_codex":0.00040220082,"about_ca_system_score_gemma":0.00046125092,"threshold_uncertainty_score":0.0621714},"labels":[],"label_agreement":null},{"id":"W4399796974","doi":"10.1016/b978-0-12-820480-1.00170-4","title":"MRI of brain plasticity","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Neuroscience; Plasticity; Neuroplasticity; Psychology; Physics","score_opus":0.04383439821937826,"score_gpt":0.32673139408632296,"score_spread":0.2828969958669447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399796974","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015556976,0.14048047,0.03539362,0.0037281893,0.003495516,0.00006746135,0.00046312765,0.0013147515,0.8135012],"genre_scores_gemma":[0.0046244413,0.046036568,0.010492588,0.0011998182,0.0011085694,0.000052280262,0.0002562647,0.00030126786,0.93592817],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99992085,0.000010658396,0.0000039089123,0.000016358443,0.000040886574,0.000007334741],"domain_scores_gemma":[0.99987066,0.000060026592,0.0000059839604,0.00001848451,0.000028983728,0.000015879683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022986981,0.0008677821,0.0005389127,0.0019823632,0.0003443417,0.0013448052,0.00065688975,0.0012915756,0.100968465],"category_scores_gemma":[0.00052729493,0.00048500532,0.00031523337,0.000952576,0.0006504392,0.0017080285,0.00096470705,0.0015250782,0.05297065],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030561845,0.000026374993,0.00008774142,0.00042685829,0.000011785327,0.00027617795,0.00008134009,0.00036700946,0.0071500177,0.026236767,0.22683369,0.7384717],"study_design_scores_gemma":[0.0000054394322,0.000019404191,0.0004510941,0.00028199525,0.000008806936,0.0017754553,0.000030156698,0.00032112797,0.0018542416,0.017700108,0.9775414,0.00001073813],"about_ca_topic_score_codex":0.0011056219,"about_ca_topic_score_gemma":0.0043144054,"teacher_disagreement_score":0.100968465,"about_ca_system_score_codex":0.0004131477,"about_ca_system_score_gemma":0.0004383994,"threshold_uncertainty_score":0.33777314},"labels":[],"label_agreement":null},{"id":"W4399835591","doi":"10.14740/jmc4206","title":"Prompt Identification and Intervention for Ischemic Monomelic Neuropathy in Preventing Major Patient Disability","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Cases","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Intervention (counseling); Identification (biology); Psychiatry","score_opus":0.058917780985413115,"score_gpt":0.3970325341333588,"score_spread":0.3381147531479457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399835591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9515921,0.02251348,0.008919894,0.0030272028,0.00034392287,0.00016060389,0.000051748946,0.0003138231,0.013077179],"genre_scores_gemma":[0.99292845,0.0031056262,0.0021261026,0.00069482136,0.00024753812,0.000029820589,0.00004902748,0.000008627035,0.0008101116],"study_design_codex":"design_other","study_design_gemma":"case_report","domain_scores_codex":[0.99990547,0.000015420537,0.000010904556,0.000012346917,0.000010068065,0.000045937097],"domain_scores_gemma":[0.9996792,0.00006854639,0.00008454684,0.000015412019,0.000022482516,0.00012978699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015301326,0.00032361384,0.00029424625,0.00040712618,0.00062779145,0.0004065299,0.00025528058,0.00076274545,0.0012610747],"category_scores_gemma":[0.00073040836,0.000083177605,0.00024831863,0.00013828164,0.00023250098,0.00038510127,0.00044408708,0.0007349104,0.00019621463],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011086008,0.0018664824,0.2566438,0.00074370706,0.00008817836,0.31606236,0.00065884803,0.0008147435,0.018659111,0.0012101025,0.005623615,0.39652053],"study_design_scores_gemma":[0.00020868117,0.004177938,0.2245708,0.0011835821,0.00019374373,0.7329152,0.0010589905,0.0025865668,0.011813641,0.0021637592,0.019049793,0.00007735259],"about_ca_topic_score_codex":0.0003237175,"about_ca_topic_score_gemma":0.0008329477,"teacher_disagreement_score":0.0012610747,"about_ca_system_score_codex":0.0002078282,"about_ca_system_score_gemma":0.00045241372,"threshold_uncertainty_score":0.004218757},"labels":[],"label_agreement":null},{"id":"W4399835759","doi":"10.1093/cercor/bhae220","title":"Structural connectivity changes in unilateral hearing loss","year":2024,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University Health Network; University of Toronto; University of New Brunswick; Canada Research Chairs; Toronto Western Hospital; Krembil Foundation","funders":"Canadian Institutes of Health Research","keywords":"Hearing loss; Connectome; Connectomics; Audiology; Diffusion MRI; Node (physics); Unilateral hearing loss; Psychology; Medicine; Neuroscience; Magnetic resonance imaging; Functional connectivity; Physics","score_opus":0.07232046924430291,"score_gpt":0.35845888716737523,"score_spread":0.2861384179230723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399835759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99935836,0.00007395014,0.00025590035,0.000017017683,0.0000010595313,0.0000035919861,0.000037226906,0.000006576211,0.00024629792],"genre_scores_gemma":[0.9998012,0.000022442564,0.00007648652,0.000004595888,0.0000012581629,0.000002265849,0.000027342136,0.0000010118159,0.00006335195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998814,0.000019340152,0.000009877738,0.000029331148,0.00003207384,0.00002794658],"domain_scores_gemma":[0.9996271,0.000089382025,0.00015538528,0.00003140897,0.000030183195,0.00006655573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021752846,0.00023027475,0.00017517341,0.0010276762,0.00022521011,0.00024361788,0.0001483215,0.00017314086,0.0015826757],"category_scores_gemma":[0.0015545749,0.0001233487,0.00013043219,0.00035266328,0.00051121524,0.00036150558,0.00047183933,0.00013682105,0.000083466904],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014493703,0.00012252755,0.842899,0.00012367417,0.0002884592,0.006914368,0.0015015919,0.0026266002,0.07273143,0.0007001308,0.0005898952,0.070052855],"study_design_scores_gemma":[0.000007450515,0.00012120912,0.99431217,0.0000033926992,0.000022740056,0.0031163997,0.00019581676,0.0007410528,0.0010240099,0.00037518537,0.00007418189,0.000006360377],"about_ca_topic_score_codex":0.0031238075,"about_ca_topic_score_gemma":0.004957503,"teacher_disagreement_score":0.0031238075,"about_ca_system_score_codex":0.00026716397,"about_ca_system_score_gemma":0.00014011783,"threshold_uncertainty_score":0.006211281},"labels":[],"label_agreement":null},{"id":"W4399914534","doi":"10.1038/s42003-024-06420-1","title":"Associative white matter tracts selectively predict sensorimotor learning","year":2024,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Minority Health and Health Disparities; SBE Office of Multidisciplinary Activities; Division of Behavioral and Cognitive Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Directorate for Social, Behavioral and Economic Sciences; Government of Canada; U.S. Department of Health and Human Services; National Institutes of Health; National Science Foundation","keywords":"White matter; Fractional anisotropy; Psychology; Tractography; Associative learning; Lateralization of brain function; Cognitive psychology; Diffusion MRI; Artificial intelligence; Neuroscience; Computer science; Medicine; Magnetic resonance imaging","score_opus":0.08983519086896198,"score_gpt":0.40879287206141246,"score_spread":0.3189576811924505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399914534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978941,0.00002861851,0.0017572257,0.000023894516,0.000001577509,0.0000041674666,0.000065988344,0.00002097412,0.00020340364],"genre_scores_gemma":[0.9990115,0.000012624694,0.00075405557,0.000004917118,0.0000013263191,0.0000031852746,0.00005371334,0.0000054029683,0.000153274],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998235,0.0000337344,0.000013119031,0.00008244473,0.000025046671,0.000022196322],"domain_scores_gemma":[0.998599,0.00042738856,0.0005458566,0.00021371526,0.00009240533,0.00012169525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006431408,0.00021659526,0.00021562597,0.00044344564,0.00014296512,0.00045114997,0.00013294973,0.00034511863,0.0014230513],"category_scores_gemma":[0.0035096183,0.00016402647,0.00016804854,0.00017773312,0.0004255877,0.00040375566,0.00027661823,0.0003304796,0.00016881977],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065295794,0.00019168701,0.8651118,0.00003580626,0.0002590801,0.00019900898,0.00042305907,0.007034369,0.0964729,0.00058478606,0.00022945345,0.028805083],"study_design_scores_gemma":[0.000007302022,0.00017709004,0.97896135,0.000005346942,0.000028642742,0.00021437218,0.000062923566,0.010884196,0.008306244,0.0011962166,0.00014731154,0.000009063253],"about_ca_topic_score_codex":0.0017569346,"about_ca_topic_score_gemma":0.0041570626,"teacher_disagreement_score":0.0017569346,"about_ca_system_score_codex":0.00017511728,"about_ca_system_score_gemma":0.00022113367,"threshold_uncertainty_score":0.004760623},"labels":[],"label_agreement":null},{"id":"W4399918218","doi":"10.1002/hbm.26758","title":"Can gray matter loss in early adolescence be explained by white matter growth?","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; Alberta Children's Hospital; Baycrest Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Gray (unit); White matter; Psychology; Developmental psychology; Medicine; Magnetic resonance imaging; Nuclear medicine; Radiology","score_opus":0.0398145550865226,"score_gpt":0.31325661813882133,"score_spread":0.27344206305229873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399918218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975138,0.0007050922,0.00076692953,0.00024226026,0.000011578496,0.0000056278973,0.00015629032,0.000015241869,0.00058330543],"genre_scores_gemma":[0.9994672,0.00017758712,0.00016872514,0.000019573234,0.000010333646,0.0000051484103,0.00006813882,0.0000057808616,0.00007743202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999785,0.00006119767,0.00001913712,0.00005156906,0.000038573082,0.000044486605],"domain_scores_gemma":[0.99823254,0.0006218361,0.0007408904,0.00019220634,0.00011884457,0.00009372733],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010394908,0.00037809362,0.00035650353,0.0011486439,0.00020553163,0.00042019933,0.00050003524,0.00048525177,0.0010807856],"category_scores_gemma":[0.0051211873,0.00024623307,0.00034012846,0.0005690926,0.0006504829,0.000579712,0.00041145232,0.0004969254,0.0001776528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015045822,0.000029485287,0.99141544,0.000020929087,0.00005415014,0.00033215364,0.00024108961,0.0002782708,0.0020237605,0.00024498737,0.00014296584,0.005066187],"study_design_scores_gemma":[0.0000027342974,0.00004180101,0.9969131,0.000013254537,0.000024272644,0.0005220268,0.0001705716,0.0011541127,0.00046454513,0.0005304169,0.00016040386,0.0000028357101],"about_ca_topic_score_codex":0.0056105894,"about_ca_topic_score_gemma":0.0060335905,"teacher_disagreement_score":0.0056105894,"about_ca_system_score_codex":0.00021588951,"about_ca_system_score_gemma":0.00022351053,"threshold_uncertainty_score":0.011155844},"labels":[],"label_agreement":null},{"id":"W4399980465","doi":"10.1002/mrm.30195","title":"Characterization of the orientation dependence of magnetization transfer measures in single and crossing‐fiber white matter","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Diffusion MRI; Homogeneity (statistics); Characterization (materials science); Orientation (vector space); Magnetization transfer; White matter; Nuclear magnetic resonance; Materials science; Physics; Mathematics; Optics; Magnetic resonance imaging; Computer science; Geometry; Artificial intelligence; Statistics; Medicine","score_opus":0.032957997790857535,"score_gpt":0.3076968442036872,"score_spread":0.27473884641282964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399980465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8715791,0.0012708948,0.12508489,0.000084324194,0.00002402488,0.00006285572,0.00039509634,0.0003025456,0.0011963178],"genre_scores_gemma":[0.9696257,0.00038071212,0.028639453,0.000029499995,0.000028063292,0.000049591585,0.0006623066,0.00015403476,0.00043055727],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99968255,0.00007569026,0.000029045617,0.000111556335,0.00007285088,0.000028309532],"domain_scores_gemma":[0.9981262,0.00059068046,0.00047760556,0.00036307675,0.00035633805,0.0000860939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016412517,0.000560912,0.00039189958,0.00066587934,0.00023558261,0.0006142014,0.00025420342,0.00038121452,0.00068095885],"category_scores_gemma":[0.005253102,0.00018949287,0.00027992605,0.0005286867,0.00040546493,0.0005269362,0.00039285346,0.00036848933,0.0002432317],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086751435,0.00018475765,0.062600166,0.00084694,0.00050842937,0.00035112706,0.00071866455,0.015669413,0.7702625,0.0014820083,0.0007871018,0.14572139],"study_design_scores_gemma":[0.000044039785,0.00075286627,0.5063272,0.0001174784,0.00051854225,0.0028855663,0.00026385314,0.10014905,0.37980798,0.004117553,0.0049236123,0.00009228507],"about_ca_topic_score_codex":0.0012743494,"about_ca_topic_score_gemma":0.0020378898,"teacher_disagreement_score":0.0016412517,"about_ca_system_score_codex":0.0002067335,"about_ca_system_score_gemma":0.0004764246,"threshold_uncertainty_score":0.008679926},"labels":[],"label_agreement":null},{"id":"W4399985193","doi":"10.1371/journal.pone.0305818","title":"A comparison of white matter microstructure and correlates with neuropsychological measures in younger and older adults","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Corpus callosum; Neuropsychology; White matter; Diffusion MRI; Young adult; Psychology; Population; Cognition; Medicine; Audiology; Gerontology; Magnetic resonance imaging; Psychiatry; Neuroscience","score_opus":0.05820287161750912,"score_gpt":0.32567462806126357,"score_spread":0.2674717564437544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399985193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992964,0.00025027036,0.00008244843,0.000013604166,0.0000024209978,0.000004941134,0.00013483058,0.0000028243364,0.00021225346],"genre_scores_gemma":[0.99927706,0.000098451,0.00016793604,0.00002085841,0.00001040118,0.000006304088,0.00018835804,0.0000015219651,0.00022916251],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988973,0.0000144672495,0.000017474451,0.000041378928,0.000023400864,0.000013553318],"domain_scores_gemma":[0.9994789,0.000054313256,0.00027644983,0.000032416647,0.00007349865,0.00008447695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004282015,0.00029241195,0.00024552838,0.0008069251,0.00020753732,0.00036286135,0.00014051923,0.00034307587,0.0014000969],"category_scores_gemma":[0.0013496676,0.00014018251,0.00015502214,0.00036596242,0.00020590196,0.00043840712,0.00030581417,0.0001402063,0.00026647255],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033359026,0.00006457284,0.98915684,0.000025437024,0.00010545013,0.00013739419,0.00034790285,0.000049011236,0.0039570853,0.000038688748,0.00010880599,0.005675189],"study_design_scores_gemma":[0.0000035187195,0.000101094236,0.9994373,0.0000025832037,0.000009210807,0.0001409978,0.00006842721,0.000036898185,0.00011540623,0.000026610547,0.000056914065,0.0000011537871],"about_ca_topic_score_codex":0.0020968255,"about_ca_topic_score_gemma":0.0032586497,"teacher_disagreement_score":0.0020968255,"about_ca_system_score_codex":0.00014111381,"about_ca_system_score_gemma":0.00011820402,"threshold_uncertainty_score":0.004683733},"labels":[],"label_agreement":null},{"id":"W4399995661","doi":"10.1162/imag_a_00221","title":"Imaging of the superficial white matter in health and disease","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; White (mutation); Medicine; Magnetic resonance imaging; Radiology; Chemistry","score_opus":0.03323279792111178,"score_gpt":0.3574973428935282,"score_spread":0.3242645449724164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399995661","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021804804,0.90747154,0.051076047,0.0066231904,0.0007539201,0.00007022714,0.00043269387,0.00028252837,0.011485037],"genre_scores_gemma":[0.18133941,0.71936375,0.08562368,0.0045436528,0.0028800406,0.00019450624,0.00065636967,0.00015042895,0.005248171],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99948585,0.00018274752,0.000046083467,0.00009856966,0.00012199212,0.00006463228],"domain_scores_gemma":[0.999348,0.00029521246,0.000102758175,0.000038634847,0.00015979768,0.000055594504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019950194,0.0006397771,0.0007882313,0.002717229,0.0003210773,0.0019556873,0.0009801198,0.0025098023,0.0018832333],"category_scores_gemma":[0.0023546338,0.0003622154,0.00045781513,0.0016597923,0.0014417012,0.0024176294,0.0012877862,0.0013278447,0.00075266894],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047413836,0.00010808745,0.01454459,0.014730893,0.00058805454,0.0036964705,0.0012409146,0.0028497477,0.11352339,0.02757152,0.03254806,0.78812414],"study_design_scores_gemma":[0.000082400395,0.0008701146,0.05736417,0.016393106,0.0012942619,0.053716134,0.0023500356,0.011898525,0.07670395,0.12442247,0.6545582,0.00034672115],"about_ca_topic_score_codex":0.0016857329,"about_ca_topic_score_gemma":0.0023616136,"teacher_disagreement_score":0.002717229,"about_ca_system_score_codex":0.00073208223,"about_ca_system_score_gemma":0.00086614065,"threshold_uncertainty_score":0.010550737},"labels":[],"label_agreement":null},{"id":"W4400051699","doi":"10.1002/hbm.26771","title":"Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"NIH Blueprint for Neuroscience Research; National Institute of Neurological Disorders and Stroke","keywords":"Cingulum (brain); Precuneus; Tractography; Neuroscience; Psychology; Posterior cingulate; Population; Human brain; Resting state fMRI; Neuroimaging; Fractional anisotropy; Anatomy; Diffusion MRI; Cognition; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.1650740918079777,"score_gpt":0.37170056318072503,"score_spread":0.20662647137274734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400051699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970733,0.0005565291,0.0015105805,0.000048387075,0.0000018687508,0.0000054442316,0.000103205675,0.000008923145,0.0006918251],"genre_scores_gemma":[0.9981681,0.00028495697,0.0012805789,0.000009086173,0.000004735815,0.0000050510425,0.00010832324,0.0000026491364,0.00013642648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999291,0.000012837816,0.000004690885,0.000024844805,0.000017306731,0.0000113141305],"domain_scores_gemma":[0.9997582,0.00004988577,0.00008569106,0.00003384488,0.00004475725,0.000027557608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001576305,0.0001293746,0.00010392753,0.00089857785,0.00029432873,0.00033499606,0.00013478479,0.00014411412,0.00092523935],"category_scores_gemma":[0.00075336755,0.00009166648,0.00010552191,0.0005297693,0.00038879615,0.0002955026,0.00028836523,0.00011890446,0.000097163946],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040085005,0.000028448294,0.5685508,0.0002952981,0.0003522781,0.0018629867,0.0024759637,0.0010808966,0.33357602,0.0021999206,0.0004998687,0.088676676],"study_design_scores_gemma":[0.0000044474386,0.000034859262,0.9908118,0.000016582839,0.00004727626,0.0011733655,0.0003663805,0.0009633183,0.004552759,0.0008941481,0.0011293646,0.0000056698973],"about_ca_topic_score_codex":0.0063429894,"about_ca_topic_score_gemma":0.022644946,"teacher_disagreement_score":0.0063429894,"about_ca_system_score_codex":0.00017499778,"about_ca_system_score_gemma":0.000234218,"threshold_uncertainty_score":0.012612104},"labels":[],"label_agreement":null},{"id":"W4400051904","doi":"10.1002/hbm.26693","title":"Surface‐based morphometry of the corpus callosum in young children of ages 1–5","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Dental and Craniofacial Research; Wellcome Trust; Saban Research Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Bill and Melinda Gates Foundation","keywords":"Corpus callosum; Sexual dimorphism; White matter; Psychology; Cognition; Brain morphometry; Neuroscience; Anatomy; Developmental psychology; Biology; Medicine; Magnetic resonance imaging; Zoology","score_opus":0.0702995056777756,"score_gpt":0.35040828119709005,"score_spread":0.28010877551931446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400051904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989465,0.00007092357,0.00037257903,0.000013027939,0.0000023902576,0.00000436651,0.000343499,0.000022788226,0.00022402249],"genre_scores_gemma":[0.99833554,0.000099760444,0.0009873693,0.0000045597035,0.0000025082352,0.000009906847,0.00038057717,0.000014100733,0.00016576194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987423,0.000019247113,0.00001080822,0.000037029862,0.000033974906,0.000024674147],"domain_scores_gemma":[0.9994727,0.00011424745,0.00023229413,0.000040796134,0.00009392793,0.000046117377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034693678,0.0003070526,0.00021741171,0.0019151843,0.00026836948,0.0004929573,0.00020957015,0.0002898899,0.0010670964],"category_scores_gemma":[0.0016813803,0.00017152623,0.00035626197,0.00087178586,0.00031145918,0.00032394938,0.00044942572,0.00022312556,0.000218589],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034207138,0.000027455408,0.95260966,0.000073897034,0.000098066885,0.0007193479,0.0022316037,0.001088987,0.0154161975,0.00022525557,0.0004755089,0.026692],"study_design_scores_gemma":[8.513592e-7,0.00002587859,0.9981318,0.000004889031,0.000008916481,0.0003286788,0.00039964312,0.00042427127,0.00048414269,0.00003291702,0.00015374091,0.0000041977605],"about_ca_topic_score_codex":0.014977481,"about_ca_topic_score_gemma":0.013791629,"teacher_disagreement_score":0.014977481,"about_ca_system_score_codex":0.0002902707,"about_ca_system_score_gemma":0.000236055,"threshold_uncertainty_score":0.029780626},"labels":[],"label_agreement":null},{"id":"W4400135600","doi":"10.3389/fradi.2024.1416672","title":"Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data","year":2024,"lang":"en","type":"article","venue":"Frontiers in Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"European Commission; Wellcome Trust","keywords":"Deconvolution; Tractography; Diffusion MRI; Diffusion; Medicine; Medical physics; Computer science; Radiology; Physics; Magnetic resonance imaging; Algorithm; Thermodynamics","score_opus":0.04914655114847281,"score_gpt":0.3503692760602306,"score_spread":0.3012227249117578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400135600","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44971308,0.0012264495,0.5431102,0.0019540817,0.000086631706,0.00026906328,0.0004750416,0.00044246705,0.002722966],"genre_scores_gemma":[0.633027,0.0007296187,0.36408874,0.00023532793,0.000053786327,0.00027385086,0.00056077435,0.0002700218,0.0007609058],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985851,0.00077469595,0.000110712725,0.00016868654,0.00031916035,0.00004164381],"domain_scores_gemma":[0.98834956,0.007254486,0.0008693531,0.0016011473,0.0016256546,0.00029975697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006873302,0.00067991286,0.00043488413,0.0006486616,0.00046072996,0.0011944819,0.0007858913,0.0008680666,0.0017893568],"category_scores_gemma":[0.028930243,0.00037945728,0.00045489424,0.0006150347,0.0008404295,0.00124215,0.0013067942,0.0007707088,0.0004733938],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004930421,0.0003844973,0.10925385,0.0021239964,0.0006189157,0.004462432,0.0017953612,0.08323011,0.4315826,0.021072188,0.0026597702,0.33788586],"study_design_scores_gemma":[0.00028672605,0.0038352783,0.118962884,0.0005125992,0.00055212947,0.016715392,0.0010270979,0.479148,0.3366193,0.020581244,0.021486264,0.00027320298],"about_ca_topic_score_codex":0.002266911,"about_ca_topic_score_gemma":0.0035678977,"teacher_disagreement_score":0.006873302,"about_ca_system_score_codex":0.0004642347,"about_ca_system_score_gemma":0.0015182877,"threshold_uncertainty_score":0.036349893},"labels":[],"label_agreement":null},{"id":"W4400336623","doi":"10.1038/s41537-024-00478-w","title":"A systematic review of structural and functional magnetic resonance imaging studies on the neurobiology of depressive symptoms in schizophrenia spectrum disorders","year":2024,"lang":"en","type":"review","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Toronto","funders":"","keywords":"PsycINFO; Neuroimaging; Functional magnetic resonance imaging; Major depressive disorder; Depression (economics); Cochrane Library; MEDLINE; Schizophrenia (object-oriented programming); Brain Structure and Function; Psychology; Systematic review; Magnetic resonance imaging; Diffusion MRI; Psychiatry; Depressive symptoms; Meta-analysis; Clinical psychology; Medicine; Neuroscience; Cognition; Internal medicine; Radiology","score_opus":0.03790875485051529,"score_gpt":0.3469683465234314,"score_spread":0.3090595916729161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400336623","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012404611,0.9969036,0.00020363067,0.0002523026,0.00010246588,0.0003327359,0.00064345956,0.000010635776,0.00031056514],"genre_scores_gemma":[0.009876623,0.9878292,0.0007325253,0.0004471266,0.00006200895,0.00056028325,0.00033530899,0.000005335953,0.00015155575],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9942147,0.00165931,0.0026243848,0.00044682669,0.00087569136,0.00017909144],"domain_scores_gemma":[0.9851562,0.009949847,0.0029798343,0.0001951824,0.0015276945,0.00019128826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0061444426,0.0016919087,0.008524214,0.013220881,0.00078698545,0.002193574,0.0020199595,0.0015654825,0.004981556],"category_scores_gemma":[0.023639277,0.0009885436,0.006515535,0.014958949,0.00084011967,0.002286131,0.0016326638,0.00088346074,0.0003754087],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012054465,0.0000071180207,0.0004973802,0.96775424,0.0047139344,0.00013402457,0.00013490528,0.00006775343,0.00016567417,0.000142671,0.0012339364,0.025027752],"study_design_scores_gemma":[0.00020026404,0.00017111385,0.004984422,0.90411437,0.07058417,0.0005453112,0.00025287154,0.0000717729,0.00018252533,0.0003012016,0.018555708,0.000036182697],"about_ca_topic_score_codex":0.010502968,"about_ca_topic_score_gemma":0.03828018,"teacher_disagreement_score":0.013220881,"about_ca_system_score_codex":0.0034497266,"about_ca_system_score_gemma":0.012953896,"threshold_uncertainty_score":0.03249532},"labels":[],"label_agreement":null},{"id":"W4400395422","doi":"10.1101/2024.07.05.602300","title":"Motor training improves impaired cortico-cerebellar connectivity in cerebellar ataxia","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Cerebellar Degeneration; Cerebellum; Neuroscience; Degeneration (medical); Motor learning; Cerebellar diseases; Medicine; Physical medicine and rehabilitation; Psychology; Pathology","score_opus":0.044341167842959245,"score_gpt":0.2893026463364276,"score_spread":0.24496147849346836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400395422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981212,0.00013752871,0.0014039391,0.00001544257,0.0000020158038,0.000008002528,0.000059117145,0.000052548898,0.00020016723],"genre_scores_gemma":[0.99876,0.0000729192,0.00090903987,0.0000059493273,0.0000014304281,0.00000772008,0.00009039062,0.000005013578,0.00014758883],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993193,0.000013448745,0.0000072018497,0.000026334881,0.000010890316,0.000010313754],"domain_scores_gemma":[0.99992144,0.00001947038,0.000035971392,0.000007773426,0.000004265657,0.000011010967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012506543,0.0002573124,0.00015760178,0.00020463155,0.00011690518,0.00016562908,0.00010176871,0.00018526266,0.0007317676],"category_scores_gemma":[0.00037982696,0.00012753923,0.00013114755,0.00010449055,0.00015224323,0.000113554655,0.00013742656,0.000098671975,0.00008754949],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012862223,0.00029770314,0.14438115,0.0002151027,0.000339816,0.00084576936,0.00041030292,0.004853245,0.7506345,0.00019121598,0.00044944437,0.09609543],"study_design_scores_gemma":[0.000034990015,0.00083967304,0.94898546,0.000012633603,0.00015484632,0.0011888064,0.00008150005,0.0060946285,0.04170195,0.0002666299,0.0006297641,0.000009188293],"about_ca_topic_score_codex":0.0015153468,"about_ca_topic_score_gemma":0.0040615667,"teacher_disagreement_score":0.0015153468,"about_ca_system_score_codex":0.00015559212,"about_ca_system_score_gemma":0.000119562195,"threshold_uncertainty_score":0.0030130148},"labels":[],"label_agreement":null},{"id":"W4400491270","doi":"10.1016/j.compbiomed.2024.108811","title":"Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors","year":2024,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Institució Catalana de Recerca i Estudis Avançats; Northern California Institute for Research and Education; Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Pfizer; Biogen; BioClinica; Nvidia; F. Hoffmann-La Roche; Alzheimer's Society; University of Southern California; GlaxoSmithKline; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Artificial intelligence; Computer science; Segmentation; Pipeline (software); Pattern recognition (psychology); Neuroimaging; Magnetic resonance imaging; Similarity (geometry); Brain atlas; Brain tissue; Prior probability; Medicine; Radiology; Bayesian probability; Biomedical engineering; Image (mathematics)","score_opus":0.0551296310800513,"score_gpt":0.396634208431548,"score_spread":0.3415045773514967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400491270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04644049,0.00059118116,0.94380575,0.00037458647,0.000052199095,0.00007273611,0.00043860576,0.007183773,0.0010406828],"genre_scores_gemma":[0.39759654,0.00054070994,0.5925495,0.0006308542,0.00008325684,0.00023971352,0.0030227457,0.0009953973,0.004341274],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99942976,0.000111824105,0.000029293837,0.00022455321,0.00013269883,0.00007182917],"domain_scores_gemma":[0.9990048,0.0003847616,0.00016296835,0.00019757761,0.00019328126,0.000056748333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016674324,0.0014076367,0.0008334658,0.0011391633,0.00040940644,0.0010504513,0.0015663294,0.001568828,0.0016711799],"category_scores_gemma":[0.004150203,0.00064890616,0.0010601741,0.0006809209,0.0008477148,0.0012530247,0.0017430193,0.0020484691,0.001112022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037294606,0.0002904598,0.0038200056,0.00026864512,0.00027912573,0.00017809466,0.00025334078,0.36842296,0.04714251,0.0059957127,0.009620644,0.56335557],"study_design_scores_gemma":[0.000018631017,0.00005778722,0.0008765373,0.000023514782,0.000023788018,0.000065056796,0.000015149539,0.9826462,0.009123337,0.006060261,0.0010718446,0.000017870821],"about_ca_topic_score_codex":0.005685573,"about_ca_topic_score_gemma":0.0095471945,"teacher_disagreement_score":0.005685573,"about_ca_system_score_codex":0.0010916423,"about_ca_system_score_gemma":0.0014310702,"threshold_uncertainty_score":0.011304975},"labels":[],"label_agreement":null},{"id":"W4400524585","doi":"10.3174/ajnr.a8297","title":"Fractional Anisotropy is a More Sensitive Diagnostic Biomarker Than Mean Kurtosis for Patients with Parkinson Disease with Cognitive Dysfunction: A Diffusional Kurtosis Map Tract-Based Spatial Statistics Study","year":2024,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Kurtosis; Medicine; Fractional anisotropy; Biomarker; Parkinson's disease; Disease; Statistics; Diffusion MRI; Internal medicine; Radiology; Magnetic resonance imaging; Mathematics","score_opus":0.02171088772215245,"score_gpt":0.3148241680250375,"score_spread":0.293113280302885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400524585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99904436,0.0001877049,0.00047850623,0.00002826185,0.0000029601886,0.000007646796,0.000058228063,0.0000058509704,0.00018642508],"genre_scores_gemma":[0.9996039,0.000026723486,0.0002657467,0.000004933608,0.000005548407,0.0000041474204,0.000048730642,0.0000013910188,0.000038904214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979657,0.000056598983,0.00003160294,0.000051567346,0.00003977696,0.000023849352],"domain_scores_gemma":[0.99846184,0.0004586817,0.00064372976,0.000108960696,0.00018087841,0.00014589982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008817225,0.00041057507,0.00036735414,0.0010232048,0.00030325312,0.0005399653,0.00019732983,0.0004512061,0.0011513381],"category_scores_gemma":[0.003485073,0.0001696068,0.0003180523,0.00044742035,0.00037482864,0.0005515823,0.00032930681,0.0002512989,0.00022983013],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046528594,0.00006222044,0.99077964,0.000023533186,0.000117224634,0.00021859401,0.0001313093,0.00021194053,0.0028812834,0.00006727454,0.00008147777,0.004960208],"study_design_scores_gemma":[0.000033817996,0.00035960312,0.9932481,0.000011394916,0.00009590162,0.0016143644,0.00017705512,0.0027739787,0.001191473,0.00023650286,0.00024560085,0.000012247506],"about_ca_topic_score_codex":0.0010881568,"about_ca_topic_score_gemma":0.0013297752,"teacher_disagreement_score":0.0011513381,"about_ca_system_score_codex":0.00031705384,"about_ca_system_score_gemma":0.00034367706,"threshold_uncertainty_score":0.0046629906},"labels":[],"label_agreement":null},{"id":"W4400642964","doi":"10.1162/imag_a_00247","title":"Uncovering patterns of white matter degeneration in normal aging: Links between morphometry and microstructure","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Degeneration (medical); Psychology; Biology; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.026552404324141014,"score_gpt":0.3235926997866115,"score_spread":0.29704029546247046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400642964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98623717,0.0014859126,0.010934768,0.00010643536,0.000005522649,0.000013488432,0.00045138688,0.00006729696,0.00069799577],"genre_scores_gemma":[0.9934702,0.0005940662,0.005410252,0.000024610237,0.000007050386,0.000009618335,0.0002072282,0.000013277847,0.0002636751],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986506,0.00002882688,0.000013710203,0.00004990005,0.000028135966,0.000014417145],"domain_scores_gemma":[0.9994361,0.00009534446,0.00023534335,0.00011386018,0.00007625208,0.000043163363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081863726,0.0002485754,0.00025366328,0.0013156773,0.000220853,0.0005591889,0.00016356558,0.00027138507,0.00055026636],"category_scores_gemma":[0.001691704,0.00017038664,0.00019932391,0.0007264149,0.000529799,0.0007131793,0.00044181608,0.00023338295,0.000140815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044004302,0.00004405551,0.75062984,0.00022684419,0.0002777546,0.000288456,0.0015474852,0.0029509964,0.15173411,0.0018704396,0.00049315294,0.08949682],"study_design_scores_gemma":[0.0000021993415,0.00009136231,0.9876682,0.000024094083,0.00004096389,0.00054657774,0.0002474921,0.0031814524,0.004857137,0.0027014322,0.00062649226,0.000012569802],"about_ca_topic_score_codex":0.0035221528,"about_ca_topic_score_gemma":0.00847859,"teacher_disagreement_score":0.0035221528,"about_ca_system_score_codex":0.00022345768,"about_ca_system_score_gemma":0.00036341214,"threshold_uncertainty_score":0.0070033073},"labels":[],"label_agreement":null},{"id":"W4400822590","doi":"10.3389/fnins.2024.1391407","title":"White matter microstructure, traumatic brain injury, and disruptive behavior disorders in girls and boys","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut national de psychiatrie légale Philippe-Pinel; Université de Montréal; Université de Sherbrooke; McGill University","funders":"National Institute on Drug Abuse; National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"White matter; Psychology; Clinical psychology; Medicine; Developmental psychology; Magnetic resonance imaging","score_opus":0.022922172466045075,"score_gpt":0.33934897885010357,"score_spread":0.3164268063840585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400822590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99910444,0.00020744491,0.000019624395,0.00004239201,0.0000041182075,0.0000042530237,0.00033202628,0.0000027705744,0.0002827788],"genre_scores_gemma":[0.9992066,0.0001621688,0.00006579883,0.000017605547,0.000006172177,0.000008575874,0.00034221009,0.0000024210156,0.00018844643],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997887,0.000023589664,0.000022219672,0.00006324594,0.000052085157,0.000050200375],"domain_scores_gemma":[0.99950564,0.000051583273,0.0002587597,0.000020087647,0.000038507773,0.00012534898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028660885,0.00038143605,0.00038517325,0.0010458067,0.00065576757,0.00070345844,0.00042736594,0.00038757495,0.0029848986],"category_scores_gemma":[0.000931029,0.00025731316,0.0003353984,0.00091792544,0.00039993168,0.00041201047,0.0006542874,0.00045216476,0.00029393725],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020190291,0.000014670032,0.9987532,0.0000072315347,0.000014299362,0.00009300802,0.00016572996,0.000008375506,0.00013927674,0.000013081537,0.00004015384,0.00073088973],"study_design_scores_gemma":[0.0000010702729,0.000032555585,0.99922204,0.0000060798843,0.000006917471,0.0002604632,0.00033008127,0.000011767115,0.000038598308,0.000009458236,0.00008043044,5.988111e-7],"about_ca_topic_score_codex":0.013270877,"about_ca_topic_score_gemma":0.014498311,"teacher_disagreement_score":0.013270877,"about_ca_system_score_codex":0.0003477976,"about_ca_system_score_gemma":0.00041456148,"threshold_uncertainty_score":0.026387274},"labels":[],"label_agreement":null},{"id":"W4400903047","doi":"10.1186/s13041-024-01115-4","title":"The myelin water imaging transcriptome: myelin water fraction regionally varies with oligodendrocyte-specific gene expression","year":2024,"lang":"en","type":"article","venue":"Molecular Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Michael Smith Health Research BC; BC Children's Hospital; International Foundation for Research in Paraplegia; Craig H. Neilsen Foundation; National Science Foundation","keywords":"Myelin; Brain atlas; Neuroimaging; Gene expression; Biology; Transcriptome; Human brain; Neuroscience; Gene; Computational biology; Genetics; Central nervous system","score_opus":0.021237354560969424,"score_gpt":0.28844119972183135,"score_spread":0.26720384516086193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400903047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.957325,0.0014140372,0.030199207,0.00012631193,0.00002435575,0.00005606678,0.00774882,0.00030239834,0.0028040048],"genre_scores_gemma":[0.96759385,0.0011869477,0.021875191,0.00015001025,0.000026718142,0.00024239294,0.006535953,0.00016628105,0.002222549],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997789,0.000026667667,0.000012787163,0.00009519698,0.00005530973,0.00003117751],"domain_scores_gemma":[0.9996358,0.0000925048,0.000116724215,0.00003157382,0.00009758953,0.000025721287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030693464,0.0002305122,0.00036333074,0.00079257425,0.00031258364,0.0005332685,0.00014102246,0.00024611832,0.0011590547],"category_scores_gemma":[0.0007523305,0.00015600437,0.00023353341,0.0010684192,0.00033567977,0.0003788706,0.00033935177,0.0003156821,0.00032507646],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017932536,0.000031426407,0.03088337,0.00018856187,0.000068780435,0.000094429444,0.00038595524,0.0003434759,0.9495016,0.0003785566,0.00037645968,0.017568005],"study_design_scores_gemma":[0.000008970977,0.00031039107,0.8203741,0.00005702238,0.00017508921,0.0009101003,0.00062185706,0.0033378063,0.16760081,0.0013178668,0.0052411575,0.00004484881],"about_ca_topic_score_codex":0.0010827009,"about_ca_topic_score_gemma":0.001811778,"teacher_disagreement_score":0.0011590547,"about_ca_system_score_codex":0.0001935901,"about_ca_system_score_gemma":0.0002524049,"threshold_uncertainty_score":0.0038774014},"labels":[],"label_agreement":null},{"id":"W4400909329","doi":"10.1073/pnas.2403212121","title":"Sex and mental health are related to subcortical brain microstructure","year":2024,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation","funders":"National Institute of Mental Health; University of California, San Diego","keywords":"Amygdala; Psychology; Anxiety; Neuroscience; Thalamus; Mental health; Brain Structure and Function; Autism; Depression (economics); Diffusion MRI; Neuroimaging; Clinical psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.0518229110192636,"score_gpt":0.39850460994258463,"score_spread":0.346681698923321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400909329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99388593,0.0026728907,0.000441007,0.00022629678,0.000023092154,0.000012898903,0.00043750415,0.000007844005,0.0022924615],"genre_scores_gemma":[0.9988619,0.0003259319,0.00017239833,0.00004387648,0.000013552019,0.000004057746,0.00011186358,0.000005825639,0.00046056195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998053,0.000033637345,0.000016624212,0.000078946556,0.000038630194,0.000026970278],"domain_scores_gemma":[0.9993431,0.00012788898,0.00034256608,0.0000587554,0.000057743833,0.00006978614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021767452,0.00024038213,0.00019360153,0.0005467633,0.0002463815,0.00047948415,0.00016795675,0.00026530895,0.004093383],"category_scores_gemma":[0.0015646672,0.00013081782,0.00022185067,0.00036458744,0.00036208247,0.0002519601,0.00033167776,0.00019563532,0.00025624232],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024817704,0.000025396199,0.97412294,0.000045446744,0.00018844013,0.00027974916,0.00051218795,0.00004762764,0.005091908,0.00033036276,0.00022923006,0.01887842],"study_design_scores_gemma":[0.000001825035,0.000028250244,0.99890363,0.0000054499824,0.000011966892,0.00034220977,0.00007824394,0.00003303661,0.00016981989,0.00020161842,0.00022189831,0.0000021048636],"about_ca_topic_score_codex":0.0015322675,"about_ca_topic_score_gemma":0.0039879745,"teacher_disagreement_score":0.004093383,"about_ca_system_score_codex":0.00013084576,"about_ca_system_score_gemma":0.0001302624,"threshold_uncertainty_score":0.01369369},"labels":[],"label_agreement":null},{"id":"W4400932948","doi":"10.1162/imag_a_00259","title":"Tractography from T1-weighted MRI: Empirically exploring the clinical viability of streamline propagation without diffusion MRI","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Alzheimer's Association; National Institute on Aging; National Institute of Diabetes and Digestive and Kidney Diseases; Vanderbilt Memory and Alzheimer's Center; Vanderbilt University Medical Center; Vanderbilt University; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; National Institute of Mental Health; National Institutes of Health; National Science Foundation","keywords":"Tractography; Diffusion MRI; Computer science; Population; Neuroimaging; Limiting; White matter; Artificial intelligence; Magnetic resonance imaging; Medicine; Psychology; Neuroscience; Radiology","score_opus":0.12484921621911774,"score_gpt":0.41529681972330534,"score_spread":0.29044760350418763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400932948","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4351768,0.0017764102,0.5528251,0.0021855033,0.00022781143,0.00032891257,0.0014716274,0.003031384,0.0029765249],"genre_scores_gemma":[0.84437263,0.00092139497,0.14923745,0.00045384298,0.00009258604,0.00020918639,0.0020375613,0.0005746849,0.0021007624],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99906963,0.0004510102,0.000057881454,0.00023401962,0.00012629518,0.00006120716],"domain_scores_gemma":[0.9905524,0.0069667078,0.00065506133,0.00070303027,0.0007833022,0.00033956533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005029349,0.0012245744,0.000778498,0.0010845467,0.00047337572,0.0015907752,0.0014817463,0.001987852,0.0016190098],"category_scores_gemma":[0.029786745,0.00045517398,0.0008287734,0.00074990006,0.001240461,0.00247319,0.0015773516,0.0020882753,0.00071137375],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010802988,0.00020237811,0.02980784,0.00038748817,0.00036391112,0.0005022246,0.0004049512,0.84839624,0.004069797,0.005647886,0.004415343,0.10472154],"study_design_scores_gemma":[0.000036266287,0.00011273362,0.0014096434,0.000040338575,0.000027334976,0.000108884036,0.000030434636,0.99204755,0.0018432846,0.0037357463,0.0005913363,0.000016446933],"about_ca_topic_score_codex":0.020040989,"about_ca_topic_score_gemma":0.017478716,"teacher_disagreement_score":0.020040989,"about_ca_system_score_codex":0.0015550044,"about_ca_system_score_gemma":0.002254448,"threshold_uncertainty_score":0.039848685},"labels":[],"label_agreement":null},{"id":"W4401314990","doi":"10.1016/j.neuroimage.2024.120775","title":"Evaluation of cervical spinal cord atrophy using a modified SIENA approach","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; National Institute for Nanotechnology; Dodd-Walls Centre; Central European Initiative; U.S. Department of Defense","keywords":"Atrophy; Spinal cord; Medicine; Magnetic resonance imaging; Multiple sclerosis; Sample size determination; Nuclear medicine; Radiology; Physical medicine and rehabilitation; Pathology; Mathematics; Statistics","score_opus":0.2849929251162904,"score_gpt":0.44899335193755213,"score_spread":0.16400042682126176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401314990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5414129,0.006157044,0.43331143,0.0003051106,0.0002473709,0.0012214902,0.005365684,0.004269763,0.0077092443],"genre_scores_gemma":[0.539732,0.0015115639,0.44906804,0.00012056267,0.00008607133,0.00074445544,0.0041841646,0.00042949818,0.004123591],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99885607,0.00017558508,0.0001253728,0.00035370866,0.00042249434,0.00006676086],"domain_scores_gemma":[0.99860966,0.00032249896,0.00021888464,0.00020725223,0.0005670526,0.00007457573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015898832,0.0009337238,0.00097505597,0.0062252884,0.0004605249,0.0013784445,0.0008563918,0.00085785403,0.002576892],"category_scores_gemma":[0.00492287,0.00030165218,0.0010952043,0.0018056475,0.0005332408,0.0006611818,0.0010890352,0.0004502246,0.0007100174],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001643296,0.00020904721,0.0759538,0.0016807936,0.0022356508,0.0008428138,0.0009804823,0.043126993,0.15368205,0.0034070837,0.00477003,0.7114679],"study_design_scores_gemma":[0.00019356277,0.0016852587,0.3797989,0.00046532947,0.0014043562,0.007977938,0.00093267765,0.4662215,0.10428631,0.007036391,0.029480606,0.000517232],"about_ca_topic_score_codex":0.007833747,"about_ca_topic_score_gemma":0.015774416,"teacher_disagreement_score":0.007833747,"about_ca_system_score_codex":0.0006256218,"about_ca_system_score_gemma":0.0012107717,"threshold_uncertainty_score":0.015576303},"labels":[],"label_agreement":null},{"id":"W4401367286","doi":"10.4103/nrr.nrr-d-23-01392","title":"A radiomics approach for predicting gait freezing in Parkinson’s disease based on resting-state functional magnetic resonance imaging indices: A cross-sectional study","year":2024,"lang":"en","type":"article","venue":"Neural Regeneration Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Liaoning Province","keywords":"Magnetic resonance imaging; Parkinson's disease; Gait; Medicine; Disease; Functional magnetic resonance imaging; Physical medicine and rehabilitation; Gait analysis; Pathology; Radiology","score_opus":0.1611351498607611,"score_gpt":0.4212158446894742,"score_spread":0.2600806948287131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401367286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990416,0.00015891875,0.00045785404,0.000012536864,0.000006888266,0.00003836723,0.000082774015,0.000003533933,0.00019759093],"genre_scores_gemma":[0.99918157,0.0000764209,0.00047274074,0.000016052272,0.000010025072,0.0000287899,0.00013696971,0.000001477028,0.000075939075],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996959,0.00011111676,0.000039966228,0.0000790173,0.000046577505,0.000027434091],"domain_scores_gemma":[0.99887687,0.0003467272,0.00024595048,0.00008827944,0.00029777383,0.0001442974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016468139,0.0005196656,0.00040013305,0.0012485351,0.00028079265,0.00046178696,0.00024281531,0.0006269227,0.0006448479],"category_scores_gemma":[0.0028611189,0.0003076621,0.00053843425,0.0003468908,0.0003094843,0.00054626056,0.00034971203,0.00037488673,0.00029801045],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005572364,0.00023030795,0.9943481,0.000014692362,0.000116743664,0.00010492176,0.00018632131,0.00014617291,0.0010905835,0.000012967845,0.00004655608,0.0031453392],"study_design_scores_gemma":[0.000033618067,0.0019120069,0.9947503,0.00000984733,0.00013171953,0.0005203017,0.0003151845,0.001786886,0.00032521895,0.000030191079,0.00017126251,0.000013421688],"about_ca_topic_score_codex":0.0015005663,"about_ca_topic_score_gemma":0.0017076,"teacher_disagreement_score":0.0016468139,"about_ca_system_score_codex":0.0001811899,"about_ca_system_score_gemma":0.00017127079,"threshold_uncertainty_score":0.0087093115},"labels":[],"label_agreement":null},{"id":"W4401385585","doi":"10.3389/fnins.2024.1440653","title":"Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Barrow Neurological Foundation; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Kurtosis; Diffusion MRI; White matter; Diffusion imaging; Cognitive impairment; Diffusion; Magnetic resonance imaging; Cognition; Psychology; Nuclear magnetic resonance; Neuroscience; Medicine; Physics; Radiology; Mathematics; Statistics","score_opus":0.05171655342244838,"score_gpt":0.2997681900204657,"score_spread":0.2480516365980173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401385585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99259937,0.0012101863,0.0054061003,0.000048571612,0.0000053764047,0.000038489725,0.00013150078,0.000021144462,0.000539337],"genre_scores_gemma":[0.99070543,0.00087771245,0.008001481,0.00002635613,0.000016076738,0.000022774682,0.00013227107,0.00000444218,0.00021347785],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99989176,0.000026010526,0.00001266162,0.000026556061,0.000026965794,0.000016130169],"domain_scores_gemma":[0.9997919,0.00003730868,0.00007417297,0.00001662169,0.000045942612,0.00003415989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008282326,0.00049960456,0.00027288575,0.0018698768,0.00024976133,0.00043000642,0.00020911146,0.00027407997,0.0006360969],"category_scores_gemma":[0.0008327017,0.00012955088,0.00022583477,0.0005420623,0.00037098647,0.0005189817,0.00043032796,0.00019857271,0.00010121339],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013340259,0.00034950709,0.3742655,0.00074392895,0.0005693053,0.0017420504,0.0009971183,0.0013426065,0.52589196,0.0006685576,0.00048741384,0.09160804],"study_design_scores_gemma":[0.000040723902,0.001193185,0.9301974,0.00006700471,0.00031095886,0.005572294,0.0006972678,0.0050664875,0.05393468,0.0014411231,0.0014278641,0.000050937557],"about_ca_topic_score_codex":0.0015423262,"about_ca_topic_score_gemma":0.0033417458,"teacher_disagreement_score":0.0018698768,"about_ca_system_score_codex":0.000166533,"about_ca_system_score_gemma":0.00032476822,"threshold_uncertainty_score":0.0043801665},"labels":[],"label_agreement":null},{"id":"W4401507606","doi":"10.1101/2024.08.12.607581","title":"Longitudinal deformation based morphometry pipeline to study neuroanatomical differences in structural MRI based on SyN unbiased templates","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Hospital for Sick Children; Ontario Brain Institute","funders":"","keywords":"dBm; Pipeline (software); Segmentation; Magnetic resonance imaging; Brain size; Neuroimaging; Longitudinal study; Volume (thermodynamics); Computer science; Statistical power; Psychology; Artificial intelligence; Neuroscience; Pattern recognition (psychology); Medicine; Mathematics; Statistics; Pathology; Physics; Radiology; Telecommunications","score_opus":0.04383876866835115,"score_gpt":0.3062636692934381,"score_spread":0.26242490062508694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401507606","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.096910745,0.00051774026,0.8762955,0.00034093473,0.00008170705,0.00038540523,0.0035081091,0.020572258,0.0013875178],"genre_scores_gemma":[0.33428645,0.00036934612,0.64768946,0.00022876865,0.0000965695,0.00079819513,0.011215568,0.0015423679,0.0037732017],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969196,0.00003945787,0.000018436476,0.00010602865,0.00010523895,0.00003890018],"domain_scores_gemma":[0.99945253,0.00013042279,0.00009358047,0.00012059123,0.00016189252,0.000040986943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011414945,0.00078024296,0.00075746037,0.0017142785,0.00032094907,0.0008288311,0.0010262526,0.0006284907,0.0035393508],"category_scores_gemma":[0.0024669257,0.00047836156,0.0010890455,0.001023566,0.00028288126,0.00048785572,0.0010502337,0.0007329757,0.0019730295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006798681,0.00039959722,0.019197172,0.00040353442,0.0004934546,0.00043469577,0.00047667974,0.07356183,0.2263651,0.0048941164,0.022293614,0.6508004],"study_design_scores_gemma":[0.00008285643,0.00033233187,0.03133065,0.00002815547,0.000119883436,0.000604421,0.00012461674,0.90296227,0.04504719,0.0071748025,0.012123709,0.00006914844],"about_ca_topic_score_codex":0.004678557,"about_ca_topic_score_gemma":0.00889825,"teacher_disagreement_score":0.004678557,"about_ca_system_score_codex":0.00039833342,"about_ca_system_score_gemma":0.0010108897,"threshold_uncertainty_score":0.0118403435},"labels":[],"label_agreement":null},{"id":"W4401522547","doi":"10.1097/wad.0000000000000642","title":"DXA-Measured Abdominal Adipose Depots and Structural Brain Integrity in Postmenopausal Women","year":2024,"lang":"en","type":"article","venue":"Alzheimer Disease & Associated Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Adipose tissue; Medicine; Abdominal fat; Atrophy; Postmenopausal women; Intra-Abdominal Fat; Brain tissue; Subcutaneous fat; Lesion; Subcutaneous adipose tissue; Magnetic resonance imaging; Internal medicine; Endocrinology; Radiology; Pathology; Obesity; Visceral fat; Insulin resistance","score_opus":0.035195802899079476,"score_gpt":0.3394532787900382,"score_spread":0.30425747589095875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401522547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981065,0.0010020816,0.000047822392,0.000058546186,0.0000055366245,0.0000042141673,0.0003376817,0.0000024809442,0.00043512418],"genre_scores_gemma":[0.99934024,0.00029936843,0.000054929824,0.000025821513,0.000007826264,0.0000046826485,0.00014552854,7.2310013e-7,0.00012080028],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991834,0.000020536632,0.000008748843,0.000023950066,0.000015349444,0.000013051338],"domain_scores_gemma":[0.9996406,0.00006460285,0.00018770268,0.00003412893,0.000038691145,0.000034277735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004015463,0.00021346846,0.00020290859,0.00033121073,0.00025058902,0.00042285843,0.00017648427,0.00021263622,0.0013776249],"category_scores_gemma":[0.0010216379,0.00014484844,0.00022714709,0.0005067552,0.000190083,0.00011951193,0.00025467062,0.00032106167,0.00013488893],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027874598,0.000018446812,0.9961552,0.000025225349,0.00013162119,0.000047753485,0.000093798015,0.000028337017,0.0006072975,0.00002093957,0.0000694668,0.0025230667],"study_design_scores_gemma":[0.000008848051,0.000046152345,0.9993973,0.000009449687,0.000066557564,0.00011707704,0.00007534778,0.000026666617,0.000073445284,0.00003341,0.00014472273,0.0000011695473],"about_ca_topic_score_codex":0.005673409,"about_ca_topic_score_gemma":0.0090158265,"teacher_disagreement_score":0.005673409,"about_ca_system_score_codex":0.00014916726,"about_ca_system_score_gemma":0.00016801716,"threshold_uncertainty_score":0.011280775},"labels":[],"label_agreement":null},{"id":"W4401525937","doi":"10.1016/j.mri.2025.110424","title":"Harmonized connectome resampling for variance in voxel sizes","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vanderbilt Kennedy Center, Vanderbilt University Medical Center; Georgia Clinical and Translational Science Alliance; McMaster University; National Institute on Aging; Vanderbilt Institute for Clinical and Translational Research; National Cancer Institute; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University","keywords":"Resampling; Connectome; Variance (accounting); Voxel; Computer science; Statistics; Artificial intelligence; Pattern recognition (psychology); Mathematics; Psychology; Neuroscience; Functional connectivity","score_opus":0.046902943086093454,"score_gpt":0.3656866638133341,"score_spread":0.31878372072724065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401525937","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.104668684,0.0002678132,0.88681555,0.00019849262,0.00018268952,0.0011203947,0.0015591296,0.004063042,0.0011242488],"genre_scores_gemma":[0.28282088,0.00013414783,0.7047246,0.00024370554,0.00006452106,0.0035451069,0.004309421,0.0026540067,0.0015035233],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99540836,0.0021126478,0.00036674587,0.0011674828,0.0007254934,0.00021921181],"domain_scores_gemma":[0.9892777,0.0040681665,0.00047452684,0.0049381936,0.0011369605,0.00010436862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012593657,0.00084576383,0.0012103474,0.0017361878,0.0012727663,0.0012569394,0.0015567666,0.0009811901,0.004218257],"category_scores_gemma":[0.042486273,0.0005623354,0.001681281,0.0018039165,0.0012067201,0.00093241525,0.00218942,0.0018287018,0.0010272225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032608309,0.0009497485,0.031681865,0.0012891799,0.0026223133,0.000852341,0.004463589,0.18042602,0.10851203,0.053263865,0.030993227,0.58168507],"study_design_scores_gemma":[0.0008237239,0.0016102789,0.061129,0.00016380464,0.00072959875,0.0010363322,0.00075729284,0.7071633,0.10303738,0.07520872,0.048046887,0.00029372043],"about_ca_topic_score_codex":0.004830102,"about_ca_topic_score_gemma":0.006961356,"teacher_disagreement_score":0.012593657,"about_ca_system_score_codex":0.00074007915,"about_ca_system_score_gemma":0.0017871096,"threshold_uncertainty_score":0.06660241},"labels":[],"label_agreement":null},{"id":"W4401540984","doi":"10.3390/app14167001","title":"MRI Diffusion Connectomics-Based Characterization of Progression in Alzheimer’s Disease","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University; Memorial University of Newfoundland","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; St. Francis Xavier University; Canada Foundation for Innovation; National Institute of Biomedical Imaging and Bioengineering; Nova Scotia Research Innovation Trust; Foundation for the National Institutes of Health","keywords":"Connectomics; Diffusion MRI; Disease; Medicine; Biomarker; Neuroscience; Pathology; Psychology; Magnetic resonance imaging; Radiology; Connectome; Functional connectivity; Biology","score_opus":0.06855626450805484,"score_gpt":0.38315750755329625,"score_spread":0.3146012430452414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401540984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9857017,0.0015762277,0.010278963,0.00014484757,0.000009117982,0.000020641632,0.0015221616,0.00006701615,0.00067931105],"genre_scores_gemma":[0.99304247,0.00048777717,0.004773495,0.000018415882,0.000016196955,0.000017162085,0.0014306773,0.000011780028,0.00020204367],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998319,0.00007318707,0.000013760547,0.00004474501,0.000021749822,0.000014712623],"domain_scores_gemma":[0.99932885,0.00019305396,0.00020741473,0.00011977577,0.00009240895,0.000058466925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011305016,0.00038404617,0.00037733364,0.0015045912,0.0001983411,0.0005681777,0.00022875803,0.0002733855,0.00056816335],"category_scores_gemma":[0.0026095419,0.000118949836,0.0002391543,0.0007152587,0.00023297455,0.00051551627,0.00036158954,0.00030678103,0.00018265165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009410087,0.00016939866,0.84685826,0.0001944927,0.00060195354,0.00036335,0.00038237762,0.017942484,0.038858,0.0014218878,0.0014357887,0.090831056],"study_design_scores_gemma":[0.000029194338,0.00020177048,0.90883285,0.00007505772,0.00018872981,0.0011019369,0.00023161776,0.073241316,0.0064380406,0.007371739,0.0022415533,0.000046162404],"about_ca_topic_score_codex":0.0031142058,"about_ca_topic_score_gemma":0.0065096244,"teacher_disagreement_score":0.0031142058,"about_ca_system_score_codex":0.00018739514,"about_ca_system_score_gemma":0.00027922663,"threshold_uncertainty_score":0.0061921477},"labels":[],"label_agreement":null},{"id":"W4401557770","doi":"10.1002/nbm.5227","title":"Automatic deep learning segmentation of the hippocampus on high‐resolution diffusion magnetic resonance imaging and its application to the healthy lifespan","year":2024,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation; University Hospital Foundation; Ministry of Advanced Education, Government of Alberta; Women and Children's Health Research Institute; Children's Health Research Institute","keywords":"Fractional anisotropy; Diffusion MRI; Magnetic resonance imaging; Segmentation; Artificial intelligence; Hippocampus; Computer science; Sørensen–Dice coefficient; Voxel; Population; Pattern recognition (psychology); Image segmentation; Neuroscience; Medicine; Psychology; Radiology","score_opus":0.017071568410379562,"score_gpt":0.3269405340313867,"score_spread":0.30986896562100713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401557770","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75126684,0.0013789587,0.24293439,0.0003056695,0.000086103915,0.00011835619,0.0007977795,0.0015930114,0.0015188637],"genre_scores_gemma":[0.88356876,0.0002848636,0.11348674,0.00006537295,0.000029595896,0.00007111281,0.00068318413,0.000087928325,0.0017224891],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997209,0.00007371576,0.000018242174,0.00011392109,0.00004161824,0.000031679945],"domain_scores_gemma":[0.999413,0.00019135464,0.00009089029,0.0001012617,0.00017068001,0.0000327835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010056453,0.00064435863,0.00043039396,0.0008930396,0.00025768657,0.0004391912,0.0005291901,0.0007078976,0.0007113626],"category_scores_gemma":[0.0024457762,0.00027147486,0.00054955017,0.0003341384,0.000330398,0.0004255938,0.0006589759,0.00038863087,0.00029179594],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079480343,0.00025602174,0.026970673,0.0002534554,0.00033960937,0.00048284157,0.0004488206,0.14902611,0.104313724,0.0019066236,0.0040700324,0.7111374],"study_design_scores_gemma":[0.000042730084,0.00026076482,0.027411697,0.000050903076,0.00007290299,0.00046327652,0.00008246201,0.9355335,0.031031528,0.0031304453,0.0018731806,0.00004656172],"about_ca_topic_score_codex":0.0072800466,"about_ca_topic_score_gemma":0.010717772,"teacher_disagreement_score":0.0072800466,"about_ca_system_score_codex":0.000408769,"about_ca_system_score_gemma":0.0006464272,"threshold_uncertainty_score":0.014475346},"labels":[],"label_agreement":null},{"id":"W4401589671","doi":"10.1038/s41390-024-03463-2","title":"Methodological considerations on diffusion MRI tractography in infants aged 0–2 years: a scoping review","year":2024,"lang":"en","type":"review","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Neuroimaging; Psychology; Neuroscience; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.7491203727056088,"score_gpt":0.6474514212079429,"score_spread":0.10166895149766597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401589671","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015974873,0.99718565,0.00054411805,0.001212109,0.00035533606,0.000092127615,0.000108069136,0.000008559377,0.00033416963],"genre_scores_gemma":[0.0021297298,0.9938744,0.002034704,0.0010424025,0.0002221601,0.00040780014,0.00013401476,0.000012908376,0.00014183913],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9764865,0.006954745,0.0112966895,0.0016541495,0.0032808871,0.00032698136],"domain_scores_gemma":[0.7561037,0.20893854,0.014860111,0.0030811387,0.016316907,0.00069963234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03585478,0.0016912322,0.0048840335,0.015065691,0.0013949389,0.004654235,0.0032900607,0.004226401,0.0035783283],"category_scores_gemma":[0.1662471,0.0015096866,0.005642264,0.012720109,0.0025268232,0.0064575975,0.00288573,0.0030318275,0.0009474646],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008850939,0.000018618688,0.00088311377,0.61506146,0.0016147952,0.0003079091,0.0010199432,0.00031946672,0.00035653927,0.0033517971,0.009154246,0.3678236],"study_design_scores_gemma":[0.000016841559,0.00004103295,0.0012194122,0.8853564,0.0038057044,0.00037887166,0.00037019714,0.00009933066,0.0002092811,0.0018787277,0.10658661,0.000037576538],"about_ca_topic_score_codex":0.011933803,"about_ca_topic_score_gemma":0.022425666,"teacher_disagreement_score":0.03585478,"about_ca_system_score_codex":0.0039202883,"about_ca_system_score_gemma":0.018843697,"threshold_uncertainty_score":0.18962044},"labels":[],"label_agreement":null},{"id":"W4401693937","doi":"10.1038/s41386-024-01934-y","title":"Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry","year":2024,"lang":"en","type":"review","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Neuromelanin; Catecholaminergic; Neuroscience; Locus coeruleus; Substantia nigra; Dopaminergic; Biomarker; Psychology; Dopamine; Biology; Central nervous system; Biochemistry","score_opus":0.30786089324811633,"score_gpt":0.5419774707818467,"score_spread":0.23411657753373033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401693937","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011211165,0.99837315,0.00034366723,0.000312262,0.00015005673,0.0000065276104,0.000026442443,0.000009377284,0.0006662535],"genre_scores_gemma":[0.0009422946,0.99735343,0.0006274402,0.0003255297,0.00022335447,0.0000121676885,0.00004837944,0.0000023570624,0.0004651064],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99983776,0.00003885843,0.000020713529,0.00003507264,0.00004679749,0.00002075355],"domain_scores_gemma":[0.99949276,0.0003008691,0.000059645274,0.00001716675,0.00010078006,0.000028741219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012021322,0.0010929658,0.0015432943,0.001605271,0.00019393189,0.0011061998,0.00090183335,0.001274478,0.0034649957],"category_scores_gemma":[0.0013889769,0.00031093878,0.00049142924,0.0014899749,0.0006457853,0.0013528359,0.0007434428,0.0018329576,0.0019523816],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015699341,0.000077800054,0.00020930427,0.011894313,0.00014359683,0.00020745335,0.000027512304,0.0003191661,0.003069347,0.0036481996,0.018511439,0.96173483],"study_design_scores_gemma":[0.00011023429,0.0002585573,0.0014852706,0.006471743,0.0004370362,0.0019055561,0.00007804543,0.0003669892,0.00276899,0.008515607,0.9775434,0.000058473957],"about_ca_topic_score_codex":0.0013908665,"about_ca_topic_score_gemma":0.0032696552,"teacher_disagreement_score":0.0034649957,"about_ca_system_score_codex":0.000565674,"about_ca_system_score_gemma":0.001492966,"threshold_uncertainty_score":0.011591554},"labels":[],"label_agreement":null},{"id":"W4401737335","doi":"10.1016/j.mri.2024.110221","title":"Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Diffusion MRI; White matter; Diffusion; Microstructure; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Physics; Medicine; Radiology; Thermodynamics; Composite material","score_opus":0.02711337820230662,"score_gpt":0.3125536775083727,"score_spread":0.28544029930606607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401737335","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028088175,0.0007030349,0.9681988,0.0004213873,0.000020615513,0.000058043486,0.00018704316,0.00025445802,0.002068385],"genre_scores_gemma":[0.6169318,0.0036319618,0.36487955,0.00021776844,0.00008970099,0.00074022583,0.0005602555,0.00033325193,0.012615533],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987507,0.000040728533,0.000006704617,0.000036503247,0.000028231398,0.000012796542],"domain_scores_gemma":[0.99963367,0.00019922484,0.00006207955,0.000028636046,0.000060114384,0.000016274274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008421748,0.0007025754,0.00066562457,0.0004107295,0.00022611163,0.0010605943,0.0008896425,0.0015546394,0.00096182624],"category_scores_gemma":[0.0016564454,0.0005144358,0.0008010448,0.00036801278,0.00042611422,0.0008141819,0.0006328156,0.00089033914,0.00036098095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041517924,0.000033678334,0.0009414795,0.00008360977,0.00004025629,0.000097613614,0.00005952456,0.9707529,0.0052868784,0.011686782,0.00040410264,0.01057163],"study_design_scores_gemma":[0.0000047635535,0.000010876049,0.00019424161,0.000007939002,0.0000076049673,0.000026684605,0.000006900287,0.9954917,0.00038426075,0.0033101505,0.00054834515,0.0000065736217],"about_ca_topic_score_codex":0.0068412726,"about_ca_topic_score_gemma":0.0047970833,"teacher_disagreement_score":0.0068412726,"about_ca_system_score_codex":0.0004932986,"about_ca_system_score_gemma":0.00076289667,"threshold_uncertainty_score":0.013602912},"labels":[],"label_agreement":null},{"id":"W4401827704","doi":"10.1101/2024.08.21.608995","title":"Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer’s disease","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Concordia University","funders":"","keywords":"Apolipoprotein E; Family history; Disease; White matter; Affect (linguistics); Glycated hemoglobin; Psychology; Cognition; Risk factor; Blood pressure; Medicine; Internal medicine; Gerontology; Endocrinology; Neuroscience; Type 2 diabetes; Diabetes mellitus; Magnetic resonance imaging","score_opus":0.04311881122111306,"score_gpt":0.27275612125670345,"score_spread":0.2296373100355904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401827704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988954,0.00031869646,0.00013135464,0.000050344042,0.000008986834,0.0000015642665,0.0001845246,0.0000043265195,0.00040469418],"genre_scores_gemma":[0.99918,0.00009344091,0.00009938199,0.000016644455,0.000014303496,0.000001888453,0.00012533623,0.000003091696,0.00046581868],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998758,0.000025037376,0.000010700426,0.000047075275,0.000017701528,0.00002356422],"domain_scores_gemma":[0.9995364,0.00008350179,0.00018683288,0.00005744059,0.00004973971,0.00008613484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030924685,0.00032006294,0.00024534937,0.00053759426,0.00019208294,0.00042796685,0.00015901028,0.00033515485,0.0035108144],"category_scores_gemma":[0.0010269015,0.0001349701,0.00030614762,0.00039024095,0.00014994988,0.00017105488,0.0002488792,0.00026912277,0.00024076932],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006663276,0.00005345641,0.99041533,0.000015431784,0.0001859396,0.00029762526,0.00011214956,0.000047566384,0.0033094902,0.000047698028,0.00014348963,0.0047055017],"study_design_scores_gemma":[0.00000411042,0.000055097087,0.99898106,0.000003148087,0.00004064189,0.00030001526,0.000056033045,0.000113227965,0.00027476597,0.00008886636,0.00008110596,0.0000018915536],"about_ca_topic_score_codex":0.0014458349,"about_ca_topic_score_gemma":0.0016421253,"teacher_disagreement_score":0.0035108144,"about_ca_system_score_codex":0.00008347733,"about_ca_system_score_gemma":0.0001768183,"threshold_uncertainty_score":0.011744797},"labels":[],"label_agreement":null},{"id":"W4401828721","doi":"10.1097/j.pain.0000000000003345","title":"What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review","year":2024,"lang":"en","type":"review","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arthritis Society","keywords":"Magnetic resonance imaging; Narrative review; Narrative; Chronic pain; Medicine; Functional magnetic resonance imaging; Diffusion MRI; Psychology; Neuroscience; Radiology; Philosophy; Intensive care medicine; Linguistics","score_opus":0.059806742251609805,"score_gpt":0.3814469241030221,"score_spread":0.3216401818514123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401828721","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000071999115,0.9986952,0.000038234542,0.00070356857,0.00019271988,0.000002410058,0.000014140185,0.0000018627088,0.00027993816],"genre_scores_gemma":[0.00076965406,0.9983784,0.000063074265,0.00040512538,0.00029106977,0.000003962896,0.000014005085,9.028459e-7,0.00007377512],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995603,0.00010743327,0.00010383833,0.000087934364,0.0001101941,0.000030361723],"domain_scores_gemma":[0.99704283,0.0021849568,0.0003217652,0.000039048176,0.0003377007,0.00007367854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001097655,0.00075220293,0.0016629131,0.0035094516,0.00046628033,0.0019533378,0.0009774785,0.0018888023,0.0034870545],"category_scores_gemma":[0.00495632,0.00033018106,0.00087755354,0.0035897116,0.0009319151,0.0028476706,0.00076882687,0.0015989549,0.0008186147],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013532405,0.000040920113,0.0006157068,0.20457666,0.00042027657,0.0005184704,0.0005606539,0.00030098794,0.0005995358,0.007510819,0.046453144,0.73826754],"study_design_scores_gemma":[0.00003714131,0.00014007083,0.0037867413,0.18641782,0.0012293011,0.007040746,0.00081603153,0.00018881568,0.00032955897,0.006355463,0.79358155,0.00007661719],"about_ca_topic_score_codex":0.0021856844,"about_ca_topic_score_gemma":0.0032086812,"teacher_disagreement_score":0.0035094516,"about_ca_system_score_codex":0.0009846864,"about_ca_system_score_gemma":0.0029795566,"threshold_uncertainty_score":0.011665344},"labels":[],"label_agreement":null},{"id":"W4401852142","doi":"10.1016/j.media.2024.103309","title":"Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Inference; Computer science; Generative model; Artificial intelligence; Machine learning; Statistical inference; Bayesian inference; Bayesian probability; Pattern recognition (psychology); Generative grammar; Mathematics; Statistics","score_opus":0.07956383460373577,"score_gpt":0.39229125966041684,"score_spread":0.31272742505668105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401852142","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029502325,0.00006161764,0.96939474,0.00017921114,0.00001280075,0.000033970326,0.00008499837,0.00036412897,0.00036608858],"genre_scores_gemma":[0.779261,0.00017119567,0.21806142,0.00012914224,0.00008846011,0.00017125542,0.00080168684,0.0001534468,0.001162447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823904,0.0007241722,0.000069762646,0.000530891,0.00029177224,0.00014437287],"domain_scores_gemma":[0.9928639,0.004729116,0.00073793955,0.0008834895,0.0005428669,0.00024264726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002754307,0.00086640945,0.0012579329,0.0015807127,0.00072525523,0.0014321937,0.0018509825,0.0020587612,0.001716962],"category_scores_gemma":[0.014152261,0.0007093279,0.0014017179,0.0014536891,0.0016190645,0.002770408,0.0022800236,0.002435406,0.00075195637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046636365,0.0006778172,0.015211252,0.00033367134,0.0006528888,0.0005543648,0.0008863694,0.58062136,0.018329674,0.07523413,0.0057036444,0.3013284],"study_design_scores_gemma":[0.000009287016,0.000036974205,0.0007625684,0.00000742016,0.000023997725,0.000046018085,0.000032632674,0.9680378,0.0008470715,0.029974692,0.00021264752,0.000009010834],"about_ca_topic_score_codex":0.0040436545,"about_ca_topic_score_gemma":0.0067277583,"teacher_disagreement_score":0.0040436545,"about_ca_system_score_codex":0.0006825949,"about_ca_system_score_gemma":0.0017780021,"threshold_uncertainty_score":0.014566302},"labels":[],"label_agreement":null},{"id":"W4401856347","doi":"10.1101/2024.08.19.608590","title":"The developing hippocampus: Microstructural evolution through childhood and adolescence","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Engineering and Physical Sciences Research Council; UK Research and Innovation; National Institutes of Health; Children's Hospital Foundation; Canada First Research Excellence Fund; Canada Research Chairs; Wellcome Trust; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Diffusion MRI; Subiculum; Hippocampus; Neuroscience; Psychology; Soma; Neurite; White matter; Medicine; Chemistry; Magnetic resonance imaging; Dentate gyrus","score_opus":0.021995759269147163,"score_gpt":0.2766549236822922,"score_spread":0.25465916441314507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401856347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998733,0.00055399846,0.00019945123,0.000019805986,0.0000013625371,0.0000030833858,0.00015646122,0.0000046770415,0.00032826953],"genre_scores_gemma":[0.99885213,0.0005289755,0.0003462598,0.0000051037696,0.0000014464501,0.0000054673437,0.00012283183,0.0000041706044,0.00013362496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998957,0.000014527091,0.000009872389,0.00003267461,0.000026749543,0.000020544081],"domain_scores_gemma":[0.9996623,0.000060949344,0.00014395999,0.000022847722,0.000077699995,0.000032248056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028816075,0.00015210989,0.0001755461,0.0007077418,0.0001908208,0.00050119957,0.00014939514,0.00018164191,0.000491156],"category_scores_gemma":[0.0010607424,0.0001724375,0.00019681048,0.0004691527,0.0002696349,0.00043353127,0.000368768,0.00019928666,0.00013036591],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024687542,0.00003021153,0.94837934,0.00007552244,0.00006865651,0.0006259977,0.0035751746,0.00039160787,0.014514713,0.00030758564,0.00016253265,0.03162172],"study_design_scores_gemma":[5.903331e-7,0.000028850634,0.99813557,0.000010267271,0.000009441881,0.000397606,0.00049220596,0.00010361668,0.00049252366,0.00006417332,0.00026268166,0.00000230753],"about_ca_topic_score_codex":0.0067509026,"about_ca_topic_score_gemma":0.010499386,"teacher_disagreement_score":0.0067509026,"about_ca_system_score_codex":0.00022001671,"about_ca_system_score_gemma":0.00025012332,"threshold_uncertainty_score":0.013423204},"labels":[],"label_agreement":null},{"id":"W4401894643","doi":"10.1002/hbm.26811","title":"Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega‐analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes","year":2024,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of British Columbia Hospital; Alberta Children's Hospital; University of Calgary; University of British Columbia; Queen's University","funders":"RWTH Aachen University","keywords":"Voxel; Concussion; White matter; Diffusion MRI; Grey matter; Psychology; Poison control; Medicine; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.06095162663689272,"score_gpt":0.37330124197634734,"score_spread":0.3123496153394546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401894643","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53030527,0.38277003,0.059445497,0.0027677768,0.00016251295,0.00083557825,0.019497227,0.00024624736,0.0039699525],"genre_scores_gemma":[0.92510223,0.037059646,0.029808264,0.00048563746,0.000110353576,0.00080571836,0.0061116307,0.00006535727,0.00045112518],"study_design_codex":"design_other","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9974819,0.0011155088,0.00047969155,0.0005531593,0.0002911722,0.00007854781],"domain_scores_gemma":[0.9862541,0.009826281,0.0018788202,0.0010205056,0.00090807123,0.00011217396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057173218,0.00056776736,0.0012921527,0.0086364625,0.0004926435,0.00133611,0.00085944263,0.00049171457,0.0013016918],"category_scores_gemma":[0.024319919,0.0004171585,0.0026300773,0.0053008236,0.0006144201,0.0009800125,0.0014246765,0.00040787124,0.00018246593],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015497241,0.0001326091,0.3252411,0.118751526,0.035477906,0.001642414,0.0039236206,0.004272976,0.016908545,0.004972325,0.0052091577,0.48191825],"study_design_scores_gemma":[0.000266419,0.0016057761,0.7634009,0.025576519,0.09250597,0.0025730978,0.0055050966,0.011214541,0.008281968,0.01989541,0.068961725,0.0002125267],"about_ca_topic_score_codex":0.0033719463,"about_ca_topic_score_gemma":0.010064599,"teacher_disagreement_score":0.0086364625,"about_ca_system_score_codex":0.00053847115,"about_ca_system_score_gemma":0.0021110093,"threshold_uncertainty_score":0.030236423},"labels":[],"label_agreement":null},{"id":"W4401928009","doi":"10.3389/fnhum.2024.1432830","title":"Sex differences in patterns of white matter neuroplasticity after balance training in young adults","year":2024,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Neuroplasticity; Psychology; Balance (ability); Motor skill; White matter; Motor learning; Developmental psychology; Young adult; Physical medicine and rehabilitation; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.03339143975419038,"score_gpt":0.30101934352845217,"score_spread":0.26762790377426177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401928009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998928,0.0002952339,0.00011116884,0.000028426302,0.000008652501,0.0000046190085,0.00014679116,0.0000030703684,0.00047388763],"genre_scores_gemma":[0.9990017,0.00009223486,0.00007217392,0.000021010741,0.0000060150414,0.0000063623543,0.00008290943,0.0000025463848,0.0007150253],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993265,0.000006993657,0.0000064990595,0.000028509543,0.000013360613,0.0000118924145],"domain_scores_gemma":[0.99977666,0.000034513938,0.00010898064,0.0000139514095,0.000030981144,0.000034994653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001897355,0.00013329895,0.00016348061,0.0002649798,0.00013372557,0.00018078332,0.000080919395,0.00017004192,0.0027001642],"category_scores_gemma":[0.00060331303,0.00006755932,0.00008271647,0.00010644338,0.00014010823,0.00014796342,0.0001382633,0.00008457642,0.00031802352],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002060338,0.00017541136,0.87823004,0.00012332566,0.00011176696,0.00097653904,0.0021903464,0.000066640074,0.06414937,0.00015773487,0.00050328457,0.05125526],"study_design_scores_gemma":[0.000003600638,0.00017109286,0.9986034,0.0000049061223,0.0000066172074,0.000265619,0.00013221458,0.000017842214,0.0006132385,0.000029705605,0.00014997902,0.0000017841202],"about_ca_topic_score_codex":0.00067970034,"about_ca_topic_score_gemma":0.0015179941,"teacher_disagreement_score":0.0027001642,"about_ca_system_score_codex":0.00007211172,"about_ca_system_score_gemma":0.00007954638,"threshold_uncertainty_score":0.009032905},"labels":[],"label_agreement":null},{"id":"W4401977490","doi":"10.21203/rs.3.rs-4883534/v1","title":"MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"Engineering and Physical Sciences Research Council","keywords":"Oligodendrocyte; Neuroscience; Cell type; Human brain; Cell; Pathology; Biology; Medicine; Myelin; Central nervous system; Genetics","score_opus":0.08121285262941325,"score_gpt":0.44149022490200146,"score_spread":0.3602773722725882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401977490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898056,0.0007374134,0.0069491873,0.00012453574,0.000011837266,0.000008727262,0.0005536416,0.0000735563,0.001735524],"genre_scores_gemma":[0.9960335,0.0004449312,0.001906383,0.000036715788,0.000015049417,0.000009695382,0.00030723584,0.00004599692,0.0012005372],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992204,0.000014605739,0.0000042703236,0.000022621034,0.000018900584,0.000017522341],"domain_scores_gemma":[0.99948835,0.00013368431,0.00018272374,0.000043269807,0.00009801741,0.0000538804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026917027,0.00015566972,0.00014643602,0.00075223914,0.00010669652,0.00047334374,0.000140259,0.00028004832,0.0013602528],"category_scores_gemma":[0.0014098885,0.00022766965,0.00012866742,0.000440559,0.00022442515,0.00026382477,0.00021486192,0.0002059644,0.00033171],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008478842,0.000047200705,0.17575152,0.00016767123,0.0001278174,0.0005169737,0.00070121535,0.001226541,0.76355016,0.0012728389,0.0011985077,0.0545917],"study_design_scores_gemma":[0.000007335668,0.000083280924,0.9547151,0.000017733257,0.000056167468,0.0009255969,0.00024127292,0.0015134219,0.040608335,0.0008595795,0.0009560556,0.00001623612],"about_ca_topic_score_codex":0.0018545081,"about_ca_topic_score_gemma":0.002895006,"teacher_disagreement_score":0.0018545081,"about_ca_system_score_codex":0.0001461144,"about_ca_system_score_gemma":0.00021537674,"threshold_uncertainty_score":0.004550576},"labels":[],"label_agreement":null},{"id":"W4402029496","doi":"10.1101/2024.08.29.610312","title":"Stable White Matter Structure in the First Three Years after Psychosis Onset","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; London Health Sciences Centre; Western University","funders":"","keywords":"Psychosis; White matter; White (mutation); Psychology; Psychiatry; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.020669453105410872,"score_gpt":0.27041650564796876,"score_spread":0.24974705254255788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402029496","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988312,0.00015090112,0.00012060433,0.000022210123,0.0000027608264,0.0000044638614,0.0006862489,0.0000113057395,0.00017035045],"genre_scores_gemma":[0.99842215,0.000048611008,0.000052491352,0.000007661341,0.0000026370772,0.0000047358144,0.0013043205,0.0000031339011,0.00015425462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998171,0.000030583295,0.0000138742735,0.00005810773,0.000030639956,0.000049757473],"domain_scores_gemma":[0.9989133,0.00014777684,0.00043171918,0.00012844047,0.00018901541,0.00018987557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005411826,0.00020645082,0.00036244388,0.0010696286,0.0004997675,0.00070807675,0.0002611816,0.00039736895,0.0011766254],"category_scores_gemma":[0.0018321616,0.00018226873,0.00026834285,0.0005628711,0.0002621511,0.00037107983,0.0006763867,0.0004021044,0.00031849835],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021538553,0.00010146501,0.978441,0.000038338658,0.00020559828,0.0009048417,0.00043185346,0.000350346,0.009117119,0.00010749299,0.00048207876,0.007666036],"study_design_scores_gemma":[0.00000494824,0.0001024549,0.9986694,0.0000056280646,0.000017703185,0.00030003148,0.00008886041,0.0002418127,0.0003578854,0.00007049456,0.00013620514,0.0000047461485],"about_ca_topic_score_codex":0.013985427,"about_ca_topic_score_gemma":0.016474262,"teacher_disagreement_score":0.013985427,"about_ca_system_score_codex":0.00045119386,"about_ca_system_score_gemma":0.0003618951,"threshold_uncertainty_score":0.02780807},"labels":[],"label_agreement":null},{"id":"W4402148258","doi":"","title":"Can We Encode Intra-and Inter-Variability with Log Jacobian Maps Derived from Brain Morphological Deformations Using Pediatric MRI Scans?","year":2024,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canada First Research Excellence Fund; Polytechnique Montréal","keywords":"ENCODE; Jacobian matrix and determinant; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Mathematics; Biology; Gene; Applied mathematics; Genetics","score_opus":0.030640994637806,"score_gpt":0.2803198884322599,"score_spread":0.2496788937944539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402148258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4234301,0.0035453625,0.5609753,0.003242316,0.00048164648,0.000072924,0.0028612847,0.0015399876,0.0038509585],"genre_scores_gemma":[0.8945175,0.003139096,0.09787275,0.00031742742,0.0002997857,0.0000614995,0.0014216169,0.0007444873,0.0016258801],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978536,0.0000757405,0.00001656817,0.00005576989,0.000038678674,0.000027885251],"domain_scores_gemma":[0.99722654,0.0014984009,0.0004053101,0.0003409777,0.00042383268,0.00010497891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001317877,0.00052415224,0.00033488078,0.0008211465,0.00012716097,0.0012297396,0.00040377726,0.0006348266,0.0013403529],"category_scores_gemma":[0.015643531,0.00029004965,0.00045119386,0.0010173314,0.0003791201,0.0019302436,0.0004893675,0.0008427728,0.0005364817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009061585,0.000121081226,0.1016788,0.0004840372,0.0005167531,0.0006738729,0.00084144593,0.08363853,0.06214263,0.0060509476,0.0104016345,0.73254406],"study_design_scores_gemma":[0.00006210532,0.0004965475,0.25277352,0.00053018174,0.00069094414,0.0031769157,0.0010171245,0.6346835,0.039185666,0.04553694,0.021565214,0.0002812391],"about_ca_topic_score_codex":0.0031269405,"about_ca_topic_score_gemma":0.0049334187,"teacher_disagreement_score":0.0031269405,"about_ca_system_score_codex":0.00017400112,"about_ca_system_score_gemma":0.00059009116,"threshold_uncertainty_score":0.0069696903},"labels":[],"label_agreement":null},{"id":"W4402232009","doi":"10.7554/elife.83838","title":"White matter structural bases for phase accuracy during tapping synchronization","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Laboratory for Brain, Music and Sound Research","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Consejo Nacional de Ciencia y Tecnología","keywords":"Tapping; Synchronization (alternating current); White matter; Phase (matter); Computer science; Neuroscience; Biology; Physics; Medicine; Acoustics; Telecommunications; Magnetic resonance imaging","score_opus":0.05085489224150328,"score_gpt":0.40634679874448176,"score_spread":0.35549190650297846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402232009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99842286,0.000057615172,0.0011023564,0.000008049685,0.000001260146,0.000005853914,0.00010127055,0.000013679544,0.000286947],"genre_scores_gemma":[0.9994124,0.000021657837,0.0003649386,0.0000027787698,0.000003236888,0.0000040227364,0.00008831212,0.0000049056603,0.00009780006],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99992704,0.000008600222,0.0000079859565,0.000034137374,0.000013714861,0.00000856612],"domain_scores_gemma":[0.99938357,0.0001980261,0.000220108,0.00007174726,0.000063938576,0.00006244702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016844558,0.0001840987,0.00013323998,0.00058853306,0.00010769807,0.00030400956,0.00008798604,0.00016398221,0.0013432237],"category_scores_gemma":[0.0019332101,0.00012947332,0.000068857364,0.0002569974,0.00024156489,0.00021528722,0.00022485778,0.00012125006,0.00012779036],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009221523,0.000060522812,0.29901803,0.00009372062,0.00015576479,0.00042285878,0.00089704694,0.001110121,0.662957,0.0003413353,0.0001304982,0.033890918],"study_design_scores_gemma":[0.000005790317,0.000060932023,0.994115,0.000002622295,0.00001159787,0.00027451216,0.000050476046,0.0008246324,0.0044418355,0.00013563999,0.00007303425,0.0000039874567],"about_ca_topic_score_codex":0.0011640425,"about_ca_topic_score_gemma":0.002361901,"teacher_disagreement_score":0.0013432237,"about_ca_system_score_codex":0.00006389796,"about_ca_system_score_gemma":0.00007852665,"threshold_uncertainty_score":0.0044935346},"labels":[],"label_agreement":null},{"id":"W4402311891","doi":"10.1121/10.0028500","title":"Investigating muscle coordination patterns with Granger causality analysis in protrusive motion from tagged and diffusion MRI","year":2024,"lang":"en","type":"article","venue":"JASA Express Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute on Deafness and Other Communication Disorders; National Cancer Institute; National Institutes of Health","keywords":"Motion (physics); Tongue; Granger causality; Motion analysis; Muscle fibre; Dynamics (music); Biology; Diffusion; Anatomy; Computer science; Computer vision; Artificial intelligence; Biological system; Physics; Acoustics; Machine learning; Medicine","score_opus":0.030075468857216594,"score_gpt":0.30597365991621495,"score_spread":0.2758981910589984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402311891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79204214,0.00078642444,0.20466788,0.00021126114,0.000036742855,0.000059651884,0.00049639156,0.00032283322,0.0013766199],"genre_scores_gemma":[0.95665085,0.00045552716,0.041352957,0.000033272947,0.00003121593,0.000034201927,0.00053521,0.00005563855,0.00085110095],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99981683,0.000049560967,0.000015482472,0.000051669555,0.000038320803,0.000028072323],"domain_scores_gemma":[0.9992048,0.00034016187,0.00021234373,0.000093302086,0.00009125703,0.000058143574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006956072,0.0005037481,0.00031668105,0.002040938,0.00024735925,0.0007267469,0.00024996238,0.0004145887,0.0013655787],"category_scores_gemma":[0.0027881372,0.00020400406,0.00032527454,0.0017238656,0.00041908043,0.00052244315,0.0005327112,0.000404125,0.00027455596],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028529272,0.0004237545,0.14637914,0.0005795311,0.0006670769,0.003396356,0.001372922,0.10969496,0.30149165,0.011700727,0.0022916375,0.4191493],"study_design_scores_gemma":[0.00013590268,0.0004942203,0.28690088,0.00009920206,0.00031557123,0.0028825651,0.000986694,0.62646693,0.047982678,0.029636439,0.003916951,0.00018197847],"about_ca_topic_score_codex":0.0016032472,"about_ca_topic_score_gemma":0.002580595,"teacher_disagreement_score":0.002040938,"about_ca_system_score_codex":0.0001706157,"about_ca_system_score_gemma":0.00037185947,"threshold_uncertainty_score":0.004568279},"labels":[],"label_agreement":null},{"id":"W4402354789","doi":"10.1002/mrm.30279","title":"Particle‐based MR modeling with diffusion, microstructure, and enzymatic reactions","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; University of Toronto; Innovation, Science and Economic Development Canada","keywords":"Biological system; SIGNAL (programming language); Diffusion; Imaging phantom; Nuclear magnetic resonance; In silico; Brownian dynamics; Diffusion MRI; Biomedical engineering; Magnetic resonance imaging; Brownian motion; Chemistry; Computer science; Materials science; Physics; Thermodynamics; Medicine; Optics","score_opus":0.04344542131942288,"score_gpt":0.3333778175657322,"score_spread":0.28993239624630934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402354789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17404376,0.00045935498,0.81625676,0.0004997282,0.00009265325,0.00015509325,0.00018763654,0.00029236905,0.008012662],"genre_scores_gemma":[0.9003118,0.0006672964,0.08967795,0.00014363564,0.00003983611,0.0003365501,0.00017310555,0.00010995716,0.008539793],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998692,0.00004206975,0.00000724908,0.00002981079,0.000035052508,0.000016594624],"domain_scores_gemma":[0.99959797,0.00020836745,0.00007483985,0.000035131437,0.00006003037,0.000023695298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041385347,0.00057095283,0.00060937786,0.00037411167,0.00034496337,0.00080521265,0.0010019056,0.0015280078,0.00082426256],"category_scores_gemma":[0.0011507899,0.0004600497,0.0007727477,0.0002858862,0.0007575261,0.00077486946,0.000485385,0.0004904874,0.00023791753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011567965,0.000016566568,0.00024640755,0.000015950794,0.000009074441,0.00005186029,0.00002445316,0.98949987,0.005597825,0.0038139755,0.000041326603,0.00067102956],"study_design_scores_gemma":[0.000005276003,0.000008837816,0.000074795746,0.0000013581515,0.0000029956097,0.000012998952,0.0000027798735,0.9985421,0.0006712161,0.00047048344,0.00020426784,0.000002924414],"about_ca_topic_score_codex":0.0078090946,"about_ca_topic_score_gemma":0.002853587,"teacher_disagreement_score":0.0078090946,"about_ca_system_score_codex":0.0008606009,"about_ca_system_score_gemma":0.0009496951,"threshold_uncertainty_score":0.015527308},"labels":[],"label_agreement":null},{"id":"W4402354923","doi":"10.1002/mrm.30247","title":"Rational approximation of golden angles: Accelerated reconstructions for radial MRI","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; Deutsche Forschungsgemeinschaft; National Institute on Aging; National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Deutsches Zentrum für Herz-Kreislaufforschung","keywords":"Golden ratio; Sampling (signal processing); Precomputation; Equidistant; Computer science; Algorithm; Imaging phantom; Mathematics; Golden hamster; Artificial intelligence; Computer vision; Computation; Optics; Geometry; Physics","score_opus":0.08137913570329844,"score_gpt":0.3705281476296144,"score_spread":0.2891490119263159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402354923","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0069949366,0.00008928731,0.9919768,0.000027523874,0.000010964416,0.000014546006,0.000014477377,0.00016634786,0.00070515607],"genre_scores_gemma":[0.12183242,0.00022075021,0.87667644,0.00003209984,0.000016453168,0.000047785128,0.00007486962,0.00017573978,0.00092351006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962556,0.00016264051,0.000020086036,0.00003641182,0.0001302102,0.000024924488],"domain_scores_gemma":[0.9992342,0.0003108379,0.00012979851,0.0001464887,0.00012957714,0.00004905948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011985947,0.0006109165,0.00031519702,0.0004935862,0.00018144595,0.00069915625,0.0005965778,0.0004630112,0.001573247],"category_scores_gemma":[0.003404864,0.0002794389,0.0003809242,0.000405259,0.00060315325,0.00069063006,0.0007237045,0.00068124576,0.0008310747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000648221,0.00009085483,0.002260784,0.00031287398,0.000053470325,0.0003795181,0.0004206973,0.42006752,0.10370674,0.201457,0.002645569,0.26795682],"study_design_scores_gemma":[0.000011807862,0.00004621458,0.00018937842,0.00001617321,0.000005589823,0.00016506681,0.000010476681,0.97316754,0.013864144,0.009216945,0.0032929142,0.000013724585],"about_ca_topic_score_codex":0.0007371409,"about_ca_topic_score_gemma":0.00089929905,"teacher_disagreement_score":0.001573247,"about_ca_system_score_codex":0.00045925486,"about_ca_system_score_gemma":0.0005166915,"threshold_uncertainty_score":0.0063388348},"labels":[],"label_agreement":null},{"id":"W4402389629","doi":"10.1101/2024.09.05.610266","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Zona incerta; Zona; Diffusion MRI; Diffusion; Cartography; Geology; Geography; Neuroscience; Psychology; Magnetic resonance imaging; Biology; Medicine; Physics; Radiology; Virology; Human immunodeficiency virus (HIV)","score_opus":0.043735647785188084,"score_gpt":0.2841951467688496,"score_spread":0.24045949898366153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402389629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8337078,0.00457712,0.14900781,0.0012836531,0.000052374737,0.00017411856,0.0034468244,0.0009603245,0.0067899576],"genre_scores_gemma":[0.9441477,0.0011574194,0.05112105,0.00011988438,0.000027637725,0.000069008405,0.0007117043,0.00014842906,0.0024970248],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998852,0.000019217812,0.0000057072307,0.00004907178,0.000028198048,0.000012540021],"domain_scores_gemma":[0.9997464,0.00007878261,0.000064560525,0.000046079527,0.0000476431,0.000016498085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040084467,0.00023418093,0.00014931896,0.0016469159,0.00022456599,0.00085421815,0.0003041519,0.00033985716,0.0017071123],"category_scores_gemma":[0.0015382613,0.0002694545,0.0001433379,0.00065337983,0.00038535928,0.00043292023,0.0003363403,0.0003318359,0.0005434101],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087415555,0.000086071865,0.054043468,0.00058067247,0.00028913675,0.00090775616,0.0011699067,0.010417857,0.69951934,0.00999965,0.0060795336,0.21603245],"study_design_scores_gemma":[0.00012142709,0.0002791546,0.5947124,0.00029544614,0.00032507387,0.008917266,0.000950822,0.09530113,0.24011898,0.02077141,0.037992273,0.00021462067],"about_ca_topic_score_codex":0.0073712002,"about_ca_topic_score_gemma":0.010527204,"teacher_disagreement_score":0.0073712002,"about_ca_system_score_codex":0.0003810074,"about_ca_system_score_gemma":0.00044099893,"threshold_uncertainty_score":0.014656544},"labels":[],"label_agreement":null},{"id":"W4402418555","doi":"10.1016/j.neuroimage.2024.120850","title":"Ultra-high-resolution mapping of myelin and g-ratio in a panel of Mbp enhancer-edited mouse strains using microstructural MRI","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; Lunenfeld-Tanenbaum Research Institute; University Health Network; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Myelin; High resolution; Resolution (logic); Enhancer; Chemistry; Materials science; Molecular biology; Biology; Computer science; Neuroscience; Biochemistry; Geography; Artificial intelligence; Remote sensing; Gene","score_opus":0.07542896647390292,"score_gpt":0.3381736405925891,"score_spread":0.2627446741186862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402418555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.869525,0.00094354484,0.1243865,0.00017678471,0.00006023321,0.00017894145,0.0021743097,0.0010073538,0.001547226],"genre_scores_gemma":[0.8180336,0.0018686751,0.16559711,0.00023321276,0.0000250669,0.00078819774,0.0029804811,0.001493956,0.008979633],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99959546,0.00005837798,0.000052858948,0.00014576434,0.00009072206,0.000056865127],"domain_scores_gemma":[0.999198,0.00012984408,0.0003209041,0.00010575525,0.00013837632,0.000107104875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011429366,0.0012695972,0.00045036557,0.0017068726,0.00039116375,0.0006453183,0.00049970625,0.0008007983,0.0012812817],"category_scores_gemma":[0.00060008833,0.0004997751,0.00045307836,0.00042152047,0.0007103708,0.0005104355,0.00059844455,0.0014150598,0.0003742488],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007727159,0.000032094667,0.00023429214,0.000018662508,0.000010214494,0.000027996883,0.000036776582,0.00012731524,0.99809855,0.00012579419,0.00003217668,0.0011789103],"study_design_scores_gemma":[0.00001609697,0.00034557507,0.006781749,0.00002039479,0.00006349975,0.00036961978,0.00005546888,0.0021232725,0.9885184,0.00021582145,0.0014665225,0.00002342267],"about_ca_topic_score_codex":0.001098596,"about_ca_topic_score_gemma":0.003224597,"teacher_disagreement_score":0.0017068726,"about_ca_system_score_codex":0.00031928514,"about_ca_system_score_gemma":0.00024322172,"threshold_uncertainty_score":0.006044507},"labels":[],"label_agreement":null},{"id":"W4402476141","doi":"10.1371/journal.pone.0310312","title":"White matter disconnection impacts proprioception post-stroke","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Proprioception; Disconnection; Superior longitudinal fasciculus; Fasciculus; White matter; Psychology; Physical medicine and rehabilitation; Arcuate fasciculus; Neuroimaging; Neuroscience; Corticospinal tract; Stroke (engine); Corpus callosum; Corona radiata (embryology); Inferior longitudinal fasciculus; Grey matter; Medicine; Magnetic resonance imaging; Tractography; Diffusion MRI; Physics; Internal medicine","score_opus":0.06886686923058691,"score_gpt":0.3159629885609188,"score_spread":0.2470961193303319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402476141","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993113,0.00017444724,0.00010767481,0.000021544101,0.0000015515243,0.0000047929707,0.00006520103,0.000006921006,0.000306508],"genre_scores_gemma":[0.99933654,0.00013028334,0.00006107947,0.000012591053,0.0000020894563,0.000007120305,0.00011157411,0.0000023562552,0.00033630524],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987614,0.000014236326,0.000015465888,0.000031157746,0.000029829338,0.00003312293],"domain_scores_gemma":[0.9995591,0.00007708539,0.00022662556,0.000027872773,0.00005308222,0.000056284473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016227216,0.00023698025,0.00027404496,0.00041232517,0.00024523033,0.00043167986,0.000109179,0.00024165868,0.002051458],"category_scores_gemma":[0.0012330466,0.000089433815,0.00013751372,0.00024625703,0.00036050152,0.00042185548,0.0005539757,0.0002937025,0.0003001507],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004579552,0.0009652856,0.7255928,0.00031702666,0.00043110747,0.0024487039,0.0017154047,0.0013289611,0.16143778,0.00019838841,0.00063264114,0.100352384],"study_design_scores_gemma":[0.0000037876755,0.00045290563,0.9970204,0.000010234998,0.000022624936,0.0003462132,0.00016809057,0.00015328643,0.0015658966,0.00010634745,0.00014534559,0.000004901752],"about_ca_topic_score_codex":0.0029170618,"about_ca_topic_score_gemma":0.0058198906,"teacher_disagreement_score":0.0029170618,"about_ca_system_score_codex":0.0002697349,"about_ca_system_score_gemma":0.0002769716,"threshold_uncertainty_score":0.006862879},"labels":[],"label_agreement":null},{"id":"W4402544130","doi":"10.1016/j.cccb.2024.100369","title":"The effects of a six-month exercise intervention on white matter microstructure in older adults at risk for diabetes","year":2024,"lang":"en","type":"article","venue":"Cerebral Circulation - Cognition and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Western University; Canada Research Chairs","keywords":"Diabetes mellitus; Medicine; Intervention (counseling); Physical therapy; Gerontology; Endocrinology; Psychiatry","score_opus":0.01327237237505767,"score_gpt":0.3007230457551044,"score_spread":0.2874506733800467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402544130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99963725,0.00014358659,0.00003878837,0.000022045813,0.000011377535,0.000039987975,0.00001640895,0.000004331674,0.00008622227],"genre_scores_gemma":[0.9986091,0.00031697282,0.0003953626,0.0000784666,0.000030785628,0.00014568245,0.000073632946,0.0000013477833,0.00034860143],"study_design_codex":"randomized_trial","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.9998282,0.00005088809,0.000022618353,0.00003176494,0.00001938131,0.00004696578],"domain_scores_gemma":[0.9996667,0.000052070012,0.00006980414,0.000022770753,0.00003390736,0.00015462744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042438792,0.00038120706,0.0006254218,0.00027644503,0.0003715912,0.00021695717,0.00021069412,0.0006334586,0.00081907347],"category_scores_gemma":[0.0008164486,0.00018601601,0.00045862648,0.00014650797,0.00017183332,0.00017799123,0.0003027727,0.00045874936,0.00011722903],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.36730522,0.16484384,0.08630267,0.0014494783,0.0019694744,0.0005460423,0.001482865,0.0008741611,0.09353423,0.000085060106,0.0007462222,0.28086066],"study_design_scores_gemma":[0.014939316,0.3156848,0.6623563,0.00007975594,0.0007995818,0.00011154744,0.0003126551,0.00073359197,0.0042764177,0.000064094376,0.0006135701,0.000028314726],"about_ca_topic_score_codex":0.0013385721,"about_ca_topic_score_gemma":0.0026656154,"teacher_disagreement_score":0.0013385721,"about_ca_system_score_codex":0.0001254827,"about_ca_system_score_gemma":0.00020921178,"threshold_uncertainty_score":0.0027401447},"labels":[],"label_agreement":null},{"id":"W4402555343","doi":"10.1002/alz.14161","title":"Morphometry of medial temporal lobe subregions using high‐resolution T2‐weighted MRI in ADNI3: Why, how, and what's next?","year":2024,"lang":"en","type":"review","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Universidad de Castilla-La Mancha; Fred A. And Barbara M. Erb Family Foundation; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; Biogen; BioClinica; Meso Scale Diagnostics; Novartis Pharmaceuticals Corporation; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; University of Pennsylvania; Merck; Alzheimer's Drug Discovery Foundation; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; AbbVie; Fujirebio Europe; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Temporal lobe; Lobe; High resolution; Anatomy; T2 weighted; Magnetic resonance imaging; Cartography; Psychology; Geology; Neuroscience; Medicine; Geography; Radiology; Epilepsy; Remote sensing","score_opus":0.14616736262954372,"score_gpt":0.3854787341895066,"score_spread":0.2393113715599629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402555343","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047580276,0.8043652,0.08573459,0.040576015,0.004584754,0.00040819953,0.0023246668,0.0012982042,0.0131281195],"genre_scores_gemma":[0.11938757,0.6763815,0.17364043,0.010715425,0.0056018825,0.0004982793,0.0031417378,0.00076732953,0.009865818],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957436,0.00012721309,0.00006314356,0.0000807238,0.0001283109,0.000026204532],"domain_scores_gemma":[0.9992355,0.00021692956,0.00012987162,0.000060267317,0.00031792268,0.00003953102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003331084,0.0005903361,0.00060337485,0.0019479684,0.00029283352,0.0021085397,0.0010497371,0.0011742259,0.0011415227],"category_scores_gemma":[0.0037151463,0.00045795983,0.0008031199,0.0011164545,0.0008964373,0.0019886673,0.0006440989,0.0013752038,0.0012909952],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044503712,0.00005116092,0.020416517,0.004406704,0.00056152424,0.0011374488,0.0010995312,0.0013511301,0.02141555,0.0057099094,0.08462183,0.85878366],"study_design_scores_gemma":[0.00010532191,0.00081380375,0.097793624,0.007849675,0.0012234423,0.014914829,0.0019849718,0.0050240024,0.027142476,0.034751423,0.80789953,0.00049694715],"about_ca_topic_score_codex":0.0029557801,"about_ca_topic_score_gemma":0.008788063,"teacher_disagreement_score":0.003331084,"about_ca_system_score_codex":0.0008438107,"about_ca_system_score_gemma":0.00091716833,"threshold_uncertainty_score":0.01761663},"labels":[],"label_agreement":null},{"id":"W4402699223","doi":"10.48550/arxiv.2408.12921","title":"Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR$^2$-CSD) of Diffusion MRI Data","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Deconvolution; Diffusion; Diffusion MRI; Physics; Algorithm; Computer science; Statistical physics; Magnetic resonance imaging; Radiology; Medicine; Thermodynamics","score_opus":0.16298231659628606,"score_gpt":0.27464767176666266,"score_spread":0.1116653551703766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402699223","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056803484,0.0008995891,0.93417275,0.00041173428,0.00008743327,0.0001392601,0.0013826289,0.004280261,0.0018228228],"genre_scores_gemma":[0.22213817,0.0010545786,0.7687638,0.00034149893,0.000044232645,0.00027821233,0.004093864,0.0012549453,0.0020308343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992393,0.00015980532,0.00005762628,0.00017604671,0.00031650628,0.000050720944],"domain_scores_gemma":[0.99822646,0.00070657,0.00022352287,0.00036817443,0.00039956343,0.00007568092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021742762,0.0011289669,0.00073456974,0.0011097108,0.00043562683,0.0009307581,0.0010941019,0.0009902937,0.0014666218],"category_scores_gemma":[0.007190417,0.00040564628,0.00092759705,0.0010632257,0.00095626153,0.0012204202,0.001301046,0.0012446536,0.0006978618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010334068,0.00021912158,0.0045529506,0.001334581,0.00054224295,0.0006128058,0.00052018964,0.4368189,0.21242367,0.01844037,0.016903289,0.30659854],"study_design_scores_gemma":[0.000057371028,0.00016449722,0.0030788204,0.000058620302,0.000081523096,0.0006947273,0.000083251114,0.88812256,0.084975496,0.008725928,0.01381733,0.00013990233],"about_ca_topic_score_codex":0.0056589935,"about_ca_topic_score_gemma":0.009163373,"teacher_disagreement_score":0.0056589935,"about_ca_system_score_codex":0.00059823075,"about_ca_system_score_gemma":0.0022180227,"threshold_uncertainty_score":0.011498809},"labels":[],"label_agreement":null},{"id":"W4402894228","doi":"10.1002/mrm.30298","title":"Investigating microstructural changes between in vivo and perfused ex vivo marmoset brains using oscillating gradient and b‐tensor encoded diffusion <scp>MRI</scp> at 9.<scp>4 T</scp>","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Center for Research Computing, University of Pittsburgh; Canada Research Chairs; University of Pittsburgh; Canada First Research Excellence Fund; National Science Foundation","keywords":"Ex vivo; Diffusion MRI; Fractional anisotropy; In vivo; Kurtosis; Nuclear magnetic resonance; Perfusion; Fixation (population genetics); Materials science; Biomedical engineering; Chemistry; Magnetic resonance imaging; Biology; Physics; Medicine; Internal medicine; Mathematics; Radiology; Genetics","score_opus":0.054555015936560536,"score_gpt":0.32491782410609354,"score_spread":0.270362808169533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402894228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98489064,0.000393602,0.014110972,0.000060703096,0.000009322304,0.000025018784,0.000109675966,0.000057848276,0.00034221663],"genre_scores_gemma":[0.9805741,0.00045752272,0.018090596,0.00004614602,0.000009991585,0.000053148953,0.00022357541,0.000037447175,0.00050760433],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999293,0.000014670481,0.00000633549,0.000020286274,0.00001812124,0.000011296688],"domain_scores_gemma":[0.9998306,0.0000309715,0.00005831642,0.000024942778,0.00003269458,0.000022464828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040262434,0.00035617824,0.00018131331,0.000283021,0.00025935675,0.00025961627,0.00029460105,0.00047998826,0.00077877106],"category_scores_gemma":[0.0005283638,0.00022540882,0.0001967829,0.00013332767,0.00045863105,0.0003827096,0.0002571883,0.00032855888,0.00010899873],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001007454,0.000021654629,0.00083084014,0.000039180588,0.00001862467,0.000114861126,0.000049191905,0.00062389177,0.996247,0.00009917942,0.00001945595,0.001835425],"study_design_scores_gemma":[0.000035691082,0.0009763972,0.065391876,0.000025225128,0.0001261562,0.0016686767,0.00014247993,0.012568937,0.91714287,0.0006547551,0.001236335,0.000030616862],"about_ca_topic_score_codex":0.0011730354,"about_ca_topic_score_gemma":0.0012528899,"teacher_disagreement_score":0.0011730354,"about_ca_system_score_codex":0.00023647244,"about_ca_system_score_gemma":0.000244945,"threshold_uncertainty_score":0.0026051998},"labels":[],"label_agreement":null},{"id":"W4402906635","doi":"10.1101/2024.09.25.614579","title":"Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Modal; Aggregate (composite); White matter; Materials science; Magnetic resonance imaging; Medicine; Composite material; Radiology","score_opus":0.06456217936251007,"score_gpt":0.30309320108048665,"score_spread":0.23853102171797658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402906635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67656446,0.00040441347,0.31983876,0.00014760382,0.000016237651,0.00009469293,0.0009619844,0.0010743457,0.0008975001],"genre_scores_gemma":[0.8673315,0.0001890962,0.13102916,0.000044709363,0.000021067168,0.000074620606,0.0005535811,0.00017499684,0.000581162],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999798,0.000046780766,0.000014622575,0.000079781945,0.000047317808,0.000013520524],"domain_scores_gemma":[0.9994948,0.00013021441,0.00015327461,0.00010186161,0.00008270627,0.000037255857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063679175,0.00066070055,0.00038757772,0.0014310449,0.0002168304,0.0006768742,0.00042322942,0.0005303796,0.0012236324],"category_scores_gemma":[0.0019809392,0.00021458676,0.00035651712,0.00056479446,0.00030915695,0.00058354426,0.0005540826,0.00044108575,0.00031326414],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013712823,0.00022513693,0.06487912,0.00059590384,0.0005889167,0.0007616884,0.00078653236,0.059810612,0.63559633,0.0040023522,0.0019862193,0.2293959],"study_design_scores_gemma":[0.000084078965,0.0006463484,0.30382356,0.00006254251,0.00029220144,0.0033536702,0.00034702674,0.50292015,0.17387785,0.011156231,0.0032715914,0.00016474693],"about_ca_topic_score_codex":0.0014404681,"about_ca_topic_score_gemma":0.0020455136,"teacher_disagreement_score":0.0014404681,"about_ca_system_score_codex":0.00020253245,"about_ca_system_score_gemma":0.00017245198,"threshold_uncertainty_score":0.0040934086},"labels":[],"label_agreement":null},{"id":"W4402943543","doi":"10.1016/j.neurobiolaging.2024.09.013","title":"Midlife dynamics of white matter architecture in lexical production","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"Biotechnology and Biological Sciences Research Council; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Language production; Speech production; White matter; Psychology; Production (economics); Cognitive psychology; Linguistics; Cognition; Neuroscience; Medicine","score_opus":0.02816459705956561,"score_gpt":0.33052041618497535,"score_spread":0.30235581912540976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402943543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99741757,0.00036364273,0.00052747776,0.000041024672,0.0000051987877,0.000008828891,0.0008443074,0.000013781861,0.0007780985],"genre_scores_gemma":[0.9976661,0.00015071851,0.00061855686,0.000031445776,0.0000064016303,0.000018942765,0.00066371,0.000012065767,0.0008320939],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991477,0.000008683659,0.00000648995,0.000043129665,0.000010258682,0.000016764167],"domain_scores_gemma":[0.99959046,0.000047069385,0.00016243159,0.00004926797,0.00008633236,0.000064367516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037194576,0.0002707661,0.00019466961,0.0010501457,0.0004369138,0.0008880736,0.0002983052,0.000437937,0.0015898674],"category_scores_gemma":[0.0010433303,0.00018601511,0.00014779194,0.00049287884,0.0003478233,0.00062099204,0.0005074714,0.00037137445,0.0003788383],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013054371,0.00020147237,0.8884748,0.00014924882,0.00020714628,0.002865755,0.0034571365,0.0005343474,0.06693894,0.0011552139,0.0012103629,0.033499982],"study_design_scores_gemma":[0.0000020603761,0.0000658247,0.9965384,0.00001126477,0.000015277716,0.00041033997,0.0003555548,0.00014419084,0.0012727656,0.0005362983,0.0006423595,0.000005728991],"about_ca_topic_score_codex":0.0055159037,"about_ca_topic_score_gemma":0.0112843225,"teacher_disagreement_score":0.0055159037,"about_ca_system_score_codex":0.00028170593,"about_ca_system_score_gemma":0.00020858258,"threshold_uncertainty_score":0.010967612},"labels":[],"label_agreement":null},{"id":"W4402946633","doi":"10.1167/jov.24.10.1129","title":"High-resolution diffusion MRI of the cortico-cortical connections between lower visual areas reveals divergence of connections and enhanced connectivity of the central visual field representation","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University","funders":"","keywords":"Representation (politics); Diffusion MRI; Visual field; Neuroscience; Divergence (linguistics); Geology; Diffusion; Computer science; Psychology; Physics; Magnetic resonance imaging; Medicine; Philosophy; Radiology; Political science","score_opus":0.02878254338115882,"score_gpt":0.3757099250149787,"score_spread":0.34692738163381986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402946633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9516515,0.0020977214,0.042469054,0.00028968076,0.000020785292,0.000047443842,0.000715835,0.00019036302,0.002517569],"genre_scores_gemma":[0.9795216,0.0008337262,0.01787845,0.00009813858,0.000017688351,0.000026094513,0.00056691753,0.000069811496,0.0009876696],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998764,0.00001690693,0.000011987322,0.000045630648,0.000031186115,0.000017800961],"domain_scores_gemma":[0.9997141,0.0000841341,0.00008120589,0.00004975842,0.000036631453,0.000034256467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005863916,0.0004601574,0.00030883588,0.001148628,0.0002898719,0.0005663475,0.00027906828,0.00039164562,0.0028112184],"category_scores_gemma":[0.001303307,0.00033282884,0.00018330084,0.0006583786,0.0005975358,0.00078767946,0.0004374205,0.00048707786,0.00034847084],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031942414,0.00006820448,0.015834592,0.0005115228,0.00017877082,0.00069613825,0.00066422933,0.00089224527,0.93329626,0.0014299598,0.0009829836,0.04512565],"study_design_scores_gemma":[0.000082088794,0.0006163951,0.7281834,0.00012589872,0.00023371879,0.011858251,0.0005890271,0.0073812525,0.23770878,0.0076671494,0.005470202,0.00008380434],"about_ca_topic_score_codex":0.0019293405,"about_ca_topic_score_gemma":0.005927789,"teacher_disagreement_score":0.0028112184,"about_ca_system_score_codex":0.0001812656,"about_ca_system_score_gemma":0.000245311,"threshold_uncertainty_score":0.00940448},"labels":[],"label_agreement":null},{"id":"W4403021640","doi":"10.52294/001c.123347","title":"The Douglas-Bell Canada Brain Bank Post-mortem Brain Imaging Protocol","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Protocol (science); Neuroscience; Medicine; Psychology; Pathology","score_opus":0.01905484560485165,"score_gpt":0.3331046117301227,"score_spread":0.314049766125271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403021640","genre_codex":"methods","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.089181244,0.010761334,0.47317013,0.008305071,0.0040484983,0.12742504,0.11042781,0.01181304,0.16486788],"genre_scores_gemma":[0.081217945,0.01039652,0.5110992,0.0067130644,0.0005674564,0.14362046,0.09736676,0.003693147,0.14532547],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99762005,0.00035374126,0.00023997911,0.00034156573,0.0011938701,0.00025070927],"domain_scores_gemma":[0.99408746,0.00033643848,0.00025724486,0.0011209007,0.0036787249,0.000519211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005504025,0.0014576425,0.0011270194,0.0027475765,0.004267353,0.0018891906,0.0042078043,0.0021190192,0.05501198],"category_scores_gemma":[0.0055087204,0.0010811203,0.00071485795,0.0018691169,0.0022071262,0.0010564754,0.0022992406,0.0027075203,0.020334441],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006097023,0.0009454558,0.005826676,0.0035755318,0.0002141029,0.0062505445,0.002778283,0.002989545,0.20433792,0.031047737,0.5920494,0.14388777],"study_design_scores_gemma":[0.00045872433,0.0006439649,0.020703685,0.0012477365,0.00014955942,0.004317801,0.0006256149,0.0016473533,0.02988568,0.0038552869,0.9362405,0.00022416055],"about_ca_topic_score_codex":0.10288305,"about_ca_topic_score_gemma":0.33284694,"teacher_disagreement_score":0.10288305,"about_ca_system_score_codex":0.0062078517,"about_ca_system_score_gemma":0.026390024,"threshold_uncertainty_score":0.20456839},"labels":[],"label_agreement":null},{"id":"W4403090217","doi":"10.1007/978-3-031-72069-7_45","title":"TractOracle: Towards an Anatomically-Informed Reward Function for RL-Based Tractography","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Tractography; Function (biology); Artificial intelligence; Diffusion MRI; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.05447009360161693,"score_gpt":0.35388631582252805,"score_spread":0.29941622222091113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403090217","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007808566,0.000089344605,0.9964737,0.00006430674,0.000024857374,0.000009612992,0.0000531448,0.001762103,0.0007421285],"genre_scores_gemma":[0.049845427,0.00030426524,0.94202983,0.000112898546,0.000089141104,0.000086043954,0.0003166893,0.0018269917,0.0053887498],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996314,0.00010037245,0.000022487016,0.000083355524,0.00012745571,0.00003485854],"domain_scores_gemma":[0.9993036,0.00031740146,0.000056465862,0.00012481363,0.00013315996,0.00006450548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010300752,0.001022525,0.0009933383,0.00055505784,0.0004221407,0.0019394617,0.0018829106,0.0021637494,0.008364341],"category_scores_gemma":[0.003025209,0.0005718327,0.0009399869,0.00073105353,0.0008872705,0.0015807728,0.002090742,0.0023390527,0.005454001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023692341,0.000073700845,0.0003966786,0.0003173995,0.000104113315,0.00022723422,0.0001471912,0.22505349,0.035781886,0.10857848,0.02253952,0.6065434],"study_design_scores_gemma":[0.000011456163,0.00002809512,0.00011757891,0.000025770592,0.000010493494,0.00011413921,0.00000895271,0.94899035,0.0066678263,0.036052797,0.007953875,0.000018679133],"about_ca_topic_score_codex":0.0024612446,"about_ca_topic_score_gemma":0.0039056116,"teacher_disagreement_score":0.008364341,"about_ca_system_score_codex":0.0005875172,"about_ca_system_score_gemma":0.0009849548,"threshold_uncertainty_score":0.02798152},"labels":[],"label_agreement":null},{"id":"W4403299410","doi":"10.52294/001c.123922","title":"Bilateral differences in structural connectivity of the afferent visual pathways of children with perinatal stroke","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tractography; Stroke (engine); Fractional anisotropy; Diffusion MRI; Visual cortex; Medicine; Psychology; Population; Neuroscience; Cardiology; Audiology; Magnetic resonance imaging; Radiology","score_opus":0.025756258519602258,"score_gpt":0.2943239145301624,"score_spread":0.2685676560105601,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403299410","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995159,0.000047731748,0.00005649855,0.0000079224255,5.220146e-7,0.000002439014,0.0001716218,0.000002179779,0.00019515649],"genre_scores_gemma":[0.99946624,0.00007775162,0.00012738544,0.0000053111494,9.756106e-7,0.0000068126433,0.00017971527,0.0000019082447,0.00013394411],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999846,0.000014686867,0.000017510652,0.000047893674,0.0000319459,0.000041902724],"domain_scores_gemma":[0.9996387,0.00006863179,0.00017693356,0.000019546871,0.000046229936,0.00004992578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018026539,0.00025707824,0.00022350202,0.00102695,0.0002516907,0.00043717914,0.00017517274,0.00022774843,0.002541822],"category_scores_gemma":[0.0012888728,0.00016456867,0.00016228316,0.0005233031,0.00034811808,0.0003127288,0.00030892243,0.00018007505,0.00022141448],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016907394,0.000028748174,0.98707205,0.000029015155,0.00004722091,0.0009428582,0.0006436035,0.00014465951,0.0046423455,0.00006889663,0.00012986909,0.0060816575],"study_design_scores_gemma":[0.0000015108428,0.000034031505,0.99819595,0.0000036940376,0.000009154304,0.001010186,0.00031377035,0.00005954579,0.00028727742,0.000024139274,0.00005898579,0.0000016585483],"about_ca_topic_score_codex":0.012016382,"about_ca_topic_score_gemma":0.015031075,"teacher_disagreement_score":0.012016382,"about_ca_system_score_codex":0.0003294076,"about_ca_system_score_gemma":0.00027250696,"threshold_uncertainty_score":0.02389288},"labels":[],"label_agreement":null},{"id":"W4403348570","doi":"10.1016/j.mri.2024.110255","title":"Comparisons of MR and EM inferred tissue microstructure properties using a human autopsy corpus callosum sample","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Corpus callosum; Autopsy; Sample (material); Tissue sample; Anatomy; Pathology; Medicine; Chemistry","score_opus":0.06286301817996268,"score_gpt":0.3530613754392496,"score_spread":0.2901983572592869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403348570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992486,0.00019733627,0.0062807305,0.000029273042,0.000005431788,0.000013750781,0.00032621901,0.00007118048,0.0005900133],"genre_scores_gemma":[0.99479383,0.0001483054,0.0043017566,0.000016277376,0.0000058759947,0.0000081646895,0.00031246516,0.000028724058,0.00038452767],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999492,0.000011144067,0.000004759089,0.00001733655,0.000012412297,0.000005102743],"domain_scores_gemma":[0.999605,0.00015041193,0.000042416083,0.0000679633,0.000116354975,0.00001789511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003628285,0.00025028552,0.00016083264,0.0005430676,0.00028350603,0.00030513504,0.0002320169,0.00045688087,0.0011187221],"category_scores_gemma":[0.0015001877,0.00017016502,0.00012487418,0.00029393192,0.00039654455,0.000184606,0.00020596244,0.00016742111,0.00024723736],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018278072,0.00024298263,0.054347806,0.0003777866,0.00021151848,0.0052269963,0.0016882173,0.0149045335,0.8619542,0.0007168781,0.00074087176,0.05776049],"study_design_scores_gemma":[0.00011071816,0.0012391151,0.57910275,0.00009484941,0.0006345543,0.0191795,0.0030900117,0.07009982,0.31710324,0.001561342,0.0076819235,0.00010217242],"about_ca_topic_score_codex":0.003066096,"about_ca_topic_score_gemma":0.0037797021,"teacher_disagreement_score":0.003066096,"about_ca_system_score_codex":0.00009256895,"about_ca_system_score_gemma":0.0001692238,"threshold_uncertainty_score":0.0060964823},"labels":[],"label_agreement":null},{"id":"W4403371687","doi":"10.7759/cureus.71389","title":"A Comparative Study of Frontal and Cerebellar Lobe Volumes Between Patients With First-Episode Schizophrenia and Healthy Controls and Its Association With Psychopathology and Neurological Soft Signs in Patients","year":2024,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Krishna Institute Of Medical Sciences Deemed To Be University","keywords":"Medicine; Frontal lobe; Positive and Negative Syndrome Scale; Bayesian multivariate linear regression; Psychopathology; Cross-sectional study; Schizophrenia (object-oriented programming); Montreal Cognitive Assessment; Cerebellum; Internal medicine; Logistic regression; Audiology; Cognition; Psychiatry; Linear regression; Psychosis; Cognitive impairment; Pathology","score_opus":0.03062352256791595,"score_gpt":0.31694728032416525,"score_spread":0.2863237577562493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403371687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99970835,0.000100972575,0.00002072729,0.0000045802526,9.3878333e-7,0.0000024334913,0.000044322114,0.0000011869801,0.000116476476],"genre_scores_gemma":[0.9998029,0.00004009906,0.000033105032,0.0000040974396,0.0000018712809,0.0000027248016,0.00007510956,6.5955044e-7,0.000039468683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99985373,0.00002522566,0.000022105647,0.0000488166,0.000024981586,0.000025085961],"domain_scores_gemma":[0.9996234,0.00006619972,0.0001788576,0.000025118292,0.000032483076,0.000073790165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002603805,0.0002964041,0.00022477635,0.0009865805,0.00030634442,0.0004075863,0.00013795437,0.00026702113,0.0013918835],"category_scores_gemma":[0.0009717562,0.00018480042,0.00017962043,0.0003258997,0.00027403657,0.0002797177,0.0003094368,0.00014972886,0.00011461806],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004926468,0.00007589839,0.99214077,0.000025845078,0.00007540023,0.000463181,0.0004042854,0.000042288357,0.0031053075,0.000034106004,0.000041324114,0.0030990574],"study_design_scores_gemma":[0.0000072249845,0.00016790978,0.9987282,0.0000029352482,0.000013134287,0.00067768316,0.00021082467,0.000036444453,0.00008701222,0.000016359281,0.00005006522,0.0000020347718],"about_ca_topic_score_codex":0.002709272,"about_ca_topic_score_gemma":0.003555581,"teacher_disagreement_score":0.002709272,"about_ca_system_score_codex":0.00021726583,"about_ca_system_score_gemma":0.00017104771,"threshold_uncertainty_score":0.005387008},"labels":[],"label_agreement":null},{"id":"W4403553634","doi":"10.1007/978-981-97-8043-3_68","title":"Identifying Neuronal Damage and Plasticity by Analyzing Changes in Diffusion Tensor Imaging","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Diffusion MRI; Plasticity; Neuroscience; Diffusion; Psychology; Medicine; Materials science; Physics; Radiology; Magnetic resonance imaging","score_opus":0.018343899781031996,"score_gpt":0.27741319465665204,"score_spread":0.25906929487562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403553634","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04496518,0.05786956,0.81452537,0.002592013,0.0012694586,0.00012455706,0.0013115229,0.0025521244,0.07479028],"genre_scores_gemma":[0.18756317,0.08696721,0.55360585,0.0007119687,0.0014627392,0.00012843296,0.0016174659,0.001045608,0.16689749],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999243,0.0000054831016,0.000004225947,0.000023711533,0.000036460337,0.00000579163],"domain_scores_gemma":[0.99987185,0.000067170346,0.00001589179,0.000013489246,0.000022353237,0.0000091549155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000252939,0.0006786702,0.00045925815,0.0010054925,0.000109572204,0.0010483235,0.00045430075,0.0006582079,0.0059268847],"category_scores_gemma":[0.00045931028,0.0002800443,0.00036517216,0.0009472233,0.00037096808,0.00094824,0.00028803773,0.00060740486,0.004569461],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006952961,0.000051053627,0.0008999259,0.00056483713,0.000059382393,0.00032067735,0.000083339706,0.0050547,0.20155367,0.010624957,0.017786065,0.7629318],"study_design_scores_gemma":[0.000035307316,0.00057574926,0.026184583,0.0006296572,0.00029249766,0.011508892,0.00030347292,0.15041238,0.35692286,0.15724657,0.29565254,0.00023563196],"about_ca_topic_score_codex":0.00038704643,"about_ca_topic_score_gemma":0.0009092894,"teacher_disagreement_score":0.0059268847,"about_ca_system_score_codex":0.00016134646,"about_ca_system_score_gemma":0.00016838442,"threshold_uncertainty_score":0.019827366},"labels":[],"label_agreement":null},{"id":"W4403588636","doi":"10.1162/imag_a_00356","title":"Hippocampal microscopic fractional anisotropy is reduced in temporal lobe epilepsy","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fractional anisotropy; Diffusion MRI; Temporal lobe; Subiculum; White matter; Magnetic resonance imaging; Axon; Hippocampal formation; Epilepsy surgery; Epilepsy; Neuroscience; Medicine; Dentate gyrus; Pathology; Psychology; Radiology","score_opus":0.05245541796340334,"score_gpt":0.38512766917043356,"score_spread":0.3326722512070302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403588636","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99952805,0.00008494629,0.00012489167,0.000020797954,0.000001774811,0.0000013739655,0.00004258698,0.000007683137,0.00018789322],"genre_scores_gemma":[0.99979657,0.000025272688,0.000058207366,0.000004507972,0.0000016937186,5.94351e-7,0.00003145108,0.0000021033125,0.00007964947],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995077,0.00000587629,0.000006715729,0.000017792407,0.000010382972,0.000008537103],"domain_scores_gemma":[0.9996625,0.000040463106,0.0002051393,0.000037411763,0.00002294227,0.000031468433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012797426,0.00022323539,0.00017081578,0.00041749646,0.00014292257,0.00020843068,0.000098783064,0.00016095921,0.0010265827],"category_scores_gemma":[0.00086870417,0.00016862413,0.00012055752,0.00020459467,0.00031229766,0.00022646718,0.00019584829,0.00016768616,0.00014673248],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033610023,0.00011041089,0.8093087,0.000090481764,0.00027015313,0.004924445,0.00085882324,0.0010817023,0.14335333,0.00020894458,0.00046369046,0.035968248],"study_design_scores_gemma":[0.000011585631,0.00011285902,0.9932856,0.0000027535348,0.000025220608,0.0030518805,0.000100172714,0.0005316027,0.0025989627,0.00012282106,0.00015156284,0.000004964225],"about_ca_topic_score_codex":0.003000984,"about_ca_topic_score_gemma":0.0041980115,"teacher_disagreement_score":0.003000984,"about_ca_system_score_codex":0.00019707206,"about_ca_system_score_gemma":0.00011625586,"threshold_uncertainty_score":0.005967021},"labels":[],"label_agreement":null},{"id":"W4403706251","doi":"10.1016/j.mri.2024.110265","title":"Corrigendum to “Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices” [Magnetic Resonance Imaging 113 (2024) 110221]","year":2024,"lang":"en","type":"erratum","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Magnetic resonance imaging; Diffusion MRI; Diffusion-Weighted Magnetic Resonance Imaging; Nuclear magnetic resonance; White matter; Materials science; Medicine; Physics; Radiology","score_opus":0.026316507779777686,"score_gpt":0.30002112444735946,"score_spread":0.2737046166675818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403706251","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012908099,0.002096672,0.0033643048,0.036969345,0.9395062,0.00008351446,0.0022919744,0.001078209,0.014480869],"genre_scores_gemma":[0.004145138,0.0073157772,0.0101517895,0.06482812,0.23164578,0.00033761497,0.0063260295,0.0029115623,0.6723382],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961526,0.0006272346,0.0004990124,0.0006105427,0.0018661665,0.00024444578],"domain_scores_gemma":[0.98165214,0.0034438907,0.0005484635,0.0012237864,0.012468296,0.0006634191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002881699,0.0029679704,0.0028703792,0.0050847484,0.004091754,0.0041330084,0.004016591,0.008295508,0.14300321],"category_scores_gemma":[0.03559054,0.0014670779,0.0028029454,0.0030948278,0.001625336,0.0025589643,0.0026503268,0.0069738994,0.10966786],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009510462,0.0000042652723,0.000012958353,0.00003635536,0.000004305178,0.000042628955,0.0000041894173,0.00004504284,0.000038107068,0.00037304242,0.99658316,0.0028464873],"study_design_scores_gemma":[0.000028126306,0.00002193466,0.00049369724,0.00017882694,0.000039643117,0.00017277662,0.000026063139,0.00074198906,0.00042777162,0.00394525,0.9938784,0.000045493078],"about_ca_topic_score_codex":0.04811271,"about_ca_topic_score_gemma":0.08145376,"teacher_disagreement_score":0.14300321,"about_ca_system_score_codex":0.0043255175,"about_ca_system_score_gemma":0.0044994964,"threshold_uncertainty_score":0.47839338},"labels":[],"label_agreement":null},{"id":"W4404061408","doi":"10.1038/s41380-024-02784-2","title":"White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Brain Institute; Centre for Addiction and Mental Health; Dalhousie University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Norges Forskningsråd; National Health and Medical Research Council; Stiftelsen för Strategisk Forskning; Hjärnfonden; U.S. Department of Health and Human Services; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche; National Institute of Mental Health; Vetenskapsrådet; Government of Canada; Deutsche Forschungsgemeinschaft","keywords":"Bipolar disorder; Psychology; White matter; Psychiatry; Obesity; Medicine; Cognition; Internal medicine; Magnetic resonance imaging","score_opus":0.012956464741473692,"score_gpt":0.30532487556777693,"score_spread":0.2923684108263032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404061408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985795,0.00012056796,0.000081550184,0.000057598885,0.000010353417,0.00002457571,0.0007938593,0.0000026804762,0.00032929415],"genre_scores_gemma":[0.9957695,0.00020631698,0.00033750304,0.00017912414,0.000026301801,0.00008407206,0.001993882,0.0000132971345,0.0013899774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999627,0.00007791176,0.00004053621,0.00012651636,0.000044244647,0.00008385252],"domain_scores_gemma":[0.9993191,0.00004971685,0.00027057985,0.00010806553,0.0000999662,0.00015261877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078775,0.0008118187,0.0005843254,0.0009094493,0.0021508671,0.0013374329,0.0008628614,0.0010744818,0.0018164581],"category_scores_gemma":[0.0011665551,0.0011062683,0.000812194,0.0016844759,0.00044122813,0.00090345583,0.0013392352,0.0010285862,0.00058616616],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002683879,0.00013953623,0.99591297,0.0000143468,0.00027184747,0.00019842618,0.0010145704,0.000020576963,0.000566444,0.000049670452,0.00050361094,0.0010395261],"study_design_scores_gemma":[0.000020021247,0.000067119756,0.9982768,0.00001131959,0.00010824714,0.00019925977,0.0008605621,0.000037345442,0.000033388176,0.000032859447,0.0003460521,0.000007077893],"about_ca_topic_score_codex":0.023085082,"about_ca_topic_score_gemma":0.041463457,"teacher_disagreement_score":0.023085082,"about_ca_system_score_codex":0.0004960761,"about_ca_system_score_gemma":0.000421063,"threshold_uncertainty_score":0.045901418},"labels":[],"label_agreement":null},{"id":"W4404089810","doi":"10.1152/jn.00408.2024","title":"Magnetic resonance diffusion tensor imaging for detecting the cerebral microstructure changes in patients with CSVD-induced mild cognitive impairment","year":2024,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Entorhinal cortex; Hippocampus; Fractional anisotropy; Diffusion MRI; Receiver operating characteristic; Atrophy; Internal medicine; Montreal Cognitive Assessment; Dementia; Medicine; Cardiology; Psychology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.022220803669820835,"score_gpt":0.29912103811219903,"score_spread":0.2769002344423782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404089810","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99630153,0.0017502442,0.0005209911,0.00009528212,0.000018303555,0.00006667388,0.00015032156,0.000017045617,0.0010796323],"genre_scores_gemma":[0.99841106,0.00045601552,0.00072853075,0.000026873658,0.000020879466,0.000020661359,0.00012382459,0.0000018589071,0.00021043397],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997993,0.000058512578,0.000034027224,0.000035045545,0.00004814128,0.000025043031],"domain_scores_gemma":[0.9996166,0.00010378152,0.0000858457,0.000026488915,0.000093903385,0.00007342681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001042467,0.0005741442,0.0004235255,0.0013508069,0.00030515366,0.00066072575,0.00032973028,0.0005182637,0.00059184426],"category_scores_gemma":[0.001780153,0.000147183,0.00026993584,0.00045718907,0.00024780043,0.00041141253,0.00028339255,0.00042956046,0.00015331717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002318196,0.00043163553,0.9519586,0.00012800426,0.00022575044,0.0008216085,0.00013004607,0.00048826728,0.011327476,0.00015300451,0.00040403267,0.031613465],"study_design_scores_gemma":[0.0000994618,0.0010714168,0.9908351,0.000051732302,0.00020572597,0.0015122475,0.00020173975,0.003285105,0.0019673128,0.00023854504,0.0005116868,0.00002002453],"about_ca_topic_score_codex":0.0028894849,"about_ca_topic_score_gemma":0.005697087,"teacher_disagreement_score":0.0028894849,"about_ca_system_score_codex":0.00031538488,"about_ca_system_score_gemma":0.00059507886,"threshold_uncertainty_score":0.005745411},"labels":[],"label_agreement":null},{"id":"W4404130284","doi":"10.1101/2024.11.07.24316876","title":"Transdiagnostic alterations in white matter microstructure associated with suicidal thoughts and behaviours in the ENIGMA Suicidal Thoughts and Behaviours consortium","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Dalhousie University","funders":"Instituto de Salud Carlos III; National Institutes of Health; Canadian Institutes of Health Research; Junta de Andalucía; National Institute of Mental Health; Ministero della Salute; Japan Society for the Promotion of Science; National Health and Medical Research Council; Dalhousie University; Universiteit Leiden; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; Wellcome Trust; Instituto de Investigación Marqués de Valdecilla; European Commission; Japan Agency for Medical Research and Development; Bundesministerium für Bildung und Forschung; National Alliance for Research on Schizophrenia and Depression; University of Minnesota; Deutsche Forschungsgemeinschaft; Nova Scotia Health Research Foundation; Medical Research Council; American Foundation for Suicide Prevention","keywords":"Fractional anisotropy; Corpus callosum; Suicidal ideation; Psychology; White matter; Diffusion MRI; Psychiatry; Medicine; Clinical psychology; Poison control; Injury prevention; Neuroscience; Magnetic resonance imaging","score_opus":0.030427590266131534,"score_gpt":0.317941579987709,"score_spread":0.2875139897215775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404130284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961235,0.00027387112,0.00037348372,0.0001167091,0.000012731676,0.00008111859,0.0025769838,0.000016869193,0.00042471234],"genre_scores_gemma":[0.99219304,0.00016748084,0.00077018305,0.0000690069,0.000018924055,0.00014639541,0.0061000567,0.000023089546,0.00051191746],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900985,0.0003560389,0.00013729207,0.00023199311,0.00015742144,0.00010731965],"domain_scores_gemma":[0.99690884,0.00029525682,0.0012177563,0.00043632553,0.0006940161,0.00044778033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024921196,0.00054113485,0.0007112273,0.0015432268,0.00072734477,0.0010505044,0.00073690695,0.0005608938,0.0019131555],"category_scores_gemma":[0.005789653,0.00042719996,0.00082547736,0.0012178986,0.00040707726,0.0003794043,0.0027798882,0.0006143337,0.00037126738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007282935,0.000056089506,0.99045384,0.00008387781,0.0007684171,0.00022968551,0.00041867272,0.00015712384,0.00092334475,0.00010399701,0.0014827611,0.0045938506],"study_design_scores_gemma":[0.000060045266,0.000083002764,0.99756867,0.000040026473,0.00018777365,0.0007331339,0.00024994963,0.0002293796,0.0001461266,0.00012266827,0.00056609424,0.000013032396],"about_ca_topic_score_codex":0.009580053,"about_ca_topic_score_gemma":0.01188809,"teacher_disagreement_score":0.009580053,"about_ca_system_score_codex":0.00052512717,"about_ca_system_score_gemma":0.0006200026,"threshold_uncertainty_score":0.019048572},"labels":[],"label_agreement":null},{"id":"W4404289864","doi":"10.2196/64825","title":"Multiparametric MRI Assessment of Morpho-Functional Muscle Changes Following a 6-Month FES-Cycling Training Program: Pilot Study in People With a Complete Spinal Cord Injury","year":2024,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Istituto Nazionale per l'Assicurazione Contro Gli Infortuni sul Lavoro; Ministero della Salute","keywords":"Spinal cord injury; Cycling; Functional electrical stimulation; Physical medicine and rehabilitation; Back muscles; Medicine; Preprint; Training (meteorology); Physical therapy; Spinal cord; Psychology; Neuroscience; Computer science; Internal medicine; Stimulation; Physics","score_opus":0.11753916975689538,"score_gpt":0.4294734938374198,"score_spread":0.3119343240805244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404289864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974304,0.000020785552,0.000042552936,0.0000067249975,0.0000016447281,0.000090468115,0.00001770424,0.0000021326869,0.00007484215],"genre_scores_gemma":[0.99913245,0.000035045454,0.00024562026,0.00002696272,0.00001264771,0.0002069125,0.00009654561,0.0000011273459,0.00024268024],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997875,0.00005913378,0.000013787837,0.000040607265,0.000027464408,0.00007150243],"domain_scores_gemma":[0.9995759,0.000040297633,0.000055592707,0.000025674948,0.000095935015,0.000206497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007632585,0.0005835891,0.0005979759,0.00055629405,0.0006775893,0.00023395196,0.00026742852,0.000793007,0.0010038653],"category_scores_gemma":[0.00073790835,0.00027723503,0.000538512,0.00022026818,0.00033464402,0.00028727503,0.00041519504,0.00041074245,0.00028733938],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.046413224,0.089088105,0.7225019,0.0004697606,0.00047580112,0.0026252128,0.006936017,0.00076850626,0.07112104,0.00003489761,0.00035657498,0.05920889],"study_design_scores_gemma":[0.0007961542,0.07220817,0.9238195,0.000010533442,0.000119596254,0.00035592963,0.0008363489,0.0002981875,0.0013045787,0.000015605128,0.0002171664,0.000018271598],"about_ca_topic_score_codex":0.0027565288,"about_ca_topic_score_gemma":0.0035053769,"teacher_disagreement_score":0.0027565288,"about_ca_system_score_codex":0.00023003054,"about_ca_system_score_gemma":0.00033256938,"threshold_uncertainty_score":0.0054810047},"labels":[],"label_agreement":null},{"id":"W4404339721","doi":"10.3389/fphys.2024.1487953","title":"A diffusion tensor imaging-based multidimensional study of brain structural changes after long-term high-altitude exposure and their relationships with cognitive function","year":2024,"lang":"en","type":"article","venue":"Frontiers in Physiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Cognition; Effects of high altitude on humans; Montreal Cognitive Assessment; Psychology; Magnetic resonance imaging; Medicine; Internal medicine; Audiology; Cognitive impairment; Neuroscience","score_opus":0.021523040737430884,"score_gpt":0.28622009124766096,"score_spread":0.26469705051023007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404339721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998547,0.00039488377,0.0005728422,0.000042700864,0.0000059947156,0.00002647602,0.00016796225,0.000004732619,0.00023749922],"genre_scores_gemma":[0.9983381,0.0002695975,0.0009472431,0.000014436317,0.000014863952,0.000028671353,0.00018049827,0.0000014110341,0.00020512244],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992156,0.000020032136,0.000009930897,0.000017212089,0.000016137481,0.000015155395],"domain_scores_gemma":[0.9997235,0.000018616178,0.00009628338,0.000017713253,0.00006226538,0.00008169922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035517206,0.00029615496,0.00018631652,0.0007705531,0.0003369239,0.00030319675,0.00015423493,0.0002584937,0.0005077179],"category_scores_gemma":[0.00049553905,0.00008072794,0.00022019866,0.000499361,0.00024309584,0.00032408405,0.0002944623,0.00024316074,0.000087744986],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011347311,0.0005196481,0.91983086,0.00028457752,0.0005548749,0.0010099594,0.00062406145,0.0005275712,0.044384714,0.00017915912,0.00044806785,0.030501895],"study_design_scores_gemma":[0.00001452325,0.00031153284,0.9977265,0.000007217917,0.00005341534,0.0004379855,0.00014106136,0.0005766948,0.0004971164,0.000065548964,0.00016052234,0.000007819597],"about_ca_topic_score_codex":0.0034102744,"about_ca_topic_score_gemma":0.0053651636,"teacher_disagreement_score":0.0034102744,"about_ca_system_score_codex":0.00025235917,"about_ca_system_score_gemma":0.00036738845,"threshold_uncertainty_score":0.006780863},"labels":[],"label_agreement":null},{"id":"W4404340498","doi":"10.1093/braincomms/fcae353","title":"Compensatory mechanisms amidst demyelinating disorders: insights into cognitive preservation","year":2024,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Queen's University; McGill University; Montreal Neurological Institute and Hospital; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Health Canada; Government of Canada; Ontario Institute for Regenerative Medicine; Hospital for Sick Children; Canadian Bee Research Fund; Fondation Brain Canada","keywords":"Neuroscience; Cognition; Multiple sclerosis; Saccade; Psychology; Magnetoencephalography; Diffusion MRI; Neuroimaging; Tractography; White matter; Myelin; Eye movement; Magnetic resonance imaging; Medicine; Electroencephalography; Central nervous system; Psychiatry","score_opus":0.09096486323302172,"score_gpt":0.40057447805293295,"score_spread":0.3096096148199112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404340498","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942319,0.0013651048,0.0023701363,0.00022809641,0.000005182944,0.0000070335136,0.000076113436,0.000033853168,0.0016825515],"genre_scores_gemma":[0.9976363,0.0005906133,0.0015292207,0.000019961248,0.0000048932075,0.0000054180173,0.000036129917,0.0000031236468,0.00017432867],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987054,0.000026272412,0.000009354896,0.000035317877,0.000028054053,0.000030533865],"domain_scores_gemma":[0.9995696,0.000087539236,0.00017223557,0.000061139406,0.0000563494,0.000053115597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048157675,0.00042069712,0.00017158937,0.00086791813,0.00016290206,0.0006353378,0.00033426713,0.00022934942,0.0005001125],"category_scores_gemma":[0.0013319472,0.000095113945,0.00021829014,0.00029974148,0.0007814837,0.00086136267,0.00035426323,0.00029478845,0.00006125901],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004998549,0.00035984986,0.6393822,0.0003999657,0.00020557431,0.0040333746,0.0076058083,0.0035566394,0.10425682,0.017549817,0.0006154069,0.22153467],"study_design_scores_gemma":[0.000014389034,0.0004193178,0.96118253,0.00006545574,0.000064996915,0.0035043084,0.002419382,0.00461845,0.012401243,0.013769268,0.0015117376,0.000028899118],"about_ca_topic_score_codex":0.0024115853,"about_ca_topic_score_gemma":0.0035963715,"teacher_disagreement_score":0.0024115853,"about_ca_system_score_codex":0.00042894544,"about_ca_system_score_gemma":0.0004487051,"threshold_uncertainty_score":0.004795134},"labels":[],"label_agreement":null},{"id":"W4404349164","doi":"10.1038/s41583-024-00878-y","title":"Reply to ‘Issues of parcellation in the calculation of structure–function coupling’","year":2024,"lang":"en","type":"review","venue":"Nature reviews. Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Coupling (piping); Function (biology); Psychology; Statistical physics; Computer science; Mathematics; Physics; Materials science","score_opus":0.12526227443637436,"score_gpt":0.4734032259864475,"score_spread":0.3481409515500732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404349164","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000092684786,0.058216635,0.0010072893,0.83214706,0.107725985,0.000009464573,0.00016765561,0.0000920789,0.00054117263],"genre_scores_gemma":[0.001836093,0.042600855,0.0012386851,0.8315684,0.11825159,0.00006280503,0.0001556307,0.00013531683,0.0041505857],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99647623,0.00085774594,0.0005813782,0.00064341346,0.0011268527,0.0003144401],"domain_scores_gemma":[0.9781837,0.01332483,0.0012565181,0.00080132333,0.005195438,0.0012381305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010393822,0.0020979163,0.0029498013,0.001982201,0.0017465083,0.00408118,0.0053840596,0.025128318,0.0060009724],"category_scores_gemma":[0.035231527,0.001454943,0.0019738108,0.0018620073,0.0075140754,0.0098496005,0.0036993797,0.047896273,0.010343415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005571992,0.00000976513,0.00004831281,0.0003195867,0.00003247109,0.000083492974,0.00007342611,0.00008443673,0.00012205033,0.004740787,0.9815855,0.012844477],"study_design_scores_gemma":[0.00010295894,0.00005475565,0.0005395959,0.0006235436,0.000051242132,0.0006577672,0.00010877421,0.00025179674,0.00036477335,0.025039082,0.97212404,0.00008169975],"about_ca_topic_score_codex":0.004276403,"about_ca_topic_score_gemma":0.004956146,"teacher_disagreement_score":0.025128318,"about_ca_system_score_codex":0.0020526904,"about_ca_system_score_gemma":0.0038471897,"threshold_uncertainty_score":0.054968476},"labels":[],"label_agreement":null},{"id":"W4404395863","doi":"10.52202/079017-0425","title":"On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Computer science; Metadata; Artificial intelligence; Machine learning; Training (meteorology); Generative model; Generative grammar; Transfer of learning; Field (mathematics); Training set; Data mining; Mathematics","score_opus":0.08187471162418929,"score_gpt":0.37248853495099205,"score_spread":0.29061382332680274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404395863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01901484,0.0007001125,0.9747704,0.00057003193,0.000111953384,0.000047456786,0.000048558984,0.0007094415,0.0040272526],"genre_scores_gemma":[0.5165336,0.002779419,0.4675422,0.0004171147,0.00025960754,0.00023106934,0.00027111243,0.0007627208,0.011203105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977344,0.00008385528,0.0000145439435,0.00006488126,0.00003604566,0.00002728777],"domain_scores_gemma":[0.99861896,0.0006294153,0.00011761017,0.0003178423,0.00019641226,0.000119691824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011047107,0.00111342,0.00080025214,0.00037235557,0.00046359416,0.0009613841,0.0014143802,0.0014557047,0.009544512],"category_scores_gemma":[0.0054435227,0.00036448112,0.0006190912,0.00032322964,0.0007465136,0.0026872454,0.0014848892,0.0023133382,0.001367555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034670442,0.00043553632,0.001142584,0.0005493299,0.0001309272,0.0001592932,0.00025102985,0.3869755,0.05532919,0.19569546,0.0044574062,0.35452697],"study_design_scores_gemma":[0.000021180209,0.000112344285,0.0004324978,0.00007554576,0.000027492973,0.00006844121,0.000026558562,0.9228693,0.011520836,0.061409555,0.003405616,0.000030574287],"about_ca_topic_score_codex":0.0016732648,"about_ca_topic_score_gemma":0.0018634862,"teacher_disagreement_score":0.009544512,"about_ca_system_score_codex":0.00045195752,"about_ca_system_score_gemma":0.0006241757,"threshold_uncertainty_score":0.031929612},"labels":[],"label_agreement":null},{"id":"W4404579697","doi":"10.1016/j.compbiomed.2024.109410","title":"Deep learning-based denoising for unbiased analysis of morphology and stiffness in amyloid fibrils","year":2024,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Korea Health Industry Development Institute; Information Technology Research Centre; Ministry of Health and Welfare","keywords":"Morphology (biology); Amyloid fibril; Stiffness; Noise reduction; Amyloid (mycology); Artificial intelligence; Computer science; Biological system; Pattern recognition (psychology); Materials science; Amyloid β; Chemistry; Biology; Composite material; Medicine; Internal medicine; Disease","score_opus":0.048127487474445,"score_gpt":0.397424460641367,"score_spread":0.349296973166922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404579697","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03654627,0.00023898575,0.96140635,0.000121355464,0.00002121538,0.000020640413,0.00008027749,0.0009437946,0.000621105],"genre_scores_gemma":[0.43302757,0.00034336574,0.56311125,0.00015481636,0.00002978504,0.00009597214,0.0004216999,0.00022960926,0.0025859105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997098,0.00005681655,0.000016648133,0.00006224659,0.000116740644,0.00003759695],"domain_scores_gemma":[0.999395,0.00024890917,0.0000634006,0.0000731696,0.00018738546,0.000032138443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011063104,0.0005070113,0.0004676866,0.0006740392,0.00028646982,0.00044431514,0.0006662237,0.00068703486,0.000744721],"category_scores_gemma":[0.001998652,0.0003226456,0.00057564717,0.0005009011,0.0004488362,0.0006532942,0.0007541717,0.0009599915,0.0002899482],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025538864,0.00015950324,0.0034524882,0.000194247,0.00013488217,0.00021865159,0.00021923416,0.40701988,0.1794285,0.010047884,0.00312828,0.39574113],"study_design_scores_gemma":[0.0000028333602,0.000015281983,0.00037764953,0.000003580958,0.000005748588,0.00002301359,0.000005576491,0.9873574,0.010112239,0.0016500899,0.0004414852,0.0000051848256],"about_ca_topic_score_codex":0.0029682568,"about_ca_topic_score_gemma":0.00615347,"teacher_disagreement_score":0.0029682568,"about_ca_system_score_codex":0.0005287928,"about_ca_system_score_gemma":0.0008176444,"threshold_uncertainty_score":0.0059019327},"labels":[],"label_agreement":null},{"id":"W4404903795","doi":"10.3390/life14121580","title":"Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models","year":2024,"lang":"en","type":"article","venue":"Life","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Strong; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Arizona State University; Biogen; Eli Lilly and Company; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Positron emission tomography; Neuroimaging; Partial volume; Leverage (statistics); Statistical power; Pet imaging; Magnetic resonance imaging; Amyloid (mycology); Computer science; Artificial intelligence; Biomedical engineering; Nuclear medicine; Medicine; Pathology; Neuroscience; Radiology; Mathematics; Biology","score_opus":0.16426662318476207,"score_gpt":0.3816011422324775,"score_spread":0.21733451904771542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404903795","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033409715,0.00037740194,0.96496314,0.0002549501,0.000013785273,0.000017667802,0.00006220746,0.0005328719,0.00036825257],"genre_scores_gemma":[0.5801609,0.0005810259,0.4173902,0.00024591398,0.000031368116,0.00006260901,0.000268845,0.00020813958,0.0010509584],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971884,0.00010784678,0.000016596401,0.000059017108,0.000071615716,0.000026072554],"domain_scores_gemma":[0.99878246,0.00073949306,0.00018318421,0.00012374301,0.0001278732,0.000043179003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013746165,0.000696161,0.0004951016,0.0005045427,0.00016314907,0.00078530144,0.0006442417,0.0008565366,0.0005835059],"category_scores_gemma":[0.004627622,0.00033896166,0.0006046322,0.00040969456,0.0004924299,0.0013207601,0.00096242165,0.0010848695,0.00024511112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030774364,0.00013534672,0.0023633325,0.00022199895,0.00012374192,0.00020173853,0.00014340345,0.7484615,0.085321605,0.0076329224,0.0012651684,0.15382154],"study_design_scores_gemma":[0.0000047652898,0.000015600468,0.0001474185,0.000004555135,0.0000066942553,0.000039213068,0.000002971935,0.99198157,0.005966662,0.001589071,0.00023463309,0.000006949224],"about_ca_topic_score_codex":0.0018272992,"about_ca_topic_score_gemma":0.0026578014,"teacher_disagreement_score":0.0018272992,"about_ca_system_score_codex":0.00047529582,"about_ca_system_score_gemma":0.000651556,"threshold_uncertainty_score":0.00726974},"labels":[],"label_agreement":null},{"id":"W4404933030","doi":"10.1038/s41380-024-02821-0","title":"Deciphering white matter microstructural alterations in catatonia according to ICD-11: replication and machine learning analysis","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft; Physicians' Services Incorporated Foundation","keywords":"Catatonia; Psychomotor learning; Cohort; White matter; Fractional anisotropy; Corpus callosum; Psychology; Magnetic resonance imaging; Replication (statistics); Psychomotor retardation; Psychiatry; Medicine; Internal medicine; Neuroscience; Cognition; Pathology; Radiology; Schizophrenia (object-oriented programming); Virology","score_opus":0.0168071735524025,"score_gpt":0.3306560348096529,"score_spread":0.31384886125725037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404933030","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99638844,0.00012300654,0.001795068,0.000026263215,0.000013405867,0.00009163581,0.001305291,0.000049790797,0.000207139],"genre_scores_gemma":[0.9948159,0.000051736908,0.0013679533,0.000013225494,0.000008015329,0.000091952774,0.003445317,0.000021629563,0.0001841798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989231,0.00027988944,0.00016814606,0.00039552708,0.00015753707,0.000075701384],"domain_scores_gemma":[0.99540126,0.0007602645,0.00078251434,0.0019986301,0.0008388007,0.00021838686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033358305,0.00066814746,0.00063521,0.00100602,0.00036586405,0.0007798144,0.00054345385,0.0005598811,0.00079591415],"category_scores_gemma":[0.008656126,0.00023498543,0.00088301935,0.0005871072,0.00039389875,0.00031497533,0.00093708426,0.00071976654,0.00034294723],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008915576,0.00015534641,0.96463794,0.000095124415,0.0007182241,0.00044571952,0.00046833022,0.0012458424,0.009945053,0.00007416194,0.00083815696,0.020484556],"study_design_scores_gemma":[0.000034645906,0.00021160416,0.99383116,0.000016164262,0.00014836494,0.0004970378,0.00012862206,0.002938284,0.0016230585,0.00008579598,0.00047108476,0.000014167108],"about_ca_topic_score_codex":0.005942714,"about_ca_topic_score_gemma":0.007051916,"teacher_disagreement_score":0.005942714,"about_ca_system_score_codex":0.00033549085,"about_ca_system_score_gemma":0.00033282695,"threshold_uncertainty_score":0.017641783},"labels":[],"label_agreement":null},{"id":"W4405030241","doi":"10.48550/arxiv.2411.19339","title":"Towards a Mechanistic Explanation of Diffusion Model Generalization","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Institute for Advanced Research","keywords":"Generalization; Diffusion; Computer science; Statistical physics; Mathematical economics; Epistemology; Economics; Philosophy; Physics; Thermodynamics","score_opus":0.17553938457602006,"score_gpt":0.2696021957492422,"score_spread":0.09406281117322216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405030241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045232605,0.0003832308,0.9379876,0.0035389792,0.00012490676,0.000063722124,0.0001514591,0.0008096119,0.011707871],"genre_scores_gemma":[0.90793836,0.00069556467,0.08526064,0.000672089,0.00012794875,0.00015526038,0.00016079085,0.00025836524,0.004730976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995646,0.000107255095,0.000021041154,0.00014452873,0.00010143103,0.00006110646],"domain_scores_gemma":[0.99802554,0.0008510202,0.00021111478,0.0006016406,0.00021640213,0.00009441647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023766705,0.0006667779,0.00066562585,0.00078984525,0.00059231493,0.0015667015,0.002486247,0.0026610203,0.005076977],"category_scores_gemma":[0.008415436,0.0005385651,0.00094412325,0.00035962914,0.002617858,0.004605017,0.0020575556,0.0028745488,0.00080573536],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000660692,0.00008452418,0.0022291532,0.00017190655,0.00009155959,0.00031467862,0.0005879037,0.30296308,0.015142918,0.65053713,0.0029481857,0.024862884],"study_design_scores_gemma":[0.000020037292,0.0000397453,0.0007700828,0.000028845776,0.000012370178,0.0001563456,0.000044714252,0.53943825,0.001963212,0.45581368,0.0016834687,0.000029278775],"about_ca_topic_score_codex":0.0017595456,"about_ca_topic_score_gemma":0.0011552365,"teacher_disagreement_score":0.005076977,"about_ca_system_score_codex":0.00079595175,"about_ca_system_score_gemma":0.000694992,"threshold_uncertainty_score":0.016984165},"labels":[],"label_agreement":null},{"id":"W4405303900","doi":"10.1109/tci.2024.3516574","title":"FgC2F-UDiff: Frequency-Guided and Coarse-to-Fine Unified Diffusion Model for Multi-Modality Missing MRI Synthesis","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modality (human–computer interaction); Computer science; Artificial intelligence; Computer vision","score_opus":0.1243962032311734,"score_gpt":0.3944708048256058,"score_spread":0.2700746015944324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405303900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006740964,0.00015385271,0.990391,0.00011071094,0.000034490768,0.000027546677,0.000041102794,0.00031301088,0.0021873114],"genre_scores_gemma":[0.6755997,0.00035641357,0.31368655,0.00022358076,0.00006387475,0.0002712741,0.00027161423,0.00013165238,0.0093953395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99974006,0.000049277223,0.000015331567,0.00007565874,0.000076836775,0.000042697808],"domain_scores_gemma":[0.99966705,0.00010720227,0.000045729732,0.00004858777,0.000098636905,0.000032720767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081481494,0.00077415025,0.000678689,0.0005012753,0.0004646097,0.0006779656,0.0017298927,0.0016743413,0.0023979158],"category_scores_gemma":[0.0015644202,0.0003207964,0.00071924506,0.00041414672,0.0006041846,0.0012655557,0.0010109778,0.0009522988,0.00042733722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008511497,0.000048715094,0.0005001063,0.00008225053,0.00003538067,0.00012782498,0.00009512427,0.8736508,0.009132405,0.030002618,0.0024227214,0.08381697],"study_design_scores_gemma":[0.000003221748,0.000013871262,0.00003836244,0.0000024845765,0.0000034587724,0.00001620563,0.000002504424,0.9967757,0.00069353305,0.0018833162,0.0005633482,0.0000039771066],"about_ca_topic_score_codex":0.007885416,"about_ca_topic_score_gemma":0.006764319,"teacher_disagreement_score":0.007885416,"about_ca_system_score_codex":0.00092788,"about_ca_system_score_gemma":0.00093795476,"threshold_uncertainty_score":0.015679061},"labels":[],"label_agreement":null},{"id":"W4405372902","doi":"10.3390/brainsci14121252","title":"Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation","year":2024,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Hebei University","keywords":"Neuroimaging; Diffusion MRI; Artificial intelligence; Deep learning; Computer science; Magnetoencephalography; Tensor (intrinsic definition); Rank (graph theory); Sensor fusion; Pattern recognition (psychology); Machine learning; Magnetic resonance imaging; Psychology; Neuroscience; Mathematics; Medicine; Electroencephalography","score_opus":0.051272985969632784,"score_gpt":0.3926637304508105,"score_spread":0.3413907444811777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405372902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0229976,0.00035273551,0.97512895,0.0002083626,0.000037121434,0.000032384687,0.00014198353,0.0006954288,0.00040549232],"genre_scores_gemma":[0.56257755,0.0005128541,0.4341583,0.00017399379,0.00010268591,0.00011122654,0.0006193633,0.00012866048,0.001615337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946123,0.00017537859,0.000041541454,0.00012442384,0.00012689385,0.00007048227],"domain_scores_gemma":[0.9985545,0.00044630078,0.00025842965,0.00018387535,0.00046823465,0.00008853385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024915966,0.0014877958,0.000876061,0.0009518843,0.00037233374,0.0007722309,0.0009399895,0.0009515129,0.00134012],"category_scores_gemma":[0.00514677,0.00032267574,0.0010226454,0.0007377583,0.00050859165,0.0016857225,0.0012840312,0.0015645988,0.0006529528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003510735,0.00020982517,0.0055761635,0.00016225448,0.00020534942,0.00018315646,0.00019304025,0.51680636,0.026538646,0.009936523,0.004190201,0.4356474],"study_design_scores_gemma":[0.0000032773492,0.00003304571,0.00038621994,0.000006393185,0.000013745148,0.00002937283,0.000007956978,0.9925943,0.0038821716,0.0026582861,0.00037481336,0.0000103791235],"about_ca_topic_score_codex":0.0046880906,"about_ca_topic_score_gemma":0.0048931846,"teacher_disagreement_score":0.0046880906,"about_ca_system_score_codex":0.0007146424,"about_ca_system_score_gemma":0.0010993587,"threshold_uncertainty_score":0.013176978},"labels":[],"label_agreement":null},{"id":"W4405385553","doi":"10.1523/jneurosci.2139-23.2024","title":"Individual Variability in the Structural Connectivity Architecture of the Human Brain","year":2024,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fundamental Research Funds for the Central Universities; State Key Laboratory of Cognitive Neuroscience and Learning; National Natural Science Foundation of China","keywords":"Cognition; Tractography; Neuroscience; Connectome; Human brain; Connectomics; Laminar organization; Psychology; Functional connectivity; Diffusion MRI; Biology; Medicine","score_opus":0.0669868368762148,"score_gpt":0.3873426448932615,"score_spread":0.32035580801704666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405385553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923683,0.00018320631,0.006660256,0.00002636972,0.0000023083833,0.0000049665555,0.0003580035,0.000032341442,0.00036421808],"genre_scores_gemma":[0.9988329,0.00004259475,0.00080065156,0.000002836831,0.0000029171701,0.0000034578318,0.00026285136,0.0000050688586,0.00004677815],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996401,0.000117884694,0.000030243578,0.0001383957,0.00004779111,0.000025504785],"domain_scores_gemma":[0.99895155,0.000551804,0.00021020923,0.00017521894,0.00007723635,0.000033941546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006458471,0.00014444954,0.00019425206,0.0012179259,0.00013194582,0.00032268866,0.00013011505,0.00015629665,0.00047298064],"category_scores_gemma":[0.003152488,0.00009454949,0.0001945822,0.0007195131,0.00025915727,0.00029075233,0.00029758146,0.00011919076,0.00007998634],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016620028,0.00003089397,0.8962825,0.00008793255,0.0008854244,0.0003077375,0.0008550033,0.010934147,0.024906022,0.0011522907,0.0007310494,0.06366085],"study_design_scores_gemma":[0.0000017621901,0.000026977996,0.9879744,0.0000045817014,0.000031339256,0.00042155915,0.000090334936,0.008794717,0.0008021193,0.0014734081,0.00036825155,0.000010486118],"about_ca_topic_score_codex":0.0019223299,"about_ca_topic_score_gemma":0.0040622223,"teacher_disagreement_score":0.0019223299,"about_ca_system_score_codex":0.00011944973,"about_ca_system_score_gemma":0.00011636366,"threshold_uncertainty_score":0.003822267},"labels":[],"label_agreement":null},{"id":"W4405459036","doi":"10.1007/s00429-024-02884-3","title":"Involvement of the left uncinate fasciculus in the amyotrophic lateral sclerosis: an exploratory longitudinal multi-modal neuroimaging and neuropsychological study","year":2024,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"","keywords":"Diffusion MRI; Amyotrophic lateral sclerosis; Fractional anisotropy; Inferior longitudinal fasciculus; Uncinate fasciculus; Medicine; Fasciculus; Superior longitudinal fasciculus; Cardiology; Resting state fMRI; Neuropsychology; Neuroimaging; Neuroscience; Psychology; Audiology; Internal medicine; Magnetic resonance imaging; Radiology; Cognition","score_opus":0.0910966967118141,"score_gpt":0.33427803069617246,"score_spread":0.24318133398435837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405459036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99910766,0.00019197603,0.00012711782,0.00004612186,0.0000018224924,0.00001198702,0.000041518997,0.000002828153,0.0004690495],"genre_scores_gemma":[0.9995003,0.00010230113,0.00010081995,0.000022615592,0.000008541797,0.000009796199,0.00004529889,0.0000010523181,0.00020937648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998184,0.000040303377,0.000018368657,0.00004343656,0.000024271543,0.000055225526],"domain_scores_gemma":[0.99949396,0.00013792052,0.00013352401,0.000045626464,0.00008772366,0.00010125957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000790752,0.00051377626,0.00027937815,0.0010244923,0.0009262008,0.00039351406,0.00033905345,0.0006228722,0.0009885503],"category_scores_gemma":[0.0012443911,0.00033955468,0.00026843548,0.00032887512,0.001173427,0.00081666955,0.0006352339,0.00038169287,0.0002599033],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027044816,0.0009981734,0.83056325,0.00007856619,0.00014033575,0.09089166,0.0026755172,0.0006377222,0.060008697,0.00025878538,0.0002098522,0.010833128],"study_design_scores_gemma":[0.00004881612,0.0016639876,0.9122768,0.000025046107,0.00012133651,0.07967984,0.001052416,0.0007248649,0.003368751,0.0003281333,0.0006788726,0.00003119977],"about_ca_topic_score_codex":0.005549522,"about_ca_topic_score_gemma":0.0054705795,"teacher_disagreement_score":0.005549522,"about_ca_system_score_codex":0.00042579367,"about_ca_system_score_gemma":0.00063846755,"threshold_uncertainty_score":0.011034429},"labels":[],"label_agreement":null},{"id":"W4405483262","doi":"10.1007/s00701-024-06374-7","title":"Mini-strokes within Broca-caudate connections during left insular glioma awake surgery cause transient severe naming deficits","year":2024,"lang":"en","type":"article","venue":"Acta Neurochirurgica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Medicine; Neuroradiology; Neurology; Perseveration; Stroke (engine); Exact test; Diffusion MRI; Magnetic resonance imaging; Effective diffusion coefficient; Neurosurgery; Glioma; Radiology; Surgery; Audiology; Cognition","score_opus":0.04718354036768995,"score_gpt":0.30554855444189927,"score_spread":0.2583650140742093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405483262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982485,0.0021719474,0.0020588003,0.0018106207,0.0003788107,0.00009595883,0.00033567395,0.00024026216,0.0104230745],"genre_scores_gemma":[0.99796164,0.00036559257,0.00019853932,0.00027916118,0.00018958129,0.000012145178,0.00013317863,0.000016303567,0.0008437877],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9998253,0.000016280328,0.000017213517,0.000032112963,0.0000278882,0.00008131598],"domain_scores_gemma":[0.9990784,0.00023680914,0.0002769208,0.000110098335,0.00007093564,0.00022680256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011467316,0.001058925,0.00050256395,0.0007704664,0.0008356328,0.00060490397,0.0007347591,0.0017356442,0.0027673417],"category_scores_gemma":[0.0016873907,0.00045031882,0.0005640857,0.0005914346,0.0009776605,0.0010367043,0.00051334035,0.0024366525,0.0008453771],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007157692,0.0001191591,0.032958426,0.00006249176,0.00008575851,0.95279217,0.00018257083,0.00012646722,0.0046701753,0.00017567696,0.001052287,0.0070590144],"study_design_scores_gemma":[0.0001286805,0.00051458174,0.1802713,0.000044221782,0.000277551,0.8075448,0.00039432137,0.0011546508,0.0067270724,0.0008954348,0.0019766649,0.00007065354],"about_ca_topic_score_codex":0.008400115,"about_ca_topic_score_gemma":0.015290472,"teacher_disagreement_score":0.008400115,"about_ca_system_score_codex":0.000940493,"about_ca_system_score_gemma":0.0008263324,"threshold_uncertainty_score":0.016702414},"labels":[],"label_agreement":null},{"id":"W4405515272","doi":"10.1001/jamanetworkopen.2024.51678","title":"Frontal White Matter Changes and Craving Recovery in Inpatients With Heroin Use Disorder","year":2024,"lang":"en","type":"article","venue":"JAMA Network Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Craving; Heroin; Medicine; Opioid use disorder; Psychological intervention; Psychiatry; Mood; Psychology; Clinical psychology; Internal medicine; Opioid; Addiction; Drug","score_opus":0.0419218034781447,"score_gpt":0.3201518424256862,"score_spread":0.2782300389475415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405515272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99967325,0.00005039564,0.00001648282,0.000024078152,0.0000017977407,0.0000036164051,0.00010310658,0.0000012162881,0.00012610217],"genre_scores_gemma":[0.99937844,0.00006498937,0.00005300379,0.000023403269,0.000004395788,0.000005210071,0.00025379224,8.3847095e-7,0.00021583996],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999368,0.000008034268,0.0000066897915,0.000015528103,0.000013550634,0.000019383879],"domain_scores_gemma":[0.99978334,0.000014954195,0.00011092975,0.000012939654,0.000028073631,0.000049702867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017168807,0.00017505919,0.00019754276,0.00035937416,0.00046874632,0.00030243085,0.00016145433,0.00021840922,0.0018554935],"category_scores_gemma":[0.0006109067,0.00017255775,0.0001500802,0.0002634339,0.0001785549,0.0002594935,0.00027727784,0.00029728285,0.00016561788],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013697089,0.00006044618,0.99724907,0.000005373972,0.000018197572,0.00018834829,0.00012064825,0.000017158198,0.0005513482,0.000009014545,0.000102423604,0.0015409566],"study_design_scores_gemma":[0.00000254396,0.000035044613,0.99963164,0.0000023108478,0.0000039904376,0.00014063105,0.00008598448,0.000031481624,0.000029970332,0.000006746254,0.000028953238,6.530857e-7],"about_ca_topic_score_codex":0.012458268,"about_ca_topic_score_gemma":0.038752917,"teacher_disagreement_score":0.012458268,"about_ca_system_score_codex":0.00036503683,"about_ca_system_score_gemma":0.00029539192,"threshold_uncertainty_score":0.024771512},"labels":[],"label_agreement":null},{"id":"W4405635575","doi":"10.7554/elife.94917.2.sa0","title":"Author response: Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Biology; Tractography; Anatomy; Bridging (networking); Fractional anisotropy; Neuroscience; Evolutionary biology; Computer science; Medicine; Magnetic resonance imaging; Artificial intelligence","score_opus":0.0990567845682077,"score_gpt":0.3961257767576528,"score_spread":0.2970689921894451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405635575","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027579914,0.0049566524,0.003136189,0.64703965,0.28913876,0.00037066918,0.0036731595,0.0013153399,0.04761162],"genre_scores_gemma":[0.036611155,0.011052405,0.004693437,0.30652586,0.10985891,0.00073591515,0.0037005993,0.0020856864,0.52473605],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99542254,0.0010618648,0.00041338036,0.00060441694,0.0020883083,0.00040934788],"domain_scores_gemma":[0.95467556,0.011339917,0.0022527664,0.001981374,0.025974128,0.003776288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004795672,0.00072524726,0.00090886984,0.001411291,0.0016143626,0.0029801785,0.0012097884,0.0057887863,0.18635072],"category_scores_gemma":[0.06855316,0.00033305676,0.00059066934,0.0009458723,0.0017132774,0.0021831237,0.0032117546,0.003659544,0.07966138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007129011,0.000006046907,0.00024833743,0.00044145738,0.000009291164,0.00012862778,0.00017423615,0.00004408347,0.00029020547,0.00058985874,0.9844617,0.013534915],"study_design_scores_gemma":[0.000027939433,0.000029390641,0.00087496534,0.00044040644,0.00000995253,0.00022405658,0.0006145389,0.000089376175,0.00035706427,0.0011949552,0.996114,0.00002343481],"about_ca_topic_score_codex":0.0019875586,"about_ca_topic_score_gemma":0.0044986084,"teacher_disagreement_score":0.18635072,"about_ca_system_score_codex":0.0015454141,"about_ca_system_score_gemma":0.004747299,"threshold_uncertainty_score":0.6234052},"labels":[],"label_agreement":null},{"id":"W4405635920","doi":"10.7554/elife.94917.2","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Anatomy; Biology; Tractography; Fractional anisotropy; Neuroscience; Magnetic resonance imaging; Computer science; Medicine; Artificial intelligence","score_opus":0.06363895321397584,"score_gpt":0.34557660972726695,"score_spread":0.2819376565132911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405635920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90158063,0.0010018764,0.09412165,0.00015600005,0.000012460695,0.000027470649,0.0005613734,0.0003438647,0.0021947082],"genre_scores_gemma":[0.934399,0.0006265183,0.06387038,0.000042008425,0.000009463328,0.000034255652,0.00024178838,0.00014895666,0.00062759407],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998267,0.000046466197,0.000010938443,0.00004984715,0.000044245764,0.000021776565],"domain_scores_gemma":[0.9993586,0.00016236093,0.00022799596,0.0001039196,0.00010554654,0.000041615855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004902981,0.00032977367,0.00026460618,0.0016314586,0.00026924623,0.0013096511,0.00027313537,0.0003921496,0.0011155317],"category_scores_gemma":[0.0011535523,0.00037064462,0.00021660022,0.00058631925,0.00076224527,0.00079677324,0.0009224258,0.00036787053,0.00024883103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024276177,0.00002794068,0.01930378,0.00032694594,0.000147885,0.00037212414,0.0016000861,0.010265104,0.9186245,0.0040902807,0.00029784327,0.044700734],"study_design_scores_gemma":[0.000029160543,0.00030388244,0.63055843,0.0003351247,0.0002606649,0.0030371193,0.0018607193,0.0638825,0.26354125,0.02162289,0.014343635,0.00022464388],"about_ca_topic_score_codex":0.0017699719,"about_ca_topic_score_gemma":0.0036246255,"teacher_disagreement_score":0.0017699719,"about_ca_system_score_codex":0.00026462687,"about_ca_system_score_gemma":0.00033777778,"threshold_uncertainty_score":0.0037318468},"labels":[],"label_agreement":null},{"id":"W4405656544","doi":"10.3389/fnins.2024.1467786","title":"Multi-tensor fixel-based metrics in tractometry: application to multiple sclerosis","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; Consejo Nacional de Ciencia y Tecnología; Université de Sherbrooke","keywords":"Diffusion MRI; Tractography; Tensor (intrinsic definition); Artificial intelligence; Computer science; White matter; Pattern recognition (psychology); Pipeline (software); Fractional anisotropy; Mathematics; Medicine; Radiology; Magnetic resonance imaging; Geometry","score_opus":0.11011443424357255,"score_gpt":0.358482281332626,"score_spread":0.24836784708905346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405656544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019499127,0.00036719866,0.9774645,0.00015524373,0.000025826228,0.00006628763,0.0001347809,0.0019903043,0.00029677444],"genre_scores_gemma":[0.09680233,0.00032676378,0.90150785,0.000028705355,0.00001870546,0.00005776481,0.00021076378,0.0004166246,0.0006304657],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99941635,0.00016647193,0.000043365755,0.00015352239,0.00018622648,0.000034117955],"domain_scores_gemma":[0.9981146,0.00077067316,0.00029184998,0.0002882537,0.00039429945,0.00014031761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002085228,0.0012047052,0.00068369554,0.0018633202,0.00051047927,0.0012206685,0.0007587651,0.0011256648,0.0013663593],"category_scores_gemma":[0.00639318,0.00053099974,0.00075728534,0.0017473674,0.0007016109,0.001335301,0.0013855386,0.00092271186,0.0005673314],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003196096,0.00013554626,0.00645002,0.00033411718,0.00027913833,0.0004898346,0.0004277387,0.25300494,0.08554391,0.011559964,0.0028281768,0.638627],"study_design_scores_gemma":[0.000024791236,0.00019402856,0.0040036943,0.00003862078,0.00003815584,0.0005067157,0.000043061256,0.9521743,0.030072201,0.007881529,0.0049540317,0.0000688474],"about_ca_topic_score_codex":0.007057788,"about_ca_topic_score_gemma":0.010159453,"teacher_disagreement_score":0.007057788,"about_ca_system_score_codex":0.000752985,"about_ca_system_score_gemma":0.0012914146,"threshold_uncertainty_score":0.014033437},"labels":[],"label_agreement":null},{"id":"W4405721377","doi":"10.3390/s24248173","title":"Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Breast cancer; Medicine; Receiver operating characteristic; Cancer; Prostate cancer; Diffusion MRI; Mammography; Magnetic resonance imaging; Gold standard (test); Modality (human–computer interaction); Medical imaging; Radiology; Medical physics; Computer science; Internal medicine; Artificial intelligence","score_opus":0.024322844281075114,"score_gpt":0.3334430636174504,"score_spread":0.3091202193363753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405721377","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47496134,0.0021379336,0.5165678,0.00070361194,0.00008542759,0.000119843346,0.00027522875,0.0010892861,0.004059663],"genre_scores_gemma":[0.826267,0.00074328773,0.17156492,0.00019696142,0.000022067543,0.00009043611,0.00022773287,0.0001681952,0.0007193222],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998035,0.00006021417,0.0000110723395,0.000046585894,0.000058231424,0.000020339083],"domain_scores_gemma":[0.9995509,0.00018542513,0.00011100098,0.00004269474,0.00008207164,0.000027857768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006175098,0.00047948823,0.00024431478,0.00034504032,0.00014325726,0.00048229264,0.00029509046,0.0003902685,0.00045672365],"category_scores_gemma":[0.0021303368,0.00018651062,0.00020592139,0.00027986921,0.00034219932,0.00048741416,0.00039239172,0.00040275021,0.000155612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057279423,0.00017638535,0.0024380102,0.0003268388,0.000067841385,0.00021026957,0.00015720478,0.17870596,0.7519427,0.0036869529,0.0014902434,0.06022479],"study_design_scores_gemma":[0.000043224245,0.00038615364,0.0022132578,0.000023172819,0.00006484614,0.0003438195,0.000047853868,0.54430723,0.44670767,0.0015921085,0.0042044255,0.00006620462],"about_ca_topic_score_codex":0.00067683234,"about_ca_topic_score_gemma":0.00094991736,"teacher_disagreement_score":0.00067683234,"about_ca_system_score_codex":0.00039384767,"about_ca_system_score_gemma":0.00056458806,"threshold_uncertainty_score":0.0032657385},"labels":[],"label_agreement":null},{"id":"W4405737824","doi":"10.3390/curroncol31120595","title":"A Longitudinal Multimodal Imaging Study in Patients with Temporo-Insular Diffuse Low-Grade Tumors: How the Inferior Fronto-Occipital Fasciculus Provides Information on Cognitive Outcomes","year":2024,"lang":"en","type":"article","venue":"Current Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministero della Salute","keywords":"Inferior longitudinal fasciculus; Boston Naming Test; Fasciculus; Medicine; Fractional anisotropy; Tractography; White matter; Grey matter; Audiology; Neuropsychology; Magnetic resonance imaging; Radiology; Cognition; Psychiatry","score_opus":0.0677534620503598,"score_gpt":0.3906204305209329,"score_spread":0.3228669684705731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405737824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99982625,0.000036738566,0.000028673812,0.00000723958,5.3389647e-7,0.0000013092263,0.00003255887,5.091231e-7,0.00006629037],"genre_scores_gemma":[0.9997571,0.000028593051,0.000039223356,0.0000051226734,0.0000020907485,0.0000019941654,0.00009702654,4.779538e-7,0.00006833554],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999542,0.0000065259,0.000004683337,0.000014120203,0.000006544323,0.000013955471],"domain_scores_gemma":[0.99970835,0.000039922732,0.00012950269,0.00001904671,0.000037132522,0.00006592297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021462563,0.00015285447,0.00014966077,0.00040255624,0.00021834382,0.00033511044,0.00008828625,0.00019094258,0.00089213555],"category_scores_gemma":[0.0006923302,0.0000859127,0.00013685014,0.00025648993,0.00017886145,0.00030852685,0.00017374962,0.00019609774,0.0001767202],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038256144,0.00004977824,0.9925432,0.0000065113386,0.000018594561,0.00042576223,0.00018104492,0.00004143659,0.003203351,0.000011468894,0.000035839836,0.0031004876],"study_design_scores_gemma":[0.0000053471404,0.00026792506,0.99826473,0.0000026246516,0.0000137720235,0.00073662045,0.00017008361,0.00009681566,0.0003370319,0.000023738532,0.00007831284,0.0000029950577],"about_ca_topic_score_codex":0.00195368,"about_ca_topic_score_gemma":0.0032413478,"teacher_disagreement_score":0.00195368,"about_ca_system_score_codex":0.00023342678,"about_ca_system_score_gemma":0.00017680212,"threshold_uncertainty_score":0.003884554},"labels":[],"label_agreement":null},{"id":"W4405975791","doi":"10.1101/2024.12.24.630267","title":"Anatomy-to-Tract Mapping Infers White Matter Pathways Without Diffusion Streamline Propagation","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Tractography; Diffusion MRI; Computer science; Artificial intelligence; Human Connectome Project; Distortion (music); Bundle; Segmentation; Streamlines, streaklines, and pathlines; Process (computing); White matter; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Biology; Physics; Neuroscience","score_opus":0.030981754218409038,"score_gpt":0.28654245570942743,"score_spread":0.2555607014910184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405975791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14564253,0.0009165541,0.83680266,0.0006048253,0.00013053174,0.00013786281,0.0014424488,0.012222801,0.0020997436],"genre_scores_gemma":[0.56964403,0.000838411,0.41591662,0.0003366977,0.00014497314,0.00023062507,0.006601032,0.0020848347,0.0042028334],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994087,0.00012371922,0.00003017712,0.00030218172,0.00009158563,0.00004360113],"domain_scores_gemma":[0.99865556,0.0005295613,0.0002245141,0.0003601774,0.00014622249,0.00008401785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016989714,0.0016972035,0.0009452457,0.001724831,0.00065578945,0.001637981,0.0012888813,0.0015234078,0.0018189792],"category_scores_gemma":[0.0067546507,0.0008821398,0.0015417961,0.001274671,0.0008768916,0.0027184428,0.0016168708,0.0021878404,0.0013369413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039950054,0.00016557676,0.008790371,0.0004409855,0.0005232963,0.0003885533,0.00041236528,0.56655186,0.027158542,0.014783066,0.012180051,0.36820582],"study_design_scores_gemma":[0.000031221152,0.000065371765,0.0014076435,0.000025612357,0.000032991713,0.00020480341,0.00003678477,0.9687377,0.006589008,0.020056421,0.0027878112,0.000024655534],"about_ca_topic_score_codex":0.009455412,"about_ca_topic_score_gemma":0.017055506,"teacher_disagreement_score":0.009455412,"about_ca_system_score_codex":0.0009522271,"about_ca_system_score_gemma":0.0020746724,"threshold_uncertainty_score":0.018800735},"labels":[],"label_agreement":null},{"id":"W4406197134","doi":"10.1002/alz.094891","title":"A harmonized, histology‐based protocol for selection of medial temporal lobe cortical subregion ranges on magnetic resonance imaging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Magnetic resonance imaging; Temporal lobe; Selection (genetic algorithm); Protocol (science); Functional magnetic resonance imaging; Artificial intelligence; Computer science; Psychology; Neuroscience; Medicine; Pathology; Radiology; Epilepsy","score_opus":0.08603957029224812,"score_gpt":0.3817699912048395,"score_spread":0.2957304209125914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406197134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11384588,0.0007922053,0.8412111,0.00034490039,0.00038151734,0.029771386,0.0012684856,0.0038999512,0.00848465],"genre_scores_gemma":[0.05412502,0.00045736437,0.9099053,0.0002833461,0.00008783062,0.02877172,0.0015174099,0.0014009638,0.003451059],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954855,0.0010900946,0.0010179274,0.0012027018,0.0008953235,0.00030833125],"domain_scores_gemma":[0.9883206,0.0013533812,0.0007127055,0.004664861,0.0045261164,0.0004224902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012978381,0.0016683287,0.0012805576,0.0033176343,0.002449198,0.001036654,0.002302751,0.0016219211,0.009724976],"category_scores_gemma":[0.0073827608,0.0019336417,0.0012925867,0.0016506889,0.0018066465,0.0011739078,0.0020624108,0.0019737592,0.0051096384],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015591108,0.00052628265,0.0037022238,0.0009639595,0.0000988929,0.0014031255,0.0015977814,0.001502656,0.92476916,0.002829843,0.004736601,0.0563104],"study_design_scores_gemma":[0.0016765239,0.008963288,0.13225827,0.0009343087,0.0007840456,0.014956447,0.0019026878,0.03562871,0.6460049,0.0061785523,0.14997229,0.0007399799],"about_ca_topic_score_codex":0.000972688,"about_ca_topic_score_gemma":0.003420067,"teacher_disagreement_score":0.012978381,"about_ca_system_score_codex":0.0006418316,"about_ca_system_score_gemma":0.0022701912,"threshold_uncertainty_score":0.06863701},"labels":[],"label_agreement":null},{"id":"W4406200478","doi":"10.1002/alz.088849","title":"Postmortem MRI signature of Hippocampal Sclerosis of Aging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Hippocampal sclerosis; Hippocampal formation; Signature (topology); Medicine; Neuroscience; Pathology; Multiple sclerosis; Psychology; Temporal lobe; Epilepsy; Psychiatry; Mathematics","score_opus":0.0671703147120653,"score_gpt":0.3370752229886436,"score_spread":0.2699049082765783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406200478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990074,0.00015399145,0.00025672454,0.0000074566983,0.0000024367296,0.0000071853856,0.00020623987,0.000014044333,0.000344677],"genre_scores_gemma":[0.9992718,0.00004608094,0.00028764494,0.00001009064,0.000005063992,0.000003854392,0.00020950734,0.0000024520955,0.0001636117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999112,0.000015588017,0.000008856588,0.000034060868,0.000016058819,0.0000142050885],"domain_scores_gemma":[0.99962485,0.00003755513,0.00015493581,0.00004716267,0.00008467361,0.000050718063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022382147,0.00021869429,0.00018023806,0.0009183327,0.0001864514,0.00019513883,0.00015178736,0.00013723395,0.0011484496],"category_scores_gemma":[0.0004522158,0.0001290599,0.00006915097,0.0003015366,0.00020607753,0.000100971134,0.00021426313,0.00012765944,0.00014449569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014240778,0.0001279715,0.79569143,0.000104263985,0.0001811618,0.0031202212,0.000607983,0.00036683638,0.18154365,0.000115639865,0.00062187813,0.016094863],"study_design_scores_gemma":[0.0000031890954,0.00009885927,0.99577373,0.0000026009334,0.0000113679425,0.0017950619,0.00006753463,0.00009795243,0.0020145283,0.000028347624,0.00010442387,0.0000024631977],"about_ca_topic_score_codex":0.0019648278,"about_ca_topic_score_gemma":0.0036710594,"teacher_disagreement_score":0.0019648278,"about_ca_system_score_codex":0.00011337753,"about_ca_system_score_gemma":0.00010053389,"threshold_uncertainty_score":0.003906727},"labels":[],"label_agreement":null},{"id":"W4406200945","doi":"10.1002/alz.093247","title":"White Matter Integrity of Age‐Related Hearing Loss and Cognitive Impairment","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Audiology; Montreal Cognitive Assessment; White matter; Psychology; Fractional anisotropy; Diffusion MRI; Cognitive decline; Superior longitudinal fasciculus; Cognition; Effects of sleep deprivation on cognitive performance; Population; Dementia; Hearing loss; Medicine; Gerontology; Magnetic resonance imaging; Psychiatry; Cognitive impairment; Disease; Internal medicine","score_opus":0.053606880687252355,"score_gpt":0.34933400448983526,"score_spread":0.2957271238025829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406200945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986858,0.0004179672,0.00008829471,0.000016401795,0.0000021454662,0.0000064346896,0.00027776795,0.00000585526,0.0004993602],"genre_scores_gemma":[0.9994721,0.000088168934,0.00009648756,0.000015018072,0.000005984074,0.000004307742,0.00012967858,0.0000015409202,0.00018685544],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998776,0.000013903418,0.000016625794,0.000042138723,0.000028360457,0.000021485605],"domain_scores_gemma":[0.9992316,0.00008533033,0.00046429882,0.000040632392,0.000094669944,0.00008341187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032337513,0.0002702544,0.0001988319,0.0014989803,0.0002207827,0.00045795742,0.00020822787,0.0002723776,0.0024520282],"category_scores_gemma":[0.0009861614,0.00010146038,0.00013716826,0.00063367625,0.0002731992,0.00027845116,0.00032622143,0.00014491392,0.00023230135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007243947,0.000094110765,0.9757401,0.00008376916,0.0002321679,0.0006367407,0.00028115875,0.0001786307,0.012030013,0.000097107426,0.00025237954,0.009649458],"study_design_scores_gemma":[0.0000017588952,0.00003486509,0.9991386,0.0000034862182,0.000014614255,0.0003229555,0.00004072882,0.00005683366,0.000285486,0.00004701478,0.000052182208,0.0000014511683],"about_ca_topic_score_codex":0.0043093488,"about_ca_topic_score_gemma":0.0044353628,"teacher_disagreement_score":0.0043093488,"about_ca_system_score_codex":0.00018944682,"about_ca_system_score_gemma":0.0001639747,"threshold_uncertainty_score":0.008568525},"labels":[],"label_agreement":null},{"id":"W4406201315","doi":"10.1002/alz.092362","title":"Post‐mortem MR imaging of tau pathology – a pilot study","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Toronto; University Health Network; Toronto Western Hospital; Parkinson's Clinic of Eastern Toronto & Movement Disorders Centre; Hospital for Sick Children; Occupational Cancer Research Centre","funders":"","keywords":"Tau pathology; Pathology; Medicine; Alzheimer's disease; Disease","score_opus":0.07115574344779192,"score_gpt":0.3641402115747239,"score_spread":0.292984468126932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99736017,0.0005379833,0.00068013265,0.000046383666,0.000027902897,0.00027918647,0.00017215144,0.000030469788,0.0008656834],"genre_scores_gemma":[0.99704945,0.00041202383,0.0009229737,0.00007350483,0.00008015076,0.00012997787,0.0005035672,0.000014140599,0.0008142826],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997559,0.00006456865,0.000025487558,0.000079687255,0.00002572649,0.00004852707],"domain_scores_gemma":[0.99893576,0.00023095234,0.00012189242,0.00023402843,0.00027516705,0.00020206187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012360705,0.0009723837,0.00048534942,0.0009031554,0.0007287314,0.0003638439,0.000434229,0.0010235796,0.002803965],"category_scores_gemma":[0.0012949045,0.00036997828,0.0004806934,0.00024129398,0.0009145801,0.00048480844,0.0005285854,0.0005591987,0.0011606556],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03420118,0.03205134,0.19229233,0.00089636183,0.0006429898,0.08674066,0.0037527427,0.0004958841,0.5931542,0.00036828913,0.0019847474,0.053419266],"study_design_scores_gemma":[0.0026091198,0.1560614,0.6889355,0.00009678149,0.0007618515,0.08704401,0.0016801542,0.0014759449,0.05237226,0.0004864843,0.008325918,0.00015049927],"about_ca_topic_score_codex":0.0010678632,"about_ca_topic_score_gemma":0.0010001751,"teacher_disagreement_score":0.002803965,"about_ca_system_score_codex":0.00025819885,"about_ca_system_score_gemma":0.00028007236,"threshold_uncertainty_score":0.009380162},"labels":[],"label_agreement":null},{"id":"W4406201399","doi":"10.1002/alz.090781","title":"Links between cognition and multivariate brain white matter differences in individuals with family history of Alzheimer's disease","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Alzheimer Society of Canada; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Multivariate statistics; White matter; Cognition; Family history; Disease; Brain size; Psychology; Multivariate analysis; White (mutation); Neuroscience; Medicine; Biology; Genetics; Internal medicine; Magnetic resonance imaging; Gene; Computer science","score_opus":0.06833019083614691,"score_gpt":0.3193577257615229,"score_spread":0.251027534925376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99950564,0.000077763136,0.0000925044,0.000022172744,0.0000020761927,0.0000012670854,0.00011870349,0.0000038205826,0.00017615664],"genre_scores_gemma":[0.99976224,0.0000204959,0.00007085252,0.0000035282658,0.0000036953627,0.000001094013,0.000077181605,0.0000011156543,0.000059786373],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997657,0.000055764755,0.000023478342,0.000085868,0.000039828574,0.00002938142],"domain_scores_gemma":[0.9988268,0.0003316793,0.0004986569,0.00011346655,0.00008088821,0.00014848051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056920596,0.00043962663,0.00026955342,0.0011477672,0.0004093403,0.000495927,0.0002190027,0.00034991282,0.002269933],"category_scores_gemma":[0.0021295059,0.0001769792,0.00039004852,0.00095187745,0.00031601213,0.00030589322,0.00040458984,0.00040827112,0.00014637223],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001354179,0.000034874614,0.99737,0.000005529728,0.00013722286,0.00008512215,0.00007923127,0.00010451,0.00039193718,0.000030086308,0.000043339078,0.0015826953],"study_design_scores_gemma":[0.0000013309,0.000029352155,0.9994388,0.0000012803255,0.000018230956,0.00013053698,0.000049691524,0.00019837296,0.00005359654,0.000054061893,0.000022858785,0.0000018417952],"about_ca_topic_score_codex":0.00530276,"about_ca_topic_score_gemma":0.005902523,"teacher_disagreement_score":0.00530276,"about_ca_system_score_codex":0.00020410582,"about_ca_system_score_gemma":0.00019582456,"threshold_uncertainty_score":0.010543764},"labels":[],"label_agreement":null},{"id":"W4406201579","doi":"10.1002/alz.085994","title":"Can neuroimaging methods help us to disentangle WMH etiology in AD?","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Diffusion MRI; Neuroimaging; Fractional anisotropy; Neuropathology; White matter; Pathology; Magnetic resonance imaging; Neuroscience; Amyloid (mycology); Ex vivo; Medicine; In vivo; Psychology; Disease; Biology; Radiology","score_opus":0.08564462893579457,"score_gpt":0.423573589266043,"score_spread":0.33792896033024844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48042363,0.34766853,0.06927533,0.065510206,0.006462981,0.00028596344,0.0056421272,0.001355093,0.023376035],"genre_scores_gemma":[0.8084561,0.08737985,0.08557728,0.0068810596,0.0055072317,0.0002697625,0.0019230462,0.00021314465,0.0037924428],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99934167,0.00025321118,0.00010194911,0.00013746516,0.00011300138,0.000052551022],"domain_scores_gemma":[0.99635136,0.0012544717,0.0007553058,0.00040639247,0.0009988872,0.00023353809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042074467,0.001413682,0.0016060736,0.0043733786,0.00040345557,0.0024059296,0.0011577581,0.001992428,0.0032375015],"category_scores_gemma":[0.010417532,0.0004518862,0.00087740645,0.0017743236,0.0011031858,0.0044261925,0.0009262489,0.0017363407,0.0016320383],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009984451,0.00045748783,0.31786916,0.0031464682,0.0015487835,0.0020386975,0.00048082572,0.00200481,0.015068397,0.0055580237,0.03653376,0.61429507],"study_design_scores_gemma":[0.00019422003,0.0012128119,0.6965414,0.008321607,0.0013380098,0.0128359,0.0035497902,0.026862128,0.008994323,0.1444856,0.09515544,0.0005087112],"about_ca_topic_score_codex":0.002012833,"about_ca_topic_score_gemma":0.0030915812,"teacher_disagreement_score":0.0043733786,"about_ca_system_score_codex":0.00042681428,"about_ca_system_score_gemma":0.00045284172,"threshold_uncertainty_score":0.022251368},"labels":[],"label_agreement":null},{"id":"W4406209725","doi":"10.1002/alz.091117","title":"Exploring heterogeneity in Motoric Cognitive Risk Syndrome using Volumetric MRI‐guided Clustering","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Cluster analysis; Cognition; Magnetic resonance imaging; Medicine; Physical medicine and rehabilitation; Psychology; Computer science; Neuroscience; Artificial intelligence; Radiology","score_opus":0.2779196360340695,"score_gpt":0.39007970819867677,"score_spread":0.11216007216460727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406209725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9573251,0.00036550863,0.03930117,0.0001354548,0.000019255083,0.00021554975,0.0017787776,0.00023044582,0.00062870834],"genre_scores_gemma":[0.9839685,0.000049696646,0.013732177,0.000023034776,0.000012246482,0.00008726958,0.0019499674,0.000032229018,0.00014487653],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980495,0.00064544444,0.00022456923,0.0006209977,0.00028728432,0.00017208338],"domain_scores_gemma":[0.99699795,0.001283725,0.0005972388,0.0004087094,0.00054118456,0.00017128923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002686467,0.00078732974,0.0008840435,0.0063944617,0.0007741835,0.0016298938,0.0011694545,0.0006636407,0.0013344181],"category_scores_gemma":[0.008004683,0.00022962905,0.0017402645,0.0028227337,0.00048530195,0.0003760169,0.0014085672,0.00047309406,0.00028339526],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009581348,0.0002608536,0.91230303,0.00026777684,0.002880009,0.0004948767,0.0012208293,0.019792927,0.009972869,0.0015905754,0.0026444066,0.04761369],"study_design_scores_gemma":[0.00010256569,0.0002771932,0.81162626,0.000100207915,0.0006204133,0.000934138,0.0016777196,0.17256191,0.0031734805,0.007365641,0.0014347136,0.00012574595],"about_ca_topic_score_codex":0.01750941,"about_ca_topic_score_gemma":0.012938242,"teacher_disagreement_score":0.01750941,"about_ca_system_score_codex":0.00088181824,"about_ca_system_score_gemma":0.0010062883,"threshold_uncertainty_score":0.034814954},"labels":[],"label_agreement":null},{"id":"W4406209861","doi":"10.1002/alz.083704","title":"Harmonization of diffusion MRI measures is crucial for white matter tract normative assessment in ADNI","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Normative; Diffusion MRI; Harmonization; White matter; Diffusion; Psychology; Medicine; Magnetic resonance imaging; Political science; Radiology; Physics; Law","score_opus":0.06404005221395062,"score_gpt":0.3724719858851196,"score_spread":0.30843193367116895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406209861","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45398512,0.0034300345,0.46811852,0.0019590792,0.00062445615,0.002822005,0.038035862,0.009490304,0.021534571],"genre_scores_gemma":[0.63062626,0.00064553885,0.2907138,0.0007185323,0.00027410974,0.0041272286,0.06556354,0.0046174238,0.0027136037],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9854292,0.0056645935,0.0020128775,0.004020067,0.0024352868,0.00043792106],"domain_scores_gemma":[0.9787128,0.0036110014,0.0019578752,0.009920472,0.0054574045,0.00034044287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023291392,0.001006111,0.001290002,0.0022580815,0.0014632862,0.0036886097,0.0019437768,0.0010607904,0.004287406],"category_scores_gemma":[0.06821879,0.00065980136,0.0009638012,0.0030838065,0.0012916194,0.0018175858,0.0031480242,0.001012062,0.004170987],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022286358,0.0005933995,0.2985383,0.0017171552,0.0025577988,0.0005566329,0.004048071,0.021150064,0.028302936,0.017867079,0.16456226,0.45787776],"study_design_scores_gemma":[0.0008334449,0.0008325592,0.55795926,0.0012142,0.0016258294,0.0034890561,0.003103956,0.0791411,0.043399952,0.066367306,0.24164595,0.00038742227],"about_ca_topic_score_codex":0.0041543655,"about_ca_topic_score_gemma":0.006853728,"teacher_disagreement_score":0.023291392,"about_ca_system_score_codex":0.0006239631,"about_ca_system_score_gemma":0.0021555638,"threshold_uncertainty_score":0.123178124},"labels":[],"label_agreement":null},{"id":"W4406222660","doi":"10.1002/alz.093795","title":"Postmortem MRI signature of Hippocampal Sclerosis of Aging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"","keywords":"Hippocampal sclerosis; Hippocampal formation; Signature (topology); Neuroscience; Multiple sclerosis; Medicine; Pathology; Psychology; Psychiatry; Temporal lobe; Mathematics","score_opus":0.0671703147120653,"score_gpt":0.3370752229886436,"score_spread":0.2699049082765783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406222660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990074,0.00015399145,0.00025672454,0.0000074566983,0.0000024367296,0.0000071853856,0.00020623987,0.000014044333,0.000344677],"genre_scores_gemma":[0.9992718,0.00004608094,0.00028764494,0.00001009064,0.000005063992,0.000003854392,0.00020950734,0.0000024520955,0.0001636117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999112,0.000015588017,0.000008856588,0.000034060868,0.000016058819,0.0000142050885],"domain_scores_gemma":[0.99962485,0.00003755513,0.00015493581,0.00004716267,0.00008467361,0.000050718063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022382147,0.00021869429,0.00018023806,0.0009183327,0.0001864514,0.00019513883,0.00015178736,0.00013723395,0.0011484496],"category_scores_gemma":[0.0004522158,0.0001290599,0.00006915097,0.0003015366,0.00020607753,0.000100971134,0.00021426313,0.00012765944,0.00014449569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014240778,0.0001279715,0.79569143,0.000104263985,0.0001811618,0.0031202212,0.000607983,0.00036683638,0.18154365,0.000115639865,0.00062187813,0.016094863],"study_design_scores_gemma":[0.0000031890954,0.00009885927,0.99577373,0.0000026009334,0.0000113679425,0.0017950619,0.00006753463,0.00009795243,0.0020145283,0.000028347624,0.00010442387,0.0000024631977],"about_ca_topic_score_codex":0.0019648278,"about_ca_topic_score_gemma":0.0036710594,"teacher_disagreement_score":0.0019648278,"about_ca_system_score_codex":0.00011337753,"about_ca_system_score_gemma":0.00010053389,"threshold_uncertainty_score":0.003906727},"labels":[],"label_agreement":null},{"id":"W4406222901","doi":"10.1002/alz.094084","title":"Exploring the effects of using multiple different cerebellar reference regions to improve tau‐PET harmonization ‐ The HEAD Study","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Standardized uptake value; Cerebellum; Nuclear medicine; Harmonization; Reference values; Context (archaeology); Psychology; Positron emission tomography; Medicine; Neuroscience; Biology; Physics; Internal medicine","score_opus":0.19257388931497577,"score_gpt":0.3687361545296678,"score_spread":0.17616226521469203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406222901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93712294,0.0027682362,0.056001067,0.0003210605,0.00011388528,0.0002857563,0.00078862975,0.0006276164,0.0019708688],"genre_scores_gemma":[0.9741364,0.0001752987,0.02406154,0.00011622792,0.000038681446,0.00020111345,0.00052355544,0.00030035683,0.00044684138],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9931142,0.0046511083,0.0003933279,0.0012062866,0.00043134278,0.00020387639],"domain_scores_gemma":[0.9849474,0.007274676,0.0019109759,0.0035685457,0.0019070434,0.00039133214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017367233,0.0009830231,0.0011098858,0.00070985744,0.0009528951,0.0017778397,0.0011800582,0.0008765646,0.002406446],"category_scores_gemma":[0.033523843,0.000530769,0.0015704017,0.0010426309,0.00074985827,0.00080515514,0.0013538587,0.0007063299,0.0005458655],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.020354364,0.0007986261,0.6267123,0.0012003322,0.015261944,0.0010220342,0.0029532576,0.024497664,0.050786406,0.0026564316,0.005059492,0.24869716],"study_design_scores_gemma":[0.001008131,0.0073863436,0.8550396,0.00026223107,0.01314739,0.0017065671,0.0012064275,0.041702166,0.057288215,0.0041889627,0.016797617,0.00026634513],"about_ca_topic_score_codex":0.006046106,"about_ca_topic_score_gemma":0.009895685,"teacher_disagreement_score":0.017367233,"about_ca_system_score_codex":0.0005625174,"about_ca_system_score_gemma":0.000928426,"threshold_uncertainty_score":0.09184778},"labels":[],"label_agreement":null},{"id":"W4406223146","doi":"10.1002/alz.094116","title":"Inflammation in the white matter relates to core Alzheimer's disease pathophysiological processes","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Translocator protein; White matter; Microglia; Astrogliosis; Neuroinflammation; Dementia; Cognitive decline; Psychology; Pathology; Medicine; Diffusion MRI; Internal medicine; Neuroscience; Magnetic resonance imaging; Inflammation; Disease; Central nervous system","score_opus":0.06938848726882091,"score_gpt":0.34645497272340453,"score_spread":0.2770664854545836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986766,0.00065815035,0.00022749927,0.000036673337,0.000004653771,0.0000039089764,0.00007006786,0.0000038446246,0.00031869166],"genre_scores_gemma":[0.9993705,0.00022346407,0.00013284797,0.000014850163,0.000015953352,0.000004374926,0.00007120741,0.0000012162039,0.00016556769],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998241,0.00004570587,0.000019933188,0.000053014024,0.000025326031,0.00003203844],"domain_scores_gemma":[0.999406,0.000095852134,0.00034132198,0.000035126766,0.00006197875,0.000059744667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051681534,0.00044199554,0.00034716306,0.00040519697,0.0002625095,0.0006068566,0.00011585326,0.0002672223,0.0013850221],"category_scores_gemma":[0.0010006074,0.0001518538,0.0002413667,0.00040068154,0.00026280398,0.00027739312,0.00025961924,0.00027130227,0.00016665104],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001900286,0.00012008098,0.962259,0.00008699571,0.0002640745,0.00035257245,0.0002723262,0.00022689956,0.026581163,0.000106634914,0.00020264622,0.0076272273],"study_design_scores_gemma":[0.000007599256,0.00017856552,0.9973335,0.00000871053,0.00006722062,0.00042788545,0.000080269536,0.00020099286,0.0013585002,0.00019130483,0.00014256593,0.0000028887955],"about_ca_topic_score_codex":0.00092637073,"about_ca_topic_score_gemma":0.0010598016,"teacher_disagreement_score":0.0013850221,"about_ca_system_score_codex":0.0001435614,"about_ca_system_score_gemma":0.00014817987,"threshold_uncertainty_score":0.0046334267},"labels":[],"label_agreement":null},{"id":"W4406223252","doi":"10.1002/alz.094000","title":"In vivo data‐driven patterns of Amyloid‐ and Tau accumulation associated with AD progression using 18F‐MK6240 and 18F‐NAV4694 PET","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Voxel; Positron emission tomography; Cognitive impairment; Standardized uptake value; Nuclear medicine; In vivo; Spatial normalization; Neuroimaging; Amyloid (mycology); Pittsburgh compound B; Grey matter; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Psychology; White matter; Radiology; Biology; Disease","score_opus":0.12560127233161428,"score_gpt":0.40887756190496066,"score_spread":0.2832762895733464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949987,0.0001474322,0.004260849,0.000010485257,0.000002334215,0.000014462507,0.0003093675,0.000050540722,0.00020587945],"genre_scores_gemma":[0.99344265,0.00009426773,0.0056200824,0.000012333697,0.0000028206234,0.000033799017,0.00049164926,0.00003070335,0.00027170306],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998165,0.000054407144,0.000011923295,0.000058765123,0.00003508039,0.00002346494],"domain_scores_gemma":[0.9997496,0.00006981826,0.00008379605,0.000035011803,0.000044584376,0.00001719294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053211517,0.00026244042,0.00033310533,0.00054626446,0.0001372045,0.0005497985,0.00022024215,0.00030781055,0.00045135623],"category_scores_gemma":[0.0010109147,0.00036976108,0.0002472383,0.00037405262,0.00025256883,0.00018829461,0.00015992869,0.00021648666,0.0001326323],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021665706,0.00015424202,0.09526942,0.00014409346,0.00023765083,0.00035861216,0.0002769663,0.0061273216,0.8683781,0.00015076315,0.00021697869,0.026519302],"study_design_scores_gemma":[0.00007112043,0.00083837315,0.7648819,0.000012656062,0.00022548526,0.0033706815,0.00016705613,0.032272544,0.19674717,0.00048796824,0.000847325,0.000077797304],"about_ca_topic_score_codex":0.0024474533,"about_ca_topic_score_gemma":0.0030697377,"teacher_disagreement_score":0.0024474533,"about_ca_system_score_codex":0.00029163712,"about_ca_system_score_gemma":0.00021608206,"threshold_uncertainty_score":0.0048663616},"labels":[],"label_agreement":null},{"id":"W4406223305","doi":"10.1002/alz.093909","title":"Links between cognition and multivariate brain white matter differences in individuals with family history of Alzheimer's disease","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Concordia University","funders":"","keywords":"White matter; Cognition; Family history; Multivariate statistics; Disease; Psychology; Brain size; Multivariate analysis; Alzheimer's disease; Developmental psychology; Neuroscience; Medicine; Internal medicine; Magnetic resonance imaging; Computer science","score_opus":0.06833019083614691,"score_gpt":0.3193577257615229,"score_spread":0.251027534925376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995048,0.00007550796,0.00009667282,0.000020247808,0.0000020096895,0.0000012087605,0.00012106527,0.0000039056013,0.00017457105],"genre_scores_gemma":[0.9997695,0.000018871639,0.000069808855,0.0000034624213,0.0000034204058,0.0000010559577,0.00007548094,0.0000011183896,0.000057151232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99978906,0.00004957959,0.00002087525,0.00007924277,0.00003417155,0.000027012622],"domain_scores_gemma":[0.99895966,0.00029729455,0.00043108588,0.000106296095,0.00007237932,0.00013329415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005285736,0.00041832944,0.00025919284,0.0011122222,0.00039099093,0.00046094914,0.00020312384,0.0003318109,0.0022277536],"category_scores_gemma":[0.0018941172,0.00016682941,0.0003736932,0.0009134758,0.00029369324,0.00028009212,0.00036701266,0.0003815646,0.00014167198],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001445813,0.000033446086,0.9972568,0.000005357174,0.00013873055,0.000086872926,0.00007224527,0.0001045386,0.0004465025,0.00002999114,0.000042831587,0.0016381224],"study_design_scores_gemma":[0.0000013574254,0.00002864169,0.99943894,0.0000011696584,0.00001837244,0.00013264146,0.000044632154,0.00019893546,0.00005708479,0.00005286539,0.000023415625,0.0000017457304],"about_ca_topic_score_codex":0.0050647776,"about_ca_topic_score_gemma":0.005623038,"teacher_disagreement_score":0.0050647776,"about_ca_system_score_codex":0.00018979267,"about_ca_system_score_gemma":0.00018089404,"threshold_uncertainty_score":0.010070622},"labels":[],"label_agreement":null},{"id":"W4406239147","doi":"10.1101/2025.01.07.631402","title":"EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Polytechnique Montréal; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Segmentation; Computer science; Artificial intelligence; Ghosting; Spinal cord; Computer vision; Functional magnetic resonance imaging; Ground truth; Preprocessor; Pattern recognition (psychology); Medicine; Neuroscience; Psychology; Radiology","score_opus":0.19308266940326882,"score_gpt":0.4375408830752436,"score_spread":0.24445821367197476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406239147","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.076434664,0.0035981322,0.6679719,0.0013342539,0.0006332592,0.0011487727,0.11297997,0.13207372,0.0038252892],"genre_scores_gemma":[0.16538413,0.0020530021,0.59975386,0.0011011405,0.00016888404,0.0016652972,0.21170872,0.010538617,0.007626341],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948883,0.00008110278,0.00003897099,0.00024049928,0.00009565716,0.000054935896],"domain_scores_gemma":[0.9994605,0.00018037167,0.00006755621,0.00013519551,0.00010675667,0.0000496174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001274123,0.0021373883,0.001100893,0.0019400673,0.0006057113,0.0015648052,0.0029453544,0.0018875162,0.005326116],"category_scores_gemma":[0.003871553,0.0009906141,0.0019716686,0.0011858246,0.00046789547,0.0010884518,0.0020608814,0.0016563209,0.0041548624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022190993,0.0006286926,0.012003857,0.0027183867,0.002151506,0.0012223463,0.0005213738,0.14975289,0.049685918,0.005204416,0.30633888,0.46755266],"study_design_scores_gemma":[0.00050010905,0.0005013146,0.012864717,0.00046951114,0.00049781287,0.0022490576,0.0001521737,0.8068794,0.0685271,0.019713068,0.08738072,0.00026500842],"about_ca_topic_score_codex":0.012384356,"about_ca_topic_score_gemma":0.036040705,"teacher_disagreement_score":0.012384356,"about_ca_system_score_codex":0.001051067,"about_ca_system_score_gemma":0.0023059247,"threshold_uncertainty_score":0.024624527},"labels":[],"label_agreement":null},{"id":"W4406249842","doi":"10.1016/b978-0-12-818894-1.00035-5","title":"From diffusion models to fiber orientations","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion; Fiber; Materials science; Physics; Composite material; Thermodynamics","score_opus":0.057286745752930045,"score_gpt":0.3337178140014015,"score_spread":0.27643106824847147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249842","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012385119,0.027438078,0.79826015,0.002964113,0.0021215908,0.000024535866,0.0007928675,0.0024840138,0.16467614],"genre_scores_gemma":[0.03939712,0.080660135,0.32367912,0.0010900699,0.0021891224,0.00014145291,0.0021388407,0.002132038,0.5485722],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99989295,0.000017957169,0.0000059519934,0.000030055628,0.000047881767,0.00000514723],"domain_scores_gemma":[0.9997404,0.0001297859,0.0000144272035,0.000043197262,0.000057133984,0.000015116062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034815224,0.0014669284,0.00079186156,0.0012968916,0.00030733523,0.0020452586,0.0008685486,0.0015399313,0.028491613],"category_scores_gemma":[0.0010791195,0.0008371147,0.0006382442,0.0016725129,0.0008163933,0.003281626,0.0009987069,0.0019609148,0.017925158],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011054841,0.000018717265,0.00009564928,0.0003203381,0.00002817912,0.00011314458,0.000094640476,0.021261074,0.0018181667,0.49992228,0.13806733,0.33824936],"study_design_scores_gemma":[0.000004632076,0.000009706217,0.00014222093,0.00017229146,0.00001391743,0.00023594162,0.00003448515,0.0391097,0.0008856832,0.64962906,0.30973393,0.000028407672],"about_ca_topic_score_codex":0.002789178,"about_ca_topic_score_gemma":0.0032298798,"teacher_disagreement_score":0.028491613,"about_ca_system_score_codex":0.00082051946,"about_ca_system_score_gemma":0.00063293416,"threshold_uncertainty_score":0.095313966},"labels":[],"label_agreement":null},{"id":"W4406249847","doi":"10.1016/b978-0-12-818894-1.00032-x","title":"Machine learning in tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Université de Sherbrooke","funders":"","keywords":"Tractography; Neuroscience; Psychology; Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.03499768014462313,"score_gpt":0.31553050630763796,"score_spread":0.28053282616301484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249847","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001264639,0.09973466,0.43535596,0.00414743,0.004734039,0.00007267826,0.0010054668,0.0036655678,0.45001948],"genre_scores_gemma":[0.01028894,0.058490887,0.11406359,0.0010884524,0.0031120616,0.00015152757,0.001056258,0.0015560456,0.81019217],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997402,0.000048582333,0.000016145712,0.00005798148,0.00012446438,0.000012773821],"domain_scores_gemma":[0.99928826,0.00044263393,0.000030576302,0.00010700285,0.00009794499,0.0000335612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050752965,0.0014272594,0.0013320709,0.0021764569,0.0004146083,0.0026055127,0.00078754994,0.0017045934,0.07459288],"category_scores_gemma":[0.0015418526,0.00081160176,0.0005922322,0.0030721275,0.0009807864,0.003185521,0.0013907977,0.0024399953,0.054546162],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011132109,0.000028398706,0.00011189421,0.00053652696,0.000028289964,0.000087636756,0.00009772466,0.004593386,0.0012036737,0.09507529,0.23580375,0.66242236],"study_design_scores_gemma":[0.000005923588,0.000022042705,0.00043822042,0.00044544795,0.00001742129,0.00044440196,0.000040579947,0.009968254,0.00079244305,0.16035175,0.8274475,0.000026118008],"about_ca_topic_score_codex":0.001274929,"about_ca_topic_score_gemma":0.0029057348,"teacher_disagreement_score":0.07459288,"about_ca_system_score_codex":0.0007134101,"about_ca_system_score_gemma":0.0005971817,"threshold_uncertainty_score":0.24953806},"labels":[],"label_agreement":null},{"id":"W4406249850","doi":"10.1016/b978-0-12-818894-1.00037-9","title":"Current challenges and opportunities for tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Université de Sherbrooke","funders":"","keywords":"Tractography; Current (fluid); Psychology; Geology; Medicine; Diffusion MRI; Oceanography; Radiology; Magnetic resonance imaging","score_opus":0.18447455694137602,"score_gpt":0.3614914835877903,"score_spread":0.1770169266464143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249850","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013523289,0.50437254,0.19980234,0.04115246,0.013978679,0.0000735497,0.00064030814,0.0028875035,0.23574033],"genre_scores_gemma":[0.012122029,0.51008356,0.20799604,0.0051093893,0.010707049,0.00016651084,0.00075277436,0.0014657741,0.2515968],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995765,0.00013375044,0.000032313386,0.000060208706,0.0001651506,0.000032094013],"domain_scores_gemma":[0.9965155,0.0024227614,0.000073587966,0.0002239548,0.0005291658,0.00023515408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024183425,0.001017537,0.0010060957,0.002607289,0.00066513225,0.005737328,0.001618146,0.0026854377,0.06131682],"category_scores_gemma":[0.0040528653,0.0006197651,0.00070893974,0.0028519076,0.0028686095,0.007087514,0.0017971984,0.0034073747,0.02405044],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034151937,0.000028077347,0.00015623367,0.00095968135,0.000022042243,0.0001950226,0.00016681787,0.0016881849,0.0012010268,0.17338552,0.20935583,0.61280745],"study_design_scores_gemma":[0.0000067018377,0.000023946523,0.00016182622,0.00058718416,0.000009754522,0.0006332433,0.000112097594,0.002100821,0.00034473426,0.17993222,0.816062,0.000025595593],"about_ca_topic_score_codex":0.002930862,"about_ca_topic_score_gemma":0.0065530087,"teacher_disagreement_score":0.06131682,"about_ca_system_score_codex":0.0014024376,"about_ca_system_score_gemma":0.0027119801,"threshold_uncertainty_score":0.20512521},"labels":[],"label_agreement":null},{"id":"W4406249897","doi":"10.1016/b978-0-12-818894-1.00026-4","title":"Diffusion MRI acquisition for tractography: Beyond the in vivo adult human brain","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Human brain; Neuroscience; Psychology; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.023900918092789932,"score_gpt":0.32082866794688786,"score_spread":0.2969277498540979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249897","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023460882,0.15710147,0.6546489,0.0065701264,0.0024944441,0.00009518636,0.0008253959,0.0029609941,0.17295738],"genre_scores_gemma":[0.023721172,0.23677,0.46902072,0.0024084907,0.0027051645,0.0001708045,0.0008374979,0.0021671983,0.26219904],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99985325,0.0000325496,0.000011629494,0.000037311325,0.00005812923,0.0000069930347],"domain_scores_gemma":[0.99916315,0.00057761994,0.000024433453,0.000090601134,0.00010119748,0.00004298199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007213304,0.0009131112,0.0006246322,0.00087211945,0.00022041461,0.002232746,0.0009374512,0.0016757087,0.03452784],"category_scores_gemma":[0.001132427,0.0006293074,0.0003289027,0.0010096182,0.0011568653,0.002759186,0.00087202067,0.0019159465,0.015497376],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005608589,0.000032148222,0.00018713404,0.0012429875,0.00003493982,0.00030257337,0.00024139282,0.002013346,0.023166377,0.093870185,0.10900832,0.7698446],"study_design_scores_gemma":[0.00000933759,0.00006658651,0.00081188005,0.00056617527,0.000025140067,0.002755466,0.000092066824,0.004238765,0.006634099,0.088450916,0.8963084,0.00004114661],"about_ca_topic_score_codex":0.0010869245,"about_ca_topic_score_gemma":0.002244813,"teacher_disagreement_score":0.03452784,"about_ca_system_score_codex":0.0004365318,"about_ca_system_score_gemma":0.00065413245,"threshold_uncertainty_score":0.115507126},"labels":[],"label_agreement":null},{"id":"W4406249912","doi":"10.1016/b978-0-12-818894-1.00010-0","title":"Single-shell diffusion models: From DTI to HARDI","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Diffusion; Shell (structure); Neuroscience; Psychology; Materials science; Physics; Medicine; Magnetic resonance imaging","score_opus":0.08899307441662753,"score_gpt":0.3175447907616004,"score_spread":0.2285517163449729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249912","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018240446,0.046901263,0.9009149,0.0030981812,0.0009769255,0.000034576864,0.0010099168,0.0019862833,0.043253835],"genre_scores_gemma":[0.070463546,0.09388006,0.7146952,0.0013648106,0.002074782,0.00020669287,0.0020695836,0.0024859824,0.11275942],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999871,0.00002945831,0.00000986216,0.0000378442,0.00004337758,0.000008433591],"domain_scores_gemma":[0.99932754,0.00036888348,0.00003919925,0.00010897512,0.00010910676,0.00004630466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007360143,0.0013309086,0.0012268539,0.00093631,0.00028652334,0.002636832,0.001595192,0.0019480332,0.01237269],"category_scores_gemma":[0.0021247326,0.0009946986,0.0007723899,0.0016851423,0.0010500887,0.002942618,0.0010826838,0.0025647508,0.008641964],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004611086,0.00004185345,0.00027602268,0.00083081727,0.00008073006,0.00021118189,0.00013543718,0.06673029,0.0042262413,0.40827456,0.10342377,0.41572294],"study_design_scores_gemma":[0.000009772725,0.000027579084,0.00037526924,0.00022081021,0.00002900463,0.0004922633,0.000040926887,0.21758772,0.0020601838,0.6305263,0.1485677,0.000062541054],"about_ca_topic_score_codex":0.0025695735,"about_ca_topic_score_gemma":0.0027210708,"teacher_disagreement_score":0.01237269,"about_ca_system_score_codex":0.0008396607,"about_ca_system_score_gemma":0.00083094725,"threshold_uncertainty_score":0.041390836},"labels":[],"label_agreement":null},{"id":"W4406249945","doi":"10.1016/b978-0-12-818894-1.00001-x","title":"Diffusion MRI acquisition for tractography: Diffusion encoding","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Diffusion; Encoding (memory); Computer science; Neuroscience; Psychology; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.04062800354253887,"score_gpt":0.3271607197921676,"score_spread":0.2865327162496287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249945","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009971252,0.04128468,0.8612932,0.0020155462,0.0016964992,0.00011693616,0.0013751804,0.0069562667,0.08426453],"genre_scores_gemma":[0.010848887,0.047234774,0.78314656,0.00092389516,0.0012126671,0.00021493612,0.0016374558,0.004135524,0.1506453],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997161,0.000048524813,0.000028157758,0.00008540755,0.00010798265,0.000013830151],"domain_scores_gemma":[0.9992005,0.0004613655,0.00003818183,0.00011192178,0.0001464909,0.000041429983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082106306,0.0017093119,0.00090940297,0.0014523248,0.00037371455,0.002922024,0.0012211511,0.0024702298,0.08275524],"category_scores_gemma":[0.002003423,0.0011376359,0.00060846435,0.0021559792,0.0008424585,0.0025698852,0.0010790346,0.00237315,0.06742924],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054093965,0.000023550954,0.00010557222,0.0010153662,0.000033725082,0.000253756,0.00010441771,0.0029411896,0.015409946,0.039262958,0.14696479,0.7938306],"study_design_scores_gemma":[0.000024429812,0.00007039091,0.0009133008,0.0007150251,0.000046454123,0.0036306395,0.0000804213,0.01706033,0.014573233,0.084911905,0.8778775,0.00009647261],"about_ca_topic_score_codex":0.001370189,"about_ca_topic_score_gemma":0.002547411,"teacher_disagreement_score":0.08275524,"about_ca_system_score_codex":0.0005494085,"about_ca_system_score_gemma":0.0008069993,"threshold_uncertainty_score":0.27684385},"labels":[],"label_agreement":null},{"id":"W4406249946","doi":"10.1016/b978-0-12-818894-1.00029-x","title":"Deterministic fiber tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Fiber; Computer science; Materials science; Medicine; Diffusion MRI; Radiology; Composite material; Magnetic resonance imaging","score_opus":0.043032978637481095,"score_gpt":0.3283351373224557,"score_spread":0.28530215868497455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249946","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014445728,0.010483851,0.63519776,0.00086020835,0.00095095776,0.000032385902,0.0006151127,0.004035647,0.34637955],"genre_scores_gemma":[0.022847896,0.013341188,0.17778555,0.0002713251,0.0005323201,0.00007010424,0.001030411,0.0013428306,0.7827783],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988747,0.000010835734,0.000004855292,0.00003707491,0.00005363057,0.0000061012943],"domain_scores_gemma":[0.99981767,0.00007129255,0.0000095466,0.00004866002,0.000039590617,0.000013344624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020139072,0.0009468051,0.0006372845,0.0009099129,0.00037076374,0.0017231988,0.000590263,0.0011200508,0.08198616],"category_scores_gemma":[0.00057613436,0.0005947483,0.0003851477,0.0010126049,0.0006184298,0.0014060737,0.0011189124,0.0011841931,0.056096863],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019635796,0.000018325942,0.00017166257,0.00024271136,0.000024183832,0.00015529334,0.00008147229,0.0124690235,0.0064094258,0.13407291,0.11822684,0.7281085],"study_design_scores_gemma":[0.0000062319564,0.000018552793,0.00051084603,0.0001732076,0.000018308077,0.0007228539,0.000034241133,0.034121808,0.0039173826,0.1733652,0.78707886,0.000032364856],"about_ca_topic_score_codex":0.00163009,"about_ca_topic_score_gemma":0.0034999312,"teacher_disagreement_score":0.08198616,"about_ca_system_score_codex":0.00050472596,"about_ca_system_score_gemma":0.0005654449,"threshold_uncertainty_score":0.274271},"labels":[],"label_agreement":null},{"id":"W4406249967","doi":"10.1016/b978-0-12-818894-1.00020-3","title":"Tractography validation Part 2: The use of anatomical model systems and measures for validation","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Model validation; Computer science; Data science; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.1431679597984093,"score_gpt":0.3398599600333243,"score_spread":0.196692000234915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249967","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001554079,0.007867675,0.98211277,0.0008922525,0.0005629279,0.000066476765,0.00024972632,0.00089000503,0.005804016],"genre_scores_gemma":[0.053439297,0.015069107,0.902718,0.00072595937,0.0014775944,0.0004482784,0.0013838023,0.0038713715,0.020866621],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941843,0.0027836887,0.00050815864,0.0009020798,0.0015255689,0.00009614832],"domain_scores_gemma":[0.96992254,0.02226224,0.0010915373,0.0034835117,0.0030621684,0.00017803231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013247278,0.0021282954,0.0020032246,0.003651454,0.000619922,0.0051959916,0.0018576547,0.00298553,0.009948528],"category_scores_gemma":[0.046724,0.0015550879,0.0019336491,0.0029903853,0.004229346,0.0058234427,0.0021552427,0.0038289898,0.0056867236],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009523724,0.000061714265,0.001986103,0.001344354,0.00033566105,0.00017705081,0.0003770401,0.054143667,0.007340229,0.14986931,0.029907402,0.7543622],"study_design_scores_gemma":[0.000030863688,0.0002983983,0.006755324,0.0017264453,0.00023015605,0.0017485203,0.00015330249,0.3473237,0.022805255,0.4996937,0.11897926,0.00025517386],"about_ca_topic_score_codex":0.0024423376,"about_ca_topic_score_gemma":0.0016632243,"teacher_disagreement_score":0.013247278,"about_ca_system_score_codex":0.0014757027,"about_ca_system_score_gemma":0.0020451897,"threshold_uncertainty_score":0.07005918},"labels":[],"label_agreement":null},{"id":"W4406249969","doi":"10.1016/b978-0-12-818894-1.00027-6","title":"Linking behavior with white matter networks","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"White (mutation); White matter; Biology; Medicine","score_opus":0.028053720992555067,"score_gpt":0.29923250529536083,"score_spread":0.2711787843028058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249969","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062278085,0.014658997,0.25401184,0.0057904394,0.0014940896,0.000041457137,0.0013532965,0.0023957265,0.71402633],"genre_scores_gemma":[0.045567974,0.026669517,0.111974165,0.0012293231,0.0012969493,0.000109748136,0.001651352,0.0007655991,0.8107354],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999943,0.000008722483,0.0000024420888,0.000021980328,0.000020795182,0.000003100591],"domain_scores_gemma":[0.9997968,0.00013039334,0.000013856247,0.000025388115,0.000021243255,0.000012332465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018699905,0.0006647982,0.0002834166,0.00094458356,0.0002718784,0.0017731418,0.00044120877,0.0007687836,0.06138812],"category_scores_gemma":[0.00076380384,0.00031441756,0.00035983697,0.0012567982,0.00045612437,0.0021918546,0.00069791806,0.0009457231,0.01670609],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014127646,0.00003070122,0.00065868354,0.00022146068,0.0000433669,0.00021213277,0.00018534718,0.007872307,0.0031774903,0.32629415,0.112185344,0.5491049],"study_design_scores_gemma":[0.000003796162,0.000015573914,0.0017194503,0.00021821355,0.000022518248,0.0004073781,0.0000734649,0.0107635,0.0012274467,0.62669826,0.35883126,0.00001916516],"about_ca_topic_score_codex":0.0013280691,"about_ca_topic_score_gemma":0.0024398165,"teacher_disagreement_score":0.06138812,"about_ca_system_score_codex":0.00045950097,"about_ca_system_score_gemma":0.0003212595,"threshold_uncertainty_score":0.20536369},"labels":[],"label_agreement":null},{"id":"W4406249987","doi":"10.1016/b978-0-12-818894-1.00023-9","title":"Methods and statistics for diffusion MRI tractometry","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Diffusion; Diffusion MRI; Statistics; Statistical physics; Computer science; Mathematics; Physics; Medicine; Magnetic resonance imaging; Radiology; Thermodynamics","score_opus":0.05563087874895355,"score_gpt":0.41417792358470623,"score_spread":0.35854704483575267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249987","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002577197,0.011084101,0.97434765,0.0007364116,0.0011230424,0.000027707527,0.0005931712,0.0017986305,0.010031515],"genre_scores_gemma":[0.006001146,0.020940695,0.9061578,0.0007335094,0.002697149,0.00043202296,0.0017707737,0.0027235826,0.058543302],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99857175,0.00046593352,0.00016652838,0.00024650505,0.0005112684,0.00003797676],"domain_scores_gemma":[0.9954934,0.0030040143,0.00016400391,0.0006731824,0.00060499465,0.000060390194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024222247,0.0023693172,0.0017469134,0.0025123428,0.00046987814,0.0027251705,0.0016956055,0.002382177,0.028176447],"category_scores_gemma":[0.009305322,0.0012013436,0.0012961371,0.003879299,0.0016428751,0.0032556292,0.0014358083,0.004103942,0.032808755],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027709117,0.000041618056,0.0002971931,0.0010516463,0.00008588236,0.00016673343,0.0001595508,0.013045718,0.002543959,0.24020708,0.17799664,0.56437624],"study_design_scores_gemma":[0.000016975751,0.000038637867,0.0012082916,0.00054478226,0.0000663499,0.0008665927,0.00006838957,0.06947688,0.0024745774,0.515542,0.4096023,0.000094239374],"about_ca_topic_score_codex":0.0020815213,"about_ca_topic_score_gemma":0.002783056,"teacher_disagreement_score":0.028176447,"about_ca_system_score_codex":0.00078377366,"about_ca_system_score_gemma":0.0012013871,"threshold_uncertainty_score":0.09425962},"labels":[],"label_agreement":null},{"id":"W4406250042","doi":"10.1016/b978-0-12-818894-1.00030-6","title":"Probabilistic tractography","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Probabilistic logic; Psychology; Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.05037777134875867,"score_gpt":0.32734000110396644,"score_spread":0.2769622297552078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250042","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010605459,0.010784112,0.7176188,0.0011217563,0.00078847434,0.00004191649,0.0010793906,0.0070019867,0.26050302],"genre_scores_gemma":[0.021272127,0.017728433,0.28793123,0.00043083564,0.0008431999,0.00012894634,0.0028749024,0.0031409701,0.66564935],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998147,0.000024183608,0.0000085389365,0.00006222903,0.0000802082,0.000010077882],"domain_scores_gemma":[0.99965215,0.00014213394,0.000016988304,0.00009441048,0.00007143611,0.000022859085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042114334,0.0012736971,0.0008422008,0.0017249755,0.0004336435,0.002466232,0.0008375224,0.0014584924,0.114190556],"category_scores_gemma":[0.0012902054,0.0007948989,0.00071207236,0.0016674799,0.00077177404,0.0022108026,0.0013377386,0.0014097885,0.0958863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015973086,0.000014705249,0.00013793628,0.00021660456,0.00003077804,0.00011870026,0.00006720619,0.007135004,0.0033697928,0.081486054,0.15264109,0.75476617],"study_design_scores_gemma":[0.000006919198,0.000023671746,0.00067170506,0.00021300143,0.000026897173,0.0010700946,0.000033830947,0.025747705,0.0031002893,0.17667976,0.7923862,0.000040052062],"about_ca_topic_score_codex":0.0023166444,"about_ca_topic_score_gemma":0.0037931204,"teacher_disagreement_score":0.114190556,"about_ca_system_score_codex":0.00053893944,"about_ca_system_score_gemma":0.0006662428,"threshold_uncertainty_score":0.38200545},"labels":[],"label_agreement":null},{"id":"W4406250051","doi":"10.1016/b978-0-12-818894-1.00019-7","title":"Diffusion MRI acquisition for tractography: Diffusion sequences","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Diffusion; Diffusion imaging; Computer science; Medicine; Radiology; Physics; Magnetic resonance imaging","score_opus":0.040346980600094215,"score_gpt":0.33013603123248936,"score_spread":0.28978905063239513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250051","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011986012,0.060194727,0.791873,0.002468552,0.002377933,0.00016300526,0.0022286065,0.011655506,0.12784009],"genre_scores_gemma":[0.00875533,0.060977973,0.6726506,0.0012333631,0.0015790985,0.0002786307,0.002580332,0.006236159,0.24570853],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996495,0.000053013464,0.000036498604,0.00009941039,0.00014555106,0.000016020354],"domain_scores_gemma":[0.9989723,0.0005847132,0.00004592474,0.00013377302,0.00020391977,0.000059415954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009178887,0.0021203535,0.0011945036,0.0020940537,0.0003969385,0.0030401237,0.001468363,0.00275738,0.12551175],"category_scores_gemma":[0.0023427256,0.0012813824,0.0006593585,0.0025279676,0.00088880624,0.0030080045,0.001215858,0.002557487,0.11648905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049365048,0.000028717313,0.000101588754,0.0010246566,0.000028157147,0.00025175873,0.000093575,0.0020438689,0.010936625,0.02407669,0.20918751,0.75217754],"study_design_scores_gemma":[0.00001940346,0.00006354073,0.00085074105,0.000660549,0.00003404449,0.0037955462,0.00006396065,0.007981546,0.008653122,0.048756216,0.9290465,0.00007469811],"about_ca_topic_score_codex":0.0015501207,"about_ca_topic_score_gemma":0.0032010863,"teacher_disagreement_score":0.12551175,"about_ca_system_score_codex":0.0005477904,"about_ca_system_score_gemma":0.0008649423,"threshold_uncertainty_score":0.41987866},"labels":[],"label_agreement":null},{"id":"W4406250086","doi":"10.1016/b978-0-12-818894-1.00036-7","title":"Tractography in pathological anatomy: Some general considerations","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Pathological anatomy; Pathological; Anatomy; Medicine; Pathology; Radiology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.051792435581865574,"score_gpt":0.3435095831315025,"score_spread":0.2917171475496369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250086","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019762085,0.50733256,0.27301234,0.022590233,0.0090725785,0.00012869334,0.0003861349,0.00073502643,0.18476626],"genre_scores_gemma":[0.025623986,0.52653986,0.20240086,0.012143844,0.026824035,0.00059281534,0.0006005261,0.00093531754,0.20433873],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99948114,0.00021021078,0.000055778077,0.000091755144,0.00012777303,0.000033392866],"domain_scores_gemma":[0.9984629,0.0011066714,0.00004824232,0.00009039597,0.00021557232,0.00007627321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026277332,0.0018154079,0.0016255954,0.0034816535,0.0008241943,0.0035675091,0.0022463056,0.0049309004,0.012653143],"category_scores_gemma":[0.002450798,0.0007877418,0.00095054065,0.0030716835,0.005432199,0.0054873773,0.0016819222,0.0049457233,0.008471133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058071848,0.00010796177,0.00047032617,0.0018452284,0.00007902073,0.0018479377,0.0004951928,0.0047088107,0.002182411,0.5048846,0.1397711,0.34354937],"study_design_scores_gemma":[0.000012578966,0.00009421107,0.0010664497,0.0011897555,0.000037888476,0.004831889,0.00020616884,0.0028197377,0.0006606712,0.46910307,0.5199051,0.00007244102],"about_ca_topic_score_codex":0.0023681216,"about_ca_topic_score_gemma":0.0058274274,"teacher_disagreement_score":0.012653143,"about_ca_system_score_codex":0.0015371412,"about_ca_system_score_gemma":0.0011932907,"threshold_uncertainty_score":0.042328954},"labels":[],"label_agreement":null},{"id":"W4406250100","doi":"10.1016/b978-0-12-818894-1.00004-5","title":"Tractography validation part 3: Lessons learned through validation studies","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Psychology; Computer science; Neuroscience; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.20737022110032607,"score_gpt":0.4248103367021694,"score_spread":0.21744011560184331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250100","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0042710574,0.012064162,0.9682791,0.0052202563,0.001033284,0.00016617602,0.0003966821,0.0012776876,0.007291534],"genre_scores_gemma":[0.095285065,0.014165293,0.86006707,0.0027406674,0.0024935529,0.00045478015,0.002280369,0.0044614407,0.018051803],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98068136,0.013011401,0.0013280554,0.0018542111,0.0028534918,0.0002715034],"domain_scores_gemma":[0.7470524,0.18141611,0.0037028636,0.030800628,0.035709478,0.0013184822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.066980645,0.0031959827,0.0033720601,0.0025654668,0.0011724595,0.0059031365,0.005040191,0.0046992353,0.011596957],"category_scores_gemma":[0.22881773,0.001652708,0.0020985513,0.0020401196,0.0046729627,0.009202881,0.0036307322,0.006883856,0.0057490794],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039297642,0.00023114863,0.00526518,0.0014661053,0.0007298345,0.00047300535,0.0008897744,0.037749536,0.0039682835,0.050465625,0.05234115,0.8460273],"study_design_scores_gemma":[0.00022570639,0.00070732745,0.0077129626,0.006180479,0.00076020457,0.0025349362,0.0007091714,0.25225246,0.03096174,0.54457486,0.15300521,0.00037493114],"about_ca_topic_score_codex":0.007923021,"about_ca_topic_score_gemma":0.0067009176,"teacher_disagreement_score":0.066980645,"about_ca_system_score_codex":0.0019447597,"about_ca_system_score_gemma":0.0043865475,"threshold_uncertainty_score":0.35423172},"labels":[],"label_agreement":null},{"id":"W4406250106","doi":"10.1016/b978-0-12-818894-1.00017-3","title":"Tractography validation Part 1: Foundations, numerical simulations, and phantom models","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Imaging phantom; Tractography; Computer science; Nuclear medicine; Medicine; Radiology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.06992056873028775,"score_gpt":0.3455646180430042,"score_spread":0.27564404931271647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250106","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017589884,0.0028732189,0.97944814,0.00063745654,0.00016738579,0.000044853514,0.0003103162,0.000698376,0.014061295],"genre_scores_gemma":[0.11513559,0.013561008,0.81249475,0.00043279788,0.00053483783,0.00039719138,0.0017203973,0.002922839,0.0528006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994568,0.00018895835,0.000037220172,0.000084135565,0.00020579046,0.00002710083],"domain_scores_gemma":[0.99790907,0.0013345253,0.0001281101,0.0002639581,0.00032548062,0.000038915703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012721767,0.0012226752,0.0010073982,0.001055198,0.00046133643,0.002372281,0.0012340683,0.0017733275,0.015360544],"category_scores_gemma":[0.0076655876,0.00099636,0.0009054267,0.0012140505,0.0015384832,0.002503056,0.0012306214,0.001778715,0.005992068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060733564,0.00007015923,0.0008255575,0.00071186613,0.00006958279,0.00026246422,0.00023559248,0.47465107,0.011186852,0.25327763,0.03347701,0.2251715],"study_design_scores_gemma":[0.00000853219,0.0000440986,0.00057935354,0.00028871282,0.000027727468,0.00042776536,0.00003658686,0.79891115,0.006148406,0.15382397,0.03966075,0.000042920412],"about_ca_topic_score_codex":0.0036978356,"about_ca_topic_score_gemma":0.0028125031,"teacher_disagreement_score":0.015360544,"about_ca_system_score_codex":0.0009747275,"about_ca_system_score_gemma":0.0012715663,"threshold_uncertainty_score":0.051386118},"labels":[],"label_agreement":null},{"id":"W4406250126","doi":"10.1016/b978-0-12-818894-1.09994-8","title":"Spherical harmonics","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Zonal spherical harmonics; Spin-weighted spherical harmonics; Spherical harmonics; Harmonics; Physics; Vector spherical harmonics","score_opus":0.06095962306599624,"score_gpt":0.3380871245711569,"score_spread":0.2771275015051607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250126","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010887481,0.015363505,0.14371814,0.00085233187,0.0022120767,0.0000415193,0.0008527234,0.0020045931,0.83386636],"genre_scores_gemma":[0.0114615355,0.009208364,0.033923086,0.00021246877,0.0007637413,0.000054433647,0.0011471859,0.0008899032,0.94233924],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99975425,0.000025310645,0.000011029239,0.000048870475,0.00014757086,0.000012957875],"domain_scores_gemma":[0.9997532,0.000051727893,0.0000116615565,0.00007431425,0.000087187036,0.000021916507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027512352,0.001261056,0.00089360867,0.0017227074,0.00054305594,0.0024759362,0.00076765736,0.0009809489,0.12352505],"category_scores_gemma":[0.00082355447,0.00049365935,0.00047765506,0.0021081816,0.0006980454,0.0020231265,0.0014122154,0.0016176177,0.09329992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020488988,0.000013774652,0.00006890605,0.00021017232,0.000013669282,0.00007706549,0.00012997036,0.0019218067,0.0031665314,0.17260769,0.21108238,0.61068755],"study_design_scores_gemma":[0.0000047448857,0.000017290717,0.00028912752,0.000083902756,0.000009125202,0.0004192162,0.000058648347,0.003877161,0.0019439714,0.05554122,0.9377382,0.000017431414],"about_ca_topic_score_codex":0.001786119,"about_ca_topic_score_gemma":0.0021355697,"teacher_disagreement_score":0.12352505,"about_ca_system_score_codex":0.0005341481,"about_ca_system_score_gemma":0.0005022762,"threshold_uncertainty_score":0.41323245},"labels":[],"label_agreement":null},{"id":"W4406250132","doi":"10.1016/b978-0-12-818894-1.00002-1","title":"Tractography visualization","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Visualization; Neuroscience; Psychology; Computer science; Medicine; Artificial intelligence; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.042214420144186665,"score_gpt":0.34683259649290554,"score_spread":0.3046181763487189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250132","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012332285,0.0047023646,0.5557964,0.0006916519,0.00080765336,0.000071019254,0.002233065,0.026229022,0.4082355],"genre_scores_gemma":[0.010939288,0.0076644956,0.22256123,0.00034759895,0.0003959938,0.00013991476,0.0040449053,0.008547199,0.74535936],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998016,0.000021920243,0.000011914715,0.000053693155,0.000096786775,0.00001414956],"domain_scores_gemma":[0.99963534,0.00013308266,0.000013690829,0.00010580931,0.00007845612,0.00003360418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031005545,0.0015344584,0.0008331791,0.0020576448,0.00056224887,0.0035628695,0.000973012,0.0012379468,0.27625856],"category_scores_gemma":[0.0011849259,0.00095728063,0.000905105,0.0022036508,0.000573849,0.0022544242,0.0019547038,0.0016149168,0.1597347],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022456967,0.000017949133,0.0001380241,0.0002795945,0.000024581848,0.00023121103,0.00015093318,0.0031820561,0.007388912,0.03836695,0.28112096,0.6690764],"study_design_scores_gemma":[0.000009583361,0.000016695169,0.0005221212,0.00023435237,0.000018135055,0.001048629,0.000060810118,0.011365422,0.004149068,0.057493873,0.92504984,0.000031506203],"about_ca_topic_score_codex":0.0020578837,"about_ca_topic_score_gemma":0.0040099374,"teacher_disagreement_score":0.27625856,"about_ca_system_score_codex":0.000397183,"about_ca_system_score_gemma":0.0006690475,"threshold_uncertainty_score":0.92417693},"labels":[],"label_agreement":null},{"id":"W4406250231","doi":"10.1016/b978-0-12-818894-1.00021-5","title":"Improving tractography using anatomical priors and multimodal integration","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec en Outaouais","funders":"","keywords":"Prior probability; Tractography; Computer science; Artificial intelligence; Diffusion MRI; Medicine; Radiology; Bayesian probability; Magnetic resonance imaging","score_opus":0.033405986212041945,"score_gpt":0.32430407573151215,"score_spread":0.2908980895194702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250231","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00095867994,0.0020209202,0.98913926,0.0002368607,0.00017679212,0.000008933957,0.000105948944,0.0017789949,0.0055735363],"genre_scores_gemma":[0.0157167,0.0056369905,0.94873506,0.00012181532,0.00036165598,0.00003249888,0.000496301,0.0012290328,0.027669966],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997619,0.00003719952,0.000012782689,0.000071737326,0.00010478552,0.000011633622],"domain_scores_gemma":[0.9993555,0.0003532487,0.000045337707,0.00011176377,0.00010639441,0.000027689657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007143068,0.0016852643,0.00085757213,0.0012656763,0.00023021482,0.0020308343,0.0009314061,0.0015473481,0.018389529],"category_scores_gemma":[0.0023519357,0.0008288836,0.0008588036,0.0016806648,0.0006029348,0.0018916818,0.0012101999,0.0020173725,0.012146054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042763935,0.000024655963,0.00012672554,0.00023102011,0.00006090572,0.00009246591,0.000041496165,0.05310489,0.02066554,0.019957578,0.021970013,0.88368195],"study_design_scores_gemma":[0.000022036571,0.00011617591,0.0012943932,0.00024922565,0.00011953907,0.001268927,0.000043623048,0.692463,0.031103795,0.13394578,0.13927075,0.00010271837],"about_ca_topic_score_codex":0.0019837182,"about_ca_topic_score_gemma":0.0035147704,"teacher_disagreement_score":0.018389529,"about_ca_system_score_codex":0.00037053405,"about_ca_system_score_gemma":0.0004933592,"threshold_uncertainty_score":0.061519086},"labels":[],"label_agreement":null},{"id":"W4406250261","doi":"10.1016/b978-0-12-818894-1.00013-6","title":"Dissecting white matter pathways: Automatic and semiautomatic approaches","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"White matter; Computer science; Neuroscience; Psychology; Medicine","score_opus":0.06733804487472023,"score_gpt":0.2921523119491402,"score_spread":0.22481426707441998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029413493,0.004985245,0.97970873,0.00032789583,0.00024058676,0.000085496205,0.00029867043,0.0026375214,0.0087746335],"genre_scores_gemma":[0.01215208,0.0044536474,0.9723919,0.00014577003,0.0001099926,0.000069212736,0.00043733785,0.00076333253,0.009476704],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99931145,0.00009436876,0.000062943654,0.00018728155,0.00031120272,0.000032824842],"domain_scores_gemma":[0.998187,0.0010757917,0.000095663854,0.00025251848,0.00033774954,0.000051332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017924211,0.0013547571,0.00073129113,0.0028021834,0.00044549242,0.0037861767,0.0021113649,0.0017976877,0.012422995],"category_scores_gemma":[0.0028194003,0.0012059399,0.00086228276,0.001915138,0.0010448078,0.0024919796,0.00095581927,0.0016521937,0.007383404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007265838,0.000036378202,0.00048486688,0.00074839446,0.00005218331,0.00017257279,0.00015586312,0.0040722657,0.038152594,0.012526264,0.014412089,0.9291139],"study_design_scores_gemma":[0.00007670715,0.00041482798,0.013594991,0.0012487477,0.00028727498,0.017587623,0.00072235113,0.2541752,0.15294725,0.20716983,0.35128543,0.00048977137],"about_ca_topic_score_codex":0.0014581847,"about_ca_topic_score_gemma":0.0041503194,"teacher_disagreement_score":0.012422995,"about_ca_system_score_codex":0.00038923876,"about_ca_system_score_gemma":0.0013406147,"threshold_uncertainty_score":0.0415591},"labels":[],"label_agreement":null},{"id":"W4406250263","doi":"10.1016/b978-0-12-818894-1.00009-4","title":"Tractography: Applications to neurodevelopment, aging, and plasticity","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Neuroscience; Plasticity; Neuroplasticity; Tractography; Psychology; Medicine; Materials science; Diffusion MRI; Magnetic resonance imaging","score_opus":0.040147636839029714,"score_gpt":0.323033680408383,"score_spread":0.28288604356935326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250263","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036365748,0.32983434,0.4215827,0.0061329585,0.0040494637,0.00007912677,0.0014670535,0.004867563,0.22835024],"genre_scores_gemma":[0.025402024,0.32231283,0.24624085,0.0015131484,0.003209385,0.00019564049,0.0010881413,0.0014465052,0.39859143],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998981,0.000015130329,0.0000079822985,0.000024715857,0.00004793213,0.0000062067634],"domain_scores_gemma":[0.9996395,0.00022367775,0.000018046168,0.000028659544,0.000057154975,0.00003291478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034705122,0.0010929967,0.0007075267,0.0018417728,0.00029945897,0.00224904,0.0005980862,0.0015901333,0.036571458],"category_scores_gemma":[0.0007528106,0.0004309326,0.00051958236,0.0022079023,0.0010646873,0.0017461941,0.0007757454,0.001277576,0.015294666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033179844,0.000022535163,0.0003488852,0.00074064254,0.000043564076,0.00027014385,0.00017604508,0.0031414765,0.008347616,0.058209293,0.13060276,0.7980639],"study_design_scores_gemma":[0.000010701884,0.000053014228,0.0017398131,0.0005726362,0.00003562987,0.0025963464,0.00014108614,0.0077753947,0.0027472894,0.14775197,0.8365252,0.000050848732],"about_ca_topic_score_codex":0.0021818506,"about_ca_topic_score_gemma":0.0062125484,"teacher_disagreement_score":0.036571458,"about_ca_system_score_codex":0.00049026444,"about_ca_system_score_gemma":0.000721937,"threshold_uncertainty_score":0.12234378},"labels":[],"label_agreement":null},{"id":"W4406256038","doi":"10.1088/2057-1976/ada8b0","title":"Nyquist ghost elimination for diffusion MRI by dual-polarity readout at low b-values","year":2025,"lang":"en","type":"article","venue":"Biomedical Physics & Engineering Express","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada","funders":"Stiftelsen Assar Gabrielssons Fond; Cancerfonden","keywords":"Ghosting; Polarity (international relations); Diffusion MRI; SIGNAL (programming language); Physics; Diffusion; Isotropy; Kurtosis; Nuclear magnetic resonance; Polarity reversal; Nyquist frequency; Algorithm; Optics; Mathematics; Computer science; Chemistry; Computer vision; Statistics; Magnetic resonance imaging; Medicine","score_opus":0.017690822592697705,"score_gpt":0.3179522657743437,"score_spread":0.300261443181646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406256038","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3942082,0.0011911545,0.59922415,0.00075866637,0.00013917078,0.00014027796,0.00020286224,0.0009283341,0.0032071846],"genre_scores_gemma":[0.611906,0.0008354662,0.38540602,0.00017452335,0.000047968024,0.00008245236,0.00012274779,0.0002111036,0.0012137502],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998504,0.000047839745,0.000010411417,0.000025541944,0.00004771763,0.000018206852],"domain_scores_gemma":[0.99961805,0.00014117616,0.00007689543,0.000059990998,0.00006536875,0.000038489627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048684067,0.0006398674,0.00034126558,0.00035876944,0.00022775712,0.0007549713,0.00040435544,0.0007211799,0.0014800421],"category_scores_gemma":[0.0018948646,0.00036813927,0.00016404306,0.00023376066,0.00042859538,0.0007995428,0.000765499,0.00071476464,0.00055456476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032908525,0.000022470706,0.00035162503,0.000117751544,0.000010726407,0.000161701,0.000052378156,0.0006011738,0.973146,0.000833501,0.0001861309,0.0241875],"study_design_scores_gemma":[0.00006083873,0.0003334789,0.0025214057,0.00004130574,0.000045183056,0.0015184365,0.000035609675,0.03253887,0.95780253,0.0017802715,0.0032785183,0.000043434553],"about_ca_topic_score_codex":0.00019798097,"about_ca_topic_score_gemma":0.0003671551,"teacher_disagreement_score":0.0014800421,"about_ca_system_score_codex":0.00014531963,"about_ca_system_score_gemma":0.00030623548,"threshold_uncertainty_score":0.0049512386},"labels":[],"label_agreement":null},{"id":"W4406270907","doi":"10.1007/s10334-026-01355-6","title":"Associations between iron and mean kurtosis in iron-rich grey matter nuclei in aging","year":2025,"lang":"en","type":"preprint","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Kurtosis; Grey matter; Mathematics; Statistics; Medicine; Magnetic resonance imaging; White matter","score_opus":0.039184659137859484,"score_gpt":0.35416199296336454,"score_spread":0.3149773338255051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406270907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972011,0.0008840492,0.0009374239,0.00009821162,0.000025658397,0.000005817872,0.00031589772,0.000032820404,0.00049898913],"genre_scores_gemma":[0.9978188,0.00025974517,0.00083739444,0.0000344187,0.00003374944,0.000010238663,0.00024523184,0.000019856248,0.00074043113],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99979633,0.0000355236,0.000023321685,0.000083570034,0.0000352366,0.000025898371],"domain_scores_gemma":[0.9982508,0.00038241135,0.00066073245,0.00021061739,0.00033991324,0.00015557051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084484805,0.00045780136,0.00031344098,0.00090255373,0.000318845,0.00053337525,0.00030607203,0.00044420778,0.0017178792],"category_scores_gemma":[0.0043464494,0.00026543823,0.0003419762,0.0004290493,0.00044861488,0.0007049597,0.00052297104,0.00044086674,0.00028933652],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016462291,0.00006605766,0.95758647,0.00012970866,0.00052682165,0.00059043866,0.000802714,0.0004413561,0.013766426,0.00039927464,0.0012852075,0.02275931],"study_design_scores_gemma":[0.000007092223,0.00007809727,0.99670804,0.000012997407,0.00005860036,0.0005774675,0.00012682036,0.0005411974,0.0009904035,0.0005851779,0.00029938144,0.000014740961],"about_ca_topic_score_codex":0.0022435468,"about_ca_topic_score_gemma":0.003023438,"teacher_disagreement_score":0.0022435468,"about_ca_system_score_codex":0.0002303246,"about_ca_system_score_gemma":0.00015292107,"threshold_uncertainty_score":0.0057468414},"labels":[],"label_agreement":null},{"id":"W4406501509","doi":"10.1016/s0084-3970(09)79181-9","title":"10.1016/s0084-3970(09)79181-9","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Functional magnetic resonance imaging; Nuclear magnetic resonance; Medicine; Neuroimaging; Neuroscience; Psychology; Radiology; Physics","score_opus":0.024946955395429734,"score_gpt":0.2681998120168722,"score_spread":0.24325285662144247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406501509","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006332525,0.00046262675,0.0011122023,0.0005486009,0.0003481944,0.0001287349,0.0010357288,0.0011377123,0.99459296],"genre_scores_gemma":[0.0007486535,0.00020180958,0.0005809076,0.00024064533,0.000069436646,0.00007155763,0.00051082444,0.00019387969,0.9973822],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920493,0.00006298841,0.000074028605,0.00027786862,0.00020772393,0.00017251147],"domain_scores_gemma":[0.99746025,0.0007582948,0.0001702421,0.00031007454,0.00051203254,0.00078908406],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014036027,0.0026539266,0.0017751034,0.002714957,0.0020893896,0.003455702,0.0035467695,0.0054665445,0.98966265],"category_scores_gemma":[0.002184857,0.0009963072,0.0013989793,0.0027610168,0.0019589076,0.005273597,0.0034424395,0.002878581,0.9921497],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038070447,0.00021602662,0.0009865883,0.00051399274,0.000036906902,0.00024068078,0.00010716411,0.00054492196,0.0017970563,0.005345438,0.3092319,0.68059874],"study_design_scores_gemma":[0.000079611294,0.00015679406,0.0010405614,0.0003998935,0.00001885645,0.00037568703,0.00018316999,0.0005126008,0.0005107502,0.0010457459,0.99564266,0.000033670058],"about_ca_topic_score_codex":0.0051200236,"about_ca_topic_score_gemma":0.004015025,"teacher_disagreement_score":0.010337353,"about_ca_system_score_codex":0.001141837,"about_ca_system_score_gemma":0.0015615261,"threshold_uncertainty_score":0.014744878},"labels":[],"label_agreement":null},{"id":"W4406522036","doi":"10.1016/j.yneu.2013.04.009","title":"10.1016/j.yneu.2013.04.009","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Arcuate fasciculus; Tractography; Medicine; Diffusion MRI; Fasciculus; Radiology; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.02426337712801217,"score_gpt":0.2676022629608561,"score_spread":0.24333888583284394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406522036","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007929279,0.013890659,0.009988864,0.009647874,0.002868336,0.00011761152,0.0033125866,0.0029114503,0.9493332],"genre_scores_gemma":[0.023310203,0.0056883027,0.005870439,0.002081151,0.00071828265,0.000099261066,0.0017653961,0.0004246809,0.96004224],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99971205,0.000024124438,0.000024018473,0.000099591874,0.00007709365,0.00006302952],"domain_scores_gemma":[0.9992686,0.00016039035,0.00009394064,0.000058886257,0.0001661783,0.0002519111],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008372204,0.0011745112,0.0005823361,0.0015531153,0.00085848046,0.0028457146,0.0010099144,0.003147574,0.8774701],"category_scores_gemma":[0.0016543989,0.00040106176,0.000496455,0.0007879257,0.0010222406,0.0026722308,0.0012202878,0.0013733826,0.82166797],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022520896,0.00018726115,0.004662008,0.000416355,0.000044053864,0.0005561227,0.0001223695,0.0004474697,0.0012393973,0.009447078,0.20100453,0.78164804],"study_design_scores_gemma":[0.000069299,0.000118487835,0.0063668983,0.0011039979,0.000057372155,0.0046868953,0.0004557083,0.0011127825,0.0011946745,0.012212122,0.97257936,0.000042380623],"about_ca_topic_score_codex":0.0028010043,"about_ca_topic_score_gemma":0.0024352309,"teacher_disagreement_score":0.122529924,"about_ca_system_score_codex":0.00070342555,"about_ca_system_score_gemma":0.0010961994,"threshold_uncertainty_score":0.17477405},"labels":[],"label_agreement":null},{"id":"W4406807036","doi":"10.1016/j.neuroimage.2025.121031","title":"Decoding cortical folding patterns in marmosets using machine learning and large language model","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Hebei United University","keywords":"Folding (DSP implementation); Computer science; Decoding methods; Artificial intelligence; Natural language processing; Cognitive science; Psychology; Algorithm; Engineering","score_opus":0.05371819581743156,"score_gpt":0.39664179365520125,"score_spread":0.3429235978377697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406807036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81521225,0.001457089,0.17523944,0.00050470047,0.000056130484,0.000083326464,0.0033476506,0.0025276297,0.0015717964],"genre_scores_gemma":[0.9330352,0.0003227755,0.059581075,0.00010375794,0.000030362095,0.00012704617,0.005838325,0.00014505725,0.00081635645],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971265,0.00007646509,0.000016961489,0.00011321486,0.000029164905,0.00005154817],"domain_scores_gemma":[0.9996939,0.00014420487,0.000042196363,0.000042359414,0.000052751042,0.000024576753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005291899,0.00087709964,0.0006653906,0.0013096344,0.0005373711,0.00072825205,0.00048131056,0.00055010046,0.0012098467],"category_scores_gemma":[0.0016768402,0.000232503,0.0014702205,0.0009297352,0.0003831749,0.00047845184,0.00067345746,0.0005714894,0.00052388106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014218744,0.0003670971,0.14021881,0.00054499024,0.0010434674,0.0015726562,0.0007480322,0.21336518,0.17843369,0.004058621,0.0057963943,0.45242923],"study_design_scores_gemma":[0.00002729953,0.0001474209,0.041701224,0.00003759625,0.00017390483,0.00027174238,0.00031667814,0.92999387,0.014937745,0.010872977,0.0014673179,0.000052212014],"about_ca_topic_score_codex":0.00838039,"about_ca_topic_score_gemma":0.01212512,"teacher_disagreement_score":0.00838039,"about_ca_system_score_codex":0.00058436743,"about_ca_system_score_gemma":0.00064588187,"threshold_uncertainty_score":0.016663194},"labels":[],"label_agreement":null},{"id":"W4406936014","doi":"10.3389/fneur.2025.1507475","title":"Electroacupuncture combined with cognitive rehabilitation outperforms cognitive rehabilitation alone in treating post-stroke cognitive impairment: a randomized controlled trial","year":2025,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Shanghai Municipal Health Commission","keywords":"Montreal Cognitive Assessment; Cognitive rehabilitation therapy; Electroacupuncture; Supramarginal gyrus; Medicine; Cognition; Stroke (engine); Rehabilitation; Verbal learning; Randomized controlled trial; Effects of sleep deprivation on cognitive performance; Fusiform gyrus; Physical therapy; Physical medicine and rehabilitation; Psychology; Internal medicine; Acupuncture; Neuroscience; Psychiatry; Cognitive impairment; Pathology","score_opus":0.006289308848466026,"score_gpt":0.2858935654695705,"score_spread":0.2796042566211045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406936014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.968527,0.022273218,0.0006703465,0.0005607999,0.0011890938,0.0048503648,0.0003827943,0.00010323807,0.001443217],"genre_scores_gemma":[0.9764281,0.009786789,0.0021858208,0.0009768372,0.0010330764,0.0074634175,0.00031234906,0.000012039712,0.0018016631],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9989975,0.00048243554,0.000137446,0.00017566387,0.00009341431,0.000113543094],"domain_scores_gemma":[0.999191,0.00032864753,0.00016989191,0.000047158028,0.00006901814,0.00019440586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015694145,0.0011104769,0.00421581,0.00073543686,0.0005702733,0.0009945632,0.0010884725,0.0023190405,0.00558987],"category_scores_gemma":[0.0020849947,0.00052583084,0.0021490853,0.0007274037,0.0008154526,0.00089696667,0.00047802425,0.0020782512,0.0004576092],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.9675003,0.010157138,0.00028655585,0.002322224,0.002183333,0.000030405643,0.00003015036,0.00010587856,0.0007853926,0.000059223028,0.00019418077,0.016345114],"study_design_scores_gemma":[0.93183106,0.06313814,0.0021703301,0.00017695915,0.0018004754,0.000018215025,0.000028708364,0.00029418006,0.00018481001,0.00006702298,0.00027691774,0.000013148962],"about_ca_topic_score_codex":0.001726786,"about_ca_topic_score_gemma":0.0029158732,"teacher_disagreement_score":0.00558987,"about_ca_system_score_codex":0.00059204403,"about_ca_system_score_gemma":0.000949821,"threshold_uncertainty_score":0.018700004},"labels":[],"label_agreement":null},{"id":"W4406962873","doi":"10.1161/str.56.suppl_1.24","title":"Abstract 24: Iron deposition changes of ipsilateral ventral posterolateral nuclei correlate with central post-stroke pain after thalamic infarction","year":2025,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Infarction; Ischemic stroke; Cardiology; Ischemia; Myocardial infarction","score_opus":0.01156478996736028,"score_gpt":0.26550098420324086,"score_spread":0.2539361942358806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406962873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993692,0.00014456733,0.00014677506,0.000011857613,0.0000017327014,0.0000069805633,0.000055754866,0.000004590495,0.0002584871],"genre_scores_gemma":[0.99964523,0.000041899584,0.00006845032,0.0000063524544,0.0000047352173,0.000005084024,0.00007936386,9.636256e-7,0.00014789654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999443,0.000010518909,0.0000076395945,0.000013434671,0.000012574967,0.000011517087],"domain_scores_gemma":[0.99979097,0.000029025368,0.00010594716,0.000013058813,0.000023766597,0.000037286623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014186297,0.00021382842,0.00015887478,0.00049979036,0.000115244286,0.00018834112,0.00015692024,0.0002005602,0.0034707482],"category_scores_gemma":[0.0005329776,0.00009273117,0.00012129909,0.00020041931,0.00019110995,0.000115512295,0.00015828628,0.00009973725,0.00026724345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003077138,0.00018894479,0.9041514,0.00020007255,0.00021441636,0.005134943,0.00026760183,0.00018978708,0.07215969,0.00006990538,0.00033574813,0.014010287],"study_design_scores_gemma":[0.000023116047,0.00040854947,0.9924455,0.000006164428,0.000035812904,0.004768158,0.000057619927,0.00027049775,0.0018577144,0.000045531066,0.000078299374,0.0000030585068],"about_ca_topic_score_codex":0.00066402287,"about_ca_topic_score_gemma":0.0007672263,"teacher_disagreement_score":0.0034707482,"about_ca_system_score_codex":0.00010948561,"about_ca_system_score_gemma":0.00009086615,"threshold_uncertainty_score":0.011610806},"labels":[],"label_agreement":null},{"id":"W4406972261","doi":"10.1016/j.jocmr.2024.101258","title":"Towards electrocardiogram-free diffusion tensor cardiac magnetic resonance using a machine learning approach","year":2025,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Diffusion MRI; Angiology; Medicine; Cardiac magnetic resonance; Nuclear magnetic resonance; Magnetic resonance imaging; Tensor (intrinsic definition); Artificial intelligence; Cardiology; Radiology; Computer science; Physics; Mathematics","score_opus":0.022894659073126714,"score_gpt":0.2823678662109494,"score_spread":0.2594732071378227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406972261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003578511,0.00015204241,0.994989,0.00015066136,0.000029942752,0.0000158542,0.0000466769,0.00042480897,0.00061242597],"genre_scores_gemma":[0.13752687,0.00041731153,0.8568474,0.0002611297,0.00015770401,0.00007926598,0.00049347786,0.00032052703,0.0038963987],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960726,0.000113642316,0.000023715638,0.00010820716,0.00011404445,0.000033140943],"domain_scores_gemma":[0.9984518,0.00060730835,0.00014585204,0.00019740932,0.00051943684,0.00007817364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009809602,0.0008365138,0.0010339362,0.00092786486,0.00045528574,0.0012553494,0.0014010785,0.0015235738,0.00251577],"category_scores_gemma":[0.003820794,0.00058074476,0.00087299873,0.0005994941,0.00048004344,0.0012209511,0.0018594672,0.0014484616,0.0024756524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019848815,0.00024780422,0.0021547237,0.0002848702,0.00017274824,0.00023702109,0.0001238026,0.27326915,0.034993347,0.025178935,0.008518368,0.65462077],"study_design_scores_gemma":[0.000009504212,0.000024730793,0.00024933496,0.000011787813,0.000015049174,0.000075468735,0.000011814182,0.98819005,0.0021898488,0.0076403646,0.0015712536,0.000010768739],"about_ca_topic_score_codex":0.0030998061,"about_ca_topic_score_gemma":0.0046583167,"teacher_disagreement_score":0.0030998061,"about_ca_system_score_codex":0.00032165542,"about_ca_system_score_gemma":0.0010833853,"threshold_uncertainty_score":0.008416057},"labels":[],"label_agreement":null},{"id":"W4406981800","doi":"10.1016/j.jocmr.2024.101384","title":"Inline automated post-processing and on-scanner diffusion tensor maps visualization for cardiac diffusion tensor imaging using FIRE","year":2025,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Siemens (Canada)","funders":"","keywords":"Diffusion MRI; Medicine; Visualization; Scanner; Angiology; Diffusion; Cardiac imaging; Tensor (intrinsic definition); Artificial intelligence; Computer vision; Radiology; Computer science; Cardiology; Magnetic resonance imaging; Geometry; Physics; Mathematics","score_opus":0.020559667874763734,"score_gpt":0.3215332973577026,"score_spread":0.3009736294829389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406981800","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046114624,0.00057709706,0.9058736,0.0005259279,0.00025480677,0.00034758082,0.0034589008,0.03717856,0.005668992],"genre_scores_gemma":[0.10191038,0.0005972463,0.8787685,0.00029355957,0.00010927264,0.00041236152,0.003230275,0.0076465523,0.0070317695],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99978536,0.00003528497,0.000025893592,0.000038543974,0.00006969801,0.000045199038],"domain_scores_gemma":[0.999209,0.0002476799,0.00007788157,0.00016813162,0.00024585985,0.000051484232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097190065,0.0012893326,0.0005729039,0.0013360229,0.00056642044,0.0018257907,0.0010589976,0.00087242,0.024418272],"category_scores_gemma":[0.002924708,0.00070706767,0.00068780367,0.0007035529,0.0002450235,0.0009841397,0.0011268234,0.00093965104,0.0057166545],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022373977,0.00035116475,0.00720172,0.0009253741,0.00034235386,0.0011536826,0.00078901835,0.008804037,0.15798207,0.0060943672,0.067031756,0.7470872],"study_design_scores_gemma":[0.00035064225,0.00047936026,0.017716046,0.00033788633,0.00026302395,0.003284058,0.0005232862,0.34652975,0.4615614,0.015503137,0.15316576,0.00028566777],"about_ca_topic_score_codex":0.0029180008,"about_ca_topic_score_gemma":0.008212754,"teacher_disagreement_score":0.024418272,"about_ca_system_score_codex":0.00028030237,"about_ca_system_score_gemma":0.0013947696,"threshold_uncertainty_score":0.08168721},"labels":[],"label_agreement":null},{"id":"W4407029036","doi":"10.7554/elife.101950.2","title":"From histology to macroscale function in the human amygdala","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Savoy Foundation","keywords":"Amygdala; Neuroscience; Neuroimaging; Human brain; Spatial normalization; Voxel; Psychology; Computer science; Artificial intelligence","score_opus":0.08474947672382899,"score_gpt":0.4147889573534217,"score_spread":0.3300394806295927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407029036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9240192,0.0006904191,0.07312226,0.00022875582,0.00002009975,0.000021275819,0.00039184556,0.00017906752,0.0013270763],"genre_scores_gemma":[0.9870797,0.00026870036,0.012121045,0.00004557087,0.000006309177,0.000010024033,0.00009650472,0.000039813138,0.00033232002],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999554,0.000009195547,0.0000024689768,0.000013489576,0.000013705456,0.0000056345975],"domain_scores_gemma":[0.9999124,0.000019274537,0.000026875543,0.000019798063,0.000014770804,0.00000696449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001812471,0.00011187519,0.00008701448,0.000425391,0.00011890583,0.00033255765,0.00014322913,0.00017654117,0.0008865564],"category_scores_gemma":[0.0005701497,0.00019745519,0.00010637134,0.00018907705,0.0004409729,0.00030133632,0.00026352057,0.00018731867,0.0001582496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014669332,0.000015338346,0.016815433,0.00012484287,0.00005205937,0.00035056716,0.0006626142,0.006458478,0.9354394,0.0019312663,0.00048197058,0.037521325],"study_design_scores_gemma":[0.000014340912,0.0002031721,0.7798429,0.00006724152,0.00007538159,0.004013395,0.00081725384,0.05790674,0.14155768,0.010388146,0.005050259,0.00006342774],"about_ca_topic_score_codex":0.0016144563,"about_ca_topic_score_gemma":0.0031866522,"teacher_disagreement_score":0.0016144563,"about_ca_system_score_codex":0.00016605477,"about_ca_system_score_gemma":0.00016542658,"threshold_uncertainty_score":0.0032101274},"labels":[],"label_agreement":null},{"id":"W4407030709","doi":"10.1016/j.pscychresns.2025.111958","title":"Correlation study between the microstructural abnormalities of medial prefrontal cortex and white matter hyperintensities with mild cognitive impairment patients: A diffusion kurtosis imaging study","year":2025,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Kurtosis; White matter; Prefrontal cortex; Psychology; Diffusion MRI; Cognitive impairment; Correlation; Audiology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.036444473273477544,"score_gpt":0.3656877081897759,"score_spread":0.32924323491629837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407030709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993662,0.00025847007,0.00008518221,0.000014179162,0.0000032990295,0.0000110209,0.00010729652,0.0000019589602,0.0001522798],"genre_scores_gemma":[0.9993517,0.00011454781,0.00015632868,0.000010397157,0.000015562588,0.000011464654,0.00021494231,0.0000012230889,0.00012384212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997615,0.000033025965,0.00004861447,0.00008169415,0.000044121276,0.00003107332],"domain_scores_gemma":[0.99900407,0.00015449489,0.00045338302,0.000059388614,0.00014936576,0.00017934167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042852882,0.00043894825,0.0003508864,0.0013105402,0.00035481245,0.0003623297,0.00020971066,0.00043458393,0.0013629736],"category_scores_gemma":[0.0018303912,0.0003005175,0.0003280975,0.0006297718,0.00023924622,0.00040986744,0.00033714928,0.0002949875,0.0002594361],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028094903,0.00006121811,0.99572194,0.000027172939,0.0000826426,0.00063046947,0.00012682873,0.00002899764,0.0012613778,0.000012540845,0.000060384245,0.0017054565],"study_design_scores_gemma":[0.000010311524,0.00024194282,0.9967114,0.0000040879413,0.000045383385,0.0023246577,0.00013862428,0.00012700222,0.00022843685,0.000026447242,0.00013602278,0.0000057324883],"about_ca_topic_score_codex":0.001436088,"about_ca_topic_score_gemma":0.0014762881,"teacher_disagreement_score":0.001436088,"about_ca_system_score_codex":0.00017788366,"about_ca_system_score_gemma":0.00020985729,"threshold_uncertainty_score":0.004559636},"labels":[],"label_agreement":null},{"id":"W4407103892","doi":"10.7554/elife.103530.1.sa1","title":"Reviewer #1 (Public review): Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Cartography; Diffusion; Zona; Geography; Biology; Neuroscience; Physics; Virology","score_opus":0.13312969900421867,"score_gpt":0.3878983160392467,"score_spread":0.254768617035028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103892","genre_codex":"editorial","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000626589,0.008740883,0.0024111583,0.40264624,0.57264996,0.0024771017,0.0043918146,0.00091766776,0.005138698],"genre_scores_gemma":[0.0155409295,0.015273296,0.006178375,0.5670688,0.32458764,0.012017365,0.0031606646,0.0018363926,0.054336444],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9464448,0.01595133,0.010287908,0.0049070823,0.020537877,0.0018709686],"domain_scores_gemma":[0.4166964,0.06493483,0.028761683,0.01702834,0.46120638,0.0113724675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.067555085,0.0020065333,0.00420285,0.006070055,0.004263165,0.00944156,0.005529218,0.018075293,0.05249693],"category_scores_gemma":[0.43400022,0.0015683493,0.0037194798,0.0034733864,0.0037308198,0.0049213525,0.004225871,0.008188851,0.028648881],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065251945,0.0000067014544,0.00020624412,0.0019788323,0.00004506063,0.0000709025,0.00007529644,0.000026757036,0.000078720586,0.00016824502,0.9916146,0.0056633516],"study_design_scores_gemma":[0.00036110435,0.000049795482,0.0022502453,0.008762318,0.00025862534,0.0004800928,0.00040003902,0.00039443103,0.00056679023,0.0017183811,0.98462313,0.00013504832],"about_ca_topic_score_codex":0.0055184574,"about_ca_topic_score_gemma":0.008263388,"teacher_disagreement_score":0.067555085,"about_ca_system_score_codex":0.0077951266,"about_ca_system_score_gemma":0.019616332,"threshold_uncertainty_score":0.3572697},"labels":[],"label_agreement":null},{"id":"W4407103926","doi":"10.7554/elife.103530.1","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Zona; Diffusion; Diffusion MRI; Cartography; Geography; Geology; Biology; Neuroscience; Physics; Magnetic resonance imaging; Medicine; Radiology; Virology","score_opus":0.08933693897071142,"score_gpt":0.3609058517935722,"score_spread":0.2715689128228608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8234101,0.005375781,0.15685734,0.0014689821,0.000056042696,0.00018322183,0.0036815447,0.0009947391,0.007972251],"genre_scores_gemma":[0.94403774,0.0012924542,0.051053308,0.0001273676,0.000025223251,0.00007087513,0.0006581462,0.00014721778,0.0025877361],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998796,0.00001930492,0.000005964153,0.000050626593,0.000031148225,0.000013414969],"domain_scores_gemma":[0.99973494,0.00008173733,0.00006929168,0.000045723813,0.00005110905,0.000017272869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004359872,0.00023071538,0.00015161681,0.00163869,0.00023404631,0.00087629264,0.00031682785,0.00034596174,0.0017543272],"category_scores_gemma":[0.0016849138,0.0002712937,0.00014056668,0.00067182793,0.00042664201,0.00046644016,0.00036470097,0.00034363038,0.0005527952],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009251678,0.00008637857,0.05379802,0.0006876958,0.00031081287,0.00097020436,0.0013752027,0.011331393,0.6677947,0.012262874,0.006553956,0.24390355],"study_design_scores_gemma":[0.00012836208,0.00028807542,0.58882004,0.00037424997,0.000362644,0.009597113,0.0011346976,0.08877723,0.23930627,0.024352213,0.04661472,0.00024443268],"about_ca_topic_score_codex":0.007729732,"about_ca_topic_score_gemma":0.011644129,"teacher_disagreement_score":0.007729732,"about_ca_system_score_codex":0.0004168824,"about_ca_system_score_gemma":0.00048860826,"threshold_uncertainty_score":0.015369475},"labels":[],"label_agreement":null},{"id":"W4407103944","doi":"10.7554/elife.103530","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Zona; Diffusion; Diffusion MRI; Cartography; Geography; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Physics; Radiology; Virology","score_opus":0.08933693897071142,"score_gpt":0.3609058517935722,"score_spread":0.2715689128228608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8234101,0.005375781,0.15685734,0.0014689821,0.000056042696,0.00018322183,0.0036815447,0.0009947391,0.007972251],"genre_scores_gemma":[0.94403774,0.0012924542,0.051053308,0.0001273676,0.000025223251,0.00007087513,0.0006581462,0.00014721778,0.0025877361],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998796,0.00001930492,0.000005964153,0.000050626593,0.000031148225,0.000013414969],"domain_scores_gemma":[0.99973494,0.00008173733,0.00006929168,0.000045723813,0.00005110905,0.000017272869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004359872,0.00023071538,0.00015161681,0.00163869,0.00023404631,0.00087629264,0.00031682785,0.00034596174,0.0017543272],"category_scores_gemma":[0.0016849138,0.0002712937,0.00014056668,0.00067182793,0.00042664201,0.00046644016,0.00036470097,0.00034363038,0.0005527952],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009251678,0.00008637857,0.05379802,0.0006876958,0.00031081287,0.00097020436,0.0013752027,0.011331393,0.6677947,0.012262874,0.006553956,0.24390355],"study_design_scores_gemma":[0.00012836208,0.00028807542,0.58882004,0.00037424997,0.000362644,0.009597113,0.0011346976,0.08877723,0.23930627,0.024352213,0.04661472,0.00024443268],"about_ca_topic_score_codex":0.007729732,"about_ca_topic_score_gemma":0.011644129,"teacher_disagreement_score":0.007729732,"about_ca_system_score_codex":0.0004168824,"about_ca_system_score_gemma":0.00048860826,"threshold_uncertainty_score":0.015369475},"labels":[],"label_agreement":null},{"id":"W4407161502","doi":"10.1038/s42003-025-07528-8","title":"A multimodal characterization of low-dimensional thalamocortical structural connectivity patterns","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Hospital for Sick Children; Max-Planck-Gesellschaft; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Bundesministerium für Bildung und Forschung; Canada Research Chairs; McGill University","keywords":"Thalamus; Neuroscience; Connectome; Human Connectome Project; Diffusion MRI; Functional connectivity; Default mode network; Stimulus modality; Psychology; Sensory system; Medicine; Magnetic resonance imaging","score_opus":0.05494794832803931,"score_gpt":0.3950609596979854,"score_spread":0.3401130113699461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407161502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90165776,0.00030485657,0.094461136,0.00019151345,0.000006032859,0.000020624222,0.0009230847,0.00013787475,0.0022970997],"genre_scores_gemma":[0.9893378,0.00013201103,0.009838593,0.00001280963,0.00000986728,0.0000117069285,0.00040294262,0.000017937009,0.00023637564],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999324,0.00001620842,0.0000036651875,0.00002047606,0.000014473829,0.000012751105],"domain_scores_gemma":[0.9997677,0.00008198742,0.000057449008,0.000028853832,0.000035464967,0.000028482124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015133113,0.00018089541,0.00014327162,0.0010138646,0.00014834217,0.0005964346,0.00013164998,0.00019911285,0.0012671099],"category_scores_gemma":[0.0011869536,0.00010266594,0.00021562292,0.000624946,0.00032376597,0.0005445469,0.00031770987,0.00022143222,0.00015419362],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004348794,0.0000999617,0.14304602,0.00034391822,0.00030360662,0.0010017925,0.0015874418,0.0538679,0.55222905,0.028392702,0.0028259591,0.21586679],"study_design_scores_gemma":[0.000017559607,0.00016463923,0.6149967,0.0000490586,0.00011715513,0.001995976,0.00062928215,0.3167214,0.022953656,0.039964538,0.0022975726,0.00009256471],"about_ca_topic_score_codex":0.0012276354,"about_ca_topic_score_gemma":0.0026274233,"teacher_disagreement_score":0.0012671099,"about_ca_system_score_codex":0.00014450328,"about_ca_system_score_gemma":0.00015971108,"threshold_uncertainty_score":0.0042389035},"labels":[],"label_agreement":null},{"id":"W4407295955","doi":"10.1111/jon.70019","title":"Magnetization Transfer Ratio in the Typically Developing Pediatric Spinal Cord: Normative Data and Age Correlation","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; White matter; Magnetization transfer; Magnetic resonance imaging; Spinal cord; Nuclear medicine; Correlation; Fasciculus; Dorsum; Anatomy; Radiology","score_opus":0.09257360947177605,"score_gpt":0.3904115014308506,"score_spread":0.29783789195907456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407295955","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9878982,0.0011798928,0.004775072,0.000029571975,0.000012880521,0.00004865264,0.0029080373,0.00030216906,0.0028456235],"genre_scores_gemma":[0.99031734,0.0004316647,0.005556898,0.000015091686,0.000011451733,0.00008944296,0.0033188683,0.000052150972,0.00020711636],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992342,0.000115251365,0.000120519486,0.00019170083,0.00029982097,0.000038506343],"domain_scores_gemma":[0.9971506,0.00064078247,0.0007599812,0.00034795637,0.0010174931,0.000083272455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012879113,0.00040962934,0.00026750984,0.002091582,0.00024906555,0.00041237863,0.0004928424,0.00038369757,0.0013991493],"category_scores_gemma":[0.006439689,0.000105237224,0.00015707669,0.0013839824,0.00034474814,0.00038256642,0.00035198967,0.00019998485,0.0005065565],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030329372,0.000049801252,0.9341763,0.00016963982,0.00010256053,0.0007140088,0.0005615841,0.00089911907,0.008233425,0.0002852993,0.0010519555,0.05345308],"study_design_scores_gemma":[0.0000069399243,0.00016005314,0.9877928,0.000037523852,0.000043280485,0.004604628,0.00020646982,0.0009403142,0.0041853604,0.00016701581,0.0018428225,0.00001283847],"about_ca_topic_score_codex":0.00419427,"about_ca_topic_score_gemma":0.0047127544,"teacher_disagreement_score":0.00419427,"about_ca_system_score_codex":0.00032422837,"about_ca_system_score_gemma":0.0003322208,"threshold_uncertainty_score":0.008339703},"labels":[],"label_agreement":null},{"id":"W4407419860","doi":"10.1002/hbm.70143","title":"Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross‐Sectional Datasets Across the Lifespan","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; Georgia Clinical and Translational Science Alliance; Pfizer; Biogen; BioClinica; National Center for Research Resources; F. Hoffmann-La Roche; Vanderbilt University; Vanderbilt Memory and Alzheimer's Center; Novartis Pharmaceuticals Corporation; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Magnetic resonance imaging; Motion (physics); Diffusion MRI; Functional magnetic resonance imaging; Neuroimaging; Psychology; Computer vision; Artificial intelligence; Computer science; Neuroscience; Medicine; Radiology","score_opus":0.0494239448141113,"score_gpt":0.40001855553710297,"score_spread":0.3505946107229917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407419860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9608331,0.0017111734,0.033067796,0.00036103072,0.000036341127,0.00009627857,0.0030175892,0.00025711211,0.00061958964],"genre_scores_gemma":[0.9694793,0.0006923281,0.024192186,0.00008840401,0.000040523435,0.00025126382,0.0047580493,0.00010257568,0.0003952567],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998494,0.0006024997,0.00019963202,0.00049018936,0.00014808647,0.00006562624],"domain_scores_gemma":[0.99551976,0.0012462807,0.0014065752,0.001195374,0.000531629,0.000100340025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044436962,0.0004786423,0.00040102776,0.0013846126,0.0006021578,0.00075120473,0.0005231019,0.0005321793,0.00060301874],"category_scores_gemma":[0.013188883,0.00035135282,0.00046615192,0.0015344766,0.0004984677,0.0008139256,0.0009352834,0.0004138754,0.00022518885],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005913749,0.00009964369,0.893877,0.00055103697,0.0018890006,0.00044672875,0.0015262199,0.005410924,0.022779224,0.0016409184,0.003058368,0.06812958],"study_design_scores_gemma":[0.000022332328,0.00014727842,0.9805099,0.00009359033,0.00033054542,0.0007801003,0.00029558636,0.008278272,0.0040723076,0.0020631447,0.0033749687,0.000031982992],"about_ca_topic_score_codex":0.004126517,"about_ca_topic_score_gemma":0.011705139,"teacher_disagreement_score":0.0044436962,"about_ca_system_score_codex":0.00035621494,"about_ca_system_score_gemma":0.00047589038,"threshold_uncertainty_score":0.02350074},"labels":[],"label_agreement":null},{"id":"W4407591286","doi":"10.7554/elife.101950.3","title":"From histology to macroscale function in the human amygdala","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Sickkids Research Institute; Savoy Foundation; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Amygdala; Neuroscience; Neuroimaging; Human brain; Spatial normalization; Cytoarchitecture; Voxel; Anatomy; Biology; Computer science; Artificial intelligence","score_opus":0.05220968834402858,"score_gpt":0.400782774699086,"score_spread":0.34857308635505746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407591286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8702515,0.0015476837,0.12397345,0.00034781813,0.000026982456,0.00003780291,0.0005115334,0.00028209697,0.0030212076],"genre_scores_gemma":[0.97101665,0.0007945127,0.02721421,0.000096238,0.000011564976,0.000020894147,0.00016630086,0.00008346229,0.00059614854],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999484,0.000009426853,0.0000028693223,0.000016760383,0.000015963233,0.0000065952217],"domain_scores_gemma":[0.99991846,0.000017235425,0.000021873437,0.000020447831,0.000014322081,0.000007667183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021487237,0.0001247435,0.00008921677,0.00055139913,0.00013042708,0.00039203896,0.00015240416,0.00018267674,0.00075364544],"category_scores_gemma":[0.00057760463,0.00023143251,0.00013126116,0.0002425395,0.0004935803,0.0004019668,0.00029778693,0.00024982658,0.00015602757],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001466943,0.0000142246845,0.017537804,0.00017312926,0.0000624647,0.00038724882,0.00107655,0.006238755,0.9112438,0.0030226375,0.0005299847,0.059566833],"study_design_scores_gemma":[0.000016049966,0.0002564397,0.789968,0.000115572984,0.00010817215,0.0046120933,0.0012141522,0.053144936,0.12549785,0.015161873,0.009818501,0.000086349675],"about_ca_topic_score_codex":0.0019000986,"about_ca_topic_score_gemma":0.0046665776,"teacher_disagreement_score":0.0019000986,"about_ca_system_score_codex":0.0001996587,"about_ca_system_score_gemma":0.00023301963,"threshold_uncertainty_score":0.0037780404},"labels":[],"label_agreement":null},{"id":"W4407710349","doi":"10.1002/mrm.30465","title":"Interpretation of inhomogeneous magnetization transfer in myelin water using a four‐pool model with dipolar reservoirs","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; McGill University; University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; International Collaboration on Repair Discoveries","keywords":"Myelin; Magnetization transfer; White matter; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Dipole; Drop (telecommunication); Biophysics; Physics; Neuroscience; Biology; Medicine; Radiology; Central nervous system","score_opus":0.04129908535081966,"score_gpt":0.32660694325929646,"score_spread":0.2853078579084768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407710349","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22717881,0.00046917915,0.7699501,0.00020580163,0.00002733449,0.00009529398,0.00006567398,0.00047337066,0.0015343601],"genre_scores_gemma":[0.93169165,0.0003633474,0.06471864,0.00005614022,0.000011047909,0.000093880364,0.000057320583,0.000070079645,0.0029379698],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999368,0.000021885317,0.0000030531658,0.000013854302,0.000013385091,0.0000110179435],"domain_scores_gemma":[0.999816,0.00008149316,0.000037104837,0.000021166734,0.000027842923,0.00001636581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043161586,0.00058634917,0.00024299364,0.0003703271,0.00016903464,0.00038816364,0.0008454984,0.00054336735,0.0010599323],"category_scores_gemma":[0.0008281423,0.00024807156,0.00030299134,0.00016723842,0.0004186895,0.00093654153,0.0004482105,0.00035426475,0.0002225239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042144206,0.0001078457,0.0027687747,0.0003619964,0.00010860783,0.0010367533,0.00024426228,0.2063355,0.74713665,0.015687086,0.0004966119,0.025294594],"study_design_scores_gemma":[0.000017655624,0.00018512405,0.0005407327,0.000013263362,0.000033792752,0.00021366109,0.00003113208,0.9261198,0.06893634,0.0028506748,0.0010393277,0.000018511972],"about_ca_topic_score_codex":0.0015711467,"about_ca_topic_score_gemma":0.0010872377,"teacher_disagreement_score":0.0015711467,"about_ca_system_score_codex":0.00045701198,"about_ca_system_score_gemma":0.00049861404,"threshold_uncertainty_score":0.003545761},"labels":[],"label_agreement":null},{"id":"W4407777100","doi":"10.1016/j.pnpbp.2025.111294","title":"White matter integrity and verbal memory following a first episode of psychosis: A longitudinal study","year":2025,"lang":"en","type":"article","venue":"Progress in Neuro-Psychopharmacology and Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research","keywords":"Psychosis; Psychology; White matter; Verbal memory; Psychiatry; Developmental psychology; Clinical psychology; Medicine; Cognition","score_opus":0.054293657111784244,"score_gpt":0.4096242642019829,"score_spread":0.35533060709019865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407777100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9994429,0.0001641926,0.000047098805,0.00003216132,0.0000035351668,0.000014686239,0.00014913113,0.0000025147872,0.00014376063],"genre_scores_gemma":[0.99897385,0.00014072184,0.00013473244,0.000032634616,0.000009144434,0.000022979393,0.0004055563,0.0000026742562,0.0002777487],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995074,0.00013414932,0.0000431139,0.00012035083,0.000086227934,0.00010869422],"domain_scores_gemma":[0.9982456,0.00016890571,0.00060793734,0.000239331,0.00028778997,0.00045052412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015881358,0.0003648604,0.0004340132,0.00068598473,0.0013685419,0.0010352969,0.0005635271,0.0009670947,0.0010904144],"category_scores_gemma":[0.0025257056,0.00053974375,0.000716944,0.00088947936,0.00039775707,0.001043631,0.00086559786,0.0014298598,0.00042008038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008801406,0.000657002,0.99404514,0.00001918616,0.00019976124,0.00032677385,0.0008950659,0.000035352346,0.0005082281,0.000023993522,0.0001334218,0.002275984],"study_design_scores_gemma":[0.000025184976,0.00072908687,0.99791664,0.000014849008,0.00009097837,0.00038516722,0.00043023968,0.000097278826,0.000066395485,0.000038642218,0.00019633929,0.000009133937],"about_ca_topic_score_codex":0.013534727,"about_ca_topic_score_gemma":0.014804736,"teacher_disagreement_score":0.013534727,"about_ca_system_score_codex":0.0005628711,"about_ca_system_score_gemma":0.0007265807,"threshold_uncertainty_score":0.026911914},"labels":[],"label_agreement":null},{"id":"W4407788542","doi":"10.1016/j.bpsgos.2025.100472","title":"Stable White Matter Structure in the First Three Years After Psychosis Onset","year":2025,"lang":"en","type":"article","venue":"Biological Psychiatry Global Open Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"Janssen Canada; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Sunovion; Canadian Institutes of Health Research; Canada Research Chairs; Canada First Research Excellence Fund; National Institutes of Health; Western University; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Brain and Behavior Research Foundation; McGill University; Mitsubishi Tanabe Pharma Corporation","keywords":"Psychosis; White matter; Psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04428910245027392,"score_gpt":0.3820150096875228,"score_spread":0.3377259072372489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407788542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99740064,0.00028038007,0.00012938106,0.00005911251,0.000008225399,0.000010039465,0.0018101507,0.000013676751,0.0002884896],"genre_scores_gemma":[0.99655354,0.00009473542,0.00007705542,0.000017283413,0.0000052364962,0.000011333983,0.0029786893,0.00000442556,0.00025769716],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997472,0.00003871912,0.000019655045,0.00007620115,0.000043655476,0.000074627154],"domain_scores_gemma":[0.99828905,0.0001602516,0.0006938696,0.00020923465,0.00029823955,0.00034928543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091501506,0.00023988506,0.0003643491,0.0009829833,0.0006841208,0.0009394,0.00035012636,0.000497381,0.0020750584],"category_scores_gemma":[0.0033055127,0.00019208642,0.00043662186,0.0005529354,0.0002988247,0.00050722377,0.0010438195,0.0006071835,0.0005302406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001900136,0.00007973209,0.98537076,0.000040688115,0.00019961986,0.0004761375,0.00047832253,0.00017830389,0.0025271224,0.000116717296,0.0008082662,0.007824182],"study_design_scores_gemma":[0.0000059027725,0.000104107094,0.99890137,0.000013398113,0.000020927626,0.00022304052,0.0001319498,0.00013014776,0.00015927757,0.000105645544,0.00019858532,0.0000055729956],"about_ca_topic_score_codex":0.01866624,"about_ca_topic_score_gemma":0.027763486,"teacher_disagreement_score":0.01866624,"about_ca_system_score_codex":0.0007256797,"about_ca_system_score_gemma":0.0006767952,"threshold_uncertainty_score":0.037115157},"labels":[],"label_agreement":null},{"id":"W4407793608","doi":"10.1101/2025.02.19.638284","title":"White-matter controllability at birth predicts social engagement and language outcomes in toddlerhood","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"","keywords":"Controllability; White (mutation); Psychology; White matter; Developmental psychology; Medicine; Mathematics; Chemistry","score_opus":0.028304870949952165,"score_gpt":0.2964071252606344,"score_spread":0.26810225431068224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407793608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991848,0.00008188782,0.00030879775,0.000023551751,0.0000028965653,0.0000027698354,0.00019313495,0.000009040323,0.0001932044],"genre_scores_gemma":[0.9990175,0.00008326836,0.0003208991,0.000010113454,0.0000017956689,0.000011137399,0.0003301346,0.0000052473856,0.00021985351],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997955,0.000029512968,0.000023859178,0.00007923005,0.00003178032,0.00004010006],"domain_scores_gemma":[0.9991134,0.00018520915,0.00037060576,0.00009544521,0.00009390347,0.00014143388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052516995,0.00048747502,0.0002649864,0.00067193486,0.00038911132,0.0006921188,0.000291981,0.00031716572,0.0010116459],"category_scores_gemma":[0.00269607,0.00025835595,0.0005116506,0.00032566054,0.00035808742,0.00029436802,0.0009002343,0.0004311448,0.00015950199],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013783903,0.000025350288,0.9928231,0.000014623916,0.00012003619,0.0003295882,0.00033399463,0.00056568236,0.0014067359,0.0001517016,0.00014558979,0.0039456473],"study_design_scores_gemma":[0.0000016632246,0.000036766858,0.9978575,0.000011458948,0.0000301872,0.0001395283,0.00023990854,0.00095287204,0.0003846382,0.00022345946,0.00011658838,0.000005433149],"about_ca_topic_score_codex":0.03309431,"about_ca_topic_score_gemma":0.03854143,"teacher_disagreement_score":0.03309431,"about_ca_system_score_codex":0.00069990655,"about_ca_system_score_gemma":0.00041259784,"threshold_uncertainty_score":0.06580335},"labels":[],"label_agreement":null},{"id":"W4407819042","doi":"10.1002/hbm.70165","title":"The <i>Psy</i>chosis <scp>MRI</scp><i>Share</i>d <i>D</i>ata Resource (Psy‐<scp>ShareD</scp>)","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research Council","keywords":"Neuroimaging; Schizophrenia (object-oriented programming); General partnership; Data sharing; Psychology; Psychosis; Resource (disambiguation); Medicine; Psychiatry; Computer science; Business; Pathology; Finance","score_opus":0.055153388133853155,"score_gpt":0.3326830771960151,"score_spread":0.2775296890621619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407819042","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016642315,0.0034523131,0.0049899174,0.012486184,0.002108345,0.0007597013,0.88649607,0.0055263224,0.08251695],"genre_scores_gemma":[0.01832478,0.0081214085,0.029062048,0.010249254,0.0014768956,0.0041139754,0.83790994,0.009795373,0.08094637],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965688,0.0008842014,0.00054984883,0.0006659627,0.0009956058,0.0003355536],"domain_scores_gemma":[0.97904384,0.0057024662,0.0023969354,0.0041181264,0.006230868,0.0025078664],"candidate_categories":["open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0061942083,0.0011550615,0.0024985964,0.004576594,0.0020299389,0.004858757,0.0042640576,0.002780585,0.53303134],"category_scores_gemma":[0.047858596,0.001104735,0.0015982335,0.009460004,0.0010364203,0.004019001,0.007027091,0.0026229175,0.23540851],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032094354,0.0000168143,0.00058643497,0.0013304751,0.00009057879,0.00011110823,0.00008086603,0.00007369673,0.00023778279,0.0015504735,0.9678252,0.027775662],"study_design_scores_gemma":[0.0005590935,0.000048126054,0.005152351,0.0017509806,0.00012067004,0.00035963114,0.00010641693,0.0002344013,0.00040768227,0.006105453,0.9851011,0.000054056396],"about_ca_topic_score_codex":0.024913052,"about_ca_topic_score_gemma":0.042783268,"teacher_disagreement_score":0.99573594,"about_ca_system_score_codex":0.0030139675,"about_ca_system_score_gemma":0.013436666,"threshold_uncertainty_score":0.6660741},"labels":[],"label_agreement":null},{"id":"W4407987573","doi":"10.1002/mrm.30424","title":"Considerations and recommendations from the <scp>ISMRM</scp> Diffusion Study Group for preclinical diffusion <scp>MRI</scp> : Part 3—Ex vivo imaging: Data processing, comparisons with microscopy, and tractography","year":2025,"lang":"en","type":"review","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"H2020 European Research Council; National Cancer Institute; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; National Institute on Drug Abuse; Institut de Valorisation des Données; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Vlaamse regering; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; Canada First Research Excellence Fund; Universiteit Antwerpen; Canada Foundation for Innovation; Fonds Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; National Science Foundation; National Institute of Neurological Disorders and Stroke; Generalitat de Catalunya; Wellcome Trust","keywords":"Ex vivo; Diffusion MRI; Tractography; Diffusion imaging; Microscopy; Magnetic resonance imaging; In vivo; Nuclear magnetic resonance; Neuroscience; Medicine; Pathology; Biology; Physics; Radiology","score_opus":0.12290899044640002,"score_gpt":0.4309845932417162,"score_spread":0.30807560279531615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407987573","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016716196,0.037093125,0.09259299,0.75961524,0.03386504,0.005022787,0.008898884,0.008181447,0.053058796],"genre_scores_gemma":[0.006006462,0.06794826,0.47408277,0.3426948,0.012718961,0.013007289,0.015372029,0.0055399407,0.062629506],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9314496,0.027944883,0.011528133,0.0025070147,0.024458952,0.0021114242],"domain_scores_gemma":[0.5884556,0.12616849,0.021370621,0.026918137,0.21297488,0.02411234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.112154976,0.002200509,0.002489853,0.0065901843,0.0026847648,0.00876715,0.014927047,0.01976039,0.022247713],"category_scores_gemma":[0.24831596,0.0020346765,0.0040934393,0.005892666,0.0057314364,0.009423208,0.00698101,0.017918218,0.0483181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014126133,0.00017864072,0.00039380972,0.0015634922,0.00004253964,0.0002138551,0.00033916676,0.0005566306,0.0010937416,0.004220075,0.9046842,0.086572535],"study_design_scores_gemma":[0.00016303713,0.00012618999,0.0008777024,0.0072577307,0.00011577404,0.0003787063,0.00045158277,0.00055862725,0.001261439,0.012795204,0.9758763,0.00013772928],"about_ca_topic_score_codex":0.018631011,"about_ca_topic_score_gemma":0.022427266,"teacher_disagreement_score":0.112154976,"about_ca_system_score_codex":0.003634127,"about_ca_system_score_gemma":0.04450788,"threshold_uncertainty_score":0.5931393},"labels":[],"label_agreement":null},{"id":"W4407987811","doi":"10.1002/mrm.30429","title":"Considerations and recommendations from the <scp>ISMRM</scp> diffusion study group for preclinical diffusion <scp>MRI</scp> : Part 1: In vivo small‐animal imaging","year":2025,"lang":"en","type":"review","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"National Cancer Institute; National Institute of Mental Health; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; Universiteit Antwerpen; Canada First Research Excellence Fund; Norges Forskningsråd; Fonds Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; National Science Foundation; National Institute of Neurological Disorders and Stroke; Generalitat de Catalunya; National Institute on Drug Abuse; Institut de Valorisation des Données; National Institute of Biomedical Imaging and Bioengineering; Vlaamse regering; European Commission","keywords":"In vivo; Diffusion; Diffusion imaging; Chemistry; Diffusion MRI; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Physics; Biology; Radiology","score_opus":0.10475546549551583,"score_gpt":0.40542778403316126,"score_spread":0.3006723185376454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407987811","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013934432,0.0592443,0.08302382,0.73666424,0.045561377,0.0041983365,0.011109467,0.0065859463,0.052219078],"genre_scores_gemma":[0.006676663,0.096678056,0.35124004,0.42619565,0.019702349,0.013216813,0.016458552,0.0050564674,0.06477537],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9365405,0.029236961,0.010328322,0.0026281143,0.019396195,0.0018699215],"domain_scores_gemma":[0.6185921,0.15198322,0.01947287,0.024670335,0.16439274,0.020888766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.10279759,0.0023938823,0.003053138,0.0063318615,0.002171091,0.008286859,0.013036188,0.020553354,0.02996487],"category_scores_gemma":[0.28499785,0.0017973763,0.0041114874,0.0055009173,0.00539148,0.010492323,0.006954355,0.018931963,0.060870674],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016359892,0.00011455035,0.00022903328,0.0020460954,0.000044153785,0.00017136273,0.00024367403,0.00036565404,0.00080202706,0.0037728816,0.91915476,0.07289215],"study_design_scores_gemma":[0.00015642098,0.00012813693,0.0007405379,0.009300725,0.00011627613,0.00039377183,0.00041281438,0.00037060436,0.0010685052,0.013765848,0.97341466,0.0001316053],"about_ca_topic_score_codex":0.010042296,"about_ca_topic_score_gemma":0.013112919,"teacher_disagreement_score":0.10279759,"about_ca_system_score_codex":0.0031900513,"about_ca_system_score_gemma":0.028612353,"threshold_uncertainty_score":0.5436521},"labels":[],"label_agreement":null},{"id":"W4408061855","doi":"10.7554/elife.94917.3","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Scleroseforeningen","keywords":"White matter; Bridging (networking); Evolutionary biology; Biology; Anatomy; Neuroscience; Computer science; Medicine; Magnetic resonance imaging","score_opus":0.041203847167856904,"score_gpt":0.33508642851343073,"score_spread":0.2938825813455738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408061855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88872164,0.0011250741,0.10641205,0.00017095187,0.000014144088,0.00004265938,0.000603927,0.00034734627,0.002562258],"genre_scores_gemma":[0.90593535,0.0008569034,0.09188656,0.000060810067,0.000010200026,0.00006453818,0.0002872197,0.00018439036,0.00071405346],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999782,0.000053659394,0.000015359488,0.00006912242,0.000052172603,0.000027630025],"domain_scores_gemma":[0.9993734,0.00015941635,0.00022494819,0.00010601123,0.00009292636,0.000043349708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055420963,0.000386753,0.00028935418,0.0015789722,0.00033254022,0.0013449346,0.00032753372,0.000427712,0.001047952],"category_scores_gemma":[0.0012488259,0.0004083015,0.00026577557,0.00064209284,0.0008100615,0.00089399784,0.0010946247,0.00048643758,0.00022129208],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024834272,0.00003245423,0.02201746,0.00040071408,0.00017098615,0.00045212472,0.00237828,0.009445212,0.911642,0.004205882,0.00026298297,0.048743535],"study_design_scores_gemma":[0.000032788917,0.0003986288,0.6528074,0.0004264217,0.0003523756,0.0036026426,0.0021690307,0.052940305,0.24928759,0.020262266,0.017468141,0.00025238952],"about_ca_topic_score_codex":0.0024556373,"about_ca_topic_score_gemma":0.006273849,"teacher_disagreement_score":0.0024556373,"about_ca_system_score_codex":0.00030992928,"about_ca_system_score_gemma":0.00044121232,"threshold_uncertainty_score":0.0048826933},"labels":[],"label_agreement":null},{"id":"W4408061889","doi":"10.7554/elife.94917.3.sa3","title":"Author response: Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bridging (networking); White matter; Evolutionary biology; Geography; Biology; Computer science; Medicine","score_opus":0.09015636814630748,"score_gpt":0.395265702107038,"score_spread":0.3051093339607305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408061889","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018506232,0.002708055,0.0024268897,0.71431804,0.25056082,0.00020008736,0.0025321762,0.00078170066,0.024621654],"genre_scores_gemma":[0.04019403,0.009288211,0.0042290813,0.3743809,0.103470504,0.00048360368,0.0035906772,0.0013500974,0.46301296],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.995889,0.0010197345,0.00032442523,0.0005663531,0.0018005988,0.00039987496],"domain_scores_gemma":[0.95259166,0.012647982,0.001958158,0.0020097103,0.027365774,0.0034267385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005693039,0.00068946136,0.00086324173,0.0010907057,0.0017089173,0.0029845126,0.0012363737,0.0063912966,0.16964132],"category_scores_gemma":[0.076547064,0.00034545668,0.00067967933,0.0007773645,0.0015744923,0.002106538,0.0027608199,0.004754442,0.0665723],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007544268,0.0000048112715,0.000186072,0.00027161813,0.00001003482,0.000109707646,0.00010600385,0.000050064027,0.00022425718,0.0009761965,0.98831916,0.0096666375],"study_design_scores_gemma":[0.00004857449,0.000037791557,0.0011001988,0.00038991173,0.000015056202,0.00025191187,0.0006291905,0.00015175759,0.0005198538,0.0026501722,0.99417216,0.000033463206],"about_ca_topic_score_codex":0.003245558,"about_ca_topic_score_gemma":0.0070801754,"teacher_disagreement_score":0.16964132,"about_ca_system_score_codex":0.001566747,"about_ca_system_score_gemma":0.0057708495,"threshold_uncertainty_score":0.56750673},"labels":[],"label_agreement":null},{"id":"W4408076912","doi":"10.1016/j.dcn.2025.101540","title":"White matter microstructure in school-age children with down syndrome","year":2025,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Psychology; White matter; White (mutation); Developmental psychology; Magnetic resonance imaging; Medicine; Chemistry","score_opus":0.018783958102442145,"score_gpt":0.3019772539410905,"score_spread":0.28319329583864833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408076912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993844,0.00020146956,0.00004719451,0.000014723523,0.0000031006264,0.0000049853966,0.00014373877,0.000007727589,0.00019269733],"genre_scores_gemma":[0.99905986,0.0002688652,0.00016790401,0.000025312658,0.0000039148053,0.0000109826,0.00024339963,0.000004474132,0.00021520334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998012,0.00002251689,0.000021914635,0.000066890476,0.00004688816,0.000040569073],"domain_scores_gemma":[0.99953747,0.000050539864,0.00019799675,0.000031328855,0.00009765953,0.00008498323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033364596,0.00048900547,0.00038989703,0.0017004157,0.0004181225,0.0006062392,0.00019856876,0.00041704453,0.0011937403],"category_scores_gemma":[0.00093258097,0.00033416678,0.00029993872,0.0005651297,0.00055946026,0.00046412056,0.0004347173,0.00038076701,0.00029445192],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002781176,0.00009316954,0.975932,0.00006344861,0.00012351367,0.0014025494,0.0012301565,0.00009067781,0.013662059,0.00006167835,0.0002586163,0.0068040057],"study_design_scores_gemma":[0.0000029424773,0.00005323204,0.99887234,0.000004167178,0.000013076835,0.00050099456,0.00018348658,0.000018071572,0.00024367396,0.000016447357,0.00008944964,0.0000021382739],"about_ca_topic_score_codex":0.012548637,"about_ca_topic_score_gemma":0.012804436,"teacher_disagreement_score":0.012548637,"about_ca_system_score_codex":0.00050919194,"about_ca_system_score_gemma":0.00029138784,"threshold_uncertainty_score":0.02495116},"labels":[],"label_agreement":null},{"id":"W4408099246","doi":"10.1073/pnas.2412160122","title":"Curve-fitting alone cannot validate neutral theory","year":2025,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Curve fitting; Mathematics; Statistics","score_opus":0.11205389369712819,"score_gpt":0.38933975755917816,"score_spread":0.27728586386204995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408099246","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024952858,0.001031923,0.009894219,0.9612419,0.013167423,0.000031726784,0.00012235726,0.00014561885,0.011869536],"genre_scores_gemma":[0.13696627,0.0024530182,0.018465856,0.7829122,0.049448416,0.0001963486,0.00030230804,0.00029468868,0.008960974],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98981583,0.0036209784,0.00087648537,0.001174145,0.0037587516,0.0007538056],"domain_scores_gemma":[0.86012596,0.112557426,0.002719798,0.008015546,0.013680823,0.0029004149],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.023994962,0.0008000653,0.0017985556,0.001281333,0.0020428046,0.0042429934,0.0043986407,0.023860015,0.010145379],"category_scores_gemma":[0.19842027,0.00046723514,0.00134987,0.00080609246,0.00816963,0.006086311,0.002090201,0.03016681,0.008510043],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043215926,0.00018922694,0.006202173,0.00028020053,0.00023411619,0.0051075392,0.0006279523,0.0015468596,0.0005483555,0.16083108,0.7086956,0.115304805],"study_design_scores_gemma":[0.0002697045,0.00013547724,0.0016974626,0.0005480438,0.00010426056,0.0037182556,0.000856677,0.011434328,0.0012111515,0.6963239,0.28358436,0.000116432035],"about_ca_topic_score_codex":0.002231371,"about_ca_topic_score_gemma":0.0023879418,"teacher_disagreement_score":0.976005,"about_ca_system_score_codex":0.0024910388,"about_ca_system_score_gemma":0.0036162678,"threshold_uncertainty_score":0.126899},"labels":[],"label_agreement":null},{"id":"W4408105333","doi":"10.1016/j.jad.2025.03.005","title":"Modulation of cerebellar homotopic connectivity by modified electroconvulsive therapy at rest: Study of first-episode, drug-naive adolescent major depressive disorder","year":2025,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Health and Family Planning Commission of Hubei Province; Department of Science and Technology, Hubei Provincial People's Government; Institute of Clinical and Translational Sciences; Health Commission of Hubei Province; McGill University","keywords":"Electroconvulsive therapy; Drug-naïve; Major depressive disorder; Psychology; Neuroscience; Drug; Cerebellum; Medicine; Psychiatry; Cognition","score_opus":0.01462537213739195,"score_gpt":0.31399185662286694,"score_spread":0.299366484485475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408105333","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996754,0.000060009603,0.00003648427,0.000016542806,0.000002985176,0.000018629418,0.000031035786,0.0000011686661,0.00015768563],"genre_scores_gemma":[0.9996001,0.00008299502,0.00005209083,0.000026074753,0.000006034784,0.000018428032,0.000051757965,0.0000012623177,0.00016119477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999126,0.00003328986,0.000005042278,0.000019544696,0.0000112592215,0.00001837759],"domain_scores_gemma":[0.9998698,0.00003412029,0.000030047022,0.000012888798,0.000011272469,0.000041789503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014880032,0.000381098,0.0005434246,0.00017807848,0.00023198726,0.00031049357,0.00032909872,0.00033776346,0.001152425],"category_scores_gemma":[0.00046013482,0.00015585673,0.00014156084,0.00019700667,0.00037847494,0.00017431915,0.0001457722,0.0004300534,0.000097168384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.14763238,0.020396534,0.42035827,0.00052368804,0.0018148748,0.005132114,0.0015705152,0.001516431,0.31496403,0.00051667675,0.0012722174,0.08430233],"study_design_scores_gemma":[0.0014572365,0.010795056,0.98276615,0.000009473921,0.00019894645,0.000662723,0.00027814842,0.0011235737,0.0023101962,0.00009880031,0.00028510403,0.000014524303],"about_ca_topic_score_codex":0.005619512,"about_ca_topic_score_gemma":0.014139945,"teacher_disagreement_score":0.005619512,"about_ca_system_score_codex":0.00042006094,"about_ca_system_score_gemma":0.00031591454,"threshold_uncertainty_score":0.011173606},"labels":[],"label_agreement":null},{"id":"W4408111203","doi":"10.1101/2025.02.27.25322897","title":"Leveraging multimodal neuroimaging and GWAS for identifying modality-level causal pathways to Alzheimer’s disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Public Health Ontario; University of Toronto","funders":"National Heart, Lung, and Blood Institute; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Hjartavernd; Connaught Fund; Simon Fraser University; Krembil Foundation; University of Toronto; Erasmus Medisch Centrum; Bundesministerium für Bildung und Forschung; Institut National de la Santé et de la Recherche Médicale; Université de Lille; Canadian Institutes of Health Research; Centre hospitalier régional universitaire de Lille; Centre for Addiction and Mental Health Foundation; Wellcome Trust; Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer's disease; National Institute on Aging; Alzheimer's Association","keywords":"Imaging genetics; Biobank; Neuroimaging; Genome-wide association study; Modality (human–computer interaction); Mendelian randomization; Causality (physics); Genetic association; Genomics; Psychology; Computer science; Data science; Computational biology; Neuroscience; Biology; Genetic variants; Bioinformatics; Artificial intelligence; Genetics; Genome; Gene; Single-nucleotide polymorphism","score_opus":0.2798626862278928,"score_gpt":0.4197805164507116,"score_spread":0.13991783022281884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408111203","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16353345,0.0022809303,0.81594783,0.003299413,0.00020236945,0.0001715716,0.007835253,0.004193687,0.002535427],"genre_scores_gemma":[0.7543449,0.0010394675,0.23676318,0.000658372,0.00040677993,0.00023073507,0.004273112,0.00051734544,0.0017660231],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978383,0.0013137636,0.00013815296,0.00041484265,0.0001836636,0.00011132017],"domain_scores_gemma":[0.9905191,0.0069749425,0.0007172757,0.0012605423,0.00030536647,0.00022274436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064904243,0.0008143833,0.000984474,0.0026898424,0.0004235624,0.0013401046,0.00080308854,0.00073360995,0.006004307],"category_scores_gemma":[0.02798155,0.000437932,0.0017862789,0.002500551,0.0005955084,0.0007689107,0.0015560448,0.0010141805,0.00068477215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019148841,0.00026939026,0.43460196,0.0009487485,0.005995378,0.003396109,0.0007686754,0.038122375,0.013467391,0.03638282,0.026635192,0.43749702],"study_design_scores_gemma":[0.0005985024,0.0005461625,0.21129003,0.00030016442,0.0032845482,0.0031122828,0.00035600766,0.4498716,0.009548598,0.29533985,0.025534345,0.00021794681],"about_ca_topic_score_codex":0.0046887826,"about_ca_topic_score_gemma":0.0052616736,"teacher_disagreement_score":0.0064904243,"about_ca_system_score_codex":0.0002678909,"about_ca_system_score_gemma":0.0009459102,"threshold_uncertainty_score":0.034325063},"labels":[],"label_agreement":null},{"id":"W4408120172","doi":"10.21037/qims-24-1516","title":"White matter microstructural alterations are associated with cognitive decline in benzodiazepine use disorders: a multi-shell diffusion magnetic resonance imaging study","year":2025,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Magnetic resonance imaging; Diffusion MRI; Shell (structure); Benzodiazepine; Cognition; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion; Medicine; Nuclear magnetic resonance; Neuroscience; Psychology; Psychiatry; Materials science; Physics; Internal medicine; Radiology","score_opus":0.061787237893749826,"score_gpt":0.3723903835233813,"score_spread":0.3106031456296314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408120172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996288,0.00014172077,0.00006519718,0.000012829849,9.57066e-7,0.0000057854472,0.000049081333,0.0000012837602,0.000094347706],"genre_scores_gemma":[0.9996501,0.0000714205,0.00011543301,0.000007888068,0.0000039274532,0.000004182088,0.00007776748,8.020532e-7,0.00006846665],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99992657,0.000011656308,0.000013187018,0.000021755552,0.0000147941055,0.000012060649],"domain_scores_gemma":[0.9995597,0.000061468716,0.00022211543,0.000028062776,0.00005873418,0.00006992225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002646821,0.0003219552,0.00022506264,0.0008927836,0.0003138405,0.00034133263,0.00017045782,0.00025426742,0.00086842483],"category_scores_gemma":[0.0008417824,0.00017716442,0.00028689404,0.00041615317,0.00026470862,0.00031047844,0.00038976732,0.00024295611,0.00012349346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044966064,0.000065365144,0.9931785,0.000033114135,0.0001066873,0.00042360998,0.00020807101,0.000068596615,0.0023513888,0.000018397162,0.000042139807,0.0030545315],"study_design_scores_gemma":[0.0000083816,0.00010023999,0.9987816,0.000005180031,0.000035425834,0.0004911359,0.00012673903,0.00024121154,0.00013164064,0.000022867729,0.000052844378,0.0000027250207],"about_ca_topic_score_codex":0.0055361856,"about_ca_topic_score_gemma":0.008342426,"teacher_disagreement_score":0.0055361856,"about_ca_system_score_codex":0.00026802605,"about_ca_system_score_gemma":0.00022000623,"threshold_uncertainty_score":0.011007965},"labels":[],"label_agreement":null},{"id":"W4408126894","doi":"10.1002/mrm.30436","title":"<scp>3D MERMAID</scp> : <scp>3D</scp> Multi‐shot enhanced recovery motion artifact insensitive diffusion for submillimeter, multi‐shell, and <scp>SNR</scp> ‐efficient diffusion imaging","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Imaging phantom; Flip angle; Physics; Pulse sequence; Artifact (error); Scanner; Optics; Single shot; Diffusion; Nuclear magnetic resonance; Materials science; Computer science; Computer vision; Magnetic resonance imaging","score_opus":0.03692552816653036,"score_gpt":0.3238531735608782,"score_spread":0.2869276453943479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408126894","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22086756,0.0014648479,0.7183105,0.0014467427,0.0003744737,0.0004961276,0.0029482336,0.015290148,0.038801413],"genre_scores_gemma":[0.42687112,0.00042061458,0.552177,0.00040737478,0.0000691105,0.00039593034,0.003038868,0.0016126775,0.0150073385],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99990296,0.000014178175,0.000004312601,0.000013520241,0.000056858484,0.000008182723],"domain_scores_gemma":[0.99965274,0.000042346364,0.000058315665,0.00006181789,0.00013769955,0.0000470191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003923676,0.0005304405,0.0002218879,0.00035409964,0.0002048875,0.0005198514,0.00066133175,0.0005786844,0.005859136],"category_scores_gemma":[0.00054133526,0.00029483062,0.00017641581,0.000264227,0.00031887752,0.00054275244,0.00047033638,0.0005264056,0.0014203334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007245259,0.0001304508,0.00093561783,0.00040796658,0.00007978663,0.0010580173,0.00011698128,0.026916863,0.84940547,0.014090452,0.027918328,0.07821549],"study_design_scores_gemma":[0.00015786798,0.0004651096,0.0036079146,0.00005212337,0.000034177894,0.002357562,0.00003059506,0.28884163,0.62200725,0.0025335138,0.07978436,0.00012792784],"about_ca_topic_score_codex":0.001189842,"about_ca_topic_score_gemma":0.0026225022,"teacher_disagreement_score":0.005859136,"about_ca_system_score_codex":0.0003983175,"about_ca_system_score_gemma":0.00060858094,"threshold_uncertainty_score":0.019600749},"labels":[],"label_agreement":null},{"id":"W4408161681","doi":"10.1002/mrm.30435","title":"Considerations and recommendations from the <scp>ISMRM</scp> diffusion study group for preclinical diffusion <scp>MRI</scp> : Part 2—Ex vivo imaging: Added value and acquisition","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Drug Abuse; National Institute on Aging; National Cancer Institute; Generalitat de Catalunya; National Institutes of Health; Vlaamse regering; Fonds Wetenschappelijk Onderzoek; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Ex vivo; Diffusion; In vivo; Diffusion MRI; Diffusion imaging; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Nuclear medicine; Medicine; In vitro; Physics; Biochemistry; Biology; Radiology; Thermodynamics","score_opus":0.04485616966101895,"score_gpt":0.3638918068535761,"score_spread":0.3190356371925571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408161681","genre_codex":"commentary","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016732764,0.058697347,0.04817078,0.75074416,0.04002388,0.0049220254,0.0047261133,0.0035915663,0.08745091],"genre_scores_gemma":[0.008789296,0.10601787,0.29060045,0.45404306,0.019236386,0.012897123,0.008896201,0.0022865294,0.09723313],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.95138025,0.018280849,0.007347539,0.001724733,0.019215887,0.0020508412],"domain_scores_gemma":[0.7623302,0.06384557,0.015192817,0.011921762,0.12875398,0.017955774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07755635,0.001977199,0.0022249436,0.004862943,0.0025274085,0.0071839183,0.010816275,0.0248942,0.021415876],"category_scores_gemma":[0.16137709,0.0017588239,0.0034500316,0.003944899,0.004364698,0.0071542347,0.0049568587,0.017230483,0.044415917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011633094,0.00019539204,0.00033571647,0.001553696,0.000031005744,0.0002851216,0.00026305014,0.00050326163,0.001384384,0.004532122,0.8954203,0.095379665],"study_design_scores_gemma":[0.00009961771,0.00012477225,0.00075382186,0.0055256663,0.000070473,0.00039155458,0.0003603518,0.00029424217,0.00111815,0.007575485,0.9835898,0.00009599191],"about_ca_topic_score_codex":0.012200395,"about_ca_topic_score_gemma":0.016600026,"teacher_disagreement_score":0.07755635,"about_ca_system_score_codex":0.0040206676,"about_ca_system_score_gemma":0.03829068,"threshold_uncertainty_score":0.4101621},"labels":[],"label_agreement":null},{"id":"W4408229559","doi":"10.1101/2025.03.06.641646","title":"The relationship of white matter tract orientation to vascular geometry in the human brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Wellcome Trust","keywords":"White matter; Orientation (vector space); Geometry; Human brain; White (mutation); Geology; Psychology; Mathematics; Neuroscience; Medicine; Biology","score_opus":0.03911334127865196,"score_gpt":0.32078400047885086,"score_spread":0.2816706592001989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408229559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99222696,0.00035517302,0.0054099425,0.000052574283,0.000007299804,0.000017144883,0.00023621443,0.000059769547,0.0016350157],"genre_scores_gemma":[0.9969959,0.00021084551,0.0023267658,0.0000109194625,0.000010023817,0.000006202776,0.0001383645,0.000029609799,0.00027151237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977154,0.00007130986,0.000016486421,0.000074365664,0.000043265685,0.000023033037],"domain_scores_gemma":[0.99885345,0.00029611983,0.00049418135,0.00014682248,0.00013992233,0.00006957881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037498111,0.00018359261,0.00015588957,0.00096051075,0.00016030124,0.00068598706,0.00010426652,0.00023403339,0.0011201916],"category_scores_gemma":[0.0034578883,0.00016324897,0.000101779864,0.00071001984,0.00043848465,0.0003205381,0.00021181628,0.00011942171,0.00031836476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009037116,0.000065497115,0.748112,0.00011894111,0.00040116571,0.0007609873,0.0012949781,0.0077962894,0.15325412,0.0020524468,0.0010531512,0.08418662],"study_design_scores_gemma":[0.0000035947724,0.00006474291,0.99229175,0.000007844339,0.000025495847,0.0008747506,0.00010565085,0.0025774096,0.0026355875,0.00088115624,0.0005174254,0.000014600277],"about_ca_topic_score_codex":0.003028955,"about_ca_topic_score_gemma":0.0041620387,"teacher_disagreement_score":0.003028955,"about_ca_system_score_codex":0.00017100465,"about_ca_system_score_gemma":0.0002268551,"threshold_uncertainty_score":0.006022632},"labels":[],"label_agreement":null},{"id":"W4408250548","doi":"10.1016/j.neurobiolaging.2025.03.003","title":"Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer's disease","year":2025,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital; Université de Montréal; Concordia University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Disease; Family history; Medicine; White (mutation); White matter; Gerontology; Psychology; Internal medicine; Genetics; Biology; Gene; Magnetic resonance imaging","score_opus":0.03910536625496768,"score_gpt":0.2980154925984705,"score_spread":0.2589101263435028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408250548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987802,0.00048976217,0.00014321032,0.000033611766,0.000008758225,0.0000035057383,0.0001507247,0.0000046987407,0.00038541283],"genre_scores_gemma":[0.9992995,0.00011193714,0.00010826447,0.000016662614,0.000009137955,0.0000027726696,0.000103627266,0.0000026273274,0.00034530926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998584,0.000026018613,0.000017592989,0.000054205317,0.000019783387,0.000023995884],"domain_scores_gemma":[0.999635,0.000064136184,0.00016582313,0.00004911455,0.00003840547,0.000047481855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000376047,0.00028631062,0.0002088339,0.00049093366,0.00025319017,0.00044119847,0.00017544068,0.00032855573,0.002383238],"category_scores_gemma":[0.0010812028,0.00012415751,0.0004109627,0.0003981812,0.0001623522,0.00016349931,0.00027937602,0.00023992511,0.0002014658],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004284066,0.000027402806,0.9913748,0.000021369777,0.00022987847,0.00020419198,0.000116270654,0.00005278423,0.0017437614,0.000049884875,0.000081855935,0.0056693796],"study_design_scores_gemma":[0.0000024672552,0.000040830808,0.9992095,0.000003900998,0.000047337468,0.00025012094,0.000050265542,0.00011227868,0.00011472259,0.0000748107,0.00009160887,0.0000020829143],"about_ca_topic_score_codex":0.0026967572,"about_ca_topic_score_gemma":0.0044142776,"teacher_disagreement_score":0.0026967572,"about_ca_system_score_codex":0.0001021467,"about_ca_system_score_gemma":0.00018982381,"threshold_uncertainty_score":0.007972717},"labels":[],"label_agreement":null},{"id":"W4408252633","doi":"10.1101/2025.02.27.640654","title":"<i>Ex vivo</i> human brain volumetry: validation of magnetic resonance imaging measurements","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute; Université du Québec à Trois-Rivières","funders":"","keywords":"Magnetic resonance imaging; Gold standard (test); Ex vivo; Nuclear medicine; Automated method; Biomedical engineering; Segmentation; In vivo; White matter; Atrophy; Medicine; Artificial intelligence; Pathology; Computer science; Radiology; Biology","score_opus":0.04392171318554433,"score_gpt":0.3041903960060731,"score_spread":0.2602686828205288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408252633","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45546407,0.0024184291,0.5332279,0.0003523767,0.00025911783,0.000303832,0.0029795042,0.0017282572,0.0032665085],"genre_scores_gemma":[0.8025583,0.0007982853,0.19093919,0.00028603472,0.00010479677,0.00047559224,0.0030439617,0.00049120537,0.0013026313],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979159,0.0009064511,0.00023219433,0.0004967283,0.00038534237,0.00006338464],"domain_scores_gemma":[0.99485624,0.0013565856,0.00071801094,0.0016160748,0.0013533958,0.00009966356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043228115,0.00092262006,0.00036639828,0.00067864504,0.00041667896,0.00092080387,0.0012523165,0.0007039292,0.0015755061],"category_scores_gemma":[0.0063281483,0.00032250935,0.00034327857,0.00042789977,0.0011955468,0.0005737962,0.00081790984,0.00043557413,0.0007862115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006701055,0.00017642768,0.0325953,0.000820197,0.0004022733,0.00031599103,0.0005718607,0.005950285,0.90058315,0.0012979271,0.0022544912,0.05436197],"study_design_scores_gemma":[0.00008599086,0.0012768133,0.13968547,0.00015079795,0.00033335312,0.0041866237,0.00025933134,0.0254671,0.8163229,0.0019377073,0.01016963,0.00012418185],"about_ca_topic_score_codex":0.00097517855,"about_ca_topic_score_gemma":0.0014810023,"teacher_disagreement_score":0.0043228115,"about_ca_system_score_codex":0.00024147604,"about_ca_system_score_gemma":0.00034853662,"threshold_uncertainty_score":0.02286148},"labels":[],"label_agreement":null},{"id":"W4408293277","doi":"10.52294/001c.130075","title":"Understanding variability in brain MRI templates: Optimal sample sizes for representative population averages","year":2025,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Canada First Research Excellence Fund; McGill University","keywords":"Template; Sample (material); Sample size determination; Population; Computer science; Statistics; Artificial intelligence; Mathematics; Medicine; Chromatography; Chemistry","score_opus":0.13109705640806182,"score_gpt":0.40271285709053734,"score_spread":0.2716158006824755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408293277","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.084335595,0.0003515862,0.9132704,0.00024305399,0.000053309202,0.00037371245,0.00020021507,0.000568938,0.0006032081],"genre_scores_gemma":[0.46513572,0.00020233303,0.531774,0.0001668696,0.000070223345,0.0014132581,0.00071462145,0.00025396116,0.0002690449],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9915115,0.005518829,0.0004928034,0.0014818764,0.00084967905,0.0001452356],"domain_scores_gemma":[0.90773726,0.079088286,0.002388272,0.0067120455,0.0036021238,0.0004720004],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.032825056,0.0004987952,0.0009599728,0.0010391645,0.00050370034,0.0011589188,0.0012319225,0.0015476517,0.0012082942],"category_scores_gemma":[0.15929677,0.0004349818,0.0007555989,0.00081378716,0.001136779,0.0019112891,0.0012668142,0.0011455968,0.00033817103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029445828,0.00054978585,0.059189383,0.0010415168,0.0010197462,0.00064345537,0.004626719,0.16443308,0.04622698,0.04036399,0.007780937,0.6711799],"study_design_scores_gemma":[0.00055184896,0.0017207471,0.057064146,0.0003309277,0.00049947965,0.0011840899,0.00083338947,0.7687234,0.03637965,0.12320765,0.009336528,0.00016819291],"about_ca_topic_score_codex":0.00072841096,"about_ca_topic_score_gemma":0.00088265934,"teacher_disagreement_score":0.96717495,"about_ca_system_score_codex":0.0004066035,"about_ca_system_score_gemma":0.0008053109,"threshold_uncertainty_score":0.17359757},"labels":[],"label_agreement":null},{"id":"W4408528886","doi":"10.1002/hbm.70188","title":"White Matter Microstructure Among Straight and Gay Cisgender Men, <i>Sao Praphet Song</i>, and Straight Cisgender Women in Thailand","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Centre for Addiction and Mental Health; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Corpus callosum; White matter; Cingulum (brain); Psychology; Diffusion MRI; Corona radiata (embryology); Population; Generalizability theory; Superior longitudinal fasciculus; Developmental psychology; Demography; Neuroscience; Medicine; Internal medicine; Sociology; Magnetic resonance imaging; Hormone","score_opus":0.03375090106925206,"score_gpt":0.31570396658989275,"score_spread":0.2819530655206407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408528886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99971086,0.000054086562,0.000022135753,0.000008929889,0.0000010732276,0.000003024801,0.00005131769,7.0931554e-7,0.00014791444],"genre_scores_gemma":[0.9995939,0.0000711984,0.00005746937,0.000013587611,0.0000018537474,0.000004948737,0.00007717009,9.294739e-7,0.00017886239],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999255,0.0000121921585,0.000009389752,0.000024642442,0.000010815075,0.000017395561],"domain_scores_gemma":[0.9998375,0.000015074972,0.00006826515,0.00000959868,0.000019525512,0.00004997849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012812873,0.0002249841,0.00014939558,0.00046493777,0.0005434474,0.00054508983,0.00013897284,0.00018821958,0.0010169728],"category_scores_gemma":[0.00039277383,0.00020901239,0.00016344569,0.0004458221,0.0004436972,0.0002995395,0.00044007212,0.00018746876,0.00013672141],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038883442,0.000049039518,0.97756755,0.00007490432,0.0000728757,0.00086037535,0.007591092,0.00006334479,0.00563583,0.000076400094,0.00013327274,0.0074863215],"study_design_scores_gemma":[0.000004860054,0.00011501181,0.99399936,0.000012050518,0.000019886467,0.0006491849,0.0047122743,0.00009883371,0.00020234908,0.00004202857,0.00013812305,0.00000600247],"about_ca_topic_score_codex":0.014374429,"about_ca_topic_score_gemma":0.021974659,"teacher_disagreement_score":0.014374429,"about_ca_system_score_codex":0.00020881837,"about_ca_system_score_gemma":0.00023658946,"threshold_uncertainty_score":0.02858156},"labels":[],"label_agreement":null},{"id":"W4408548800","doi":"10.1080/10255842.2025.2472015","title":"Is a 3D representation of muscle architecture needed to model craniomaxillofacial skeletal mechanics?","year":2025,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Sunnybrook Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Representation (politics); Architecture; Computer science; Skeletal muscle; Medicine; Geography; Anatomy; Political science","score_opus":0.05397550222691014,"score_gpt":0.4128762470811565,"score_spread":0.3589007448542464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408548800","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06648509,0.0011349424,0.92034036,0.0019797946,0.0002043095,0.000103699,0.0012930502,0.00088102126,0.0075777206],"genre_scores_gemma":[0.6954896,0.00508361,0.29189193,0.00083095033,0.00012796401,0.00042145245,0.0014319589,0.00041003994,0.0043125134],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998605,0.00002906592,0.000009431122,0.000028283832,0.000059129816,0.000013602905],"domain_scores_gemma":[0.99978906,0.00005552407,0.000038999504,0.000047904286,0.0000504978,0.000017969916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030774102,0.00052092003,0.0004522322,0.00045252347,0.0002478711,0.0013421911,0.00094038463,0.0014050076,0.0018932826],"category_scores_gemma":[0.0014983574,0.0006522295,0.00062630995,0.000384384,0.0007208384,0.0011704118,0.0005349796,0.0005748991,0.0011862507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000087552035,0.00014041878,0.010552266,0.00052954187,0.00013120151,0.00066754787,0.00047540676,0.67919844,0.08459988,0.051234905,0.0075927963,0.16479011],"study_design_scores_gemma":[0.000017789127,0.00006820641,0.0041634683,0.00011597324,0.000044713586,0.00057007675,0.00020496426,0.9514488,0.0049356055,0.01451132,0.023865301,0.000053767253],"about_ca_topic_score_codex":0.0061174124,"about_ca_topic_score_gemma":0.007985562,"teacher_disagreement_score":0.0061174124,"about_ca_system_score_codex":0.00031869518,"about_ca_system_score_gemma":0.0008365494,"threshold_uncertainty_score":0.012163579},"labels":[],"label_agreement":null},{"id":"W4408560758","doi":"10.1162/imag_a_00526","title":"Microstructure-informed brain tissue classification using clustering of quantitative MRI measures","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada; Canadian Institutes of Health Research; Biogen; Sanofi","keywords":"White matter; Magnetic resonance imaging; Voxel; Brain tissue; Fractional anisotropy; Cluster analysis; Multiple sclerosis; Pathology; Segmentation; Medicine; Diffusion MRI; Pathological; Artificial intelligence; Computer science; Pattern recognition (psychology); Radiology; Biomedical engineering","score_opus":0.11966148007359705,"score_gpt":0.45276459835472965,"score_spread":0.3331031182811326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408560758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11281896,0.00040961604,0.8843899,0.00014284895,0.00002680637,0.00019473847,0.00022620325,0.0008225031,0.0009683524],"genre_scores_gemma":[0.6722544,0.00023520626,0.32582554,0.00005989826,0.00004255539,0.00020102448,0.00060649595,0.00017104679,0.00060386094],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988398,0.00032146223,0.00008787383,0.00037277042,0.00027766454,0.00010041365],"domain_scores_gemma":[0.9981623,0.00056509086,0.00036029043,0.00030681965,0.0005404426,0.00006503024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029716105,0.0008409539,0.0009465219,0.003923394,0.0004616246,0.0014461481,0.0008046596,0.0008928525,0.00053900905],"category_scores_gemma":[0.0058543882,0.00044126261,0.0009798473,0.0018824178,0.0007753773,0.0009767956,0.000894732,0.000565054,0.00033831745],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088544306,0.00030959485,0.02885467,0.0004868152,0.0007650017,0.0002972113,0.0009218907,0.29628637,0.15626118,0.008463457,0.0030514086,0.50341696],"study_design_scores_gemma":[0.000040923478,0.00018076408,0.032892127,0.000043730186,0.00011394885,0.0002448618,0.00019158555,0.9310283,0.020017006,0.013622868,0.0014982304,0.00012559013],"about_ca_topic_score_codex":0.004360438,"about_ca_topic_score_gemma":0.004567211,"teacher_disagreement_score":0.004360438,"about_ca_system_score_codex":0.0008575337,"about_ca_system_score_gemma":0.0007545552,"threshold_uncertainty_score":0.01571554},"labels":[],"label_agreement":null},{"id":"W4408646494","doi":"10.1186/s41747-025-00570-5","title":"Connectivity related to major brain functions in Alzheimer disease progression: microstructural properties of the cingulum bundle and its subdivision using diffusion-weighted MRI","year":2025,"lang":"en","type":"article","venue":"European Radiology Experimental","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; University of Southern California; BioClinica; Bristol-Myers Squibb; Eli Lilly and Company; Biogen","keywords":"Cingulum (brain); Diffusion MRI; Neuroscience; Fractional anisotropy; Tractography; White matter; Psychology; Uncinate fasciculus; Alzheimer's disease; Dementia; Medicine; Magnetic resonance imaging; Pathology; Radiology; Disease","score_opus":0.03494078093468672,"score_gpt":0.33986643232350067,"score_spread":0.30492565138881395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408646494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921674,0.00029716812,0.006801277,0.0000404551,0.0000019776944,0.000021495318,0.0003146198,0.00005098285,0.00030460517],"genre_scores_gemma":[0.9922707,0.00014273469,0.006783231,0.0000054038737,0.000004755645,0.00002098121,0.0006640429,0.000013455124,0.00009476261],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998895,0.000024992987,0.000008583527,0.000041022697,0.00002139585,0.000014475223],"domain_scores_gemma":[0.99956006,0.00014856375,0.00015862756,0.000042444724,0.00005284498,0.00003751196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053430337,0.00034471136,0.0002091681,0.0019527642,0.00031103424,0.0007286998,0.00017156304,0.00028529752,0.00044626708],"category_scores_gemma":[0.0018359447,0.0001496388,0.00036064367,0.0009171658,0.00028232328,0.00038184336,0.0003229823,0.00022042889,0.00009237549],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000990509,0.00012478203,0.7634426,0.00023734318,0.0006409995,0.00049362326,0.0012074012,0.027172469,0.0649193,0.0014434201,0.0012284494,0.13809906],"study_design_scores_gemma":[0.00002186699,0.000104633946,0.92719215,0.000045184235,0.00015588317,0.00064968603,0.0002276779,0.064007014,0.0046886797,0.0021672843,0.0007112923,0.00002865319],"about_ca_topic_score_codex":0.007784325,"about_ca_topic_score_gemma":0.015358626,"teacher_disagreement_score":0.007784325,"about_ca_system_score_codex":0.00034753693,"about_ca_system_score_gemma":0.00034198698,"threshold_uncertainty_score":0.015478075},"labels":[],"label_agreement":null},{"id":"W4408658106","doi":"10.1038/s41598-025-93033-1","title":"Gauge equivariant convolutional neural networks for diffusion MRI","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; Canadian Open Neuroscience Platform; Canada Research Chairs","keywords":"Diffusion MRI; Convolutional neural network; Equivariant map; Computer science; Tensor (intrinsic definition); Angular resolution (graph drawing); Artificial intelligence; Fractional anisotropy; SIGNAL (programming language); Pattern recognition (psychology); Physics; Algorithm; Mathematics; Geometry; Magnetic resonance imaging; Pure mathematics; Combinatorics","score_opus":0.04298510535479371,"score_gpt":0.3545560619039544,"score_spread":0.31157095654916067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408658106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018745402,0.0009819361,0.97638625,0.00032285566,0.00006454354,0.000023380895,0.00022396554,0.0012312796,0.002020408],"genre_scores_gemma":[0.5739137,0.0016460975,0.41348392,0.00025508497,0.00010774065,0.00013120298,0.0011986595,0.00033051558,0.008933105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998134,0.000041272157,0.0000110741385,0.00004791555,0.00006022826,0.00002624161],"domain_scores_gemma":[0.9996481,0.0001409337,0.000049866292,0.000059495575,0.00007802294,0.000023578004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005350811,0.0006874828,0.0004176471,0.0003708604,0.00018647594,0.0004315879,0.0007457937,0.00056799955,0.0013573897],"category_scores_gemma":[0.0020754298,0.00027371175,0.00046380455,0.0005104265,0.00048097185,0.0006041232,0.0006882731,0.001334807,0.0005371087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075573975,0.000044797023,0.0009736581,0.00009137599,0.00007999699,0.00008979512,0.00005227174,0.7497943,0.010819635,0.041347936,0.0040370673,0.19259363],"study_design_scores_gemma":[0.0000016484684,0.000008959033,0.00011662701,0.0000044593744,0.00000408289,0.000009722908,0.0000022039324,0.99089724,0.0011885486,0.0068330993,0.0009293001,0.0000041015055],"about_ca_topic_score_codex":0.0081864735,"about_ca_topic_score_gemma":0.012868199,"teacher_disagreement_score":0.0081864735,"about_ca_system_score_codex":0.00096743606,"about_ca_system_score_gemma":0.00073835254,"threshold_uncertainty_score":0.016277611},"labels":[],"label_agreement":null},{"id":"W4408743981","doi":"10.1007/s10334-025-01244-4","title":"Assessing measurement consistency of a diffusion tensor imaging (DTI) quality control (QC) anisotropy phantom","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre; Systems, Applications & Products in Data Processing (Canada); McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Imaging phantom; Diffusion MRI; Fractional anisotropy; Anisotropy; Consistency (knowledge bases); Nuclear magnetic resonance; Tractography; Tensor (intrinsic definition); Physics; Medicine; Magnetic resonance imaging; Computer science; Optics; Mathematics; Radiology; Artificial intelligence","score_opus":0.07346922782753491,"score_gpt":0.4073890482619861,"score_spread":0.3339198204344512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408743981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59263736,0.0015914794,0.3997219,0.00047476767,0.00018075407,0.00029440448,0.00056059466,0.0024561144,0.0020824785],"genre_scores_gemma":[0.9069531,0.00018317459,0.0909822,0.00016843899,0.000020609932,0.00011245136,0.00063681253,0.00052851613,0.0004146164],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9906583,0.0030493604,0.0013420506,0.0020842727,0.0025653113,0.00030078946],"domain_scores_gemma":[0.92459506,0.03828,0.009410483,0.009807613,0.017011855,0.00089493574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020667741,0.0006228025,0.0004806256,0.0017314111,0.000868693,0.0021224874,0.0012013706,0.0019088153,0.0009458106],"category_scores_gemma":[0.089076,0.0006896848,0.0005678204,0.0013836398,0.00131959,0.0011491424,0.0014228176,0.0007943745,0.00028395237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006877059,0.00086936774,0.27600563,0.0011110596,0.0022743065,0.0007684497,0.0034109035,0.080791555,0.40132016,0.0071073235,0.0034187816,0.21604544],"study_design_scores_gemma":[0.00037474738,0.0020589447,0.21579088,0.00028365757,0.001818048,0.003377049,0.0007044623,0.50891507,0.25397167,0.003760927,0.008625792,0.00031883354],"about_ca_topic_score_codex":0.0060161576,"about_ca_topic_score_gemma":0.0036123525,"teacher_disagreement_score":0.020667741,"about_ca_system_score_codex":0.000844572,"about_ca_system_score_gemma":0.0012920753,"threshold_uncertainty_score":0.10930282},"labels":[],"label_agreement":null},{"id":"W4408819125","doi":"10.1371/journal.pone.0304449","title":"A Riemannian framework for incorporating white matter bundle prior in orientation distribution function based tractography algorithms","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Computer science; Diffusion MRI; Bundle; Prior probability; Artificial intelligence; Connectome; Algorithm; Orientation (vector space); Fiber bundle; Context (archaeology); Parallelizable manifold; Voxel; Computer vision; Magnetic resonance imaging; Mathematics; Bayesian probability; Functional connectivity; Geometry; Biology; Neuroscience","score_opus":0.059503971055531006,"score_gpt":0.3293319319535799,"score_spread":0.2698279608980489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408819125","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013525634,0.000092820614,0.99794203,0.000051585354,0.000009151095,0.000013311297,0.00002333253,0.00032173432,0.00019346898],"genre_scores_gemma":[0.07066394,0.0003571208,0.9267301,0.00009288995,0.00006624846,0.000115773095,0.0002702614,0.00044498395,0.0012587322],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990081,0.00041506547,0.000068948866,0.00019158566,0.00026094963,0.000055412802],"domain_scores_gemma":[0.99829966,0.00069672236,0.00017712392,0.00028034017,0.000424004,0.00012223724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021189605,0.0013357876,0.001077767,0.0013456822,0.00051354757,0.0011576214,0.0015279694,0.0013451441,0.0013259314],"category_scores_gemma":[0.006414069,0.00076612015,0.001301181,0.001019702,0.0010322325,0.0019177053,0.0015859266,0.0019561946,0.000936203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080469414,0.000052202795,0.001241468,0.00018199638,0.00013248579,0.0002212296,0.00023866039,0.707921,0.013811762,0.05608923,0.003555377,0.21647409],"study_design_scores_gemma":[0.0000060965403,0.000030633753,0.00021108017,0.000009241733,0.000008380449,0.00005845413,0.0000060161597,0.9865262,0.001302795,0.009578805,0.0022470194,0.0000152534285],"about_ca_topic_score_codex":0.008350285,"about_ca_topic_score_gemma":0.008657202,"teacher_disagreement_score":0.008350285,"about_ca_system_score_codex":0.0011397353,"about_ca_system_score_gemma":0.0015349509,"threshold_uncertainty_score":0.01660335},"labels":[],"label_agreement":null},{"id":"W4409028149","doi":"10.1101/2025.03.26.645559","title":"Standardization of postmortem human brainstem along the rostrocaudal axis to accommodate for heterogeneity in samples","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"","keywords":"Brainstem; Standardization; Biology; Pathology; Neuroscience; Medicine; Computer science","score_opus":0.06053224548258985,"score_gpt":0.33899775684001415,"score_spread":0.2784655113574243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409028149","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3827807,0.0055239205,0.5922765,0.0003614605,0.00074582594,0.002165415,0.0049476423,0.0021994764,0.008999068],"genre_scores_gemma":[0.47808525,0.0034068555,0.4968203,0.00054507266,0.00017375674,0.0061843456,0.0076407604,0.0023281963,0.0048154662],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99754447,0.00042192443,0.00039957158,0.0009211042,0.00056079746,0.00015209761],"domain_scores_gemma":[0.99598986,0.00050683954,0.00062820927,0.0015279533,0.0012251302,0.000121928824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044437046,0.0008962307,0.00056619156,0.0020089909,0.0013795964,0.0013587738,0.0009695044,0.00091758533,0.0039356146],"category_scores_gemma":[0.0053886017,0.00075685827,0.00049954647,0.0012799419,0.0016329164,0.00078037195,0.0016819158,0.0011518889,0.0020161949],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089135236,0.00013459307,0.012494281,0.00080567074,0.00013917217,0.0004301531,0.0012279103,0.0019637647,0.9328835,0.0033686222,0.0018331726,0.04382788],"study_design_scores_gemma":[0.0001229308,0.0019759077,0.17194857,0.00067094935,0.00057663285,0.00291106,0.0011319328,0.0066982154,0.74961865,0.004701289,0.059492134,0.0001517638],"about_ca_topic_score_codex":0.0013588455,"about_ca_topic_score_gemma":0.0050024623,"teacher_disagreement_score":0.0044437046,"about_ca_system_score_codex":0.0005846516,"about_ca_system_score_gemma":0.0009371427,"threshold_uncertainty_score":0.02350086},"labels":[],"label_agreement":null},{"id":"W4409210508","doi":"10.1016/j.ejrad.2025.112098","title":"Diffusion MRI tractography with along-tract profiling reveals subtle neurodevelopmental differences between moderate and late preterm infants","year":2025,"lang":"en","type":"article","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"Calgary Health Foundation; Alberta Children's Hospital Research Institute; Alberta Children's Hospital Foundation; Koninklijke Nederlandse Akademie van Wetenschappen; Wellcome Trust","keywords":"Medicine; Diffusion MRI; Tractography; Profiling (computer programming); Magnetic resonance imaging; Radiology","score_opus":0.0346405438625101,"score_gpt":0.30299424609960107,"score_spread":0.268353702237091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409210508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99541533,0.00029259,0.003620316,0.000035894525,0.0000020224943,0.000006494755,0.00018693462,0.00003189193,0.00040841394],"genre_scores_gemma":[0.99589646,0.00023744893,0.0034046676,0.000011495049,0.0000024560088,0.000010016393,0.00020091735,0.000021048598,0.00021542072],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998155,0.00004443954,0.000026935699,0.00005268325,0.000034821267,0.000025620973],"domain_scores_gemma":[0.9993192,0.00012534256,0.00032541942,0.000080202175,0.00008073137,0.000069030415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051945314,0.00027788998,0.00016553167,0.0007051162,0.00016346455,0.0005341435,0.00019119763,0.0002762377,0.0010243133],"category_scores_gemma":[0.0023688022,0.00016366012,0.00019801156,0.00030849155,0.00026979405,0.00045375281,0.00046832967,0.00023273942,0.00019952774],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009821665,0.00004127617,0.7491977,0.00019136576,0.00018600396,0.0018525433,0.0009622328,0.00089040335,0.19113468,0.0006782681,0.00034701254,0.053536408],"study_design_scores_gemma":[0.0000037214309,0.0001216371,0.9790908,0.00005476447,0.000045597295,0.004184409,0.00028554405,0.0022327811,0.013044443,0.0003361866,0.0005907446,0.000009535262],"about_ca_topic_score_codex":0.002403969,"about_ca_topic_score_gemma":0.0044631907,"teacher_disagreement_score":0.002403969,"about_ca_system_score_codex":0.00023406128,"about_ca_system_score_gemma":0.00026305893,"threshold_uncertainty_score":0.004779935},"labels":[],"label_agreement":null},{"id":"W4409238054","doi":"10.1002/oby.24277","title":"Sex‐specific white matter alterations in children exposed to high pregestational <scp>BMI</scp>","year":2025,"lang":"en","type":"article","venue":"Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"Alberta Children's Hospital Research Institute; Jacobs Foundation","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Medicine; Overweight; White matter; Offspring; Body mass index; Pregnancy; Pediatrics; Endocrinology; Magnetic resonance imaging; Pathology; Biology","score_opus":0.02134412088106482,"score_gpt":0.2974359276915425,"score_spread":0.2760918068104777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409238054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99931896,0.00018710639,0.000039610593,0.000020523146,0.0000033454714,0.000002635419,0.00019208,0.000004340292,0.00023146614],"genre_scores_gemma":[0.99917895,0.00012817589,0.00008465537,0.000017611172,0.000003392,0.000003559053,0.00017766329,0.000002507366,0.00040355363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984646,0.000018086765,0.000007864106,0.000041165615,0.000039888317,0.00004645621],"domain_scores_gemma":[0.9995974,0.000024911265,0.00024990513,0.000020774221,0.000041961797,0.000065157714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020939717,0.00034168424,0.00020979825,0.00050748343,0.00030857834,0.0004618008,0.0001935986,0.00029892527,0.0016233657],"category_scores_gemma":[0.00047095705,0.0002055918,0.00025403986,0.0004691225,0.00024895396,0.00016000726,0.00028265157,0.00035815145,0.00012272595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014352765,0.000033636166,0.9937522,0.00001426941,0.000059880724,0.0002604359,0.00020043811,0.000024386218,0.003420355,0.000025365347,0.00008668403,0.0019788616],"study_design_scores_gemma":[5.6531644e-7,0.000020809726,0.9996705,0.0000015380986,0.0000055293312,0.000112996735,0.000044506207,0.000008486952,0.00008516908,0.0000043379737,0.000044999666,5.703173e-7],"about_ca_topic_score_codex":0.016921876,"about_ca_topic_score_gemma":0.025341455,"teacher_disagreement_score":0.016921876,"about_ca_system_score_codex":0.00028307337,"about_ca_system_score_gemma":0.0003735429,"threshold_uncertainty_score":0.033646762},"labels":[],"label_agreement":null},{"id":"W4409248602","doi":"10.1101/2025.04.07.25325401","title":"Diffusion MRI-based measures of neurite microstructure associate with future risk of Alzheimer’s Disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Alzheimer's disease; Diffusion MRI; Disease; Diffusion; Neurite; Medicine; Neuroscience; Psychology; Magnetic resonance imaging; Internal medicine; Chemistry; Radiology; Physics","score_opus":0.04320602276908402,"score_gpt":0.31993010434402014,"score_spread":0.2767240815749361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409248602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995539,0.0011667379,0.0007414253,0.000093430936,0.00001149215,0.0000063163293,0.0016364177,0.000023262786,0.00078183744],"genre_scores_gemma":[0.99668235,0.00038884272,0.0009838542,0.00001738567,0.000020209893,0.000009318354,0.0012898843,0.000007008025,0.0006012545],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998622,0.000025243922,0.00002331175,0.000049967242,0.00002367427,0.000015524249],"domain_scores_gemma":[0.99909115,0.00016769933,0.00042671702,0.00011092814,0.00012130484,0.00008214364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006091624,0.00038698385,0.00031080304,0.0009361329,0.00020056078,0.00057169347,0.00021685852,0.0003196217,0.002732284],"category_scores_gemma":[0.0019429233,0.00012098027,0.00026865568,0.0007291415,0.0002131331,0.00035951965,0.00035510943,0.00023322168,0.0003098734],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046174263,0.000041615887,0.9845904,0.00007707933,0.00038368587,0.00011366214,0.000090628615,0.00024326697,0.0040086186,0.00012289152,0.00048682332,0.009379569],"study_design_scores_gemma":[0.000006682967,0.0000409258,0.9976419,0.000013840867,0.00007115763,0.00037937725,0.000047818372,0.00038883457,0.00057688076,0.00046452406,0.00036320114,0.0000048550346],"about_ca_topic_score_codex":0.0022822525,"about_ca_topic_score_gemma":0.0032990777,"teacher_disagreement_score":0.002732284,"about_ca_system_score_codex":0.00017477233,"about_ca_system_score_gemma":0.00014679086,"threshold_uncertainty_score":0.009140372},"labels":[],"label_agreement":null},{"id":"W4409255900","doi":"10.1162/imag_a_00552","title":"Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; Servier; Georgia Clinical and Translational Science Alliance; Eisai; H. Lundbeck A/S; National Institute of Mental Health and Neurosciences; Pfizer; Biogen; BioClinica; Vanderbilt University; University of Southern California; National Institute of Dental and Craniofacial Research; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Diffusion MRI; Magnetic resonance imaging; Neuroimaging; Brain aging; Disease; Psychology; Neuroscience; Cognition; Medicine; Pathology; Radiology","score_opus":0.03237756794422935,"score_gpt":0.3517147861451662,"score_spread":0.31933721820093686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409255900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74491054,0.0060864007,0.24006003,0.0008419785,0.0002249973,0.0001089615,0.0026374094,0.0012635869,0.0038660776],"genre_scores_gemma":[0.92910373,0.0021369634,0.06384414,0.00016802693,0.00016620578,0.000065299566,0.002123286,0.000121927376,0.002270318],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99970007,0.000069946815,0.000023495591,0.00013693786,0.000040428215,0.000029210745],"domain_scores_gemma":[0.9990225,0.0003341868,0.00021614863,0.00012265728,0.0002456157,0.000058980157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015322857,0.0009059936,0.00064209715,0.0011524706,0.00020955755,0.0008508101,0.0004134002,0.000822979,0.00085640844],"category_scores_gemma":[0.0036958754,0.00028324453,0.0007390301,0.00036659848,0.00023993722,0.001090378,0.00066434284,0.0005890805,0.0006456176],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016108736,0.0002733492,0.2869342,0.0006406012,0.0008398169,0.00082641124,0.00081330095,0.09972218,0.0774071,0.0033306247,0.008826515,0.518775],"study_design_scores_gemma":[0.000053023057,0.0005483591,0.2438435,0.00026543226,0.00065239344,0.0031556804,0.00038281342,0.6831053,0.040691115,0.01698521,0.010137628,0.00017959205],"about_ca_topic_score_codex":0.0036590397,"about_ca_topic_score_gemma":0.0077766604,"teacher_disagreement_score":0.0036590397,"about_ca_system_score_codex":0.00025074507,"about_ca_system_score_gemma":0.00041083992,"threshold_uncertainty_score":0.008103609},"labels":[],"label_agreement":null},{"id":"W4409353465","doi":"10.21037/qims-24-1440","title":"Brain white matter microstructural alterations in patients with diabetic retinopathy: an automated fiber-tract quantification study","year":2025,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diabetic retinopathy; White matter; Medicine; Pathology; Fiber tract; Computer science; Diabetes mellitus; Magnetic resonance imaging; Radiology; Endocrinology","score_opus":0.04005825587990369,"score_gpt":0.3780055563282895,"score_spread":0.33794730044838583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409353465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99890673,0.00009334179,0.00080416404,0.000006385004,0.0000011892336,0.000015283897,0.00006425788,0.000012421703,0.0000961973],"genre_scores_gemma":[0.998481,0.000037373677,0.001303021,0.000007079867,0.000003012357,0.000009080592,0.00010111778,0.0000028441111,0.000055495228],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997292,0.00008735789,0.000027446233,0.000084389954,0.000047103582,0.00002457209],"domain_scores_gemma":[0.99911803,0.00018891446,0.00033835936,0.00013662665,0.0001491953,0.00006878628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010301056,0.00037984052,0.00029828332,0.0008787827,0.00035526245,0.00031496122,0.0001958522,0.00041461582,0.00057676673],"category_scores_gemma":[0.0016229175,0.00018640306,0.0002868896,0.0004401785,0.000215224,0.00028348956,0.0002860105,0.00017904556,0.0001543572],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002109372,0.00042057107,0.9442289,0.00008070534,0.0004012241,0.00076622074,0.000539985,0.0011269528,0.02424455,0.00008615603,0.00015708663,0.025838278],"study_design_scores_gemma":[0.00005960814,0.00059982284,0.9892314,0.000011342473,0.00013434158,0.001582997,0.00018520918,0.006107874,0.0017449823,0.00007261027,0.00025425886,0.000015552041],"about_ca_topic_score_codex":0.0029667078,"about_ca_topic_score_gemma":0.0033266195,"teacher_disagreement_score":0.0029667078,"about_ca_system_score_codex":0.00028353685,"about_ca_system_score_gemma":0.00020772043,"threshold_uncertainty_score":0.005898893},"labels":[],"label_agreement":null},{"id":"W4409428638","doi":"10.52294/001c.133510","title":"Longitudinal deformation-based morphometry pipeline to study neuroanatomical differences in structural MRI based on SyN unbiased templates","year":2025,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Krembil Foundation; Douglas Mental Health University Institute; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Alliance de recherche numérique du Canada; University of Toronto; Innovation, Science and Economic Development Canada","keywords":"Template; Pipeline (software); Deformation (meteorology); Anatomy; Computer science; Geology; Artificial intelligence; Biology","score_opus":0.039477860949327315,"score_gpt":0.3423003763430829,"score_spread":0.3028225153937556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409428638","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053079553,0.00055795256,0.9197063,0.00030320315,0.00009082546,0.00048476315,0.004284132,0.01995226,0.0015410973],"genre_scores_gemma":[0.18788737,0.0005066242,0.78789294,0.00027232934,0.00009352782,0.0011505332,0.015292593,0.0023283781,0.0045756362],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99967754,0.000037131238,0.000022276457,0.00012230653,0.00010373687,0.000037081023],"domain_scores_gemma":[0.99948525,0.000117629046,0.00009497272,0.00012476368,0.00014222572,0.000035059606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012803613,0.00088390865,0.0008370433,0.0014926327,0.00040199384,0.00090195023,0.0010670873,0.0006828656,0.0044675083],"category_scores_gemma":[0.0026814817,0.0005357803,0.0013546216,0.0010620275,0.00034193762,0.00056953647,0.0012120353,0.0010463807,0.0027021256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055315276,0.0003785902,0.017849812,0.00053620466,0.0005831286,0.000370464,0.0006268431,0.04956359,0.1991907,0.0065609477,0.029484622,0.69430196],"study_design_scores_gemma":[0.00015714882,0.00054647686,0.05189658,0.000057592802,0.00028358822,0.0013654752,0.00021709444,0.82413757,0.07067251,0.014740601,0.03579865,0.00012666146],"about_ca_topic_score_codex":0.0052140057,"about_ca_topic_score_gemma":0.0126468595,"teacher_disagreement_score":0.0052140057,"about_ca_system_score_codex":0.00045380776,"about_ca_system_score_gemma":0.0014185302,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4409451448","doi":"10.1162/imag_a_00559","title":"Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Mila - Quebec Artificial Intelligence Institute; CARE Canada; Montreal Neurological Institute and Hospital; International Collaboration On Repair Discoveries; University of British Columbia; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Université de Montréal; Polytechnique Montréal","funders":"Institut TransMedTech; H2020 European Research Council; National Institute of Neurological Disorders and Stroke; Instituto de Salud Carlos III; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; HORIZON EUROPE Framework Programme; Agència de Gestió d'Ajuts Universitaris i de Recerca; Institut de Valorisation des Données; Agentura Pro Zdravotnický Výzkum České Republiky; University College London Hospitals NHS Foundation Trust; Center for Neurobehavioral Development; European Commission; Ministerstvo Zdravotnictví Ceské Republiky; National Natural Science Foundation of China; National Institutes of Health; International Collaboration on Repair Discoveries; Rosetrees Trust; Ministerstvo Školství, Mládeže a Tělovýchovy; Craig H. Neilsen Foundation; Ataxia UK; National Imaging Facility; Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona; National Institute for Health and Care Research; H2020 Marie Skłodowska-Curie Actions; Courtois Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; Canada Foundation for Innovation; SpinalCure Australia; University of Pennsylvania; Wings for Life; Canada First Research Excellence Fund; Max-Planck-Gesellschaft; Bristol-Myers Squibb; “la Caixa” Foundation; Deutsche Forschungsgemeinschaft; University of Queensland; American Heart Association; Réseau en Bio-Imagerie du Quebec; University of Minnesota","keywords":"Neuroimaging; Central nervous system; Brain size; Neuroscience; Center (category theory); In vivo; Medicine; Psychology; Biology; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.013895481833627606,"score_gpt":0.3068382174446539,"score_spread":0.2929427356110263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409451448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996147,0.00006723342,0.0001694944,0.000007849959,0.000001389981,0.000004269191,0.000033954653,0.0000018588598,0.00009913324],"genre_scores_gemma":[0.9995697,0.000033079385,0.0002059488,0.0000088996485,0.000008256954,0.0000056565286,0.000094477444,0.0000033834674,0.00007071838],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996451,0.00013621528,0.000019616355,0.00011937127,0.00004477763,0.00003483121],"domain_scores_gemma":[0.9984825,0.00033813756,0.0005195447,0.00036131934,0.0001241403,0.00017429274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008685929,0.00036319115,0.00033893148,0.0006356848,0.0003479034,0.00048167267,0.00031603803,0.00036378737,0.00097370567],"category_scores_gemma":[0.001631715,0.0002793358,0.0003143945,0.0005668757,0.00054650486,0.0005775408,0.00046040397,0.00028606862,0.0002047514],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010568834,0.0002426004,0.98197216,0.00002817478,0.00045195656,0.00025170797,0.00050344487,0.00017982392,0.009908513,0.000089443165,0.00013431569,0.005181051],"study_design_scores_gemma":[0.000008055131,0.00018102322,0.99885154,0.0000019080971,0.00004849224,0.0002653629,0.000093255316,0.00026901966,0.0001817612,0.00002433824,0.00007089661,0.000004459365],"about_ca_topic_score_codex":0.0018121636,"about_ca_topic_score_gemma":0.0024920863,"teacher_disagreement_score":0.0018121636,"about_ca_system_score_codex":0.00016382265,"about_ca_system_score_gemma":0.00019893979,"threshold_uncertainty_score":0.0045936108},"labels":[],"label_agreement":null},{"id":"W4409487638","doi":"10.1162/imag_a_00567","title":"Delineation of the trigeminal-lateral parabrachial-central amygdala tract in humans","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; Krembil Foundation; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; University of Toronto; Canada Research Chairs","keywords":"Parabrachial Nucleus; Neuroscience; Amygdala; Lateral parabrachial nucleus; Medicine; Anatomy; Biology; Central nervous system","score_opus":0.039538107805077556,"score_gpt":0.37162943088871747,"score_spread":0.3320913230836399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409487638","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96922135,0.0012731615,0.023876008,0.00018678361,0.000019541227,0.000052082316,0.0005069566,0.00010184966,0.0047623278],"genre_scores_gemma":[0.99334586,0.0002891315,0.0051795975,0.000039036957,0.000005035939,0.000027169226,0.00014868814,0.000018343215,0.00094703306],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999404,0.000010634724,0.0000030456793,0.000024573297,0.000012628999,0.000008617734],"domain_scores_gemma":[0.9999038,0.00001963126,0.000031217915,0.000015525931,0.000017671207,0.000012206566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018178987,0.00012210238,0.00015184541,0.00033478823,0.00020790451,0.0003122944,0.00012697339,0.00029883126,0.002662053],"category_scores_gemma":[0.00032830745,0.00011119027,0.00009162374,0.00016264504,0.0004241065,0.00032001015,0.00014978883,0.00019771159,0.00029949812],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001398044,0.00017824415,0.1167745,0.0004440982,0.00019219505,0.0037033337,0.0013597492,0.004292531,0.70958203,0.013548841,0.0031375578,0.1453889],"study_design_scores_gemma":[0.000077752025,0.0007750606,0.85756105,0.00022891875,0.00013435961,0.019717263,0.00076778064,0.024818003,0.065411665,0.011246108,0.019177474,0.00008461276],"about_ca_topic_score_codex":0.003422512,"about_ca_topic_score_gemma":0.0086226575,"teacher_disagreement_score":0.003422512,"about_ca_system_score_codex":0.00026821214,"about_ca_system_score_gemma":0.0002520502,"threshold_uncertainty_score":0.00890547},"labels":[],"label_agreement":null},{"id":"W4409489633","doi":"10.1142/s0219887825502007","title":"Heisenberg spin chain models and Bäcklund transformations of isotropic curves in ℂ3","year":2025,"lang":"en","type":"article","venue":"International Journal of Geometric Methods in Modern Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea","keywords":"Isotropy; Spin (aerodynamics); Physics; Chain (unit); Mathematical physics; Heisenberg model; Quantum mechanics; Ferromagnetism; Thermodynamics","score_opus":0.1111423339458594,"score_gpt":0.4857761111357464,"score_spread":0.374633777189887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409489633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40229446,0.0009291482,0.53377193,0.0013961203,0.00037081935,0.000111935835,0.00018181094,0.00021274957,0.060731083],"genre_scores_gemma":[0.91285104,0.0008173948,0.06382724,0.00032692222,0.00031988416,0.00009689448,0.0001842719,0.0001389161,0.021437371],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99968445,0.00006249269,0.000018015273,0.00007028159,0.00011382301,0.000051028794],"domain_scores_gemma":[0.9996145,0.000048393722,0.000104019295,0.000070223345,0.00008270979,0.0000800918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005773561,0.0006643267,0.00048081003,0.0011890342,0.00079145614,0.0014879147,0.0008531371,0.0012257069,0.0031961724],"category_scores_gemma":[0.0011500546,0.00023904831,0.0007548544,0.00048898405,0.0017882216,0.0037921453,0.00093505747,0.0012435338,0.0005625329],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008696173,0.000013828783,0.00013306453,0.000010235854,0.0000050469316,0.00009101304,0.0001292243,0.0034084616,0.0015551241,0.9921882,0.00019095618,0.0022661607],"study_design_scores_gemma":[0.000012689218,0.00003520567,0.00022311567,0.000010630689,0.000004830258,0.00012636428,0.0001252461,0.053652935,0.00084355567,0.9415707,0.0033798376,0.000014739571],"about_ca_topic_score_codex":0.0016954788,"about_ca_topic_score_gemma":0.0011494145,"teacher_disagreement_score":0.0031961724,"about_ca_system_score_codex":0.00080998585,"about_ca_system_score_gemma":0.000809828,"threshold_uncertainty_score":0.010692298},"labels":[],"label_agreement":null},{"id":"W4409665004","doi":"10.7554/elife.96625.2","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Thalamus; Cerebellum; Neuroscience; Diffusion; Biology; Physics","score_opus":0.04797523747320988,"score_gpt":0.3343625564876865,"score_spread":0.2863873190144766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409665004","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97944814,0.000705144,0.01879535,0.000032174008,0.000008286737,0.000014536857,0.0003969595,0.00017052432,0.00042884937],"genre_scores_gemma":[0.9792027,0.0011589951,0.017395731,0.000021415823,0.0000029661737,0.000056688703,0.0004244203,0.00008814978,0.0016490762],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99994576,0.0000059661174,0.000003945981,0.000019932953,0.000016151558,0.000008338965],"domain_scores_gemma":[0.9998441,0.00002260534,0.00006482116,0.000012747425,0.000035622594,0.000020092762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018558002,0.00032239285,0.00022151247,0.00040159834,0.00008493738,0.00024187373,0.00021745669,0.00022322964,0.00041936096],"category_scores_gemma":[0.00029437305,0.00016732104,0.00017111491,0.00012569154,0.00020030966,0.0002156192,0.000260568,0.00024820454,0.00013038555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061732164,0.0000040717937,0.0016087886,0.000031552983,0.000008204535,0.00010856817,0.00004912207,0.00030007208,0.9943072,0.00008072319,0.000019697882,0.003420334],"study_design_scores_gemma":[0.0000075406497,0.0004923167,0.06094315,0.00002575374,0.00007401986,0.0008092985,0.00026091468,0.0072508254,0.92874676,0.00021967135,0.0011423735,0.000027361586],"about_ca_topic_score_codex":0.0020768247,"about_ca_topic_score_gemma":0.002844109,"teacher_disagreement_score":0.0020768247,"about_ca_system_score_codex":0.00021342837,"about_ca_system_score_gemma":0.00020429584,"threshold_uncertainty_score":0.00412941},"labels":[],"label_agreement":null},{"id":"W4409709964","doi":"10.21203/rs.3.rs-6480729/v1","title":"Brain Dissection Photogrammetry for Studying Human White Matter Connections: a Unique Resource for Integrating Ex-vivo and In-vivo Multimodal Datasets","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre National de la Recherche Scientifique; Université de Sherbrooke","keywords":"Ex vivo; Photogrammetry; White matter; Computer science; Resource (disambiguation); Dissection (medical); In vivo; Artificial intelligence; Computer vision; Neuroscience; Biology; Medicine; Anatomy; Magnetic resonance imaging; Radiology","score_opus":0.13324129880321525,"score_gpt":0.4874112130988974,"score_spread":0.3541699142956821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409709964","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0097356,0.0005443188,0.9765534,0.00027249145,0.00007702315,0.00010394998,0.004582735,0.003122094,0.0050083706],"genre_scores_gemma":[0.13155155,0.0023761226,0.85115814,0.00019303651,0.00013620326,0.0004478903,0.006567649,0.0024201411,0.0051492658],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995876,0.00006203324,0.000027840386,0.00010335035,0.00019631087,0.000022891467],"domain_scores_gemma":[0.9990577,0.00021662306,0.000083654486,0.0004289877,0.000164264,0.000048847378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005517261,0.0009881774,0.00055102195,0.0024527668,0.00040923103,0.0012522169,0.00079753855,0.0009395575,0.012124646],"category_scores_gemma":[0.0018111038,0.0007385538,0.00047350372,0.0024805453,0.0005609679,0.0011504292,0.0016521984,0.00095416425,0.0046970523],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020051611,0.00017729396,0.004349224,0.00088142866,0.00025395263,0.0007200387,0.0006030024,0.02760966,0.36121595,0.018456038,0.044224527,0.5413084],"study_design_scores_gemma":[0.00011992126,0.00018537784,0.044093702,0.00035140675,0.00027356375,0.008574868,0.00083577895,0.26520756,0.37989324,0.093232,0.20688841,0.00034417392],"about_ca_topic_score_codex":0.0010306627,"about_ca_topic_score_gemma":0.0030489133,"teacher_disagreement_score":0.012124646,"about_ca_system_score_codex":0.00023132973,"about_ca_system_score_gemma":0.0009675965,"threshold_uncertainty_score":0.04056102},"labels":[],"label_agreement":null},{"id":"W4409727375","doi":"10.1101/2025.04.14.648733","title":"White matter geometry confounds Diffusion Tensor Imaging Along Perivascular Space (DTI-ALPS) measures","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Wellcome Trust","keywords":"Diffusion MRI; White matter; Perivascular space; Geometry; Space (punctuation); Physics; Geology; Magnetic resonance imaging; Mathematics; Medicine; Computer science; Anatomy; Radiology","score_opus":0.023398528204105946,"score_gpt":0.2737017571994477,"score_spread":0.2503032289953418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409727375","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9451782,0.0025111043,0.04669497,0.00045080614,0.00009088379,0.00010335054,0.0016858131,0.0002306213,0.0030542293],"genre_scores_gemma":[0.9885013,0.00029230223,0.009951269,0.00008930755,0.00005102654,0.00007521375,0.00057403627,0.00010168794,0.0003638123],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99815,0.0005994733,0.00028008036,0.0005353919,0.00034421013,0.000090795766],"domain_scores_gemma":[0.993057,0.0023727284,0.00260303,0.00097626523,0.00078382035,0.00020722342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004099034,0.0007297825,0.0004206454,0.0011357848,0.0007177691,0.0013899078,0.00047581957,0.00040698063,0.0018418825],"category_scores_gemma":[0.01733363,0.00030309072,0.00031718507,0.0011424484,0.0011036362,0.0010904243,0.0010006821,0.00044746665,0.00022319151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012887439,0.000113343616,0.7938193,0.0014635687,0.001832619,0.0012261464,0.002342754,0.010915697,0.065672554,0.014596974,0.004430556,0.1022977],"study_design_scores_gemma":[0.00004666741,0.00026450868,0.9150842,0.00031190822,0.00053838536,0.003814671,0.00057805475,0.016864425,0.02781208,0.027094519,0.007483649,0.00010681034],"about_ca_topic_score_codex":0.0026099153,"about_ca_topic_score_gemma":0.0057919184,"teacher_disagreement_score":0.004099034,"about_ca_system_score_codex":0.00039453743,"about_ca_system_score_gemma":0.0005143642,"threshold_uncertainty_score":0.02167797},"labels":[],"label_agreement":null},{"id":"W4409890982","doi":"10.1007/s00429-025-02922-8","title":"Small brains but big challenges: white matter tractography in early life samples","year":2025,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"CHIST-ERA; Agence Nationale de la Recherche; Royal Children's Hospital Foundation","keywords":"White matter; Tractography; White (mutation); Psychology; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06383955807671973,"score_gpt":0.28865875241622196,"score_spread":0.22481919433950223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409890982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9050233,0.0054250117,0.0813649,0.0025532704,0.00015172453,0.000098103104,0.0018326684,0.00025180297,0.003299434],"genre_scores_gemma":[0.94380325,0.0023298203,0.049585074,0.00034909943,0.00014265768,0.00010264014,0.0010935926,0.0002987282,0.0022950782],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99960035,0.00015653677,0.000028305907,0.00009474318,0.00007019409,0.000049852497],"domain_scores_gemma":[0.9975272,0.0010580379,0.00030587148,0.00041447373,0.00037346184,0.00032093877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023661251,0.0004956349,0.0004236874,0.0010124963,0.0007431152,0.0012273706,0.0006283105,0.0011544852,0.0012897323],"category_scores_gemma":[0.010231967,0.00043025654,0.00026797852,0.00074127666,0.0010146947,0.0015042516,0.0008114742,0.0010435386,0.0005528474],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012510809,0.00033220142,0.54004043,0.0009850945,0.0008815723,0.009806848,0.007909563,0.005954993,0.08011577,0.0122749265,0.017485427,0.3229621],"study_design_scores_gemma":[0.000039118073,0.00029660735,0.88958293,0.00032059476,0.00021228462,0.0113215875,0.0038675745,0.012063267,0.012342921,0.04935161,0.020515684,0.00008582057],"about_ca_topic_score_codex":0.0066323923,"about_ca_topic_score_gemma":0.023629598,"teacher_disagreement_score":0.0066323923,"about_ca_system_score_codex":0.0004248761,"about_ca_system_score_gemma":0.0010363286,"threshold_uncertainty_score":0.013187587},"labels":[],"label_agreement":null},{"id":"W4409905333","doi":"10.1007/s00429-025-02924-6","title":"Due to difference in anatomical definitions, population variability and tractography methods, it will not be possible to standardize brain tractography for users, or will it?","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; Wellcome Leap; Canada Research Chairs; Hope for Depression Research Foundation","keywords":"Tractography; Population; Psychology; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.09689947693585951,"score_gpt":0.4222279968961041,"score_spread":0.3253285199602446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409905333","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011870399,0.99604046,0.0006686352,0.0018643948,0.00047395093,0.0000054343145,0.00006299393,0.000016962656,0.00074835576],"genre_scores_gemma":[0.00095379626,0.99560237,0.0013742599,0.0010107041,0.00043993175,0.000014642759,0.000085601634,0.000009898361,0.0005088531],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99931514,0.00017172843,0.00012507851,0.00015864361,0.0001920139,0.000037380938],"domain_scores_gemma":[0.99517125,0.0031296252,0.00038682952,0.00017703102,0.00103068,0.00010458955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003528656,0.0008322611,0.0021849005,0.002458323,0.00029377083,0.0020228107,0.001302501,0.0014919469,0.0041313185],"category_scores_gemma":[0.006759035,0.00029962033,0.0010382774,0.002771221,0.0012300354,0.0025793714,0.00074297574,0.0027565763,0.0025367048],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006647278,0.000024188485,0.000262611,0.019262169,0.00019823466,0.000060089693,0.00006572178,0.0003121344,0.0009492586,0.008132994,0.026974265,0.94369185],"study_design_scores_gemma":[0.00002829271,0.000078387115,0.0020261065,0.015304716,0.0003911447,0.0009229506,0.00014548244,0.00018913297,0.00069535244,0.009779934,0.9703883,0.00005016699],"about_ca_topic_score_codex":0.0040498716,"about_ca_topic_score_gemma":0.0064673494,"teacher_disagreement_score":0.0041313185,"about_ca_system_score_codex":0.0010272758,"about_ca_system_score_gemma":0.0036928302,"threshold_uncertainty_score":0.018661559},"labels":[],"label_agreement":null},{"id":"W4409905343","doi":"10.1007/s00429-025-02921-9","title":"The scientific value of tractography: accuracy vs usefulness","year":2025,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Université de Bordeaux; Agence Nationale de la Recherche; European Commission; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Hope for Depression Research Foundation","keywords":"Tractography; Value (mathematics); Psychology; Computer science; Medical physics; Medicine; Diffusion MRI; Radiology; Machine learning; Magnetic resonance imaging","score_opus":0.025902433290218938,"score_gpt":0.31960660354039766,"score_spread":0.2937041702501787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409905343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10975991,0.27569038,0.33911774,0.21852972,0.009070564,0.00036236286,0.0027502214,0.0009970944,0.043722086],"genre_scores_gemma":[0.8380196,0.049115244,0.08053592,0.012013036,0.016334714,0.00020427525,0.00043312885,0.0006283195,0.002715757],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.86274177,0.09013935,0.0107259955,0.008449182,0.02700499,0.00093873707],"domain_scores_gemma":[0.20837954,0.6805035,0.030916639,0.046992987,0.031010045,0.0021973643],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2034983,0.0019478431,0.0046906923,0.014606985,0.0014691841,0.010279706,0.0039943834,0.008323863,0.0043810927],"category_scores_gemma":[0.5451658,0.0014904332,0.0020248457,0.0066685397,0.023103757,0.019174786,0.005353019,0.0075080367,0.0020230464],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028310043,0.00026566975,0.23892848,0.00781248,0.009743917,0.0011268918,0.0031289714,0.012868425,0.003055667,0.17374127,0.025922917,0.52057433],"study_design_scores_gemma":[0.0005382149,0.00081356306,0.063508935,0.0057677114,0.0031776598,0.004961875,0.0018101962,0.058459293,0.0052474164,0.80511546,0.050087612,0.0005121274],"about_ca_topic_score_codex":0.0021730752,"about_ca_topic_score_gemma":0.002082958,"teacher_disagreement_score":0.2034983,"about_ca_system_score_codex":0.0029003199,"about_ca_system_score_gemma":0.0034556692,"threshold_uncertainty_score":0.9822284},"labels":[],"label_agreement":null},{"id":"W4409947176","doi":"10.1101/2025.04.25.650626","title":"Multivariate white matter microstructure alterations in older adults with coronary artery disease","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Ontario Brain Institute; Sunnybrook Health Science Centre; Université de Montréal; Concordia University; Institut Universitaire de Gériatrie de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Fondation Brain Canada","keywords":"Multivariate statistics; Coronary artery disease; Cardiology; White (mutation); White matter; Internal medicine; Medicine; Disease; Multivariate analysis; Microstructure; Materials science; Magnetic resonance imaging; Mathematics; Radiology; Chemistry; Metallurgy","score_opus":0.012997203915251393,"score_gpt":0.26018792049747963,"score_spread":0.24719071658222824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409947176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99961287,0.000107579486,0.00006342961,0.000009745537,0.0000018241549,0.000003064289,0.000089173096,0.000002544276,0.000109799694],"genre_scores_gemma":[0.99974376,0.000028981985,0.000060523,0.000006570972,0.0000044567255,0.000002062193,0.00009467241,6.919218e-7,0.000058404126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99987125,0.000022402455,0.000020476878,0.000040120085,0.000027863589,0.000017846442],"domain_scores_gemma":[0.9995554,0.000054743323,0.000252694,0.00003664111,0.00005163447,0.000048811762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029222915,0.0003761291,0.00025799166,0.00070278125,0.00029913825,0.00036189906,0.0001474073,0.00032815474,0.0011840995],"category_scores_gemma":[0.0010524783,0.00014346123,0.0002119076,0.0005555072,0.00015503069,0.00024396842,0.0003177677,0.00023759155,0.00012275849],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002239781,0.00003329061,0.99611366,0.000010250255,0.00008092701,0.000118670825,0.00008264957,0.000059002796,0.0010394714,0.000013783811,0.000057248315,0.0021671003],"study_design_scores_gemma":[0.000002725305,0.00007408009,0.9994079,0.00000139824,0.00001727058,0.00017440687,0.000047904476,0.00015194045,0.00006703418,0.000021404785,0.000032626947,0.000001392138],"about_ca_topic_score_codex":0.0028659264,"about_ca_topic_score_gemma":0.0037236826,"teacher_disagreement_score":0.0028659264,"about_ca_system_score_codex":0.00013137021,"about_ca_system_score_gemma":0.000105068866,"threshold_uncertainty_score":0.0056984425},"labels":[],"label_agreement":null},{"id":"W4410044611","doi":"10.1063/5.0258081","title":"Measuring the velocity autocorrelation function using diffusion NMR","year":2025,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vetenskapsrådet","keywords":"Autocorrelation; Scaling; Diffusion; Nuclear magnetic resonance; Permeability (electromagnetism); Function (biology); Chemistry; Self-diffusion; Statistical physics; Exponent; Magnet; Molecular dynamics; Anomalous diffusion; Physics; Materials science; Molecular physics; Membrane; Mathematics; Computer science; Thermodynamics; Computational chemistry; Statistics; Geometry","score_opus":0.08160887345774435,"score_gpt":0.33556937164731543,"score_spread":0.25396049818957106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410044611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5717584,0.0011702369,0.41916412,0.000302446,0.00009335082,0.00009975198,0.0007023149,0.00141482,0.00529449],"genre_scores_gemma":[0.915029,0.0008672035,0.08246847,0.000058483034,0.000033811473,0.00008865084,0.00026900935,0.00007917193,0.0011062049],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99985003,0.00002302,0.000007983613,0.000042466025,0.000051536423,0.00002499193],"domain_scores_gemma":[0.99961567,0.00017750158,0.00008052346,0.000035544017,0.000061722814,0.000028931356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035126694,0.00034544631,0.00023365702,0.00056056835,0.00022967154,0.0003465307,0.00032475026,0.00042659036,0.000948043],"category_scores_gemma":[0.0013799551,0.00014644832,0.0001421876,0.00041109242,0.0003501726,0.0005417513,0.00035014725,0.0005127518,0.00026539445],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000099561345,0.00004559807,0.0018266566,0.00012184188,0.000019489027,0.0000847223,0.00007542446,0.008228327,0.96302086,0.004391994,0.0004422343,0.021643208],"study_design_scores_gemma":[0.000023861197,0.00028777696,0.005774041,0.000029762057,0.000027742399,0.0003101035,0.00007511429,0.25613257,0.7308202,0.0030094464,0.0034295944,0.0000797891],"about_ca_topic_score_codex":0.0018208537,"about_ca_topic_score_gemma":0.0017198634,"teacher_disagreement_score":0.0018208537,"about_ca_system_score_codex":0.0003896163,"about_ca_system_score_gemma":0.00037555565,"threshold_uncertainty_score":0.0036205053},"labels":[],"label_agreement":null},{"id":"W4410075648","doi":"10.1101/2025.04.29.651339","title":"A combined neuroanatomy, ex vivo imaging and immunohistochemistry defined MRI mask for the human paraventricular nucleus of the thalamus","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Neuroscience; Thalamus; Neuroanatomy; Magnetic resonance imaging; Human brain; Ex vivo; Anatomy; Biology; Voxel; Computer science; In vivo; Artificial intelligence; Medicine; Radiology","score_opus":0.018051623961105705,"score_gpt":0.2792097397888182,"score_spread":0.2611581158277125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410075648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39984068,0.0012309304,0.5904192,0.0004238258,0.00011700771,0.0002237637,0.0017401184,0.0014566289,0.004547924],"genre_scores_gemma":[0.7571451,0.00048905215,0.23738968,0.00015619243,0.000034522167,0.00020061512,0.0015505817,0.0006216412,0.0024126493],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997615,0.00003523453,0.000017628752,0.000083729305,0.00007910234,0.000022752181],"domain_scores_gemma":[0.9997892,0.00003852141,0.000047038444,0.000051641375,0.000059793114,0.0000137235265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049797236,0.00038456914,0.00023233303,0.0006505592,0.0003112333,0.0007646453,0.00056715106,0.0005947225,0.0018166241],"category_scores_gemma":[0.0012322348,0.0003238527,0.00035034705,0.0003349076,0.00056670525,0.0004080402,0.00048669058,0.0003219825,0.0007480547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023215212,0.000038309612,0.0050480254,0.00030751404,0.00010482354,0.0008640853,0.00053135306,0.00914684,0.92201024,0.004035616,0.0014204005,0.056260575],"study_design_scores_gemma":[0.00007132768,0.0005545851,0.111903414,0.0001873474,0.0003555271,0.013598854,0.00077310775,0.12537943,0.69976515,0.011319778,0.03595381,0.0001377415],"about_ca_topic_score_codex":0.0029482672,"about_ca_topic_score_gemma":0.0066262884,"teacher_disagreement_score":0.0029482672,"about_ca_system_score_codex":0.00037869927,"about_ca_system_score_gemma":0.00075462676,"threshold_uncertainty_score":0.00607723},"labels":[],"label_agreement":null},{"id":"W4410142627","doi":"10.1523/jneurosci.0096-25.2025","title":"Beyond Motor Control: Diffusion MRI Reveals Associations between the Cerebello-VTA Pathway and Socio-affective Behaviors in Humans","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Diffusion MRI; Psychology; Neuroscience; Control (management); Diffusion; Cognitive psychology; Medicine; Physics; Computer science; Magnetic resonance imaging; Artificial intelligence","score_opus":0.031976109158424186,"score_gpt":0.351825254258974,"score_spread":0.3198491451005498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410142627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9899093,0.0034185296,0.0011602977,0.0005846678,0.000028067276,0.000016496973,0.00051619514,0.000026977392,0.0043394035],"genre_scores_gemma":[0.9975102,0.00073135627,0.0004826494,0.000092183356,0.000018584105,0.0000060172065,0.00019296669,0.000007838118,0.00095819286],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999899,0.000016610667,0.000005725321,0.00005083979,0.000012753391,0.0000150476735],"domain_scores_gemma":[0.99980444,0.000030132922,0.00006975367,0.000029207638,0.000031573487,0.000034982415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024263571,0.00023775495,0.00019332336,0.0008325716,0.00032249646,0.0007939874,0.0003204449,0.00046307655,0.0020963447],"category_scores_gemma":[0.00084507064,0.0001694812,0.000116683004,0.00040913644,0.000554689,0.00055824337,0.00036204452,0.00036100985,0.00030525084],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012787032,0.0002684375,0.836013,0.00023903757,0.00051902514,0.0052117654,0.0021840732,0.00046445185,0.05688826,0.0022939872,0.003137791,0.09150147],"study_design_scores_gemma":[0.000008507176,0.000072320996,0.9931647,0.000027442204,0.000042966327,0.00236017,0.0003543742,0.00040119953,0.00067736756,0.0011445107,0.0017333928,0.0000130302915],"about_ca_topic_score_codex":0.012861604,"about_ca_topic_score_gemma":0.020106083,"teacher_disagreement_score":0.012861604,"about_ca_system_score_codex":0.00032708436,"about_ca_system_score_gemma":0.00021483426,"threshold_uncertainty_score":0.025573492},"labels":[],"label_agreement":null},{"id":"W4410250211","doi":"10.1101/2025.05.09.653169","title":"A Unified Imaging-Histology Framework for Superficial White Matter Architecture Studies in the Human Brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Hospital for Sick Children; Savoy Foundation; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"White matter; Architecture; Human brain; Neuroimaging; Histology; Computer science; Artificial intelligence; Neuroscience; Psychology; Medicine; Pathology; Geography; Magnetic resonance imaging; Radiology; Archaeology","score_opus":0.05607601025933815,"score_gpt":0.3541923202867194,"score_spread":0.2981163100273812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410250211","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015518952,0.0001097662,0.99737525,0.00008363651,0.000009209897,0.00003341336,0.0001389434,0.00029529273,0.00040256092],"genre_scores_gemma":[0.07406317,0.0005515644,0.9227657,0.00010616479,0.00007135966,0.00034120027,0.00075919466,0.00029774368,0.0010438279],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99955803,0.00016725689,0.000034505567,0.00009465013,0.00011633974,0.000029162871],"domain_scores_gemma":[0.9991825,0.00024409508,0.00015558924,0.00014642165,0.00020093827,0.00007047089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001671701,0.00086259755,0.0007203793,0.0025706466,0.00062348606,0.0022387411,0.0020228452,0.0011335668,0.002429351],"category_scores_gemma":[0.0026122811,0.0006768758,0.0019926897,0.0012065397,0.0013733316,0.001113908,0.0029002333,0.0011203986,0.0010011904],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006470913,0.0001017244,0.0035188172,0.00046065787,0.00018640344,0.00090221426,0.0003979027,0.63297147,0.024057964,0.23947443,0.004378312,0.09348543],"study_design_scores_gemma":[0.000006586609,0.000032776006,0.0008508835,0.000046036374,0.000023873381,0.00018490413,0.000058385212,0.8859083,0.0011649224,0.1051177,0.006583115,0.000022490194],"about_ca_topic_score_codex":0.006150237,"about_ca_topic_score_gemma":0.0094230175,"teacher_disagreement_score":0.006150237,"about_ca_system_score_codex":0.00084005046,"about_ca_system_score_gemma":0.0019246569,"threshold_uncertainty_score":0.012228906},"labels":[],"label_agreement":null},{"id":"W4410308882","doi":"10.1038/s41598-025-00886-7","title":"Multiscale gradients of corticopontine structural connectivity","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Tractography; Context (archaeology); Cerebellum; Cognition; Brainstem; Diffusion MRI; Biology; Anatomy; Magnetic resonance imaging; Medicine","score_opus":0.03328700621610978,"score_gpt":0.3593777805707021,"score_spread":0.3260907743545923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410308882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72963434,0.00071406673,0.26224452,0.0005855816,0.00005047988,0.00006836796,0.002805104,0.00069133396,0.0032062768],"genre_scores_gemma":[0.96585333,0.00026290386,0.03188204,0.00002784627,0.000016366621,0.00003979193,0.0010183043,0.000111517504,0.0007879805],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998828,0.000026732725,0.000006431224,0.00004060757,0.00002394917,0.000019398458],"domain_scores_gemma":[0.9997316,0.000096753145,0.000053007047,0.00004861552,0.000045913384,0.00002404665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037446187,0.00026696766,0.00020228002,0.0010058249,0.0002103906,0.00072391663,0.00019479159,0.0002408017,0.0013091804],"category_scores_gemma":[0.0020914795,0.00016566162,0.00038084347,0.0006952974,0.00039135787,0.00059421535,0.00040314012,0.00042586165,0.00020000184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060554757,0.00012270446,0.066420905,0.00073284755,0.00072518864,0.0013028958,0.0020126484,0.27734187,0.3429768,0.065104865,0.013028903,0.22962473],"study_design_scores_gemma":[0.000033056505,0.0001338892,0.28071603,0.00010362064,0.000171611,0.0015350415,0.0004443675,0.60676855,0.03236583,0.06457514,0.013015112,0.00013777052],"about_ca_topic_score_codex":0.0053089256,"about_ca_topic_score_gemma":0.010809543,"teacher_disagreement_score":0.0053089256,"about_ca_system_score_codex":0.00034043618,"about_ca_system_score_gemma":0.00054241135,"threshold_uncertainty_score":0.010556042},"labels":[],"label_agreement":null},{"id":"W4410519647","doi":"10.1101/2025.05.14.654080","title":"Repeated Subconcussive Head Impacts Compromise White Matter Integrity and Bimanual Coordination in Collegiate Football Players","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Head (geology); Compromise; Football; Football players; College football; Aeronautics; Engineering; History; Political science","score_opus":0.03406424164529666,"score_gpt":0.30789568555939295,"score_spread":0.2738314439140963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410519647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99979526,0.000027294533,0.000028850829,0.0000040182754,5.066787e-7,0.000003808896,0.000038075035,0.0000017048316,0.0001004524],"genre_scores_gemma":[0.9995208,0.00002445115,0.00004704636,0.0000064266455,0.0000025141246,0.0000060546877,0.00010260035,0.0000011207055,0.00028904632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998233,0.000017826349,0.00001471926,0.000051224586,0.00004080013,0.00005228713],"domain_scores_gemma":[0.9994754,0.00003756993,0.00026605814,0.00003569616,0.000085944885,0.00009937535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020288557,0.00034324994,0.0002559796,0.00070092053,0.00039226908,0.00036785018,0.0002610713,0.0004018417,0.0018413855],"category_scores_gemma":[0.0007080498,0.00022132773,0.00015118775,0.00043525052,0.0002794429,0.0002553721,0.0004301077,0.00019109047,0.000303191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030461422,0.00015694558,0.9867089,0.000026939892,0.00006817038,0.00040170903,0.00033077734,0.00007921383,0.008078165,0.000013442016,0.000087415705,0.0037437778],"study_design_scores_gemma":[0.0000016107125,0.00012005274,0.9994899,0.0000019647916,0.000004024875,0.00013268329,0.000089903515,0.000023894507,0.00010633405,0.000003939912,0.00002473356,7.716588e-7],"about_ca_topic_score_codex":0.011446076,"about_ca_topic_score_gemma":0.018806446,"teacher_disagreement_score":0.011446076,"about_ca_system_score_codex":0.00023302095,"about_ca_system_score_gemma":0.00029741693,"threshold_uncertainty_score":0.022758901},"labels":[],"label_agreement":null},{"id":"W4410594449","doi":"10.1093/braincomms/fcaf193","title":"Sensitivity of diffusion tensor imaging to regional mixed cerebrovascular pathology","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of British Columbia; The Scarborough Hospital; University of Toronto; Sunnybrook Health Science Centre; Simon Fraser University","funders":"Health Research; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; Sensitivity (control systems); Medicine; Diffusion; Pathology; Magnetic resonance imaging; Radiology; Physics; Engineering","score_opus":0.06520047307115506,"score_gpt":0.3761593914150825,"score_spread":0.3109589183439274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410594449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99032366,0.0014203998,0.006238317,0.00015383463,0.000034049972,0.000025125892,0.00032707164,0.0001079043,0.0013695892],"genre_scores_gemma":[0.99894327,0.00007007306,0.000716397,0.000019843945,0.000016643653,0.000004615195,0.000106918385,0.000012863671,0.0001092919],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973617,0.0012468292,0.00024238994,0.0005802562,0.00041174117,0.000157032],"domain_scores_gemma":[0.9676109,0.020900581,0.0057268464,0.003073259,0.0019354817,0.00075300236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007152335,0.00072762906,0.0006682768,0.0016686463,0.0002768842,0.0013036677,0.00040560588,0.00046492333,0.0016333277],"category_scores_gemma":[0.03390802,0.0005262899,0.0007747783,0.0005326632,0.00071145064,0.0008043373,0.0010585362,0.000556342,0.0003605713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090809417,0.000050158742,0.9680577,0.00011268036,0.0016547809,0.00020091432,0.00023717806,0.003486094,0.010850051,0.00023717628,0.00024493944,0.013960437],"study_design_scores_gemma":[0.0000073771303,0.00024749324,0.983779,0.000025512183,0.0002651331,0.0008246295,0.00010019152,0.01093743,0.0026137047,0.00092147593,0.0002521918,0.00002587327],"about_ca_topic_score_codex":0.0018405231,"about_ca_topic_score_gemma":0.0014218951,"teacher_disagreement_score":0.007152335,"about_ca_system_score_codex":0.00020891834,"about_ca_system_score_gemma":0.00021460498,"threshold_uncertainty_score":0.037825584},"labels":[],"label_agreement":null},{"id":"W4410708406","doi":"10.1093/bjro/tzaf014","title":"Myelin mapping in patients with rheumatoid arthritis-related fatigue: a TBSS-MTR study of integrity","year":2024,"lang":"en","type":"article","venue":"BJR|Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"University of Aberdeen; Pfizer","keywords":"Rheumatoid arthritis; Structural integrity; Medicine; Myelin; White matter; Internal medicine; Structural engineering; Radiology; Engineering; Central nervous system; Magnetic resonance imaging","score_opus":0.09358581657652058,"score_gpt":0.37787659341259255,"score_spread":0.28429077683607196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410708406","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99867696,0.00030069146,0.000570456,0.000013985232,0.0000018703219,0.000014116079,0.00017487335,0.00001013935,0.00023676276],"genre_scores_gemma":[0.9993967,0.000051547064,0.00034137414,0.000004414176,0.0000039559286,0.000008656478,0.00010676777,0.000002948838,0.000083619445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99983656,0.000040798066,0.000026778387,0.000050539707,0.000023351802,0.000021906631],"domain_scores_gemma":[0.9993309,0.00010016244,0.0003190471,0.00008453415,0.000099492776,0.0000659485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063127145,0.00033305516,0.00028611935,0.0010336436,0.00030273403,0.0003641588,0.00016092238,0.00026369424,0.0017272565],"category_scores_gemma":[0.0016878535,0.00012502071,0.00021394691,0.0005557723,0.00027337924,0.00029741012,0.00042855207,0.00014419852,0.0003460515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024976647,0.0001221449,0.93872994,0.00015637658,0.00037137326,0.0009835407,0.0012197513,0.0006125468,0.03344733,0.00012422612,0.00026175487,0.021473354],"study_design_scores_gemma":[0.000025130483,0.0005908718,0.9938002,0.000016878712,0.00009777518,0.0022554721,0.00028507912,0.000988896,0.0014900832,0.0001454013,0.0002956223,0.000008613308],"about_ca_topic_score_codex":0.001071101,"about_ca_topic_score_gemma":0.0011933214,"teacher_disagreement_score":0.0017272565,"about_ca_system_score_codex":0.00012501988,"about_ca_system_score_gemma":0.00015181341,"threshold_uncertainty_score":0.005778253},"labels":[],"label_agreement":null},{"id":"W4410741941","doi":"10.1038/s41598-025-99724-z","title":"The relationship of white matter tract orientation to vascular geometry in the human brain","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"White matter; Diffusion MRI; Fiber tract; Orientation (vector space); Anatomy; Fractional anisotropy; Human brain; Neuroscience; Voxel; Biology; Medicine; Pathology; Magnetic resonance imaging; Geometry; Mathematics; Radiology","score_opus":0.04575417525798251,"score_gpt":0.3772887596440092,"score_spread":0.3315345843860267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410741941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99222696,0.00035517302,0.0054099425,0.000052574283,0.000007299804,0.000017144883,0.00023621443,0.000059769547,0.0016350157],"genre_scores_gemma":[0.9969959,0.00021084551,0.0023267658,0.0000109194625,0.000010023817,0.000006202776,0.0001383645,0.000029609799,0.00027151237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99977154,0.00007130986,0.000016486421,0.000074365664,0.000043265685,0.000023033037],"domain_scores_gemma":[0.99885345,0.00029611983,0.00049418135,0.00014682248,0.00013992233,0.00006957881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037498111,0.00018359261,0.00015588957,0.00096051075,0.00016030124,0.00068598706,0.00010426652,0.00023403339,0.0011201916],"category_scores_gemma":[0.0034578883,0.00016324897,0.000101779864,0.00071001984,0.00043848465,0.0003205381,0.00021181628,0.00011942171,0.00031836476],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009037116,0.000065497115,0.748112,0.00011894111,0.00040116571,0.0007609873,0.0012949781,0.0077962894,0.15325412,0.0020524468,0.0010531512,0.08418662],"study_design_scores_gemma":[0.0000035947724,0.00006474291,0.99229175,0.000007844339,0.000025495847,0.0008747506,0.00010565085,0.0025774096,0.0026355875,0.00088115624,0.0005174254,0.000014600277],"about_ca_topic_score_codex":0.003028955,"about_ca_topic_score_gemma":0.0041620387,"teacher_disagreement_score":0.003028955,"about_ca_system_score_codex":0.00017100465,"about_ca_system_score_gemma":0.0002268551,"threshold_uncertainty_score":0.006022632},"labels":[],"label_agreement":null},{"id":"W4410756831","doi":"10.1017/s0954579425000367","title":"Testing the ecophenotype hypothesis: Differences in white matter microstructure in youth with conduct disorder with versus without a history of childhood abuse","year":2025,"lang":"en","type":"article","venue":"Development and Psychopathology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Public Health","funders":"HORIZON EUROPE Framework Programme; Economic and Social Research Council; Bundesministerium für Bildung und Forschung; Universität Zürich; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; UK Research and Innovation; National Science Foundation","keywords":"Fractional anisotropy; Corpus callosum; Psychology; White matter; Sexual abuse; Child abuse; Diffusion MRI; Physical abuse; Superior longitudinal fasciculus; Fasciculus; Clinical psychology; Poison control; Injury prevention; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.0646917933197815,"score_gpt":0.284459099789703,"score_spread":0.21976730646992151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410756831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99978834,0.000022958773,0.000052051622,0.000010385256,0.0000018187042,0.000003323331,0.000043001706,8.1835753e-7,0.00007724165],"genre_scores_gemma":[0.9998242,0.000009775292,0.00005629274,0.000008269988,0.0000021330898,0.000005168351,0.000070894144,9.822377e-7,0.00002231477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995291,0.00013821428,0.000050449446,0.00013234738,0.000056582605,0.00009329899],"domain_scores_gemma":[0.99900645,0.00022592748,0.00042714865,0.00009582707,0.000095328025,0.00014936541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069422176,0.0003709341,0.0002485074,0.0009015382,0.000476881,0.0005124603,0.00026914457,0.0003640547,0.0014021212],"category_scores_gemma":[0.0020345023,0.00016168541,0.0003504381,0.00044377756,0.00049861905,0.0004161284,0.00070334243,0.0003727123,0.00011361585],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021471526,0.00004086404,0.9968149,0.000006075195,0.000050598992,0.00009359565,0.00019169922,0.000020831378,0.0015456874,0.000037890786,0.000032947126,0.0009502683],"study_design_scores_gemma":[0.00000325726,0.00007760518,0.99907386,0.0000033873441,0.000015064736,0.00018887584,0.0003331681,0.000083580155,0.00015158449,0.00003653496,0.000031769894,0.0000012910035],"about_ca_topic_score_codex":0.0033032384,"about_ca_topic_score_gemma":0.004390377,"teacher_disagreement_score":0.0033032384,"about_ca_system_score_codex":0.00021339665,"about_ca_system_score_gemma":0.00018377564,"threshold_uncertainty_score":0.0065680146},"labels":[],"label_agreement":null},{"id":"W4410946066","doi":"10.1016/j.mri.2025.110443","title":"Rapid 1 mm isotropic diffusion tensor imaging with denoising and improved parameter estimation for detecting focal hippocampal lesions in temporal lobe epilepsy","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs","keywords":"Diffusion MRI; Hippocampal formation; Temporal lobe; Epilepsy; Isotropy; Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Noise reduction; Medicine; Biomedical engineering; Neuroscience; Materials science; Optics; Radiology; Magnetic resonance imaging; Mathematics; Psychology; Acoustics; Geometry","score_opus":0.021814285447326644,"score_gpt":0.3052864779706673,"score_spread":0.28347219252334066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410946066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8209961,0.0036589033,0.17348467,0.00034003367,0.00004827606,0.00017996342,0.00017420245,0.00040304568,0.00071486604],"genre_scores_gemma":[0.7695927,0.0024332772,0.2265673,0.0000839016,0.00003351185,0.00018674161,0.00034202106,0.00013904298,0.00062160566],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997304,0.000117456104,0.000030037045,0.000045367087,0.000055245528,0.00002139826],"domain_scores_gemma":[0.99964595,0.00012967504,0.00007409463,0.000050234386,0.000071137554,0.000028858847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002443596,0.0005389148,0.00040130122,0.00066920026,0.00018941212,0.00047359988,0.00028878232,0.00053066097,0.00032052523],"category_scores_gemma":[0.0030535879,0.00035189406,0.0004029077,0.0003643286,0.0003417028,0.0004776182,0.00039331848,0.00041780097,0.00013388798],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022766043,0.00021894161,0.008430863,0.0005831015,0.00027448105,0.00055525644,0.0004305164,0.017995205,0.8041857,0.0013022793,0.0007883026,0.16295871],"study_design_scores_gemma":[0.00041141166,0.0032615038,0.09550297,0.00014321473,0.00091193797,0.004679056,0.0003262779,0.3247122,0.55890477,0.005408627,0.0054361974,0.00030184406],"about_ca_topic_score_codex":0.0015682097,"about_ca_topic_score_gemma":0.003992472,"teacher_disagreement_score":0.002443596,"about_ca_system_score_codex":0.000255385,"about_ca_system_score_gemma":0.00061409693,"threshold_uncertainty_score":0.012923121},"labels":[],"label_agreement":null},{"id":"W4410948111","doi":"10.1162/imag.a.49","title":"Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Modal; White matter; Aggregate (composite); Magnetic resonance imaging; Materials science; Medicine; Radiology; Composite material","score_opus":0.0864788581969707,"score_gpt":0.37344812854845294,"score_spread":0.28696927035148223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410948111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79680693,0.0003252756,0.20069914,0.00012378668,0.000009788219,0.000072877185,0.0005946091,0.00058689597,0.00078071776],"genre_scores_gemma":[0.91253686,0.00018607404,0.08635062,0.000035490302,0.000013057585,0.00004639362,0.00038830438,0.00013005533,0.0003131865],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998043,0.000043688207,0.000015460266,0.00007799354,0.000045484987,0.000012986979],"domain_scores_gemma":[0.9994997,0.00013991061,0.00015113581,0.00010605274,0.00007139859,0.000031872158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062343286,0.00047395323,0.00029474657,0.0014324739,0.00023950297,0.00062991463,0.00033248286,0.00047290337,0.0009275339],"category_scores_gemma":[0.0023798586,0.00021551334,0.00034005565,0.00064906786,0.00033515866,0.00069779996,0.0005377834,0.00040932567,0.00020123774],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012381598,0.00024736347,0.09171701,0.0005606758,0.00077287084,0.0007787487,0.0014211155,0.05597672,0.5836307,0.0041475594,0.0015573191,0.2579518],"study_design_scores_gemma":[0.00007353447,0.0006442235,0.48901397,0.00006983435,0.0003844016,0.0041703703,0.000535611,0.34951285,0.13721973,0.015300743,0.0028957769,0.000178917],"about_ca_topic_score_codex":0.0021978752,"about_ca_topic_score_gemma":0.0039850813,"teacher_disagreement_score":0.0021978752,"about_ca_system_score_codex":0.00020348828,"about_ca_system_score_gemma":0.0002000501,"threshold_uncertainty_score":0.004370153},"labels":[],"label_agreement":null},{"id":"W4410966131","doi":"10.1007/978-1-0716-4438-6_30","title":"Functional MRI of the Spinal Cord","year":2025,"lang":"en","type":"book-chapter","venue":"Neuromethods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; Medicine; Neuroscience; Psychology","score_opus":0.1685469080467526,"score_gpt":0.42495596588025186,"score_spread":0.25640905783349927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410966131","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013377296,0.3314339,0.061186027,0.0066757095,0.009657352,0.00008561948,0.00054148486,0.00074140215,0.5883408],"genre_scores_gemma":[0.008417378,0.19953892,0.03600979,0.0042985734,0.005897606,0.00010859518,0.0003913285,0.0003513841,0.7449864],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999243,0.000013801486,0.0000048321244,0.000013577824,0.000037546502,0.000005904632],"domain_scores_gemma":[0.9998179,0.00011422121,0.0000075367743,0.000012665951,0.000034342196,0.000013391286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030968973,0.000753365,0.00050115155,0.0013606896,0.00026571043,0.0010408643,0.00087785465,0.0012041607,0.023268927],"category_scores_gemma":[0.00048215315,0.0003445632,0.00028487595,0.00076535204,0.00088894216,0.001488517,0.0005169173,0.001361046,0.010164662],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005525615,0.00003955598,0.00010239707,0.0014244608,0.00001922425,0.0005444682,0.00012076618,0.00076852215,0.009526103,0.07867817,0.30020142,0.6085196],"study_design_scores_gemma":[0.0000060083053,0.00003383146,0.0005966639,0.0005385928,0.000011029717,0.003153778,0.00004127532,0.0004017634,0.0020608604,0.040035676,0.95310044,0.000020192483],"about_ca_topic_score_codex":0.0010663058,"about_ca_topic_score_gemma":0.0041243816,"teacher_disagreement_score":0.023268927,"about_ca_system_score_codex":0.00044449157,"about_ca_system_score_gemma":0.00058179465,"threshold_uncertainty_score":0.077842355},"labels":[],"label_agreement":null},{"id":"W4411009153","doi":"10.1002/hbm.70245","title":"Mapping Caudolenticular Gray Matter Bridges in the Human Brain Striatum Through Diffusion Magnetic Resonance Imaging and Tractography","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université de Sherbrooke","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Human Connectome Project; Diffusion MRI; Putamen; White matter; Magnetic resonance imaging; Human brain; Connectome; Striatum; Nuclear magnetic resonance; Caudate nucleus; Artificial intelligence; Physics; Neuroscience; Computer science; Psychology; Radiology; Medicine","score_opus":0.03518705620220358,"score_gpt":0.32583069353233846,"score_spread":0.2906436373301349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411009153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8781426,0.0016299502,0.117233396,0.00023966693,0.000012666945,0.000120240926,0.0007310788,0.00037629675,0.0015141552],"genre_scores_gemma":[0.90291804,0.0010669155,0.09395229,0.000056603367,0.000010378273,0.00008609723,0.0008192421,0.000085572516,0.0010048901],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998946,0.000025427433,0.0000064186347,0.000035451987,0.000028747896,0.000009351464],"domain_scores_gemma":[0.999846,0.00004468961,0.000044589648,0.000022224845,0.000026288759,0.00001615084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034384095,0.0003424702,0.00030493233,0.0007928639,0.0002422862,0.000726202,0.0002616382,0.00042879116,0.00063987926],"category_scores_gemma":[0.0012398827,0.00024351617,0.0003729115,0.0005707194,0.000293677,0.0003873367,0.0003934782,0.00022347922,0.00018439963],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007160112,0.00015376903,0.043328334,0.0006949078,0.0006308144,0.001777558,0.0013790913,0.06388722,0.5835797,0.004474836,0.002693832,0.29668388],"study_design_scores_gemma":[0.0001161811,0.00051569263,0.36107364,0.00029413294,0.00034968747,0.0070319916,0.0007064629,0.41997313,0.18709078,0.011896666,0.010768105,0.00018353101],"about_ca_topic_score_codex":0.009626667,"about_ca_topic_score_gemma":0.02996118,"teacher_disagreement_score":0.009626667,"about_ca_system_score_codex":0.00030827103,"about_ca_system_score_gemma":0.00068472256,"threshold_uncertainty_score":0.019141257},"labels":[],"label_agreement":null},{"id":"W4411010217","doi":"10.1016/j.mri.2025.110445","title":"Comparing single-shot EPI and 2D-navigated, multi-shot EPI diffusion tensor imaging acquisitions in the lumbar spinal cord at 3T","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University; Society for Anthropological Sciences; National Institutes of Health; National Multiple Sclerosis Society","keywords":"Single shot; Shot (pellet); Diffusion MRI; Spinal cord; Lumbar; Medicine; Anatomy; Materials science; Radiology; Physics; Magnetic resonance imaging; Optics","score_opus":0.08584864028324021,"score_gpt":0.36745536553047603,"score_spread":0.28160672524723585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411010217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96734834,0.0009272476,0.030284213,0.00010803482,0.000025692085,0.000084632054,0.00032827805,0.00016065627,0.0007328671],"genre_scores_gemma":[0.9565614,0.00077805447,0.04095067,0.00012901396,0.000053670505,0.00014666074,0.00063379534,0.00010764655,0.0006390325],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996966,0.00007782875,0.0000315267,0.00009917276,0.000068827554,0.000025927367],"domain_scores_gemma":[0.9991339,0.00022337728,0.00016701268,0.00012421809,0.00028407053,0.00006743785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014800042,0.0003955991,0.0003803404,0.00058547547,0.00028156766,0.00069513806,0.00036533186,0.00064239645,0.00065867393],"category_scores_gemma":[0.0035041661,0.00029299746,0.00028358307,0.00031295398,0.0003417859,0.0006304534,0.00039816904,0.0003237092,0.00015183483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035456356,0.00042438428,0.06423758,0.00085832126,0.0010597018,0.0012882545,0.0011415284,0.0053315223,0.83743113,0.00088580797,0.0011452205,0.082650945],"study_design_scores_gemma":[0.00034649196,0.0052129216,0.65814334,0.00011756887,0.0016546356,0.01230037,0.00085541053,0.034599364,0.2790613,0.002869911,0.004654667,0.00018403753],"about_ca_topic_score_codex":0.0014187307,"about_ca_topic_score_gemma":0.004168918,"teacher_disagreement_score":0.0014800042,"about_ca_system_score_codex":0.00019889353,"about_ca_system_score_gemma":0.00036926492,"threshold_uncertainty_score":0.0078270435},"labels":[],"label_agreement":null},{"id":"W4411010286","doi":"10.1101/2025.05.30.25328630","title":"Gray matter microstructure from in-vivo diffusion MRI reflects post-mortem neuropathology severity and clinical progression of Alzheimer’s disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"National Institutes of Health; Cleveland Clinic; Northern California Institute for Research and Education; National Institute on Aging; Emory University; University of Southern California","keywords":"Neuropathology; Diffusion MRI; Gray (unit); Disease; Neuroscience; In vivo; Pathology; Medicine; Magnetic resonance imaging; Psychology; Biology; Radiology","score_opus":0.04840301331926834,"score_gpt":0.40796145377888315,"score_spread":0.3595584404596148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411010286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99650395,0.00043104298,0.0017533231,0.000080380654,0.000005018212,0.000008954706,0.00061329233,0.000033523396,0.0005705169],"genre_scores_gemma":[0.99753904,0.00019287494,0.0011681123,0.000019628997,0.00000866088,0.0000062906997,0.0006037692,0.000005922203,0.00045563333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99991107,0.000019827685,0.000008693356,0.000031576496,0.00001972074,0.000009102569],"domain_scores_gemma":[0.9996588,0.00005388785,0.00018350274,0.00004834789,0.000032420354,0.00002301944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005904782,0.00026111514,0.00021861382,0.0006070073,0.000091619375,0.00039348422,0.00016194726,0.00019966476,0.0016192503],"category_scores_gemma":[0.00095957826,0.00011707665,0.000094179566,0.00033381584,0.00026916177,0.00023884076,0.00014062338,0.00016906462,0.00026531704],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008852354,0.00016015948,0.8102708,0.0001685412,0.00040666046,0.00013726983,0.00035696785,0.00092786335,0.15879789,0.00031892443,0.0010328615,0.026536757],"study_design_scores_gemma":[0.00000661326,0.000073881056,0.98983616,0.000006328491,0.000037640224,0.0002561567,0.000042287284,0.0007449766,0.008389117,0.00028218812,0.00032069124,0.0000039212177],"about_ca_topic_score_codex":0.0015798371,"about_ca_topic_score_gemma":0.002937463,"teacher_disagreement_score":0.0016192503,"about_ca_system_score_codex":0.00022183331,"about_ca_system_score_gemma":0.00020523886,"threshold_uncertainty_score":0.0054169297},"labels":[],"label_agreement":null},{"id":"W4411063250","doi":"10.1007/s00429-025-02932-6","title":"MRI and non-MRI quantifiable neuroanatomical and functional parameters are useful for tractography","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Wellcome Trust","keywords":"Tractography; Neuroscience; Diffusion MRI; Psychology; Magnetic resonance imaging; Computer science; Medicine; Radiology","score_opus":0.0597558029076259,"score_gpt":0.34575043608806444,"score_spread":0.28599463318043855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411063250","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015516079,0.99473625,0.0014680644,0.0014266634,0.0003986704,0.00000673791,0.00004410302,0.000023209604,0.001741017],"genre_scores_gemma":[0.0014469225,0.9954574,0.0016661449,0.00037860358,0.00037613584,0.000014489197,0.00005753314,0.000008732368,0.0005941091],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995086,0.00013124589,0.0000810443,0.00008711459,0.00016229457,0.0000297166],"domain_scores_gemma":[0.9978479,0.0014231002,0.00017562848,0.000090700276,0.00040567736,0.00005703236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002000421,0.0008932001,0.0016898377,0.0033612077,0.00029750628,0.0021373222,0.00086776307,0.0015870323,0.0035539304],"category_scores_gemma":[0.0031475243,0.0004204834,0.0008286076,0.0027786423,0.0016851858,0.0029417663,0.00085781486,0.0029846148,0.0032287668],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004231447,0.00002050707,0.00019725153,0.01668803,0.00014151754,0.00015482937,0.0001073194,0.0007271944,0.0016393755,0.02737078,0.018455397,0.93445563],"study_design_scores_gemma":[0.0000072190282,0.000045933764,0.00092108914,0.007213365,0.00011714104,0.0010220677,0.000098849916,0.0002715563,0.0007831595,0.019662939,0.9698202,0.000036469737],"about_ca_topic_score_codex":0.001321746,"about_ca_topic_score_gemma":0.0021712305,"teacher_disagreement_score":0.0035539304,"about_ca_system_score_codex":0.00088254997,"about_ca_system_score_gemma":0.0019509094,"threshold_uncertainty_score":0.0118890405},"labels":[],"label_agreement":null},{"id":"W4411138398","doi":"10.1002/hbm.70255","title":"Microstructural Characterization of Short Association Fibers Related to Long‐Range White Matter Tracts in Normative Development","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"White matter; Normative; Association (psychology); Characterization (materials science); Psychology; Neuroscience; Medicine; Materials science; Magnetic resonance imaging; Nanotechnology; Philosophy; Radiology; Epistemology","score_opus":0.02964620367892138,"score_gpt":0.3201241704359451,"score_spread":0.2904779667570237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411138398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99784195,0.00021861398,0.0010266654,0.00002127569,0.0000023394343,0.0000061990468,0.00050116604,0.00001538261,0.0003664253],"genre_scores_gemma":[0.99704474,0.00018757465,0.00173066,0.000009253992,0.0000021886553,0.000021832633,0.00056304067,0.000015564678,0.00042511546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997125,0.000034551704,0.000034950917,0.00013508923,0.000052162708,0.00003067903],"domain_scores_gemma":[0.9985929,0.00027872465,0.0005382036,0.00014900303,0.0003189888,0.00012212887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008096089,0.0003469604,0.00022787029,0.0012831563,0.00031599854,0.00058088783,0.0003212065,0.0004253267,0.0012613535],"category_scores_gemma":[0.0030683766,0.00021495885,0.00027058905,0.0005421183,0.00051803206,0.0007059277,0.0005106309,0.00031803804,0.00022265018],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026196023,0.000043750155,0.9410312,0.00008466214,0.00009712248,0.0005892482,0.0014860447,0.00058946933,0.02913408,0.00060444727,0.00030541583,0.02577253],"study_design_scores_gemma":[0.0000015698406,0.000045081255,0.9957632,0.000016828037,0.000018613016,0.00072897895,0.00030689978,0.00063959253,0.001771136,0.0003273536,0.00037366088,0.000007079927],"about_ca_topic_score_codex":0.010003091,"about_ca_topic_score_gemma":0.014831433,"teacher_disagreement_score":0.010003091,"about_ca_system_score_codex":0.00030135267,"about_ca_system_score_gemma":0.00048506106,"threshold_uncertainty_score":0.019889712},"labels":[],"label_agreement":null},{"id":"W4411165765","doi":"10.1016/j.bpsc.2025.06.001","title":"Neurite Density and Kurtosis in the Gray Matter of People With Early Schizophrenia","year":2025,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; Western University","funders":"Janssen Canada; Fonds de Recherche du Québec - Santé; Sunovion; Canadian Institutes of Health Research; Canadian Psychiatric Association; Canada First Research Excellence Fund; Canada Research Chairs; Canada Foundation for Innovation; Physicians' Services Incorporated Foundation; Western University; Academic Medical Organization of Southwestern Ontario; McGill University; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Gray (unit); Kurtosis; Neurite; Neuroscience; Psychiatry; Psychology; Medicine; Biology; Radiology; Mathematics; Statistics","score_opus":0.0389110924635004,"score_gpt":0.3264922113081556,"score_spread":0.2875811188446552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411165765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9991916,0.00012904257,0.00014268013,0.00003065737,0.0000020849996,0.0000042015886,0.00035822505,0.0000060976995,0.0001354766],"genre_scores_gemma":[0.9992748,0.00006897457,0.00025408604,0.000006215543,0.0000022081863,0.0000070885367,0.00031674007,0.0000031472505,0.000066745866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997857,0.000047004374,0.00002359191,0.000068889516,0.000046204466,0.000028583945],"domain_scores_gemma":[0.9986571,0.0003977677,0.0005386669,0.00015085527,0.00012228334,0.00013323549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008262348,0.00049048767,0.0003974123,0.0010165713,0.00039317732,0.0005421586,0.00018854343,0.00033083645,0.0017687903],"category_scores_gemma":[0.0039258506,0.00019989145,0.0005161896,0.0005619397,0.0004653297,0.00038203466,0.0007465314,0.00037538653,0.00016962687],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017200117,0.00008522737,0.977081,0.00011296103,0.00039796994,0.00022076677,0.0011674654,0.0014157722,0.0045988583,0.00019486873,0.00034367538,0.012661307],"study_design_scores_gemma":[0.00001686125,0.00006711532,0.99746394,0.000016989086,0.0000636876,0.00018211521,0.0003158593,0.0010700622,0.0002577044,0.0004386861,0.00009750109,0.000009468393],"about_ca_topic_score_codex":0.013103588,"about_ca_topic_score_gemma":0.015982607,"teacher_disagreement_score":0.013103588,"about_ca_system_score_codex":0.00054265,"about_ca_system_score_gemma":0.00032404668,"threshold_uncertainty_score":0.02605462},"labels":[],"label_agreement":null},{"id":"W4411203935","doi":"10.1371/journal.pone.0324802","title":"Math skills and microstructure of the middle longitudinal fasciculus: A developmental investigation","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Fasciculus; Inferior longitudinal fasciculus; Superior longitudinal fasciculus; Microstructure; Psychology; Medicine; Diffusion MRI; Chemistry; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.07168577405719179,"score_gpt":0.2811281177496088,"score_spread":0.209442343692417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411203935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988477,0.00027956392,0.0003493546,0.000019431509,0.0000013173186,0.0000038377843,0.00016945625,0.0000065700247,0.00032282542],"genre_scores_gemma":[0.9980934,0.00036722576,0.0010254688,0.000008611633,0.00000461126,0.000008730587,0.00018683773,0.0000053967988,0.00029959407],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998714,0.000016010988,0.000012572239,0.000056716584,0.00002227689,0.000021128257],"domain_scores_gemma":[0.9993451,0.00010556394,0.00034477515,0.00005830723,0.00007761151,0.000068708345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036386817,0.00022383982,0.00014119643,0.0014565532,0.00017663075,0.0003560124,0.00016905704,0.00024823623,0.0010607878],"category_scores_gemma":[0.0012968701,0.00014208595,0.0001866081,0.00041064023,0.00040302236,0.00037225813,0.00042388414,0.00020756421,0.00016659845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000313597,0.00007514652,0.8853742,0.000075005686,0.000071361006,0.0009815757,0.0012045559,0.00027955568,0.080388345,0.0003850719,0.00012418763,0.030727265],"study_design_scores_gemma":[0.0000011203998,0.000066816945,0.996783,0.0000053432177,0.000010478616,0.0006437116,0.0000878836,0.00014543673,0.0019700665,0.00007492183,0.00020774618,0.0000034613188],"about_ca_topic_score_codex":0.0032323587,"about_ca_topic_score_gemma":0.0038459236,"teacher_disagreement_score":0.0032323587,"about_ca_system_score_codex":0.00024338713,"about_ca_system_score_gemma":0.00035653528,"threshold_uncertainty_score":0.0064271092},"labels":[],"label_agreement":null},{"id":"W4411236123","doi":"10.1093/mnrasl/slaf062","title":"SHAM-OT: rapid subhalo abundance matching with optimal transport","year":2025,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"Spine Education and Research Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Physics; Astrophysics; Abundance (ecology); Astronomy; Biology; Ecology","score_opus":0.01253571060582177,"score_gpt":0.2506089550133551,"score_spread":0.23807324440753336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411236123","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018932242,0.000099838086,0.9776552,0.00022989414,0.000040651776,0.0000719154,0.00014473627,0.0015582222,0.0012673907],"genre_scores_gemma":[0.40726694,0.00011810023,0.5866381,0.00034472116,0.00010517794,0.0002372319,0.0008744336,0.00081230386,0.0036029615],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992493,0.00023724459,0.000055223893,0.00013050575,0.00022231725,0.000105375184],"domain_scores_gemma":[0.997595,0.0013694891,0.0002252048,0.0003525291,0.00028792542,0.00016981461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002032061,0.00064437796,0.001197806,0.0010383056,0.0006664628,0.0014878312,0.0021967879,0.0016228905,0.0060471497],"category_scores_gemma":[0.010369635,0.00066948764,0.00110292,0.0011805109,0.0011834973,0.002057817,0.003208366,0.0015613062,0.000984023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048691075,0.00014187448,0.0036435237,0.00014734657,0.00008901203,0.00021035086,0.00022026907,0.7507148,0.0034258238,0.07781886,0.0057074935,0.15739377],"study_design_scores_gemma":[0.000023188672,0.000015102342,0.00011427239,0.0000045647525,0.000004170119,0.000017296603,0.000011536723,0.9795476,0.00042622947,0.019299233,0.00053185073,0.000005018849],"about_ca_topic_score_codex":0.009286118,"about_ca_topic_score_gemma":0.008301265,"teacher_disagreement_score":0.009286118,"about_ca_system_score_codex":0.0014303563,"about_ca_system_score_gemma":0.0024097105,"threshold_uncertainty_score":0.020229757},"labels":[],"label_agreement":null},{"id":"W4411266029","doi":"10.55458/neurolibre.00039","title":"Parkinson’s disease in the spinal cord: an exploratorystudy to establish T2*w, MTR and diffusion-weighted imaging metricvalues","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Courtois Foundation; Canada First Research Excellence Fund; Polytechnique Montréal","keywords":"Metric (unit); Parkinson's disease; Diffusion MRI; Spinal cord; Medicine; Disease; Psychology; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Economics; Operations management","score_opus":0.08573376771606607,"score_gpt":0.40164159119129,"score_spread":0.31590782347522395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411266029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98879135,0.0043783686,0.0025923902,0.00032244655,0.00004194938,0.00043576056,0.001913765,0.000053679516,0.0014701835],"genre_scores_gemma":[0.9838256,0.0021726864,0.008529774,0.00021508611,0.00010380233,0.0003939154,0.0034754262,0.000059309834,0.0012242452],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991561,0.0002834179,0.00008313239,0.00018101108,0.00020776191,0.00008860494],"domain_scores_gemma":[0.9978255,0.00040442462,0.00049831445,0.00042537332,0.0005592654,0.0002871251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041332105,0.0013924794,0.0010054776,0.0012422682,0.00086742867,0.0011680712,0.00064490753,0.0011514686,0.002290029],"category_scores_gemma":[0.005262609,0.0005049586,0.0007110701,0.0009605533,0.00080357236,0.0013482556,0.001595546,0.00095968245,0.00075753906],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02286515,0.004792433,0.7130875,0.0023732975,0.0021534823,0.01617489,0.0054770987,0.0013353262,0.06510082,0.001502805,0.008291107,0.15684609],"study_design_scores_gemma":[0.00072665437,0.007130214,0.9543571,0.0002721789,0.001161465,0.014158665,0.0015119811,0.0016780616,0.008404058,0.0026408439,0.007827884,0.00013082048],"about_ca_topic_score_codex":0.0032417576,"about_ca_topic_score_gemma":0.0054080007,"teacher_disagreement_score":0.0041332105,"about_ca_system_score_codex":0.0007959157,"about_ca_system_score_gemma":0.0007690456,"threshold_uncertainty_score":0.021858752},"labels":[],"label_agreement":null},{"id":"W4411349417","doi":"10.1007/s00429-025-02964-y","title":"The tractographer’s dilemma: understanding sources of variability in tractography","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Hanarth Fonds; European Research Council; Alzheimer Nederland; Galen and Hilary Weston Foundation","keywords":"Dilemma; Tractography; Psychology; Computer science; Philosophy; Medicine; Diffusion MRI; Epistemology; Radiology; Magnetic resonance imaging","score_opus":0.08098850839584715,"score_gpt":0.3625468262216743,"score_spread":0.28155831782582713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411349417","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015587456,0.9778953,0.004975146,0.015060825,0.0010250222,0.0000055323494,0.000046038742,0.000039938543,0.0007963393],"genre_scores_gemma":[0.002989669,0.9786104,0.006560111,0.006382332,0.004545629,0.000026594369,0.00007156914,0.00004090034,0.0007727599],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986639,0.0005356237,0.0001708591,0.000231701,0.00036125781,0.000036604906],"domain_scores_gemma":[0.9830142,0.013640187,0.0005033682,0.0004441533,0.0021686535,0.00022932877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068493187,0.0010176735,0.0026908964,0.0030729645,0.00046003258,0.003075054,0.0020944024,0.004038651,0.0025510676],"category_scores_gemma":[0.01616862,0.00047108927,0.0009727533,0.0028853498,0.0045210538,0.008036619,0.0015954693,0.0071017733,0.00173865],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054513275,0.000026213864,0.00046484687,0.0077934484,0.00024833172,0.00022731918,0.00031556227,0.00080879417,0.0007582568,0.03773826,0.06014381,0.8914207],"study_design_scores_gemma":[0.000029581674,0.000082855055,0.0017903991,0.012038561,0.00022088131,0.0023147885,0.00045471758,0.0012548997,0.0005560859,0.15552865,0.82558817,0.00014046552],"about_ca_topic_score_codex":0.0044311094,"about_ca_topic_score_gemma":0.005850468,"teacher_disagreement_score":0.0068493187,"about_ca_system_score_codex":0.0015034813,"about_ca_system_score_gemma":0.0038428449,"threshold_uncertainty_score":0.036223114},"labels":[],"label_agreement":null},{"id":"W4411349534","doi":"10.1007/s00429-025-02938-0","title":"Think deep in the tractography game: deep learning for tractography computing and analysis","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Tractography; Deep learning; Computer science; Artificial intelligence; Data science; Psychology; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.033750727196719565,"score_gpt":0.36135284852739324,"score_spread":0.3276021213306737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411349534","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007702465,0.9555909,0.034361757,0.0026688694,0.00066976517,0.000033786433,0.0002475375,0.00048527785,0.005171753],"genre_scores_gemma":[0.008834273,0.9529567,0.029919121,0.0014261334,0.00092053734,0.0000928197,0.00047052777,0.00013209297,0.0052477377],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998754,0.000031873013,0.000011750814,0.000020794985,0.00004893568,0.000011136487],"domain_scores_gemma":[0.9995685,0.0002935878,0.000028843571,0.00001560967,0.00006121052,0.00003213182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005271751,0.0008831473,0.00083221664,0.0009389686,0.00014049525,0.00095464895,0.0009688381,0.0012153896,0.0058973273],"category_scores_gemma":[0.0013569336,0.00027787354,0.0005067325,0.0011405211,0.00048569098,0.0013188218,0.0007147266,0.002255835,0.0023665775],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055228847,0.000052995074,0.000104092425,0.0040712445,0.0001230526,0.000060765524,0.00002392188,0.0022636508,0.0010489118,0.008415321,0.039261173,0.9445197],"study_design_scores_gemma":[0.00010818472,0.00016376146,0.0008159341,0.004513405,0.00025028124,0.0010097936,0.00003836116,0.011454668,0.0031808221,0.048973724,0.9293984,0.00009278272],"about_ca_topic_score_codex":0.0016876045,"about_ca_topic_score_gemma":0.0037296058,"teacher_disagreement_score":0.0058973273,"about_ca_system_score_codex":0.0004228776,"about_ca_system_score_gemma":0.00096492126,"threshold_uncertainty_score":0.019728482},"labels":[],"label_agreement":null},{"id":"W4411626609","doi":"10.1016/j.neuroimage.2025.121324","title":"Diffusion Bubble Model: A novel MRI approach for detection and subtyping of neonatal punctate white matter lesions","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Centre de recherche du CHU Sainte-Justine; Canada First Research Excellence Fund; China Scholarship Council; Polytechnique Montréal; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Voxel; White matter; Nuclear magnetic resonance; Isotropy; Diffusion; Magnetic resonance imaging; Anisotropy; Chemistry; Nuclear medicine; Physics; Optics; Radiology; Medicine","score_opus":0.04398671906828196,"score_gpt":0.31851831759380167,"score_spread":0.2745315985255197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411626609","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.077392094,0.00064514496,0.9202173,0.00013356585,0.000030842082,0.000062405656,0.00020667401,0.0007573619,0.00055457413],"genre_scores_gemma":[0.5517192,0.00074465247,0.44543374,0.00006926624,0.000053922027,0.00017939399,0.00049233827,0.00022150131,0.0010859161],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99980193,0.00005768573,0.000014467718,0.000055352004,0.000050442955,0.000020245214],"domain_scores_gemma":[0.99954945,0.00017120711,0.00009831681,0.00004484155,0.000083327155,0.000052863266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005520923,0.0007402756,0.0006005195,0.0014951178,0.00022399439,0.0006073059,0.0007147303,0.00075533177,0.00054700096],"category_scores_gemma":[0.0017947783,0.00027920614,0.0005934991,0.00050528964,0.00035985722,0.00088145287,0.0006876565,0.0005261703,0.00020195414],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085593906,0.00017664471,0.03758037,0.00040253968,0.0003144516,0.0014097595,0.0004835389,0.17153364,0.50617677,0.026634816,0.0025447549,0.2518868],"study_design_scores_gemma":[0.000016893338,0.00013676057,0.004856189,0.000013062728,0.00004728194,0.00075400306,0.000049875907,0.96598047,0.020957604,0.005416171,0.0017238881,0.000047753],"about_ca_topic_score_codex":0.0032987564,"about_ca_topic_score_gemma":0.002408213,"teacher_disagreement_score":0.0032987564,"about_ca_system_score_codex":0.00038240562,"about_ca_system_score_gemma":0.00055505335,"threshold_uncertainty_score":0.0065591335},"labels":[],"label_agreement":null},{"id":"W4411661858","doi":"10.1007/s00415-025-13201-1","title":"Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration","year":2025,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; NOSM University; Women and Children’s Health Research Institute; University of Alberta; Centre for Addiction and Mental Health; Toronto Public Health; Sunnybrook Health Science Centre; Western University; Bruyère; Ottawa Hospital; Health Sciences Centre; University Health Network; Wilfrid Laurier University; Montreal Neurological Institute and Hospital; Baycrest Hospital; McGill University; University of Ottawa; Ontario Brain Institute; Toronto Western Hospital; Canada Research Chairs","funders":"","keywords":"Neuroinflammation; Neurodegeneration; Neurology; Neuroradiology; Neuroscience; Diffusion MRI; Medicine; Psychology; Magnetic resonance imaging; Pathology; Internal medicine; Inflammation; Disease","score_opus":0.030498215015040117,"score_gpt":0.3328593692701872,"score_spread":0.3023611542551471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411661858","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9808795,0.010467043,0.0051208413,0.0003123921,0.00007092119,0.00004333854,0.00044817373,0.00007966868,0.002578024],"genre_scores_gemma":[0.99488515,0.0021957299,0.0014467424,0.00008581762,0.00012507378,0.000026543563,0.0002651734,0.000025693998,0.0009440272],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967194,0.00007354097,0.00004636835,0.0001074385,0.000055207747,0.000045516063],"domain_scores_gemma":[0.9971173,0.00044541026,0.0017574811,0.00016410844,0.00033316034,0.00018265938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092636934,0.00076892355,0.0007985275,0.0013643457,0.00042177064,0.00074758363,0.00033158323,0.00057205016,0.0022174309],"category_scores_gemma":[0.0021363096,0.00027086833,0.0004273914,0.0009880654,0.00073028344,0.0012478841,0.0004454738,0.000576559,0.00035397575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006888879,0.000462223,0.6534912,0.0016539955,0.001867164,0.0036761365,0.0010378051,0.00063590973,0.27402395,0.0010992509,0.0011581673,0.05400526],"study_design_scores_gemma":[0.000030414665,0.00069983763,0.9636769,0.00010335095,0.00046680696,0.0055114985,0.00050054,0.0007800937,0.02454576,0.0024920052,0.0011519251,0.000040952236],"about_ca_topic_score_codex":0.001034865,"about_ca_topic_score_gemma":0.0011288207,"teacher_disagreement_score":0.0022174309,"about_ca_system_score_codex":0.00023824963,"about_ca_system_score_gemma":0.0003334577,"threshold_uncertainty_score":0.007418096},"labels":[],"label_agreement":null},{"id":"W4411729192","doi":"10.1016/j.neuroimage.2025.121347","title":"Comparison of post-stroke white matter assessment using disconnectome-symptom mapping versus quantitative diffusion MRI","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Medical Rehabilitation Research; National Institute of General Medical Sciences; National Institutes of Health; Deutsche Forschungsgemeinschaft; National Institute of Child Health and Human Development; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs","keywords":"White matter; Diffusion MRI; Stroke (engine); Diffusion; Medicine; Psychology; Physical medicine and rehabilitation; Radiology; Magnetic resonance imaging; Physics","score_opus":0.10560227963598093,"score_gpt":0.44323627140923383,"score_spread":0.33763399177325293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411729192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922312,0.0003063503,0.0059785885,0.00002621774,0.0000073781466,0.00004362988,0.0010211555,0.000048347563,0.00033719288],"genre_scores_gemma":[0.99304926,0.000114522045,0.0039181462,0.000018117515,0.000012196791,0.00010475683,0.002573998,0.000021917907,0.0001870073],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99860966,0.000541925,0.00017300542,0.0004081371,0.00018992739,0.00007742183],"domain_scores_gemma":[0.997558,0.0010057576,0.0006477504,0.00044608887,0.00023735316,0.0001050693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026958175,0.0005086925,0.0004523288,0.0013141774,0.00016715823,0.00073367526,0.00040173923,0.00057481084,0.0008245195],"category_scores_gemma":[0.0059050843,0.00013181403,0.00039571623,0.00065272447,0.00040533277,0.0006560917,0.00080699247,0.00022328965,0.00027012895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012583891,0.0003957928,0.80491227,0.00097596087,0.0052749556,0.0004066378,0.0012482378,0.0057723685,0.06864687,0.00095201895,0.0011638546,0.09766721],"study_design_scores_gemma":[0.00010329153,0.0011434164,0.97856516,0.000035734778,0.00031194466,0.0008296214,0.00027449508,0.010593689,0.0063916333,0.00068573264,0.0010232418,0.0000419999],"about_ca_topic_score_codex":0.0008076717,"about_ca_topic_score_gemma":0.0018847685,"teacher_disagreement_score":0.0026958175,"about_ca_system_score_codex":0.00015823632,"about_ca_system_score_gemma":0.0001930699,"threshold_uncertainty_score":0.014257014},"labels":[],"label_agreement":null},{"id":"W4411894088","doi":"10.1002/mrm.30620","title":"Myelin water and tensor‐valued diffusion imaging: (How) are they related?","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; Philips (Canada); University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Myelin; Pathological; Tractography; Pathology; Abnormality; Correlation; Multiple sclerosis; Medicine; Neuroscience; Biology; Magnetic resonance imaging; Central nervous system; Radiology; Mathematics","score_opus":0.024904762421955735,"score_gpt":0.3171838362803847,"score_spread":0.292279073858429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411894088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9272346,0.046573304,0.014773564,0.0047148974,0.00028577232,0.00008911192,0.00047056703,0.00013142111,0.005726828],"genre_scores_gemma":[0.98967534,0.0052704504,0.003935417,0.00026314732,0.00018000968,0.000026169344,0.00012428778,0.000028278055,0.00049675675],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99883837,0.0003957193,0.000092750655,0.00028125136,0.00024812488,0.0001437481],"domain_scores_gemma":[0.992269,0.0021249468,0.003021917,0.00059743045,0.0016227659,0.0003639707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002758332,0.0005804761,0.00076864153,0.0020415462,0.00033653982,0.002240835,0.0005935681,0.0008931673,0.00190111],"category_scores_gemma":[0.018830653,0.00042175033,0.00054887537,0.0023123964,0.0017672015,0.0035132125,0.0010058044,0.00096838456,0.0004522361],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049295934,0.0001475519,0.76711315,0.0007637701,0.0011280999,0.00047463854,0.0019182856,0.0015034212,0.0101114465,0.0057905447,0.0017609071,0.20879528],"study_design_scores_gemma":[0.000018902781,0.00034074447,0.97319305,0.00033544653,0.0003280707,0.0014817627,0.0015762778,0.0044367923,0.0021502222,0.013772259,0.0022863469,0.00008010459],"about_ca_topic_score_codex":0.004616723,"about_ca_topic_score_gemma":0.0029341162,"teacher_disagreement_score":0.004616723,"about_ca_system_score_codex":0.00060678343,"about_ca_system_score_gemma":0.0007204284,"threshold_uncertainty_score":0.014587641},"labels":[],"label_agreement":null},{"id":"W4412166637","doi":"10.1017/cjn.2025.10174","title":"E.2 Isolated restricted diffusion at admission predicts survival in patients of glioblastoma (IRD-GB) – a prospective pilot study","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Glioblastoma; Prospective cohort study; Internal medicine; Oncology; Medicine; Diffusion; Cancer research; Physics; Thermodynamics","score_opus":0.04163984647954227,"score_gpt":0.31332197764372854,"score_spread":0.27168213116418627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412166637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996754,0.000043475604,0.000022579788,0.000008570313,0.000001910119,0.000006223795,0.00012310612,0.000001397329,0.000117351105],"genre_scores_gemma":[0.99970156,0.000019813928,0.000039394024,0.0000053426916,0.000004073352,0.0000059523295,0.00017900759,6.618678e-7,0.000044048335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997904,0.000054800075,0.00002269634,0.000051093706,0.000031380147,0.00004981231],"domain_scores_gemma":[0.99874085,0.00031510636,0.00043386503,0.0000934631,0.00015400644,0.00026267802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005849063,0.00030561863,0.00020445445,0.0005987664,0.00029299772,0.0004140652,0.00021840922,0.00038212887,0.0019954161],"category_scores_gemma":[0.0023473953,0.00017856613,0.000346116,0.0004602355,0.00023510423,0.00037109383,0.0003755288,0.00034625953,0.00041988198],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030867523,0.00004516636,0.9988788,0.000003720338,0.000013529895,0.000046275083,0.000020044403,0.000017318125,0.00011293708,0.000003286219,0.00002948079,0.0005208365],"study_design_scores_gemma":[0.000022798651,0.00060798984,0.9984327,0.0000036102817,0.000032010088,0.00042680444,0.00008139073,0.00020156872,0.00008457471,0.00001291174,0.00009004348,0.0000034990883],"about_ca_topic_score_codex":0.0027821127,"about_ca_topic_score_gemma":0.0026660655,"teacher_disagreement_score":0.0027821127,"about_ca_system_score_codex":0.00020545542,"about_ca_system_score_gemma":0.00030251275,"threshold_uncertainty_score":0.006675303},"labels":[],"label_agreement":null},{"id":"W4412166743","doi":"10.1017/cjn.2025.10310","title":"P.165 Comparison of preoperative diffusion tensor imaging tractography platforms for intrinsic brain lesions","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton; Workers Compensation Board of Alberta","funders":"","keywords":"Diffusion MRI; Tractography; Medicine; Neuroscience; Nuclear magnetic resonance; Radiology; Psychology; Magnetic resonance imaging; Physics","score_opus":0.073518601362403,"score_gpt":0.3690019808808544,"score_spread":0.2954833795184514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412166743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99635136,0.00042277435,0.0018493464,0.00002016676,0.000015248125,0.000047328096,0.00034076654,0.000029448995,0.00092357164],"genre_scores_gemma":[0.99783605,0.00010059094,0.0013908391,0.000007541307,0.000013021501,0.000042415948,0.0004389496,0.000019289439,0.00015131135],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989109,0.000261712,0.00026318672,0.00016021845,0.00030604468,0.00009796619],"domain_scores_gemma":[0.9905612,0.0043959483,0.0021834031,0.0005795675,0.0017534888,0.00052645116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027778812,0.00041267887,0.00029413405,0.0016491581,0.00026979638,0.00077317865,0.00031251778,0.00025820278,0.0052873045],"category_scores_gemma":[0.012077123,0.00018269711,0.00068669935,0.0006832754,0.00040414502,0.0009078277,0.0007314807,0.00029663,0.001185709],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00462331,0.00013856657,0.9233571,0.00018956808,0.00021847177,0.0004070069,0.0003773713,0.0007011725,0.00430944,0.00010411683,0.00044600174,0.065127864],"study_design_scores_gemma":[0.000083578336,0.006688477,0.9796679,0.000089753215,0.0002280728,0.0033254789,0.0004647647,0.0030523108,0.004965735,0.00020181248,0.0011990354,0.00003303953],"about_ca_topic_score_codex":0.0005955674,"about_ca_topic_score_gemma":0.0008021914,"teacher_disagreement_score":0.0052873045,"about_ca_system_score_codex":0.0003473226,"about_ca_system_score_gemma":0.0004655427,"threshold_uncertainty_score":0.017687857},"labels":[],"label_agreement":null},{"id":"W4412392585","doi":"10.1038/s41597-025-05350-9","title":"In vivo submillimeter diffusion MRI dataset of 9 macaque brains curated for tractography","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"HORIZON EUROPE Framework Programme; Université de Bordeaux; Alliance de recherche numérique du Canada; Conseil Régional Aquitaine; European Commission","keywords":"Macaque; Tractography; Diffusion MRI; Neuroscience; Computer science; Biology; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.11451306423913672,"score_gpt":0.4241875787324237,"score_spread":0.309674514493287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412392585","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4679831,0.006059244,0.073525764,0.0013426845,0.00038560326,0.0007028115,0.43080038,0.01123228,0.007968216],"genre_scores_gemma":[0.2349556,0.0016323683,0.086798996,0.00037605548,0.00014291702,0.0012424173,0.6679913,0.0014178791,0.005442491],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996124,0.00004316805,0.00004396392,0.00015759737,0.00009486349,0.000048032132],"domain_scores_gemma":[0.9991073,0.00012371046,0.00009250193,0.00027246465,0.00033283216,0.0000712328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000552525,0.0012894493,0.0009862211,0.0020305165,0.0009624404,0.0006862238,0.00084288523,0.0011439191,0.0029924035],"category_scores_gemma":[0.001763072,0.00034941142,0.0011873941,0.0017607395,0.0005420072,0.00040673435,0.0011628866,0.0009557679,0.0029714308],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014038201,0.00070028903,0.033411015,0.003925073,0.0014996574,0.0052944943,0.0018305775,0.021827187,0.3199619,0.003952481,0.3054076,0.30078587],"study_design_scores_gemma":[0.00034739226,0.0006698927,0.23588082,0.00069269683,0.00097536785,0.011903077,0.00085864135,0.040470283,0.099842094,0.0099455025,0.5980451,0.00036913788],"about_ca_topic_score_codex":0.017194832,"about_ca_topic_score_gemma":0.038073275,"teacher_disagreement_score":0.017194832,"about_ca_system_score_codex":0.0005840464,"about_ca_system_score_gemma":0.0016174536,"threshold_uncertainty_score":0.034189522},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"agree"},{"id":"W4412413781","doi":"10.1007/s11357-025-01773-9","title":"Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fiber calibre, and vascularization","year":2025,"lang":"en","type":"article","venue":"GeroScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Caliber; Fiber; Biology; Anatomy; White (mutation); Order (exchange); Neuroscience; Medicine; Genetics; Engineering; Magnetic resonance imaging; Mechanical engineering; Chemistry","score_opus":0.09633646232879,"score_gpt":0.3509578979395293,"score_spread":0.2546214356107393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412413781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9472697,0.0005377072,0.045462083,0.0010632647,0.00014253518,0.000056938516,0.00050451414,0.00017330746,0.004790108],"genre_scores_gemma":[0.9898469,0.00012806867,0.008978971,0.00009053533,0.000033357584,0.000031346888,0.0001016841,0.000077138466,0.0007119882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99929,0.0001677167,0.00005430175,0.00030137316,0.00012959845,0.000056939552],"domain_scores_gemma":[0.99154156,0.0032080768,0.0024018323,0.0016941762,0.0007074049,0.00044698303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039009282,0.00083797105,0.00030447333,0.0010145028,0.00049367885,0.0014552965,0.0013517373,0.00083781534,0.00589213],"category_scores_gemma":[0.013939991,0.00030285932,0.00037527544,0.00045858012,0.003289271,0.0032353941,0.0009294775,0.0010288939,0.00033848488],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023567618,0.0005382512,0.5729855,0.00054437265,0.0004657403,0.002015306,0.0047426834,0.0065448317,0.17263688,0.17353994,0.0012993837,0.062330373],"study_design_scores_gemma":[0.00013347351,0.0020129676,0.6934713,0.00016010071,0.00044500933,0.0031211353,0.0043227607,0.03208114,0.07187246,0.18739474,0.0048526633,0.00013240323],"about_ca_topic_score_codex":0.0013400569,"about_ca_topic_score_gemma":0.0017277177,"teacher_disagreement_score":0.00589213,"about_ca_system_score_codex":0.0006085261,"about_ca_system_score_gemma":0.0011577934,"threshold_uncertainty_score":0.02063036},"labels":[],"label_agreement":null},{"id":"W4412530434","doi":"10.1371/journal.pbio.3003241","title":"Personalised regional modelling predicts tau progression in the human brain","year":2025,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Engineering and Physical Sciences Research Council; Greta och Johan Kocks stiftelser; Fonds de Recherche du Québec - Santé; Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse; National Institute of Mental Health; Cure Alzheimer's Fund; Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse; F. Hoffmann-La Roche; Hjärnfonden; National Institute on Aging; Alzheimer's Association; Wellcome Trust; GHR Foundation","keywords":"Biology; Neuroscience; Human brain; Computational biology","score_opus":0.1507732709786695,"score_gpt":0.4172186440886334,"score_spread":0.2664453731099639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412530434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71508205,0.0016500881,0.27393717,0.0012372747,0.00012526845,0.00011033489,0.0021203551,0.0011246809,0.0046127154],"genre_scores_gemma":[0.9801048,0.0004141976,0.016453465,0.00010203378,0.000032527532,0.00007708123,0.0006275389,0.00012919873,0.0020593118],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998977,0.000039175146,0.000004459755,0.00003504438,0.00001078932,0.000012785988],"domain_scores_gemma":[0.99958605,0.00022962854,0.00006595439,0.0000407553,0.000045995395,0.00003163452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066290714,0.0006462476,0.0006239316,0.0005743864,0.0002066789,0.0008840456,0.0006938822,0.0013307001,0.001440272],"category_scores_gemma":[0.0022006438,0.00040170192,0.0009231666,0.00038649092,0.0004085378,0.00047096104,0.0004739146,0.0006002554,0.0004993625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009520713,0.000030596504,0.003627176,0.00002488648,0.00004727013,0.00008694995,0.00003824687,0.9890191,0.0013167849,0.0007182545,0.00044502795,0.004550526],"study_design_scores_gemma":[0.000005987699,0.000014924295,0.0008086035,0.000004457546,0.000008351867,0.00003116869,0.0000062617232,0.99772924,0.00019769717,0.0009983797,0.0001887001,0.0000062758263],"about_ca_topic_score_codex":0.014543061,"about_ca_topic_score_gemma":0.011979093,"teacher_disagreement_score":0.014543061,"about_ca_system_score_codex":0.00070982095,"about_ca_system_score_gemma":0.0007511084,"threshold_uncertainty_score":0.028916836},"labels":[],"label_agreement":null},{"id":"W4412573094","doi":"10.1007/s11357-025-01787-3","title":"Variations in perfusion detectable in advance of microstructure in white matter aging","year":2025,"lang":"en","type":"article","venue":"GeroScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Microstructure; White (mutation); Medicine; Materials science; Chemistry; Magnetic resonance imaging; Metallurgy; Radiology","score_opus":0.01655770807556216,"score_gpt":0.32980770114065394,"score_spread":0.31324999306509177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412573094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984894,0.0026135184,0.008637044,0.0002508549,0.00007409608,0.00002319534,0.0007332841,0.00009940071,0.002674575],"genre_scores_gemma":[0.9956305,0.0007136506,0.0024122396,0.00006011045,0.000086355474,0.000013207423,0.00019265708,0.000021446023,0.00086988707],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999361,0.000014018751,0.000005299734,0.00001743293,0.000012478599,0.000014710818],"domain_scores_gemma":[0.9996772,0.000077758836,0.000113707385,0.000029095227,0.000054773598,0.000047505688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043732589,0.00030287,0.0001650324,0.0006906942,0.00017492553,0.000515656,0.00019426557,0.00058142684,0.0018085748],"category_scores_gemma":[0.0011772206,0.00020370938,0.00013313763,0.0005062495,0.00029362243,0.0007342684,0.00030275105,0.000536496,0.0001644769],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043466347,0.00017101124,0.15609223,0.00042535923,0.00028169053,0.0034647093,0.0010512918,0.0015477762,0.74085075,0.0035606727,0.0017345316,0.086473204],"study_design_scores_gemma":[0.000039959097,0.0009295569,0.9020189,0.00005791602,0.00021625287,0.0037820884,0.00044155927,0.004436662,0.07969085,0.006167122,0.0021769647,0.000042198863],"about_ca_topic_score_codex":0.0014004076,"about_ca_topic_score_gemma":0.0018714124,"teacher_disagreement_score":0.0018085748,"about_ca_system_score_codex":0.00014172737,"about_ca_system_score_gemma":0.00020041608,"threshold_uncertainty_score":0.0060502887},"labels":[],"label_agreement":null},{"id":"W4412589709","doi":"10.1038/s44400-025-00024-0","title":"Smoking predicts brain atrophy in 10,134 healthy individuals and is potentially influenced by body mass index","year":2025,"lang":"en","type":"article","venue":"npj Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada); AXYS Technologies (Canada)","funders":"National Institute on Aging; National Institutes of Health","keywords":"Precuneus; White matter; Atrophy; Brain size; Temporal lobe; Body mass index; Medicine; Neuroimaging; Neurodegeneration; Imaging biomarker; Internal medicine; Posterior cingulate; Dementia; Cardiology; Psychology; Magnetic resonance imaging; Neuroscience; Cortex (anatomy); Radiology; Cognition; Epilepsy","score_opus":0.0178539470451032,"score_gpt":0.3365159294493598,"score_spread":0.31866198240425664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412589709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9996158,0.000059659953,0.000047229663,0.000009123751,0.0000033675885,0.00000696607,0.0001460062,0.0000034290208,0.00010838252],"genre_scores_gemma":[0.99938786,0.000030472569,0.00007382803,0.000010147613,0.000004940639,0.000009637463,0.00026221402,0.0000022628913,0.00021866345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99968004,0.00010408417,0.000025832856,0.000085633794,0.00005667427,0.000047653706],"domain_scores_gemma":[0.99947757,0.00012986331,0.00016241928,0.000060250823,0.000058361467,0.00011162168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007298705,0.0004712678,0.00036392212,0.0005101108,0.0005688689,0.0004437454,0.00039484052,0.00070423447,0.0016542367],"category_scores_gemma":[0.0014268713,0.0005260848,0.000447159,0.00047326338,0.00034511514,0.00033805709,0.0004481746,0.0005229042,0.00038746413],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003790686,0.00007272719,0.99830973,0.000004632599,0.00007075504,0.000040395942,0.000043838547,0.00003417264,0.0003267078,0.000006405504,0.000057054833,0.00065463525],"study_design_scores_gemma":[0.000009833045,0.00012552961,0.9994885,0.0000013049727,0.000028657538,0.00008038002,0.00004092393,0.0001306613,0.00003512699,0.000011524524,0.000045457524,0.0000020827765],"about_ca_topic_score_codex":0.0068507465,"about_ca_topic_score_gemma":0.011150736,"teacher_disagreement_score":0.0068507465,"about_ca_system_score_codex":0.00018726797,"about_ca_system_score_gemma":0.00020684645,"threshold_uncertainty_score":0.0136217475},"labels":[],"label_agreement":null},{"id":"W4412602088","doi":"10.1001/jamanetworkopen.2025.22211","title":"Distinct Patterns of Weight Gain, Age, and Subcortical Microstructure in Early Adolescence","year":2025,"lang":"en","type":"article","venue":"JAMA Network Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Weight gain; Medicine; Body mass index; Cohort; Overweight; Demography; Percentile; Cohort study; Longitudinal study; Obesity; Synaptic pruning; Weight change; Gerontology; Internal medicine; Psychology; Weight loss; Body weight; Pathology","score_opus":0.027604382389156076,"score_gpt":0.33935597113193594,"score_spread":0.31175158874277986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412602088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981177,0.0006600703,0.00022985387,0.00004870777,0.000004512039,0.000008964076,0.00042256629,0.0000067259266,0.00050092954],"genre_scores_gemma":[0.9988341,0.00029904337,0.0002816369,0.0000175865,0.000003963555,0.000012857237,0.0003106444,0.000004360992,0.00023582597],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997764,0.000037012647,0.000020818445,0.000078000965,0.000041985328,0.000045755674],"domain_scores_gemma":[0.9993111,0.00007874726,0.00036945796,0.000048040554,0.000105148996,0.00008756386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053993956,0.00022290528,0.00021462729,0.00079969753,0.00026782884,0.0005479285,0.00026491363,0.00027063032,0.00094838184],"category_scores_gemma":[0.0016222562,0.00020959952,0.00027681404,0.0007947156,0.00030149694,0.0003462947,0.0004541585,0.00032522244,0.00012316981],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047453115,0.000012483948,0.99593264,0.000014646596,0.000048588165,0.00004230828,0.00021446632,0.0000246242,0.00062774285,0.00006707514,0.00007300684,0.0028950744],"study_design_scores_gemma":[4.2582795e-7,0.000010445779,0.9996749,0.00000556498,0.0000074233103,0.00004580578,0.000080280784,0.000037439066,0.000046494824,0.000020201043,0.00007018232,7.547674e-7],"about_ca_topic_score_codex":0.013681947,"about_ca_topic_score_gemma":0.034858067,"teacher_disagreement_score":0.013681947,"about_ca_system_score_codex":0.0002531221,"about_ca_system_score_gemma":0.0004023897,"threshold_uncertainty_score":0.027204633},"labels":[],"label_agreement":null},{"id":"W4412627997","doi":"10.1371/journal.pone.0327828","title":"Assessing quantitative MRI techniques using multimodal comparisons","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Concordia University; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Heart And Stroke Foundation Of Quebec; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Bundesministerium für Bildung und Forschung; Horizon 2020 Framework Programme; Deutsche Forschungsgemeinschaft; Natural Sciences and Engineering Research Council of Canada; European Commission; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Heart and Stroke Foundation of Canada","keywords":"White matter; Fractional anisotropy; Neuroscience; Magnetization transfer; Context (archaeology); Neuroimaging; Grey matter; Diffusion MRI; Brain tissue; Contrast (vision); Cognitive neuroscience; Brain mapping; Computer science; Nuclear magnetic resonance; Magnetic resonance imaging; Artificial intelligence; Cognition; Biology; Physics; Medicine","score_opus":0.31408587125337306,"score_gpt":0.4598301876674588,"score_spread":0.14574431641408575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412627997","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09007125,0.0023303903,0.89497924,0.00041120028,0.00021133716,0.0006260095,0.0015065141,0.0021431085,0.007720933],"genre_scores_gemma":[0.51607674,0.0011015336,0.47781077,0.00020169294,0.00019131832,0.0011779717,0.0012212656,0.0007132016,0.0015054063],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99050343,0.0036143013,0.0009872784,0.002188696,0.0024451215,0.00026116948],"domain_scores_gemma":[0.97733855,0.011636432,0.0042120637,0.0029425058,0.0036268658,0.00024357252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018621327,0.002030415,0.00093297724,0.007324536,0.00080741895,0.004028927,0.0011396614,0.0012695749,0.0052100825],"category_scores_gemma":[0.049073234,0.00055747526,0.0010107862,0.005377626,0.0017919077,0.003297678,0.002165044,0.0010583824,0.0010632839],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080245954,0.00032344024,0.09494267,0.0034296315,0.0028200117,0.00043199476,0.0029362424,0.028895585,0.15019943,0.04075677,0.0059323823,0.6685293],"study_design_scores_gemma":[0.00016640633,0.0032675415,0.33965433,0.0012543775,0.0020955778,0.0038351936,0.0037585904,0.28376764,0.14008129,0.166899,0.05439931,0.0008207587],"about_ca_topic_score_codex":0.001207207,"about_ca_topic_score_gemma":0.0016736415,"teacher_disagreement_score":0.018621327,"about_ca_system_score_codex":0.00090540556,"about_ca_system_score_gemma":0.0010478741,"threshold_uncertainty_score":0.098480165},"labels":[],"label_agreement":null},{"id":"W4412831590","doi":"10.1162/imag.a.115","title":"High resolution diffusion tensor imaging of the human cortex reveals non-linear trajectories over the healthy lifespan","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Diffusion MRI; Diffusion; Cortex (anatomy); High resolution; Tensor (intrinsic definition); Resolution (logic); Neuroscience; Psychology; Physics; Medicine; Mathematics; Computer science; Artificial intelligence; Geology; Magnetic resonance imaging; Geometry; Radiology","score_opus":0.03466408011579197,"score_gpt":0.36411149534523335,"score_spread":0.3294474152294414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412831590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911526,0.00263016,0.0035299468,0.0001381769,0.000008518861,0.000014334708,0.0010030452,0.00007262914,0.001450548],"genre_scores_gemma":[0.9941064,0.0016203843,0.002936386,0.000035646535,0.0000084603125,0.00001046481,0.0006656855,0.00001755592,0.0005989844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999162,0.000015434665,0.0000094035895,0.000024673605,0.000021025924,0.000013278677],"domain_scores_gemma":[0.999724,0.000034442084,0.00011380568,0.000032567215,0.00007107923,0.000024108787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034783175,0.00025119638,0.00013586548,0.00088320574,0.00016821221,0.00035660993,0.0000868067,0.00018960929,0.00043917907],"category_scores_gemma":[0.0012323733,0.0001510526,0.00012405596,0.00056471373,0.0002440843,0.00033944318,0.00021421285,0.00014455922,0.0002159937],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005853998,0.00007731762,0.5510618,0.0004318732,0.00050378154,0.002594998,0.0025222998,0.003672403,0.23720612,0.0016544343,0.0038120619,0.19587754],"study_design_scores_gemma":[0.0000043955415,0.000100958525,0.9899138,0.000029229437,0.000042011066,0.0015996811,0.00019277618,0.0012083193,0.0042271595,0.0009234527,0.0017418684,0.00001622432],"about_ca_topic_score_codex":0.008006394,"about_ca_topic_score_gemma":0.0126040075,"teacher_disagreement_score":0.008006394,"about_ca_system_score_codex":0.00018480713,"about_ca_system_score_gemma":0.00028003473,"threshold_uncertainty_score":0.015919566},"labels":[],"label_agreement":null},{"id":"W4412839143","doi":"10.1002/hbm.70265","title":"Enhanced Detection of Age‐Related and Cognitive Declines Using Automated Hippocampal‐To‐Ventricle Ratio in Alzheimer's Patients","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; National Institutes of Health; Health Canada; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Fondation Brain Canada; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Atrophy; Segmentation; Fornix; Neuroimaging; Psychology; Biomarker; Alzheimer's disease; Neuroscience; Internal medicine; Audiology; Medicine; Hippocampus; Disease; Artificial intelligence; Computer science; Chemistry","score_opus":0.06619587824073389,"score_gpt":0.3785401440390851,"score_spread":0.3123442657983512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412839143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99105775,0.0009140387,0.0061541563,0.00005042751,0.000024073835,0.000041596093,0.0007315755,0.00028994877,0.0007363696],"genre_scores_gemma":[0.9920387,0.00021234367,0.0066384617,0.000037172787,0.000032692,0.000032272754,0.00067470263,0.00003578795,0.00029788658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99964285,0.00010095017,0.00003496215,0.00012768857,0.00005975461,0.0000338659],"domain_scores_gemma":[0.9991366,0.00026364136,0.00021204796,0.00008354405,0.00024345014,0.00006071731],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011887737,0.0006590984,0.00068727386,0.0019630482,0.0002461934,0.0007687045,0.00054563663,0.0007258242,0.0007721956],"category_scores_gemma":[0.0026841853,0.0002778105,0.0003771995,0.00050836,0.00025362047,0.00050107756,0.00055772456,0.00027091455,0.000314533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004812086,0.0004161922,0.73018914,0.00054542767,0.0010837931,0.0013471626,0.001230644,0.012593071,0.06790246,0.00044331115,0.002973976,0.17646272],"study_design_scores_gemma":[0.00011385763,0.00043045456,0.90772283,0.000063967454,0.00032587902,0.002209345,0.0003562441,0.07162159,0.015031184,0.0008826241,0.0011679592,0.000073950345],"about_ca_topic_score_codex":0.0047517573,"about_ca_topic_score_gemma":0.007911815,"teacher_disagreement_score":0.0047517573,"about_ca_system_score_codex":0.0002575095,"about_ca_system_score_gemma":0.00021744613,"threshold_uncertainty_score":0.00944823},"labels":[],"label_agreement":null},{"id":"W4412852879","doi":"10.1111/jnc.70167","title":"In Vivo Cortical Microstructure: Relationships With Tauopathy and Cognitive Impairment in the Elderly","year":2025,"lang":"en","type":"article","venue":"Journal of Neurochemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Carleton University; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Tauopathy; Diffusion MRI; Neuroscience; Dementia; Positron emission tomography; Cognitive decline; Fractional anisotropy; Cognitive impairment; Cognition; Audiology; Medicine; Internal medicine; Magnetic resonance imaging; Radiology; Disease; Neurodegeneration","score_opus":0.023576526742192027,"score_gpt":0.32302054769049326,"score_spread":0.29944402094830125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412852879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988073,0.00034334767,0.00021058957,0.00002832448,0.0000029570879,0.0000048319725,0.00037163522,0.0000071617,0.0002238655],"genre_scores_gemma":[0.9995478,0.00005472307,0.00012122737,0.0000064556166,0.0000048330603,0.0000029948087,0.00018085976,0.0000012899517,0.000079804886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988353,0.0000212404,0.000020667003,0.00004045029,0.00001941948,0.000014705612],"domain_scores_gemma":[0.999113,0.00013725924,0.00040747845,0.00012184188,0.00014926457,0.00007122762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005498593,0.00039170892,0.00029844718,0.0007952842,0.00027178536,0.00052918633,0.00020941313,0.00032515085,0.0008903235],"category_scores_gemma":[0.002673498,0.00016479699,0.00022448892,0.00054903835,0.00023042191,0.00034100233,0.00037312202,0.00020595104,0.0001445697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028259054,0.000030653697,0.9933429,0.000024147299,0.00017224651,0.000082677565,0.00015181606,0.00022697673,0.0022041234,0.000039766022,0.000118958094,0.0033231382],"study_design_scores_gemma":[0.0000021425794,0.000028462211,0.99915075,0.000002876693,0.000021092963,0.00010887596,0.000059921396,0.00031357037,0.00017742327,0.00008904513,0.000043658856,0.0000020922123],"about_ca_topic_score_codex":0.006251358,"about_ca_topic_score_gemma":0.011080115,"teacher_disagreement_score":0.006251358,"about_ca_system_score_codex":0.00020917387,"about_ca_system_score_gemma":0.00014433885,"threshold_uncertainty_score":0.012429953},"labels":[],"label_agreement":null},{"id":"W4412921945","doi":"10.1101/2025.07.24.666667","title":"The role of white matter myelin in structural-functional network coupling","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"White matter; Coupling (piping); Myelin; Functional connectivity; Neuroscience; Psychology; Computer science; Materials science; Medicine; Composite material; Central nervous system; Magnetic resonance imaging","score_opus":0.017952489269755324,"score_gpt":0.2643323456352827,"score_spread":0.24637985636552737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412921945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5228005,0.00086673064,0.47240514,0.0003954772,0.000019037749,0.000024810137,0.00015643866,0.00030989302,0.0030219948],"genre_scores_gemma":[0.98208517,0.0002666238,0.01705403,0.000019241266,0.000015012635,0.000020048476,0.00004120331,0.00003952863,0.0004591422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99979705,0.00007620429,0.000007779787,0.00005318172,0.000037271493,0.000028527242],"domain_scores_gemma":[0.99927014,0.00041010778,0.00014842747,0.00008142265,0.000051460625,0.000038435377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006521067,0.00035411227,0.00027247163,0.0005419,0.00035725677,0.00091771997,0.00047335593,0.000605378,0.00064869836],"category_scores_gemma":[0.0040481505,0.00029000625,0.00039079695,0.00053474255,0.00075019564,0.0019041888,0.0007489363,0.00048966013,0.00010148041],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010720139,0.000045958765,0.015476206,0.000109001056,0.00013524223,0.0002534155,0.0004979078,0.8414489,0.04662692,0.06675174,0.0003393282,0.028208062],"study_design_scores_gemma":[0.0000046535247,0.000035272453,0.01277622,0.000013910291,0.000023705956,0.00012488736,0.000054064807,0.92391074,0.0032073406,0.059180032,0.00064734044,0.000021720969],"about_ca_topic_score_codex":0.0026916387,"about_ca_topic_score_gemma":0.0020948001,"teacher_disagreement_score":0.0026916387,"about_ca_system_score_codex":0.00045373684,"about_ca_system_score_gemma":0.0003855,"threshold_uncertainty_score":0.005351901},"labels":[],"label_agreement":null},{"id":"W4413099917","doi":"10.1007/s00429-025-02998-2","title":"A thousand ways to tailor your tractography-based connectome","year":2025,"lang":"en","type":"letter","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Hôpitaux Universitaires de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Connectome; Tractography; Human Connectome Project; Computer science; Weighting; Connectomics; Diffusion MRI; Artificial intelligence; Data science; Functional connectivity; Psychology; Neuroscience; Magnetic resonance imaging; Physics; Medicine","score_opus":0.04690433661336975,"score_gpt":0.31654436477652365,"score_spread":0.2696400281631539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413099917","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010199519,0.0025915036,0.016956592,0.95241505,0.021517798,0.00004808552,0.00019993585,0.000637363,0.004613675],"genre_scores_gemma":[0.01570885,0.0047562034,0.039133787,0.8178079,0.09089961,0.0003220162,0.00025896874,0.0006419748,0.030470764],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986084,0.00056656153,0.0001381212,0.00014496004,0.0004522894,0.0000897001],"domain_scores_gemma":[0.9797484,0.014007316,0.0005162869,0.0013107744,0.002563881,0.0018534155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047048205,0.00068933296,0.0010599187,0.00083343755,0.0012972429,0.002953444,0.0009390335,0.012521927,0.010533101],"category_scores_gemma":[0.03934822,0.00049274915,0.0010028951,0.0005727128,0.0020424663,0.0029907965,0.0012630401,0.018215893,0.010345382],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017901814,0.00007719458,0.0011831458,0.00006884581,0.00007130126,0.0009630261,0.00007858749,0.00051279215,0.0013687335,0.008664656,0.89039767,0.09643508],"study_design_scores_gemma":[0.00039620366,0.00016859447,0.0018091542,0.00039040088,0.00007031053,0.003416219,0.0002515332,0.0076256683,0.0016661098,0.14174429,0.8423148,0.0001467204],"about_ca_topic_score_codex":0.0017175071,"about_ca_topic_score_gemma":0.005038807,"teacher_disagreement_score":0.012521927,"about_ca_system_score_codex":0.0010551035,"about_ca_system_score_gemma":0.001131765,"threshold_uncertainty_score":0.035236716},"labels":[],"label_agreement":null},{"id":"W4413159892","doi":"10.1016/j.media.2025.103743","title":"Exploring the robustness of TractOracle methods in RL-based tractography","year":2025,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Artificial intelligence; Computer science; Tractography; Computer vision; Diffusion MRI; Biology; Magnetic resonance imaging; Radiology; Medicine","score_opus":0.16667939381837615,"score_gpt":0.47539322498763364,"score_spread":0.3087138311692575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413159892","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26176316,0.0034391698,0.72544277,0.0012215296,0.00018127306,0.0001558118,0.00072035723,0.003603099,0.0034727708],"genre_scores_gemma":[0.81144273,0.0008490309,0.18257034,0.00023013192,0.00016788694,0.00007183644,0.0014081689,0.0014397532,0.0018201226],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99541134,0.0024511833,0.00031465365,0.00087582564,0.00071123394,0.00023570852],"domain_scores_gemma":[0.93985254,0.04678631,0.0034431804,0.005472395,0.003624349,0.0008211798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01319676,0.0018265967,0.0011963898,0.00295781,0.0010328005,0.003962961,0.0018921376,0.0031896436,0.0030760043],"category_scores_gemma":[0.08949001,0.00076188834,0.0012476452,0.0015431606,0.0018649359,0.003195662,0.0022240386,0.002087863,0.0012357632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026922082,0.00023548474,0.022508051,0.0010298061,0.0014501119,0.00043554025,0.00054087833,0.62034196,0.029966742,0.0119726015,0.0035481374,0.30527848],"study_design_scores_gemma":[0.000040759885,0.00015265329,0.0037969956,0.00008092732,0.000085293635,0.00022328517,0.00008590483,0.98164535,0.007422393,0.005574884,0.0008569728,0.000034674908],"about_ca_topic_score_codex":0.011893181,"about_ca_topic_score_gemma":0.010934171,"teacher_disagreement_score":0.01319676,"about_ca_system_score_codex":0.0008949102,"about_ca_system_score_gemma":0.0017107674,"threshold_uncertainty_score":0.06979203},"labels":[],"label_agreement":null},{"id":"W4413183765","doi":"10.1101/2025.08.06.668521","title":"A Scalable Toolkit for Modeling 3D Surface-based Brain Geometry","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of British Columbia","funders":"National Institute on Aging; National Institutes of Health; National Health and Medical Research Council; Norges Forskningsråd; Medical University of South Carolina; National Imaging Facility; Bundesministerium für Bildung und Forschung; Australian Rotary Health; Swinburne University of Technology; University of New South Wales; Deutsche Forschungsgemeinschaft; John S. Dunn Foundation; European Commission; National Institute of Mental Health; Ministerio de Ciencia, Tecnología e Innovación; University of Texas Health Science Center at Houston","keywords":"Geometry; Surface (topology); Scalability; Computer science; Computer graphics (images); Mathematics; Database","score_opus":0.048447476899320184,"score_gpt":0.305939608424462,"score_spread":0.25749213152514183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413183765","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020813958,0.00011487699,0.9688571,0.00016019777,0.000046568708,0.00009110991,0.002285991,0.025070298,0.0012925288],"genre_scores_gemma":[0.07531743,0.0005391774,0.89783627,0.00023221828,0.00005626622,0.0009943349,0.008260477,0.012054016,0.0047097453],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944144,0.00008761788,0.0000497365,0.00008206484,0.00029761696,0.00004156171],"domain_scores_gemma":[0.99910563,0.00036609438,0.00006482389,0.00019752502,0.00019327183,0.000072580966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009646051,0.0012613541,0.0010585927,0.0012746116,0.00063507655,0.0027106882,0.003466901,0.0010722817,0.013778574],"category_scores_gemma":[0.003516847,0.001070466,0.0020413382,0.0012799912,0.0007112612,0.0012780689,0.0035934541,0.0021193346,0.006383047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032572474,0.00016819435,0.0040687956,0.0013363754,0.0007549333,0.0009778576,0.0010044847,0.43384087,0.032966726,0.10015726,0.16625234,0.25814646],"study_design_scores_gemma":[0.000057176916,0.000019183088,0.00071986346,0.000053155207,0.000028256132,0.00022063004,0.00006353303,0.91224635,0.004242893,0.04064343,0.041655708,0.000049832746],"about_ca_topic_score_codex":0.00786925,"about_ca_topic_score_gemma":0.015242072,"teacher_disagreement_score":0.013778574,"about_ca_system_score_codex":0.000620059,"about_ca_system_score_gemma":0.0019598857,"threshold_uncertainty_score":0.04609388},"labels":[],"label_agreement":null},{"id":"W4413223952","doi":"10.21203/rs.3.rs-7247101/v1","title":"Pontine Functional Connectivity Gradients","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Pons; Neuroscience; Pontine nuclei; Cerebellum; Cerebral cortex; Biology; Functional connectivity; Psychology; Anatomy","score_opus":0.24161425691648258,"score_gpt":0.4992522449537585,"score_spread":0.2576379880372759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13191366,0.0019707826,0.7893984,0.0048348876,0.00071048684,0.00019860255,0.0029939213,0.0011063785,0.066873044],"genre_scores_gemma":[0.68383485,0.00244857,0.24674664,0.000506114,0.00069389807,0.00022656545,0.0022082594,0.0005723893,0.06276277],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99984705,0.000035044945,0.0000058751593,0.0000600514,0.000035782283,0.000016286536],"domain_scores_gemma":[0.9994906,0.00019504775,0.000055983193,0.000065763954,0.000120963494,0.00007160346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051485206,0.00059977244,0.00029530207,0.0016327999,0.00043080794,0.0012393774,0.00066024513,0.0009203566,0.012944919],"category_scores_gemma":[0.0038927363,0.00028660067,0.00031912295,0.00086343463,0.00077033613,0.0020781138,0.00095883704,0.00100673,0.0014450082],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015790739,0.00008628516,0.0022602314,0.00028667532,0.000114495386,0.00071750965,0.00031190852,0.010776526,0.021351645,0.82727426,0.019339727,0.11732282],"study_design_scores_gemma":[0.00004587193,0.00007015417,0.010640292,0.000049729584,0.00005286341,0.0014680207,0.00013334904,0.1037017,0.0078046713,0.84753585,0.028463138,0.000034397337],"about_ca_topic_score_codex":0.0019769159,"about_ca_topic_score_gemma":0.0029869827,"teacher_disagreement_score":0.012944919,"about_ca_system_score_codex":0.00042810765,"about_ca_system_score_gemma":0.0007683629,"threshold_uncertainty_score":0.04330504},"labels":[],"label_agreement":null},{"id":"W4413323186","doi":"10.1523/jneurosci.0790-25.2025","title":"Multivariate White Matter Microstructure Alterations in Older Adults with Coronary Artery Disease","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Ontario Brain Institute; Sunnybrook Health Science Centre; Université de Montréal; Concordia University; Institut Universitaire de Gériatrie de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Heart and Stroke Foundation of Canada","keywords":"Cardiology; White matter; Medicine; Internal medicine; Coronary artery disease; Cognitive decline; Magnetic resonance imaging; Cognition; Dementia; Radiology; Disease; Psychiatry","score_opus":0.01714424457512084,"score_gpt":0.3164412437319306,"score_spread":0.2992969991568098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413323186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9997004,0.00009917776,0.000048847574,0.000009601319,0.0000014134312,0.0000023384443,0.000048587306,0.000002062936,0.00008748051],"genre_scores_gemma":[0.9997639,0.000036891026,0.000057524223,0.000007355716,0.0000049476575,0.000001888454,0.000072356816,6.885096e-7,0.000054326152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998684,0.000024640845,0.000020590907,0.00003971485,0.000029429926,0.000017154296],"domain_scores_gemma":[0.99957603,0.000052382293,0.00024296863,0.000033508204,0.000044849494,0.00005027549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027619346,0.00032079272,0.00024691204,0.0007097522,0.00028478474,0.00032896636,0.00014056975,0.00031172505,0.0008525488],"category_scores_gemma":[0.0011521687,0.00014556288,0.00021147485,0.00051135366,0.00017212966,0.00024599725,0.00032694347,0.00022904719,0.000108536246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023526826,0.000031738084,0.9955382,0.000008897495,0.000073877185,0.00013556733,0.00011888061,0.000059559665,0.00091199274,0.0000137081715,0.00005567095,0.0028166103],"study_design_scores_gemma":[0.0000025350728,0.00006871588,0.9994624,0.000001230239,0.000014762525,0.00016807167,0.00005183772,0.00013474218,0.000046981782,0.000018141634,0.00002909078,0.0000014991105],"about_ca_topic_score_codex":0.003155657,"about_ca_topic_score_gemma":0.0046408703,"teacher_disagreement_score":0.003155657,"about_ca_system_score_codex":0.00013558258,"about_ca_system_score_gemma":0.000107457105,"threshold_uncertainty_score":0.006274581},"labels":[],"label_agreement":null},{"id":"W4413326697","doi":"10.1101/2025.08.15.25331829","title":"Cognitive Reserve Disrupts Cognitive Decline from White Matter Hyperintensities","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College; York University; Carleton University","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; Japan Atomic Energy Agency; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Natural Sciences and Engineering Research Council of Canada; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Hyperintensity; Cognition; Cognitive reserve; Cognitive decline; Effects of sleep deprivation on cognitive performance; Disconnection; Psychology; Lesion; Neuroscience; White matter; Magnetic resonance imaging; Cognitive impairment; Medicine; Dementia; Internal medicine; Disease; Psychiatry; Radiology","score_opus":0.0849119792704019,"score_gpt":0.38673091300934026,"score_spread":0.30181893373893837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413326697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9903702,0.00030466093,0.007438437,0.00016122164,0.000007943474,0.00001603003,0.000925393,0.00013090676,0.0006452049],"genre_scores_gemma":[0.9929327,0.00018298911,0.0054312046,0.000042206673,0.000011240453,0.000026706199,0.0010433672,0.000027774846,0.00030180768],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998252,0.000054408087,0.000014702089,0.000062319115,0.000024324449,0.000019206142],"domain_scores_gemma":[0.99921453,0.00033804838,0.0002409702,0.00010466404,0.000042106683,0.00005965944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008783001,0.00040007735,0.0002642817,0.0007607935,0.00023221964,0.00070919446,0.00027376943,0.00028055476,0.0013324027],"category_scores_gemma":[0.0037091235,0.00016221107,0.0004459709,0.0005863947,0.00054613774,0.00059237395,0.0008982611,0.000542926,0.00014313015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023137194,0.0003412305,0.74850756,0.0009676097,0.00223969,0.0011485665,0.0031760032,0.041268148,0.05509824,0.0052858954,0.003993077,0.13566025],"study_design_scores_gemma":[0.000035644032,0.00019621222,0.9481023,0.0000682527,0.00029252184,0.00068935816,0.00040333284,0.032427356,0.0050035357,0.01124966,0.00149459,0.000037150312],"about_ca_topic_score_codex":0.0062471414,"about_ca_topic_score_gemma":0.012138212,"teacher_disagreement_score":0.0062471414,"about_ca_system_score_codex":0.00026495758,"about_ca_system_score_gemma":0.00043104496,"threshold_uncertainty_score":0.012421548},"labels":[],"label_agreement":null},{"id":"W4413335507","doi":"10.1093/braincomms/fcaf305","title":"Superficial and deep white matter abnormalities in temporal lobe epilepsy","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London; University of Western Australia; National Institute for Health and Care Research; National Imaging Facility; Medical Research Centre; Wellcome Trust","keywords":"Temporal lobe; White matter; Epilepsy; Grey matter; Neuroimaging; Fractional anisotropy; Abnormality; Psychology; Magnetic resonance imaging; Medicine; Diffusion MRI; Cohort; Hippocampus; Hippocampal sclerosis; Temporal cortex; Nuclear medicine; Neuroscience; Audiology; Pathology; Radiology; Psychiatry","score_opus":0.051417317376212704,"score_gpt":0.3642687004136942,"score_spread":0.3128513830374815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413335507","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9987897,0.0001359371,0.0003386591,0.000025395218,0.0000030270967,0.000007037955,0.00016007165,0.000007080867,0.0005330493],"genre_scores_gemma":[0.99942017,0.00004064611,0.00018339333,0.000013577296,0.000003847913,0.000005318315,0.00013536187,0.0000028688185,0.00019490457],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998939,0.00001476694,0.000020483709,0.00003054189,0.000024086592,0.000016254853],"domain_scores_gemma":[0.99937576,0.00011794943,0.00030542066,0.00007038436,0.000055742203,0.00007466896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045160606,0.00027102823,0.00015621068,0.0006083884,0.00017359329,0.00043652116,0.00011197263,0.000259074,0.0024940085],"category_scores_gemma":[0.0011669951,0.00013151686,0.00018089196,0.00027139852,0.00041072382,0.00041981114,0.00055692083,0.0002467134,0.00024268638],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036145963,0.00010835937,0.84695387,0.00018084324,0.00029999952,0.0036014535,0.0010942948,0.00053308153,0.118319176,0.00038815328,0.0004695766,0.024436623],"study_design_scores_gemma":[0.000016366086,0.00020082187,0.99321944,0.000012210683,0.000033803248,0.002616225,0.00018271092,0.00033472115,0.0027793297,0.00032979305,0.00026606984,0.000008515306],"about_ca_topic_score_codex":0.0016852524,"about_ca_topic_score_gemma":0.0028484736,"teacher_disagreement_score":0.0024940085,"about_ca_system_score_codex":0.00013467841,"about_ca_system_score_gemma":0.0001490636,"threshold_uncertainty_score":0.008343279},"labels":[],"label_agreement":null},{"id":"W4413340964","doi":"10.1101/2025.08.13.25333630","title":"Axonal Degeneration Across the Alzheimer’s Disease Spectrum: A Longitudinal MRI and Fluid Biomarker Study","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Dementia; Biomarker; Cognitive decline; Degeneration (medical); Cognition; Neuropathology; Effects of sleep deprivation on cognitive performance; Disease; Medicine; Neuroscience; Cohort; Psychology; Oncology; Internal medicine; Pathology; Biology","score_opus":0.13278439267153413,"score_gpt":0.4122324645585679,"score_spread":0.27944807188703374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413340964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99836534,0.00028125924,0.0002939868,0.00012936917,0.000014039309,0.000030177831,0.00060446386,0.00000982609,0.00027158987],"genre_scores_gemma":[0.9962853,0.00025152645,0.00080326543,0.0001668812,0.000053207055,0.00007520082,0.0016149189,0.000013244321,0.0007363337],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993666,0.00019264632,0.00005471263,0.00018747253,0.00008558417,0.00011312527],"domain_scores_gemma":[0.99794894,0.00017670324,0.00045446004,0.00050933624,0.00036220584,0.00054837635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032075928,0.0007182909,0.0005933614,0.0007290884,0.0013256939,0.0013734663,0.0005881607,0.001026328,0.0011383671],"category_scores_gemma":[0.0047682477,0.00058272947,0.00071043946,0.00096390315,0.00054371316,0.0009958,0.0013722609,0.0011483693,0.0006984796],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004878565,0.001341613,0.98122704,0.000042145894,0.0007038723,0.000528898,0.0007105273,0.00016008079,0.0017140331,0.0002477633,0.0010581949,0.0073872684],"study_design_scores_gemma":[0.0003751463,0.0017254822,0.99200577,0.000034626493,0.00055711356,0.0009235726,0.0005874623,0.0009589468,0.00033734893,0.00066320214,0.0017857607,0.000045526514],"about_ca_topic_score_codex":0.008500108,"about_ca_topic_score_gemma":0.006893835,"teacher_disagreement_score":0.008500108,"about_ca_system_score_codex":0.0005189882,"about_ca_system_score_gemma":0.0009963703,"threshold_uncertainty_score":0.016963601},"labels":[],"label_agreement":null},{"id":"W4413352538","doi":"10.3389/fneur.2025.1612598","title":"Improved injury detection through harmonizing multi-site neuroimaging data after experimental TBI: a Translational Outcomes Project in Neurotrauma consortium study","year":2025,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, Los Angeles; National Institute of Neurological Disorders and Stroke; Vivian L. Smith Foundation; Johns Hopkins University; Georgetown University; Uniformed Services University of the Health Sciences; University of Waterloo; Henry M. Jackson Foundation","keywords":"Statistical power; Neuroimaging; Outlier; Univariate; Voxel; Harmonization; Statistical parametric mapping; Population; Sample size determination; Medicine; Traumatic brain injury; Psychology; Multivariate statistics; Statistics; Neuroscience; Psychiatry; Mathematics; Magnetic resonance imaging; Radiology","score_opus":0.13125389996010506,"score_gpt":0.4102484699397621,"score_spread":0.27899456997965705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413352538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8931722,0.00015566772,0.10309143,0.00030651988,0.000067677836,0.0010379566,0.0010738967,0.00049422996,0.0006003846],"genre_scores_gemma":[0.9220128,0.00009868845,0.07143893,0.00015863909,0.00006300954,0.002322563,0.00285642,0.00032340662,0.0007255802],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99088985,0.00473353,0.00064502493,0.0012031522,0.0021214257,0.00040703415],"domain_scores_gemma":[0.9837736,0.0020382788,0.0038981661,0.005040836,0.004202055,0.0010469801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022365721,0.00093072833,0.0013593833,0.0012146183,0.0005566592,0.0008876823,0.0011324951,0.00066704775,0.001434704],"category_scores_gemma":[0.01681576,0.00040071094,0.0012068627,0.0013695329,0.0010405752,0.00085025,0.002979756,0.0010912872,0.00029369158],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.026584705,0.009608586,0.28100055,0.0011606166,0.0067052073,0.0011164997,0.0030993419,0.027976725,0.25493455,0.0037787973,0.007636587,0.37639794],"study_design_scores_gemma":[0.0017236357,0.020677522,0.81814367,0.000111894915,0.0024341713,0.0015173486,0.0010343206,0.04209843,0.09820321,0.004344419,0.009408417,0.0003029833],"about_ca_topic_score_codex":0.0017256276,"about_ca_topic_score_gemma":0.0024682553,"teacher_disagreement_score":0.022365721,"about_ca_system_score_codex":0.00049542,"about_ca_system_score_gemma":0.0018261697,"threshold_uncertainty_score":0.118282616},"labels":[],"label_agreement":null},{"id":"W4413395701","doi":"10.1101/2025.08.15.670595","title":"Characterizing neuronal cell bodies in human postmortem cerebral white matter tracts","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"White matter; Neuroscience; Cell bodies; Biology; Human brain; Pathology; Anatomy; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.02955704536588889,"score_gpt":0.28089769204802334,"score_spread":0.25134064668213446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413395701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9561672,0.0074722283,0.03184847,0.00007676397,0.00006198964,0.00011042284,0.0008894562,0.00015992839,0.003213548],"genre_scores_gemma":[0.960617,0.0049044634,0.030035228,0.00012826479,0.00003546552,0.00018749617,0.0017268592,0.00008946575,0.002275729],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998567,0.00001317961,0.000010060848,0.00005949488,0.0000362538,0.00002432851],"domain_scores_gemma":[0.99987614,0.000025503752,0.000023152992,0.000021881504,0.000039939445,0.000013450073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026975136,0.00021006248,0.00016740116,0.0011331674,0.00028021418,0.00033715685,0.00018850624,0.00032054022,0.001011699],"category_scores_gemma":[0.0004336819,0.00019478139,0.00012827663,0.00043207695,0.00037213342,0.00019613253,0.00028795478,0.00021733501,0.00040729155],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035755523,0.000055425993,0.05536931,0.00026460248,0.00009184017,0.002445821,0.00085559604,0.0003704699,0.91059285,0.0007970949,0.0004572721,0.028342152],"study_design_scores_gemma":[0.00004462422,0.0007771007,0.6341898,0.00023379011,0.00019706393,0.028852327,0.0015697206,0.00491541,0.30941987,0.0018453641,0.017904915,0.000050026774],"about_ca_topic_score_codex":0.00170196,"about_ca_topic_score_gemma":0.00388931,"teacher_disagreement_score":0.00170196,"about_ca_system_score_codex":0.0001341684,"about_ca_system_score_gemma":0.0001549905,"threshold_uncertainty_score":0.003384471},"labels":[],"label_agreement":null},{"id":"W4413440516","doi":"10.21203/rs.3.rs-7361397/v1","title":"Longitudinal Visualization Tools for Advanced Characterization of Multiple Sclerosis Lesions Using Diffusion MRI and Magnetization Transfer Imaging Metrics","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; Université de Sherbrooke","keywords":"Diffusion MRI; Lesion; Magnetization transfer; Multiple sclerosis; White matter; Computer science; Visualization; Radiology; Magnetic resonance imaging; Artificial intelligence; Pathology; Medicine","score_opus":0.27826180301709097,"score_gpt":0.4659820557567396,"score_spread":0.18772025273964865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413440516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028253976,0.0007209451,0.9613914,0.00060222024,0.00005933611,0.000066211884,0.001169463,0.0065330258,0.0012033887],"genre_scores_gemma":[0.21497431,0.0009851311,0.7775559,0.00007940123,0.00014095286,0.00026101398,0.0015711455,0.0018113946,0.0026207145],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996093,0.00011956158,0.000050581355,0.00006496496,0.00012343854,0.000032176125],"domain_scores_gemma":[0.99619895,0.0014813056,0.00072057464,0.0004764361,0.00090803206,0.00021468147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018303728,0.0011234354,0.00059920165,0.003383925,0.00038581196,0.0031061133,0.00075046986,0.0009954002,0.007187457],"category_scores_gemma":[0.010108955,0.00060765824,0.000593546,0.001741288,0.00032986392,0.0028953431,0.0016175391,0.001100036,0.0019302013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008066765,0.00029349356,0.020879474,0.0006398506,0.00021190071,0.0007844354,0.000998945,0.037554268,0.12168847,0.044181745,0.024250088,0.7477107],"study_design_scores_gemma":[0.00009141781,0.00024300463,0.012539167,0.00018256022,0.00012896428,0.0017498435,0.00045822735,0.81279933,0.07993837,0.060537413,0.031184256,0.00014741885],"about_ca_topic_score_codex":0.0013093855,"about_ca_topic_score_gemma":0.001500497,"teacher_disagreement_score":0.007187457,"about_ca_system_score_codex":0.00032324105,"about_ca_system_score_gemma":0.0010171758,"threshold_uncertainty_score":0.024044454},"labels":[],"label_agreement":null},{"id":"W4413445538","doi":"10.18060/29082","title":"Effect of Cigarette Smoking and Alcohol Use on White Matter Tract Integrity","year":2025,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cigarette smoking; Alcohol; White (mutation); White matter; Medicine; Environmental health; Chemistry; Internal medicine; Magnetic resonance imaging; Organic chemistry","score_opus":0.0374371625871624,"score_gpt":0.3570489508855109,"score_spread":0.3196117882983485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413445538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99898404,0.00027143388,0.00010472726,0.000023827426,0.0000033836754,0.000005153686,0.000106141066,0.000006372546,0.00049493514],"genre_scores_gemma":[0.9996018,0.000044382396,0.00008587284,0.00000785779,0.000003873851,0.0000029621763,0.000063425876,0.000003695432,0.00018610159],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997291,0.00007467457,0.000027150358,0.00006695342,0.000057637262,0.000044399778],"domain_scores_gemma":[0.99799466,0.000728872,0.0006096825,0.00018536275,0.00017159594,0.000309864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006007828,0.00026422678,0.00029158875,0.00052245456,0.00027142826,0.00045053306,0.00020320849,0.00026204163,0.0027802824],"category_scores_gemma":[0.0016830539,0.00017773225,0.0003553177,0.00039818767,0.00033656016,0.00028750187,0.00032190175,0.00029046586,0.00017177976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001045835,0.000050257317,0.99004316,0.000012686043,0.0003083829,0.00010946221,0.000057295136,0.00005504284,0.0041418024,0.000023355022,0.000041345742,0.004111392],"study_design_scores_gemma":[0.000001711033,0.00011036192,0.9992236,0.0000017277433,0.00006054132,0.00013956844,0.000017895349,0.00012280699,0.00025223242,0.000021210919,0.00004666298,0.0000016543381],"about_ca_topic_score_codex":0.00333291,"about_ca_topic_score_gemma":0.009330918,"teacher_disagreement_score":0.00333291,"about_ca_system_score_codex":0.0002137161,"about_ca_system_score_gemma":0.00023814585,"threshold_uncertainty_score":0.009301007},"labels":[],"label_agreement":null},{"id":"W4413445665","doi":"10.18060/29106","title":"Relationship between Perivascular Space Burden, White Matter Hyperintensities, and Cognitive Function","year":2025,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Perivascular space; Cognition; White matter; Space (punctuation); Psychology; Cognitive psychology; Medicine; Neuroscience; Magnetic resonance imaging; Pathology; Philosophy; Radiology; Linguistics","score_opus":0.03968803237689291,"score_gpt":0.31254009013241457,"score_spread":0.2728520577555217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413445665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99811804,0.00065255066,0.00014371431,0.000057395795,0.0000058850014,0.000012809555,0.00027731046,0.000010085411,0.0007223288],"genre_scores_gemma":[0.9990422,0.00014305717,0.00028601353,0.000014154572,0.000013616915,0.00001079171,0.00021963766,0.0000021963156,0.00026826776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997938,0.00004354711,0.000026809976,0.000057878846,0.000052113497,0.000025848834],"domain_scores_gemma":[0.99782556,0.00044610346,0.0011011165,0.00011542557,0.00025378796,0.00025791905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081301556,0.00047647342,0.00025994098,0.0011985438,0.00036460013,0.0006372957,0.00039682194,0.00042972903,0.0029472245],"category_scores_gemma":[0.003618854,0.0001677957,0.00022106348,0.0006338668,0.00032049805,0.00043521303,0.00035651782,0.0003499692,0.00024583266],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002466125,0.000060887738,0.99622524,0.00002097922,0.00010936572,0.00007458164,0.00005817794,0.000056499306,0.000320313,0.000023471066,0.000082847604,0.0027208696],"study_design_scores_gemma":[0.000003820751,0.00006789833,0.9993687,0.000004556181,0.000025719639,0.00015734183,0.000028776516,0.00015028218,0.00007604332,0.000056014764,0.000058469257,0.0000023672821],"about_ca_topic_score_codex":0.005804934,"about_ca_topic_score_gemma":0.0067709056,"teacher_disagreement_score":0.005804934,"about_ca_system_score_codex":0.00027762091,"about_ca_system_score_gemma":0.000400685,"threshold_uncertainty_score":0.011542261},"labels":[],"label_agreement":null},{"id":"W4413509559","doi":"10.1016/j.jrras.2025.101876","title":"Deep learning-based magnetic resonance imaging image reconstruction in the assessment of brain microstructural changes in Parkinson's disease patients","year":2025,"lang":"en","type":"article","venue":"Journal of Radiation Research and Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Parkinson's disease; Disease; Nuclear magnetic resonance; Neuroimaging; Medicine; Neuroscience; Materials science; Psychology; Pathology; Radiology; Physics","score_opus":0.03243055240761956,"score_gpt":0.388594276016298,"score_spread":0.35616372360867843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413509559","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9618097,0.001193398,0.035928473,0.00015460199,0.000011223132,0.00005475106,0.00015590954,0.000121866666,0.00057011284],"genre_scores_gemma":[0.9860005,0.00024951698,0.013373844,0.00002930976,0.000006903175,0.000020445652,0.00010124253,0.000004817722,0.00021342824],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9996953,0.00015514207,0.000027166172,0.000053308428,0.00004309487,0.000025955489],"domain_scores_gemma":[0.99968565,0.00013533357,0.00006579422,0.000023603909,0.000068082314,0.000021627962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012935996,0.00037667344,0.0003589901,0.0004520389,0.00011299955,0.00045300883,0.00021409403,0.0004114433,0.00037794944],"category_scores_gemma":[0.002371973,0.00013256882,0.00033329212,0.00022000309,0.00019718934,0.0003656545,0.00031663547,0.00022207455,0.000121218145],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032347706,0.00060894445,0.3396502,0.00037691108,0.00051944755,0.000969262,0.0004148229,0.09114201,0.06704461,0.0012004953,0.0010818697,0.49375668],"study_design_scores_gemma":[0.00008039354,0.0010162111,0.14880309,0.00005472469,0.00018086944,0.0011488803,0.00016255607,0.8288029,0.01735832,0.0012712672,0.0010825797,0.000038285878],"about_ca_topic_score_codex":0.0014885304,"about_ca_topic_score_gemma":0.0020413226,"teacher_disagreement_score":0.0014885304,"about_ca_system_score_codex":0.00021828702,"about_ca_system_score_gemma":0.00027699195,"threshold_uncertainty_score":0.006841302},"labels":[],"label_agreement":null},{"id":"W4413878449","doi":"10.1038/s42003-025-08774-6","title":"Anatomical insights into the superior longitudinal system from integrative in- vivo and ex-vivo mapping","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Provincia Autonoma di Trento","keywords":"Ex vivo; In vivo; Biology; Genetics","score_opus":0.0664635604551278,"score_gpt":0.3751419750123706,"score_spread":0.3086784145572428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413878449","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48507166,0.00073481875,0.51151043,0.0001446583,0.000017688875,0.000046788657,0.000516961,0.00040252786,0.0015545383],"genre_scores_gemma":[0.86953485,0.0006504221,0.12838787,0.000034130793,0.000014457236,0.00005325811,0.00051323225,0.00010929815,0.0007024506],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998745,0.000048321348,0.000010207658,0.00003282145,0.000022733107,0.000011390421],"domain_scores_gemma":[0.99960035,0.0001472076,0.00007939603,0.00010021639,0.000048099762,0.00002478522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009777057,0.00044969618,0.00021309835,0.0007081928,0.00018648643,0.00060836,0.00028577854,0.00029499058,0.0016556862],"category_scores_gemma":[0.0014434061,0.00029128618,0.00029790506,0.0004173508,0.00059899123,0.00073932135,0.00039972167,0.0003535805,0.0003409355],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026429328,0.00008540864,0.047991313,0.0005985744,0.0002369281,0.0009802189,0.0017718378,0.032973856,0.7834408,0.012031871,0.00081620045,0.11880867],"study_design_scores_gemma":[0.000070277885,0.0010232908,0.35775954,0.00032942588,0.00044513677,0.008859945,0.0013506936,0.30983815,0.24763241,0.05129142,0.021233352,0.00016644335],"about_ca_topic_score_codex":0.0012973944,"about_ca_topic_score_gemma":0.0038946911,"teacher_disagreement_score":0.0016556862,"about_ca_system_score_codex":0.00019477915,"about_ca_system_score_gemma":0.0003940362,"threshold_uncertainty_score":0.005538881},"labels":[],"label_agreement":null},{"id":"W4413981681","doi":"10.1139/jpn.090177","title":"White-matter abnormalities in adolescents with long-term inhalant and cannabis use: a diffusion magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Intoxicative inhalant; Term (time); White matter; Medicine; Diffusion MRI; Diffusion imaging; Diffusion-Weighted Magnetic Resonance Imaging; Nuclear magnetic resonance; Pediatrics; Radiology; Physics; Astronomy","score_opus":0.017109069483508214,"score_gpt":0.30101840219703285,"score_spread":0.28390933271352464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413981681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9998265,0.00005600943,0.000023556724,0.000008684111,8.957112e-7,0.0000044703206,0.00002018914,6.6329653e-7,0.00005895342],"genre_scores_gemma":[0.9997061,0.00008165807,0.00009426937,0.0000108150225,0.0000028966842,0.0000059463882,0.00004649082,8.5605404e-7,0.000051000607],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998472,0.000027070439,0.00002117955,0.000032860826,0.000038891125,0.00003279646],"domain_scores_gemma":[0.9993813,0.000087171975,0.00025314197,0.000023168186,0.00009331163,0.00016193379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031611364,0.00031763656,0.000314791,0.00077343354,0.00047503557,0.00038104283,0.00021710327,0.00046739017,0.00080020097],"category_scores_gemma":[0.00092846976,0.0002841111,0.00022162442,0.00043326066,0.00043114254,0.00038506326,0.00040791987,0.0003927879,0.00011252118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070991235,0.00008897614,0.99509454,0.000013869727,0.000019820023,0.0013758505,0.0003997715,0.000013376564,0.0017258982,0.000014762052,0.000023756009,0.0011584752],"study_design_scores_gemma":[0.0000057521006,0.00015461666,0.996323,0.000005913077,0.000020078298,0.0027256855,0.00045671134,0.000041789095,0.00018663565,0.000008356177,0.000069465445,0.0000020275131],"about_ca_topic_score_codex":0.0056288503,"about_ca_topic_score_gemma":0.011514633,"teacher_disagreement_score":0.0056288503,"about_ca_system_score_codex":0.00033337984,"about_ca_system_score_gemma":0.00048626025,"threshold_uncertainty_score":0.011192203},"labels":[],"label_agreement":null},{"id":"W4414080826","doi":"10.1371/journal.pcbi.1013459","title":"Blood flow in the human cerebral cortex: Large-scale pial vascularization and 1D simulation","year":2025,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Health Research Council of New Zealand; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Pulsatile flow; Blood flow; Cerebral blood flow; Hemodynamics; Blood pressure; Cerebral autoregulation; Intracranial pressure","score_opus":0.0369265125769312,"score_gpt":0.35566203552426284,"score_spread":0.31873552294733165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414080826","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5094481,0.00087931723,0.4740477,0.0010391406,0.00010676396,0.00021468863,0.0011477628,0.00088270695,0.012233826],"genre_scores_gemma":[0.9514808,0.00064428465,0.045080792,0.0001419833,0.000037120597,0.00021793487,0.00034643224,0.00008690736,0.0019637581],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99989605,0.000034402707,0.00000399526,0.000024158442,0.000026758486,0.000014627468],"domain_scores_gemma":[0.99972135,0.00019335847,0.000024920175,0.00001759088,0.000024326144,0.00001840975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002246662,0.00044563605,0.0003537487,0.00037327164,0.00031978203,0.0007887468,0.0006754546,0.0008908652,0.0014115893],"category_scores_gemma":[0.0012638441,0.0003220236,0.0005740361,0.00042827314,0.00060894067,0.00041528253,0.000554879,0.00046869295,0.00019649377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025034366,0.000019483066,0.0007010931,0.000025496249,0.000012417161,0.00011846002,0.00005718675,0.9930809,0.0013970926,0.00097663,0.00029480158,0.003291344],"study_design_scores_gemma":[0.000007071037,0.000010515016,0.00033463517,0.0000036451274,0.0000044343747,0.000031356376,0.000011674947,0.9981377,0.00032756428,0.00077801076,0.00034880108,0.0000044813905],"about_ca_topic_score_codex":0.017469915,"about_ca_topic_score_gemma":0.0075642285,"teacher_disagreement_score":0.017469915,"about_ca_system_score_codex":0.0006211385,"about_ca_system_score_gemma":0.0010368555,"threshold_uncertainty_score":0.034736454},"labels":[],"label_agreement":null},{"id":"W4414083439","doi":"10.1109/tbme.2025.3607105","title":"Spherical Harmonics Representation Learning for High-Fidelity and Generalizable Super-Resolution in Diffusion MRI","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Youth Innovation Promotion Association of the Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Representation (politics); Harmonics; Signal processing; Diffusion MRI; Spherical harmonics; Diffusion; Data acquisition; Pattern recognition (psychology)","score_opus":0.030566198256701434,"score_gpt":0.32079380328000306,"score_spread":0.29022760502330164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414083439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057325717,0.00031152056,0.9928295,0.0001848559,0.000023009321,0.000023093342,0.00005163705,0.00036477798,0.000479091],"genre_scores_gemma":[0.31005442,0.0014785517,0.6821476,0.00039824256,0.0001813697,0.00013738083,0.0006359581,0.0004128201,0.0045535564],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996117,0.000098068864,0.000023137225,0.00008438832,0.000150279,0.000032496828],"domain_scores_gemma":[0.99916613,0.00033163888,0.00013493918,0.00014361093,0.00017119908,0.0000524856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010046809,0.0008621061,0.00065211474,0.00059046835,0.00026372392,0.0006959587,0.0010432821,0.0008685088,0.0016925249],"category_scores_gemma":[0.0038478205,0.00037066458,0.00084810785,0.0006571941,0.00064154505,0.0014575842,0.0012300308,0.0017973772,0.00075053354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019293612,0.000113094444,0.0011442975,0.00036276886,0.00014560469,0.0002270654,0.00018169095,0.42485622,0.042775378,0.022134542,0.008397251,0.4994692],"study_design_scores_gemma":[0.000006418519,0.000023807836,0.00016572425,0.000008796233,0.000012706463,0.000076489305,0.000009009931,0.98865384,0.004557102,0.005192632,0.0012817363,0.000011663298],"about_ca_topic_score_codex":0.0026881606,"about_ca_topic_score_gemma":0.0035154303,"teacher_disagreement_score":0.0026881606,"about_ca_system_score_codex":0.00049903983,"about_ca_system_score_gemma":0.00085119164,"threshold_uncertainty_score":0.0056620836},"labels":[],"label_agreement":null},{"id":"W4414155731","doi":"10.7554/elife.96625.3","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cerebellum; Thalamus; Taurine; Attenuation; Central nervous system; Neurite","score_opus":0.04797523747320988,"score_gpt":0.3343625564876865,"score_spread":0.2863873190144766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414155731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97944814,0.000705144,0.01879535,0.000032174008,0.000008286737,0.000014536857,0.0003969595,0.00017052432,0.00042884937],"genre_scores_gemma":[0.9792027,0.0011589951,0.017395731,0.000021415823,0.0000029661737,0.000056688703,0.0004244203,0.00008814978,0.0016490762],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994576,0.0000059661174,0.000003945981,0.000019932953,0.000016151558,0.000008338965],"domain_scores_gemma":[0.9998441,0.00002260534,0.00006482116,0.000012747425,0.000035622594,0.000020092762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018558002,0.00032239285,0.00022151247,0.00040159834,0.00008493738,0.00024187373,0.00021745669,0.00022322964,0.00041936096],"category_scores_gemma":[0.00029437305,0.00016732104,0.00017111491,0.00012569154,0.00020030966,0.0002156192,0.000260568,0.00024820454,0.00013038555],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061732164,0.0000040717937,0.0016087886,0.000031552983,0.000008204535,0.00010856817,0.00004912207,0.00030007208,0.9943072,0.00008072319,0.000019697882,0.003420334],"study_design_scores_gemma":[0.0000075406497,0.0004923167,0.06094315,0.00002575374,0.00007401986,0.0008092985,0.00026091468,0.0072508254,0.92874676,0.00021967135,0.0011423735,0.000027361586],"about_ca_topic_score_codex":0.0020768247,"about_ca_topic_score_gemma":0.002844109,"teacher_disagreement_score":0.0020768247,"about_ca_system_score_codex":0.00021342837,"about_ca_system_score_gemma":0.00020429584,"threshold_uncertainty_score":0.00412941},"labels":[],"label_agreement":null},{"id":"W4414168204","doi":"10.1016/j.mri.2025.110522","title":"Correction of orientation dependence in magnetization transfer measures in the context of tractometry: Challenges, pitfalls and solutions","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Université de Sherbrooke","keywords":"Orientation (vector space); Context (archaeology); Magnetization; Variance (accounting); Diffusion; Work (physics); Polynomial; Measure (data warehouse)","score_opus":0.04497411306941035,"score_gpt":0.3230898056104971,"score_spread":0.27811569254108676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414168204","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0209003,0.0021925608,0.97311145,0.0009438849,0.00027045538,0.000058827183,0.00016947392,0.001715696,0.0006372447],"genre_scores_gemma":[0.27180114,0.0019227499,0.7214355,0.0004128189,0.00023514961,0.00012465606,0.0006202775,0.001877495,0.0015702483],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99413705,0.00234501,0.00047866334,0.0013020219,0.0015035224,0.00023373192],"domain_scores_gemma":[0.9643448,0.019447323,0.004311599,0.0071486398,0.00438207,0.00036547353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011174243,0.0015857137,0.0014034965,0.0014688777,0.001195429,0.002316423,0.0019198075,0.0016410758,0.0013163233],"category_scores_gemma":[0.06006465,0.0007550245,0.00077199546,0.0022861275,0.001662276,0.0020941913,0.0018899794,0.0027223676,0.0010957965],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005804903,0.00013034733,0.021686628,0.0023433617,0.00079012505,0.0006886649,0.0015775375,0.085335486,0.11584141,0.031167565,0.009052546,0.73080593],"study_design_scores_gemma":[0.000064970016,0.00042134567,0.037223224,0.0008751309,0.00038968032,0.0035928679,0.00085662614,0.6449031,0.16502082,0.08861405,0.05770535,0.0003329551],"about_ca_topic_score_codex":0.006250668,"about_ca_topic_score_gemma":0.008336909,"teacher_disagreement_score":0.011174243,"about_ca_system_score_codex":0.00096332247,"about_ca_system_score_gemma":0.0026679463,"threshold_uncertainty_score":0.0590958},"labels":[],"label_agreement":null},{"id":"W4414370731","doi":"10.1101/2025.09.16.25335779","title":"Revisiting the Role of Structural Connectivity-Based Parcellation in Thalamic Nuclei Segmentation: comparison with recent state-of-the-art methods","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Segmentation; Thalamus; Workflow; Pattern recognition (psychology); Diffusion MRI","score_opus":0.05460757683439453,"score_gpt":0.39934570138231706,"score_spread":0.3447381245479225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414370731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39074323,0.017408786,0.58139473,0.0031741995,0.00019005996,0.0002784298,0.001002064,0.0016783349,0.0041302],"genre_scores_gemma":[0.7645403,0.0038032958,0.22902428,0.00018483328,0.00017995307,0.00010472003,0.0011170744,0.00051066093,0.00053491653],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99691486,0.00119282,0.0001988301,0.0007460154,0.00082613365,0.00012130512],"domain_scores_gemma":[0.98477626,0.009382226,0.0014727045,0.0016906408,0.0024438868,0.00023416517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009967168,0.00091534416,0.00078391895,0.0038329714,0.0007202777,0.003839008,0.0016498538,0.0010246187,0.0013981794],"category_scores_gemma":[0.026207678,0.00037386405,0.0008629741,0.0020350097,0.001773926,0.0028459271,0.001320406,0.0009209044,0.0005403401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009609745,0.00010506052,0.09277176,0.0019922396,0.0017612182,0.00031614176,0.003063282,0.059915777,0.04609246,0.014258009,0.0041336366,0.7746295],"study_design_scores_gemma":[0.00009102158,0.00081652217,0.20815794,0.0008321031,0.0008348721,0.0018494028,0.0016518662,0.7009117,0.045084514,0.025242643,0.014267841,0.00025956382],"about_ca_topic_score_codex":0.008556134,"about_ca_topic_score_gemma":0.017251587,"teacher_disagreement_score":0.009967168,"about_ca_system_score_codex":0.001839574,"about_ca_system_score_gemma":0.0015262935,"threshold_uncertainty_score":0.052712023},"labels":[],"label_agreement":null},{"id":"W4414371298","doi":"10.1002/nbm.70148","title":"Evaluating a Cellular Microstructure Model Within Apoptotic Cell Death via Diffusion Magnetic Resonance and Long Diffusion Times","year":2025,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Apoptosis; Intracellular; Diffusion; Programmed cell death; Myeloid leukemia; Cancer; Immune system","score_opus":0.03292858301950447,"score_gpt":0.34859327333847784,"score_spread":0.3156646903189734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414371298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93257207,0.00036425694,0.066219606,0.00009169,0.000009057569,0.000018451254,0.00008678196,0.000062125284,0.00057592965],"genre_scores_gemma":[0.9939032,0.0001805409,0.005414141,0.000010185916,0.00000179064,0.00001650404,0.000043584238,0.0000062919544,0.0004237069],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999616,0.000008190901,0.0000020857049,0.00001063281,0.0000097869715,0.000007745618],"domain_scores_gemma":[0.999866,0.00005089608,0.000033483677,0.000011773227,0.000025882151,0.000011893391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018162008,0.00022183478,0.00015508008,0.0001857875,0.000110739515,0.00019090487,0.00024370012,0.00036637016,0.00039449907],"category_scores_gemma":[0.00041672704,0.00010610653,0.00017390476,0.00013617832,0.00026197344,0.00036061,0.00016181126,0.00025208553,0.000064523134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021354892,0.000075111275,0.0028806527,0.00010219187,0.000026105028,0.00025022746,0.000092461785,0.21240465,0.7761259,0.0027452891,0.00012472458,0.00495912],"study_design_scores_gemma":[0.000012998455,0.00018633807,0.003145709,0.0000046139394,0.000016466396,0.000085723565,0.000036860947,0.9123696,0.082717985,0.0010181532,0.00039036575,0.000015160168],"about_ca_topic_score_codex":0.002034635,"about_ca_topic_score_gemma":0.0012219847,"teacher_disagreement_score":0.002034635,"about_ca_system_score_codex":0.00037331486,"about_ca_system_score_gemma":0.00020934548,"threshold_uncertainty_score":0.0040456653},"labels":[],"label_agreement":null},{"id":"W4414394996","doi":"10.1002/brb3.70919","title":"Microstructural Hippocampal Alterations in Alzheimer's Disease: A Systematic Review and Meta‐Analysis of Diffusion Kurtosis Imaging","year":2025,"lang":"en","type":"review","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hippocampal formation; Kurtosis; Diffusion; Hippocampus; Diffusion MRI","score_opus":0.08828730761518705,"score_gpt":0.4191704529746279,"score_spread":0.33088314535944086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414394996","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059614587,0.9924194,0.00047736944,0.00016289765,0.00009739288,0.00019267539,0.0005005595,0.000019517141,0.0001686564],"genre_scores_gemma":[0.22832678,0.76484466,0.0030007395,0.000766425,0.00030811477,0.0014137438,0.0010000662,0.000033825672,0.0003055437],"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99204564,0.003407369,0.0025128783,0.0009673759,0.0008102277,0.00025651924],"domain_scores_gemma":[0.98231345,0.012819132,0.0028315994,0.0005604506,0.0012756436,0.00019964871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011417951,0.0025107479,0.015844008,0.0064377426,0.00071617437,0.0032638686,0.0019225953,0.0019687507,0.0025480192],"category_scores_gemma":[0.027152058,0.00124359,0.02654914,0.0080014495,0.0007218021,0.0015181227,0.0013714802,0.0013349087,0.0002513092],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013624077,0.000021204203,0.007089526,0.42062017,0.5575632,0.00015755139,0.000105522304,0.0004011006,0.00033957022,0.000111831316,0.0006185375,0.01160947],"study_design_scores_gemma":[0.00031677142,0.00013133773,0.006791531,0.028726494,0.9621677,0.00010663202,0.00004892918,0.00015243146,0.00012899964,0.00015159686,0.0012556919,0.000021902317],"about_ca_topic_score_codex":0.005620287,"about_ca_topic_score_gemma":0.013889559,"teacher_disagreement_score":0.015844008,"about_ca_system_score_codex":0.0017193141,"about_ca_system_score_gemma":0.0027537933,"threshold_uncertainty_score":0.06038463},"labels":[],"label_agreement":null},{"id":"W4414403629","doi":"10.1101/2025.09.22.675000","title":"Evaluating the quality of brainstem ROI registration using structural and diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Western Hospital; University Health Network; University of Toronto; Ontario Brain Institute; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Region of interest; Brainstem; Diffusion MRI; Fractional anisotropy; Pattern recognition (psychology); Robustness (evolution); Metric (unit); Image registration; Image quality","score_opus":0.12822983302517535,"score_gpt":0.40723773259713847,"score_spread":0.27900789957196315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414403629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73045856,0.0014598946,0.26312116,0.00024826478,0.00010431849,0.00045407977,0.00071828347,0.0020159325,0.0014195509],"genre_scores_gemma":[0.9235349,0.00019063299,0.07472913,0.000042726442,0.000017987637,0.00016252002,0.0005431436,0.00028856786,0.0004903329],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99702543,0.0011718952,0.0003452987,0.0008525943,0.00046715196,0.00013775754],"domain_scores_gemma":[0.9929395,0.0037629977,0.0008741325,0.0010115874,0.0012713551,0.00014037667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009247711,0.00090881647,0.000794121,0.0011627809,0.0005882059,0.0013500861,0.0007026989,0.00095634494,0.0016949647],"category_scores_gemma":[0.02757053,0.00049316505,0.00069241726,0.0006652333,0.0007233463,0.0014203895,0.0011160297,0.0005399449,0.0006339729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006312626,0.00042499573,0.086862914,0.0016505384,0.0020772903,0.00056835526,0.0029280859,0.0643089,0.4700797,0.003070701,0.0024000136,0.35931587],"study_design_scores_gemma":[0.00029182644,0.004061704,0.2359381,0.00020308676,0.0010877394,0.0019189096,0.0010057173,0.49292803,0.250833,0.0064002313,0.0049829585,0.00034867012],"about_ca_topic_score_codex":0.0036122939,"about_ca_topic_score_gemma":0.004765336,"teacher_disagreement_score":0.009247711,"about_ca_system_score_codex":0.00036379063,"about_ca_system_score_gemma":0.00070519216,"threshold_uncertainty_score":0.0489071},"labels":[],"label_agreement":null},{"id":"W4414492054","doi":"10.1101/2025.09.22.677842","title":"Distinct cellular processes drive motor skill learning in the human brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fondo para la Investigación Científica y Tecnológica; National Institute of Dental and Craniofacial Research; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Human brain; Precuneus; Neuroplasticity; Motor learning; Diffusion MRI; Soma; Motor skill; Hippocampus","score_opus":0.027500140735174424,"score_gpt":0.2959379614449278,"score_spread":0.26843782070975336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414492054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95093095,0.0036783786,0.038989533,0.00047379467,0.00003129318,0.000048430124,0.00027041667,0.000267977,0.005309273],"genre_scores_gemma":[0.98920536,0.0015739679,0.007847041,0.0000744793,0.000013931542,0.000025102856,0.00012390148,0.00001911937,0.0011170283],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99993443,0.000006908131,0.0000031894276,0.000028057264,0.00001677142,0.000010614113],"domain_scores_gemma":[0.99992836,0.000011594808,0.00002600302,0.000009716118,0.000013639343,0.000010804148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009896787,0.00017240446,0.00019622305,0.00028107708,0.0001387766,0.00040375607,0.00019715306,0.0003372454,0.0006303729],"category_scores_gemma":[0.00029073737,0.00012140209,0.00016267388,0.00018000294,0.0005052911,0.0005052263,0.00032775395,0.0003054759,0.00027367548],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014294067,0.00005270221,0.014012274,0.00020174596,0.0000530283,0.0002759408,0.00041242767,0.0024065243,0.89949405,0.005280585,0.00042979335,0.07723787],"study_design_scores_gemma":[0.000032785454,0.00058325595,0.5445306,0.00013506632,0.00009870757,0.0019194453,0.0008231639,0.030483903,0.37613744,0.033374507,0.011802512,0.00007860975],"about_ca_topic_score_codex":0.0016443728,"about_ca_topic_score_gemma":0.002874583,"teacher_disagreement_score":0.0016443728,"about_ca_system_score_codex":0.00034730954,"about_ca_system_score_gemma":0.00026481817,"threshold_uncertainty_score":0.0032696128},"labels":[],"label_agreement":null},{"id":"W4414509608","doi":"10.1002/hbm.70366","title":"A Combined Neuroanatomy, Ex Vivo Imaging, and Immunohistochemistry Defined <scp>MRI</scp> Mask for the Human Paraventricular Nucleus of the Thalamus","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Thalamus; Ex vivo; Human brain; Nucleus; Translation (biology); In vivo; Voxel; Magnetic resonance imaging","score_opus":0.026351798345765877,"score_gpt":0.316765132927157,"score_spread":0.2904133345813911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414509608","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18472965,0.00067699037,0.806223,0.00032608365,0.000079016165,0.00019852277,0.0011922686,0.0016414203,0.004933159],"genre_scores_gemma":[0.48416707,0.0007087195,0.508217,0.00019746803,0.00004461654,0.00036312744,0.002041297,0.00080110435,0.0034596175],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999754,0.000033641554,0.000015888008,0.0000764431,0.000097391596,0.000022629596],"domain_scores_gemma":[0.9997973,0.000033417225,0.000050194576,0.00005068015,0.000051306662,0.000017180924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047747232,0.00048084397,0.00023304984,0.00055146037,0.00034343783,0.0007371138,0.0006724672,0.0005800168,0.0019377401],"category_scores_gemma":[0.0009867427,0.0003353858,0.0003054616,0.0004079,0.00066820066,0.00047717494,0.0005594946,0.00040951552,0.0007950508],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011421727,0.00002930873,0.002117982,0.0002443246,0.00006163246,0.0006632889,0.00031476968,0.0052522817,0.92780644,0.005008618,0.0018724721,0.05651466],"study_design_scores_gemma":[0.00004861425,0.00036216958,0.06587772,0.00012747209,0.00019375059,0.008321324,0.00036390516,0.08869478,0.7823614,0.009610203,0.043941796,0.00009689124],"about_ca_topic_score_codex":0.0030723596,"about_ca_topic_score_gemma":0.008687165,"teacher_disagreement_score":0.0030723596,"about_ca_system_score_codex":0.00034161797,"about_ca_system_score_gemma":0.0011201848,"threshold_uncertainty_score":0.0064824224},"labels":[],"label_agreement":null},{"id":"W4414516295","doi":"10.3390/neurolint17100154","title":"Fractional Anisotropy Alterations in Key White Matter Pathways Associated with Cognitive Performance Assessed by MoCA","year":2025,"lang":"en","type":"article","venue":"Neurology International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Fasciculus; Inferior longitudinal fasciculus; Cognition; Biomarker","score_opus":0.023099932438510218,"score_gpt":0.3166568386578504,"score_spread":0.29355690621934016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414516295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983993,0.00045262204,0.00018897167,0.00002246069,0.0000045304373,0.0000129948885,0.00035145422,0.000012164927,0.00055545516],"genre_scores_gemma":[0.99922335,0.00008299033,0.00019770114,0.000005693659,0.0000057613024,0.000008754869,0.00022950253,0.0000026552825,0.00024369196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998097,0.000019409938,0.000021842272,0.00006213822,0.00004779288,0.000039174764],"domain_scores_gemma":[0.99909043,0.000068665875,0.0005638325,0.000051692907,0.00012899925,0.00009644217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000499347,0.0006100368,0.00036516314,0.0015307099,0.00045024772,0.00068598514,0.00024479558,0.00032202547,0.0016982842],"category_scores_gemma":[0.0019601907,0.00011630443,0.00034796228,0.0007099203,0.00028564673,0.0003815872,0.00042074083,0.00032336373,0.00023750911],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011802907,0.00006839397,0.9803884,0.00005802844,0.00039186332,0.00025938946,0.00030665763,0.00023998159,0.005308969,0.00008035763,0.00019985618,0.011517783],"study_design_scores_gemma":[0.000005623232,0.00010157496,0.99868494,0.000008279864,0.00004075162,0.0002574248,0.00007995263,0.00017743206,0.00045283465,0.00006724575,0.000119468226,0.000004497397],"about_ca_topic_score_codex":0.010559701,"about_ca_topic_score_gemma":0.011329452,"teacher_disagreement_score":0.010559701,"about_ca_system_score_codex":0.00034642662,"about_ca_system_score_gemma":0.00034267514,"threshold_uncertainty_score":0.020996511},"labels":[],"label_agreement":null},{"id":"W4414562304","doi":"10.1101/2025.09.26.678469","title":"Subthreshold violations of trajectory predictions are sensitive to TMS of Cerebellum CRUS I/II","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Fondation de France; Agence Nationale de la Recherche; Institut National de la Santé et de la Recherche Médicale; Deutsche Forschungsgemeinschaft","keywords":"Trajectory; Transcranial magnetic stimulation; Illusion; Electroencephalography; Modulation (music); Task (project management)","score_opus":0.035553404289907095,"score_gpt":0.289438461151674,"score_spread":0.2538850568617669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414562304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969783,0.00013492303,0.0023151936,0.00004288088,0.000014215332,0.000023729406,0.000058926988,0.000042193496,0.00038957424],"genre_scores_gemma":[0.99945134,0.000037424947,0.00030011067,0.000019466108,0.0000040293285,0.000009631846,0.00002786517,0.0000060225025,0.00014409592],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999038,0.00001891452,0.00000896268,0.000021007365,0.000029285518,0.000018052679],"domain_scores_gemma":[0.9995499,0.00013669132,0.0001948102,0.000042952888,0.00002848787,0.000047081572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014610103,0.00024488708,0.00016481978,0.00013656922,0.000060812403,0.0001437884,0.00011607531,0.00025622253,0.0011586071],"category_scores_gemma":[0.0014935497,0.00010797519,0.000107014326,0.00008143153,0.00031464547,0.0001416197,0.0002268017,0.00039036415,0.00009530016],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009708438,0.000029324769,0.0018179405,0.000039892904,0.00001471185,0.0002805062,0.00007227993,0.00014070816,0.9938066,0.000060183316,0.00004771597,0.0027192486],"study_design_scores_gemma":[0.00019277207,0.003321504,0.5421693,0.00003140358,0.000085525935,0.003249347,0.00026667956,0.0060976273,0.44243124,0.0011365057,0.0009885784,0.000029550662],"about_ca_topic_score_codex":0.00046918262,"about_ca_topic_score_gemma":0.00047833464,"teacher_disagreement_score":0.0011586071,"about_ca_system_score_codex":0.000114864124,"about_ca_system_score_gemma":0.00007390507,"threshold_uncertainty_score":0.0038759112},"labels":[],"label_agreement":null},{"id":"W4414613967","doi":"10.53555/qxw7sp51","title":"Quantum Mechanical Simulations In Diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Southampton","keywords":"Bloch equations; Spin diffusion; Quantum; Magnetic field; Diffusion; Formalism (music); Flow (mathematics); Spin echo; Diffusion equation; Spin (aerodynamics)","score_opus":0.36489803478972227,"score_gpt":0.4027617854837921,"score_spread":0.03786375069406983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414613967","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06365592,0.0011266543,0.9011551,0.0021263314,0.0002800235,0.00021262938,0.00064948655,0.0010256284,0.029768165],"genre_scores_gemma":[0.6222646,0.0014808084,0.35805047,0.000585422,0.00019780277,0.0008857017,0.00066918816,0.0008084026,0.015057582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997099,0.00012001529,0.00001581366,0.00003242068,0.0000930114,0.00002879724],"domain_scores_gemma":[0.99871707,0.00087219244,0.00007843385,0.00009296998,0.00016973911,0.00006961516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008901674,0.0004175587,0.00056203536,0.00050294615,0.0008380944,0.00078675826,0.0010510955,0.0014315064,0.005744715],"category_scores_gemma":[0.0030707943,0.00041448005,0.0007549706,0.0004952722,0.0010951333,0.00123911,0.0011393657,0.0009865016,0.0006358927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002955023,0.000047835576,0.00069205876,0.00010574688,0.000028168004,0.00010125208,0.0001451955,0.88013655,0.002571033,0.10812986,0.001390281,0.006622531],"study_design_scores_gemma":[0.000011222328,0.0000061092237,0.000086871856,0.000007334397,0.0000028930676,0.000013236331,0.000009529608,0.9815994,0.00038442432,0.015983654,0.0018888072,0.00000659287],"about_ca_topic_score_codex":0.008197105,"about_ca_topic_score_gemma":0.003766435,"teacher_disagreement_score":0.008197105,"about_ca_system_score_codex":0.0009425509,"about_ca_system_score_gemma":0.0011592408,"threshold_uncertainty_score":0.019218028},"labels":[],"label_agreement":null},{"id":"W4414656468","doi":"10.3390/axioms14100743","title":"First and Second Moments of Spherical Distributions That Are Relevant for Biological Applications","year":2025,"lang":"en","type":"article","venue":"Axioms","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anisotropy; Moment (physics); Distribution (mathematics); Bessel function; Divergence (linguistics); Method of moments (probability theory); Trigonometric functions; Second moment of area; Upper and lower bounds","score_opus":0.07442368640475619,"score_gpt":0.3633774067911345,"score_spread":0.28895372038637834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414656468","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022045042,0.0019903716,0.95232844,0.0012556553,0.00024068977,0.000025382284,0.00028651964,0.00024379672,0.02158402],"genre_scores_gemma":[0.749102,0.0077349623,0.21926439,0.001111144,0.0012657446,0.00015448238,0.0007649858,0.00071098155,0.019891402],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990821,0.00022617396,0.000066315675,0.00018743936,0.00032491304,0.00011300823],"domain_scores_gemma":[0.9953934,0.0025442836,0.0005987232,0.00050197623,0.000770436,0.00019116077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022651465,0.00084806466,0.0006214254,0.0022649353,0.0007311793,0.0024711406,0.0009130251,0.0011537638,0.0052495804],"category_scores_gemma":[0.012874324,0.0003261608,0.00083418284,0.0016985881,0.0032479155,0.0042604934,0.0011112557,0.0022635045,0.0015867876],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021284528,0.000014481078,0.0005384115,0.00010130611,0.000009978207,0.00020409182,0.00020342394,0.00877408,0.0056853443,0.96197325,0.0022662815,0.02020804],"study_design_scores_gemma":[0.0000055953024,0.000017336457,0.0017265888,0.000053568365,0.000008788303,0.0009341812,0.00017129065,0.06714561,0.0031734575,0.9177715,0.0089459475,0.000046109155],"about_ca_topic_score_codex":0.001379356,"about_ca_topic_score_gemma":0.0009286848,"teacher_disagreement_score":0.0052495804,"about_ca_system_score_codex":0.00090555527,"about_ca_system_score_gemma":0.0009795938,"threshold_uncertainty_score":0.017561615},"labels":[],"label_agreement":null},{"id":"W4414672190","doi":"10.1101/2025.09.29.678806","title":"Lifespan Trajectories of Asymmetry in White Matter Tracts","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Euroimmun Medizinische Labordiagnostika; Common Fund; National Institute of General Medical Sciences; National Institute on Deafness and Other Communication Disorders; National Institute of Mental Health; National Institute on Aging; Biotechnology and Biological Sciences Research Council; Avid Radiopharmaceuticals; University of Cambridge; University of Calgary; IXICO; Servier; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; University of Queensland; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; National Institute on Drug Abuse; University of Pennsylvania; Vanderbilt University; Pfizer; BioClinica; Biogen; Illinois Department of Public Health; National Center for Advancing Translational Sciences; Cure Alzheimer's Fund; Alzheimer's Association; National Institutes of Health; U.S. Department of Health and Human Services; National Health and Medical Research Council; Foundation for the National Institutes of Health","keywords":"White matter; Asymmetry; Lateralization of brain function; Brain asymmetry; Neuroimaging; Scope (computer science); Association (psychology)","score_opus":0.027781070003884654,"score_gpt":0.29095870653653794,"score_spread":0.2631776365326533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414672190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98503715,0.00074691506,0.002929724,0.0000884431,0.000007094924,0.000009593528,0.010236173,0.00006556994,0.0008794291],"genre_scores_gemma":[0.98471767,0.00041867798,0.0038320262,0.000029294191,0.000005086243,0.00002904458,0.010310558,0.000030573276,0.0006270421],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998503,0.000028654216,0.000012761419,0.000073131065,0.000017625274,0.000017471179],"domain_scores_gemma":[0.9990748,0.00020778227,0.00026066808,0.0001503538,0.0002150324,0.00009134781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090336456,0.00022968973,0.0001733632,0.0011907121,0.00024375705,0.00042092698,0.00015082765,0.00018299438,0.0012407994],"category_scores_gemma":[0.0031980188,0.00012715987,0.00025553966,0.0006950301,0.00016625297,0.0004149776,0.00061036716,0.0002761089,0.000269014],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038820173,0.00003134543,0.91756535,0.00012477527,0.00031587377,0.0005588964,0.0013094085,0.0038262215,0.013147432,0.0022989612,0.004350451,0.056083113],"study_design_scores_gemma":[0.000007482805,0.00008057573,0.98559314,0.00007093383,0.000094560266,0.0007732928,0.0003325239,0.0030471568,0.00190473,0.0023401561,0.0057329885,0.000022434022],"about_ca_topic_score_codex":0.0045699384,"about_ca_topic_score_gemma":0.009823541,"teacher_disagreement_score":0.0045699384,"about_ca_system_score_codex":0.00023304872,"about_ca_system_score_gemma":0.00028457708,"threshold_uncertainty_score":0.0090866685},"labels":[],"label_agreement":null},{"id":"W4414712871","doi":"10.1016/j.neuroimage.2025.121489","title":"Early White Matter Microstructure Alterations in Infants with Down Syndrome","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; Uncinate fasciculus; White matter; Diffusion MRI; Trisomy; Inferior longitudinal fasciculus","score_opus":0.014862701400506802,"score_gpt":0.3019618203962363,"score_spread":0.2870991189957295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414712871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995913,0.00015377904,0.00009421524,0.000009917492,0.0000014192198,0.0000022935594,0.000045038905,0.0000044894323,0.000097477016],"genre_scores_gemma":[0.9990771,0.00033827452,0.00032668991,0.000013100451,0.0000031794502,0.000006306037,0.000089471476,0.000002475653,0.00014344661],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998567,0.00002650938,0.000018897364,0.00003719152,0.000037043446,0.000023511155],"domain_scores_gemma":[0.9997218,0.00004706174,0.00014786387,0.000014205325,0.000033906195,0.000034982655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025702507,0.00031468866,0.00021481502,0.00065576314,0.00017103855,0.00025879257,0.0001180147,0.00027691695,0.0005046495],"category_scores_gemma":[0.0009831374,0.00018067683,0.00015215571,0.00022463559,0.00022594804,0.00017255939,0.00031930953,0.0002028082,0.00007513528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005252452,0.00005421829,0.9276026,0.00007212548,0.000055610806,0.0073805023,0.0013201383,0.00016774522,0.042361464,0.000105736064,0.00017148197,0.020183222],"study_design_scores_gemma":[0.0000017016532,0.00010325381,0.99501956,0.000009613292,0.000015338368,0.003116794,0.00017454741,0.000101376805,0.0013358647,0.000018994224,0.00009958652,0.0000032505982],"about_ca_topic_score_codex":0.0036145241,"about_ca_topic_score_gemma":0.0036881492,"teacher_disagreement_score":0.0036145241,"about_ca_system_score_codex":0.00024317324,"about_ca_system_score_gemma":0.0001470576,"threshold_uncertainty_score":0.0071869493},"labels":[],"label_agreement":null},{"id":"W4414867530","doi":"10.1016/j.mri.2025.110539","title":"Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; Vanderbilt Kennedy Center, Vanderbilt University Medical Center; Vanderbilt Institute for Clinical and Translational Research; National Institute on Aging; National Cancer Institute; National Institutes of Health; Vanderbilt University","keywords":"Anisotropy; Voxel; Diffusion MRI; Sensitivity (control systems); Fractional anisotropy; Tractography; Thermal diffusivity","score_opus":0.021869585696872734,"score_gpt":0.33425271619481484,"score_spread":0.3123831304979421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414867530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72644067,0.0048624063,0.26361826,0.0004985872,0.00014557665,0.0002168122,0.0008774178,0.0006175195,0.0027227858],"genre_scores_gemma":[0.9834457,0.0003212203,0.015370389,0.000080141035,0.000040754578,0.00006333484,0.00039195723,0.00012743587,0.0001590148],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98731273,0.0061021494,0.0010173876,0.0030303858,0.0022989453,0.00023836896],"domain_scores_gemma":[0.8484231,0.12044434,0.014559066,0.01153309,0.004519049,0.00052128546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025675254,0.00076168467,0.00073399,0.0016992625,0.0005298296,0.001614275,0.0006070498,0.00066520483,0.0008660471],"category_scores_gemma":[0.13339849,0.0005469791,0.0007285758,0.0012169171,0.002039282,0.0011169736,0.0014162518,0.00071002624,0.0002352282],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002997839,0.00013074013,0.5953021,0.0018206001,0.005018346,0.0009143864,0.0030131892,0.1019875,0.089297436,0.007935271,0.0018282279,0.18975437],"study_design_scores_gemma":[0.00010833408,0.0005888273,0.778712,0.0002636146,0.0009381979,0.0039609093,0.0004161215,0.14619344,0.034533527,0.03070197,0.0033792763,0.00020378012],"about_ca_topic_score_codex":0.002715417,"about_ca_topic_score_gemma":0.001779844,"teacher_disagreement_score":0.025675254,"about_ca_system_score_codex":0.0007441431,"about_ca_system_score_gemma":0.0005308955,"threshold_uncertainty_score":0.13578534},"labels":[],"label_agreement":null},{"id":"W4414905029","doi":"10.1101/2025.10.03.25337290","title":"Towards repeatable and converging methods in diffusion MRI: Evidence from a longitudinal chronic pain cohort","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Repeatability; Fractional anisotropy; Diffusion MRI; Cohort; White matter; Chronic pain; Diffusion imaging","score_opus":0.10245665909581683,"score_gpt":0.4348610783171668,"score_spread":0.33240441922135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414905029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890371,0.0017738714,0.0072333687,0.00033740213,0.00004983939,0.000089401394,0.0005605526,0.00005720297,0.0008613097],"genre_scores_gemma":[0.9953311,0.00032734394,0.0032503621,0.00008192219,0.000043454926,0.00007131894,0.0005812138,0.00004478613,0.00026854925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.98699176,0.0065881163,0.0011476118,0.0027901959,0.0020299389,0.0004523431],"domain_scores_gemma":[0.9339154,0.01886281,0.016665265,0.017514352,0.011698248,0.0013439282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038448557,0.0005940616,0.00061214407,0.0015663502,0.0011732102,0.0029640477,0.0020479583,0.0013825148,0.0016381019],"category_scores_gemma":[0.06774057,0.0007084267,0.0010348122,0.0013185423,0.0017150996,0.0018250358,0.0017427846,0.00113672,0.00055801676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050133665,0.000099448705,0.9802127,0.00009926801,0.00082214916,0.00015771542,0.0015813478,0.00026289624,0.0011864904,0.00025761744,0.00043732297,0.0143816965],"study_design_scores_gemma":[0.00004329259,0.0005588766,0.9940613,0.00010523607,0.00029617554,0.0005513949,0.0007071549,0.0011052398,0.0007304883,0.0006912092,0.0011168075,0.000032973512],"about_ca_topic_score_codex":0.007303155,"about_ca_topic_score_gemma":0.0066403043,"teacher_disagreement_score":0.038448557,"about_ca_system_score_codex":0.00057045056,"about_ca_system_score_gemma":0.0008922241,"threshold_uncertainty_score":0.20333785},"labels":[],"label_agreement":null},{"id":"W4415010674","doi":"10.7554/elife.96625.4","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cerebellum; Thalamus; Neurite; Attenuation; Taurine; Diffusion MRI; Diffusion","score_opus":0.03124378646310415,"score_gpt":0.3209232413370653,"score_spread":0.28967945487396113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415010674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9604818,0.0010871566,0.03691755,0.00006297359,0.00001441215,0.000019988101,0.00046596458,0.00031331272,0.0006368477],"genre_scores_gemma":[0.95733404,0.0024575794,0.037018053,0.00004462039,0.0000063901216,0.00008737764,0.00064450875,0.00016436956,0.0022430893],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999291,0.0000069503335,0.0000050524022,0.00002768162,0.000020519547,0.000010772765],"domain_scores_gemma":[0.9998437,0.000021022597,0.00006522644,0.00001200322,0.000037579186,0.000020457848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021971611,0.00042160985,0.0002588333,0.0004513982,0.00010215918,0.000267015,0.00024864697,0.0002943043,0.0003918228],"category_scores_gemma":[0.00037359667,0.00021137182,0.00021444175,0.00015008119,0.00021971756,0.00029965604,0.00032216118,0.0003122197,0.00013701204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006614032,0.000005045608,0.001628385,0.00004278272,0.0000107581955,0.00012420803,0.000067910485,0.00049579534,0.9924229,0.0001352465,0.000034271543,0.0049665566],"study_design_scores_gemma":[0.000011339873,0.0005763885,0.04929139,0.00003724728,0.00011646609,0.00094390416,0.00030051457,0.011765509,0.93482006,0.00041325323,0.0016839207,0.00003987526],"about_ca_topic_score_codex":0.0023896634,"about_ca_topic_score_gemma":0.004174498,"teacher_disagreement_score":0.0023896634,"about_ca_system_score_codex":0.00023218665,"about_ca_system_score_gemma":0.00027248694,"threshold_uncertainty_score":0.0047515035},"labels":[],"label_agreement":null},{"id":"W4415057797","doi":"10.31083/jin36357","title":"Reappraising the Anatomy of the Ansa Lenticularis in the Human Brain: A Cadaveric, Focused Fiber Micro-Dissection Study Perspective","year":2025,"lang":"en","type":"article","venue":"Journal of Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Perspective (graphical); Microdissection; Tractography; Fiber tract; Fiber; Cadaveric spasm","score_opus":0.04431137675831527,"score_gpt":0.41872808108439374,"score_spread":0.3744167043260785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415057797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9568587,0.0037614908,0.03423947,0.00009296789,0.000044790166,0.00014922155,0.00047497664,0.00013203174,0.0042464067],"genre_scores_gemma":[0.96456647,0.0029301234,0.02863802,0.000092213864,0.000020480902,0.00008613823,0.000406492,0.000034310015,0.0032257927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999207,0.00000765635,0.000006641455,0.000034936602,0.000017273855,0.000012775116],"domain_scores_gemma":[0.9997836,0.000045489072,0.00003225969,0.00008047302,0.00004416439,0.000013988557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054828636,0.00035159828,0.00017058058,0.0009802656,0.00028338446,0.00029295526,0.00027744655,0.00039099486,0.0035127734],"category_scores_gemma":[0.00023689397,0.00031449823,0.00018323479,0.0002341655,0.0007110291,0.00038576138,0.00023875399,0.00035132887,0.00065724953],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033839737,0.00019150967,0.013836362,0.00033187857,0.00010562289,0.009390497,0.0008780566,0.0013164583,0.9167493,0.001258526,0.0004412498,0.05516226],"study_design_scores_gemma":[0.0001514998,0.0053683408,0.3509547,0.0005350112,0.00062134047,0.21855421,0.0022721058,0.010599193,0.36063,0.0024141273,0.047772586,0.00012689695],"about_ca_topic_score_codex":0.0020858513,"about_ca_topic_score_gemma":0.004334524,"teacher_disagreement_score":0.0035127734,"about_ca_system_score_codex":0.00027312653,"about_ca_system_score_gemma":0.00040613321,"threshold_uncertainty_score":0.011751413},"labels":[],"label_agreement":null},{"id":"W4415116021","doi":"10.1101/2025.10.12.681536","title":"A Comprehensive Characterization of the Phospholipid and Cholesterol Composition of the Uncinate Fasciculus in the Human Brain: Evidence of Age‐Related Alterations","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Uncinate fasciculus; Myelin; Phospholipid; White matter; Cholesterol; Cortex (anatomy); Depression (economics); Triglyceride; Prefrontal cortex","score_opus":0.04040338551975504,"score_gpt":0.3021549334276938,"score_spread":0.26175154790793875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415116021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947001,0.0033450767,0.0008372064,0.000031044347,0.000006277087,0.000011115081,0.0005652162,0.000011812133,0.0004922227],"genre_scores_gemma":[0.99653244,0.0014478463,0.0009085578,0.000032569176,0.0000069055586,0.000012082714,0.0005479799,0.0000066558537,0.0005048313],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999248,0.000008232246,0.00000892882,0.000029969342,0.000015638094,0.000012499623],"domain_scores_gemma":[0.9998338,0.000016975971,0.000058581994,0.000023454673,0.000047745976,0.000019269382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016907413,0.00024619952,0.00020062849,0.0009666778,0.00020031979,0.0002682413,0.000101885904,0.0002554644,0.00070535654],"category_scores_gemma":[0.00036157438,0.000114364775,0.0001010268,0.00042153432,0.00019415206,0.00017319698,0.00024008712,0.00016391421,0.0002195398],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016715743,0.000051964587,0.20528227,0.00022377833,0.00018240948,0.0011725493,0.0005897981,0.00009378654,0.7595531,0.00016912597,0.00023231481,0.030777361],"study_design_scores_gemma":[0.000010219442,0.00028282564,0.9527728,0.000027391952,0.00008482592,0.004664109,0.00031407826,0.00029057494,0.039259307,0.00014267444,0.0021398177,0.000011443584],"about_ca_topic_score_codex":0.0019506653,"about_ca_topic_score_gemma":0.0017591562,"teacher_disagreement_score":0.0019506653,"about_ca_system_score_codex":0.00010900475,"about_ca_system_score_gemma":0.000100756275,"threshold_uncertainty_score":0.003878653},"labels":[],"label_agreement":null},{"id":"W4415225287","doi":"10.1227/neu.0000000000003792","title":"Resectability of White Matter Tracts in Patients With Language-Critical Gliomas","year":2025,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Temporal lobe; Magnetic resonance imaging; Central nervous system disease; Operculum (bryozoa); Hyperintensity","score_opus":0.020009986665413794,"score_gpt":0.3330147159183774,"score_spread":0.3130047292529636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415225287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995865,0.000117827905,0.00005524516,0.000012388262,0.0000016532355,0.0000023792404,0.00006848071,0.0000022964462,0.00015324527],"genre_scores_gemma":[0.9997794,0.000051818024,0.000038763374,0.0000035779472,0.0000031215504,0.000001697844,0.00008810206,0.0000010412023,0.00003251204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986637,0.000015567826,0.000019159843,0.000038067756,0.000029917734,0.00003090925],"domain_scores_gemma":[0.99904424,0.00013449031,0.00060240814,0.000041992684,0.00006244261,0.00011445208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022185319,0.00031822093,0.00016473509,0.000596197,0.00025190966,0.0003389203,0.00021549835,0.0002717499,0.001113943],"category_scores_gemma":[0.0015394108,0.00013097121,0.00021229264,0.00040511356,0.00030036827,0.00038310458,0.00030246863,0.0003130656,0.0002010214],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008497977,0.0000077295645,0.99760747,0.000005952575,0.000011236532,0.0006155369,0.000027108326,0.000040811126,0.0005304132,0.000008167987,0.000025090692,0.0010355242],"study_design_scores_gemma":[0.0000040873365,0.00009751284,0.9942987,0.0000061193045,0.000018473502,0.0047397865,0.00012891216,0.000181086,0.00037991258,0.000040422092,0.00010155563,0.000003269501],"about_ca_topic_score_codex":0.0013132792,"about_ca_topic_score_gemma":0.0021770399,"teacher_disagreement_score":0.0013132792,"about_ca_system_score_codex":0.00016201491,"about_ca_system_score_gemma":0.00026208884,"threshold_uncertainty_score":0.003726542},"labels":[],"label_agreement":null},{"id":"W4415248294","doi":"10.1038/s41598-025-20016-7","title":"Standardization of postmortem human brainstem along the rostrocaudal axis to accommodate for inter-specimen structural heterogeneity","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"National Institute on Aging; National Institutes of Health","keywords":"Brainstem; Standardization; Postmortem studies; Central nervous system; Brain development","score_opus":0.05055876487264321,"score_gpt":0.39105012773952097,"score_spread":0.34049136286687776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415248294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5777444,0.0040335096,0.40198955,0.00030600425,0.0006641763,0.0028415355,0.0019693782,0.0009399007,0.009511573],"genre_scores_gemma":[0.61980194,0.0023237371,0.36664605,0.000436858,0.000113657705,0.0037982515,0.0025725719,0.00089703937,0.0034098453],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972283,0.000665487,0.00054449483,0.00079502736,0.000641483,0.00012522175],"domain_scores_gemma":[0.99445206,0.0006074439,0.00083649054,0.0020523102,0.0019248734,0.0001268171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006485802,0.00067129894,0.00048410372,0.0018836359,0.0012862436,0.0012391512,0.0008435646,0.00070233975,0.0025435004],"category_scores_gemma":[0.0073782615,0.00062476733,0.0003810221,0.0011294596,0.0017686253,0.00077356107,0.0013498494,0.00088785443,0.0010611325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015639727,0.00026812512,0.046970177,0.0008903194,0.00021560324,0.0011584678,0.003291072,0.0031756477,0.85829717,0.0053876177,0.002014161,0.0767676],"study_design_scores_gemma":[0.00016970228,0.004175472,0.41459984,0.0008050287,0.0005819056,0.0058624838,0.0031782286,0.009278575,0.5016525,0.0047796345,0.054737605,0.00017901498],"about_ca_topic_score_codex":0.0018246163,"about_ca_topic_score_gemma":0.0077232644,"teacher_disagreement_score":0.006485802,"about_ca_system_score_codex":0.00049924967,"about_ca_system_score_gemma":0.0008341125,"threshold_uncertainty_score":0.034300625},"labels":[],"label_agreement":null},{"id":"W4415249470","doi":"10.46298/mbj.16170","title":"Cumulative Directional Strain and Fractional Anisotropy Changes in the Corpus Callosum After a Football Season","year":2025,"lang":"en","type":"article","venue":"Multidisciplinary Biomechanics Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Corpus callosum; Anisotropy; Strain (injury); Football","score_opus":0.04771591689516888,"score_gpt":0.3671117044093601,"score_spread":0.3193957875141912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415249470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99926525,0.00008996169,0.000073495066,0.00003414248,0.0000107168435,0.0000049967207,0.00014071107,0.0000058771525,0.0003748672],"genre_scores_gemma":[0.99902093,0.000052924377,0.00003204612,0.000012650979,0.000012303554,0.0000070986407,0.00015509124,0.0000046908863,0.00070224825],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999884,0.000010916497,0.000005506409,0.000024902965,0.00001572638,0.000058911344],"domain_scores_gemma":[0.9993013,0.00012736187,0.0001442932,0.000061409766,0.00013552778,0.00023006019],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025337056,0.0002448537,0.00037522908,0.0005690261,0.00045432325,0.00059118436,0.00026285285,0.0007299772,0.0022202483],"category_scores_gemma":[0.0013682958,0.00018531161,0.0002505587,0.0004939427,0.00043095887,0.0003600058,0.00039384412,0.0006899544,0.00036429008],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.024120847,0.0020221446,0.8178335,0.00014585922,0.00063580525,0.0061518257,0.002547497,0.0028546916,0.09030685,0.00040984622,0.0017429872,0.05122821],"study_design_scores_gemma":[0.0000060919847,0.00024771644,0.9982237,0.0000059688305,0.000024480256,0.00023551022,0.00025520838,0.00020332012,0.00058666477,0.000057763325,0.00014136551,0.000012185497],"about_ca_topic_score_codex":0.034358405,"about_ca_topic_score_gemma":0.03229289,"teacher_disagreement_score":0.034358405,"about_ca_system_score_codex":0.00036490304,"about_ca_system_score_gemma":0.0005260231,"threshold_uncertainty_score":0.06831688},"labels":[],"label_agreement":null},{"id":"W4415298994","doi":"10.1093/schbul/sbaf172","title":"Altered Cortical Gyrification Is Associated with Cortical and White Matter Microstructure in Individuals with Early Psychosis: A Multimodal Neuroimaging Study","year":2025,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"National Institute of Mental Health; Japan Agency for Medical Research and Development","keywords":"Cytoarchitecture; Gyrification; White matter; Neuroimaging; Grey matter; Cerebral cortex; Insula","score_opus":0.01631633499069506,"score_gpt":0.29830287972734215,"score_spread":0.2819865447366471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415298994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99974924,0.000046913814,0.000065944216,0.000011240935,3.858594e-7,0.0000053817707,0.000038375332,0.0000016376168,0.00008094385],"genre_scores_gemma":[0.9998288,0.000019679346,0.00007378992,0.0000044886965,0.0000013719562,0.000004376523,0.000038680355,7.3987206e-7,0.00002783598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99984765,0.000035107787,0.000016325812,0.00004933355,0.000022530394,0.000028974217],"domain_scores_gemma":[0.9995554,0.00008412347,0.0002278941,0.000038557315,0.000030851028,0.00006307327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035154584,0.00047160708,0.00030201997,0.0011413085,0.00037616462,0.0004022154,0.00022768961,0.0004648841,0.0011655799],"category_scores_gemma":[0.0013756676,0.0002973639,0.00026097524,0.00060332107,0.0005245801,0.00035869214,0.00059226213,0.00028300265,0.00010322608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063779,0.00008455499,0.9854364,0.000037309386,0.00014470643,0.0011999267,0.00076417124,0.00011523851,0.0076387944,0.000051086226,0.000056428136,0.0038336092],"study_design_scores_gemma":[0.0000066629327,0.00009122627,0.99850607,0.000003873134,0.000027941778,0.00081573625,0.0001678604,0.00012830633,0.00017296786,0.000053471096,0.000022851786,0.000003022418],"about_ca_topic_score_codex":0.0025203596,"about_ca_topic_score_gemma":0.003666068,"teacher_disagreement_score":0.0025203596,"about_ca_system_score_codex":0.00029904416,"about_ca_system_score_gemma":0.0002123562,"threshold_uncertainty_score":0.0050114393},"labels":[],"label_agreement":null},{"id":"W4415375973","doi":"10.1038/s41598-025-20328-8","title":"Advancing image-based meta-analysis through systematic use of crowdsourced NeuroVault data","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Mental Health; National Institutes of Health; Florida International University","keywords":"Spurious relationship; Human Connectome Project; Set (abstract data type); Heuristic; Neuroimaging; Selection (genetic algorithm); Estimator; Connectome","score_opus":0.22183971592356214,"score_gpt":0.416917559587585,"score_spread":0.19507784366402284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415375973","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012427483,0.03196406,0.9127989,0.005716707,0.0009274288,0.0068592015,0.020707346,0.0052232193,0.0033756618],"genre_scores_gemma":[0.1758726,0.0048529063,0.78007746,0.0022259592,0.00033835735,0.023640849,0.010598696,0.0017895178,0.00060361705],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.6292816,0.32518443,0.016993275,0.016042018,0.011632283,0.0008664284],"domain_scores_gemma":[0.30110154,0.5757787,0.02124152,0.0877363,0.013152847,0.0009890671],"candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3022937,0.004014644,0.007395093,0.016273843,0.002164603,0.0073139207,0.0069268793,0.0030709477,0.006431042],"category_scores_gemma":[0.5882954,0.0026408702,0.019724013,0.015644494,0.0025586318,0.004097469,0.009251446,0.0035879605,0.0012357291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030652212,0.00031147338,0.041988656,0.12670158,0.3111131,0.0012947561,0.009520607,0.05307629,0.004054967,0.054812714,0.047508515,0.3465521],"study_design_scores_gemma":[0.0066728536,0.0011308352,0.02950368,0.035980985,0.21905206,0.0008470307,0.0025292707,0.08956482,0.008502559,0.44564125,0.159256,0.0013186949],"about_ca_topic_score_codex":0.006498941,"about_ca_topic_score_gemma":0.010087425,"teacher_disagreement_score":0.69770634,"about_ca_system_score_codex":0.0035541127,"about_ca_system_score_gemma":0.013142041,"threshold_uncertainty_score":0.8603961},"labels":[],"label_agreement":null},{"id":"W4415408384","doi":"10.1002/hbm.70386","title":"Mapping Human Proprioceptive Projections of Upper Limb Muscles Through Spinal Cord <scp>fMRI</scp>","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Agence Nationale de la Recherche; Agence de l'innovation de Défense; Centre National de la Recherche Scientifique; Aix-Marseille Université","keywords":"Proprioception; Spinal cord; Myotome; Functional magnetic resonance imaging; Wrist; Somatosensory system; Electromyography; Upper limb; Magnetic resonance imaging","score_opus":0.11460665955832795,"score_gpt":0.3976209959361577,"score_spread":0.28301433637782974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415408384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7731533,0.0028319631,0.21817732,0.0006260531,0.000041918433,0.000103633414,0.00067540817,0.0005258695,0.0038646103],"genre_scores_gemma":[0.95938456,0.00066828536,0.038743306,0.00010967888,0.00003220008,0.00005870485,0.00018491136,0.00003065008,0.0007877037],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999492,0.000013149215,0.0000027885499,0.000015891505,0.000012385822,0.0000065468],"domain_scores_gemma":[0.99993217,0.000030621286,0.000014874942,0.0000054045445,0.000011104761,0.0000058377796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014319514,0.000280262,0.00012031187,0.0002216314,0.00010925721,0.00018755226,0.00014318366,0.00023213925,0.0009593625],"category_scores_gemma":[0.0005678345,0.00006848854,0.00008409959,0.00016217596,0.00022245136,0.00015888372,0.00015185874,0.00012998744,0.00012942519],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002445307,0.000042783893,0.0048362496,0.00028738036,0.000048361362,0.0005569999,0.000106982334,0.0083941445,0.8440271,0.0005543788,0.0012893245,0.13961177],"study_design_scores_gemma":[0.00006421661,0.0007336912,0.312625,0.00014869211,0.00019736637,0.0045398036,0.0002118739,0.22840808,0.44105145,0.0044760257,0.0074782413,0.00006557154],"about_ca_topic_score_codex":0.0022472942,"about_ca_topic_score_gemma":0.005344351,"teacher_disagreement_score":0.0022472942,"about_ca_system_score_codex":0.00012846882,"about_ca_system_score_gemma":0.00024259387,"threshold_uncertainty_score":0.0044683814},"labels":[],"label_agreement":null},{"id":"W4415456288","doi":"10.1007/s00429-025-03025-0","title":"Rethinking tractography and neuroanatomy: does image resolution hold the key?","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Université de Sherbrooke","funders":"European Research Council; Canada Research Chairs","keywords":"Tractography; Resolution (logic); Image resolution; Projection (relational algebra); Diffusion MRI; Connectome; Image (mathematics); Diffusion imaging","score_opus":0.038656618432298694,"score_gpt":0.33801836096818777,"score_spread":0.2993617425358891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415456288","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000059200862,0.9955325,0.0006409087,0.0026653083,0.00042973147,0.0000034480602,0.000013563074,0.0000116101,0.0006437403],"genre_scores_gemma":[0.0008267103,0.99530196,0.0010941065,0.0015152757,0.0007686978,0.000012594044,0.000026356678,0.0000137782545,0.00044053595],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989039,0.00029778216,0.0001801425,0.00017948862,0.0003688312,0.00006988344],"domain_scores_gemma":[0.99430037,0.0039638286,0.00030606074,0.00020011136,0.0010550071,0.0001746343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005573198,0.0012020973,0.0029574402,0.00324801,0.00054023915,0.0035372644,0.0023228917,0.0034639928,0.0028908632],"category_scores_gemma":[0.006579367,0.0006186002,0.00093644916,0.003313555,0.0053792326,0.008453713,0.0017659032,0.006643869,0.003048884],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005704171,0.0000298734,0.0002166093,0.017799733,0.00015748116,0.00015690624,0.00029601448,0.00050807354,0.0012123394,0.05793639,0.036171235,0.8854584],"study_design_scores_gemma":[0.00001258572,0.000062001505,0.0006560635,0.008071216,0.00008623709,0.00095185544,0.00020999518,0.00017345308,0.0004478863,0.04148736,0.9477908,0.000050453087],"about_ca_topic_score_codex":0.0029110527,"about_ca_topic_score_gemma":0.0034930427,"teacher_disagreement_score":0.005573198,"about_ca_system_score_codex":0.0020448675,"about_ca_system_score_gemma":0.0035891505,"threshold_uncertainty_score":0.029474258},"labels":[],"label_agreement":null},{"id":"W4415464241","doi":"10.1101/2025.10.22.683760","title":"Bridging Histology and Tractography: First In-Vivo Visualization of Short-Range Prefrontal Connections Informed by Primate Tract-Tracing","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Prefrontal cortex; Bridging (networking); Primate; Connectome; Visualization; Cognition; Nonhuman primate","score_opus":0.025505865460210924,"score_gpt":0.3032880370588792,"score_spread":0.27778217159866825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415464241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20814276,0.001757501,0.7833993,0.00042573988,0.00005314451,0.00008257624,0.00062248146,0.0013615501,0.0041549434],"genre_scores_gemma":[0.62912667,0.0018769832,0.36472663,0.00013625911,0.0000332976,0.00012397331,0.00051380164,0.0005671559,0.002895397],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998048,0.000067932946,0.000009833371,0.00004450726,0.000050881365,0.000022013788],"domain_scores_gemma":[0.9995191,0.00015560751,0.000087707034,0.0001253062,0.00007630585,0.000036002213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007222163,0.00037861135,0.0002707844,0.00069427444,0.00040924,0.0008110212,0.00040237358,0.0007354576,0.0018024764],"category_scores_gemma":[0.0015943295,0.00044870254,0.00023444141,0.0004996548,0.000797115,0.00060079,0.0007089907,0.0008526415,0.0006500097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015399742,0.00004519229,0.007658406,0.00037562262,0.00012733712,0.00090056245,0.00095432054,0.013718776,0.86152565,0.008210646,0.0018916685,0.10443792],"study_design_scores_gemma":[0.00006995448,0.00052518083,0.09960682,0.00053855777,0.00023500154,0.0112093985,0.00084997586,0.23191762,0.5195663,0.05534029,0.07993619,0.00020472016],"about_ca_topic_score_codex":0.0028396107,"about_ca_topic_score_gemma":0.0073710675,"teacher_disagreement_score":0.0028396107,"about_ca_system_score_codex":0.00036285925,"about_ca_system_score_gemma":0.00061970577,"threshold_uncertainty_score":0.006029904},"labels":[],"label_agreement":null},{"id":"W4415522803","doi":"10.1038/s41398-025-03602-1","title":"Transdiagnostic alterations in white matter microstructure associated with suicidal thoughts and behaviours in the ENIGMA Suicidal Thoughts and Behaviours consortium","year":2025,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Dalhousie University","funders":"National Institute on Drug Abuse; Weill Institute for Neurosciences, University of California, San Francisco; National Institute of Mental Health; National Center for Complementary and Integrative Health; National Institute on Aging; Instituto de Salud Carlos III; National Health and Medical Research Council; Engineering and Physical Sciences Research Council; National Center for Advancing Translational Sciences; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; Instituto de Investigación Marqués de Valdecilla; Junta de Andalucía; University of California, San Francisco; Ministero della Salute; Bundesministerium für Bildung und Forschung; Universiteit Leiden; Japan Agency for Medical Research and Development; Deutsche Forschungsgemeinschaft; South African Medical Research Council; Japan Society for the Promotion of Science; Conselho Nacional de Desenvolvimento Científico e Tecnológico; University of Texas Health Science Center at Houston; Dalhousie University; Nova Scotia Health Research Foundation; Scottish Funding Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Center for Research Resources; Agence Nationale de la Recherche; Wellcome Trust; Bill and Melinda Gates Foundation; National Alliance for Research on Schizophrenia and Depression; University of Minnesota; Ministerio de Ciencia e Innovación; American Foundation for Suicide Prevention; European Commission; Brain and Behavior Research Foundation; John S. Dunn Foundation; Universidad de Sevilla; Chief Scientist Office, Scottish Government Health and Social Care Directorate; Scottish Government; U.S. Department of Health and Human Services","keywords":"Corpus callosum; Fractional anisotropy; Suicidal ideation; White matter; Diffusion MRI; Poison control; Young adult","score_opus":0.01910613751411181,"score_gpt":0.3157839278725122,"score_spread":0.29667779035840036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415522803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99497557,0.00038507412,0.0005307661,0.00015369868,0.000015670807,0.000119398865,0.003241683,0.000023023129,0.0005552597],"genre_scores_gemma":[0.98848104,0.00028418837,0.0012178541,0.00009648499,0.00002453316,0.00021791349,0.008901785,0.000033276214,0.00074297725],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999148,0.00029406018,0.0001234522,0.0002052215,0.00013147936,0.00009782894],"domain_scores_gemma":[0.9972801,0.00025930704,0.0010158038,0.00041855001,0.00061907666,0.00040720872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023769464,0.0005151176,0.0006968158,0.0015132964,0.000679027,0.0010453191,0.000724007,0.0005300506,0.001766834],"category_scores_gemma":[0.0060214354,0.00044244953,0.0008321112,0.0011644107,0.00038817598,0.00036248897,0.003182311,0.0005879822,0.00036397277],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011588949,0.00007631313,0.98258185,0.0001487824,0.0011112664,0.00042331062,0.00079638505,0.00023124619,0.0015176542,0.00017849615,0.0023943933,0.009381321],"study_design_scores_gemma":[0.000073989744,0.00008931508,0.9967507,0.00004967408,0.00025241982,0.0010371531,0.00027332368,0.00022281578,0.00017858154,0.00017329477,0.0008823115,0.000016552272],"about_ca_topic_score_codex":0.010684147,"about_ca_topic_score_gemma":0.01279126,"teacher_disagreement_score":0.010684147,"about_ca_system_score_codex":0.0005464655,"about_ca_system_score_gemma":0.0007564526,"threshold_uncertainty_score":0.02124387},"labels":[],"label_agreement":null},{"id":"W4415523828","doi":"10.1093/braincomms/fcaf420","title":"Thalamus involvement in genetic frontotemporal dementia assessed using structural and diffusion MRI: a GENFI study","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Health Sciences Centre; Occupational Cancer Research Centre; Montreal Neurological Institute and Hospital; University of Toronto; Western University; Douglas Mental Health University Institute; Université Laval","funders":"National Institute of Mental Health; NIHR Cambridge Biomedical Research Centre; Instituto de Salud Carlos III; Canadian Institutes of Health Research; National Institutes of Health; Alzheimer Nederland; Medical Research Council; Department of Health and Social Care; Medical Research Council Canada; Alzheimer’s Research UK; Weston Brain Institute; ZonMw; Wellcome Trust; University College London; Stichting Dioraphte; National Institute of Neurological Disorders and Stroke; University of Cambridge; Bundesministerium für Bildung und Forschung; National Institute on Aging; National Institute for Health and Care Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministero della Salute; Alzheimer's Society; Deutsche Forschungsgemeinschaft; Brain Research UK; Nvidia; Ontario Brain Institute; UK Dementia Research Institute; Vetenskapsrådet; Alzheimer's Association","keywords":"Frontotemporal dementia; Thalamus; Mutation; Diffusion MRI; Dementia; Pons; Effective diffusion coefficient","score_opus":0.11341533745719364,"score_gpt":0.42152545146379233,"score_spread":0.3081101140065987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415523828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99954283,0.0000742239,0.0000458516,0.000009894056,0.000001647615,0.0000061603146,0.000103339116,0.0000017967726,0.00021428663],"genre_scores_gemma":[0.9994869,0.000042637163,0.000090992326,0.000013157922,0.000005845646,0.000007073522,0.00024325277,0.0000023847458,0.00010776492],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997174,0.00007175117,0.000023941784,0.00009346317,0.000058296526,0.000035101573],"domain_scores_gemma":[0.999326,0.00016743843,0.00024918767,0.00008351225,0.0000743533,0.00009948129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007222404,0.0007003045,0.00031640826,0.0010436539,0.00042215703,0.00058333325,0.00043554837,0.0006364626,0.0014602733],"category_scores_gemma":[0.0016794973,0.000305602,0.00049865874,0.0005915034,0.0006312203,0.00044304886,0.00051973294,0.00037243063,0.00021905992],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009171773,0.00012580855,0.9918349,0.000023044919,0.00023650467,0.0012415623,0.0005299707,0.00008027895,0.002958727,0.00005987735,0.000103913546,0.0018883024],"study_design_scores_gemma":[0.000017096982,0.00022318913,0.99799144,0.0000042658935,0.000067017485,0.0012310127,0.00014467842,0.0001017244,0.00010354404,0.000028092942,0.00008401485,0.000004010464],"about_ca_topic_score_codex":0.008258867,"about_ca_topic_score_gemma":0.008847877,"teacher_disagreement_score":0.008258867,"about_ca_system_score_codex":0.0005142669,"about_ca_system_score_gemma":0.00024953045,"threshold_uncertainty_score":0.016421616},"labels":[],"label_agreement":null},{"id":"W4415531709","doi":"10.1016/j.drugalcdep.2025.112948","title":"Abnormal white matter microstructure in tobacco use disorder: A machine learning study based on whole-brain skeletonized DTI data","year":2025,"lang":"en","type":"article","venue":"Drug and Alcohol Dependence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; Canadian Anesthesiologists' Society","keywords":"Discriminative model; Nicotine; Multivariate statistics; White matter; Diffusion MRI; Pattern recognition (psychology)","score_opus":0.040477120492502315,"score_gpt":0.34411179275469095,"score_spread":0.30363467226218865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415531709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9990049,0.000059664733,0.0006809015,0.00002216637,0.0000021463688,0.0000057148795,0.00012048378,0.000009182936,0.0000949154],"genre_scores_gemma":[0.99864846,0.00007642151,0.0009217785,0.000007976886,0.000006595134,0.000003460106,0.00022460119,0.000007099622,0.00010353743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99990845,0.000028837698,0.000010735979,0.000025776048,0.000016345219,0.000009922608],"domain_scores_gemma":[0.99922943,0.00031269703,0.00017434465,0.00011605685,0.0000998075,0.000067568944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006699625,0.00021719106,0.0002325695,0.0008681464,0.0002863562,0.0004355664,0.0002169518,0.00028402035,0.0007035345],"category_scores_gemma":[0.0021246164,0.00014673122,0.00028330286,0.0007355091,0.000339322,0.0003711115,0.0002013212,0.00029273162,0.00013317291],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020439595,0.00048808378,0.8971733,0.00007523506,0.0003959873,0.0008737213,0.0005095324,0.0036221202,0.05044417,0.0003710754,0.00045987093,0.043542914],"study_design_scores_gemma":[0.000015059481,0.00017285593,0.97619957,0.000007472872,0.00009306764,0.0008547076,0.00011912742,0.01934647,0.002688044,0.0002877688,0.00020401039,0.000011794176],"about_ca_topic_score_codex":0.007034468,"about_ca_topic_score_gemma":0.0097211795,"teacher_disagreement_score":0.007034468,"about_ca_system_score_codex":0.0002103491,"about_ca_system_score_gemma":0.00028519935,"threshold_uncertainty_score":0.013987064},"labels":[],"label_agreement":null},{"id":"W4415595897","doi":"10.1073/pnas.2502674122","title":"Quantitative MRI of the hippocampus reveals microstructural trajectories of aging and Alzheimer’s disease pathology","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Douglas Mental Health University Institute; McGill University; McGill Genome Centre; Montreal Neurological Institute and Hospital","funders":"National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Canada Research Chairs; McGill University; National Institutes of Health; Alzheimer's Association","keywords":"Hippocampal formation; Hippocampus; Pathological; Disease; Ageing; Brain aging; Degeneration (medical); Dementia","score_opus":0.07504404563849823,"score_gpt":0.3938925772449612,"score_spread":0.318848531606463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415595897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99865615,0.00014525786,0.00097161514,0.000012913976,0.0000010990633,0.000003015599,0.000075015894,0.000010420384,0.00012458059],"genre_scores_gemma":[0.99921095,0.00004148751,0.0006189233,0.0000062747135,0.0000019053535,0.0000022136367,0.000053575277,0.0000027850565,0.00006176882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999163,0.00002068073,0.000008276043,0.000026959746,0.000017116517,0.000010589938],"domain_scores_gemma":[0.999647,0.00007167561,0.00014992587,0.00005620081,0.00004838888,0.000026816113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045241072,0.00016803828,0.0001330375,0.00050889887,0.00009330497,0.00022749994,0.000109756555,0.00015306025,0.00033775976],"category_scores_gemma":[0.0011689173,0.00012658534,0.00009475727,0.000250234,0.00023815516,0.000242592,0.00020441176,0.00012057188,0.000056432993],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074649986,0.00006285835,0.8038113,0.000089363166,0.00035935958,0.00034255392,0.0009821614,0.0017637092,0.16061781,0.00042070283,0.00032445719,0.030479176],"study_design_scores_gemma":[0.0000037394775,0.000082822866,0.996247,0.000002865481,0.000018614212,0.00032857762,0.00007440255,0.0009330453,0.0019966688,0.00020495201,0.0001017131,0.000005630053],"about_ca_topic_score_codex":0.0022939818,"about_ca_topic_score_gemma":0.0035673887,"teacher_disagreement_score":0.0022939818,"about_ca_system_score_codex":0.00013908022,"about_ca_system_score_gemma":0.00009814833,"threshold_uncertainty_score":0.004561305},"labels":[],"label_agreement":null},{"id":"W4415958339","doi":"10.1038/s41467-025-64788-y","title":"Brain dissection photogrammetry: a tool for studying human white matter connections integrating ex vivo and in vivo multimodal datasets","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Provincia Autonoma di Trento; Centre National de la Recherche Scientifique; Université de Sherbrooke","keywords":"White matter; Tractography; Neuroimaging; Ex vivo; Human brain; Dissection (medical)","score_opus":0.043548607285335134,"score_gpt":0.40693170972642173,"score_spread":0.3633831024410866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415958339","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008685278,0.00033935427,0.95239735,0.00033056608,0.00008245015,0.00025160232,0.009491363,0.022482052,0.0059399926],"genre_scores_gemma":[0.0920606,0.00095168647,0.8828539,0.00023971483,0.00005794619,0.0009481358,0.009804928,0.009452327,0.0036308505],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99940073,0.00010960326,0.00004953831,0.00015205881,0.00024775794,0.00004028489],"domain_scores_gemma":[0.9986707,0.00053917227,0.00014401771,0.00041197342,0.0001423662,0.00009175684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012528683,0.0009874409,0.0005393634,0.0031442181,0.0006267862,0.0019791948,0.0011134895,0.001019873,0.018779904],"category_scores_gemma":[0.003840967,0.0009781622,0.00086493324,0.0017667246,0.00087926135,0.0018221645,0.004500129,0.0013315693,0.0051854774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057802926,0.00014497041,0.0074083693,0.0024380612,0.00030426527,0.0012281236,0.0035737075,0.032170694,0.15523142,0.045456134,0.10854286,0.6429234],"study_design_scores_gemma":[0.00019784975,0.00024981052,0.034890402,0.001009948,0.00019661576,0.0055347467,0.0020444074,0.18516189,0.13242029,0.13836895,0.49932536,0.000599732],"about_ca_topic_score_codex":0.0016841504,"about_ca_topic_score_gemma":0.005219408,"teacher_disagreement_score":0.018779904,"about_ca_system_score_codex":0.00044728452,"about_ca_system_score_gemma":0.0013468285,"threshold_uncertainty_score":0.062825024},"labels":[],"label_agreement":null},{"id":"W4416002342","doi":"10.22541/au.176253018.86072169/v1","title":"Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Canadian Institutes of Health Research; National Health and Medical Research Council; National Natural Science Foundation of China","keywords":"Undersampling; Acceleration; Sampling (signal processing); Diffusion; Iterative reconstruction; Pattern recognition (psychology); Signal reconstruction","score_opus":0.10011544123521207,"score_gpt":0.350063010551624,"score_spread":0.2499475693164119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416002342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013613205,0.00019949769,0.9848691,0.00013338943,0.000015735843,0.000016089998,0.000050216866,0.00053820683,0.0005643978],"genre_scores_gemma":[0.24545127,0.0007403673,0.75000924,0.00017404075,0.000041362593,0.0000742275,0.00046554403,0.0002944358,0.0027494999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997099,0.00006905333,0.000015336045,0.0000719549,0.00010624514,0.000027426211],"domain_scores_gemma":[0.99947125,0.00018883479,0.00008486034,0.000113409464,0.000101330486,0.000040400617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009873549,0.0008943834,0.0007026969,0.00056362967,0.00023802121,0.00071375247,0.00074735924,0.0008233904,0.0011756383],"category_scores_gemma":[0.0023161417,0.0006409058,0.0008266739,0.000489626,0.00052541407,0.0011535937,0.0010736975,0.0014639776,0.00060358224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035461507,0.00009600039,0.0018968846,0.00044787553,0.0001677961,0.00047441383,0.00030931403,0.5560159,0.102836214,0.028779706,0.004415203,0.304206],"study_design_scores_gemma":[0.000008486113,0.000026625628,0.00015916115,0.00000931405,0.000011794088,0.00014223828,0.0000118233,0.98606354,0.008919068,0.003470506,0.0011632558,0.000014170031],"about_ca_topic_score_codex":0.0030302485,"about_ca_topic_score_gemma":0.0045671933,"teacher_disagreement_score":0.0030302485,"about_ca_system_score_codex":0.00033146248,"about_ca_system_score_gemma":0.0011452612,"threshold_uncertainty_score":0.006025195},"labels":[],"label_agreement":null},{"id":"W4416079897","doi":"10.1227/ons.0000000000001848","title":"Revisiting the Telovelar Approach for Lesions of the Mesial Part of the Cerebellar Peduncles by Using the Cerebellar Functional Networks to Guide Surgical Practice","year":2025,"lang":"en","type":"article","venue":"Operative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"White matter; Dissection (medical); Cerebellum; Brain anatomy; Clinical neurology; Microsurgery","score_opus":0.07352704740947871,"score_gpt":0.3731775910478172,"score_spread":0.29965054363833854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416079897","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81219804,0.003770312,0.17481221,0.0012741544,0.00013304067,0.00021519471,0.00008910513,0.00039877597,0.0071091536],"genre_scores_gemma":[0.80883646,0.002767484,0.18662472,0.00026234653,0.000085717234,0.000070893,0.000077189565,0.0000681189,0.0012070357],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99987555,0.000023985498,0.000018888495,0.000029445633,0.000031574473,0.000020553347],"domain_scores_gemma":[0.9997008,0.000070465154,0.00008827781,0.00005467354,0.00005030503,0.00003545908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061903783,0.00041528075,0.00014134975,0.00089482026,0.00034511153,0.0010499911,0.00042466412,0.00048053075,0.001069697],"category_scores_gemma":[0.00092007115,0.00015766326,0.00026184157,0.000246192,0.00077901,0.0013446203,0.00047828403,0.00060927594,0.00040728998],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003589567,0.00020508714,0.07376281,0.0007532775,0.00013097306,0.02605855,0.0021905547,0.011024865,0.39489892,0.006788219,0.0016393217,0.4821885],"study_design_scores_gemma":[0.00020582817,0.0043280483,0.33789465,0.0017363342,0.0006825099,0.2701664,0.0074429386,0.069398776,0.18689062,0.025667652,0.095194615,0.00039148584],"about_ca_topic_score_codex":0.001237638,"about_ca_topic_score_gemma":0.005464022,"teacher_disagreement_score":0.001237638,"about_ca_system_score_codex":0.00042060707,"about_ca_system_score_gemma":0.0013791418,"threshold_uncertainty_score":0.003578484},"labels":[],"label_agreement":null},{"id":"W4416140053","doi":"10.1093/neuonc/noaf201.1317","title":"NCOG-50. Correlation of tract-based diffusion metrics with visuospatial function following glioma surgery","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; White matter; Arcuate fasciculus; Fractional anisotropy; Superior longitudinal fasciculus; Tractography; Fasciculus; Inferior longitudinal fasciculus; Human Connectome Project; Glioma","score_opus":0.03657880437120672,"score_gpt":0.3415430757264585,"score_spread":0.3049642713552518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416140053","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99774396,0.00013681296,0.00011852015,0.000039134222,0.0000060516763,0.000010901445,0.00061541767,0.000017285538,0.0013119404],"genre_scores_gemma":[0.99888164,0.000036019934,0.00007611608,0.0000071410627,0.000001804929,0.000008121186,0.0006042366,0.00000344225,0.0003814496],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999143,0.000010053763,0.000013265932,0.000014960261,0.000024093793,0.000023342996],"domain_scores_gemma":[0.99879164,0.00014191223,0.0005376324,0.00004918172,0.00022633627,0.00025339396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018946326,0.00011642648,0.00012537038,0.0004384916,0.00015767918,0.00029598165,0.00015584275,0.00024603854,0.0032560301],"category_scores_gemma":[0.0020724551,0.00005181902,0.00010127208,0.00040977917,0.00020018937,0.00023534754,0.0002642663,0.00022948397,0.0005335258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043416303,0.000036692527,0.9866817,0.000021498214,0.000030814866,0.0001807341,0.000053172582,0.0002497794,0.0031259323,0.000028886665,0.0004797088,0.008676954],"study_design_scores_gemma":[0.0000025534844,0.00012575879,0.99868494,0.0000039982906,0.0000055071428,0.0002153562,0.000046266017,0.00021912025,0.0004283819,0.000024275216,0.00024146482,0.0000023725627],"about_ca_topic_score_codex":0.006725728,"about_ca_topic_score_gemma":0.011121463,"teacher_disagreement_score":0.006725728,"about_ca_system_score_codex":0.0005758694,"about_ca_system_score_gemma":0.00035489045,"threshold_uncertainty_score":0.0133731365},"labels":[],"label_agreement":null},{"id":"W4416183376","doi":"10.1109/mipr67560.2025.00037","title":"Structural Mri Synthesis for Alzheimer's Disease Via Conditional Diffusion on Anatomical Masks","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Becton Dickinson (Canada)","funders":"","keywords":"Segmentation; Synthetic data; Generative model; Pattern recognition (psychology); Diffusion MRI; Process (computing); Fidelity; Neuroimaging","score_opus":0.05282526902645439,"score_gpt":0.37558248393275095,"score_spread":0.32275721490629655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416183376","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045997836,0.0006734088,0.94813174,0.00049766054,0.00006776178,0.00006182025,0.0005017305,0.0022835198,0.0017845863],"genre_scores_gemma":[0.5484473,0.00094050256,0.44404027,0.00045278427,0.00008675812,0.00014104263,0.001951882,0.00064951484,0.0032900008],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997918,0.000056264777,0.000013092243,0.000060541155,0.000059112834,0.000019197552],"domain_scores_gemma":[0.9991979,0.00045246098,0.000094565694,0.00011974933,0.00009396876,0.0000413862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090308493,0.00072559324,0.00042909966,0.0007033173,0.00020709433,0.0007661829,0.00060075906,0.00078813406,0.0013602361],"category_scores_gemma":[0.0031444062,0.00043670472,0.00094851054,0.00040171648,0.00047564233,0.0005816619,0.0008112592,0.00094946224,0.00059425645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025702233,0.000058666737,0.0023026539,0.00026148785,0.00010938909,0.00036609898,0.00018865067,0.7685549,0.046230145,0.012585799,0.004566169,0.16451901],"study_design_scores_gemma":[0.000010743793,0.000030734445,0.0002840506,0.000013130795,0.000015961617,0.0002229717,0.000009965975,0.9822427,0.010298576,0.005314738,0.0015434322,0.000012990646],"about_ca_topic_score_codex":0.0030543937,"about_ca_topic_score_gemma":0.0040710676,"teacher_disagreement_score":0.0030543937,"about_ca_system_score_codex":0.0005213778,"about_ca_system_score_gemma":0.0008086066,"threshold_uncertainty_score":0.006073177},"labels":[],"label_agreement":null},{"id":"W4416234271","doi":"10.3389/fonc.2025.1605190","title":"Wallerian degeneration of the corticospinal tract following multimodal high-grade glioma treatment: a case series and recommendations for radiotherapy planning","year":2025,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Corticospinal tract; Radiation therapy; Wallerian degeneration; Pyramidal tracts; Complication; Glioma; Etiology; Astrocytoma","score_opus":0.04877081833163789,"score_gpt":0.3965515109962655,"score_spread":0.34778069266462763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416234271","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636471,0.016135342,0.008279372,0.0037898966,0.00027966045,0.00041211172,0.00021359348,0.00017280706,0.007070122],"genre_scores_gemma":[0.9867302,0.0074371137,0.003331048,0.0006780147,0.00085011206,0.00011333433,0.00022697203,0.000021848418,0.0006114258],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.99929225,0.00015396399,0.00017897354,0.00011978143,0.00009352415,0.00016150282],"domain_scores_gemma":[0.9984133,0.0004503161,0.0006402247,0.00012413572,0.00016519128,0.00020675253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077281357,0.0011479285,0.0005145248,0.0021358521,0.001284132,0.0013767751,0.0010964104,0.0032544027,0.001841588],"category_scores_gemma":[0.004025085,0.0004392704,0.0006969433,0.0013023069,0.0011940844,0.002208603,0.0007561121,0.0010063023,0.0009895033],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006478106,0.00009798519,0.18842305,0.00021024204,0.000024772078,0.78734535,0.0005637419,0.00044131873,0.0013884063,0.00034084733,0.0016786265,0.019420896],"study_design_scores_gemma":[0.000011730168,0.00009323648,0.035475582,0.00019577221,0.000040826893,0.9593852,0.0011802285,0.00072845037,0.0005867548,0.000497951,0.0017610018,0.000043347372],"about_ca_topic_score_codex":0.0020147017,"about_ca_topic_score_gemma":0.0022141133,"teacher_disagreement_score":0.0032544027,"about_ca_system_score_codex":0.0010015764,"about_ca_system_score_gemma":0.0011413655,"threshold_uncertainty_score":0.0072669983},"labels":[],"label_agreement":null},{"id":"W4416257142","doi":"10.1002/hbm.70408","title":"Utility of Harmonisation for Fixel‐Based Metrics in Travelling Subjects and Alzheimer's Disease Data","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Japan Agency for Medical Research and Development; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Metric (unit); Comparability; Scanner; White matter; Subject matter","score_opus":0.3215893071424486,"score_gpt":0.4295181423094712,"score_spread":0.10792883516702262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416257142","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6151431,0.0017309291,0.35637367,0.00078976364,0.00041819908,0.001762985,0.0077269473,0.0113269845,0.004727523],"genre_scores_gemma":[0.7155976,0.00023747342,0.26895675,0.00021449965,0.000095059455,0.001350151,0.010813044,0.0017015542,0.00103392],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98792493,0.006624408,0.00107596,0.0028618409,0.0012387624,0.0002740833],"domain_scores_gemma":[0.98069775,0.0075348676,0.00223794,0.00612813,0.003138003,0.0002632846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02412028,0.00090483075,0.0009139712,0.0023835327,0.0010222207,0.0021774897,0.0014278446,0.00087175646,0.0015886372],"category_scores_gemma":[0.06828556,0.00033676845,0.0011846845,0.0025690394,0.0014316018,0.0014705125,0.0031401778,0.0008340903,0.0008657446],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005123591,0.0006104114,0.13067637,0.0016114109,0.003744944,0.0007353182,0.007215516,0.05323217,0.040831335,0.009101494,0.030834261,0.71628314],"study_design_scores_gemma":[0.0010752531,0.0036681904,0.40344214,0.00071541965,0.0017960537,0.0023906755,0.0060922178,0.36971527,0.057593517,0.037311688,0.11554217,0.00065734045],"about_ca_topic_score_codex":0.0036426417,"about_ca_topic_score_gemma":0.0041609043,"teacher_disagreement_score":0.02412028,"about_ca_system_score_codex":0.0006604786,"about_ca_system_score_gemma":0.0011181623,"threshold_uncertainty_score":0.12756181},"labels":[],"label_agreement":null},{"id":"W4416291370","doi":"10.1038/s42003-025-08954-4","title":"Early but discontinued exposure to a language exerts lasting effects on white matter architecture in the brain","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Centre for Research on Brain, Language and Music","keywords":"Mandarin Chinese; Arcuate fasciculus; White matter; Cognition; Neuroscience of multilingualism; Lateralization of brain function; Expressive Suppression; Neuroimaging","score_opus":0.028771641143775076,"score_gpt":0.36678769723325383,"score_spread":0.33801605608947877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416291370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99980253,0.000035460118,0.00002339137,0.000007195618,5.931071e-7,0.0000012177117,0.000011232909,9.014794e-7,0.0001174555],"genre_scores_gemma":[0.999521,0.00005218376,0.00009112221,0.000010356402,0.0000016671704,0.000007142991,0.000034661112,0.000001389795,0.00028049876],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998553,0.000028024397,0.000007681724,0.000044076372,0.000023422452,0.000041525345],"domain_scores_gemma":[0.9995987,0.00006643804,0.00014727714,0.000028827446,0.000038921564,0.00011983553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022821515,0.00021834718,0.00016415681,0.0003077548,0.0002695763,0.00039565982,0.00012176913,0.00024233147,0.0010837065],"category_scores_gemma":[0.00075571093,0.00009220124,0.000109099376,0.00012719225,0.0004839995,0.00023088505,0.000353994,0.00021788507,0.000094121744],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015053252,0.00045807316,0.6471075,0.00009082889,0.00007903687,0.0019586673,0.0053304303,0.00006911393,0.31827092,0.00022869097,0.000119171855,0.02478215],"study_design_scores_gemma":[0.0000023964312,0.00021704158,0.9960752,0.0000037001614,0.0000063819325,0.0001883332,0.00068292004,0.000015877959,0.0026772409,0.000038645438,0.000089422996,0.0000028130612],"about_ca_topic_score_codex":0.002556395,"about_ca_topic_score_gemma":0.0066806767,"teacher_disagreement_score":0.002556395,"about_ca_system_score_codex":0.00024993715,"about_ca_system_score_gemma":0.00024920734,"threshold_uncertainty_score":0.0050830245},"labels":[],"label_agreement":null},{"id":"W4416388641","doi":"10.1038/s42003-025-08981-1","title":"Microstructural maturation of the adult mouse brain","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Canada","keywords":"Kurtosis; Fractional anisotropy; Diffusion MRI; Oligodendrocyte; White matter; Myelin; Diffusion","score_opus":0.05152972534530199,"score_gpt":0.3994223674831016,"score_spread":0.34789264213779963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416388641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9341322,0.0063830162,0.04862761,0.0003654081,0.00015639457,0.00015285432,0.0046391883,0.0009919981,0.004551344],"genre_scores_gemma":[0.9364271,0.005132677,0.04055509,0.0002847207,0.00004782705,0.0004392816,0.0038973016,0.00044661033,0.012769428],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997607,0.0000210245,0.000027077494,0.00008896786,0.00006895174,0.000033226257],"domain_scores_gemma":[0.9994998,0.00004586887,0.00018392924,0.000048567086,0.00012451898,0.00009723552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000521302,0.00058849325,0.00022956492,0.0015975077,0.0002572884,0.00052710803,0.00041074204,0.00054361473,0.0018362096],"category_scores_gemma":[0.000333254,0.00037309428,0.00039829774,0.0002883941,0.00040440075,0.00056606985,0.00041883162,0.0010295665,0.00059472193],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011744652,0.000026496642,0.00059291476,0.00006811442,0.000016800084,0.00010434967,0.00006903659,0.00012052627,0.9951687,0.00031313006,0.00010934,0.0032931983],"study_design_scores_gemma":[0.00002312769,0.00065541454,0.027948169,0.000081215134,0.00011916605,0.0015382417,0.00013122086,0.0017213228,0.95828176,0.0007097384,0.00875947,0.000031177588],"about_ca_topic_score_codex":0.0009678283,"about_ca_topic_score_gemma":0.0013381961,"teacher_disagreement_score":0.0018362096,"about_ca_system_score_codex":0.00029805393,"about_ca_system_score_gemma":0.0003004387,"threshold_uncertainty_score":0.0061427355},"labels":[],"label_agreement":null},{"id":"W4416431621","doi":"10.1615/critrevbiomedeng.2025059839","title":"Diffusion Tensor Imaging for Brain Injury Assessment: Methodological Foundations and Clinical Insights","year":2025,"lang":"en","type":"article","venue":"Critical Reviews in Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McMaster University Medical Centre; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Diffusion MRI; Neuroimaging; Interpretability; Traumatic brain injury; White matter; Functional neuroimaging","score_opus":0.20445534852867076,"score_gpt":0.5546723545852813,"score_spread":0.35021700605661055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416431621","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018951034,0.8747703,0.10633408,0.01224111,0.000851551,0.00012285188,0.00021200844,0.00013229751,0.00344072],"genre_scores_gemma":[0.028251415,0.878392,0.08692715,0.0019883486,0.0030231546,0.00033131763,0.00021986231,0.00009931523,0.00076753023],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965448,0.0016750672,0.00041680658,0.00047334196,0.0007830018,0.00010693503],"domain_scores_gemma":[0.9835528,0.012150051,0.0010969848,0.00069114676,0.0022186157,0.00029043457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015395707,0.0016222832,0.0022837047,0.0044480376,0.000534295,0.0040913615,0.0016852042,0.0028169856,0.001438847],"category_scores_gemma":[0.02488933,0.00078060175,0.0010460842,0.0031521597,0.0046487623,0.003390684,0.0020087385,0.0049393605,0.0009937836],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012750621,0.000091014714,0.0050514764,0.0122240605,0.00058698346,0.00046213905,0.0006034843,0.0056981444,0.0056439424,0.13111855,0.018568844,0.81982386],"study_design_scores_gemma":[0.00008918567,0.00070631306,0.014072398,0.022783859,0.0008206322,0.007030494,0.00072197453,0.029247284,0.009219628,0.48030695,0.4345066,0.0004947269],"about_ca_topic_score_codex":0.0029196257,"about_ca_topic_score_gemma":0.0031140207,"teacher_disagreement_score":0.015395707,"about_ca_system_score_codex":0.0017720187,"about_ca_system_score_gemma":0.0037642743,"threshold_uncertainty_score":0.0814212},"labels":[],"label_agreement":null},{"id":"W4416510209","doi":"10.1162/imag.a.1035","title":"Advanced diffusion imaging in grey matter reflects individual differences in cognitive ability in older adults","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; DoD Alzheimer's Disease Neuroimaging Initiative; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Working memory; Cognition; Diffusion MRI; Elementary cognitive task; Task (project management); Lateralization of brain function; Diffusion","score_opus":0.03717804297074438,"score_gpt":0.3725359190231563,"score_spread":0.3353578760524119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416510209","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986475,0.00025674902,0.00038943667,0.000030755444,0.000005464467,0.000009278525,0.00019574823,0.0000098915125,0.00045506124],"genre_scores_gemma":[0.9989666,0.00009810947,0.00048444315,0.000019369132,0.000006606578,0.000008273934,0.00015920015,0.0000022500053,0.0002551488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998481,0.000021439328,0.00003105998,0.0000527465,0.000030156605,0.000016427006],"domain_scores_gemma":[0.9993362,0.0001226712,0.0002934174,0.00007818061,0.00010344879,0.00006609751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070738443,0.00039576925,0.00031425516,0.0008401293,0.0002386634,0.0004636399,0.00016092177,0.0005541085,0.0011479334],"category_scores_gemma":[0.0022713093,0.00014838007,0.00024992618,0.00038736183,0.0002382269,0.0006124548,0.0003652427,0.00031651507,0.00026898374],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000348053,0.00006587086,0.97962075,0.000045606314,0.00014539952,0.00018822972,0.00044461945,0.00020585618,0.009672132,0.00009342248,0.00017298233,0.008997206],"study_design_scores_gemma":[0.0000033801693,0.0001323937,0.99832875,0.0000060143498,0.00002926352,0.00026696484,0.000112223475,0.0003324774,0.0005529726,0.00012816481,0.00010363209,0.0000036788026],"about_ca_topic_score_codex":0.0018254442,"about_ca_topic_score_gemma":0.0042154077,"teacher_disagreement_score":0.0018254442,"about_ca_system_score_codex":0.0001225302,"about_ca_system_score_gemma":0.00010474955,"threshold_uncertainty_score":0.003840208},"labels":[],"label_agreement":null},{"id":"W4416595726","doi":"10.1038/s41598-025-25400-x","title":"Challenges and best practices when using ComBAT to harmonize diffusion MRI data","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; Q & T Research; Université de Sherbrooke","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Mitacs; Eisai; Québec Consortium for Drug Discovery; University of Southern California; Université de Sherbrooke; Northern California Institute for Research and Education; BioClinica; Natural Sciences and Engineering Research Council of Canada; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Best practice; Consistency (knowledge bases); Normative; Multiplicative function; Set (abstract data type); Population","score_opus":0.3568150277456852,"score_gpt":0.4593066519482567,"score_spread":0.10249162420257152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416595726","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010943852,0.0041929698,0.93168855,0.03763771,0.0011106397,0.0016821079,0.00073269196,0.0029017385,0.009109708],"genre_scores_gemma":[0.049571723,0.0015578261,0.94067335,0.003611875,0.00041917345,0.0018955659,0.0005602387,0.0011279904,0.00058218837],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.7788318,0.17674997,0.012775987,0.010168387,0.01979692,0.0016768727],"domain_scores_gemma":[0.5082026,0.32106012,0.014091068,0.103175536,0.049677696,0.0037929844],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.29979393,0.0019905563,0.0025113106,0.0039014437,0.0031534545,0.015936283,0.009658716,0.004512439,0.0052549015],"category_scores_gemma":[0.5595648,0.0017175123,0.0024533852,0.0044789515,0.008401692,0.015279513,0.011960315,0.007925803,0.0052210344],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011252436,0.00054845196,0.018023353,0.003586577,0.0012918144,0.00062949327,0.012905892,0.026784552,0.0073995735,0.22797807,0.07095659,0.6287704],"study_design_scores_gemma":[0.0005939643,0.0007745392,0.007661017,0.006629703,0.00034548892,0.0013327511,0.008279743,0.07862971,0.01508125,0.6600612,0.21986358,0.0007470611],"about_ca_topic_score_codex":0.0044489796,"about_ca_topic_score_gemma":0.00484446,"teacher_disagreement_score":0.29979393,"about_ca_system_score_codex":0.0021565312,"about_ca_system_score_gemma":0.008982492,"threshold_uncertainty_score":0.8634788},"labels":[],"label_agreement":null},{"id":"W4416610599","doi":"10.1002/hbm.70417","title":"In Vivo Quantification of White Matter Pathways in the Human Hippocampus","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; White matter; Hippocampus; In vivo; Cognition; Human brain","score_opus":0.08480388152076788,"score_gpt":0.3596885992740911,"score_spread":0.2748847177533232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416610599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81204534,0.001876538,0.18224207,0.000110856214,0.000025153922,0.00010780548,0.0012408578,0.00040008474,0.001951301],"genre_scores_gemma":[0.9008481,0.0012138401,0.095246196,0.000090119676,0.00001284947,0.00015288613,0.00079638,0.000116955765,0.0015227173],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999254,0.000015311787,0.0000055665228,0.000031935764,0.000015684644,0.0000060577627],"domain_scores_gemma":[0.99990654,0.000029879102,0.000018270983,0.000016550735,0.000019649216,0.000009135957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037941386,0.00021060997,0.00017090814,0.0004969948,0.00014402003,0.00034170182,0.00016774677,0.00030755156,0.0013484258],"category_scores_gemma":[0.0006234361,0.00023356815,0.00012316933,0.00027429275,0.00018324179,0.0003159398,0.00023415704,0.00019530153,0.00025213577],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057564024,0.00007735401,0.010220848,0.00027539145,0.00018140068,0.00024961465,0.00039025344,0.0064784894,0.9198501,0.0012160572,0.001042345,0.05944245],"study_design_scores_gemma":[0.0001994336,0.00153463,0.24188992,0.00014390016,0.00061399944,0.0071277884,0.0007195276,0.122358076,0.5951017,0.011255827,0.01893273,0.0001225215],"about_ca_topic_score_codex":0.0016597512,"about_ca_topic_score_gemma":0.002588473,"teacher_disagreement_score":0.0016597512,"about_ca_system_score_codex":0.00010177152,"about_ca_system_score_gemma":0.00023380856,"threshold_uncertainty_score":0.004510939},"labels":[],"label_agreement":null},{"id":"W4416697937","doi":"10.1111/epi.70038","title":"Mapping white matter tracts with <scp>SEEG</scp> electrodes","year":2025,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Epilepsy Research UK","keywords":"Stereoelectroencephalography; White matter; Tractography; Electrode; Deep brain stimulation; Stimulation; Radiomics","score_opus":0.024930474713962335,"score_gpt":0.3077977485338836,"score_spread":0.28286727381992127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416697937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99027973,0.0002942853,0.00790725,0.000033908793,0.000004202726,0.00003359496,0.00039611256,0.0000599248,0.0009910009],"genre_scores_gemma":[0.9956671,0.0001381179,0.0035127334,0.000015921905,0.0000068574286,0.000023546068,0.00032373733,0.000012915317,0.00029894357],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99986875,0.000019644353,0.000015551765,0.000041156407,0.000036602683,0.000018296692],"domain_scores_gemma":[0.99960095,0.0000959043,0.00018070558,0.000043245887,0.000046779,0.000032434342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023718843,0.00029551587,0.00017199136,0.00058741926,0.00016784371,0.00031462658,0.00013391672,0.0002231794,0.0014962102],"category_scores_gemma":[0.00093803916,0.00009156338,0.00016428788,0.000494319,0.0003397334,0.00029720634,0.00023791479,0.00010796778,0.00038245137],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011588108,0.000060193262,0.77496654,0.00030713776,0.00016621922,0.007912894,0.00037896645,0.002088917,0.11881994,0.00036934856,0.0008766262,0.09289445],"study_design_scores_gemma":[0.00004917114,0.0005805568,0.934524,0.00004945906,0.000073906755,0.02396269,0.00016863336,0.0032630234,0.035075616,0.00038781064,0.00185132,0.000013729544],"about_ca_topic_score_codex":0.0011498267,"about_ca_topic_score_gemma":0.002966457,"teacher_disagreement_score":0.0014962102,"about_ca_system_score_codex":0.0001724186,"about_ca_system_score_gemma":0.00032835003,"threshold_uncertainty_score":0.0050053},"labels":[],"label_agreement":null},{"id":"W4416842357","doi":"10.1186/s40478-025-02183-w","title":"MRI investigation of orientation-dependent changes in microstructure and function in a mouse model of mild traumatic brain injury","year":2025,"lang":"en","type":"article","venue":"Acta Neuropathologica Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Peer Reviewed Alzheimer’s Research Program; Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Traumatic brain injury; Diffusion MRI; Kurtosis; Neuroimaging; Magnetic resonance imaging; Thermal diffusivity; Rotation (mathematics)","score_opus":0.09943251725005171,"score_gpt":0.359532328680109,"score_spread":0.2600998114300573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416842357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9708345,0.0020506075,0.020395422,0.00056924415,0.0001422744,0.00017396882,0.0032175519,0.0006132398,0.0020031584],"genre_scores_gemma":[0.94778895,0.0037372068,0.031204471,0.0005102226,0.000059700407,0.0007723523,0.0037773957,0.00031420816,0.011835525],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99960667,0.000045249224,0.00004592236,0.00012574805,0.00009682514,0.000079643374],"domain_scores_gemma":[0.99933124,0.000044843815,0.0002552989,0.00007661231,0.0001299517,0.00016203581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070563616,0.0009668833,0.00060694886,0.001717943,0.00044501896,0.0006063201,0.00055726623,0.001140319,0.0015036395],"category_scores_gemma":[0.00035771058,0.00062073104,0.0006206547,0.0004942154,0.00068692485,0.0005523094,0.0004500918,0.0024664432,0.00064161693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025296645,0.00013717735,0.0007404607,0.00006952692,0.000026615953,0.0001077459,0.000060706567,0.00017728195,0.9969536,0.00019811912,0.00013060911,0.0011450743],"study_design_scores_gemma":[0.0001249421,0.0035907773,0.041192193,0.00009701702,0.00028845013,0.0017542274,0.00029912972,0.006864621,0.93830854,0.00072421535,0.006682843,0.00007291068],"about_ca_topic_score_codex":0.001995894,"about_ca_topic_score_gemma":0.003171734,"teacher_disagreement_score":0.001995894,"about_ca_system_score_codex":0.00054110674,"about_ca_system_score_gemma":0.00043525346,"threshold_uncertainty_score":0.005030215},"labels":[],"label_agreement":null},{"id":"W4417146313","doi":"10.3389/fpsyt.2025.1650055","title":"Cortical microstructural changes in schizophrenia spectrum disorders using quantitative T1 mapping","year":2025,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research","keywords":"Schizophrenia (object-oriented programming); Reliability (semiconductor); Schizophrenia spectrum; Neuroimaging; Brain mapping; Selection (genetic algorithm); Functional connectivity","score_opus":0.029352305162599533,"score_gpt":0.34511024494519527,"score_spread":0.31575793978259575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417146313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.972499,0.0034648424,0.020447163,0.0002381735,0.000017575996,0.0000937066,0.0008510244,0.00020841231,0.0021800792],"genre_scores_gemma":[0.9887579,0.00094370375,0.009646179,0.00003206575,0.000013022949,0.000046806468,0.00019347844,0.00002931125,0.00033758173],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998248,0.00006105461,0.000018688119,0.00003923413,0.000041388557,0.000014827317],"domain_scores_gemma":[0.9993672,0.0001639308,0.000289539,0.000051058592,0.00008669122,0.000041641266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010701795,0.0005422653,0.00018614925,0.0017501401,0.00016118468,0.0006614279,0.00026690378,0.00035203414,0.0016803682],"category_scores_gemma":[0.0017451156,0.0001958324,0.00018271593,0.0004582048,0.00033142837,0.00043755898,0.00043324125,0.00020100646,0.00017578914],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038295728,0.000184902,0.32118335,0.0014439045,0.00081996934,0.0016428164,0.0013748596,0.0058243847,0.3848909,0.001525273,0.0016301556,0.27564994],"study_design_scores_gemma":[0.00009553726,0.0006478174,0.9160154,0.0003041976,0.00038040243,0.006402973,0.00067398435,0.022144994,0.044964943,0.0053646187,0.002901654,0.00010335638],"about_ca_topic_score_codex":0.002096143,"about_ca_topic_score_gemma":0.0029299967,"teacher_disagreement_score":0.002096143,"about_ca_system_score_codex":0.00030663953,"about_ca_system_score_gemma":0.00027777607,"threshold_uncertainty_score":0.005659759},"labels":[],"label_agreement":null},{"id":"W4417189574","doi":"10.1002/hbm.70414","title":"Psychotic‐Like Experiences and White Matter Microstructure: A Fixel‐Based Analysis Approach With Robust Replication Across Two Cohorts","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Centre Hospitalier Universitaire Sainte-Justine","funders":"Medical Research Council; H. Lundbeck A/S; Fédération pour la Recherche sur le Cerveau; Fondation pour la Recherche Médicale; Fondation de France; National Imaging Facility; Bundesministerium für Bildung und Forschung; National Natural Science Foundation of China; Centre of Excellence for Integrative Brain Function, Australian Research Council; Lundbeckfonden; Institut National de la Santé et de la Recherche Médicale; HORIZON EUROPE Framework Programme; Agence Nationale de la Recherche; Mission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives; UK Research and Innovation; Science Foundation Ireland; European Commission; Australian Government; Deutsche Forschungsgemeinschaft; National Institutes of Health; Fondation de l'Avenir pour la Recherche Médicale Appliquée","keywords":"White matter; Diffusion MRI; Neuroimaging; Replication (statistics); Tractography; Schizotypy; Diffusion imaging","score_opus":0.05083138182168458,"score_gpt":0.36338135314713954,"score_spread":0.312549971325455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417189574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94161576,0.00046057004,0.051106244,0.0002458895,0.00012507496,0.0010704076,0.0038514833,0.00036820027,0.0011564228],"genre_scores_gemma":[0.96301687,0.000074514865,0.029286826,0.00013781914,0.00002904371,0.003089385,0.0026545746,0.00029714787,0.0014137524],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9906942,0.0039084684,0.00043557087,0.0037601052,0.0007544105,0.0004472681],"domain_scores_gemma":[0.98019505,0.005083133,0.0022677353,0.009680974,0.002206221,0.00056683493],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023819229,0.0011692841,0.0012293701,0.0010923039,0.0025681697,0.0016521622,0.0016854368,0.0014120666,0.0036517528],"category_scores_gemma":[0.041929327,0.0007743207,0.0028387317,0.0010463792,0.0021088135,0.00094686233,0.0027322127,0.0018823041,0.0007073285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012414864,0.0011306892,0.76474464,0.0010504618,0.022627557,0.0025152138,0.012343617,0.0061118677,0.06444978,0.005860903,0.010727429,0.096022956],"study_design_scores_gemma":[0.0011531864,0.0032210357,0.95577425,0.0002259625,0.004791523,0.0016806534,0.0012215924,0.00806299,0.007639254,0.0051079094,0.010904275,0.00021738913],"about_ca_topic_score_codex":0.014323277,"about_ca_topic_score_gemma":0.025562268,"teacher_disagreement_score":0.023819229,"about_ca_system_score_codex":0.0010792187,"about_ca_system_score_gemma":0.0017502144,"threshold_uncertainty_score":0.12596959},"labels":[],"label_agreement":null},{"id":"W4417399411","doi":"10.1016/j.neuroimage.2025.121656","title":"Spatially regularized super-resolved constrained spherical deconvolution (SR2-CSD) of diffusion MRI data","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Social Fund; Ministerio de Ciencia, Innovación y Universidades","keywords":"Deconvolution; Spatial coherence; Prior probability; Tractography; Image resolution; Spherical harmonics; Diffusion MRI; Orientation (vector space); Coherence (philosophical gambling strategy)","score_opus":0.0675359183058252,"score_gpt":0.3609758912461194,"score_spread":0.2934399729402942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417399411","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043141674,0.0008437293,0.9508292,0.00032321172,0.00007026664,0.00010572431,0.0007897989,0.0026257138,0.0012706964],"genre_scores_gemma":[0.21702282,0.0010166473,0.7761093,0.00034318242,0.00004687083,0.00025511885,0.0024897088,0.0009795087,0.0017369702],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99916387,0.0001966004,0.00006568404,0.0001705906,0.00035457074,0.00004877752],"domain_scores_gemma":[0.9977963,0.00082667527,0.00029798917,0.00041558268,0.0005805561,0.00008296329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002386611,0.0010877294,0.000713197,0.0010618627,0.00039891672,0.00092170533,0.001027223,0.00086978055,0.0013391656],"category_scores_gemma":[0.008129852,0.00038691232,0.00081323914,0.0009939664,0.00081640854,0.0011697888,0.0013389011,0.0011844491,0.0006026013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000992281,0.00021680706,0.0051480825,0.0013609693,0.0005934475,0.0005659951,0.0005768056,0.33506754,0.25332907,0.016279297,0.013955615,0.3719142],"study_design_scores_gemma":[0.000064720334,0.00018470759,0.0034468991,0.000074059564,0.00010620367,0.000761544,0.00009596568,0.85912585,0.112028286,0.009495192,0.014453763,0.00016276744],"about_ca_topic_score_codex":0.0046008374,"about_ca_topic_score_gemma":0.0077914107,"teacher_disagreement_score":0.0046008374,"about_ca_system_score_codex":0.000536597,"about_ca_system_score_gemma":0.002221658,"threshold_uncertainty_score":0.01262176},"labels":[],"label_agreement":null},{"id":"W53841409","doi":"10.1007/978-3-642-33415-3_86","title":"Tractometer: Online Evaluation System for Tractography","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Deconvolution; Wavelet; Artificial intelligence; Noise reduction; Pattern recognition (psychology); Data mining; Algorithm; Diffusion MRI","score_opus":0.10058233065189592,"score_gpt":0.4048299809011763,"score_spread":0.30424765024928035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W53841409","genre_codex":"software","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023084175,0.00048336855,0.28792492,0.00019737777,0.00030169621,0.00081077404,0.025926381,0.6574898,0.00378157],"genre_scores_gemma":[0.29805544,0.0010909146,0.5012201,0.00075541105,0.0003678729,0.0039625787,0.09177876,0.08146339,0.021305528],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998738,0.0002783311,0.00022607774,0.00027048957,0.00038902185,0.00009811836],"domain_scores_gemma":[0.9939323,0.002704884,0.0004170678,0.0007913741,0.0016324272,0.0005219257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028233859,0.002522397,0.0015427154,0.0039247433,0.00047686166,0.001984997,0.0015903611,0.0013623397,0.042725418],"category_scores_gemma":[0.010937622,0.0006413113,0.00071892096,0.0016551347,0.0003427926,0.002203066,0.0020404777,0.0009194937,0.015577036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061686737,0.00060530286,0.013928781,0.0016656372,0.0005912771,0.0006921601,0.00051387725,0.009762,0.05190735,0.0034663058,0.31432942,0.59636915],"study_design_scores_gemma":[0.001606146,0.0016830114,0.04231519,0.0004647597,0.00052749226,0.0022623239,0.00037548586,0.6041236,0.18535066,0.012763378,0.14772427,0.00080371695],"about_ca_topic_score_codex":0.0035891437,"about_ca_topic_score_gemma":0.00437188,"teacher_disagreement_score":0.042725418,"about_ca_system_score_codex":0.00054582837,"about_ca_system_score_gemma":0.0011982357,"threshold_uncertainty_score":0.14293075},"labels":[],"label_agreement":null},{"id":"W560408112","doi":"10.71781/18789","title":"Étude de la réorganisation fonctionnelle des aires cérébrales de réception des afférences auditives chez les personnes ayant une atteinte structurelle","year":2007,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Monaural; Psychology; Lesion; Corpus callosum; Neuroscience; Anatomy; Audiology; Medicine","score_opus":0.014503197538364574,"score_gpt":0.2521426594933745,"score_spread":0.23763946195500993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W560408112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938439,0.0013325525,0.0016815717,0.00018462208,0.000031137868,0.000050617185,0.00031298862,0.00003843122,0.0025242537],"genre_scores_gemma":[0.99538165,0.000621687,0.0009006215,0.000048249043,0.000028995719,0.00003625115,0.000107034866,0.000015850916,0.0028596795],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99979407,0.000035288507,0.000011221015,0.000060779515,0.0000534617,0.000045222416],"domain_scores_gemma":[0.9993549,0.00030314422,0.00008830265,0.00003962849,0.00018104987,0.000032911812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005350408,0.00045701457,0.00031307215,0.0005769009,0.00040145539,0.00079425494,0.00029697976,0.0005427734,0.004410124],"category_scores_gemma":[0.0022558125,0.00022985753,0.00028307285,0.0003467688,0.0006760467,0.00055156316,0.00021480332,0.0005549256,0.00054350594],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003617312,0.00032869616,0.33512402,0.0005517454,0.00048060474,0.010638453,0.021293856,0.0008464475,0.37846723,0.0010785891,0.0021960598,0.24537706],"study_design_scores_gemma":[0.00004130917,0.00037752962,0.982451,0.000023281458,0.00008510094,0.003003776,0.0012437087,0.00039323152,0.010297086,0.00012395476,0.0019390748,0.000020962556],"about_ca_topic_score_codex":0.05554681,"about_ca_topic_score_gemma":0.032629676,"teacher_disagreement_score":0.05554681,"about_ca_system_score_codex":0.0005330693,"about_ca_system_score_gemma":0.00054555427,"threshold_uncertainty_score":0.11044699},"labels":[],"label_agreement":null},{"id":"W575675008","doi":"10.1212/wnl.84.14_supplement.s15.007","title":"Longitudinal Voxel-Based Analysis of Brain Atrophy over 6 and 12 Months in CBD and PSP from Two Multicenter Studies (S15.007)","year":2015,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Voxel-based morphometry; Atrophy; Voxel; Neuroscience; Medicine; Multicenter study; Physical medicine and rehabilitation; Pathology; Psychology; Radiology; Magnetic resonance imaging; White matter; Randomized controlled trial","score_opus":0.09675726929919488,"score_gpt":0.39920910675740184,"score_spread":0.302451837458207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W575675008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99927455,0.00008949838,0.000077283796,0.00001372324,0.0000018697142,0.000012805173,0.0004359422,0.000007963692,0.00008631964],"genre_scores_gemma":[0.9973966,0.000034959055,0.0003628546,0.000012897073,0.000004708732,0.000027504731,0.002039523,0.000008765248,0.00011215676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992842,0.00021104002,0.000075829565,0.00025846093,0.000114333045,0.00005603049],"domain_scores_gemma":[0.9977457,0.0001818608,0.00071857,0.00039954795,0.0005447503,0.00040960533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030383524,0.00051896024,0.00058107474,0.0015233147,0.00078502716,0.0006601674,0.0008066146,0.0005772664,0.0010642821],"category_scores_gemma":[0.0031620176,0.00032619966,0.00059889903,0.00078682613,0.00049480505,0.0003959783,0.0011036746,0.000454154,0.00027379344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003824554,0.0002740683,0.9768853,0.0000628908,0.00073060486,0.00090092554,0.00095157704,0.00019084502,0.008235362,0.000037374604,0.00053321494,0.007373266],"study_design_scores_gemma":[0.000047056157,0.00026511645,0.99857605,0.000006314631,0.00007145264,0.00037436918,0.00013770691,0.0001254003,0.00019979755,0.000014174722,0.00017833366,0.0000042648194],"about_ca_topic_score_codex":0.010447142,"about_ca_topic_score_gemma":0.0181587,"teacher_disagreement_score":0.010447142,"about_ca_system_score_codex":0.00059334893,"about_ca_system_score_gemma":0.00041705667,"threshold_uncertainty_score":0.020772696},"labels":[],"label_agreement":null},{"id":"W577586447","doi":"10.1016/j.dib.2015.05.019","title":"Quantitative analysis of the myelin g -ratio from electron microscopy images of the macaque corpus callosum","year":2015,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université Laval; Montreal Neurological Institute and Hospital; McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Myelin; Corpus callosum; Axon; Macaque; Magnetic resonance imaging; Electron microscope; Stereology; Anatomy; Myelin sheath; Aspect ratio (aeronautics); Biology; Pathology; Chemistry; Nuclear magnetic resonance; Materials science; Medicine; Physics; Neuroscience; Central nervous system; Optics; Radiology","score_opus":0.11724128166656239,"score_gpt":0.41942288485755297,"score_spread":0.3021816031909906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W577586447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96029556,0.0018910033,0.034272797,0.00007319839,0.000015848931,0.00006074276,0.0008998036,0.0004705138,0.0020205635],"genre_scores_gemma":[0.9416523,0.0011824955,0.054600272,0.00003599386,0.000024005361,0.000062504456,0.0007751942,0.00017547671,0.0014917029],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998584,0.000017075175,0.000014031706,0.00003243712,0.000056261662,0.000021747659],"domain_scores_gemma":[0.9995554,0.0000939883,0.000106361105,0.000041902775,0.00016860844,0.0000336679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045819124,0.0003919041,0.0002170207,0.0032058978,0.00035403518,0.00052534515,0.00021520862,0.0003454249,0.001486265],"category_scores_gemma":[0.0007356412,0.00015580843,0.00017142648,0.0008651291,0.00028699386,0.0003945128,0.0003039223,0.0002370763,0.00021624242],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013712328,0.000018108762,0.0029779652,0.00024861572,0.00005845524,0.00018501401,0.00023262059,0.0007500521,0.9746208,0.0004042787,0.00016604426,0.020200962],"study_design_scores_gemma":[0.00001918319,0.00043691497,0.299171,0.00013209603,0.00026514224,0.0046726447,0.0006332578,0.023787813,0.66260105,0.0018118069,0.0063775,0.00009159235],"about_ca_topic_score_codex":0.001954528,"about_ca_topic_score_gemma":0.0025683383,"teacher_disagreement_score":0.0032058978,"about_ca_system_score_codex":0.00030482857,"about_ca_system_score_gemma":0.00018093198,"threshold_uncertainty_score":0.0049721003},"labels":[],"label_agreement":null},{"id":"W620785370","doi":"","title":"Phantomas: a flexible software library to simulate diffusion MR phantoms","year":2014,"lang":"en","type":"preprint","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Preprocessor; Imaging phantom; Pipeline (software); Software; Diffusion MRI; Diffusion; Field (mathematics); Artificial intelligence; Magnetic resonance imaging; Physics; Nuclear medicine; Radiology; Mathematics; Medicine; Programming language","score_opus":0.04425934752557032,"score_gpt":0.34723979454588894,"score_spread":0.3029804470203186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W620785370","genre_codex":"methods","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026357702,0.00050987944,0.77780825,0.00025961848,0.00020918726,0.0002472883,0.0077769095,0.20766437,0.002888774],"genre_scores_gemma":[0.05443296,0.0017173745,0.7197423,0.00086378236,0.00018557039,0.0031918604,0.029686805,0.1782933,0.011886018],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909914,0.00020994133,0.00012409512,0.00012467471,0.00036062303,0.00008154066],"domain_scores_gemma":[0.99680483,0.0019563753,0.00022065612,0.00036495482,0.00047376403,0.00017945272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023803546,0.002392977,0.0014546175,0.0023047589,0.0007737797,0.0021127267,0.0048543112,0.0021257054,0.054264117],"category_scores_gemma":[0.010776538,0.002208601,0.0019466867,0.0013210714,0.0006448704,0.0018922547,0.0031008967,0.0031441837,0.01823917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014864105,0.00046295475,0.0027354606,0.0033531615,0.00077973487,0.0013329842,0.0008253372,0.13181798,0.040597692,0.031150647,0.44884175,0.33661598],"study_design_scores_gemma":[0.0009800963,0.00026134818,0.0015981303,0.00044349875,0.00019764833,0.002058139,0.000099079676,0.5056607,0.060203034,0.039859943,0.38817456,0.0004639072],"about_ca_topic_score_codex":0.002874438,"about_ca_topic_score_gemma":0.0038151878,"teacher_disagreement_score":0.054264117,"about_ca_system_score_codex":0.0006656922,"about_ca_system_score_gemma":0.0018339377,"threshold_uncertainty_score":0.18153155},"labels":[],"label_agreement":null},{"id":"W657417801","doi":"10.1016/j.neuroimage.2015.06.033","title":"Multivariate combination of magnetization transfer, T 2 * and B0 orientation to study the myelo-architecture of the in vivo human cortex","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; National Multiple Sclerosis Society Lone Star","keywords":"Magnetization transfer; Myelin; Multivariate statistics; Cortex (anatomy); Contrast (vision); Orientation (vector space); Nuclear magnetic resonance; Content (measure theory); Chemistry; Nuclear medicine; Biology; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging; Physics; Central nervous system; Artificial intelligence; Computer science; Statistics; Radiology","score_opus":0.05875683033107572,"score_gpt":0.3591327970337346,"score_spread":0.30037596670265887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W657417801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9229047,0.00077733846,0.074715815,0.00022591298,0.000031623316,0.00003128367,0.0003230439,0.00020359577,0.0007867772],"genre_scores_gemma":[0.9791373,0.00043801227,0.019611329,0.000032302927,0.00003891716,0.000019166815,0.00012239974,0.00008283006,0.00051773706],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999442,0.000018191864,0.0000032612047,0.000010856582,0.000013642057,0.000009971904],"domain_scores_gemma":[0.9997204,0.00010515717,0.000056962937,0.000032006836,0.000044423028,0.000041041152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000521932,0.0004711611,0.0002815988,0.00083574944,0.00019740267,0.00043121018,0.00016218121,0.0002747081,0.0008247301],"category_scores_gemma":[0.00097098056,0.00020868701,0.00022125916,0.00083153736,0.00024155524,0.00047893214,0.00027656922,0.00048325883,0.00015154223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020794843,0.00027678677,0.03397619,0.00032348002,0.00038571283,0.00034557967,0.0002290434,0.011375665,0.8211922,0.0010396503,0.0014636267,0.12731266],"study_design_scores_gemma":[0.00021110581,0.0015929451,0.4132497,0.000051136307,0.0009040855,0.004656684,0.00046121952,0.26127818,0.30680946,0.006279516,0.0043585794,0.00014743493],"about_ca_topic_score_codex":0.0011407613,"about_ca_topic_score_gemma":0.0028194513,"teacher_disagreement_score":0.0011407613,"about_ca_system_score_codex":0.000097468874,"about_ca_system_score_gemma":0.00033678598,"threshold_uncertainty_score":0.0027602315},"labels":[],"label_agreement":null},{"id":"W6885906044","doi":"10.1371/journal.pone.0279823.s001","title":"General context effect: Full pictures with the context vs. firstly presented images (pictures without the context) at p&lt; .05, family-wise error (FWE) corrected for multiple comparison.","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Pattern recognition (psychology); Visualization; Feature (linguistics); Statistical analysis","score_opus":0.05834125457593781,"score_gpt":0.3325987668574668,"score_spread":0.274257512281529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6885906044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5340783,0.008134297,0.07868322,0.0043633366,0.023397123,0.00776045,0.19312531,0.015583089,0.1348749],"genre_scores_gemma":[0.7861274,0.0015712517,0.0614862,0.0036506054,0.00094194897,0.019744935,0.031507567,0.017370768,0.07759934],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9958664,0.00073979824,0.00033255495,0.001527592,0.0009364308,0.00059722573],"domain_scores_gemma":[0.98275214,0.011833966,0.0015188614,0.0017166137,0.0013770891,0.00080126815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005025103,0.003839575,0.0045007165,0.001993234,0.0017734481,0.0034153587,0.0032544646,0.003276083,0.16573675],"category_scores_gemma":[0.0411852,0.0015000429,0.002007004,0.0015632556,0.002050932,0.008483782,0.0035039547,0.007245615,0.016154911],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.115112975,0.0056192623,0.015312982,0.01955834,0.0047490546,0.0034091144,0.0048927176,0.0036662049,0.30563477,0.013692281,0.40060222,0.107750095],"study_design_scores_gemma":[0.009788617,0.016962504,0.64924294,0.0050422354,0.0087385755,0.0053415773,0.004086854,0.015599266,0.088352405,0.068830416,0.12687697,0.0011376374],"about_ca_topic_score_codex":0.006171989,"about_ca_topic_score_gemma":0.0067947926,"teacher_disagreement_score":0.16573675,"about_ca_system_score_codex":0.0013553752,"about_ca_system_score_gemma":0.0015080083,"threshold_uncertainty_score":0.5544447},"labels":[],"label_agreement":null},{"id":"W6889808992","doi":"10.26044/ecr2020/c-13687","title":"\"Correlation of Resting State fMRI and Diffusion Tensor Imaging in Mild Traumatic Brain Injury\"","year":2020,"lang":"en","type":"article","venue":"European Society of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre de Santé et de Services Sociaux Cavendish","funders":"","keywords":"Resting state fMRI; Diffusion MRI; Diffusion; Neuroimaging; Tractography; Brain mapping","score_opus":0.06330271749414192,"score_gpt":0.33137730551624706,"score_spread":0.26807458802210515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6889808992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9732251,0.008708413,0.0070532765,0.005172849,0.00060006214,0.00014472741,0.0005955508,0.0001675307,0.004332516],"genre_scores_gemma":[0.99048775,0.002485837,0.0033665497,0.00048682233,0.00048477136,0.00003592937,0.00047784272,0.000022502172,0.0021518853],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999634,0.00013023269,0.000049885475,0.000057566966,0.00008950641,0.00003876794],"domain_scores_gemma":[0.99856746,0.00056800985,0.0002699242,0.00009777694,0.00040302408,0.00009362483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003323699,0.00026633742,0.00027736192,0.0009014257,0.00034655497,0.0007556572,0.00065398845,0.00090702926,0.0010011928],"category_scores_gemma":[0.011394105,0.00023470802,0.00037726818,0.00048126583,0.0005137858,0.0006282012,0.0004101723,0.00044399867,0.00035617317],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0068249763,0.00059553026,0.54442453,0.001051376,0.0009788977,0.008433039,0.001792308,0.0017785305,0.05830362,0.0034791662,0.025881767,0.34645626],"study_design_scores_gemma":[0.00009583515,0.0006281089,0.96426123,0.00014246302,0.000614506,0.010376036,0.0005192512,0.003958127,0.011184285,0.002329221,0.005832139,0.000058759106],"about_ca_topic_score_codex":0.0032503107,"about_ca_topic_score_gemma":0.0070334054,"teacher_disagreement_score":0.003323699,"about_ca_system_score_codex":0.00022139866,"about_ca_system_score_gemma":0.0009381281,"threshold_uncertainty_score":0.017577648},"labels":[],"label_agreement":null},{"id":"W6901437950","doi":"10.60692/dhm26-4b264","title":"Tractography at 3T MRI of Corpus Callosum Tracts Crossing White Matter Hyperintensities","year":2016,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; University of Toronto; Queen's University","funders":"","keywords":"Hyperintensity; White matter; Corpus callosum; Diffusion MRI; Tractography; Fractional anisotropy","score_opus":0.056304909901160896,"score_gpt":0.26474150177468153,"score_spread":0.20843659187352065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901437950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98450905,0.00033009815,0.014136675,0.000044851637,0.000005336094,0.00002916782,0.00027565085,0.0001413834,0.00052775873],"genre_scores_gemma":[0.9863523,0.00019872427,0.012757902,0.000015857473,0.000005666404,0.000027315691,0.00028056515,0.000062755935,0.00029886464],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9998148,0.00005220577,0.00001459728,0.000068011286,0.00003634765,0.000014156416],"domain_scores_gemma":[0.9989039,0.0002791475,0.00039769715,0.00014561682,0.00021211282,0.00006155993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006963149,0.00034985394,0.0002542439,0.0012093126,0.00038368953,0.0007828272,0.00020513614,0.00043608175,0.0013314005],"category_scores_gemma":[0.002417389,0.00022913676,0.00038368566,0.00059733994,0.00048628668,0.00045808838,0.00019996178,0.00024541488,0.00023702343],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002111964,0.00012636618,0.3538968,0.00060067134,0.0011619963,0.0027642518,0.003714562,0.01631436,0.51000255,0.0016706133,0.0015879525,0.10604792],"study_design_scores_gemma":[0.00006259978,0.0003327972,0.9095994,0.00009412938,0.00023921249,0.006720961,0.0004814102,0.027914336,0.050537586,0.0017238721,0.002204519,0.00008902536],"about_ca_topic_score_codex":0.0076816557,"about_ca_topic_score_gemma":0.0128654605,"teacher_disagreement_score":0.0076816557,"about_ca_system_score_codex":0.00052663015,"about_ca_system_score_gemma":0.00046235582,"threshold_uncertainty_score":0.015273929},"labels":[],"label_agreement":null},{"id":"W6901772981","doi":"10.60692/85pph-h2r25","title":"Altered coupling of resting-state cerebral blood flow and functional connectivity in Meige syndrome","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Cerebral blood flow; Neurovascular bundle; Precentral gyrus; Middle frontal gyrus; Perfusion; Blood flow; Perfusion scanning; Voxel; Blood-oxygen-level dependent","score_opus":0.08301841575121341,"score_gpt":0.27563846348308496,"score_spread":0.19262004773187155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901772981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9995128,0.00008919793,0.00022485624,0.000011856545,9.3591996e-7,0.0000026422724,0.000050631777,0.0000042232296,0.00010278394],"genre_scores_gemma":[0.99968386,0.000039463834,0.00016450245,0.000006104382,0.0000033102335,0.000003697336,0.000056665078,9.591189e-7,0.00004147687],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99993587,0.000012110414,0.0000064220835,0.000024116152,0.000010573171,0.000010886786],"domain_scores_gemma":[0.99987674,0.00003358391,0.00005757891,0.0000055272244,0.000007955992,0.000018623152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117477335,0.00025116955,0.0001886188,0.00046260332,0.00012004475,0.00016768952,0.00010784163,0.00024248216,0.0015720144],"category_scores_gemma":[0.00058505876,0.0000867837,0.00010686729,0.00018891359,0.00021541596,0.00017089803,0.00016427941,0.00010945639,0.000059572656],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028397024,0.00017570039,0.7547562,0.0001346791,0.0003367544,0.009019221,0.0007422872,0.001015628,0.19642231,0.00038544225,0.00040381847,0.033768274],"study_design_scores_gemma":[0.000015945143,0.00019146249,0.99152184,0.0000039916386,0.000032947515,0.004828896,0.000091726215,0.00065408763,0.0023424083,0.00020934518,0.00010157301,0.0000058577402],"about_ca_topic_score_codex":0.0014065492,"about_ca_topic_score_gemma":0.0011271756,"teacher_disagreement_score":0.0015720144,"about_ca_system_score_codex":0.000120437915,"about_ca_system_score_gemma":0.0000938757,"threshold_uncertainty_score":0.005258918},"labels":[],"label_agreement":null},{"id":"W6901965036","doi":"10.60692/xa8tc-g9b05","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Cognition; Executive functions; Dementia; Cognitive impairment; Executive dysfunction","score_opus":0.06329485058994336,"score_gpt":0.2947313742875131,"score_spread":0.23143652369756976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901965036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99982375,0.000028886894,0.000024721961,0.0000043611144,8.489722e-7,0.0000037162088,0.000027192993,5.254003e-7,0.000085915664],"genre_scores_gemma":[0.99967635,0.00003553841,0.000050592564,0.0000062068725,0.0000035171756,0.000005148501,0.000090441295,8.5359756e-7,0.00013129735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998728,0.000020755067,0.000022297369,0.000035236135,0.000017947119,0.000030884465],"domain_scores_gemma":[0.9994338,0.00006893806,0.00025374387,0.000038582635,0.00007029956,0.00013454507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026936125,0.0004328202,0.00028451116,0.00077577383,0.00047248992,0.00055887346,0.00019002102,0.00036276036,0.001110093],"category_scores_gemma":[0.0009887551,0.00027995784,0.0003022873,0.0006300303,0.0004778347,0.00046397946,0.00043512546,0.00024349063,0.00017816662],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000792686,0.000195724,0.9899401,0.000039563376,0.00007995475,0.00084232446,0.0021596195,0.000035226305,0.0032396582,0.000021575917,0.000048984086,0.0026046557],"study_design_scores_gemma":[0.000010071215,0.00023861244,0.9982256,0.0000029890396,0.00002270328,0.0006340501,0.00062647223,0.00006794801,0.000100516845,0.000020416797,0.000046861125,0.000003708967],"about_ca_topic_score_codex":0.0077287704,"about_ca_topic_score_gemma":0.0072960057,"teacher_disagreement_score":0.0077287704,"about_ca_system_score_codex":0.00022346815,"about_ca_system_score_gemma":0.00022064864,"threshold_uncertainty_score":0.015367568},"labels":[],"label_agreement":null},{"id":"W6906675206","doi":"10.17605/osf.io/nwv8g","title":"Hubner (2023). Keeping Ahead of Chronic Wasting Disease: An Assessment of Trans-Boundary Cervid Movement in British Columbia - UBCO M.Sc. Thesis Repository","year":2023,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chronic wasting disease; Wasting; Movement (music); Population","score_opus":0.030474493541289116,"score_gpt":0.34014136558412933,"score_spread":0.3096668720428402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906675206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36223775,0.033826485,0.0055813678,0.074304424,0.002966176,0.0014260623,0.26665577,0.0027760381,0.25022584],"genre_scores_gemma":[0.60047936,0.025515795,0.02155091,0.0045497273,0.00044066674,0.0012895608,0.061287284,0.001440119,0.28344658],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9992976,0.000061757455,0.00006141012,0.000080936756,0.0003913906,0.000106748535],"domain_scores_gemma":[0.99408203,0.0005629486,0.00042308855,0.00025520945,0.0032533463,0.0014233197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016996033,0.00047972915,0.00039275122,0.0030229262,0.0023218787,0.0022612193,0.00097162975,0.00081909343,0.033346184],"category_scores_gemma":[0.0094214855,0.0004290426,0.0003088488,0.004360833,0.00091547327,0.0010531242,0.0014440289,0.0012198775,0.009030097],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017384804,0.000052247804,0.10503808,0.00041772443,0.00003197959,0.0003443426,0.0048027686,0.00016014854,0.0004525383,0.00131027,0.6652191,0.22199693],"study_design_scores_gemma":[0.00003529041,0.000050624993,0.7664565,0.0009384656,0.000058243124,0.0005411191,0.0068781567,0.00027562695,0.0008138051,0.0016878942,0.22216621,0.00009807912],"about_ca_topic_score_codex":0.82597727,"about_ca_topic_score_gemma":0.90721905,"teacher_disagreement_score":0.17402273,"about_ca_system_score_codex":0.006401188,"about_ca_system_score_gemma":0.011976034,"threshold_uncertainty_score":0.35009515},"labels":[],"label_agreement":null},{"id":"W6911390267","doi":"10.5281/zenodo.11726703","title":"les taches d un agent commercial dans une banque pdf","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Limiting; State owned; Commercial banking; Security market","score_opus":0.0974405021559019,"score_gpt":0.33059531715986906,"score_spread":0.23315481500396718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6911390267","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071893837,0.0041780164,0.011853127,0.0013323842,0.0042705736,0.0001611709,0.0012292925,0.0024683524,0.9673176],"genre_scores_gemma":[0.020566817,0.0038457792,0.005776089,0.0005726007,0.0007632117,0.00008723855,0.00089585525,0.0011733932,0.96631914],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994708,0.00004263151,0.000024079913,0.00006006728,0.0003385705,0.00006391367],"domain_scores_gemma":[0.99911445,0.00018561959,0.000052730826,0.00011180055,0.00040403818,0.00013136592],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005909461,0.000794219,0.00044747128,0.0010714802,0.0013530627,0.0030293337,0.00064505264,0.0012314029,0.4616996],"category_scores_gemma":[0.0017918368,0.00034736135,0.0006111629,0.0009548391,0.0007567418,0.00419636,0.0012772633,0.0017578211,0.2674538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042805454,0.00013157197,0.00039934984,0.0008627964,0.000018783248,0.0009786737,0.00070089754,0.00040452418,0.020402793,0.023402913,0.55499715,0.39727238],"study_design_scores_gemma":[0.000015935035,0.00005903252,0.00047273893,0.0001221258,0.000007303805,0.0005521173,0.00018667034,0.00015632345,0.0042764302,0.00064885116,0.9934877,0.000014652907],"about_ca_topic_score_codex":0.002316824,"about_ca_topic_score_gemma":0.004185218,"teacher_disagreement_score":0.5383004,"about_ca_system_score_codex":0.0005988457,"about_ca_system_score_gemma":0.0007414254,"threshold_uncertainty_score":0.7678202},"labels":[],"label_agreement":null},{"id":"W6920687054","doi":"10.6084/m9.figshare.28630036.v1","title":"Additional file 1 of Connectivity related to major brain functions in Alzheimer disease progression: microstructural properties of the cingulum bundle and its subdivision using diffusion-weighted MRI","year":2025,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Region of interest; Subdivision; Cingulum (brain); Voxel; Retrosplenial cortex; Distortion (music); Pattern recognition (psychology)","score_opus":0.04905254241155561,"score_gpt":0.34899369539510944,"score_spread":0.29994115298355384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920687054","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034754188,0.000020072848,0.00031678184,0.000078405115,0.000025753261,0.00010780653,0.9984559,0.00024154116,0.0004062785],"genre_scores_gemma":[0.012203204,0.00021986631,0.0069934535,0.00045201575,0.00015326352,0.004505628,0.9672851,0.0012176652,0.0069698766],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99948585,0.0000651423,0.00011265998,0.00013582158,0.00012328543,0.00007708533],"domain_scores_gemma":[0.98854107,0.008396213,0.0007007622,0.0006797117,0.0013817692,0.00030050206],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012594201,0.0018208149,0.0016230219,0.0021332297,0.0010370214,0.0019108497,0.0018908071,0.0014873779,0.86000645],"category_scores_gemma":[0.024522366,0.0006810598,0.0008820901,0.0030965835,0.00027418268,0.0019546293,0.001181879,0.0011453764,0.13716203],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008585271,0.00018062063,0.0039491416,0.0038069233,0.00007280578,0.00026580016,0.00009387873,0.00056532543,0.00038777324,0.0006047377,0.9760784,0.013136022],"study_design_scores_gemma":[0.020203825,0.0010785599,0.082186714,0.0076398975,0.0006040997,0.0039588977,0.0010480434,0.0077660875,0.0039989506,0.020203695,0.8508285,0.0004826637],"about_ca_topic_score_codex":0.006569864,"about_ca_topic_score_gemma":0.011560171,"teacher_disagreement_score":0.86000645,"about_ca_system_score_codex":0.0010415234,"about_ca_system_score_gemma":0.0017522884,"threshold_uncertainty_score":0.19968373},"labels":[],"label_agreement":null},{"id":"W6920687338","doi":"10.60692/z0kkx-dby80","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Diffusion MRI; Core (optical fiber); Neuroimaging","score_opus":0.08639512390122667,"score_gpt":0.29637261351750305,"score_spread":0.20997748961627638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920687338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96950275,0.017013038,0.0017401995,0.00012831751,0.000022703427,0.00012082822,0.010971351,0.000052733565,0.00044824427],"genre_scores_gemma":[0.9865866,0.0031239875,0.0017681587,0.00009676997,0.000019609639,0.00020331566,0.0079374,0.000058664125,0.00020544212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959462,0.0014518879,0.0007894207,0.0012134587,0.000430466,0.00016853979],"domain_scores_gemma":[0.99445677,0.0018826737,0.0016778192,0.0010652426,0.0006261583,0.00029125914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070076897,0.0011000826,0.0016610547,0.0031713347,0.0008547682,0.0013091193,0.0007375491,0.0005444662,0.0013995931],"category_scores_gemma":[0.010139156,0.0006431993,0.002919201,0.0046942467,0.0005596554,0.00046753968,0.001975071,0.00038195294,0.0003192103],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038240012,0.00010140101,0.9067348,0.0022063565,0.049565013,0.000347689,0.0014505534,0.0006628339,0.0049431985,0.00022725087,0.0020863104,0.027850665],"study_design_scores_gemma":[0.0002471999,0.0002643485,0.9758099,0.00022958673,0.019714119,0.0003336365,0.00034218113,0.00016181845,0.0005483528,0.00022622163,0.0020870895,0.00003542294],"about_ca_topic_score_codex":0.015447306,"about_ca_topic_score_gemma":0.019892257,"teacher_disagreement_score":0.015447306,"about_ca_system_score_codex":0.00063691684,"about_ca_system_score_gemma":0.00093728915,"threshold_uncertainty_score":0.03706062},"labels":[],"label_agreement":null},{"id":"W6928789993","doi":"10.3897/zookeys.179.2601.map8","title":"Map 8 from: Webster R, Sweeney J, DeMerchant I, Silk P, Mayo P (2012) New Coleoptera records from New Brunswick, Canada: Cerambycidae. ZooKeys 179: 309-311. https://doi.org/10.3897/zookeys.179.2601","year":2012,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"SILK; Historical record; Line drawings","score_opus":0.07088916089450704,"score_gpt":0.28627580877802894,"score_spread":0.2153866478835219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6928789993","genre_codex":"dataset","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008997611,0.0015735624,0.00168106,0.0009896061,0.000819416,0.00027653883,0.654447,0.003889738,0.33542332],"genre_scores_gemma":[0.010730581,0.00516141,0.008270993,0.00043437927,0.00045095125,0.00065268594,0.6471002,0.003314502,0.32388428],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996655,0.000026814869,0.00001978772,0.000063576044,0.00013364044,0.000090784844],"domain_scores_gemma":[0.99884915,0.00015185984,0.00007961809,0.00009627434,0.00065639155,0.00016664644],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003575287,0.0016532495,0.0010070446,0.0049482794,0.0009800751,0.003071888,0.0015391939,0.0010716665,0.7215268],"category_scores_gemma":[0.0029592644,0.000474545,0.0008857804,0.008129975,0.00063162803,0.0017032989,0.0016697025,0.0013891642,0.45007068],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042734955,0.000013767655,0.00044533607,0.0006895626,0.0000133023295,0.00008489691,0.00009454763,0.00010936184,0.00014200645,0.0004908321,0.9729796,0.02489416],"study_design_scores_gemma":[0.000037877788,0.0000063127723,0.0032253389,0.00035650653,0.000014551181,0.000088282504,0.00015302982,0.00011084476,0.00016612338,0.0005872538,0.99523735,0.000016468626],"about_ca_topic_score_codex":0.1782454,"about_ca_topic_score_gemma":0.2798948,"teacher_disagreement_score":0.8217546,"about_ca_system_score_codex":0.0014903779,"about_ca_system_score_gemma":0.0039681066,"threshold_uncertainty_score":0.3972082},"labels":[],"label_agreement":null},{"id":"W6928886133","doi":"10.3897/zookeys.788.26048.figures1-12","title":"Figures 1-12 from: Schmidt CB, Sullivan BJ (2018) Three species in one: a revision of Clemensia albata Packard (Erebidae, Arctiinae, Lithosiini). In: Schmidt BC, Lafontaine JD (Eds) Contributions to the systematics of New World macro-moths VII. ZooKeys 788: 39-55. https://doi.org/10.3897/zookeys.788.26048","year":2018,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Systematics; State (computer science)","score_opus":0.08606102278607895,"score_gpt":0.3274063947683063,"score_spread":0.24134537198222733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6928886133","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013679705,0.0029002456,0.001521228,0.0009866949,0.0045876172,0.0003310121,0.0455928,0.0011493185,0.9415631],"genre_scores_gemma":[0.016677208,0.0051700175,0.006192435,0.000881337,0.0012628868,0.00044860673,0.04473761,0.0018387131,0.92279124],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997081,0.00002681752,0.000018784707,0.00006176821,0.00015008381,0.00003437486],"domain_scores_gemma":[0.9995567,0.00008638182,0.000044154076,0.000051881638,0.00020297435,0.000057875997],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002054752,0.0011962593,0.0005236554,0.002035185,0.0017006351,0.0012282735,0.0010073953,0.0008144959,0.7280855],"category_scores_gemma":[0.0014809987,0.00038935547,0.00060111994,0.0025714515,0.00076610106,0.0021172261,0.001096305,0.0015435874,0.4587609],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027103597,0.000006599334,0.00015533346,0.00015454635,0.0000025895765,0.00009196825,0.00012787733,0.00004642664,0.00020825739,0.0015491673,0.9679487,0.029681532],"study_design_scores_gemma":[0.0000032843147,0.000003851239,0.0007444425,0.000077976736,0.0000021251044,0.0001303416,0.00006379285,0.000018734114,0.000061601786,0.00033967174,0.9985513,0.0000027798967],"about_ca_topic_score_codex":0.019737603,"about_ca_topic_score_gemma":0.051151272,"teacher_disagreement_score":0.7280855,"about_ca_system_score_codex":0.0015818689,"about_ca_system_score_gemma":0.0012223573,"threshold_uncertainty_score":0.38785297},"labels":[],"label_agreement":null},{"id":"W6929460105","doi":"10.5066/p97r96is","title":"Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Degree Flowlines","year":2021,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Wetland; Impervious surface; Hydrology (agriculture); Habitat; Restoration ecology; Nature Conservation; Wetland conservation; Recreational use","score_opus":0.06389841341094381,"score_gpt":0.3153651365480106,"score_spread":0.2514667231370668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929460105","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027232978,0.000024336414,0.00004080043,0.00003747555,0.0000065887752,0.000008299132,0.9989442,0.000099990764,0.0005659732],"genre_scores_gemma":[0.0007655032,0.000033075747,0.00022156244,0.000015876925,0.0000031102013,0.00005101951,0.9983309,0.000023611585,0.00055541424],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99956864,0.00003899905,0.00005173176,0.00011343489,0.00015284466,0.00007431492],"domain_scores_gemma":[0.9982492,0.0002195642,0.00021681175,0.00021736328,0.0009064485,0.00019064029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050151546,0.0010375842,0.00070809736,0.0023163622,0.0007179661,0.0011718683,0.001703432,0.0008431753,0.026382666],"category_scores_gemma":[0.0030514072,0.00044195805,0.0005462999,0.0058317967,0.00032893405,0.0006213517,0.0010414921,0.00079274154,0.019100698],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033782704,0.000012758599,0.003398016,0.00029310826,0.000017813205,0.000022551398,0.00003207484,0.00028073124,0.00006514662,0.00032913085,0.9931393,0.0023754374],"study_design_scores_gemma":[0.00018966713,0.000012810794,0.0326826,0.0002991262,0.000023601337,0.00004624806,0.00019234921,0.0010378663,0.00028949455,0.0007530722,0.9644406,0.000032583608],"about_ca_topic_score_codex":0.49256486,"about_ca_topic_score_gemma":0.7135825,"teacher_disagreement_score":0.49256486,"about_ca_system_score_codex":0.0039226855,"about_ca_system_score_gemma":0.005446544,"threshold_uncertainty_score":0.9793956},"labels":[],"label_agreement":null},{"id":"W6930154912","doi":"10.5281/zenodo.12340696","title":"mcgraw-hill ryerson chemistry 11 2011 pdf","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Process (computing); Subject (documents); Bridge (graph theory); Resource (disambiguation); The Internet; Chemistry education; Virtual lab","score_opus":0.06049457925126113,"score_gpt":0.3090227688378551,"score_spread":0.248528189586594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930154912","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00048215972,0.008645716,0.005485176,0.0017397292,0.0019653158,0.00027161592,0.0063021863,0.0039936593,0.97111434],"genre_scores_gemma":[0.0006978024,0.00512307,0.0015848002,0.00046915188,0.00011573517,0.000084431995,0.0030070927,0.0006094655,0.9883084],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941087,0.000034869438,0.00002838363,0.000104033126,0.00036589813,0.00005605138],"domain_scores_gemma":[0.99929404,0.00008197202,0.00003361899,0.00011644242,0.00034495123,0.0001288959],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007191388,0.0017217522,0.0015046492,0.0020609668,0.0013017551,0.0039389697,0.0021843081,0.0017068441,0.7706737],"category_scores_gemma":[0.0015634759,0.0014000762,0.0010666953,0.002485671,0.0005158957,0.003825214,0.0020095415,0.00353378,0.79100066],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005355995,0.00007421723,0.000053129563,0.00059792254,0.000013850372,0.00006930194,0.000039822116,0.00017497236,0.003050871,0.0035863481,0.83184874,0.16043717],"study_design_scores_gemma":[0.0000068968666,0.00001568544,0.00006192363,0.00006143617,0.0000031729019,0.00004476756,0.000015978509,0.000056610123,0.00056639477,0.0004302568,0.9987286,0.000008267735],"about_ca_topic_score_codex":0.0032709686,"about_ca_topic_score_gemma":0.009457033,"teacher_disagreement_score":0.22932631,"about_ca_system_score_codex":0.0012254477,"about_ca_system_score_gemma":0.00250553,"threshold_uncertainty_score":0.32710612},"labels":[],"label_agreement":null},{"id":"W6930397088","doi":"10.5281/zenodo.14135892","title":"PM_134927_B_Maarke","year":2021,"lang":"nl","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Period (music); Exposition (narrative); Government (linguistics); Quarter (Canadian coin); Subject (documents)","score_opus":0.09596298050184221,"score_gpt":0.32909117195004345,"score_spread":0.23312819144820124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930397088","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00039269228,0.00029593412,0.0011518731,0.00082409347,0.0010611619,0.00011005709,0.053932883,0.00901481,0.93321633],"genre_scores_gemma":[0.0022256013,0.00030386003,0.0006394834,0.00025121335,0.00021738173,0.0000967871,0.015697084,0.0057459422,0.9748225],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996151,0.00003855513,0.00001855121,0.000110064226,0.0001500883,0.000067553774],"domain_scores_gemma":[0.9982102,0.00035130724,0.000086319844,0.00030007004,0.00061278127,0.00043929744],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00044098613,0.0008871128,0.00086337584,0.001602558,0.0012680788,0.005563864,0.0012576603,0.0013145016,0.95180374],"category_scores_gemma":[0.0038969284,0.0006305925,0.00040782982,0.0032751379,0.00045393672,0.0026322599,0.002185359,0.0011469268,0.9399345],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002653873,0.000008182011,0.00006945119,0.000050663028,9.676564e-7,0.000014153692,0.000018510631,0.000018019276,0.00010219768,0.00043409664,0.9824012,0.016855946],"study_design_scores_gemma":[0.0000133771255,0.000007723863,0.00046179525,0.00004074872,0.0000013159017,0.000035723264,0.000037105565,0.000033057655,0.00018627546,0.00024106319,0.99893683,0.0000048341803],"about_ca_topic_score_codex":0.006748156,"about_ca_topic_score_gemma":0.0065862015,"teacher_disagreement_score":0.048196256,"about_ca_system_score_codex":0.0010240902,"about_ca_system_score_gemma":0.00094259536,"threshold_uncertainty_score":0.06874609},"labels":[],"label_agreement":null},{"id":"W6930425449","doi":"10.5281/zenodo.10402001","title":"Research protocol. Worldwide trends in sodium and potassium intakes in children and adolescents: a systematic review and meta-analysis","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Blood pressure; Sodium; Potassium; High sodium; Kidney disease; Dietary Sodium","score_opus":0.11834855531793197,"score_gpt":0.38380085748942167,"score_spread":0.2654523021714897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930425449","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005927857,0.032014765,0.0073182895,0.0018653701,0.0013310511,0.7952396,0.15144038,0.0012691243,0.0035935484],"genre_scores_gemma":[0.0076576406,0.003723479,0.0068943226,0.0008460576,0.00007357504,0.97206724,0.0066401176,0.00007765568,0.0020200196],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.98755276,0.00468059,0.004074426,0.0018754946,0.0012519237,0.0005647533],"domain_scores_gemma":[0.9854483,0.0055912053,0.0038735853,0.0018774034,0.0027488205,0.0004607354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.025412269,0.0039347904,0.015885245,0.007962229,0.0016428424,0.0047652777,0.0033335565,0.0038414106,0.08204193],"category_scores_gemma":[0.047617033,0.0029941155,0.019285586,0.007553687,0.0022320175,0.00451057,0.0030066692,0.0033182995,0.0060908757],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008018545,0.00009418732,0.0016218836,0.9242472,0.03299825,0.00017320411,0.00040324414,0.00070110784,0.00037044738,0.0017565148,0.018029263,0.01158614],"study_design_scores_gemma":[0.11372114,0.002242212,0.026343243,0.46867666,0.22349998,0.0006855468,0.0012155623,0.0031757853,0.0015463792,0.012953117,0.14537637,0.00056408864],"about_ca_topic_score_codex":0.009183075,"about_ca_topic_score_gemma":0.017943542,"teacher_disagreement_score":0.08204193,"about_ca_system_score_codex":0.0069892085,"about_ca_system_score_gemma":0.016973443,"threshold_uncertainty_score":0.27445757},"labels":[],"label_agreement":null},{"id":"W6930527726","doi":"10.5281/zenodo.11841300","title":"Kb psychiatrie pdf gratuit","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paraphernalia; Nucleofection; Limiting; Context (archaeology)","score_opus":0.06464322918848939,"score_gpt":0.32373092840694484,"score_spread":0.2590876992184554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930527726","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022897092,0.0020385557,0.00037296134,0.006901151,0.006586908,0.0001656119,0.006078967,0.0032457318,0.97438115],"genre_scores_gemma":[0.00078067224,0.0012331519,0.00029123123,0.0019276785,0.00087756803,0.000050612023,0.001793926,0.00093419885,0.99211085],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991347,0.000076668635,0.000048238377,0.00009719899,0.00050938193,0.00013377653],"domain_scores_gemma":[0.9961863,0.0004147713,0.00016643044,0.00030628615,0.0018658488,0.0010603785],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00054813275,0.0012534484,0.0011151992,0.0024359573,0.0018938584,0.0054514646,0.0014555452,0.0024442875,0.945189],"category_scores_gemma":[0.0076843887,0.0007580305,0.00069697684,0.0016853478,0.0007199212,0.0040511084,0.0042886822,0.0031155474,0.9363125],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000099227655,0.000006408018,0.000010238753,0.000053321604,6.3895186e-7,0.000030144585,0.000016941329,0.0000055964533,0.000041739288,0.00026564868,0.9847149,0.014844522],"study_design_scores_gemma":[0.000006893295,0.000005146808,0.00010493518,0.000089856876,7.957659e-7,0.00012829086,0.000055161327,0.000010709758,0.000041265095,0.00018140979,0.99937063,0.000004900681],"about_ca_topic_score_codex":0.006536874,"about_ca_topic_score_gemma":0.0136827,"teacher_disagreement_score":0.054811,"about_ca_system_score_codex":0.0019452188,"about_ca_system_score_gemma":0.002302393,"threshold_uncertainty_score":0.07818115},"labels":[],"label_agreement":null},{"id":"W6930560715","doi":"10.5281/zenodo.14366804","title":"globalbioticinteractions/globalbioticinteractions: v0.27.2","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Interoperability; Context (archaeology); Key (lock); Process (computing)","score_opus":0.07944087637282128,"score_gpt":0.3564202520129595,"score_spread":0.27697937564013825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930560715","genre_codex":"software","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013076192,0.00041302457,0.06794997,0.00071271264,0.00045157794,0.00017069043,0.070561394,0.81395173,0.04448122],"genre_scores_gemma":[0.03136815,0.0005028956,0.08023782,0.0015866298,0.00029346274,0.0007145291,0.33181414,0.49949846,0.053983856],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99843377,0.00025181368,0.00008099183,0.0003352302,0.00066629593,0.00023196837],"domain_scores_gemma":[0.99807006,0.00033108113,0.00008490291,0.00087710493,0.00033931382,0.0002975424],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0030605737,0.0035297729,0.0017245568,0.0016667251,0.0011552294,0.004490292,0.0045484127,0.0034786058,0.22726284],"category_scores_gemma":[0.0058241608,0.0023163313,0.0021305487,0.0016044735,0.0011852691,0.0047624423,0.0055118375,0.0038652709,0.24425714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058928423,0.00006255475,0.0006512705,0.0004406929,0.00013040674,0.00010770737,0.00012843555,0.0013729285,0.004146053,0.0069456706,0.96439236,0.021032616],"study_design_scores_gemma":[0.00037533417,0.000052591146,0.0007291749,0.00007360803,0.00004771839,0.00014487268,0.000042463475,0.009381285,0.012808988,0.016064754,0.9601618,0.000117399715],"about_ca_topic_score_codex":0.008824186,"about_ca_topic_score_gemma":0.009860572,"teacher_disagreement_score":0.77273715,"about_ca_system_score_codex":0.00158193,"about_ca_system_score_gemma":0.0016595979,"threshold_uncertainty_score":0.76026994},"labels":[],"label_agreement":null},{"id":"W6930978024","doi":"10.5281/zenodo.4489215","title":"Osmia (Centrosmia) nigriventris","year":2011,"lang":"de","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bay; North sea","score_opus":0.13662739112436095,"score_gpt":0.3109746497342994,"score_spread":0.17434725860993844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930978024","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.867336,0.0063254503,0.0051395916,0.00042495606,0.00024186748,0.00020162237,0.006224326,0.0005226291,0.11358357],"genre_scores_gemma":[0.9727145,0.0015424608,0.0042029833,0.00026082774,0.000042275573,0.00008177057,0.0035815588,0.00003854113,0.017535118],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988127,0.000008385477,0.000013869765,0.00004645181,0.000036804693,0.000013204214],"domain_scores_gemma":[0.99990284,0.0000128297925,0.00003688328,0.000010162102,0.000025998139,0.000011297294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000827676,0.00029403844,0.00018089713,0.0007979688,0.00070592004,0.00028606507,0.00031715454,0.00031383926,0.0028793118],"category_scores_gemma":[0.00018053097,0.00013599743,0.00018788323,0.00046009905,0.00027100858,0.00047540886,0.0006150239,0.00042110536,0.0013977508],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008024124,0.00012193638,0.07436779,0.001049412,0.00020045729,0.0053064227,0.0029323958,0.0012818474,0.5063905,0.0024466317,0.013622732,0.3914774],"study_design_scores_gemma":[0.00007434127,0.00046994453,0.63819975,0.0003081322,0.0002446287,0.009452357,0.0021053883,0.00077934435,0.029802795,0.0012672981,0.3172386,0.0000573764],"about_ca_topic_score_codex":0.0038006792,"about_ca_topic_score_gemma":0.011921856,"teacher_disagreement_score":0.0038006792,"about_ca_system_score_codex":0.00041008278,"about_ca_system_score_gemma":0.00017846706,"threshold_uncertainty_score":0.009632289},"labels":[],"label_agreement":null},{"id":"W6931103072","doi":"10.5281/zenodo.4339840","title":"Anthomyza equiseti Roháćek & Barber 2016, sp. nov.","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Carex; Bay; Pollen; Hay; Peat","score_opus":0.09087258302477849,"score_gpt":0.32847050741635386,"score_spread":0.23759792439157537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931103072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45876992,0.05748678,0.013214903,0.004452542,0.0024187972,0.001846285,0.013156832,0.0012228123,0.4474311],"genre_scores_gemma":[0.86416584,0.023575822,0.016566256,0.0019936652,0.0011363355,0.0008435771,0.009270773,0.00015235033,0.08229529],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99971527,0.000027560023,0.000027111664,0.000102080536,0.00009402772,0.000034043253],"domain_scores_gemma":[0.9997048,0.000041407984,0.00009934178,0.0000325774,0.000088883935,0.00003287035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026311362,0.0010881122,0.00047998736,0.001491567,0.0021133781,0.0007718844,0.0008011246,0.0012489978,0.009232371],"category_scores_gemma":[0.0010110891,0.0004447815,0.00022362737,0.00096132734,0.00090973533,0.0016391083,0.0009362458,0.0013740133,0.005286369],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012303907,0.0003333205,0.08562347,0.0034653738,0.00046265498,0.01418858,0.0077649117,0.003113371,0.045284458,0.0056012417,0.10867534,0.72425693],"study_design_scores_gemma":[0.00021557834,0.00031642965,0.42231598,0.0017365732,0.00059050997,0.02194224,0.0028013312,0.0012560054,0.0033357202,0.0019209799,0.5434802,0.000088469795],"about_ca_topic_score_codex":0.018624103,"about_ca_topic_score_gemma":0.033248007,"teacher_disagreement_score":0.018624103,"about_ca_system_score_codex":0.00087973406,"about_ca_system_score_gemma":0.00067074125,"threshold_uncertainty_score":0.037031412},"labels":[],"label_agreement":null},{"id":"W6931227347","doi":"10.5281/zenodo.2575124","title":"An open science approach to standardizing T1 mapping","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Transparency (behavior); Software; Field (mathematics); Open science; Open source; Open data","score_opus":0.21364604167460896,"score_gpt":0.42669402829967085,"score_spread":0.21304798662506189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931227347","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012453927,0.0010894046,0.97804934,0.0097616315,0.001503901,0.000055240547,0.00012294938,0.0018602828,0.006311777],"genre_scores_gemma":[0.06626743,0.002976931,0.9128138,0.0050029103,0.003345943,0.00037134267,0.00048322364,0.0032203053,0.0055181454],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.97541183,0.010494793,0.0015464422,0.0031542815,0.008672914,0.00071963336],"domain_scores_gemma":[0.88548577,0.05602091,0.0042634737,0.032945372,0.01885055,0.0024338586],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.04395663,0.0015295233,0.0014650355,0.0034764165,0.0023914261,0.0141109135,0.0061042556,0.0067548715,0.012973879],"category_scores_gemma":[0.13282964,0.0012102448,0.0019192365,0.0026827457,0.009285083,0.015965257,0.012161219,0.01064471,0.006141185],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031459864,0.00008806702,0.00089822867,0.00048259806,0.00012904053,0.00024634175,0.0013547884,0.0077062524,0.011010666,0.6371763,0.025710572,0.31488252],"study_design_scores_gemma":[0.000054569387,0.000104848135,0.00027206118,0.0002855822,0.000043207845,0.00044452705,0.00022607125,0.014471485,0.012144017,0.81928366,0.15255521,0.00011479176],"about_ca_topic_score_codex":0.00090900576,"about_ca_topic_score_gemma":0.00069448585,"teacher_disagreement_score":0.99389577,"about_ca_system_score_codex":0.002132636,"about_ca_system_score_gemma":0.0044747884,"threshold_uncertainty_score":0.23246759},"labels":[],"label_agreement":null},{"id":"W6931267091","doi":"10.5281/zenodo.4589366","title":"dockstore/dockstore-ui2: 2.7.4","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Interface (matter); Process (computing); Identification (biology); User interface; Set (abstract data type)","score_opus":0.09066590561079756,"score_gpt":0.3327679811899743,"score_spread":0.24210207557917673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931267091","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006708725,0.00031283262,0.05111507,0.0004844687,0.00040479764,0.00022207771,0.050094612,0.8581897,0.038505506],"genre_scores_gemma":[0.013558077,0.0006048546,0.031281564,0.0011490139,0.0002369022,0.00072850863,0.15220807,0.7354703,0.06476277],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99822015,0.00017280638,0.00020762155,0.00033606347,0.00065207056,0.00041120753],"domain_scores_gemma":[0.9952577,0.0009748595,0.000179764,0.0015429389,0.0012568013,0.0007879283],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0036733325,0.00445694,0.0037484074,0.003047306,0.0014694226,0.008736716,0.010114081,0.0035506545,0.46981],"category_scores_gemma":[0.013071633,0.0041464977,0.002707434,0.0035517784,0.0011712075,0.008855496,0.011137736,0.006275969,0.5377198],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004314982,0.00006392788,0.00027206697,0.00030331386,0.00004434883,0.00008633092,0.0000991253,0.00041717233,0.0007123483,0.0029875713,0.97930497,0.015277383],"study_design_scores_gemma":[0.0007353909,0.00004071033,0.0009339532,0.0002712618,0.000051499646,0.000245551,0.00010620283,0.008404316,0.0070870323,0.012950017,0.96895796,0.00021614217],"about_ca_topic_score_codex":0.008372666,"about_ca_topic_score_gemma":0.005517219,"teacher_disagreement_score":0.46981,"about_ca_system_score_codex":0.0017189803,"about_ca_system_score_gemma":0.0020266445,"threshold_uncertainty_score":0.7562517},"labels":[],"label_agreement":null},{"id":"W6931783036","doi":"10.5281/zenodo.7264584","title":"IMPACT OF COVID-19 ON INFLOW OF FOREIGN DIRECT INVESTMENT.","year":2022,"lang":"en","type":"book-chapter","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Foreign direct investment; Inflow; Multinational corporation; Recession; World economy; Quarter (Canadian coin); Investment (military); Constructive","score_opus":0.1162170048877067,"score_gpt":0.34941457100669526,"score_spread":0.23319756611898856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931783036","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04427173,0.107272096,0.0011344262,0.013737827,0.0030162467,0.00004478001,0.0039127925,0.00027621715,0.8263339],"genre_scores_gemma":[0.4147941,0.13390084,0.0025597932,0.0034896855,0.0013563051,0.00005627366,0.006955274,0.00024243818,0.43664527],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995969,0.00007056953,0.00001592384,0.000043267497,0.00020512856,0.00006822198],"domain_scores_gemma":[0.9991328,0.00032714964,0.00011797565,0.00003497492,0.00029116333,0.00009587877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044551666,0.00036688728,0.00011840483,0.0012619013,0.0003930649,0.0029105465,0.00033390464,0.0004143102,0.018179152],"category_scores_gemma":[0.0012273618,0.00009046611,0.0002636344,0.0017753865,0.00037052698,0.0011525276,0.0010119384,0.00098946,0.003281835],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018170827,0.00006764174,0.018826967,0.0015828825,0.00005725551,0.0015056266,0.00093282276,0.0027870676,0.0014268744,0.14386566,0.3538995,0.47486597],"study_design_scores_gemma":[0.000007290835,0.0000653761,0.036758002,0.00064966123,0.000023589686,0.0012316476,0.0006976574,0.0005989076,0.0012962419,0.0076352777,0.9510128,0.000023522358],"about_ca_topic_score_codex":0.008287404,"about_ca_topic_score_gemma":0.012390067,"teacher_disagreement_score":0.018179152,"about_ca_system_score_codex":0.0017418177,"about_ca_system_score_gemma":0.0016887689,"threshold_uncertainty_score":0.060815334},"labels":[],"label_agreement":null},{"id":"W6939670003","doi":"10.6084/m9.figshare.19565791.v1","title":"Additional file 1 of Towns and trails drive carnivore movement behaviour, resource selection, and connectivity","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Environment and Protected Areas; University of British Columbia","funders":"","keywords":"Carnivore; Resource (disambiguation); Movement (music); Habitat; Selection (genetic algorithm); Function (biology)","score_opus":0.045407687948656815,"score_gpt":0.2920948518311393,"score_spread":0.2466871638824825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939670003","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00030464793,0.000007693005,0.0001981658,0.000045180546,0.0000066072967,0.000038687744,0.9987923,0.000096068565,0.0005106255],"genre_scores_gemma":[0.02005059,0.000120371034,0.004040936,0.00030845765,0.000052751162,0.002472506,0.9641217,0.00051369454,0.008319074],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99963164,0.00008677356,0.000056807017,0.00010793534,0.00005673425,0.000060087437],"domain_scores_gemma":[0.98829937,0.0089318445,0.00074850227,0.00064426643,0.0010997173,0.00027641642],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010195678,0.0007981631,0.0009935139,0.0016810249,0.0008139861,0.0010727722,0.0016228696,0.0009125485,0.8054777],"category_scores_gemma":[0.019548321,0.0004751789,0.00074499426,0.0038933556,0.00020311085,0.0014346411,0.0007572897,0.0008374291,0.10929019],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015671375,0.00007858674,0.0061995685,0.0010656372,0.000052594103,0.000053390864,0.00009918589,0.0009814427,0.000033584998,0.0007285973,0.98358685,0.0069637503],"study_design_scores_gemma":[0.0071032085,0.0004591298,0.11289192,0.004142891,0.0005332713,0.0009219428,0.0016320918,0.010995718,0.0007622451,0.023454186,0.83682454,0.00027874732],"about_ca_topic_score_codex":0.027938532,"about_ca_topic_score_gemma":0.043374773,"teacher_disagreement_score":0.8054777,"about_ca_system_score_codex":0.00076222594,"about_ca_system_score_gemma":0.0014432899,"threshold_uncertainty_score":0.27746248},"labels":[],"label_agreement":null},{"id":"W6950452120","doi":"10.5281/zenodo.7853589","title":"What matters in reinforcement learning for tractography - Trained models","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Hyperparameter; Reinforcement; Training (meteorology); Artificial neural network","score_opus":0.12044598153088538,"score_gpt":0.33502085466450593,"score_spread":0.21457487313362056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6950452120","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04085846,0.0018002247,0.91336864,0.017568354,0.0012683158,0.0001795048,0.0023611796,0.008054778,0.014540472],"genre_scores_gemma":[0.71687067,0.0010453063,0.2498168,0.0058385828,0.0007401546,0.0004835838,0.0044115987,0.0031961368,0.01759723],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979804,0.0010350009,0.000075334945,0.00053476135,0.0002406829,0.00013388193],"domain_scores_gemma":[0.9912916,0.0059766904,0.00039652333,0.0013146156,0.0006599518,0.00036064596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046164887,0.0011154058,0.0011212346,0.00028707623,0.0004980806,0.0019927477,0.001806871,0.0018961664,0.013270616],"category_scores_gemma":[0.0383663,0.0005419765,0.0005812687,0.00034130237,0.0012733915,0.004960715,0.0012638447,0.003701892,0.0037828116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009925893,0.00033619953,0.010048867,0.0007040177,0.00031546288,0.00029331594,0.00029262304,0.51755875,0.0046059648,0.0772746,0.14413175,0.24344587],"study_design_scores_gemma":[0.00008590158,0.00007317189,0.00069967116,0.00012552358,0.000045884393,0.00007937887,0.000050433668,0.9008645,0.002505238,0.08820235,0.007234645,0.000033323875],"about_ca_topic_score_codex":0.0042054555,"about_ca_topic_score_gemma":0.0051429668,"teacher_disagreement_score":0.013270616,"about_ca_system_score_codex":0.0014347784,"about_ca_system_score_gemma":0.0017830185,"threshold_uncertainty_score":0.044394612},"labels":[],"label_agreement":null},{"id":"W6950617641","doi":"10.5683/sp3/aiahgw","title":"Scénario 69_3","year":2025,"lang":"fr","type":"dataset","venue":"Borealis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"3d simulation; 3d model; Frame (networking)","score_opus":0.0538308744748698,"score_gpt":0.3728492578674505,"score_spread":0.3190183833925807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6950617641","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002869012,0.00030409254,0.0012680024,0.00061484205,0.0002538531,0.00015600199,0.9788871,0.0017230972,0.013924037],"genre_scores_gemma":[0.008305609,0.00015239161,0.0017555762,0.00019612587,0.000040538762,0.00023102951,0.9853538,0.00014485404,0.0038200316],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99880266,0.00033908812,0.000116529096,0.0003071442,0.0002407728,0.00019378732],"domain_scores_gemma":[0.99845207,0.00050381746,0.00010482343,0.00038070124,0.00036327966,0.0001952355],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012465323,0.0019154515,0.00079818326,0.0018661034,0.0010460643,0.00175358,0.0020018332,0.0025608551,0.054037586],"category_scores_gemma":[0.0056692334,0.00034319283,0.0019694273,0.0021108375,0.00047577015,0.0013362386,0.0015010529,0.00185944,0.04133868],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033989918,0.00007150588,0.0022544442,0.00059674535,0.000061622995,0.00018153475,0.000057305937,0.0025802949,0.00017377693,0.0017691775,0.98265773,0.009256073],"study_design_scores_gemma":[0.00031199865,0.00008496064,0.006987482,0.00046092586,0.00003907718,0.00036576766,0.00035486545,0.0040472583,0.0007606187,0.0045131296,0.98201066,0.00006330005],"about_ca_topic_score_codex":0.041418564,"about_ca_topic_score_gemma":0.09840086,"teacher_disagreement_score":0.9459624,"about_ca_system_score_codex":0.002056572,"about_ca_system_score_gemma":0.0022889008,"threshold_uncertainty_score":0.18077374},"labels":[],"label_agreement":null},{"id":"W6957721200","doi":"10.60692/0rczc-zbf06","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Cognition; Executive functions; Dementia; Cognitive impairment; Executive dysfunction","score_opus":0.06329485058994336,"score_gpt":0.2947313742875131,"score_spread":0.23143652369756976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957721200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99982375,0.000028886894,0.000024721961,0.0000043611144,8.489722e-7,0.0000037162088,0.000027192993,5.254003e-7,0.000085915664],"genre_scores_gemma":[0.99967635,0.00003553841,0.000050592564,0.0000062068725,0.0000035171756,0.000005148501,0.000090441295,8.5359756e-7,0.00013129735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998728,0.000020755067,0.000022297369,0.000035236135,0.000017947119,0.000030884465],"domain_scores_gemma":[0.9994338,0.00006893806,0.00025374387,0.000038582635,0.00007029956,0.00013454507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026936125,0.0004328202,0.00028451116,0.00077577383,0.00047248992,0.00055887346,0.00019002102,0.00036276036,0.001110093],"category_scores_gemma":[0.0009887551,0.00027995784,0.0003022873,0.0006300303,0.0004778347,0.00046397946,0.00043512546,0.00024349063,0.00017816662],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000792686,0.000195724,0.9899401,0.000039563376,0.00007995475,0.00084232446,0.0021596195,0.000035226305,0.0032396582,0.000021575917,0.000048984086,0.0026046557],"study_design_scores_gemma":[0.000010071215,0.00023861244,0.9982256,0.0000029890396,0.00002270328,0.0006340501,0.00062647223,0.00006794801,0.000100516845,0.000020416797,0.000046861125,0.000003708967],"about_ca_topic_score_codex":0.0077287704,"about_ca_topic_score_gemma":0.0072960057,"teacher_disagreement_score":0.0077287704,"about_ca_system_score_codex":0.00022346815,"about_ca_system_score_gemma":0.00022064864,"threshold_uncertainty_score":0.015367568},"labels":[],"label_agreement":null},{"id":"W6957900148","doi":"10.60692/0qd81-van75","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Diffusion MRI; Core (optical fiber); Neuroimaging","score_opus":0.08639512390122667,"score_gpt":0.29637261351750305,"score_spread":0.20997748961627638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957900148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96950275,0.017013038,0.0017401995,0.00012831751,0.000022703427,0.00012082822,0.010971351,0.000052733565,0.00044824427],"genre_scores_gemma":[0.9865866,0.0031239875,0.0017681587,0.00009676997,0.000019609639,0.00020331566,0.0079374,0.000058664125,0.00020544212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959462,0.0014518879,0.0007894207,0.0012134587,0.000430466,0.00016853979],"domain_scores_gemma":[0.99445677,0.0018826737,0.0016778192,0.0010652426,0.0006261583,0.00029125914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070076897,0.0011000826,0.0016610547,0.0031713347,0.0008547682,0.0013091193,0.0007375491,0.0005444662,0.0013995931],"category_scores_gemma":[0.010139156,0.0006431993,0.002919201,0.0046942467,0.0005596554,0.00046753968,0.001975071,0.00038195294,0.0003192103],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0038240012,0.00010140101,0.9067348,0.0022063565,0.049565013,0.000347689,0.0014505534,0.0006628339,0.0049431985,0.00022725087,0.0020863104,0.027850665],"study_design_scores_gemma":[0.0002471999,0.0002643485,0.9758099,0.00022958673,0.019714119,0.0003336365,0.00034218113,0.00016181845,0.0005483528,0.00022622163,0.0020870895,0.00003542294],"about_ca_topic_score_codex":0.015447306,"about_ca_topic_score_gemma":0.019892257,"teacher_disagreement_score":0.015447306,"about_ca_system_score_codex":0.00063691684,"about_ca_system_score_gemma":0.00093728915,"threshold_uncertainty_score":0.03706062},"labels":[],"label_agreement":null},{"id":"W6957936600","doi":"10.60692/gnma5-j5308","title":"Subject–Motion Correction in HARDI Acquisitions: Choices and Consequences","year":2014,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital","funders":"","keywords":"Motion (physics); Orientation (vector space); Noise (video); Match moving; Set (abstract data type); Interpolation (computer graphics); Software; Transformation (genetics)","score_opus":0.054041223314886554,"score_gpt":0.2810328532407359,"score_spread":0.22699162992584934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957936600","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57762945,0.010197626,0.39604935,0.002344268,0.0004838966,0.0036982698,0.0015597732,0.0012937118,0.006743749],"genre_scores_gemma":[0.6887073,0.002784877,0.2978257,0.0016323105,0.00023971543,0.0041262023,0.0016752305,0.0014369003,0.0015717264],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.8881663,0.07126422,0.011569093,0.009256452,0.018810024,0.0009340175],"domain_scores_gemma":[0.7741836,0.17818566,0.017107025,0.019494131,0.009664238,0.0013653979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.11466098,0.0020408798,0.0013125982,0.0014688623,0.0014002188,0.0028087236,0.0018417991,0.0028987746,0.0018535922],"category_scores_gemma":[0.2406406,0.0008626345,0.0012271625,0.0019246974,0.00450164,0.003171891,0.0031392972,0.0017358533,0.00093150686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.032486927,0.0025186825,0.120950446,0.007970897,0.005462231,0.0016126549,0.004482691,0.0625527,0.1106331,0.025990414,0.007852529,0.61748683],"study_design_scores_gemma":[0.004532921,0.029456647,0.2706237,0.006413803,0.0057116514,0.007668477,0.0032139563,0.15329528,0.29509383,0.15102245,0.07085614,0.0021111658],"about_ca_topic_score_codex":0.00059462787,"about_ca_topic_score_gemma":0.0009633578,"teacher_disagreement_score":0.11466098,"about_ca_system_score_codex":0.0007813359,"about_ca_system_score_gemma":0.00083051895,"threshold_uncertainty_score":0.6063925},"labels":[],"label_agreement":null},{"id":"W6958044850","doi":"10.60692/06rtj-2m915","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Segmentation; White matter; Bundle; Diffusion MRI; Fiber bundle","score_opus":0.07414940868802887,"score_gpt":0.27084432861359076,"score_spread":0.19669491992556187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958044850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9217205,0.0013221701,0.0723119,0.0005324475,0.00025845156,0.00026347468,0.0012174055,0.00068230147,0.001691325],"genre_scores_gemma":[0.980719,0.000116345116,0.016144881,0.00016399547,0.00007034086,0.00022718131,0.0019629225,0.00033286656,0.00026244792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9581354,0.01829836,0.0048323637,0.011365498,0.0064453953,0.00092301756],"domain_scores_gemma":[0.84620214,0.09385514,0.01838534,0.022548242,0.017438086,0.0015711057],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04789079,0.0007111246,0.0010231468,0.0022055695,0.0014553359,0.0024431415,0.0012058072,0.0012854064,0.00081655796],"category_scores_gemma":[0.14108594,0.00041549004,0.0012140283,0.0017853208,0.0024046826,0.0017745849,0.0028605205,0.0012803992,0.0004587769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004094856,0.000419395,0.7460354,0.0010961444,0.0041800067,0.00062468904,0.016403435,0.020125149,0.028418107,0.0030724104,0.008753501,0.16677685],"study_design_scores_gemma":[0.00022783501,0.0012297706,0.8633124,0.00063268794,0.0013182238,0.0016623831,0.006650852,0.066893585,0.023279985,0.022547884,0.011923303,0.00032103024],"about_ca_topic_score_codex":0.0016448542,"about_ca_topic_score_gemma":0.0021270774,"teacher_disagreement_score":0.9521092,"about_ca_system_score_codex":0.0007933979,"about_ca_system_score_gemma":0.0007238921,"threshold_uncertainty_score":0.2532738},"labels":[],"label_agreement":null},{"id":"W6958395042","doi":"10.6084/m9.figshare.27274189.v1","title":"Additional file 1 of High-cost users after sepsis: a population-based observational cohort study","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Ottawa; Trillium Health Centre; University of British Columbia; Western University; Institute for Clinical Evaluative Sciences; McMaster University; University of Toronto; University Health Network","funders":"","keywords":"Observational study; Cohort study; Cohort; Data collection; Research design","score_opus":0.09433529156298764,"score_gpt":0.35077160987754114,"score_spread":0.2564363183145535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958395042","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016864364,0.00006185301,0.00025925072,0.00010315706,0.000029679777,0.00019181785,0.9964496,0.00006703736,0.0011511233],"genre_scores_gemma":[0.050274774,0.00047271585,0.0044143917,0.0014778211,0.00023826816,0.008775173,0.91566694,0.00040450247,0.018275484],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9988422,0.0002520633,0.00029045224,0.00029628232,0.00013886963,0.00018020885],"domain_scores_gemma":[0.98413795,0.009609892,0.0024646902,0.0012119228,0.0018132484,0.0007622537],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012110554,0.0010407949,0.001505714,0.002888713,0.001261932,0.0013150909,0.001665154,0.0015511238,0.6880937],"category_scores_gemma":[0.0255323,0.00076204335,0.001254193,0.005861656,0.00032157387,0.0018251123,0.0012336576,0.0011699543,0.077130914],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084204314,0.0003149148,0.03493022,0.0033197398,0.00024307014,0.0002069856,0.00017159367,0.0004901116,0.00009022426,0.0012465056,0.9469104,0.011234253],"study_design_scores_gemma":[0.01487353,0.0011603435,0.49085793,0.012020343,0.0011916999,0.0036386775,0.0029866619,0.004545286,0.00072452094,0.01763141,0.44976258,0.0006070066],"about_ca_topic_score_codex":0.014119686,"about_ca_topic_score_gemma":0.015608722,"teacher_disagreement_score":0.6880937,"about_ca_system_score_codex":0.0009808723,"about_ca_system_score_gemma":0.0018659587,"threshold_uncertainty_score":0.4448964},"labels":[],"label_agreement":null},{"id":"W6976445412","doi":"10.60692/wn0sf-1h128","title":"High resolution diffusion imaging in the unfixed post-mortem infant brain at 7T","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Context (archaeology); Diffusion MRI; Tractography; Diffusion imaging; High resolution; Brain tissue; Human brain","score_opus":0.039260283882608014,"score_gpt":0.2790321893806808,"score_spread":0.23977190549807278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976445412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98126996,0.0011823811,0.013637069,0.00032382688,0.000034906527,0.000034646513,0.0007337322,0.00021014303,0.0025734007],"genre_scores_gemma":[0.9799653,0.0008311817,0.01597998,0.000115547315,0.000032357268,0.000044801,0.0008906238,0.00010054273,0.002039646],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999262,0.000015614305,0.0000047857857,0.000016746593,0.000022260929,0.000014387754],"domain_scores_gemma":[0.9997881,0.000044126784,0.00003237628,0.000023805045,0.00008798083,0.000023653742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040177852,0.00021459536,0.0002788898,0.0005626112,0.00038781427,0.0004065285,0.00028291068,0.0005080706,0.0025459114],"category_scores_gemma":[0.0006136158,0.00018508204,0.0001240063,0.00031595066,0.00028684916,0.00030379457,0.00028259202,0.00050170766,0.00041699427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000585642,0.00006725054,0.009402609,0.00018808663,0.000058891703,0.0044142334,0.0005387565,0.0009555176,0.9605565,0.00084300205,0.0011856871,0.021203972],"study_design_scores_gemma":[0.000087375025,0.0022508607,0.387892,0.00020854054,0.00041881995,0.02624479,0.0011755733,0.010371396,0.5545031,0.0024459532,0.0142808985,0.00012069189],"about_ca_topic_score_codex":0.0022288137,"about_ca_topic_score_gemma":0.004347746,"teacher_disagreement_score":0.0025459114,"about_ca_system_score_codex":0.00016468359,"about_ca_system_score_gemma":0.00017497975,"threshold_uncertainty_score":0.008516967},"labels":[],"label_agreement":null},{"id":"W6976483059","doi":"10.60692/sdwb0-b6g13","title":"High resolution diffusion imaging in the unfixed post-mortem infant brain at 7T","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Context (archaeology); Diffusion MRI; Tractography; Diffusion imaging; High resolution; Brain tissue; Human brain","score_opus":0.039260283882608014,"score_gpt":0.2790321893806808,"score_spread":0.23977190549807278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976483059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98126996,0.0011823811,0.013637069,0.00032382688,0.000034906527,0.000034646513,0.0007337322,0.00021014303,0.0025734007],"genre_scores_gemma":[0.9799653,0.0008311817,0.01597998,0.000115547315,0.000032357268,0.000044801,0.0008906238,0.00010054273,0.002039646],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999262,0.000015614305,0.0000047857857,0.000016746593,0.000022260929,0.000014387754],"domain_scores_gemma":[0.9997881,0.000044126784,0.00003237628,0.000023805045,0.00008798083,0.000023653742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040177852,0.00021459536,0.0002788898,0.0005626112,0.00038781427,0.0004065285,0.00028291068,0.0005080706,0.0025459114],"category_scores_gemma":[0.0006136158,0.00018508204,0.0001240063,0.00031595066,0.00028684916,0.00030379457,0.00028259202,0.00050170766,0.00041699427],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000585642,0.00006725054,0.009402609,0.00018808663,0.000058891703,0.0044142334,0.0005387565,0.0009555176,0.9605565,0.00084300205,0.0011856871,0.021203972],"study_design_scores_gemma":[0.000087375025,0.0022508607,0.387892,0.00020854054,0.00041881995,0.02624479,0.0011755733,0.010371396,0.5545031,0.0024459532,0.0142808985,0.00012069189],"about_ca_topic_score_codex":0.0022288137,"about_ca_topic_score_gemma":0.004347746,"teacher_disagreement_score":0.0025459114,"about_ca_system_score_codex":0.00016468359,"about_ca_system_score_gemma":0.00017497975,"threshold_uncertainty_score":0.008516967},"labels":[],"label_agreement":null},{"id":"W6976546751","doi":"10.60692/9bvr8-p7s07","title":"Identification and Classification of Alzheimer's Disease Patients Using Novel Fractional Motion Model","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hurst exponent; Receiver operating characteristic; Correlation; Pattern recognition (psychology); Diffusion MRI; Fractional Brownian motion; Detrended fluctuation analysis; Exponent","score_opus":0.17790635687034637,"score_gpt":0.31222454646661385,"score_spread":0.13431818959626748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976546751","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91322535,0.0009401196,0.08440208,0.0002053029,0.00004184049,0.00007288459,0.00026556212,0.00022643164,0.0006204136],"genre_scores_gemma":[0.9753699,0.0002751221,0.023561986,0.000027348515,0.000035068566,0.000039987426,0.00037546034,0.00001052646,0.00030453413],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978703,0.000049366132,0.000029872825,0.0000660321,0.00003564588,0.000031984313],"domain_scores_gemma":[0.99961853,0.00014489233,0.0000824088,0.000030513631,0.00008868501,0.0000349502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073136576,0.00054098683,0.000719232,0.0017261598,0.0002515254,0.0006431598,0.00029192647,0.0007070094,0.0004128038],"category_scores_gemma":[0.0017680521,0.00012546689,0.0006594544,0.00041812452,0.00018378528,0.0004941977,0.0003068071,0.00028318324,0.00018711624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018370051,0.00050291047,0.6080725,0.00019891396,0.0004677678,0.001968499,0.0007742649,0.05256016,0.03948666,0.0015543288,0.0027599286,0.2898171],"study_design_scores_gemma":[0.0000829308,0.00042744604,0.17636156,0.000046342884,0.00021597234,0.0018432573,0.00032320092,0.8120078,0.0041772947,0.0030820363,0.0013625147,0.00006958862],"about_ca_topic_score_codex":0.002374441,"about_ca_topic_score_gemma":0.0016608443,"teacher_disagreement_score":0.002374441,"about_ca_system_score_codex":0.00023120998,"about_ca_system_score_gemma":0.00033841454,"threshold_uncertainty_score":0.004721284},"labels":[],"label_agreement":null},{"id":"W6976597944","doi":"10.60692/nqdvd-9np21","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Segmentation; White matter; Bundle; Diffusion MRI; Fiber bundle","score_opus":0.07414940868802887,"score_gpt":0.27084432861359076,"score_spread":0.19669491992556187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976597944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9217205,0.0013221701,0.0723119,0.0005324475,0.00025845156,0.00026347468,0.0012174055,0.00068230147,0.001691325],"genre_scores_gemma":[0.980719,0.000116345116,0.016144881,0.00016399547,0.00007034086,0.00022718131,0.0019629225,0.00033286656,0.00026244792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9581354,0.01829836,0.0048323637,0.011365498,0.0064453953,0.00092301756],"domain_scores_gemma":[0.84620214,0.09385514,0.01838534,0.022548242,0.017438086,0.0015711057],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04789079,0.0007111246,0.0010231468,0.0022055695,0.0014553359,0.0024431415,0.0012058072,0.0012854064,0.00081655796],"category_scores_gemma":[0.14108594,0.00041549004,0.0012140283,0.0017853208,0.0024046826,0.0017745849,0.0028605205,0.0012803992,0.0004587769],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004094856,0.000419395,0.7460354,0.0010961444,0.0041800067,0.00062468904,0.016403435,0.020125149,0.028418107,0.0030724104,0.008753501,0.16677685],"study_design_scores_gemma":[0.00022783501,0.0012297706,0.8633124,0.00063268794,0.0013182238,0.0016623831,0.006650852,0.066893585,0.023279985,0.022547884,0.011923303,0.00032103024],"about_ca_topic_score_codex":0.0016448542,"about_ca_topic_score_gemma":0.0021270774,"teacher_disagreement_score":0.9521092,"about_ca_system_score_codex":0.0007933979,"about_ca_system_score_gemma":0.0007238921,"threshold_uncertainty_score":0.2532738},"labels":[],"label_agreement":null},{"id":"W6977136271","doi":"10.6084/m9.figshare.13357659.v1","title":"Additional file 4 of The effect of a pharmacist consultation on pregnant women’s quality of life with a special focus on nausea and vomiting: an intervention study","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Intervention (counseling); Quality of life (healthcare); Pharmacist; Focus group; Nausea; Baseline (sea); Focus (optics)","score_opus":0.10438433448930275,"score_gpt":0.37825961261674257,"score_spread":0.27387527812743984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977136271","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020978882,0.0000716685,0.0001939948,0.00044046898,0.000060790167,0.0016847448,0.99170214,0.00012347862,0.0036249047],"genre_scores_gemma":[0.117592625,0.0007280668,0.0077742743,0.0031379426,0.00052404933,0.07576767,0.7351553,0.0005686509,0.058751326],"study_design_codex":"not_applicable","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.99888283,0.00039909262,0.00022936941,0.0001377203,0.00018890062,0.00016213681],"domain_scores_gemma":[0.97212493,0.019953756,0.0029244595,0.0009891719,0.0032129842,0.00079468143],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0023252333,0.00070977624,0.0013476324,0.0012251892,0.0010688391,0.00083336723,0.0013862797,0.0010793174,0.7921316],"category_scores_gemma":[0.034280755,0.0004026612,0.001524925,0.0018039072,0.0001808923,0.001216074,0.0007280636,0.0010341726,0.046735346],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0067064506,0.0012309497,0.007062055,0.0075727412,0.00028365597,0.0001047757,0.00015582588,0.00049325614,0.00006156845,0.00087465474,0.9514561,0.02399796],"study_design_scores_gemma":[0.17453559,0.008156706,0.27475747,0.020069951,0.0026607024,0.0008280807,0.0015818522,0.005378905,0.0014292868,0.011180548,0.499007,0.0004138702],"about_ca_topic_score_codex":0.012918697,"about_ca_topic_score_gemma":0.017944837,"teacher_disagreement_score":0.7921316,"about_ca_system_score_codex":0.001453716,"about_ca_system_score_gemma":0.0023053412,"threshold_uncertainty_score":0.296499},"labels":[],"label_agreement":null},{"id":"W6980568879","doi":"","title":"Clifton wind farm owners enter partnership with Canadian energy firm [Bangor Daily News, Maine]","year":2016,"lang":"en","type":"other","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"General partnership; Energy (signal processing); Wind power; Renewable energy; Government (linguistics); Work (physics)","score_opus":0.03869472779378222,"score_gpt":0.3163243483050506,"score_spread":0.2776296205112684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6980568879","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016625515,0.0041845054,0.00041801622,0.039789975,0.0071453573,0.00015870479,0.008358153,0.001113863,0.9371688],"genre_scores_gemma":[0.0012709284,0.0007862831,0.000116328796,0.0015131929,0.00029631215,0.0000132765335,0.0009546878,0.00011466703,0.9949344],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989998,0.00002782367,0.000027148773,0.000066518725,0.00064754963,0.00023128299],"domain_scores_gemma":[0.9977087,0.00021045405,0.000074095755,0.00010427952,0.001250354,0.0006521344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011833209,0.0008369396,0.00050880015,0.0014325762,0.003774262,0.0057197507,0.0008444854,0.0053001447,0.2596262],"category_scores_gemma":[0.0030865446,0.00049350876,0.0006129777,0.0013921347,0.0007985301,0.0015586999,0.001321308,0.0041563446,0.10645461],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001720668,0.000009410041,0.00011232765,0.000017412462,0.0000010972443,0.000043373708,0.000014464998,0.000016105032,0.00006512705,0.0008621303,0.98822254,0.010618694],"study_design_scores_gemma":[0.000007721036,0.00000806512,0.0015337808,0.000032665328,0.0000022538172,0.000021708105,0.000055605775,0.000050015926,0.00010036559,0.00023756997,0.99794096,0.000009258548],"about_ca_topic_score_codex":0.3912027,"about_ca_topic_score_gemma":0.80135244,"teacher_disagreement_score":0.6087973,"about_ca_system_score_codex":0.005017616,"about_ca_system_score_gemma":0.012940271,"threshold_uncertainty_score":0.86853623},"labels":[],"label_agreement":null},{"id":"W6982192183","doi":"","title":"Haydn et l'opera buffa, analyse dramaturgique et stylistique de \"La fedelta premiata\" (French text, Joseph Haydn, Austria)","year":2000,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subject (documents); Context (archaeology); Feature (linguistics); Identity (music)","score_opus":0.007788213969374981,"score_gpt":0.2318637448835944,"score_spread":0.22407553091421942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6982192183","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013173055,0.1859643,0.0032705143,0.06532096,0.004585051,0.00003240064,0.0009107559,0.00018196038,0.72656107],"genre_scores_gemma":[0.20883991,0.044288643,0.002045285,0.0043033403,0.003206063,0.00006938999,0.00029393932,0.00019317564,0.73676026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99979264,0.00007391366,0.000008977029,0.000032944637,0.000059560152,0.000031962725],"domain_scores_gemma":[0.99987245,0.000072132745,0.000018038467,0.000007134349,0.000016140797,0.00001416231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036980002,0.0004785401,0.00018659618,0.0014595413,0.0029142976,0.0038200081,0.00034303582,0.0015554655,0.016879426],"category_scores_gemma":[0.0011873121,0.00019169798,0.00011283783,0.0013112507,0.002518496,0.002274362,0.00089982664,0.0018524721,0.0021694389],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006161131,0.00002099158,0.0004102956,0.00012493538,0.000004563409,0.00016995303,0.009679168,0.00013690605,0.00041101463,0.48836464,0.41716644,0.08344949],"study_design_scores_gemma":[0.000005381256,0.000003984506,0.0015800479,0.00006518294,0.0000018340957,0.00008821312,0.0012718999,0.00004802513,0.00017053739,0.008035482,0.9887255,0.000003934721],"about_ca_topic_score_codex":0.09127837,"about_ca_topic_score_gemma":0.16024429,"teacher_disagreement_score":0.09127837,"about_ca_system_score_codex":0.0049096486,"about_ca_system_score_gemma":0.0018149,"threshold_uncertainty_score":0.18149418},"labels":[],"label_agreement":null},{"id":"W6983403260","doi":"","title":"Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware [accepted manuscript]","year":2018,"lang":"en","type":"article","venue":"Research Bank (Australian Catholic University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Tractography; Siemens; Variance (accounting); Data acquisition; Protocol (science); Diffusion MRI; Optic radiation; Loop (graph theory); Epilepsy surgery","score_opus":0.26923883609895466,"score_gpt":0.4482483460042289,"score_spread":0.17900950990527426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6983403260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6832426,0.004368711,0.30090588,0.00052605325,0.00035311666,0.0008157048,0.0007016775,0.0015954392,0.007490906],"genre_scores_gemma":[0.8145988,0.0015044523,0.1789078,0.00018389049,0.00014535051,0.00058684114,0.0007959603,0.00075941544,0.0025174157],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979875,0.0009721084,0.00018909901,0.0003827782,0.0004112211,0.000057302594],"domain_scores_gemma":[0.9921193,0.0042142347,0.0009586977,0.0014407762,0.0011556434,0.00011132781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058761616,0.000615234,0.00036629857,0.00039162417,0.00033504015,0.0013204023,0.0008123836,0.00063783646,0.0058357213],"category_scores_gemma":[0.019437607,0.00041104812,0.00030765624,0.0004978931,0.00071357057,0.0009822223,0.00044101532,0.0004978231,0.0014493852],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042989957,0.00041898325,0.062136278,0.0021021229,0.0006678026,0.0007668902,0.0010516224,0.006689605,0.37180063,0.0027828426,0.004577093,0.54270726],"study_design_scores_gemma":[0.00054144097,0.0054576118,0.53704643,0.0009919027,0.0012673265,0.010375377,0.00048983545,0.07776519,0.3200657,0.012984927,0.03264197,0.0003722501],"about_ca_topic_score_codex":0.00096425635,"about_ca_topic_score_gemma":0.002006376,"teacher_disagreement_score":0.0058761616,"about_ca_system_score_codex":0.00036897813,"about_ca_system_score_gemma":0.00082005945,"threshold_uncertainty_score":0.03107655},"labels":[],"label_agreement":null},{"id":"W6990497220","doi":"","title":"Diffusion imaging of white matter fibre tracts","year":2004,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Diffusion MRI; Imaging phantom; White matter; Tractography; Magnetic resonance imaging; Tracking (education); Partial volume; Diffusion; Fiber tract; Point spread function","score_opus":0.02391838742505104,"score_gpt":0.2983301245031977,"score_spread":0.27441173707814664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6990497220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58213186,0.07546993,0.22664689,0.010604158,0.0014223179,0.0006740178,0.0068949284,0.0017019087,0.09445395],"genre_scores_gemma":[0.72357225,0.04300971,0.12754136,0.00066060794,0.00041004294,0.00029259027,0.0020196363,0.0003479246,0.102145806],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998708,0.000023893308,0.000009493901,0.000049695365,0.00002573244,0.000020317011],"domain_scores_gemma":[0.99980086,0.000041691645,0.00003909835,0.000019777568,0.00006839618,0.000030141664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051196915,0.0005211681,0.00030445014,0.0019449474,0.0005683849,0.0008810842,0.0002930167,0.00067773985,0.009699893],"category_scores_gemma":[0.0012377045,0.00025466722,0.00026723277,0.00086125795,0.0004297114,0.0011167001,0.0004511981,0.000553311,0.0013108217],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079947687,0.00015600926,0.0146280695,0.002096874,0.00024464712,0.0014693142,0.00083074544,0.0013028493,0.42494696,0.0136022745,0.01908056,0.5208422],"study_design_scores_gemma":[0.00023728391,0.0013505674,0.3267035,0.0015190328,0.0004891515,0.015828548,0.0013217694,0.017626831,0.40062392,0.053226024,0.1808068,0.00026666172],"about_ca_topic_score_codex":0.009686592,"about_ca_topic_score_gemma":0.022166379,"teacher_disagreement_score":0.009699893,"about_ca_system_score_codex":0.0006440523,"about_ca_system_score_gemma":0.0009559924,"threshold_uncertainty_score":0.032449365},"labels":[],"label_agreement":null},{"id":"W6991361011","doi":"","title":"Guerre et paix : La valse à deux temps de l'atome au Canada","year":2021,"lang":"fr","type":"other","venue":"R-libre (Université Téluq)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"First world war; Context (archaeology); Portrait; Object (grammar)","score_opus":0.022795062552245574,"score_gpt":0.277538736026601,"score_spread":0.25474367347435545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6991361011","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12667589,0.025941923,0.0025147654,0.081325874,0.0018834615,0.00006186688,0.0009426562,0.00024732735,0.76040626],"genre_scores_gemma":[0.41132522,0.011163026,0.0021375576,0.0054155192,0.000193882,0.000033893786,0.00024280527,0.00022806713,0.56926006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99924386,0.00011763552,0.000011251477,0.00013269566,0.00024155664,0.0002530203],"domain_scores_gemma":[0.99960214,0.00006584509,0.00002891571,0.000026357447,0.0001310703,0.00014567471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005394719,0.00038784771,0.00030252282,0.0009552349,0.018604886,0.0060472237,0.0005743804,0.0019347997,0.031723548],"category_scores_gemma":[0.0014825523,0.00026764482,0.0002742138,0.0015637031,0.010935925,0.0022027683,0.00272947,0.0022506607,0.0023916685],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022409503,0.000035676778,0.0087839775,0.0002318228,0.00003109117,0.00169241,0.11717685,0.00025632355,0.0019385664,0.5466808,0.19437853,0.12856993],"study_design_scores_gemma":[0.000007890504,0.000016305485,0.008165731,0.0002116981,0.0000131240595,0.00031039005,0.037352078,0.00007927036,0.0005075361,0.007529833,0.94577277,0.000033352575],"about_ca_topic_score_codex":0.9457124,"about_ca_topic_score_gemma":0.9819219,"teacher_disagreement_score":0.054287612,"about_ca_system_score_codex":0.033949375,"about_ca_system_score_gemma":0.03636602,"threshold_uncertainty_score":0.24632108},"labels":[],"label_agreement":null},{"id":"W6996142048","doi":"","title":"Reduced field of view diffusion imaging at 7T using the “blOCh” pulse design package","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"iNano Medical (Canada)","funders":"","keywords":"Field (mathematics); Pulse (music); Diffusion; Electromagnetic field; Reliability (semiconductor)","score_opus":0.09656309656697007,"score_gpt":0.3796296811499766,"score_spread":0.2830665845830065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6996142048","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005309257,0.000092244074,0.98901016,0.00021184527,0.000044435597,0.000097521566,0.00044789663,0.00265706,0.0021296495],"genre_scores_gemma":[0.030674089,0.00015128162,0.96172214,0.00020904197,0.000033592354,0.0004602864,0.0007113113,0.0014029498,0.00463537],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99971455,0.00010188002,0.00001146617,0.000035043475,0.00010708935,0.000029965327],"domain_scores_gemma":[0.9994362,0.00019969257,0.000047534566,0.00008109077,0.00019668626,0.00003879196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010473008,0.0008078603,0.0007086327,0.00046186376,0.00038809198,0.0010630839,0.0013849416,0.0015185246,0.017161356],"category_scores_gemma":[0.001494621,0.00072432787,0.0005595034,0.00064633234,0.00032358454,0.00074531947,0.00056489836,0.0018050985,0.006505795],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023722725,0.0003189489,0.0012738899,0.0013410551,0.00050686294,0.0009938072,0.00047243625,0.10076022,0.4135154,0.101766706,0.051234934,0.32544345],"study_design_scores_gemma":[0.0002627389,0.00068628823,0.0019920445,0.000096746895,0.00018588969,0.0010708018,0.00005622424,0.6536025,0.21794611,0.02176889,0.10212803,0.00020380526],"about_ca_topic_score_codex":0.0009591471,"about_ca_topic_score_gemma":0.0021659166,"teacher_disagreement_score":0.017161356,"about_ca_system_score_codex":0.00043659296,"about_ca_system_score_gemma":0.0010175612,"threshold_uncertainty_score":0.05741048},"labels":[],"label_agreement":null},{"id":"W7006586430","doi":"","title":"Upper and extra-motoneuron involvement in early motoneuron disease: a diffusion tensor imaging study","year":2011,"lang":"en","type":"article","venue":"EUR Research Repository (Erasmus University Rotterdam)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Pediatric Oncology Group","funders":"","keywords":"Diffusion MRI; Diffusion; Tensor (intrinsic definition); Intensity (physics); Noise (video)","score_opus":0.1186860102379764,"score_gpt":0.3415962067385941,"score_spread":0.2229101965006177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7006586430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978382,0.0005660703,0.00028825225,0.00008088387,0.000008931312,0.000022582333,0.00007030174,0.0000052475534,0.0011195923],"genre_scores_gemma":[0.9983911,0.00041490863,0.0003356919,0.000062217274,0.00004635255,0.000013016673,0.000110617344,0.000005326597,0.00062076305],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997539,0.00004004077,0.00004572878,0.000055202956,0.000035615238,0.0000694474],"domain_scores_gemma":[0.99928004,0.00019145037,0.0001453974,0.00008706378,0.00010954468,0.00018641677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011105256,0.0010603579,0.0008544181,0.0015497037,0.0008175572,0.0007223502,0.0007188442,0.0013705649,0.0038817134],"category_scores_gemma":[0.0017026309,0.0005712054,0.0004974111,0.00082257215,0.0010079166,0.0012128928,0.0009327013,0.0006360405,0.0010701754],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006486106,0.0015948031,0.60081494,0.00042891334,0.0004156434,0.26934674,0.0025590896,0.00042919855,0.09285886,0.0006766252,0.00068745844,0.023701731],"study_design_scores_gemma":[0.00019970509,0.0016725049,0.86046404,0.00010122723,0.00035111426,0.13014205,0.00072702626,0.0007781628,0.0041493312,0.00044897193,0.00091954967,0.000046302706],"about_ca_topic_score_codex":0.0024281808,"about_ca_topic_score_gemma":0.0031060393,"teacher_disagreement_score":0.0038817134,"about_ca_system_score_codex":0.00043999474,"about_ca_system_score_gemma":0.0005060201,"threshold_uncertainty_score":0.012985647},"labels":[],"label_agreement":null},{"id":"W7014465020","doi":"","title":"Probing tissue microstructure using oscillating spin echo gradients","year":2018,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Manitoba; University of Winnipeg","keywords":"Axon; Spin echo; Diffusion; Monte Carlo method; Gradient echo; Cylinder; Planar; Range (aeronautics); Measure (data warehouse)","score_opus":0.039345015143173095,"score_gpt":0.30488886098625095,"score_spread":0.2655438458430779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7014465020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89963937,0.0008798713,0.09567468,0.00017319349,0.00004567649,0.000059606897,0.00021891514,0.0003989078,0.0029097944],"genre_scores_gemma":[0.94882065,0.00063830905,0.049064316,0.00009656648,0.0000113604265,0.000060376362,0.00023288386,0.00004758609,0.0010279212],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998921,0.000015455622,0.000004864,0.000026240501,0.000044747838,0.000016607906],"domain_scores_gemma":[0.999767,0.000108252534,0.00002998145,0.000023983695,0.00005607959,0.000014621828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002829155,0.00021522319,0.00015324177,0.00020658098,0.00017910582,0.00030973667,0.00037097692,0.00031029174,0.00048401835],"category_scores_gemma":[0.00062909693,0.00022717807,0.00013240977,0.00028299753,0.00030352763,0.0004386312,0.0002431313,0.00036594569,0.00016336217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091635506,0.000035557125,0.0013697098,0.00008598677,0.0000142089075,0.00012996163,0.00011530071,0.024748702,0.96191955,0.0015563422,0.00031322532,0.009619823],"study_design_scores_gemma":[0.00004818938,0.00042044738,0.006875758,0.000028034514,0.000033444237,0.00022196307,0.00011025369,0.47845235,0.5074992,0.002435818,0.003813203,0.000061273495],"about_ca_topic_score_codex":0.0015395501,"about_ca_topic_score_gemma":0.0017653089,"teacher_disagreement_score":0.0015395501,"about_ca_system_score_codex":0.0003530939,"about_ca_system_score_gemma":0.00023982194,"threshold_uncertainty_score":0.0030611157},"labels":[],"label_agreement":null},{"id":"W7027949612","doi":"","title":"Diffusion of personal health information : self-determining and empowering practices for Manitoba Inuit","year":2012,"lang":"en","type":"other","venue":"VIUSpace (Vancouver Island University Library)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Relevance (law); Health information; Health care; Set (abstract data type); Space (punctuation); HRHIS; Information system; Personally identifiable information","score_opus":0.022553993890534942,"score_gpt":0.274778308119597,"score_spread":0.2522243142290621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7027949612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97347844,0.00037720983,0.0008424636,0.0056130104,0.000023211702,0.00008133226,0.000030975407,0.000025269605,0.019528076],"genre_scores_gemma":[0.99119335,0.00057965703,0.0011667939,0.0005450102,0.000005498298,0.000038689876,0.000021727865,0.00001650565,0.006432676],"study_design_codex":"qualitative","study_design_gemma":"qualitative","domain_scores_codex":[0.9987155,0.00062271184,0.00005936636,0.00010196183,0.00023203118,0.00026834328],"domain_scores_gemma":[0.997607,0.001095336,0.00026243163,0.000099104196,0.00044738594,0.00048867636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025348957,0.00020894264,0.000155966,0.000965663,0.008536425,0.0039072945,0.0008871602,0.00049350807,0.0039190208],"category_scores_gemma":[0.006562197,0.00027921225,0.00014994974,0.0011773979,0.0030057188,0.0021436266,0.004105897,0.0009516266,0.00023279534],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015608657,0.00008106438,0.022673557,0.00006956258,0.0000033976064,0.0010509928,0.9439756,0.00002817299,0.001149942,0.003933543,0.00084316824,0.026175363],"study_design_scores_gemma":[0.000004576464,0.0000738854,0.02513276,0.00020838059,0.000014526286,0.0006169704,0.9299046,0.00039770512,0.0007832425,0.0011578046,0.04167492,0.00003053487],"about_ca_topic_score_codex":0.5432689,"about_ca_topic_score_gemma":0.7333341,"teacher_disagreement_score":0.45673108,"about_ca_system_score_codex":0.009348283,"about_ca_system_score_gemma":0.0154468585,"threshold_uncertainty_score":0.9188417},"labels":[],"label_agreement":null},{"id":"W7029452335","doi":"","title":"Investigating VTA, SNc and dopamine projections in the brain using MRI","year":2018,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Dopamine; Dopaminergic; Neurotransmitter; Neuron; Neuroimaging; Central nervous system; Brain mapping","score_opus":0.2442081936304015,"score_gpt":0.4090928660723926,"score_spread":0.1648846724419911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7029452335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8819703,0.0068107694,0.09938554,0.0008664509,0.00005696344,0.00014647019,0.00056330254,0.00023727007,0.009962871],"genre_scores_gemma":[0.910209,0.007407829,0.07643472,0.00038102575,0.000071164846,0.00016327745,0.00028881832,0.00007654274,0.0049676625],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99994576,0.000011189544,0.0000037049765,0.000012654408,0.000013580706,0.000013137061],"domain_scores_gemma":[0.999895,0.000028495693,0.000023747838,0.000008292656,0.000029286768,0.000015218239],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033275396,0.0002592309,0.00015928068,0.0010290664,0.0002746866,0.00042428434,0.00023937513,0.0004364076,0.0015487788],"category_scores_gemma":[0.00040718983,0.00028110362,0.00014668409,0.00035513207,0.00030079324,0.0008629794,0.0002914976,0.0005148351,0.00030480648],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023824154,0.00008371675,0.010343483,0.0003428585,0.000067420384,0.0009500602,0.00020897148,0.00091474806,0.92748064,0.0018745943,0.00042350075,0.057071757],"study_design_scores_gemma":[0.00008700063,0.001928031,0.3453839,0.00043334073,0.0004206298,0.026495548,0.0018638448,0.028844511,0.56549007,0.01307023,0.015869794,0.000113016526],"about_ca_topic_score_codex":0.0018889434,"about_ca_topic_score_gemma":0.003830025,"teacher_disagreement_score":0.0018889434,"about_ca_system_score_codex":0.00021464814,"about_ca_system_score_gemma":0.00032278837,"threshold_uncertainty_score":0.0051811337},"labels":[],"label_agreement":null},{"id":"W7074072862","doi":"","title":"Diffusion-tensor imaging at 3 T - Detection of white matter alterations in neurological patients on the basis of normal values","year":2007,"lang":"en","type":"article","venue":"UCL Discovery (University College London)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Confidence interval; Diffusion imaging; Anisotropy; Spatial normalization; Isotropy; Magnetic resonance imaging","score_opus":0.01474593932125867,"score_gpt":0.2366414716413514,"score_spread":0.22189553232009274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7074072862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945491,0.00017162677,0.004227756,0.00007053558,0.0000055029564,0.00003855676,0.00020784217,0.000066309454,0.00066285365],"genre_scores_gemma":[0.99533904,0.000060273418,0.004307773,0.000011670102,0.000006873276,0.000021160602,0.00014988246,0.0000077085915,0.00009551198],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973494,0.000078087854,0.000038183094,0.00005634465,0.00006658221,0.000025839301],"domain_scores_gemma":[0.9993474,0.00016907665,0.00021311904,0.000051367173,0.00015238835,0.000066631466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010999957,0.0004704462,0.00027432622,0.0011084006,0.00020466257,0.0004280613,0.0002472706,0.00032927105,0.00076864735],"category_scores_gemma":[0.0041482784,0.00010942299,0.00023514121,0.00033279648,0.0003681296,0.00036692663,0.00028169437,0.00028690824,0.0001827189],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017931386,0.00013846804,0.8456782,0.00013977436,0.00019754062,0.0018659978,0.00080760143,0.0014994676,0.09607299,0.00040020864,0.00096741796,0.050439216],"study_design_scores_gemma":[0.000057505214,0.00040564538,0.96900386,0.000027704918,0.000070833674,0.00397728,0.00018726298,0.009392394,0.015735526,0.0006089993,0.000508631,0.000024390863],"about_ca_topic_score_codex":0.0024898755,"about_ca_topic_score_gemma":0.002679664,"teacher_disagreement_score":0.0024898755,"about_ca_system_score_codex":0.00030014353,"about_ca_system_score_gemma":0.00034684615,"threshold_uncertainty_score":0.0058173537},"labels":[],"label_agreement":null},{"id":"W7086785543","doi":"10.5281/zenodo.17307263","title":"Digital book & tutorial","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Workflow; Preprocessor; Work (physics)","score_opus":0.04687585758568818,"score_gpt":0.30917007210102704,"score_spread":0.26229421451533885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7086785543","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008699632,0.012278022,0.026033115,0.005287026,0.01985099,0.00025879734,0.006592526,0.013989892,0.9148397],"genre_scores_gemma":[0.0010870552,0.0043285163,0.006241195,0.0015125457,0.0026225902,0.0000942049,0.00413158,0.0020676367,0.9779147],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997008,0.000023354643,0.000012375448,0.0000526664,0.00018240615,0.00002842546],"domain_scores_gemma":[0.9991352,0.0001816849,0.000029923924,0.00006298702,0.0003458928,0.00024441077],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00042964672,0.001265349,0.0007828958,0.0017820792,0.0008266325,0.0039313384,0.0012864419,0.0012477213,0.62736887],"category_scores_gemma":[0.0023301945,0.0004676337,0.00072871405,0.0017594275,0.00024049355,0.0035000392,0.0018811962,0.0018516988,0.5423352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000090324575,0.00002021515,0.000023273975,0.00008377924,0.0000015618591,0.00003273991,0.000017035596,0.00009691536,0.00021751768,0.001920418,0.9148694,0.08270809],"study_design_scores_gemma":[0.000002372344,0.000007422322,0.00006586002,0.000047908477,0.0000012947136,0.000093381284,0.000013535093,0.00008111829,0.000067138375,0.0011124266,0.9985033,0.0000042653146],"about_ca_topic_score_codex":0.0012785547,"about_ca_topic_score_gemma":0.0037498928,"teacher_disagreement_score":0.62736887,"about_ca_system_score_codex":0.00064799737,"about_ca_system_score_gemma":0.00083923194,"threshold_uncertainty_score":0.5315131},"labels":[],"label_agreement":null},{"id":"W7096269665","doi":"","title":"© Science and Education Publishing DOI:10.12691/env-3-3-3 Flood Vulnerability Assessment of Niger Delta States","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Niger delta; Vulnerability (computing); Flooding (psychology); Flood myth; Vulnerability assessment; Quarter (Canadian coin); Delta; Risk assessment","score_opus":0.09850929873630512,"score_gpt":0.4285512833466199,"score_spread":0.33004198461031475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096269665","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014658831,0.0028850487,0.01056791,0.007642308,0.0014861585,0.00012680638,0.0034590801,0.00074378145,0.95843005],"genre_scores_gemma":[0.12263214,0.007509716,0.015708923,0.0009990087,0.0002959932,0.0000918715,0.0037443521,0.0002589024,0.8487591],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99974436,0.000031458407,0.000024951187,0.00004241447,0.00012475405,0.000032126074],"domain_scores_gemma":[0.9992748,0.00013444836,0.000056331708,0.000103103426,0.00032618636,0.00010513385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053807354,0.00025275868,0.00018930597,0.001757464,0.00069278525,0.0035796103,0.00037369088,0.0009399439,0.19844103],"category_scores_gemma":[0.0015066111,0.0001372397,0.00024460754,0.00238345,0.00052755006,0.0012211418,0.0009901215,0.00073425024,0.061733976],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004663879,0.000093940645,0.013762317,0.00030370403,0.000012495211,0.0004071713,0.00034049602,0.001482059,0.0030339037,0.041884754,0.18713439,0.7514981],"study_design_scores_gemma":[0.000006413087,0.00003748586,0.016016046,0.00044082283,0.0000072580033,0.0006936049,0.00083299016,0.0019296585,0.0019051536,0.011887402,0.9662271,0.000016079106],"about_ca_topic_score_codex":0.006344979,"about_ca_topic_score_gemma":0.0069253347,"teacher_disagreement_score":0.19844103,"about_ca_system_score_codex":0.0009883742,"about_ca_system_score_gemma":0.0022250134,"threshold_uncertainty_score":0.6638514},"labels":[],"label_agreement":null},{"id":"W7096400195","doi":"","title":"maturation and correlation with postmortem findings in infancyBrain","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Correlation; Sample (material); Human brain; Postmortem studies; Sample size determination","score_opus":0.016657812774074854,"score_gpt":0.2924128781095858,"score_spread":0.275755065335511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096400195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965892,0.0008041291,0.00019827593,0.00006583836,0.000012939785,0.00000777507,0.00021484258,0.000019435925,0.002087564],"genre_scores_gemma":[0.9981034,0.0007322181,0.0003473541,0.000015187147,0.00001499546,0.0000115768025,0.00027845733,0.000011684024,0.00048509342],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971825,0.000062810344,0.000028551829,0.00007427531,0.00006133504,0.00005462665],"domain_scores_gemma":[0.99871266,0.0002389384,0.0005221553,0.0001178968,0.0002396591,0.00016872998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006677169,0.00022822166,0.00016566289,0.001979825,0.00027302967,0.00054656423,0.00030550064,0.00032601715,0.0021083932],"category_scores_gemma":[0.0042268564,0.0002587595,0.00015253836,0.0005030634,0.0005698264,0.00036402588,0.0005170036,0.00046497435,0.0004498344],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041300035,0.000054656266,0.9594095,0.000042498603,0.000033695334,0.005298513,0.0011001455,0.00009630192,0.015444823,0.00044516945,0.0006707456,0.01699095],"study_design_scores_gemma":[0.0000018303679,0.00006180088,0.99240655,0.00001573999,0.000007326577,0.005504472,0.0002402202,0.000069315356,0.0010686909,0.00012921466,0.00049073173,0.0000040105197],"about_ca_topic_score_codex":0.0024411492,"about_ca_topic_score_gemma":0.0036532625,"teacher_disagreement_score":0.0024411492,"about_ca_system_score_codex":0.0003530091,"about_ca_system_score_gemma":0.00026319263,"threshold_uncertainty_score":0.007053256},"labels":[],"label_agreement":null},{"id":"W7097165581","doi":"","title":"TITLE: ANALYSIS OF FUNCTIONAL MRI FOR PRESURGICAL MAPPING: REPRODUCIBILITY, AUTOMATED THRESHOLDS,","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Permission; Acknowledgement; Honor; Signature (topology); Feature (linguistics)","score_opus":0.11149755240205592,"score_gpt":0.3930460201479506,"score_spread":0.2815484677458947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097165581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"reproducibility","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":"reproducibility","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1523806,0.06189124,0.57098854,0.015580121,0.076214895,0.0026126914,0.038081665,0.009190148,0.07306011],"genre_scores_gemma":[0.50429237,0.024170758,0.27160394,0.0025473097,0.02056325,0.0026842444,0.049238306,0.008679063,0.11622074],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99752074,0.0005762395,0.0004256353,0.00054999837,0.00087164954,0.000055740762],"domain_scores_gemma":[0.98184764,0.009228196,0.0015412277,0.0012525098,0.005728792,0.00040158464],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008875989,0.0010394205,0.00088440534,0.0030912785,0.0006014672,0.0025797077,0.001349203,0.0010821234,0.03571972],"category_scores_gemma":[0.037688415,0.00038716133,0.000653723,0.0025975222,0.0007593941,0.002444934,0.0008548701,0.0008492068,0.019402685],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021622875,0.00014987457,0.011741611,0.003990929,0.00036549813,0.00027321235,0.00038869577,0.0025674948,0.02273886,0.005045645,0.38119334,0.56938255],"study_design_scores_gemma":[0.0006487896,0.002710216,0.2466732,0.003591994,0.0010815305,0.0121101355,0.00060747185,0.055462744,0.168275,0.033073284,0.47515452,0.0006110668],"about_ca_topic_score_codex":0.00045263264,"about_ca_topic_score_gemma":0.00055512105,"teacher_disagreement_score":0.99112403,"about_ca_system_score_codex":0.00059578085,"about_ca_system_score_gemma":0.001305253,"threshold_uncertainty_score":0.11949438},"labels":[],"label_agreement":null},{"id":"W7097199262","doi":"","title":"Probabilistic Topography of Human Corpus Callosum Using Cytoarchitectural Parcellation and High Angular Resolution Diffusion","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Diffusion MRI; Probabilistic logic; Pattern recognition (psychology); Tractography; Somatosensory system; Voxel; Landmark; Fiber tract","score_opus":0.10750804987505869,"score_gpt":0.35558865931998,"score_spread":0.24808060944492133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097199262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98098147,0.00012169637,0.018291894,0.000033307177,0.0000025282195,0.000017161734,0.00018835548,0.00008016629,0.0002833384],"genre_scores_gemma":[0.9950867,0.00004082082,0.004607238,0.0000030940366,0.0000023772761,0.0000072253406,0.00010591288,0.000010739773,0.00013579913],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99992573,0.000018777402,0.000003294712,0.000029800449,0.000014985593,0.0000073536385],"domain_scores_gemma":[0.9997036,0.00012241895,0.00005744625,0.000053569493,0.000046558405,0.000016305426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031473997,0.00019591888,0.0000999816,0.0008336489,0.00016479826,0.0003309027,0.00017296067,0.00019694565,0.0010324848],"category_scores_gemma":[0.0013028738,0.00015008563,0.00015698386,0.0004115969,0.00030140555,0.00038879892,0.00020052829,0.000120582474,0.0001319925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010018388,0.00009239887,0.29498374,0.00029373742,0.0003827085,0.0007861795,0.0020297263,0.04959111,0.47281754,0.0024050015,0.0011124846,0.17450361],"study_design_scores_gemma":[0.000018431148,0.000087126,0.88257927,0.000010633226,0.0000701007,0.00083309185,0.00016597322,0.09615411,0.018145114,0.0012365595,0.00066528853,0.000034360113],"about_ca_topic_score_codex":0.012053256,"about_ca_topic_score_gemma":0.013089073,"teacher_disagreement_score":0.012053256,"about_ca_system_score_codex":0.00023979408,"about_ca_system_score_gemma":0.00022942948,"threshold_uncertainty_score":0.023966193},"labels":[],"label_agreement":null},{"id":"W7097756428","doi":"","title":"2Sherbrooke, QC,CA,Université de Sherbrooke,Sherbrooke Connectivity Imaging Lab,","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Set (abstract data type); Noise (video); Identification (biology)","score_opus":0.026535601364685836,"score_gpt":0.28613577529779854,"score_spread":0.2596001739331127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097756428","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0740234,0.03168643,0.050839335,0.08192947,0.009956528,0.0019427874,0.11596762,0.010903206,0.62275124],"genre_scores_gemma":[0.11567025,0.008933655,0.056143563,0.0060330676,0.00080555864,0.0012045148,0.0200581,0.002592015,0.7885594],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867994,0.00014375833,0.00005389282,0.00043036058,0.00046461416,0.00022728143],"domain_scores_gemma":[0.9938911,0.000798101,0.00016509941,0.0005562548,0.0032375508,0.0013520377],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0017345705,0.0015870022,0.0009746216,0.002346557,0.0041168267,0.002651643,0.0032590074,0.0022763188,0.24941006],"category_scores_gemma":[0.007119649,0.0008280165,0.0006110301,0.0021116412,0.0014705334,0.0017277359,0.0012831106,0.002668129,0.059268557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010254619,0.00015548707,0.007325893,0.0005994915,0.00011282179,0.0013774814,0.00061366794,0.0008340497,0.0063880053,0.013660327,0.81675684,0.15115042],"study_design_scores_gemma":[0.0010411998,0.0002976679,0.09294212,0.0010178703,0.00028210194,0.004123281,0.0011341333,0.005983714,0.014288756,0.014264451,0.86439484,0.00022992036],"about_ca_topic_score_codex":0.31476408,"about_ca_topic_score_gemma":0.74030256,"teacher_disagreement_score":0.75058997,"about_ca_system_score_codex":0.010728955,"about_ca_system_score_gemma":0.018324938,"threshold_uncertainty_score":0.83435977},"labels":[],"label_agreement":null},{"id":"W7106206700","doi":"","title":"Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography.","year":2025,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université du Québec à Montréal; University of Alberta; Université de Sherbrooke","funders":"","keywords":"Tractography; Grand Challenges; Relevance (law); Neuroinformatics; 2019-20 coronavirus outbreak; Translational research","score_opus":0.07447673012838404,"score_gpt":0.3108779646974531,"score_spread":0.23640123456906906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106206700","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022384082,0.13496305,0.11511639,0.71705484,0.013730783,0.00013326872,0.0010978525,0.0018400777,0.013825315],"genre_scores_gemma":[0.06674382,0.26125145,0.5551988,0.07903594,0.015026929,0.0010500195,0.0033926773,0.0034765587,0.014823859],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9858467,0.007948515,0.001306506,0.0010426765,0.002860546,0.000995123],"domain_scores_gemma":[0.870497,0.063849464,0.004664965,0.014605403,0.024233665,0.02214953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06390192,0.0012399636,0.0016073419,0.0037697235,0.0035263377,0.016451918,0.004386454,0.00827508,0.028336173],"category_scores_gemma":[0.09849715,0.0009141384,0.0015390876,0.0025777845,0.009803617,0.028465886,0.014045965,0.014155588,0.012076297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023064874,0.00011609223,0.002533963,0.002466547,0.00018721119,0.00035492072,0.0017106028,0.0016411375,0.001407288,0.24544024,0.3427937,0.40111765],"study_design_scores_gemma":[0.000042114043,0.00008865469,0.00091935985,0.0038164833,0.000059256017,0.0007945758,0.0014626428,0.0015804038,0.00053639465,0.42193368,0.5686523,0.00011413609],"about_ca_topic_score_codex":0.007522409,"about_ca_topic_score_gemma":0.015760947,"teacher_disagreement_score":0.06390192,"about_ca_system_score_codex":0.0053941454,"about_ca_system_score_gemma":0.04776073,"threshold_uncertainty_score":0.3379497},"labels":[],"label_agreement":null},{"id":"W7106238655","doi":"10.48550/arxiv.2511.16471","title":"FastSurfer-CC: A robust, accurate, and comprehensive framework for corpus callosum morphometry","year":2025,"lang":"en","type":"preprint","venue":"DZNE Pub","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Society; University of Southern California; Biogen; Deutsches Zentrum für Neurodegenerative Erkrankungen; GlaxoSmithKline; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Corpus callosum; Commissure; Focus (optics); Remyelination","score_opus":0.15559769935946707,"score_gpt":0.40757803451743435,"score_spread":0.25198033515796725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106238655","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039539756,0.0006874014,0.97759706,0.00027455005,0.00008677489,0.00010013336,0.0013960593,0.0152092865,0.00069483626],"genre_scores_gemma":[0.06185456,0.001172633,0.91844314,0.0003140459,0.00020331824,0.0005330188,0.0066870805,0.0077095325,0.0030825923],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989656,0.00023100285,0.00006316435,0.00024842596,0.0003942475,0.000097548014],"domain_scores_gemma":[0.99839836,0.0006077938,0.00018578183,0.0003201462,0.0003936311,0.000094295225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021525812,0.0027635796,0.0016657186,0.0043254807,0.0014378985,0.0030874251,0.002901607,0.0028714247,0.0054341904],"category_scores_gemma":[0.008000141,0.0013423612,0.0026807727,0.002201867,0.0013505104,0.001946318,0.0029691502,0.0029276602,0.0037092133],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036464963,0.00015968863,0.002853168,0.00091453735,0.00080773665,0.0004447639,0.0004712913,0.2777974,0.040321484,0.031081071,0.078963965,0.5658202],"study_design_scores_gemma":[0.00004079269,0.000057273683,0.0019304244,0.000087733635,0.00005938993,0.0005358673,0.00004738845,0.93145776,0.01350509,0.030701078,0.021447223,0.00013006391],"about_ca_topic_score_codex":0.017617406,"about_ca_topic_score_gemma":0.031231184,"teacher_disagreement_score":0.017617406,"about_ca_system_score_codex":0.0012005537,"about_ca_system_score_gemma":0.004469413,"threshold_uncertainty_score":0.03502971},"labels":[],"label_agreement":null},{"id":"W7110949963","doi":"10.1162/imag.a.1080","title":"Revisiting the interpretation of axon diameter mapping using higher-order signal representations","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Wolfson Foundation; Center for Advanced Imaging Innovation and Research; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Axon; Scaling; Estimator; Robustness (evolution); SIGNAL (programming language); Perpendicular; Monte Carlo method","score_opus":0.07640376401577224,"score_gpt":0.4004362656322108,"score_spread":0.32403250161643854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7110949963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055031627,0.00038514356,0.94247967,0.00026581838,0.00005931634,0.000025107236,0.00007527844,0.00044070306,0.0012373546],"genre_scores_gemma":[0.7271224,0.00058326015,0.27008364,0.00013961592,0.000103815306,0.00005966731,0.00013520739,0.00027128553,0.0015009934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952626,0.00016176215,0.00003205401,0.000105898005,0.00013663647,0.00003741209],"domain_scores_gemma":[0.9970451,0.0016762904,0.00041391345,0.0004387257,0.00034156672,0.00008445251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016677101,0.00047187824,0.00042899352,0.0008769747,0.00026118333,0.0013591684,0.0008674221,0.0007661522,0.0016131195],"category_scores_gemma":[0.007041839,0.00023984208,0.0004944283,0.0005221626,0.0009175867,0.0015762427,0.0010071689,0.0010020164,0.00040504968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032127753,0.00014907276,0.006178117,0.0010396347,0.0001285885,0.0011860037,0.000909054,0.29143408,0.23985794,0.17177111,0.0026857227,0.28433943],"study_design_scores_gemma":[0.000007810546,0.000054632717,0.002530569,0.000033539494,0.000019247072,0.00029917722,0.00004839212,0.95346165,0.015778942,0.026032388,0.0017063383,0.000027403545],"about_ca_topic_score_codex":0.0013313676,"about_ca_topic_score_gemma":0.0010543128,"teacher_disagreement_score":0.0016677101,"about_ca_system_score_codex":0.00048666785,"about_ca_system_score_gemma":0.00054545153,"threshold_uncertainty_score":0.0088198185},"labels":[],"label_agreement":null},{"id":"W7112282630","doi":"","title":"Sleep Health and White Matter Integrity in the UK Biobank","year":2025,"lang":"en","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"LMC Diabetes & Endocrinology (Canada)","funders":"","keywords":"White matter; Insomnia; Fractional anisotropy; Sleep (system call); Biobank; Actigraphy","score_opus":0.17357306589573054,"score_gpt":0.4050871247249946,"score_spread":0.23151405882926404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7112282630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864174,0.0013460075,0.0005027876,0.000399887,0.000032204698,0.000074888674,0.0097637195,0.000011707277,0.0014512723],"genre_scores_gemma":[0.9895047,0.0007038805,0.0009127447,0.00031327197,0.000032979282,0.00021789776,0.005532891,0.000014188367,0.002767418],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985259,0.0004565236,0.0003019453,0.00036288527,0.00021450514,0.00013821758],"domain_scores_gemma":[0.9961765,0.0004800544,0.0017600444,0.00080876146,0.0005576543,0.00021692169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013099512,0.0001932327,0.00039867382,0.0013529912,0.00080457376,0.0009164551,0.00049743557,0.00052278413,0.0044704336],"category_scores_gemma":[0.0078052315,0.00031376237,0.00023262207,0.0021173963,0.00039488287,0.00063021015,0.0017750612,0.00038456274,0.0008754753],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004301276,0.00005094212,0.97542894,0.00015680476,0.00015821074,0.00028786267,0.0022303727,0.00007285919,0.0010737912,0.00034117428,0.0063577653,0.013411135],"study_design_scores_gemma":[0.000016056301,0.00004734171,0.99514294,0.00006006858,0.0000369219,0.00021589854,0.00045923438,0.000052067833,0.00015337719,0.00009207683,0.0037150143,0.000009113424],"about_ca_topic_score_codex":0.047766674,"about_ca_topic_score_gemma":0.07055556,"teacher_disagreement_score":0.047766674,"about_ca_system_score_codex":0.00077007996,"about_ca_system_score_gemma":0.0006863647,"threshold_uncertainty_score":0.09497732},"labels":[],"label_agreement":null},{"id":"W7113260559","doi":"","title":"Étude du rôle pronostique des déconnexions cérébrales chez les patients présentant une occlusion de l'artère basilaire","year":2025,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Modified Rankin Scale; Stroke (engine); Logistic regression; Magnetic resonance imaging; Occlusion; Infarction; Cerebral infarction","score_opus":0.02042952591352124,"score_gpt":0.28468242435375035,"score_spread":0.2642528984402291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7113260559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988902,0.00040522465,0.00013288736,0.000048863134,0.0000038120736,0.0000035417474,0.00014943622,0.0000036081215,0.00036242825],"genre_scores_gemma":[0.99930537,0.00016270256,0.00014576262,0.000010772464,0.00002022769,0.0000058303212,0.0002490412,0.0000018443192,0.00009844769],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997763,0.000062736166,0.000022451828,0.00004939358,0.000055003078,0.000034136818],"domain_scores_gemma":[0.9975775,0.0010052407,0.00082564587,0.00006743878,0.0003310942,0.00019307673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068384997,0.00034965453,0.00028379215,0.00067177095,0.0002603229,0.0009898753,0.00024282411,0.0004362096,0.0010418866],"category_scores_gemma":[0.0047424845,0.00011372435,0.00025319547,0.0004783677,0.0002731549,0.0005316974,0.00025889103,0.00039556914,0.00025999724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005330071,0.00002860195,0.991736,0.000017959735,0.00005048662,0.00019356045,0.00009477777,0.00013246461,0.00042671725,0.00002659555,0.00006913336,0.0066906298],"study_design_scores_gemma":[0.0000315805,0.00041187016,0.99533683,0.000018797698,0.000079573554,0.0015270164,0.00018769763,0.0013635742,0.00048708194,0.00007220616,0.00047283448,0.000010913941],"about_ca_topic_score_codex":0.002795288,"about_ca_topic_score_gemma":0.0038141331,"teacher_disagreement_score":0.002795288,"about_ca_system_score_codex":0.00036009258,"about_ca_system_score_gemma":0.00030023025,"threshold_uncertainty_score":0.005558014},"labels":[],"label_agreement":null},{"id":"W7114381595","doi":"","title":"Sex-specific white matter alterations in children exposed to high pregestational BMI","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Splenium; Corpus callosum; Fractional anisotropy; White matter; Overweight; Offspring; Pregnancy; Wechsler Adult Intelligence Scale","score_opus":0.05236405623082192,"score_gpt":0.32837319482187005,"score_spread":0.27600913859104814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7114381595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993,0.00022859086,0.00003952445,0.000022750595,0.0000035974601,0.0000033035642,0.00017995427,0.00000439406,0.00021801727],"genre_scores_gemma":[0.9992273,0.00016202684,0.00008404639,0.000017853275,0.00000396958,0.0000044314456,0.00021636744,0.0000024735941,0.00028159926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980384,0.000022144886,0.000010628912,0.000058338108,0.000052237472,0.00005286452],"domain_scores_gemma":[0.9994771,0.000037537546,0.0003430861,0.000027100165,0.000050700848,0.00006438066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025794664,0.00034633136,0.00022397838,0.0005590074,0.00028228265,0.00041396002,0.00024561593,0.0003269322,0.0015383243],"category_scores_gemma":[0.00068272505,0.00020727034,0.00032788957,0.00052566576,0.00028025798,0.00018375444,0.0003428596,0.00036755082,0.00013734102],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008044185,0.00001810868,0.9971999,0.0000090579115,0.00003520349,0.00015255241,0.00014095826,0.000016097349,0.0010568817,0.000013296959,0.00005278656,0.0012248044],"study_design_scores_gemma":[5.103746e-7,0.000018169943,0.9997428,0.0000016163078,0.000004673995,0.000100341524,0.00004327761,0.000006206729,0.000050015286,0.0000028312684,0.000029092196,4.8694807e-7],"about_ca_topic_score_codex":0.02046803,"about_ca_topic_score_gemma":0.0327678,"teacher_disagreement_score":0.02046803,"about_ca_system_score_codex":0.00035135218,"about_ca_system_score_gemma":0.00044411593,"threshold_uncertainty_score":0.040697753},"labels":[],"label_agreement":null},{"id":"W7115036435","doi":"","title":"Modelling the microstructural effects of white matter hyperintensities","year":2025,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Biomedical Research Council; Medical Research Council; Wellcome Trust","keywords":"Hyperintensity; White matter; White noise; Welding","score_opus":0.025649400140560167,"score_gpt":0.2807553727119799,"score_spread":0.25510597257141976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115036435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.801873,0.0008457907,0.19384933,0.0003628434,0.0000480127,0.00011489727,0.0010343064,0.00039727264,0.0014744572],"genre_scores_gemma":[0.9581975,0.00042026324,0.038221546,0.00004947207,0.000018762157,0.00016539056,0.0005931165,0.000075574004,0.0022584111],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975926,0.000085548425,0.000012899619,0.00008020368,0.00002494328,0.000037175374],"domain_scores_gemma":[0.99845934,0.0011862759,0.00018826096,0.000061902276,0.000064700216,0.000039415758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010490472,0.00077292736,0.00049705803,0.00068309956,0.00026021447,0.00087339967,0.00084488065,0.0012743421,0.0008521216],"category_scores_gemma":[0.0033655344,0.00058692676,0.0013561544,0.00048276092,0.0005106019,0.00059597596,0.00057919143,0.000856759,0.00018930524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072338386,0.000040678664,0.007455324,0.0000728168,0.000097073185,0.00008894981,0.00007108199,0.98237616,0.002847772,0.0015233704,0.00016657825,0.005187967],"study_design_scores_gemma":[0.000006337686,0.000032040385,0.0019769685,0.000008389003,0.000023430408,0.000025087416,0.000015328524,0.99599814,0.0004922189,0.001162801,0.00025169796,0.0000075400476],"about_ca_topic_score_codex":0.022953764,"about_ca_topic_score_gemma":0.018969733,"teacher_disagreement_score":0.022953764,"about_ca_system_score_codex":0.00088872324,"about_ca_system_score_gemma":0.0011672371,"threshold_uncertainty_score":0.04564029},"labels":[],"label_agreement":null},{"id":"W7115824167","doi":"","title":"Keeping It Consistent: Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Higher Order Diffusion Tensor MRI Sequences","year":2025,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Kurtosis; Diffusion MRI; Repeatability; Fractional anisotropy; Imaging phantom; Anisotropy; Intraclass correlation; Tensor (intrinsic definition)","score_opus":0.10161508667914616,"score_gpt":0.32881324207797247,"score_spread":0.22719815539882632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115824167","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4185099,0.0016678228,0.5737485,0.00033624278,0.00027057936,0.00068056874,0.00044962298,0.002139258,0.0021974873],"genre_scores_gemma":[0.6986709,0.00063359283,0.29730564,0.000283852,0.000051991563,0.0010934835,0.00064293126,0.0004865735,0.00083094597],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9959436,0.0011636837,0.00037707324,0.00084871426,0.0015205287,0.00014633767],"domain_scores_gemma":[0.9895118,0.004282218,0.0019815613,0.0017491039,0.0022554344,0.00021995962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006271721,0.00073132216,0.00047732802,0.00087883306,0.00052305375,0.0015243848,0.000920967,0.0011035873,0.0007083245],"category_scores_gemma":[0.024558302,0.00061569957,0.00041630675,0.0006488786,0.00095844065,0.0009130969,0.0009194998,0.00062849314,0.00035283866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083863275,0.00036327538,0.018692702,0.0005524427,0.00016773326,0.0002741898,0.0011249755,0.01524291,0.87334484,0.0017916769,0.0011881832,0.08641853],"study_design_scores_gemma":[0.00017185566,0.006694332,0.080485664,0.0002894559,0.0009982424,0.0036258881,0.0006602814,0.15335582,0.7264666,0.0027947812,0.02406738,0.00038969383],"about_ca_topic_score_codex":0.0013386842,"about_ca_topic_score_gemma":0.001639205,"teacher_disagreement_score":0.006271721,"about_ca_system_score_codex":0.0006199037,"about_ca_system_score_gemma":0.0011230792,"threshold_uncertainty_score":0.033168435},"labels":[],"label_agreement":null},{"id":"W7116829184","doi":"10.1002/alz70862_110231","title":"Sex differences in white matter hyperintensity pathophysiology","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Pathophysiology; Hyperintensity; White matter; Animal studies","score_opus":0.047670494239238415,"score_gpt":0.32121785807004744,"score_spread":0.273547363830809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116829184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98111683,0.0046804827,0.0030636424,0.00042791216,0.000069309935,0.000045186553,0.0074736755,0.00007219317,0.0030506407],"genre_scores_gemma":[0.9939679,0.00089449243,0.0009646456,0.00010925848,0.000037378442,0.000033157434,0.003087097,0.000034572604,0.0008715125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996093,0.00007358813,0.000053017804,0.00017153737,0.000051128318,0.0000415196],"domain_scores_gemma":[0.99922895,0.00022552267,0.00030406372,0.00011848088,0.00008769956,0.000035231213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094084215,0.00039280063,0.0003516435,0.00050295715,0.00023817197,0.0005365553,0.0003194377,0.00031747005,0.004884819],"category_scores_gemma":[0.002568745,0.00016870824,0.0003258456,0.0004677106,0.00031405536,0.00033367268,0.00035860858,0.00019762284,0.00072058017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016837224,0.00005769882,0.93451923,0.00042757724,0.0008034119,0.0007901166,0.001329261,0.0004883861,0.009304985,0.0017360466,0.004088838,0.04477068],"study_design_scores_gemma":[0.000020736099,0.00011827277,0.9908655,0.000081291095,0.00012566248,0.0018727905,0.00017635975,0.0005192941,0.0008407765,0.001693836,0.0036713402,0.000014269623],"about_ca_topic_score_codex":0.0009932106,"about_ca_topic_score_gemma":0.0010535006,"teacher_disagreement_score":0.004884819,"about_ca_system_score_codex":0.00010050274,"about_ca_system_score_gemma":0.000131954,"threshold_uncertainty_score":0.016341329},"labels":[],"label_agreement":null},{"id":"W7116853221","doi":"10.1371/journal.pdig.0001155","title":"Autism spectrum disorder detection using diffusion tensor imaging and machine learning","year":2025,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Agence Universitaire de la Francophonie; University of Edinburgh; Mrs Gladys Row Fogo Charitable Trust","keywords":"Diffusion MRI; Fractional anisotropy; Autism spectrum disorder; Support vector machine; Neuroimaging; Pattern recognition (psychology); White matter; Generalization; Random forest; Anisotropy","score_opus":0.03973981842652238,"score_gpt":0.3362264295065378,"score_spread":0.2964866110800154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116853221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7068483,0.0012923056,0.28338033,0.00038249258,0.000070544476,0.000545713,0.0018247317,0.003855997,0.0017995284],"genre_scores_gemma":[0.73384905,0.00032564177,0.26299646,0.00008353711,0.000034606663,0.00022791725,0.0018058304,0.00006103789,0.00061592204],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842525,0.0005695518,0.00016975847,0.00042327718,0.00032538298,0.00008685692],"domain_scores_gemma":[0.9974298,0.001106081,0.0003663262,0.00023223179,0.00076530775,0.000100255456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002313653,0.0008137131,0.0007169183,0.0035890841,0.00037538813,0.0006886845,0.0005220987,0.0008484704,0.0008522584],"category_scores_gemma":[0.0075613083,0.0002629461,0.0006345486,0.0008792036,0.0002826373,0.00080047216,0.0006674217,0.00042461616,0.00059128134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012069329,0.00053224585,0.11332958,0.00035771722,0.00041033252,0.00056356465,0.00020662491,0.040316455,0.047460176,0.00081888534,0.003992224,0.7908052],"study_design_scores_gemma":[0.00008687623,0.0006024002,0.091704816,0.00006809349,0.000118946446,0.0015111706,0.0001489273,0.87105054,0.031107742,0.001768973,0.001744272,0.0000871465],"about_ca_topic_score_codex":0.0042498866,"about_ca_topic_score_gemma":0.0044916607,"teacher_disagreement_score":0.0042498866,"about_ca_system_score_codex":0.0004890999,"about_ca_system_score_gemma":0.00055574364,"threshold_uncertainty_score":0.0122359395},"labels":[],"label_agreement":null},{"id":"W7116873550","doi":"10.1002/alz70862_109829","title":"Advanced MRI biomarkers for efficient clinical trial designs in Progressive Supranuclear Palsy (PSP)","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Clinical trial; Progressive supranuclear palsy; Magnetic resonance imaging; Sample size determination; Biomarker","score_opus":0.13863381392749036,"score_gpt":0.4472783274104305,"score_spread":0.30864451348294014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116873550","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06733014,0.021475833,0.7976024,0.009030122,0.004368696,0.08042897,0.00663087,0.0036685066,0.009464444],"genre_scores_gemma":[0.19792281,0.0021269887,0.646686,0.0023405512,0.00085835735,0.14706084,0.0015959286,0.00036125098,0.0010472685],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.8680745,0.11463813,0.006866411,0.003840949,0.005529611,0.0010505137],"domain_scores_gemma":[0.84006554,0.109916784,0.022731394,0.011582945,0.013137658,0.0025656733],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.15478683,0.0017981867,0.0038988856,0.0025056098,0.0009920573,0.0036090654,0.0018412338,0.0029450897,0.010811638],"category_scores_gemma":[0.20259891,0.0015823774,0.0030170397,0.0019954075,0.0017584665,0.0029070848,0.002923261,0.0033911464,0.0019222768],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.10159893,0.00316232,0.038798023,0.021788932,0.013582732,0.0009662377,0.0011205983,0.043401577,0.014466825,0.041489594,0.046284653,0.6733396],"study_design_scores_gemma":[0.103934765,0.066081256,0.08872936,0.009794564,0.015453602,0.0017200218,0.00048024522,0.22551966,0.023883125,0.24600121,0.21766983,0.0007323382],"about_ca_topic_score_codex":0.0002935751,"about_ca_topic_score_gemma":0.0005431962,"teacher_disagreement_score":0.8452132,"about_ca_system_score_codex":0.0018357489,"about_ca_system_score_gemma":0.0050402726,"threshold_uncertainty_score":0.8186008},"labels":[],"label_agreement":null},{"id":"W7116965308","doi":"10.64898/2025.12.20.695692","title":"Anatomical White Matter Tracts Span the Cortical Hierarchy to Support Cognitive Diversity","year":2025,"lang":"en","type":"article","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Pennsylvania","keywords":"Hierarchy; Cognition; White matter; Association (psychology); Projection (relational algebra); Bridge (graph theory)","score_opus":0.028940693073203665,"score_gpt":0.29302832824420044,"score_spread":0.26408763517099676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116965308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8651682,0.00200194,0.11901931,0.0005797957,0.000056835066,0.000042825697,0.0008319609,0.00059811474,0.011701003],"genre_scores_gemma":[0.9467624,0.0010815865,0.048577353,0.00015806519,0.000028038812,0.00004059639,0.00044804782,0.00011932592,0.0027847],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99981433,0.00003036869,0.0000146425455,0.000075108626,0.0000362117,0.000029267849],"domain_scores_gemma":[0.9995283,0.00008403556,0.00020110309,0.000064038526,0.0000630736,0.000059548438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035803585,0.00027087325,0.00025417458,0.0011446358,0.0004721833,0.0011327766,0.00026143622,0.00038613332,0.0024537502],"category_scores_gemma":[0.00089478365,0.00025522802,0.00026223506,0.0007323651,0.00074349914,0.0009657085,0.000625052,0.0005826684,0.00056932267],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002558509,0.00005215608,0.067574024,0.00030543178,0.0001820843,0.0005775584,0.0010590282,0.0026264898,0.79586136,0.03534591,0.0016395435,0.09452058],"study_design_scores_gemma":[0.00004094153,0.00035757665,0.79290676,0.0002920978,0.00019570315,0.0027719166,0.00091978733,0.01337412,0.109669074,0.05329503,0.026089251,0.000087660024],"about_ca_topic_score_codex":0.003046278,"about_ca_topic_score_gemma":0.008377149,"teacher_disagreement_score":0.003046278,"about_ca_system_score_codex":0.00039766758,"about_ca_system_score_gemma":0.0007404266,"threshold_uncertainty_score":0.008208573},"labels":[],"label_agreement":null},{"id":"W7116988651","doi":"10.1002/alz70861_108716","title":"Valiltramiprosate Effects on Microstructural Integrity of Grey and White Matter in APOE4/4 Homozygotes with Early AD and their Correlations to Clinical Outcomes: MRI Mean Diffusivity Results from the 78‐Week APOLLOE4 Phase 3 Trial","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"White matter; Thermal diffusivity; Hippocampal formation; Grey matter; Phase (matter); Diffusion MRI; Neurodegeneration; Neuroimaging","score_opus":0.05821910477358937,"score_gpt":0.37004393269767943,"score_spread":0.31182482792409005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116988651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99955386,0.00024006555,0.000027593995,0.00001159639,0.000001754313,0.0000117683185,0.00007594897,0.0000027475105,0.00007456015],"genre_scores_gemma":[0.9993272,0.000095785916,0.00013646067,0.00002063282,0.0000075781163,0.000020733143,0.00024495574,0.000002608988,0.00014400824],"study_design_codex":"randomized_trial","study_design_gemma":"observational","domain_scores_codex":[0.99980253,0.00007958381,0.000022238866,0.00003956428,0.00003012522,0.000025895468],"domain_scores_gemma":[0.99951077,0.00012207244,0.00019330447,0.00004773505,0.000050946408,0.00007518808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014455712,0.00049142784,0.00060992286,0.00027493315,0.00017874107,0.00040539232,0.00024593793,0.00032254655,0.0010580104],"category_scores_gemma":[0.0009737367,0.00015574665,0.0003814661,0.00015872534,0.00020305684,0.00021116978,0.0001545466,0.00028260957,0.00016142339],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.49782157,0.004920287,0.34528092,0.0004197604,0.0027353626,0.0005255513,0.00031470187,0.0007806756,0.067971334,0.00007447722,0.0006977863,0.07845755],"study_design_scores_gemma":[0.022388618,0.052406374,0.9097747,0.00004572998,0.0019530371,0.0009485684,0.00011690518,0.0012398926,0.010059512,0.00019535913,0.00083745364,0.00003374089],"about_ca_topic_score_codex":0.00057386595,"about_ca_topic_score_gemma":0.00081297185,"teacher_disagreement_score":0.0014455712,"about_ca_system_score_codex":0.00023194456,"about_ca_system_score_gemma":0.00018562675,"threshold_uncertainty_score":0.007645011},"labels":[],"label_agreement":null},{"id":"W7117062403","doi":"10.1002/alz70862_110131","title":"Microstructural differences in white matter tracts in Alzheimer’s disease, cerebrovascular disease, and Parkinson's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; Disease; Diffusion MRI; Magnetic resonance imaging; White (mutation)","score_opus":0.03351699596125572,"score_gpt":0.3047288863599643,"score_spread":0.2712118903987086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117062403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99258715,0.00090398185,0.00039436226,0.00005233699,0.000007382539,0.000025822725,0.0052608973,0.000011241054,0.0007569582],"genre_scores_gemma":[0.99209505,0.0003205363,0.000727919,0.000033708195,0.000011852375,0.000040525825,0.0065418435,0.0000073531264,0.00022124145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995234,0.000073366486,0.00009237804,0.00016689481,0.00009014426,0.000053842745],"domain_scores_gemma":[0.99898916,0.00018206332,0.00040397345,0.0001822963,0.00015993055,0.0000825965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081038766,0.0003264806,0.0004000495,0.0017379151,0.0006944213,0.00078698207,0.00029930286,0.00029963147,0.001529168],"category_scores_gemma":[0.0023727743,0.00023010201,0.00034819622,0.0018020587,0.00044964429,0.0003358286,0.000634627,0.00022310941,0.00022438943],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043624683,0.00002620883,0.986814,0.00010483941,0.00031957467,0.00017760378,0.00029846551,0.00028830854,0.0015998052,0.00012572741,0.0010095249,0.00879966],"study_design_scores_gemma":[0.00000982002,0.000022256429,0.9982492,0.00001920504,0.000051059873,0.00025241767,0.00008752637,0.00031357468,0.00019782943,0.00021501786,0.00057774136,0.000004372189],"about_ca_topic_score_codex":0.041187704,"about_ca_topic_score_gemma":0.10062376,"teacher_disagreement_score":0.041187704,"about_ca_system_score_codex":0.000650442,"about_ca_system_score_gemma":0.0006985196,"threshold_uncertainty_score":0.08189595},"labels":[],"label_agreement":null},{"id":"W7117234009","doi":"10.1002/alz70856_100338","title":"Sex differences in white matter hyperintensity pathophysiology","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Pathophysiology; Hyperintensity; White matter; Animal studies","score_opus":0.047670494239238415,"score_gpt":0.32121785807004744,"score_spread":0.273547363830809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117234009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98111683,0.0046804827,0.0030636424,0.00042791216,0.000069309935,0.000045186553,0.0074736755,0.00007219317,0.0030506407],"genre_scores_gemma":[0.9939679,0.00089449243,0.0009646456,0.00010925848,0.000037378442,0.000033157434,0.003087097,0.000034572604,0.0008715125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996093,0.00007358813,0.000053017804,0.00017153737,0.000051128318,0.0000415196],"domain_scores_gemma":[0.99922895,0.00022552267,0.00030406372,0.00011848088,0.00008769956,0.000035231213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094084215,0.00039280063,0.0003516435,0.00050295715,0.00023817197,0.0005365553,0.0003194377,0.00031747005,0.004884819],"category_scores_gemma":[0.002568745,0.00016870824,0.0003258456,0.0004677106,0.00031405536,0.00033367268,0.00035860858,0.00019762284,0.00072058017],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016837224,0.00005769882,0.93451923,0.00042757724,0.0008034119,0.0007901166,0.001329261,0.0004883861,0.009304985,0.0017360466,0.004088838,0.04477068],"study_design_scores_gemma":[0.000020736099,0.00011827277,0.9908655,0.000081291095,0.00012566248,0.0018727905,0.00017635975,0.0005192941,0.0008407765,0.001693836,0.0036713402,0.000014269623],"about_ca_topic_score_codex":0.0009932106,"about_ca_topic_score_gemma":0.0010535006,"teacher_disagreement_score":0.004884819,"about_ca_system_score_codex":0.00010050274,"about_ca_system_score_gemma":0.000131954,"threshold_uncertainty_score":0.016341329},"labels":[],"label_agreement":null},{"id":"W7117259059","doi":"10.1002/alz70856_098641","title":"Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Disease; Inflammation; White matter; Genetic architecture; Vascular disease; Senescence; Cellular architecture","score_opus":0.018011445062366592,"score_gpt":0.2950078279124745,"score_spread":0.2769963828501079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117259059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99845445,0.00023945574,0.0007101334,0.000024845409,0.0000020896698,0.000005363945,0.00035715106,0.000014369481,0.00019212937],"genre_scores_gemma":[0.999054,0.00006326942,0.0005572062,0.000013920399,0.0000038578914,0.000005436677,0.0002031563,0.0000053542417,0.000093814924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996611,0.00008642133,0.000032760006,0.0001462422,0.000044075634,0.000029403855],"domain_scores_gemma":[0.9991972,0.00015130406,0.0003805119,0.00013454849,0.00008372538,0.00005272503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073253474,0.0003241842,0.00029312205,0.000911016,0.00025640533,0.0004939206,0.00021091543,0.00023447024,0.00084733765],"category_scores_gemma":[0.0012157665,0.0001499742,0.0003628432,0.00091070664,0.00033911713,0.00015884706,0.00043164755,0.00021451783,0.00008242859],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049462233,0.000047232334,0.95802206,0.000047819,0.0012301807,0.00026498793,0.0002679505,0.0007843188,0.029712062,0.00036717465,0.0002952925,0.00846618],"study_design_scores_gemma":[0.0000034406135,0.000030442536,0.9985915,0.000004087498,0.0000843774,0.00010438623,0.00002871837,0.00042813207,0.0004457016,0.00020208953,0.00007439877,0.000002779571],"about_ca_topic_score_codex":0.0051962133,"about_ca_topic_score_gemma":0.0058574085,"teacher_disagreement_score":0.0051962133,"about_ca_system_score_codex":0.00018258323,"about_ca_system_score_gemma":0.00020759687,"threshold_uncertainty_score":0.010331929},"labels":[],"label_agreement":null},{"id":"W7117293742","doi":"10.1002/alz70856_104478","title":"Microstructural differences in white matter tracts in Alzheimer's disease, cerebrovascular disease, and Parkinson's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; Disease; Diffusion MRI; Magnetic resonance imaging; White (mutation)","score_opus":0.02952110442464411,"score_gpt":0.299392257337648,"score_spread":0.2698711529130039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117293742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924704,0.00086387026,0.00037293645,0.000047526868,0.0000065868676,0.00002613949,0.0054749073,0.000011871569,0.0007257512],"genre_scores_gemma":[0.9920665,0.0003099972,0.00069992256,0.000032501728,0.000010748642,0.000041506806,0.006605887,0.0000072684984,0.00022562157],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995499,0.000067058354,0.00008629239,0.0001584539,0.00008578022,0.0000524315],"domain_scores_gemma":[0.9990613,0.00016626636,0.0003790025,0.0001682569,0.00014557852,0.00007972125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007568698,0.00032150274,0.0003989234,0.0017135041,0.0006829808,0.00078044296,0.00028865927,0.00029366554,0.0015138045],"category_scores_gemma":[0.0022522565,0.00021844587,0.0003311845,0.0017955737,0.00044423642,0.0003111197,0.00062386465,0.00020754285,0.00022022743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004131328,0.00002439431,0.9874866,0.000097602184,0.0002850767,0.00016917384,0.0002777727,0.00027285924,0.0015812482,0.000113773945,0.0009331309,0.008345086],"study_design_scores_gemma":[0.000009454979,0.000021132906,0.99835986,0.000017526145,0.00004810522,0.00023584488,0.00008399162,0.00029429852,0.00019465564,0.0001947953,0.0005362501,0.000004070544],"about_ca_topic_score_codex":0.043761916,"about_ca_topic_score_gemma":0.10730661,"teacher_disagreement_score":0.043761916,"about_ca_system_score_codex":0.00065385795,"about_ca_system_score_gemma":0.00072143285,"threshold_uncertainty_score":0.08701438},"labels":[],"label_agreement":null},{"id":"W7117303328","doi":"10.1212/wnl.0000000000214582","title":"Integrating Intracranial EEG and Tractography","year":2025,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"","score_opus":0.0234489022100841,"score_gpt":0.34005754197472293,"score_spread":0.3166086397646388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117303328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07179019,0.007447804,0.8972731,0.0010448116,0.00054469996,0.00012821647,0.0012893705,0.0043120864,0.01616971],"genre_scores_gemma":[0.5647085,0.012964021,0.41073793,0.00040190213,0.0011828332,0.00009224111,0.0010615566,0.0010085469,0.007842495],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997502,0.000074735275,0.00002178383,0.000049786566,0.00007858443,0.000024901981],"domain_scores_gemma":[0.99917907,0.00034761557,0.000070798895,0.00012298551,0.00023913526,0.00004044647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005053935,0.0008432034,0.00051239366,0.002780901,0.00019822067,0.0019874782,0.00039047076,0.00052768714,0.0034755378],"category_scores_gemma":[0.0035425741,0.0002822821,0.0004601708,0.0020416598,0.0003332143,0.001613519,0.00074960536,0.000493005,0.0014518193],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023756325,0.00008938774,0.02846597,0.00040002048,0.0004881939,0.0014888851,0.00023574485,0.015874704,0.055467825,0.005866444,0.005996941,0.8853883],"study_design_scores_gemma":[0.00014403934,0.0007178269,0.21717355,0.0009499781,0.0016227019,0.017202009,0.0011794784,0.4321531,0.078949116,0.15856795,0.0910109,0.00032931715],"about_ca_topic_score_codex":0.0064219018,"about_ca_topic_score_gemma":0.014522089,"teacher_disagreement_score":0.0064219018,"about_ca_system_score_codex":0.00030700548,"about_ca_system_score_gemma":0.0007785736,"threshold_uncertainty_score":0.012769043},"labels":[],"label_agreement":null},{"id":"W7117569236","doi":"10.1055/s-0045-1814098","title":"Diffusion Tensor Imaging to Analyze White Matter Tract Abnormalities in Major Psychiatric Disorders","year":2025,"lang":"en","type":"article","venue":"Avicenna Journal of Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Pathophysiology; Major depressive disorder; Tractography; Diffusion imaging","score_opus":0.01335015821961329,"score_gpt":0.3359721219370203,"score_spread":0.32262196371740703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117569236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97879076,0.0030290463,0.010304882,0.0002504067,0.000055314587,0.000594397,0.0035251284,0.0001379062,0.0033122606],"genre_scores_gemma":[0.98116595,0.0007387488,0.015368497,0.000032868447,0.000027287386,0.00030500808,0.0011899759,0.00002527245,0.0011463427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997564,0.00007612885,0.00004465561,0.00003868751,0.000058821588,0.000025205794],"domain_scores_gemma":[0.9993112,0.00014848115,0.0002775427,0.000046539073,0.00014363317,0.00007259251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012525558,0.00052958826,0.00038000933,0.0025742033,0.00021567204,0.00046111224,0.00026053173,0.0001992498,0.0021615124],"category_scores_gemma":[0.002591445,0.00013444757,0.00051450863,0.0016022193,0.00016887803,0.00031693355,0.00028269496,0.00039013644,0.0003153879],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025203056,0.00030727786,0.83697325,0.0008167535,0.0012039143,0.00210138,0.00051668356,0.001970721,0.02234977,0.0013004409,0.0031241148,0.12681535],"study_design_scores_gemma":[0.000081452934,0.00071791606,0.9850114,0.000059154663,0.00018481277,0.0017487471,0.00024791533,0.007295319,0.001599432,0.001123533,0.0019058419,0.000024435858],"about_ca_topic_score_codex":0.0030715128,"about_ca_topic_score_gemma":0.004943096,"teacher_disagreement_score":0.0030715128,"about_ca_system_score_codex":0.00035521845,"about_ca_system_score_gemma":0.00040111836,"threshold_uncertainty_score":0.0072309375},"labels":[],"label_agreement":null},{"id":"W7119504168","doi":"10.1002/alz70856_106960","title":"In vivo mean diffusivity is associated with neuropathology markers of Alzheimer's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Douglas College","funders":"","keywords":"Neuropathology; Senile plaques; Cerebral amyloid angiopathy; Biomarker; White matter; Neurodegeneration; Neurofibrillary tangle; Disease","score_opus":0.03173778335946836,"score_gpt":0.31938305870818523,"score_spread":0.28764527534871687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7119504168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985298,0.00024150882,0.00054378365,0.000038211478,0.000003353699,0.0000046569407,0.000288806,0.00001414371,0.00033568667],"genre_scores_gemma":[0.9991917,0.00004376887,0.0002984788,0.0000041444173,0.0000040494624,0.000004953709,0.00022474906,0.00000446022,0.00022372666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997657,0.00006242456,0.00003694655,0.0000751107,0.000036246347,0.000023576638],"domain_scores_gemma":[0.997547,0.00042521424,0.0014259685,0.00022782868,0.00021741205,0.00015664336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058028445,0.00035983662,0.00035028878,0.00080174237,0.00024873472,0.00054909516,0.00022726796,0.0002639465,0.0029312733],"category_scores_gemma":[0.0024116256,0.0001875707,0.00016848672,0.0004200968,0.00025823282,0.0002542994,0.00036113118,0.0003690608,0.00024840125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065802096,0.000100738805,0.97223705,0.000052169635,0.0002481018,0.00023350102,0.00017339965,0.00026219647,0.020311506,0.00012542852,0.0002626657,0.0053352993],"study_design_scores_gemma":[0.000006547394,0.0000855014,0.9965346,0.000006882162,0.000041586565,0.00081238564,0.00006182184,0.0005124925,0.0015523552,0.00018804238,0.00019274728,0.0000049849577],"about_ca_topic_score_codex":0.0013583992,"about_ca_topic_score_gemma":0.0013703724,"teacher_disagreement_score":0.0029312733,"about_ca_system_score_codex":0.00024751708,"about_ca_system_score_gemma":0.00022109933,"threshold_uncertainty_score":0.009806037},"labels":[],"label_agreement":null},{"id":"W7126232837","doi":"10.1162/nol.e.241","title":"The White Matter Connectome Supporting Speech and Language in the Human","year":2025,"lang":"en","type":"article","venue":"Neurobiology of Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"White matter; Connectome; Connectomics; Lateralization of brain function; Diffusion MRI; Reading (process); Functional connectivity; Human brain","score_opus":0.021267148409192912,"score_gpt":0.3656625327855713,"score_spread":0.3443953843763784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7126232837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60155445,0.11950141,0.14892834,0.056838896,0.017478287,0.00020781223,0.0057722153,0.0015301195,0.048188366],"genre_scores_gemma":[0.7460391,0.1254983,0.08528083,0.0051017334,0.017662102,0.0001940089,0.0025496434,0.00052136753,0.017152904],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99989986,0.000018419641,0.0000088274965,0.000034050547,0.000028128628,0.000010696909],"domain_scores_gemma":[0.99943787,0.00031718172,0.00010258754,0.000031225994,0.00006419782,0.00004692506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004796546,0.00032382834,0.00026620895,0.0015414754,0.0004356372,0.0011024462,0.00033714256,0.0006844642,0.0029034903],"category_scores_gemma":[0.001487166,0.00016867752,0.00028602988,0.00070278364,0.0010039844,0.0017308136,0.0006062776,0.00065034936,0.00035348308],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035939045,0.0000694186,0.037888244,0.00196011,0.0005631265,0.001865652,0.0012615245,0.0044818437,0.1078595,0.05249823,0.09075185,0.7004412],"study_design_scores_gemma":[0.0000553799,0.0005639578,0.299119,0.0014250487,0.0006852976,0.0093065975,0.0024288495,0.02506768,0.034017015,0.2081196,0.41891906,0.00029254114],"about_ca_topic_score_codex":0.0011964724,"about_ca_topic_score_gemma":0.0037847615,"teacher_disagreement_score":0.0029034903,"about_ca_system_score_codex":0.00033000356,"about_ca_system_score_gemma":0.0005782416,"threshold_uncertainty_score":0.009713173},"labels":[],"label_agreement":null},{"id":"W7132412335","doi":"","title":"Associations between white matter structural properties and global cognition as measured by MoCA scores in older adults","year":2024,"lang":"en","type":"article","venue":"Lithuanian University of Health Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Cognition; White matter; Tractography; Cognitive decline; Cognitive Assessment System; Diffusion MRI; Voxel","score_opus":0.05440461188945767,"score_gpt":0.31985591380875,"score_spread":0.26545130191929234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132412335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99922466,0.00030790552,0.000038565147,0.000016060929,0.000003549917,0.0000067297206,0.000144149,0.0000029663977,0.0002553917],"genre_scores_gemma":[0.9995321,0.000095357995,0.000069805734,0.000010147994,0.000011076239,0.0000066070725,0.00017639632,8.616174e-7,0.00009765808],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998541,0.00001961228,0.000026395312,0.000045270262,0.000030741194,0.00002396468],"domain_scores_gemma":[0.99920493,0.00011654547,0.00040973874,0.000045303044,0.00010230289,0.00012118498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048503812,0.00045946665,0.00032158705,0.0012014221,0.00033187988,0.00048121833,0.00020416713,0.00050941645,0.0015866266],"category_scores_gemma":[0.001737897,0.00015012958,0.0003182,0.0005580681,0.00025676764,0.0003246252,0.0003506438,0.00027601785,0.0001401336],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017882345,0.000029963847,0.9975158,0.000017130214,0.0001008262,0.000074707044,0.00005857597,0.000038573686,0.0002944229,0.000009509854,0.000054889813,0.0016266161],"study_design_scores_gemma":[0.000002456935,0.000045234206,0.9997173,0.0000020190273,0.000021234397,0.00008133582,0.000026780146,0.000041912594,0.000022482322,0.000014445304,0.000023749211,0.0000010861215],"about_ca_topic_score_codex":0.0030660536,"about_ca_topic_score_gemma":0.0052998806,"teacher_disagreement_score":0.0030660536,"about_ca_system_score_codex":0.00014437173,"about_ca_system_score_gemma":0.00012268312,"threshold_uncertainty_score":0.0060964227},"labels":[],"label_agreement":null},{"id":"W7132962706","doi":"","title":"Modeling Isotropic and Anisotropic Diffusion in Aging Brain White Matter with MRI","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Anisotropy; Isotropy; White matter; Diffusion MRI; Fractional anisotropy; Diffusion","score_opus":0.02629674239357279,"score_gpt":0.3581952664341419,"score_spread":0.33189852404056913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132962706","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17082459,0.002493548,0.81870943,0.0012215363,0.00014934201,0.00016515244,0.00045878653,0.0007207016,0.005256862],"genre_scores_gemma":[0.78407305,0.0050995983,0.19298786,0.0003491573,0.00021088278,0.00045127815,0.0005392599,0.0002520254,0.0160369],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998416,0.00005236743,0.000008472051,0.000049250375,0.00002641621,0.000021900309],"domain_scores_gemma":[0.99944097,0.00031316467,0.00011164346,0.00004208523,0.00006073534,0.00003132144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092722644,0.00078690524,0.0006499435,0.0006200986,0.00029203473,0.0012645731,0.0010484423,0.0017159529,0.0007327177],"category_scores_gemma":[0.0029494294,0.00062892697,0.0011716238,0.0005334327,0.00064150075,0.0009930482,0.0007529229,0.00085034524,0.00034376228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049976014,0.000037429058,0.001177674,0.000060165064,0.00004541433,0.00008430329,0.00008955349,0.9779243,0.0030565055,0.008711709,0.00058616494,0.008176837],"study_design_scores_gemma":[0.000005331476,0.000017833489,0.00029255453,0.000009058419,0.00000998295,0.000027012382,0.000008087733,0.9951448,0.00030763514,0.0034864019,0.00068287324,0.000008366362],"about_ca_topic_score_codex":0.015727386,"about_ca_topic_score_gemma":0.009849791,"teacher_disagreement_score":0.015727386,"about_ca_system_score_codex":0.00081317057,"about_ca_system_score_gemma":0.0011929866,"threshold_uncertainty_score":0.031271696},"labels":[],"label_agreement":null},{"id":"W7132963379","doi":"","title":"From Structure to Function: Social and Cognitive Networks in Children Born Very Low Birth Weight","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Low birth weight; Diffusion MRI; Cognition; Affect (linguistics)","score_opus":0.016770201925742252,"score_gpt":0.34649680589754234,"score_spread":0.3297266039718001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132963379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988945,0.0003485674,0.000064425905,0.00011570724,0.000002707919,0.0000037208258,0.00007896511,0.0000027770093,0.0004886752],"genre_scores_gemma":[0.9990682,0.00038240178,0.00018090422,0.000022715578,0.0000033951255,0.000009321484,0.000093824754,0.0000024308476,0.00023679883],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99981695,0.000026654672,0.000009984603,0.000055001434,0.00004535224,0.000045980272],"domain_scores_gemma":[0.99972945,0.000041617248,0.00012833203,0.000013199038,0.000029638533,0.000057641348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028576466,0.0002938885,0.00024700575,0.00068836333,0.00042938997,0.0008576314,0.00029071464,0.0003312954,0.0010488748],"category_scores_gemma":[0.0014396138,0.0001939524,0.0003220611,0.0004479132,0.0004535524,0.0007878078,0.00067733397,0.0005373304,0.000119186334],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014221454,0.00011669668,0.97246146,0.00006800096,0.000094305244,0.000582105,0.0036108587,0.00023878882,0.003015449,0.00033442245,0.00030848454,0.019027203],"study_design_scores_gemma":[0.0000011488095,0.000048754566,0.99831367,0.000014038676,0.000013077588,0.0002082081,0.0008696938,0.00011197771,0.00013014105,0.00014025194,0.00014566006,0.0000033947883],"about_ca_topic_score_codex":0.017035509,"about_ca_topic_score_gemma":0.020828614,"teacher_disagreement_score":0.017035509,"about_ca_system_score_codex":0.0005917605,"about_ca_system_score_gemma":0.00036696176,"threshold_uncertainty_score":0.033872724},"labels":[],"label_agreement":null},{"id":"W7133002250","doi":"","title":"Multiparametric and Multivariate Analysis of White Matter Microstructure and its Relationship with Psychosexuality","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Hospital for Sick Children","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Transgender; Multivariate statistics; Multivariate analysis; Neuroimaging; Sexual orientation","score_opus":0.07908626917155533,"score_gpt":0.43635865806241747,"score_spread":0.35727238889086216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133002250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99626666,0.00035007027,0.0025399574,0.000055536366,0.0000049404885,0.00000988281,0.00023182208,0.000018372133,0.0005227274],"genre_scores_gemma":[0.99837625,0.0001661492,0.0011144654,0.000007299647,0.0000056562126,0.000008284546,0.00012413786,0.0000055503137,0.00019206798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997923,0.00006414573,0.000025106487,0.00005574422,0.00003711309,0.000025665815],"domain_scores_gemma":[0.9988386,0.00038626735,0.00040955807,0.00017298586,0.00012027672,0.00007228144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007390938,0.00018228438,0.00015753311,0.0007276277,0.00022736505,0.00051480817,0.00012679675,0.0001260289,0.0010185539],"category_scores_gemma":[0.002483916,0.000098187935,0.0003473322,0.00066086557,0.00021088729,0.00029369915,0.0003231323,0.00025212855,0.0000747205],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026941934,0.00006649228,0.93478894,0.00010590311,0.000762589,0.000259916,0.00074170606,0.0012854688,0.017370872,0.000821618,0.0003754144,0.043151654],"study_design_scores_gemma":[0.0000016715044,0.000053436008,0.9951822,0.000010216264,0.000073099196,0.00021830924,0.0002687676,0.002237991,0.0012637764,0.00043740764,0.00024495966,0.000008033749],"about_ca_topic_score_codex":0.00419911,"about_ca_topic_score_gemma":0.0064133215,"teacher_disagreement_score":0.00419911,"about_ca_system_score_codex":0.00019608559,"about_ca_system_score_gemma":0.00029560152,"threshold_uncertainty_score":0.008349359},"labels":[],"label_agreement":null},{"id":"W7133020232","doi":"","title":"Characterizing Topological and Topographical Resilience in Structural Networks Supporting Language in Childhood","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; Strong","keywords":"Tractography; Resilience (materials science); Representation (politics); Deconvolution; Psychological resilience; Topology (electrical circuits); Language model","score_opus":0.02189960200563452,"score_gpt":0.4001682106898068,"score_spread":0.3782686086841723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133020232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99430156,0.00013899025,0.0045159003,0.000042824973,0.0000024282483,0.000006135965,0.000260524,0.000036147325,0.00069550757],"genre_scores_gemma":[0.99597293,0.00018278866,0.003234801,0.000008630838,0.0000025350744,0.000013354948,0.00028745475,0.000016746753,0.00028080153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99986124,0.000025340309,0.00000783573,0.00004637492,0.000022883063,0.00003623053],"domain_scores_gemma":[0.9991825,0.0002293518,0.00031388222,0.0000855782,0.00009384641,0.00009477956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041050932,0.00022210315,0.00013726769,0.00096188724,0.00025067574,0.00055134896,0.00017159904,0.00022264614,0.0014640355],"category_scores_gemma":[0.0019440638,0.00023591731,0.00020841458,0.00048288266,0.00053108734,0.00066780846,0.00052974554,0.00032187445,0.0002262395],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000498171,0.000084298736,0.62164176,0.00030810182,0.00028181274,0.0012246432,0.0038411075,0.017144652,0.2575457,0.006266786,0.0012331303,0.089929834],"study_design_scores_gemma":[0.000006702666,0.00015281263,0.9545987,0.00005906235,0.00007383816,0.0010158485,0.0010454037,0.014778945,0.024035139,0.002688102,0.0015224335,0.000022987357],"about_ca_topic_score_codex":0.0033112813,"about_ca_topic_score_gemma":0.007609225,"teacher_disagreement_score":0.0033112813,"about_ca_system_score_codex":0.00036708527,"about_ca_system_score_gemma":0.00035450258,"threshold_uncertainty_score":0.0065839887},"labels":[],"label_agreement":null},{"id":"W7161938113","doi":"10.82308/46062","title":"Combined application of voxel-based morphometry and magnetization transfer ratio for group analysis of magnetic resonance images","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Magnetization transfer; White matter; Voxel; Population; Magnetic resonance imaging; Voxel-based morphometry; Context (archaeology)","score_opus":0.015147482049937638,"score_gpt":0.3078146013710807,"score_spread":0.29266711932114303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7161938113","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028605318,0.0009353026,0.9620295,0.0002411395,0.00016523122,0.00039328658,0.0006182196,0.0036254588,0.0033865387],"genre_scores_gemma":[0.049862072,0.0006023434,0.9470624,0.000026360989,0.00006960632,0.0004839891,0.00034676935,0.0003966862,0.0011498047],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982039,0.00062566064,0.00012334966,0.00042147678,0.00054346904,0.00008207202],"domain_scores_gemma":[0.99774194,0.00097140775,0.00024566142,0.00041238984,0.00057527336,0.0000533935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044259233,0.0011074819,0.0014664235,0.004605504,0.00039431805,0.0019866668,0.00103006,0.00056002045,0.0049032043],"category_scores_gemma":[0.008814858,0.00046151082,0.0012846219,0.0041894885,0.0006252141,0.0013907056,0.0011225807,0.0012895297,0.001837765],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017826908,0.00017690001,0.006503191,0.0005790628,0.0008489792,0.00016210423,0.0007654922,0.009005786,0.068763316,0.009646534,0.003951478,0.89941883],"study_design_scores_gemma":[0.00030925786,0.0024260955,0.16919713,0.00044007297,0.0024618958,0.0030767594,0.001519767,0.46825632,0.13717256,0.11745117,0.09716255,0.0005264337],"about_ca_topic_score_codex":0.00085231697,"about_ca_topic_score_gemma":0.0015033573,"teacher_disagreement_score":0.0049032043,"about_ca_system_score_codex":0.00033759075,"about_ca_system_score_gemma":0.00081735157,"threshold_uncertainty_score":0.023406804},"labels":[],"label_agreement":null},{"id":"W804767602","doi":"10.1016/j.nicl.2015.06.007","title":"Altered whole-brain white matter networks in preclinical Alzheimer's disease","year":2015,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; Janssen Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Servier; Innogenetics; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Synarc; University of Southern California; Novartis Pharmaceuticals Corporation; IXICO; Takeda Pharmaceutical Company; Medpace; Genentech; Biogen Idec; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Neurodegeneration; White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Neuroimaging; Connectome; Medicine; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Psychology; Disease; Pathology; Functional connectivity; Magnetic resonance imaging","score_opus":0.2835831370933138,"score_gpt":0.47840786024234194,"score_spread":0.19482472314902816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W804767602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992329,0.00017064942,0.00034967985,0.000006359828,8.052947e-7,0.000004628484,0.00008990002,0.0000065177915,0.00013856523],"genre_scores_gemma":[0.99933004,0.000097188225,0.0003405205,0.000004444794,0.0000017261141,0.000006105132,0.00013462055,0.0000018379699,0.000083584535],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999347,0.000015583819,0.000007484661,0.000020869351,0.0000112206335,0.000010113311],"domain_scores_gemma":[0.99979144,0.000040610365,0.00009763164,0.000022692146,0.000017318085,0.000030343183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028485613,0.00031434326,0.00021870491,0.0007742805,0.00014081366,0.00029127783,0.00012222667,0.00018217613,0.00069697754],"category_scores_gemma":[0.0006895495,0.00013882914,0.000108306725,0.0003063041,0.00024521514,0.000347673,0.00022238836,0.00014481846,0.00008484598],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040895753,0.00027592393,0.7748893,0.00020152527,0.00048122337,0.0014001802,0.0009073612,0.0042883772,0.18188702,0.00067457213,0.00034504,0.03055986],"study_design_scores_gemma":[0.000014028051,0.0002384929,0.9940025,0.0000057120474,0.00004294438,0.0005295863,0.00008534729,0.001888507,0.00250668,0.0005277564,0.00015308807,0.0000054203365],"about_ca_topic_score_codex":0.0015311416,"about_ca_topic_score_gemma":0.0025799875,"teacher_disagreement_score":0.0015311416,"about_ca_system_score_codex":0.00019881142,"about_ca_system_score_gemma":0.0001219945,"threshold_uncertainty_score":0.0030444264},"labels":[],"label_agreement":null},{"id":"W838115849","doi":"10.1016/j.neuroimage.2015.06.038","title":"In vivo mapping of human spinal cord microstructure at 300 mT/m","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Spinal cord; White matter; Axon; Anatomy; Diffusion MRI; Neuroscience; Biology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.11007648811325242,"score_gpt":0.38734587001366616,"score_spread":0.2772693819004137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W838115849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95372367,0.0016920726,0.03420924,0.00067387917,0.00003611402,0.0000956403,0.0008205525,0.000381233,0.008367657],"genre_scores_gemma":[0.988947,0.00062639057,0.007410441,0.00011289905,0.00002182753,0.000032060747,0.00015318743,0.00004115198,0.002655138],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999753,0.0000046697437,0.0000015021255,0.00000467341,0.000007835488,0.000005936621],"domain_scores_gemma":[0.9999182,0.00003425454,0.000009030745,0.000009208773,0.000019226038,0.000010087465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001188504,0.00010896807,0.00009979109,0.0003649573,0.0002318725,0.00036099486,0.00015143,0.0005002472,0.0027891],"category_scores_gemma":[0.00043494822,0.00015368105,0.0000694126,0.00023543171,0.00023688989,0.00030796084,0.0001743105,0.0002576023,0.00038703662],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011179241,0.00012697009,0.0022851415,0.00015348883,0.00002346505,0.0005502751,0.00025903032,0.001627823,0.9687782,0.0009549203,0.0011507635,0.022971993],"study_design_scores_gemma":[0.0002481314,0.0020115739,0.2356292,0.00011369226,0.00016818047,0.009445746,0.00072857365,0.018783377,0.719753,0.004666564,0.008388083,0.00006382753],"about_ca_topic_score_codex":0.002432648,"about_ca_topic_score_gemma":0.0034447028,"teacher_disagreement_score":0.0027891,"about_ca_system_score_codex":0.00013447399,"about_ca_system_score_gemma":0.00027192922,"threshold_uncertainty_score":0.009330511},"labels":[],"label_agreement":null},{"id":"W90999908","doi":"10.1007/978-3-642-31298-4_34","title":"Function-Valued Mappings, Total Variation and Compressed Sensing for diffusion MRI","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion MRI; Hilbert space; Minification; Compressed sensing; Formalism (music); Algorithm; Unit sphere; Diffusion; Magnetic resonance imaging; Artificial intelligence; Mathematics; Pure mathematics; Physics","score_opus":0.03782224024557197,"score_gpt":0.29631795854297743,"score_spread":0.2584957182974055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W90999908","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004121319,0.047204826,0.9300583,0.0016127345,0.0010351073,0.00002897266,0.00022208698,0.00018795951,0.015528625],"genre_scores_gemma":[0.15744296,0.094702,0.68793917,0.0011914412,0.0055620647,0.00016884117,0.0007119473,0.00033773502,0.051943816],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972695,0.00008642645,0.00002404014,0.00005910297,0.000091937494,0.000011494439],"domain_scores_gemma":[0.99954,0.00032924645,0.000031179545,0.00003556506,0.000048928032,0.0000149947045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007676987,0.0010599439,0.0008725783,0.00094613904,0.00022189593,0.0016176854,0.0006928242,0.0015279279,0.0028922793],"category_scores_gemma":[0.00202288,0.00035944014,0.00057995296,0.001651997,0.0015907405,0.0018773815,0.0008017947,0.0021272525,0.0009145688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005398062,0.000042341275,0.00013150541,0.0007689748,0.000048467726,0.00019040906,0.00020116383,0.033948563,0.011697812,0.7220914,0.017404173,0.21342123],"study_design_scores_gemma":[0.000010458015,0.000080058875,0.00036970022,0.00009221033,0.0000252983,0.0005878753,0.000050305538,0.16074227,0.0026265136,0.7973431,0.03802244,0.000049838898],"about_ca_topic_score_codex":0.0005971834,"about_ca_topic_score_gemma":0.0005963592,"teacher_disagreement_score":0.0028922793,"about_ca_system_score_codex":0.00031102297,"about_ca_system_score_gemma":0.00032072852,"threshold_uncertainty_score":0.009675682},"labels":[],"label_agreement":null},{"id":"W910086267","doi":"10.1016/j.bandl.2015.06.006","title":"Fiber tracking of the frontal aslant tract and subcomponents of the arcuate fasciculus in 5–8-year-olds: Relation to speech and language function","year":2015,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Psychology; Fractional anisotropy; Fasciculus; Fiber tract; Diffusion MRI; Neuroscience; Audiology; Cognitive psychology; Magnetic resonance imaging; Medicine","score_opus":0.036315339610534035,"score_gpt":0.31350800807523166,"score_spread":0.27719266846469764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W910086267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9993974,0.00008154773,0.00019833844,0.000012878039,0.0000031361244,0.0000028459776,0.00010258367,0.000005293379,0.00019594977],"genre_scores_gemma":[0.998743,0.0001133679,0.00039354266,0.000010119811,0.0000036322904,0.000004332821,0.00012132816,0.0000034918671,0.00060719356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999113,0.000009204881,0.000008409498,0.00002740773,0.000011883589,0.000031669693],"domain_scores_gemma":[0.99960524,0.00008781144,0.00011028864,0.000030296853,0.00010334665,0.00006301532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032280313,0.00019961337,0.00014965535,0.00094195566,0.0002948978,0.0002791649,0.00017234743,0.0004715774,0.0012941103],"category_scores_gemma":[0.0009434197,0.00018867635,0.00016846502,0.0002909437,0.00027482255,0.0004891915,0.00022951896,0.0002515789,0.00029972175],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013373235,0.00017515293,0.90717334,0.000031315383,0.0000784593,0.003002833,0.0010866749,0.0004505923,0.0635966,0.00015756994,0.00030797828,0.022602173],"study_design_scores_gemma":[0.000003755548,0.000083950945,0.9962058,0.000004869101,0.000013131586,0.0009605629,0.00026073508,0.00051740435,0.0017874215,0.000037556325,0.00012046595,0.0000043435643],"about_ca_topic_score_codex":0.03622762,"about_ca_topic_score_gemma":0.046176434,"teacher_disagreement_score":0.03622762,"about_ca_system_score_codex":0.00026747672,"about_ca_system_score_gemma":0.00030444664,"threshold_uncertainty_score":0.072033465},"labels":[],"label_agreement":null}]}